Methods in Enzymology Vol 460: Chemokines, Part A

METHODS IN ENZYMOLOGY Editors-in-Chief JOHN N. ABELSON AND MELVIN I. SIMON Division of Biology California Institute of...

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METHODS IN ENZYMOLOGY Editors-in-Chief

JOHN N. ABELSON AND MELVIN I. SIMON Division of Biology California Institute of Technology Pasadena, California, USA Founding Editors

SIDNEY P. COLOWICK AND NATHAN O. KAPLAN

Academic Press is an imprint of Elsevier 525 B Street, Suite 1900, San Diego, CA 92101-4495, USA 30 Corporate Drive, Suite 400, Burlington, MA 01803, USA 32 Jamestown Road, London NW1 7BY, UK First edition 2009 Copyright # 2009, Elsevier Inc. All rights reserved No part of this publication may be reproduced, stored in a retrieval system or transmitted in any form or by any means electronic, mechanical, photocopying, recording or otherwise without the prior written permission of the publisher Permissions may be sought directly from Elsevier’s Science & Technology Rights Department in Oxford, UK: phone (+44) (0) 1865 843830; fax (+44) (0) 1865 853333; email: permissions@ elsevier.com. Alternatively you can submit your request online by visiting the Elsevier web site at http://elsevier.com/locate/permissions, and selecting Obtaining permission to use Elsevier material Notice No responsibility is assumed by the publisher for any injury and/or damage to persons or property as a matter of products liability, negligence or otherwise, or from any use or operation of any methods, products, instructions or ideas contained in the material herein. Because of rapid advances in the medical sciences, in particular, independent verification of diagnoses and drug dosages should be made For information on all Academic Press publications visit our website at elsevierdirect.com ISBN: 978-0-12-374908-6 ISSN: 0076-6879 Printed and bound in United States of America 09 10 11 12 10 9 8 7 6 5 4 3 2 1

CONTRIBUTORS

Sarah Able Pfizer GRD-Sandwich Laboratories, Sandwich, Kent, United Kingdom Antonio Alcami Centro de Biologıá Molecular Severo Ochoa (Consejo Superior de Investigaciones Cientı´ficas-Universidad Autońoma de Madrid), Cantoblanco, Madrid, Spain, and Department of Medicine, University of Cambridge, Cambridge, United Kingdom Paola Allavena Department of Immunology and Inflammation, IRCCS Istituto Clinico Humanitas, Rozzano (Milan), Italy Mee Y. Bartee Division of Cardiovascular Medicine, Department of Medicine and Department of Molecular Genetics and Microbiology, University of Florida, Gainesville, Florida, USA Adit Ben-Baruch Department of Cell Research and Immunology, George S. Wise Faculty of Life Sciences, Tel Aviv University, Tel Aviv, Israel Paolo Bianchi Laboratory of Molecular Gastroenterology, IRCCS Istituto Clinico Humanitas, Rozzano (Milan), Italy Emma Blair Department of Chemistry, and Division of Immunology, Infection and Inflammation, Glasgow Biomedical Research Center, Glasgow University, Glasgow, United Kingdom Raffaella Bonecchi Laboratory of Leukocyte Biology, Department of Translational Medicine, University of Milan, IRCCS Istituto Clinico Humanitas, Italy Elena M. Borroni Laboratory of Leukocyte Biology, Department of Translational Medicine, University of Milan, IRCCS Istituto Clinico Humanitas, Italy James R. Broach Department of Molecular Biology, Princeton University, Princeton, New Jersey, USA xiii

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Contributors

Chiara Buracchi Laboratory of Leukocyte Biology, Department of Translational Medicine, University of Milan, IRCCS Istituto Clinico Humanitas, Italy Erbin Dai Department of Medicine, University of Florida, Gainesville, Florida, USA John F. DiPersio Division of Oncology, Siteman Cancer Center, Washington University School of Medicine, St. Louis, Missouri, USA Patrick Dorr Pfizer GRD-Sandwich Laboratories, Sandwich, Kent, United Kingdom Pieter C. Dorrestein Skaggs School of Pharmacy and Pharmaceutical Science, University of California, San Diego, La Jolla, California, USA Marco Erreni Department of Immunology and Inflammation, IRCCS Istituto Clinico Humanitas, Rozzano (Milan), Italy Barry J. Evans Department of Pathology, Anatomy and Cell Biology, Thomas Jefferson University, Philadelphia, Pennsylvania, USA Marco Fabbri Department of Immunology and Inflammation, IRCCS Istituto Clinico Humanitas, Rozzano (Milan), Italy Nobutaka Fujii Department of Chemogenomics, Graduate School of Pharmaceutical Sciences, Kyoto University, Sakyo-ku, Kyoto, Japan Kerry B. Goralski Department of Pharmacology, Faculty of Medicine, and College of Pharmacy, Faculty of Health Professions Dalhousie University, Halifax, Nova Scotia, Canada Gerard J. Graham Division of Immunology, Infection and Inflammation, Glasgow Biomedical Research Center, Glasgow University, Glasgow, United Kingdom Paul Griffin Pfizer GRD-Sandwich Laboratories, Sandwich, Kent, United Kingdom J. Silvio Gutkind Oral and Pharyngeal Cancer Branch, National Institute of Dental and Craniofacial Research, National Institutes of Health, Bethesda, Maryland, USA

Contributors

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Amy-Joan L. Ham Department of Biochemistry, Vanderbilt University School of Medicine, Nashville, Tennessee, USA Tracy M. Handel Skaggs School of Pharmacy and Pharmaceutical Science, University of California, San Diego, La Jolla, California, USA Karen E. Hedin Department of Immunology, College of Medicine, Mayo Clinic, Rochester, Minnesota, USA Richard Horuk Department of Pharmacology, UC Davis, Davis, California, USA Becky Irvine Pfizer GRD-Sandwich Laboratories, Sandwich, Kent, United Kingdom Neil Isaacs Department of Chemistry, Glasgow Biomedical Research Centre, Glasgow University, Glasgow, United Kingdom Ian James Pfizer GRD-Sandwich Laboratories, Sandwich, Kent, United Kingdom Tom Kershaw Cell Biology Unit, MRC Laboratory for Molecular Cell Biology, and Department of Cell and Developmental Biology, University College London, London, United Kingdom Kimberly N. Kremer Department of Immunology, College of Medicine, Mayo Clinic, Rochester, Minnesota, USA Ashok Kumar Endocrine Research Unit, Mayo Clinic, Rochester, Minnesota, USA Luigi Laghi Laboratory of Molecular Gastroenterology, IRCCS Istituto Clinico Humanitas, Rozzano (Milan), Italy Meizhang Li Neuroinflammation Research Center, Department of Neurosciences, Lerner Research Institute, Cleveland Clinic, Cleveland, Ohio, USA Sergio A. Lira Immunology Institute, Mount Sinai School of Medicine, New York, New York, USA

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Contributors

Liying Liu Department of Medicine, University of Florida, Gainesville, Florida, USA Massimo Locati Department of Translational Medicine, University of Milan, IRCCS Istituto Clinico Humanitas, Via Manzoni, Rozzano (Milano), Italia Alexandra R. Lucas Division of Cardiovascular Medicine, Department of Medicine and Department of Molecular Genetics and Microbiology, University of Florida, Gainesville, Florida, USA Malcolm Macartney Pfizer GRD-Sandwich Laboratories, Sandwich, Kent, United Kingdom Colin Macaulay Division of Cardiovascular Medicine, University of Florida, Gainesville, Florida, USA Roy Mansfield Pfizer GRD-Sandwich Laboratories, Sandwich, Kent, United Kingdom Alberto Mantovani Department of Translational Medicine, University of Milan, IRCCS Istituto Clinico Humanitas, Via Manzoni, Rozzano (Milano), Italia Adriano Marchese Department of Pharmacology, Stritch School of Medicine, Loyola University Chicago, Maywood, Illinois, USA Mark Marsh Cell Biology Unit, MRC Laboratory for Molecular Cell Biology, and Department of Cell and Developmental Biology, University College London, London, United Kingdom Andrea P. Martin Immunology Institute, Mount Sinai School of Medicine, New York, New York, USA Daniel Martin Oral and Pharyngeal Cancer Branch, National Institute of Dental and Craniofacial Research, National Institutes of Health, Bethesda, Maryland, USA David Maussang Leiden/Amsterdam Center for Drug Research, Division of Medicinal Chemistry, Faculty of Sciences, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands Clare McCulloch Department of Chemistry, and Division of Immunology, Infection and Inflammation, Glasgow Biomedical Research Center, Glasgow University, Glasgow, United Kingdom

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Contributors

Grant McFadden Department of Molecular Genetics Florida, Gainesville, Florida, USA

and

Microbiology,

University

of

Pauline McLean Department of Chemistry, and Division of Immunology, Infection and Inflammation, Glasgow Biomedical Research Center, Glasgow University, Glasgow, United Kingdom Dana McIvor Division of Cardiovascular Medicine, University of Florida, Gainesville, Florida, USA Raymond L. Mernaugh Department of Biochemistry, Vanderbilt University School of Medicine, Nashville, Tennessee, USA Tsipi Meshel Department of Cell Research and Immunology, George S. Wise Faculty of Life Sciences, Tel Aviv University, Tel Aviv, Israel Detlef Michel Institute of Virology, Ulm University Clinic, Ulm, Germany Ken Miller Pfizer GRD-Groton Laboratories, Groton, Connecticut, USA James Mills Pfizer GRD-Sandwich Laboratories, Sandwich, Kent, United Kingdom Massimilliano Mirolo Laboratory of Leukocyte Biology, Department of Translational Medicine, University of Milan, IRCCS Istituto Clinico Humanitas, Italy Ganesh Munuswamy-Ramanujam Division of Cardiovascular Medicine, Department of Medicine and Department of Molecular Genetics and Microbiology, University of Florida, Gainesville, Florida, USA Carolyn Napier Pfizer GRD-Sandwich Laboratories, Sandwich, Kent, United Kingdom Iva Navratilova Pfizer GRD-Sandwich Laboratories, Sandwich, Kent, United Kingdom Manuela Nebuloni Pathology Unit, L. Sacco Institute of Medical Sciences, University of Milan, Milan, Italy

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Contributors

Nicole F. Neel Department of Cancer Biology, Vanderbilt University School of Medicine, Nashville, Tennessee, USA Bruno Nervi Division of Oncology, Siteman Cancer Center, Washington University School of Medicine, St. Louis, Missouri, USA Robert J. B. Nibbs Division of Immunology, Infection and Inflammation, Glasgow Biomedical Research Center, Glasgow University, Glasgow, United Kingdom Morgan O’Hayre Skaggs School of Pharmacy and Pharmaceutical Science, University of California, San Diego, La Jolla, California, USA Shinya Oishi Department of Chemogenomics, Graduate School of Pharmaceutical Sciences, Kyoto University, Sakyo-ku, Kyoto, Japan Fabio Pasqualini Laboratory of Leukocyte Biology, Department of Translational Medicine, University of Milan, IRCCS Istituto Clinico Humanitas, Italy James E. Pease Leukocyte Biology Section, National Heart and Lung Institute, Imperial College London, London, United Kingdom Stephen C. Peiper Department of Pathology, Anatomy and Cell Biology, Thomas Jefferson University, Philadelphia, Pennsylvania, USA Manos Perros Pfizer GRD-Sandwich Laboratories, Sandwich, Kent, United Kingdom Dayanidhi Raman Department of Cancer Biology, and Veterans Affairs Medical Center, Vanderbilt University School of Medicine, Nashville, Tennessee, USA Pablo Ramirez Division of Oncology, Siteman Cancer Center, Washington University School of Medicine, St. Louis, Missouri, USA Richard M. Ransohoff Neuroinflammation Research Center, Department of Neurosciences, Lerner Research Institute, Cleveland Clinic, Cleveland, Ohio, USA Michael P. Rettig Division of Oncology, Siteman Cancer Center, Washington University School of Medicine, St. Louis, Missouri, USA

Contributors

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Alan Riboldi-Tunniclife Department of Chemistry, Glasgow Biomedical Research Centre, Glasgow University, Glasgow, United Kingdom Ann J. Richmond Department of Cancer Biology, and Veterans Affairs Medical Center, Vanderbilt University School of Medicine, Nashville, Tennessee, USA Graham Rickett Pfizer GRD-Sandwich Laboratories, Sandwich, Kent, United Kingdom Harriet Root Pfizer GRD-Sandwich Laboratories, Sandwich, Kent, United Kingdom Remo C. Russo Department of Biochemistry and Immunology, Instituto de Ciencias Biologicas, Universidade Federal de Minas Gerais, Belo Horizonte, Brazil, and Laboratory of Leukocyte Biology, Department of Translational Medicine, University of Milan, IRCCS Istituto Clinico Humanitas, Italy Elna van der Ryst Pfizer GRD-Sandwich Laboratories, Sandwich, Kent, United Kingdom Jiqing Sai Department of Cancer Biology, and Veterans Affairs Medical Center, Vanderbilt University School of Medicine, Nashville, Tennessee, USA Catherina L. Salanga Skaggs School of Pharmacy and Pharmaceutical Science, University of California, San Diego, La Jolla, California, USA Benedetta Savino Laboratory of Leukocyte Biology, Department of Translational Medicine, University of Milan, IRCCS Istituto Clinico Humanitas, Italy Andreas Schreiber Institute of Virology, Ulm University Clinic, Ulm, Germany Limin Shang Immunology Institute, Mount Sinai School of Medicine, New York, New York, USA Nathalie Signoret Centre for Immunology and Infection, Department of Biology and Hull York Medical School, University of York, York, United Kingdom Olivia L. Sims Department of Immunology, College of Medicine, Mayo Clinic, Rochester, Minnesota, USA

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Contributors

Christopher J. Sinal Department of Pharmacology, Faculty of Medicine, Dalhousie University, Halifax, Nova Scotia, Canada Martine J. Smit Leiden/Amsterdam Center for Drug Research, Division of Medicinal Chemistry, Faculty of Sciences, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands Gali Soria Department of Cell Research and Immunology, George S. Wise Faculty of Life Sciences, Tel Aviv University, Tel Aviv, Israel Nagarajan Vaidehi Division of Immunology, Beckman Research Institute of the City of Hope, Duarte, California, USA Abel Viejo-Borbolla Centro de Biologıá Molecular Severo Ochoa, (Consejo Superior de Investigaciones Cientı´ficas-Universidad Autońoma de Madrid), Cantoblanco, Madrid, Spain, and Immunology Institute, Mount Sinai School of Medicine, New York, New York, USA Henry F. Vischer Leiden/Amsterdam Center for Drug Research, Division of Medicinal Chemistry, Faculty of Sciences, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands Zixuan Wang Department of Pathology, Anatomy and Cell Biology, and Department of Surgery, Thomas Jefferson University, Philadelphia, Pennsylvania, USA Sile`ne T. Wavre-Shapton Molecular Medicine NHL1, Imperial College, South Kennigton, London, United Kingdom Mike Westby Pfizer GRD-Sandwich Laboratories, Sandwich, Kent, United Kingdom Jinming Yang Department of Cancer Biology, and Veterans Affairs Medical Center, Vanderbilt University School of Medicine, Nashville, Tennessee, USA Yanshi Zhu Department of Chemistry, Glasgow Biomedical Research Centre, Glasgow University, Glasgow, United Kingdom

PREFACE

Chemokines and chemokine receptors are the eyes and ears of the immune system, and under normal healthy conditions they guide the migration of leukocytes within the body to areas of assault or injury. Of course, this system can be broken, corrupted, compromised, and led astray in a variety of ways. Immune cells can attack their own tissues leading to autoimmune diseases such as rheumatoid arthritis and multiple sclerosis. Many pathogens have evolved ways to ‘‘blind’’ the immune system, thus allowing them to go undetected and propagate freely. Viruses such as HIV-1 have been shown to use specific transmembrane chemokine receptors as one path to cellular entry and infection. The progression of cancer can even be aided by the good intentions of immune system–mediated vascularization. The list goes on, and hence the scientific community has long realized the importance of understanding and eventually being able to manipulate this complex system. As a result, the number of papers addressing chemokines and chemokine receptors has grown exponentially over the last decade. In 1997, Richard Horuk edited volumes 287 and 288 of the Methods in Enzymology series on chemokines and chemokine receptors, putting together the first comprehensive practical guide to studying these molecules. Since then many new technologies and methodologies have been designed and implemented in the study of these proteins. Volumes 460 and 461 of Methods in Enzymology seek to compile and highlight these recent methods, explain their importance, and clearly describe in detail the protocols necessary for successful experimental reproduction. Volume 460 focuses on studying the roles of chemokines and chemokine receptors in disease states, atypical chemokine receptors, and chemokine signaling, as well as chemokine related proteins from pathogens. Volume 461 deals with the assays and methods used to study structure and function of these proteins and to characterize their ultimate goal of cell migration. These methods span a wide spectrum of multidisciplinary techniques, from new spectroscopic advances to in situ cell-selective protein expression to devices designed to mimic the conditions of flow present in blood vessels where in situ leukocyte migration occurs. Many of the authors from the first volumes have returned in the present work to build upon the foundation they laid over a decade ago. In addition,

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many newer researchers have pitched in and lent their expansive expertise to the cause. Compilations like this are assembled by the immense efforts of many individual researchers and we emphatically offer our thanks and gratitude to all of the authors who contributed to making these volumes a reality. TRACY M. HANDEL AND DAMON J. HAMEL

METHODS IN ENZYMOLOGY

VOLUME I. Preparation and Assay of Enzymes Edited by SIDNEY P. COLOWICK AND NATHAN O. KAPLAN VOLUME II. Preparation and Assay of Enzymes Edited by SIDNEY P. COLOWICK AND NATHAN O. KAPLAN VOLUME III. Preparation and Assay of Substrates Edited by SIDNEY P. COLOWICK AND NATHAN O. KAPLAN VOLUME IV. Special Techniques for the Enzymologist Edited by SIDNEY P. COLOWICK AND NATHAN O. KAPLAN VOLUME V. Preparation and Assay of Enzymes Edited by SIDNEY P. COLOWICK AND NATHAN O. KAPLAN VOLUME VI. Preparation and Assay of Enzymes (Continued) Preparation and Assay of Substrates Special Techniques Edited by SIDNEY P. COLOWICK AND NATHAN O. KAPLAN VOLUME VII. Cumulative Subject Index Edited by SIDNEY P. COLOWICK AND NATHAN O. KAPLAN VOLUME VIII. Complex Carbohydrates Edited by ELIZABETH F. NEUFELD AND VICTOR GINSBURG VOLUME IX. Carbohydrate Metabolism Edited by WILLIS A. WOOD VOLUME X. Oxidation and Phosphorylation Edited by RONALD W. ESTABROOK AND MAYNARD E. PULLMAN VOLUME XI. Enzyme Structure Edited by C. H. W. HIRS VOLUME XII. Nucleic Acids (Parts A and B) Edited by LAWRENCE GROSSMAN AND KIVIE MOLDAVE VOLUME XIII. Citric Acid Cycle Edited by J. M. LOWENSTEIN VOLUME XIV. Lipids Edited by J. M. LOWENSTEIN VOLUME XV. Steroids and Terpenoids Edited by RAYMOND B. CLAYTON xxiii

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VOLUME XVI. Fast Reactions Edited by KENNETH KUSTIN VOLUME XVII. Metabolism of Amino Acids and Amines (Parts A and B) Edited by HERBERT TABOR AND CELIA WHITE TABOR VOLUME XVIII. Vitamins and Coenzymes (Parts A, B, and C) Edited by DONALD B. MCCORMICK AND LEMUEL D. WRIGHT VOLUME XIX. Proteolytic Enzymes Edited by GERTRUDE E. PERLMANN AND LASZLO LORAND VOLUME XX. Nucleic Acids and Protein Synthesis (Part C) Edited by KIVIE MOLDAVE AND LAWRENCE GROSSMAN VOLUME XXI. Nucleic Acids (Part D) Edited by LAWRENCE GROSSMAN AND KIVIE MOLDAVE VOLUME XXII. Enzyme Purification and Related Techniques Edited by WILLIAM B. JAKOBY VOLUME XXIII. Photosynthesis (Part A) Edited by ANTHONY SAN PIETRO VOLUME XXIV. Photosynthesis and Nitrogen Fixation (Part B) Edited by ANTHONY SAN PIETRO VOLUME XXV. Enzyme Structure (Part B) Edited by C. H. W. HIRS AND SERGE N. TIMASHEFF VOLUME XXVI. Enzyme Structure (Part C) Edited by C. H. W. HIRS AND SERGE N. TIMASHEFF VOLUME XXVII. Enzyme Structure (Part D) Edited by C. H. W. HIRS AND SERGE N. TIMASHEFF VOLUME XXVIII. Complex Carbohydrates (Part B) Edited by VICTOR GINSBURG VOLUME XXIX. Nucleic Acids and Protein Synthesis (Part E) Edited by LAWRENCE GROSSMAN AND KIVIE MOLDAVE VOLUME XXX. Nucleic Acids and Protein Synthesis (Part F) Edited by KIVIE MOLDAVE AND LAWRENCE GROSSMAN VOLUME XXXI. Biomembranes (Part A) Edited by SIDNEY FLEISCHER AND LESTER PACKER VOLUME XXXII. Biomembranes (Part B) Edited by SIDNEY FLEISCHER AND LESTER PACKER VOLUME XXXIII. Cumulative Subject Index Volumes I-XXX Edited by MARTHA G. DENNIS AND EDWARD A. DENNIS VOLUME XXXIV. Affinity Techniques (Enzyme Purification: Part B) Edited by WILLIAM B. JAKOBY AND MEIR WILCHEK


VOLUME XXXV. Lipids (Part B) Edited by JOHN M. LOWENSTEIN VOLUME XXXVI. Hormone Action (Part A: Steroid Hormones) Edited by BERT W. O’MALLEY AND JOEL G. HARDMAN VOLUME XXXVII. Hormone Action (Part B: Peptide Hormones) Edited by BERT W. O’MALLEY AND JOEL G. HARDMAN VOLUME XXXVIII. Hormone Action (Part C: Cyclic Nucleotides) Edited by JOEL G. HARDMAN AND BERT W. O’MALLEY VOLUME XXXIX. Hormone Action (Part D: Isolated Cells, Tissues, and Organ Systems) Edited by JOEL G. HARDMAN AND BERT W. O’MALLEY VOLUME XL. Hormone Action (Part E: Nuclear Structure and Function) Edited by BERT W. O’MALLEY AND JOEL G. HARDMAN VOLUME XLI. Carbohydrate Metabolism (Part B) Edited by W. A. WOOD VOLUME XLII. Carbohydrate Metabolism (Part C) Edited by W. A. WOOD VOLUME XLIII. Antibiotics Edited by JOHN H. HASH VOLUME XLIV. Immobilized Enzymes Edited by KLAUS MOSBACH VOLUME XLV. Proteolytic Enzymes (Part B) Edited by LASZLO LORAND VOLUME XLVI. Affinity Labeling Edited by WILLIAM B. JAKOBY AND MEIR WILCHEK VOLUME XLVII. Enzyme Structure (Part E) Edited by C. H. W. HIRS AND SERGE N. TIMASHEFF VOLUME XLVIII. Enzyme Structure (Part F) Edited by C. H. W. HIRS AND SERGE N. TIMASHEFF VOLUME XLIX. Enzyme Structure (Part G) Edited by C. H. W. HIRS AND SERGE N. TIMASHEFF VOLUME L. Complex Carbohydrates (Part C) Edited by VICTOR GINSBURG VOLUME LI. Purine and Pyrimidine Nucleotide Metabolism Edited by PATRICIA A. HOFFEE AND MARY ELLEN JONES VOLUME LII. Biomembranes (Part C: Biological Oxidations) Edited by SIDNEY FLEISCHER AND LESTER PACKER

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VOLUME LIII. Biomembranes (Part D: Biological Oxidations) Edited by SIDNEY FLEISCHER AND LESTER PACKER VOLUME LIV. Biomembranes (Part E: Biological Oxidations) Edited by SIDNEY FLEISCHER AND LESTER PACKER VOLUME LV. Biomembranes (Part F: Bioenergetics) Edited by SIDNEY FLEISCHER AND LESTER PACKER VOLUME LVI. Biomembranes (Part G: Bioenergetics) Edited by SIDNEY FLEISCHER AND LESTER PACKER VOLUME LVII. Bioluminescence and Chemiluminescence Edited by MARLENE A. DELUCA VOLUME LVIII. Cell Culture Edited by WILLIAM B. JAKOBY AND IRA PASTAN VOLUME LIX. Nucleic Acids and Protein Synthesis (Part G) Edited by KIVIE MOLDAVE AND LAWRENCE GROSSMAN VOLUME LX. Nucleic Acids and Protein Synthesis (Part H) Edited by KIVIE MOLDAVE AND LAWRENCE GROSSMAN VOLUME 61. Enzyme Structure (Part H) Edited by C. H. W. HIRS AND SERGE N. TIMASHEFF VOLUME 62. Vitamins and Coenzymes (Part D) Edited by DONALD B. MCCORMICK AND LEMUEL D. WRIGHT VOLUME 63. Enzyme Kinetics and Mechanism (Part A: Initial Rate and Inhibitor Methods) Edited by DANIEL L. PURICH VOLUME 64. Enzyme Kinetics and Mechanism (Part B: Isotopic Probes and Complex Enzyme Systems) Edited by DANIEL L. PURICH VOLUME 65. Nucleic Acids (Part I) Edited by LAWRENCE GROSSMAN AND KIVIE MOLDAVE VOLUME 66. Vitamins and Coenzymes (Part E) Edited by DONALD B. MCCORMICK AND LEMUEL D. WRIGHT VOLUME 67. Vitamins and Coenzymes (Part F) Edited by DONALD B. MCCORMICK AND LEMUEL D. WRIGHT VOLUME 68. Recombinant DNA Edited by RAY WU VOLUME 69. Photosynthesis and Nitrogen Fixation (Part C) Edited by ANTHONY SAN PIETRO VOLUME 70. Immunochemical Techniques (Part A) Edited by HELEN VAN VUNAKIS AND JOHN J. LANGONE


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VOLUME 71. Lipids (Part C) Edited by JOHN M. LOWENSTEIN VOLUME 72. Lipids (Part D) Edited by JOHN M. LOWENSTEIN VOLUME 73. Immunochemical Techniques (Part B) Edited by JOHN J. LANGONE AND HELEN VAN VUNAKIS VOLUME 74. Immunochemical Techniques (Part C) Edited by JOHN J. LANGONE AND HELEN VAN VUNAKIS VOLUME 75. Cumulative Subject Index Volumes XXXI, XXXII, XXXIV–LX Edited by EDWARD A. DENNIS AND MARTHA G. DENNIS VOLUME 76. Hemoglobins Edited by ERALDO ANTONINI, LUIGI ROSSI-BERNARDI, AND EMILIA CHIANCONE VOLUME 77. Detoxication and Drug Metabolism Edited by WILLIAM B. JAKOBY VOLUME 78. Interferons (Part A) Edited by SIDNEY PESTKA VOLUME 79. Interferons (Part B) Edited by SIDNEY PESTKA VOLUME 80. Proteolytic Enzymes (Part C) Edited by LASZLO LORAND VOLUME 81. Biomembranes (Part H: Visual Pigments and Purple Membranes, I) Edited by LESTER PACKER VOLUME 82. Structural and Contractile Proteins (Part A: Extracellular Matrix) Edited by LEON W. CUNNINGHAM AND DIXIE W. FREDERIKSEN VOLUME 83. Complex Carbohydrates (Part D) Edited by VICTOR GINSBURG VOLUME 84. Immunochemical Techniques (Part D: Selected Immunoassays) Edited by JOHN J. LANGONE AND HELEN VAN VUNAKIS VOLUME 85. Structural and Contractile Proteins (Part B: The Contractile Apparatus and the Cytoskeleton) Edited by DIXIE W. FREDERIKSEN AND LEON W. CUNNINGHAM VOLUME 86. Prostaglandins and Arachidonate Metabolites Edited by WILLIAM E. M. LANDS AND WILLIAM L. SMITH VOLUME 87. Enzyme Kinetics and Mechanism (Part C: Intermediates, Stereo-chemistry, and Rate Studies) Edited by DANIEL L. PURICH VOLUME 88. Biomembranes (Part I: Visual Pigments and Purple Membranes, II) Edited by LESTER PACKER

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VOLUME 89. Carbohydrate Metabolism (Part D) Edited by WILLIS A. WOOD VOLUME 90. Carbohydrate Metabolism (Part E) Edited by WILLIS A. WOOD VOLUME 91. Enzyme Structure (Part I) Edited by C. H. W. HIRS AND SERGE N. TIMASHEFF VOLUME 92. Immunochemical Techniques (Part E: Monoclonal Antibodies and General Immunoassay Methods) Edited by JOHN J. LANGONE AND HELEN VAN VUNAKIS VOLUME 93. Immunochemical Techniques (Part F: Conventional Antibodies, Fc Receptors, and Cytotoxicity) Edited by JOHN J. LANGONE AND HELEN VAN VUNAKIS VOLUME 94. Polyamines Edited by HERBERT TABOR AND CELIA WHITE TABOR VOLUME 95. Cumulative Subject Index Volumes 61–74, 76–80 Edited by EDWARD A. DENNIS AND MARTHA G. DENNIS VOLUME 96. Biomembranes [Part J: Membrane Biogenesis: Assembly and Targeting (General Methods; Eukaryotes)] Edited by SIDNEY FLEISCHER AND BECCA FLEISCHER VOLUME 97. Biomembranes [Part K: Membrane Biogenesis: Assembly and Targeting (Prokaryotes, Mitochondria, and Chloroplasts)] Edited by SIDNEY FLEISCHER AND BECCA FLEISCHER VOLUME 98. Biomembranes (Part L: Membrane Biogenesis: Processing and Recycling) Edited by SIDNEY FLEISCHER AND BECCA FLEISCHER VOLUME 99. Hormone Action (Part F: Protein Kinases) Edited by JACKIE D. CORBIN AND JOEL G. HARDMAN VOLUME 100. Recombinant DNA (Part B) Edited by RAY WU, LAWRENCE GROSSMAN, AND KIVIE MOLDAVE VOLUME 101. Recombinant DNA (Part C) Edited by RAY WU, LAWRENCE GROSSMAN, AND KIVIE MOLDAVE VOLUME 102. Hormone Action (Part G: Calmodulin and Calcium-Binding Proteins) Edited by ANTHONY R. MEANS AND BERT W. O’MALLEY VOLUME 103. Hormone Action (Part H: Neuroendocrine Peptides) Edited by P. MICHAEL CONN VOLUME 104. Enzyme Purification and Related Techniques (Part C) Edited by WILLIAM B. JAKOBY


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VOLUME 105. Oxygen Radicals in Biological Systems Edited by LESTER PACKER VOLUME 106. Posttranslational Modifications (Part A) Edited by FINN WOLD AND KIVIE MOLDAVE VOLUME 107. Posttranslational Modifications (Part B) Edited by FINN WOLD AND KIVIE MOLDAVE VOLUME 108. Immunochemical Techniques (Part G: Separation and Characterization of Lymphoid Cells) Edited by GIOVANNI DI SABATO, JOHN J. LANGONE, AND HELEN VAN VUNAKIS VOLUME 109. Hormone Action (Part I: Peptide Hormones) Edited by LUTZ BIRNBAUMER AND BERT W. O’MALLEY VOLUME 110. Steroids and Isoprenoids (Part A) Edited by JOHN H. LAW AND HANS C. RILLING VOLUME 111. Steroids and Isoprenoids (Part B) Edited by JOHN H. LAW AND HANS C. RILLING VOLUME 112. Drug and Enzyme Targeting (Part A) Edited by KENNETH J. WIDDER AND RALPH GREEN VOLUME 113. Glutamate, Glutamine, Glutathione, and Related Compounds Edited by ALTON MEISTER VOLUME 114. Diffraction Methods for Biological Macromolecules (Part A) Edited by HAROLD W. WYCKOFF, C. H. W. HIRS, AND SERGE N. TIMASHEFF VOLUME 115. Diffraction Methods for Biological Macromolecules (Part B) Edited by HAROLD W. WYCKOFF, C. H. W. HIRS, AND SERGE N. TIMASHEFF VOLUME 116. Immunochemical Techniques (Part H: Effectors and Mediators of Lymphoid Cell Functions) Edited by GIOVANNI DI SABATO, JOHN J. LANGONE, AND HELEN VAN VUNAKIS VOLUME 117. Enzyme Structure (Part J) Edited by C. H. W. HIRS AND SERGE N. TIMASHEFF VOLUME 118. Plant Molecular Biology Edited by ARTHUR WEISSBACH AND HERBERT WEISSBACH VOLUME 119. Interferons (Part C) Edited by SIDNEY PESTKA VOLUME 120. Cumulative Subject Index Volumes 81–94, 96–101 VOLUME 121. Immunochemical Techniques (Part I: Hybridoma Technology and Monoclonal Antibodies) Edited by JOHN J. LANGONE AND HELEN VAN VUNAKIS VOLUME 122. Vitamins and Coenzymes (Part G) Edited by FRANK CHYTIL AND DONALD B. MCCORMICK

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VOLUME 123. Vitamins and Coenzymes (Part H) Edited by FRANK CHYTIL AND DONALD B. MCCORMICK VOLUME 124. Hormone Action (Part J: Neuroendocrine Peptides) Edited by P. MICHAEL CONN VOLUME 125. Biomembranes (Part M: Transport in Bacteria, Mitochondria, and Chloroplasts: General Approaches and Transport Systems) Edited by SIDNEY FLEISCHER AND BECCA FLEISCHER VOLUME 126. Biomembranes (Part N: Transport in Bacteria, Mitochondria, and Chloroplasts: Protonmotive Force) Edited by SIDNEY FLEISCHER AND BECCA FLEISCHER VOLUME 127. Biomembranes (Part O: Protons and Water: Structure and Translocation) Edited by LESTER PACKER VOLUME 128. Plasma Lipoproteins (Part A: Preparation, Structure, and Molecular Biology) Edited by JERE P. SEGREST AND JOHN J. ALBERS VOLUME 129. Plasma Lipoproteins (Part B: Characterization, Cell Biology, and Metabolism) Edited by JOHN J. ALBERS AND JERE P. SEGREST VOLUME 130. Enzyme Structure (Part K) Edited by C. H. W. HIRS AND SERGE N. TIMASHEFF VOLUME 131. Enzyme Structure (Part L) Edited by C. H. W. HIRS AND SERGE N. TIMASHEFF VOLUME 132. Immunochemical Techniques (Part J: Phagocytosis and Cell-Mediated Cytotoxicity) Edited by GIOVANNI DI SABATO AND JOHANNES EVERSE VOLUME 133. Bioluminescence and Chemiluminescence (Part B) Edited by MARLENE DELUCA AND WILLIAM D. MCELROY VOLUME 134. Structural and Contractile Proteins (Part C: The Contractile Apparatus and the Cytoskeleton) Edited by RICHARD B. VALLEE VOLUME 135. Immobilized Enzymes and Cells (Part B) Edited by KLAUS MOSBACH VOLUME 136. Immobilized Enzymes and Cells (Part C) Edited by KLAUS MOSBACH VOLUME 137. Immobilized Enzymes and Cells (Part D) Edited by KLAUS MOSBACH VOLUME 138. Complex Carbohydrates (Part E) Edited by VICTOR GINSBURG


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VOLUME 139. Cellular Regulators (Part A: Calcium- and Calmodulin-Binding Proteins) Edited by ANTHONY R. MEANS AND P. MICHAEL CONN VOLUME 140. Cumulative Subject Index Volumes 102–119, 121–134 VOLUME 141. Cellular Regulators (Part B: Calcium and Lipids) Edited by P. MICHAEL CONN AND ANTHONY R. MEANS VOLUME 142. Metabolism of Aromatic Amino Acids and Amines Edited by SEYMOUR KAUFMAN VOLUME 143. Sulfur and Sulfur Amino Acids Edited by WILLIAM B. JAKOBY AND OWEN GRIFFITH VOLUME 144. Structural and Contractile Proteins (Part D: Extracellular Matrix) Edited by LEON W. CUNNINGHAM VOLUME 145. Structural and Contractile Proteins (Part E: Extracellular Matrix) Edited by LEON W. CUNNINGHAM VOLUME 146. Peptide Growth Factors (Part A) Edited by DAVID BARNES AND DAVID A. SIRBASKU VOLUME 147. Peptide Growth Factors (Part B) Edited by DAVID BARNES AND DAVID A. SIRBASKU VOLUME 148. Plant Cell Membranes Edited by LESTER PACKER AND ROLAND DOUCE VOLUME 149. Drug and Enzyme Targeting (Part B) Edited by RALPH GREEN AND KENNETH J. WIDDER VOLUME 150. Immunochemical Techniques (Part K: In Vitro Models of B and T Cell Functions and Lymphoid Cell Receptors) Edited by GIOVANNI DI SABATO VOLUME 151. Molecular Genetics of Mammalian Cells Edited by MICHAEL M. GOTTESMAN VOLUME 152. Guide to Molecular Cloning Techniques Edited by SHELBY L. BERGER AND ALAN R. KIMMEL VOLUME 153. Recombinant DNA (Part D) Edited by RAY WU AND LAWRENCE GROSSMAN VOLUME 154. Recombinant DNA (Part E) Edited by RAY WU AND LAWRENCE GROSSMAN VOLUME 155. Recombinant DNA (Part F) Edited by RAY WU VOLUME 156. Biomembranes (Part P: ATP-Driven Pumps and Related Transport: The Na, K-Pump) Edited by SIDNEY FLEISCHER AND BECCA FLEISCHER

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VOLUME 157. Biomembranes (Part Q: ATP-Driven Pumps and Related Transport: Calcium, Proton, and Potassium Pumps) Edited by SIDNEY FLEISCHER AND BECCA FLEISCHER VOLUME 158. Metalloproteins (Part A) Edited by JAMES F. RIORDAN AND BERT L. VALLEE VOLUME 159. Initiation and Termination of Cyclic Nucleotide Action Edited by JACKIE D. CORBIN AND ROGER A. JOHNSON VOLUME 160. Biomass (Part A: Cellulose and Hemicellulose) Edited by WILLIS A. WOOD AND SCOTT T. KELLOGG VOLUME 161. Biomass (Part B: Lignin, Pectin, and Chitin) Edited by WILLIS A. WOOD AND SCOTT T. KELLOGG VOLUME 162. Immunochemical Techniques (Part L: Chemotaxis and Inflammation) Edited by GIOVANNI DI SABATO VOLUME 163. Immunochemical Techniques (Part M: Chemotaxis and Inflammation) Edited by GIOVANNI DI SABATO VOLUME 164. Ribosomes Edited by HARRY F. NOLLER, JR., AND KIVIE MOLDAVE VOLUME 165. Microbial Toxins: Tools for Enzymology Edited by SIDNEY HARSHMAN VOLUME 166. Branched-Chain Amino Acids Edited by ROBERT HARRIS AND JOHN R. SOKATCH VOLUME 167. Cyanobacteria Edited by LESTER PACKER AND ALEXANDER N. GLAZER VOLUME 168. Hormone Action (Part K: Neuroendocrine Peptides) Edited by P. MICHAEL CONN VOLUME 169. Platelets: Receptors, Adhesion, Secretion (Part A) Edited by JACEK HAWIGER VOLUME 170. Nucleosomes Edited by PAUL M. WASSARMAN AND ROGER D. KORNBERG VOLUME 171. Biomembranes (Part R: Transport Theory: Cells and Model Membranes) Edited by SIDNEY FLEISCHER AND BECCA FLEISCHER VOLUME 172. Biomembranes (Part S: Transport: Membrane Isolation and Characterization) Edited by SIDNEY FLEISCHER AND BECCA FLEISCHER


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VOLUME 173. Biomembranes [Part T: Cellular and Subcellular Transport: Eukaryotic (Nonepithelial) Cells] Edited by SIDNEY FLEISCHER AND BECCA FLEISCHER VOLUME 174. Biomembranes [Part U: Cellular and Subcellular Transport: Eukaryotic (Nonepithelial) Cells] Edited by SIDNEY FLEISCHER AND BECCA FLEISCHER VOLUME 175. Cumulative Subject Index Volumes 135–139, 141–167 VOLUME 176. Nuclear Magnetic Resonance (Part A: Spectral Techniques and Dynamics) Edited by NORMAN J. OPPENHEIMER AND THOMAS L. JAMES VOLUME 177. Nuclear Magnetic Resonance (Part B: Structure and Mechanism) Edited by NORMAN J. OPPENHEIMER AND THOMAS L. JAMES VOLUME 178. Antibodies, Antigens, and Molecular Mimicry Edited by JOHN J. LANGONE VOLUME 179. Complex Carbohydrates (Part F) Edited by VICTOR GINSBURG VOLUME 180. RNA Processing (Part A: General Methods) Edited by JAMES E. DAHLBERG AND JOHN N. ABELSON VOLUME 181. RNA Processing (Part B: Specific Methods) Edited by JAMES E. DAHLBERG AND JOHN N. ABELSON VOLUME 182. Guide to Protein Purification Edited by MURRAY P. DEUTSCHER VOLUME 183. Molecular Evolution: Computer Analysis of Protein and Nucleic Acid Sequences Edited by RUSSELL F. DOOLITTLE VOLUME 184. Avidin-Biotin Technology Edited by MEIR WILCHEK AND EDWARD A. BAYER VOLUME 185. Gene Expression Technology Edited by DAVID V. GOEDDEL VOLUME 186. Oxygen Radicals in Biological Systems (Part B: Oxygen Radicals and Antioxidants) Edited by LESTER PACKER AND ALEXANDER N. GLAZER VOLUME 187. Arachidonate Related Lipid Mediators Edited by ROBERT C. MURPHY AND FRANK A. FITZPATRICK VOLUME 188. Hydrocarbons and Methylotrophy Edited by MARY E. LIDSTROM VOLUME 189. Retinoids (Part A: Molecular and Metabolic Aspects) Edited by LESTER PACKER

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VOLUME 190. Retinoids (Part B: Cell Differentiation and Clinical Applications) Edited by LESTER PACKER VOLUME 191. Biomembranes (Part V: Cellular and Subcellular Transport: Epithelial Cells) Edited by SIDNEY FLEISCHER AND BECCA FLEISCHER VOLUME 192. Biomembranes (Part W: Cellular and Subcellular Transport: Epithelial Cells) Edited by SIDNEY FLEISCHER AND BECCA FLEISCHER VOLUME 193. Mass Spectrometry Edited by JAMES A. MCCLOSKEY VOLUME 194. Guide to Yeast Genetics and Molecular Biology Edited by CHRISTINE GUTHRIE AND GERALD R. FINK VOLUME 195. Adenylyl Cyclase, G Proteins, and Guanylyl Cyclase Edited by ROGER A. JOHNSON AND JACKIE D. CORBIN VOLUME 196. Molecular Motors and the Cytoskeleton Edited by RICHARD B. VALLEE VOLUME 197. Phospholipases Edited by EDWARD A. DENNIS VOLUME 198. Peptide Growth Factors (Part C) Edited by DAVID BARNES, J. P. MATHER, AND GORDON H. SATO VOLUME 199. Cumulative Subject Index Volumes 168–174, 176–194 VOLUME 200. Protein Phosphorylation (Part A: Protein Kinases: Assays, Purification, Antibodies, Functional Analysis, Cloning, and Expression) Edited by TONY HUNTER AND BARTHOLOMEW M. SEFTON VOLUME 201. Protein Phosphorylation (Part B: Analysis of Protein Phosphorylation, Protein Kinase Inhibitors, and Protein Phosphatases) Edited by TONY HUNTER AND BARTHOLOMEW M. SEFTON VOLUME 202. Molecular Design and Modeling: Concepts and Applications (Part A: Proteins, Peptides, and Enzymes) Edited by JOHN J. LANGONE VOLUME 203. Molecular Design and Modeling: Concepts and Applications (Part B: Antibodies and Antigens, Nucleic Acids, Polysaccharides, and Drugs) Edited by JOHN J. LANGONE VOLUME 204. Bacterial Genetic Systems Edited by JEFFREY H. MILLER VOLUME 205. Metallobiochemistry (Part B: Metallothionein and Related Molecules) Edited by JAMES F. RIORDAN AND BERT L. VALLEE


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VOLUME 206. Cytochrome P450 Edited by MICHAEL R. WATERMAN AND ERIC F. JOHNSON VOLUME 207. Ion Channels Edited by BERNARDO RUDY AND LINDA E. IVERSON VOLUME 208. Protein–DNA Interactions Edited by ROBERT T. SAUER VOLUME 209. Phospholipid Biosynthesis Edited by EDWARD A. DENNIS AND DENNIS E. VANCE VOLUME 210. Numerical Computer Methods Edited by LUDWIG BRAND AND MICHAEL L. JOHNSON VOLUME 211. DNA Structures (Part A: Synthesis and Physical Analysis of DNA) Edited by DAVID M. J. LILLEY AND JAMES E. DAHLBERG VOLUME 212. DNA Structures (Part B: Chemical and Electrophoretic Analysis of DNA) Edited by DAVID M. J. LILLEY AND JAMES E. DAHLBERG VOLUME 213. Carotenoids (Part A: Chemistry, Separation, Quantitation, and Antioxidation) Edited by LESTER PACKER VOLUME 214. Carotenoids (Part B: Metabolism, Genetics, and Biosynthesis) Edited by LESTER PACKER VOLUME 215. Platelets: Receptors, Adhesion, Secretion (Part B) Edited by JACEK J. HAWIGER VOLUME 216. Recombinant DNA (Part G) Edited by RAY WU VOLUME 217. Recombinant DNA (Part H) Edited by RAY WU VOLUME 218. Recombinant DNA (Part I) Edited by RAY WU VOLUME 219. Reconstitution of Intracellular Transport Edited by JAMES E. ROTHMAN VOLUME 220. Membrane Fusion Techniques (Part A) Edited by NEJAT DU¨ZGU¨NES, VOLUME 221. Membrane Fusion Techniques (Part B) Edited by NEJAT DU¨ZGU¨NES, VOLUME 222. Proteolytic Enzymes in Coagulation, Fibrinolysis, and Complement Activation (Part A: Mammalian Blood Coagulation Factors and Inhibitors) Edited by LASZLO LORAND AND KENNETH G. MANN

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VOLUME 223. Proteolytic Enzymes in Coagulation, Fibrinolysis, and Complement Activation (Part B: Complement Activation, Fibrinolysis, and Nonmammalian Blood Coagulation Factors) Edited by LASZLO LORAND AND KENNETH G. MANN VOLUME 224. Molecular Evolution: Producing the Biochemical Data Edited by ELIZABETH ANNE ZIMMER, THOMAS J. WHITE, REBECCA L. CANN, AND ALLAN C. WILSON VOLUME 225. Guide to Techniques in Mouse Development Edited by PAUL M. WASSARMAN AND MELVIN L. DEPAMPHILIS VOLUME 226. Metallobiochemistry (Part C: Spectroscopic and Physical Methods for Probing Metal Ion Environments in Metalloenzymes and Metalloproteins) Edited by JAMES F. RIORDAN AND BERT L. VALLEE VOLUME 227. Metallobiochemistry (Part D: Physical and Spectroscopic Methods for Probing Metal Ion Environments in Metalloproteins) Edited by JAMES F. RIORDAN AND BERT L. VALLEE VOLUME 228. Aqueous Two-Phase Systems Edited by HARRY WALTER AND GO¨TE JOHANSSON VOLUME 229. Cumulative Subject Index Volumes 195–198, 200–227 VOLUME 230. Guide to Techniques in Glycobiology Edited by WILLIAM J. LENNARZ AND GERALD W. HART VOLUME 231. Hemoglobins (Part B: Biochemical and Analytical Methods) Edited by JOHANNES EVERSE, KIM D. VANDEGRIFF, AND ROBERT M. WINSLOW VOLUME 232. Hemoglobins (Part C: Biophysical Methods) Edited by JOHANNES EVERSE, KIM D. VANDEGRIFF, AND ROBERT M. WINSLOW VOLUME 233. Oxygen Radicals in Biological Systems (Part C) Edited by LESTER PACKER VOLUME 234. Oxygen Radicals in Biological Systems (Part D) Edited by LESTER PACKER VOLUME 235. Bacterial Pathogenesis (Part A: Identification and Regulation of Virulence Factors) Edited by VIRGINIA L. CLARK AND PATRIK M. BAVOIL VOLUME 236. Bacterial Pathogenesis (Part B: Integration of Pathogenic Bacteria with Host Cells) Edited by VIRGINIA L. CLARK AND PATRIK M. BAVOIL VOLUME 237. Heterotrimeric G Proteins Edited by RAVI IYENGAR VOLUME 238. Heterotrimeric G-Protein Effectors Edited by RAVI IYENGAR


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VOLUME 239. Nuclear Magnetic Resonance (Part C) Edited by THOMAS L. JAMES AND NORMAN J. OPPENHEIMER VOLUME 240. Numerical Computer Methods (Part B) Edited by MICHAEL L. JOHNSON AND LUDWIG BRAND VOLUME 241. Retroviral Proteases Edited by LAWRENCE C. KUO AND JULES A. SHAFER VOLUME 242. Neoglycoconjugates (Part A) Edited by Y. C. LEE AND REIKO T. LEE VOLUME 243. Inorganic Microbial Sulfur Metabolism Edited by HARRY D. PECK, JR., AND JEAN LEGALL VOLUME 244. Proteolytic Enzymes: Serine and Cysteine Peptidases Edited by ALAN J. BARRETT VOLUME 245. Extracellular Matrix Components Edited by E. RUOSLAHTI AND E. ENGVALL VOLUME 246. Biochemical Spectroscopy Edited by KENNETH SAUER VOLUME 247. Neoglycoconjugates (Part B: Biomedical Applications) Edited by Y. C. LEE AND REIKO T. LEE VOLUME 248. Proteolytic Enzymes: Aspartic and Metallo Peptidases Edited by ALAN J. BARRETT VOLUME 249. Enzyme Kinetics and Mechanism (Part D: Developments in Enzyme Dynamics) Edited by DANIEL L. PURICH VOLUME 250. Lipid Modifications of Proteins Edited by PATRICK J. CASEY AND JANICE E. BUSS VOLUME 251. Biothiols (Part A: Monothiols and Dithiols, Protein Thiols, and Thiyl Radicals) Edited by LESTER PACKER VOLUME 252. Biothiols (Part B: Glutathione and Thioredoxin; Thiols in Signal Transduction and Gene Regulation) Edited by LESTER PACKER VOLUME 253. Adhesion of Microbial Pathogens Edited by RON J. DOYLE AND ITZHAK OFEK VOLUME 254. Oncogene Techniques Edited by PETER K. VOGT AND INDER M. VERMA VOLUME 255. Small GTPases and Their Regulators (Part A: Ras Family) Edited by W. E. BALCH, CHANNING J. DER, AND ALAN HALL VOLUME 256. Small GTPases and Their Regulators (Part B: Rho Family) Edited by W. E. BALCH, CHANNING J. DER, AND ALAN HALL

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VOLUME 257. Small GTPases and Their Regulators (Part C: Proteins Involved in Transport) Edited by W. E. BALCH, CHANNING J. DER, AND ALAN HALL VOLUME 258. Redox-Active Amino Acids in Biology Edited by JUDITH P. KLINMAN VOLUME 259. Energetics of Biological Macromolecules Edited by MICHAEL L. JOHNSON AND GARY K. ACKERS VOLUME 260. Mitochondrial Biogenesis and Genetics (Part A) Edited by GIUSEPPE M. ATTARDI AND ANNE CHOMYN VOLUME 261. Nuclear Magnetic Resonance and Nucleic Acids Edited by THOMAS L. JAMES VOLUME 262. DNA Replication Edited by JUDITH L. CAMPBELL VOLUME 263. Plasma Lipoproteins (Part C: Quantitation) Edited by WILLIAM A. BRADLEY, SANDRA H. GIANTURCO, AND JERE P. SEGREST VOLUME 264. Mitochondrial Biogenesis and Genetics (Part B) Edited by GIUSEPPE M. ATTARDI AND ANNE CHOMYN VOLUME 265. Cumulative Subject Index Volumes 228, 230–262 VOLUME 266. Computer Methods for Macromolecular Sequence Analysis Edited by RUSSELL F. DOOLITTLE VOLUME 267. Combinatorial Chemistry Edited by JOHN N. ABELSON VOLUME 268. Nitric Oxide (Part A: Sources and Detection of NO; NO Synthase) Edited by LESTER PACKER VOLUME 269. Nitric Oxide (Part B: Physiological and Pathological Processes) Edited by LESTER PACKER VOLUME 270. High Resolution Separation and Analysis of Biological Macromolecules (Part A: Fundamentals) Edited by BARRY L. KARGER AND WILLIAM S. HANCOCK VOLUME 271. High Resolution Separation and Analysis of Biological Macromolecules (Part B: Applications) Edited by BARRY L. KARGER AND WILLIAM S. HANCOCK VOLUME 272. Cytochrome P450 (Part B) Edited by ERIC F. JOHNSON AND MICHAEL R. WATERMAN VOLUME 273. RNA Polymerase and Associated Factors (Part A) Edited by SANKAR ADHYA VOLUME 274. RNA Polymerase and Associated Factors (Part B) Edited by SANKAR ADHYA


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VOLUME 275. Viral Polymerases and Related Proteins Edited by LAWRENCE C. KUO, DAVID B. OLSEN, AND STEVEN S. CARROLL VOLUME 276. Macromolecular Crystallography (Part A) Edited by CHARLES W. CARTER, JR., AND ROBERT M. SWEET VOLUME 277. Macromolecular Crystallography (Part B) Edited by CHARLES W. CARTER, JR., AND ROBERT M. SWEET VOLUME 278. Fluorescence Spectroscopy Edited by LUDWIG BRAND AND MICHAEL L. JOHNSON VOLUME 279. Vitamins and Coenzymes (Part I) Edited by DONALD B. MCCORMICK, JOHN W. SUTTIE, AND CONRAD WAGNER VOLUME 280. Vitamins and Coenzymes (Part J) Edited by DONALD B. MCCORMICK, JOHN W. SUTTIE, AND CONRAD WAGNER VOLUME 281. Vitamins and Coenzymes (Part K) Edited by DONALD B. MCCORMICK, JOHN W. SUTTIE, AND CONRAD WAGNER VOLUME 282. Vitamins and Coenzymes (Part L) Edited by DONALD B. MCCORMICK, JOHN W. SUTTIE, AND CONRAD WAGNER VOLUME 283. Cell Cycle Control Edited by WILLIAM G. DUNPHY VOLUME 284. Lipases (Part A: Biotechnology) Edited by BYRON RUBIN AND EDWARD A. DENNIS VOLUME 285. Cumulative Subject Index Volumes 263, 264, 266–284, 286–289 VOLUME 286. Lipases (Part B: Enzyme Characterization and Utilization) Edited by BYRON RUBIN AND EDWARD A. DENNIS VOLUME 287. Chemokines Edited by RICHARD HORUK VOLUME 288. Chemokine Receptors Edited by RICHARD HORUK VOLUME 289. Solid Phase Peptide Synthesis Edited by GREGG B. FIELDS VOLUME 290. Molecular Chaperones Edited by GEORGE H. LORIMER AND THOMAS BALDWIN VOLUME 291. Caged Compounds Edited by GERARD MARRIOTT VOLUME 292. ABC Transporters: Biochemical, Cellular, and Molecular Aspects Edited by SURESH V. AMBUDKAR AND MICHAEL M. GOTTESMAN VOLUME 293. Ion Channels (Part B) Edited by P. MICHAEL CONN

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VOLUME 294. Ion Channels (Part C) Edited by P. MICHAEL CONN VOLUME 295. Energetics of Biological Macromolecules (Part B) Edited by GARY K. ACKERS AND MICHAEL L. JOHNSON VOLUME 296. Neurotransmitter Transporters Edited by SUSAN G. AMARA VOLUME 297. Photosynthesis: Molecular Biology of Energy Capture Edited by LEE MCINTOSH VOLUME 298. Molecular Motors and the Cytoskeleton (Part B) Edited by RICHARD B. VALLEE VOLUME 299. Oxidants and Antioxidants (Part A) Edited by LESTER PACKER VOLUME 300. Oxidants and Antioxidants (Part B) Edited by LESTER PACKER VOLUME 301. Nitric Oxide: Biological and Antioxidant Activities (Part C) Edited by LESTER PACKER VOLUME 302. Green Fluorescent Protein Edited by P. MICHAEL CONN VOLUME 303. cDNA Preparation and Display Edited by SHERMAN M. WEISSMAN VOLUME 304. Chromatin Edited by PAUL M. WASSARMAN AND ALAN P. WOLFFE VOLUME 305. Bioluminescence and Chemiluminescence (Part C) Edited by THOMAS O. BALDWIN AND MIRIAM M. ZIEGLER VOLUME 306. Expression of Recombinant Genes in Eukaryotic Systems Edited by JOSEPH C. GLORIOSO AND MARTIN C. SCHMIDT VOLUME 307. Confocal Microscopy Edited by P. MICHAEL CONN VOLUME 308. Enzyme Kinetics and Mechanism (Part E: Energetics of Enzyme Catalysis) Edited by DANIEL L. PURICH AND VERN L. SCHRAMM VOLUME 309. Amyloid, Prions, and Other Protein Aggregates Edited by RONALD WETZEL VOLUME 310. Biofilms Edited by RON J. DOYLE VOLUME 311. Sphingolipid Metabolism and Cell Signaling (Part A) Edited by ALFRED H. MERRILL, JR., AND YUSUF A. HANNUN


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VOLUME 312. Sphingolipid Metabolism and Cell Signaling (Part B) Edited by ALFRED H. MERRILL, JR., AND YUSUF A. HANNUN VOLUME 313. Antisense Technology (Part A: General Methods, Methods of Delivery, and RNA Studies) Edited by M. IAN PHILLIPS VOLUME 314. Antisense Technology (Part B: Applications) Edited by M. IAN PHILLIPS VOLUME 315. Vertebrate Phototransduction and the Visual Cycle (Part A) Edited by KRZYSZTOF PALCZEWSKI VOLUME 316. Vertebrate Phototransduction and the Visual Cycle (Part B) Edited by KRZYSZTOF PALCZEWSKI VOLUME 317. RNA–Ligand Interactions (Part A: Structural Biology Methods) Edited by DANIEL W. CELANDER AND JOHN N. ABELSON VOLUME 318. RNA–Ligand Interactions (Part B: Molecular Biology Methods) Edited by DANIEL W. CELANDER AND JOHN N. ABELSON VOLUME 319. Singlet Oxygen, UV-A, and Ozone Edited by LESTER PACKER AND HELMUT SIES VOLUME 320. Cumulative Subject Index Volumes 290–319 VOLUME 321. Numerical Computer Methods (Part C) Edited by MICHAEL L. JOHNSON AND LUDWIG BRAND VOLUME 322. Apoptosis Edited by JOHN C. REED VOLUME 323. Energetics of Biological Macromolecules (Part C) Edited by MICHAEL L. JOHNSON AND GARY K. ACKERS VOLUME 324. Branched-Chain Amino Acids (Part B) Edited by ROBERT A. HARRIS AND JOHN R. SOKATCH VOLUME 325. Regulators and Effectors of Small GTPases (Part D: Rho Family) Edited by W. E. BALCH, CHANNING J. DER, AND ALAN HALL VOLUME 326. Applications of Chimeric Genes and Hybrid Proteins (Part A: Gene Expression and Protein Purification) Edited by JEREMY THORNER, SCOTT D. EMR, AND JOHN N. ABELSON VOLUME 327. Applications of Chimeric Genes and Hybrid Proteins (Part B: Cell Biology and Physiology) Edited by JEREMY THORNER, SCOTT D. EMR, AND JOHN N. ABELSON VOLUME 328. Applications of Chimeric Genes and Hybrid Proteins (Part C: Protein–Protein Interactions and Genomics) Edited by JEREMY THORNER, SCOTT D. EMR, AND JOHN N. ABELSON

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VOLUME 329. Regulators and Effectors of Small GTPases (Part E: GTPases Involved in Vesicular Traffic) Edited by W. E. BALCH, CHANNING J. DER, AND ALAN HALL VOLUME 330. Hyperthermophilic Enzymes (Part A) Edited by MICHAEL W. W. ADAMS AND ROBERT M. KELLY VOLUME 331. Hyperthermophilic Enzymes (Part B) Edited by MICHAEL W. W. ADAMS AND ROBERT M. KELLY VOLUME 332. Regulators and Effectors of Small GTPases (Part F: Ras Family I) Edited by W. E. BALCH, CHANNING J. DER, AND ALAN HALL VOLUME 333. Regulators and Effectors of Small GTPases (Part G: Ras Family II) Edited by W. E. BALCH, CHANNING J. DER, AND ALAN HALL VOLUME 334. Hyperthermophilic Enzymes (Part C) Edited by MICHAEL W. W. ADAMS AND ROBERT M. KELLY VOLUME 335. Flavonoids and Other Polyphenols Edited by LESTER PACKER VOLUME 336. Microbial Growth in Biofilms (Part A: Developmental and Molecular Biological Aspects) Edited by RON J. DOYLE VOLUME 337. Microbial Growth in Biofilms (Part B: Special Environments and Physicochemical Aspects) Edited by RON J. DOYLE VOLUME 338. Nuclear Magnetic Resonance of Biological Macromolecules (Part A) Edited by THOMAS L. JAMES, VOLKER DO¨TSCH, AND ULI SCHMITZ VOLUME 339. Nuclear Magnetic Resonance of Biological Macromolecules (Part B) Edited by THOMAS L. JAMES, VOLKER DO¨TSCH, AND ULI SCHMITZ VOLUME 340. Drug–Nucleic Acid Interactions Edited by JONATHAN B. CHAIRES AND MICHAEL J. WARING VOLUME 341. Ribonucleases (Part A) Edited by ALLEN W. NICHOLSON VOLUME 342. Ribonucleases (Part B) Edited by ALLEN W. NICHOLSON VOLUME 343. G Protein Pathways (Part A: Receptors) Edited by RAVI IYENGAR AND JOHN D. HILDEBRANDT VOLUME 344. G Protein Pathways (Part B: G Proteins and Their Regulators) Edited by RAVI IYENGAR AND JOHN D. HILDEBRANDT VOLUME 345. G Protein Pathways (Part C: Effector Mechanisms) Edited by RAVI IYENGAR AND JOHN D. HILDEBRANDT


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VOLUME 346. Gene Therapy Methods Edited by M. IAN PHILLIPS VOLUME 347. Protein Sensors and Reactive Oxygen Species (Part A: Selenoproteins and Thioredoxin) Edited by HELMUT SIES AND LESTER PACKER VOLUME 348. Protein Sensors and Reactive Oxygen Species (Part B: Thiol Enzymes and Proteins) Edited by HELMUT SIES AND LESTER PACKER VOLUME 349. Superoxide Dismutase Edited by LESTER PACKER VOLUME 350. Guide to Yeast Genetics and Molecular and Cell Biology (Part B) Edited by CHRISTINE GUTHRIE AND GERALD R. FINK VOLUME 351. Guide to Yeast Genetics and Molecular and Cell Biology (Part C) Edited by CHRISTINE GUTHRIE AND GERALD R. FINK VOLUME 352. Redox Cell Biology and Genetics (Part A) Edited by CHANDAN K. SEN AND LESTER PACKER VOLUME 353. Redox Cell Biology and Genetics (Part B) Edited by CHANDAN K. SEN AND LESTER PACKER VOLUME 354. Enzyme Kinetics and Mechanisms (Part F: Detection and Characterization of Enzyme Reaction Intermediates) Edited by DANIEL L. PURICH VOLUME 355. Cumulative Subject Index Volumes 321–354 VOLUME 356. Laser Capture Microscopy and Microdissection Edited by P. MICHAEL CONN VOLUME 357. Cytochrome P450, Part C Edited by ERIC F. JOHNSON AND MICHAEL R. WATERMAN VOLUME 358. Bacterial Pathogenesis (Part C: Identification, Regulation, and Function of Virulence Factors) Edited by VIRGINIA L. CLARK AND PATRIK M. BAVOIL VOLUME 359. Nitric Oxide (Part D) Edited by ENRIQUE CADENAS AND LESTER PACKER VOLUME 360. Biophotonics (Part A) Edited by GERARD MARRIOTT AND IAN PARKER VOLUME 361. Biophotonics (Part B) Edited by GERARD MARRIOTT AND IAN PARKER VOLUME 362. Recognition of Carbohydrates in Biological Systems (Part A) Edited by YUAN C. LEE AND REIKO T. LEE

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VOLUME 363. Recognition of Carbohydrates in Biological Systems (Part B) Edited by YUAN C. LEE AND REIKO T. LEE VOLUME 364. Nuclear Receptors Edited by DAVID W. RUSSELL AND DAVID J. MANGELSDORF VOLUME 365. Differentiation of Embryonic Stem Cells Edited by PAUL M. WASSAUMAN AND GORDON M. KELLER VOLUME 366. Protein Phosphatases Edited by SUSANNE KLUMPP AND JOSEF KRIEGLSTEIN VOLUME 367. Liposomes (Part A) Edited by NEJAT DU¨ZGU¨NES, VOLUME 368. Macromolecular Crystallography (Part C) Edited by CHARLES W. CARTER, JR., AND ROBERT M. SWEET VOLUME 369. Combinational Chemistry (Part B) Edited by GUILLERMO A. MORALES AND BARRY A. BUNIN VOLUME 370. RNA Polymerases and Associated Factors (Part C) Edited by SANKAR L. ADHYA AND SUSAN GARGES VOLUME 371. RNA Polymerases and Associated Factors (Part D) Edited by SANKAR L. ADHYA AND SUSAN GARGES VOLUME 372. Liposomes (Part B) Edited by NEJAT DU¨ZGU¨NES, VOLUME 373. Liposomes (Part C) Edited by NEJAT DU¨ZGU¨NES, VOLUME 374. Macromolecular Crystallography (Part D) Edited by CHARLES W. CARTER, JR., AND ROBERT W. SWEET VOLUME 375. Chromatin and Chromatin Remodeling Enzymes (Part A) Edited by C. DAVID ALLIS AND CARL WU VOLUME 376. Chromatin and Chromatin Remodeling Enzymes (Part B) Edited by C. DAVID ALLIS AND CARL WU VOLUME 377. Chromatin and Chromatin Remodeling Enzymes (Part C) Edited by C. DAVID ALLIS AND CARL WU VOLUME 378. Quinones and Quinone Enzymes (Part A) Edited by HELMUT SIES AND LESTER PACKER VOLUME 379. Energetics of Biological Macromolecules (Part D) Edited by JO M. HOLT, MICHAEL L. JOHNSON, AND GARY K. ACKERS VOLUME 380. Energetics of Biological Macromolecules (Part E) Edited by JO M. HOLT, MICHAEL L. JOHNSON, AND GARY K. ACKERS VOLUME 381. Oxygen Sensing Edited by CHANDAN K. SEN AND GREGG L. SEMENZA


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VOLUME 382. Quinones and Quinone Enzymes (Part B) Edited by HELMUT SIES AND LESTER PACKER VOLUME 383. Numerical Computer Methods (Part D) Edited by LUDWIG BRAND AND MICHAEL L. JOHNSON VOLUME 384. Numerical Computer Methods (Part E) Edited by LUDWIG BRAND AND MICHAEL L. JOHNSON VOLUME 385. Imaging in Biological Research (Part A) Edited by P. MICHAEL CONN VOLUME 386. Imaging in Biological Research (Part B) Edited by P. MICHAEL CONN VOLUME 387. Liposomes (Part D) Edited by NEJAT DU¨ZGU¨NES, VOLUME 388. Protein Engineering Edited by DAN E. ROBERTSON AND JOSEPH P. NOEL VOLUME 389. Regulators of G-Protein Signaling (Part A) Edited by DAVID P. SIDEROVSKI VOLUME 390. Regulators of G-Protein Signaling (Part B) Edited by DAVID P. SIDEROVSKI VOLUME 391. Liposomes (Part E) Edited by NEJAT DU¨ZGU¨NES, VOLUME 392. RNA Interference Edited by ENGELKE ROSSI VOLUME 393. Circadian Rhythms Edited by MICHAEL W. YOUNG VOLUME 394. Nuclear Magnetic Resonance of Biological Macromolecules (Part C) Edited by THOMAS L. JAMES VOLUME 395. Producing the Biochemical Data (Part B) Edited by ELIZABETH A. ZIMMER AND ERIC H. ROALSON VOLUME 396. Nitric Oxide (Part E) Edited by LESTER PACKER AND ENRIQUE CADENAS VOLUME 397. Environmental Microbiology Edited by JARED R. LEADBETTER VOLUME 398. Ubiquitin and Protein Degradation (Part A) Edited by RAYMOND J. DESHAIES VOLUME 399. Ubiquitin and Protein Degradation (Part B) Edited by RAYMOND J. DESHAIES VOLUME 400. Phase II Conjugation Enzymes and Transport Systems Edited by HELMUT SIES AND LESTER PACKER

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VOLUME 401. Glutathione Transferases and Gamma Glutamyl Transpeptidases Edited by HELMUT SIES AND LESTER PACKER VOLUME 402. Biological Mass Spectrometry Edited by A. L. BURLINGAME VOLUME 403. GTPases Regulating Membrane Targeting and Fusion Edited by WILLIAM E. BALCH, CHANNING J. DER, AND ALAN HALL VOLUME 404. GTPases Regulating Membrane Dynamics Edited by WILLIAM E. BALCH, CHANNING J. DER, AND ALAN HALL VOLUME 405. Mass Spectrometry: Modified Proteins and Glycoconjugates Edited by A. L. BURLINGAME VOLUME 406. Regulators and Effectors of Small GTPases: Rho Family Edited by WILLIAM E. BALCH, CHANNING J. DER, AND ALAN HALL VOLUME 407. Regulators and Effectors of Small GTPases: Ras Family Edited by WILLIAM E. BALCH, CHANNING J. DER, AND ALAN HALL VOLUME 408. DNA Repair (Part A) Edited by JUDITH L. CAMPBELL AND PAUL MODRICH VOLUME 409. DNA Repair (Part B) Edited by JUDITH L. CAMPBELL AND PAUL MODRICH VOLUME 410. DNA Microarrays (Part A: Array Platforms and Web-Bench Protocols) Edited by ALAN KIMMEL AND BRIAN OLIVER VOLUME 411. DNA Microarrays (Part B: Databases and Statistics) Edited by ALAN KIMMEL AND BRIAN OLIVER VOLUME 412. Amyloid, Prions, and Other Protein Aggregates (Part B) Edited by INDU KHETERPAL AND RONALD WETZEL VOLUME 413. Amyloid, Prions, and Other Protein Aggregates (Part C) Edited by INDU KHETERPAL AND RONALD WETZEL VOLUME 414. Measuring Biological Responses with Automated Microscopy Edited by JAMES INGLESE VOLUME 415. Glycobiology Edited by MINORU FUKUDA VOLUME 416. Glycomics Edited by MINORU FUKUDA VOLUME 417. Functional Glycomics Edited by MINORU FUKUDA VOLUME 418. Embryonic Stem Cells Edited by IRINA KLIMANSKAYA AND ROBERT LANZA


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VOLUME 419. Adult Stem Cells Edited by IRINA KLIMANSKAYA AND ROBERT LANZA VOLUME 420. Stem Cell Tools and Other Experimental Protocols Edited by IRINA KLIMANSKAYA AND ROBERT LANZA VOLUME 421. Advanced Bacterial Genetics: Use of Transposons and Phage for Genomic Engineering Edited by KELLY T. HUGHES VOLUME 422. Two-Component Signaling Systems, Part A Edited by MELVIN I. SIMON, BRIAN R. CRANE, AND ALEXANDRINE CRANE VOLUME 423. Two-Component Signaling Systems, Part B Edited by MELVIN I. SIMON, BRIAN R. CRANE, AND ALEXANDRINE CRANE VOLUME 424. RNA Editing Edited by JONATHA M. GOTT VOLUME 425. RNA Modification Edited by JONATHA M. GOTT VOLUME 426. Integrins Edited by DAVID CHERESH VOLUME 427. MicroRNA Methods Edited by JOHN J. ROSSI VOLUME 428. Osmosensing and Osmosignaling Edited by HELMUT SIES AND DIETER HAUSSINGER VOLUME 429. Translation Initiation: Extract Systems and Molecular Genetics Edited by JON LORSCH VOLUME 430. Translation Initiation: Reconstituted Systems and Biophysical Methods Edited by JON LORSCH VOLUME 431. Translation Initiation: Cell Biology, High-Throughput and Chemical-Based Approaches Edited by JON LORSCH VOLUME 432. Lipidomics and Bioactive Lipids: Mass-Spectrometry–Based Lipid Analysis Edited by H. ALEX BROWN VOLUME 433. Lipidomics and Bioactive Lipids: Specialized Analytical Methods and Lipids in Disease Edited by H. ALEX BROWN VOLUME 434. Lipidomics and Bioactive Lipids: Lipids and Cell Signaling Edited by H. ALEX BROWN VOLUME 435. Oxygen Biology and Hypoxia Edited by HELMUT SIES AND BERNHARD BRU¨NE

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VOLUME 436. Globins and Other Nitric Oxide-Reactive Protiens (Part A) Edited by ROBERT K. POOLE VOLUME 437. Globins and Other Nitric Oxide-Reactive Protiens (Part B) Edited by ROBERT K. POOLE VOLUME 438. Small GTPases in Disease (Part A) Edited by WILLIAM E. BALCH, CHANNING J. DER, AND ALAN HALL VOLUME 439. Small GTPases in Disease (Part B) Edited by WILLIAM E. BALCH, CHANNING J. DER, AND ALAN HALL VOLUME 440. Nitric Oxide, Part F Oxidative and Nitrosative Stress in Redox Regulation of Cell Signaling Edited by ENRIQUE CADENAS AND LESTER PACKER VOLUME 441. Nitric Oxide, Part G Oxidative and Nitrosative Stress in Redox Regulation of Cell Signaling Edited by ENRIQUE CADENAS AND LESTER PACKER VOLUME 442. Programmed Cell Death, General Principles for Studying Cell Death (Part A) Edited by ROYA KHOSRAVI-FAR, ZAHRA ZAKERI, RICHARD A. LOCKSHIN, AND MAURO PIACENTINI VOLUME 443. Angiogenesis: In Vitro Systems Edited by DAVID A. CHERESH VOLUME 444. Angiogenesis: In Vivo Systems (Part A) Edited by DAVID A. CHERESH VOLUME 445. Angiogenesis: In Vivo Systems (Part B) Edited by DAVID A. CHERESH VOLUME 446. Programmed Cell Death, The Biology and Therapeutic Implications of Cell Death (Part B) Edited by ROYA KHOSRAVI-FAR, ZAHRA ZAKERI, RICHARD A. LOCKSHIN, AND MAURO PIACENTINI VOLUME 447. RNA Turnover in Bacteria, Archaea and Organelles Edited by LYNNE E. MAQUAT AND CECILIA M. ARRAIANO VOLUME 448. RNA Turnover in Eukaryotes: Nucleases, Pathways and Analysis of mRNA Decay Edited by LYNNE E. MAQUAT AND MEGERDITCH KILEDJIAN VOLUME 449. RNA Turnover in Eukaryotes: Analysis of Specialized and Quality Control RNA Decay Pathways Edited by LYNNE E. MAQUAT AND MEGERDITCH KILEDJIAN VOLUME 450. Fluorescence Spectroscopy Edited by LUDWIG BRAND AND MICHAEL L. JOHNSON


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VOLUME 451. Autophagy: Lower Eukaryotes and Non-Mammalian Systems (Part A) Edited by DANIEL J. KLIONSKY VOLUME 452. Autophagy in Mammalian Systems (Part B) Edited by DANIEL J. KLIONSKY VOLUME 453. Autophagy in Disease and Clinical Applications (Part C) Edited by DANIEL J. KLIONSKY VOLUME 454. Computer Methods (Part A) Edited by MICHAEL L. JOHNSON AND LUDWIG BRAND VOLUME 455. Biothermodynamics (Part A) Edited by MICHAEL L. JOHNSON, JO M. HOLT, AND GARY K. ACKERS (RETIRED) VOLUME 456. Mitochondrial Function, Part A: Mitochondrial Electron Transport Complexes and Reactive Oxygen Species Edited by WILLIAM S. ALLISON AND IMMO E. SCHEFFLER VOLUME 457. Mitochondrial Function, Part B: Mitochondrial Protein Kinases, Protein Phosphatases and Mitochondrial Diseases Edited by WILLIAM S. ALLISON AND ANNE N. MURPHY VOLUME 458. Complex Enzymes in Microbial Natural Product Biosynthesis, Part A: Overview Articles and Peptides Edited by DAVID A. HOPWOOD VOLUME 459. Complex Enzymes in Microbial Natural Product Biosynthesis, Part B: Polyketides, Aminocoumarins and Carbohydrates Edited by DAVID A. HOPWOOD VOLUME 460. Chemokines, Part A Edited by TRACY M. HANDEL AND DAMON J. HAMEL

C H A P T E R

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Chemokines in Human Breast Tumor Cells: Modifying Their Expression Levels and Determining Their Effects on the Malignancy Phenotype Gali Soria, Tsipi Meshel, and Adit Ben-Baruch Contents 1. Introduction 2. Modifying Chemokine Expression in Breast Tumor Cells 2.1. Transfection (microporation) procedures: MCF-7, T47D, and MDA-MB-231 cells 2.2. Tumor cell handling after microporation 2.3. Determination of transfection outcome 3. Establishment of Primary Local Breast Tumors and Pulmonary Metastases 3.1. Formation of primary tumors by T47D cells 3.2. Formation of pulmonary metastases by MDA-MB-231 cells Acknowledgments References

4 5 5 8 9 9 10 12 15 15

Abstract Chemokines have been recently recognized as important regulators of breast malignancy; however, much remains unknown regarding their roles in this disease. Improved understanding of chemokine contribution to breast cancer often requires studies in which the expression levels of chemokines by the tumor cells are modified (increased or decreased). In addition, it is essential to determine the roles of various chemokines in experimental in vivo model systems of breast cancer, using hormone-dependent or -independent human breast tumor cells (such as MCF-7, T47D and MDA-MB-231 cells). Since investigators often encounter difficulties in implementing these techniques in their studies of breast cancer, we hereby provide a detailed description of microporation approaches for modifying chemokine expression levels in human breast tumor cells, and of the measures

Department of Cell Research and Immunology, George S. Wise Faculty of Life Sciences, Tel Aviv University, Tel Aviv, Israel Methods in Enzymology, Volume 460 ISSN 0076-6879, DOI: 10.1016/S0076-6879(09)05201-X

#

2009 Elsevier Inc. All rights reserved.

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required for establishment of xenograft models of primary tumors and of metastasis by such cells. In the breast malignancy context, the guidelines presented herein should enable researchers in the field to establish essential means for determination of chemokine roles in this disease.

1. Introduction A large body of evidence indicates that chemokines are major regulators of malignancy, acting at many different levels to reduce or to promote tumor development and/or progression (Ben-Baruch, 2006a). Chemokine activities in malignancy are mediated primarily by their ability to induce chemotaxis of leukocytes, endothelial cells, and/or the tumor cells. Indeed, it is known that specific chemokines chemoattract to tumor sites leukocyte subpopulations that may promote antitumor activities (such as Th1 cells or natural killer cells), while other chemokines are responsible for large quantities of deleterious tumor-associated macrophages (TAM) at tumor sites (Allavena et al., 2007; Ben-Baruch, 2006a; Soria and Ben-Baruch, 2008; Vandercappellen et al., 2008). In parallel, specific chemokines upregulate endothelial cell migration and proliferation, therefore promoting angiogenesis, whereas other chemokines have powerful angiostatic properties (BenBaruch, 2006a; Salcedo and Oppenheim, 2003; Strieter et al., 2006). Another very important activity of chemokines is induction of tumor cell invasion and migration, thereby playing key roles in dictating site-directed metastasis formation (Ben-Baruch, 2006a, 2007; Zlotnik et al., 2006). Chemokines can execute such multifaceted roles in malignancy because they are expressed by cells of the tumor microenvironment, and in many cases also by the tumor cells themselves. As such, they can affect through autocrine pathways the ability of the cancer cells to express tumorpromoting functions, and can also act in paracrine manners on host cells, thereby influencing their roles in malignancy. Of the various malignant diseases, breast cancer has attracted the attention of many researchers, whose joint efforts have provided improved insights into the roles of chemokines in disease development and progression (Ben-Baruch, 2006a,b, 2007; Soria and Ben-Baruch, 2008; Zlotnik et al., 2006). However, our understanding of chemokine roles in breast cancer is only at its beginning, and extensive research is required in order to enable improved use of chemokines for diagnostic, prognostic, or therapeutic purposes in this disease. To enable better elucidation of the roles played by specific chemokines in breast malignancy, it is necessary to define the autocrine and paracrine effects of tumor-cell–derived chemokines. Such analyses are enabled by studies modulating chemokine expression levels in the tumor cells, either

Chemokine Expression and Effects in Breast Cancer

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increasing them by overexpression or reducing them by different measures, such as siRNA. In parallel, it is important to determine the effects of chemokine expression levels on tumor growth and metastasis in animal model systems. This can be done by using breast tumor cells that express chemokines endogenously, or alternatively with cells whose chemokine expression levels were modified by appropriate measures. Many researchers find it difficult to reach high transfection yields in breast cancer cells, including the routinely used MCF-7, T47D, and MDAMB-231 cells. In addition, investigators often encounter difficulties in establishing tumors of hormone-dependent human breast tumor cells, or pulmonary metastases. To comply with the needs of investigators in the field, we hereby provide detailed methods for successful modification of chemokine expression levels in human breast tumor cells, by microporation. Thereafter, we describe the procedures of forming primary xenograft tumors by human breast tumor cells in the mammary fat pad of mice, and producing ‘‘experimental’’ pulmonary metastases in female mice.

2. Modifying Chemokine Expression in Breast Tumor Cells In this part, we provide the optimal conditions and procedures for modifying chemokine expression in human breast tumor cells, by microporation. Microporation is a unique electroporation technology using a pipette tip as an electroporation space (http://www.microporator.com). The protocols include microporations of the MCF-7 and T47D hormone-dependent human breast carcinoma cell lines, and of the MDAMB-231 cells that are hormone independent (for details on the cells, please consult the guidelines of the American Type Culture Collection [ATCC]). Using microporation, a high success rate of over 60 to 80% transient transfection can be achieved in the above mentioned breast tumor cells with a variety of vectors, including HA or GFP-tagged vectors coding for chemokines. If selection-carrying vectors are used, one can proceed to establishment of cell populations stably overexpressing the chemokines. Alternatively, the same transfection conditions could be used with the pSUPER vector for expression of short interfering RNA; however, in this case it is essential to have a selective marker that would enable formation of stable transfectants.

2.1. Transfection (microporation) procedures: MCF-7, T47D, and MDA-MB-231 cells Based on our experience, we recommend using the microporation technology in order to transfect the above mentioned breast tumor cells. The MicroPorator (MP-100 MicroPorator) and its accompanying devices and

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materials are manufactured by Digital Bio (Seoul, Korea) (http://www. microporator.com). The manufacturer’s instructions include recommended conditions for microporation of a variety of cell types, including MCF-7, T47D, and MDA-MB-231 cells. Nevertheless, we have performed careful calibrations for microporation of MCF-7 and T47D cells, leading to improved transfection yields and cell survival rates (please see below). Accordingly, we provide detailed microporation conditions for these two cell lines. For MDA-MB-231 cells, we describe one of the three conditions that were recommended by the manufacturer, which we found highly suitable in terms of transfection yields and cell viability. 2.1.1. Required materials Devices and materials of the microporation apparatus Digital Bio (http:// www.microporator.com) provides the main device (MP-100 MicroPorator), Pipette Station, MicroPorator pipettes, gold-tips, microporation tubes, and buffers (Buffer R, resuspension buffer; Buffer E, electrolytic buffer). Additional materials

Cells of interest: MCF-7, T47D, and MDA-MB-231 cells can all be obtained from the American Type Culture Collection (ATCC). DNA of interest: DNA of high quality (endotoxin-free plasmid DNA) is recommended, although lower-grade DNA would also allow reasonable yields of transfection. Growth medium: The growth medium for the cells contains DMEM supplemented with 10% FCS and 2% glutamine. Antibiotics (e.g., penicillin, streptomycin, nystatin) could be used during cell growth, but should be avoided in the microporation stage (see Section 2.1.2). Although MCF-7 and T47D cells are hormone dependent, in most laboratories they are routinely grown in culture without estrogen (17b-estradiol, E2) or progesterone. Under these conditions, the cells are highly proliferative, and respond well to a variety of stimuli without hormone supplementation. However, the growth of these cells in in vivo xenograft models depends exclusively on estrogen (see Section 3). Please note that in specific studies there may be a need, or interest, to perform experiments in cells that were stimulated by the relevant hormones, estrogen or estrogen þ progesterone. In such case, the cells are routinely grown without the hormones, and are then exposed to a cycle of stimulation by the hormones. Cells undergoing hormonal treatment should be grown in phenol-red free medium, supplemented by charcoalstripped serum. For cell growth with estrogen only, the hormone (E8875, Sigma Aldrich, St. Louis, MO) is added at 10–8 or 10–9 M, for 3 to 7 consecutive days (conditions used vary by laboratory). The culture medium (phenol-red free, including charcoal-stripped serum) should be


7

replaced daily. For estrogen þ progesterone stimulation, the cells are cultured first with estrogen for 1 day (as above), and for additional 2 days in the presence of estrogen þ progesterone (progesterone: P6149, Sigma), both at 108 M. As before, the medium (phenol-red free, including charcoal-stripped serum) should be replaced daily. Other reagents

Trypsin-EDTA solution (trypsin 0.25%, EDTA 0.05%) Caþþ and Mgþþ-free PBS1

Disposables

1.5-ml (Eppendorf) and 10-ml tubes 6 and 10-cm tissue culture plates

2.1.2. Tumor cell preparation for microporation One day prior to microporation Culture the cells in a 10 cm tissue culture plate with fresh growth medium. The cells should reach 60 to 80% confluency on the microporation day. On the day of microporation You will need warm trypsin solution for cell removal from growth plates. You also need warm growth medium for trypsin neutralization, and for the microporation procedure (See note at the end of the paragraph). Therefore, prewarm an aliquot of the trypsin solution and of the growth medium at 37 . Following microporation, you will need to transfer the cells from each microporation tube to a tissue culture plate with growth medium containing serum and supplements. For T47D cells, use a 6 cm tissue culture plate with 3 ml medium for each microporation; for MCF-7 and MDA-MB-231 cells, use a 10 cm tissue culture plate with 8 ml of medium for each microporation. Prepare such plate/s in advance, in a humidified 37 , 5% CO2 incubator. Note: Do not add antibiotics (e.g., penicillin, streptomycin, nystatin) to the growth medium, which is added to the cells prior to microporation. The antibiotics can be added afterward to the collecting tissue culture plates, used at the end of the microporation stage. Prior to the microporation step itself, prepare the cells together with the DNA. To this end, trypsinize the cells with trypsin-EDTA solution, neutralize the trypsin by antibiotic free, serum-containing growth medium. The procedure described below is suitable for one transfection of 1.2 106 cells: Pellet your pool of tumor cells at 1200 rpm (140g) for 7 min at room temperature (RT). Count the cells and pellet 1.2 106 cells in 1.5 ml (Eppendorf ) tube at 2000 rpm (400g) for 3 min at RT. Following cell washing

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in 1 ml of Caþþ and Mgþþ-free PBSx1, resuspend the cell pellet in 120 ml buffer R (107 cells/ml). Add 5 mg of plasmid DNA into the 1.5 ml tube and gently pipette the cells up and down. Avoid storing the tube longer than 15 to 30 min at RT, as this would reduce transfection efficiency and cell viability. 2.1.3. Microporation The microporations are done in 10-ml or 100-ml gold-tips, which are inserted into the microporation tube. The size of the tip, whether 10 ml or 100 ml, depends on the amount of cells undergoing microporation, according to the manufacturer’s instructions. For example, for microporation of 1.2 106 cells, use a 100-ml gold-tip. Please note that you first need to prepare the microporation apparatus and set up the pulse conditions. Only then can you proceed to perform the microporation step itself.

Preparation of the microporation apparatus: To prepare the apparatus, add 3 ml of Buffer E into the microporation tube. Then set up the pulse conditions of the pipette station, as follows: For MCF-7 cells: pulse voltage, 1100; pulse width, 20; pulse number, 2. For T47D cells: pulse voltage, 1100; pulse width, 20; pulse number, 2. For MDA-MB-231 cells: pulse voltage, 1350; pulse width, 20; pulse number, 2. Performing the microporation: The following details are suitable for each microporation of 1.2 106 cells by a 100-ml gold-tip: Mix the cell-DNA mixture gently with a standard pipette, and then aspirate the cell-DNA mixture using the MicroPorator pipette carrying the gold-tip. Avoid air bubbles during pipetting (the smallest air bubble would induce a spark that will ruin the transfection). Afterward, insert the MicroPorator pipette into the Pipette Station and press the Start button on the LCD panel. When the high-voltage button turns red, press it to transfect by the MicroPorator. After the pulse, immediately transfer the cell sample into the 6-cm plate (for T47D cells) or 10-cm plate (for MCF-7 and MDAMB-231 cells) that was prepared in advance with warm growth medium (can include antibiotics).

2.2. Tumor cell handling after microporation Immediately after the microporation, rock the plates gently to ensure even distribution of the cells. Next, incubate the plate at 37 in a humidified CO2 incubator. In transient transfections, checking the chemokine expression 2 days after microporation is advised. For establishment of cell populations that express the vector in a stable fashion, add the appropriate antibiotic 1 or 2 days after the microporation, as applicable.

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CCL5 extracellular expression (OD–450 nm)

1.4 1.2

*

1 0.8 0.6 0.4 0.2 0

pE-GFP

pE-GFP-CCL5

Figure 1.1 Overexpression of CCL5 in MCF-7 human breast carcinoma cells. MCF-7 cells were transfected with pE-GFP or pE-GFP-CCL5 vectors, following the procedures detailed above. Stable transfectants of both cell types were cultured under similar conditions for 24 h in serum-free medium.The expression of secreted CCL5 was determined in cell supernatants of stable transfectants by ELISA assays, using coating and detecting antibodies to GFP.The high expression levels of CCL5 in pE-GFP-CCL5 transfectants, as compared to the pE-GFP control transfected cells, were confirmed by ELISA assays with coating and detecting antibodies to CCL5 (data not shown). The analyses were done at the linear range of absorbance (*p ¼ 0.03).

2.3. Determination of transfection outcome According to the vectors used for transfection, and whether overexpression or downregulation of chemokine expression was performed, chemokine expression in the transfected cells can be determined in several ways. Although this chapter does not discuss in detail the methods for determination of transfection outcome, we would like to note that chemokine expression could be evaluated by ELISA assays, Western blots, FACS analyses, and/or confocal analyses (e.g., if a GFP-carrying vector was used). Accordingly, Fig. 1.1 shows the overexpression of CCL5 in stable MCF-7 transfectants, determined by ELISA.

3. Establishment of Primary Local Breast Tumors and Pulmonary Metastases In this section, we provide detailed description of the methods for establishment of primary tumors and pulmonary metastases in xenograft model systems using human breast cancer cells. Procedures are given for two cell types, T47D and MDA-MB-231. (See note concerning MCF-7 cells.

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For details on the cells, consult the guidelines of the American Type Culture Collection [ATCC].)

T47D cells: When the appropriate conditions are used, these hormonedependent human breast cancer cells give a high yield of primary local tumors in the mammary fat pad of female mice. However, due to their relatively mild aggressiveness, these cells do not form metastases.

Note: Similar to T47D cells, tumor formation by MCF-7 cells is highly dependent on estrogen supplementation. In essence, it is expected that the procedure for in vivo tumor formation by MCF-7 cells would follow the guidelines of T47D cells. Nevertheless, laboratories use different variants of these cells, such as the MCF-7-ras cells (expressing activated ras oncogene), which form tumors in the absence of exogenous estrogen and form pulmonary metastases as well (Karnoub et al., 2007; Orimo et al., 2005).

MDA-MB-231 cells: These are highly metastatic, hormone-independent human breast carcinoma cells. In procedures of intravenous injection of the tumor cells, these cells form ‘‘experimental’’ pulmonary metastasis (in contrast to ‘‘spontaneous’’ pulmonary metastases, which are derived from the primary tumor) with very high yield.

To elucidate the roles of chemokines in tumor growth and metastasis formation, many different measures could be taken. Between others, they include overexpression of chemokines or of chemokine knock-down in the tumor cells, as described above. In these cases, one should consider the use of vectors in which the transcription of the chemokine can be controlled in vivo.

3.1. Formation of primary tumors by T47D cells As indicated above (Section 2.1.1), although T47D cells are hormonedependent, they are usually kept in culture without estrogen/progesterone supplementation. Under these conditions, the cells proliferate and respond well to a variety of stimuli. In case of need or interest, estrogen (with or without progesterone) can be added to the cells (as described in Section 2.1.1). In contrast, the in vivo growth of T47D cells is strictly dependent on estrogen supplementation. Therefore, 9 to 10 days prior to tumor cell injection, the mice have to be implanted with estrogen pellets (details follow). In addition, the cells are injected together with matrigel, shown to be extremely useful in establishing xenografts by many human cancer cell lines (Mullen et al., 1996). The matrigel is a solubilized tissue basement membrane matrix rich in extracellular matrix proteins, which was originally isolated from the Engelbreth-Holm-Swarm (EHS) mouse tumor.


11

3.1.1. Required materials Mice and supplementary material for tumor cell injection

Mice: Female SCID mice, 6 to 8 weeks of age (e.g., CB-17-SCID-BG mice, Harlan, Indianapolis, IN, catalog no. 2CB17BG25). Estrogen pellets: 17b-estradiol, 60-day–release pellets of 1.7 mg/pellet (Innovative Research of America, Sarasota, FL) Trochar: 10-gauge (MP-182, Innovative Research of America) Matrigel (FAL356234, BD Biosciences) Growth medium and trypsin-EDTA solution (as above) PBS1

Disposables

1.5-ml (Eppendorf ) tubes, 10-ml round-bottom tubes, 1 ml-syringes, needles (25 gauge)

3.1.2. Mice handling prior to tumor cell inoculation Maintain a colony of female SCID mice under specific pathogen-free (SPF) conditions. This includes autoclaved water and food, and filtered cages. Let mice acclimatize for 3 to 5 days prior to implantation of estrogen pellets. The implantation of the pellets is performed 9 to 10 days prior to injection of the tumor cells. The pellets are implanted with trochar to the lateral side of the neck of the mouse. To this end, put the estrogen pellet in a standing position on the needle of the trochar away from sharp edge. Press the trochar gently, so that the estrogen pellet would be stable in this position (if the trochar is pointed downward, the pellet should not fall). Hold the trochar with your stronger hand. With the other hand, lift skin on the lateral side of the neck of the mouse and insert the trochar. When the pellet contacts the skin, twist the trochar sideways and insert pellet. 3.1.3. Tumor cell preparation One day prior to tumor cell injection A day before tumor cell injection, you need to pre-prepare both the matrigel and the cells. The matrigel forms a highly viscous gel above 10 . To avoid this gel formation, the matrigel should be kept cold throughout the experimental stages. To this end, put the matrigel 1 day prior to the injection at 4 . Also, cool to 4 all the necessary equipments (syringes, needles, pipettes, etc.). T47D cells should be cultured 1 day before their injection in 10-cm tissue-culture plates with fresh growth medium, so that they will reach 60 to 80% confluency on the injection day.

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Gali Soria et al.

On the day of tumor cell injection T47D cells are injected at concentration of 5 105 cells/100 ml, 100 ml/mouse in a suspension that contains matrigel. The procedure provided below is suitable for injection to 20 mice. Note that the amounts of cells and matrigel that are given below are suitable for 40 mice: They were calculated in a large excess due to a considerable loss of material at the time of cell injection. On the whole, you would need 2 107 cells. On the day of cell injection, prewarm an aliquot of the culture medium and the trypsin-EDTA solution. Trypsinize the cells, neutralize the trypsin with serum-containing growth medium, and centrifuge the cells at 1200 rpm (140g) for 7 min at 4 . Next, resuspend the pelleted cells in growth medium and after counting them, transfer 2 107 cells to a 10-ml round bottom tube. Pellet the cells by centrifugation as above, wash them with 10 ml PBS 1, aspirate the PBS, and transfer the resuspended cells to 4 . Adjust the volume to 2 ml with fresh and ice-cold PBS 1, and mix the cell suspension with 2 ml of ice-cold matrigel. The resulting cell-matrigel mixture would be at a final concentration of 5 106 cells/ml. To avoid warming of the cell-matrigel mixture, and due to its high viscosity, aliquoting the cell-matrigel mixture into several aliquots is advised. In the specific example given previously, the cells can be aliquoted to eight 1.5-ml (Eppendorf) tubes, each containing 500 ml of the cell-matrigel mixture. Keep the tubes on wet ice until injection.

3.1.4. Tumor cell inoculation to mice Tumor cell injection is done subcutaneously at the mammary fat pad. Mix gently one aliquot of cell-matrigel mixture. Draw 100 ml of the mixture into 1-ml syringe without a needle. Then, add a 25-gauge needle, and inject cells slowly (5 to 6 s) to the lower-right mammary fat pad of the mouse. 3.1.5. Determining tumor growth and survival Tumors start developing within several days following tumor cell injection (Fig. 1.2A), at times in proximity to the abdomen surface, and in others internally. Follow tumor establishment daily, feeling the developing tumors with your fingertips. Determine the lag period until tumor appearance and survival of the mice. The size of the tumors in three dimensions can be determined by calibrated caliper in excised tumors, after sacrificing the mice.

3.2. Formation of pulmonary metastases by MDA-MB-231 cells 3.2.1. Required materials Mice and supplementary material for tumor cell injection

Mice: Female SCID mice, 6 to 8 weeks of age (e.g., CB-17-SCID-BG mice, Harlan, Indianapolis, IN, catalog no. 2CB17BG25)

13


% Mice with tumors

A

120 100 80 60 40 20 0

0

5

B

10 Days

15

20

C Mouse no.

Number of metastases *

1 2 3 4 5 6 7

>300 >300 240 211 138 134 +++

Figure 1.2 Formation of primary tumors and pulmonary metastases by human breast carcinoma cells in female SCID mice. (A) Formation of primary tumors in the mammary fat pad of female SCID mice byT47D cells. T47D cells were injected subcutaneously to the mammary fat pads of five female SCID mice, in concentrations of 5 105 cells/100 ml, 100 ml per mouse. Tumor formation was followed daily. (B) Formation of pulmonary metastases in female SCID mice by MDA-MB-231 cells. MDA-MB-231 cells were injected intravenously to the tail vein of seven female SCID mice, in concentrations of 7.5 105 cells/100 ml, 100 ml per mouse. The mice were sacrificed 21 days after tumor cell inoculation. Metastases were counted following injection of india ink solution. *In all cases, micrometastases were present, but they were not counted. þþþA mouse in which only micrometastases were detected. (C) White pulmonary metastases detected against the black background of india ink^stained lung.

Growth medium and trypsin-EDTA solution (as above) PBS 1

Other materials

India ink solution (15% india ink, 85% water, 3 drops NH4OH/100 ml) Feket’s solution (300 ml 70% ethanol, 30 ml 37% formaldehyde, 5 ml glacial acetic acid) Lamp (to warm the mice) and restraining tube (for holding the mice) Disposables:

10 ml round bottom tubes, 1-ml syringes, needles (25 gauge)

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Gali Soria et al.

3.2.2. Mice handling prior to tumor cell inoculation Maintain a colony of female SCID mice under specific pathogen-free (SPF) conditions. This includes autoclaved water and food, and filtered cages. Let mice acclimatize for 3 to 5 days prior to tumor cell injection. 3.2.3. Tumor cell preparation One day prior to tumor cell injection One day prior to tumor cell injection, transfer the MDA-MB-231 tumor cells into a 10-cm tissue culture plate with fresh growth medium, to reach 60 to 80% confluency on the day of injection. On the day of tumor cell injection The MDA-MB-231 cells are injected at a concentration of 7.5 105 cells/100 ml, 100 ml/mouse. The procedure provided in the following is suitable for injection of 20 mice. On the whole, you would need a total of 1.5 107 cells; however, preparing extra cells, such as a total of 2 107 cells, is advisable. On the day of tumor cell injection, prewarm an aliquot of culture medium and the trypsin-EDTA solution. Following cell trypsinization, neutralize the trypsin with serum-containing growth medium, and centrifuge the cells at 1200 rpm (140g) for 7 min at 4 . Next, resuspend the cell pellet with 5 ml of growth medium and count the cells. Transfer 2 107 cells to a 10-ml round-bottom tube and pellet the cells by centrifugation at 1200 rpm for 7 min at 4 . Wash the cells with 10 ml PBS 1 and aspirate the PBS, and then add fresh PBS 1 to a final volume of 2.7 ml, leading to final cell concentration of 7.5 106 cells/ml. Keep the cells on ice until injection of the tumor cells.

3.2.4. Tumor cell inoculation to mice The MDA-MB-231 cells are routinely injected intravenously. To this end, warm mice with a lamp until they rub their faces and veins are visible. Following gentle cell mixing, load a syringe with the cells, and tap the bubbles out. Place mouse in restraining tube, pulling gently on the tail until taut, rub the tail with 70% alcohol, and inject the tumor cells into the tail vein. Wipe with tissue. 3.2.5. Determining formation of pulmonary metastases Upon intravenous injection, MDA-MB-231 cells give rise to a large number of pulmonary metastases. One cannot detect metastases without sacrificing the mice; therefore, you need to follow the mice daily and sacrifice them when they weaken, that is, when their fur is not shiny and their appearance seems abnormal. A heavy load of metastases usually develops within 3 weeks after tumor cell injection (Fig. 1.2B).


15

For determination of pulmonary metastases, sacrifice the mice according to local procedures; avoid neck dislocation. Pulmonary metastases are detected by intratracheal injection of india ink solution, which stains the lungs black, leaving the white metastases visible (Fig. 1.2C). To this end, the trachea of the dead animal should be dissected free from the surrounding structures (e.g., by putting tweezers under the trachea). The india ink solution (2 to 4 ml) should be injected via the trachea into the lungs until each of the lobes is inflated and stains black. Dislocate the lungs and wash the india ink in double-distilled water. Next, place the lungs in fresh Feket’s solution for 24 h at RT. In parallel to weighing the lungs, count white metastases against the black color of the lung background. Please note that when a heavy metastatic load is obtained, some of the metastases may merge together, and counting may be difficult. In such a case, a binocular may be of assistance, enabling a certain degree of discrimination between the merging metastases.

ACKNOWLEDGMENTS The research relevant to this paper was supported by The Israel Science Foundation; The Israel Cancer Association; The Ela Kodesz Institute for Research on Cancer Development and Prevention; The Federico Foundation.

REFERENCES Allavena, P., Sica, A., Solinas, G., Porta, C., and Mantovani, A. (2007). The inflammatory micro-environment in tumor progression: The role of tumor-associated macrophages. Crit. Rev. Oncol. Hematol. 67, 11438–11446. Ben-Baruch, A. (2006a). The multifaceted roles of chemokines in malignancy. Cancer Metastasis Rev. 25, 357–371. Ben-Baruch, A. (2006b). ‘‘Pro-malignancy and putative anti-malignancy chemokines in the regulation of breast cancer progression.’’ In Veskler, Barbara A., ed., Focus on Immunology Research, pp. 1–46. Nova Science Publisher, New York. Ben-Baruch, A. (2007). Organ selectivity in metastasis: Regulation by chemokines and their receptors. Clin. Exp. Metastasis 25, 345–356. Karnoub, A. E., Dash, A. B., Vo, A. P., Sullivan, A., Brooks, M. W., Bell, G. W., Richardson, A. L., Polyak, K., Tubo, R., and Weinberg, R. A. (2007). Mesenchymal stem cells within tumour stroma promote breast cancer metastasis. Nature 449, 557–563. Mullen, P., Ritchie, A., Langdon, S. P., and Miller, W. R. (1996). Effect of Matrigel on the tumorigenicity of human breast and ovarian carcinoma cell lines. Int. J. Cancer 67, 816–820. Orimo, A., Gupta, P. B., Sgroi, D. C., Arenzana-Seisdedos, F., Delaunay, T., Naeem, R., Carey, V. J., Richardson, A. L., and Weinberg, R. A. (2005). Stromal fibroblasts present in invasive human breast carcinomas promote tumor growth and angiogenesis through elevated SDF-1/CXCL12 secretion. Cell 121, 335–348. Salcedo, R., and Oppenheim, J. J. (2003). Role of chemokines in angiogenesis: CXCL12/ SDF-1 and CXCR4 interaction, a key regulator of endothelial cell responses. Microcirculation 10, 359–370.

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Soria, G., and Ben-Baruch, A. (2008). The inflammatory chemokines CCL2 and CCL5 in breast cancer. Cancer Lett. 267, 281–285. Strieter, R. M., Burdick, M. D., Mestas, J., Gomperts, B., Keane, M. P., and Belperio, J. A. (2006). Cancer CXC chemokine networks and tumour angiogenesis. Eur. J. Cancer 42, 768–778. Vandercappellen, J., Van Damme, J., and Struyf, S. (2008). The role of CXC chemokines and their receptors in cancer. Cancer Lett. 267, 226–244. Zlotnik, A., Yoshie, O., and Nomiyama, H. (2006). The chemokine and chemokine receptor superfamilies and their molecular evolution. Genome Biol. 7, 243.

C H A P T E R

T W O

CCR5 Pharmacology Methodologies and Associated Applications Roy Mansfield,* Sarah Able,* Paul Griffin,* Becky Irvine,* Ian James,* Malcolm Macartney,* Ken Miller,† James Mills,* Carolyn Napier,* Iva Navratilova,* Manos Perros,* Graham Rickett,* Harriet Root,* Elna van der Ryst,* Mike Westby,* and Patrick Dorr* Contents 1. Introduction 2. CCR5 Signaling Assays and Application to Quantify and Characterize Ligand-Dependent Agonism, Antagonism, and Inverse Agonism 2.1. CCR5-mediated Ca2þ signaling 2.2. CCR5 cellular internalization assay 2.3. Application of CCR5 receptor internalization assay to investigate antagonist-dependent functional receptor occupancy in vivo (clinical trials) 2.4. GTP-associated CCR5 inverse agonism assay 2.5. cAMP-response-element-luciferase reporter gene assay 3. CCR5-Associated Ligand-Binding Assays 3.1. Radiolabeled CCR5 chemokine-binding assays 3.2. Radiolabeled antagonist-binding and -dissociation assays 3.3. Real-time ligand binding using Biacore technology 3.4. Real time HIV-1 gp120-CCR5 binding assay 3.5. Application of gp120 binding to characterize functional occupancy in vitro 4. Surrogate In Vitro Antiviral Assays 4.1. HIV-1 gp160-CCR5–mediated cell–cell fusion assay 4.2. Antiviral assays 5. CCR5 Site-Directed Mutagenesis and Ligand Docking Studies 5.1. Structural model generation 5.2. CCR5 site-directed mutagenesis

* {

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19 19 24

25 28 30 33 33 34 34 35 37 38 38 40 43 44 45

Pfizer GRD-Sandwich Laboratories, Sandwich, Kent, United Kingdom Pfizer GRD-Groton Laboratories, Groton, Connecticut, USA

Methods in Enzymology, Volume 460 ISSN 0076-6879, DOI: 10.1016/S0076-6879(09)05202-1

#


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Roy Mansfield et al.

5.3. Transfection of HEK Ga15 cells with pIRESneo-CCR5 (various isoforms) and pCRE-luc 5.4. CRE-Luc reporter assay 5.5. Example results/data 6. Non-HIV Indications–Associated Studies, Human CCR5 Knock-In Mice 6.1. Vector construction for hCCR5 knock-in 6.2. Transfection and human CCR5 knock-in mouse generation 6.3. Materials References

45 46 46 48 48 49 50 52

Abstract The G protein–coupled chemokine (C-C motif ) receptor, CCR5, was originally characterized as a protein responding functionally to a number of CC chemokines. As with chemokine receptors in general, studies indicate that CCR5 plays a role in inflammatory responses to infection, although its exact role in normal immune function is not completely defined. The vast majority of research into CCR5 has been focused on its role as an essential and predominant coreceptor for HIV-1 entry into host immune cells. Discovery of this role was prompted by the elucidation that individuals homozygous for a 32 bp deletion in the CCR5 gene do not express the receptor at the cell surface, and as a consequence, are remarkably resistant to HIV-1 infection, and apparently possess no other clear phenotype. Multiple studies followed with the ultimate aim of identifying drugs that functionally and physically blocked CCR5 to prevent HIV-1 entry, and thus provide a completely new approach to treating infection and AIDS, the world’s biggest infectious disease killer. To this end, functional antagonists with potent anti–HIV-1 activity have been discovered, as best exemplified by maraviroc, the first new oral drug for the treatment of HIV-1 infection in 10 years. In this chapter, the specific methods used to characterize CCR5 primary pharmacology and apply the data generated to enable drug discovery, notably maraviroc, for the treatment of HIV infection and potentially inflammatory-based indications, are described.

1. Introduction The CCR5-associated methods included in this chapter are described in fine detail to enable their various subtleties to be captured as far as possible for the reader, especially where the method in question is subject to failure due to minor changes in assay conditions. As the predominant application of CCR5 research is toward the discovery of agents to treat HIV infection, CCR5-associated virology methodologies are included. Where helpful for the reader, specific reagent volumes and working conditions are also described as ‘‘typical’’ in order to help their transfer to practical laboratory

CCR5 Primary Pharmacology Methods and Applications

19

situations. Where such fine details are captured elsewhere, an outline is given with the associated citation for the sake of brevity. Where methods and applications are described, but not available for transfer to third-party laboratories due to their proprietary nature, a citation and overview of the method are described. Example data, results, and application for specific methods are also described or cited both for purposes of providing information per se as well as to enable assay setup in independent laboratories where applicable or desired. The antagonists and agonists either discovered or used to exemplify the methods and associated applications or results are described in Table 2.1 with specific citation for each provided in the text.

2. CCR5 Signaling Assays and Application to Quantify and Characterize Ligand-Dependent Agonism, Antagonism, and Inverse Agonism Chemokine interaction with CCR5 initiates several events. The receptor associates with G proteins, leading to activation of signaling processes, that is, changes in receptor conformation, G-protein interaction and GTP binding, and intracellular Ca2þ redistribution and receptor internalization. A number of cognate/endogenous CC chemokines (see Table 2.2) bind to CCR5 with different affinities and abilities to activate the receptor (Blanpain et al., 2003). Discovery and characterization of novel, noncognate ligands, including quantification of their inhibitory (i.e., antagonistic) potencies can be determined using the various assays developed to measure chemokine-induced CCR5 signaling. The methods can be applied to show the qualitative functional binding of a ligand (i.e., agonism, inverse agonism, and functional antagonism), and the quantification in potency (i.e., EC50 [agonists]) or IC50 [antagonists]).

2.1. CCR5-mediated Ca2þ signaling This method was adapted from a previous reported methodology (Combadiere et al., 1996), and a summary with application for drug discovery has been reported (Dorr et al., 2005b; Napier et al., 2005). A CCR5 agonist would be expected to trigger a cascade of intracellular signaling events that may lead to activation of the target cell. Conversely, a functional antagonist or inverse agonist of the receptor would bind without triggering an intracellular signal to prevent attachment of the cognate chemokines and subsequent signaling events. Agonists bind to the CCR5 receptor to induce a signal transduction cascade provoking, among other events, redistribution of intracellular Ca2þ from the endoplasmic reticulum (i.e., Ca2þ flux). Ca2þ flux can be measured by the increase in fluorescence of an intracellular dye

Table 2.1 CCR5 antagonists described in this chapter CCR5 antagonist: status/application

Structure and general chemotype

Maraviroc (UK-427857): Approved drug for the F treatment of HIV-1 infection (Dorr et al., F 2005b; Dorr and Perros, 2008; Fatkenheuer et al., 2008)

N N H N

N

N

O

Tropane azole N

PF-232798: Phase 2 (Dorr et al., 2008)

N H N

N

O

N

O F Tropane imidazipiperidine

UK-484900: Eexperimental CCR5 antagonist and inflammatory indications tool

N N H N

N

N

O O

O F Tropane imidazipiperidine

N

PF-501606: Experimental antagonist and docking standard.

O N

N

O N O

N

Tropane imidazopiperidine

x

Table 2.1 (continued) CCR5 antagonist: status/application

Structure and general chemotype N

UK-396794: Experimental CCR5 antagonist O (Dorr et al., 2005a; Haworth et al., 2007)

N H N

N

O

Tropane benzimidazole

Me

UK-433370: Experimental CCR5 antagonist (Dorr et al., 2005a)

F

N N

H N

F

N

N

O

Tropane azole N

O

UK-438235: Experimental CCR5 antagonist (Haworth et al., 2007)

N

N H N

N

Tropane benzimidazole O

SCH-C Former clinical candidate (Tsamis et al., 2003a)

N

N+

O−

N

O N

Br Bis-piperidine

(continued)

22


Table 2.1 (continued) CCR5 antagonist: status/application

Structure and general chemotype N

UK-107543: CCR5 HTS hit (agonist) (Dorr et al., 2005b)

N

N

N

Imidazopyridine

Table 2.2 Cognate ligands for CCR5 Systematic ligand name

Original ligand name

CCL3 CCL4 CCL5

MIP-1a (macrophage inflammatory protein 1a) MIP-1b (macrophage inflammatory protein 1a) RANTES (regulated on activation, normally T -cell expressed and secreted)

CCL7 CCL8 CCL14 CCL3L1

MCP-2 (monocyte chemoattractant protein 1) HCC-1 (Haemofiltrate CC chemokine 1) LD78b

resulting from its combination with intracellular Ca2þ released from the ER. This can be monitored in real time using a fluorescent laser imaging plate reader (FLIPR) or an equivalent workstation technology. This allows a real-time assay of agonist and antagonist effects on CCR5-mediated Ca2þ flux in HEK-293 cells expressing the human chemokine receptor. 2.1.1. CCR5 stable transfected cell culture and preparation for calcium signaling assays CCR5 stably transfected cells, such as CHO or HEK-293 cells, are prepared in an appropriate cell culture medium to a density of 1 106 cells/ml. Suitable aliquots of this cell suspension (e.g., 100 ml for a 96-well, plate-based assay) are transferred into every well of poly-D-lysine plates

23


FLIPR-compatible plates and incubated overnight in a growth incubator (humidified 5% (v/v) CO2 incubator at 37 ) to ensure cell adhesion. 2.1.2. Calcium dye preparation and cell dye loading for calcium signaling assays A Calcium Plus KitTM dye is dissolved in 10 ml Ca2þ flux buffer (see Section 6.3) before adding 90 ml of the same buffer to create the final working solution. The media from the plated cells is removed and the adherent cells washed twice by removal of culture medium and replacement with 2 100 ml PBS into each well. The PBS is removed and the adherent cells are incubated with dye preparation (100 ml/well) and left gently rocking for 3 h. The dye is then aspirated and the plates washed three times with Ca2þ flux buffer, prior to addition of additional buffer (160 ml) immediately before the Ca2þ flux assay is undertaken. 2.1.3. Ca2þ flux assay Antagonist dilutions (20 ml, at appropriate concentrations) are added to designated wells of the dye-loaded cell plate after 30 s into a prewritten fluorescence program, to examine agonist activity. Chemokines (20 ml to enable testing at the predetermined EC50 at final assay concentration [FAC]) are added to each well after 4 min. Buffer–buffer and MIP-1b–buffer controls are performed to establish contribution of the artifact signal. 2.1.4. Example data and results The profile of maraviroc in this assay is shown in Fig. 2.1 as an example of a functional CCR5 antagonist. 1000 nM maraviroc

13,000

16 nM maraviroc

Fluorescent counts

12,000

4 nM maraviroc

11,000

Vehicle control

10,000 9000 8000 7000 6000 5000

Maraviroc 0

50

RANTES 100

150

200 250 Time (s)

300

350

400

450

Figure 2.1 Effect of RANTES (CCR5 agonist) and maraviroc (CCR5 functional antagonist) on recombinant CCR5-mediated Ca2þ signaling in HEK cells. The dynamic change in fluorescence after the addition of maraviroc (marked) is shown, as well as subsequent addition of agonist RANTES as marked 4 min later.

24


2.2. CCR5 cellular internalization assay To enable characterization of ligand binding with association to agonism or antagonism, it is necessary to see if test compounds induce CCR5 internalization or not. A method for this has been summarized with application in reported drug discoveries (Dorr et al., 2003b, 2005b). Antiviral activity by CCR5 cognate chemokines is mediated by internalization of receptor, whereas antagonists block the receptor and stabilize a conformation that is not recognizable by CCR5-tropic (R5) HIV-CD4 complex. CCR5internalization–mediated antiviral activity has been reported to lead to HIV-1 resistance through tropism shift (Mosier et al., 1999), although the viruses used in such studies are associated with random tropism shift per se (i.e., shift to CXCR4 without CCR5 antagonist selection pressure) (Westby et al., 2004, 2007). A tropism shift to escape antagonist antiviral activity has not been observed to date in clinical or preclinical studies (Dorr and Perros, 2008). In light of the low and variable levels of CCR5 expression on primary cells, 300.19/R5 cells (an internalization-competent recombinant human CCR5 expressing mouse pre–B-cell line) can be used for quantitative preclinical pharmacology studies. Cell surface CCR5 levels are measured using a human CCR5-specific monoclonal antibody, with an associated labeled secondary antibody to enable fluorescenceactivated cell sorting (FACS) technology (alternatively, the primary antibody can be custom labeled). Endogenous CCR5 agonists and the CXCR4 agonist stromal derived factor 1a (SDF-1a) can be used as positive and negative CCR5 internalization controls, respectively. 2.2.1. Cell culture and reagent preparation 300.19/R5 cells (mouse pre–B-cell line, recombinantly expressing human CCR5) are cultured in a DMEM medium and adjusted to a cell density of 5 106/ml by dilution in the same medium. Anti-CCR5 antibody (2D7see Section 6.3) is diluted 1:10 in 0.5% (w/v) BSA/PBS. Antibody IgG2a (isotype control for the assay, see Section 6.3) is similarly diluted. The anti2D7 phycoerythrin (PE)–labeled, goat anti-mouse secondary antibody (see Section 6.3) is used at a 1:20 dilution in 0.5% (w/v) BSA/PBS. RANTES and SDF-1a (or any other cognate chemokine, see Section 6.3) is dissolved in PBS (100 mM), and then further diluted from a 1-mM final assay concentration (FAC) in cell culture medium. 2.2.2. FACS Assay 300.19/R5 cells (100 ml) at 5 106 cells/ml are added to each assay tube. Antagonists or chemokine controls (10 ml) are added to appropriate assay tubes to enable profiling (usually at 100 nM or below in situ). The tubes are incubated 37 for 45 min to enable CCR5 internalization. The samples are centrifuged (1500 rpm in a benchtop centrifuge) and washed twice in 0.5%


25

(w/v) BSA/PBS (100 ml). Washed samples are resuspended in 40 ml of the same buffer. Anti-CCR5 antibodies or isotype controls are then added to the samples followed by incubation for 45 min at 4 to enable antibody binding to CCR5. The samples are washed once in 0.5% (w/v) BSA/PBS, followed by the addition of 75 ml phycoerythrin (PE)–goat, anti-mouse secondary antibody with incubation at 4 for 45 min in the dark to enable binding. The samples are subsequently centrifuged (1500 rpm in a benchtop centrifuge for 5 min), washed twice in 0.5% (w/v) BSA/PBS (100 ml) and resuspended in 1% (v/v) formaldehyde/PBS (1 ml) for fixing. The fixed cells are processed using suitable instrumentation (e.g., Becton Dickinson FACScalibur), using excitation/emission wavelengths of 488 nm/530 nm, respectively. 2.2.3. Example results/data Figure 2.2 highlights the data generated from this method as plotted by fluorescence overlays showing chemokine induction of CCR5 cellular internalization. The plots highlight that agonism results in receptor internalisation and that antagonists do not induce this event. This method can also be modified by the addition of a ‘‘wash-and-chase’’ phase where cells are washed following a period of incubation with antagonists (for a set period) and then progressed to chemokine-induced internalization studies with FACS analysis. This enables the functional offset of the antagonist to be characterized and used to compare various antagonists. Figure 2.3 highlights this application with the experimental antagonist UK-484900 (Table 2.1), highlighting prolonged blockade of chemokine-induced CCR5 internalization, following removal (by cell washing) of exogenous antagonist and a 2-h incubation prior to chemokine addition.

2.3. Application of CCR5 receptor internalization assay to investigate antagonist-dependent functional receptor occupancy in vivo (clinical trials) As part of drug clinical development, it is becoming increasingly important to ensure that compounds under evaluation induce the desired mechanismassociated pharmacology in humans. The FACS-based CCR5 internalization assay has been adapted to enable functional CCR5 occupancy studies in humans. Placebo versus maraviroc (i.e., CCR5 antagonist)-dependent inhibition of MIP-1b–mediated CCR5 internalization (i.e., functional occupancy) can be assessed in CD4 T lymphocytes prepared from whole-blood citrate CPT (cell preparation tubes) samples taken from healthy volunteers participating in a clinical study designed to investigate CCR5 occupancy in vivo. The difference in CCR5 expression on the cell surface in the presence of high concentration exogenously supplied maraviroc treated (total CCR5) versus untreated (maximum internalization) peripheral

26


A

B 80

Control SDF-1a RANTES + 2 hr media RANTES

Control SDF-1a RANTES

Counts

4 ⬚C

Counts

37 ⬚C

80

0 100

101

102 103 Fluorescence C

104

0 100

80

102 103 Fluorescence

104

Control SDF-1a 10 nM UK-427857 100 nM UK-427857

Counts

37 ⬚C

101

0 100

101

102 103 Fluorescence

104

Figure 2.2 Effect of maraviroc on 300.19 cell surface CCR5 levels (anti-CCR5 antibody^dependent cell population fluorescence). Isotype control fluorescence counts (y-axis) is depicted in grey. RANTES (100 nM)-induced reduction of CCR5 is shown by a reduction in fluorescence (green line in 2A) relative to parallel experiments using the negative control ligand SDF-1a (red line in 2A). Reemergence of CCR5 at the cell surface is apparent following a 2-h incubation period post addition of RANTES (blue line, 2A). RANTES-induced reduction in cell population fluorescence is reduced at 4 (2B) highlighting internalization to be an active biological process. Maraviroc did not affect cell population fluorescence at10 nM or 100 nM (blue and green lines, respectively, in 2C), as also seen for the negative control SDF-1a (red line). (From Dorr P., and Perros, M. (2008). CCR5 inhibitors in HIV therapy. Expert Opin. Drug Discov.3, 1^16; Dorr, P., et al. (2005). Maraviroc (UK-427,857), a potent, orally bioavailable, and selective smallmolecule inhibitor of chemokine receptor CCR5 with broad-spectrum anti-human immunodeficiency virus type1activity. Antimicrob. Agents Chemother.49,4721^4732.)

blood lymphocytes (PBLs) subjected to MIP-1b challenge, gives estimate of the proportion of free CCR5 present on the cell surface at any given plasma concentration of maraviroc. These data can then be used to estimate the degree of receptor occupancy obtained at different doses (and exposures) of maraviroc, or indeed any other CCR5 antagonist in clinical evaluation.

27


Counts

A

Counts

B

Counts

C

120 100 80 60 40 20 0 100 120 100 80 60 40 20 0

120 100 80 60 40 20 0

101

102 FL2-H

103

104

100

101

102 FL2-H

103

104

100

101

102 FL2-H

103

104

Figure 2.3 Prolonged inhibition of UK-484900 (antagonist)-dependent inhibition of chemokine-induced CCR5 internalization in 300.19 cells. Flourescence plot overlays of a representative FACS experiment with human CCR5 expressed on 300.19/R5 cells. Fluorescence units are shown on the x-axis, and cell counts on the y-axis. UK-484,900 is assayed at 1000 nM, 100 nM, and 10 nM (f3A, B, and C, respectively). Cells are treated with RANTES in the presence of the compound (depicted in black), following compound removal and wash (pink), or a further 1.5-h incubation (orange).Vehicle control is depicted in green.Total fluorescence (no RANTES) is depicted in red, and the isotype negative control is depicted in blue.

2.3.1. Dosing and sampling regimen CCR5 antagonists such as maraviroc versus placebo are dosed to volunteers at known levels for the purpose of evaluating dose-occupancy correlation. Blood samples are then taken (into citrate-CPT tubes, 4 ml) at intervals after dosing to evaluate occupancy. The residual CCR5receptor expression on CD4 positive lymphocyte populations is determined by FACS analysis of processed sodium citrate CPT anticoagulated whole-blood samples.

28


2.3.2. Sample preparation and FACS analysis Peripheral blood lymphocyte–rich plasma samples are isolated by centrifugation of CPT tubes at 1550g for 25 min at room temperature (RT) in a swing-out–rotor bench centrifuge. The buffy coat layer of cells is resuspended in the plasma. Each cell-enriched plasma sample (250 ml) is pipetted into three separately labeled 12 75–mm polystyrene roundbottomed tubes (Tube 1 [isotype control], Tube 2 [maraviroc-stabilized CCR5], and Tube 3 [test sample]). An aliquot (50 ml) of CCR5 stabilizing solution (see Section 6.3) is added to Tube 2, while PBS (1% (w/v) BSA) (50 ml) is added to Tubes 1 and 3, before briefly vortexing on a medium setting for 2 s and incubating at 37 for 30 min. All tubes are centrifuged at 400g for 5 min to isolate cells. Aliquots (15 ml) of MIP-1b (100 nM) are added to all tubes, and then gently vortexed on a medium setting for 2 s to resuspend pellet in fluid. The tubes are then incubated uncapped for 45 min in a growth incubator to enable CCR5 internalization. Aliquots (1 ml) of 0.5% (v/v) paraformaldehyde in PBS are added to each tube, followed by vortex (2 s) and incubation (10 min) in the dark at RT to fix the cells. Cells are washed with PBS/centrifugation (400g for 5 min) prior to antibody addition (50 ml—MsIgG R-phycoerythrin [PE], isotype control [Tube 1]; anti-CCR5 2D7, PE labeled, maraviroc stabilized and test samples [Tubes 2 and 3]). All tubes are then vortexed (2 s) and incubated for 20 min in the dark at RT, washed with PBS/BSA as before, with resuspension in 0.5 ml of 1%(v/v) paraformaldehyde by vortexing (2 s). Samples can be stored at 2 to 8 until FACS analysis as described above. 2.3.3. Example results/data The PBL population CCR5-mediated fluorescence profile and MIP-1b– induced effect to reduce this signal through receptor internalization on the cells taken from human volunteers are highlighted in Fig. 2.4. The effect of blockade of this agonist-induced internalization is used to measure the functional occupation of maraviroc in clinical studies, and example data highlighting the dynamic dose-occupancy relationship is highlighted in Fig. 2.5.

2.4. GTP-associated CCR5 inverse agonism assay CCR5 interacts with multiple G-protein species in recombinant cells, following binding of the various endogenous agonist ligands (Mueller et al., 2002, 2006; Mueller and Strange, 2004a, 2004b; Peltonen et al., 1998). MIP-1b–dependent stimulation of GTP can be examined using a radiolabeled nonhydrolyzable form of GTP (gS-GTP) exactly as described by (Haworth et al., 2007) to characterize the inverse agonism mechanism

29


Maraviroc plus chemokine

Vehicle plus chemokine 60

40

CCR5

30 20 10

Cell counts

Cell counts

50

50 40

CCR5

30 20

:

10 103 102 101 PE-dependent fluorescence

104

102 103 101 PE-dependent fluorescence

104

Figure 2.4 CCR5 occupancy assay in/ex vivo. FACS analysis of PBLs blockade of chemokine (MIP-1b)-induced CCR5 internalization by maraviroc in ex vivo PBMCs, as measured by PE-conjugated anti-CCR5-Mab (2D7) fluorescence measurements on a FACS technology platform.The presence of maraviroc inhibits MIP-1bînduced CCR5 internalization compared tovehicle. Analysis of placebo versus maraviroc dosed samples using this methodology enabled the dynamic functional occupancy of CCR5 to be profiled (Fig. 2.5).

% CCR5 functional occupancy

120 100 100 mg

80

25 mg

60

3 mg 10 mg

40

Placebo

20 0

0

10

20

30 Time (h)

40

50

60

Figure 2.5 Dynamic functional occupancy of CCR5 in humans by maraviroc blood sample for assay of CCR5-internalization on isolated PBMCs taken at times indicated following single dose to healthy volunteers. Data are mean SD for each cohort. Note that 20% of 2D7-anti-CCR5^recognized CCR5 is not internalized by MIP-1b, leading to an apparent occupancy level of 20% for placebo-dosed human volunteers.

that is measurable in recombinant systems which underpins the functional antagonism of antiviral CCR5 inhibitors (Dorr et al., 2005b; Strizki et al., 2001). GTP binding to CCR5 is measured based on previously described methods ( Jansson et al., 1999; Labrecque et al., 2005). These can also be adapted to a time-resolved fluorometric assay, using a Europium (Eu3þ) labeled gS-GTP to avoid use of radioactivity.

30


2.4.1. Membrane preparation and GTP-binding assay CCR5 stable transfected HEK-293 cells are cultured to a confluency between 50 and 70% in standard culture medium (e.g., DMEM), typically in a 225-cm2 flask. Cells are washed once with PBS. The PBS is removed and the cells dislodged by rapping the side of the culture flask in the presence of 10 ml culture medium, harvested by centrifugation (350g for 10 min). Pelleted cells are resuspended in 15 ml lysis buffer (see Section 6.3), and homogenized with a handheld homogenizer (5 to 10 s on ice, three to four times). The homogenate is centrifuged at 40,000g for 30 min at 4 . The membranous pellet is resuspended in a minimal volume of lysis buffer (see Section 6.3) prior to estimation of protein concentration (e.g., Bradford microassay). Membrane aliquots (50 ml at 500 mg/ml) are added to designated wells of a 96-well assay plate. GTP binding is measured using a Delfia GTP-binding assay kit (see Section 6.3), according to the manufacturer’s protocol, with a ‘‘preoptimized’’ GTP assay buffer (see Section 6.3). Assay buffer (50 ml) is added to the plate wells prior to incubation at RT for 30 min with gentle rotary shaking. MIP-1b and test compounds are diluted in 50 mM HEPES buffer, pH 7.4, over a desired concentration range. The test compound is added and incubated at RT for 30 min prior to the addition of 10 ml GTP-Eu3þ (100 nM FAC). The reaction is incubated for a further 30 min at 37 before washing with 300 ml/well of ice-cold wash buffer (supplied with assay kit) and reading immediately at 615 nm using an appropriate plate reader. Basal GTP binding is calculated from the mean values obtained for vehicle control-designated wells (50 mM HEPES, pH 7.4). The effect of MIP-1b and the test compound on GTP incorporation is measured for each well (and meaned), with percent stimulation relative to vehicle control calculated. Nonspecific binding (NSB) is subtracted (NSB is determined as the background binding of GTP to the assay plate in the absence of membranes). 2.4.2. Example data and results Vicriviroc, maraviroc, and its analogues UK-396794 and UK-438235 show the classic inverse agonist profile of small concentration-dependent reductions in GTP-binding assays, compared to relatively large agonist-stimulated increase in binding as previously reported (Dorr et al., 2005b; Haworth et al., 2007; Strizki et al., 2001). This is depicted in the case of maraviroc in Fig. 2.6.

2.5. cAMP-response-element-luciferase reporter gene assay The cAMP-response-element-luciferase (CRE-luc) plasmid codes for a cAMP response element upstream of a luciferase reporter gene. HEKGa15 cells can be transiently cotransfected with the CRE-luc

31


1600

Stimulated/basal GTP binding (%)

1400 MIP-1b MIP-1

1200 1000 800 600 400 200 0

Maraviroc 3

6

10

30 60 100 Ligand concentration (nM)

300

600

1000

Figure 2.6 Inverse agonism of CCR percent by maraviroc. Stimulation of GTP binding to membrane preparations from CCR5-expressing HEK-293 cells by MIP-1b(pink line and data points), and UK-427,857 (blue line and data points). Data points represent the ratio of GTP binding in the presence of ligand over basal levels of GTP binding in vehicle control assays.

construct and a plasmid encoding the human CCR5 receptor. The transfected cells are stimulated with forskolin to activate adenylate cyclase, and increase intracellular cAMP to enable an assay window. The cAMP binds to its response element, which activates transcription of the luciferase reporter gene, leading to an increase in measured luminescence. The CCR5 receptor is a Gi-linked GPCR when expressed in an appropriate background, and agonism inhibits adenylate cyclase, reducing the intracellular cAMP concentration and thus decreasing the luminescence signal. The effect of preincubation with antagonists on the dose–response curve to MIP-1b, and therefore its functional activity at the CCR5 receptor can thereby be investigated. 2.5.1. Transient transfections and assay plate preparation Bulk preparations of human CCR5 receptor DNA (in the expression vector pIRESneo) and CRE-luc plasmid DNA (see Section 6.3) are used for transfections. HEKGa15 cells are cultured in standard medium (see Section 6.3), and passaged at 90% confluency using cell dissociation solution. Cells are transfected at 50 to 80% confluency in T75 flasks, using

32


lipofectamine (Plus) reagent. OptiMEM reduced serum medium is used in all transfection procedures. Two solutions are prepared for each transfection: Solution 1 ¼ 4 mg human CCR5 receptor DNA, 2.5 mg CRE-luc DNA, 45 ml Plus reagent, 0.75 ml OptiMEM; and Solution 2 ¼ 22.5 ml lipofectamine, 0.75 ml OptiMEM. Solution 1 is incubated at RT for 15 min. Solutions 1 and 2 are then mixed and incubated at RT for 15 min, before the addition of 7 ml OptiMEM. The flasks containing the cells for transfection are removed from the incubator and the media removed. The cells are washed in 10 ml OptiMEM, and the DNA/lipofectamine/OptiMEM mix (Solutions 1 and 2) added. The flasks are incubated in a growth incubator overnight. For cell plate preparation, DMEM medium without phenol red, supplemented with 10% (w/v) dialysed FCS, is used in the cell plate preparation. Media is removed from the transfected cells and each flask is washed once in 10 ml PBS. Cell dissociation solution is added (2 ml) and the flasks incubated at RT for up to 5 min. The flasks are tapped to dislodge the cells, and approximately 8 ml media (as above) added. The cells are pelleted by centrifugation at 1000g for 5 min. The cells are resuspended in fresh media and plated out (90 ml) into 96-well plates (2.5 104 cells/well), and are left to adhere overnight in a growth incubator. 2.5.2. CRE-luc assay To inhibit phophodiestrase activity and enable cAMP detection accordingly, isobutylmethylxanthine (500 mM in DMSO) is diluted to 1 mM in 0.1% (w/v) BSA/PBS to make the antagonist diluent. Test compounds e.g., maraviroc are diluted in antagonist diluent to 10x final assay concentration. MIP-1b is prepared at 36 mM in 0.1% (w/v) BSA/PBS, and aliquoted for freezing/use. MIP-1b is then diluted in 0.1% (w/v) BSA/PBS to 12 final assay concentration. Forskolin (1 mM in DMSO) is diluted to 3.6 mM in 0.1% (w/v) BSA/PBS to give a FAC of 300 nM. Test compounds (10 ml) are added to the cell and incubated at 37 for 30 min, prior to addiction of MIP-1b and forskolin (10 ml each). The plates are mixed gently, and incubated at 37 for 5 h. After equilibration to RT for 10 min. SteadyGlo luciferase (see Section 6.3) is prepared according to manufacturer’s instructions, added (100 ml/well), and incubated at RT for 10 to 15 min before reading luminescence on an appropriate plate reader with data transfer system to determine percent of cAMP inhibition values. 2.5.3. Example results/data Maraviroc at 1, 3, and 10 nM, caused a dose-dependent rightward shift of the dose–response curve to MIP-1b, together with a marked suppression of the maximum response, indicative of insurmountable antagonism (Fig. 2.7). The maraviroc pKb is determined following an assumption of hemiequilibrium conditions, and a double reciprocal regression is then constructed, and the slope of the line is used to calculate the Kb. The pKb

33

% Fitted max of control curve


150

Control 1 nM UK-427, 857

100

3 nM UK-427, 857 10 nM UK-427, 857

50 0 −12 −50

−11

−10

−9

−8

−7

−6

Log10 [MIP-1b]M

Figure 2.7 Effect of maraviroc on MIP-1b dose^response curveDose^response in the absence and presence of 1, 3, and 10 nM of former. Each data point represents the mean of n ¼ 4 experiments. In each experiment, the mean of duplicate wells is calculated.

value of maraviroc is determined as 9.4 (95% confidence interval 9.01– 9.75). A more detailed description of analysis of this type has been comprehensively reported for CCR5 (Kenakin et al., 2006; Watson et al., 2005b).

3. CCR5-Associated Ligand-Binding Assays The affinity of CCR5 ligands including antagonists with therapeutic potential can be characterized in terms of their potency in a range of binding assays, and also to examine relevant kinetic properties such as physical and functional receptor dissociation rates. This can be used for compound characterisation, or comparison in order to guide a synthetic program.

3.1. Radiolabeled CCR5 chemokine-binding assays Radiolabeled cognate chemokine-binding assays to recombinant CCR5 (membranes and whole cells) has been extensively reported to a level of detail that would enable straightforward setup in an independent laboratory. Classic membrane-filter binding assays were originally developed and reported by Combadiere et al. (1996), and described in detail to enable the characterization of specific CCR5 antagonist such as maraviroc by Dorr et al. (2005b) and Napier et al. (2005), and the bicyclics SCH-C and SCH-D (vicriviroc) by Strizki et al. (2001, 2005) and Tagat et al. (2004). Modification to enable homogenous assays using scintillation proximity assay technology for greater screening amenity has also been reported for the characterization of aplaviroc (Watson et al., 2005b). These and signaling assays have been applied across CCR5 isoforms in order to select

34


appropriate species to examine the mechanistic toxicology of CCR5 antagonists (Mosley et al., 2006; Napier et al., 2005).

3.2. Radiolabeled antagonist-binding and -dissociation assays Physical association and dissociation studies for maraviroc have been reported in fine detail by Napier et al. (2005). These include competition studies where excess unlabeled maraviroc is used to prevent reassociation of 3H-maraviroc in ligand-binding experiments (either isolated membrane preparations or intact recombinant CCR5-expressing cell lines). Data from such experiments highlighted the slow physical dissociation of maraviroc (T1/2 ¼ 16 h; see Napier et al., 2005)). This is a phenomenon that appears to be consistent for CCR5 antagonists and no freely reversible antagonists have been reported to date. Intriguingly, experiments that assess functional offset by gp120 offset or chemokine on-set assays (Dorr et al., 2005a; Watson et al., 2005a) imply even longer antagonist dissociation, or more strictly, receptor recovery. For gp120 binding, this may be a consequence of this glycoprotein linking to CCR5 clusters rather than single receptors for infection, and so antagonist dissociation may be required from each CCR5 molecule prior to a gp120accepting formation can be adopted, or that antagonist dissociation is followed by a period of CCR5 being in a nonfunctional conformation, or both.

3.3. Real-time ligand binding using Biacore technology Biacore offers a technology platform that can monitor the binding of ligands to receptors and monitor interactions based on induced changes in the refractive index. This enables interactions to be monitored in real time, rather than by sampling at time points, and avoid the use of radiolabeled ligands. 3.3.1. Immobilization of 1D4 monoclonal antibody on a CM4 surface The monoclonal antibody 1D4 (see Section 6.3) is immobilized on a CM4 sensor chip using standard amine-coupling chemistry. HBS-N (10 mM Hepes, 0.15 M NaCl, pH 7.4) is used as the running buffer. The carboxymethyl dextran surface requires activation with a 12-min duration injection of a 1:1 ratio of 0.4 M 1-ethyl-3-(3-dimethylaminopropyl) carbodimide hydrochloride (EDC):0.1 M N-hydroxy succinimide (NHS). The antibody is coupled to the surface with a 15-min injection of 1D4 diluted in 10 mM sodium acetate (pH 5.0). Remaining activated groups are blocked with a 7-min injection of 1 M ethanolamine (pH 8.5). To obtain a 1D4 surface density of approximately 12,000 RU, immobilization is performed at 30 using Biacore S51.


35

3.3.2. Ligand binding to receptors CCR5 is solubilized as described previously (Navratilova et al., 2006) and captured by 1D4 immobilized on surfaces within a CM4 chip at densities equating to approximately 4000 RU (the running buffer consists of 50 mM Hepes, pH 7.0, 150 mM NaCl, 0.02% (w/v) CHS, 0.1% (w/v) DOM, 0.1% (w/v) CHAPS, and 50 nM DOPC/DOPS [7:3]). Small-molecule CCR5 compounds are dissolved in dimethyl sulfoxide (DMSO) and diluted into 50 mM HEPES (pH 7.0), 150 mM NaCl, 0.02% (w/v) CHS, 0.1% DOM, 0.1% CHAPS, and 50 nM DOPC/DOPS (7:3) to concentrations of 1 to 20 mM. These solutions are then serially diluted threefold in running buffer to produce the concentration series for each inhibitor. The receptor surfaces are stabilized by at least eight start-up buffer blanks before injecting a compound. To reference for drift, two blank injections are performed between analyte injections. Compounds are injected at a flow rate of 30 ml/min, and the association and dissociation phases are monitored for 1 and 10 min, respectively. The receptor surfaces are not regenerated between analyte injections. Instead, the injections are performed from lowest to highest concentrations and the data are normalized for the maximum binding capacity as described previously (Navratilova et al., 2006). 3.3.3. Example data and results Antagonist binding to solubilized CCR5 is highlighted in Fig. 2.8. The compounds are injected over freshly prepared CCR5 surfaces in increasing concentrations. All binding responses are globally fitted with a 1:1 interaction model that used a different maximum binding capacity (Rmax) for each analyte injection and data are normalized for Rmax. The compounds highlighted in Fig. 2.8 show their relative CCR5 affinities and physical association and dissociation rates.

3.4. Real time HIV-1 gp120-CCR5 binding assay CCR5 antagonists bind the receptor and stabilize a conformation that is unable to bind the HIV-1 gp120-CD4 complex. The method detailed in the following requires preparation of a crude gp120-containing extract to enable an empiric assay for IC50 determination, although commercially available sources of purified or semipurified gp120 also generate signals in this assay albeit to a lesser extent (Rickett et al., 2003). The requirement for gp120 preparations to enable a sufficiently high signal to noise in this assay reduces the ability of the assay to resolve/differentiate compounds of IC50 potencies less than 20 nM. Other limitations are the empiric nature of the screen and limited scope for kinetic validation. However, this assay is amendable to high throughput screening, and has utility for scrutinizing the molecular interaction for inhibitors of HIV-1 gp160-CCR5–mediated

36

Normalised response (% Rmax)


120 100 80 60 40 20 0

Maraviroc ka = 1.1 (±0.1) ⫻ 105 M−1s−1 kd = 6.0 (±0.2) ⫻ 10−4 s−1 KD = 25.0 (±4.0) ⫻ 10−9 M t1/2 = 1165 s 0

50

100

150

200

250

300

120 100 80 60 40 20 0

UK-438235−40 ka = 3.5 (±0.1) ⫻ 104 M−1s−1 kd = 7.1 (±0.1) ⫻ 10−4 s−1 KD = 2.0 (±0.1) ⫻ 10−8 M t1/2 = 976 s 0

50

100

150

200

250

300

10 8 6 4 2 0

UK-107543 (agonist) ka = 1.14(7)E + 06 kd = 0.27(2) KD = 2.40(20)E − 07 t1/2 = 2.56721178 0

50

100

150

200

250

Time(s)

Figure 2.8 Profile of small molecule antagonist and agonist binding in Biacore. Graphs highlighting association and dissociation of various CCR5 ligands as measured by dynamic change in refractive index on Biacore.

cell–cell fusion (Fig. 2.9), which better resemble the HIV-1 entry process in infection, and is now the favored screen for HTS (Dorr et al., 2003a), but does not define the specific interaction blocked by inhibitory compounds. 3.4.1. Preparation and assay of soluble recombinant gp120 CHO cells stably transfected with the HIV-1 gp120 expression vector pEE14.1 (see Section 6.3) are cultured in 200-ml roller bottles for 4 days, which is replaced by 200 ml DMEM-S medium with 1% (w/v) FCS for 3 days prior to supernatant harvest for gp120 preparation. The cell supernatant is concentrated by ultrafiltration and empirically quantified in the assay described in the following using a Europium-labeled, anti–HIV-1 gp120 IgG antibody (see Section 6.3) in the time-resolved fluorescence immunoassay (TRFIA). 3.4.2. Inhibition of soluble recombinant HIV-1 gp120 (Ba-L strain) binding to CCR5 by TRFIA This assay is performed as essentially as described by (Dobbs et al., 2001), and is depicted in Fig. 2.9. HEK-293 cell aliquots (100 ml at 1 106 cells/ml) are plated into poly-D-lysine–coated plates and incubated in a growth incubator overnight. A 1:1 mix of soluble recombinant human CD4 (sCD4, diluted to 4.5 nM in culture medium; see Section 6.3) and HIV-1

37


gp120-sCD4-CCR5 binding

gp160-CCR5 cell-cell fusion gp160

Eu-cryptate

TAT

CHO

anti-gp120

TAT CD4

gp120 CCR5

sCD4

Hela P4

CCR5 b-Gal

+

b-Gal

Figure 2.9 Cartoon depictions of gp120-sCD4-CCR5 binding and gp160-CCR5 cell^ cell fusion assays.

gp120 (e.g., Ba-L strain) are incubated at RT for 15 min before its addition to PBS-washed cells, in the presence of dilutions of maraviroc to enable IC50 determination. The assay plates are incubated at 37 for 1 h and washed. Eu3þ labeled anti-gp120 antibody (1/500 dilution in assay buffer; see Section 6.3) is added to each well (50 ml) and incubated 1 h. The plate is washed three times with assay buffer, prior to the addition of enhancement solution (200 ml/well; see Section 6.3) and measurement of Eu3þ fluorescence. Nonspecific binding is taken as the fluorescence measured for gp120 incubated with cells in the absence of preincubation with sCD4. The data can be used to examine dose–response for compound-dependent inhibition of HIV gp120-sCD4 complex binding to CCR5 as shown for maraviroc in Fig. 2.10.

3.5. Application of gp120 binding to characterize functional occupancy in vitro CCR5 antagonists have slow physical dissociation from the receptor, as measured using radiolabeled antagonist competition assay. To investigate the more clinically relevant endpoint of dynamic compound stabilization of HIV-1 ‘‘unrecognizable’’ conformation (i.e., time required for receptor to become amenable for HIV-gp120 binding following antagonist onset), a wash-and-chase modification of the gp120 assay can be undertaken. This also offers the advantage of cross-compound comparisons, without the need for custom radiolabeling of each antagonist. The methodology is essentially the same, except that the following a 30min period of antagonist association (period in excess of the tritiated antagonist binding to a steady-state signal (various compounds, data not shown), the assay plates

38


100 90 80

% Inhibition

70 60 50

Fusion gp120

40 30 20 10 0 0.001

0.01

0.1

1

10

100

1000

[Maraviroc] (nM)

Figure 2.10 Dose^response curves for maraviroc-dependent inhibition of gp120sCD4 binding to CCR5, and gp160-CCR5 cell^cell fusion maraviroc-dependent inhibition of gp120 binding to CCR5 (red) and gp160-CCR5^mediated cell^cell fusion (black).

containing confluent, nonexpanding cell populations are washed three times in PBS to remove all exogenous antagonist, incubated for a set period (e.g., overnight), prior to completion of the assay for IC50 determination. The assay is run without the wash step, where exogenous antagonist is present throughout the assay in parallel. Control studies (unpublished) have shown that the wash-and-chase steps do not alter compound potency per se. The IC50 ratio for gp120-binding inhibition for assays run under non-wash versus wash-and-chase gives an indication of the functional occupancy of a given antagonist (as exemplified for PF-232798 in Fig. 2.11), and enable comparisons of different antagonists as previously reported (Dorr et al., 2005a, 2008).

4. Surrogate In Vitro Antiviral Assays The role of CCR5 as a coreceptor important in antiviral drug discovery has led to de novo assay developments that are of a bespoke nature. The novelty of CCR5 as an antiviral target has also led to the development of new surrogate antiviral assays, and modifications of infectious virus-based antiviral assays. These are described in the following in no particular order.

4.1. HIV-1 gp160-CCR5–mediated cell–cell fusion assay A high-throughput fully automated HIV-1 envelope or gp160-CCR5– dependent cell–cell fusion assay (fusion assay) has been previously reported in detail, and shown to be highly predictive of antiviral activity, with a

39

% Inhibition gp120-sCD4 binding


120 100 80 60 40

No wash

20 0

Wash and chase 0.1

1

10

100

1000

10000

[PF-232798] (nM)

Figure 2.11 Functional offset of PF-232798 from CCR5 as measured by a wash-andchase gp120-sCD4^binding assay. Dose^response curves for PF-232798^dependent inhibition of gp120-sCD4 binding to CCR5 in the presence of exogenous dosed antagonist (no wash) and when removed and incubated for 24 h (wash and chase).

greater correlation to antagonist potency in primary cell-based antiviral assays (deemed the most reliable predictor of efficacy in humans from a pharmacology perspective), than either the chemokine or gp120-binding assays (Bradley et al., 2004; Dorr et al., 2003a). This has enabled extensive screening for CCR5 ligands (and inhibitors against other cell-entry–associated targets), without the need to use hazardous systems such as infectious HIV preparations or radioligands. The fusion assay is depicted in Fig. 2.9, and requires functional complete viral envelope protein gp160, which is naturally processed into two linked subunits, gp120 and gp41. To enable quantitative evaluation of the process, the HeLaP4 cells express a b-galactosidase reporter gene under the control of HIV-1-LTR, while the gp160expressing CHO cells also expressed the HIV-1 transcriptional activator Tat. Fusion between the two cell lines allows soluble Tat from the CHOgp160 cells to transactivate the HIV-1 LTR present in the HeLaP4, leading to the expression of b-galactosidase. The level of b-galactosidase is determined using the fluorogenic substrate 4-methylumbelliferyl-galactopyranoside (MUG). b-galactosidase cleaves MUG to generate fluorescent 4-methylumbelliferone. Inhibition of cell–cell fusion reduces fluorescent signal levels in this assay relative to mock-treated controls, to enable dose– response evaluation (see Fig. 2.10). The methods and application of this method have been described in fine detail (Bradley et al., 2004) and are not included here for the sake of brevity. This assay can also be modified to become a direct antiviral assay by supplanting the CHO cell line with CCR5-tropic whole HIV virus (predetermined titer). However, correlation studies with antiviral activity of CCR5 antagonists in primary

40


cell–based assays with infectious virus show no advantage in the use of virus versus CHO cells in this reporter assay (unpublished data, Pfizer GRD), highlighting the advantage of the cell–cell fusion system in terms of safety and assay amenability.

4.2. Antiviral assays A range of antiviral assays have been used to profile CCR5 antagonists ranging from systems using ex vivo native cells, through to proprietary high throughput recombinant systems as described in detail by Petropoulos et al. (2000), which are commercially available for compound screening (PhenoSenseTM assay) or for determination of HIV coreceptor usage (i.e., tropism) of patient HIV samples (TrofileTM assay). The details of these assays are not described here in light of their proprietary nature. The principles of their use and general methodologies in the field of CCR5 research are outlined in Dorr et al. (2005b) and Westby et al. (2007). In light of the notorious difficulty yet high importance in establishing cross-laboratory consistency with native cell–based antiviral assays, and their general utility in establishing target exposure levels in patients for dose setting in clinical trials, fine details in these methods are described. 4.2.1. CCR5-associated primary cell–based antiviral assays: Peripheral blood lymphocytes and monocyte-derived macrophages HIV-1 replicative systems Cell preparation: Peripheral blood lymphocytes Peripheral blood lymphocytes (PBLs) are typically prepared in convenient batch sizes using buffy coats from individual donors or combined from two to four HIV- and HBV-seronegative donors. Each buffy coat is diluted in an equal volume of PBS and mixed. From this, 30 ml is layered onto 20 ml of Ficoll-Paque in 50 ml centrifuge tubes, followed by centrifugation for 30 min at 1000g at RT. The PBLs are harvested at the Ficoll–plasma interface. The PBLs are washed twice in PBS by centrifugation for 10 min at 500g at 4 . Contaminating erythrocytes are lysed by adding 9 ml sterile water, stored at 4 , to the resuspended PBL pellet, followed immediately by 1 ml of RT 10 Hanks Buffered Saline. PBS is added to a final volume of 45 ml and the PBLs are pelleted by centrifugation for 10 min at 100g at 4 . The pellet is washed twice more in PBS at 4 prior to resuspension and pooling of pellets from other tubes in 30 ml RPMI cell culture medium at RT. Cells can be pooled, and if required, frozen (liquid nitrogen storage) from individual donors at this stage. Cell viability is determined, such as by trypan blue exclusion. Only cell suspensions showing greater than 95% viability are typically used in antiviral assays. The cell suspensions are adjusted to 1 106 cells/ml by the addition of fresh RT RPMI cell culture medium containing 1.5 mg/ml phytohemaglutinin (PHA) to enable enhanced


41

CCR5 expression to facilitate viral entry, aliquoted into 50 ml cultures and incubated for 3 days in a growth incubator, prior to counting for viral expansion or antiviral assays. Cell preparation: Monocyte-derived macrophages Harvested buffy coats (single donors) are diluted with an equal volume of DPBS and layered in 30-ml aliquots onto an Accuspin tube prior to centrifugation for 30 min at RT (1000g). Harvested monocyte-derived macrophages (MDMs) are washed three times in approximately 50 ml PBS and centrifuged for 10 min at 750g prior to resuspension in RPMI growth medium. Monocytes are adjusted to 1.0 105/well (200 ml) in a 96-well plate and incubated in a growth incubator for 1 h (to enable MDM-selective adhesion). The supernatant is discarded from the cells, and plates are washed twice with 200 ml RT PBS, prior to addition of fresh cell culture medium (200 ml) and incubated for 7 days prior to antiviral assay in a growth incubator. Antiviral assay: PBL cultures PBLs are infected for 1 h at 37 with a predetermined volume of virus calculated to give an equal amount of HIV-1 reverse transcriptase (RT) activity per virus stock. Infected cells are washed and added to assay plates (e.g., 7.2 104 cells/well [200 ml] for a 96-well plate) containing serial dilutions of test compounds (in RPMI culture medium and DMSO 0.1% (v/v) FAC). After 5 to 7 days of incubation, the cultures are examined visually with a microscope for evidence of cytotoxicity and viral replication and compound-dependent inhibition is quantified by measuring RT activity (see the following). Antiviral assay: MDM cultures MDMs are used after 7 days in culture (to enable full differentiation). The supernatant is replaced with 50 ml of either compound preparation or vehicle (RPMI medium containing DMSO at 0.1% (v/v) FAC). Cells are transferred to a growth incubator for 1 h, and then 50 ml of pretiter virus stock (see the following) is added prior to return to the incubator for 3 h. Following removal of medium, plates are washed five times using 200 ml of RT PBS per well prior to readdition of test compounds and vehicle at 2 FAC equivalent. A further 50 ml of cell culture medium are added to all wells and plates transferred to a growth incubator for 7 days. After this period, culture supernatant is harvested from the assay plates and tested directly in the HIV-1 RT detection assay as a surrogate of HIV-1 replication for compound susceptibility profiling and quantification (i.e., IC50 and IC90). Reverse transcriptase assay RT activity is quantified in culture supernatants using and appropriate assay kit such as the Quan-T-RT assay (see Section 6.3) (Amersham Pharmacia Biotech). Assay reagent sufficient for the whole assay is prepared based on the following reagent volumes

42


per well: 50ml H2O; 19 ml assay buffer; 10 ml primer/template bead/scintillant complex, and 1 ml [3H]TTP. The mixture is vortexed to ensure full suspension of the beads, and 80 ml are transferred to each well of a 96-well Isoplate, to which 20 ml culture supernatant or standard is added and mixed by pipetting. The plate is sealed and incubated at 37 for 1 h in a growth incubator to allow incorporation of the tritiated thymidine triphosphate into the primer/template by the virus RT enzyme. The reaction is terminated with the addition of the supplied stop solution (EDTA) containing 1% (w/v) SDS) to inactivate HIV-1. Light emission (SPA bead-driven from kit) is measured in a scintillation counter (results recorded as cpm). Samples are considered positive for virus if the cpm value is fourfold greater than that of the uninfected cell control. An RT standard curve (Quant-T kit; see Section 6.3) ranging from 0 to 10 mU/ml is prepared in culture medium and treated in the same manner as the test material. Expansion and storage of HIV-1 stocks HIV-1 isolates (laboratory and primary origin; see Section 6.3) can progress through a typical methodology as follows to supply virus of sufficient titer for antiviral assay: Typically, an aliquot (0.5 ml) of isolate sample is added to a 15-ml conical centrifuge tube, prior to the addition of 1.0 107 PBLs, in RT RPMI growth medium. Following incubation for 1 h in a growth incubator, the infected cells are pelleted by centrifugation at 225g for 10 min, and resuspended in a small volume of RPMI medium at RT. The resuspended cells are transferred to a T75 tissue culture flask and diluted up to a final volume up to 50 ml with RPMI growth medium containing IL-2 (enhances proliferation and CCR5 expression) at 10 ng/ml. The cells are reincubated for 3 to 4 days. After this, 25 ml of the spent medium is removed and replaced with 30 ml fresh growth medium containing IL-2 (10 ng/ml). Following, 3 4 days incubation as before, 20 ml of the supernatant is assayed for reverse transcriptase (RT) activity for evidence of replication as described above. Counts above 2000 cpm are deemed sufficiently high to enable CCR5 antagonist antiviral testing. Supernatants with counts less than 2000 cpm/20 ml supernatant in the RT assay are typically further expanded by replacement of half the culture medium with fresh, and addition of a further 1 107 PBL cells, with a further 3- to 4-day incubation and RT assay until counts of more than 2000 cpm are achieved. HIV-1 resistance to CCR5 antagonists This has become a rapidly growing research field that cannot be detailed to the level as for more direct CCR5 pharmacology- and virology-associated methodologies. However, this important preclinical and clinical field has been included in a recent review with citations of key methodologies and applications included (Dorr and Perros, 2008). The methodology for viral passage for generating

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120 100

% Inhibition

80

MVC plus MVC Res CC185

60

MVC plus start CC185 PF-232798 plus start CC185 PF-232798 plus MVC Res CC185

40 20 0 −20 1.0E-11

1.0E-10

1.0E-09

1.0E-08

1.0E-07

[Antagonist] (M)

Figure 2.12 Antiviral dose^response curves highlighting activity of PF-232798 against laboratory-generated MVCRES HIV-1 isolate CC1/85. All data points are from parallel PBL cultures using RT activity as measurement of HIV-1 replication. Inhibition is measured versus vehicle-dosed control cultures. MVC retained expected activity against passaged control start cultures of HIV-1 isolate CC1/85 (blue line and data points), and is inactive against MVC-passaged isolate (red line and data points). PF-232798 shows retention of activity against both passaged isolates (green and pink lines and data points). Graphs highlighting association and dissociation of various CCR5 ligands as measured by dynamic change in refractive index on Biacore.

laboratory-resistant CCR5 antagonist HIV strains and examining crossresistance has been extensively detailed and exemplified (Westby et al., 2007). Example results and data Figure 2.12 shows the dose–response curves for CCR5 antagonist profiling in PBL-based antiviral assays, using a laboratorygenerated maraviroc-resistant (MVCRES) isolate generated by long-term serial passage in gradually increasing maraviroc concentrations (Dorr et al., 2008; Westby et al., 2007). This has been used to show the potential of second-generation CCR5 antagonists to retain activity against laboratory generated MVCRES isolates (see Fig. 2.12).

5. CCR5 Site-Directed Mutagenesis and Ligand Docking Studies The techniques for visualizing ligand-GPCR interactions are significantly hampered by the insolubility of the receptors, and the associated difficulties involved in crystal formation for x-ray diffraction. To investigate the molecular interactions between CCR5 antagonists and specific amino

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acids of the CCR5 receptor, and to support a computer-assisted docking model of maraviroc and other CCR5 antagonists into the presumed binding pocket, a CCR5 site-directed mutagenesis–based approach can be used. By homology modeling with bovine rhodospin, a structurally characterized GPCR (Palczewski et al., 2000), amino acid residues that are presumed to form the CCR5 equivalent of the retinol-binding pocket of bovine rhodopsin can be identified. This region of the CCR5 receptor has been widely identified as the binding site for CCR5 antagonists and numerous models reported, including an excellent cross-template study (Kondru et al., 2008). Although all such studies have been retrospective (i.e., visual models generated following antagonist design and established SARs), the structural information has highlighted receptor–ligand interactions that might be the driving various SARs observed. The example cited here shows the use of structural information on the CCR5 program and various antagonists, and specifically its application to rationalize the SAR associated with crossand nonoverlapping activity against laboratory generated MVCRES virus (strain CC1/85). This strain, in common with all HIV-1 isolates that eventually acquire resistance to maraviroc following in vitro passage or prolonged clinical exposure, gains cell entry through maraviroc-occupied CCR5 rather than via CXCR4 (Dorr and Perros, 2008; Westby et al., 2004, 2007).

5.1. Structural model generation Following site-directed mutagenesis of selected residues in CCR5 the interaction of antagonists with a selected residue can be determined in terms of change in functional affinity. For this, the EC50 of chemokine (e.g., MIP-1b)-induced signaling is determined, and compared to that measured for wildtype receptor. For this, expression plasmids encoding the CCR5 isoforms can be individually cotransfected into HEK cells in combination with a plasmid encoding a CRE-dependent luciferase reporter gene. Following elevation of intracellular cAMP levels by exposure to forskolin (a nonspecific activator of adenylate cyclase), CCR5 signaling is subsequently measured by MIP-1b–induced agonism of the receptor, which reduces of intracellular cAMP levels due to CCR5 Gi protein coupling. Intracellular levels of cAMP can be assessed following luciferase expression as a result of cAMP-dependent induction of the cre-luc reporter plasmid. Antagonistdependent inhibition of MIP-1b–induced signaling of each CCR5 isoform is thus enabled through IC50 measurement. The change in IC50 values for each mutant can be compared to wildtype to gain insight into which residues in the putative binding pocket formed an interaction with a given antagonist. The very general rule is that interaction is proportional to the loss in IC50 against the mutated residue as compared to wildtype. The MIP-1b–dependent reduction of cAMP levels is deemed to be a consequence of CCR5 signaling, in light of this chemokine being a highly specific cognate ligand for this


45

receptor, and the absence of such signaling being seen in the absence of recombinant receptor, and complete inhibition seen at high doses of applied CCR5 antagonist. Computer-assisted docking using this ‘‘IC50-shift’’ parameter of antagonists requires an initial dock of a test compound of known crystal structure and rigidity, with following docks of test compounds thereafter. Site directed mutagenesis studies as reported here run against this compound resulted in a loss in potency for the Y108A and E283A mutants. This enabled an overlay and subsequent docking of other CCR5 antagonists such as maraviroc, vicriviroc, and PF-232798 into the modeled putative binding pocket of CCR5 using a Pfizer software package (FLOPS, Flexes Ligands Optimizing Property Similarity). Similar packages are reported with this type of utility (Kondru et al., 2008; Tsamis et al., 2003b).

5.2. CCR5 site-directed mutagenesis Mutant CCR5 isoforms made de novo or sourced directly are cloned into an appropriate expression plasmid, such as pIRESneo (see Section 6.3 section). For de novo mutations and the desired mutation (e.g., glutamic acid 283, alanine (E283A)) is constructed using polymerase chain reaction (PCR)– based site directed mutagenesis methodology with the wildtype CCR5encoding pIRESneo plasmid as the substrate DNA source, and mutant-specific primer pairs for E283A. The PCR is run according to a manufacturer’s instructions (e.g., Quikchange mutagenesis kit; see Section 6.3). Parent template wildtype CCR5 DNA is removed by digestion using methylasedependent Dpn-1 endonuclease (part of Quikchange kit), leaving amplified mutant CCR5. The retained DNA preparations containing the CCR5 point mutations are transformed into XL-1 blue supercompetent E. coli (according to associated kit instructions) and incubated overnight on plates containing LB agar supplemented with 100 mg/ml ampicillin at 37 . Resulting colonies are expanded (e.g., 5 ml cultures of LB broth containing 100 mg/ml ampicillin at 37 overnight). Plasmid DNA is purified from the E. coli cultures using a Miniprep kit (see Section 6.3) according to the manufacturer’s protocol and the insert verified using restriction digest with EcoRV. Cultures associated with the expected restriction pattern are replated. Confirmed sequencevalidated clones are bulked up (e.g., 200 ml culture), DNA extracted, and quantified by UV spectroscopy (using maxi prep kit; see Section 6.3) for large-scale plasmid purification and HEK cell transfection.

5.3. Transfection of HEK Ga15 cells with pIRESneo-CCR5 (various isoforms) and pCRE-luc This method is a modification of the CRE-luc assay described above, with the following modifications: Solution 1 contains 7.5 mg CCR5 construct, 2.5 mg pCRE-luc reporter plasmid (see Section 6.3), 45 ml lipofectamine

46


plus reagent, and 800 ml optimem (see Section 6.3). Solution 2 contains 22.5 ml lipofectamine and 800 ml optimem. Transfected cells are washed with prewarmed (37 ) optimem (10 ml) and growth media (20 ml) prior to incubation overnight in a growth incubator and trypsin-EDTA treatment (1 ml supplied reagent; see Section 6.3) incubation for 2 min at RT, media resuspension, to 3 105 viable cells/ml. Cells are plated at 90 ml/well in 96-well, white opaque plates, incubated overnight prior to functional (CRE-luc) assay.

5.4. CRE-Luc reporter assay The CCR5-associated CRE-luc assay was described above. This can be undertaken for mutants versus wildtype to measure the effect of the mutation on the IC50 value. Loss in potency is implicated with a loss in binding at the mutation site. The docking pattern is computed accordingly.

5.5. Example results/data The data from such studies enable overlays of various antagonists based on an initial dock into CCR5, and can be validated using functional inhibition studies comparing compound potency for mutated versus wildtype receptor. This is exemplified in Fig. 2.13A where maraviroc and analogues in the monocyclic tropane series show an inhibitory potency loss against CCR5 signaling following Y108A and E283A mutation. The resultant docks respectably show the hydrophobic and ionic interactions at these residues by the phenyl and amine moieties of maraviroc. Similar interactions are seen with the tropane antagonist PF-232798 (Fig. 2.13B). A dock of the bispiperidine (i.e., bicyclic) CCR5 antagonist SCH-C is shows no equivalent interaction with Y108 (Fig. 2.13c), consistent with previous reports, highlighting this residue to be relatively unimportant in enabling interaction with CCR5 (Tsamis et al., 2003a). Comparative docks with other templates within the tropane series of CCR5 antagonists can be made to highlight differential occupation potentially underpinning the SAR required to enable activity against the laboratory generated MVCRES HIV-1 CC1/85, which has evolved resistance through multiple envelope mutation to enable entry via maraviroc-occupied CCR5 (Westby et al., 2004, 2007). The overlays highlight the additional spatial occupation by the imidazopiperidine group of PF-232798 (and UK-484900; see Table 2.1) around the ECL2 region, which is believed to stabilize CCR5 in a conformation that MVCRES HIV-1 CC1/85 cannot bind. This represents highly specific SAR, as close-in analogue benzimidazole tropanes such as UK-396794 and UK-438235 (see Table 2.1 and Fig. 2.13D) are inactive against MVCRES HIV-1 CC1/85 (Dorr et al., 2005a; Dorr and Perros, 2008; Westby et al., 2005).

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A ECL2

E283 Y108

C

B E283

E283

Y108

Y108

D E283

Y108

UK-433370 (cyclopropyl-triazole): inactive against MVCRES HIV-1 CC185

UK-396794 (benzimidazole): inactive against MVCRES HIV-1 CC185

PF-232798 (imidazopiperidine) active against MVCRES HIV-1 CC185

Figure 2.13 Computer-assisted docks of CCR5 antagonists and HIV resistance SAR. Computer-modeled docking of maraviroc (green) into the transmembrane pocket of CCR5, highlighting hydrophobic interaction between the maraviroc phenyl moiety with the tyrosine (Y) 108, and the ionic interaction between the tropane basic amine and the glutamic acid (E) 283 (A). Overlaps between maraviroc and PF-232798 (purple) and the bicyclic CCR5 antagonist SCH-C (yellow) are highlighted in (B) and (C), respectively. The extracellular loop 2 (ECL2) hinge region of CCR5 is highlighted. SAR associated with antiviral activity of CCR5 antagonists in the tropane series against laboratory-generated MVCRES HIV-1 CC185, with the requirement of differential occupancy at the ECL2 hinge region (specifically achieved by the imidazopiperidine substituent) highlighted, is shown in (D). Maraviroc is depicted in green and test compounds are depicted in purple. Full structures of compounds are shown inTable 2.1.

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6. Non-HIV Indications–Associated Studies, Human CCR5 Knock-In Mice CCR5 is a chemokine receptor, and has subsequently been investigated as a potential target against a wide range of predominantly inflammatory disorders. Such studies have been driven by expression studies in disease states and pharmacogenomic data highlighting positive, negative, or neutral correlation with diseases. Animal models using CCR5 ligands have also inferred association of CCR5 antagonism with efficacy against various disorders. Reviews on the potential of CCR5 antagonist for treatment of non-HIV diseases include Turner et al. (2007) and Wells et al. (2006). Preclinical evaluation of the utility of CCR5 antagonists against non-HIV diseases would be greatly facilitated by a highly potent and selective murine CCR5 antagonist. Unfortunately, no such tool has been reported, and compounds in current clinical HIV programs are highly selective for primate isoforms, and are devoid of activity against rodent species CCR5. To this end, a human CCR5 knock-in mouse has been constructed, where the human ORF supplants the murine ORF to ensure expression, and physiological role is as analogous to wildtype as possible. This, together with the identification of UK-484900 as a highly potent and selective human CCR5 antagonist with equivalent primary and selectivity pharmacology to maraviroc, coupled a PK profile (and dosing regime) in mice that ensures free compound exposure to be equivalent to maraviroc as seen in HIV-1 associated clinical practice (i.e., 100% functional CCR5 blockade), and has enabled a model for studying antagonist efficacy in various murine disease models (Dorr, 2008). Further validation has shown that hCCR5 is activated by murine chemokines (same EC50 as for human chemokines), and this is inhibited by hCCR5 antagonists. This validation of the model and utility in non-HIV diseases has recently been reported by (Dorr, 2008).

6.1. Vector construction for hCCR5 knock-in To generate a knock-in CCR5 mouse model, homologous recombination is used to replace the murine CCR5 gene with its human orthologue. Only the coding sequence of the human gene is inserted; thus the recombinant locus retains all mouse CCR5 cis-regulatory sequences and is expected to express the human CCR5 gene with the same cell specificity. The neomycin-resistance cassette used for targeting into ES cells is flanked by loxP sites and placed immediately after the stop codon (see Fig. 2.14). Therefore, the only permanent alteration of the locus is a 34 bp loxP site left after subsequent CRE-mediated recombination (Sauer and Henderson,

loxP

Spe

Stop

Human CCR5

Neomycin resistance

Xbol

3 kb Murine genomic DNA

BamH1 Sca

Kpn

ATG

loxP

3.5 kb Murine genomic DNA

Not1

49


Figure 2.14 CCR5 knock-in miceçtarget vector. Neomycin resistance cassette used for targeting into ES cells by homologous recombination with murine orthologue^ flanking regions (in situ) for human CCR5 (ORF-only) knock-in mice generation.The selection, excision, and marker restriction sites are shown.

1988). To achieve the seamless insertion of the human coding sequence into the mouse locus, the 50 arm of the targeting vector is constructed by overlapping PCR. The reverse oligo used to amplify the 3 kb of the murine genomic sequence upstream of the ATG includes 10 bp of the human coding sequence (Table 2.3). Likewise, the forward oligo used to amplify the human cDNA incorporated 30 bp of mouse genomic sequence at its 50 end, while the reverse primer contains a BamH1 cloning site, the loxP sequence, and stop codons. To complete the seamless junction at the ATG, another PCR is performed, which uses these two products as template to make a shorter product that bridges the mouse and human sequences. The full-length 50 homology arm is then assembled using naturally occurring restriction sites. The 30 homology arm is also made by PCR, using oligos that included a second loxP site in the forward primer. The completed homology arms are cloned into the pJNS2 vector containing PGKneomycin phosphotransferase for positive selection and the HSV thymidine kinase gene for negative selection. All products should be sequenced to ensure accuracy of the PCR.

6.2. Transfection and human CCR5 knock-in mouse generation The linearized targeting vector is electroporated into E14 129 ES cells (Hooper et al., 1987). Targeted clones can be identified by Southern blot using a 50 probe generated by PCR using oligos 585F/1521R and a 30 probe is made using oligos 9570F/10524. Targeting the 50 is determined by Sca1digestion (wt ¼ 6.5 kb, targeted ¼ 5.8 kb) and 30 targeting by Spe1 digestion (wt ¼ 11, targeted ¼ 7.5). Heterozygous animals carrying the targeted human allele are bred to mice expressing Cre recombinase under control of the E2A promoter (Lakso et al., 1996) to remove the neomycinresistance cassette, and then bred to homozygosity for the human CCR5, with cell surface expression checked in target cells (e.g., splenocytes, PBLs, etc.) using FACS technology as described above. These mice are available from Pfizer-GRD and are used in various academic laboratories as tools to investigate the potential of CCR5 antagonists to treat diverse inflammatory diseases.

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Table 2.3 Oligos used to build CCR5 KI vector

CCR5-10254R CCR5-9570F CCR5-585F CCR5-1521R CCR5-Kpn1755F CCR5-Not9496R CCR5-50 arm-R hCCR5-50 F hCCR5-50 R

CATGATCTTCTTCATTCTCC TCCTTGCATTTCACTCTAGC GGAACTTGAGAATATCATCC GATTTGAAGGTAACAGAGCG ATGGTACCATTGGTGTCTGGGATAAAGC ATAAGAATGCGGCCGCTCCAGCATTCTGCAGATCCACC GATAATCCATCCTGCAAGAG CCTATGAATAAATAAAAGAC GTCTTTTATTTATTCATAGGCTCTTGCAGGATGGATTA TCAAGTGTCAAGTCCAATCTATGAC TTGGATCCATAACTTCGTATAATGTATGCTATACGAA GTTATTCATCATCACAAGCCCACAG

hCCR5 30 arm-F

ATATTTCCTGCTCCCCAGTG ATACTCGAGATAACTTCGTATAGCATACATTATACGAAGT TATCCTGGTTGACTTTTGTGTATCACGTAG

hCCR5-690R muCCR5-4697-F

CCTCTTCTTCTCATTTCG CACTACTCATTCTTTCTGGC

6.3. Materials Most materials described as reagents can be sourced from various commercial suppliers. Bespoke materials (and their final preparation) used in the methods are listed in the following against each method section number, with associated supplier. 2.1. CCR5-associated Ca2þ signaling—Ca2þ flux buffer and assay reagents: One bottle HANKS balanced salts powder (Sigma), 1.6 ml of 1 M CaCl2 (Sigma), 10 ml of 1 M HEPES, pH 8 (Sigma, cat no. H-0763), made up to 1 l with sterile water and adjusted to pH 7.4 with hydrochloric acid (HCl). Calcium Plus Kit (Molecular Devices). 2.2. Receptor internalization signaling assay—Assay buffer: RPMI (10% FBS) (RPMI, Gibco Invitrogen Corporation), RANTES and SDF-1a (R&D Systems, Becton Dickinson), FACScalibur (Cell Quest Software). Mouse antihuman CCR5 monoclonal antibodies: 2D7 (Pharmingen). Isotype control antibodies: mouse IgG2a, (Pharmingen). Secondary PE-labeled antibody: PE-labeled goat anti-mouse antibody (Sigma). Sodium citrate CPT (4-ml draw) blood tubes (Becton Dickinson). Sample processing tubes (12 75-mm polystyrene round bottomed) and caps (push fit) (Sarstedt Ltd). Reagents: MIP-1b working solution (R & D systems, 100 nM MIP-1b) aliquots stored frozen at – 70 . CCR5 stabilizing solution (600 nM maraviroc in PBS), stabilizing control solution (PBS), CCR5 MsIgG R-phycoerythrin 2D7 antiCCR5 antibody (Pharmingen) (PE-labeling by custom order).


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2.4. GTP-associated CCR5 inverse agonism assay—Delfia GTPbinding kit (Perkin Elmer). Assay buffer: 50 mM HEPES, pH 7.4, containing 1 mM GDP, 10 mM MgCl2, 100 mM NaCl, and 100 mg/ ml saponin. MIP-1b (R & D Systems). Lysis buffer: 20 mM HEPES in purified water, containing 1 mM CaCl2, one tablet COMPLETETM protease inhibitors per 50-ml lysis buffer (BoehringerMannheim) adjusted to pH 7.4 (2 M HCl). 2.5. CRE-luciferase (CRE-Luc) reporter gene assay—Steady Glo Luciferase reagent (Promega). pCRE-luc, Pathdetect CRE cis reporting system (Stratagene). IBMX (Sigma). Human recombinant MIP-1b (R&D Systems). Forskolin (Sigma). 3.3. Real-time ligand binding using Biacore technology—Biacore 2000 and S51 optical biosensors, CM4 sensor chips, and the aminecoupling kit (Biacore AB). 1D4 antibody (University of British Columbia). The human chemokine receptor CCR5 is overexpressed in Cf2Th canine thymocyte cells as described previously (Mirzabekov et al., 1999); the cells are propagated by the National Cell Culture Center and contain a C-terminal linear C9 peptide tag (TETSQVAPA) that is recognized by the 1D4 monoclonal antibody (Oprian et al., 1987). Lipids (synthetic phospholipid blend [Dioleoyl] DOPC: DOPS [7:3, w/w]), Mini-Extruder kit, and polycarbonate filters (100 nm) (Avanti Polar Lipids). 3.4. HIV gp120 binding assay—pEE14.1 (Ba-L strain, Lonza Biologics). Human-soluble CD4 (Immunodiagnostics). Europium-labeled anti–HIV-1 gp120 IgG antibody (AALTO). Enhancement solution (EG&G Wallac). Wash buffer, Dulbecco’s PBS (Gibco). 4.2.1. CCR5-associated primary cell–based antiviral assays, peripheral blood lymphocytes (PBLs) and monocyte-derived macrophages (MDMs) HIV-1 replicative systems—HIV-1 isolates and strains and MT-2 cells: AIDS Reagent Project (NIBSC, Potters Bar, Herts, UK). All antiviral drug susceptibility assays are performed in RPMI 1640 medium, containing 10% v/v heat inactivated FCS, 2 mM L-glutamine, and antibiotics (1 U/ml penicillin and 0.1 mg/ml streptomycin). Phytohaemagglutinin (PHA), 1.5 mg/ml (Murex, Abbott Laboratories). Human recombinant interleukin2 (IL-2), 10 ng/ml (R&D Systems). QuanT RT kits (Amersham Pharmacia Biotech). 5. CCR5 site-directed mutagenesis and ligand docking studies— Plasmid pIRES neo (Clontech) pCRE-luc (Stratagene). Quikchange Site-Directed Mutagenesis kit (Stratagene). EcoRV (R&D Systems). QIAprep 8 Miniprep KitCat and QIAfilter Plasmid Maxi Kit (Qiagen). One ShotÒ TOP10 chemically competent cells E. coli (Invitrogen). HEK Ga15 cells (Aurora). HEK cell media: Dulbecco’s Modified Eagles Medium (DMEM) supplemented with 10% fetal calf serum, 2 mM

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L-glutamine, sodium pyruvate, HEPES, nonessential amino acids, and blasticidin. DMEM (Dulbecco’s), with/without phenol red (Invitrogen). Blasticidin (Invitrogen R21001). OptiMEM 1 (Invitrogen). Lipofectamine reagent (Invitrogen). Plus reagent (Invitrogen). Steady Glo Luciferase reagent (Promega). pCRE-luc, Pathdetect CRE cis reporting system (Stratagene). IBMX (Sigma). 6. Non-HIV indications–associated studies, human CCR5 knock-in mice—Animals are housed in an AAALAC-accredited facility and handled according to Pfizer global research guidelines complying with the U.S. Public Health Service policy for the care and use of laboratory animals. PCR is carried out using Expand HighFidelity polymerase (Roche, Laval, QC, Canada).

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(2005b). Maraviroc (UK-427,857), a potent, orally bioavailable, and selective smallmolecule inhibitor of chemokine receptor CCR5 with broad-spectrum anti-human immunodeficiency virus type 1 activity. Antimicrob. Agents Chemother. 49, 4721–4732. Dorr, P., Westby, M., McFadyen, L., Mori, J., Davis, J., Perruccio, F., Jones, R., Stupple, P., Middleton, D., and Perros, M. (2008). PF-232798, a Second Generation Oral CCR5 Antagonist. 15th Conference on Retroviruses and Opportunistic Infections, pp. 3–6. Boston. (Boston). February, 2008. Abstract 737. Dorr, P. (2008). Maraviroc outlook in HIV and non-HIV diseases. HIV-Infection and Organ Transplantation Symposium University Medical Center Hamburg-Eppendorf Hamburg, Germany. Haworth, B., Lin, H., Fidock, M., Dorr, P., and Strange, P. G. (2007). Allosteric effects of antagonists on signalling by the chemokine receptor CCR5. Biochem. Pharmacol. 74, 891–897. Epub 2007 Jun 26. Hooper, M., Hardy, K., Handyside, A., Hunter, S., and Monk, M. (1987). HPRT-deficient (Lesch-Nyhan) mouse embryos derived from germline colonization by cultured cells. Nature 326, 292–295. Jansson, C. C., Pohjanoksa, K., Lang, J., Wurster, S., Savola, J. M., and Scheinin, M. (1999). Alpha2-adrenoceptor agonists stimulate high-affinity GTPase activity in a receptor subtype-selective manner. Eur. J. Pharmacol. 374, 137–146. Kenakin, T., Jenkinson, S., and Watson, C. (2006). Determining the potency and molecular mechanism of action of insurmountable antagonists. J. Pharmacol. Exp. Ther. 319, 710–723. Epub 2006 Jul 20. Kondru, R., Zhang, J., Ji, C., Mirzadegan, T., Rotstein, D., Sankuratri, S., and Dioszegi, M. (2008). Molecular interactions of CCR5 with major classes of small-molecule anti-HIV CCR5 antagonists. Mol. Pharmacol. 73, 789–800. Epub 2007 Dec 20. Labrecque, J., Anastassov, V., Lau, G., Darkes, M., Mosi, R., and Fricker, S. P. (2005). The development of an europium-GTP assay to quantitate chemokine antagonist interactions for CXCR4 and CCR5. Assay Drug Dev. Technol. 3, 637–648. Lakso, M., Pichel, J. G., Gorman, J. R., Sauer, B., Okamoto, Y., Lee, E., Alt, F. W., and Westphal, H. (1996). Efficient in vivo manipulation of mouse genomic sequences at the zygote stage. Proc. Natl. Acad. Sci. USA 93, 5860–5865. Mirzabekov, T., Bannert, N., Farzan, M., Hofmann, W., Kolchinsky, P., Wu, L., Wyatt, R., and Sodroski, J. (1999). Enhanced expression, native purification, and characterization of CCR5, a principal HIV-1 coreceptor. J. Biol. Chem. 274, 28745–28750. Mosier, D. E., Picchio, G. R., Gulizia, R. J., Sabbe, R., Poignard, P., Picard, L., Offord, R. E., Thompson, D. A., and Wilken, J. (1999). Highly potent RANTES analogues either prevent CCR5-using human immunodeficiency virus type 1 infection in vivo or rapidly select for CXCR4-using variants. J. Virol. 73, 3544–3550. Mosley, M., Pullen, S., Botham, A., Gray, A., Napier, C., Mansfield, R., and Holbrook, M. (2006). The molecular cloning and functional expression of the dog CCR5. Vet Immunol. Immunopathol. 113, 415–420. Epub 2006 Jun 27. Mueller, A., Mahmoud, N. G., Goedecke, M. C., McKeating, J. A., and Strange, P. G. (2002). Pharmacological characterization of the chemokine receptor, CCR5. Br. J. Pharmacol. 135, 1033–1043. Mueller, A., Mahmoud, N. G., and Strange, P. G. (2006). Diverse signalling by different chemokines through the chemokine receptor CCR5. Biochem. Pharmacol. 72, 739–748. Epub 2006 Jul 17. Mueller, A., and Strange, P. G. (2004a). CCL3, acting via the chemokine receptor CCR5, leads to independent activation of Janus kinase 2 ( JAK2) and Gi proteins. FEBS Lett. 570, 126–132. Mueller, A., and Strange, P. G. (2004b). The chemokine receptor, CCR5. Int. J. Biochem. Cell. Biol. 36, 35–38.

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Napier, C., Sale, H., Mosley, M., Rickett, G., Dorr, P., Mansfield, R., and Holbrook, M. (2005). Molecular cloning and radioligand binding characterization of the chemokine receptor CCR5 from rhesus macaque and human. Biochem. Pharmacol. 71, 163–172. Epub 2005 Nov. 18. Navratilova, I., Dioszegi, M., and Myszka, D. G. (2006). Analyzing ligand and small molecule binding activity of solubilized GPCRs using biosensor technology. Anal. Biochem. 355, 132–139. Epub 2006 May 15. Oprian, D. D., Molday, R. S., Kaufman, R. J., and Khorana, H. G. (1987). Expression of a synthetic bovine rhodopsin gene in monkey kidney cells. Proc. Natl. Acad. Sci. USA 84, 8874–8878. Palczewski, K., Kumasaka, T., Hori, T., Behnke, C. A., Motoshima, H., Fox, B. A., Le Trong, I., Teller, D. C., Okada, T., Stenkamp, R. E., Yamamoto, M., and Miyano, M. (2000). Crystal structure of rhodopsin: A G. protein-coupled receptor. Science 289, 739–745. Peltonen, J. M., Pihlavisto, M., and Scheinin, M. (1998). Subtype-Specific Stimulation of [S-35]Gtp-Gamma-S Binding by Recombinant Alpha(2)-Adrenoceptors. European Journal of Pharmacology 355, 275–279. Petropoulos, C. J., Parkin, N. T., Limoli, K. L., Lie, Y. S., Wrin, T., Huang, W., Tian, H., Smith, D., Winslow, G. A., Capon, D. J., and Whitcomb, J. M. (2000). A novel phenotypic drug susceptibility assay for human immunodeficiency virus type 1. Antimicrob. Agents Chemother. 44, 920–928. Rickett, G., Dobbs, S., Griffin, P., Dorr, P., Hitchcock, C., and Perros, M. (2003). Development of a high throughput time resolved immunoassay to support discovery of HIV-1 entry inhibitors. 43rd Annual Interscience Conference on Antimicrobial Agents and Chemotherapy, Abstract F-1461. Sauer, B., and Henderson, N. (1988). Site-specific DNA recombination in mammalian cells by the Cre recombinase of bacteriophage P1. Proc. Natl. Acad. Sci. USA 85, 5166–5170. Strizki, J. M., Tremblay, C., Xu, S., Wojcik, L., Wagner, N., Gonsiorek, W., Hipkin, R. W., Chou, C. C., Pugliese-Sivo, C., Xiao, Y., Tagat, J. R., Cox, K., et al. (2005). Discovery and characterization of vicriviroc (SCH 417690), a CCR5 antagonist with potent activity against human immunodeficiency virus type 1. Antimicrob. Agents Chemother. 49, 4911–4919. Strizki, J. M., Xu, S., Wagner, N. E., Wojcik, L., Liu, J., Hou, Y., Endres, M., Palani, A., Shapiro, S., Clader, J. W., Greenlee, W. J., Tagat, J. R., et al. (2001). SCH-C (SCH 351125), an orally bioavailable, small molecule antagonist of the chemokine receptor CCR5, is a potent inhibitor of HIV-1 infection in vitro and in vivo. Proc. Natl. Acad. Sci. USA 98(22), pp. 12718–12723. Tagat, J. R., McCombie, S. W., Nazareno, D., Labroli, M. A., Xiao, Y., Steensma, R. W., Strizki, J. M., Baroudy, B. M., Cox, K., Lachowicz, J., Varty, G., and Watkins, R. (2004). Piperazine-based CCR5 antagonists as HIV-1 inhibitors. IV. Discovery of 1-[(4,6-dimethyl-5-pyrimidinyl)carbonyl]-4-[4-[2-methoxy-1(R)-4-(trifluoromethyl) phenyl]ethyl-3(S)-methyl-1-piperaz inyl]-4-methylpiperidine (Sch-417690/Sch-D), a potent, highly selective, and orally bioavailable CCR5 antagonist. J. Med. Chem. 47, 2405–2408. Tsamis, F., Gavrilov, S., Kajumo, F., Seibert, C., Kuhmann, S., Ketas, T., Trkola, A., Palani, A., Clader, J. W., Tagat, J. R., McCombie, S., Baroudy, B., et al. (2003a). Analysis of the mechanism by which the small-molecule CCR5 antagonists SCH351125 and SCH-350581 inhibit human immunodeficiency virus type 1 entry. J. Virol. 77, 5201–5208. Tsamis, F., Gavrilov, S., Kajumo, F., Seibert, C., Kuhmann, S., Ketas, T., Trkola, A., Palani, A., Clader, J. W., Tagat, J. R., McCombie, S., Baroudy, B., et al. (2003b). Analysis of the mechanism by which the small-molecule CCR5 antagonists SCH-


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351125 and SCH-350581 inhibit human immunodeficiency virus type 1 entry. J. Virol. 77, 5201–5208. Turner, J. E., Steinmetz, O. M., Stahl, R. A., and Panzer, U. (2007). Targeting of Th1-associated chemokine receptors CXCR3 and CCR5 as therapeutic strategy for inflammatory diseases. Mini Rev. Med. Chem. 7, 1089–1096. Watson, C., Jenkinson, S., Kazmierski, W., and Kenakin, T. (2005a). The CCR5 receptorbased mechanism of action of 873140, a potent allosteric noncompetitive HIV entry inhibitor. Mol. Pharmacol. 67, 1268–1282. Watson, C., Jenkinson, S., Kazmierski, W., and Kenakin, T. (2005b). The CCR5 receptorbased mechanism of action of 873140, a potent allosteric noncompetitive HIV entry inhibitor. Mol. Pharmacol. 67, 1268–1282. Epub 2005 Jan. 11. Wells, T. N., Power, C. A., Shaw, J. P., and Proudfoot, A. E. (2006). Chemokine blockers-therapeutics in the making? Trends Pharmacol. Sci. 27, 41–47. Epub 2005 Nov. 28. Westby, M., Smith-Burchnell, C., Hamilton, D., Robas, N., Irvine, B., Fidock, M., Mills, J., Perruccio, F., Mori, J., Macartney, M., Barber, C., Dorr, P., et al. (2005). UK-427,857resistant Primary Isolates are Susceptible to Structurally-related CCR5 Antagonists. In ‘‘12th Conference on Retroviruses and Opportunistic Infections,’’ Boston, MA. Westby, M., Smith-Burchnell, C., Mori, J., Lewis, M., Mosley, M., Stockdale, M., Dorr, P., Ciaramella, G., and Perros, M. (2007). Reduced maximal inhibition in phenotypic susceptibility assays indicates that viral strains resistant to the CCR5 antagonist maraviroc utilize inhibitor-bound receptor for entry. J. Virol. 81, 2359–2371. Westby, M., Smith-Burchnell, C., Mori, J., Lewis, M., Whitcomb, J., Petropoulos, C., and Perros, M. (2004). In vitro Escape of R5 Primary Isolates from the CCR5 Antagonist, UK-427,857, is Difficult to Achieve and Involves Continued Use of the CCR5 Receptor. In ‘‘XIII International HIV Drug Resistance Workshop,’’ Tenerife.

C H A P T E R

T H R E E

CXCR4 and Mobilization of Hematopoietic Precursors Michael P. Rettig, Pablo Ramirez, Bruno Nervi, and John F. DiPersio Contents 1. Introduction 2. HSPC Mobilizing Agents that Target the CXCL12/CXCR4 Axis 3. Donor Selection for HSPC Mobilization 3.1. Selection of mice for HSPC mobilization 3.2. Selection of humans for HSPC mobilization 4. Flow Cytometric Enumeration of Mobilized HSPCs 4.1. Flow cytometric enumeration of murine HSPCs 4.2. Flow cytometric enumeration of human HSPCs 5. Dosing and Kinetics of HSPC Mobilization by G-CSF and Plerixafor 5.1. G-CSF 5.2. Plerixafor 6. Flow Cytometric Analysis of CXCR4 Expression on Human CD34þ Subsets 6.1. Evaluation of cell surface CXCR4 on human CD34þ cell subsets 7. Functional Characterization of Mobilized HSPCs 7.1. In vitro assays of differentiation 7.2. Transmigration assays 7.3. Transplantation assays for mouse and human HSPCs 8. Concluding Remarks Acknowledgment References

58 59 64 64 64 65 65 65 66 66 67 69 70 73 73 73 74 80 80 80

Abstract The binding of the chemokine [C-X-C motif ] ligand 12 (CXCL12 or stromal cell– derived factor 1a [SDF-1a]) constitutively produced by bone marrow stromal cells and osteoblasts, to the CXC receptor (CXCR) 4, a transmembrane chemokine receptor expressed on hematopoietic stem and progenitor cells (HSPCs),

Division of Oncology, Siteman Cancer Center, Washington University School of Medicine, St. Louis, Missouri, USA Methods in Enzymology, Volume 460 ISSN 0076-6879, DOI: 10.1016/S0076-6879(09)05203-3

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Michael P. Rettig et al.

has emerged as a key signal for HSPC trafficking to and from the bone marrow. Disruption of CXCL12/CXCR4 signaling causes leukocytosis, with the release of HSPCs, neutrophils, and lymphocytes into the peripheral blood. Although mobilized peripheral blood has become the preferred source of stem cells for both autologous and allogeneic transplantation, the optimum strategy for obtaining mobilized products from donors is the subject of ongoing study. Granulocyte colony–stimulating factor (G-CSF) and plerixafor (AMD3100) are two agents used clinically to induce HSPC mobilization by disruption of the CXCL12/CXCR4 interaction. This chapter describes current procedures used to phenotypically and functionally characterize murine and human HSPCs mobilized by G-CSF or plerixafor.

1. Introduction The majority of hematopoietic stem and progenitor cells (HSPCs) reside in the bone marrow in a highly organized microenvironment consisting of marrow stromal cells, osteoblasts, osteoclasts, and other extracellular matrix proteins (e.g., collagens, fibronectins, proteoglycans) (Adams and Scadden, 2006; Kiger et al., 2000; Kollet et al., 2007; Wilson and Trumpp, 2006; Xie and Spradling, 2000). HSPCs express a number of cell surface molecules such as lymphocyte function–associated antigen-1 (LFA-1), very late antigen 4 (VLA-4), CXCR4, CXCR2, CD44, CD62L, and CD117 (c-kit) that mediate their adherence in the bone marrow (BM) microenvironment (Adams and Scadden, 2006; Lapidot et al., 2005; Wilson and Trumpp, 2006). These interactions play important roles in regulating HSPC trafficking, as well as self-renewal, proliferation, and differentiation processes (Kiel and Morrison, 2008; Wilson and Trumpp, 2006). Under normal conditions, a small number of HSPCs circulate in the peripheral blood. However, the number of circulating HSPCs can be increased 10- to 100-fold with administration of chemotherapy and/or cytokines in a process termed ‘‘stem cell mobilization’’ (Bensinger et al., 2009; Papayannopoulou and Scadden, 2008; Winkler and Levesque, 2006). Mobilized HSPCs can be collected by large-volume apheresis techniques in numbers sufficient for use in hematopoietic stem cell transplants, and upon reinfusion, are capable of homing to the BM cavity and regenerating the full array of hematopoietic lineages. Compared to BM, use of peripheral blood stem cells in hematopoietic stem cell transplantation results in more rapid hematologic reconstitution, reduced hospitalization costs, and avoids the risks of general anesthesia and discomfort with a BM harvest (Group, 2005). Because of these advantages, the use of mobilized HSPCs over marrow as a stem cell source continues to increase such that greater than 95% of

CXCR4 and Mobilization

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autologous transplants and 75% of allogeneic hematopoietic stem cell transplants in adults are currently being performed with mobilized HSPCs (Bensinger et al., 2009). The optimal method for mobilization of HSPCs remains a subject of investigation. Although various agents have been used to mobilize HSPCs, only granulocyte colony-stimulating factor (G-CSF) (filgrastim, NeupogenÒ , Amgen, Thousand Oaks, CA), granulocyte-macrophage colony-stimulating factor (GM-CSF) (sargramostim, LeukineÒ , Bayer Healthcare Pharmaceuticals, Seattle, WA), stem cell factor (ancestim, StemgenÒ , Amgen, Thousand Oaks, CA, available in Canada and New Zealand only), and plerixafor (Mozobil, AMD3100, Genzyme Corporation, Cambridge, MA) are approved clinically for use in stem cell mobilization (Bensinger et al., 2009). Currently, G-CSF is the most commonly used agent to induce HSPC mobilization. However, because optimal mobilization requires from 4 to 6 days of G-CSF administration, donors may experience significant inconvenience, including bone pain, fatigue, headache, and nausea. Furthermore, while no long-term sequelae have been confirmed with short-term G-CSF, there are reports of serious acute toxicities related to its use as well as concerns that it can induce genetic and epigenetic modifications in HSPCs (Hernandez et al., 2005; Nagler et al., 2004; Shapira et al., 2003; Tigue et al., 2007). Accordingly, a less toxic, more rapid, and yet efficient method for collection of HSPCs from donors is still required and would represent a clear advance.

2. HSPC Mobilizing Agents that Target the CXCL12/CXCR4 Axis Targeted disruption of the interaction between CXCR4 and CXCL12 has received considerable attention since it may provide a method to efficiently and rapidly mobilize HSPCs from the BM into the periphery as well as inhibiting the metastatic process and HIV-1 infection (Burger and Peled, 2009; Grande et al., 2008; Khan et al., 2007; Uy et al., 2008). CXCL12 is a chemokine constitutively produced at high levels in the BM by stromal cells such as osteoblasts, endothelial cells, and a subset of reticular cells (Calvi et al., 2003; Dar et al., 2005; Imai et al., 1999; Jung et al., 2006; Ponomaryov et al., 2000). It is a potent chemoattractant for HSPCs and has been shown to regulate cell adhesion, survival, and cell-cycle status (Peled et al., 1999; Sugiyama et al., 2006; Watt and Forde, 2008). Interestingly, CXCL12 gene polymorphism has been proposed as a conditional factor for human CD34þ stem cell mobilization, with the presence of the SDF1-30 A allele as a predictive factor of good CD34þ cell mobilization (Benboubker

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et al., 2001). More recently, a second receptor, CXCR7, was identified that binds CXCL12 with an affinity that is approximately 10-fold higher than the affinity for CXCR4 (Balabanian et al., 2005a; Burns et al., 2006). Although the role of CXCR7 in CXCL12-dependent chemotaxis is not fully understood, there is evidence that CXCR7 lacks intrinsic chemotactic activity toward CXCL12, and functions instead by sequestering CXCL12 and modifying CXCR4 signaling (Boldajipour et al., 2008; Hartmann et al., 2008; Sierro et al., 2007). CXCR4 is a member of the large family of seven transmembrane domain receptors coupled to heterotrimeric Gi proteins and functions as a coreceptor for HIV-1 cell entry (Bleul et al., 1996; Feng et al., 1996; Fredriksson et al., 2003; Loetscher et al., 1994; Oberlin et al., 1996). Both CXCL12 (Bleul et al., 1996; Oberlin et al., 1996) and macrophage migrating inhibiting factor (MIF) (Bernhagen et al., 2007) are ligands for CXCR4. The binding of CXCR4 to CXCL12 results in activation of multiple signal transduction pathways ultimately triggering chemotaxis (Busillo and Benovic, 2007; Kucia et al., 2004). Targeted disruption of either CXCL12 or CXCR4 is lethal in mice, resulting in very similar developmental defects, including the failure of HSPC migration from the fetal liver to the BM, defects in lymphoid and myeloid hematopoiesis, and cerebellar dysgenesis (Ma et al., 1998; Nagasawa et al., 1996; Tachibana et al., 1998; Zou et al., 1998). Furthermore, wildtype mice transplanted with CXCR4-deficient progenitor cells have high circulating levels of HSPCs, indicating poor retention in the BM (Christopher et al., 2009; Ma et al., 1999). Finally, multiple preclinical and clinical studies have shown that pharmacologic interference in the axis between marrowderived CXCL12 and CXCR4 expressed on HSPCs using various CXCR4 modulators, including antagonist, peptide agonist, and modified CXCL12 analogues stimulate HSPC mobilization in a target-dependent manner (Nervi et al., 2006; Pelus, 2008). There are three potential mechanisms to explain how CXCR4 could regulate HSPC mobilization: (1) downregulation of cell surface CXCR4 by internalization or proteolysis, (2) disruption of the CXCL12 chemokine gradient between the BM and plasma, and (3) receptor antagonism via direct blocking of the CXCR4/CXCL12 interaction (Table 3.1). Decreased expression of CXCR4 on mobilized HSPCs has been reported following administration of G-CSF (Christopher et al., 2009; Dlubek et al., 2006; Levesque et al., 2003; Oelschlaegel et al., 2007; Semerad et al., 2005), a CXCL12 analogue (met-SDF-1b) (Shen et al., 2001; Yang et al., 1999), and CXCL12-derived peptide agonists (CTCE-0021, CTCE-0214) (Faber et al., 2007; Pelus et al., 2005; Zhong et al., 2004). Since native CXCL12 itself downregulates CXCR4 expression but does not result in significant mobilization (Haribabu et al., 1997; Orsini et al., 1999;

Class

Growth factor

Growth factor

Bicyclam

Peptide

Peptide

CXCL12 analog

Compound

G-CSF

Pegylated G-CSF

Plerixafor

T140

T134

Met-SDF1b

CXCR4 agonist

CXCR4 antagonist

CXCR4 antagonist

Granulocyte expansion/ activation, protease release, and cleavage of adhesion molecules, downregulation of CXCL12 in osteoblasts Granulocyte expansion/ activation, protease release and cleavage of adhesion molecules, downregulation of CXCL12 in osteoblasts CXCR4 antagonist

Mechanism

Table 3.1 CXCR4-mediated mobilization of murine HSPC

SC IV

10 mg/kg 300 mg

SC

IV

3 mg/kg 5 mg/kg

SC

SC

25 mg

5 mg/kg

SC

Route

250 mg/kg/ day x 5 days

Dose

48 h

1h

1–2 h

1–3 h

3–6 h

Day 3

Day 5

HSPC peak mobilization

(continued)

Broxmeyer et al., 2005 Ramirez et al., 2008 Abraham et al., 2007 Iyer et al., 2008 Shen et al., 2001

de Haan et al., 2000

Molineux et al., 1990

Reference

CXCL12 peptide analog CXCL12 peptide analog Sulfated polysaccharide

CTCE0021 CTCE0214 FucS IV

75 mg 100 mg/kg

CXCR4 agonist

Disruption of CXCL12 chemotactic gradient

IV

SC

Route

25 mg/kg

Dose

CXCR4 agonist

Mechanism

1.5 h

4h

1h

HSPC peak mobilization

Pelus, et al., 2005 Zhong et al., 2004 Sweeney et al., 2002

Reference

G-CSF, granulocyte colony-stimulating factor; Met-SDF, N-terminal methionine stromal cell---derived factor; FucS, sulfated polysaccharide fucoidan; IV, intravenous; SC, subcutaneous; n.d., not determined.

Class

Compound

Table 3.1 (continued)


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Signoret et al., 1997, 1998), it is generally believed that a threshold level of CXCR4 downregulation may be required for these agents to induce HSPC mobilization (Busillo and Benovic, 2007; Kucia et al., 2004). Concerning the second mechanism whereby CXCR4 could modulate HSPC mobilization, studies have shown that disruption of the CXCL12 gradient between the BM and the peripheral blood by the administration of sulfated polysaccharides (Sweeney et al., 2002) or adenovirus expressing CXCL12 (Hattori et al., 2001) results in an increase in circulating CXCL12 and HSPC mobilization. More relevant physiologically, recent studies have shown that a key step in G-CSF–induced HSPC mobilization is loss of CXCL12 expression by osteoblasts in the BM (Christopher et al., 2009; Katayama et al., 2006; Semerad et al., 2005). Since similar results were observed following mobilization of mice with Flt3L or stem cell factor (Christopher et al., 2009), this loss of osteoblast-produced CXCL12 may represent a common pathway in cytokine-induced mobilization. Finally, several CXCR4 antagonists have been described, of which plerixafor (Broxmeyer et al., 2005; Liles et al., 2003; Uy et al., 2008), T140 (Abraham et al., 2007), and T134 (Iyer et al., 2008) have been shown to rapidly mobilize HSPCs. Additional evidence for the critical role that CXCR4 plays in leukocyte trafficking has been obtained from patients with the genetic immunodeficiency syndrome WHIM (warts, hypogammaglobulinemia, infections, myelokathexis). WHIM syndrome is a rare congenital immunodeficiency disorder characterized by susceptibility to human papilloma virus infectioninduced warts, B-cell lymphopenia and hypogammaglobulinemia, chronic noncyclic neutropenia, and BM myeloid hyperplasia with apoptosis (Gorlin et al., 2000; Gulino, 2003). Most cases of WHIM syndrome have been linked to autosomal dominant mutations in CXCR4, all of which truncate the C-terminal tail of CXCR4 (Balabanian et al., 2005b; Gulino et al., 2004; Hernandez et al., 2003). Multiple studies have demonstrated that loss of the intracellular tail of CXCR4 prevents its internalization and desensitization in response to CXCL12 (Balabanian et al., 2005b; Gulino et al., 2004; Kawai et al., 2005). This loss of homologous desensitization leads to long-lasting activation of G-proteins and sustained functional activity of the chemokine receptor as evidenced by increased chemotaxis to CXCL12, F-actin polymerization, intracellular calcium release, and endothelial adhesion (Balabanian et al., 2005b, 2008; Gulino et al., 2004). Since CXCL12 is expressed constitutively at high levels in the BM, it is not surprising that WHIM leukocytes preferentially traffic to the marrow. In fact, expression of the WHIM-type mutated CXCR4 in healthy human CD34þ cells enhances their chemotactic response to CXCL12 and BM engraftment in immunodeficient mice (Kawai et al., 2007).

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3. Donor Selection for HSPC Mobilization 3.1. Selection of mice for HSPC mobilization Mice aged 8 weeks or older are used for mobilization experiments. When purchased from commercial vendors or obtained from outside sources, we allow the mice to acclimate to our facility for at least 1 week before use. All animal use should be in accordance with the guidelines of each individual’s Institutional Animal Care and Use Committee, the Federal Animal Welfare Act, and conform to recommendations in the Guide for the Care and Use of Laboratory Animals (Institute of Laboratory Animal Resources, National Research Council, National Academy of Sciences, 1996). Similar to humans, there is a wide variation in the magnitude of HSPC mobilization by different inbred strains of mice in response to G-CSF. Following treatment of mice with 200 mg/kg/d G-CSF for 5 days, Roberts et al. (1997) observed a 10-fold range in the number of circulating progenitor cells between different inbred strains of mice, with the mobilization efficacy roughly aligning in the following order: DBA > 129Sv > BALB/c ¼ SJL > C57Bl/6 ¼ C3H/He. Similarly, Broxmeyer and colleagues (2005) reported that the combination of G-CSF and plerixafor induced significantly greater mobilization of HSPCs in DBA mice compared with either C57Bl/6 or C3H/He. Although the exact mechanism/s for this large interstrain variation remains unresolved, both genetic determinants and the size of the stem cell pool play a role in the efficiency of mobilization by G-CSF (reviewed in Herbert et al., 2008). Because of the broad variability in mobilization efficiency by different strains of mice, it is preferable to test at least two strains of mice that differ in responsiveness to G-CSF when setting up mobilization experiments (Herbert et al., 2008).

3.2. Selection of humans for HSPC mobilization At our institution, eligible donors are between the ages of 18 and 70 years inclusive with evidence of adequate organ function (left ventricular ejection fraction more than 40%, formal pulmonary function testing showing a forced expiratory volume in 1 s [FEV1], more than 50% of predicted and a diffusing lung capacity for carbon dioxide [DLCO], more than 40% of predicted [corrected for hemoglobin]), a serum creatinine clearance of more than 40% of normal, a total bilirubin less than two times normal or absence of hepatic fibrosis/cirrhosis, no evidence of a severe central or peripheral neurologic abnormality, no evidence of active infection, be HIV negative, and have an Eastern Cooperative Oncology Group (ECOG) performance status of 0 or 1. Donors must give written consent in accordance with the Declaration of Helsinki on a study approved by the Human Studies


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Committee at Washington University. In the case of studies involving plerixafor, the Food and Drug Administration (FDA) approved the study under an investigator-held investigational new drug application.

4. Flow Cytometric Enumeration of Mobilized HSPCs Previous chapters in this journal (Hawley et al., 2006; Lin and Goodell, 2006) and elsewhere (Ema et al., 2006; Fukuda and Pelus, 2008; Herbert et al., 2008; Robinson and van Os, 2008) provide current procedures used to phenotypically characterize and isolate candidate human and murine HSPCs. The reader is referred to these publications for detailed methodology. In the following, we first briefly summarize the most common phenotypes used to characterize murine and human HSPCs.

4.1. Flow cytometric enumeration of murine HSPCs Among the subsets that define hematopoietic stem cells, CD34 c-kitþ Sca-1þ lineage marker (CD34KSL) cells are regarded as one of the populations that have the highest enrichment of HSPCs in adult mouse BM (Giebel and Punzel, 2008; Weissman and Shizuru, 2008). More recently, Morrison and colleagues (Kiel et al., 2005) have used markers from the SLAM family—CD150, CD244, and CD48—to differentiate stem cells from more committed progenitor cells. The most primitive murine stem cells were found to reside within the CD150þCD244–CD48– subpopulation.

4.2. Flow cytometric enumeration of human HSPCs The enumeration of cells that express the cell surface marker CD34 present on human HSPCs is used to assess the adequacy of stem cell numbers for hematopoietic stem cell transplantation. In humans, the CD34þ cell population contains progenitors committed to the myeloid, erythroid, megakaryoid, and lymphoid lineages, as well as primitive progenitors and stem cells capable of long-term reconstitution (Giebel and Punzel, 2008; Weissman and Shizuru, 2008). Although no adequate threshold exists, a minimum of 2.0 106 CD34þ cells/kg body weight is used by many centers to ensure adequate neutrophil recovery after transplant (Gandhi et al., 1999; Montgomery and Cottler-Fox, 2007; Tricot et al., 1995). Additionally, 5 106 CD34þ cells/kg has been considered by some to be the optimal target as it results in faster platelet recovery post transplant (Bensinger et al., 1995; Brown et al., 1997; Weaver et al., 1995).

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5. Dosing and Kinetics of HSPC Mobilization by G-CSF and Plerixafor 5.1. G-CSF 5.1.1. Mobilization of murine HSPCs by G-CSF Mice are typically mobilized with recombinant human G-CSF (Amgen, Thousand Oaks, CA) diluted in phosphate buffered saline (PBS) with 0.1% low endotoxin bovine serum albumin (BSA, Sigma) and administered by daily subcutaneous injection for 5 days at a dose of 250 mg/kg (Molineux et al., 1990). Although the mechanism by which G-CSF induces HSPC mobilization remains controversial, the absence of a mobilization response in CXCR4–/– BM chimeras indicates the absolute dependence of this chemokine receptor in G-CSF–induced HSPC mobilization (Christopher et al., 2009). Pegylated-G-CSF (pegfilgrastim, Neulasta, Amgen, Inc) is a longerlasting variant of G-CSF and was approved by the FDA in the USA to prevent prolonged neutropenia following chemotherapy for nonhematological malignancies (Kroschinsky et al., 2008). The 33-h plasma half-life of pegfilgrastim is substantially longer than the 4- to 6-h half-life of G-CSF due to decreased serum clearance (Zamboni, 2003). Peak mobilization of murine CFU-GM and CAFC by pegfilgrastim is observed 3 days after a single subcutaneous injection of 25 mg (de Haan et al., 2000). 5.1.2. Mobilization of human HSPCs by G-CSF When G-CSF is used alone for human HSPC mobilization, the recommended dose is 10 mg/kg subcutaneous daily (either as a bolus or continuous infusion) beginning at least 4 days before the first apheresis session and continued until the last apheresis session (Gazitt et al., 1999) (Neupogen [filgrastim]). Circulating CD34þ stem cell levels usually peak on the 5th day of G-CSF (Lane et al., 1995). Administration of G-CSF at a dose of at least 10 mg/kg/day for 5 days is usually required to achieve the mobilization goal of 5 106 CD34þ cells/kg of recipient body weight, a dose considered suitable for reproducible, rapid, and consistent engraftment of both neutrophils and platelets (Henon et al., 1992; Schmitz et al., 1996). Although the Food and Drug Administration (FDA) approved pegfilgrastim for the prevention of prolonged neutropenia after chemotherapy for nonhematological malignancies, its potential as a mobilizing agent is still being explored. In healthy donors, a single dose of 12 mg pegfilgrastim has been shown to mobilize CD34þ stem cells with a similar magnitude and kinetics as standard G-CSF (Hill et al., 2006; Kroschinsky et al., 2005).


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High-dose GCSF was investigated as a primary mobilization regimen throughout the 1990s (Kobbe et al., 1999; Sheridan et al., 1994; Zeller et al., 1996). Although seldom used today for primary mobilization, high-dose GCSF regimens are occasionally employed for remobilization (Boeve et al., 2004; Wang et al., 2007). Doses ranging from 16 to 32 mg/kg subcutaneous daily to 12 to 16 mg/kg subcutaneous twice daily have been considered as high-dose regimes (Bensinger et al., 2009).

5.2. Plerixafor 5.2.1. Mobilization of murine HSPCs by plerixafor Plerixafor (Genzyme, Cambridge, MA) is supplied as a sterile isotonic aqueous solution at 10 mg/ml. Broxmeyer and colleagues (2005) showed that a single-dose administration of 5 mg/kg subcutaneous plerixafor induces rapid mobilization of hematopoietic progenitor cells (HPCs) and long term repopulating cells to the blood of mice, with maximal mobilization of the HSPCs occurring 1 h postinjection. In agreement with these published results, we found that treatment of 129 B6 F1 mice with subcutaneous plerixafor results in rapid mobilization of white blood cells (WBC) and HPCs, with peak CFU-GM levels achieved 3 h after a single injection of 5 mg/kg plerixafor (Ramirez et al., 2008). Furthermore, we reported that repetitive subcutaneous injection of 5 mg/kg plerixafor to mice every 24 h results in a similar mobilization of progenitors (CFU-GM) after each injection (Nervi et al., 2009). Similar data were generated by Hubel et al. (2004) using normal human volunteers. These data demonstrate that subcutaneous plerixafor can be given daily resulting in similar kinetics and magnitude of progenitor mobilization with no obvious tachyphylaxis. In a separate series of experiments, we tested the efficacy of murine HSPC mobilization following intravenous administration of 1, 3, or 5 mg/kg plerixafor (Ramirez et al., 2008). Analysis of the dose–response relationship indicated that intravenous plerixafor resulted in more rapid mobilization (peak 1 h) than subcutaneous administration. Doses higher than 3 mg/kg intravenous plerixafor were lethal to the mice. 5.2.2. Mobilization of human HSPCs by plerixafor The FDA approved plerixafor for use in combination with G-CSF to mobilize HSPCs in patients with non-Hodgkin’s lymphoma and multiple myeloma undergoing autologous transplantation in December 2008. Subcutaneous injection of 240 mg/kg plerixafor is initiated after the patient has received 10 mg/kg/day G-CSF for 4 days, followed by leukapheresis beginning 11 h after drug treatment (MOZOBIL [plerixafor injection]).

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We recently published results from a Phase II study evaluating the safety and efficacy of plerixafor for CD34þ stem cell mobilization in allogeneic transplantation (Devine et al., 2008). Twenty-five donors were treated with a single subcutaneous dose of 240 mg/kg plerixafor and underwent apheresis 4 h later, with collection of enough stem cells for transplant (defined as >2 106 CD34þ cells/kg) in two-thirds of the donors. Twenty patients with hematologic malignancies received plerixafor-mobilized stem cell products with no adverse events. Although the CD34þ doses obtained were lower than that observed with a standard G-CSF mobilization regimen, the plerixafor-mobilized allografts functioned well and promoted rapid and durable multilineage hematopoiesis in the recipients. In our Phase II study discussed above, only 16 of the first 24 donors mobilized with subcutaneous plerixafor (240 mg/kg) collected the minimal required target of 2 106 CD34þ cells/kg in a single apheresis (Devine et al., 2008). Based on preliminary data suggesting higher (twofold) and earlier (1 h vs. 3 h) progenitor mobilization in mice after intravenous versus subcutaneous dosing of plerixafor (Ramirez et al., 2008), we amended our trial and began testing the safety and efficacy of increasing doses of intravenous plerixafor (80, 160, 240, 320, 400, and 480 mg/kg over 30 min) on the kinetics and magnitude of allogeneic HSPC mobilization. In an ongoing Phase I safety evaluation of intravenous plerixafor, allogeneic related donors are initially mobilized with increasing doses of intravenous plerixafor. After 4 days of drug clearance, the same donors are then mobilized with a single subcutaneous dose of 240 mg/kg plerixafor, and collected cells are used as a source of stem cells for transplantation. Consistent with our hypothesis, patients treated intravenously with 240 mg/kg plerixafor had higher peak levels of CD34þ cells/ml blood at every time point evaluated compared to the same plerixafor dose administered subcutaneously (Rettig et al., 2008). Furthermore, we have noted a clear dose–response effect of increasing doses of intravenous plerixafor. Of the seven donors who received 320 mg/kg intravenous plerixafor, all achieved peak levels of CD34/kg greater than 20 CD34/ml (range 22 to 38/ml), a level that we as well as others have shown is highly correlated with achieving more than 2 106 CD34/kg after a single apheresis (Bensinger et al., 2009; Pusic et al., 2008). Since no related dose-limiting toxicity has yet been determined, we plan to complete the final two intravenous dose cohorts (400 mg/kg and 480 mg/kg). These encouraging studies suggest that intravenous plerixafor may be a more effective mobilizing agent with a low side effect profile. We predict, based on this preliminary data, that the optimal dose of intravenous plerixafor will result in similar rates of achieving 2 106 CD34/kg after a single apheresis procedure compared to G-CSF in less time (4 h vs. 5 days).


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6. Flow Cytometric Analysis of CXCR4 Expression on Human CD34þ Subsets A variety of cell types express the CXCR4 receptor, including peripheral blood lymphocytes (B cells and T cells), monocytes, neutrophils, pre–B cells, mast cells, CD34þ HPCs, endothelial cells, intestinal and alveolar epithelial cells, astrocytes, microglia, and neurons (Khan et al., 2007). CXCR4 receptors cycle continuously to and from the cell surface in a ligand-independent manner, with the majority of CXCR4 being stored in an intracellular pool (Busillo and Benovic, 2007; Marchese et al., 2008; Zhang et al., 2004). The function of these large stores of intracellular CXCR4 remains unclear. In our recently published Phase II study evaluating the safety and efficacy of plerixafor for CD34þ stem cell mobilization in allogeneic transplantation (Devine et al., 2008), eight normal donors were mobilized sequentially with plerixafor and G-CSF. These donors initially received one subcutaneous injection of 240 mg/kg plerixafor, followed by leukapheresis beginning 4 h after drug treatment. After 10 days of drug clearance, the same donors were mobilized with 5 days subcutaneous injection of 10 mg/kg/day G-CSF, and leukapheresed on day 5. Interestingly, we found via flow cytometry that plerixafor mobilized a unique population of CD34dim cells which were present in 3- to 10-fold higher numbers compared to G-CSF mobilized CD34þ cells (Rettig et al., 2008). We further characterized CD34 immunoselected cells obtained after plerixafor or G-CSF mobilization of normal human donors by staining for CD34-APC and CD45RA-FITC. This staining and gating approach has allowed us to separate CD34þ cells in plerixafor mobilized products into three separate subsets (only two in G-CSF mobilized grafts), with the CD34dimCD45RAþ subset relatively specific to plerixafor compared to G-CSF mobilized products (Fig. 3.1). Of interest, two of the key molecules responsible for stem cell homing, retention, and trafficking, CXCR4 and VLA-4, were significantly overexpressed in the CD34dimCD45RAþ subset compared to the CD34þCD45RA– and CD34þCD45RAþ cells (Fig. 3.1). Others have shown that CD34þCD45RAþ cells represent more committed progenitors (reviewed in Blom and Spits, 2006; Weissman and Shizuru, 2008), with two different CD34dimCD45RAþ progenitor cell subsets having been described in the literature (Blom et al., 2000; Freud et al., 2005). Ongoing studies in the lab are further characterizing the CD34dimCD45RAþ progenitor cell subset preferentially mobilized by plerixafor. Below we describe in detail our method to purify and phenotype these different CD34þ stem cell subsets.

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Plerixafor

G-CSF 15.7

21

62.9

16.7 CD34

CD34

A

80.8

2.34

CD45RA

CD45RA

% of max

% of max

B

CXCR4

CXCR4

% of max

% of max

C

VLA-4

VLA-4

CD45RA−CD34+ CD45RA+CD34+ CD45RA+CD34dim

Figure 3.1 Coexpression of CD45RA on human CD34þ cells identifies the CD34dim subset. (A) Healthy donors were treated with a single injection of 240 mg/kg AMD3100 or given 10 mg/kg/day G-CSF for 5 days. CD34þ cells from leukapheresis products were purified by CD34 immunoselection using an autoMACS device and the expression of CD34 and CD45RA was evaluated by flow cytometry. CD45RAþCD34dim cells are enriched in AMD3100-mobilized products. (B-C) CD45RAþCD34dim cells from AMD3100-mobilized products express high levels of surface CXCR4 (B) and VLA-4 (C).

6.1. Evaluation of cell surface CXCR4 on human CD34þ cell subsets Aliquots of leukapheresis products are obtained in evacuated tubes coated with ethylene-diaminetetra-acetic acid (EDTA) or sodium heparin after informed consent in conformity with a human subjects protocol approved by an institutional review board. Rapid processing of samples is particularly important, since surface expression of CXCR4 may increase with time due to release from intracellular stores (Forster et al., 1998; Shalekoff and Tiemessen, 2001). Cold (4 ) storage stabilizes human CD34þ cells.


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1. Pass leukapheresis product through 30 mm nylon mesh (Miltenyi PreSeparation Filters, #130-041-407) into a sterile 50 ml conical tube to remove cell clumps. Dilute cells by adding 20 to 30 ml of cold running buffer ( phosphate-buffered saline supplemented with 0.5% bovine serum albumin and 2 mM EDTA, stored at 4 ). 2. Perform a viable cell count on a hemacytometer. 3. Pellet cells at 300g for 5 min at 4 . 4. To prepare the cells for magnetic selection, decant supernatant and resuspend the cell pellet in a final volume of 300 ml of running buffer per 108 cells. 5. Isolate CD34þ cells by positive selection using a CD34 Microbead Kit (cat. no. 130-046-702, Miltenyi Biotec, Auburn, CA) and autoMACS Separator (Miltenyi Biotec) according to the manufacturer’s instructions. Set aside an aliquot of 106 cells immediately before application to the autoMACS separator to use a pre-sort control for flow cytometry. Run sample through the autoMACS separator using the ‘‘posseld’’ (doublepositive selection) program and collect both the positive (enriched CD34þ cells) and negative (CD34– cells) fractions. 6. Perform a viable cell count on both the positive and negative fractions using a hemacytometer. After CD34 positive selection of 6 ml of leukapheresis material, we typically obtain 5 106 and 2 106 CD34þ cells from G-CSF (10 mg/kg/day 5 days) and plerixafor (240 mg/kg subcutaneous) mobilized donors, respectively. 7. Label tubes and aliquot cells for flow cytometry as described in Table 3.2. Approximately 10 105 CD34– cells (negative sort) are used per tube to setup the instrument (compensation controls). In contrast, because of the limited number of CD34þ cells obtained, we usually only aliquot 0.5 to 1 105 CD34þ cells (positive sort) per tube for the gating controls (fluorescence minus one controls) and experimental sample. All samples are placed in a final volume of 100 ml of running buffer for flow cytometry analysis. Negative gating controls are analyzed to establish the level of background fluorescence resulting from autofluorescence and nonspecific antibody binding. Furthermore, fluorescence minus one gating controls are preferred over isotype controls because isotype controls are not always matched to the concentration of the test monoclonal antibody (mAb). Extracellular staining of cells is performed as described in Table 3.2 by the addition of the following antihuman monoclonal antibodies (all obtained from BD Biosciences): CD4-FITC (clone RPA-T4, cat. no 555346), CD4-PE (clone RPA-T4, cat. no. 555347), CD4-APC (clone RPA-T4, cat. no. 555349), CD45RA-FITC (clone HI100, cat. no. 555488), CXCR4-PE (clone 1D9, cat. no. 551510), and CD34-APC (clone 581, cat. no. 555824). The amount of antibody added to each sample

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Table 3.2 Staining setup for evaluation of CXCR4 on CD34þ cell subsets Tube no.

Sample

No. cells (105)

Compensation controls 1 CD34– 10 2 CD34– 10 3 CD34– 10 4 CD34– 10 Gating controls 5 CD34þ 0.5 6 CD34þ 0.5 7 CD34þ 0.5 Experimental samples 8 pre 10 9 CD34– 0.5 10 CD34þ 10

FITC

PE

Viability

APC

— CD4 — —

— — CD4 —

7-AAD 7-AAD 7-AAD 7-AAD

— — — CD4

— CD45RA CD45RA

CXCR4 — CXCR4

7-AAD 7-AAD 7-AAD

CD34 CD34 —

CD45RA CD45RA CD45RA

CXCR4 CXCR4 CXCR4

7-AAD 7-AAD 7-AAD

CD34 CD34 CD34

7-AAD, 7-amino-actinomycin D; APC, allophycocyanin; FITC, fluorescein isothiocyanate; PE, phycoerythrin.

is adjusted according to the number of cells used per the manufacturer’s instructions. Since CD34þ cells are immunoselected using the antihuman CD34 clone QBEND/10, post-sort analyses of CD34 expression must be performed using a separate mAb clone. The APC-conjugated anti-CD34 clone 581 provides a very bright signal that can be easily distinguished from the negative gating control. Additionally, the mAb most commonly used to study cell surface CXCR4 expression, clone 12G5, does not bind in the presence of plerixafor (Khan et al., 2007). Clone 12G5 binds to an epitope on the second extracellular loop of CXCR4 that overlaps the plerixafor binding site on the extracellular loop 2 and the adjacent transmembrane segment TM4. Therefore, we use a separate clone, 1D9, which is not inhibited by plerixafor. The epitope recognized by antibody 1D9 is contained within the N-terminus of CXCR4 (Forster et al., 1998). 1. Incubate samples for 30 min at 4 in the dark. 2. Remove unreacted antibodies by washing the cells twice in 3 ml of running buffer. After the final wash, decant the supernatant and resuspend the cells in 300 ml of running buffer. Keep samples on ice until analysis. 3. We assess cell viability concomitantly with flow cytometry evaluation of stained cells by the addition of 7-amino-actinomycin D (cat. no. 559925, BD Biosciences). 4. Analyze the samples on a flow cytometer equipped for excitation wavelengths of 488 and 633 nm.


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7. Functional Characterization of Mobilized HSPCs 7.1. In vitro assays of differentiation In vitro assays of differentiation have been developed to quantify murine and human HSPC content (Sutherland et al., 1989). In short-term colonyforming cell (CFC) assays, test samples are cultured in a semisolid matrix supplemented with nutrients and cytokines for 2 weeks at 37 . During this culture period, CFCs proliferate and produce discrete cell clusters or colonies of morphologically recognizable daughter cells that can be quantified by light microscopy. Based on the selection of the appropriate media and culture conditions, CFC assays can be used to quantify myeloid multipotential progenitors (CFU-GEMM and CFU-GM) and lineage-restricted progenitors of the erythrocyte (CFU-E and BFU-E), granulocyte (CFU-G), monocyte-macrophage (CFU-M), megakayocyte (CFU-Mk), and B-cell (CFU–pre-B) lineages. The standardized short-term colony assays discussed above easily quantify lineage-committed progenitors, but are not adequate for the detection of more primitive HSPCs. Two assays, the cobblestone-area–forming-cell (CAFC) assay (de Haan et al., 2002) and the long-term culture-initiating cell (LTC-IC) assay (Lemieux et al., 1995; Sutherland et al., 1991), have been developed to measure more primitive stem cell frequencies. Both the CAFC and LTC-IC assays rely on adherent stromal cells for hematopoietic support and are quantified in vitro based on their capacity to generate myeloid cells for at least 5 weeks of culture. Additionally, the LTC-IC assay can be used in a quantitative manner by limiting dilution analysis to provide an estimate of the primitive cell pool within a product (Coulombel, 2004). The reader is referred to previous chapters in this series (Broxmeyer et al., 2006) and elsewhere (Miller et al., 2008; van Os et al., 2008) for detailed descriptions of the CFC, CAFC, and LTC-IC procedures (see also www.stemcell.com/technical/manuals.asp).

7.2. Transmigration assays Trafficking of HSPCs to the BM following transplantation is believed to be a critical step for hematopoietic reconstitution. Studies by Voermans et al. (2001) showed that enhanced in vitro migration of human CD34þ cells to CXCL12 was associated with improved in vivo hematopoietic recovery. Since CXCL12-induced migration is not dependent on CXCR4 expression levels alone (Voermans et al., 2001), and treatment with plerixafor, G-CSF or other mobilizing agents that target the CXCL12/CXCR4 interaction alter CXCL12 signaling, others and we often test the ability of

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mobilized HSPCs to migrate to CXCL12 using transwell migration assays. We perform these assays according to the protocol described elsewhere by Fukuda and Pelus (2008).

7.3. Transplantation assays for mouse and human HSPCs Long-term repopulating stem cells are defined by their ability to self-renew and to differentiate into mature cells of all hematopoietic lineages. The definitive assay for stem cell activity in a test sample is the complete and sustained (>6 months) reconstitution of all hematopoietic lineages in irradiated recipients by transplanted HSPCs (Herbert et al., 2008; Purton and Scadden, 2007). The most common type of transplantation assay used to measure murine primitive stem cell activity is the competitive repopulation assay (Harrison, 1980). This assay measures the functional potential of an unknown ‘‘test’’ source of HSPCs (e.g., mobilized grafts) against a set known number of whole BM cells. The competing cells ensure the survival of lethally irradiated recipients transplanted with a low number of test HSPCs and allow quantification of the reconstitution activity. For donor versus host identification in transplantation assays, investigators commonly use C57BL/6 (B6) mice congenic for the CD45 (Ly5, common leukocyte antigen) locus to discriminate among the three potential sources of stem cells (test cells, competitor BM cells, and the host). We routinely use C57BL/6 (CD45.2þ) as recipients, congenic C57BL/6 (CD45.1þ) mice for mobilization, and hybrid C57BL/6 (CD45.1þCD45.2þ) mice as BM donors. The number of repopulating units (RU) in the test sample is then determined by measuring the contribution of the test sample to donor chimerism at various time points after transplantation (Harrison et al., 1993; Purton and Scadden, 2007; Yuan et al., 2005). The value of the repopulating unit is indicative of the amount of repopulating activity within the test sample. Although determination of the repopulating unit provides important information about the overall function of a test sample, it does not provide information on the quantity of primitive stem cells within the graft. The frequency of stem cells in an unknown test sample can be determined by performing limiting dilution competitive repopulation assays. In these studies, a series of dilutions of the test source are again competed against a set number of competing BM cells. The number of mice negative for reconstitution in each test cell dose is determined, and the frequency of HSPCs (competitive repopulating units, CRU) is estimated using Poisson statistics (Purton and Scadden, 2007; Szilvassy et al., 1989, 1990; Taswell, 1981). The most definitive test of long-term hematopoietic stem cells potential is the serial transplantation assay (Purton and Scadden, 2007). In this assay, the test sample is transplanted into sequential serial transplant recipients, and


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the ability of the transplanted population to sustain hematopoiesis is determined. Since the limiting dilution competitive repopulation assay can be used to incorporate all three types of the long-term repopulating stem cell assays discussed above (RU, CRU, and serial transplantation), we will describe the assay in greater detail in the following. 7.3.1. Limiting dilution competitive repopulation assay Wildtype C57BL/6J (CD45.2þ) and a congenic strain of C567BL/6 that have the CD45.1 gene (B6.SJL-PtPrc*Pep3BoyJ) are obtained from The Jackson Laboratory (Bar Harbor, ME). Hybrid C57BL/6J B6.SJLPtPrc*Pep3BoyJ F1 (CD45.1þ/CD45.2þ heterozygous) are bred at our animal facility. The Ly5/CD45 antigen is expressed on all hematopoietic cells except erythrocytes, and polymorphism between CD45.1 and CD45.2 provides a quick and convenient method for detecting donor cells within leukocytes of recipients using flow cytometric techniques. All mice are 8 to 10 weeks old and sex-matched. Wildtype C57BL/6J (CD45.2þ) recipients are exposed to a lethal dose of total body irradiation from 12 to 24 h before transplantation. Since irradiation toxicity levels can be variable between institutions, it is preferable that all investigators assess the level of radiation that their mice can tolerate without any morbidity and mortality. Typical irradiation doses range for C57BL/6 mice range from 1000 cGy to 1100 cGy TBI. At least 16 to 20 mice are irradiated per experiment. Low-density mononuclear cells (LDMNCs) are isolated from mobilized B6.SJL-PtPrc*Pep3BoyJ (CD45.1þ) mice using murine lympholyte (Cedarlane Laboratories, Burlington, Ontario, Canada). Approximately 2 107 total LDMNCs are needed to inject at least four mice at a minimum of three different cell doses. For plerixafor, we typically treat 20 to 25 CD45.1þ B6 donor mice with 5 mg/kg subcutaneous plerixafor and harvest peripheral blood 3 h later. For GCSF, we treat 10 to 15 CD45.1þ B6 donor mice with G-CSF (250 mg/kg/day) for 5 days and harvest peripheral blood 4 h after the last injection of G-CSF. Isolate BM cells aseptically from C57BL/6J B6.SJL-PtPrc*Pep3BoyJ F1 (CD45.1þ/CD45.2þ) mice. We sacrifice 1 CD45.1þ/CD45.2þ B6 BM donor mouse for every 15 to 20 lethally irradiated CD45.2þ B6 mice undergoing transplantation. LDMNCs from mobilized CD45.1þ B6 mice are mixed with unfractionated CD45.1þ/CD45.2þ B6 competitor BM cells. At least four mice at a minimum of three different cell doses should be evaluated to allow statistical comparison of test (CD45.1þ) cell engraftment between treatment groups at limiting dilution (Purton and Scadden, 2007). Most investigators inject between 2 to 5 105 competing BM cells per mouse. However, the number of LDMNCs injected per mouse is variable between institutions

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and each mobilizing agent. For plerixafor and G-CSF mobilized grafts, we and others (Broxmeyer et al., 2005) have set the ratio of donor (CD45.1þ) blood cells to competitor (CD45.1þ/CD45.2þ) BM cells as the number or LDMNCs in three, two, or one donor mice to a constant number of 5 105 competitor BM cells (CD45.1þ/CD45.2þ). For example, at a 3:1 ratio, we mix the number of LDMNCs obtained from the peripheral blood of three donor mice (CD45.1þ) with 5 105 competitor BM cells (CD45.1þ/CD45.2þ). Others mix 5 105 competitor BM cells with 2 106, 1.5 106, or 1 106 LDMNCs to yield LDMNC to BM ratios of 4:1, 3:1, or 2:1, respectively (Fukuda et al., 2007). Pilot experiments are recommended to obtain the range of LDMNCs required to achieve durable test sample engraftment. Four B6 (CD45.2þ) mice that received 1000 cGy TBI and 5 105 competitor BM cells (CD45.1þ/CD45.2þ) without donor test cells were used as controls. Hematopoietic repopulation is evaluated monthly for at least 6 months to demonstrate long-term multilineage reconstitution in the CD45.1þ and CD45.1þ/CD45.2þ donor cell subsets. Multilineage analysis is performed on the blood by flow cytometry using antimouse monoclonal antibodies against CD45.1, CD45.2, and the lineage markers B220 (B lymphoid), CD3 (T lymphoid), Mac1 (monocyte/macrophage), and Gr1 (granulocyte). At least 20,000 events are acquired on a flow cytometer. Since myeloid progenitors and their progeny have short half-lives compared to lymphoid progeny, it is important to demonstrate myeloid reconstitution in the test-cell subset following transplantation. Furthermore, Bryder et al. (2004) demonstrated that the RB6-8C5 mAb detecting Gr-1 also binds to a subpopulation of CD3þCD8þ T cells present in the peripheral blood. Therefore, granulocyte reconstitution should be defined as Gr-1þ cells negative for expression of T-cell markers like CD3. The percentage of chimerism is calculated based on flow cytometry data as follows: % chimerism ¼ (% test donor cells) 100 / (% test donor cells þ % competitor cells). Most investigators consider that primitive stem cells are present in the test donor cells when the percent chimerism is greater than 1% for all myeloid (granulocytes and macrophages), B-lymphoid, and T-lymphoid lineages at 6 months after transplantation. The number of repopulating units (RU) in test donor cells is calculated according to the method of Harrison et al. (1993) as follows: % chimerism ¼ (% chimerism) (no. of competitor cells/105) /(100 – % chimerism). One RU is defined as the amount of repopulating activity in 105 BM cells from wildtype mice (Ema et al., 2006; Purton and Scadden, 2007). In limiting dilution assays, the frequency of competitive repopulating units (CRU) among test donor cells is estimated on the basis of Poisson statistics; the ranges of CRUs are given as 95% confidence intervals. StemCell Technologies has developed a program, L-Calc, to aid in the data analysis of limiting dilution assays. This software is free to download from


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the company website. Of note, CRU and RU are different (Ema et al., 2006; Purton and Scadden, 2007). CRU measures the quantity of HSPCs, whereas RU measures the functional quality of HSPCs. Furthermore, since short-term repopulating cells can reconstitute multiple lineages for at least 16 weeks, most researchers determine RU and CRU values from data collected at least 6 months post-transplantation. It should be noted, that noncompetitive primary transplantation assays can be performed to mimic how transplants are performed clinically. In a noncompetitive transplant, test cells (typically 1 to 2 106) are injected into lethally irradiated congenic recipients in the absence of competing BM cells. Although the primary endpoint in noncompetitive transplants is the time to recovery of peripheral blood neutrophils, platelets, and hemoglobin, donor chimerism can also be determined as described. 7.3.2. Secondary transplantation Wildtype C57BL/6J (CD45.2þ) recipients are exposed to a single dose of lethal (1000 cGy) total body irradiation from a 37Cesium source at a rate of 95 cGy/minute 12 to 24 h before transplantation. Primary recipient mice are sacrificed at 6 months post-transplant and the contents of their femurs are pooled within the respective treatment groups. Pooled BM cells (1 106) are injected via the tail vein using a 27-gauge needle in 0.2 ml of PBS within 12 h after irradiation of C57BL/6J (CD45.2þ) recipients. If possible, at least 10 secondary recipients should be injected with BM cells harvested from the primary recipients. The proportions of CD45.2 donor and CD45.1 competitor cell engraftment in the secondary recipients were measured at 2, 6, 14, and 27 weeks using the same methods. Tertiary transplantations were carried out in the same manner. 7.3.3. Immune-deficient mouse models to study human stem cell–repopulation capacity Several xenotransplantation models have been developed as surrogate assays of human HSPC activity, with the majority relying on the use of different strains of immunodeficient mice with various degrees of residual innate immunity. Nonobese diabetic (NOD) mice crossed with severe combined immunodeficient (SCID) mice represent the most accepted and widely used immune-deficient animal for quantitative comparison of human HSPC activity (Cashman et al., 1997; Larochelle et al., 1996; Pflumio et al., 1996). NOD/SCID mice stringently engraft only primitive human hematopoietic stem cells (scid-reconstituting cells [SRC]) that repopulate the BM with predominantly CD34þCD19þ pro-B cells exhibiting a poor capacity to terminally differentiate, and to a lesser degree, myeloid cells. In contrast to the SRC, more committed human progenitor populations are able to engraft NOD/SCID mice back-crossed with the b2-microglobulin–null

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(b2mnull) allele (Kollet et al., 2000, 2001). These NOD/SCIDbmnull mice exhibit a more absolute immunodeficiency than NOD/SCID mice and have virtually no NK cell function. In fact, compared to NOD/SCID controls, NOD/SCIDb2mnull mice support a greater than 10-fold higher level of SRC frequency upon transplantation of small numbers (8 104 cells) of human cord–blood mononuclear cells and become reconstituted with lymphoid CD45þCD19þ cells (no T cells) and myeloid CD45þCD33þ cells. This enhanced SRC frequency in NOD/SCIDbmnull mice is caused by the increased engraftment of human myeloid and lymphoid short term repopulating hematopoietic cells (Eaves et al., 2001; Glimm et al., 2001). Two major limitations of the NOD/SCIDbmnull xenograft model are their poor reproduction rate and short life span (approximately 6 months due to accelerated thymic lymphomagenesis). One alternative to using NOD/SCIDbmnull mice for measuring human HSPC activity is to treat NOD/SCID mice with a monoclonal antibody (mAb) against the interleukin-2 receptor bchain (IL-2Rb, CD122). The anti-CD122 mAb eradicates CD122-expressing cell populations, including NK cells and macrophages that mediate a negative effect on human engraftment. Compared to NOD/ SCIDb2mnull mice, anti-CD122 treated NOD/SCID mice exhibit a nearly threefold greater human cell engraftment upon transplantation of human cord–blood mononuclear cells (McKenzie et al., 2005). A second alternative to using NOD/SCIDb2mnull mice in SRC assays is to use NOD/SCID mice harboring a complete null mutation of the interleukin 2 receptor common g chain (NOD/SCID/gcnull) (Ito et al., 2002; Shultz et al., 2005). Similar to NOD/SCID-b2mnull mice, NOD/SCID/gcnull mice have reduced activities and numbers of NK cells. However, unlike NOD/SCID-b2mnull mice, NOD/SCID/gcnull mice can survive long term (15 months) because they do not develop thymic lymphomas, have a reproduction rate similar to normal wildtype mice, and exhibit multilineage engraftment of mature and functional CD3þCD4þ and CDþCD8þ T cells, Igþ B cells, NK cells, monocytes/macrophages, and plasmacytoid dendritic cells following transplantation of human CD34þ HSCs. Furthermore, since NOD/SCID/gcnull mice require no anti-CD122/IL-2Rb monoclonal antibody treatment for human cell engraftment, they provide a significant cost advantage over NOD/SCID mice. NOD/LtSz-Prkdcscid/Prkdcscid (NOD/SCID), NOD/LtSz-Prkdcscid/ Prkdcscidbmnull (NOD/SCID-b2mnull), and NOD.Cg-Prkdcscid Il2rgtm1Wjl/ SzJ (NOD/SCID/gcnull) mice are obtained from Jackson Laboratories (Bar Harbor, ME), and bred at our animal facility. NOD/SCID mice are known to be ‘‘leaky,’’ and sometimes develop mouse CD3þ T cells that can impede human cell engraftment. Therefore, we screen the peripheral blood of all NOD/SCID mice by flow cytometry with antimouse monoclonal antibodies (CD45, CD3, and DX5) and eliminate any mice exhibiting more than 1% CD3þ T cells.


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All immunodeficient mice are housed in a specific pathogen-free facility in sterile microisolator cages, and given autoclaved food and water ad libitum. All manipulations are performed aseptically on a laminar flow bench. We condition 8- to 10-week-old NOD/SCID, NOD/SCIDb2mnull, and NOD/SCID/gcnull mice with 300 cGy, 300 cGy, and 250 cGy of single-dose total body g irradiation (TBI), respectively, using a Shepard Mark IV Cesium137 irradiator. However, since irradiation toxicity levels can be variable between institutions, it is preferable that each investigator assesses the level of radiation that their mice can tolerate without any morbidity and mortality. Typical irradiation doses range from 250 cGy to 300 cGy TBI. NOD/SCID mice treated with anti-CD122 antibody are given injections of 200 mg purified antibody into the intraperitoneal cavity immediately after irradiation. The anti-CD122 monoclonal antibody generated from the hybridoma cell line TM-b1 can be purchased from Bio Express Inc. (West Lebanon, NH). Human mobilized peripheral blood mononuclear cells and purified CD34þ cells are injected via the tail vein using a 27-gauge needle in 0.2 ml of PBS within 12 h after irradiation. A range of human MNC (106 to 40 106 cells) or purified CD34þ cells (2 104 to 1 106 cells) are injected into quadruplicate mice at a minimum of three different doses per donor to allow direct statistical comparison of human cell engraftment between treatment groups at limiting dilution. Control mice are irradiated but do not receive human cells. Ten to 12 weeks after transplantation, BM (femurs and tibias), spleen, and peripheral blood are recovered, single cell suspensions prepared, and numbers of total nucleated cells are determined using a hemacytometer. The appropriate dilution of antibodies, as titered against human or mouse peripheral blood mononuclear cells, are incubated with 1 to 5 105 cells for 30 min at 4 and then washed two times in phosphate-buffered saline (PBS) plus 0.5% bovine serum albumin. At least 10,000 events are acquired on a flow cytometer. Antimouse CD45 and antihuman CD45 mAb are used to determine the number of mouse and human hematopoietic cells, respectively. Engrafted mouse BM is further analyzed for the frequency of human B-lymphoid cells (CD20-FITC, CD19-PE), myeloid cells (CD14FITC, CD33-PE), T-lymphoid cells (CD4-FITC, CD8-PE), and primitive HSPCs (CD34-FITC, CD38-PE). All antibodies are purchased from Becton Dickinson (San Diego, CA). To accurately set up the cytometer, we mix equal numbers of BM cells from a control, untransplanted immunodeficient mouse with human PBMCs. These control samples are then stained individually with antihuman CD45 and antimurine CD45 or simultaneously with the antihuman CD45/antimurine CD45-lineage cocktails described.

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The proportion of human cells in each mouse is calculated as follows: % huCD45þ ¼ [no. huCD45þ/(no. huCD45þ þ no. muCD45þ)]. Mice are considered engrafted when at least 1% of human CD45þ cells are detected in the mouse BM. Short-term human reconstitution potential is measured by sacrificing and analyzing mice 6 weeks after transplantation. Levels of human engraftment are reported as the mean SD for mice grouped according to transplanted cell numbers and compared using a Student’s t-test. SCID repopulating cell (SRC) analysis is performed using the single-hit model and Poisson statistics at limiting dilution with 95% confidence intervals. Typically, data from three limiting dilution experiments are pooled and analyzed using L-Calc software (Stem Cell Technologies; free software download).

8. Concluding Remarks Disruption of CXCL12/CXCR4 signaling is a critical step in HSPC mobilization by G-CSF, plerixafor, and additional agents in development. We (Devine et al., 2008; Hess et al., 2007; Rettig et al., 2008) and others (Fruehauf et al., 2006; Jin et al., 2008; Pelus and Fukuda, 2008) have found intrinsic differences between HSPCs mobilized with plerixafor and G-CSF, including differences in cell surface markers, cell cycle, gene expression profiles, and NOD/SCID repopulating capacity. The optimum strategy for obtaining mobilized peripheral blood from donors is the subject of ongoing study.

ACKNOWLEDGMENT This work was supported by Genzyme Corporation.

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Double-Label Nonradioactive In Situ Hybridization for the Analysis of Chemokine Receptor Expression in the Central Nervous System Meizhang Li and Richard M. Ransohoff Contents 92 93 93 94 94 95 95 96 97 98 98 99 101 102

1. Introduction 2. Basic Protocol for ISH (Using Digoxygenin-Labeled Probe) 2.1. Equipment and reagent 2.2. Tissue preparation 2.3. Total RNA purification 2.4. First-strand cDNA synthesis 2.5. cDNA clones of chemokine receptors 2.6. Generation of ISH probe by in vitro transcription 2.7. Hybridization 2.8. Posthybridization washing 2.9. Development of ISH signals 2.10. Controls 3. Comments References

Abstract Chemokines are a family of mainly-secreted proteins, traditionally associated with regulation of leukocyte trafficking during host defense and pathological immune/inflammatory reactions. All chemokines signal to G protein-coupled receptors. Recent studies show that chemokines and their receptors are also expressed by neuroepithelial cells, and govern developmental, physiological and pathological processes through actions towards these cells, as well as infiltrating and resident hematopoietic cells. Understanding chemokine action at the tissue level therefore requires defining which cells express chemokine receptors. At a first level of approximation (and lacking appropriate

Neuroinflammation Research Center, Department of Neurosciences, Lerner Research Institute, Cleveland Clinic, Cleveland, Ohio, USA Methods in Enzymology, Volume 460 ISSN 0076-6879, DOI: 10.1016/S0076-6879(09)05204-5

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immunohistochemical reagents) this determination can be made by in situ hybridization (ISH), which localizes mRNA expression for chemokines and their receptors at the cellular level. Here we provide a protocol for ISH and demonstrate its application for localizing mRNA encoding two chemokine receptors, CXCR4 and CXCR7 in murine CNS tissues.

1. Introduction In the central nervous system (CNS), chemokines and chemokine receptors are constitutively or inducibly expressed in neurons (Belmadani et al., 2005; Hermann et al., 2008; Khan et al., 2008; Lu et al., 2002), astrocytes (Carter et al., 2007; van Heteren et al., 2008; Zheng et al., 2008), microglia (Biber et al., 2002; Cardona et al., 2006; Huang et al., 2005), and oligodendrocyte lineage cells (Dziembowska et al., 2005; Kadi et al., 2006; PadovaniClaudio et al., 2006). In this regard, chemokines represent an inherent system that helps establish and maintain CNS homeostasis (Li and Ransohoff, 2008). The healthy CNS is an immune activity–free site, which peripheral leukocytes do not enter freely due to the unique structure of the blood–brain barrier (BBB) (Ransohoff et al., 2003). Furthermore, dendritic cells (DCs) as the key antigen-presenting cells in both adaptive immunity and autoimmunity, are absent from the healthy CNS (Pashenkov and Teleshova, 2003). Thus, aberrant invasion of peripheral leukocytes into the CNS is a cardinal feature of neuroinflammation-mediated human brain disorders. Multiple sclerosis (MS) is a neuroinflammation-mediated demyelinating disease. Previous studies demonstrated expression of chemokines and chemokine receptors in CNS lesions in MS tissue sections (Srensen et al., 2002; Trebst et al., 2003; Mahad et al., 2004; Kivisa¨kk, et al., 2004). In a mouse model of inflammation-mediated demyelination, experimental autoimmune encephalomyelitis (EAE), expression of chemokines was reproducibly and specifically increased (Ransohoff et al., 1997). Detailed analyses further supported the hypothesis that chemokines regulated the recruitment of peripheral leukocytes into the CNS (Huang et al., 2000; Lu et al., 2002; Mahad et al., 2003) during neuroinflammation. In addition, chemokines potentially mediate local cellular pathogenesis in the lesion sites of EAE (Carlson et al., 2008; Sunnemark et al., 2005). Unfortunately, very few chemokine receptor antibodies are suitable for application in immunohistochemical evaluation of murine CNS tissues. Falsepositive results are more the rule than the exception. To further explore the roles of chemokine receptors in mouse models of CNS diseases, we applied double-label nonradioactive in situ hybridization (double ISH) to evaluate the expression of chemokine receptors in various cell types (Fig. 4.1). ISH also provides a useful method to establish the cellular sources of chemokine receptor expression (Ransohoff et al., 1997).

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Double-Label Nonradioactive In Situ Hybridization

A

B

C

D

E

F

F F⬘

Figure 4.1 Detection of CXCR4 and CXCR7 mRNA expression in healthy ventral spinal cord by double-fluorescent ISH. Double-fluorescent ISH was performed with digoxygenin-labeled antisense CXCR4 probe (red, developed with Texas red) and CXCR7 (green, developed with tyramide-fluorescein). Colocalization of CXCR4 and CXCR7 in a neuron was indicated by arrows. (A) CXCR7; (B) CXCR4; (C) DAPI; (D) CXCR7 and CXCR4; (E) CXCR7, CXCR4, and DAPI. An area was shown by both low power (F) and high power (F0 ). Scale bars: 0.4 cm ¼ 25 mm.

2. Basic Protocol for ISH (Using DigoxygeninLabeled Probe) 2.1. Equipment and reagent 1. 2. 3. 4.

Moist chamber Hybridization oven TRIzol Reagent (Invitrogen, Carlsbad, CA) Hybri-Well Press-Seal hybridization chamber (Sigma, St.Louis, MO)

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5. SuperScript III First-strand synthesis system for reverse transcription polymerase chain reaction (Invitrogen, Carlsbad, CA) 6. TOPO TA cloning kit (Invitrogen, Carlsbad, CA) 7. TSA Fluorescein system (PerkinElmer, Massachusetts, MA) 8. DIG RNA labeling mix (Roche, Indianapolis, IN) 9. Biotin RNA labeling mix (Roche, Indianapolis, IN) 10. Fluorescein RNA labeling mix (Roche, Indianapolis, IN) 11. Superfrost Plus microscope slides (Fisher, Pittsburgh, PA) Solutions are prepared with autoclaved 1% (v/v) diethyl pyrocarbonate water (DEPC-water). All glassware is washed in DEPC water and baked at 125 to 150 overnight.

2.2. Tissue preparation 1. All tissue preparation is done with gloves to avoid RNase contamination. To purify high-quality total RNA, fresh tissues are needed. 2. Paraffin-embedded tissues: Tissues are dissected from experimental animals and fixed in 10% (w/v) formalin (Fisher, Pittsburgh, PA) for at least 5 days at room temperature (RT). Paraffin-embedded tissues are prepared by a histology service (housed either in a clinical pathology department or research department core facility). Sections are collected on Superfrost Plus microscope slides at a thickness between 5 to 30 mm. One slide from each block is stained with hematoxylin and eosin (H&E) for histology correlation. Slides can be kept in histology box at RT for quite a long time. Sections need to be deparaffinization before hybridization. Briefly, slides are baked at 65 for 15 min until the paraffin is melted and immediately immersed in staining trays through two changes of fresh xylene (10 min for each) with gentle mixing. For rehydration, slides are passed twice through 100, 95, and 75% ethanol, respectively, and rinsed once in 1 PBS. 3. Paraformaldehyde (PFA) fixed tissues: Animals are sacrificed and perfused with 4% (w/v) PFA. Brains and spinal cords are removed from animals and fixed in 4% PFA at 4 overnight, following treatment with 15 to 30% (w/v) sucrose for 1 to 3 days at 4 . Tissues are embedded in Tissue-Tek O.C.T. Compound (Sakura). Next, 15 to 30 mm tissue sections are collected on the Superfrost Plus microscope slides by cryosectioning. Slides are dried at RT and baked at 50 for 30 min before hybridization. 4. Frozen tissues: Fresh tissues are directly frozen on dry ice and sectioned by cryosectioning.

2.3. Total RNA purification Homogenize 50 mg of tissue in 1 ml of TRIzol Reagent by using a 1-ml tip and leave at RT for 5 to 10 min. Add 0.2 ml of chloroform and vortex. Centrifuge the sample at 12,000 rpm for 15 min. Transfer the supernatant


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carefully in a clean 1.5 ml-Eppendorf tube. Precipitate the total RNA by adding 0.5 ml of isopropanol and centrifuge the sample at 12,000 rpm for 15 min. Wash the total RNA pellet once with 75% ethanol. Spin the sample at 12,000 rpm for 15 min and completely remove the residual ethanol. Use 100 ml RNase-free water to dissolve the total RNA. Remove 2 ml sample for OD260/280 measurement. The OD260/280 for purity RNA should be between 1.99 and 2.1. Alternatively, check the total RNA quality on a 1.2% (w/v) agarose gel, using ethidium bromide staining and UV light to visualize ribosomal RNA bands.

2.4. First-strand cDNA synthesis Use SuperScript III first-strand synthesis system (Invitrogen) and follow the protocol provided by the manufacturer to synthesize the first-strand cDNA. Briefly, prepare 10 ml of mix (including 1 ml 50 mM oligo (dT)20, 1 ml 10 mM dNTP, and 1 mg total RNA in 8 ml RNase-free water). Incubate 10 ml mix at 65 for 5 min and place on ice for at least 1 min. Prepare another 10 ml of reaction buffer according the following recipe: 10 RT buffer, 2 ml 25 mM MgCl2, 4 ml 0.1 M DTT, 2 ml RNase inhibitor (40 U/ml), 1 ml SuperScript III RT (200 U/ml), 1 ml Add this reaction buffer to the 10-ml mix and incubate at 50 for 50 min. Stop the reaction at 85 for 5 min and chill on ice. Finally, add 1 ml of RNaseH and incubate the reaction at 37 for 20 min.

2.5. cDNA clones of chemokine receptors 1. Design specific PCR primers for chemokines or chemokine receptors. 2. Use 0.5 ml first-strand DNA as PCR template to amplify the expression fragments of chemokines or chemokine receptors in a 25-ml PCR reaction described in the following:

Water, 18.85 ml 10 PCR buffer, 2.5 ml 10 nM dNTP, 0.4 ml 20 nM forward primer, 0.50 ml 20 nM reverse primer, 0.50 ml 50 mM MgCl2, 0.75 ml DNA polymerase (1 U/ml), 0.5 ml

Run the PCR reactions in a thermal cycler by denaturing at 95 for 1 min; anneal at 58 , 1 min; and extend at 72 , 1.5 min, for a total 30 cycles.

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3. After PCR, remove 5 ml PCR product to run a 1.2% agarose gel and check the PCR amplification. 4. Set up a TOPO cloning reaction by following the standard protocol provided by the manufacturer. Briefly, prepare 6 ml of reaction mix (1.0 ml fresh PCR product, 3 ml salt solution, 3 ml water, 1 ml TOPO vector), and incubate the reaction at RT for 5 min. 5. Mix 2 ml TOPO cloning reaction with competent Escherichia coli cells and mix gently. 6. Incubate the competent cells on ice for 30 min and heat-shock for 30 s at 42 . 7. Add 250 ml S.O.C. medium (recipe for 1000 ml of S.O.C. medium is described in the following) and shake the competent cells at 37 for 1 h. Bacto-tryptone (Becton, Dickinson and Company, USA), 20 g Bacto-yeast extract (Becton, Dickinson and Company, USA), 5 g NaCl, 0.5 g 1 M KCl, 2.5 ml Add water, 1000 ml Note: Adjust pH to 7.0 with 10 M NaOH, autoclave to sterilize, and add 20 ml of sterile 1 M glucose immediately before use. 8. Spread 10 to 100 ml cells on 100 mg/ml ampicillin agar plates, and incubate plates at 37 overnight. 9. Randomly pick 10 colonies to culture the bacteria and prepare plasmid DNAs. Verify the cDNA plasmid clones by restriction enzyme (RE) analysis or sequencing.

2.6. Generation of ISH probe by in vitro transcription 1. Digest 10 mg plasmid DNA with an appropriate RE at 37 for 1 h. Check the plasmid DNA digestion in 1.2% agarose gel. Note: Set up two digestion reactions in 1.5-ml Eppendorf tubes. One is for antisense labeling and another for sense-control labeling. 2. Precipitate linearized DNA by adding one-ninth volume of 3 M NaOAc, pH 4.8, and two volumes of 100% ethanol. 3. Spin down at 4 for 15 min. Wash the pellet once with 70% ethanol. 4. Resuspend the pellet in 50 ml RNase-free water. 5. Prepare a 50 ml IVT reaction described as follows: 10 reaction buffer, 5 ml 0.1 M DTT, 5 ml Digoxygenin-UTP mix, 2.5 ml RNAsin, 10 units RNA polymerase (T3, T7, or Sp6), 90units Linearized plasmid DNAs, 1 to 2.5 mg RNase-free water, up to 50 ml

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Incubate the IVT reaction at 37 for 1 to 2 h. After that, remove 5 ml IVT reaction to check the labeling in a 1.2% agarose gel. Note: Fluorescein-12-UTP or Biotin-16-UTP mix can be used for double labeling. 6. Stop the IVT reaction by adding 50 ml of stop buffer. 7. Precipitate probe rRNA with one-ninth volume of 3 M NaOAc, pH 4.8, and two volumes of 100% ethanol at –80 for at least 30 min. 8. Centrifuge at 12,000 rpm at 4 for 15 min and discard the supernatant. 9. Wash the pellet with 80% ethanol, centrifuge at 4 for 10 min, and discard the supernatant. 10. Dry the pellet at RT for 5 min and suspend the pellet in 50 to 100 ml of RNase-free water.

2.7. Hybridization 1. Fix the slides in 4% PFA at RT for 30 min. 2. Wash the slides twice (5 min each time) with DEPC-1 PBS at RT. 3. Treat the slides with 50 mg/ml proteinase K (Sigma) in PK buffer (see following recipe for 50 ml) at RT for 10 to 15 min. Stock solution

Volume added

1 M Tris-HCl, pH 7.5 2.5 ml 0.5 M EDTA 0.5 ml DEPC water 47 ml 4. 5. 6. 7.

Final concentration

50 mM Tris-HCl, pH7.5 5 mM EDTA –

Rinse the slides once with DEPC-1 PBS at RT. Fix the slides in 4% PFA at RT for 30 min. Wash the slides twice (5 min each time) with DEPC-1 PBS at RT. Prepare 50 ml of prehybridization buffer as indicated in the following, and prehybridize the slides at 60 for 3 4 h. Stock concentration

Volume added

Final concentration

Formamide 20 SSC 50 mg/ml yeast tRNA (Sigma) 100 mg/ml heparin 100 Denhardt’s solution 10% Tween 20 (Sigma) 10% CHAPS (Sigma) 0.5 M EDTA DEPC water

25 ml 12.5 ml 0.3 ml 50 ml 0.5 ml 0.5 ml 0.5 ml 0.5 ml 10.2 ml

50% 5 SSC 0.3 mg/ml 100 mg/ml 1 Denhardt’s solution 0.1% 0.1% 5 mM –

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8. Cover the slides by hybridization chambers and add 100 ml prehybridization buffer with 1 to 2 mg/ml probe rRNA into the chambers. Slides are kept in a moist chamber and further hybridized at 60 for overnight.

2.8. Posthybridization washing Note: After hybridization, using RNase-free buffers is not necessary. 1. Discard the hybridization chambers and wash the slides in 1 SSC at 60 for 10 min. 2. Wash the slides twice in 2 SSC at 37 for 30 min each, followed by a wash with 1.5 SSC at 60 for 10 min. 3. Treat tissue sections with 0.1 mg/ml RNase A (Sigma) in 2 SSC at 37 for 30 min. 4. Wash the slides in 2 SSC at RT for 10 min. 5. Wash the slides twice in 0.2 SSC at 60 for 30 min each. 6. Wash the slides once in 0.2 SSC at RT for 15 min. 7. Wash the slides three times in PBT buffer, 0.1% (v/v) Triton X-100 (Sigma) in 1 PBS, at RT for 15 min each. 8. Block the tissue sections in 20% (v/v) heat-inactivated sheep serum in PBT buffer for 4 h at RT.

2.9. Development of ISH signals 1. Incubate the slides with goat antidigoxygenin antibody conjugated with AP (alkaline phosphatase) diluted 1:2000 in 20% heat-inactivated sheep serum in PBT buffer at 4 overnight. 2. Wash the slides three times in PBT at RT for 30 min each. 3. Wash the slides twice with alkaline phosphatase buffer (AP) (recipe for 500 ml follows) at RT for 5 min each. Stock concentration Volume added

Final concentration

1 M Tris, pH 9.5 1 M MgCl2 5 M NaCl 20% Tween-20

50 ml 25 ml 10 ml 2.5 ml

Water

412.5 ml

100 mM Tris, pH 9.5 50 mM MgCl2 100 mM NaCl 0.1% Tween-20 5 mM Levamisole –

4. Prepare 50 ml of AP buffer with 50 ml NBT (BioRad) and 175 ml BCIP (BioRad).


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Note: 80 mg/ml stock NBT (nitro blue tetrazolium chloride) is prepared in 70% (v/v) dimethyl formamide (Sigma); 60 mg/ml stock BCIP (5-bromo-4-chloro-3-indolyl phosphate, toluidine salt) is prepared in 100% dimethyl formamide. 5. Develop the ISH signals for 2 to 10 h at RT in the dark. 6. Wash the slides twice with 1 PBS at RT for 10 min each. 7. Fix the slides at RT for 15 min and mount the slides in 50% glycerol with 1 PBS.

2.10. Controls It is essential to generate control hybridizations for each ISH experiment to enable data interpretation. Such controls must address both technical and biological variability. Positive controls using housekeeping genes such as beta-actin or GAPDH are employed to verify the presence of hybridizable mRNA that is detectable by ISH. Sense probes or sections from gene knockout mice or control mice (in disease model experiments) are useful to exclude unspecific signals. Initial screening of all slides is performed by an observer blinded to genetics, treatment, or illness status of the animal from which the specimen was derived; probe identity; and probe polarity. 2.10.1. Special ISH protocols Double ISH 1. Follow the basic protocol (described above) to label two different ISH probes. For example, one is labeled with digoxygenin and another is labeled with fluorescein. 2. Prepare the hybridization buffer with both probes (1 to 2 mg/ml) and hybridize at 60 overnight. 3. Follow the basic protocol (described above) to wash the slides and block with 20% heat-inactivated sheep serum in PBT buffer at 4 overnight. 4. Incubate the slides with sheep anti–digoxygenin-AP at 4 for overnight. 5. Wash the slides three times in PBT buffer at RT for 30 min each. 6. Wash the slides twice in AP buffer at RT for 5 min each. 7. Develop the slides with NBT/BCIP until the desired signal is observed. Note: A sense control probe is helpful to confirm the right hybridization signals. For most chemokine receptors, a cell type–dependent signal pattern is desired. 8. Wash the slides three times in 1 PBS at RT for 5 min each. 9. Inactivate the AP in TE (100 mM Tris-HCl, pH 7.5, 50 mM EDTA) at 85 for 10 min. 10. Wash the slides three times in 1 PBS at RT for 5 min each. 11. Wash the slides once in PBT at RT for 10 min each.

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12. Block the slides with 20% heat-inactivated sheep serum in PBT at RT for 1 h. 13. Incubate the slides with goat anti–fluorescein-AP antibody diluted 1:3000 in 20% heat-inactivated sheep serum in PBT at 4 overnight. 14. Wash the slides three times in PBT at RT for 30 min each. 15. Wash the slides twice in AP buffer at RT for 5 min each. 16. Develop the second ISH signal with 50 ml INT (BioRad) and 175 ml BCIP at RT for 3 to 4 h. Note: 40 mg/ml INT (2-[4-iodophenyl]-3-[4-nitrophenyl]-5-phenyltetrazolium chloride) is prepared in 70% (v/v) dimethyl formamide. To obtain good double ISH signals, the weaker probe should be developed first. 17. Fix the slides at RT for 15 min and mount in 50% glycerol with 1 PBS. Fluorescent double ISH

1. Follow the double ISH protocol (described above) to hybridize the slides with two different probes that are labeled by either digoxygenin or fluorescein. 2. After hybridization, wash the slides by following the basic ISH protocol (described above). 3. Incubate the slides with sheep anti-digoxygenin-AP at 4 overnight. 4. Wash the slides three times in PBT buffer at RT for 30 min each. 5. Wash the slides three times in AP buffer (pH 7.6) at RT for 5 min each. 6. Dissolve one Fast Red tablet (Roche) in 2 ml of AP buffer (pH7.6) and filter the solution through a 0.45-mm filter (Millipore, Cork, Ireland). 7. Incubate the slides with Fast Red solution in dark for 3 to 4 h until the desired signal is obtained. Note: The single antisense ISH developed by NBT/BCIP (positive control) and sense ISH (negative control) developed by Fast Red are helpful in evaluating the specific signal. 8. Wash the slides three times in PBT buffer at RT for 30 min each. 9. Block the slides with 20% heat-inactivated sheep serum in PBT at RT for 1 h. 10. Incubate the slides with sheep anti-fluorescein-POD (peroxidase) (Roche) 1:5000 in PBT at 4 overnight. 11. Wash the slides three times in PBT buffer at RT for 30 min each. 12. Dilute tyramide-fluorescein (1:50) in the amplification buffer supplied in the TSA Fluorescein system. 13. Incubate the slides with diluted tyramide-fluorescein at RT for 10 to 15 min.


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14. Wash the slides three times in PBT buffer at RT for 5 min each. 15. Wash the slides three times in 1 PBS at RT for 5 min each. 16. Mount the slides in VECTASHIELD mount medium with or without DAPI (Vector Laboratory, Burlingame, CA). ISH and immunohistochemistry (IHC)

1. Follow the basic protocol (described above) to complete the nonfluorescent ISH first. 2. Fix the slides in 4% PFA at RT for 30 min. 3. Wash the slides three times in PBT at RT for 5 min each. 4. Incubate the slides in 3% H2O2 (hydrogen peroxide) at RT for 30 min to inactivate the AP. 5. Wash the slides three times in PBT at RT for 5 min each. 6. Block the slides with 10% heat-inactivated goat serum at RT for 30 min. 7. Incubate the primary antibody at 4 for overnight. 8. Wash the slides three times in PBT at RT for 5 min each. 9. Incubate the secondary antibody conjugated with biotin at RT for 1 h. 10. Wash the slides three times in PBT at RT for 5 min each. 11. Wash the slides three times in 1 PBS at RT for 5 min each. 12. Incubate the slides in ABC complex solution at RT for 1 h. ABC complex is made using the ABC Elite Kit (Vector Laboratory). Make the solution at least 30 min before use. 13. Wash the slides three times in 1 PBS at RT for 5 min each. 14. Incubate the slides in DAB (Sigma) solution with 0.01% H2O2 for 5 to 10 min. To make DAB (3, 30 -diaminobenzidine) solution, two DAB tablets are dissolved into 30 ml of 1 PBS supplemented with 10 ml H2O2. 15. Wash the slides three times in 1 PBS at RT for 5 min each. 16. Fix the slides for 15 min at RT and mount slides in 50% glycerol in 1 PBS.

3. Comments Given their wide-ranging biology in the CNS, chemokine receptors have been extensively investigated. The critical issue of the cellular source(s) of chemokine receptors in the CNS cannot, in most cases, be addressed by the direct IHC approach. The remaining options are ISH, use of transgenic mice with reporter genes expressed from chemokine receptor promoters, or flow cytometry using CNS tissue lysates.

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REFERENCES Belmadani, A., Tran, P. B., Ren, D., Assimacopoulos, S., Grove, E. A., and Miller, R. J. (2005). The chemokine stromal cell-derived factor-1 regulates the migration of sensory neuron progenitors. J. Neurosci. 25, 3995–4003. Biber, K., Dijkstra, I., Trebst, D., De Groot, C. J., Ransohoff, R. M., and Boddeke, H. W. (2002). Functional expression of CXCR3 in cultured mouse and human astrocytes and microglia. Neuroscience 112, 487–497. Cardona, A. E., Pioro, E. P., Sasse, M. E., Kostenko, V., Cardona, S. M., Dijkstra, I. M., Huang, D., Kidd, G., Dombrowski, S., Dutta, R., Lee, J. C., Cook, D. N., et al. (2006). Control of microglial neurotoxicity by the fractalkine receptor. Nat. Neurosci. 9, 917–924. Carlson, T., Kroenke, M., Rao, P., Lane, T. E., and Segal, B. (2008). The Th17-ELRþ CXC chemokine pathway is essential for the development of central nervous system autoimmune disease. J. Exp. Med. 205, 811–823. Carter, S. L., Mu¨ller, M., Manders, P. M., and Campbell, I. L. (2007). Induction of the genes for Cxcl9 and Cxcl10 is dependent on IFN-gamma but shows differential cellular expression in experimental autoimmune encephalomyelitis and by astrocytes and microglia in vitro. Glia 55, 1728–1739. Dziembowska, M., Tham, T. N., Lau, P., Vitry, S., Lazarini, F., and Dubois-Dalcq, M. (2005). A role for CXCR4 signaling in survival and migration of neural and oligodendrocyte precursors. Glia 50, 258–269. Hermann, G. E., Van Meter, M. J., and Rogers, R. C. (2008). CXCR4 receptors in the dorsal medulla: Implications for autonomic dysfunction. Eur. J. Neurosci. 27, 855–864. Huang, D., Han, Y., Rani, R. M., Glabinski, A., Trebst, C., Srensen, T., Tani, M., Wang, J., Chien, P., O’Bryan, S., Bielecki, B., Zhou, Z. L., et al. (2000). Chemokines and chemokine receptors in inflammation of the nervous system: Manifold roles and exquisite regulation. Immunol. Rev. 177, 52–67. Huang, D., Wujek, J., Kidd, G., He, T. T., Cardona, A., Sasse, M. E., Stein, E. J., Kish, J., Tani, M., Charo, I. F., Proudfoot, A. E., Rollins, B. J., et al. (2005). Chronic expression of monocyte chemoattractant protein-1 in the central nervous system causes delayed encephalopathy and impaired microglial function in mice. FASEB J. 19, 761–772. Kadi, L., Selvaraju, R., de Lys, P., Proudfoot, A. E., Wells, T. N., and Boschert, U. (2006). Differential effects of chemokines on oligodendrocyte precursor proliferation and myelin formation in vitro. J. Neuroimmunol. 174, 133–146. Khan, M. Z., Brandimarti, R., Shimizu, S., Nicolai, J., Crowe, E., and Meucci, O. (2008). The chemokine CXCL12 promotes survival of postmitotic neurons by regulating Rb protein. Cell Death Differ. 15, 1663–1672. Kivisa¨kk, P., Mahad, D. J., Callahan, M. K., Sikora, K., Trebst, C., Tucky, B., Wujek, J., Ravid, R., Staugaitis, S. M., Lassmann, H., and Ransohoff, R. M. (2004). Expression of CCR7 in multiple sclerosis: Implications for CNS immunity. Ann. Neurol. 55, 627–638. Li, M., and Ransohoff, R. M. (2008). Multiple roles of chemokine CXCL12 in the central nervous system: A migration from immunology to neurobiology. Prog. Neurobiol. 84, 116–131. Lu, M., Grove, E. A., and Miller, R. J. (2002). Abnormal development of the hippocampal dentate gyrus in mice lacking the CXCR4 chemokine receptor. Proc. Natl. Acad. Sci. USA 99, 7090–7095. Mahad, D. J., and Ransohoff, R. M. (2003). The role of MCP-1 (CCL2) and CCR2 in multiple sclerosis and experimental autoimmune encephalomyelitis (EAE). Semin. Immunol. 15, 23–32.


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Mahad, D. J., Trebst, C., Kivisa¨kk, P., Staugaitis, S. M., Tucky, B., Wei, T., Lucchinetti, C. F., Lassmann, H., and Ransohoff, R. M. (2004). Expression of chemokine receptors CCR1 and CCR5 reflects differential activation of mononuclear phagocytes in pattern II and pattern III multiple sclerosis lesions. J. Neuropathol. Exp. Neurol. 63, 262–273. Padovani-Claudio, D. A., Liu, L., Ransohoff, R. M., and Miller, R. H. (2006). Alterations in the oligodendrocyte lineage, myelin, and white matter in adult mice lacking the chemokine receptor CXCR2. Glia 54, 471–483. Pashenkov, M., and Teleshova, N. (2003). Inflammation in the central nervous system: The role for dendritic cells. Brain Pathol. 13, 23–33. Ransohoff, R. M., Kivisa¨kk, P., and Kidd, G. (2003). Three or more routes for leukocyte migration into the central nervous system. Nat. Rev. Immunol. 3, 569–581. Ransohoff, R. M., Tani, M., Glabinski, A. R., Chernosky, A., Krivacic, K., Peterson, J. W., Chien, H. F., and Trapp, B. D. (1997). Chemokines and chemokine receptors in model neurological pathologies: Molecular and immunocytochemical approaches. Methods Enzymol. 287, 319–348. Srensen, T. L., Trebst, C., Kivisa¨kk, P., Klaege, K. L., Majmudar, A., Ravid, R., Lassmann, H., Olsen, D. B., Strieter, R. M., Ransohoff, R. M., and Sellebjerg, F. (2002). Multiple sclerosis: A study of CXCL10 and CXCR3 co-localization in the inflamed central nervous system. J. Neuroimmunol. 127, 59–68. Sunnemark, D., Eltayeb, S., Nilsson, M., Wallstro¨m, E., Lassmann, H., Olsson, T., Berg, A. L., and Ericsson-Dahlstrand, A. (2005). CX3CL1 (fractalkine) and CX3CR1 expression in myelin oligodendrocyte glycoprotein-induced experimental autoimmune encephalomyelitis: kinetics and cellular origin. J. Neuroinflammation 2, 17. Trebst, C., Staugaitis, S. M., Kivisa¨kk, P., Mahad, D., Cathcart, M. E., Tucky, B., Wei, T., Rani, M. R., Horuk, R., Aldape, K. D., Pardo, C. A., Lucchinetti, C. F., et al. (2003). CC chemokine receptor 8 in the central nervous system is associated with phagocytic macrophages. Am. J. Pathol. 162, 427–438. van Heteren, J. T., Rozenberg, F., Aronica, E., Troost, D., Lebon, P., and Kuijpers, T. W. (2008). Astrocytes produce interferon-alpha and CXCL10, but not IL-6 or CXCL8, in Aicardi-Goutie`res syndrome. Glia 56, 568–578. Zheng, J. C., Huang, Y., Tang, K., Cui, M., Niemann, D., Lopez, A., Morgello, S., and Chen, S. (2008). HIV-1-infected and/or immune-activated macrophages regulate astrocyte CXCL8 production through IL-1beta and TNF-alpha: Involvement of mitogen-activated protein kinases and protein kinase R. J. Neuroimmunol. 200, 100–110.

C H A P T E R

F I V E

Expression of Chemokines and Chemokine Receptors in Human Colon Cancer Marco Erreni,* Paolo Bianchi,† Luigi Laghi,† Massimiliano Mirolo,§ Marco Fabbri,* Massimo Locati,‡ Alberto Mantovani,‡ and Paola Allavena* Contents 1. Introduction 2. Materials and Methods 2.1. Cell culture and tissue collection and processing 2.2. TaqMan Low Density Array 2.3. Quantitative real-time RT-PCR (Q-PCR) 2.4. Enzyme-linked immunosorbent assay 2.5. Statistical analysis 3. Results 3.1. TaqMan Low Density Array analysis of eight colon cancer samples 3.2. CCL3, CCL4, and CXCL8 expression in colon cancer 3.3. Regulation of CXCL8 expression in colon cancer cell lines 3.4. CXCL8 correlation with OPN and SPARC 4. Discussion Acknowledgments References

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Abstract Human colorectal cancer (CRC), the second largest cause of tumor-related death in Western countries, represents a paradigm for the now well-established connections between inflammation and cancer. In this study, we investigated

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Department of Immunology and Inflammation, IRCCS Istituto Clinico Humanitas, Rozzano (Milan), Italy Laboratory of Molecular Gastroenterology, IRCCS Istituto Clinico Humanitas, Rozzano (Milan), Italy Department of Translational Medicine, University of Milan, IRCCS Istituto Clinico Humanitas, Via Manzoni, Rozzano (Milano), Italia Laboratory of Leukocyte Biology, Department of Translational Medicine, University of Milan, IRCCS Istituto Clinico Humanitas, Italy


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which inflammatory mediators are mostly expressed in the microenvironment of human CRC. The RNA profile of a large panel of inflammatory genes, in particular chemokines and chemokine receptors, was analyzed in eight surgical tumor samples and in paired normal tissues from CRC patients. We employed an ‘‘inflammatory gene card’’ (TaqMan Low Density Array by Applied Biosystem), designed by our group, containing probes for 24 chemokines and 17 chemokine receptors. Several chemokines were strongly upregulated in the tumor microenvironment, most frequently CCL4 and CCL5, chemotactic for monocytes/ macrophages and T cells, and the corresponding receptors CCR1 and CCR5; the angiogenic chemokines CXCL1 and CXCL8, and the receptor CXCR2. The antiangiogenic chemokines CXCL9 and CXCL10 were also expressed, but in the absence of the receptor CXCR3. Selected results have been confirmed in a larger number of samples. The levels of mRNA CXCL8 were significantly associated with the levels of osteopontin, a matrix-associated protein that shares with chemokines important functions such as induction of cell migration and survival, and modulation of the neoangiogenesis. Overall these results could be helpful to identify the most relevant inflammatory pathways present in CRC tumors and to build a solid rationale for future therapeutic interventions based on anti-inflammatory strategies.

1. Introduction Links between cancer and inflammation were first suggested in the 19th century on the basis of observations that tumors often arise at sites of chronic inflammation and that inflammatory cells are present in the biopsied samples from tumors (Mantovani et al., 2001). Epidemiological studies have shown that chronic inflammation predisposes individuals to various types of cancer, including microbial infections, autoimmune diseases, and inflammatory conditions of unknown origin. The hallmarks of cancer-related inflammation include the presence in tumor tissues of inflammatory cells and soluble mediators such as chemokines, cytokines and prostaglandins, tissue remodeling, and angiogenesis (Coussens and Werb, 2002; Karin, 2006; Mantovani, 2005; Mantovani et al., 2008). Chemokines are chemotactic cytokines that cause the direct migration of leukocytes and are induced by inflammatory cytokines, growth factors, and pathogenic stimuli. Many human cancers have a complex chemokine network that regulates the extent and phenotype of the infiltrating leukocytes, as well as have an effect on tumor growth, survival, migration, and angiogenesis (Balkwill, 2004). The pattern of chemokine-receptor and ligand expression in a tissue is generally correlated with the numbers and types of infiltrating cells that are present in the tumor microenvironment (Balkwill, 2004; Karin and Greten, 2005; Rossi and Zlotnik, 2000). The influence of the immune response in the behavior of neoplasia has been extensively investigated. There is little doubt that adaptive immune

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cells, especially cytotoxic CD8þ T-cell effectors, have the potential to limit tumor progression (Dunn et al., 2004). The protective function of CD8þ T cells has been demonstrated in patients with melanoma, ovarian, and colorectal cancer (CRC) (Coukos et al., 2005; Taylor et al., 2007). Recently, Galon and colleagues (Galon et al., 2006; Pages et al., 2005) demonstrated that the presence of a strong immune-cell infiltrate is associated with the absence of early metastatic processes, which include vascular emboli, lymphatic invasion, and perineural invasion, demonstrating a beneficial effect of the host’s immune response. On the other hand, the persistence of active innate immune responses (i.e., chronic inflammation) at tumor sites has been more frequently associated with poor clinical outcome (Balkwill, 2004; Coussens and Werb, 2002; Dunn et al., 2004; Karin, 2006; Mantovani, 2005; Mantovani et al., 2001, 2008). The links between inflammation and cancer promotion are especially strong in human colorectal carcinoma (CRC), the second largest cause of cancer-related death in Western countries. Patients with inflammatory bowel disease, both ulcerative colitis and Crohn’s disease, are at increased risk of developing colorectal cancer. Even precancerous tissues show signs of inflammation. Accordingly, treatment with nonsteroidal anti-inflammatory agents decreases the incidence of colon cancer, and the mortality that results from it (Bertagnolli, 2003). The contribution of macrophages to CRC development is quite controversial. Bailey et al. (2007) demonstrated that the increase of macrophages number in all areas within the tumor correlated with advanced tumor stage. In contrast, Forssell et al. (2007) showed that in CRC, macrophages are localized principally at the tumor front and positively influenced prognosis. These contrasting results may be explained by the ‘‘macrophages balance hypothesis,’’ proposed by our group, to convey the idea that macrophages may inhibit or stimulate tumor growth according to their functional polarization and state of activation (Mantovani et al., 2002, 2004; Pollard, 2004). While M1-polarized macrophages, activated by IFNg and bacterial products such as LPS, usually have tumoricidal activity, M2 macrophages, differentiated in the presence of Th2 cytokines (IL-4, IL-13) or IL-10, most frequently are not cytotoxic, favor tumor cell proliferation and the angiogenic switch, and lead to tumor progression and invasion (Mantovani et al., 2008). In this context, it is clear that inflammatory mediators, such as chemokines, cytokines, and growth factors play a pivotal role in the recruitment of the inflammatory infiltrate and in the buildup of the tumor microenvironment. In this study, we investigated the expression of chemokines and chemokine-receptors in surgical samples of human CRC. We analyzed the mRNA profile using a customized TaqMan Low Density Array (Lu et al., 2008). The results show a strong upregulation of chemokines and chemokine-receptors, indicating the pivotal role of these inflammatory mediators in the growth and progression of CRC.

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2. Materials and Methods 2.1. Cell culture and tissue collection and processing Thirty colon cancer samples and corresponding normal tissues were obtained via surgical resection from the Department of Gastroenterology, Istituto Clinico Humanitas IRCCS, Rozzano, Milan. The samples were immediately treated with RNAlater (Ambion) for 24 h at 4 , and subsequently dried and stored at –80 . All patients consented to the study. CRC cell lines HCT116, HT29, and SW620 were cultured in RPMI 1640 medium supplemented with 10% fetal bovine serum (Lonza, BioWhittaker), 2 mM Ultraglutamine1 (Lonza, BioWhittaker), and 100 U/ml penicillin/streptavidin (Lonza, BioWhittaker) at 37 in 5% CO2. Total RNA was isolated both from tissue specimens and cell lines using TRI Reagent (Ambion). Total RNA was quantified by Nanodrop Spectrophotometer ND-1000 and its quality was examined by 1.5% agarose gel electrophoresis. 2mg of total RNA were reverse-transcribed using the High-Capacity cDNA Archive kit (Applied Biosystems) according to the manufacturer’s instructions.

2.2. TaqMan Low Density Array Eight colon cancer samples and their corresponding normal tissues were used for low-density array (LDA) analysis. The LDA contains eight sampleloading lines, each connected by microchannel to 48 miniature reaction chambers for a total of 384 wells per card. Gene-specific exon-spanning primers and TaqMan probes were factory-designed and embedded in each well. We chose 96 genes from Applied Biosystems Assays-on-DemandTM Gene Expression Products: five housekeeping genes (HPRT, 18S, GAPDH, B2M, ACTB) and 91 inflammation-related genes. The LDA in this study was configured into four identical 96-gene sets (two samples in duplicate). A total of 100 ml of reaction mixture with 100 ng of cDNA template and 50 ml 2 of TaqMan Universal PCR Master Mix (Applied Biosystems) was added to each line of LDA after vortex and brief centrifugation. Each reaction cell contained 1 ml of reaction mixture with 1 ng of mRNA. LDA were sealed with a TaqMan LDA sealer (Applied Biosystems) before centrifugation. The PCR amplification was performed in the microfluidic card sample block of an ABI PrismÒ 7900HT Fast Real-Time PCR System (Applied Biosystems). The amplification protocol was used as follows: 2 min at 50 to activate uracil-DNA glycosylase (Forssell et al. 2007), 10 min at 94.5 (activation), 40 cycles of denaturation at 97 for 30 s, and annealing and extension at 59.7 for 1 min. The relative amount of each target gene


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mRNA to the mean of the five housekeeping genes (HPRT, 18S, GAPDH, B2M, and ACTB) was calculated as 2–DCt, where DCt ¼ Ct – Ctmean of housekeeping genes. The fold-change of each target gene mRNA to the corresponding normal tissue was calculated as 2–DDCt, where DDCt ¼ DCttarget gene in tumor tissue – DCttarget gene in normal tissue. The threshold cycle Ct was automatically given by the SDS2.2 software package (Applied Biosystems).

2.3. Quantitative real-time RT-PCR (Q-PCR) Several genes were further analyzed via the SYBR Green-based Q-PCR assay in an additional 30 colon cancer samples and corresponding normal tissue. 18S was used as an internal control to normalize samples. All genespecific exon-spanning primers were domestically designed. The sequences are indicated in the following: 18S: Forward: 50 CGC CGC TAG AGG TGA AAT TC 30 Reverse: 50 CTT TCG CTC TGG TCC GTC TT 30 CCL3: Forward: 50 TGC AAC CAG TTC TCT GCA TC 30 Reverse: 50 AAT CTG CCG GGA GGT GTA 30 CCL4: Forward: 50 TTA CTA TGA GAC CAG CAG CCT CT 30 Reverse: 50 CAG CAC AGA CTT GCT TGC TT 30 OPN: Forward: 50 CGC AGA CCT GAC ATC CAG T 30 Reverse: 50 GGC TGT CCC AAT CAG AAG G 30 SPARC: Forward: 50 GTG CAG AGG AAA CCG AAG AG 30 Reverse: 50 TGT TTG CAG TGG TGG TTC TG 30 CXCL8: Forward: 50 CTG CGC CAA CAC AGA AAT TA 30 Reverse: 50 TTG AAG AGG GCT GAG AAT TCA 30 Each PCR reaction of 25 ml consisted of a 4-ml aliquot of each cDNA (40 ng mRNA for target genes and 1 ng mRNA for 18S gene), 0.2 mM forward and reverse primers and 12.5 ml of Power SYBR Green PCR Master Mix (Applied Biosystem). The Q-PCR program follows: 2 min at 50 , 10 min at 95 , 40 cycles of 15 s at 95 , and 1 min for 60 . The melting curve analysis was carried out at 95 for 15 s, 60 for 15 s, and 95 for 15 s. Each sample was amplified in triplicate in 96-well PCR microplates on an ABI PrismÒ 7900HT Fast Real-Time PCR System (Applied Biosystems). Data analysis followed the same protocol as that in LDA.

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2.4. Enzyme-linked immunosorbent assay CXCL8 levels in cell-line supernatants were measured using human IL-8 DuoSet ELISA Development System (R&D Systems). Cells were cultured in six-well plates at a concentration of 500,000 cells/well and treated with TNFa (10 ng/ml) alone or in combination with TGFb (2 ng/ml) at 37 in 5% CO2. After 24 h, supernatants were collected, filtered using 0.2 mm cellulose-acetate syringe filters (Albet-Jacs), and stored at –20 . The IL-8 DuoSet ELISA Development System (R&D Systems) was used for CXCL8 detection. Briefly, a 96-well flat bottom microplate (Costar) was coated with 4 mg/ml of captured antibody, diluted in Reagent Diluent (R&D Systems) (0.1% BSA, 0.05% Tween 20 in PBS, pH 7.2–7.4) at 4 O/N. Each well was washed in Washing Buffer (0.05% Tween 20, PBS, pH 7.2–7.4) and blocked with 1% BSA in Washing Buffer for 2 h at RT. Wells were washed three times and then 50 ml of sample were added to each wells and incubated for 2 h at RT. Each sample was analyzed in duplicate and threefold serial dilutions in Reagent Diluent were performed. A standard curve was performed using recombinant CXCL8, using twofold serial dilution in Reagent Diluent and a high standard point of 2 ng/ml. Each well was then washed in washing buffer and incubated with 50 ml of detection antibody for 2 h RT. Next, 50 ml of streptavidin-HRP were added to each well for 20 min at RT. Development was performed using the 3,30 ,5,50 tetramethyl-benzidine (TMB) Liquid Substrate System (SIGMA), and reaction was blocked by H2SO4 2N. The amount of CXCL8 was evaluated by optical density using the VersaMax microplate reader (Molecular Devices) set to 450 nm.

2.5. Statistical analysis The StatsDirect software was applied for the statistical analysis. The significance of differential gene expression among normal and tumor tissues were determined using the nonparametric Mann-Whitney U-test. A p-value of less than 0.05 was considered statistically significant. Simple linear regression analysis was used to determine mRNA correlation among the target genes.

3. Results 3.1. TaqMan Low Density Array analysis of eight colon cancer samples To investigate the role of chemokines and their receptors in colon cancer tissues, we performed a large screening of inflammation-related genes in eight human colon cancer samples and corresponding normal tissues, using the TaqMan Low Density Array (Applied Biosystem), customized with

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91 inflammation-related genes, selected by us, and 5 housekeeping genes. Among the 91 inflammation-related genes, 24 were chemokines and 17 were chemokine-receptors. Table 5.1 shows an overview of the results from eight samples of CRC tumors. The data are expressed as relative to each utologous normal tissue (adjacent colonic mucosa). Considering a fold-change greater than two, several ligands were upregulated. Among CC chemokines, CCL1, CCL3, CCL4, CCL7, CCL20, CCL25, and CCL26 were more frequently transcribed compared to normal tissues. The corresponding receptors, CCR8 Table 5.1 Overview: Expression of chemokine system in microenvironment of human CRC samples Stage1 Stage2 Stage2 Stage3 Stage3 Stage3 Stage4 Stage4 CCL1 CCL11 CCL14/15 CCL17 CCL18 CCL2 CCL20 CCL21 CCL25 CCL26 CCL3 CCL4 CCL7 CCL8 CCR1 CCR3 CCR5 CCR6 CCR8 CMKLR1 CXCL1 CXCL10 CXCL9 CXCR3 CXCR4 CXCL8 CXCR2 CXCL12

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mRNA of chemokines and receptors from CRC tumors were analyzed via a customized TaqMan Low Density Array. Data are expressed relative to autologous normal tissues. Grey box depicts a fold equal or greater than two. Eight tumor samples representative of various clinical stages are shown.

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and CCR6, were also upregulated, but others, CCR1 and CCR5, were less than 2. Among CXC chemokines, high levels of CXCL1 and CXCL8 and the corresponding receptor CXCR2 were found. High levels of CXCL9 and CXCL10 were also found, but not their receptor CXCR3. Surprisingly, the chemokine CCL2, frequently produced by several tumor types including CRC, or the constitutive chemokine CXCL12, were not upregulated. To better appreciate the configuration of the chemokine system in the normal colonic mucosa, the data were analyzed relative to the mean of the five housekeeping genes customized in the LDA. Two representative cases are presented in Fig. 5.1. Panels A and B show the mRNA levels of chemokines and receptors in one early-stage tumor, while Panels C and D show levels in an advanced stage tumor, respectively. The normal colonic mucosa (white bars) expresses several chemokines; CCL2, CCL5, CCL14/CCL15, CCL20, CCL21, and CXCL12 are expressed most frequently. Some of these chemokines were further upregulated in tumor samples (black bars), but not always reach the cut-off of twofold. Other chemokines such as CCL3, CCL4, and CXCL9, CXCL10, and especially CXCL8 were more selectively overexpressed in the tumor tissue. Among chemokine receptors, CXCR4 and CXCR7—both binding CXCL12—were found in the normal mucosa, while in the tumor tissue several receptors were upregulated, including CCR1 and CCR5, both binding CCL3 and CCL4, and CXCR2, recognizing CXCL8. We further decided to investigate the expression of these specific ligands in a larger series of CRC samples.

3.2. CCL3, CCL4, and CXCL8 expression in colon cancer To confirm the data obtained by the TaqMan Low Density Array, we further investigated mRNA expression of CCL3 and CCL4 in another 20 colon cancer tissues and their corresponding normal tissue. As shown in Fig. 5.2A, there is a significant increase in CCL3 expression in tumor samples compared with the normal colonic mucosa (p ¼ 0.05). CCL4 median expression is higher in tumor tissues, but this difference is at the limit of significance ( p ¼ 0.07). Moreover, there is higher amount of CCL4 than CCL3, both in normal and tumor tissue. Subsequently, we focused our attention on CXCL8, since it has been extensively demonstrated that this ligand is strongly overexpressed in various tumor types. We then investigated CXCL8 mRNA expression in 30 colon cancer tissues and corresponding normal mucosa: as shown in Fig. 5.2C, there is a strong significant increase in CXCL8 expression in tumor tissues (p < 0.0001).When compared to CCL3 and CCL4, CXCL8 shows the same mRNA expression in normal mucosa, but its expression is markedly higher in tumor samples. Both for CCL3, CCL4 and CXCL8 there is no significant correlation with tumor stage (data not shown).

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Figure 5.1 ExpressionofmRNAforchemokinesandchemokine receptorsintwotumorsamples from CRCpatients,analyzedbyacustomized TaqMan Low DensityArray. Results in left panels refer to an early-stage tumor (Stage 2); right panel refers to an advanced-stage tumor (Stage 4). Chemokine ligands are depicted in panels A and C, and receptors in panels B and D. Shown are the mRNA levels relative to the mean of the five housekeeping genes customized in the LDA in the normal autologous colonic mucosa (white bar) and in the tumor tissue (black bar).

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3.3. Regulation of CXCL8 expression in colon cancer cell lines Three CRC tumor cell lines were studied for the expression of CXCL8 mRNA and protein secretion. The cell lines SW620 and HT29 secreted low but detectable levels of CXCL8 constitutively, while HCT116 cells did not. An increased production was obtained upon stimulation with TNFa and TGFb, two mediators frequently found at the tumor site. Accordingly, mRNA levels were increased in TNFa/TGFb-stimulated cells. Surprisingly, TNFa stimulation alone increased mRNA levels in SW620 and HT29 cells, but not protein production (Fig. 5.3). A

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Figure 5.3 Regulation of CXCL8 in tumor cells lines derived from human CRC. Protein levels (panel A) were measured by a commercial ELISA in cell supernatants; mRNA levels (panel B) were analyzed by RT-PCR. Cells were either untreated (medium), or stimulated with TNFa (20 ng/ml) and TGFb (20/ ng/ml) for 24 h for protein expression or 6 h for mRNA.

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3.4. CXCL8 correlation with OPN and SPARC Among the most expressed genes in the LDA, we found osteopontin (OPN) and Secreted Protein Acidic and Rich in Cysteine (SPARC). It has been demonstrated that osteopontin is not only a matrix protein, but has also chemotactic activity for leukocytes, and is involved, together with CXCL8, in prostate cancer recurrence. Both OPN and SPARC contribute to the deposition and remodeling of the extracellular matrix (ECM) and to the development of angiogenesis, a function shared by CXCL8 as well. We therefore investigated the expression of OPN and SPARC in CRC samples, and their relationship with CXCL8. As shown in Fig. 5.4, there is a significant increase in both mRNA OPN (Fig. 5.4A) and SPARC (Fig. 5.4B) in tumor tissues compared to normal mucosa ( p < 0.0001). Interestingly, we found a significant linear correlation between mRNA OPN and CXCL8 A

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expression in tumor tissues ( p ¼ 0.001) (Fig. 5.4C), while there was no correlation between CXCL8 and SPARC ( p ¼ 0.9) (Fig. 5.4D).

4. Discussion In this study, we have investigated the chemokine system in samples of human colorectal tumors. To obtain a global view of which chemokines and receptors are overexpressed in the tumor microenvironment, we have used a customized TaqMan Low Density Array containing probes for 24 ligands and 17 receptors. Several CC and CXC chemokines were strongly upregulated in tumor samples compared to the paired normal colonic mucosa. Interestingly, a number of chemokines were constitutively expressed also in the normal tissue, such as CCL2, CCL20, and CXCL12. The significance of their expression in normal colonic mucosa is likely explained by the abundant presence, at this site, of immune effectors of both innate and adaptive immunity, to maintain the local homeostasis. These chemokines were not or only slightly elevated in tumor samples. In contrast, other ligands, such as the inflammatory cytokines CCL3, CCL4, CXCL8, and a few others, were significantly increased compared to the normal counterpart tissue. CCL3 and CCL4 are chemotactic for monocytes/macrophages and T cells, the major components of tumor-infiltrating leucocytes in colorectal tumors, as well as in other tumor histotypes. Of note, while the subset of CD8þ T cells has been defined as protective antitumor effectors in CRC and their number associated with better prognosis (Galon et al., 2006), the role of macrophages is more ambiguous. Some studies on different tumor types, have described divergent result reporting a correlation with a favorable clinical outcome (Bailey et al., 2007; Forssell et al., 2007) or, in marked contrast, an association with tumor progression—in the majority of tumors (Allavena et al., 2008; Deconto et al., 2008). These contrasting results may be interpreted in view of the macrophage balance hypothesis and the distinct function of polarized macrophage populations (Mantovani et al., 2002). In our study, we found an increased expression of CCL3 and CCL4 in tumor samples, but no association with the stage of disease, in that earlystage tumors also had high levels of these chemokines compared to normal tissues (data not shown). The chemokine CXCL8 attracts mainly neutrophils; these leukocytes are short-living and are not usually present in tumors. Recently, it has been reported that myeloid derived suppressor cells (MDSC) express the CXCR2 receptor and may respond to CXCL8 (Sica and Bronte, 2007). The contribution of CXCL8 in the recruitment of MDSC warrants further investigation. CXCL8 and other members of the same family have been extensively studied for their role in stimulating neoplastic growth, such as in melanoma

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(Richmond, 2002). In addition, these chemokines may promote tumor progression and invasion by stimulating the process of neoangiogenesis and the activation of matrix proteases (Murphy, 2001; Strieter et al., 2006). In this study, mRNA CXCL8 was strongly expressed in CRC samples, in line with previous reports (Schottelius and Dinter, 2006). The receptor CXCR2 was also found upregulated in selected tumor samples (not shown). To gain some information on the regulation of CXCL8, we performed in vitro experiments with cytokine-activated tumor-cell lines derived from CRC. Two cell lines were able to constitutively produce CXCL8 and its secretion was increased upon stimulation with TNFa and TGFb, two major cytokines present at the tumor site. It is well established that other members of the CXC family possess antiangiogenic activity (Strieter et al., 2006). In the tumor microenvironment, the balance between proangiogenic and antiangiogenic chemokines may determine the degree of angiogenesis and the consequent tumor progression. In our study, we also found high levels of two antiangiogenic chemokines, CXCL9 and CXCL10, but no significant expression of their specific receptor CXCR3 was detected. Hence, it is likely that the proangiogenic effect of CXCL8 prevails. The TaqMan array we used contained several other probes coding for inflammation-related genes. Two genes remarkably upregulated in cancer samples were OPN and SPARC. These glycoproteins belong to the large family of ECM proteins and have generated great interest in cancer biology. Evidence in vivo and in vitro indicates that SPARC is a key modulator of the tumor microenvironment, as this protein influences tumor cell survival, migration, angiogenesis, and ECM remodeling (Chlenski et al., 2006; Clark and Sage, 2008; Podhajcer et al., 2008). Nevertheless, its underlying mechanisms and true impact on tumor progression are yet to be determined. Recently it has been reported that macrophage-derived SPARC induces cancer cell migration, acting at the step of integrin aVb5 (Sangaletti et al., 2008). The other matricellular protein, OPN, is also important to bridge cancer cells with the ECM. The relevance of OPN expression to human cancer has been investigated in several studies (Koh et al., 2007; Wai and Kuo, 2008). OPN levels are usually elevated in aggressive tumors when compared with low-grade tumors or with the normal tissue and correlate with the presence of metastatic disease. Moreover, OPN is included in lists of genes that predict poor prognosis in patients with various types of cancer (Graudens et al., 2006; Wai and Kuo, 2008). Yet, the mechanism by which OPN supports metastasis is not clear. Tumor cell interaction with OPN is mediated via the adhesion receptor CD44 and its variants expressed by tumor cells (e.g., CD44v6) and by beta-integrins (Bellahcene et al., 2008). Recently McAllister et al. (2008) proposed that soluble OPN released by cancer cells can activate bone marrow cells to be recruited at the tumor site,


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fostering tumor progression. In our study, and in line with previous reports, mRNA of OPN and SPARC were strongly upregulated in tumor samples. Of interest, a linear correlation was found between the expression of OPN and CXCL8. As mentioned above, these two mediators share some important functions such as cell mobility and cell survival via integrin activation (Caruso et al., 2008). In contrast, no significant correlation was found between the levels of SPARC and CXCL8. Collectively, this study investigated the complex network of chemokines and receptors in the tumor microenvironment of human CRCs. The approach we used was to employ a TaqMan Low Density Array to screen a large number of ligands and receptors that would have been very laborious to perform with the conventional RT-PCR. This initial screening led to identification of the most expressed genes in tumor samples, and was therefore very informative for selection of a more restricted panel of candidate molecules for further investigation. The results of this study may be helpful to build a solid rationale for novel therapeutic interventions targeted to specific inflammatory molecules, and to identify novel prognostic CRC markers.

ACKNOWLEDGMENTS This work was supported by the Italian Association for Cancer Research (AIRC), MIUR target project Oncologia 2006, and Alleanza Contro il Cancro.

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Kaposi’s Sarcoma Virally Encoded, G-Protein–Coupled Receptor: A Paradigm for Paracrine Transformation Daniel Martin and J. Silvio Gutkind Contents 1. Introduction 2. Cloning of vGPCR 2.1. Outline 2.2. Procedure 3. Assaying vGPCR Transforming Activity In Vitro 3.1. Overview 3.2. Procedure 4. vGPCR Transforming Activity In Vivo Using Xenograft Systems 4.1. Overview 4.2. Procedure 5. In Vivo Targeted Infection Using the TVA-RCAS System 5.1. Overview 5.2. Procedure 5.3. Viral production 6. vGPCR-Induced Paracrine Transformation 6.1. Overview 6.2. Procedure 7. Characterization of vGPCR-Induced Molecular Signaling 7.1. Outline 8. Evaluation of Activation of Second-Messenger– Generating Systems 8.1. Overview 8.2. Procedure

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9. Activation of Signal-Transducing Protein Kinases and Small GTPases 10. Akt Kinase Assay 10.1. Overview 10.2. Procedure 11. vGPCR Stimulated Activation of Rac1-Pulldown Assays 11.1. Overview 11.2. Procedure 12. Western Blotting Using Phospho-Specific Antibodies 12.1. Overview 12.2. Procedure 13. Activation of Transcription Factors 14. Global Changes in Gene Expression: Microarray Analysis 14.1. Overview 14.2. Procedure 15. NFkB Luciferase Assays 15.1. Overview 15.2. Procedure 16. NFkB Binding Assays 16.1. Overview 16.2. Procedure 17. Nuclear Translocation of NFkB 17.1. Overview 17.2. Procedure Acknowledgments References

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Abstract Kaposi’s sarcoma (KS) is an angioproliferative disease caused by infection with human herpesvirus 8 (HHV-8), also known as Kaposi’s sarcoma-associated herpesvirus (KSHV). This virus encodes 84 open-reading frames (ORFs), many of which represent pirated versions of human genes. One of them, ORF74, encodes a predicted seven-span transmembrane receptor termed vGPCR that is similar to the human IL8 receptor CXCR2, which displays strong oncogenic activity in vitro and in vivo by a complex interplay of direct and autocrine/ paracrine mechanisms. vGPCR has been shown to be both necessary and sufficient for the formation and progression of KS-like lesions in experimental model systems. Due to the fundamental role of vGPCR in the pathogenesis of KS, understanding the molecular mechanisms elicited by this unique chemokine receptor can be exploited to devise new strategies for KS management, as well as to gain novel insights into how KSHV subverts key physiological processes such as cell proliferation, chemotaxis, angiogenesis, and immunomodulation for its replicative advantage. Here we describe multiple techniques and strategies that have been used to study the unique properties and functions of vGPCR and its role in oncogenesis.

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1. Introduction The human herpesvirus 8 (HHV8) (also termed Kaposi’s sarcomaassociated herpesvirus [KSHV]) is the etiologic agent of Kaposi’s sarcoma (KS) and two lymphoproliferative diseases, multicentric Castleman’s disease and primary effusion lymphoma (Cesarman and Mesri, 2007; Chang et al., 1994). KS is an angioproliferative disease manifested in four different variants that vary in the onset, progression, and clinical implication (Schwartz et al., 2008). Classical KS, the first described, affects elderly population of the Mediterranean area, appearing in extremities, normally as an indolent disease. The endemic variant is a more aggressive form, occurring mostly in young males in some sub-Saharan African countries (Morris, 2003). A third variant, the iatrogenic KS, is developed by transplant recipients undergoing immunosuppression regimes, and finally, the AIDS-associated KS is the most aggressive variant and is frequently fatal being still the most common cancer arising in AIDS patients (Laney et al., 2007). The introduction of highly active antiretroviral therapy (HAART) has caused a dramatic decrease in the proportion of new AIDS-defining KS cases and a regression in the size of existing KS lesions (Bower et al., 2006). However, there is still a risk of recurrence of AIDS-associated KS that we cannot afford to ignore (Rezza et al., 1999). Indeed, in parts of the developing world, KS has tragically emerged as one of the most frequent cancers among children and adult men (Schwartz et al., 2008), and KS remains a significant cause of morbidity and mortality among the world AIDS population (Cheung et al., 2005). Initial characterization of KS lesions identified the presence of multiple cytokines and growth factors. Unlike many other tumor-derived cell cultures, isolates from KS lesions strictly require supplementation with growth factor and chemokines such as VEGF and oncostatin M, providing an early insight into the central role secreted factors play in KS development and maintenance (reviewed in Cesarman and Mesri, 2007; Ganem, 2006). In this regard, upon sequencing of the KSHV genome, several virally encoded genes and cytokines have been identified and shown to play roles in cell proliferation, immune surveillance evasion, and host cell recruitment. These include multiple virally encoded secreted factors such as vIL6, vCCL-1, vCCL-2, and vCCL-3, and a number of viral proteins that promote the production of host cytokines, chemokines, and growth factors (Ganem, 2006). Among these molecules, the open reading frame 74 (ORF74) encodes a constitutively active G-protein–coupled receptor termed vGPCR that is highly related to the IL8 chemokine receptor CXCR2 (Arvanitakis, 1997). vGPCR promotes the release of proangiogenic growth factors and exhibits potent transforming activity in cells in culture (Bais et al., 1998; Sodhi et al., 2000). Furthermore, when expressed as a transgene or when virally transduced into endothelial cells, vGPCR readily leads to the development of KS-like lesions in animal models

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(Guo et al., 2004; Jensen et al., 2005; Montaner et al., 2003; Yang et al., 2000). This strong growth-promoting and tumorigenic activity of vGPCR involves the robust stimulation of the expression and release of multiple chemokines and endothelial growth factors, which promote the proliferation of KSHV infected cells in a an autocrine and paracrine fashion (Martin et al., 2008; Montaner et al., 2003; Sodhi et al., 2004a). While recent studies have highlighted the critical role of vGPCR in KS development (Mutlu et al., 2007), the emerging information on how vGPCR exerts its potent sarcomagenic activity in animal models has now provided an opportunity for the development of molecularly targeted therapies aimed at interfering with vGPCR-initiated pathways in human KS (Montaner et al., 2006; Sodhi et al., 2006). In this regard, early studies showed that vGPCR stimulates several mitogenic pathways, including the MAPK and p38 pathways and the small G-protein Rac1, which play a role in vGPCR-induced pathogenesis (Bais et al., 1998; Dadke et al., 2003; Montaner et al., 2004; Sodhi et al., 2000). Subsequently, it was observed that vGPCR promotes the survival and subsequent transformation of endothelial cells by the activation of the phosphatidylinositol-3-kinase (PI3K)– Akt pathway (Sodhi et al., 2004b). Systematic analysis of the molecular mechanism by which the activation of Akt contributes to vGPCR-induced sarcomagenesis revealed that mTOR, a protein kinase that acts as a downstream target of Akt, is strictly required for the tumorigenic activity of vGPCR (Sodhi et al., 2006), thereby providing a molecular target for therapeutic intervention in this angioproliferative disease. Indeed, drugs that inhibit the PI3K-Akt-mTOR pathway can halt the progression of KS and even induce its regression both in animal models and in the clinical setting (Chaisuparat et al., 2008; Sodhi et al., 2004b; Stallone et al., 2005). The identification of suitable molecular targets for KS treatment has ignited renewed interest in understanding the molecular mechanisms involved in vGPCR-mediated angioproliferation, immunomodulation and transformation. Here we describe a number of techniques and strategies to study several molecular aspects of vGPCR with particular focus in its direct and paracrine transforming ability in vitro and in vivo. We will not assume previous experience from the reader and we will emphasize practical simplifications that we have developed in some of the protocols that we expect can be useful also for the characterization of other chemokine receptors.

2. Cloning of vGPCR 2.1. Outline KSHV RNA can be obtained form several sources including KS biopsies, pleural effusions, body cavity B-cell lymphomas (BCBL), cell lines, and KS-derived spindle-cell cultures (Browning et al., 1994) and the KSHV


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phage library (National Institutes of Health, AIDS Research and Reference Reagent Program, Rockville, MD). Because of the limited availability of commercial antibodies for vGPCR, it is advised to epitope-tag the protein. As GPCRs interact with Ga subunits and with the internalization and intracellular targeting machinery by their c-terminal tails, it is recommended to add small tags N-terminally. Addition of bulkier N-terminal tags, such as GFP or derivatives, normally results in reduced vGPCR activity (unpublished results).

2.2. Procedure RNA should be extracted using standard methods such as the TriZOL (Invitrogen, Carlsbad, CA) method. Following manufacturer’s recommendations regarding the specific volume of TriZOL reagent to use depending on the origin of the source (tissue or cell line) and mass, homogenization will be accomplished by finely mincing, grinding in LN2, or scrapping of the sample in TriZOL. Incubate the samples for 5 min at room temperature, centrifuge, and add 1:5 of the volume of chloroform and vortex vigorously. Incubate the samples for an additional 15 min. Centrifuge the samples at 12,000g for 15 min, and collect the upper phase containing the RNA. Precipitate the RNA by adding 1:2 of the original TriZol volume of isopropyl alcohol. Incubate for 15 min at room temperature and centrifuge at 12,000g for 10 min at 4 . Wash the RNA pellet once with 75% EtOH, air dry, and resuspend the pellet in RNAse-free water. Use 100 ng of RNA as template for cDNA synthesis using Superscript II (Invitrogen). Assemble the reaction following the manufacturer’s recommendations but extend the synthesis at 42 for up to 2 h. Remove RNA by treatment with RNAse H. This cDNA can be used as template for PCR, or alternatively, Lambda Phage KSHV Library DNA that can be obtained from the National Institutes of Health, AIDS Research and Reference Reagent Program, Rockville, MD, can be used as well. Amplify vGPCR using the following oligos containing BglII and EcoRI sites (underlined) used for the subsequent cloning (or modify accordingly); the vGPCR start codon is boldfaced. Fwd: 50 -ATAAGATCTATGGCGGCCGAGGATTTCCTAAC-30 Rev: 50 -ATAGAATTCCTACGTGGTGGCGCCGGACATGAA-30 Use 100 ng of cDNA or lambda DNA as template using a high-fidelity polymerase. Conditions for PCR are as follows: 95 , 2 min initial denaturation; 30 cycles of 95 30 s, 60 30 s, and 68 1.5 min; and a final 7min extension at 68 . PCR amplification of vGPCR yields a 1.1-Kb fragment. Gel-purify the PCR product and clone in an expression vector.

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3. Assaying vGPCR Transforming Activity In Vitro 3.1. Overview One of the most remarkable cellular effects of vGPCR is the acquisition of a transformed phenotype that can be experimentally induced by transfecting mouse fibroblasts with vGPCR (Bais et al., 1998). A very convenient way to detect and characterize molecules involved in vGPCR’s transforming ability is to cotransfect the cells with shRNA-encoding vectors targeted to molecules of interest or expression vectors for their interfering mutants, and thus study cooperation or inhibition in cell transformation.

3.2. Procedure Transfect NIH 3T3 cells by the calcium phosphate precipitation technique (Wigler et al., 1977) with a vGPCR expression vector and optionally other expression or shRNA-encoding plasmids together with 1 mg of pcDNAIIIb-gal, a plasmid expressing the enzyme b-galactosidase, adjusting the total amount of plasmid DNA with empty vector, and maintaining the cells in DMEM supplemented with 10% calf bovine serum. The day after transfection, wash the cells in medium supplemented with 5% calf serum, and maintain them, changing the same medium twice a week until foci are scored 3 to 4 weeks later. Fix the plates with PBS containing 2% (v/v) formaldehyde and 0.2% (v/v) glutaraldehyde and stain at 37 for b-galactosidase activity with a PBS solution containing 2 mM MgCl2, 5 mM K3Fe(CN)6, 5 mM K4Fe(CN)6, and 0.1% 5-bromo-4-chloro-3-indolyl-b-Dgalactopyranoside (X-gal) to evaluate the transfection efficiency.

4. vGPCR Transforming Activity In Vivo Using Xenograft Systems 4.1. Overview The initial studies that led to the realization of vGPCR as a putative oncogene were performed using mouse xenograft models (Bais et al., 1998). This method still remains the gold standard to evaluate transforming potential in vivo, while also provides a simple model, albeit with limitations, to screen for potential therapeutic targets.


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4.2. Procedure SVEC cells lines were used to induce endothelial tumor xenografts in athymic mice as described previously (Montaner et al., 2003). Female athymic (nu/nu) nude mice (Harlan Sprague-Dawley, Frederick, MD), 5 to 6 weeks of age and weighing 18 to 20 g, are routinely used in these studies, and are housed in appropriate sterile filter-capped cages and fed and watered ad libitum. Briefly, exponentially growing stable cultures of vGPCR expressing cells are harvested, washed, and resuspended in DMEM. One million viable cells are transplanted subcutaneously into both flanks of the athymic mice. Normally, SVEC-vGPCR induced tumors progress slowly, within 1 to 2 months. For tumor growth analysis, tumor weight is determined as described previously (Montaner et al., 2003), whereby tumor volume (LW 2/2, where L and W represent the length and the width of the tumor) is converted to weight (milligrams) assuming unit density. Alternatively, we have begun to use cell lines expressing the red-shifted GFP derivative mCherry and firefly luciferase. These cell lines allow for careful quantitative analysis of the tumor volume and ‘‘metabolic status’’ using bioluminescence detectors such as the Xenogen IVIS Lumina II. Because steady production of mCherry and luciferase is associated with normal metabolism of these cells, the analysis of these two markers allows for early visualization of changes in tumor status before apparent changes in tumor volume occurs, for example when evaluating small molecule inhibitors of tumor growth. Regardless of the method used for evaluation, the animals are monitored twice weekly for tumor volume. Results of animal experiments are normally expressed as mean standard error, and the unpaired Student’s t test is used to determine the difference between experimental and control groups for each of the cell lines.

5. In Vivo Targeted Infection Using the TVA-RCAS System 5.1. Overview The limitations in the tumorigenicity studies using xenograft models can be overcome with the use of the RCAS system (Hughes, 2004). This system allows the expression of genes in mammalian cells in vivo through specific somatic infection and requires two components. It involves the use of an avian retrovirus derived from the Rous sarcoma virus (RSV), a member of the family of avian sarcoma-leukosis viruses (ASLVs) and a cell surface glycoprotein, TVA, which serves as receptor for this virus, thereby enabling viral infection (reviewed in Fisher et al., 1999). Because TVA is only expressed in avian cells, the virus is unable to infect mammalian cells.

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However, it is possible to express this molecule as a transgene, thus enabling specific infection, which will be restricted to the cell types or tissues expressing Tva. To study the role of vGPCR in KS pathogenesis in vivo, we developed a RCAS-based retroviral gene transfer system to specifically express this KSHV oncogene in mouse endothelial cells (Fig. 6.1). We engineered transgenic mice to express the avian retroviral receptor, Tva, under the control of the vascular endothelial cell-specific TIE2 promoter (Montaner et al., 2003). Indeed, expression of this receptor is exclusively detectable in endothelial cells (Montaner et al., 2003). RCAS retroviral vector encoding vGPCR are generated using standard cloning techniques, and viral production is performed on the chicken fibroblast cell line DF-1.

5.2. Procedure For the generation of an endothelial-specific TVA-expressing transgenic line, the TIE2-Tva transgene was created by insertion of the pg800 tva cDNA as a NotI fragment into a bluescript SK (þ) vector containing the murine 2.1-kb HindIII TIE2 promoter fragment and SV40 poly (A) signal sequence (Montaner et al., 2003). The plasmid also included, downstream of the tva cassette, a 10-kb autonomous endothelial-specific enhancer located in the first intron of the mouse TIE2 gene, which allows specific and uniform gene expression to all vascular endothelial cells in vivo. Transgenic mice are generated in FVB/N mice using standard techniques and identified by Southern blot using the Tva cDNA as a probe. Genotypes are determined by Southern blotting and by PCR with tail DNA.

5.3. Viral production RCAS vectors are replication-incompetent in mammalian cells; however, they are competent for replication in avian cells. This property enables very efficient viral production upon transfection of the RCAS vector or by viral infection of available stocks in avian cells. Eventually all cells become infected and start producing viruses, reaching titers as high as 1011 infective units (i.u.) per milliliter in concentrated stocks. A simple protocol for viral production follows. DF-1 chicken fibroblasts are maintained in DMEM with high glucose and sodium pyruvate, supplemented with 10% FBS and 1% penicillin/streptomycin. DF-1 cells are transfected using ExGen 500 reagent (Fermentas) with RCAS vectors to produce recombinant viruses. It is always advisable to produce RCAS GFP viruses in parallel, as they can be easily monitored by fluorescence microscopy, and thus serve as positive controls for viral production and titration. Initially transfection efficiency is normally low, at less than 20%; however, due to the replication of the virus in the transfected cells most cells are actively producing virus in 3 to 4 days. Cell cultures have to be actively expanded and split as necessary,

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RCAS viral production RCAS (avian retrovirus)

RCAS vector Transfection

Retroviral stocks 2 weeks

DF-1 cells TIE2-TVA mouse

Endothelial cellspecific gene transfer vGPCR

TVA

Endothelial cell

MAPK Akt p38 NFκB

IL8 VEGF SDF-1

Multiple signaling events paracrine transformation spindle cell growth angiogenesis Kaposi’s sarcomagenesis

Figure 6.1 Overview of the RCAS system. The two components of the RCAS system are depicted in the figure. A recombinant avian retrovirus (RCAS) is produced in DF-1 chicken fibroblast. Somatic expression of genes of interest, such as vGPCR, in mice is achieved by the tissue-restricted transgenic expression of the glycoproteinTVA, which acts as a receptor for avian leukosis^derived retroviruses. In particular, the expression of TVA in endothelial cells using the Tie2-TVA transgenic animal system enables the endothelial-specific expression of vGPCR and other genes of interest in vivo in a highthroughput fashion.

as retroviruses can only infect cells undergoing division. Once all the cells are producing virus (as judged by GFP fluorescence), let the cells reach confluence, wait an additional 48 h, and collect cell-free viral supernatants. Supernatants can be immediately used, frozen, or combined for concentration. For concentration, 30 ml of virus-containing supernatant are ultracentrifuged in an SW28 Beckman (Fullerton, CA) rotor at 22,000 rpm at 4 for 2 h. Pellets are resuspended in 1/100 of the original volume in PBS and viral titers are determined by limiting dilution. Briefly,

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mammalian TVA-expressing cells, such as SVEC-TVA cells, are seeded into six-well culture dishes at 30% confluence and infected with serial 10-fold dilutions of concentrated viral supernatants in growth medium. Cell numbers expressing the retroviral-transduced proteins are determined by immunofluorescence, and viral titers expressed as the number of infective units (i.u.) per milliliter. Viral stocks are injected intraperitoneally into 5-day-old FVB/TIE2-Tva littermates (100 ml/mouse) at the indicated viral load. Mice are genotyped at 21 days of age. Depending on the viral titer, animals could die within the first 2 months after infection, displaying multiple hemorrhages and small angioproliferative lesions. If titer is low enough for the animals to survive (approximately 105 i.u.), KS-like lesions will develop within the first year, normally appearing after 6 months.

6. vGPCR-Induced Paracrine Transformation 6.1. Overview KS lesions are characterized histologically by predominant proliferating spindle cells, angiogenesis, erythrocyte-replete vascular slits, profuse edema, and a variable inflammatory cell infiltrate (Schwartz et al., 2008). The presence of KSHV-infected cells increases as the lesion progresses, but many cells including some of the dominant spindle cells present in KS lesions remain uninfected even in advanced lesions (Chiou et al., 2002), while displaying a transformed phenotype. vGPCR is considered a lytic gene, but its powerful KS-driving properties are evident in spite of the fact that the expression of this receptor is restricted to a small percentage— between 1 and 5%—of the cells in human lesions. The origin of these few vGPCR-expressing cells could be due to a basal level of viral replication, an aborted lytic cycle, or dysregulated expression of vGPCR (Nador et al., 2001; Sodhi et al., 2004a). In an effort to mimic the cellular composition of human KS lesions in our animal xenograft model, we generate mixed populations using a small percentage of the cells expressing vGPCR while the majority express three of the major latent transcripts, namely, LANA, vFLIP, and vCyclin (Fakhari and Dittmer, 2002). While the oncogenic potential of these genes is the focus of intense debate, when coexpressed in SVEC cells, they do not induce cellular transformation and do not form tumors in xenograft models (Montaner et al., 2003). However, in the presence of 10% SVEC-vGPCR cells and their induced secreted factors, these cells initiate an exuberant proliferation becoming tumorigenic through a process known as paracrine transformation.


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6.2. Procedure For the generation of the SVEC line expressing the three latent transcripts, we first generated a line expressing vFLIP and vCyclin, as both are expressed as a naturally occurring bicistronic mRNA. Once a stable pool of clones was selected and characterized, cells were submitted to a second round of transfection with a LANA expression vector cotransfected with 1:10 of the total DNA of a vector encoding a different resistance gene than the one used in the first place. To reconstitute the cellular composition of human KS in mice, 1 105 SVEC-vGPCR cells are combined with 9 105 SVEC LANA/vFLIP/vCyclin cells prior to injection into female (nu/nu) athymic mice. As a negative control, SVEC-vGPCR cells can be substituted by inactive mutant vGPCR (vGPCRD5) or the parental cell line (Montaner et al., 2003). The animals are monitored twice weekly for tumor formation for 3 months. For analysis, tumor weight is determined by converting tumor volume (LW2/2) (where L and W represent longest length and shortest width of the tumor) to weight.

7. Characterization of vGPCR-Induced Molecular Signaling 7.1. Outline Characterization of the molecular responses elicited by vGPCR is essential to understand its role in KS initiation and progression. A number of methods have been used to study the cellular signaling triggered by the expression of this receptor. Initial studies showed that unlike its closest homolog, CXCR2, this receptor requires no ligand binding to activate a number of signaling events (Arvanitakis et al., 1997). However, vGPCR still retains the ability to bind a number of molecules, further modulating its intrinsic activity and include IL8, Groa and several other CXC and CC type chemokines (Rosenkilde et al., 1999). A simple method to evaluate the activity of the receptor is the analysis of second messengers and activated signaling molecules after transient transfection of the receptor. However, large overexpression of vGPCR can be toxic to cells, including those of endothelial and fibroblastic origin. To perform transient transfection experiments, it is therefore advisable to initially evaluate a range of concentrations of vGPCR expression vectors (dose–response) for every cell line. Most classical vGPCR activity experiments have been performed using COS-1 and COS-7 cells in addition to NIH 3T3 fibroblasts, but other cell lines such as the murine immortalized endothelial cell line SVEC 4-10 can be also used.

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8. Evaluation of Activation of Second-Messenger–Generating Systems 8.1. Overview The accumulation of second messengers is an early event in the signal transduction induced by GPCRs. In particular, vGPCR strongly stimulates phosphatidylinositol bisphosphate (PIP2) hydrolysis upon expression. Gaq proteins, when triggered by receptors, activate the plasma-membrane– bound enzyme phospholipase C-b (PLC) (Sternweis and Smrcka, 1992). This enzyme hydrolyzes PIP2 in the plasma membrane to release inositol 1,4,5-trisphosphate (IP3). This molecule is labile, being quickly hydrolyzed to two inositol phosphate subproducts, IP2 and IP1. Part of the IP3 generated binds to specific receptors on the endoplasmic reticulum, which induce opening of calcium-release channels (Berridge, 2005). This quickly raises the concentration of Ca2þ ions in the cytosol, causing a burst of ionic calcium that will lead to the activation of important effectors such as PKC or the NFAT transcription factor (Berridge, 2005; Crabtree and Olson, 2002). The following procedure is based in the purification and measurement of inositol produced in response to vGPCR expression from a radiolabeled precursor.

8.2. Procedure To measure inositol phosphate levels in transiently transfected cells, perform transfections in 12-well plates using increasing amounts of a vGPCR expression vector and a GFP or other fluorescent protein–encoding plasmid to assess for efficiency of transfection and vGPCR-induced toxicity. DNA amounts should be maintained constant by the addition of empty expression vector. The transfection method should be optimized beforehand for every particular cell type. We have successfully transfected a number of cell lines, including COS-7, NIH 3T3, and SVEC using the ExGen500 reagent (Fermentas, Burlington, Ontario). Briefly, dissolve 2 mg of the DNA mixture in 100 ml of 150 mM NaCl, and add 6.6 ml of ExGen500 reagent, mix by vortexing and incubate for 10 min at room temperature. Add complexes drop-wise to the wells and swirl to ensure appropriate distribution. Incubate the cells for 12 to 16 h before removing complexes, and label the cells by adding fresh complete medium containing 1 mCi/ml myo-[3H]-inositol (DuPont/NEN, Boston, MA), incubating for an additional 24 h. Remove and safely discard the media, rinse once with warm PBS, and replace with prewarmed serum-free medium containing 10 mM HEPES, pH 7.4, and 10 mM LiCl, an inhibitor of inositol phosphatases. Cells are collected at different time points (usually 10 min to 1 h), rinsed once with ice-cold


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PBS, and then the reaction is halted by addition of 1 ml ice-cold trichloroacetic acid (TCA) in each well. Water-soluble [3H]-inositol phosphates are separated from unincorporated [3H]-inositol using anion-exchange chromatography on Dowex-Cl columns (Mallinckrodt Baker, Phillipsburg, NJ) and measured using scintillation counting as described (Gutkind et al., 1991).

9. Activation of Signal-Transducing Protein Kinases and Small GTPases vGPCR activates a number of mitogenic and stress pathways including the PI3K/Akt, MAPK, and p38 pathways leading to increased survival, proliferation, and production of secreted factors (Bais et al., 1998; Dadke et al., 2003; Montaner et al., 2001; Sodhi et al., 2000, 2004a). In addition, vGPCR also activates the small G protein Rac1, which has been shown to play a role in vGPCR-induced sarcomagenesis (Montaner et al., 2004).

10. Akt Kinase Assay 10.1. Overview While there are a number of techniques that have been traditionally used to study the activation of kinases, the widespread availability of phosphospecific antibodies has relegated most of them to a second option. Nonetheless, in vitro kinase assays are still considered the gold standard to assess kinase activity, and we have used them successfully to analyze the activation of Akt and MAPK in response to vGPCR expression (Bais et al., 1998; Montaner et al., 2001).

10.2. Procedure To assay for Akt activation induced by vGPCR, split COS-7 1:5 in 10% fetal bovine serum containing DMEM the day previous to transfection. Transfect cells using ExGen500 reagent (see above) with a cocktail containing 0.5 mg pCEFL-HA-Akt1 (or other epitope-tagged Akt expression vector) plus increasing concentrations of a vGPCR-encoding vector, normalizing DNA amounts to 10 mg per plate using empty vector. It is recommended to also add 1 to 2 mg of a GFP encoding vector to monitor efficiency of transfection and toxicity. Incubate the cells with transfection complexes for 24 h, and then starve cells in serum free medium for 16 h, or alternatively, 4 h, if cells are too sensitive to starvation. Discard medium and

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wash with cold PBS twice, making sure to aspirate as much PBS as possible. Add 1 ml (for a 10 cm plate) or 600 ml (for a 6-cm plate) of cold lysis buffer (1% triton X-100, 10% glycerol, 137 mM NaCl, 20 mM Tris-HCl, pH 7.5, 1 mg/ml aprotinin and leupeptin, 1 mM PMSF, 20 mM NaF, 1 mM NaPPi, and 1 mM of freshly prepared Na3VO4). Scrape cells and transfer to Eppendorf tubes. Shake 10 min at 4 (vortexing 30 s also works). Clear the samples by centrifugation at 12,000g, for 10 min at 4 . This will sediment unbroken cells, membranes, mitochondria, and nuclei. Transfer cleared supernatant to new tubes containing 1 ml of anti-HA antibody (12CA5 clone, Covance, Princeton, NJ). Transfer the samples to an orbital rocker and leave rocking at 4 for 2 h. Add 20 ml of a 50% slurry of Gammabind Protein-G sepharose beads (GE Healthcare, Piscataway, NJ). Rock the samples for an additional 1 h at 4 . Centrifuge at 12,000g for 15 s. As the beads loosely pack at the bottom of the tube, use a micropipette instead of suction to carefully remove the supernatant and discard. Resuspend in 1 ml of cold lysis buffer and centrifuge again. Wash the beads twice with 1 ml cold lysis buffer. Wash once with 1 ml cold water and finally wash once with 1 ml ‘‘cold’’ kinase buffer (1 kinase buffer: 20 mM HEPES, pH 7.4, 10 mM MgCl2, 10 mM MnCl2, prepared as a 10 stock) and carefully remove all supernatant. For the kinase reaction, resuspend beads in 25 ml of 1 complete ‘‘hot’’ kinase buffer (supplement 1 kinase buffer with 0.05 mg/ml histone H2B substrate, 5 mM ATP, 1 mM DTT, and 10 mCi of [g32P]-ATP). Shake 30 min at room temperature (30 min at 30 also works). Terminate the reaction by adding 5 ml of 5 protein loading buffer, boil, and load into a 15% SDS-PAGE acrylamide gel including the beads. Transfer gel to Immobilon-P membranes (Millipore, Billerica, MA) and expose the area containing the substrate H2B, around 15 kDa. Confirm by Western blot the presence of immunoprecipitated HA-Akt (around 60 kDa, but note that it runs very close to the IgG heavy chain).

11. vGPCR Stimulated Activation of Rac1-Pulldown Assays 11.1. Overview The principle of the assay depends on the ability of active, GTP-bound form of Rac1, to interact with the Rac1 binding domain on the N-terminal portion of PAK1 (PAK-N) expressed as a glutathione-S-transferase fusion protein (Montaner et al., 2004; Tan et al., 2006). The PAK-N-GST protein is first expressed in bacteria and the recombinant protein is isolated with glutathione-sepharose beads. These beads are then used to capture the active form of Rac1 from lysates of vGPCR expressing COS-7 cells, and the


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fraction of active Rac1 is detected by Western blotting having as a reference the amount of Rac1 detected in parallel in total cell lysates.

11.2. Procedure Preparation of PAK-N beads The expression vector pGEX encodes the glutathione S-transferase (GST) fusion protein with the isolated GTP-dependent binding domain of the Rac1 effector PAK1 (Teramoto et al., 1996). Transform BL21 Escherichia coli with GST-PAK-N and plate the bacteria on LB-agar containing 50 mg/ml ampicillin. Pick a colony of GST-PAK-N–transformed BL21 cells and start a liquid culture in 5 ml of LB-ampicillin, leave overnight at 37 with constant shaking. On the following day, transfer the culture into a 1-1 bottle containing 250 ml of LB-ampicillin, and leave 2 to 3 h at 37 with constant shaking. Add 0.2 mM IPTG (isopropyl b-D-thiogalactopyranoside, Sigma, cat. no. I-5502, prepare a 200-mM stock in water and keep it frozen in small aliquots), transfer the culture to room temperature and leave it overnight with constant shaking. Harvest the bacteria by centrifugation and resuspend in 10 ml of ice-cold PBS-Triton-EDTA including protease inhibitors (1% Triton X-100, 1 mM EDTA, 1 mM PMSF, 10 mg/ml each aprotinin and leupeptin). Transfer the lysates to a 50-ml polypropylene centrifuge tube and freeze-thaw three times by immersing in an ethanol dry-ice bath followed by thawing in cold water. Keep the lysates on ice and sonicate three times for 10 s each to disrupt genomic DNA. Centrifuge at 14,000 rpm (Beckman JA-17 Rotor or equivalent). In the meantime prepare 250 ml of glutathione-sepharose beads (GE Healthcare cat. no. 17-0756-01 or similar) by washing them with PBS-Triton-EDTA. Transfer the supernatant of the lysates to a 15-ml tube and incubate with the beads for 30 min at 4 with constant shaking. Centrifuge at 4 for 1 min at 3000 rpm. Resuspend the beads in PBS-Triton-EDTA containing protease inhibitors, transfer to a microcentrifuge tube, and wash three times; resuspend the beads each time by vortexing, and spin down briefly. Wash three times with PBS containing protease inhibitors and resuspend in 500 ml of this buffer. For the experiment, use 50 ml of resuspended beads per sample. We prefer to keep the beads at 4 and use them within a week. Experiment Transfect COS-7 cells with wildtype vGPCR or a mutant inactive form such as vGPCR R143A to be used as a negative control. The day after transfection leave the cells in serum free media and process the experiment the following day. Wash once with ice cold PBS and keep the plates on ice from that point on, and use ice-cold buffers. Lyse the cells at 4 with 1 ml of a buffer containing 50 mM Tris, pH 7.5, 0.15 M NaCl, 1% Triton X-100, 5 mM EDTA, 10 mM MgCl2, 10 mg/ml aprotinin, 10 mg/ml leupeptin, and

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1 mM phenylmethylsulfonyl fluoride. Transfer the lysates to microcentrifuge tubes, centrifuge at 14,000 rpm for 5 min at 4 , and transfer the supernatants to new tubes for the isolation of GTP-Rac1 and 75 ml to a second set of tubes for total cell lysates. Incubate the cell lysates with 50 ml of GST-PAK-N beads (vortex briefly before taking the indicated volume), leave at 4 for 30 to 45 min in an orbital rocker, wash three times with lysis buffer, vortex, and spin down briefly for each wash. Detect the active GTP-bound form of Rac1 associated with GST-PAK-N and the total Rac1 in cell lysates by Western blot analysis using a monoclonal antibody against Rac1 (Santa Cruz Biotechnology).

12. Western Blotting Using Phospho-Specific Antibodies 12.1. Overview In most cases the activity of signal-transducing kinases is regulated by phosphorylation on specific residues. In addition, when a specific substrate has been defined for a particular kinase, its activity can be determined by analyzing the status of phosphorylation of its cellular substrates or direct targets. Western blotting with phospho-specific antibodies for the most relevant kinases and their substrates provides a very fast and convenient alternative to the classical kinase assays and is routinely used in most laboratories. We have used Western blot analysis of most mitogenic pathways to assess for the activity of vGPCR, with particular emphasis on the MAPK and PI3K/Akt/mTOR pathways (Montaner et al., 2001; Sodhi et al., 2000).

12.2. Procedure Cell and tissue lysates are prepared by incubation on an appropriate volume of SDS-lysis buffer (50 mM Tris-HCl, pH 7.4, 100 mM NaCl, 1 mM EDTA, 1% SDS, 2% Triton X-100, 1% b-mercaptoethanol). This buffer will extract and denature all the proteins in the cell but disrupts the nuclear membrane, provoking the release of genomic DNA that will increase the viscosity of the solution. Scrape the cells or grind the tissue in this buffer and transfer to Eppendorf tubes. Cutting the pipette tips to increase the diameter will ease pipetting into the tubes. Keep samples at 4 . Sonicate samples for 10 sec on ice with a tip sonicator (5 watts) to shear the DNA; avoid overheating the samples. The viscosity will be reduced after this procedure. Add 5 SDS-loading buffer and boil the samples. Resolve the samples by SDS-PAGE, transfer into Immobilon-P membranes (Millipore), and proceed with Western blotting. We normally block for 1 h in 5% non-fat dry


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milk in T-TBS (50 mM, Tris-HCl, pH 7.5, 150 mM NaCl, 0.05% Tween-20), followed by a 2-h to overnight incubation with primary antibody diluted in 0.5 to 5% BSA. Wash the membranes three times with T-TBS and incubate for 1 h with the appropriate HRP-conjugated secondary antibody (Southern Biotech, Birmingham, AL) diluted 1:30,000 in 5% milk in T-TBS. Wash three times for 10 min with T-TBS, and perform an enhanced chemiluminiscence reaction (Immobilon Western, Chemiluminiscent HRP substrate, Millipore, or related kits) for development following the manufacturer’s instructions. Primary antibodies are normally diluted at 1:1000 to 1:5000, but require individual optimization. Antibodies frequently used in our laboratory include phospho-specific rabbit monoclonal antibodies from Cell Signaling (Danvers, MA) including phospho-S6 S32, phospho-Akt S473, phospho-Akt T308, phospho-p70S6K T389, phospho-mTOR S2448, and phospho-p44/42 (Erk1/2). Many excellent antibodies for similar targets are also available from other companies, and should be evaluated.

13. Activation of Transcription Factors Changes in gene expression due to the activation or repression of transcription factors in the nucleus represent the ultimate target of molecular signaling events initiated by vGPCR expression. In particular, a number of transcription factors have been identified that are activated or repressed by vGPCR-stimulated pathways. They include AP-1, HIF-1, NFAT, FOXO, and NFkB, among others (Cannon et al., 2003; Martin et al., 2008; Sodhi et al., 2000). Our recent studies have been focused in the contribution and mechanism of activation of the NFkB transcription factor by vGPCR, as it plays a fundamental role in the production and secretion of numerous chemokines and growth factors implicated in the development of KS (Martin et al., 2008). Here, we provide methods that we use routinely to evaluate global changes in gene expression at the coarse level, as well as the fine detailed analysis of particular transcription factors.

14. Global Changes in Gene Expression: Microarray Analysis 14.1. Overview Generally speaking, gene expression profiling consists on the isolation of mRNA from test samples and controls, synthesis of fluorescently labeled cDNA and then hybridization onto a DNA or oligonucleotide microarray

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representing all or part of the genomic transcripts of a given organism. In recent years, a number of complementary platforms for gene expression analysis have rapidly evolved. Our first studies on vGPCR-induced transcriptional changes were conducted on custom-designed spotted long oligonucleotide arrays containing around 40,000 features. These platforms have been clearly surpassed by much more dense microarrays leveraging sophisticated on spot oligonucleotide synthesis with advanced quality control measures and highly optimized workflows. Several vendors offer very integrated platforms for genomics and gene expression profiling, with individual strengths and weaknesses. We provide here a method based on the gene expression platform from Agilent (Santa Clara, CA), but similar platforms from alternative vendors as Affimetrix, Illumina, or Nimblegen have been extensively used and provide perfectly valid alternatives. Due to the massive data generation capabilities of microarrays analysis, careful experimental design is a prerequisite for gene expression profiling. Sample replication is of paramount importance to determine the robustness of the subsequent analysis. We have learned that biological replicates (i.e., taking several independent replicates or repetitions of the same experimental point) are much more important than experimental replicates (i.e., repeating the microarray procedure for the same sample) and that three to four goodquality biological replicates provide sufficient statistical power to identify hundreds of genes with altered expression.

14.2. Procedure We provide here a brief summary of the steps that we follow routinely when performing microarrays in our murine endothelial cells. We systematically use Agilent’s supplied materials and reagents and follow the manufacturer’s protocols, as they have been extensively optimized for this particular application. Briefly, total RNA is extracted from exponentially growing SVEC lines serum starved for 16 h using GenEluteTM Mammalian Total RNA Miniprep Kit (Sigma-Aldrich, St. Louis, MO). Total RNAs are quality evaluated with Agilent 2100 Bioanalyzer normally discarding samples with RNA integrity number, RIN less than 7 (Schroeder et al., 2006). Labeled cDNA used as targets for hybridizations are synthesized by Quick Amp kit (Agilent Technologies, Palo Alto, CA) from total RNA samples and universal mouse reference (Stratagene, La Jolla, CA) in the presence of CyTM3 and CyTM5 reactive dye, respectively. The labeled probes are hybridized with oligonucleotide microarrays for 17 h at 65 . Slides are immediately scanned in an Agilent DNA Microarray Scanner. Spot quantification and data normalization are performed using Agilent’s Feature Extraction software and data analysis is performed on the TIGR Multi Experiment Viewer (TMEV) v4.1 platform (Institute for Genome Research, TIGR, Rockville, MD, http://www.tm4.org/).


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Our normal repertoire of analyses includes the significance analysis of microarrays (SAM) algorithm, cluster analysis, and Pavlidis template matching (PMT) analysis (see Martin et al., 2008), and are performed as implemented in TMEV v4.1 with settings left to default. For SAM analysis, the d-value is similar to the Student’s t. Briefly, SAM computes the mean value of each gene for each group and the values are submitted to a t-test (observed d-value). Gene values are then randomly iterated between samples and groups, and the test is repeated until all possible combinations are reached, typically more than 100, and the results are averaged (expected dvalue). If there is no significant difference between groups, the expected and observed d-values are similar. One of the advantages of this analysis is that it is possible to interactively adjust the statistical parameter ‘‘delta-value,’’ which defines the threshold of false-positives or ‘‘false discovery rate’’ (FDR) present in the gene list. In this statistical test, the q-value is defined as the FDR analogue of the p-value. The q-value of an individual hypothesis test is the minimum FDR at which the test may be called significant. To confirm the expression profiles of significant genes, quantitative RT-PCR is carried out in respective independent samples. In addition, we also routinely use Gene Set Enrichment Analysis (GSEA v2.0, Broad Institute, MIT) to tease out biologically meaningful information. GSEA is an algorithm that executes a weighted comparison of experimentally generated significant gene lists against a collection of metabolic and signaling pathways (Subramanian et al., 2005). These gene lists were gleaned from publicly available manually curated databases plus sets representing gene expression signatures of genetic and chemical perturbations that have been culled from experimental results in the literature. In this bioinformatic tool, each occurrence of a significant gene in any of the signature gene sets is counted as a hit toward that gene set. For example, the NFkB list includes genes that are involved in the activation of NFkB or are transcriptional targets of this transcription factor.

15. NFkB Luciferase Assays 15.1. Overview vGPCR promotes the activation of the NFkB transcription factor (Dadke et al., 2003; Martin et al., 2008; Montaner et al., 2004; Shepard et al., 2001). NFkB exists in an inactive form bound to the inhibitory IkB proteins in the cytoplasm. Activation of the regulatory IKB kinases (IKKa and IKKb) results in the degradation of the IkB proteins releasing the NFkB homoand hetero-dimers, which subsequently translocate to the nucleus where they activate appropriate target genes (Hayden and Ghosh, 2008). The assay to monitor this activity assesses the expression and function of reporter

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genes such as luciferase or chloramphenicol acetyl transferase (CAT), which are cloned in a plasmid downstream of the NFkB response element. The synthesis and activity of these enzymes reflects the activity of NFkB. In this section, we will describe the NFkB-luciferase assay as it is performed in SVEC 4-10 cells.

15.2. Procedure SVEC cells are split the day before so that they are 60 to 70% confluent at the time of transfection. Cells are transfected at least in triplicate, in 24-well plates using the ExGen500 reagent (Fermentas) with various quantities of empty vector or a vGPCR expression plasmid in combination with 100 ng of the NFkB luciferase reporter (Stratagene, La Jolla, CA) and 50 ng of pCEFLmyc hRL-EGFP, an EF-1a–driven humanized Renilla reniformis luciferase for normalization. Sixteen h after transfection, complexes are removed, and cells washed once with PBS and incubated for 24 h in serum-free DMEM. Extending the time after transfection before the luciferase assay is performed is not recommended, as this normally leads to increased background luciferase expression while not improving the induction of luciferase by vGPCR. Luciferase activity is detected using a DualGlo Luciferase Assay Kit (Promega, Madison, WI) and a microtiter plate luminometer (Dynex Tech, Chantilly, VA). Briefly, media is removed from the wells and the cells are washed once with PBS. Cells are lysed by incubation in 100 ml of 1 Dual-Glo luciferase reagent (diluted in DMEM) for 15 min at room temperature. Lysates are then transferred to a 96-well opaque microtiter plate, including blanks, and firefly luciferase activity is measured using a glow-type protocol. Once finished, 50 ml of Stop’n’Glo reagent are added to each well, and incubated for an additional 15 min. After that incubation, Renilla luciferase activity can be measured, again using a glow protocol. The normalized relative luciferase activity for each data point is obtained by dividing the firefly counts by the corresponding Renilla counts.

16. NFkB Binding Assays 16.1. Overview An alternative method for determination of transcription factor activation is the analysis of the binding of activated transcription factors to their cognate binding sequences. Homo- and hetero-dimers of members of the Rel/ NFkB family specifically recognize the 50 -GGGACTTTCC-30 nucleotide


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sequence (reviewed in Hayden and Ghosh, 2008; Karin, 2006). The p50/p65 heterodimers and the p50 homodimers are the most common dimers found in the NFkB signaling pathway (Karin, 2006). A traditional method for assaying these events are the electrophoretic mobility shift assays (EMSA), where cell lysates or nuclear extracts are incubated with radiolabeled oligonucleotides containing the binding sequence of the transcription factor of interest. After incubation, the samples are resolved by nondenaturing electrophoresis and autoradiography and analyzed for the presence of retarded, transcription factor–bound oligonucleotide bands. The identity of the transcription factor bound to the sequence is determined by super-shift assays, where the samples are incubated with the oligonucleotides in the presence of antibodies specific to the transcription factor of interest. This results in even higher retardation due to the increased molecular weight of the antibody-transcription factor complexes. Alternatively, a new type of transcription factor–binding assays are being developed based on an ELISA-like format, that do not require the use the radioactivity and inherently identify the bound transcription factor. In this case, samples are incubated in a 96-well plate coated with immobilized oligonucleotides containing the binding sequence and then the bound factors are detected with appropriate antibodies followed by ECL or chromogenic assays, thus providing quantitative results. We have successfully used these assays to quantify the activation of NFkB in response to vGPCR.

16.2. Procedure This procedure is based on the TransAM NF-kB p65 kit from Activemotif (Carlsbad, CA). The assay requires the preparation of nuclear extracts from transiently or stably vGPCR-transfected cells, serum-starved for 16 h prior to the experiment. As a positive control, cells treated for 1 h with 20 ng/ml of either TNFa or IL-1b could be used. For consistency, nuclear extracts are prepared using Nuclear Extract Kit (Active Motif ), and the assay is performed following the manufacturer’s recommendations. Briefly, proteins in nuclear extracts are quantified and 1 mg of total protein is incubated for 1 h in the presence of binding buffer to allow the binding of activated NFkB to the immobilized oligonucleotides in the well. Bound factors are washed three times and incubated in the presence of p65 antibodies for 1 h. Wells are washed again three times and incubated for an additional hour with a horseradish peroxidase (HRP)–conjugated secondary antibody. After washing the wells four times, a chemiluminescent reaction is used. Light emission is evaluated using a Dynex MLX system (Dynex Tech) luminometer.

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17. Nuclear Translocation of NFkB 17.1. Overview NFkB shuttles in and out of the nucleus depending on its association with the IkB proteins, thus regulating its activity. Free, active NFkB homo- and hetero-dimers quickly translocate to the nucleus. Immunohistochemistry for the presence of nuclear NFkB components provides an additional method to assess the early activation of this transcription factor in response to several stimuli, including vGPCR. Moreover, as opposed to the methods mentioned above this assay has the advantage that it can be used in paraffinembedded archived material, for example using normal and pathological tissues of diverse origin, without further manipulation and is easily quantifiable. We routinely assay for NFkB activation using antibodies against p65.

17.2. Procedure This procedure is meant to be used for formalin-fixed paraffin-embedded tissues of mouse and human origin, for tissue culture samples, see the following. Briefly, tissue slides are dewaxed in xylene, hydrated through graded alcohols and distilled water, and washed thoroughly with PBS. Antigen retrieval is done using 10 mM citrate buffer (pH 6) in a microwave oven for 20 min (2 min at 100% power and 18 min at 10% power). The slides are allowed to cool down for 30 min at room temperature, rinsed twice with PBS, and incubated in 3% hydrogen peroxide in PBS for 30 min to quench the endogenous peroxidase. The sections are then washed in distilled water and PBS and incubated in the blocking solution (5% bovine serum albumin in PBS) for 1 h at room temperature. Excess solution is discarded and the sections incubated overnight with primary antibody (rabbit polyclonal anti-p65, purchased from Neomarkers, Fremont, CA) diluted in 1:100 blocking solution at 4 . After washing with PBS, the slides are sequentially incubated with the biotinylated secondary antibody (Vector Laboratories, Burlingame, CA; 1:300) for 1 h, followed by the ABC complex (Vector Stain Elite, ABC kit, Vector Laboratories) for 30 min at room temperature. The slides are washed and developed in 3,3-diaminobenzidine (Sigma FASTDAB tablet, Sigma Chemical, St. Louis, MO) under microscopic control. The reactions are stopped by immersing the slides in tap water; the tissues are then counterstained with Mayer’s hematoxylin, dehydrated, cleared in xylene, and mounted. For immunofluorescence experiments using cell lines, cells are transfected in 35-mm dishes with the appropriate expression plasmids. After 8 h, cells are split and seeded onto collagen IV–coated glass slides and cultured for an additional 48 h. Cells are serum-starved for 16 h, washed once with


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cold PBS, and fixed in 4% paraformaldehyde in PBS for 10 min at room temperature. Cells are washed three times with PBS and permeabilized for 5 min with PBS containing 0.5% NP-40. Cells are washed again twice and incubated in blocking solution (3% BSA in PBS) for 20 min. Slides are incubated with primary antibody (rabbit polyclonal anti-p65, 1:100 in blocking solution) for 1 h at room temperature, washed three times, and incubated with appropriate secondary antibodies for an additional hour. Slides are washed once with PBS, nuclei stained with 1 mg/ml Hoechst 33258 in PBS for 5 min at room temperature, washed three times with PBS and once with distilled water, and mounted using Vectashield mounting medium (Vector Labs, Burlingame, CA). In both cases, activated NFkB can be visually scored and represented as a percentage of transfected cells showing nuclear staining with respect to the total cell number.

ACKNOWLEDGMENTS This research was supported by the National Institutes of Health Intramural AIDS Targeted Antiviral Program and the National Institute of Dental and Craniofacial Research.

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C H A P T E R

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Pharmacological and Biochemical Characterization of Human Cytomegalovirus-Encoded G Protein–Coupled Receptors David Maussang,*,1 Henry F. Vischer,*,1 Andreas Schreiber,† Detlef Michel,† and Martine J. Smit* Contents 1. Introduction 2. Virally Encoded GPCR Engineering 3. vGPCR Expression, Trafficking, and Radioligand Binding 3.1. Microscopic visualization of the cellular localization of vGPCRs 3.2. Enzyme-linked immunosorbent assay 3.3. Radioligand binding assays 3.4. Internalization assays 4. vGPCR-Induced Signal Transduction 4.1. Inositol phosphate production 4.2. Intracellular [Ca2þ] measurements 4.3. Reporter gene assays 5. vGPCR-Induced Oncogenesis 5.1. Cellular transformation: Foci formation assay 5.2. Cell proliferation assay: Cyclin D1 expression 5.3. In vivo xenograft models 6. Generation of Recombinant HCMV Strains by Markerless Bacterial Artificial Chromosome Mutagenesis 7. Conclusions Acknowledgments References

* { 1

152 154 156 156 156 157 159 159 159 160 160 162 162 163 164 165 167 167 167

Leiden/Amsterdam Center for Drug Research, Division of Medicinal Chemistry, Faculty of Sciences, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands Institute of Virology, Ulm University Clinic, Ulm, Germany Both authors contributed equally to this work


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David Maussang et al.

Abstract Human cytomegalovirus (HCMV) is a widely spread herpesvirus that can have serious consequences in immunocompromised hosts. Interestingly, HCMV genome encodes for four viral G protein–coupled receptors (vGPCRs), namely, US27, US28, UL33, and UL78. Thus far, US28 and UL33 have been shown to activate signaling pathways in a ligand-independent manner. US28 is the best characterized vGPCR and has been shown to be potentially involved in the development of HCMV-related diseases. As such, detailed investigation of these viral GPCR is of importance in order to understand molecular events occurring during viral pathogenesis and the potential identification of novel therapeutic targets. Herewith, we describe several approaches to study these HCMV-encoded vGPCRs. Using molecular biology, tags can be introduced in the vGPCRs, which may facilitate the study of their protein expression with various techniques, such as microscopy, Western blotting, enzyme-linked immunosorbent assay (ELISA), and flow cytometry. Furthermore, radioligand binding studies can be performed to screen for ligands for vGPCRs, but also to study kinetics of internalization. We also describe several signal transduction assays that can evaluate the signaling activity of these vGPCRs. In addition, we discuss different proliferation assays and an in vivo xenograft model that were used to identify the oncogenic potential of US28. The study of these vGPCRs in their viral context can be examined using recombinant HCMV strains generated by bacterial artificial chromosome mutagenesis. Finally, we show how these mutants can be used in several pharmacological and biochemical assays.

1. Introduction Human cytomegalovirus (HCMV), a member of the human b-herpesvirus family, also referred to as human herpesvirus-5 (HHV-5), is widely spread among the population. Although its presence is mostly asymptomatic in immunocompetent hosts, HCMV-positive immunosuppressed patients are at risk for the development of serious inflammatory diseases (SoderbergNaucler, 2006). Furthermore, HCMV has been linked to the development of proliferative diseases, such as colon cancer and glioblastoma (Cobbs et al., 2002; Harkins et al., 2002). While the Kaposi’s sarcoma–associated herpesvirus (KSHV) and the Epstein-Barr virus (EBV) are considered oncogenic viruses, HCMV appears to preferentially infect cancer cells to further increase their malignant phenotype (Cinatl et al., 2004). Interestingly, like other herpesviruses, the HCMV genome encodes viral G protein–coupled receptors (vGPCRs), referred to as US27, US28, UL33, and UL78, that appear on the surface of human cells upon viral infection (Fig. 7.1A) (Rosenkilde et al., 2008). Thus far, UL33 and US28 have been shown to constitutively activate various signaling pathways in a

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Characterization of HCMV-Encoded Viral GPCRs

A

Wild type US28

B g a b

HCMV

g a b Signaling

UL33

UL78

US27

US28

C

Δ2–22

R129A Human cell

US28 mutants g a b

g a b

Δ300

signaling

Figure 7.1 Expression and signaling of vGPCRs. (A) HCMV infection of human cells leads to the expression of the four viral GPCRUS27, US28, UL33, and UL78. (B) US28 signals both in a ligand-independent and -dependent manner and undergoes rapid constitutive internalization. (C) US28 mutants show different signaling and internalization properties than the wildtype receptor. US28-R129A does not couple to G proteins and presents no constitutive activity. D2-22-US28 still shows constitutive activity but can no longer bind chemokines. US28-D300 still binds chemokines and exhibits a higher constitutive activity due to a reduced internalization rate compared to the wildtype receptor.

ligand-independent manner (Casarosa et al., 2001, 2003a). The significance of vGPCR in viral pathogenesis is exemplified by the work on the KSHVencoded GPCR ORF74. This receptor possesses constitutive activity as well as ligand-induced signaling properties. In vitro assays first demonstrated the transforming properties of ORF74 (Bais et al., 1998), and development of transgenic animal models confirmed the ability of ORF74 to induce Kaposi’s sarcoma–like diseases (Yang et al., 2000). As such, the KSHVencoded vGPCR was revealed to be a key player in viral diseases and highlights the importance of vGPCRs in the pathologies of herpesviruses. Among the four vGPCRs encoded by HCMV, US28 is the most extensively studied. US28 binds several chemokines from the CC and CX3C families and was suggested to act as a chemokine sink (Bodaghi et al., 1998; Kledal et al., 1998). In addition, US28 constitutively activates the phospholipase C and the NF-kB transcription factor (Fig. 7.1B) (Casarosa et al., 2001). Based on these findings, a potential involvement of US28 in HCMV-related diseases has been suggested. For instance, ligand stimulation of US28 showed that it can induce migration of smooth muscle cells, providing a rationale for the implication of US28 in the pathogenesis of cardiovascular diseases (Streblow et al., 1999). We also demonstrated that the constitutive activity of US28 is responsible for the formation of tumors in a xenograft model, implying that US28 may be an oncomodulatory viral protein (Maussang et al., 2006). Studies of the other HCMV-encoded

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GPCRs are still required to elucidate their role during viral infection and their importance in the development of viral diseases. In this chapter, we describe several techniques that can be applied to study virally encoded GPCRs in more detail. Various research questions can be addressed using molecular, cellular, as well as viral techniques.

2. Virally Encoded GPCR Engineering The HCMV-encoded GPCR US28 displays ligand-dependent and -independent signaling properties, possesses a broad spectrum of chemokine binding capacity and shows constitutive internalization (Vischer et al., 2006). UL33 signals and internalizes in a constitutive manner, while US27 and UL78 appear silent. All three vGPCRs are thus far orphans since no ligands have been found to bind these receptors. In order to dissect the contribution of chemokine binding, various US28 mutants were generated (Fig. 7.1C). Truncation of the N-terminus of US28 by deleting amino acid residues 2-22 (i.e., D(2-22)-US28) results in a mutant incapable of binding chemokines but that still presents constitutive activity (Casarosa et al., 2003b; Stropes and Miller, 2008). Ala-substitution of the Arg3.50/129 of the conserved DRY motif at the bottom of transmembrane helix 3 (i.e., US28-R129A) impairs G protein–mediated signaling without affecting chemokine binding and constitutive internalization (Stropes and Miller, 2008; Waldhoer et al., 2003). Constitutive receptor phosphorylation and internalization is attenuated by Ala substitution of all Ser and Thr residues in the intracellular C-terminal tail or truncation of this domain by deleting the last 54 amino acid residues (i.e., US28-D300) (Miller et al., 2003; Mokros et al., 2002; Waldhoer et al., 2003). Since high-quality antibodies against the majority of GPCRs, including the HCMV-encoded receptors, are not available, N-terminal epitopetagged receptors, among others, are generated. Tags such as hemaglutinin, FLAG, or c-myc, are used to allow detection of expression of vGPCRs with commercially available high-affinity antibodies in different assays such as microscopy, Western blotting, fluorescent-activated cell sorting (FACS) analysis, or enzyme-linked immunosorbent assay (ELISA) (McIlhinney, 2004). Various epitope tags have been successfully fused to the N-terminus of US28 (Casarosa et al., 2003b; Fraile-Ramos et al., 2002; Miller et al., 2003; Waldhoer et al., 2003), US27 (Fraile-Ramos et al., 2002), and UL33 (Margulies et al., 1996). Alternatively, engineered variants of green fluorescent protein (GFP) from the jellyfish Aequorea victoria have been genetically fused, in frame, by replacing the stop codon to the C-terminus of HCMV-encoded GPCRs, allowing localization studies by means of fluorescent (confocal) microscopy (Fraile-Ramos et al., 2001, 2002;

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Stropes and Miller, 2008; Waldhoer et al., 2002, 2003). The most optimal tag needs to be empirically determined for each receptor and should not interfere significantly with ligand binding, receptor signaling, and expression. Various methodologies can be used to introduce site-directed mutations or epitope tags, or to generate fusion proteins (Blomenro¨hr et al., 2004; McIlhinney, 2004). Nonetheless, PCR-based approaches using highfidelity DNA polymerase (e.g., Pfu) can be used universally to generate all these different constructs. Short N-terminal tags are introduced after the initial methionine of a vGPCR by using chimeric forward primer (Tf ), consisting of the tag-encoding sequence at the 50 end and a fully complementary GPCR-specific sequence at the 30 end, in combination with a reverse open-reading frame (ORF) primer (Or) in a single PCR (Fig. 7.2A). Site-directed mutations are introduced using a three-step PCR strategy (Fig. 7.2B). In the first PCR, the 50 - and 30 -end cDNA fragments are generated in parallel by using overlapping reverse (Mr) and forward (Mf ) mutation primers in combination with forward (Of ) and reverse (Or) ORF primers, respectively. The two PCR fragments are then fused in a selfprimed PCR, taking advantage of the introduced overlapping sequences. Next, the fusion products are amplified in a third PCR using the primers Of and Or (Blomenro¨hr et al., 2004). In principle, this three-step PCR approach can also be used to generate GPCR–GFP fusion proteins. However, such fusion proteins are more easily generated by substituting the stop B

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Figure 7.2 Generation of mutated vGPCR using polymerase chain reactions. (A) N-terminal tagged GPCR are created by PCR using a forward primer (Tf ) containing the tag-encoding sequence at the 50 -end and a fully complementary GPCRspecific sequence at the 30 -end, in combination with a reverse open-reading frame (ORF) primer (Or). (B) Three-step PCR strategy for the creation of a point mutation. In the first PCR, the 50 - and 30 -end cDNA fragments are generated in parallel using overlapping reverse (Mr) and forward (Mf ) mutation primers in combination with forward (Of ) and reverse (Or) ORF primers, respectively.The two PCR fragments are then fused in a self-primed PCR, taking advantage of the introduced overlapping sequences. Next, the fusion products are amplified using the primers Of and Or.

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codon of the GPCR with a restriction-endonuclease (RE) site, which is also introduced at the 50 end of the GFP-encoding cDNA. The GPCR–GFP fusion protein is then generated by ligation of both cDNAs.

3. vGPCR Expression, Trafficking, and Radioligand Binding 3.1. Microscopic visualization of the cellular localization of vGPCRs HEK 293T or COS-7 cells that are transiently transfected with vGPCRGFP fusion protein constructs using 25-kDa linear polyethylenimine (PEI) or DEAE-dextran, respectively (Casarosa et al., 2005; Verzijl et al., 2008), are grown on poly-L-lysine–coated coverslips. Cells are washed with phosphate-buffered saline (PBS) and subsequently fixed with 4% paraformaldehyde in PBS for 10 min at room temperature. Next, the cells are mounted in Vectashield mounting medium (Vector Laboratories) and analyzed using a confocal laser scanning microscope (e.g., Zeiss LSM 510) with excitation at 505 nm and emission at 530 nm.

3.2. Enzyme-linked immunosorbent assay An ELISA can be used to monitor membrane and intracellular expression of vGPCRs. HEK 293T or COS-7 cells transfected with epitope-tagged GPCRs are seeded in poly-L-lysine–coated 24-well plates (2.5 105 and 1.5 105 cells/well, respectively). The next day, cells are fixed using 4% paraformaldehyde in PBS. Samples are then washed with Tris-buffered saline (TBS). Half of the wells can be permeabilized with 0.5% Nonidet P-40 in TBS to detect intracellularly localized GPCRs. After blocking nonspecific sites with 1% nonfat-dried milk in 0.1 M NaHCO3, pH 8.6, for 1 h, cells are incubated with the anti-epitope tag antibody in TBS containing 0.1% BSA for 1.5 h at room temperature or overnight at 4 C. Next, the cells are washed three times with TBS, and incubated with the appropriate horseradish peroxidase–conjugated secondary antibody in 1% nonfat-dried milk in 0.1 M NaHCO3, pH 8.6, for 1.5 h at room temperature. Unbound antibodies are washed away with TBS and peroxidase activity is visualized using 3,30 ,5,50 -tetramethylbenzidine liquid substrate system (Sigma-Aldrich). Reactions are terminated by adding 0.5 M H2SO4, and absorption is measured at 450 nm using a Victor2 1420 multilabel plate reader (Fig. 7.3A).

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−12 −11 −10 −9 −8 Log [CX3CL1]

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Figure 7.3 US28 protein expression and internalization in transfected cells. (A) Hemagglutinin-tagged US28 (HA-US28) encoding plasmid is transfected into HEK 293T cells. Twenty-four hours later, the epitope-tagged protein is detected using an ELISA assay against the HA tag. (B) Radiolabeled [125I]-CX3CL1 binds to US28-expressing membranes. Cold CX3CL1 displaces the radioligand in a dose-dependent manner down to the level observed in membranes prepared from mock-transfected control cells. (C) Internalization studies indicate that US28 rapidly internalizes radiolabeled chemokines as soon as 5 min after their addition at 37 C.

3.3. Radioligand binding assays Direct interactions between chemokine ligands and US28 can be quantified using radioligand binding studies. Radiolabeled human chemokines (125I) are commercially available from PerkinElmer or can be iodinated in-house using Pierce iodination reagent or Bolton-Hunter reagents (Daugherty et al., 2000). Three distinct types of radioligand binding experiments can be performed: kinetic, saturation, and competition binding (Bylund et al., 2004). Kinetic binding experiments measure the rate of ligand-receptor complex formation and/or dissociation in time. Saturation binding

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experiments measure the equilibrium binding of increasing concentrations of radioligand and are used to determine the affinity (Kd) of the radioligand for a receptor and the number of receptors (Bmax) in a sample. In competition binding experiments, the equilibrium binding of a single concentration radioligand is measured in the presence of increasing concentrations of an unlabeled ligand, allowing determination of the affinity (Ki) of numerous unlabeled ligands for a receptor. Radioligand binding assays can be performed on intact cells or membrane preparations. Membrane preparations are commonly used in high-throughput drug screens, whereas the more cumbersome intact cell binding assays allows quantification of receptor cell surface levels and internalization kinetics. Membranes are prepared from, for example, US28-transfected HEK 293T or COS-7 cells. Two days after transfection, the cells are harvested in ice-cold PBS supplemented with 1 mM EDTA, and centrifuged at 1500g for 10 min at 4 C. Pellets are washed once in the same buffer and subsequently resuspended and homogenized in ice-cold membrane buffer (15 mM Tris, pH 7.5, 1 mM EGTA, 0.3 mM EDTA, and 2 mM MgCl2) using a motorized Teflon-glass homogenizer (10 strokes at 1200 rpm). Membranes are then subjected to two freeze–thaw cycles using liquid nitrogen and subsequently centrifuged at 40,000g for 25 min at 4 C. Pellets are washed once with ice-cold Tris-sucrose buffer (20 mM Tris, pH 7.4, and 250 mM sucrose), before being resuspended in the same buffer and frozen in liquid nitrogen. For competition binding experiments in 96-well microplates, 25 ml 125I-chemokine (0.25 nM/well) in binding buffer (50 mM Hepes, pH 7.4, 1 mM CaCl2, 5 mM MgCl2, 100 mM NaCl, and 0.5% BSA) are dispensed together with 25 ml of increasing concentrations unlabeled ligand in each well. Next, binding reactions are initiated by adding 50 ml of purified membrane (0.5– 10 mg membrane protein/well) and incubated for 2 h at room temperature with gentle agitation. The optimal amount of membrane protein and concentration of 125I-chemokine (0.3–0.7 Kd) need to be empirically determined in order to obtain a maximal detection window without binding more than 10% of the radioligand. Incubations are terminated by filtration through a UniFilter-96 GF/C (Perkin-Elmer) presoaked in 0.3% PEI, and subsequently washed with ice-cold binding buffer supplemented with 0.5 M NaCl using a Filtermate Harvester (Perkin-Elmer). Radioactivity is quantified by liquid scintillation using a Wallac MicroBeta TriLux (Perkin-Elmer). Next, radioligand binding is plotted as function of the logarithm of the unlabeled ligand concentration (Fig. 7.3B), and IC50 values are determined by nonlinear curve fitting using GraphPad Prism. The affinity of the unlabeled ligand (Ki) is calculated using the ChengPrusoff equation: Ki ¼ IC50/(1 þ [125I-chemokine]/Kd) (Cheng and Prusoff, 1973).


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3.4. Internalization assays US28 acts as a decoy receptor for many inflammatory chemokines by removing them from the microenvironment of HCMV-infected cells through rapid and constitutive internalization. As such, US28 may attenuate the inflammatory response by reducing the recruitment of chemokineresponding inflammatory cells (Billstrom et al., 1999; Bodaghi et al., 1998; Fraile-Ramos et al., 2001; Randolph-Habecker et al., 2002). Internalization kinetics can be monitored by quantification of 125I-chemokine uptake by US28-expressing cells. To this end, transiently US28-expressing HEK 293T (1.6 105 cells/well) are seeded in poly-L-lysine–coated 48-well plates. The next day, medium is aspirated and cells are incubated at 37 C with 0.25 nM 125I-chemokine in prewarmed binding buffer using time intervals ranging from 5 min to 1 h. Incubations are terminated by placing the plates on ice and immediately washing the cells three times with icecold binding buffer supplemented with 0.5 M NaCl. For each time point, total radioactivity was determined by collecting one set of cells in lysis buffer (0.5% Nonidet P-40, 0.1% sodium dodecyl sulfate, 0.5% deoxycholic acid), whereas a second set of cells was first incubated for 10 min in ice-cold acidified DMEM (pH 2.0) to remove surface-bound chemokine before being collected in lysis buffer. Control experiments revealed that the acidic incubation removed all surface-bound chemokine while leaving the receptor surface intact. Next, radioactivity in collected cell lysates is quantified using a Wallac Compugamma counter (PerkinElmer). The percentage of 125I-chemokine internalization is calculated for each time point using: internalization (%) ¼ (acid-resistant radioactivity/total radioactivity) 100 (Fig. 7.3C).

4. vGPCR-Induced Signal Transduction 4.1. Inositol phosphate production Both UL33 and US28 constitutively activate the enzyme phospholipase Cb to produce inositol triphosphate (InsP3) and diacylglycerol by hydrolyzing plasma membrane phosphatidylinositol 4,5-bisphosphates (PIP2). Prelabeling the cells overnight with myo-[2-3H]-inositol allows metabolic incorporation into PIP2. PLCb-catalyzed production of 3H-InsP3 is measured in the presence of lithium, which inhibits the rapid dephosphorylation of InsP to inositol, resulting in the accumulation of 3H-InsP (Huckle and Conn, 1987). HEK 293T (5 104 cells/well) or COS-7 cells (3 104 cells/ well) that are transiently transfected with US28 or UL33, or SVEC4-10 cells (5 104 cells/well) stably expressing US28 are seeded in poly-L-lysine– coated 96-well plates and incubated overnight in 100 ml/well, Earle’s inositolfree minimal essential medium (Invitrogen) supplemented with 10 mCi/ml

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myo-[2-3H]-inositol (17 Ci/mmol; GE Healthcare). Importantly, overnight labeling of HEK 293T cells requires the supplementation of medium with 10% fetal bovine serum. The next day, cells are washed with DMEM supplemented with 25 mM Hepes (pH 7.4) and 20 mM LiCl, and subsequently incubated in the same medium in the absence or presence of ligands at 37 C for 2 h. Incubations are terminated by aspiration of the medium, and cellular lipids are extracted from the cells using 10 mM formic acid. [3H]-InsP accumulation is then quantified using 0.5 mg/well YSi-RNA–binding SPA beads (GE Healthcare) in white clear-bottomed, 96-well isoplates using a Wallac MicroBeta Trilux counter (PerkinElmer) (Fig. 7.4A) (Brandish et al., 2003). This assay can be used for US28 to screen for inverse agonist properties of chemokine ligands, such as CX3CL1 or small compounds (Hulshof et al., 2006).

4.2. Intracellular [Ca2þ] measurements US28 induces a rapid transient increase in intracellular Ca2þ levels in response to CC and CX3C chemokines (Billstrom et al., 1998; Casarosa et al., 2005; Gao and Murphy, 1994). SVEC4-10 cells stably expressing US28 are seeded in clear-bottomed black 96-well plates (4 104 cells/well) (Casarosa et al., 2005). The next day, cells are loaded with 4 mM cellpermeant Fluo-4 acetoxymethyl ester (Invitrogen) in loading buffer (Hanks’ balanced salt solution supplemented with 20 mM Hepes, pH 7.4, 2.5 mM probenecid) supplemented with 0.04% pluronic acid and 1% BSA, for 30 min at 37 in the dark. Cells are washed twice and preincubated for 1 h at 37 in the dark in loading buffer supplemented with 0.1% BSA. Intracellular Ca2þ levels are monitored at 37 by measuring fluorescence (excitation at 485 nm and emission at 520 nm) with a Novostar microplate reader (BMG Labtechnologies GmBH, Offenburg) for 10 s to determine mean basal level. Next, the chemokine is injected and fluorescence is recorded for another 50 s, after which cells are lysed by adding 5% Triton X-100 to determine maximum fluorescence. Results are expressed as percentage of maximum fluorescence (Fig. 7.4B).

4.3. Reporter gene assays Reporter gene assays are commonly used to determine the signaling properties and functional effects of GPCRs. Whether their viral counterparts are constitutively active or can be stimulated with ligands (when known), the transcriptional activity or direct transcription of various cellular factors can be analyzed. Initial characterization of US28 and UL33 constitutive signaling properties was performed using NF-kB reporter gene assays (Casarosa et al., 2001, 2003a). This reporter gene plasmid encodes the luciferase gene controlled by five successive NF-kB–binding sites (Fig. 7.4C). As such,

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Figure 7.4 US28 signals in both a ligand-dependent and -independent manner. (A) US28-expressing SVEC 4-10 cells present a ligand-independent formation of inositol phosphate (InsP) compared to mock-transfected cells. Incubation of US28-expressing cells with CX3CL1 can partially inhibit this constitutive signaling. (B) Stimulation of SVEC 4-10 cells stably expressing US28 with CCL5 induces a transient increase in intracellular calcium signaling ([Ca2þ]i). (C) Schematic representation of the various transcription factor^binding sites controlling the luciferase gene in the NF-kB and the human vascular endothelial growth factor (VEGF) promoter reporter gene plasmids. (D) HEK 293T cells are transfected with the polyethylenimine (PEI) method with pcDEF3 plasmid either empty (control) or containing the sequence of US28 together with the reporter gene plasmid.The total amount of DNAwas kept constant at 2 mg per 106 cells. Plasmid DNA (1 mg reporter gene with 900 ng pcDEF3 and 100 ng pcDEF3 either with or without US28 sequence) is diluted in 75 ml of 150 mM NaCl solution and mixed with 75 ml 150 mM NaCl containing 6 mg PEI. HEK 293Tcells are harvested and resuspended in culture medium to a concentration of 0.5 106 cells per milliliter. Two milliliters of cell suspension are added to the DNA:PEI mixture, and100 ml of transfected cells are seeded per well of a white 96-well plate. Luminescence is measured 24 h later after transfection.

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upon activation of the NF-kB transcription factor, the luciferase gene is transcribed and expressed at the protein level. Alternatively, the activation of downstream target genes such as the vascular endothelial growth factor (VEGF) can also be quantified. In that case, the luciferase gene is controlled by the endogenous promoter of the VEGF gene that contains binding sites of various transcription factors (Fig. 7.4C). This method was used to assess the proangiogenic properties of US28 (Maussang et al., 2006). HEK 293T cells are transfected with control or US28 plasmids and with either the NF-kB reporter gene or the human VEGF promoter reporter gene using the PEI method. Twenty-four hours after transfection, cells are lysed and stimulated with Luciferin (0.83 mM ATP, 0.83 mM D-Luciferin, 18.7 mM MgCl2, 0.78 mM Na2H2P2O7, 38.9 mM Tris (pH 7.8), 0.39% (v/v) glycerol, 0.03% (v/v) Triton X-100 and 2.6 mM DTT), and light emission is quantified with a Victor2 (Fig. 7.4D). This method can be extended to other transcription factors such as cyclic AMP responsiveelement–binding protein (CREB), and nuclear factor of activated T cells (NFAT) (McLean et al., 2004), and alternatively, the luciferase gene can be replaced by the b-galactosidase reporter gene (Lim et al., 2006).

5. vGPCR-Induced Oncogenesis 5.1. Cellular transformation: Foci formation assay Cellular transformation induced by human or viral oncogenes is typically assessed using stably transfected NIH-3T3 cells. These mouse fibroblasts are on the verge of transformation and allow sensitive detection of oncogenic signals, resulting in cellular transformation. However, in order to ascertain the oncogenic properties of the studied proteins, mock-transfected cells always have to be taken as a negative control in the experiment to estimate the background activity. NIH-3T3 cells are transfected with a US28encoding plasmid using the calcium phosphate method (Chen and Okayama, 1988). This plasmid also contains the antibiotic-resistant gene neomycin, allowing the selection of geneticin-resistant US28-expressing cells. NIH-3T3 cells possess cell contact–inhibition properties that disable them to proliferate when entering in contact with adjacent cells within a cell monolayer. Upon transformation, cells lose this ability and uncontrolled growth of cells leads to formation of cell foci (Maussang et al., 2006). The transforming ability of US28-expressing NIH-3T3 cells is measured when cells are cultured together with native NIH-3T3 cells that still possess cell contact inhibition. The latter grow in a monolayer, while US28transformed cells grow on top of one another, leading to the formation of foci. To this end, 2 105 naive NIH-3T3 cells are cultured together with 2 103 mock or US28 stably transfected NIH-3T3 cells for 14 days in the

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absence of antibiotic selection. Medium is refreshed biweekly. To detect the formed foci, wash cells twice with PBS and twice with ice-cold methanol, and fix them with ice-cold methanol for 5 min. After washing the dish with distilled water, stain the cells with 0.4% methylene blue for a few minutes. Wash the dishes extensively with distilled water until the rinsing water does not appear blue. Foci are then counted in each sector (Fig. 7.5A).

5.2. Cell proliferation assay: Cyclin D1 expression US28-mediated signaling pathways upregulate the expression of cyclin D1 (Fig. 7.5B) that is involved in cell cycle progression and proliferation (Maussang et al., 2006). Control or US28 stably transfected NIH-3T3 cells are seeded in a six-well plate (3 105 cells per well) and cultured overnight in DMEM supplemented with 10% calf serum. The following day, cells are synchronized in the G0 phase by serum starvation (DMEM þ 0.5% calf serum) overnight. The next day, samples are washed twice with cold PBS and lysed for 10 min on ice with 75 ml RIPA lysis buffer supplemented with protease inhibitors. Cell lysates are collected in 1.5-ml tubes, sonicated for 3 s, and subsequently centrifuged at 15,000g for 10 min at 4 C. Next, collect supernatant and use an aliquot to determine protein concentration using commercially available kits and store the remaining protein sample at –80 C. Load equal amounts of proteins onto a 10% SDSPAGE electrophoresis gel and run at constant voltage (100 V) for approximately 1.5 h. Transfer the proteins from the electrophoresis gel onto a PVDF membrane for 1 h at constant intensity (200 mA), and block the membrane in blocking buffer containing 5% dry milk for at least 1 h. Determine the cyclin-D1 protein levels using a mouse anti-cyclin D1 (Upstate Millipor, cat. no. 05-815) as primary antibody (at 4 C overnight), A

B Control

US28 Cyclin D1 b-actin

Control

US28

Figure 7.5 US28 induces a transformed phenotype and increased proliferation in NIH-3T3 cells. (A) 2 103 NIH-3T3 cells stably transfected with either mock (empty plasmid) or US28 are grown for 2 weeks together with 2 105 naive NIH-3T3 cells.The formed foci are stained with methylene blue. (B) Total lysates from mock and US28 stably transfected NIH-3T3 cells present higher expression levels of cyclin D1. Protein levels are normalized against b-actin expression.

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and an HRP-conjugated goat antimouse antibody (BioRad, cat. no. 1706516) as secondary antibody (at room temperature for 1 h). HRP-derived chemiluminescence is measured using standard commercially available kits (e.g., ECL kit, Amersham) and Imaging films (e.g., Kodak BioMax Light films). To verify that the levels of proteins are equal in all lanes, the blot is stripped using 0.2 N NaOH solution, blocked with 5% dry milk in blocking buffer, and probed for b-actin levels (Sigma, cat. no. A5440) (Smit et al., 2002).

5.3. In vivo xenograft models The tumorigenic character of vGPCRs can be confirmed using tumor xenograft models in nude mice. These mice are deprived in T cells and are consequently not able to mount T cell-mediated immune responses, such as graft rejection. To this end, 2 106 NIH-3T3 cells stably transfected with either mock or US28 are injected subcutaneously in each flank of the animal, and tumor formation is checked every other day. Each injected side is considered as an independent tumor. The length, width, and depth of growing malignancies are measured with a caliper, and the volume of the tumors is determined by calculating the half-product of the three dimensions of the tumor. Malignancies can be considered as tumors when their sizes are greater than or equal to 50 mm3. Tumor growth can be depicted as the tumor size by time post-injection (Fig. 7.6A), or by means of Kaplan-Meier curves to illustrate the percentage of mice presenting tumors over time (Fig. 7.6B). B

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Figure 7.6 Representation of US28-induced tumor formation in xenograft models. (A) Tumors formed in the flanks of nude mice injected with 2 106 US28 stably transfected NIH-3T3 cells are measured with a caliper, and the tumor volume is calculated as the half-product of the length, width, and depth. Tumor formation is followed over time after the injection of stably transfected cells. (B) Kaplan-Meier curves are used to determine the percentage of animals presenting tumors larger than 50 mm3, and show that US28-induced tumors have a 100% incidence within 21days post-injection.


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6. Generation of Recombinant HCMV Strains by Markerless Bacterial Artificial Chromosome Mutagenesis Bacterial artificial chromosome (BAC) mutagenesis has become an excellent tool to manipulate the CMV genome and to investigate the function of vGPCRs in the context of viral infection in biologically relevant cells (specifically endothelial cells, and macrophages). The generation of recombinant CMVs by BAC mutagenesis has been achieved by several research groups investigating vGPCRs (e.g., MCMV M33 (Davis-Poynter et al., 1997), RCMV R33 (Beisser et al., 1998), HCMV US28 (Minisini et al., 2003), HCMV UL33 (Casarosa et al., 2003a), RCMV R78 (Kaptein et al., 2003), and HCMV UL78 (Michel et al., 2005)). In particular, the publication of Streblow et al. in 1999 highlighted the importance for vGPCR research by demonstrating that US28 is responsible for the migration of HCMV-infected smooth muscle cells (Streblow et al., 1999). The ground for recombinant CMVs was prepared by cloning CMV genomes from various species into BACs (Brune et al., 2000; Messerle et al., 1997). Initially, BAC mutagenesis was achieved by means of shuttle plasmids using RecA-mediated recombination with homologous flanks of 500 to 3000 bp (Casarosa et al., 2003a; Michel et al., 2005), but this method was very time consuming. Later, the establishment of the Red-mediated or RecE/T-recombination to manipulate BACs provided a reliable faster technique (Borst et al., 2001; Wagner et al., 2002). However, since this method led to the persistence of undesired genetic sequences, it was not an ideal tool to generate point mutations or introduce molecular tags to the target gene. This technique has been further optimized (Tischer et al., 2006; Warming et al., 2005) and the so-called ‘‘en passant’’ mutagenesis described by Tischer et al. in 2006 is a powerful tool for the traceless introduction of potentially any mutation into the CMV genome. Markerless BAC mutagenesis is based on two recombination steps: (1) the insertion of the mutation at the target site, and (2) the excision of the positive (kanamycin resistance) and the negative (I-SceI) selection marker. Briefly, a linear DNA fragment containing the sequences needed for the two recombination steps (the directed integration and precise excision of the unwanted sequences) is generated by PCR (Tischer et al., 2006). It is then electroporated into recombination competent Escherichia coli, harboring (1) a CMV BAC genome, (2) the Red recombination system under control of a temperature-sensitive promoter, and (3) the coding sequence for the homing endonuclease I-SceI under control of an arabinose-inducible promoter. Successful integrates, controlled by PCR and restriction fragment length polymorphism (RFLP) analysis, undergo the second round of recombination

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removing the negative and positive selection marker. This step is performed by induction of the red recombination system at 42 C for 20 min and the parallel induction of I-SceI endonuclease by 1% arabinose, resulting in a mutated BAC carrying only the CMV genome with the desired mutation. The mutated BAC is checked again by PCR, RFLP with at least three restriction enzymes and sequencing of the mutated region. Recombinant virus is reconstituted by electroporation of the mutated BAC DNA into CMV permissive cells (Chevillotte et al., 2009; Sinzger et al., 2008). B

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Figure 7.7 Cell surface expression and signaling properties of vGPCRs in HCMVinfected cells. (A) Human foreskin fibroblasts (HFF) are infected with the AD169 WT and DUS28 (lacking the US28 gene) strains. Eight hours post-infection, [125I]-CCL5 specific binding is detected in cells infected with the WT virus, but it is almost completely abrogated in cells infected with the DUS28 mutant. (B) Infection of HFF cells with HCMV strain AD169 leads to a constitutive formation of inositol phosphate (InsP) 48 h postinfection. Deletion of either US28 only (DUS28) or the four vGPCRsç US27, US28, UL33, and UL78 (Quattro)çcompletely impairs InsP accumulation ( Jens Holl, Andreas Schreiber and Detlef Michel, unpublished data). (C) Human glioblastoma U373 cells infected with the HCMV strainTitan present an increased activation of the humanVEGF promoter, which is impaired after deletion of US28 gene.


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‘‘En passant’’ mutagenesis offers two major advantages: (1) recombinant BACs can be generated within less than 14 days, and (2) the method can be applied sequentially for the generation of mutations in any order. Using BAC mutagenesis, we generated different mutants derived from AD169 and TB40 HCMV strains. AD169 strains lacking US28 or also all four vGPCRs (US27, US28, UL33, and UL78) demonstrate that US28 is responsible for the observed CCL5 binding (Fig. 7.7A) and constitutive inositol phosphate formation in infected human foreskin fibroblasts (HFF) (Fig. 7.7B). Furthermore, infection of human glioblastoma U373 cells with the Titan strain induces the activation of the human VEGF promoter. After deletion of US28, the observed proangiogenic phenotype is impaired, highlighting the potential involvement of US28 in HCMV-related pathogenic conditions (Fig. 7.7C).

7. Conclusions The study of HCMV-encoded vGPCRs can be performed at several levels. For the quest of nonpeptidergic drug–like compounds that can inhibit US28-mediated activities, high-throughput screening methods for InsP formation and radioligand binding have been successfully used. Similar approaches can be used to identify cognate ligands for US27, UL33, and UL78. Signaling assays determine whether these vGPCRs are constitutively active and whether they present ligand-induced signaling properties once these receptors are deorphanized. The BAC mutagenesis method is also a very useful tool to determine the importance of vGPCRs in the context of HCMV-infected cells. In vitro and xenograft in vivo models have enabled us to delineate the oncogenic properties of US28 and highlight its potential importance in viral proliferative diseases.

ACKNOWLEDGMENTS D.M., H.F.V., and M.J.S. are supported by the Dutch Organization for Scientific Research (NWO).

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C H A P T E R

E I G H T

Identification and Characterization of Virus-Encoded Chemokine Binding Proteins Antonio Alcami*,† and Abel Viejo-Borbolla*,‡ Contents 1. Introduction 2. Methods for Studying Chemokine-Binding Proteins 2.1. Preparation of media from virus-infected cell cultures 2.2. Cross-linking of chemokines to soluble vCKBPs 2.3. Ligand blot assay 2.4. Chemokine binding to cells 2.5. Scintillation-proximity assay 2.6. FlashPlateâ assay 2.7. Surface plasmon resonance to characterize vCKBP–chemokine interactions 2.8. The use of SPR in GAG competition assays 2.9. SPR technology to investigate the interaction between vCKBPs and GAGs Acknowledgments References

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Abstract Poxviruses and herpesviruses encode a unique family of proteins that are secreted from infected cells and bind chemokines, in spite of their lack of amino acid sequence similarity to cellular chemokine receptors. Many of the methods used with host chemokines and chemokine receptors may be used to characterize these virus-encoded chemokine inhibitors. Here we focus on methodologies that have been adapted to identify secreted chemokine binding proteins from viruses, to determine their binding specificity for chemokines and to characterize their interaction with the chemokine domains involved in the recognition of chemokine receptors or glycosaminoglycans. * { {

Centro de Biologıá Molecular Severo Ochoa, Consejo Superior de Investigaciones Cientı´ficas-Universidad Autońoma de Madrid, Cantoblanco Madrid, Spain Department of Medicine, University of Cambridge, Cambridge, United Kingdom Immunology Institute, Mount Sinai School of Medicine, New York, New York, USA


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1. Introduction Viruses modulate the chemokine network by encoding homologues of chemokines and chemokine receptors, and secreted proteins that bind chemokines (Alcami, 2003; Seet et al., 2003). These mechanisms have been mainly identified in large DNA viruses such as herpesviruses and poxviruses. Virus-encoded chemokine homologues function as agonists, binding the cellular receptors and transducing signals, or antagonists, preventing the activity of chemokines by occupying chemokine receptors. Viral homologues of G protein–coupled receptors (GPCRs), the seven-transmembrane– domain chemokine receptors, are expressed at the surface of infected cells and may transduce signals in the absence of ligand. Several viral chemokine-binding proteins (vCKBPs) have been identified to date (Alcami and Saraiva, 2009). These vCKBPs are secreted in large amounts from infected cells and, despite the lack of sequence similarity to GPCRs, bind chemokines with high affinity. The myxoma virus M-T7 protein has been propose to inhibit chemokine activity by preventing the interaction of chemokines with glycolaminoglycans (GAGs) and disrupting the chemokine gradient ( Lalani et al., 1997). The interaction of chemokines with GAGs is believed to be required for proper presentation of the chemokine to the GPCRs present in the target cell in vivo (Handel et al., 2005; Johnson et al., 2005). The vaccinia virus 35-kDa protein and myxoma virus M-T1 bind CC chemokines with high affinity and neutralize their activity by preventing interaction with cellular chemokine receptors (Alcami et al., 1998; Graham et al., 1997; Smith et al., 1997). A secreted protein related to the 35-kDa vCKBP, known as A41 in vaccinia virus and E163 in ectromelia virus, has been recently shown to bind chemokines, but does not block chemokine-induced migration and it has been proposed to block chemokine–GAG interactions ( Bahar et al., 2008; Ruiz-Arguello et al., 2008). The CrmB and CrmD secreted tumor-necrosis-factor receptor homologues from poxviruses have a C-terminal domain, designated smallpox virus–encoded chemokine receptor (SECRET) domain, that binds a reduced set of chemokines. The SECRET domain is also present in three poxvirus secreted proteins and inhibits the biological activity of chemokines (Alejo et al., 2006). Three vCKBPs have been identified in herpesviruses. The M3 protein encoded by murine gammaherpesvirus 68 binds a broad range of chemokines, including CC, CXC, C, and CX3C chemokines, and neutralizes their activity ( Parry et al., 2000; van Berkel et al., 2000). The glycoprotein G from several alphaherpesviruses infecting animals binds a broad range of chemokines ( Bryant et al., 2003; Costes et al., 2005). Both M3 and glycoprotein G inhibit the interaction of chemokines with both cellular receptors and GAGs (Alexander-Brett and Fremont, 2007;

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Bryant et al., 2003; Webb et al., 2004). Finally, the pUL21.5 protein encoded by human cytomegalovirus binds CCL5 and blocks its interaction with cellular receptors (Wang et al., 2004). The methods used to study the binding properties and biological activity of viral chemokines and chemokine receptors are similar to those used to characterize the cellular homologues. This chapter will focus on methods that have been specifically used to identify vCKBPs and to characterize their binding properties. A chemokine-binding assay for cells that can also be used to characterize the binding properties of the viral chemokine and chemokine receptor homologues is described. The ability of vCKBPs to neutralize the biological activity of chemokines can be determined in standard chemokine-induced cell migration and calcium mobilization assays.

2. Methods for Studying Chemokine-Binding Proteins 2.1. Preparation of media from virus-infected cell cultures Initial screenings for the presence of vCKBPs are carried out with crude supernatants from cell cultures infected with relevant viruses (Alcami et al., 1998; Bryant et al., 2003; Graham et al., 1997; Parry et al., 2000; van Berkel et al., 2000). While removal of virus particles by centrifugation may reduce virus titers, additional methods should be used to ensure inactivation of infectious virus, such as treatment with UV light and trioxsalen, a photochemical DNA cross-linker (Tsung et al., 1996). 1. Infect cell monolayers with virus at high multiplicity of infection (5 to 10 plaque-forming units per cell) in a small volume of serum-containing tissue culture medium (i.e., 10 ml in a 175-cm2 flask). Prepare supernatants from mock-infected cells as a control. 2. After an adsorption period of 1 to 2 h at 37 C, wash monolayers three times with serum-free tissue culture medium or phosphate buffer saline (PBS) to remove any remaining virus or serum. 3. Follow the infection in a small volume of serum-free medium (i.e., 15 to 20 ml for a 175-cm2 flask) during the desired time. Normally, 24 to 48 h of infection will ensure maximal expression of viral proteins. 4. Collect the supernatants and centrifuge at 4 for 15 min at 3000 rpm to remove cellular debris. Add Hepes, pH 7.4, to a final concentration of 20 mM to stabilize the pH of the supernatants. 5. Virus particles may be removed by ultracentrifugation (i.e., 33,000g for 1 h at 4 ). 6. Inactivate infectious virus by treatment with trioxsalen and UV light. A concentrated 100 stock of trioxsalen (4,50 ,8-trimethylpsoralen, Sigma)

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is freshly prepared by dissolving 1 mg in 1 ml of dimethylsulfoxide (DMSO) at 37 for 3 h and diluted to a final concentration of 200 mg/ml in DMSO. Add 10 ml trioxsalen stock per milliliter of supernatant to a final concentration of 2 mg/ml. Incubate for 10 min at room temperature. Transfer 3-ml aliquots of the supernatant to six-well tissue culture plates. Remove the lid of the plate and expose to UV in a cross-linker for 5 min. Test the virus inactivation by titration on cell monolayers. 7. Concentrate supernatant 5- to 10-fold using a Centriprep concentrator and store at –80 .

2.2. Cross-linking of chemokines to soluble vCKBPs Most of the vCKBPs described to date were identified in cross-linking experiments to chemokines (Alcami et al., 1998; Bryant et al., 2003; Graham et al., 1997; Lalani et al., 1997; Parry et al., 2000; van Berkel et al., 2000; Wang et al., 2004). Samples that potentially contain vCKBPs, such as supernatants from virus-infected cultures, crude medium from mammalian cell or baculovirus expression systems, and purified recombinant candidate proteins, are incubated with 125I-chemokines. The interaction of chemokines with binding proteins is identified by inducing covalent cross-linking between interacting proteins and subsequent analysis by SDS-PAGE (Fig. 8.1). Nonradioactive chemokines may also be cross-linked and the complexes visualized by Western blot with specific antibodies ( Lalani et al., 1997; van Berkel et al., 2000). There is a large variety of chemical cross-linkers with different functional group specificity and length of the spacer, and one must consider that a specific cross-linker may not work for all protein–protein interactions. The cross-linkers described in the following have been successfully used to identify vCKBP–chemokine interactions. Once a vCKBP has been identified by using radioiodinated chemokines, the cross-linking may be repeated in the presence of increasing doses of unlabeled chemokines to determine the ability of other chemokines to bind the vCKBP. This method is very sensitive and will identify low-affinity interactions. It is critical that chemokine activity assays are also performed to confirm whether the vCKBP neutralizes the activity of specific chemokines. 1. Incubate 10–20 ml supernatants with 1–2 ml of 125I-chemokine (0.4–0.8 nM), commercially available at 2200 Ci/mmol, in 25 ml final volume of binding buffer (RPMI containing 20 mM Hepes, pH 7.5, and 0.1% bovine serum albumin, BSA) for 2 h at room temperature. Add 100 to 1000-fold excess of unlabeled chemokine to demonstrate specificity of the interaction, or other unlabeled chemokines to determine chemokine-binding specificity. 2. Add 2.5 ml of 10x concentrated cross-linker and incubate for 15 min at room temperature. Various cross-linkers may be used: (a) 5 nM Bis

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Figure 8.1 Identification of vCKBPs by chemokine cross-linking assay. Cross-linking of 125I-CCL3 (A), 125I-CXCL8 (B,C,E), or 125I-CXCL12 (D) with EGS to medium from cultures uninfected (mock) or infected with the indicated viruses.The field isolates of EHV-1 are indicated with an identification number (E). Cross-linking with 125 I-CXCL8 was also performed to supernatants and cell extracts (cell) from cultures infected with EHV-1 strain AB4 in the absence or presence of tunicamycin (Tm) (E). Samples were analyzed by sodium-dodecyl-sulphate polyacrylamide gel electrophoresis

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3. 4. 5. 6. 7.


(Sulfosuccinimidyl) suberate (BS3) (Pierce Chemical Co.), with a freshly prepared 10 stock solution at 50 nM dissolved in 5 mM sodium citrate, pH 5; (b) 40 mM 1-ethyl-3-(3-dimethylaminopropyl)-carbodiimide (EDC, Sigma), with a 10 stock solution at 400 mM (76 mg/ml) in water and stored at –20 ; or (c) 1 mg/ml ethylene glycol-bis-succinamidyl succinate (EGS, Sigma), with a freshly prepared 10 stock solution at 10 mg/ml in DMSO. Add 2.5 ml of 1 M Tris-HCl pH 7.5 to quench the reaction. Centrifuge the sample in a microfuge (13,000 rpm) for 15 min. This step can be avoided, but it will be recommended if high background levels are observed. Transfer 20 ml of the supernatant to a tube containing 20 ml of 2 Laemmli buffer with mercaptoethanol. Boil for 3 min. Load 10 to 15 ml in a 12% polyacrylamide gel to separate chemokines from complexes by SDS-PAGE. Fix and dry the gel, and expose to autoradiography film with two intensifying screens at –80 .

2.3. Ligand blot assay The ligand blot assay has been successfully used to identify the interaction of a variety of cytokines with their receptors and with viral proteins (Dower et al., 1985; Symons et al., 1995). Proteins are resolved by SDS-PAGE in the absence of reducing agents, transferred to a nitrocellulose membrane and incubated with radioiodinated chemokines. The major limitation of this method is that insufficient protein renaturation after immobilization onto the membrane support may limit the detection of chemokine–vCKBP interactions. 1. Resolve 10 to 20 ml of concentrated serum-free virus-infected and mockinfected supernatants or purified recombinant proteins under nonreducing conditions by SDS-PAGE. 2. Transfer the proteins onto a nitrocellulose membrane. 3. Incubate overnight at 4 the nitrocellulose membrane with blocking solution containing 3% non-fat skimmed milk powder in 10 mM Tris-HCl pH 7.4, 140 mM NaCl, and 0.02% NaN3. 4. Incubate the nitrocellulose membrane with 2 to 10 nM commercially available 125I-chemokine (220 Ci/mmol), in blocking solution for 4 h at room temperature. Binding specificity should be demonstrated in the presence of a 100- to 1000-fold excess unlabeled chemokine. (SDS-PAGE) and autoradiography. Molecular masses in kilo-daltons and the position of 125 I-labeled chemokine (CK) and vCKBP-chemokine complexes (*) are indicated. (From Bryant, N. A., Davis-Poynter, N.,Vanderplasschen, A., Alcami, A. (2003). Glycoprotein G isoforms from some alphaherpesviruses function as broad-spectrum chemokine binding proteins. EMBO J. 22,833^846, with permission.)


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5. Wash the nitrocellulose membrane with blocking solution three times for 30 min. 6. Air-dry the nitrocellulose membrane on filter paper for 10 min. 7. Place the membrane between plastic wrap and expose to autoradiography film with two intensifying screens at –80 .

2.4. Chemokine binding to cells This method is useful to determine whether vCKBPs prevent the interaction of chemokines with specific cellular receptors expressed at the cell surface (Fig. 8.2) (Alcami et al., 1998; Bryant et al., 2003; Parry et al., 2000). It may also be used to test the binding of virus-encoded chemokines to cells expressing relevant chemokine receptors or to test whether virus-infected cells or cells transfected with viral homologues of chemokine receptor genes express chemokine-binding activity. The first step of the method should be ignored to study viral chemokines and chemokine receptors. Binding assays described here with cells in suspension may also be performed with cell monolayers, but higher cell densities and chemokine-binding values are normally achieved with cells in suspension. The affinity of cellular chemokine receptors for chemokines can be determined from saturation curves. Once the affinity is known, the ability of purified vCKBPs to inhibit binding of 125I-chemokines to cellular receptors will give us an indirect indication of the binding affinity of the vCKBP–chemokine interaction. 1. Incubate various doses of supernatant containing vCKBP or purified vCKBP with commercially available 125I-chemokine (2200 Ci/mmol, final concentration 100 to 300 pM ) in 100 ml of binding medium (RPMI containing 20 mM Hepes, pH 7.5, and 0.1% BSA) for 1 h at 4 . 2. Prepare cells expressing chemokine receptors. Cells growing in suspension, such as U937 and THP-1 cells, are washed twice with binding medium by centrifugation. Cells growing in monolayer can be detached from the substrate by incubation with 0.5 mM EDTA in PBS for 10 to 15 min. Cells must be washed twice with binding medium by centrifugation and resuspended in binding medium to a concentration of 2.5 106 cells in 50 ml. 3. Add 2.5 106 cells in suspension in 50 ml and incubate for 2 h at 4 with occasional shaking. 4. Centrifuge (microfuge 30 s) 125 ml of the cell suspension through 200 ml of phthalate oil mix (1.5 parts of dibutyl phthalate, Sigma, and 1 part of dioctyl phathlate [bis(2ethylhexyl) phthalate], Aldrich) in 0.5 ml Eppendorf tubes. Aspirate the supernatant and cut with scissors the tip of the tube containing the pellet. 5. Transfer the tip of the Eppendorf tube into a suitable tube to count the radioactivity in a gamma counter.

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A

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Figure 8.2 Inhibition of chemokine binding to cellular receptors by vCKBPs. Secreted glycoprotein G from equine herpesvirus 1 (EHV-1) and bovine herpesvirus 1 (BHV-1) expressed in the baculovirus system inhibits chemokine binding to cells in a dosedependent manner. Binding assay of 125I-CCL3 and 125I-CXCL8 to U937 cells in the absence (solid triangles) or presence of increasing amounts of supernatants from Sf 21 cells infected with recombinant baculovirus expressing full-length glycoprotein G from either EHV-1 (B, D) or BHV-1 (A, C) (solid squares), or with control baculovirus (AcNPV, open squares).The dose of supernatant is expressed as cell equivalents. Binding specificity was determined in the presence of 500-fold excess of unlabeled CCL3 or CXCL8 (open circles). Purified M3 protein was used as a positive control (open triangles). Binding of chemokines is expressed as the mean standard deviation of triplicate assays. (From Bryant, N. A., Davis-Poynter, N.,Vanderplasschen, A., Alcami, A. (2003). Glycoprotein G isoforms from some alphaherpesviruses function as broad-spectrum chemokine binding proteins. EMBO J. 22, 833^846, with permission.)

2.5. Scintillation-proximity assay The scintillation-proximity assay (SPA) is a powerful quantitative-binding method ( Bosworth and Towers, 1989). This technology is available from GE Healthcare as microspheres embedded with scintillant, and various formats are available, with antibodies or proteins bound to the surface of the beads to facilitate the coupling of the protein of interest. We illustrate


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this technology while describing a protocol in which protein A–coated beads are used to characterize the interaction of chemokines with vCKBPs fused to the Fc portion of IgG1 (Alcami et al., 1998). The vCKBP-Fc protein binds to the surface of protein A–coated fluomicrospheres and the radioligand must bind to the receptor to be in close proximity to the fluomicrospheres to excite the scintillant (Fig. 8.3). One of the best advantages of this technique is that the unbound radioligand does not activate the scintillant, and thus eliminates the need to carry out extensive washings and manipulations to separate bound from free ligand. In this method, all reagents are mixed, and bound radioactivity is counted at the indicated time. It is critical to determine experimentally the amount of purified vCKBPFc to be used in the assay, which will normally be 1 to 100 ng. High concentrations of vCKBP-Fc will saturate the binding capacity of the protein A–SPA beads, and the excess vCKBP-Fc in solution will prevent binding of the radiolabeled chemokine to vCKBP-Fc–coated beads. An alternative when large amounts of vCKBP-Fc protein are needed is to precoat the protein A–SPA beads with purified viral protein, and to remove the excess of protein by washing the beads before addition of the radiolabeled chemokines. The specificity of the interaction may be demonstrated in the presence of excess unlabeled chemokine. An advantage of this method over the cross-linking assay is that it is more quantitative and allows determination of binding affinities (Fig. 8.3). This can be achieved by performing saturation curves with increasing doses of 125I-chemokine followed by Scatchard analysis. Alternatively, the affinity of vCKBP for chemokines can be indirectly calculated by determining the binding of a 125I-chemokine of known binding affinity to vCKBP in the presence of increasing doses of unlabeled chemokines. The assay described in the following is performed in tubes, but the beads and reagents may also be added to specially designed microplates to facilitate the manipulation and counting of many samples. 1. Incubate commercially available 125I-chemokines (200 to 400 pM ) with 1 to 100 ng of purified vCKBP-Fc in 100 ml of binding buffer (0.1% BSA in PBS) for 2 h at room temperature. Unlabeled chemokines can be added as necessary. Tissue culture medium is not recommended as binding buffer to avoid possible quenching when counting radioactivity due to phenol red present in the medium. As an alternative, phenol red–free tissue culture medium may be used in these assays. 2. Add 50 ml of protein A-SPA beads and incubate for 2 h at room temperature. If affinity constants will be calculated, the time of incubation necessary to reach equilibrium should be tested experimentally. 3. Determine the radioactivity bound to vCKBP-Fc by counting in a betascintillation counter.

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15.1 ± 0.6

1000

Figure 8.3 SPA to study the interaction of vCKBPs with chemokines. (A) Illustration of SPA using protein A-fluoromicrospheres containing scintillant (SPA Prot. A) to detect the interaction of 125I-chemokines with a vCKBP fused to the Fc portion of human IgG1 (vCKBP-Fc). (B) Saturation curve and Scatchard analysis of 125I-CCL3 binding to vaccinia virus 35K-Fc.The mean ( SEM) specific binding of triplicate samples and the affinity constant are shown. (C) Competitive inhibition with various doses of CC chemokines. Purified vaccinia virus 35K-Fc protein was incubated in triplicate with 50 pM 125I-CCL3 in the presence of increasing doses of unlabeled human CC chemokines: CCL2, CCL3, CCL5, and CCL11. The percentage of specific binding (mean SEM) refers to binding in the absence of competitor. The affinity constant (KD) values calculated are indicated.

4. The total radioactivity added must be determined in a beta-scintillation counter after addition of a standard scintillant to a relevant amount of 125I-chemokine.

2.6. FlashPlateâ assay The principle of the FlashPlate ( PerkinElmer Life Sciences) is the same as that of SPA, but in this case the assay has been designed in a plate format. FlashPlate is a microplate designed for binding assays with radiolabeled

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ligands (Brown et al., 1997). The interior of each well is coated with a thin layer of polystyrene-based scintillant. Following the SPA principle, the radioisotope must be in close proximity to the surface of the well to excite the scintillant (Fig. 8.4). Unbound radioligand does not activate the scintillant and thus there is no need to carry out extensive washings. FlashPlate was designed for use with microplate scintillation counters. Various FlashPlate formats are available that have secondary antibodies or other proteins precoated in the wells. In the protocol described here, a nickel-chelate FlashPlate format is used to study the interaction of chemokines with vCKBPs fused to a C-terminal 6xhis tag (vCKBP-his) (Alcami, 2004). Protein A–coated FlashPlate can also be used when the vCKBP or other receptors are expressed fused to the Fc portion of human IgG1. A

125l-chemokine

vCKBP-his Scintillant Nickel chelate flashplate (PerkinElmer life sciences) C

10000

18000 bound (cpm)

8000 6000 4000

125I-IL-8

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bound (cpm)

B

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10 100 1000 Purified M3 (ng)

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Figure 8.4 FlashPlate assay to characterize the interaction of vCKBPs with chemokines. (A) Illustration of FlashPlate assay to determine the interaction of radiolabeled chemokines with purified vCKBP expressed with a C-terminal 6xhis tag (vCKBP-his) in nickel chelate FlashPlate. (B) Binding of 200 pM 125I-IL-8 (125I-CXCL8) to increasing doses of purified murine gammaherpesvirus 68 M3 protein fused to a C-terminal 6xhis tag. The mean ( standard deviation) specific binding of triplicate samples is shown. (C) Saturation curve of 125I-IL-8 (125I-CXCL8) binding to purified M3 (1 ng).The mean ( standard deviation) specific binding of triplicate samples is shown. (From Alcami, A. (2004). Interaction of viral chemokine inhibitors with chemokines. Methods Mol. Biol. 239, 167^180, with permission.)

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As for the SPA beads from GE Healthcare, the concentration of vCKBP-his used in the assay is determined experimentally, which will normally be 1 to 100 ng per well. Figure 8.4 illustrates a typical experiment in which addition of an excess of vCKBP-his may reduce the signal. If large amounts of recombinant protein are needed, the FlashPlate may be precoated with purified viral protein, and the excess of protein removed by washing the wells before addition of 125I-chemokines. As indicated for SPA, the FlashPlate platform can be used to determine chemokine specificity, by either direct binding to 125I-chemokines or by competitive inhibition with unlabeled chemokines (Bryant et al., 2003; Webb et al., 2003). The binding affinity of the vCKBP-chemokine interaction is calculated from saturation curves or competitive inhibition assays with increasing doses of unlabeled chemokines. 1. Add commercially available 125I-chemokines (200–400 pM ) and 1 to 100 ng of purified vCKBP-his in 100 ml of binding buffer (0.1% BSA in PBS) to the wells of a nickel chelate FlashPlate. Unlabeled chemokines can be added as necessary. As indicated above for SPA, tissue culture medium is not recommended due to the presence of phenol red, and phenol red–free tissue culture medium should be used in these assays. 2. Incubate for 4 to 6 h at room temperature or for longer periods at 4 . If affinity constants will be calculated at equilibrium, the same plate may be counted several times to determine experimentally the kinetics of interaction of chemokines with the viral protein. 3. Count the FlashPlate at the desired time of incubation in a microplate scintillation counter. 4. The total radioactivity added can be determined by addition of Microscint, a scintillant designed for these counters, to control wells.

2.7. Surface plasmon resonance to characterize vCKBP–chemokine interactions Surface plasmon resonance (SPR) technology, such as BIAcore biosensors ( Biacore Life Sciences, GE Healthcare), monitors protein–protein interactions in real time and has been widely used to characterize the binding of vCKBPs to chemokines (Alejo et al., 2006; Alexander-Brett and Fremont, 2007; Ruiz-Arguello et al., 2008; Seet et al., 2001; Wang et al., 2004). SPR is a very useful and powerful method to address whether a protein of interest is able to interact with chemokines (Fig. 8.5). Once a putative vCKBP has been coupled onto a biosensor chip, all available recombinant chemokines can be used in an initial screening assay to determine the binding specificity of the candidate protein. This method offers a quantitative advantage over the cross-linking where screening of many samples is time consuming and more expensive due to the cost of the chemokine labeling. More than 40

185

Resp. diff. (RU)


1600

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200 Time (s)

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400

Figure 8.5 SPR analysis of vCKBP binding to chemokines. Sensorgrams showing binding of the indicated human (h) and mouse (m) chemokines to purified recombinant E163 from ectromelia virus analyzed by SPR. Arrows indicate end of injection and the times are shown in seconds. (From Ruiz-Arguello, M. B., Smith,V. P., Campanella, G. S., Baleux, F., Arenzana-Seisdedos, F., Luster, A. D., and Alcami, A. (2008). An ectromelia virus protein that interacts with chemokines through their glycosaminoglycan binding domain. J.Virol. 82,917^926, with permission.)

chemokines have been described in both mouse and human systems, and purified recombinant chemokines are available from a number of companies such as Peprotech or R&D Systems. Another advantage of SPR is the monitoring of the vCKBP–chemokine interaction in real time, allowing the quantification of binding affinities and providing additional information on the stability of the vCKBP–chemokine complex. This is relevant in order to understand the biology of these viral proteins. For example, a slow dissociation of the complex may enhance the ability of a particular vCKBP to inhibit chemokine activity in vivo. Another application of this technology is the screening of chemokine and vCKBP mutants to map the amino acid residues involved in the interaction and to assess the relative contribution of different binding domains when multiple interactions are occurring between two proteins. The vCKBP can be immobilized onto the biosensor chip through various methods: amine-, thiol-, and streptavidine-coupling. Proteins containing a histidine-tag can also be immobilized using NTA sensor chips. The choice of the method depends on the chemical nature of the ligand. The most common method used for vCKBPs is amine coupling since most of the vCKBPs contain free amine groups and are not very acidic. When the protein is

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very acidic, does not have free amine groups, or, on the other hand, has too many amine groups, thiol coupling is a good alternative. Thiol groups are normally present in the vCKBP, but can also be inserted into the vCKBP if needed. Reducing conditions for either the binding or regeneration of the chip should not be employed if thiol coupling is performed. When neither thiol nor amine coupling are suitable for the immobilization of the vCKBP, the protein can be biotinylated prior to the immobilization in a streptavidincontaining chip. In this section, we describe the methodology used to determine the binding properties of vCKBPs using the amine groups to immobilize the protein. The use of streptavidine coupling is described later (Section 2.9). The BIAcore chips contain several cells allowing the coupling of the vCKBP to one cell while leaving the other empty or occupied by a protein control unable to interact with chemokines. This reference cell is required for the analysis of the BIAcore sensorgram (see the following). The main limitation of the SPR technology over the cross-linking is that it does not allow the screening of complex protein mixtures such as crude medium from virus-infected cells to identify the presence of secreted vCKBPs. Moreover, the cross-linking assay allows the comparison of the binding profiles of supernatant from cells infected with wildtype virus versus a virus mutant lacking the vCKBP, to test whether a protein is the sole vCKBP encoded by a particular virus. 1. Dyalize purified recombinant vCKBP against acetate buffer. The pH of the buffer depends on the isoelectric point of the vCKBP. 2. Activate all cells of the carboxy methyl dextran 5 (CM5) chip (Biacore Life Sciences, GE Healthcare) by addition of 35 ml of NHS/EDC. This results in the modification of the carboxymethyl groups of the chip to N-hydroxysuccinimide esters. 3. Inject the vCKBP at a flow rate of 5 ml/min only in one of the chip cells. Covalent interactions will form between the amine groups of the vCKBP and the N-Hydroxysuccinimide esters of the chip surface. For initial screening purposes, approximately 5000 response units ( RU) (5000 pg/ mm2) should be coupled to the chip. To determine the kinetics of association and dissociation and to calculate the affinity constants, lower densities of vCKBP are immobilized to the chip (Rmax < 200 RU). 4. Deactivate all cells of the chip by injecting 35 ml of 1 M ethanolamine hydrochloride, pH 8.5. This will impede that the free esters react with the analyte later on. 5. Inject recombinant chemokines dissolved in HBS-EP buffer (10 mM Hepes, 150 mM, NaCl, 3 mM EDTA, 0.005% surfactant P20, pH 7.4). For initial screening purposes, the chemokines are injected at a concentration of 100 nM at a flow rate of 10 ml/min, and association and dissociation phases are monitored. The dissociation phase in a screening experiment is approximately 2 min. For kinetics experiments, the


187

chemokines are injected at different concentrations (ranging from 1 to 300 nM ) at a flow rate of 30 ml/min over a 2-min period. Following the association period, the dissociation is analyzed by running sample buffer for 5 to 10 min. 6. Regenerate the chip surface after each chemokine injection to remove all bound analyte by injecting 10 to 30 ml of 10-mM glycine-HCl, pH 2.0 to 3.0. 7. Analyze the BIAcore sensorgrams with the software BIAevaluation, version 3.2, or more recent versions. Bulk refractive index changes are removed by subtracting the reference flow cell responses, and the average response of a blank injection is subtracted from all analyte sensorgrams to remove systematic artifacts. Kinetic data are globally fitted to a 1:1 Langmuir model.

2.8. The use of SPR in GAG competition assays Some vCKBPs prevent the binding of chemokines to GAGs, thereby interfering with the presentation of the chemokine to the GPCR (Bryant et al., 2003; Lalani et al., 1997; Ruiz-Arguello et al., 2008; Webb et al., 2004). As outlined above, the SPR technology is very useful to determine the binding specificities and affinities of vCKBPs to chemokines. Similar experiments may address whether the chemokines previously bound to GAGs interact with vCKBPs and provide information on the involvement of the GAG-binding site of chemokines in the interaction to vCKBPs (Fig. 8.6). To investigate whether a vCKBP is binding to the chemokine through its GAG-binding domain a simple competition experiment can be performed. 1. Using a CM5 chip with immobilized vCKBP, inject a constant concentration of chemokine diluted in HBS-EP at a flow rate of 10 ml/min. During the rest of the experiment, use the same buffer and flow rate. Monitor association and dissociation phases in all injections. Allow dissociation to occur for 2 min. 2. Regenerate the chip by injecting 10 ml of 10-mM glycine-HCl, pH 2.0 to 3.0. 3. Preincubate the chemokine for 30 min with increasing concentrations of GAGs, such as heparin, heparan sulfate, or chondroitin sulfate. 4. Inject the same concentration of chemokine as before, together with increasing concentrations of GAGs. 5. Inject GAG alone at each of the concentrations used to ensure that GAG is not binding to the vCKBP-containing CM5 chip. 6. Analyze the BIAcore sensorgrams as described in Section 2.7. Determine maximum response by measuring RU at the end of the injection.

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hCXCL12b mCCL25 mCXCL10

100

Binding (%)

80 60 40 20 0

1:0

1:0.1 1:0.5 1:1 1:10 1:100 1:1000 Chemokine:heparin (molar ratio)

Figure 8.6 SPR analysis of the interacion of avCKBP to chemokines in the presence of GAGs. SPR binding assay of mouse CCL25, mouse CXCL10 or human CXCL12b to purified E163 from ectromelia virus in the presence of increasing concentrations of heparin. Chemokine and heparin were incubated for 15 min before injection over a E163-coupled chip and maximum response was recorded.The percentage of binding refers to the binding in the absence of heparin. (From Ruiz-Arguello, M. B., Smith,V. P., Campanella, G. S., Baleux, F., Arenzana-Seisdedos, F., Luster, A. D., and Alcami, A. (2008). An ectromelia virus protein that interacts with chemokines through their glycosaminoglycan binding domain. J.Virol. 82,917^926, with permission.)

2.9. SPR technology to investigate the interaction between vCKBPs and GAGs Some vCKBPs, such as the M-T1 protein from myxoma virus and the E163 protein from ectromelia virus, are able to interact directly with GAGs, and it has been postulated that this may be a mechanism to retain the secreted vCKBP in the vicinity of the infected tissue (Ruiz-Arguello et al., 2008; Seet et al., 2001). By occupying GAG-binding sites at the cell surface, these vCKBPs may also interfere with chemokine–GAG interactions. SPR technology may be adapted to analyze vCKBP–GAG interactions. The method involves the immobilization of byotinylated GAG to the streptavidin (SA) chip ( BIAcore Life Sciences, GE Healthcare). Once the GAG of interest is coupled to the chip, binding of purified vCKBP can be easily assessed. Furthermore, the kinetics of the interaction are easily calculated. The method also permits carrying out competition assays with other nonbyotinylated GAGs and between vCKBP and chemokines for GAGs. Due to differences in the chemical nature of GAGs and proteins, the method requires several modifications described in the following. Immobilization of GAGs instead of vCKBPs is preferable to address this question because amine coupling of vCKBP may block the accessibility of residues required for protein–GAG interaction.


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1. Inject three times 1 M NaCl in 50 mM to condition the SA biosensor chip, permitting subsequent GAG immobilization. 2. Inject biotinylated GAG at a flow rate of 5 ml/min to reach approximately 100 RU. 3. Assess the binding specificity of the vCKBP by injecting it at 100 nM diluted in HBS-EP buffer at a flow rate of 10 ml/min. Monitor association and dissociation as described in Section 2.7. For kinetics analysis, inject serial dilutions of the vCKBP in HSB-EP at a flow rate of 30 ml/min. Allow the dissociation to proceed for at least 5 min. 4. Regenerate the SA chip surface after each vCKBP injection by injecting 2 M NaCl. 5. Analyze the BIAcore sensorgrams as described in Section 2.7. A similar experiment can be performed to determine the different oligosaccharides bound by a vCKBP. This avoids having to biotinylate and immobilize each individual GAG in an SA chip. 1. Using a SA chip containing immobilized biotinylated GAG inject a constant concentration of vCKBP diluted in HBS-EP at a flow rate of 10 ml/min. During the rest of the experiment use the same buffer and flow rate. Monitor association and dissociation phases in all injections. 2. Preincubate the vCKBP with heparin, heparan sulfate, or chondroitin sulfate during 30 min. 3. Inject the solution mixture as before. 4. Analyze the BIAcore sensorgrams as described in Section 2.7. Determine maximum response by measuring RU at the end of the injection.

ACKNOWLEDGMENTS The work in the A.A.’s laboratory is funded by the Wellcome Trust, European Union, Spanish Ministry of Science and Innovation, and Comunidad de Madrid. A.V.-B. is supported by a postdoctoral contract program from the Instituto de Salud Carlos III (Spanish Ministry of Health).

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chemokine activity yet lacks sequence homology to known chemokine receptors. Virology 236, 316–327. Symons, J. A., Alcami, A., and Smith, G. L. (1995). Vaccinia virus encodes a soluble type I interferon receptor of novel structure and broad species specificity. Cell 81, 551–560. Tsung, K., Yim, J. H., Marti, W., Buller, R. M., and Norton, J. A. (1996). Gene expression and cytopathic effect of vaccinia virus inactivated by psoralen and long-wave UV light. J. Virol. 70, 165–171. van Berkel, V., Barrett, J., Tiffany, H. L., Fremont, D. H., Murphy, P. M., McFadden, G., Speck, S. H., and Virgin, H. I. (2000). Identification of a gammaherpesvirus selective chemokine binding protein that inhibits chemokine action. J. Virol. 74, 6741–6747. Wang, D., Bresnahan, W., and Shenk, T. (2004). Human cytomegalovirus encodes a highly specific RANTES decoy receptor. Proc. Natl. Acad. Sci. USA 101, 16642–16647. Webb, L. M., Clark-Lewis, I., and Alcami, A. (2003). The gammaherpesvirus chemokine binding protein binds to the N terminus of CXCL8. J. Virol. 77, 8588–8592. Webb, L. M., Smith, V. P., and Alcami, A. (2004). The gammaherpesvirus chemokine binding protein can inhibit the interaction of chemokines with glycosaminoglycans. FASEB J. 18, 571–573.

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The Chemokine-Binding Protein M3 as a Tool to Understand the Chemokine Network In Vivo Sergio A. Lira,* Abel Viejo-Borbolla,*,† Limin Shang,* and Andrea P. Martin* Contents 1. Introduction 2. Generation of Transgenic Mice Expressing M3 in Insulin-Producing b Cells 3. M3 Expression in Islets of Langerhans Blocks CCL2-, CCL21-, and CXCL13-Induced Migration of Cells to Islets 4. M3 Expression in b Cells Blocks Cellular Infiltration and Prevents Diabetes Development 5. Generation of a Conditional Transgenic System for Expression of M3 6. Concluding Remarks References

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Abstract Murine herpesvirus 68 (MHV-68) codes for a secreted chemokine-binding protein, termed M3, which interacts with a broad range of chemokines with very high affinity, inhibiting chemokine function both in vitro and in vivo. Here we describe the transgenic methodology used to study the role of M3 as an immune modulator in vivo.

1. Introduction Chemokines are chemoattractant cytokines that orchestrate the migration of leukocytes to tissues during homeostasis and following injury and infection. They are responsible for the initiation of a series of events that * {

Immunology Institute, Mount Sinai School of Medicine, New York, New York, USA Centro de Biologıá Molecular Severo Ochoa, Consejo Superior de Investigaciones Cientı´ficas-Universidad Autońoma de Madrid, Madrid, Spain


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lead to leukocyte vascular extravasation and tissue infiltration. Chemokines are classified into C, CC, CXC, and CX3C subfamilies according to the relative positioning of the N-terminal cystein residues. Most chemokines are secreted, with the exception of CXCL16 and CX3CL1, which contain a transmembrane domain. Chemokines interact with glycosminoglycans (GAGs), and this interaction seems to be required for a proper presentation of the chemokine to the specific G-protein–coupled receptors (GPCRs) present at the plasma membrane of the target cell (Cinamon et al., 2001; Proudfoot et al., 2003; Rot, 1992). There is a certain degree of redundancy in the chemokine network, with some chemokines interacting with more than one chemokine receptor and some receptors interacting with more than one chemokine. Dysregulation of the chemokine network is observed in many inflammatory and autoimmune diseases. Large DNA viruses have developed strategies to interfere with the chemokine system. One of them, used by members of the Poxviridae and Herpesviridae families, involves the expression of secreted chemokinebinding proteins that inhibit chemokine function (vCKBP) (Alcami, 2003a,b). MHV-68 is a murine gamma-2-herpesvirus closely related to two important human oncogenic viruses, KSHV and EBV. The left region of the MHV-68 genome contains 4 genes not found in KSHV or EBV. These genes are termed M (for MHV-68) followed by a number (M1 to M4) and have important immunomodulatory functions. M3 encodes for a secreted protein with the ability to bind to a broad range of chemokines with high affinity and inhibit chemokine function in vitro (Parry et al., 2000; van Berkel et al., 2000). The mechanism of action behind this inhibition involves M3 binding to the chemokine N-loop thereby interfering with the chemokine-receptor interaction (Parry et al., 2000). The analysis of the crystal structure of M3 and CCL2 reveals that M3 forms a homodimer that mimics the CCL2-interacting structure of its receptor CCR2 (Alexander et al., 2002). The use of genetically manipulated mice has contributed to the understanding of chemokine function in vivo. As we enter the new century, most of the chemokine receptors have been individually deleted by conventional gene targeting techniques. These studies have convincingly demonstrated a role for chemokines in homeostasis and disease. However, despite these advances, our understanding of the role of multiple chemokines in the context of disease is quite primitive. It has been amply documented that the pattern of chemokine expression varies dramatically during the course of diseases; not only many chemokines are expressed simultaneously, but also their temporal expression pattern varies significantly. No genetic or pharmacological tools have emerged thus far to probe on the chemokine system. We have reasoned that M3 could be a very good tool to analyze the role of chemokines in vivo during homeostasis or inflammation because it binds and

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inhibits a broad spectrum of chemokines. Our group was the first one to explore the use of M3 as a chemokine blocker in vivo using transgenic mice ( Jensen et al., 2003). The use of this technology has improved our understanding of the immunomodulatory role of M3 in vivo. Moreover, the characterization of mice expressing M3 has shed light into the role of chemokines during homeostasis and inflammation. Here we review the methods used to understand the role of M3 as an inhibitor of chemokine function in vivo. Specifically, we review the methodology employed to generate and characterize transgenic mice expressing M3. The technical approaches utilized to identify M3 as a chemokine binding protein and the molecular mechanism of chemokine inhibition are covered in Chapter 8 in this volume.

2. Generation of Transgenic Mice Expressing M3 in Insulin-Producing b Cells To study the biological effects of M3 in vivo, we generated transgenic mice expressing M3 in the pancreas (RIP-M3 mice). To this end, first we constructed the RIP-poly(A) vector containing a segment of the rat insulin promoter 2 (RIP) and the rabbit b-globin poly(A) signal ( Jensen et al., 2003). The vector was generated by replacing the tumor necrosis factor alpha (TNF-a) fragment in RIP-TNF-pBS (Grewal et al., 1996) with the rabbit b-globin poly(A) DNA segment. The rabbit b-globin poly(A) signal was PCR amplified from a plasmid containing the CMV-EGFP transgene (Okabe et al., 1997) using the oligonucleotides 50 -ACAGAGGATAT CACTCCTC AGGTGCAGGCTGC-30 , inserting an EcoRV site, and 50 -TGTCTCCTCGAGGTCGAGGGATCTCCATAAGAG-30 , inserting an XhoI site. TNF-a was released from RIP-TNF-apBS by EcoRV/SalI digestion and replaced by the rabbit b-globin poly(A) PCR-amplified fragment. To express M3 in the pancreas, we constructed the pRIPM3 plasmid that placed M3 downstream of rat insulin promoter, which has previously been shown to target transgene expression predominately to the pancreatic islets and the kidney (Grewal et al., 1996). M3 was PCR amplified from a previously described plasmid (Parry et al., 2000) using the oligonucleotides 50 -ACAGAGGAATTCGCCGCCACCATGGCCTTC CTATCCACATCTGTG-30 , inserting an EcoRIsite and a consensus Kozak sequence, and 50 -ACAGAGGATATCTCAATGATCCCCAAA ATACTCCAG-30 , inserting an EcoRV site. This PCR fragment was subcloned into the EcoRI/EcoRV site of the RIP-poly(A) vector described above, creating pRIPM3. The transgene (RIP-M3) was released from pRIPM3 by SacII/KpnI digestion. Separation of the RIP-M3 transgene from vector DNA was accomplished by zonal sucrose gradient centrifugation

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as described (Yang et al., 2000). Fractions containing the transgene were pooled; microcentrifuged through Microcon-100 filters (Amicon, Beverly, MA) and washed five times with microinjection buffer (5 mM Tris-HCl [pH 7.4], 5 mM NaCl, 0.1 mM EDTA). To generate the mice, the RIP-M3 transgene was resuspended in microinjection buffer (5 mM Tris-HCl [pH 7.4], 5 mM NaCl, 0.1 mM EDTA) to a final concentration of 1 to 5 mg/ml, microinjected into ([C57BL/6J DBA/2]F2; Jackson Laboratory, Bar Harbor, ME) eggs, and transferred into oviducts of ICR foster mothers (Charles River Laboratories, Wilmington, MA), according to published procedures (Hogan et al., 1986). At 10 days after birth, a piece of tail from the resulting animals was clipped for DNA analysis. Identification of the transgenic mice was accomplished by PCR amplification of mouse tail DNA using specific primer sets. Specifically, the primers used for detection of the RIPM3 transgene were 50 -AGTGTGCAGGCTGCCTATCAGA ATGT-30 and 50 -TCTGATGTTTTAAATGATTTGCCCTCCC-30 , which are specific for a region in the rabbit b-globin poly(A) sequence. The endogenous ZP3 gene, used as an internal control, was amplified with the following primers: 50 -CAGCTCTACATCACCTGCCA-30 and 50 -CACTGGGAAGAGA CACTCAG-30 . PCR conditions were 94 , 30 s; 60 , 30 s; and 72 , 60 s. Eleven founders were generated from microinjection of this transgene into fertilized mouse eggs and 10 transgenic lines were established from these founders. RIP-M3 transgenic mice were healthy and fertile. To test for transgene expression, the pancreas was dissected and analyzed by immunohistochemistry, using an anti-M3 polyclonal antibody (rabbit antiserum raised against M3 expressed in Escherichia coli ). Seven transgenic lines showed expression of M3 (Fig. 9.1), and one of these lines (line 31) was selected for further experiments. We also confirmed by Western blot that islets from transgenic animals secreted M3 in vitro. Islets of Langerhans were isolated as previously

Figure 9.1 M3 expression in islets of Langerhans of transgenic mice. Representative picture of M3 immunostaining in the pancreata of control (WT, left) and RIP-M3 (right) mice.


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described (Gotoh et al., 1985). The common bile duct was clamped distal to the pancreatic duct junction at its hepatic insertion and the proximal common bile duct was then cannulated using a 27-gauge needle. Then, the pancreas was infused by retrograde injection of 2 ml of ice-cold collagenase solution (1.0 mg/ ml; Sigma, St. Louis, MO) in HBSS (Invitrogen, Carlsbad, CA). Pancreatic tissue was recovered and subjected to a 15-min digestion at 37 . Subsequently, ice-cold HBSS was added and the suspension was vortexed at full speed for 10 s. Islets were handpicked under a dissection microscope. To analyze M3 expression, 200 islets from control and transgenic animals were incubated for 24 h in glucose-free medium and supernatants were collected. Twenty micrograms of protein from each sample was processed. Blots were incubated with primary antibodies against M3 and a peroxidase-conjugated goat anti-rabbit IgG (Abcam Inc, Cambridge, MA). Chemiluminescence was detected using the Western Blot Chemiluminescence Reagent Plus (Enhanced Luminol, Perkin Elmer Life Sciences). We found that transgenic RIP-M3 mice secreted immunoreactive 44-kD M3 protein after 24 h of culture, which was not present in media from control islets. To examine whether constitutive expression of M3 in the pancreas had affected the development of lymphoid or nonlymphoid tissue, we examined H&E-stained sections from RIP-M3 transgenic mice. All major organs of the RIP-M3 mice, including pancreas, kidney, thymus, spleen, and peripheral lymph nodes, appeared normal by light microscopy (data not shown). To rule out that expression of M3 affected b-cell function we performed both in vitro (insulin content and insulin release) and in vivo experiments (glucose tolerance test). To measure the insulin content, 20 fresh islets were collected in Eppendorf tubes in duplicate. To extract insulin, islets were sonicated in acid ethanol (75% ethanol, 15% HCl), and insulin content was measured by ELISA (ALPCO Diagnostic, Windham, NH) following the manufacturer’s instructions. We did not find significant differences in the insulin content between islets from control and RIP-M3 mice (n ¼ 15 per group). Later, we performed the insulin secretion assay as described by Eizirik et al. (1992) with some modifications. Briefly, 20 islets from each group were set in quintuplicate in a 24-well plate and incubated in CMRL medium (Cellgro, Mediatech Inc, Herndon, VA) supplemented with 1.7 mM glucose or with 16.7 mM glucose for 60 min at 37 in an atmosphere of 95% O2/5% CO2. Insulin released into supernatants was measured by ELISA (ALPCO Diagnostic, Windham, NH). Although higher levels of secreted insulin were detected in supernatants of cultured islets from both control and RIP-M3 transgenic mice after they were exposed to high concentrations of glucose, there was no difference between the groups. Finally, we performed a intraperitoneal glucose tolerance test. After a 16-h fast, glucose (1.5 g/kg body weight in saline [0.9% NaCl]) was administered intraperitoneally (IP). The blood glucose was monitored at 0, 30, 60, 120, and 240 min using a one-touch blood Ascensia Elite XL glucometer

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(Bayer, Elkhart, IN). We found that the blood glucose curves on 8-week-old control and RIP-M3 transgenic mice were identical. Altogether these results indicate that the insulin synthesis and secretion are not altered by expression of M3.

3. M3 Expression in Islets of Langerhans Blocks CCL2-, CCL21-, and CXCL13-Induced Migration of Cells to Islets To test the hypothesis that M3 blocks chemokine function in vivo we crossed RIP-M3 mice to mice expressing CCL21 (Chen et al., 2002), CCL2, or CXCL13 (Martin et al., 2006) in insulin-producing b cells. Our laboratory and others have shown that transgenic expression of CCL21 induces specific migration of T cells (Luther et al., 2002; Martin et al., 2004), expression of CCL2 induces migration of monocytes and DCs (Fuentes et al., 1995; Martin et al., 2006), and that CXCL13 drives specific migration of B cells (Luther et al., 2000; Martin et al., 2006). Using mice coexpressing the chemokines and M3 in b cells, we asked whether M3 would block chemokine function and prevent the migration of leukocytes to the islets and if these blocking properties would be sustained even in the presence of increasing concentration of the chemokines. To determine the degree of islet infiltration we analyzed histological sections of the pancreas of different animals. Sections were stained with H&E or with antibodies against CD45 (BD Biosciences Pharmigen, San Diego, CA) and insulin (DAKO, Carpinteria, CA). Forty to 100 islets were examined for each mouse. Insulitis was scored as follows: no lesions; small or periinsular leukocytic aggregates, usually periductal infiltrates; medium or moderate insulitis with mononuclear cells infiltrating less than 50% of the islet architecture; and large or severe insulitis with more than 50% of the islet tissue infiltrated by mononuclear cells. We did not find infiltrates in islets of control or RIP-M3 transgenic mice regardless of age (n ¼ 8 each, data not shown). As expected, mononuclear infiltrates of varying sizes were found in the pancreatic islets of RIPCCL2, RIPCCL21, and RIPCXCL13 transgenic mice (Fig. 9.2 A to C; data not shown). M3 coexpressed with CCL2 in pancreatic islets (RIP-M3/CCL2 line 251), inhibited CCL2induced accumulation of mononuclear cells (Fig. 9.2D). A similar effect was observed when M3 was coexpressed with CCL21 in transgenic islets ( Jensen et al., 2003). This blockade was less pronounced in the presence of higher levels of CCL2 (RIPM3/CCL2 line 254, Fig. 9.2E); while the center of the islets appeared less infiltrated in RIPM3/CCL2 than in RIPCCL2 line 254 animals, both the number of islets presenting periislet infiltrates and the size of these infiltrates were similar between these

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Figure 9.2 Expression of M3 in b cells blocks migration of mononuclear cells induced by CCL2 and CXCL13. (A^F) Representative immunostaining for CD45 (red) and insulin (green) in pancreata of RIP-CCL2 (line 251 A and line 254 B), RIP-CXCL13 (C), RIP-M3/ CCL2 (line 251 D and line 254 E), and RIP-M3/CXCL13 transgenic mice.

two groups. We presume that the recruitment of cells into the perivascular space was due to the increased amount of CCL2 produced by the islets of animals in line 254. When coexpressed with CXCL13 or CCL21 in pancreatic islets, M3 inhibited CXCL13- and CCL21-induced accumulation of mononuclear cells (Fig. 9.2F, data not shown). The number of islets infiltrated and the total number of cells per islet were significantly reduced in each case. Furthermore, M3 expression disturbed the organization of the infiltrates promoted by CXCL13 and CCL21 expression. The lymphocytes did not segregate in specific areas, and tended to accumulate in the periphery of the islets or closer to the ducts. Taken together these results indicate that expression of M3 in pancreatic islets blocks the accumulation of mononuclear cells induced by the ectopic expression of CCL2, CCL21, and CXCL13, and that this effect is less pronounced in RIP-M3/CCL2 mice expressing higher levels of CCL2 in the pancreas.

4. M3 Expression in b Cells Blocks Cellular Infiltration and Prevents Diabetes Development Type 1 diabetes is an autoimmune disease characterized by a local inflammatory reaction in and around islets that is followed by selective destruction of insulin-secreting b cells (Foulis, 1987). Factors leading to

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the destruction of the islets are still not known, but it is well accepted that immune-based mechanisms involving macrophages and T cells are responsible for the death of the b cells (Adorini et al., 2002; Yoon et al., 1998). We tested the hypothesis that M3 could block chemokine function, infiltration of islets and diabetes development using two different models: multiple low doses of streptozotocin (MLDS) and the non-obese diabetic (NOD) mouse. The MLDS model is a widely used model that has clinical and histoimmunological features similar to those of human disease, with T cells and macrophages playing a major pathogenic role (Elliott et al., 1997). When administered in animals at multiple low doses, b-cell toxin streptozotocin (STZ) alkylates the DNA in islet cells (Like and Rossini, 1976) and promotes release of nitric oxide (Kwon et al., 1994). Subsequently, as a result of a novel b-cell antigen expression, mononuclear cells that infiltrate the islets start a multifactorial process (Kolb-Bachofen and Kolb, 1989) resulting in the expansion of pathological response from a ‘‘mini-autoimmune response’’ into chronic immune-mediated disease. We have previously shown that only CCL20 and CCL19 were expressed at low levels in pancreatic islets of control mice prior to MLDS treatment (Martin et al., 2007). However, MLDS treatment induced high expression of several chemokines, including CXCL9, CXCL10, and CCL2, prior to the onset of diabetes (Martin et al., 2007). To induce diabetes, mice (6 to 10 weeks of age) were injected IP with STZ (40 mg/kg freshly dissolved in cold 0.1 M citrate buffer, pH 4.5; Calbiochem, EMD Biosciences, San Diego, CA) for 5 consecutive days as previously described (Flodstrom et al., 1999). The blood glucose was monitored weekly over the following 35 or 70 days using a one-touch blood Ascensia Elite XL glucometer (Bayer, Elkhart, IN). Animals were considered diabetic when their blood glucose levels were greater than 250 mg/dl in two consecutive daily measurements. Mice in the control group received a corresponding volume of sodium citrate buffer alone. Four weeks after the beginning of treatment 85% of the control mice treated with MLDS were diabetic, but only 35% of the RIP-M3 tg/wt mice and, remarkably, none of the homozygous RIPM3 mice were diabetic. After 70 days, all control mice were diabetic, but only 60% of heterozygous mice and none of the homozygous RIP-M3 mice developed disease (n ¼ 5 per group) (Fig. 9.3A). To study the cellular changes promoted by STZ treatment, we performed semiquantitative analysis on insulin/CD45-stained sections, assessing 20 to 80 islets per animal. Three grades of infiltration were based on the number of CD45-positive cells in or around the islet: grade 1 (10 to 20 cells), grade 2 (20 to 50 cells) and grade 3 (>50 cells). At least 20 sections were evaluated per mouse and per day in a blinded fashion. Mice (n ¼ 3 per group) were treated with MLDS and were sacrificed at 7, 14, and 21 days after the first injection. Infiltration of CD45þ cells into the islets of control mice was first seen on day 7 and the number of inflammatory cells and

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Figure 9.3 Expression of M3 in b cells of NOD mice blocks development of diabetes. (A) Diabetes incidence in animals treated with multiple low doses of STZ. (B) Semiquantitative analysis of islet infiltrates in pancreas from control and RIP-M3 mice, before (day 0) and after (days 7,14, and 21) MLDS treatment. (C) Cumulative incidence of diabetes in NOD nontransgenic littermates (n ¼ 61) and NOD-M3 (n ¼ 66) mice. (D) Insulitis score of pancreata from NOD and NOD-M3 mice at 10 weeks of age (n ¼ 5/group).

frequency of infiltrated islets increased thereafter. By day 21, most control islets were infiltrated by mononuclear cells and had lost normal morphologic integrity. In contrast, a small number of infiltrating cells was found in RIP-M3 tg/wt mice only after 21 days of treatment, and the morphological appearance of the islets was normal. None of the homozygous RIP-M3 mice showed infiltrating cells 21 days after STZ treatment (Fig. 9.3B). NOD mice develop autoimmunity in several organs, in particular against insulin-producing cells of the pancreas, leading to type 1 diabetes (Atkinson and Wilson, 2002). Along with others, we have shown that chemokine expression precedes development of diabetes (Bouma et al., 2005; Cardozo et al., 2003; Morimoto et al., 2004). Prediabetic NOD islets expressed inflammatory (CCL1, CCL3, CCL4, CCL22, CCL24, CXCL9, and CXCL10) as well as homeostatic chemokines (CCL21) (Martin et al., 2008). To test the hypothesis that M3 can block chemokine function and

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prevent diabetes in an autoimmune environment, we backcrossed RIP-M3 mice onto the NOD background. N11 female NOD-M3 and their NOD littermates were monitored weekly for the development of hyperglycemia using a one-touch blood Ascensia Elite XL glucometer (Bayer, Elkhart, IN). Animals were considered diabetic when their blood glucose levels were greater than 250 mg/dl in two consecutive daily measurements. By 45 weeks of age, more than 80% of the NOD female mice (n ¼ 61) were diabetic. However, expression of M3 in islets of NOD-M3 (n ¼ 66) completely abrogated the development of diabetes (Fig. 9.3C). To investigate the effect of M3 expression by b cells on insulitis, we examined pancreata from NOD and NOD-M3 female mice at 10 weeks of age (n ¼ 5 per group). Insulitis was scored as follows: grade 0, no lesions; grade 1, periinsular leukocytic aggregates, usually periductal infiltrates; grade 2, less than 25% islet destruction; and grade 3, more than 25% islet destruction. Semiquantitative analysis of islet infiltrates showed that, as expected, most (95%) islets from NOD nondiabetic mice had periinsulitis, and in some cases developed a destructive inflammatory infiltrate, with marked loss of b-cell mass. In contrast, islets from NOD-M3 mice were virtually devoid of infiltrating cells and showed a normal complement of insulin-producing cells (Fig. 9.3D). Overall, these findings indicate that b-cell expression of M3 prevents islet mononuclear infiltration and diabetes development in NOD mice and after STZ treatment. Our results suggest that the use of a chemokine receptor antagonist that can block multiple receptors like M3 may be a viable strategy to ameliorate autoimmune diabetes.

5. Generation of a Conditional Transgenic System for Expression of M3 Conventional transgenic approaches have proven to be useful in defining the functional role of M3 in blocking chemokine functions. However, constitutive over expression of M3 does not mimic the potential therapeutic use of M3 as a chemokine blocker. To examine the usefulness of M3 as therapeutic agent, we took advantage of a tetracycline-dependent gene expression system (Gossen and Bujard, 1992). To generate transgenic mice in which expression of M3 could be induced conditionally, we used the tetracycline-dependent gene expression system originally described by Gossen and Bujard (1992). In this bi-genic system the tet-activator protein (rtTA) is expressed constitutively from the ‘‘activator’’ transgene (Fig. 9.4). In the presence of the tetracycline analogue doxycycline, the rtTA protein binds to a tetracycline-responsive promoter element (TRE) present on a ‘‘reporter’’ transgene, and induces expression

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CMV promoter SV40 p(A)

rtTA M3

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b-globin p(A) LacZ

b-globin p(A)

Figure 9.4 Transgenic system for conditional expression of M3.The system consists of an activator transgene that encodes the transcriptional activator rtTA and a responder transgene that encodes M3 and LacZ. In the presence of DOX, rtTA present in tissues tareted by the CMV/b-actin promoter, binds to a tetracycline responsive element (TRE) and drives expression of both M3 and lacZ. CMV promoter, CMV enhancer/ chicken b-actin promoter; rtTA, reverse tetracycline-controlled transactivator; b-globin p(A), rabbit b-globin polyadenylation signal; TRE, tetracycline-responsive element; SV40 p(A), SV40 polyadenylation signal.

of the transgene(s) of choice. The activator transgene used here is driven by the CMV enhancer/b-actin promoter, which promotes expression of transgenes in multiple tissues. To generate the responder transgenic mice, a bidirectional responder transgene was constructed containing the M3 gene and the LacZ gene encoding b-galactosidase (b-gal) (Fig. 9.4). Nine transgenic founder mice were generated from which four transgenic lines were derived. No b-gal activity was detected in frozen sections from kidney, liver, muscle, pancreas, and spleen of transgenic mice carrying the responder transgene only, indicating that responder transgene expression was silent in the absence of rtTA. The responder mice were crossed to transgenic animals carrying the rtTA gene driven by the CMV/b-actin promoter (activator transgene). These transgenic mice express rtTA in multiple tissues (Wiekowski et al., 2001). b-gal activity was detected by a chemiluminescence-based assay in the kidneys of transgenic mice derived from all four double-transgenic lines examined 48 h after a single IP injection of 500 mg DOX. The line with the highest level of induction was selected for further analysis. Tissues from mice receiving DOX were analyzed by histochemical staining. The highest levels of b-gal activity were noted in the liver and kidney, with an intermediate level in the heart. As expected, analysis of these tissue extracts by western blot analysis demonstrated the presence of M3 immunoreactivity in DOX-treated animals, but not in their nontreated control littermates, demonstrating that M3 expression was dependent on DOX (Pyo et al., 2004). To determine whether the conditional expression of M3 interfered with a physiological response, we used the bilateral femoral arterial injury model. Double transgenic mice received DOX 2 days before injury and daily through postoperative day 10, or received vehicle only. Arterial injury produced a substantial expansion of the intima at 4 weeks in vehicle-treated mice, resulting in an I/M ratio of 0.9 (0.23). In contrast, DOX treatment resulted in a 67% reduction in intimal area ( p < 0.01) and a 68% reduction in I/M

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ratio (p < 0.05). The data demonstrated that the inducible expression of M3 was able to block bilateral femoral arterial injury (Pyo et al., 2004).

6. Concluding Remarks Previous work using knockout or transgenic mice has demonstrated the role of particular chemokines in the recruitment of distinct cell populations, and their relevance to specific disease processes. These studies provided the rationale for the development of pharmacological reagents targeting chemokine receptors. The initial failure of some of these reagents in clinical trials has prompted a reevaluation of the concept of targeting specific chemokines or their receptors. Attempts to better define the role of the chemokine system have thus far included a better description of the pattern of expression of chemokines during particular disease conditions and experiments with chemokine blockers with multiple specificities. Using genetic approaches in mice, we showed that M3 is a powerful tool to understand chemokine function in vivo. First, we showed that M3 can block chemokine-induced mobilization of leukocytes in vitro and in vivo ( Jensen et al., 2003). Second, we showed that M3 expression could prevent development of disease in two different settings: autoimmune diabetes and bilateral femoral arterial injury (Martin et al., 2007, 2008; Pyo et al., 2004). In the former studies, M3 was constitutively expressed in the pancreas of mice and was able to inhibit islet mononuclear infiltration and diabetes development in NOD mice and after STZ treatment (Martin et al., 2007, 2008). The latter study took advantage of an inducible expression system to show that M3 could have a therapeutic role (Pyo et al., 2004). While these results suggest that multichemokine blockade may represent a superior alternative to single chemokine blockade, the usefulness of this approach remains to be fully tested vis-a`-vis safety and therapeutic delivery. The therapeutic use of virus-encoded chemokine blockers such as M3, may be effective in acute conditions, but may be problematic in chronic settings due to their antigenicity. In this regard, the development of multispecific oral small molecules may be a superior alternative. The existence of chemokine-binding proteins in different viruses and even in higher organisms, suggests that chemokine-binding proteins are used to evade the immune system. It is likely that different chemokine-binding proteins may have evolved to block sets of chemokines that are relevant during specific stages of infection. The challenge ahead will be to understand which chemokine sets are important during the various stages of disease and how to develop safe and effective strategies to interfere with them.


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C H A P T E R

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M-T7: Measuring Chemokine-Modulating Activity Mee Y. Bartee,*,†,‡ Erbin Dai,† Liying Liu,† Ganesh Munuswamy-Ramanujam,*,†,‡ Colin Macaulay,* Dana McIvor,* Grant McFadden,‡ and Alexandra R. Lucas*,†,‡ Contents 210 210 211

1. Introduction 1.1. Chemokine–glycosaminoglycan interaction 1.2. Discovery and identification of the M-T7 gene 1.3. M-T7 inhibits inflammation and vasculopathic disease in animal models 2. Protein Expression 2.1. Generation of viral constructs 2.2. Purification of M-T7 3. Quantifying the Effects of M-T7 In Vitro and Ex Vivo 3.1. Cell adhesion 3.2. Membrane fluidity 3.3. Ascites assay 4. Quantifying the Effects of M-T7 on Vascular Inflammatory Responses in Rodent Vascular Transplant Models 4.1. Aortic transplant model 4.2. Tissue staining 4.3. Morphometric analysis of aortic plaque area 4.4. Statistics 5. Preclinical Toxicity Testing References

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Abstract Chemokines are important for activation of a host of cellular immune and inflammatory responses including cell signaling, activation, and communication. M-T7, a myxoma virus protein, inhibits the activity of chemokines by direct binding to chemokines and/or with glycosaminoglycans (GAGs). To study the effects of this chemokine-modulating protein (CMP), we use a variety of in vitro * { {

Division of Cardiovascular Medicine, University of Florida, Gainesville, Florida, USA Department of Medicine, University of Florida, Gainesville, Florida, USA Department of Molecular Genetics and Microbiology, University of Florida, Gainesville, Florida, USA


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and in vivo techniques to evaluate M-T7 inhibition of inflammatory cells. To quickly analyze the effects of M-T7, changes in cell adhesion and membrane fluidity are measured as well as cell migration in mouse ascites. For more physiological analyses, an aortic transplant model in rodents is used to assess change in inflammatory cell infiltrates and vascular plaque growth (rejection). Utilization of the combination of these in vitro and in vivo techniques allows for a more complete study of the chemokine-modulating activity of M-T7, and can be used to study other immune and inflammation-modulating proteins.

1. Introduction 1.1. Chemokine–glycosaminoglycan interaction Chemokines are small 8 to 12 kDa proteins that attract cells of the inflammatory and immune response systems into arteries and tissues in reaction to damage or pathogen invasion ( Weber et al., 2004). These small chemoattractant proteins create a gradient along connective tissue and cell layers by binding to highly charged, sulfated, polysaccharide chains of glycosaminoglycans (GAGs). Increasing concentrations of chemokines bound to GAGs form this gradient, also termed an ‘‘array,’’ which directs cell taxis. Once bound to GAGs, exposed chemokine domains interact with G-protein– coupled receptors (GPCRs) to direct trafficking of cells in the innate and acquired immune response systems (Parish, 2005). While the chemokine– receptor interaction is reported to have wide overlap between receptor recognition and chemokine classes, that is, to be a nonspecific and promiscuous interaction, the secondary requirement for chemokine binding to tissue GAGs is now postulated to increase the specificity of cell to chemokine and receptor interactions. The chemokine–GPCR interaction has long been known to modify cellular activation responses, but only recently has it been reported that chemokine–GAG binding also modifies immune cellular responses ( Johnson et al., 2004a,b; Proudfoot et al., 2003). GAGs have the capacity to alter cellular adhesion through binding to selectins, adhesion molecules, chemokines, and growth factors (Forsberg and Kjellen, 2001). GAGs are also reported to alter activation of serine proteases and serpins in the coagulation cascades. There are extensive layers of both cell surface and connective tissue-associated GAGs, the dominant GAG being heparan sulfate (HS). Tissue and arterial GAGs include heparan sulfate, hyaluronan, chondroitin sulfate, dermatan sulfate, and keratan sulfate. GAGs can exist as free molecules or bound to proteins to form proteoglycans with chain lengths that vary from 1 up to 25,000 disaccharide units. GAGs are highly varied and are defined by disaccharide sequences, which are modified by acetylation and/or N and O sulfation as introduced by

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enzyme reactions. Of marked interest, some GAGs and proteoglycans bind to the cell surface and can interact with membrane proteins with the potential to alter cell-signaling pathways and activation. The interactions of GAGs with cells are capable of markedly altering innate and adaptive immune cell responses. Upwards of 50 chemokines and 20 receptors are classified into four classes defined by C-terminal cysteine residues (C, CC, CXC, and CX3C) with the CC class reported as more selective for monocytes and lymphocytes and the CXC class for neutrophils. However, there is extensive redundancy in the chemokine interaction with cells and cell surface receptors (Allen et al., 2007). Chemokines recognize and bind specific GAG species based on the structure, which is varied even within the same type of GAG, and charge, which is highly negative. This chemokine–GAG interaction is now believed to introduce an additional layer of complexity. The combination of chemokine–GAG and chemokine–GPCR selectivity is postulated to increase the specificity of chemokine activity (Allen et al., 2007; Handel et al., 2005; Johnson et al., 2004b) through the required dual interaction of chemokines with both selected GAGs and selected receptors. Although current understanding of chemokine–GAG interactions is incomplete, this interaction is proving to play a pivotal role in cellular mobilization, recognition, and activation.

1.2. Discovery and identification of the M-T7 gene M-T7 was initially identified as an interferon-gamma receptor (IFN-gR) homologue that is secreted by the highly lethal rabbit poxvirus, myxoma virus (Upton et al., 1992). The M-T7 gene is encoded in the terminal inverted repeat region of the myxoma genome, and is the seventh openreading frame (Fig. 10.1A). When M-T7 is expressed in an intact virus, mortality of European rabbits is very high. When the gene is deleted in myxoma virus, a more benign infection with much reduced morbidity and mortality in rabbits results (Upton et al., 1992). Many viral genes have evolved to express proteins, working at very low concentrations, postulated to be in the femtomolar range, which effectively support viral growth and block host immune defense assaults. During this evolution, these immunemodulating proteins have developed secondary and tertiary functions, expanding the viral armamentarium (Mossman et al., 1995, 1996). In an innovative study, Lalani and McFadden (Lalani et al., 1998) discovered that this M-T7 IFNgR homologue binds to chemokines as a secondary function. In this study, M-T7 was reported to bind a wide range of chemokines including mouse, rat, and human C, CC, and CXC chemokines. Binding to IFNg was conversely species-specific and limited to rabbits alone (Mossman et al., 1995). Of greater interest, M-T7 interaction with chemokines is postulated to block binding of chemokines to

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A


B

M-T7 pDONR221

eG

FP

M-T

7-H

is6x

pFastBacDual

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BV BV

Figure 10.1 M-T7 sequence and cloning: M-T7 is a chemokine-modulating protein with a sequence homology to rabbit IFN-g. (A) Model of M-T7 generated in SWISSMODEL workspace and the amino acid sequence of the protein. (B) Protein was expressed using a baculovirus-mediated expression system. First, the M-T7 cDNA construct in pDONR221 was used as a template for generating a C-terminal His tag construct by PCR. This PCR product was cloned into pFastBacDual-eGFP, an insect expression vector.This plasmid construct was shuttled through DH10Bac cells for transposition of M-T7 and eGFP into a bacmid. Bacmids were purified and transfected into Sf 21 cells for generation of baculovirus expressing M-T7-His6x. (Panel A from Arnold, K., Bordoli, L., Kopp, J., and Schwede, T. (2006). The SWISS-MODEL workspace: A web-based environment for protein structure homology modelling. Bioinformatics 22, 195^201; Kopp, J., and Schwede,T. (2004). The SWISS-MODEL repository of annotated three-dimensional protein structure homology models. Nucleic Acids Res. 32, D230^D234; and Schwede, T., Kopp, J., Guex, N., and Peitsch, M. C. (2003). SWISSMODEL: An automated protein homology^modeling server. Nucleic Acids Res. 31, 3381^3385.)

GAGs, providing a mechanism that effectively prevents formation of a chemokine–GAG gradient, and thus reducing inflammatory cell invasion. This M-T7 function represents a unique inhibitory mechanism targeting a different domain in chemokines. Rather than interference of chemokine– GPCR binding, M-T7 is postulated to reduce chemokine–GAG interaction. Other groups have created a series of chemokine mutants that lack GAG-binding epitopes and which have the capacity to inhibit chemokinemediated inflammatory cell migration ( Johnson et al., 2004a). This novel chemokine-inhibitory action is evolutionarily advantageous for myxoma virus. Expression of chemokine inhibitors (CMPs) that target both the GPCR and GAG binding domains, in addition to blocking IFNg activity in rabbits, allows myxoma virus to efficiently downregulate the immune response. Of further benefit, these unique viral proteins have potential as new immunomodulatory therapeutic agents (Seet et al., 2001).


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1.3. M-T7 inhibits inflammation and vasculopathic disease in animal models In an initial study of inflammatory vasculopathic disease, the Lucas laboratory contrasted the ability of M-T7 to inhibit arterial inflammation and atherosclerotic plaque growth after balloon angioplasty injury in rabbit and rat models. Equivalent reductions in inflammatory cell invasion and plaque growth were detected in rabbit and rat models with M-T7 treatment. While the rabbit model might reflect M-T7–mediated blockade of IFNg, as well as inhibition of chemokine gradient formation, the IFNg homologue function is specific to rabbits. The inhibition of plaque in rats is thus believed to be due to interruption of chemokine-mediated activation of inflammatory cell responses (Liu et al., 2000). In subsequent work, M-T7 has also been demonstrated to reduce inflammation and plaque growth in rat aortic transplant models 4 weeks after a single intravenous injection of nanogram doses of M-T7. Inhibition of monocyte and T-cell infiltration into the vessel wall was reversed in part through simultaneous infusions of selected chemokines (Liu et al., 2004). A study in the Zhong laboratory (Bedard et al., 2003) subsequently confirmed reduction of chronic rejection and vasculopathy in a rat renal allograft transplant model at 5 months follow-up after an initial 10-day course of M-T7 treatments. In this paper, we present techniques used for expression and analysis of the chemokine-inhibitory function of M-T7 in both in vivo and in vitro systems.

2. Protein Expression 2.1. Generation of viral constructs Expression of some of the myxoma viral gene products has been unsuccessful in conventional bacterial protein expression systems. Exact mechanistic reasons are unknown, but protein folding and glycosylation may be contributing factors. Since the functionality of M-T7 is not easily tested, we selected an expression system that has been proven successful for expression of another myxoma virus protein, Serp-1. A baculovirus-mediated expression system in Sf 21 (Spodoptera frugiperda) (Invitrogen) and High Five (Trichoplusia ni ) (Invitrogen) cells was used for the expression and purification of M-T7. M-T7 has also been expressed in a Chinese hamster ovary (Weber et al., 2004) mammalian cell system, but we will describe the baculoviral expression here. To generate the virus, a C-terminal His–tagged construct was cloned into a pFastBacDual (Invitrogen) expression vector containing an eGFP (enhanced green fluorescent protein) reporter driven by the p10 promoter. The reporter gene is important for selection of foci containing the M-T7

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expressing virus. Sf 21 cells were used to generate the M-T7 baculovirus. The doubling time of Sf 21 cells is 24 h as opposed to 72 h for Sf 9 cells, another commonly used insect expression cell line, which means that Sf 21 cells have the advantage of being expanded more rapidly. Bacmids (baculovirus shuttle vector) are generated in DH10Bac (Invitrogen) cells by transforming with the pFastBacDual construct (Fig. 10.1B). Colonies are screened using blue/white colony screening by spreading 100 ml of 100 mM IPTG (isopropyl-beta-D-thiogalactopyranoside) and 40 ml of 20mg/ml X-gal (5-bromo-4-chloro-3-indolyl-b-D-galactopyranoside) onto selection plates (LB plates with 50 mg/ml kanamycin, 10 mg/ml tetracycline, 7 mg/ml gentamicin). Purification of bacmids can be done with standard DNA purification kits such as QIAprep Spin Miniprep Kit (Qiagen). However, due to the size of the bacmid, 150 kb, we use 100 ml of elution buffer heated to 50 C to facilitate elution off the spin column. Incorporation of M-T7 is verified by PCR (polymerase chain reaction) analysis of the bacmid. Antibiotics may be used in Sf-900 II SFM media (Invitrogen), but for the transfection reaction, the media should not contain any, just as in mammalian transfection reactions. Sf 21 cells are seeded onto six-well tissue culture plates in 1 Grace’s Insect Media (Invitrogen) at 1 106 cells/ml for a total of 2 ml (1 h before transfection) to allow the cells to adhere. One to two micrograms of DNA are preincubated in 100 ml of 1 Grace’s Insect Media in one tube and 6 ml of Cellfectin II (Invitrogen) reagent with 100 ml of 1 Grace’s Insect Media in another tube. This is incubated in the hood for 15 min before the DNA and Cellfectin II containing reagents are mixed together for 30 min at room temperature (RT). The transfection reaction mixture needs to be brought up to a final volume of 1 ml with 1 Grace’s Insect Media. Before adding the mixture to cells, cells have to be washed in 1 Grace’s Insect Media and then aspirated. The transfected cells should be incubated at 27 C for 5 h before replacement of the transfection reagent with Sf-900 II SFM. Two days after transfection, foci of eGFP expressing cells should begin to be visible, and at 72 h, baculovirus-expressing M-T7 can be harvested from the media. The collected viral supernatant can be used to infect Sf 21 cells for further amplification of the virus stock. To determine the viral titer of the construct, a viral plaque assay can be performed. Two milliliters of 5 105 Sf 21 cells/ml can be seeded onto six-well plates and allowed to adhere for 1 h on a flat surface for even cell distribution. A serial dilution of the viral stock in Sf-900 II SFM media is then set up with a final plating volume of 1 ml per well. The media from the plated cells is replaced with the diluted virus and incubated for 1 h at RT. In the meantime, 10 ml of melted sterile, 4% plating agarose should be mixed with 30 ml of 1.3X Sf-900 (Invitrogen) media and placed in a 37 C water bath. Virus must be removed quickly from the six-well plates (beginning with


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high to low concentrations) and then 2 ml of the agarose mixture should be added. The agarose should harden in 15 min. Plates are placed in a container with wet paper towels on the bottom to prevent the plates from drying out. Care needs to be taken not to disturb the monolayer of cells. Incubate in a 27 C incubator for 4 to 10 days. Formation of viral foci should be observed daily on the microscope for the appearance of green fluorescent foci. When no new foci form on 2 consecutive days, then viral titer can be calculated based on the number of foci in the well with the most diluted virus. Virus will need to be amplified by infecting suspension cultures of Sf 21 cells at MOIs (multiplicity of infection) of 0.001 to 0.005 for 24 h and then harvesting virus by spinning down the cells and collecting the virus-containing supernatant. Baculovirus can be stored at 4 C for active use of the virus; however, for long-term storage, freezer stocks should be made.

2.2. Purification of M-T7 M-T7 protein can be expressed in suspension cultures of High Five insect cells. Cells seeded at 1 106 cells/ml are infected with baculovirus containing the M-T7 gene construct at an MOI of 1 and grown in culture for 24 to 72 h before collection of secreted protein from the media. We express a C-terminal His–tagged construct of M-T7. To purify the protein from the media, M-T7 is concentrated using a 10 kDa cutoff filter, Amicon Ultra (Millipore), and buffer exchanged in 50 mM NaH2PO4 þ 300 mM NaCl þ 10 mM imidazole, pH 8.0, with Snakeskin 10 kDa cut-off dialysis tubing (Pierce). A two-step method is used to purify M-T7, first on Ni-NTA (nickelnitrilo-triacetic acid) (Qiagen). The buffer-exchanged supernatant is first centrifuged to remove any particulates in the sample. The supernatant is added to pre-equilibrated Ni-NTA slurry (50 mM NaH2PO4 þ 300 mM NaCl þ 10 mM imidazole, pH 8.0), and allowed to mix overnight at 4 C. The slurry is added to a column the next day, and allowed to flow through by gravity. The samples are then washed in 50 mM NaH2PO4 þ 300 mM NaCl þ 20 mM imidazole, pH 8.0, and eluted with 50 mM NaH2PO4 þ 300 mM NaCl þ 250 mM imidazole pH 8.0 in three 3 ml elution fractions. The elution fractions are further concentrated with a 10 kDa molecularweight cut-off Amicon Ultra centrifugal filters (Millipore), and buffer equilibrated with 50 mM Tris þ 150 mM NaCl, pH 8. These samples are further purified by size exclusion chromatography, which separates the proteins by molecular mass. Fractions are loaded onto a HiLoad 16/60 Superdex 75 (GE Healthcare) FPLC (fine-pressure liquid chromatography) column, and fractions are collected. Protein purity is verified by running the samples on SDS-PAGE (sodium dodecyl sulfate–polyacrylamide gel

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electrophoresis) and gels stained with Coomassie stain. Samples used for in vivo experiments are kept under sterile conditions after filtration through a 0.22 micron filter.

3. Quantifying the Effects of M-T7 In Vitro and Ex Vivo M-T7 has been shown to be a chemokine-modulating protein (CMP). To understand how this CMP affects inflammatory cells, changes in cellular responses to M-T7 treatment can be measured both in vitro and in vivo. Cell adhesion and membrane fluidity are established assays that monitor cellular activation in vitro, whereas in vivo cell migration using a peritoneal ascites assay performed in mice can be measured. Further analysis by flow cytometry can be conducted ex vivo from the ascites, but will not be discussed.

3.1. Cell adhesion The THP-1 (Tamm-Horsfall Protein 1) cell line is a human monocytic cell line that also possesses some macrophage characteristics. The THP-1 cell line is used in models for the study of cell activation and migration. During inflammation, monocytes migrate to the injury site along a chemokine gradient as described in Section 1. To study how M-T7 affects this phenotype, cell adhesion of activated THP-1 cells can be monitored. THP-1 cells (1 106 cells/ml) are labeled with calcein acetoxymethyl ester (calcein AM) (1 mg/ml of media) (Invitrogen) for 1 h in media (37 C/ 5% CO2/humidified). Calcein AM is a membrane-permeable fluorescent probe that is taken up by viable cells that provides a cell-labeling marker. Once the label is intracellular, endogenous esterases modify the compound, exposing a calcium-binding site. After binding calcium, the calcein AM can be excited at 495 nm and the intensity of emitted fluorescence measured at 515 nm. Labeling cells with calcein AM is a simple way to measure the number of adhered cells. Alternatively, if a filter is used in a stacked, twowell Boyden chamber, then the same calcein fluorescence label can be used to monitor cell migration through filters, basement membrane layers, or other cell layers such as endothelium in vitro. Cells are treated with activators found in normal circulating blood or in damaged tissues where the inflammatory system is upregulated. The activators that have been tested in our lab include the following: 50 ng MCP-1, 3 U/ml urokinase plasminogen activator (u-PA) (American Diagnostica),


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1 mg/ml recombinant human tissue plasminogen activator (t-PA) (HoffmannLa Roche), 1 U/ml thrombin (Warner-Lambert Canada) or 1 mg/ml phorbol myristate acetate (PMA) (Sigma-Aldrich Chemicals) for 1 h (37 C, 5% CO2, humidified). Excess calcein and activators are removed by washing with PBS (centrifuge at 1200 rpm for 8 min at RT; discard supernatant). The cells are subsequently resuspended in media at a concentration of 1 106 cells/ml and aliquoted into tubes. Saline or M-T7 (50 ng to 1 mg) is then added to the cell suspension. One aliquot of cells is set aside for generation of a standard curve. Cells at a concentration of 1 105 cells per 100 ml are plated on fibronectin or collagen III–coated, black 96-well plates, and incubated for 1 h (37 C, 5% CO2, humidified). Fibronectin plates are prepared by incubating a 96-well black plate with 5 mg of fibronectin in 100 ml of PBS per well for 24 h at 4 C. Collagen plates are prepared by similarly incubating plates with 1 mg of collagen in 100 ml of PBS per well for 4 h at 4 C. Uncoated plastic wells can also be used for these assays, as activated monocyte/macrophage cells will adhere to plastic surfaces. Cell adhesion and migration can also be performed using endothelial cell layers using similar assays to assess endothelial and monocyte cell interactions. After the 1 h incubation, nonadherent cells are removed with two cold PBS washes. This is a crucial step: the PBS should be cold so as not to strip off the adhered cells from the plate and the pipetting should be gentle enough to only remove nonadhered cells. Adherent cells are quantified by measuring calcein fluorescence using a spectrofluorometer (Thermo Fisher Scientific, Waltham, MA). To calculate the number of adherent cells, the fluorescent intensity is compared to a standard. This standard curve is generated by performing serial dilutions, using the same numbers of cells for each well, and measuring the fluorescence intensity of the calcein labeled cells set aside earlier. As mentioned previously, M-T7 is a chemokine-modulating protein (CMP). THP-1 cells activated with chemokines or chemical compounds result in the increased number of adhered cells. The inhibitory effect of M-T7 on THP-1 activation from chemokines or other activators can be seen in the change in the number of adhered cells.

3.2. Membrane fluidity Change in membrane fluidity is a measure of cellular activation. The change in core rigidity, or conversely fluidity of a membrane can be measured using 1,3-bis-(1-pyrenyl)propane (BPP) (Invitrogen), a fluorescent probe that crosses into the core lipid bi-layer (Fig. 10.2B). An activated cell has a more fluid membrane, whereas an unactivated cell is comparatively rigid. In a fluid membrane, BPP more readily forms a dimer, also termed an excimer formation (Fig. 10.2). The monomer emits light at a wavelength of 390 nm while the dimer (excimer) emits light at 485 nm, thus providing a ready

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Fluorescence intensity

A

B 300 200

−Saline (Iexc/Imon = 1.69)

100 0

−P PMA(Iexc/Imon = 0.89)

Dimer

Monomer

−100 300 400 500 600 700 Wavelength (nm)

Figure 10.2 Membrane fluidity measurement with BPP. BPP is a fluorescent probe useful for measuring the activation of cells by chemokines.The linker between the two pyrene rings affects the ‘‘monomer’’ versus ‘‘dimer’’ state of the probe. In unactivated cells, the lipid bilayer is more rigid, and therefore BPP is less mobile, resulting in a higher ratio of dimers. In activated cells, the membrane is more fluid, resulting in more mobility of BPP, and a lower ratio of dimers. In addition to the fluorescence emission at 390 nm of the monomer, when BPP is a dimer (also termed an excimer), there is an additional emission at 485 nm.The ratio of the excimer to monomer state can be used to determine the activated state of cells.

means to distinguish the presence of pyrene monomers and excimers. The ratio of excimer to monomer signal can be used to determine the activated state of a cell (Fig. 10.2A). THP-1 cells are resuspended at a concentration of 1 106 cells/ml in growth media (RPMI 1640, 10% fetal bovine serum, Pen/Strep, Sigma). A final concentration of 1 mg/ml BPP (dissolved in DMSO) is added per 1 ml of cells and incubated at 37 C, 5% CO2, humidified, for 3 h. This incubation time is important because excessive incubation will result in intracellular BPP, which would give erroneous results. However, too short of an incubation will lead to inefficient labeling of cells, resulting in a weak signal and increased signal-to-noise ratio. In our laboratory, we have found that 3 h seems to be the appropriate time for the BPP to incorporate into the lipid bi-layer. At the end of the incubation, cells are pelleted (centrifuge cells at 1200 rpm for 8 min, RT, discard supernatant). Cells are resuspended in growth media at 1 106 cells/ml and divided into 1 ml aliquots in 1.5 ml microcentrifuge tubes. Activation of cells is done with any one of the following activators: 50 ng MCP-1, 50 ng MIP-1a, 50 ng RANTES, 3 U/ml urokinase plasminogen activator (u-PA) (American Diagnostica), 1 mg/ml recombinant human tissue plasminogen activator (t-PA) (Hoffmann-La Roche), 1 U/ml thrombin (Warner-Lambert Canada) or 1 mg/ml phorbol myristate acetate (PMA) (Sigma-Aldrich) for 1 h (37 C, 5% CO2, humidified). Subsequently, cells are washed (centrifuge at 1200 rpm, 8 min, RT; discard supernatant), resuspended in growth medium, and treated with 50 ng of M-T7 in 100 ml in saline or saline only for 1 h


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(37 C, 5% CO2, humidified). To analyze the samples, cells are washed (centrifuge at 1200 rpm, 8 min, RT; discard supernatant), resuspended in 250 ml PBS. Aliquot 100 ml of cells per well into black plates. PBS is used as a blank. Samples are analyzed in a spectrophotometer by exciting at 320 nm and reading the emission at 390 nm (monomer) and 485 nm (excimer) (Fig. 10.2A). The ratio of excimer to monomer gives a measure of membrane fluidity (Fig. 10.2).

3.3. Ascites assay This mouse ascites assay is a simple and readily established animal model with minimal stress to the animal during the assay. This mouse ascites cell model is used for the study of cell migration and activation after chemokine stimulation. Ascites, also known as peritoneal cavity fluid, is fluid within the smooth, transparent membranes that line the inside of the abdomen (peritoneum) and surround the bowel and other abdominal organs. An excess of peritoneal fluid is a common clinical finding with a wide range of causes. The model used here relies on the injection of chemokines that are known to be chemoattractants, bringing cells from the blood into the peritoneal space. For this peritoneal ascites model, mononuclear cell migration and fluid accumulation are induced by intraperitoneal (IP) injection of any one of the following mouse chemokines: MCP-1, MIP-1a, RANTES. Only one chemokine is injected into each animal at a concentration of 50 ng/100 ml of saline. A major role of chemokines is to guide the migration of cells. Local administration of a chemokine, that is, MCP-1, by IP injection results in inflammatory cell invasion, dominated by early neutrophil infiltration. A more delayed mononuclear cell infiltration of predominantly monocytes, but also T lymphocytes, is then detected in response to IP injection of CC chemokines, MCP-1, RANTES, and MIP-1a. There is a smaller monocyte response to CXC chemokine injections. In our research, we have found that M-T7 injection significantly reduced inflammatory cell invasion in mouse ascites. No adverse effects, specifically no excess stress, bleeding, infection, or mortality, have been reported with chemokine injection or with M-T7 treatments. The mice have minimal if any distress and do not develop large amounts of fluid that cause discomfort by distending the animal’s belly. The fluid and cells are collected from mice under general anesthetic at the time of sacrifice. Ascites fluid and cells are only collected at one time point. For the mouse ascites model, mice are restrained and held with their ventrum exposed. A 22 gauge needle is inserted into the abdominal cavity in the lower right quadrant to avoid the cecum and bladder. The needle is directed toward the animal’s head at an angle of 15 to 20 degrees and inserted approximately 5 mm. Initially, fluid is aspirated to ensure that an

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abdominal viscus (such as bladder or colon) has not been penetrated. If clear yellow ascites fluid is detected, then 50 ng of a chemokine (MCP-1, MIP-1a, or RANTES) in 100 ml sterile saline is injected into the abdominal cavity. M-T7 is given either intravenously (IV) via tail vein or via IP injection depending on whether local or systemic responses are to be assayed. A single dose of 1.5 mg of M-T7 in 100 ml sterile saline is given by IV or IP injection. After injection, the animals are observed carefully at least twice daily, and monitored for signs of distress, hunching, chattering, decreased activity, dyspnea, anorexia, or local ascites-peritonitis. Animals having any pain or discomfort (hunching, chattering, etc.) are given 0.05 to 0.1 mg/kg weight of buprenorphine, an analgesic that is given subcutaneously (SC). After 18 h following IP injection, animals are sacrificed for collection of peritoneal fluid and cells. Mice are euthanized with an IP injection of 120 mg/kg weight of pentobarbital. In prior work, during the 18 h monitored, minimal if any abdominal distention was observed, and the risk of other side effects or mortality rate has been less than 5%. The abdominal cavity is washed with 5 ml of saline. Using sterile technique, ascitic fluid is collected with a syringe by placing an 18 or 19 gauge needle into the abdomen. Cells from ascites are isolated for further analysis by FACS, cell adhesion, and membrane fluidity.

4. Quantifying the Effects of M-T7 on Vascular Inflammatory Responses in Rodent Vascular Transplant Models In order to determine the effects of M-T7 as a chemokine-modulating protein, its role in the control of the inflammatory response was tested in a rat aortic allograft transplant model. This model is an example of a host-versusgraft response, resulting in aggressive inflammation of the transplanted vascular tissue. Significant reduction in aortic plaque formation and inflammatory cell invasion into the grafted tissue on comparison against saline or protein controls allows the study of the pro/anti-inflammatory response of M-T7 and other chemokines in vivo. Mouse aortic transplant models are also used, providing a mechanism for assaying tissue responses to transplant in specific mice strains, such as specific gene knock out or knock in models. It is important to note that the protocol we describe here is specific to rats, and that conditions for mice, such as analgesics and surgical equipment, differ for mice.

4.1. Aortic transplant model Rodent aortic transplantation entails complex surgical procedures and requires expertise in rat anatomy, knowledge of vascular surgery techniques, and fine manipulation of tissue. Special equipment, such as a Moller-Wedel


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EOS 900 operating microscope and SurgiVet Vaporizer with a rat mask attachment and a gas scavenging system, are required. We will describe the rat aortic transplant surgical model in detail, but many of the techniques here can be transferred to the mouse model with careful attention to the differences in body size for rats and mice, specifically transplanted aortic section length, suture sizes, and dosing of anesthetics. 4.1.1. Anesthetic Rats are anesthetized using a mixture of ketamine and xylazine (23.75 mg/ ml ketamine plus 1.25 mg/ml xylazine) in sterile saline. This mixture is given by IP injection at 0.1 ml/100 g weight. The rat belly is shaved and then prepared for surgery by a three-step sterilization: (1) wash with betadine soap, (2) wash with alcohol, and (3) clean with a betadine topical wash. For pain control, an SC injection of buprenorphine is given (0.05 to 0.1 mg/kg weight of the rat) immediately after the anesthetic. Isoflurane gas, an anesthetic, is given by mask with 2% oxygen as needed at a titration of 1 to 3% isoflurane until surgery is finished. 4.1.2. Aortic transplant donor To produce a chronic rejection model, the preferred donor-to-recipient mismatch pairs used in our laboratory include ACI (inbred, RT1a/RT2b/ RT3a) donor to Lewis (inbred, RT1l/RT2a/RT3a) recipient or Lewis (inbred, RT1l/RT2a/RT3a) donor to Sprague Dawley (outbred) recipient rats. The latter uses the non–inbred Sprague Dawley strain, and thus the more pure ACI donor to Lewis recipient rat strain model is preferred. After anesthetizing the rat (ACI strain) an incision is made using sterile technique from the xiphoid process to the symphysis pubis. The aorta below the renal arteries is exposed and the rat donor aorta is resected from the area below the renal artery to the iliac bifurcation (Fig. 10.3). The tissue is placed in sterile PBS. Subsequently, the rat is sacrificed by exsanguination. 4.1.3. Aortic transplant recipient Two vessel clips are placed in the middle of the aorta below the renal artery, corresponding to the aortic diameter of the sections removed from the donor rat. The aorta (3 to 5 mm in length with matched diameter) is attached by end-to-end anastomosis using interrupted sutures around the circumferences of the aorta (Fig. 10.3). Vessel clips are then removed and vessel pulsation checked, at which time the transplanted rat abdomen is also assessed for bleeding sites. The inner muscle and connective tissue are closed with an absorbent suture (4-0 coated VICRYL polyglactin 910 absorbable suture). Dermal layers of the abdominal wall are closed with either interrupted or continuous suture (sterile nylon suture will be used to close the dermal layer).

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Donor aorta

Donor rat

Transplant rat

Figure 10.3 Schematic of rat aortic transplant:The donor rat is illustrated in black and the recipient rat in purple. After the donor rat is anesthetized, aorta is removed from the region between the renal artery (where the kidney is attached) and the bifurcation of the aorta (where the aorta branches). Side branch vessels off of the aorta are first tied and removed and the aorta is divided in half. One-half of the aorta is used for the saline control and the other half for the M-T7 treated recipient rat. The donor aorta is transplanted according to end-to-end anastomosis in the recipient rat.

M-T7 is infused in a total volume of 200 ml through a 30-gauge needle via IV injection into the tail vein or penile vein (male rodents) when the clips on the aorta are removed. Protein is infused only as a one-time dose (dose ranges of 0.03 to 300 mg/g) immediately after transplant. Animals are monitored until stable and checked initially every 5 to 20 min, and then every half-hour until stable. The transplanted rat is kept warm with blankets if the recovery is prolonged. Normally, the animal is monitored in the surgical area for 2 to 4 h before transport to an animal holding facility. If the rat appears to have any discomfort (hunching, chattering, etc.), the animal is given an additional postoperative dose of buprenorphine. The rats are monitored at least daily for 4 weeks following the surgery. Sutures are removed at 7 to 10 days post surgery. At 4 weeks following the surgical procedure, the rats are humanely euthanized by euthanyl injection containing 240 mg sodium pentobarbital. The mortality rate for the aortic transplant model is 15 to 20%. Rats that show evidence of complications as a result of the transplant, such as nerve damage, aneurysm formation, hemorrhage (usually seen up to 5 days), ischemia, infection, or difficulty with normal locomotion, are euthanized. In some cases, the rat is lame temporarily on one side due to poor blood flow, and therefore must be monitored carefully, given additional pain killer, and food and water provided individually for 24 to 48 h.

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4.2. Tissue staining After 4 weeks, the transplanted aortas are removed from the recipient rats as described for the donor rats (see Section 4.1.2) and the harvested aorta is fixed, embedded, and stained for histological microscopic analysis. Aortic sections are cut into three equal-length segments from immediately above and below the suture lines. Aortic cross-sections can be stained with hematoxylin and eosin or Masson’s trichrome (Fig. 10.4). In our experience, the structural architecture of the aorta is best preserved with paraffin embedding, which is described in the following paragraphs, as opposed to cryopreservation. The aortic tissue sections are fixed in 10% neutral buffered formalin (Fisher) overnight at RT in a tissue processor. To dehydrate the tissue, the following incubations are performed for 1 h each at RT: 1:70% ethanol, 2:95% ethanol, 3:95% ethanol, 4:100% ethanol, 5:100% ethanol, 6:100% ethanol, 7:xylene, 8:xylene, 9:xylene, 10:100% ethanol. The aorta is then rehydrated in water for 1 h. Next, tissue is embedded in paraffin wax (Paraplast plus tissue embedding medium) for 1 h at 60 C. To secure the tissue for slicing, it is embedded in additional paraffin in a mold. The tissue is then cut into 4 to 5 micron sections using a standard microtome. To define the specific layers of the aorta, we use both hematoxylin and eosin (H&E) as well as Masson’s trichrome staining. With trichrome staining, smooth muscle cells stain red, collagen is green, and elastin and/or nuclei are black. With H&E staining, the invading monocytes and lymphocytes are more readily identified. Although the internal elastic lamina and collagen are readily identified as serpiginous pink lines, the trichrome stain more clearly defines these connective layers that divide the intimal, medial, and adventitial layers of the arterial wall. Immunohistochemical analysis of selected cell types or individual proteins and antigens is also used to further define cellular changes in the tissues after transplantation. We will describe Saline control

200x

M-T7 treated

200x

Figure 10.4 Trichrome staining of rat aortic transplant.Transplanted aortas from rats treated with either saline or M-T7 were trichrome stained. The arrows indicate the boundary of the plaque. The areas between the arrowheads demarcate the limits of the intimal plaque area. Compared to saline, M-T7 significantly reduced plaque formation.

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Masson’s trichrome staining in detail in the next section as a basic staining approach that provides rapid identification of plaque growth and fibrosis after aortic transplant. The paraffin has to be removed from the tissue before staining. The sections are first placed in a 60 C oven for 30 min to melt the paraffin wax and then placed in a tissue processor with the following settings: 1:xylene for 5 min, 2:xylene for 5 min, 3:100% ethanol for 2 min, 4:100% ethanol for 2 min, 5:95% ethanol for 2 min, 6:70% ethanol for 2 min, and 7:water for 2 min. 1. Tissue is stained with trichrome stain. Trichrome staining defines the internal elastic lamina which serves to outline the intimal plaque and medial layers. Tissue sections are stained with Verhoeff’s hematoxylin for 5 min (for Verhoeff’s hematoxylin, combine immediately before use 20 ml of 5% hematoxylin in ethanol and dissolve by gentle heat without boiling), 8 ml of 10% ferric chloride in water, and 8 ml Verhoeff’s iodine (2% iodine and 4% potassium iodine in water). The section is then washed for 10 min with water. 2. Dip slides in 1.4% ferric chloride 10 to 12 times until the tissue becomes dark. This can be verified under the microscope. 3. Incubate with 95% ethanol for 5 min. 4. Incubate with Biebrich-scarlet-acid-fuchsin solution for 10 min. Wash for 10 min with water. 5. Stain tissue with phosphomolybdic-phosphotungstic-acid for 15 min (1.25 g phosphomolybdic acid and 1.25 g phosphotungstic acid in 600 ml of water). 6. Incubate in fast green for 10 min (1% fast green in 1% acetic acid). Wash with water for 5 min. The fast green stain loses color readily, so the tissue needs to be checked under the microscope. If the stain is too light, the sample needs to be restained with fast green for another 10 min. 7. Dip sample in 1% acetic acid several times. 8. Dip into 95% ethanol 20 times. 9. Dip into 100% ethanol 20 times. 10. Dip into xylene two times to get rid of the alcohol. 11. Mount the sample.

4.3. Morphometric analysis of aortic plaque area After staining, the plaque size is examined and measured via microscopy. The intimal plaque image is captured by an Olympus DP71 camera attached to an Olympus BX51 microscope. Several microscopic analysis systems are available for measuring plaque area and lumen narrowing as well as for assessing changes in invading cells and tissue composition. Intimal plaque area is quantified in our lab using Image Pro 6.0 (MediaCybernetics).


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This software allows the user to manually outline the plaque area as well as trace the internal elastic lamina and external elastic lamina. Lumen narrowing can be assessed by measuring the IEL area and subtracting the plaque area. In a normal artery, the lumen area should be close to the IEL area, as the intimal layer is in general composed of one or two endothelial cell layers. Invading inflammatory cells can be counted in three separate high-power field areas and can be further normalized to the area of tissue where cells are counted. Cells can be specifically stained using immunohistochemical staining techniques to identify cell types and are counted in the intimal, medial, and adventitial layers for each specimen. Visualization of each sample is adjusted and normalized to the objective lens of the microscope, to provide accurate measurement of plaque areas. The software then quantifies the enclosed plaque area, and that number is used to calculate the significance of plaque reduction compared to the saline controls.

4.4. Statistics When aorta samples are processed, each aortic transplant sample is cut into two or three equal-length segments, and then plaque areas are measured on two to three sections from each sample. This provides a minimum of four to six stained plaque sections from each aorta for analysis. The mean value for plaque area, internal elastic lamina, lumen area, as well as percentage narrowing is calculated for each animal. These mean values are then utilized for all later statistical analyses. If more than two treatment variables are present in the study, an analysis of variance (ANOVA) is calculated to assess significance. Individual treatment groups can then be assessed using Fischer’s post-hoc least significant difference (PLSD) analysis. If only two experimental treatment groups are examined, then a Student’s unpaired, two-tailed t-test is used. For assessing cellular invasion, three areas in three differing sites using 100 microscopic objective are counted (cells per field) for each sample section and for each of the three arterial layers, intima, media, and adventitial layers. Occasionally, linear regression analysis is also performed for selected studies for correlations. The Stat view statistics program is used for all statistical analysis.

5. Preclinical Toxicity Testing Once there is proof of potential therapeutic value in preclinical animal models, a new drug must then be rigorously tested in preparation for clinic. The average time for development of a new therapeutic is 15 years from initial inception to application. For clinical development, a new antiinflammatory protein such as M-T7 requires: (1) expression and purification

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to a clinically acceptable grade, (2) an acceptable functional assay, (3) a therapeutic target, and (4) toxicity testing in preclinical and clinical trials (Serabian and Pilaro, 1999; Tolner et al., 2007). These steps in drug development are outlined in brief in the following:

Expression of a biologic, in this case an anti-inflammatory protein derived from a virus, is generally performed in a cell-based expression system that has been previously approved for expression of biologic agents already in clinic (Serabian and Pilaro, 1999). This expression requires a clean facility using good manufacturing procedures (GMP procedures) where the protein can be expressed at high yield (Tolner et al., 2007). Purification protocols for the protein must also be developed to produce a product with minimum impurities (Serabian and Pilaro, 1999). Each agent is also carefully tested for potentially toxic impurities, such as endotoxins. The expression and purification must also take into account cost of processing and storing of proteins for clinical use, as a product that is prohibitively expensive to manufacture will often fail to proceed to development for clinical use. An acceptable assay is necessary to assess drug half-life and tissue distribution, monitor clinical responsiveness, and identify potential target organs for side effects (toxic responses). One pitfall in drug development can be a lack of a functional assay for detection of active drug in the test subjects. The assay correlates drug activity with clinical responses. Assay development relies on an understanding of the mechanism of action of the drug as well as predicted cellular and molecular responses. While preclinical studies may detect broad anti-inflammatory functions, the reagent must then be targeted for a specific pathogenesis, or disorder, where there is both a clinical need as well as potential for efficacy (Serabian and Pilaro, 1999). Efficacy in animal models does not necessarily translate into efficacy in humans. Production of a therapeutic that is addressing a problem that is already well treated by current medications is not particularly useful. Centers specializing in testing therapeutic targets for new drugs have emerged in recent years. Cell samples derived from patients, such as cells isolated from the circulating blood, lung wash (alveolar lavage), or even bone marrow and joint fluid aspirates have become available. These samples are then tested for responsiveness to a new drug in vitro. Other studies are performed in silico, using software programs that model molecular targets or potential for therapeutic application in selected disease populations. Final analysis will, however, require in vivo testing, first in preclinical animal models and finally in clinical trials in humans. Preclinical testing includes both the discovery phase as well as toxicity testing (Serabian and Pilaro, 1999). The preclinical efficacy studies will not only determine efficacy in a selected animal model but will also assess


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drug delivery routes and dosing to provide a guide for effective dose range with minimal adverse events (toxicity). While initial efficacy or preliminary experimental studies are performed in basic research labs, further testing in general for toxicity or potentially to confirm efficacy are performed in labs that use good lab practice (GLP) approaches, where animal testing is carefully monitored and each stage of testing standardized. Toxicity will assess half-life, organ targets at risk for toxic responses, and immunogenicity of the reagent tested. The preclinical toxicity testing will encompass generalized effects on mortality, morbidity, and additionally a half-life analysis. These studies are aimed at a specific clinical application and the studies will vary depending on the disease to be addressed. Toxicity testing is generally done in a facility that specializes in preclinical toxicity testing under GLP conditions. This work must be very meticulously performed with rigorous standards. The baseline toxicity tests are generally performed in rodent models. For some selected studies, analyses are performed in primate models, as for example when testing for cardiac toxicity, wherein the potential effects on electrocardiogram (ECG), cardiac enzymes, and heart function can be assessed with minimal invasive approaches using simple blood tests and transthoracic noninvasive echocardiography (ultrasound of the heart), reducing potential discomfort and harm to the test subjects. If proven to have low toxicity, the subsequent analysis is used to approach the Food and Drug Administration (FDA) in the United States, the Health Protection Branch (HPB) in Canada, or equivalent governmental regulatory agencies in Europe and elsewhere in the world for assessment and approval for Phase I testing in normal volunteers. Phase I testing is then performed in normal volunteers to assess safety in humans. These tests are again performed in facilities that specialize in early clinical studies with prior approval by regulatory boards such as the FDA or HPB. Development of a new biologic is thus a complex and long-term endeavor, but with careful planning and a good team, can be successfully accomplished.

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Role of the Chemokine Scavenger Receptor D6 in Balancing Inflammation and Immune Activation Elena M. Borroni,* Chiara Buracchi,* Benedetta Savino,* Fabio Pasqualini,* Remo C. Russo,*,† Manuela Nebuloni,‡ Raffaella Bonecchi,* Alberto Mantovani,§ and Massimo Locati§ Contents 1. Introduction 2. Methods 2.1. Immunohistochemistry 2.2. TB infection model 2.3. Chemokine neutralization in vivo 2.4. Cell transfection 2.5. Immunofluorescence and confocal microscopy analysis 2.6. Chemokine scavenging assay 3. Results 4. Discussion References

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Abstract Chemokines play a major role in the induction of inflammatory reactions and development of an appropriate immune response by coordinating leukocyte recruitment. The appropriate control of the chemokine system involves several chemokine decoy receptors, with distinct specificity and tissue distribution, defined as nonactivating chemokine receptors able to bind the ligands and target them to degradation. The best-characterized representative of these receptors is D6, which is located on lymphatic endothelium and controls most inflammatory CC chemokines. Here we will discuss the expression and * {

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Laboratory of Leukocyte Biology, Department of Translational Medicine, University of Milan, IRCCS Istituto Clinico Humanitas, Italy Department of Biochemistry and Immunology, Instituto de Ciencias Biologicas, Universidade Federal de Minas Gerais, Belo Horizonte, Brazil Pathology Unit, L. Sacco Institute of Medical Sciences, University of Milan, Milan, Italy Department of Translational Medicine, University of Milan, IRCCS Istituto Clinico Humanitas, Via Manzoni, Rozzano (Milano), Italia


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regulation of D6 during challenge with the pathogen, and its role in dampening inflammation in tissues and draining lymph nodes and in the organization of a protective immune response.

1. Introduction Leukocyte trafficking is a key element in the orientation of innate and adaptive immunity, and it is mainly controlled by chemokines, small secreted proteins with chemotactic and cytokine-like activities (Mantovani, 1999). These molecules are classified according to structural properties related to the number and position of conserved cysteine residues in two major (CXC and CC) and two minor (C and CX3C) subfamilies, and according to their production in homeostatic (i.e., produced constitutively) and inflammatory (i.e., produced in response to inflammatory or immunological stimuli) chemokines (Charo and Ransohoff, 2006). Chemokine biological activities are mediated by chemokine receptors, a distinct subfamily of G protein–coupled receptors that mainly transduce intracellular signals through the activation of heterotrimeric Gai proteins. A distinct subfamily of chemoattractant receptors unable to sustain signaling activities, which includes the chemokine receptors D6, Duffy antigen receptor for chemokines (DARC, also known as the Duffy antigen), and CCX-CKR, has recently been identified (Mantovani et al., 2006). The D6 molecule recognizes an unusual broad spectrum of ligands, being able to interact with most agonists at inflammatory CC chemokine receptors from CCR1 through CCR5, while homeostatic CC chemokines, agonists at CCR6 to CCR10, are not recognized, nor are chemokines belonging to other subfamilies. While the ligand-binding profile is unusually broad, its expression is fairly restricted, D6 being detectable only in placenta and on endothelial cells of lymphatic afferent vessels in skin, gut, and lung (Martinez de la Torre et al., 2007; Nibbs et al., 1997, 2001). In vivo results in several models, including challenge with complete Freund adjuvant, have clearly demonstrated that D6 and its scavenger function are mandatory for controlling the outcome of an inflammatory reaction (Liu et al., 2006; Martinez de la Torre et al., 2005). Here we focus on how D6 is regulated during the development of an immune response, and on its role in balancing the inflammatory and protective adaptive immune response after challenge with Mycobacterium tuberculosis (TB).

2. Methods 2.1. Immunohistochemistry D6 expression was analyzed in human lung lymph nodes obtained from patients with pulmonary tuberculosis. Tissues were selected on the basis of the presence of giant cell–associated necrotic granulomas, and the tubercular

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etiology was confirmed by histochemical and biomolecular methods. Consecutive sections of 3 mm width from formalin-fixed, paraffinembedded tissues were dewaxed in xylene, rehydrated in a progressive ethanol scale, and pretreated in a microwave oven (two cycles of 5 min at 780 W, in 0.25 mM EDTA buffer, pH 8.0) for antigen retrieval. Slides were incubated for 2 h at room temperature (RT) in a humid chamber with a rat antihuman D6 monoclonal antibody (1:100; R&D Systems) or a mouse anti human CD68 monoclonal antibody (1:1500; Dako, Denmark) to detect macrophages. The reactions were revealed by nonbiotin, mouse-on-rat, HRP-polymer kit (Biocare Medical), and MACH 4TM Universal HRPpolymer kit (Biocare Medical), respectively, with 3,30 diaminobenzidine free base as chromogen (brown staining).

2.2. TB infection model D6-null mice were generated as previously described ( Jamieson et al., 2005). Homogeneous populations were established by backcrossing heterozygous mice to C57BL/6J (WT) mice for more than eight generations. WT and D6-null mice were bred in a specific pathogen-free/viral antibody–free barrier facility and used in accordance with institutional guidelines in compliance with national and international law and policies. Mice were infected via the intranasal (IN) route with the TB H37Rv strain (2 103 CFU in 20 ml), resulting in the reproducible delivery of 50 to 100 viable CFU. Each experimental group consisted of 7 to 10 mice.

2.3. Chemokine neutralization in vivo To block inflammatory chemokines, mice were treated with a mixture of goat antibodies to the CC chemokines CCL2/MCP-1, CCL3/MIP-1a, and CCL4/MIP-1b), and a monoclonal antibody to CCL5/RANTES purchased lyophilized from R&D Systems, resuspended in sterile phosphatebuffered saline (PBS), and mixed as previously described (Martinez de la Torre et al., 2005, 2007). Mice were given intraperitoneal (IP) injections of 200 ml of the mixture, equivalent to 100 mg of each antibody. Alternatively, mice were treated with 400 mg of individual antibodies specific to a single CC chemokine. On the same days, control mice received IP injections equivalent to 400 mg of irrelevant antibodies (normal goat IgG, Sigma-Aldrich) in 200 ml PBS. Mice were injected weekly, starting from the 3rd week after infection with TB.

2.4. Cell transfection CHO-K1/D6 cells were transiently transfected (80% confluency) with the Rab11-S25N/pEGFP plasmid by using Lipofectamine 2000 (Invitrogen) protocol as follow. Twenty microliters of Lipofectamine were added to

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500 ml OptiMEM medium (Gibco) and incubated for 5 min at RT. Lipofectamine was then combined with (8 mg) DNA, mixed gently, and incubated at RT for 20 min to allow DNA-Lipofectamine complexes to form. DNA-Lipofectamine complexes were added to T25 flasks and incubated at 37 C in a CO2 incubator for 24 h.

2.5. Immunofluorescence and confocal microscopy analysis CHO-K1/D6 (1 105) cells were seeded onto glass dishes in 24-well plates and grown at 37 C for 18 h. Cells were stimulated with 100 nM CCL2 in DMEM-F12, supplemented with 1% bovine serum albumin and fixed with 4% paraformaldehyde for 15 min, permeabilized with 0.3% Triton X-100 in PBS for 5 min, and incubated with 10% normal goat serum (Dako, Glostrup, Denmark) for 30 min. Fixed cells were incubated with primary antibodies for 2 h at RT. After washing three times with 0.05% Tween 20 in PBS (pH 7.4), coverslips were incubated with secondary antibodies for 1 h, extensively washed, and incubated with DAPI for 5 min. Specimens were mounted in FluoSave (Calbiochem; San Diego, CA) and high-resolution images (1024 1024 pixels) were acquired sequentially with a 60 1.4 N.A. Plan-Apochromat oil immersion objective by using a FV1000 laser-scanning confocal microscope (Olympus, Hamburg, Germany). For z-stack analysis, high-resolution images (1.024 1.024 pixels) corresponding to n ¼ 50 optical sections (slice ¼ 100 nm) were sequentially acquired as described above. Differential interference contrast (DIC) (Nomarski technique) was also used. Images were assembled and cropped using the Photoshop software (Adobe Systems, San Jose, CA). Quantitative colocalization and statistical analysis were performed using ImarisColoc software, version 4.2 (Bitplane AG, Zurich, Switzerland).

2.6. Chemokine scavenging assay CHO-K1/D6 cells were plated the day before the experiment in 96-well dishes at the concentration of 3 104 cells/well. Cells were then incubated at 37 C for 4 h in 60 ml of DMEM-F12 supplemented with 1% bovine serum albumin, 0.1 nM of 125I-CCL2 or 125I-CCL4, and indicated concentrations of unlabeled CCL2/CCL4 or 10 nM CCL2/CCL4 for indicated time points. Proteins in the supernatants were precipitated with 12.5% trichloroacetic acid (Carlo Erba Reagents, Milan, Italy) at 4 C for 15 min, and the radioactivity present in both soluble and insoluble fractions was measured with a WIZARD automatic g counter (Perkin Elmer, Waltham, MA). Degradation rate curves were obtained by data fitting with nonlinear regression and interpolation with Michaelis-Menten equations using Prism4 software (GraphPad Software, San Diego, CA).

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3. Results Expression of the D6 receptor during TB infection was investigated by immunohistochemistry on lung lymph nodes from patients with pulmonary tuberculosis. As shown in Fig. 11.1A, D6 expression was prominent in lymphatic endothelial cells, while CD68-positive macrophages did not stain for D6, both within and around granulomas. To better define the role of D6 in this pathological setting, D6-null mice were infected via the IN route with TB. At the dosage used, WT mice resisted to the infection, while D6-null mice showed significant mortality (Fig. 11.1B). Interestingly, the exaggerated susceptibility of D6-null mice to TB infection was not due to impaired control of the infectious agent, as the bacterial loads in the lung, liver, and spleen were not different in WT and D6-null mice. Conversely, a prominent inflammation-driven tissue damage was observed in several tissue districts, including lung, liver, and kidney, in D6-null animals, as compared to WT mice (data not shown) (Di Liberto et al., 2008). We therefore investigated the role of individual inflammatory CC chemokines by treating TB-infected D6-null mice with monoclonal antibodies blocking

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Figure 11.1 D6 expression and role of CC chemokines during TB infection. Panel A shows two serial sections of lung lymph nodes stained for D6 (right panel) and CD68 to detect macrophages (middle panel).Two granulomas with a high number of macrophages are present (indicated by filled areas in the left panel), while the D6 positivity is restricted to lymphatic vessels (indicated by dotted lines in the left panel). Panel B shows survival rate of WTand D6-null mice after IN exposure in the presence of blocking monoclonal antibodies to inflammatory CC chemokines, administered alone or in combination.

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the inflammatory CC chemokines under D6 control CCL2, CCL3, CCL4, and CCL5. As shown in Fig. 11.1B, none of the monoclonal antibodies provided individually was able to reverse the exaggerated D6 susceptibility to TB. On the contrary, a cocktail of monoclonal antibodies blocking all four inflammatory CC chemokines provided a partial but significant reversion of this phenotype. These results indicate that the induction of inflammatory chemokines after TB challenge is required to induce a protective immune response, and that D6 clearance of CC chemokines is needed to contain the immune response and prevent excessive tissue damage. As D6 provides a nonredundant negative regulator of the chemokine system, it was particularly relevant to investigate its regulation during the development of the infection. However, consistently with results previously obtained in in vitro settings, we have been unable to detect any significant change in D6 transcript levels in the liver, spleen, and lungs (data not shown). After ligand engagement, chemokine receptors undergo rapid internalization and recycling, allowing targeting of the ligand to lysosome and its degradation. Different from signaling chemokine receptors, we observed that D6 expression of the cell membrane was significantly upregulated in response to receptor engagement by its ligand CCL2. Receptor upregulation was particularly evident for elevated concentrations of the ligands (Bonecchi et al., 2008), and this increased expression correlated with an increased efficacy in ligand degradation (Fig. 11.2A and B). To better understand the ligand-dependent induction of receptor upregulation, D6 localization in the cell was investigated by confocal microscopy. Under resting conditions, most of the receptor was stored in perinuclear compartments, whereas ligand engagement induced relocation of a significant fraction of the receptor to the cell membrane. Concomitantly, the strong colocalization of D6 with the recycling endosome marker Rab11 observed under resting conditions was significantly reduced after ligand engagement (Fig. 11.3A and B). To investigate the molecular mechanisms responsible for the ligand-induced increased expression of D6, we overexpressed a GFP-tagged, Rab11, dominant negative mutant (Rab11S25N-EGFP), and evaluated D6 expression and colocalization after CCL2 engagement. As shown in Fig. 11.3C and D, a causative role of Rab11 in this process was demonstrated by the observation that the Rab11 dominant negative mutant was able to largely prevent receptor redistribution on the cell membrane. The colocalization of signals from the endogenous Rab11 and the transfected Rab11-S25N-EGFP demonstrated the specificity of the analysis (Fig. 11.3E and F).

4. Discussion D6 is the best-described chemokine decoy receptor and plays a crucial role in controlling leukocyte recruitment in inflamed tissues and the levels of inflammatory chemokines in draining lymph nodes (Borroni et al., 2006).

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Figure 11.2 D6 increased its scavenging rate upon ligand stimulation. (A) CHO-K1/ D6 cells were incubated for 4 h at 37 C with 0.1 nM of 125I-CCL4or 125I-CCL2 and 1 to 100 nM of CCL4 (□) or CCL2 (▪); (B) CHO-K1/D6 cells were incubated with 0.1 nM of 125 I-CCL2 and 10 nM CCL2 for the indicated time points. Data are representative of (A) the degradation rate (nmoli/s) of TCA soluble fraction of supernatants or (B) the percentage of radioactivity counted (cpm) over CHO-K1 cells in the TCA soluble (○) and TCA insoluble () fractions of the supernatants. Results (mean standard error) are from triplicates of one representative experiment of three performed.

This atypical CC chemokine receptor shares 30 to 35% sequence identity to conventional (i.e., signaling) chemokine receptors but lacks sequence motifs that are critical for the activation of Gai. Consistent with this, D6 does not support G-protein–dependent signaling functions usually activated by chemokine receptors (Bonecchi et al., 2004; Fra et al., 2003; Nibbs et al., 1997), but appears to be structurally adapted to perform chemokine scavenging being constitutively internalized and recycled back to cell surface and not downregulated after chemokine engagement (Galliera et al., 2004; Weber et al., 2004). The role of D6 as a regulator of inflammatory chemokines in in vivo settings has been investigated in different models of local inflammation using D6-null mice. Of relevance, D6-null mice showed an exacerbated inflammatory response in a model of inflammation induced by phorbol

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Figure 11.3 D6 constitutive and ligand-induced recycling is supported by a Rab11dependent mechanism. Confocal images of immunofluorescence stained CHO-K1/D6 cells. Panels show representative experiments of the double staining of D6 (red) with endogenous Rab11 (green) (A, B); D6 (red) with exogenous Rab11-S25N/pEGFP (green) (C, D); colocalization of endogenous Rab11 (blue) with transfected Rab11-S25N/pEGFP (green) (E, F).

ester skin painting and in a model of skin inflammation induced by subcutaneous injection of complete Freund adjuvant ( Jamieson et al., 2005; Martinez de la Torre et al., 2005). In particular, in this second model a significant percentage of D6-null animals also developed macroscopic granuloma-like lesions, which were evident only in a minority of WT littermates. In both models, increased levels of inflammatory CC chemokines were detected locally, and pretreatment with chemokine receptors blocking antibodies was able to prevent development of lesions, demonstrating that the increased inflammatory response was caused by an inefficient control of the chemokine system in the absence of D6.


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Although the specific roles of individual CC chemokines in the recruitment of various leukocyte populations have not been defined, both reports described an imbalance restricted to inflammatory CC chemokines, consistent with the D6-binding profile. In summary, the two models highlighted a nonredundant role of D6 in the control of local inflammation in skin, although molecular mechanisms involved are still not defined and deserve further investigation, as well as the evaluation of a similar role of D6 in other tissues. The increased inflammatory response observed in D6-null mice after injection of complete Freund adjuvant, which contains inactivated TB, prompted us to evaluate its role after challenge with the living pathogen (Di Liberto et al., 2008). As compared to WT littermates, D6-null mice preserved their ability to control the infectious agent, as shown by the comparable number of TB CFU. On the contrary, D6-null mice showed an increase in inflammatory infiltrate in lung and lymph nodes, in the levels of proinflammatory cytokines (TNFa, Il-1b, IFNg) in bronchoalveolar lavage and serum, and in the mortality rate. Given the role of D6 to act as chemokine scavenger and the detection of increased concentrations of CC chemokines (CCL2, CCL3, CCL4, and CCL5) in D6-null mice, a causative role of unbalanced chemokine concentrations was hypothesized. Blocking individual CC chemokines did not reverse the increased mortality observed in D6-null animals, indicating a redundant role of CC chemokines and the need to control the chemokine system in its entirety to properly resolve the inflammatory response, but the block of most CC inflammatory chemokines of relevance for this experimental model (CCL2, CCL3, CCL4, CCL5) using a cocktail of antibodies partially reversed the inflammatory phenotype and the increased lethality observed in D6-null mice. Interestingly, however, this approach also led to less-controlled growth of TB. Thus, during TB infection the survival of the host requires the action of inflammatory chemokines to coordinate an adequate protective immune response and control the pathogen, but the control of inflammatory CC chemokines by the D6 decoy receptor is mandatory for the resolution of the inflammatory reaction (Fig. 11.4). The expression of D6 on afferent lymphatic vessels supports the hypothesis that this receptor could be at least in part responsible for the well-known role of this compartment as active disposal system for inflammatory chemokines (Fra et al., 2003; Nibbs et al., 2001; Palframan et al., 2001). Consistently with this, D6 expression was detected on lymphatic vessels and not in granuloma-associated macrophages in human tuberculotic lymph nodes. As for other scavenger receptors, D6 has recently been shown to be regulated by soluble inflammatory mediators (McKimmie et al., 2008). Moreover, we recently reported that chemokine stimulation increased D6 membrane expression through its rapid mobilization from a Rab11-positive

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Figure 11.4 Role of D6 in the immune response to TB infection. Survival to TB challenge requires a balanced inflammatory response supporting a protective antimicrobial response without extensive tissue damage. Chemokines are key to this balance, with D6 playing a crucial role in chemokine removal (middle panel). In the absence of chemokines the inflammatory response is blunted and as a consequence an inefficient antimicrobial response lead to host death (left panel). Conversely, the absence of D6 does not significantly impact on antimicrobial response, but an excess in chemokine concentrations leads to host death for extensive tissue damage (right panel).

compartment and improves its efficiency in chemokine scavenging in a time- and ligand-dependent manner (Bonecchi et al., 2008). This behavior is not observed with signaling chemokine receptors, and resembles the activity of enzymes, which catalyze chemical conversion of specific substrates into related products. Indeed, D6 is able to mediate a time-dependent conversion of intact ligand (substrate) into degraded fragments (product) and to improve its degradation rate upon increasing the concentration of ligand. Moreover, similar to what was previously described for D6 (Fra et al., 2003; Galliera et al., 2004; Weber et al., 2004), certain enzymatic pathways undergo constitutive cycling, a phenomenon also referred to as a ‘‘futile cycle’’ because it is an energy-expensive process without energy gain. It has been proposed that this energy cost is necessary for extremely sensitive systems because small changes in the rate of one of these reactions causes a rapid change in net flux, avoiding the lengthy process of protein synthesis and allowing large changes in cells signaling to occur on a rapid time scale (Royle and Murrell-Lagnado, 2003). Constitutive cycling has also been demonstrated for several transmembrane proteins, such as receptors at mammalian-synapse (Park et al., 2004) adhesion molecules, ion channels, and transporters (Dugani and Klip, 2005; Royle and Murrell-Lagnado, 2003). Interestingly, the macrophage scavenger receptor for modified lipoproteins stabilin-1 (Prevo et al., 2004) and the macrophage scavenger receptor for hemoglobin CD163 (Schaer et al., 2006)

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Figure 11.5 Regulation of D6 activity under homeostatic and inflammatory conditions. Under homeostatic conditions, inflammatory chemokines are barely detectable, most D6 is mostly retained in a Rab11-positive intracellular compartment, few receptors constitutively cycle from the cell membrane, and no ligand scavenging activity is detectable (figure to the left). After inflammation is triggered, significant levels of chemokines are induced, D6 engagement induces the redistribution of the stored pool from the Rab11-positive compartment to the cell membrane, and a significant increase in ligand-scavenging activity is detected (right panel).

also undergo a constitutive internalization and recycling process that is significantly increased in response to ligand binding. Similarly, D6 displays enhanced scavenging activity after ligand engagement (Bonecchi et al., 2008), providing further demonstration that its activity is quite similar to the catalytic function of enzymes. Thus, it is tempting to speculate that constitutive cycling and ligand-dependent receptor upregulation might represent mechanisms used by several receptors, including D6, to rapidly modulate ligand uptake and degradation depending on the immediate needs of the tissue (Fig. 11.5).

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Structure–Function Dissection of D6, an Atypical Scavenger Receptor Robert J. B. Nibbs,* Pauline McLean,*,† Clare McCulloch,*,† Alan Riboldi-Tunnicliffe,† Emma Blair,*,† Yanshi Zhu,† Neil Isaacs,† and Gerard J. Graham* Contents 1. Introduction 1.1. Investigating D6 function using in vitro model systems 1.2. D6 as a model for determining chemokine receptor structure Ackowledgments References

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Abstract Chemokines direct leukocyte migration by activating intracellular signalling pathways through G-protein coupled chemokine receptors. However, they also bind to other surface proteins, including a group of molecules which we refer to as ‘atypical’ chemokine receptors. One such molecule is D6. D6 is structurally-related to other chemokine receptors, and binds specific proinflammatory chemokines with high affinity, but surprisingly, when expressed in heterologous cell lines, it is unable to transduce signals after chemokine engagement. Instead, by using the approaches outlined in this chapter, evidence has emerged that D6 acts as a chemokine scavenger which uses unique intracellular trafficking properties to continuously sequester extracellular chemokines into cells. It is envisaged that this suppresses inflammation in vivo by limiting pro-inflammatory chemokine bioavailability, and indeed, D6 deficient mice show exaggerated inflammatory responses to a variety of challenges. In addition to the in vitro functional studies, we also describe the methods we have used to express, purify and analyse large quantities of D6 protein. The unusually high stability of D6 and its broad subcellular distribution enables D6 to be expressed to very high levels in transfected cells, making it possible, at least in principal, to produce enough D6 to allow for purification of quantities * {

Division of Immunology, Infection and Inflammation, Glasgow Biomedical Research Center, Glasgow University, Glasgow, United Kingdom Department of Chemistry, Glasgow Biomedical Research Centre, Glasgow University, Glasgow, United Kingdom


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Robert J. B. Nibbs et al.

suitable for crystallisation. This is a key step on the path towards generating a three-dimensional structure of the molecule. Thus, the protocols we outline have helped establish chemokine scavenging as a novel paradigm in chemokine biology, and may also ultimately provide unprecedented insight into the structure of D6 and other chemokine receptors.

1. Introduction Chemokines exert their biological activity by binding to heptahelical G-protein–coupled receptors (GPCRs) on the surface of their target cells which activate intracellular signaling pathways (Rot and von Andrian, 2004). Currently, 10 signaling receptors for the CC chemokines (CCRs1–10) have been identified, along with 6 for the CXC chemokines (CXCRs1–6) and single receptors for the XC and CX3C families (Rot and von Andrian, 2004). However, there also exists a small but discrete family of ‘‘atypical receptors,’’ currently consisting of DARC, D6, CCXCKR, and CXCR7 (reviewed in Graham, 2009; Mantovani et al., 2006; Nibbs et al., 2003). These molecules show structural similarity to signaling chemokine receptors, and bind specific subsets of chemokines with high affinity. Thus, DARC and D6 bind many inflammatory chemokines; CCX-CKR binds to CCL19, 21, and 25; and CXCR7 interacts with CXCL11 and 12. Importantly, however, when expressed in heterologous cell lines, these molecules are unable to couple to signal transduction pathways used by typical signaling chemokine receptors and cannot stimulate cell migration. In fact, in these model systems, atypical receptors appear completely unable to transduce signals on chemokine binding. This is associated with subtle alterations in the canonical DRYLAIV motif found in the second intracellular loop of the signaling chemokine receptors, and modifying the DKYLEIV motif of D6 to DKYLAIV confers weak ligand-induced signaling activity (Nibbs, unpublished). Inability to signal in vitro led to hypotheses that atypical receptors act as chemokine scavengers and/or transporters designed to regulate chemokine abundance and/or localization, and thereby indirectly control leukocyte migration driven through signaling chemokine receptors. Roles for D6 and CCX-CKR as chemokine scavengers have now been supported by in vitro studies of transfected cell lines that have clearly shown these molecules to have specific biochemical properties that enable them to progressively scavenge large quantities of extracellular chemokines (Bonecchi et al., 2004, 2008; Comerford et al., 2006; Fra et al., 2003; McCulloch et al., 2008; Weber et al., 2004). D6 achieves this by constitutively trafficking to and from the cell surface via early and recycling endosomes (Bonecchi et al., 2008; Galliera et al., 2004; McCulloch et al., 2008; Weber et al., 2004). Thus, when an extracellular chemokine binds surface D6, it is

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rapidly internalized. Constitutive trafficking removes the need for signaling (which is required for effective internalization of typical chemokine receptors), and simultaneously avoids the obvious constraints to scavenging of receptor desensitization and surface receptor depletion. Interestingly, chemokine binding to D6 is particularly sensitive to the low pH found in early endosomes (Weber et al., 2004), such that any internalized chemokine is rapidly dislodged from D6, retained inside the cell, and targeted for degradation by lysosomes (Weber et al., 2004). Meanwhile, internalized D6 continues on its constitutive path back to the cell surface to become available for more chemokine scavenging. This in vitro work created a new paradigm of chemokine receptor function, and consistent with a scavenging role, D6-deficient mice develop exaggerated responses to inflammatory stimuli ( Jamieson et al., 2005; Martinez de la Torre et al., 2005; Nibbs et al., 2007; Whitehead et al., 2007), display enhanced inflammationassociated miscarriage (Martinez de la Torre et al., 2007), show increased susceptibility to inflammation-dependent cancer (Nibbs et al., 2007), and develop fatal inflammatory responses after Mycobacterium tuberculosis lung infection (Di Liberto et al., 2008). Notably, these aberrant responses are often associated with elevated chemokine abundance. Thus, it is clear that D6 is fundamentally involved in the regulation of in vivo inflammatory responses, and existing evidence strongly suggests that this is due to its ability to scavenge chemokines. Here we will describe the in vitro methods that have been used to provide evidence of D6-mediated chemokine scavenging. Data from these types of experiments have shaped current models of D6 function, and continue to inform interpretation of phenotypes observed in D6deficient mice. In addition, we will detail the approaches that we have used to overexpress and purify D6 from transfected mammalian cells as part of our ongoing efforts to generate a three-dimensional (3D) structure of the molecule (Blackburn et al., 2004). This was inspired by our finding that D6 is a remarkably stable protein that can be expressed at very high levels in transfected mammalian cells, making its purification in sufficient quantities for crystallization a very real possibility.

1.1. Investigating D6 function using in vitro model systems 1.1.1. Cell lines, plasmids, and transfection In vitro studies of D6 have relied on the use of cell lines transfected with D6 expression constructs. HEK293 cells, which are widely used to study the biochemistry of other GPCRs including chemokine receptors, have been our cell line of choice because they are readily transfectible, easy to culture, and contain a large cytoplasm ideal to visualize intracellular receptor trafficking. They have a tendency to dislodge from plastic during some applications, and adhere poorly to glass (used in preparation for confocal microscopy), but adherence can be improved by coating surfaces with

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fibronectin at 4 C overnight (or 37 C for 1 h), and then washing briefly with PBS before the cells are seeded. HEK293 cells are grown in 293 medium (i.e., Dulbecco’s minimal essential medium, 10% fetal calf serum, 5 mM glutamine, plus antibiotics) at 37 C in 5% CO2. For experimentation performed in the absence of a CO2 source, it is advisable to buffer the medium with 10 mM HEPES and adjust the pH to 7.4. For robust expression of D6 and other chemokine receptors in HEK293 cells, the pcDNA3 plasmid from Invitrogen has been our workhorse, allowing ampicillin selection in bacteria during vector construction, and neomycin/ geneticin (G418) selection in mammalian cells for stable receptor expression driven by the strong CMV promoter of pcDNA3. Sequences encoding epitope tags can be introduced by PCR onto the 50 end of the open reading frame (ORF) of GPCRs, and we have had success with hemagglutinin (HA) tags (i.e., YPYDVPDYAGPG inserted between the first two amino acids of the receptor). This enables antibody-mediated detection of the expressed receptor, and is essential if high-quality antibodies specific for the receptor itself are unavailable, a common problem with several chemokine receptors. We have been fortunate to have an effective antihuman D6 antibody (Nibbs et al., 2001), but addition of the HA tag gives additional options for experimentation and allows the same antibodies to be used on different HA-tagged receptors, thereby controlling for antibody-specific effects. To help understand the role of specific residues or motifs in D6, we have generated pcDNA3-based expression constructs in which specific mutations have been introduced into the D6 ORF. The PCR-based Site-Directed Mutagenesis kit from Stratagene works very well for this in our experience (McCulloch et al., 2008). In addition, to aid D6 visualization in living cells, we have generated and used D6-GFP expression constructs ( Weber et al., 2004). This was done by using PCR to remove the D6 stop codon and add an appropriate restriction enzyme–cutting site, and then cloning the modified ORF into the pEGFP-N series of vectors from Clontech. Fortunately, we have found that in a variety of assays, D6-GFP fusion protein behaves like untagged D6 protein in HEK293 cells. However, other atypical chemokine receptors, particularly CCX-CKR, have proved very hard to tag with GFP for reasons that we do not currently understand. When analyzing D6 function, we have used, where possible, CCR5 or CCR5-GFP as a control (Weber et al., 2004). CCR5 binds chemokines that also bind D6, such as CCL3, thus allowing us to compare D6 behavior to that of a typical signaling chemokine receptor using the same chemokine ligand. pcDNA3-based expression vectors can be readily introduced into HEK293 cells by a variety of techniques, and we routinely use the lipidbased reagents, Superfect (Qiagen) or FuGene (Roche). Some optimization of DNA/Superfect ratios is advisable, but in our experience the manufacturer’s recommended conditions consistently yield high transfection efficiency (40–80%) that are sufficient to allow of emergence of large numbers of stably transfected HEK293 cell clones. Stable transfection,


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which with HEK293 cells can be achieved by selecting after transfection by including 0.8 mg/ml G418 in the culture medium, is essential for studies on D6. D6 is a very stable protein (McCulloch et al., 2008; Weber et al., 2004), and during transient transfection many cells contain large vacuoles full of D6 protein. These cells do not survive in stable cultures, but the analysis of transient transfections is confused by these aberrant D6 overexpressing cells. Once stably transfected, single-cell clones can be derived by limiting dilution, but we typically work with pools of transfected cells to avoid clonal artifacts. Using standard techniques described in depth in our published work (McCulloch et al., 2008; Weber et al., 2004), a number of basic receptor parameters can be measured in these transfected cells, such as surface receptor expression (by flow cytometry), the affinity of receptor for chemokine (by radiolabeled ligand binding assays), and the intracellular distribution and localization of receptor (by immunofluorescent staining or direct visualization of D6-GFP coupled to confocal microscopy). However, this review will focus on methodologies that have been particularly important in characterizing the scavenging behavior of D6 in vitro, and revealing the mechanisms responsible for this activity. 1.1.2. Detection of D6 by Western blotting Although Western blotting is a widely used technique, initial attempts at detecting D6 on Western blots were hampered by the tendency of D6 to form large insoluble aggregates barely capable of entering the gel (Blackburn et al., 2004). This was caused by the 95 C heating step used to denature proteins prior to electrophoresis; D6 was able to enter the gel and electrophoresis more effectively if the incubations were carried out at temperatures less than 60 C (Blackburn et al., 2004). Thus, we now routinely use the following technique for D6 detection by Western blotting (McCulloch et al., 2008; Weber et al., 2004). First, cells are lysed in CellLytic M mammalian cell lysis buffer (Sigma). Then an equal volume of HU buffer (8 M urea, 5% SDS, 200 mM Tris-HCl, pH 8, 0.1 mM EDTA, 100 mM dithiothreitol, 0.5% bromphenol blue) is added, the samples incubated at room temperature (RT) for 10 min, and then subjected to SDS-PAGE in 4 to 12% w/v gradient acrylamide gels. The proteins are then electrophoretically transferred onto polyvinylidene difluoride membrane, and blocked overnight in 10% milk/PBS. Blots are incubated at RT in 10% milk/ PBS containing anti-D6 or anti-HA antibody for 1 to 16 h. After washing multiple times in PBS/0.1% Tween, primary antibodies are detected by covering the blot in 10% milk/PBS containing horseradish peroxidase (HRP)– coupled antimouse IgG secondary antibodies (Amersham Biosciences) for 1 h. After further repeated washes in PBS/0.1% Tween, blots are developed using chemiluminescence substrates (WestPico or WestFemto kits, Pierce Chemical) and exposed to x-ray film for appropriate periods of time. This reliable method of detecting D6 protein has, among other things, been

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instrumental in defining post-translational modifications present in D6 (e.g., sulfation, phosphorylation) (Blackburn et al., 2004; McCulloch et al., 2008), and has been essential during our attempts to purify D6 for crystallization (see the following) (Blackburn et al., 2004). Moreover, by examining the impact of the protein synthesis inhibitor cycloheximide on the abundance of D6 and a variety of mutated variants, we are beginning to understand the molecular basis for the unusually high stability of D6 and its relation to the intracellular trafficking itinerary of the protein (McCulloch et al., 2008). 1.1.3. Chemokine scavenging assays A key advance in our understanding of D6 function came when attention moved away from examining the effect of chemokines on D6, and turned instead to the effect of D6 on chemokines (Fra et al., 2003; Weber et al., 2004). Chemokine scavenging assays were developed in which chemokine removal from the medium, and its subsequent intracellular fate, could be tracked over time. Labeled chemokines were critical for these experiments, and both radioiodinated and biotinylated chemokines have been used effectively. Radiolabeled chemokines Radioiodinated chemokines are commercially available (e.g., from Amersham), or recombinant chemokines can be labeled in-house. Many chemokines are very difficult to radiolabel in a form that retains bioactivity, but, in our experience, CCL3 can be radioiodinated with minimal impact on bioactivity (Graham et al., 1993, 1994). Briefly, this is done by first coating the bottom of a 0.5-ml Eppendorf tube with 10 mg of IODOGEN (Pierce). This is achieved by dissolving the IODOGEN in chloroform to 0.1mg/ml, aliquoting 100 ml into the 0.5-ml tube, and then gently passing an air stream over the surface of the chloroform to encourage its rapid evaporation. A thin coating of IODOGEN should be visible on the bottom of the inside of the tube. Then 5 mg of CCL3 (in a maximum of 100 ml of PBS) and 1 mCi of Na125I is added to the tube, and incubated on ice for 15 min with regular gentle flicking of the tube. The reaction is then passed down a desalting column (e.g., GF5 excellulose column (Pierce)) to separate labeled protein from free iodide. Labeled chemokines can be stored at 4 C for several weeks. We have typically used a mutated version of mouse CCL3, called PM2, which is restricted in its self-aggregation potential, because previous experience had shown self-aggregation to be problematic in receptor-binding assays (Graham et al., 1994). However, we have also successfully radioiodinated wildtype recombinant human CCL3 and CCL4 using this methodology. Biotinylated chemokines Chemokines can be produced by total chemical synthesis and are extremely tolerant of C-terminal additions. We therefore had a version of the PM2 form of CCL3 synthesized so that it carried a C-terminal biotinylated lysine residue (called bioCCL3; Almac Sciences)


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(McCulloch et al., 2008; Weber et al., 2004). A similar version of CCL19, called bioCCL19, has also been prepared (Almac Sciences) (Comerford et al., 2006). Both of these biotinylated chemokines are fully functional in bioassays. They are clearly safer to use than radioiodinated chemokines, but, depending on the application, cannot be detected with the same sensitivity. By virtue of the single biotin residue per chemokine molecule, biotinylated chemokines can be mixed with labeled streptavidin to form chemokine tetramers that can be used in flow-cytometric and cell-sorting protocols. Chemokines labeled with biotin postsynthesis are not ideal because they (1) carry multiple biotin residues, possibly at sites that interfere with bioactivity, (2) are not uniformly labeled with biotin, and (3) cannot be used to form good fluorescent tetramers because the presence of multiple biotin residues per chemokine molecule allows the formation of higher-order structures. Scavenging assays Radioiodinated chemokines have been used to monitor a variety of receptor properties, particularly their affinity for chemokine and the level of surface receptor expression. However, it has been their use in chemokine scavenging assays that has been important in the study of D6, CCX-CKR, and mutated variants of these molecules. These assays in their simplest form involve the addition of radioligand to medium bathing cultured or harvested cells, with samples of medium removed over time (up to 48 h) for analysis using a gamma counter (e.g., Beckman Gamma 5500B counter). Adding unlabeled chemokine slows down radiolabeled chemokine removal and is useful when examining the long-term capability of receptors to progressively deplete chemokine over time. It is important to note that internalized radiolabeled chemokine is degraded inside cells and 125I released back into the medium, so gamma counter readings alone will be misleading, and it is critical to determine the molecular form of the retrieved radioactivity. To do this, samples of media can either be examined by SDS-PAGE (drying the gel under vacuum onto filter paper after electrophoresis and exposing it to x-ray film), or subjected to precipitation with trichloroacetic acid (TCA). This precipitates proteins from the medium, including intact radioiodinated chemokine, while leaving degradation products in the supernatant. To do this, an equal volume of 25% trichloroacetic acid (TCA) is added to test samples, the mix incubated at 4 C for 15 min, and then centrifuged (13,000 rpm, 4 C, 15 min). The supernatant is taken, and the TCA precipitate washed in ice-cold acetone; the acetone wash is combined with the nonTCA precipitable supernatant. The TCA pellet and non-TCA precipitable material are then counted in a gamma counter, and the percentage of retrieved 125I counts in TCA pellet and non-TCA precipitable is calculated as an indicator of the amount of chemokine degraded. Biotinylated chemokines can be used in a similar way, but are detected by Western blotting using HRP-coupled streptavidin (Dako). Cells are incubated in medium containing bioCCL3 or bioCCL19 and aliquots of medium taken

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over time. An equal volume of 2 LB (100 mM Tris-HCl, pH 6.5, 4% SDS, 20 mM dithiothreitol, 20% glycerol, 0.2% bromphenol blue) is added to the aliquots, which are then boiled for 5 min, and subjected to SDS-PAGE. Blots are prepared as above, and blocked with 10% milk/PBS. After washing repeatedly in PBS/0.1% Tween, the blots are exposed to HRP-coupled streptavidin for 1 h—it is essential that this is done in the PBS/0.1% Tween rather than in milk, as the milk prevents binding of streptavidin to the immobilized biotinylated chemokine on the blot. Blots are developed as above by chemiluminescence and the depletion of biotinylated chemokine from the medium quantified by densitometric scanning of the autoradiographs. For all these scavenging experiments it is advisable to do parallel experiments using control untransfected cells lacking receptor, and also include wells which contain no cells (to control for chemokine adherence to plastic). To explore the kinetics of chemokine degradation inside cells, chemokine uptake can be synchronized by loading cells at 4 C with radioligand for 1 h. After a brief (10-min maximum) shift to 37 C to drive chemokine uptake, remaining external chemokine is washed away and the cells allowed to process the internalized chemokine at 37 C. All this chemokine will have been internalized during the initial brief shift to 37 C. At time points after washing (up to 3 h), triplicate samples are spun (2600 rpm, 5 min, 4 C), the medium removed, and the cell pellet washed in medium. The original and the wash medium are combined, half of it is subjected to TCA precipitation (as above), and the amount of radioiodine in the TCA precipitable and nonprecipitable fractions determined in a gamma counter. Cell pellets are resuspended in PBS, and half of the suspension counted in a gamma counter. To the remaining samples of media and cells, an equal volume of 2 LB (100 mM Tris-HCl, pH 6.5, 4% SDS, 20 mM dithiothreitol, 20% glycerol, 0.2% bromphenol blue) is added, the samples are boiled for 5 min, and then used for SDS-PAGE (see above). These simple approaches have been used to demonstrate the ability of D6 and CCX-CKR to mediate the progressive, nondesensitized scavenging of extracellular chemokines, and to follow the fate of the chemokine internalized by these receptors. By analyzing D6 variants carrying sitedirected mutations alongside wildtype D6 in these assays it has become clear that the C-terminus of D6 is particularly important for continuous chemokine scavenging. 1.1.4. Tracking atypical receptors with antibodies D6 scavenges chemokines by constitutively trafficking to and from the cell surface. The first indication of this came from experiments showing that surface levels of D6 remained unchanged despite active chemokine uptake (Weber et al., 2004) This was true even if D6-expressing cells were loaded with high concentrations (up to 100 nM ) of chemokine at 4 C (to achieve high levels of receptor occupancy) prior to shift to 37 C. In these


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experiments, large amounts of chemokine are internalized very quickly after shift to 37 C. However, even under these conditions, there was still no change in surface D6 levels. These data were interpreted as indicating that chemokine-occupied internalized receptors were instantly replaced by other receptors from intracellular pools. This idea was supported by the fact that 95% of the total cellular complement of D6 was found in highly motile early and recycling endosomes inside transfected cells (Weber et al., 2004). To provide further evidence of constitutive trafficking of D6, antibodies have been used to track the fate of surface receptors (McCulloch et al., 2008; Weber et al., 2004), and these techniques are described briefly here. Antibody feeding to examine constitutive receptor internalization D6or D6-GFP-expressing HEK293 cells, or untransfected control cells, are grown on fibronectin-coated glass chamber slides, washed several times with PBS and then incubated in SFM (serum-free 293 medium containing 10 mM HEPES, pH 7.4, and 0.2% bovine serum albumin) at 4 C for 30 min. To load surface receptors, anti-D6 or anti-HA antibodies or Fab fragments of these antibodies are added and cells left at 4 C for a further 30 min. Cells are then washed with ice-cold SFM; as a control ice-cold SFM adjusted to pH3 can be used to strip off surface antibody. Cells are then either directly fixed (10 min in 3.5% paraformaldehyde (PFA)) or SFM is added, and the slides shifted to 37 C. Cells washed with SFM (pH3) are washed twice with SFM to return the pH to 7.4 before the 37 C incubation. Chemokines can be added at this point to explore their impact on antibody trafficking. Cells are left at 37 C for up to 3 h to allow the antibodies that were on the surface to enter the cell. The antibodies are then detected by conventional immunostaining protocols. Briefly, cells are washed with PBS, fixed for 10 min in 3.5% PFA, washed twice with PBS, and then incubated in 50 mM NH4Cl for 20 min. The fixed cells are then permeabilized in PGS (PBS, 0.2% gelatin, 0.05% saponin) for 30 min, and then PGS containing fluorophore-coupled anti-IgG antibodies for 1 h. After two washes with PGS, the cells undergo a final fixation in 3.5% PFA for 10 min, a final PBS wash, and the slides are then mounted in Vectashield (with or without 4,6-diamidino-2-phenylindole) (DAPI) (Vector Laboratories) under a coverslip sealed with nail varnish in preparation for confocal microscopy. Control experiments can be performed in the absence of saponin (the cell-permeabilizing agent). Only surface antibodies are detected; thus, by comparing these cells to those treated with saponin, it is possible to get a robust picture of the extent of uptake of the antibodies. Using antibodies to study receptor recycling Adapting the method above allows receptor recycling to be examined (Weber et al., 2004). Cells are plated as before, but this time they are loaded with antibody for up to 1 h at 37 C. They are then washed with cold SFM adjusted to pH 3 (to remove

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surface-bound antibodies), and then twice with cold SFM to reset pH to 7.4. Next, the cells are incubated in SFM containing fluorophore-coupled, anti-IgG antibodies for up to 1 h at 37 C. During this period, any internalized anti-D6 or anti-HA antibodies that recycle back to the cell surface will be available to internalize fluorescent anti-IgG antibodies. At the end of the experiment, cells are washed in PBS, fixed in 3.5% PFA for 10 min, washed again with PBS, and mounted as described above. Flow cytometry can also be employed to quantify recycling. In this case, cells are harvested by mechanical disruption or brief trypsinization before loading them with anti-D6 or anti-HA antibodies at 37 C for up to 1 h in SFM. Cells are then washed once with cold SFM adjusted to pH3 (to strip off surface antibodies), twice with cold SFM to restore pH7.4, and finally incubated at 37 or 4 C in SFM containing fluorophore-coupled antimouse IgG antibodies for up to 1.5 h. After a final PBS wash, cells are analyzed by flow cytometry with the level of fluorescence providing a direct indication of the extent of anti-D6 or anti-HA antibody recycling, which in turn reflects the extent of receptor recycling. 1.1.5. FACS-based chemokine uptake assays To examine molecular mechanisms underpinning scavenging by D6 and CCX-CKR, we have developed assays in which fluorescent tetramers can be used to quantify chemokine uptake (Comerford et al., 2006; Fra et al., 2003; Weber et al., 2004). Tetramers are generated by mixing bioCCL3 or bioCCL19 (250 ng) in 10 ml of PBS with 3 mg of Streptavidin-PE (S-PE) (Molecular Probes) at RT for 1 h. Control samples lacking Bio-CCL3 (i.e., S-PE alone) are also prepared. About 4 105 receptor-expressing transfected cells, or control untransfected cells, are resuspended in 40 ml of HEPES-buffered medium, the 10 ml of tetramers or S-PE alone is added, and the cells incubated at 37 C for 30 to 150 min with regular gentle mixing by flicking the tube. Next, 1.4 ml of ice-cold FACS buffer (i.e., PBS plus 2% fetal calf serum) are added to stop uptake, the cells retrieved by centrifugation (2600 rpm, 5 min, 4 C), resuspended in 400 ml of FACS buffer, and passed through a FACScan flow cytometer. Atypical chemokine receptors will internalize their cognate chemokine tetramers and fluoresce, detectable in the FL2 channel of the FACS machine (Comerford et al., 2006; Weber et al., 2004). Before beginning the experiment, cells can be treated with chemical or genetic inhibitors of various endocytosis or trafficking pathways to examine their impact on receptor-mediated chemokine uptake (Comerford et al., 2006; Weber et al., 2004). In particular, transient transfection of GFP-coupled protein inhibitors (e.g., dominant-negative forms of caveolin or rab proteins), coupled to two-color FACS analysis, has allowed a direct examination of the level of inhibitor expression on chemokine uptake by performing (Comerford et al., 2006; Weber et al., 2004). In these experiments, controls are essential in which parental HEK293 or D6- or CCX-CKR–expressing HEK293 cells are


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treated with PE-labeled chemokine tetramers or S-PE alone, after (1) not having been transiently transfected with GFP constructs, or (2) having been transiently transfected with untagged GFP (i.e., GFP, which has no protein attached to it). These samples are then used at the beginning of the analysis to set the detection parameters of the FACS machine and compensate correctly to avoid fluorescence bleed-through between channels. Thus, for example, when analyzing the impact of dominant-negative (DN) rab5-GFP on D6 function (Weber et al., 2004), PE-/GFP-, GFP-/PEþ, GFPþ/PE-, and PEþGFPþ gates are set using (1) untransfected parental HEK293 cells fed PE-labeled CCL3 tetramers or S-PE alone (no red, no green), (2) untransfected D6expressing cells fed PE-labeled CCL3 tetramers (red only), (3) GFP-transfected parental or D6-expressing HEK293 cells fed S-PE (green only), and (4) GFPtransfected, D6-expressing cells fed PE-labeled CCL3 tetramers (red and green). Then data are collected from test samples, that is, D6-expressing HEK293 cells transiently transfected with DN rab5-GFP constructs incubated in PE-labeled CCL3 tetramers or S-PE only. On analysis, gates of high and low rab5-GFP expressors can be set, and the mean PE fluorescence intensity and the number of PE-positive cells determined and compared with identical gates set on D6-expressing cells expressing untagged GFP, that is, with no DN rab5 attached. These approaches have revealed that atypical chemokine receptors use different routes for entry into HEK293 cells: CCX-CKR requires caveolin-1 and enters via caveolae/lipid rafts, while D6 uses clathrin-coated pits to enter rab5þ early endosomes (Comerford et al., 2006; Weber et al., 2004). In summary, the development of new methodologies to explore how chemokines are controlled by chemokine receptors has allowed new paradigms of chemokine receptor function to be proposed, and is beginning to provide insight into the molecular mechanisms responsible for these unique chemokine receptor properties. Importantly, despite the limitations of in vitro model systems, data generated by these approaches underpin our interpretation of phenotypes observed in animals lacking atypical chemokine receptors, and form the foundation of our understanding of their function in vivo.

1.2. D6 as a model for determining chemokine receptor structure Despite displaying atypical biology and biochemistry, D6 is structurally related to other chemokine receptors. It shares the common 7-transmembrane spanning structure and appears to bind chemokines in a manner similar to typical chemokine receptors. Determination of the 3D structure of D6 would therefore not just represent an important scientific advance, but would enable structural modeling of other receptors and assist in the rational design of drugs targeting these molecules. One major advantage of D6 in terms of determining structure is the ability of D6 to express to very high levels in heterologous

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transfectants, a property dependent in no small part to its very high stability (Blackburn et al., 2004; Weber et al., 2004; McCulloch et al., 2008). In addition, since much of the cellular complement of D6 is found inside cells (Blackburn et al., 2004; Weber et al., 2004; McCulloch et al., 2008), there is a much greater surface area for the receptor to occupy, providing the potential for greater levels of expression. It is thus possible in principal to generate enough D6 in transfected mammalian cells to allow for purification of milligram quantities suitable for routine crystal trialing. Moreover, these high expression levels remove the need to generate yeast, bacterial or baculoviral expression systems, and allow for the purification and analysis of functional and appropriately decorated mammalian D6. 1.2.1. Generation of heterologous transfectants expressing D6 With a few exceptions, we have found that human D6 is expressed at very high levels in all cell lines tested. However, the combination of high D6 expression, rapid doubling time, and growth to high cell density meant the murine pre–B suspension cell line L1.2 was preferred for D6 production (Blackburn et al., 2004). This cell line is maintained in RPMI 1640 containing 5 mM glutamine, 10% heat-inactivated fetal calf serum, 50 mM b-mercaptoethanol and antibiotics. The human D6 cDNA to be transfected was modified by PCR to encode an N-terminal HA epitope tag and a stretch of 10 histidine residues (His10) at the extreme C-terminus. The HA tag enables D6 detection (by flow cytometry and Western blotting), while the His10 tag allows purification of the protein using nickel- and cobalt-affinity columns. The resulting cDNA was verified by DNA sequencing and cloned into pcDNA3 (see above). We have also generated a variant of D6, which carries the HA and His10 tags, but which also has the glycosylated Asn19 residue removed by mutation (Blackburn et al., 2004). This mutation has no effect on chemokine binding or receptor stability, but since 50% of cellular D6 protein is glycosylated at this site, its removal improves the homogeneity of the purified D6 protein and may aid its packing in crystals. Lipid-based transfection reagents, such as Superfect, proved most effective for introducing plasmids into L1.2 cells, and a ratio of 6 mg plasmid to 8 ml Superfect gave optimal transfection efficiency. Stable transfectants were selected by culturing in the presence of 1.6 mg/ml G418 (geneticin), after previously finding that this effectively kills untransfected L1.2 cells. Single cell clones were then generated by culture in 96-well plates, seeding the cells at a concentration of 0.5 cells/well. High-expressing clones were selected by a variety of approaches, such as flow cytometry (using anti-HA or anti-D6 antibodies) or radioligand-binding assay. However, surface D6 protein may not accurately reflect total D6 protein. Thus, Western blotting is now used as the principal method to identify high-expressing clones and monitor D6 expression under different culture conditions.


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1.2.2. Increasing expression of D6 in transfected L1.2 clones While we are able to augment D6 expression by clonal selection, we also tested a number of approaches to induce further production. The histone deacetylase inhibitor sodium butyrate can increase expression of transcripts from plasmid vectors in stably transfected cells. Thus we examined the impact of sodium butyrate on D6 expression, attempting to define an optimal exposure time and concentration to induce further D6 expression (Blackburn et al., 2004). To do this, cells were seeded at 5 105 per milliliter in 25-cm2 flasks and either left untreated or exposed to sodium butyrate (up to 10 mM for up to 48 h). Note that at concentrations of greater than 10 mM, sodium butyrate was toxic and resulted in a marked reduction in cell viability. Cells were harvested and D6 levels assessed by Western blotting. This revealed that maximal induction was reproducibly achieved with 10 mM butyrate after 16 to 20 h exposure. Subsequent butyrate treatments were standardized at 10 mM for 18 h. We also assessed the impact of cell density on butyrate responsiveness, but found that this had a minimal effect on induction of D6 expression. It is important to note, however, that considerable variation in D6 expression was caused by the use of different batches of fetal calf serum, and it has been important to test all serum and select those batches that allow highest D6 expression. 1.2.3. Large-scale production of D6-expressing L1.2 cells One of the advantages of expressing D6 in suspension cells is the opportunity to grow these cells to very high density in large volumes of medium. To maximize this, we have routinely grown cells in large bell jars or a 15-l Applikon bioreactor (Blackburn et al., 2004). Standard operating procedures have been developed and optimized that provide the highest yield of D6 protein from both of these culture vessels. Bell jar protocol Under sterile conditions, 2.5 l of growth medium (see above) and 500 ml of D6-expressing L1.2 cells are poured into the bell jar. These cells have been previously maintained in 5 175–cm2 flasks in 37 C, 5% CO2 incubators, and are cultured to ensure that they have a density of 106 cells/ml on the day of seeding the bell jar. Fifty milliliters of 10% Pluronic F-68 (Gibco)—an antifoaming reagent—are also added. The bell jar in then incubated, with constant stirring, in a 37 C cabinet and is attached to sterile compressed air and CO2 sources running at pressures of 500 ml/min (for air) and 25 ml/min (for CO2). This provides a final concentration of 5% CO2. Five days later, 50 ml of sterile 1-M sodium butyrate and a further 2 l of medium are added. The next day the cells are harvested. Bioreactor protocol The Applikon bioreactor allows continuous monitoring of cultures and automated maintenance of favorable growth conditions. Consequently, D6 yields per milliliter of culture are typically higher from this

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piece of equipment than the bell jars. The bioreactor is loaded with 5 l of medium and 100 ml of 10% Pluronic F-68. This is allowed to reach 37 C and pH 7.4 by constant stirring and regulation of the CO2 concentration in the ‘‘air mix’’ being bubbled through the culture. Temperature is maintained by attaching a controlled heating sheet around the glass bioreactor. Temperature and pH are constantly monitored and automatically regulated throughout the culture period. The bioreactor is seeded with 1 l of L1.2 cells (previously cultured in 10 175–cm2 flasks to 106 cells/ml) and left to grow for 3 days. On day 4, an aliquot of cells is removed for counting using sterile sampling via an outflow tube attached to the bioreactor. At this stage, the bioreactor is perfused by circulating media at low flow rate (3.5 ml/min) through the bioreactor. This can be achieved in the Applikon bioreactor without losing cells, and allows the gradual, gentle, and continual replenishment of medium. This markedly improves cell growth. On day 5, a further aliquot of cells is taken for counting, perfusion is stopped, the volume of media is increased to 10 l, and 100 ml of 1 M sodium butyrate dissolved in serum-free RPMI is added to the culture and left for 18 to 24 h. On day 6, the cells are collected via a ‘‘harvest tube’’ attached to the Bioreactor. 1.2.4. Purification of D6 Cells harvested from the bell jars or the bioreactor are centrifuged at 3500 rpm for 10 min in 500-ml bottles in a GS-3 rotor in a Sorval centrifuge. The cell pellets are washed twice with PBS and then resuspended in 50 ml of buffer A (20 mM phosphate buffer, 150 mM NaCl, 10% [v/v] glycerol, pH 8.0, containing dissolved complete EDTA-free protease inhibitor cocktail tablets [Roche]) and stored at –20 C. D6 is then purified by one of the following two methods (Blackburn et al., 2004). Solubilization using DDM At all stages, samples are kept on ice and protease inhibitor tablets added as appropriate. Cells from 5 l of culture are disrupted using a French press (6555 kPa; 950 lbf/in2), and cell debris removed by centrifugation for 20 min at 20,000g. Membranes are isolated by centrifugation at 120,000g for 1 h, and the pellet resuspended in 50 ml of buffer A containing 0.05% (w/v) CHS (cholesteryl hemisuccinate, Sigma) and 2% (w/v) DDM (n-dodecyl b-D-maltoside, Glycon). This is stirred gently for 2 h at 4 C, after which any insoluble debris is removed by a 30-min spin at 120,000g. Solubilized membranes are then applied to a 5-ml nickel Hitrap column (Amersham Biosciences) connected to an AKTA Purifier 100 (Amersham Biosciences). A step gradient of imidazole in buffer A (containing 0.2% DDM and 0.005% CHS) is applied, with D6 eluting at 300 mM imidazole. Western blotting is used to identify fractions containing D6, which are then combined. For further purification and concentration of D6, the imidazole is reduced to 15 mM by dilution in buffer A (containing 0.2% DDM and 0.005% CHS), the sample is added


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to 1 ml of Talon cobalt resin (BD Clontech), packed on a column, and the D6 eluted with 150 mM imidazole. Solubilization using digitonin Cell pellets are solubilized at RT for 3 h with constant stirring in 2% digitonin in the presence of a full protease inhibitor cocktail and DNAase (to degrade DNA released during cell lysis). The mix is then spun at 7000 rpm for 30 min, in 50-ml Falcon tubes, in a benchtop centrifuge to pellet insoluble material. The soluble fraction is then further cleared by centrifugation at 20,000 rpm for 30 min in a Beckman ultracentrifuge. An equal volume of glycerol is added to the soluble fraction, along with 5ml of Talon resin, and the mixture stirred at 4 C for 3 to 16 h. During this time, the His10 tag on D6 should bind to the cobalt of the Talon resin. The resin is then packed into an empty column, using a peristaltic pump, and washed with 50 mM Tris-HCl (pH 7.5)/500 mM NaCl/30 mM Imidazole. D6 is eluted using a 30- to 500-mM imidazole gradient (in the same Tris/NaCl buffer). D6 elutes at 100 to 250 mM imidazole and can be detected by Western blotting aliquots of the eluted fractions. Finally, with D6 samples prepared using either approach, imidazole is removed using PD-10 columns (Amersham Biosciences), and further concentration of the D6 protein is achieved using Centricon columns (Vivascience). Purified D6 is then quantified using the BCA (bicinchoninic acid) assay (Pierce), and examined by Western blotting and Coomassie staining of polyacrylamide gels.

1.2.5. Functional assays Crystal trials with purified D6 are underway, with a view to generating a 3D structure of this molecule. We have also examined the ligand binding properties of purified D6 protein using scintillation proximity assays (Blackburn et al., 2004) and Biacore surface plasmon resonance–based technology (unpublished data). Another simpler approach has been to use D6 immobilized on nickel affinity beads to ‘‘pull down’’ biotinylated chemokines. His10-tagged purified D6 is first immobilized on the beads and then fed biotinylated CCL22 (bioCCL22, Almac Sciences), or premixed with bioCCL22 before the nickel beads are added. Controls are performed in which D6 or bioCCL22 are omitted from the reaction. Once all reagents have been added, the mixture is incubated at 37 C for up to 30 min and the nickel beads then retrieved by centrifugation at 14,000 rpm for 10 min. The supernatant is removed and beads washed twice in 30 mM imidazole/500 mM NaCl/50 mM Tris (pH 7.5), centrifuging at 14,000 rpm for 10 min after each wash to retrieve the beads. After the final wash solution has been removed, half the bead pellet is mixed with 20 ml of LDS loading dye (Invitrogen) while the remainder is mixed with 300 mM imidazole/500 mM NaCl/50 mM Tris (pH 7.5) to disrupt the interaction of the His10 tag on D6 with the nickel beads. This is then span at 14,000 rpm

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for 10 min and the supernatant mixed with an equal volume of LDS loading dye. Finally, the beads are stripped with EDTA (200 mM ), and the supernatant mixed with an equal volume of LDS Loading dye. All samples are then run on SDS-PAGE, Western blots prepared, and probed for D6 (as described above using anti-D6) and bioCCL22 (as described above using HRP-coupled streptavidin). In these experiments, we have found, as expected, that His10-tagged D6 binds very well to nickel beads, and importantly, that only in the presence of D6 is bioCCL22 also capable of binding to the beads. Although we do not yet know whether all purified D6 molecules retain chemokine binding activity, this simple ‘‘pull-down’’ assay has provided reassuring evidence that D6 can retain chemokine-binding activity after the rigors of its purification from L1.2 cells. The unique biochemical properties of D6 have made it possible to consider its purification in sufficient quantities to generate crystals with which to determine its three-dimensional structure. Clearly, this is not a trivial task but by optimizing D6 expression in a cell line that can be grown to high density in large culture vessels, and by developing methods to purify and analyze this protein, we are making progress toward this goal. It is hoped that armed with these methodologies, we will soon be in a position to provide the first structural information on a crystallized chemokine receptor.

ACKOWLEDGMENTS The authors are supported by research grants from the Biotechnology and Biological Sciences Research Council. R.J.B.N. thanks A. Wilson for providing support services.

REFERENCES Blackburn, P. E. (2004). Purification and biochemical characterization of the D6 chemokine receptor. Biochem. J. 379, 263–272. Bonecchi, R. (2004). Differential recognition and scavenging of native and truncated macrophage-derived chemokine (macrophage-derived chemokine/CC chemokine ligand 22) by the D6 decoy receptor. J. Immunol. 172, 4972–4976. Bonecchi, R. (2008). Regulation of D6 chemokine scavenging activity by ligand- and Rab11–dependent surface up-regulation. Blood 112, 493–503. Comerford, I., Milasta, S., Morrow, V., Milligan, G., and Nibbs, R. (2006). The chemokine receptor CCX-CKR mediates effective scavenging of CCL19 in vitro. Eur. J. Immunol. 36, 1904–1916. Di Liberto, D. (2008). Role of the chemokine decoy receptor D6 in balancing inflammation, immune activation, and antimicrobial resistance in Mycobacterium tuberculosis infection. J. Exp. Med. 205, 2075–2084. Fra, A. M. (2003). Cutting edge: Scavenging of inflammatory CC chemokines by the promiscuous putatively silent chemokine receptor D6. J. Immunol. 170, 2279–2282.


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Galliera, E. (2004). Beta-arrestin-dependent constitutive internalization of the human chemokine decoy receptor D6. J. Biol. Chem. 279, 25590–25597. Graham, G. J. (2009). D6 and the atypical chemokine receptor family: Novel regulators of immune and inflammatory processes. Eur. J. Immunol. 39, 342–351. Graham, G. J. (1993). Characterization of a receptor for macrophage inflammatory protein 1 alpha and related proteins on human and murine cells. Cell Growth Differ. 4, 137–146. Graham, G. J. (1994). Aggregation of the chemokine MIP-1 alpha is a dynamic and reversible phenomenon. Biochemical and biological analyses. J. Biol. Chem. 269, 4974–4978. Hansell, C. A., Simpson, C. V., and Nibbs, R. J. (2006). Chemokine sequestration by atypical chemokine receptors. Biochem. Soc. Trans. 34, 1009–1013. Jamieson, T. (2005). The chemokine receptor D6 limits the inflammatory response in vivo. Nat. Immunol. 6, 403–411. Mantovani, A., Bonecchi, R., and Locati, M. (2006). Tuning inflammation and immunity by chemokine sequestration: Decoys and more. Nat. Rev. Immunol. 6, 907–918. Martinez de la Torre, Y. (2005). Increased inflammation in mice deficient for the chemokine decoy receptor D6. Eur. J. Immunol. 35, 1342–1346. Martinez de la Torre, Y. (2007). Protection against inflammation- and autoantibody-caused fetal loss by the chemokine decoy receptor D6. Proc. Natl. Acad. Sci. USA 104, 2319–2324. McCulloch, C. V. (2008). Multiple roles for the carboxy-terminal tail of the chemokine scavenger D6. J. Biol. Chem. 283, 7972–7982. Nibbs, R. J. (2007). The atypical chemokine receptor D6 suppresses the development of chemically induced skin tumors. J. Clin. Invest. 117, 1884–1892. Nibbs, R. J. (2001). The beta-chemokine receptor D6 is expressed by lymphatic endothelium and a subset of vascular tumors. Am. J. Pathol. 158, 867–877. Nibbs, R., Graham, G., and Rot, A. (2003). Chemokines on the move: Control by the chemokine ‘‘interceptors’’ Duffy blood group antigen and D6. Semin. Immunol. 15, 287–294. Rot, A., and von Andrian, U. H. (2004). Chemokines in innate and adaptive host defense: Basic chemokinese grammar for immune cells. Annu. Rev. Immunol. 22, 891–928. Weber, M. (2004). The chemokine receptor D6 constitutively traffics to and from the cell surface to internalize and degrade chemokines. Mol. Biol. Cell 15, 2492–2508. Whitehead, G. S. (2007). The chemokine receptor D6 has opposing effects on allergic inflammation and airway reactivity. Am. J. Respir. Crit. Care Med. 175, 243–249.

C H A P T E R

T H I R T E E N

Modeling Small Molecule–Compound Binding to G-Protein–Coupled Receptors Nagarajan Vaidehi,* James E. Pease,† and Richard Horuk‡ Contents 1. Introduction 2. Similarity and Differences in the Crystal Structures of Class-A GPCRs Solved to Date 3. GPCR Modeling Methods 3.1. Homology structure modeling methods 3.2. Ab Initio modeling methods 3.3. Ligand-docking methods 4. Computational Methods for Receptor Flexibility and LigandInduced Conformational Changes in GPCRs 4.1. Liticon method 5. Validation of GPCR–Ligand Models 5.1. General strategies for mutagenesis 5.2. Receptor binding 6. Conclusions References

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Abstract G-protein–coupled receptors (GPCRs) form a superfamily of membrane proteins that play a crucial role in mediating physiological processes as well as pathogenesis of many critical diseases. They are one of the most successful drug targets, accounting for more than 30% of prescription drugs on the market today. Three-dimensional structural information on GPCRs will greatly aid the drug design process, and great strides are being made in obtaining crystallographic information on GPCRs. Since this process is both tedious and risky, a combination of computational methods and biophysical experiments is a useful approach to rapidly obtain information on a wide variety of GPCRs. * {

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Division of Immunology, Beckman Research Institute of the City of Hope, Duarte, California, USA Leukocyte Biology Section, National Heart and Lung Institute, Imperial College London, London, United Kingdom Department of Pharmacology, UC Davis, Davis, California, USA


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Nagarajan Vaidehi et al.

In this review, we describe the methods/protocols involved in these computational techniques, as well as methods for site-directed mutagenesis and ligandbinding assays that are currently being used for validating structural-model and small-molecule–ligand binding to GPCRs. We discuss the merits and pitfalls of the various methods used in obtaining structural and dynamic information for ligand binding to GPCRs. Another important factor to consider in drug design is the conformational flexibility of GPCRs since it has been shown that smallmolecule ligands of varied efficacy stabilize different receptor conformations leading to functional selectivity of ligands. We discuss the computational methods used to study this specific ligand-induced state.

1. Introduction The superfamily of membrane-bound proteins known as G-protein– coupled receptors (GPCRs) play a critical role in many physiological processes as well as in the pathogenesis of many diseases (Lefkowitz, 2004). GPCRs form the largest superfamily of membrane proteins that are targeted by more than 30% of the blockbuster drugs in the market today (Schlyer and Horuk, 2006). Drug design for the GPCR family can be challenging for a number of reasons, not least of which is the fact that GPCRs within a subfamily can have high sequence identity to each other, making it difficult to obtain subtype-specific drugs. Another important factor in drug design is that GPCR conformations are highly dynamic and this conformational flexibility leads to structural and functional diversity in this highly conserved topology for this class of receptors. Small-molecule ligands of varied efficacy stabilize different receptor conformations (Kobilka and Deupi, 2007) leading to functional selectivity of ligands (Mailman, 2007; Urban et al., 2007). This ligand-induced specific state is important for drug design as well. Recently great strides have been made in solving the crystal structures of squid rhodopsin (Murakami and Kouyama, 2008), ligand-free opsin (Park et al., 2008) with and without the carboxy terminus peptide of the G-protein–bound receptor (Scheerer et al., 2008), turkey b1-adrenergic receptor (Warne et al., 2008), human b2-adrenergic receptor (Cherezov et al., 2007; Rosenbaum et al., 2007), and human adenosine A2A receptor ( Jaakola et al., 2008). These structures are in addition to the earlier crystal structures of inactive rhodopsin (Li et al., 2004; Okada et al., 2004; Palczewski et al., 2000). The structures of turkey b1-adrenergic, and human b2adrenergic receptor, human adenosine A2A receptor and squid rhodopsin are in their inactive conformations. The ligand-free opsin and G-proteinpeptide–bound opsin are in partially active to active state of the receptor. This surge in crystal structures not only facilitates crystallization of other class A GPCRs, but also opens new doors for understanding the dynamics of GPCR conformations and drug discovery research on class A GPCRs.

Small-Molecule Binding to GPCRs

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Understanding small-molecule binding to GPCRs requires two steps: (1) deriving a structural model of the receptor, and (2) modeling the small-molecule–binding site in the receptor structural model. This involves a combination of biophysical methods and computational methods. Structural studies that include crystallography, NMR, other spectroscopic methods such as FRET and spin labeling require sufficient quantities of solubilized purified protein that is especially tedious for GPCRs due to the requirement for optimization of detergent for solubilization. Therefore, cell-based studies such as radiolabeled ligand binding, site-directed mutagenesis, competition binding experiments, and efficacy assays are more readily feasible for many GPCRs. Since these studies do not give direct structural information, the results in combination with a structural model generated using computational methods have been used widely to study ligand binding to GPCRs (Kristiansen, 2004). In this review, we will address the current status of these methods and analyze the merits and pitfalls of the methods.

2. Similarity and Differences in the Crystal Structures of Class-A GPCRs Solved to Date The remarkable similarity of the structures of b-adrenergic receptors, adenosine A2A receptor, and rhodopsin with less than 20% sequence similarity reveals high structural homology in class A GPCRs. However, there are subtle but important differences in the structures, especially in the extracellular (EC) and intracellular (IC) loop regions that are critical to ligand access to the binding site, ligand binding, and G-protein coupling. The extracellular loop 2 (ECL2) is more open in the b-adrenergic receptor structures in comparison to the rhodopsin structures, perhaps facilitating the entry and exit of diffusible small molecules. Unlike rhodopsin, the overall shape of the transmembrane (TM) barrel of b-adrenergic receptors is more open in the EC half than the IC half. The interhelical salt bridge between helix 3 and helix 6—the so-called ‘‘ionic lock’’—is absent in the inactive conformation of b-adrenergic, and A2A receptor structures, but is intact in the inactive rhodopsin structure, and broken in the partially active ligandfree opsin structure. It is possible that the ionic lock is not necessarily present in the inactive structure (Vogel et al., 2008). As shown by some elegant spin labeling and EPR experiments, the ionic lock is broken upon activation of rhodopsin (Farrens et al., 1996) that is also evident in the opsin structure. Thus, the ligand-free opsin structure with the G-protein–peptide bound is an eye-opener to the active state of class A GPCRs and provides a template to model the active state conformation of class A GPCRs that could show selectivity to agonists.

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3. GPCR Modeling Methods Computational methods play a key role in modeling small-molecule binding to class A GPCRs (Schlyer and Horuk, 2006). Here we describe the methods used for predicting structural models for class A GPCRs, and give specific examples for modeling chemokine receptors. The computational methods available to date rely on structural information from biophysical experiments and crystal structures of GPCRs to different degrees. Two classes of computational methods are used for modeling GPCRs: (1) comparative or homology modeling methods, and (2) ab initio methods that use minimal or no experimental information.

3.1. Homology structure modeling methods Homology modeling methods use the similarity of the modeled protein to protein(s) with known structure(s). Commonly, homology modeling methods require more than 40% sequence identity to the template structure to generate a reliable model (Eswar et al., 2008). However, class A GPCRs exhibit remarkable structural homology as evidenced from the available crystal structures of GPCRs, even when the sequence identities are less than 20%. For GPCRs, the template structures would be rhodopsin, opsin, or beta-adrenergic receptors; or the adenosine A2A receptor; or a combination of these structures. There are several software packages that perform homology modeling, including MODELLER (Eswar et al., 2008), Prime (Schrodinger Inc), DSModeler (Accelrys Software Inc), ICM (Molsoft Inc), Sybyl (Tripos Inc), MOE (Chemical Computing Group Inc) and SwissModel (available via ExPASy, http://www.expasy.org). In this review, we will describe the general requirements for materials and methods for these homology modeling software packages. For specific details on each of the methods, see individual software package manuals and a review on this subject by Akbar et al. (2006). 3.1.1. Materials

Access to any of the software packages listed above. Some of them are free of cost for academic users. A computer running Red Hat Linux/Unix, Microsoft Windows 98/ NT/2000/XP, or Apple Mac OSX operating systems; 512 MB RAM or higher; minimum of 1 GB of free hard-disk space for the output files generated, especially after optimization methods used for structure refinement. Knowledge of scripting languages such as Python and/or Perl, depending on the software used to run the scripts used for each package.


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3.1.2. Methods Homology modeling methods in general involve three major steps:

Identification of the template structure to be used for modeling the GPCR under investigation. The sequence alignment of the GPCR to be modeled with the sequences of the template(s). In the case of class A GPCRs, highly conserved residues in each TM helix are used for alignment to b-adrenergic receptors, rhodopsin, and A2A receptors. Methods to optimize the main-chain and side-chain conformations to refine the structure. The quality of the homology model depends on the similarity in the sequence alignment and the resolution of the template structure used. The modeled structures have the same backbone as the template structure, and this could be misleading for sequences with low similarity to the template. For GPCRs, the helical kinks, the tilt and rotational orientation of the TM helices can thus be misplaced; therefore, homology models have to be optimized to enable docking of ligands of different sizes and shapes. Refinement of the homology model is usually performed using a combination of tools such as molecular dynamics (MD), that is, molecular mechanics combined with experimental information as constraints. In the absence of direct structural information, optimization of the model is based on the user’s intuition and indirect experimental results such as effects of point mutation on ligand binding. Homology modeling techniques have been successful in obtaining small-molecule hits from virtual screening of ligands for some cases (Bissantz et al., 2003; Schyler and Horuk, 2006). These models will become more robust with the availability of more crystal structures. While these models are useful in explaining experimental observations, the quality of the model is dependent on the pre-existing experimental information on the receptor structure. Hence, these methods have limited use for GPCRs with very little experimental information.

3.2. Ab Initio modeling methods Ab initio structure prediction methods such as Predict (Becker et al., 2004; Shacham et al., 2004) and MembStruk (Trabanino et al., 2004; Vaidehi et al., 2002) use little or no experimental information, resulting in less bias in the GPCR model. Unlike homology models, these methods generate an ensemble of low-energy conformations that can be used for small-molecule docking. Here we describe briefly the various steps involved in these ab initio methods. Predict is a software package developed and used internally at Epix pharmaceuticals and hence the details of using this software are not known.

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3.2.1. Materials

A computer running Red Hat Linux/Unix, 512 MB RAM or higher; minimum of 5 GB of free hard disk space for the output files generated. MembStruk has a graphical user interface that can be used to execute the various steps involved in modeling the GPCR structure.

3.2.2. Method The MembStruk computational method uses the topological arrangement information of the seven TM helices from rhodopsin or the b-adrenergic receptor as a starting template for further optimization.

The first step of the MembStruk method is identification of the TM helices in the sequence, using a hydrophobicity profile generated from a multiple sequence alignment. The accuracy of the TM length predictions is plus or minus three residues on each terminus of the helix, and this is achieved by including sequences with low sequence identity (less than 20%) in generating the multiple sequence alignment. Canonical a-helices are built and the helices are arranged in an initial template similar to those of rhodopsin or b-adrenergic receptors. Unlike homology modeling, this procedure uses only the rough relative orientations of the helical axes, with no data on atomic positions. This serves as the starting point for optimization of the helices in the helical bundle. The translational orientation of the TM helices is optimized by aligning the residues that represent the position of maximum hydrophobicity in each of the TM helix to a plane. The initial rotational orientation positioning of the helices is based on hydrophobic moment and each helix is rotated so that the net hydrophobic moment of the middle of the helix (14 residues about the hydrophobic maximum) is pointing toward the lipid bilayer. The helical kinks are optimized by performing MD simulations on individual helices with all atom force field (Mayo et al., 1990) in low dielectric medium representing the lipid. Optimization of the rotational orientation of the helices: The optimization of the rotational orientation of each helix with respect to the TM bundle is important in determining which residues are inside the bundle. The rotational orientation is further optimized by deliberately rotating each of the seven helices by plus or minus 30 degrees in 5-degree increments, and reassigning the side-chains conformation using SCWRL (Canutescu et al., 2003); the potential energy of the rotated helix in the presence of all other helices is minimized. We start this procedure with helix3 and then take the best rotation angle for helix3 and further perform this optimization for helix4, followed by helices 5, 6, 7, 1, and 2. This allows optimization of the TM bundle based on the sequence of the


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GPCR being modeled, and hence produces models with backbone structures that are different from rhodopsin or the b-adrenergic receptors. A finite layer of lipids (dilauroylphosphatidylcholine) is packed around the TM bundle from the previous step using rigid body MD (Lim et al., 1996). Generation of an ensemble of low-energy conformations in MembStruk: GPCR conformations exist in multiple conformations, and therefore this method generates an ensemble of low-energy receptor conformations. This is done by systematically varying the rotational orientation of each helix by 5 degrees and then optimizing the TM barrel and calculating the total potential energy of the rotated helix. The number of inter-helical hydrogen bonds and salt bridges formed in each rotated conformation is calculated as well. Using this information, a set of rotations is chosen based on the lowest energies for each helix, and the maximum number of interhelical hydrogen bonds especially hydrogen bonds made by the residues in the middle of the TM helices. Extra- and intra-cellular loops are added using the loop builder modules in the software What If (Vriend, 1990) or MODELLER (Eswar et al., 2008). The accuracy of the predicted models from MembStruk is of low resolution, typically 2A˚ to 3A˚ in backbone conformation of the TM helices. In addition, the approximations in the placement of side chains due to the limited number of rotamer structures available for membrane proteins (Chamberlain and Bowie, 2004) lowers the resolution of these all atom models even further. However, we demonstrate that the MembStruk method can be used to generate a model for the human CCR1 chemokine receptor with no experimental information on the structure of CCR1. The Predict computational method (1) generates multiple coarse-grain packing for a GPCR. This coarse-grain optimization allows for different topological arrangement of the TM helices. B) The coarse-grain models that score better than the decoys are further optimized with the fine-grain MD optimization procedure (Becker et al., 2003). There are several class A GPCR models generated using Predict, as well as some small-molecule hits obtained for a few GPCRs as a part of a commercial effort, but the description and accuracy of these models has not been published. Given the lack of structural information for many class A GPCRs, these low-resolution models have been shown to be useful in generating hypotheses to be tested by experiments (Becker et al., 2006; Hall et al., 2009; Vaidehi et al., 2006). We predicted the structural model of human CCR1 using MembStruk. The resulting structure has the following interhelical hydrogen bonds similar to that of bovine rhodopsin and the two b-adrenergic receptors. Using the GPCR numbering system of Ballesteros and Weinstein (1995), we find that the residue D802.50 makes a 2.9-A˚

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hydrogen bond with N2977.49 and a 2.1-A˚ hydrogen bond with N521.50. E1203.39 forms a 2.9-A˚ hydrogen bond with N2977.49 and a longer hydrogen bond with H2937.45 on helix7. There is a weak or perhaps a water-mediated hydrogen bond between N752.45 and W1584.50 and also between S792.49 and S1193.38. The information gleaned from this model is valuable for understanding the similarities and differences between chemokine receptors and other class A GPCRs with known structures.

3.3. Ligand-docking methods Docking of small molecules to proteins with high-resolution structures is an arduous task in drug design and begs the question of how useful these low-resolution models really are. It has been shown both for soluble proteins and for membrane proteins that low-resolution models have a better chance of predicting the binding sites of ligands of various sizes and shapes (Bissantz et al., 2003; Rockey and Elcock, 2006; Wojciechowski and Skolnick, 2002). Docking of small molecules to GPCRs is usually performed using various ligand-docking methods such as DOCK (Freddolino et al., 2004; Vaidehi et al., 2002, 2006), AutoDock (Hiramoto et al., 2004), Glide (Hall et al., 2009), Flex (Bissantz et al., 2003), or GOLD (Ashton et al., 2004). One explanation for why the small-molecule docking works well on the low-resolution receptor models for GPCRs is that unlike globular proteins, GPCRs have a few polar or charged residues in the TM domain. Many small-molecule GPCR agonists, antagonists, or inverse agonists that are known to bind in the TM domain are polar in nature. Thus, the few polar ligand–receptor interactions can be captured more simply, compared to the numerous hydrophobic interactions in GPCR ligand–receptor interactions. However, straightforward application of the ligand-docking methods and selection of the best-scoring docked conformation for GPCRs does not yield the top-scoring ligand-docked conformation in agreement with point mutation results. Instead, a hierarchical approach that retains multiple ligand-docked conformations and further incorporates constraints and/or induced fit docking followed by optimization of the receptor and ligand is needed to obtain a docked conformation that fits the site-directed mutagenesis data. Since these methods are well established, we suggest that the reader consult a review of these methods elsewhere (Sousa et al., 2006). 3.3.1. Ligand docking to ab initio model of CCR1 The ligand BX471 was docked to the MembStruk model of human CCR1 using a hierarchical procedure based on the DOCK program (Vaidehi et al., 2006). In brief, the procedure is as follows: Using the DOCK program, several docked conformations of the ligand were generated and the


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top-scoring 100 conformations were chosen by buried surface of the ligand and the DOCK scores for further optimization. The 100 docked-ligand conformations were minimized in potential energy using the conjugate gradient method with the receptor fixed, and 10% of the top-scoring conformations were chosen by binding energy. Binding energy was calculated as the difference in potential energy of the ligand in the receptor, and the potential energy of the ligand in water was represented using the generalized Born continuum solvation model (Ghosh et al., 1998). The resulting top-scoring 10 CCR1/BX471 complex conformations were further optimized by minimizing the potential energy of the receptor and the ligand and selecting the top-scoring docked conformation by binding energy. Analysis of the docked structure of BX471 in hCCR1 (shown in Fig. 13.1) showed that residues Y1133.32 and Y1143.33 and I2596.55 interact strongly with BX471 via hydrophobic and pi-stacking interactions. The role of explicit water in the ligand binding was further examined by performing MD simulations of the CCR1/BX 471 complex in explicit lipid bilayer and water using the NAMD program (Phillips et al., 2005). We found that the urea group is highly flexible and forms hydrogen bonds with water molecules that enter the binding region rather than with the residues in CCR1 receptor. The predictions made from this model were verified subsequently by site-directed mutagenesis and radiolabeled-ligand binding as discussed in the following sections. GPCRs have a wide variety of small-molecule ligands with varied efficacy, such as the full agonists, strong partial agonists, weak partial agonists, neutral antagonists, and inverse agonists. These various types of ligands elicit different levels of biological signaling efficacy at saturating concentrations by inducing conformational changes to different extents, thus stabilizing a ‘‘ligand-induced specific state’’ (LISS) (Kobilka and Deupi, 2007; Urban et al., 2007; Yao et al., 2006). Thus, an understanding of the conformational dynamics of GPCRs, especially for the agonistbound active states, is important in achieving functional specificity in drug design (Mailman, 2007). Therefore, optimizing one model for a given GPCR is clearly inadequate and it is vital to account for receptor flexibility when ligands are bound.

4. Computational Methods for Receptor Flexibility and Ligand-Induced Conformational Changes in GPCRs The models that account for ligand-induced conformational changes are useful in gaining insights into the activation mechanism of GPCRs. Changes in inter-residue distances upon activation have been measured

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Figure 13.1 The predicted binding site of BX471 in the human CCR1 chemokine receptor. (A) A top view of the predicted structure of BX 471 in the CCR1 binding pocket. The residues shown in red (Tyr-113, Tyr-114, and Ile-259) are responsible for anchoring the ligand in this cavity. The binding site shown is located between trans˚ of the ligand BX471 are membrane helices 3, 4, 5, 6, and 7. (B) The residues within 5A shown in pink sticks. The residues Y1133.32, Y1143.33, and I2596.55 shown in red contribute the most to the binding of BX471 in human CCR1. (From Vaidehi, N., Schlyer, S., Trabanino, R. J., Floriano, W. B., Abrol, R., Sharma, S., Kochanny, M., Koovakat, S., Dunning, L., Liang, M., Fox, J. M., de Mendonca, F. L., Pease, J. E., Goddard, W. A., 3rd, and Horuk, R. (2006). Predictions of CCR1 chemokine receptor structure and BX 471 antagonist binding followed by experimental validation. J. Biol. Chem. 281, 27613–27620.)

using spin labeling and fluorescent measurements (Farrens et al., 1996; Yao et al., 2006). The active state model of rhodopsin has been modeled using annealing MD simulations with the available experimental data as


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constraints (Gouldson et al., 2004; Niv et al., 2006). All-atom MD simulations for 2 ms on trans-retinal bound rhodopsin have provided valuable insight into the counterion switching mechanism for activation (Crozier et al., 2007; Martinez-Mayorga et al., 2006). Another method of predicting the active state conformation is by using the elastic network model (ANM/ GNM), where the inter-residue contacts obtained from experiments are used in computing the principal components of molecular motion by inverting the Hessian matrix (Isin et al., 2008). These methods have been successful in uncovering some of the mechanisms associated with ligandinduced conformational changes, with partial validation of experimental observations. Vaidehi and coworkers have recently developed computational methods that systematically map the conformational changes in GPCRs in response to ligand binding (Bhattacharya et al., 2008a, 2008b). This method, known as Liticon, combines the systematic spanning of simultaneous rotational orientation of all the TM helices that will speed up the conformational search, followed by all-atom MD simulation on the best energy structure chosen from the systematic spanning analysis. This method does not use the experimental information as input for optimization, but the experimental information is used in validating the predicted active-state model.

4.1. Liticon method

The first step of the Liticon method is to pack a finite section of a lipid bilayer (dilauroyl phosphatidyl choline) around the structure of the GPCR with the docked ligand using rigid body MD simulations. The next step is to identify which of the TM helices are in direct contact with the ligand and would undergo conformational changes due to ligand binding. To this end, systematic spanning of rotational orientation of each helix is performed independently, in the presence of ligand. In this step, individual TM helices are rotated from –180 to þ180 degrees in increments of 5-degree rotations and the energy of the helix calculated. The helices whose potential energy shows substantial changes upon rotation with ligand present will be mapped using this procedure. This step involves simultaneous systematic spanning of the rotational orientation of TM helices identified to affect ligand binding in the previous step. Such an optimization procedure would allow us to go over barriers that MD simulations cannot overcome. This process generates tens of thousands of receptor conformations. For each conformation, the following optimization steps are performed: Optimization of all side-chain conformations using SCWRL 3.0. Conjugate gradient minimization of the potential energy of the ligand in the field of the rest of protein fixed until convergence of 0.1 kcal/ ˚ RMS deviation in force per atom is achieved. mol-A

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Calculation of the ligand-binding energy defined as the difference of the potential energy of the ligand with protein fixed, and the potential energy of the free ligand calculated in water using the generalized Born solvation method (Ghosh et al., 1996). Interhelical and ligand-receptor hydrogen bonds using HBPLUS 3.0 (McDonald and Thornton, 1994). This generates a multidimensional binding-energy landscape that is used to identify all the local minima in the landscape and cluster them in coordinate space using the k-means clustering algorithm. The best binding-energy conformation from each cluster is taken and then sorted by total number of interhelical HB and ligand-receptor HB, and by binding energy. The final ligand-stabilized receptor structural model is then selected based on low binding energy and high number of hydrogen bonds. Subsequently, long time-scale MD simulation is performed on the best minimum chosen from the previous step in explicit lipid and water. This step will optimize the helical kinks and tilts in response to the ligand binding. Liticon has been recently validated for prediction of active state of rhodopsin and compared to the experimental results on meta-rhodopsin and the ligand-free opsin structure (Bhattacharya et al., 2008a). It has also been used to predict the ligand-stabilized conformational states of the human b2 adrenergic receptor (b2AR) with bound ligands of various efficacies (Bhattacharya et al., 2008b). Virtual ligand screening of smallmolecule database shows that agonist-stabilized conformations show preference to agonists (of varied chemical structure) compared to the antagonist- or inverse agonist–bound structure.

5. Validation of GPCR–Ligand Models Once the GPCR of interest has been modeled, and the small compound docked by in silico means, a network of putative interactions between the receptor and compound can be envisaged. The validity of the model can then be assessed by laboratory investigation. A substantial part of our experience in this area is with the validation of antagonist-binding sites of chemokine receptors and the following methods are described with those systems in mind. However, as long as suitable systems for measuring GPCR expression and activation are available, then these may be interchanged. An approach that we have employed following analysis of a model is to generate mutations of the amino acids implicated in contacting the antagonist. This is achieved by mutation of the relevant receptor cDNA housed in a plasmid such as pCDNA3 (Invitrogen) allowing high-level expression in mammalian systems, under the hCMV promoter. Since the model is likely


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to suggest interactions of the compound with several amino acids of the GPCR, then we recommend the use of a transient transfection system, allowing data to be generated rapidly without the need to generate a battery of stable cell lines. In the first instance, we interrogate the model by asking three questions of each point mutation:

Does the mutation affect cell surface expression of the GPCR? If the mutant GPCR is expressed at the cells surface, is it still functional? If the mutant GPCR is still functional, then is it still amenable to antagonism by the small molecule of interest?

5.1. General strategies for mutagenesis Several systems are available for mutagenesis and typically rely upon the process of ‘‘overlap PCR’’ to introduce the desired mutation (Ho et al., 1989). This involves the design of complementary overlapping oligonucleotide primers that introduce the desired mutation by means of a mismatch in the DNA sequence. We favor the use of kits such as Quikchange (Stratagene, CA), which amplify the entire plasmid, circumventing the need for a subsequent cloning of the mutant receptor cDNA. We have also found it advantageous to introduce an HA-epitope tag at the amino-terminus of the receptor by an in-frame insertion at the 50 region of the open reading frame between the first and the second codons. This tag encodes only nine additional amino acids and does not appear to interfere with ligand binding. Importantly, it allows cell surface expression to be easily examined following transfection. Once mutated, the cDNA is sequenced to check that the desired mutations have been introduced, prior to expression in a suitable system. For our studies of chemokine receptors, we have found that a leukocyte cell line such as the murine pre–B-cell L1.2 affords good expression and subsequent functionality of the introduced receptor. 5.1.1. Maintenance of the L1.2 cell line Reagents

RPMI 1640 medium with Glutamax-I, 25 mM HEPES (Invitrogen cat. no. 72400-021) Certified fetal calf serum (Invitrogen,, cat. no. 16000-044) Penicillin/streptomycin liquid (Invitrogen, cat. no. 15140-122) 100 nonessential amino acids (Invitrogen, cat. no. 11140-035) 1 mM b-mercaptoethanol (Invitrogen, cat. no. 31350-010) 1 mM sodium pyruvate (Invitrogen, cat. no. 11360-039)

Heat inactivate the calf serum by incubating at 55 C for 30 min. Aliquot into 50-ml volumes, and store at –20 C until needed.

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To a 500-ml bottle of RPMI 1640 medium with Glutamax-I, 25 mM HEPES, add the following:

50 ml of heat-inactivated calf serum 5 ml of penicillin/streptomycin 5 ml of nonessential amino acids 0.5 ml of mercaptoethanol 5 ml sodium pyruvate

This buffer referred to as ‘‘complete’’ RPMI medium, can be stored at 4 C until needed. L1.2 cells should be maintained in this medium at a concentration of 0.5 to 1 106 cells/ml until required for transfection. We find that transfection of cells over a concentration of 1.5 106 cells/ml leads to suboptimal expression. 5.1.2. Transient transfection of L1.2 cells Reagents and Equipment

Biorad Gene-Pulser II Electroporator (or equivalent) Gene Pulser cuvettes, 0.4-cm gap electrode (Biorad Laboratories, Hercules, CA, cat. no. 165-2088) tRNA from baker’s yeast, 10 mg/ml solution (Sigma-Aldrich, cat. no. R-8508) RPMI 1640 medium (1), liquid with GlutaMAXTM I, 25 mM HEPES (referred to as simple RPMI) (Invitrogen, cat. no.72400-054) RPMI complete medium (see section on L1.2 cell maintenance) Sodium butyrate (Sigma-Aldrich, cat. no. B-5887)

Method All procedures are to be carried out in a laminar flow hood to maintain sterility of the cells.

1. Dissolve the sodium butyrate in sufficient tissue culture–grade water to make a 10-mM solution. Pass this through a 0.4 mm filter into a sterile container and keep at room temperature (RT), protected from light. 2. For each transfection, set aside a single electroporation cuvette into which a fixed amount of tRNA is placed to act as a carrier (50 ml of a 10 mg/ml solution). To the tRNA add the appropriate amount of plasmid DNA containing the cDNA of interest is added. For each 1 106 of L1.2 cells to be transfected, use 1 mg of plasmid DNA. We have successfully transfected between 0.5 and 40 106 L1.2 cells in each cuvette. 3. From a stock of L1.2 cells at log phase, take an aliquot and after counting with a hemocytometer, centrifuge the desired amount of cells for 5 min at 300g, RT, and decant the media. Resuspend the L1.2 cell pellet in the appropriate amount of simple RPMI media, namely 800 ml of simple RPMI for each transfection and mix the cells by gently flicking the cuvette. Incubate at RT for 20 to 30 min (preferably inside the flow hood).


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4. Electroporate the cells at 330 volts and 975 mF. If the electorporator is set to view the time constant, this typically reads 16 ms following transfection. 5. Incubate the cuvette at RT for 20 to 30 min (preferably inside the hood). 6. Break any surface cell clump by gentle pipetting and transfer the contents of the cuvette into a T-75 tissue-culture flask, containing enough complete RPMI at a final concentration of 1 106 cells/ml. 7. Incubate the transfected cells for 3 to 5 h at 37 C, 5% CO2 in a tissueculture incubator. 8. Add sufficient sodium butyrate solution to a final concentration of 10 mM (1:100 dilution). 9. After 18 to 24 h of culture, examine receptor cell surface expression by flow cytometry. 5.1.3. Assaying receptor expression Reagents

Primary antibody: For instance, HA.11, Mouse anti-HA monoclonal antibody (Covance Research Products, cat. no. MMS-101R) Secondary antibody: For example, goat antimouse FITC labeled F(ab’) 2 (Dako Cytomation, cat. no. F0479) Bovine serum albumin (BSA), fraction V powder (Sigma-Aldrich, cat. no. A2153) Dulbecco’s phosphate buffered saline (D-PBS) 1X (Invitrogen, cat. no. 14040-174) 1 M HEPES solution (Invitrogen, cat. no. 15630-049) TO-PRO-3 iodide, 1 mM solution in DMSO (Invitrogen, cat. no. 642/661)

Stock Solutions

10% sodium azide solution (1000 stock solution): Dissolve 2 g of sodium azide in 20 ml of milli-Q grade water. Store at RT. Flow cytometry staining buffer: To a 500-ml bottle of PBS, add 1.25 g of BSA and dissolve by gentle stirring to make a 0.25% (w/v) solution. Readjust the pH to 7.4 if necessary by adding five to eight drops of 1 M NaOH. Add 500 ml of 10% sodium azide solution. Method All incubations are to be carried out on ice unless otherwise stated.

1. From the flask of transfected L1.2 cells, take an aliquot and after counting with a hemocytometer, place the appropriate volume in a suitable tube (e.g., Falcon 12 75-mm test tubes, cat. no. 352052) and centrifuge for

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2. 3. 4. 5. 6.


5 min at 300g at RT, and then decant the media. Typically, 0.5 to 1 106 transfected cells are adequate for staining. Resuspend the cell pellet by gentle pipetting in 100 ml of staining buffer containing either the primary antibody or isotype control at 10 mg/ml and incubate for 15 to 30 min. Wash the cells by adding 1 ml of staining buffer and centrifuge at 300g for 5 min at RT. Decant the supernatant and resuspend the cells in 100 ml of secondary antibody diluted in staining buffer (1:20) and incubate cells for 15 to 30 min. Wash the cells as in Step 3 and resuspend cells in 500 ml of staining buffer containing TO-PRO3 at a dilution of 1:10,000. Read the samples on the flow cytometer following the manufacturer’s instructions.

We typically acquire 10,000 events and analyze the staining of live cells by excluding cells in the FL4 channel, which are TO-PRO3þve and therefore dead. Notes: The primary and secondary antibodies of choice should be compatible with the detection of the constructs to be analyzed. We routinely make use of an HA epitope tag, and therefore use an anti-HA primary antibody for detection. Likewise, we find the goat antimouse secondary antiserum fit for detection. It may pay to titer the concentrations of both antibodies to get the best staining.

5.2. Receptor binding 5.2.1. Radioligand binding assays Reagents and equipment

Radiolabeled chemokine of choice (2200 Ci/mmol) (New England Nuclear) Appropriate unlabeled competing chemokines and antagonists RPMI 1640 Medium (1X), liquid with GlutaMAXTM I, 25 mM HEPES (Invitrogen, cat. no. 72400-021) Bovine serum albumin (BSA), fraction V powder (Sigma-Aldrich, cat. no. A2153) 96-well polypropylene plates 0.4-ml soft polypropylene tubes (Sarstedt, Numbrecht, Germany, Cat. no. 72.700) Nyosil M-25Oil (TAI Lubricants, Inc, Hockessin, DE) LP3 tubes (Luckham, Burgess Hill, UK) Canine nail clippers

Stock solution

Binding buffer: 0.1% BSA in RPMI. Readjust the pH to 7.4 if necessary by adding five to eight drops of 1 M NaOH. Add sufficient 10% sodium azide solution to give a final concentration of 0.05%.


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Method

1. Prepare serial dilutions of the relevant unlabeled chemokines using the binding buffer. If the appropriate dose–response is unknown, then final concentrations of 0.03, 0.1, 0.3, 1, 3, 10, 30, and 1000 nM may prove a useful staring point. From a 10-mM stock of unlabeled chemokine, dilute 2 ml in 80 ml and 0.6 ml in 80 ml to give 2.5 stock concentrations of 100 nM and 30 nM, respectively. These can be diluted 1:10 to produce 80 ml of each subsequent concentration. 2. Prepare 100 ml of a 1 nM stock concentration of 125I-labeled chemokine in binding buffer. Refer to the data sheet accompanying the product, but typically this involves a 1:20 to 1:50 dilution of the radiolabel in binding buffer. 3. Resuspend the transfected L1.2 cells at 1 106 cells in 25 ml in binding buffer. 4. Into duplicate wells of the plate, pipette 20 ml of the serial dilutions of chemokines. In addition, pipette 20 ml of binding buffer into two separate wells. To each well, also add 5 ml of the diluted radiolabeled chemokine. 5. Into each well, pipette 25 ml of the transfected cells and mix gently by pipetting up and down a couple of times. Incubate at RT for 60 to 90 min. 6. While this is incubating, prepare tubes for centrifugation by pipetting 100 ml of Nyosil oil in the 0.5-ml tubes. We find a repeating pipette helpful here. 7. Prepare 10 ml of salt wash by dissolving 0.4 g of NaCl in assay buffer. 8. At the end of the incubation into each well, pipette 50 ml of salt wash and mix by gentle pipetting. Remove 80 ml of the mixture and layer onto a separate centrifugation tube. Close the lids of these tubes and pellet through the oil by centrifugation at 10,000g for 3 min. After centrifugation, a cell pellet should be visible at the bottom of the tube and the binding buffer should be visible as a layer on top of the oil. 9. Using the canine nail clippers, cut the bottom of the tube into an appropriate counting tube from the supernatant and collect both fractions. We use LP3 tubes on a Canberra Packard Cobra 5010 gamma counter (Canberra Packard, Pangebourne, UK). The data are routinely presented as the percentage of maximal binding observed in the presence of buffer alone and can be subjected to curve fitting and subsequent analysis using appropriate software such as PRISM (GraphPad Software Inc, San Diego, CA). Notes: The dose–response curve should be sigmoidal in nature. For subsequent experiments using antagonists to inhibit ligand binding, we recommend using the same fixed concentration of radiolabeled chemokine as used for competition with unlabeled chemokine, substituting the unlabeled

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chemokine with the appropriate antagonist. We recommend starting with a range of 0.01 nM to 10 mM of antagonist in the first instance and modifying this if necessary. As discussed above, to verify the predicted binding site of a GPCR elucidated by receptor modeling, receptor mutants have to be generated and tested in a number of ways. The mutants will, as discussed, include key residues predicted to be in the binding pocket for the small molecule that has been docked into a receptor cavity of a GPCR. As an example, recent modeling with the CCR1 receptor identified several residues, including Y1133.32, Y1143,33, and I2595.55, as forming contact points with the CCR1 antagonist BX471 (Fig. 13.1). Alanine scan mutants of these residues were then generated and tested in receptor binding and in chemotaxis assays (to be described in the following) to verify their role in the antagonist-binding site. CCR1 point mutants that included these and other residues were all transiently expressed at high levels on the surface of L1.2 cells (as described previously). The CCR1 point mutants were tested for the ability of BX 471 to displace the specific binding of 125I-CCL3 to the wildtype and mutant receptors. Whole-cell binding assays on transiently transfected L1.2 cells were performed using 0.05-nM radiolabeled CCL3 and increasing concentrations of unlabeled competitor. In all experiments, each data point was assayed in triplicate. Data are presented as the percentage of counts obtained in the absence of cold competing ligand. The binding data were curve fitted with the computer program PRISM (GraphPad Software Inc, San Diego, CA) to determine the affinity and number of sites. Using this competition-binding assay, the mutations Y113A3.32 and Y114A3.33 on TM3 and I259A6.55 on TM6 resulted in a significant reduction in binding of BX 471. Specifically, while the antagonist binds to the wildtype receptor with an IC50 of 10 nM, the IC50 for the Y113A3.32 and I259A6.55 mutants is greater than 10 mM, and for Y114A3.33 it is greater than 5 mM. The large effects of these three mutations on BX471 binding had been predicted in the computational mutation studies that showed a change in binding energy of 6.28, 5.79, and 9.24 kcal/mol, respectively. A major assumption in receptor mutagenesis studies is that any loss of function observed is due to the mutation alone and does not involve structural changes in the molecule. Such an assumption is generally valid for surface residues, but is not necessarily true for buried (structural) large hydrophobic or aromatic residues. Since the residues identified as important for binding, Y1133.32, Y1143.33, and I2596.55 are buried hydrophobic or aromatic residues it was important to determine that the mutations did not perturb the structure of the receptor. To test the structural integrity of the three CCR1 mutants Y113A3.32, Y114A3.33, and I259A6.55, both displacement binding and chemotaxis studies with the CCR1 ligand CCL3 were carried out. These studies were carried out in HEK 293 cells that constitutively expressed high levels of wildtype CCR1 receptor. The binding studies


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revealed that all three mutants had very similar affinities for binding of CCL3 (WT Ki ¼ 31.8 16.1 nM, Y113A3.32 Ki ¼ 22.3 3.1 nM, Y114A3.33 Ki 15.3 3.3 nM, I259A6.55 Ki ¼ 14.7 4.9 nM ). These data suggest that the mutations did not alter the structural integrity of CCR1, and thus further validated the idea that they played a key role in ligand binding of the antagonist BX471. 5.2.2. Direct binding assays Direct binding assays with a 125I-labeled CCR1 antagonist, BX691, were used to further characterize the CCR1 antagonist–binding site. Method

1. SPA beads (wheat germ agglutinin–coated beads) were resuspended at a concentration of 500 mg in 5 ml of binding buffer(50 mM HEPES, 5 mM MgCl2, 1 mM CaCl2, 100 mM NaCl, 5% BSA, pH 7.5). The beads were stored at 4 C overnight and warmed to RT before use. 2. HEK293 cells expressing recombinant CCR1 were resuspended in binding buffer at 1 106 cells/ml and 20,000 cells per assay point were used. Cells were incubated with SPA beads for 30 min at RT and rotated end over end. 3. Prepare serial dilutions of the CCR1 antagonist, BX 471 using the binding buffer. From a 100 mM stock of unlabeled BX 471, dilute 2 ml in 80 ml and 0.6 ml in 80 ml to give 2.5 stock concentrations of 1000 nM and 300 nM, respectively. These can be diluted 1:10 to produce 80 ml of each subsequent concentration. 4. Prepare 100 ml of a 1-nM stock concentration of 125I-labeled BX 691 in binding buffer. This involves a 1:20 to 1:50 dilution of the radiolabel in the binding buffer. 5. Into duplicate wells of the plate pipette 5 ml of the serial dilutions of the BX 471. To each well, also add 5 ml of the diluted radiolabeled BX 691. 6. 6. Into each well, pipette 40 ml of the transfected cells/SPA bead mixture and mix gently by pipetting up and down a couple of times. The plates were sealed with a clear sealer and incubated for 60 to 90 min at RT on an orbital shaker. 7. The receptor bound 125I-BX 691 excited the scintillant embedded in the beads and triggered a signal that could be detected by scintillation counter (Wallac Microbeta). Nonspecific binding was determined in the presence of 100 nM of unlabeled ligand. 8. The data are routinely presented as the percentage of maximal binding observed in the presence of buffer alone and can be subjected to curve fitting and subsequent analysis using appropriate software such as PRISM (GraphPad Software Inc, San Diego, CA).

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The resulting compound BX 691 is a functional antagonist for CCR1 with similar potency (Ki 1.7 nM ). Since BX 471 and BX 691 behave similarly as CCR1 antagonists, 125I-BX 691 was used to characterize the direct interaction of small-molecule CCR1 antagonists with CCR1. 125I-BX 691 binds to CCR1 on human monocytes as well as on HEK293 cells that express the receptor. The binding is dose-responsively inhibited by unlabeled BX 471 and BX 691, with affinities similar to those for displacing 125I-CCL3 binding. However, the CCR1 agonists CCL3, CCL5, and CCL7 failed to displace 125I-BX 691 binding to CCR1, suggesting that they do not bind to the same site on the receptor as the antagonists. These data clearly suggest that BX 471 and BX 691 are allosteric antagonists of CCR1 and bind to sites on the receptor that are nonoverlapping and distinct from the agonist-binding site. Indeed, structure–function studies have revealed that chemokines such as CCL3 bind to CCR1 via residues in the N-terminus and in the extracellular loops. Finally, the receptor mutants are analyzed to determine whether they are capable of responding functionally to a challenge by chemokines and that the antagonist can block this response, that is, whether it is a functional antagonist. To evaluate this response, we routinely carry out chemotaxis experiments using the same transfected L1.2 cells that we described previously. 5.2.3. Assaying chemokine receptor function by chemotaxis Reagents

RPMI 1640 medium with Glutamax-I, 25 mM HEPES (Invitrogen, cat. no. 72400-021) Bovine serum albumin (BSA), fraction V powder (Sigma-Aldrich, cat. no. A2153) 96-well disposable chemotaxis plate (Neuroprobe, cat. no. 101-5) Chemokines of interest, preferably in PBS at a concentration of 10 mM Stock solutions

Blocking buffer, RPMI 1% BSA Dissolve 0.1g BSA (bovine serum albumin) in 10 ml of simple RPMI (A volume of 10 ml is enough to block one plate.) Assay buffer, RPMI 0.1% BSA Make a 1/10 dilution of the blocking buffer with simple RPMI. A volume of 10 ml is enough to run an assay using one 96-well plate. Method

1. Into each well of the plate that will be used, pipette 30 ml of blocking buffer. Incubate for 30 min at RT. This step prevents excessive adhesion of chemokines to the plastic.


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2. Prepare serial dilutions of the relevant chemokines using the assay buffer. If the appropriate dose–response is unknown, then a range of 0.1, 1, 10, 100, and 1000 nM may prove to be a useful starting point as follows: To make a 1 mM solution, take 8 ml stock chemokine (10 mM ), add 72 ml assay buffer and mix by gentle flicking of the tube. From this, similar serial dilutions can be made to generate 80-ml volumes of 100-nM, 10-nM, 1-nM, and 0.1-nM chemokine dilutions. 3. Centrifuge the L1.2 transfectants for 5 min at 300g at RT. 4. Resuspend cells in a volume of assay buffer such that each 20-ml buffer contains 2 105 cells. 5. Remove the blocking buffer from each well of the chemotaxis plate with a pipette or a water vacuum with a tip at the end. 6. Into duplicate wells, pipette a final volume of 31 ml of each of the chemokine dilutions. Into two separate wells also pipette 31 ml of assay buffer. 7. Secure the membrane on top of the plate by reference to the pegs, making sure that no air bubbles are visible between the plate and the membrane. 8. Onto the top of each filter, pipette 20 ml of the cell suspension. 9. Incubate plate in a humidified chamber for 5 h at a 37 C tissue-culture incubator with 5% CO2. 10. Carefully scrape the cells from the top of the membrane, taking care to avoid damaging the membrane. 11. Using a hemocytometer, count the number of cells in each well migrating to the various concentrations of chemokine and to the buffer control. 12. Subtract the average of the buffer control counts from the averages of the other wells to generate a dose–response of migration to the appropriate chemokine. Notes: The dose–response curve is typically bell-shaped in nature, and for subsequent experiments using antagonists to inhibit cell migration, we recommend choosing a fixed concentration of chemokine that provides a significant level of chemotaxis, but is suboptimal, that is, to the left of the bell-shaped curve. Assay buffer can be prepared using a fixed concentration of chemokine and serial dilutions of antagonists generated in this buffer. These are placed in the lower well as before and cell migration assessed as before. This should generate a sigmoidal dose–response curve. We recommend starting with a range of 0.01 nM to 10 mM of antagonist in the first instance and modifying this if necessary. We used this assay recently to analyze CCR1 mutants that we had tested in receptor-binding assays as described above. The residues we had identified as important for binding in this study—Y1133.32, Y1143.33, and

284 B 691 bound (CPM)

2500 2000 1500 1000 500 0

CCL3

CCL5

CCL7 BX 471 BX 691

−12 −11 −10 −9 −8 −7 Log [competitors], M

125I-BX

125I-BX

691 bound, CPM

A


−6

3000 2500 2000 1500 1000 500 0

CCL3 CCL5 CCL7 BX 471 BX 691

−12 −11 −10 −9 −8 −7 Log [competitors], M

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Figure 13.2 Inhibition of 125I-BX 691 binding to human CCR1 by unlabeled antagonists and agonists on HEK293 cells stably expressing CCR1 (A) and human monocytes (B). Cells were incubated for 60 min at RT with 125I-BX 691 in the presence of increasing concentrations of compounds or chemokines. The bound 125I-BX 691 was determined using SPA technology. Nonspecific binding was defined as the binding in the presence of 1 mM unlabeled BX 691. Data are shown as total binding standard error from three independent experiments. (From Vaidehi, N., Schlyer, S., Trabanino, R. J., Floriano, W. B., Abrol, R., Sharma, S., Kochanny, M., Koovakat, S., Dunning, L., Liang, M., Fox, J. M., de Mendonca, F. L., Pease, J. E., Goddard, W. A., 3rd, and Horuk, R. (2006). Predictions of CCR1 chemokine receptor structure and BX 471 antagonist binding followed by experimental validation. J. Biol. Chem. 281, 27613–27620.)

I2596.55—were buried hydrophobic or aromatic residues, and it was important to determine that the mutations we made did not perturb the structure of the receptor. To test for the structural integrity of the three CCR1 mutants Y113A3.32, Y114A3.33, and I259A6.55, we carried out both displacement-binding and chemotaxis studies with the CCR1 ligand CCL3. The binding studies revealed (Fig. 13.2) that all three mutants had very similar affinities for binding of CCL3 (WT Ki ¼ 31.8 16.1 nM, Y113A3.32 Ki ¼ 22.3 3.1 nM, Y114A3.33 Ki ¼ 15.3 3.3 nM, I259A6.55 Ki ¼ 14.7 4.9 nM ). In addition, all three mutants responded chemotactically in a similar dose-responsive manner as wildtype CCR1 to increasing concentrations of CCL3 (Fig. 13.3). These data strongly suggested that the mutations did not alter the structural integrity of CCR1, and thus validated our contention that they played a key role in ligand binding of the antagonist BX 471.

6. Conclusions We have described state-of-the-art methods for small-molecule binding in GPCRs, with an example of BX471 binding to the chemokine receptor CCR1. Through this description of results on CCR1, we have shown that a combination of computational models and site-directed mutagenesis

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Figure 13.3 BX 471 inhibition of CCL3-mediated chemotaxis of L1.2 cells transiently expressing selected CCR1 point mutants. (A) Dose–response curves of BX 471 inhibition of CCL3-induced chemotactic responses of L1.2 cells transiently expressing selected CCR1 point mutants. The inhibition of the responses of each construct to a 10 nM concentration of CCL3 is illustrated. Data are representative of a typical experiment of at least two independent experiments. (From Vaidehi, N., Schlyer, S., Trabanino, R. J., Floriano, W. B., Abrol, R., Sharma, S., Kochanny, M., Koovakat, S., Dunning, L., Liang, M., Fox, J. M., de Mendonca, F. L., Pease, J. E., Goddard, W. A., 3rd, and Horuk, R. (2006). Predictions of CCR1 chemokine receptor structure and BX 471 antagonist binding followed by experimental validation. J. Biol. Chem. 281, 27613–27620.)

experiments is vital to elucidate the binding sites of small molecules in GPCRs. It also suggests that structure-based in silico rational drug design for GPCR targets is feasible using the validated structural models. The level of approximations involved in the computational modeling of ligand binding and calculation of binding energies in GPCRs to date would allow us to differentiate a very good binder ( 670 nm is measured using a long-pass filter (the detection window is indicated by the rectangle).

of six ab monomers arranged as a disc. In phycobilisomes, these discs are stacked to form a highly ordered array. PE, APC, and other phycobiliproteins in the phycobilisomes transfer light energy from one to another via FRET and ultimately to chlorophyll to achieve photosynthesis (Glazer et al., 1985; Viskari and Colyer, 2001). The FRET occurring during this process is characterized by high quantum yields (up to 98 %) and large extinction coefficients and Stoke’s shifts. Although this very high FRET efficiency relies on the specific, ordered structure of the phycobilisome, experimental protocols utilizing less-ordered phycobiliproteins, such as the PE and APC forms conjugated to mAbs, can nevertheless achieve impressive FRET efficiencies. The relative efficiency of phycobiliprotein FRET aids in the detection of FRET signals and simplifies using the PE/APC FRET chromophore pair for experimental purposes. Despite these significant advantages, some disadvantages are also associated with using the PE/APC fluorophore pair for FRET assays. Chief among these is the large size of these phycobiliprotein chromophores.

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The hexameric form of PE and APC is approximately 150 kD, which makes this FRET pair unsuitable for fine distance measurements, such as within a single molecule. This problem is compounded in our protocol since we utilize mAbs to link the chromophores to the receptors. As discussed below, this disadvantage can be ameliorated by using multiple approaches to confirm molecular interactions.

1.3. CFP/YFP fusion protein FRET To avoid potential ambiguity due to the use of receptor-binding antibodies and the bulky nature of the PE and APC fluorophores and their mAbmediated attachment to the receptors, we also used a second FRET approach for assaying CXCR4-TCR interactions in living T cells (Kumar et al., 2006). In recent years, the use of green fluorescent protein (GFP) and its color variants cyan (CFP) and yellow (YFP) fluorescent proteins, has become a prevalent approach for measuring protein–protein interactions by FRET (Chan et al., 2001; He et al., 2003a,b; Shaner et al., 2005; Tsien, 1998). In this FRET approach, the entire fluorescent sensor is encoded and expressed in cells as a fusion with the protein(s) of interest. Molecular genetic manipulation of expression plasmids makes this easy to achieve simply by transfecting cells with appropriate expression plasmids. In the CFP/YFP FRET assay, the excitation of CFP is achieved by 433-nm light, which leads to the emission of cyan fluorescence with a peak at 475 nm. If YFP is close by, energy from CFP can be transferred to YFP, and consequently emission from YFP will occur with a peak wavelength at 528 nm. Unfortunately, the CFP/YFP FRET system displays several nonideal spectral characteristics. In contrast to the PE/APC FRET pair discussed above, the CFP/YFP FRET pair suffers from weak overlap of excitation spectra and poor separation of excitation spectra, as well as poor separation of emission spectra. It is therefore more difficult to avoid potential excitation and emission spectra overlap in CFP/YFP FRET systems than in PE/APC FRET systems. Problems arising from overlap of the excitation spectra can be avoided by using 433-nm light for excitation (as recommended in our protocol below), whereas use of 458-nm light for excitation is not recommended. Problems arising from emission spectra overlap are more difficult to avoid. Very sensitive ratio imaging by a charge-coupled device (CCD) camera can be used ( Jares-Erijman and Jovrin, 2003) to reliably establish FRET using this system. Alternatively, as we describe below, CFP/YFP FRET can be established by using a spectrofluorimeter that allows examination of the entire emission spectra. This permits the confirmation of FRET by assuring that increases in YFP (acceptor) fluorescence occur concomitant with a decrease in CFP (donor) fluorescence.

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1.4. Using both FRET approaches to study CXCR4–TCR proximity We used two different FRET approaches to detect CXCR4–TCR interactions (Kumar et al., 2006). Each FRET approach has advantages and disadvantages, but by combining the approaches we were able to obtain complementary data sufficient to provide strong support for our conclusions. In addition to the technical advantages discussed above, our PE/APC FRET approach has the advantage of examining interactions between native receptors expressed on the cell surface at endogenous levels. Because it does not require transfection, this approach can be used to examine CXCR4–TCR interactions of normal T lymphocytes and other cells that are difficult to transfect. On the other hand, this PE/APC FRET approach may not be generally applicable for studying all protein–protein interactions, primarily because it relies on using mAbs to link the chromophores to the proteins. The use of mAbs requires that the proteins to be assayed must be abundantly expressed on the cell surface and that specific antibodies directed against a cell-surface–accessible epitopes are available. The mAbs might affect receptor function upon binding to the proteins, or they might also bind to epitopes too distant to allow the chromophores to interact. Although we have solved these problems specifically for our CXCR4TCR FRET assay by carefully selecting mAbs for use in the FRET assay, these issues must be considered when modifying this approach to analyze interactions between other cell-surface proteins. Another general disadvantage of the PE/APC FRET system is that both the mAbs and the PE and APC chromophores are quite large, and this necessarily reduces the molecular resolution that can be obtained from the FRET assay. For these reasons we also examined CXCR4–TCR interactions using the CFP/YFP FRET system. This system has the advantages of employing smaller-sized fluorescent probes (YFP and CFP are each approximately only 25 kD in size) and of not requiring mAbs to attach the chromophores to the proteins. Another advantage is that simple genetic manipulations are all that is required in order to investigate interactions between any two proteins. However, this system has specific disadvantages as well. Possible alterations of protein structure and function may occur simply because they are fused to the CFP or YFP proteins, and overexpression of fusion proteins might disrupt normal cellular functions in unanticipated ways. Moreover, this system can only be used to examine protein–protein interactions in cells that are transfectable or otherwise permissive of genetic manipulation. Finally, use of the CFP/YFP FRET system is significantly complicated by its nonideal spectral characteristics, as described above. Both FRET assays as we used them might be criticized because they attach a fluorescent probe (and therefore assay receptor proximity) to only one subunit of the TCR. However, this criticism is ameliorated by our

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using two FRET assays that probe behavior of different TCR subunits: the PE/APC FRET assay measures CXCR4–TCR-e interactions, while the CFP/YFP FRET assay measures CXCR4–TCR-z interactions. Additional assurance that the two CXCR4-TCR FRET assays are measuring CXCR4 interactions with the whole TCR comes from the fact that the PE/APC FRET assay only labels receptors located on the cell surface. It has previously been shown that the majority of TCR on the cell-surface are holoreceptors consisting of all a, b, g, d, e, and z TCR subunits (Alarcon et al., 1988).

2. Assaying CXCR4-TCR Proximity via the PE/APC mAb FRET Approach In this approach, flow cytometry is used to detect FRET between fluorescent monoclonal antibodies bound to endogenous cell-surface CXCR4 and TCR-CD3-e. We successfully used this first FRET assay (depicted in Fig. 19.1A) to detect SDF-1–induced increases in proximity between CXCR4 and the TCR in both normal, human peripheral blood T cells isolated from peripheral blood mononuclear cell preparations (PBMC) and the Jurkat T-cell line (Kumar et al., 2006). Unless otherwise indicated, cells are stimulated at 37 C with 0.5 to 1.0 10–7 M SDF-1 (SDF-1a, R&D Systems, Minneapolis, MN). SDF-1 is resuspended at 105 M in PBS supplemented with 0.5 % bovine serum albumin (BSA), aliquoted, and stored at –70 C. Cells must be metabolically active in order to form complexes. Solutions should also be prepared using the highest-quality and purest BSA available.

2.1. Important considerations for labeling cell-surface CXCR4 and TCR Several aspects of the labeling step are critical to ensure success of the FRET assay. First, it is important to use the particular mAb clones specified. These are CXCR4 mAb conjugated to PE (Clone #44717, R&D Systems) and TCR-CD3-e mAb conjugated to APC (Clone #UCHT1, Pharmingen, San Diego, CA). Using different mAbs may not provide the appropriate orientation and/or proximity of the conjugated fluorophores to permit the detection of FRET following CXCR4-TCR complex formation. Second, to increase the ability to detect FRET, it is important to label as high a fraction as possible of the two cell-surface receptors with the fluorescently conjugated mAbs. It is particularly critical to achieve optimal labeling of the FRET donor, which in this case is CXCR4. Care must therefore be taken


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to bind the antibodies to the cell-surface receptors under conditions of considerable antibody excess and for a sufficient amount of time. For this reason, it is recommended that before attempting FRET assays, the anti– CXCR4-PE reagent be titrated for optimal labeling conditions as determined by traditional flow cytometric analysis. We have found that some lots of anti–CXCR4-PE reagent need to be used at double or more of the percell dose recommended by the manufacturer for traditional flow cytometry in order to achieve maximal labeling of CXCR4. Different lots of anti– CXCR4-PE reagent may also vary in their PE/IgG coupling ratio and thereby affect sensitivity of the FRET assay. When the cell-surface CXCR4 of Jurkat T cells is optimally labeled for FRET assay, the cells are nearly 103 times brighter in the PE/FL2 flow cytometry channel than unstained cells. The small quantities of azide used to preserve stocks of mAbs will not inhibit receptor complex formation; however, it is important to otherwise employ azide-free solutions. Finally, it is important to avoid any warming of the samples that may permit receptor internalization during the antibody labeling step and before SDF-1 treatment. Using an ice-water bath for sample incubation during these operations is therefore preferable to using ice alone.

2.2. Detailed procedure Jurkat cells are grown in Medium A (RPMI with phenol red supplemented with L-glutamine and 5 % fetal calf serum and 5 % calf serum). Cells are used for experiments when grown to a density between 0.6 106 cells/ml and 0.9 106 cells/ml. The protocol below is also appropriate for use with normal, human PBMC T cells. Purify PBMC the same day as blood draw via a standard ficoll-gradient method from blood-bank buffy coat or apheresis cone preparations. PBMC can then be used for FRET experiments following 24 h of cell culture at 37 C in Medium A. When using PBMC, flow cytometric FRET results should be gated to include only CD3þ cells in the analysis. Prepare FACS buffer without phenol red or azide (Hanks Balanced Salt Solution supplemented with 10 mg/ml BSA and 10 mM HEPES pH 7.4). Prepare Fixing Solution (PBS with 2 % paraformaldehyde). Sterilize solutions by filtering through 0.2 mm tissue-culture filters. Solutions may be stored at 4 C for several weeks. Determine the number of cell samples required for the assay. Each sample should contain 0.5 106 cells. A minimum assay will require control samples for setting flow cytometry channel voltage and compensation in addition to experimental samples plus and minus SDF-1. For example, prepare the following cell samples: (1) unstained cells, (2) cells stained with anti–CXCR4-PE only, (3) cells stained with anti–TCR-eAPC only, (4) cells stained only with any perCP-conjugated antibody that binds to the cells (for FL3 channel setup on the cytometer), and (5) cells

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stained with both anti–CXCR4-PE anti–TCR-e-APC that will be stimulated later with either vehicle or SDF-1. Wash cell samples in ice-cold FACS buffer and aliquot into 1.5-ml Eppendorf tubes on wet ice. Stain cells with the appropriate antibodies by resuspending cell pellets in the appropriate antibody or mixture of antibodies. For anti–CXCR4-PE anti–TCR-e-APC, use the optimal concentration and volumes determined by prior titration. Incubate cells on wet ice 20 to 40 min to obtain optimal labeling of cell-surface receptors. Wash cells twice with 0.2 ml ice-cold FACS buffer. To assay SDF-1–dependent FRET, stimulate the appropriate cell samples with SDF-1 (or vehicle) as follows. Immediately after staining cells with mAbs and washing, resuspend each cell pellet in 0.2 ml FACS buffer. Add an appropriate amount of SDF-1 stock solution (or vehicle) and place test tubes in a 37 C circulating water bath for exactly 20 min. Care must be taken to control the time of the stimulation 10 s since FRET signals increase with time (Kumar et al., 2006). We previously showed that 20 min of SDF-1 stimulation achieves nearly maximal FRET signals (Kumar et al., 2006). To stop the reactions, transfer each sample into a chilled test tube containing 0.2 ml ice-cold fixing solution. Place cells at 4 C for at least 1 h to fix them, then analyze by flow cytometry immediately or after further incubation at 4 C. Fixation is not required for FRET detection if cells are kept on wet ice until flow cytometric analysis, however, fixation is recommended in order to prevent temperature- and time-dependent variations in FRET signals. 2.2.1. Flow cytometer specifications For flow cytometry, we used a dual-laser (488-nm Ar and 635-nm He-Ne) FACS Caliber (Becton Dickinson, Franklin Lakes, NJ), as described (Batard et al., 2002; Kumar et al., 2006). Excitation/emission windows were 488 nm/585 21 nm (FL2), 488 nm > 670 nm (FL3), and 635 nm/661 8 nm (FL4). The optimal voltage settings for each channel are determined as in conventional flow cytometry, that is, so that the unstained cell peak is completely on-scale. Compensation is similarly determined as in conventional flow cytometry, except that greater care should be taken to avoid over- or under-compensation of all channels. Saved instrument settings on the instrument specified above are usually approximately correct from day to day, although compensation may require fine daily adjustment.

2.3. Examples and results Figures 19.3 through 19.5 show examples of using the ‘‘mAb FRET’’ approach to analyze the SDF-1–dependent formation of CXCR4-TCR complexes. CXCR4 and TCR-CD3-e of Jurkat T cells were labeled as

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Figure 19.3 Using mAb FRET and flow cytometry to assay SDF-1^dependent CXCR4-TCR complex formation: typical responses of Jurkat Tcells and control data. (A) Results from an individual experiment performed as described in Fig. 19.1A and the text. Both CXCR4-PE and TCR-e-APC mAb were bound to the CXCR4 and TCR molecules of Jurkat T cells, and then cells were stimulated with either SDF-1 or vehicle at 37 C for 10 min. The data show that SDF-1, but not vehicle, treatment induced an increase in per-cell CXCR4-PE^TCR-e-APC FRET fluorescence (detected using the FL3 channel of the flow cytometer). (B) Control samples in which cells were analyzed as in (A) after being bound to either CD3-e-APC or CXCR4-PE alone. These control cells do not display FL3 fluorescence at the level of that induced by SDF-1 on the dually labeled cells shown in Fig. 19.3A. (C) Control sample in which cells were analyzed as in (A) after being bound to anti^CD45-APC instead of anti^ TCR-e-APC. Cells were also stained with anti^CXCR4-PE. No increase in FL3/ FRET fluorescence was detected in response to SDF-1. (From Kumar, A., Humphreys,T. D., Kremer, K. N., Bramati, P. S., Bradfield, L., Edgar, C. E., and Hedin, K. E. (2006). CXCR4 physically associates with the T cell receptor to signal in T cells. Immunity 25, 213^224, with permission.)

above with receptor-specific mAbs conjugated to PE or APC, respectively. After stimulation with SDF-1, cellular fluorescence changes associated with FRET were analyzed by flow cytometry. 2.3.1. Jurkat results and controls Figure 19.3A shows typical results for Jurkat T cells and recommended controls. SDF-1 treatment increased per-cell FRET fluorescence, which is reflected by the increase in FL3 channel fluorescence. The CXCR4-TCR

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Figure 19.4 SDF-1^dependent CXCR4-TCR complex formation requires expression of theTCR.Wildtype JurkatTcells, or a somatic mutant of Jurkat deficient in expression of TCRb and consequently deficient in cell-surface TCR expression (Batard et al., 2002), were assayed for SDF-1^dependent CXCR4-TCR complex formation by the ‘‘mAb FRET’’approach described in Fig. 19.1A, Fig. 19.3, and the text. (A) Histograms showing examples of individual experiments. (B) Bar graph showing a summary of multiple experiments as in (A). Each bar denotes the mean SDF-1^dependent FRET response standard error of the mean (SEM) for three independent experiments; results are shown as a percent of the responses of control (i.e., wildtype Jurkat) cells analyzed the same day). * Significantly different from control responses ( p < 0.05).

FL3/FRET response was specific for SDF-1, since no CXCR4-TCR FRET signals were induced when cells were stimulated with vehicle alone (Fig. 19.3A). The levels of FL3 fluorescence associated with FRET were not seen using cells labeled with either PE or APC alone (Fig. 19.3B). The controls shown in Fig. 19.3A and B should be performed in every experiment to provide assurance of proper cytometer setup. An additional control is shown in Fig. 19.3C. No FL3/FRET signals were detected when a similar approach was used to assay the proximity of CXCR4 to another abundantly expressed cell-surface receptor, CD45. The results of this control experiment indicate that the flexibility and length of the mAbs used to link the fluorophore to the receptors are not, in themselves, sufficient to permit promiscuous FRET between any pair of cell-surface receptors. Figure 19.4 shows an additional control. No FL3/FRET signals were detected using a somatic mutant of the Jurkat T-cell line that is deficient in TCRb expression and consequently also

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Figure 19.5 Methyl-b-cyclodextrin (MCD) inhibits the ability of SDF-1 to induce CXCR4-TCR FRET, suggesting that this process requires cholesterol and/or membrane fluidity.Wildtype JurkatTcells were pretreated for 20 min with 25 mM of the cholesterol chelator, methyl-b-cyclodextrin, or an equivalent amount of vehicle (RPMI). SDF-1^dependent CXCR4-TCR complex formation was then assayed by the ‘‘mAb FRET’’approach described in Fig. 19.1A, Fig. 19.3, and the text. (A) Histograms showing examples of individual experiments. (B) Bar graph showing a summary of multiple experiments as in (A). Each bar denotes the mean SDF-1^dependent FRET response standard error of the mean (SEM) for three independent experiments; results are shown as a percent of the responses of control cells pretreated with vehicle alone and analyzed the same day. * Significantly different from control responses ( p < 0.05).

deficient in cell-surface TCR expression (Kumar et al., 2006), providing assurance that a positive readout in this assay requires expression of the TCR. Several additional controls useful for confirming the authenticity of results obtained from using this ‘‘mAb FRET’’ assay are described in our published paper (Kumar et al., 2006). First, we showed that in addition to cells from the Jurkat cell line, normal, human PBMC T cells display SDF1–dependent CXCR4-TCR FRET responses. Second, we showed that the SDF-1–induced CXCR4-TCR FRET signals gradually increase with time after SDF-1 addition and plateau after approximately 20 min. Third, we showed that SDF-1–induced CXCR4-TCR FRET signals are appropriately inhibited by increasing doses of a CXCR4 antagonist. Finally, we showed that SDF-1–induced CXCR4-TCR FRET signals display a dose– response relationship consistent with SDF-1 acting by binding to CXCR4 (Kumar et al., 2006). Together, the results in Figs. 19.3 and 19.4 and additional controls described here indicate that SDF-1 stimulation causes CXCR4 and the TCR to move into close, physical proximity in both the Jurkat T-cell line and normal human T cells.

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2.3.2. Effects of methyl-b-cyclodextrin Here, we use this PE/APC mAb FRET assay to further characterize SDF1–dependent CXCR4-TCR complex formation of T cells. Jurkat T cells were pretreated with either the cholesterol chelation agent, methyl-bcyclodextrin (MCD), or vehicle. Cell-surface CXCR4 and TCR-CD3-e molecules were then stained with CXCR4-PE and TCR-CD3-e-APC mAbs, and SDF-1–dependent CXCR4-TCR complex formation was detected via FRET assay as in Fig. 19.1A. Figure 19.5 shows that MCD pretreatment abrogated the SDF-1–dependent FRET signals of the cells, suggesting that SDF-1–dependent CXCR4-TCR complex formation occurs via a process that requires cholesterol and/or membrane fluidity.

3. Assaying CXCR4-TCR Proximity via the CFP/YFP Fusion Protein Approach We also used a second FRET approach (Fig. 19.1B) to assay SDF-1– induced increases in the proximity between CXCR4-YFP and TCR-zCFP in the Jurkat T-cell line (Kumar et al., 2006).

3.1. Transient transfection of fusion proteins into Jurkat T cells 3.1.1. Plasmids and controls To express CXCR4 and TCR-CD3-z fluorescent fusion proteins in the Jurkat T-cell line, we employed transient transfection of expression plasmids encoding these proteins as fluorescent fusion proteins with YFP and CFP. We amplified cDNA encoding human CXCR4 and TCR-CD3-z via PCR and subcloned them into pEYFP-N1 and pECFP-N1, respectively (Clontech, Mountain View, CA). (The construction of these plasmids is described in Kumar et al., 2006.) It is important to initially prepare not only cell samples dually transiently transfected with both YFP and CFP fusion protein-encoding plasmids, but also control cell samples transiently transfected with either the YFP or CFP fusion protein-encoding plasmids individually. These first types of control samples are important in order to delineate the shape and intensity of the individual YFP or CFP fluorescence emission profiles under the detection conditions used and with the instrument employed. A second type of control is essential to include in each experiment: a cell sample transfected only with pcDNA3 (Invitrogen, Carlsbad, CA) or a similar ‘‘empty’’ vector. This control is required for background subtraction of fluorescence produced by the cells and media. To account for effects of transfection-related cell death on the fluorescence of the sample, it is important that the total amount of DNA used for all


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transfections in a given experiment be kept constant for all samples and controls. This can be achieved by adding to each transfection an amount of an ‘‘empty’’ vector such as pcDNA3 so as to make the total amount of plasmid DNA in each transfection equivalent. 3.1.2. Preliminary experiments to determine optimal conditions Optimal FRET between interacting fluorescent fusion proteins would ideally be achieved under conditions of high, but molar equivalent, expression of two interacting fluorescent fusion proteins. If either the donor or acceptor fusion protein is grossly overexpressed relative to the other, the FRET signal may be too weak to detect. On the other hand, depending on the cell type used and the proteins being expressed, too high a level of expression of one or both fusion proteins may be toxic to the cells. Thus, before beginning FRET experiments, it is recommended that test transfections be performed in which the amounts of the fusion protein-expressing plasmids are titrated. Such test transfections are also useful for optimizing transfection efficiency. Flow cytometry of the test transfections, and also of later experimental transfections, is useful for confirming appropriate levels of protein expression, transfection efficiency, and cell viability. Figure 19.6B shows an example. For this purpose, we use a Becton-Dickinson (Franklin Lakes, NJ) LSRII special order flow cytometer with five lasers. For CFP detection, excitation is achieved via the 407-nm laser and 505- to 520-nm emitted light is detected via a combination of a 505-nm, long-pass filter followed by a 500/40-nm bandpass filter. For YFP detection, the cells are excited with the 488-nm laser and 515- to 545-nm emitted light is detected via a combination of a 505-nm, long-pass filter followed by a 530/30-nm band-pass filter. In our hands, transiently transfecting 107 Jurkat T cells with 10 mg each of CXCR4-YFP and TCR-z-CFP–expressing plasmids yields the optimal detection of SDF-1–induced FRET signals. FRET signals were detected with dual plasmid transient transfection efficiencies of 20 to 40% (Fig. 19.6B). 3.1.3. Detailed protocol for transient transfection For analysis of complex formation between CXCR4-YFP and TCR-zCFP, Jurkat cells are grown in Medium A (RPMI without phenol red but supplemented with L-glutamine and 10% fetal calf serum) and are used for transient transfection when grown to a density between 0.6 106 cells/ml and 0.9 106 cells/ml. Jurkat cells grown to a density of greater than 106 cells/ml are only poorly transfectable by electroporation. Four cell samples are prepared for each experiment. For each sample, 107 cells in a volume of 350 ml of Medium A are mixed with plasmid DNA as follows: Sample 1, pcDNA3 (‘‘empty’’ vector, 20 mg); Sample 2, CXCR4-YFP (10 mg) and

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pcDNA3 (10 mg); Sample 3, TCR-z-CFP (10 mg) and pcDNA3 (10 mg); and Sample 4, CXCR4-YFP (10 mg) and TCR-z-CFP (10 mg). Each cell sample is then transferred to a 4-mm gap BTX electroporation cuvette and subjected to one 315-V pulse for 10 ms using a BTX T820 square-wave electroporator (BTX, Holliston, MA). The cells from each transfection are then diluted in 5 ml Medium A and cultured for 24 to 28 h.

3.2. Assaying CXCR4-YFP and TCR-z-CFP proximity by FRET 3.2.1. Preparation of transfected cell samples The length of the time between cell transfection and FRET analysis critically affects the levels of fusion protein expression and therefore the experimental outcome. In our hands, and using the conditions and amounts of the fusion protein-encoding plasmids described here, CXCR4-YFP–TCR-zCFP FRET is best detected following 24 to 28 h of culture. It is recommended that other laboratories determine the optimal post-transfection culture time (which may vary between 18 and 36 h) for their experiments. After the transfected cells are given the appropriate time in culture to


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express the fusion proteins, the cells are resuspended to a density of 1 to 2 106–cells/ml in Medium B (Hanks Balanced Salt Solution supplemented with 5% fetal calf serum and 5 mM HEPES, pH 7.4) and cultured at 37 C with 5% CO2 until FRET analysis. RPMI-based medium cannot be used at this point due to its high background fluorescence under the conditions used. 3.2.2. Collection of fluorescent spectra To detect CXCR4-YFP–TCR-z-CFP FRET, we used a Horiba Jobin Yvon (Edison, NJ) SPEX Fluorolog-3 spectrofluorimeter with 433-nm light for excitation. The emission spectra were collected at 1 nm/s from 460 nm to 580 nm. The sample was maintained at 37 C and stirred constantly using a heated cuvette and a magnetic stir bar, respectively, during all spectral assays and also throughout the entire time of the SDF-1 stimulation. SDF-1 treatment was performed while cells remained in the cuvette and the same samples were assayed to obtain spectra both before and after SDF-1 treatment. Spectral data was collected both before and after SDF-1 treatment for all four experimental cell samples (including all control cell samples). We previously determined that CXCR4-TCR complex formation detectable by the antibody FRET method increases during 20 min of SDF-1 treatment at 37 C and plateaus after 20 min (Kumar et al., 2006); therefore, we assayed for CXCR4-YFP–TCR-z-CFP FRET by the spectrofluorimetric method after 20 min of SDF-1 treatment. 3.2.3. Analysis and interpretation of fluorescent emission spectra Once the emission spectra have been gathered, it is necessary to subtract from the sample spectrum the background fluorescence emission produced by the media and cells. This subtraction also accounts for any changes in cell shape or size that might affect the spectra. To do this, cells transfected only with a plasmid vector such as pcDNA3 were analyzed for fluorescence emission before and after SDF-1 treatment. The unstimulated pcDNA3 control spectrum was then subtracted from the unstimulated experimental sample spectrum. Likewise, the SDF-1–stimulated pcDNA3 control spectrum was subtracted from the SDF-1–stimulated experimental sample spectrum. The spectra of the background-subtracted experimental samples before and after SDF-1 stimulation were then overlayed and offset in order to detect FRET. To unambiguously identify FRET signals using CFP and YFP, the enhanced emission signal of the YFP acceptor should occur together with a concomitant decrease in the CFP donor’s emission signal. As discussed in the introduction, comparing the spectra at these two wavelengths and assaying reciprocal changes in emission intensity is particularly important when using the CFP/YFP fluorophore pair to investigate FRET.

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3.3. Example Figure 19.6A shows data from a typical experiment. The grey line denotes the background-subtracted fluorescence emission spectrum of Jurkat T cells expressing both CXCR4-YFP and TCR-z-CFP before these cells have been treated with SDF-1. The background-subtracted spectrum shows a CFP emission peak centered at 475 nm and a smaller YFP emission peak centered at 528 nm. The black line denotes the background-subtracted fluorescence emission spectrum of the same cell sample following its stimulation with 5 10–8 M SDF-1 for 20 min and analyzed again. Comparison of the two spectra indicates relative changes consistent with CXCR4-YFP– TCR-z-CFP FRET signals increasing following SDF-1 treatment—a decrease in the CFP emission peak because it is donating energy to YFP, and a consequent increase in the YFP emission peak.

4. Concluding Remarks FRET experiments provide us with valuable insights into molecular dynamics and can frequently be designed to examine dynamics within living cellular systems. Combining different types of approaches, including FRET assays that employ various chromophores and that tag proteins of interest in different ways, is the most reliable way to obtain conclusions about molecular interactions in the living cell. The addition of biochemical approaches, such as copurification of proteins, can also be useful for confirming the presence of protein–protein complexes detected by FRET, and for examining the physiological significance of the interactions.

REFERENCES Alarcon, B., Berkhout, B., Breitmeyer, J., and Terhorst, C. (1988). Assembly of the human T cell receptor-CD3 complex takes place in the endoplasmic reticulum and involves intermediary complexes between the CD3-g, d, e core and single T cell receptor a or b chains. J. Biol. Chem. 263, 2953–2961. Batard, P., Szollosi, J., Luescher, I., Cerottini, J.-C., MacDonald, R., and Romero, P. (2002). The use of phycoerythrin and allophycocyanin for fluorescence resonance energy transfer analyzed by flow cytometry: Advantages and limitations. Cytometry 48, 97–105. Chan, F. K.-M., Sigel, R. M., Zacharias, D., Swofford, R., Holmes, K. L., and Tsien, R. Y. (2001). Fluorescence resonance energy transfer analysis of cell surface receptor interactions and signaling using spectral variants of the green fluorescent protein. Cytometry 44, 361–368. Ciruela, F. (2008). Fluorescence-based methods in the study of protein–protein interactions in living cells. Curr. Opin. Biotechnol. 19, 1–6. Forster, T. (1948). Zwischenmolekulare energiewanderung and fluoreszenz. Ann. Physik. 2, 55–75.


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Forster, T. (1965). Delocalized excitation and excitation transfer. In ‘‘Modern Quantum Chemistry Part III: Action of Light and Organic Crystals.’’ (O. Sinanoglu, ed.), pp. 92–137. Academic Press, New York. Glazer, A. N., Chan, C., Williams, R. C., Yeh, S. W., and Clark, J. H. (1985). Kinetics of energy flow in the phycobilisome core. Science 230, 1051–1053. He, L., Bradrick, T. D., Karpova, T. S., Wu, X., Fox, M. H., Fischer, R., McNally, J. G., Knutson, J. R., Grammer, A. C., and Lipsky, P. E. (2003a). Flow cytometric measurement of fluorescence (Forster) resonance energy transfer from cyan fluorescent protein to yellow fluorescent protein using single-laser excitation at 458 nm. Cytometry 53A, 39–54. He, L., Olson, D. P., Wu, X., Karpova, T. S., McNally, J. G., and Lipsky, P. E. (2003b). A flow cytometric method to detect protein–protein interaction in living cells by directly visualizing donor fluorophore quenching during CFP-YFP fluorescence resonance energy transfer (FRET). Cytometry 55A, 71–85. He, L., Wu, X., Simone, J., Hewgill, D., and Lipsky, P. E. (2005). Determination of tumor necrosis factor receptor-associated factor trimerization in living cells by CFP–YFP– mRFP FRET detected by flow cytometry. Nuc. Acids Res. 33, e61. Janetopoulos, C., Jin, T., and Devreotes, P. (2001). Receptor-mediated activation of heterotrimeric G proteins in living cells. Science 291, 2408–2411. Jares-Erijman, E., and Jovrin, T. M. (2003). FRET imaging. Nat. Biotechnol. 21, 1387–1395. Kumar, A., Humphreys, T. D., Kremer, K. N., Bramati, P. S., Bradfield, L., Edgar, C. E., and Hedin, K. E. (2006). CXCR4 physically associates with the T cell receptor to signal in T cells. Immunity 25, 213–224. Lakowicz, J. R. (1999). Principles of fluorescence spectroscopic ruler. Annu. Rev. Biochem. 47, 819–846. Shaner, N. C., Patterson, G. H., and Davidson, M. W. (2007). Advances in fluorescent protein technology. J. Cell Sci. 120, 4247–4260. Shaner, N. C., Steinbach, P. A., and Tsien, R. Y. (2005). A guide to choosing fluorescent proteins. Nat. Methods 2, 905–909. Stryer, L. (1967). Energy transfer: A spectroscopic ruler. Proc. Natl. Acad. Sci. USA 58, 719–726. Stryer, L. (1978). Fluorescence energy transfer as a spectroscopic ruler. Annu. Rev. Biochem. 47, 819–846. Tertoolen, L. G. J., Blanchetot, C., Jiang, G., Overvoorde, J., Gadella, T. W. J. Jr., Hunter, T., and den Hertog, J. (2001). Dimerization of receptor protein-tyrosine phosphatase alpha in living cells. BMC Cell Biol. 2, 8. Tsien, R. Y. (1998). The green fluorescent protein. Annu. Rev. Biochem. 67, 509–544. Vamosi, G., Samjanovich, S., and Szollosi, J. (2008). Dissecting interacting molecular populations by FRET. Cytometry 73A, 681–684. Vilardaga, J. P., and Nikolaev, O. (2007). Monitoring receptor signaling by intramolecular FRET. Curr. Opin. Pharmacol. 7, 547–553. Viskari, P. J., and Colyer, C. L. (2001). Separation and quantitation of phycobiliproteins using phytic acid in capillary electrophoresis with laser-induced fluorescence detection. J. Chromatography 972, 269–276. Xia, Z., and Liu, Y. (2001). Reliable and global measurement of fluorescence resonance energy transfer using fluorescence microscopes. Biophys. J. 81, 2395–2402.

C H A P T E R

T W E N T Y

Expression of CXCR4, a G-Protein– Coupled Receptor for CXCL12 in Yeast: Identification of New-Generation Inverse Agonists Barry J. Evans,* Zixuan Wang,*,§ James R. Broach,† Shinya Oishi,‡ Nobutaka Fujii,‡ and Stephen C. Peiper* Contents 400 402 402 403 404 408 410

1. Introduction 2. Methods and Discussion 2.1. Overview of yeast-signaling strategies 2.2. Experimental approach 2.3. Characterization of inverse agonists for CXCR4 3. Summary References

Abstract G-protein–coupled receptors (GPCR) are prime targets for therapies with small molecule-antagonists. Since yeast have GPCR triggered signaling pathways analogous to those present in mammalian cells, it is possible to express human receptors in yeast coupled to the pheromone responsive signaling cascade in variants that contain mammalian-yeast Ga subunit chimeras. CXCR4 and CXCR4(N119S), a constitutively active mutant were expressed in yeast coupled to pheromone responsive reporter genes, HIS3, lacZ, or FUI, and tested for signaling activity. Compounds derived from T140, an inverse agonist for CXCR4, were screened for activity using yeast cells expressing CXCR4 (N119S) and containing a FUS1-lacZ reporter gene. Levels of inhibition of beta-galactosidase activities triggered by constitutive activation of the pheromone response pathway that were obtained in the presence of the T140 derived

* { {

}

Department of Pathology, Anatomy and Cell Biology, Thomas Jefferson University, Philadelphia, Pennsylvania, USA Department of Molecular Biology, Princeton University, Princeton, New Jersey, USA Department of Chemogenomics, Graduate School of Pharmaceutical Sciences, Kyoto University, Sakyo-ku, Kyoto, Japan Department of Surgery, Thomas Jefferson University, Philadelphia, Pennsylvania, USA


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compounds correlated with affinities measured in radioligand binding inhibition experiments. The yeast signaling system may provide an effective approach for screening chemokine receptor antagonists.

1. Introduction G-protein–coupled receptors (GPCR) are encoded by a superfamily of genes that constitute approximately 1 to 2% of the human genome (Fredriksson and Schioth, 2005). It is one of the largest gene families in mammals and there is a high degree of diversity among the receptors encoded. GPCRs are present in virtually all eukaryotic cells and have a broad repertoire of ligands that include light, lipids, nucleotides, polypeptides, and proteins. The unifying topologic characteristic of GPCRs is the presence of seven hydrophobic helices that span the plasma membrane, resulting in exposure of the N-terminus and three interhelical loops to the extracellular space and orientation of the C-terminus and three interhelical loops into the cytoplasm. Signaling is mediated by coupling to heterotrimeric G proteins. GPCRs are highly accessible molecular targets for drug therapy and current estimates are that 30 to 50% of drugs are directed toward these receptors (Hopkins and Groom, 2002). Many strategies for the development of therapeutic agents use structural information to generate lead compounds, so-called rational drug design. The high-resolution structure has been determined for only two GPCRs (Palczewski et al., 2000; Rosenbaum et al., 2007), which restricts the application of this approach. In addition, the diversity among GPCRs and the integral membrane topology has limited and complicated the use of computational modeling strategies to approximate structural architecture for virtual drug design. This highlights the need for efficient screening technologies to identify lead compounds for therapeutic applications. The receptors for chemoattractant cytokines, chemokines, are GPCRs in the rhodopsin subfamily. These receptors number approximately 19, 10 for CC chemokines, 7 for CXC chemokines, 1 for C chemokines, 1 for the CX3C chemokine, and 2 nonsignaling binding heptahelical proteins (Murphy et al., 2000). There is significant redundancy in the repertoire of chemokine- and receptor-binding activities, but several chemokine– receptor pairs are exclusive. Stromal cell–derived factor 1 (SDF-1, CXCL12) is the sole ligand for CXCR4 (Bleul et al., 1996; Oberlin et al., 1996). Studies with knockout mice demonstrated that both the ligand and receptor are critical for development of the central nervous system, the cardiovascular system, and bone marrow hematopoiesis during embryologic development (Nagasawa et al., 1996; Tachibana et al., 1998; Zou et al., 1998).

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This axis is also involved in the development of B lymphocytes and the chemotaxis of lymphocytes (both T cells and B cells), granulocytes, and other inflammatory cells in response to a CXCL12 gradient. CXCR4 is expressed on primordial germ cells (Doitsidou et al., 2002) and human hematopoietic stem cells (Deichmann et al., 1997; Mo¨hle et al., 1998). Recently, a CXCR4 inhibitor of the weak partial agonist type was approved for mobilization of hematopoietic stem cells in humans. In addition to its critical role in normal physiology, CXCR4 has prominent roles in pathologic physiology. CXCR4 was the first coreceptor identified that is permissive for entry of T-cell tropic strains of the human immunodeficiency virus type 1 (HIV-1) into human target cells that coexpress CD4 (Feng et al., 1996), leading to the designation X4 for these strains. The recognition that a then-orphan GPCR closely genetically related to chemokine receptors led to the rapid identification of CCR5, the front-line coreceptor for commonly transmitted strains of HIV-1 (R5) (Deng et al., 1996; Dragic et al., 1996). Rare patients who lack functional CCR5, and are highly resistant to infection with R5 strains, may be infected with X4 strains and those treated with CCR5 antagonists may undergo a shift in tropism from R5 to X4. CXCR4, which is expressed by tumor cells of many types of malignancies, has also been shown to play a critical role in their metastasis to lung and lymph nodes, which secrete (a chemotactic gradient of ) CXCL12, and inhibition of CXCR4 blocked the spread of tumor cells (Muller et al., 2001). The finding that metastatic variants derived by biological selection from nonmetastatic cell lines have upregulation of a cadre of genes that includes CXCR4 implicates it in the migration/homing mechanisms of metastasis (Kang et al., 2003). Moreover, the formation of a niche of carcinoma-associated fibroblasts that supports tumor cells involves the CXCL12–CXCR4 axis. Thus, CXCR4 provides an opportunity as a potential molecular target in HIV-1 infection and numerous malignancies in addition to the approved role in mobilization of hematopoietic stem cells. The first CXCR4 antagonist, AMD3100, was identified through binding screens and biological assays, which have some drawbacks for high-throughput analysis. Since GPCRs play a critical role in pheromone and nutrient sensing in yeast through the MAP kinase pathway, it was possible to genetically engineer yeast strains for screening mammalian GPCRs. We have previously developed a yeast system in which human CXCR4 is functionally coupled to the pheromone response pathway for the evaluation of candidates for their inverse agonist or weak partial agonist activity for this GPCR using a reporter gene driven by a pheromoneresponsive promoter. Here we describe three yeast systems and examples of their utilization for characterizing a group of compounds derived from T140, a polypeptide CXCR4-inverse agonist.

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2. Methods and Discussion 2.1. Overview of yeast-signaling strategies Saccharomyces cerevisiae have two genes encoding GPCRs that transduce the signal of mating pheromones (STE2 and STE3) (Xue et al., 2008). The downstream pheromone-response signaling pathway initiates with activation of a G-alpha subunit (Gpa1) and is dependent on release of the Gb/Gg heterodimer (Ste4/Ste18). The liberated Ste4/Ste18 complex binds three downstream targets: Ste5, a scaffold protein; Ste20, PAK kinase; and the MAPK phospho-circuit (Ste11, Ste7, and Fus3). Upon phosphorylation, Fus3 liberates Ste12, a transcription factor, from the inhibitory complex Dig1/Dig2, thereby inducing the expression of pheromone-responsive mating genes. Transcription of the FUS1 gene is dependent on multiple members of the pheromone response–signaling pathway (Ste4, Ste4, Ste7, Ste11, and Ste12), and the upstream promoter region of FUS1 was found to have four copies of the canonical pheromone response element (Hagen et al., 1991). The pheromone response pathway provides a template for genetic engineering of a ‘‘customized’’ signaling system that can be used to characterize and select signaling variants of mammalian GPCRs, as well as an approach for screening of pharmacologic agents for these targets. We have previously described the expression of wildtype human CXCR4 linked to the pheromone response pathway in Saccharomyces cerevisiae (Zhang et al., 2002, 2004). This required the development of a yeast strain (CY12946) that contained a chimeric Ga subunit composed of segments that couple to mammalian GPCRs and yeast segments that interact with the Gb/Gg subunits that regulate the pheromone response signaling cascade. Since activation of this pathway results in cell cycle arrest, mutations in negative regulators were introduced into this yeast strain. Sequences encoding human CXCR4 (and variants) were introduced into this strain using the Cp4258 plasmid containing a selectable marker for leucine synthesis. Reporter genes lacZ and HIS3 were placed downstream of the FUS1 promoter, which is turned on following activation of this pathway. The FUS1-HIS3 reporter gene was used for growth survival experiments in yeast that are histidine auxotrophs, because HIS3 can complement this phenotype. Thus, with activation of the pheromone response pathway, yeast cells that cannot grow in medium lacking histidine are converted to histidine prototrophs that produce histidine and can grow in the absence of supplementation of the medium. This provides a growth selection strategy mechanism in which histidine-deficient cells can survive in the absence of this amino acid when there is activation of the pheromone response pathway and expression of HIS3. While the FUS1HIS3 system is ideally suited for the selection of signaling variants that confer yeast survival in selective medium, it lacks the sensitivity required for screening

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for antagonists. Therefore, the FUS1-lacZ reporter gene was used for screening experiments because it programs the expression of beta-galactosidase, which can be detected with sensitive assays with a fluorescent substrate (fluorescein di-b-D-galactopyranoside [FDG]).

2.2. Experimental approach We first used the FUS1-HIS3 reporter gene system to express human CXCR4 in Saccharomyces cerevisiae functionally coupled to the pheromone response pathway. Exposure of these yeast strains to CXCL12 induced expression of HIS3 and survival in medium lacking histidine. We were able to adapt this system to select constitutively active CXCR4 mutants. This signaling variant was isolated from a pool of CXCR4 open reading frames randomly mutated at a frequency of 0.1% to 0.3%. The open reading frames were cloned into the Cp4258 vector and introduced into yeast cells. Selection of the pool of yeast cell transformants yielded rare colonies, which contained CXCR4 that carried a mutation of Asn-119 to Ser. Further characterization of this mutant revealed that it conferred constitutive signaling in yeast and mammalian cells. In the current experiments, the Cp4258 vector was used to introduce wildtype CXCR4 or the constitutively active mutant, CXCR4(N119S), into the engineered CY12946 yeast cell strain. In addition, the FUS1-lacZ reporter gene (Cp1584) was also introduced into the yeast cells used for screening assays. Constructs were cotransformed into yeast cells using the Frozen EZ Yeast Transformation-II kit (Zymo Research, Orange, CA). Yeast cells incorporating and expressing both of these plasmids were selected for expression of the selectable marker by growth in medium lacking leucine (selection for Cp4258) and tryptophan (selection for Cp1584), respectively. These yeast cells were used for growth screens and reporter gene assays to evaluate the compounds for activity as a weak partial agonist based on the ability to stimulate either the wildtype receptor or the constitutively active mutant, a more sensitive indicator, and as an inverse agonist that suppresses the autonomous signaling of the constitutively active mutant. A third yeast-based signaling system was also tested for its utility as a screen for inhibitors using the constitutively active mutant to identify inverse agonists and, theoretically wildtype CXCR4 and CXCL12 to detect neutral antagonists and weak partial agonists. This system uses the induction of a reporter gene (FUI ) ( Jund and Lacroute, 1970) that is a permease for 5-fluoropyrimidines. In this case, CXCR4-mediated activation of the pheromone response cascade upregulates permease expression and sensitivity to 5-fluorouridine (5-FU) toxicity. Inhibition of CXCR4 signaling would suppress permease expression and block the toxicity from 5-FU. In practice, this system could be employed for inverse agonist screens with the constitutively active CXCR4 mutant, but not for neutral antagonists

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and weak partial agonists due to the prohibitive cost of the ligand that would be required to activate CXCR4. Sequences encoding the FUI transporter downstream of a FUS1 promoter were incorporated into the genome of CY12946 yeast cells at the URA3 locus by homologous recombination with the pAA7 vector using the transformation procedure described above. The assay for detection of the HIS3 reporter gene was performed as previously described (Ahang et al., 2002, 2004). Briefly, CY12946 yeast cells were grown in broth lacking leucine and histidine in 96-well plates. Growth as measured using absorbance at 600 nm was determined at sequential intervals to determine the level of expression of the pheromone responsive HIS3 reporter gene. Screening assays were performed using the FUS1-lacZ reporter gene. Yeast cells transformed with this construct were grown overnight in medium lacking leucine and tryptophan and then diluted to an absorbance at 600 nm of 0.1. The yeast was then grown in 96-well plates in the same broth in the presence or absence of candidate compounds until the absorbance at 600 nm reached 0.5. Aliquots of the yeast cell culture (10 ml) were solubilized, incubated in the presence of the fluorescent substrate (FDG) for 45 min at 37 C, and analyzed for fluorescence in a FUSION (Packard). The 5-fluorouridine assay was performed using cells expressing native CXCR4 or the N119S constitutively active mutant. CY12946 cells containing the FUS1-FUI reporter gene were grown overnight in the presence or absence of the candidate antagonist and 5-FU in broth lacking leucine and uracil (as selective pressure for maintenance of the plasmids). Growth was determined from the absorbance at 600 nm. This system is also a growth assay in which inhibition of CXCR4 signaling results in decreased permease expression and decreased sensitivity to 5-FU.

2.3. Characterization of inverse agonists for CXCR4 Analysis of CY12946-CXCR4 cells in the growth assay is shown in Fig. 20.1A. Expression of CXCR4 in CY12946 cells did not induce the pheromone responsive HIS3 gene, thus, there was no growth in histidinefree medium. In contrast, expression of CXCR4(N119S) in CY12946 cells stimulated autonomous activation of the pheromone response pathway and expression of the FUS1-HIS3 reporter gene resulting in growth in histidine-free medium. Exposure of CY12946-CXCR4(N119S) cells to 1 mM FC131 resulted in low-level inhibition of CXCR4(N119S) constitutive activity (data not shown), but the relative effect was less than was observed in the FUS1-lacZ reporter gene system, as shown below. As shown with the FUS1-lacZ reporter assay in Fig. 20.1B, there is a low level of basal beta-galactosidase activity detected in CY12946-CXCR4 cells that is not significantly different from that seen with parental CY12946 cells (data not shown). The level of enzymatic activity is not altered by FC131, which suggests that it reflects the true background of the system.

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The beta-galactosidase activity is elevated by approximately fivefold in CY12946-CXCR4(N119S) cells in this experiment, consistent with the constitutive signaling activity of this CXCR4 variant (ratios of activated to background may vary significantly depending on subtle variations in experimental conditions). Exposure of CY12946-CXCR4(N119S) cells to FC131, a second generation cyclic pentapeptide with inverse agonist activity, resulted in 60% inhibition of FUS1-lacZ reporter gene expression. The yeast FUS1-FUI permease reporter gene system was compared to the FUS1-lacZ strategy. Exposure of CY12946-CXCR4 cells to increasing amounts of 5-FU revealed a moderate decrease in cell density evident from the absorbance at 600 nm (Fig. 20.1C). Parallel exposure of CY12946CXCR4(N119S) cells to the incremental concentrations of 5-FU resulted in decreased cell density, consistent with increased transport of this toxic agent resulting from signaling by the constitutively active mutant. Whereas exposure of the constitutively active variant of CXCR4 to FC131 resulted in significant suppression of signaling in the FUS1-lacZ reporter system, this effect could not be detected in the pheromone-responsive permease system (data not shown). The basal activity of native CXCR4 (in the absence of CXCL12) was not sufficient to activate FUS1-lacZ reporter gene expression in CY12946 cells. As shown in Fig. 20.2A, exposure of CY12946-CXCR4 cells to incremental concentrations of CXCL12 resulted in activation of the reporter gene in a dose-responsive fashion. Low levels of beta-galactosidase activity were detected in cells exposed to 1 mM CXCL12, and the EC50 was approximately 3 to 5 mM. The CXCR4 response to CXCL12 in yeast cells occurs at ligand concentrations approximately three orders of magnitude higher than is seen in mammalian systems using ligand binding, calcium mobilization, or other assays, such as activation of MAP kinase signaling and chemotaxis. This may be due to the presence of a cell wall in yeast that could interfere with the binding of CXCL12 to CXCR4. This effect was not apparent at the same degree with the antagonists tested, perhaps because they are smaller than CXCL12. Alternatively, since yeast lack tyrosine sulfation, the absence of sulfation of tyrosine residues in the N-terminus of CXCR4 could be responsible for the decreased ligand binding, as has been demonstrated in mammalian systems. The requirement for high concentrations of CXCL12 for activation of signaling in CY12946-CXCR4 cells makes this approach impractical for the screening of compounds. In addition, this system cannot distinguish between the pharmacologic types of inhibitors: neutral antagonists, weak partial agonists, and inverse agonists. In contrast, the fluorescent assay for the FUS1-lacZ reporter gene using CY12946-CXCR4(N119S) cells was sensitive for the detection of the inverse agonist activity of T140 and FC131, as well as the weak partial agonist activity of AMD3100 (Fig. 20.2B). Exposure to T140, a 14–amino acid polypeptide containing an internal disulfide bond, decreased the

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Figure 20.2 Fluorescent screening assay in yeast containing the FUS1-lacZ reporter gene. (A) b-galactosidase activity of yeast expressing human CXCR4 exposed to incremental concentrations of CXCL12. (B) b-galactosidase activity of yeast expressing the CXCR4 constitutively active mutant exposed to incremental concentrations of T140, FC131, or AMD3100.

signaling of the constitutively active receptor mutant. Beta-galactosidase activity was decreased in CY12946-CXCR4(N119S) cultures exposed to 31.6 nM T140 and reached maximal inhibition at 316 nM. Exposure to 10 nM FC131, a cyclic pentapeptide downsized from the T140 template, induced slight inhibition of beta-galactosidase activity and complete inhibition was detected at concentrations of 1.0 mM. While the inhibition of [125I] CXCL12 binding to CXCR4 (in mammalian cells) by T140 and FC131 gave similar IC50 values (2 to 10 nM ) and they block HIV-1 infection of CD4 positive target cells at similar concentrations, their efficiency for inhibition of chemotaxis is different. T140 has a greater efficacy for blocking directed migration toward a CXCL12 gradient. The slopes of the ligand binding inhibition curves for T140 and FC131 are different, with T140 demonstrating a steeper decrease in binding than FC131. That relationship resembles the difference in inhibition curves obtained in the FUS1-lacZ assay with CY12946-CXCR4(N119S) cells. Exposure to AMD3100 resulted in slight inhibition of beta-galactosidase activity at 31.6 nM, with

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an increase in the lacZ reporter gene expression beginning at 316 nM. These findings are compatible with the presence of a weak partial agonist. Eight compounds derived from the T140 structure were developed in the Department of Chemogenomics, Graduate School of Pharmaceutical Sciences, Kyoto University, and tested for activity using the yeast FUS1-lacZ screening system. All compounds showed some inhibition of the autonomous activation of the pheromone response pathway by the constitutively active CXCR4. Exposure to incremental concentrations revealed that the IC50 concentrations for TR1403, TR1404, TR1405, and TY14010.R5 were between 100 nM and 500 nM (Fig. 20.3A). The latter four compounds all had complete inhibition of FUS1-lacZ activation at concentrations of 1 mM. The IC50 concentrations for FNC003, A5, A7, and A8 were all greater than 1 mM (Fig 20.3B). In contrast, the four compounds with IC50 values greater than 1 mM did not achieve full inhibition of this activity. The compounds were tested in parallel in radioligand-binding experiments to verify the findings in the yeast assay system. As we have previously described (Zhang et al., 2002), CHO cell CXCR4 transfectants were incubated with [125I]CXCL12 in the presence and absence of incremental concentrations of the individual compounds and cell bound ligand was separated from free by centrifugation through oil. As shown in Fig. 20.3C and D, the group of high-affinity inverse agonists gave standard sigmoidal inhibition kinetics for [125I]CXCL12 binding. The IC50 values for the binding inhibition studies are listed in Table 20.1. The three TR compounds all had IC50 values of 20 nM (TR14003, 23 nM; TR14004, 21 nM; TR14005, 18 nM). TY14010.R5 had an IC50 value of 13 nM and the FCN003 compound was 40 nM. Values for A5 and A8 were greater than 10 mM, and A7 was between 1 mM and 10 mM. There was good relative correlation between IC50 values determined from the fluorescent yeast system and those obtained by inhibition of radioligand ([125I] CXCL12) binding, with the exception of TY14010.R5 (TR14003: 23 nM [125I]CXCL12/246 nM yeast, TR14004: 21 nM [125I]CXCL12/ 119 nM yeast, TR14005: 18 nM [125I]CXCL12/208 nM yeast, TY14010. R5 13 nM [125I]CXCL12/526 nM yeast). Maximum inhibition was obtained at 1 mM of the active inverse agonists in both the yeast and radioligand inhibition systems. The latter technique detected inhibition at lower concentrations of compound. This could be due in part to the presence of the yeast cell wall or the size and/or structure of the antagonists.

3. Summary Human CXCR4 was expressed in Saccharomyces cerevisiae coupled to the yeast pheromone response pathway. High levels of CXCL12 were required to activate signaling using either pheromone-responsive HIS3 or


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TR14003 TR14004 TR14005 TY14010.R5

10

nM


B 120 100 80 60 40 20 0 16

A

[compound] D

150

TR14003 TR14004 TR14005 TY14010.R5

100 50 0 −50

−12

−11

−10 −9 −8 −7 Log [compound]

−6

−5

150

% of buffer I125 CXCL12 bound

% of buffer I125 CXCL12 bound

C

[compound] FCN003 A5 A7 A8

100 50 0

−50 −10

−9

−8 −6 −7 Log [compound]

−5

−4

Figure 20.3 Characterization of T140 derivatives in yeast containing the FUS1-lacZ reporter gene and radioligand-binding inhibition. (A and B) b-galactosidase activity of yeast expressing the CXCR4 constitutively active mutant exposed to incremental concentrations of candidate compounds. (C and D) Inhibition of [125I]CXCL12 binding to CHO cells exposed to incremental concentrations of candidate compounds.

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Table 20.1 Affinity of inverse agonist candidates by radioligand binding Compound

EC50

A5 A7 A8 FCN003 TR14003 TR14004 TR14005 TY1410.R5

>10 mM 1 < EC50 < 10 mM >10 M 40 nM 23 nM 21 nM 18 nM 13 nM

lacZ reporter genes to detect growth or cleavage of a fluorescent substrate, respectively. The expense of this approach precluded using ligand stimulation of native CXCR4 for screening compounds. The pheromoneresponsive HIS3 reporter gene approach, which enables positive growth selection for CXCR4 signaling, while lacking sensitivity for screening compounds, was used to select mutant forms of CXCR4 with constitutive signaling. A CXCR4 mutant with constitutive signaling was identified using the pheromone-responsive HIS3 selection. A sensitive screening assay was developed using the CXCR4 constitutively active mutant with the FUS1lacZ reporter gene to detect activation of beta-galactosidase expression using a fluorescent substrate. The sensitivity of the yeast assay, although less than inhibition of [125I]CXCL12 binding, was sufficient to detect candidates with intermediate levels of activity for CXCR4. The use of the constitutively active CXCR4 mutant has the advantage of detecting both weak partial agonists and inverse agonists (but not neutral antagonists) and distinguishing between these pharmacologic classes of antagonists. The fluorescent yeast assay is rapid, inexpensive, and easy to perform. It is well suited for highthroughput screening of libraries for GPCR antagonists. Full characterization requires the subsequent analysis of lead compounds by standard approaches, including ligand-binding inhibition and biological assays.

REFERENCES Bleul, C. C., Farzan, M., Choe, H., Parolin, C., Clark-Lewis, I., Sodroski, J., and Springer, T. A. (1996). The lymphocyte chemoattractant SDF-1 is a ligand for LESTR/fusin and blocks HIV-1 entry. Nature 382, 829–833. Deichmann, M., Kronenwett, R., and Haas, R. (1997). Expression of the human immunodeficiency virus type-1 coreceptors CXCR-4 (fusin, LESTR) and CKR-5 in CD34þ hematopoietic progenitor cells. Blood 89, 3522–3528.

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Deng, H., Liu, R., Ellmeier, W., Choe, S., Unutmaz, D., Burkhart, M., DiMarzio, P., Marmon, S., Sutton, R. E., Hill, C. M., Davis, C. B., Peiper, S. C., et al. (1996). Identification of a major co-receptor for primary isolates of HIV-1. Nature 381, 661–666. Doitsidou, M., Reichman-Fried, M., Stebler, J., Koprunner, M., Dorries, J., Meyer, D., Esguerra, C. V., Leung, T., and Raz, E. (2002). Guidance of primordial germ cell migration by the chemokine SDF-1. Cell 111, 647–659. Dragic, T., Litwin, V., Allaway, G. P., Martin, S. R., Huang, Y., Nagashima, K. A., Cayanan, C., Maddon, P. J., Koup, R. A., Moore, J. P., and Paxton, W. A. (1996). HIV-1 entry into CD4þ cells is mediated by the chemokine receptor CC-CKR-5. Nature 381, 667–673. Feng, Y., Broder, C. C., Kennedy, P. E., and Berger, E. A. (1996). HIV-1 entry cofactor: Functional cDNA cloning of a seven-transmembrane, G. protein-coupled receptor. Science 272, 872–877. Fredriksson, R., and Schioth, H. B. (2005). The repertoire of G-protein-coupled receptors in fully sequenced genomes. Mol. Pharmacol. 67, 1414–1425. Hagen, D. C., McCaffrey, G., and Sprague, G. F., Jr., (1991). Pheromone response elements are necessary and sufficient for basal and pheromone-induced transcription of the FUS1 gene of Saccharomyces cerevisiae. Mol. Cell. Biol. 11, 2952–2961. Hopkins, A. L., and Groom, C. R. (2002). The druggable genome. Nat. Rev. Drug Discov. 1, 727–730. Jund, R., and Lacroute, F. (1970). Genetic and physiological aspects of resistance to 5-fluoropyrimidines in Saccharomyces cerevisiae. J. Bacteriol. 102, 607–615. Kang, Y., Siegel, P. M., Shu, W., Drobnjak, M., Kakonen, S. M., Cordon-Cardo, C., Guise, T. A., and Massague, J. (2003). A multigenic program mediating breast cancer metastasis to bone. Cancer Cell 3, 537–549. Mo¨hle, R., Bautz, F., Rafii, S., Moore, M. A., Brugger, W., and Kanz, L. (1998). The chemokine receptor CXCR-4 is expressed on CD34þ hematopoietic progenitors and leukemic cells and mediates transendothelial migration induced by stromal cell-derived factor-1. Blood 91, 4523–4530. Muller, A., Homey, B., Soto, H., Ge, N., Catron, D., Buchanan, M. E., McClanahan, T., Murphy, E., Yuan, W., Wagner, S. N., Barrera, J. L., Mohar, A., et al. (2001). Involvement of chemokine receptors in breast cancer metastasis. Nature 410, 50–56. Murphy, P. M., Baggiolini, M., Charo, I. F., Hebert, C. A., Horuk, R., Matsuchima, K., Miller, L. H., Oppenheim, J. J., and Power, C. A. (2000). International union of pharmacology. XXII. Nomenclature for chemokine receptors. Pharmacol. Rev. 52, 145–176. Nagasawa, T., Hirota, S., Tachibana, K., Takakura, N., Nishikawa, S., Kitamura, Y., Yoshida, N., Kikutani, H., and Kishimoto, T. (1996). Defects of B-cell lymphopoiesis and bone-marrow myelopoiesis in mice lacking the CXC chemokine PBSF/SDF-1. Nature 382, 635–638. Oberlin, E., Amara, A., Bachelerie, F., Bessia, C., Virelizier, J. L., Arenzana-Seisdedos, F., Schwartz, O., Heard, J. M., Clark-Lewis, I., Legler, D. F., Loetscher, M., Baggiolini, M., et al. (1996). The CXC chemokine SDF-1 is the ligand for LESTR/fusin and prevents infection by T-cell-line-adapted HIV-1. Nature 382, 833–835. Palczewski, K., Kumasaka, T., Hori, T., Behnke, C. A., Motoshima, H., Fox, B. A., Le Trong, I., Teller, D. C., Okada, T., Stenkamp, R. E., Yamamoto, M., and Miyano, M. (2000). Crystal structure of rhodopsin: A G protein-coupled receptor. Science 289, 739–745. Roesnbaum, D. M., Cherezov, V., Hanson, M. A., Rasmussen, S. G., Thian, F. S., Kobilka, T. S., Choi, H. J., Yao, X. J., Weis, W. I., Stevens, R. C., and Kobilka, B. K. (2007). GPCR engineering yields high-resolution structural insights into beta2-adrenergic receptor function. Science 318, 1266–1273.

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Tachibana, K., Hirota, S., Iizasa, H., Yoshida, H., Kawabata, K., Kataoka, Y., Kitamura, Y., Matsushima, K., Yoshida, N., Nishikawa, S., Kishimoto, T., and Nagasawa, T. (1998). The chemokine receptor CXCR4 is essential for vascularization of the gastrointestinal tract. Nature 393, 591–594. Xue, C., Hseuh, Y. P., and Heitman, J. (2008). Magnificent seven: Roles of G proteincoupled receptors in extracellular sensing in fungi. FEMS Microbiol. Rev. 32, 1010–1032. Zhang, W. B., Navenot, J. M., Haribabu, B., Tamamura, H., Hiramatu, K., Omagari, A., Pei, G., Manfredi, J. P., Fjuii, N., Broach, J. R., and Peiper, S. C. (2002). A point mutation that confers constitutive activity to CXCR4 reveals that T140 is an inverse agonist and that AMD3100 and ALX40-4C are weak partial agonists. J. Biol. Chem. 277, 24515–24521. Zhang, W. B., Wang, Z. X., Murray, J. L., Fujii, N., Broach, J., and Peiper, S. C. (2004). Functional expression of CXCR4 in S. cerevisiae: Development of tools for mechanistic and pharmacologic studies. Ernst Schering Res. Found. Workshop 45, 125–152. Zou, Y. R., Kottmann, A. H., Kuroda, M., Taniuchi, I., and Littman, D. R. (1998). Function of the chemokine receptor CXCR4 in haematopoiesis and in cerebellar development. Nature 393, 595–599.

C H A P T E R

T W E N T Y- O N E

Ubiquitination of Chemokine Receptors Adriano Marchese Contents 414 416 417 419 421

1. Introduction 2. Cell Culture and Transfections 3. Agonist Treatment and Ubiquitination Assay 4. E3 Ubiquitin Ligase AIP4 Mediates Ubiquitination of CXCR4 References

Abstract Ubiquitin modification of proteins has traditionally been linked to proteasomal degradation, but it is now well established that it also serves nonproteasomal functions, such as DNA repair, signal transduction and endocytic trafficking among others. It is now emerging that G-protein–coupled receptor (GPCR) downregulation is mediated by receptor ubiquitination. For example, agonistdependent ubiquitination of the chemokine receptor CXCR4 by the E3 ubiquitin ligase AIP4 (atrophin interacting protein 4) targets CXCR4 for degradation in lysosomes. The ubiquitin moiety on CXCR4 serves as a signal on endosomes for entry into the degradative pathway and long-term attenuation of signaling or downregulation. Several GPCRs have been shown to be ubiquitinated, and ubiquitin-dependent trafficking may represent a general mechanism by which GPCRs are targeted to lysosomes, although some GPCRs that are targeted to lysosomes may not be directly regulated by ubiquitination. Here we describe a simple biochemical assay that we have used to study the ubiquitination of CXCR4 that can be easily applied to study the ubiquitination of any GPCR.

Department of Pharmacology, Stritch School of Medicine, Loyola University Chicago, Maywood, Illinois, USA Methods in Enzymology, Volume 460 ISSN 0076-6879, DOI: 10.1016/S0076-6879(09)05221-5

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1. Introduction Chemokine receptors belong to the large superfamily of G-protein– coupled receptors (GPCRs) that are coupled to heterotrimeric G proteins, especially the Gai subfamily, through which a wide variety of intracellular signaling pathways are activated (Busillo and Benovic, 2007). In order to ensure that signals are of the appropriate magnitude and duration signaling is rapidly terminated by a complex series of events giving rise to the phenomenon known as desensitization. Desensitization is a process whereby signaling is attenuated even in the continuous presence of stimulus. Multiple mechanisms contribute to GPCR desensitization, including, in part, the removal of the receptor from the cell surface through a process involving internalization, which sequesters the receptor from its stimulus (Moore et al., 2006; Pierce et al., 2002). The mechanisms involving GPCR internalization are not completely understood but generally involve receptor phosphorylation by G protein–coupled receptor kinases (GRKs) resulting in arrestin binding and recruitment for internalization through clathrincoated pits (Drake et al., 2006; Moore et al., 2006). As is true for many GPCRs, chemokine receptors readily undergo ligand-dependent internalization into a vesicular compartment known as an early endosome. Once on early endosomes, GPCRs are subject to an endocytic sorting event that targets them into either a recycling pathway and/or a degradative pathway (Hanyaloglu and von Zastrow, 2008; Marchese et al., 2008). Receptors that enter the recycling pathway are returned to the cell surface, giving rise to receptor resensitization where they are able to respond to further stimulation. Receptors that enter the degradative pathway are targeted to lysosomes for proteolysis, giving rise to long-term attenuation of signaling or downregulation. The mechanisms mediating endosomal sorting remain poorly understood, although for some receptors it appears that sorting into the degradative pathway is mediated by receptor ubiquitination (Hanyaloglu and von Zastrow, 2008; Marchese et al., 2008). We have shown that the CXCR4 chemokine receptor undergoes ligand-dependent post-translational modification by ubiquitin (Marchese and Benovic, 2001). Ubiquitin is a 76–amino-acid protein and is attached to proteins through an ATP-dependent enzymatic process involving three sequential enzymatic steps (Hershko and Ciechanover, 1998; Kerscher et al., 2006; Pickart, 2001). The first step is carried out by an E1 enzyme, or activating enzyme, that activates ubiquitin through hydrolysis of ATP leading to the formation of a ubiquitin-adenylate intermediate before ubiquitin is transferred to the active-site cysteine residue of the E1 to form a thiol ester intermediate with the C-terminal glycine residue of ubiquitin. In the second step, ubiquitin is subsequently transferred to the active site

CXCR4 Ubiquitination

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cysteine residue of an E2 enzyme, or ubiquitin conjugating enzyme. The third and final step in the process is carried out by the action of an E3 enzyme or ubiquitin ligase. E3 ubiquitin ligases can be broadly classified as falling within two subfamilies, HECT domain and RING finger; they differ in the manner in which ubiquitin is transferred to acceptor lysine residues on the target protein (Hershko and Ciechanover, 1998; Kerscher et al., 2006; Pickart, 2001). HECT domain E3s have an active site cysteine residue that forms a direct thiol ester intermediate with ubiquitin before transfer of the ubiquitin moiety to the e amine group of lysine residues on the target protein. In contrast, RING finger E3s do not form a direct thiol ester intermediate with ubiquitin, but rather, they act as a bridge by bringing the E2 into close proximity to the bound substrate such that transfer of ubiquitin directly from the E2 to the acceptor site lysine residue on the substrate protein can occur. Despite these differences both types of E3s play a significant role in substrate recognition thus providing the substrate specificity associated with ubiquitination reactions. Ubiquitin forms a covalent isopeptide bond with the substrate protein via the carboxyl side group of the terminal glycine residue on ubiquitin and the e amine group of a lysine residue on the substrate. Ubiquitin attachment is reversible and is subject to removal by deubiquitinating enzymes (Nijman et al., 2005). Therefore, the ubiquitination status of a protein at any given time will be dependent upon the relative ratio of ubiquitination/deubiquitination reactions occurring in cells. We have shown that the chemokine receptor CXCR4 is targeted to lysosomes via a ubiquitin-dependent pathway (Marchese and Benovic, 2001). Agonist-promoted ubiquitination of CXCR4 on carboxyl-terminal tail lysine residues by the E3 ubiquitin ligase AIP4 targets the receptor for degradation in lysosomes (Marchese and Benovic, 2001; Marchese et al., 2003b). The ubiquitin moiety on CXCR4 serves as an endosomal signal by likely mediating interactions with core components of the endocytic sorting machinery that contain ubiquitin-binding domains (Marchese et al., 2003b). Although CXCR4 has been shown to be modified with ubiquitin and targeted to lysosomes via a ubiquitin-dependent pathway, this may not occur for all chemokine receptors (Meiser et al., 2008). However, whether other chemokine receptors are regulated by ubiquitin in a similar manner to CXCR4 remains to be determined. One of the easiest methods used to determine whether a protein is modified by ubiquitin is by SDS-PAGE and immunoblotting to detect the protein of interest. Ubiquitin is a 76–amino-acid protein and when conjugated to proteins will add 8 kDa to the size of the protein. Therefore, if a protein is ubiquitinated, distinct bands that migrate slower than the unmodified protein by a factor of 8 kDa will indicate the incorporation of one ubiquitin molecule (mono-ubiquitin), 16 kDa for two (di-ubiquitin) and so on. The presence of a smear would suggest that the protein is

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polyubiquitinated. The unfortunate caveat with this method with respect to GPCRs is the lack of adequate GPCR antibodies to detect the low density of endogenous receptors in many cell types and tissues. Also, the presence of slower migrating bands/smears would still make it difficult to distinguish ubiquitin modification from other types of similar post-translational modifications. Another more commonly used approach relies on the enrichment of the receptor from cells usually by immunoprecipitation followed by SDS-PAGE and immunoblotting with antiubiquitin antibodies to detect incorporated ubiquitin. This approach has been used successfully to detect ubiquitination of CXCR4 (Marchese and Benovic, 2001, 2004; Marchese et al., 2003b) as well as other GPCRs (Shenoy et al., 2008), although there are caveats associated with this method. One caveat that would apply to CXCR4 (and most GPCRs and/or other proteins) is that because of the low percentage of the total cellular complement of CXCR4 that is ubiquitinated at any given time, we have found it difficult to detect incorporation of endogenous ubiquitin into CXCR4 by using antiubiquitin antibodies. To obviate this difficulty we have resorted to expressing a tagged version of ubiquitin in order to facilitate the ability to detect ubiquitination of CXCR4 (Marchese and Benovic, 2001, 2004; Marchese et al., 2003b). Here we describe a method that we have developed to detect ubiquitination of CXCR4 that can also be readily applied to other chemokine receptors or other members of the GPCR family.

2. Cell Culture and Transfections We use HEK293 (Microbix, Toronto, ON, Canada) and HeLa (ATCC) cells as our model cells to study CXCR4 ubiquitination and trafficking; both cell types express endogenous levels of CXCR4, although we typically use HEK293 cells for heterologous expression studies. We have shown that endogenous CXCR4 is rapidly targeted to lysosomes for proteolysis in CEM cells, a T-cell line; therefore, it appears that endocytic trafficking pathways are conserved among various cell types (Marchese and Benovic, 2001). For ubiquitination assays, we use HEK293 cells and transiently transfect cells with HA-tagged CXCR4 and FLAG-tagged ubiquitin. As discussed above, in our hands it has been difficult to observe ubiquitination of CXCR4 by immunoblotting for endogenous ubiquitin, although others have been successful (Li et al., 2004; Zaitseva et al., 2005). We typically grow HEK293 cells on 10-cm tissue culture–grade Petri dishes. HEK293 cells are seeded from a confluent 10-cm dish at a dilution of 1:3 onto a 10-cm dish containing 10 ml culture medium (DMEM supplemented with 10% fetal bovine serum). We find that with this dilution, the next-day cells are approximately 60 to 70% confluent, which is ideal


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for transfection. On the day of transfection, the medium is replaced with 10 ml of fresh culture medium. We typically use FuGENE6 transfection reagent (Roche), following the manufacturer’s instructions. We cotransfect a total of 10 mg of DNA per 10-cm dish using 30 ml of FuGENE6. For ubiquitination assays, we typically use 7 mg HA-tagged CXCR4 plus 3 mg FLAG-tagged ubiquitin. We have successfully used FLAG-tagged ubiquitin to detect ubiquitinated CXCR4 (Bhandari et al., 2007; Marchese and Benovic, 2001; Marchese et al., 2003b). As controls, parallel plates are transfected with DNA encoding either receptor or ubiquitin alone. The following day, cells from each transfection should be 100% confluent. Transfected cells are seeded onto two 6-cm dishes and allowed to grow for an additional day (18 to 24 h). The next day (i.e., day of the experiment), the cells should be approximately 90% confluent (500,000 cells). Two plates from each transfection condition are plated to allow for treatment with vehicle and agonist. By following this transfection procedure it will permit multiple treatment conditions using cells derived from the same transfection, which will reduce variability owing to differences in expression levels among transfections from plate to plate. The agonist for CXCR4 is stromal-cell–derived factor 1a (SDF-1a), also known as CXCL12, purchased from PeproTech (Rocky Hill, NJ). Single-use aliquots of SDF-1a (10 mM) resuspended in PBS containing 0.1% BSA are stored frozen at –20 C for up to 3 months.

3. Agonist Treatment and Ubiquitination Assay On the day of the experiment, cells are washed 1 with 2 ml warm DMEM and incubated with fresh 1.5 ml DMEM supplemented with 20 mM HEPES for 3 h. The media is replaced with the same media containing either vehicle (0.1% BSA in PBS) or SDF-1a (100 nM; final concentration) in a total volume of 1.5 ml. The cells are treated at 37 C for 30 min. We typically use SDF-1a at a maximal final concentration of 100 nM to ensure full receptor occupancy, enabling maximal receptor ubiquitination to facilitate detection of ubiquitinated CXCR4. We typically treat cells for 30 min because we have determined that under these conditions maximal levels of ubiquitinated CXCR4 are detected (Marchese et al., 2003b). Optimal concentrations of ligand and length of treatments will have to be empirically determined for different cell types and/or specific chemokine receptors being examined. After treatment, plates are immediately placed on ice, media is aspirated and cells are scraped in 800 ml ice-cold lysis buffer (50 mM Tris-HCl, pH 8, 150 mM NaCl, 5 mM EDTA, 0.5% sodium deoxycholate [w/v], 1% nonidet P-40 [NP40, v/v], 0.1% sodium dodecyl sulfate [SDS, w/v], 20 mM

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NEM and protease inhibitors [10 mg/ml each of pepstatin A, leupeptin, aprotinin]). It is important to include NEM to the buffer in order to block free sulfhydryl groups on catalytic-site cysteine residues of deubiquitinating enzymes (DUBs). Active DUBs in cellular lysates may remove ubiquitin attached to proteins, thus making it difficult to detect ubiquitinated proteins. In addition, please note that the lysis buffer we use to immunoprecipitate HA-tagged CXCR4 is somewhat stringent to reduce the likelihood of co-immunoprecipitating proteins that may themselves be ubiquitinated, which could confound data interpretation. We have found that these conditions work best for immunoprecipitating HA-CXCR4 from lysates prepared from HEK293 cells. If different epitope tags and/or different receptors are used, optimization studies will have to be performed. Transfer the lysates to fresh microcentrifuge tubes and place at 4 C while gently rocking for approximately 30 min to ensure complete lysis, followed by sonication on ice for 10 s at setting 10% (Branson Digital Sonifier 450). Samples are clarified by centrifugation at 21,000g for 20 min at 4 C. Save an aliquot of the cleared lysate in an equal volume of 2 sample buffer (0.0375 M Tris-HCl, pH 6.5, 8% SDS, 10% glycerol, 5% b-mercaptoethanol, 0.003% bromophenol blue) for Western blotting to assess the expression of the various constructs. To immunoprecipitate the receptor, incubate 600 ml of the cleared lysate for 1 h with a polyclonal antibody against the HA epitope (HA.11, 1:300 dilution; Covance, Emeryville, CA). Add 20 ml of a 1:1 ratio of protein A equilibrated in lysis buffer and incubate for an additional 1 h at 4 C while rocking. Briefly wash samples twice with 750 ml lysis buffer. Elute bound proteins with 20 ml 2 sample buffer at room temperature (RT) for 30 min. Because most GPCRs will aggregate when boiled and will not properly separate even under denaturing conditions, it is important not to boil samples that contain GPCRs. We typically use a Hamilton syringe equipped with a 24-gauge needle to load samples on 7% SDS-PAGE, followed by electrophoretic transfer onto nitrocellulose membranes according to the manufacturer’s recommendations (Bio-Rad, Hercules, CA). We typically separate proteins using 7% polyacrylamide gels to ensure robust separation and transfer of high-molecular-weight ubiquitinated proteins. The membrane is blocked for 30 min in 10 ml Tris-buffered saline (TBS) (50 mM Tris-HCl, pH 7.4, 150 mM NaCl) with 0.05% Tween 20 (v/v) (TBST) containing 5% non-fat dried milk (w/v) at RT while rocking. To detect incorporation of tagged ubiquitin into the receptor the membrane is probed with anti-FLAG M2 monoclonal antibody (5 mg/ml; Sigma) for at least 1 h at RT or overnight at 4 C while rocking. Wash the membrane at least 3 for 5 min at RT. Incubate the nitrocellulose membrane with 10 ml TBST-5% milk containing goat antimouse IgG conjugated to horseradish peroxidase (HRP) at a dilution of 1:10, 000. Wash the nitrocellulose membrane 5 for 10 min each in TBST.


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Overlay the nitrocellulose with 1 to 2 ml of Supersignal Chemiluminescence reagent (Pierce, Rockford, IL) for 5 min, allow the blot to dry, wrap in plastic wrap, and visualize on x-ray film. Nitrocellulose membranes can be treated with stripping buffer (62.5 mM Tris-HCl, pH 6.7, 100 mM b-mercaptoethanol, 2% SDS) to remove bound antibody and reprobed with a monoclonal anti-HA antibody (HA.11, Covance, Emeryville, CA) to detect receptor levels and to assess loading.

4. E3 Ubiquitin Ligase AIP4 Mediates Ubiquitination of CXCR4 As discussed above, the E3 ubiquitin ligase is one of the most important enzymes involved in the conjugation of ubiquitin to an acceptor lysine residue on the target protein as it provides the specificity associated with ubiquitin reactions while it mediates binding to the target protein. To further understand how CXCR4 is regulated by ubiquitin, we determined that AIP4 (atrophin interacting protein 4), a HECT-domain E3 ubiquitin ligase mediates ubiquitination of CXCR4 (Marchese et al., 2003b). To identify AIP4 as an E3 ubiquitin ligase for CXCR4, we took a candidate protein approach. There are 600 sequences in the human genome that potentially encode E3 ubiquitin ligases (Li et al., 2008), presenting a daunting to task to identify the E3 that mediates ubiquitination of any protein let alone CXCR4. Information about the possible ligase that may regulate CXCR4 came from studies performed in S. cerevisiae, the budding yeast, in which Rsp5 was found to mediate ubiquitination and internalization of the a-mating factor receptor, a GPCR (Dunn and Hicke, 2001). The human genome encodes nine orthologous E3s to yeast Rsp5, which are part of the Nedd4-like family of E3 ubiquitin ligases (Ingham et al., 2004). Members of this family are characterized by the presence of a calcium-dependent phospholipid-binding domain, three to four tandemly linked WW domains, and a HECT domain (Ingham et al., 2004). In general, the WW domains either directly or indirectly interact with their target proteins typically via PY motifs (i.e., PPXY, PPPY) (Ingham et al., 2005). As mentioned above, HECT domain E3s have a catalytic cysteine residue that forms a direct thiol ester intermediate with the terminal glycine residue of ubiquitin before transfer to an acceptor lysine residue on the target protein (Huibregtse et al., 1995). Changing the catalytic cysteine residue to a serine or alanine residue creates a catalytically inactive mutant that behaves as a dominant-negative when overexpressed in cells by inhibiting binding of the endogenous E3 to its target and thus inhibiting its activity. Initially, we took a dominantnegative approach to determine whether CXCR4 ubiquitination was regulated by E3s belonging to this family. Members of this family that we have

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examined include AIP4, Nedd4, and Nedd4-2 (Marchese et al., 2003b). HEK293 cells grown on 10-cm dishes are cotransfected as described above with HA-tagged CXCR4 (1 mg) and either wildtype or mutant versions of Nedd4, AIP4, or Nedd4-2 (1 mg) plus FLAG-ubiquitin (1 mg). Cells are treated with vehicle or SDF-1a and ubiquitination of CXCR4 is assessed as described above. Under these conditions, we have observed that cotransfection with AIP4-C830A, a catalytically inactive mutant of AIP4, attenuates agonist-promoted ubiquitination of CXCR4 and that either wildtype or catalytically inactive forms of Nedd4 and Nedd4-2 had no noticeable effect on CXCR4 ubiquitination (Marchese et al., 2003b). The amount of DNA to transfect for each construct will have to be empirically determined and titrated accordingly to avoid off-target effects. Once a candidate E3 is identified by taking the dominant-negative approach, the next step will be to further confirm a specific role for the E3 in the ubiquitination of the receptor of interest by taking a genetic approach (Marchese et al., 2003b). We have employed siRNA to reduce endogenous levels of AIP4 in HEK293 and HeLa cells (Marchese et al., 2003b). We have used a custom-designed siRNA sequence targeting AIP4 (GenBank Accession No. AF095745): GGU GAC AAA GAG CCA ACA GAG, and corresponds to nucleotides 190 to 211 relative to the start codon. The AIP4 siRNA was synthesized by Dharmacon Research (Lafayette, CO) and is supplied as 23-nucleotide duplexes with 2-nucleotide 30 (2-deoxy) thymidine overhangs. Control siRNA can be against an irrelevant protein such as luciferase. HEK293 cells are cotransfected with HA-CXCR4 plus FLAG-ubiquitin together either with vehicle, control siRNA, or AIP4-specific siRNA. Cells are seeded onto 10-cm dishes the day before transfection (about 15 h) such that the confluency at the time of transfection is at least 80%, which appears to have less-toxic effects on the cells when the transfection reagent is applied. Although there are many reagents available for siRNA transfection, we have had great success using Lipofectamine 2000 (Invitrogen, Carlsbad, CA). Add 30 ml of Lipofectamine 2000 to 1.5 ml OPTIMEM (Invitrogen, Carlsbad, CA) and incubate at RT for 5 min. In another tube, add 1.5 ml OPTI-MEM, DNA encoding receptor (1 mg), tagged ubiquitin (1 mg), and the siRNA equaling 600 pmol. Add the DNA/ siRNA/OPTI-MEM mixture dropwise to the tube containing the OPTI-MEM plus Lipofectamine 2000 and incubate at RT for 20 min. Add the mixture drop wise to cells grown on a 10-cm Petri dish containing 3.5 ml culture medium and place at 37 C for 24 h. The final concentration of the siRNA will be 100 nM. After 24 h, passage the cells onto 6-cm dishes and perform the ubiquitination experiments the next day as described above. Also, pass cells into a parallel plate to test for expression of AIP4. The custom AIP4 siRNA significantly (>90%) reduces AIP4 expression compared to vehicle- or control siRNA–treated cells (Marchese et al., 2003b).


421

Commercially available siRNA and shRNA targeting AIP4 and other E3 ubiquitin ligases are available from several companies. Recently, Nedd4 has been shown to mediate ubiquitination of the b2-adrenergic receptor (Shenoy et al., 2008), suggesting that members of the Nedd4-like E3 ubiquitin ligases may play a broad role in regulating ubiquitination of GPCRs.

REFERENCES Bhandari, D., Trejo, J., Benovic, J. L., and Marchese, A. (2007). Arrestin-2 Interacts with the Ubiquitin-Protein Isopeptide Ligase Atrophin-interacting Protein 4 and Mediates Endosomal Sorting of the Chemokine Receptor CXCR4. J. Biol. Chem. 282, 36971–36979. Busillo, J. M., and Benovic, J. L. (2007). Regulation of CXCR4 signaling. Biochim. Biophys. Acta. 1768, 952–963. Drake, M. T., Shenoy, S. K., and Lefkowitz, R. J. (2006). Trafficking of G. protein-coupled receptors. Circ Res. 99, 570–582. Dunn, R., and Hicke, L. (2001). Multiple roles for Rsp5p-dependent ubiquitination at the internalization step of endocytosis. J. Biol. Chem. 276, 25974–25981. Hanyaloglu, A. C., and von Zastrow, M. (2008). Regulation of GPCRs by endocytic membrane trafficking and its potential implications. Annu. Rev. Pharmacol. Toxicol. 48, 537–568. Hershko, A., and Ciechanover, A. (1998). The ubiquitin system. Annu. Rev. Biochem. 67, 425–479. Huibregtse, J. M., Scheffner, M., Beaudenon, S., and Howley, P. M. (1995). A family of proteins structurally and functionally related to the E6-AP ubiquitin-protein ligase. Proc. Natl. Acad. Sci. USA 92, 2563–2567. Ingham, R. J., Colwill, K., Howard, C., Dettwiler, S., Lim, C. S., Yu, J., Hersi, K., Raaijmakers, J., Gish, G., Mbamalu, G., Taylor, L., Yeung, B., et al. (2005). WW domains provide a platform for the assembly of multiprotein networks. Mol. Cell. Biol. 25, 7092–7106. Ingham, R. J., Gish, G., and Pawson, T. (2004). The Nedd4 family of E3 ubiquitin ligases: Functional diversity within a common modular architecture. Oncogene 23, 1972–1984. Kerscher, O., Felberbaum, R., and Hochstrasser, M. (2006). Modification of proteins by ubiquitin and ubiquitin-like proteins. Annu. Rev. Cell. Dev. Biol. 22, 159–180. Li, W., Bengtson, M. H., Ulbrich, A., Matsuda, A., Reddy, V. A., Orth, A., Chanda, S. K., Batalov, S., and Joazeiro, C. A. (2008). Genome-wide and functional annotation of human E3 ubiquitin ligases identifies MULAN, a mitochondrial E3 that regulates the organelle’s dynamics and signaling. PLoS ONE 3, e1487. Li, Y. M., Pan, Y., Wei, Y., Cheng, X., Zhou, B. P., Tan, M., Zhou, X., Xia, W., Hortobagyi, G. N., Yu, D., and Hung, M. C. (2004). Upregulation of CXCR4 is essential for HER2-mediated tumor metastasis. Cancer Cell. 6, 459–469. Marchese, A., and Benovic, J. L. (2001). Agonist-promoted ubiquitination of the G. protein-coupled receptor CXCR4 mediates lysosomal sorting. J. Biol. Chem. 276, 45509–45512. Marchese, A., and Benovic, J. L. (2004). Ubiquitination of G. protein-coupled receptors. Methods Mol. Biol. 259, 299–306. Marchese, A., Paing, M. M., Temple, B. R., and Trejo, J. (2008). G. Protein-Coupled Receptor Sorting to Endosomes and Lysosomes. Annu. Rev. Pharmacol. Toxicol. 48, 601–629.

422

Adriano Marchese

Marchese, A., Raiborg, C., Santini, F., Keen, J. H., Stenmark, H., and Benovic, J. L. (2003). The E3 ubiquitin ligase AIP4 mediates ubiquitination and sorting of the G. proteincoupled receptor CXCR4. Dev. Cell. 5, 709–722. Meiser, A., Mueller, A., Wise, E. L., McDonagh, E. M., Petit, S. J., Saran, N., Clark, P. C., Williams, T. J., and Pease, J. E. (2008). The chemokine receptor CXCR3 is degraded following internalization and is replenished at the cell surface by de novo synthesis of receptor. J. Immunol. 180, 6713–6724. Moore, C. A., Milano, S. K., and Benovic, J. L. (2006). Regulation of Receptor Trafficking by GRKs and Arrestins. Annu. Rev. Physiol. 69, 451–482. Nijman, S. M., Luna-Vargas, M. P., Velds, A., Brummelkamp, T. R., Dirac, A. M., Sixma, T. K., and Bernards, R. (2005). A genomic and functional inventory of deubiquitinating enzymes. Cell 123, 773–786. Pickart, C. M. (2001). Mechanisms underlying ubiquitination. Annu. Rev. Biochem. 70, 503–533. Pierce, K. L., Premont, R. T., and Lefkowitz, R. J. (2002). Seven-transmembrane receptors. Nat. Rev. Mol. Cell. Biol. 3, 639–650. Shenoy, S. K., Xiao, K., Venkataramanan, V., Snyder, P. M., Freedman, N. J., and Weissman, A. M. (2008). Nedd4 Mediates Agonist-dependent Ubiquitination, Lysosomal Targeting, and Degradation of the {beta}2-Adrenergic Receptor. J. Biol. Chem. 283, 22166–22176. Zaitseva, M., Romantseva, T., Manischewitz, J., Wang, J., Goucher, D., and Golding, H. (2005). Increased CXCR4-dependent HIV-1 fusion in activated T cells: Role of CD4/ CXCR4 association. J. Leukoc Biol. 78, 1306–1317.

Author Index

A Abboud, C. N., 68 Abdel-Rahman, E., 290 Abe, S., 290 Able, S., 17 Abraham, M., 61, 62 Abrescia, N. G., 174 Abrol, R., 270 Acott, P. D., 304 Adams, G. B., 58, 59 Adkins, D., 65 Adler, B., 166 Adorini, L., 200 Aebersold, R., 338 Agostinis, C., 232, 233 Ahearn, M., 317 Ahuja, M., 361 Ahuja, S. K., 19, 33 Akanuma, Y., 290 Akbar, N., 266 Alarcon, B., 386 Albar, J. P., 333, 338, 341 Albuqerque, C. P., 340 Alcami, A., 173, 174, 175, 176, 178, 179, 180, 181, 183, 184, 185, 187, 188, 194, 195, 198, 203, 204, 213, 236 Alcendor, D. J., 134 Aldape, K. D., 92 Alejo, A., 174, 184 Alexander, J. M., 194 Alexander, W. S., 64 Alexander-Brett, J. M., 174, 184, 200, 204 Ali, H., 60 Alizon, M., 361 Aljada, A., 290 Allavena, P., 4, 105, 106, 107, 117 Allaway, G. P., 401 Allen, C., 65 Allen, S. J., 211, 291, 305, 333 Allendorf, D. J., 60, 63 Alon, R., 59, 60, 194 Alsina, M., 66 Alt, F. W., 49 Altenbach, C., 265, 272 Altmann, D. M., 200 Altschuler, Y., 153, 165 Alvarez, R., 66 Amara, A., 60, 401

Ambinder, R. F., 134 Amiel, A., 59 Anastassov, V., 29 Anderson, G. A., 342 Anderson, J., 66 Anderson, R. G., 358 Andreoni, M., 127 Anselmo, A., 236, 240, 241 Ansorge, R., 165 Anthonsen, M. W., 307 Antonenko, S., 70 Appelbaum, F., 65 ap Rhys, C. M., 134 Aramaki, Y., 367 Archibald, S. J., 59, 69, 72 Arenzana-Seisdedos, F., 10, 59, 60, 63, 153, 159, 185, 188, 317, 401 Armand-Ugon, M., 359 Armes, J. E., 371, 375 Armour, D., 19, 20, 22, 24, 26, 29, 30, 33, 40 Arnold, K., 212 Aronica, E., 92 Arvanitakis, L., 127, 128, 130, 134, 135, 137, 153 Asaka, M., 59 Asch, A. S., 127, 128, 130, 137, 153 Asgari, Z., 128 Ashton, M., 270 Assimacopoulos, S., 92 Astle, C. M., 74, 76 Atkinson, M. A., 201 Audet, J., 78 Auffray, C., 118 Aul, C., 67 Aulakh, G., 317 Ausema, A., 61, 66 Avdi, N. J., 159 Avisar, N., 267 Avivi, L., 59 Axel, R., 130 Ayinde, D., 361 B Baba, M., 367 Bachelerie, F., 60, 63, 317, 401 Badr, C., 353 Bafna, V., 335, 340, 341, 342, 343 Baggiolini, M., 60, 358, 400, 401 Bahar, I., 273

423

424 Bahar, M. W., 174 Bai, W., 198 Bailey, C., 107, 117 Bailey, P., 291 Baiocchi, R. A., 69 Bais, C., 127, 128, 130, 137, 140, 141, 153 Bakalarski, C. E., 342 Baker, J. G., 264 Bakker, R. A., 153, 160, 162, 164 Balabanian, K., 60, 63, 317 Baleux, F., 63, 185, 188, 317 Balgley, B. M., 342 Balkwill, F., 106, 107 Ball, E. D., 60, 62 Ballesteros, J., 269 Bandura, L., 60, 63 Banerji, S., 240 Bannert, N., 51 Bansal, A. K., 118 Bansal, M., 118 Barac, A., 128, 137, 138, 143 Barbanera, M., 127 Barber, C., 46 Bardos, P., 59 Barge, A., 66 Bar-Haim, S., 267 Barkai, G., 78 Barlet, X., 118 Barlogie, B., 65 Barnes, G. T., 290, 291 Baroudy, B. M., 21, 33, 45, 46 Barrell, B. G., 165 Barrera, J. L., 401 Barrett, J., 174, 175, 176, 184, 188, 194 Barrett, J. W., 174 Barry, M., 174, 175, 176 Bartee, M. Y., 209 Barton, D. S., 198 Barzik, M., 210, 317, 318, 319 Baskaran, H., 327 Bass, G., 65 Batalov, S., 419 Batard, P., 388, 390 Batten, M., 60 Battista, M., 63 Bauser, U., 67 Bautz, F., 333, 401 Beaudenon, S., 419 Becker, O. M., 267, 269 Beckett, P., 226 Becknell, B., 69 Beck-Wirth, G., 66 Bedard, E. L., 213 Begent, R. H., 226 Begin, M., 61, 62 Begley, C. G., 67 Behnke, C. A., 44, 264, 400 Beisser, P. S., 153, 160, 165

Author Index

Bell, G. W., 10 Bellahcene, A., 118 Belmadani, A., 92 Belperio, J. A., 4, 118 Ben-Baruch, A., 3, 4 Benboubker, L., 59 Bendall, L. J., 58, 60 Benedetti, L., 118 Bengtson, M. H., 419 Ben-Hur, H., 59, 78 Bennett, C. L., 59 Benovic, J. L., 60, 63, 69, 360, 414, 415, 416, 417, 419, 420 Bensinger, W., 58, 59, 65, 67, 68 Berahovich, R., 60 Berg, A. L., 92 Berg, E., 361 Berger, A., 107, 117 Berger, E. A., 60, 401 Berkhout, B., 386 Bernard, P., 267, 270 Bernards, R., 415 Bernhagen, J., 60 Bernhardt, G., 70, 72 Berridge, M. J., 136 Bertagnolli, M. M., 107 Bertelli, F., 39 Berthebaud, M., 69 Bessia, C., 60, 401 Beuken, E., 165 Beyermann, M., 338 Beylot, M., 307 Bhandari, D., 417 Bharara, S., 152 Bhatia, J., 226 Bhatia, M., 77 Bhattacharya, S., 273, 274 Bian, H., 60, 62, 65, 74, 76 Bianchi, P., 105 Biben, C., 60 Biber, K., 92 Bidgol, A., 198 Bielecki, B., 92 Billstrom, M. A., 159, 160 Binet, C., 59 Birch, R., 65 Bissantz, C., 267, 270 Biyder, K., 61, 62 Blackburn, P. E., 237, 240, 247, 249, 250, 256, 257, 258, 259 Blagoev, B., 342 Blair, E., 237, 240, 245 Blanchetot, C., 381 Blanco, J., 359 Bland, K. I., 152 Blanpain, C., 17, 291, 361 Blaser, H., 60 Blechschmidt, M., 66

425

Author Index

Bleul, C. C., 60, 400 Blom, B., 69, 70 Blomenrohr, M., 168 Bloxham, D., 65 Bockhold, K., 77 Bodaghi, B., 153, 159 Boddeke, H. W., 92 Bodenmiller, B., 338 Boeve, S., 67 Bogerd, J., 168 Bohinjec, J., 63, 317 Boldajipour, B., 60 Bolton, K., 292 Bondar, A. N., 264 Bonde, J., 80 Bondue, A., 17 Bonecchi, R., 231, 232, 233, 236, 237, 238, 240, 241, 246 Boogaerts, M. A., 66 Boose, J. A., 294, 296 Bordoli, L., 212 Borge, O. J., 76 Borghesani, P. R., 60 Borlat, F., 194, 359, 362, 364 Bornhauser, M., 60, 66 Borroni, E. M., 231, 236, 240, 241 Borst, E. M., 165 Bosch, L., 156 Boschert, U., 92 Bosworth, N., 180 Botham, A., 34 Boulanger, V., 118 Bouma, G., 201 Bourne, H. R., 327 Bower, M., 127 Bowers, K., 154, 159 Bowie, J. U., 269 Boxberger, S., 60 Bozaoglu, K., 292 Bradfield, L., 380, 381, 382, 384, 385, 386, 388, 391, 392, 395 Bradley, J., 39 Bradrick, T. D., 384 Bradstock, K., 66 Brady, M. S., 107 Bramati, P. S., 380, 381, 382, 384, 385, 386, 388, 391, 392, 395 Brandimarti, R., 92 Brandish, P. E., 160 Brann, M. R., 137 Brass, L. F., 63, 359, 360 Braun, R., 271 Brauner-Osborne, H., 135 Bravo, R., 198 Breakefield, X. O., 353 Breitfeld, D., 70, 72 Breitkopf, S. B., 332, 333, 342 Breitmeyer, J., 386

Brekken, R. A., 118 Brelot, A., 361 Brenner, S., 63 Bresnahan, W., 175, 176, 184 Brett, T. J., 194 Brezillon, S., 291 Bridger, G., 60, 61, 63, 64, 67, 68, 69, 76, 80 Bridger, G. J., 63, 67 Bringhurst, F. R., 59 Britt, W. J., 152 Broach, J. R., 399, 402, 408 Broadbent, J., 183 Broder, C. C., 60, 401 Bromberg, J. S., 200, 201, 204 Bronson, R. T., 60 Bronte, V., 117 Brooks, H. D., 273 Brooks, M. W., 10 Brown, B. A., 183 Brown, M. F., 273 Brown, R. A., 65 Browne, H., 154 Browning, D. D., 143 Browning, P. J., 128 Broxmeyer, H. E., 61, 63, 64, 67, 73, 76 Bruggeman, C. A., 153, 160, 165 Brugger, W., 401 Brummelkamp, T. R., 415 Brune, W., 165, 166 Brunetti, C. R., 174 Bruneval, P., 107, 117 Bryant, N. A., 174, 178, 180 Bryant, S. H., 342 Bryder, D., 76 Buchanan, M. E., 401 Buet, D., 69 Bugge, T. H., 128, 131, 132, 134, 135 Bujard, H., 202 Bulla, R., 232, 233 Buller, R. M., 175 Bunce, C., 213 Buracchi, C., 231, 232, 233, 236, 238 Burdick, M. D., 4, 118 Burger, J. A., 59, 333, 334 Burger, M., 333, 334 Burgess, J., 66 Burghammer, M., 264 Burke, D. J., 338 Burkhart, M., 401 Burns, J. M., 60 Burstein, E. S., 164 Burt, C., 24, 36, 39 Burzenski, L. M., 78 Busam, K. J., 107 Buser, C., 166 Busillo, J. M., 60, 63, 69, 414 Busmann, A., 291

426

Author Index

Buss, E. C., 60 Buss, V., 264 Butcher, E. C., 290, 291, 302, 304, 305, 306 Butler, J., 66 Byk, T., 59, 78 Bylund, D. B., 157 Bystrykh, L. V., 61, 66 Bywater, R. P., 273 C Caccamo, N., 235, 239 Caceres, N., 235, 239 Cain, M., 183 Calandra, G., 60, 61, 63, 64, 67, 68, 69, 76, 80 Caligiuri, M. A., 69 Callahan, M. K., 92 Callander, N., 66 Calvi, L. M., 59 Cameron, C., 174 Camp, D. G. II, 342 Campanella, G. S., 185, 188 Campbell, D. G., 307 Campbell, I. L., 92 Campbell, J. D., 232, 239 Campbell, T. B., 61, 63, 64, 67, 76 Camps, M., 210, 211 Camus, M., 107, 117 Canasto-Chibuque, C., 198, 200, 201, 204, 232 Cannon, J. S., 134 Cannon, M., 141 Cannon, M. J., 127 Canutescu, A. A., 268 Capon, D. J., 40 Cappetti, B., 118 Carbonatto, M., 210, 212 Cardona, A. E., 92 Cardona, P. J., 235, 239 Cardona, S. M., 92 Cardozo, A. K., 201 Cardwell, L., 63 Carey, V. J., 10 Carion, A., 59 Carlson, T., 91 Carmack, A. J., 119 Carmen, G. Y., 307 Carreno, P., 239 Carter, S. L., 92 Caruso, D. J., 119 Caruz, A., 59 Casarosa, P., 153, 154, 155, 156, 160, 165 Cashen, A. F., 59, 63, 68 Cashman, J., 77, 78 Castilla, C., 59 Castronovo, V., 118 Cathcart, M. E., 92

Catron, D., 401 Cavadini, P., 63, 317 Cavallin, L. E., 128 Cayanan, C., 401 Cebon, J., 67 Cerottini, J.-C., 388, 390 Cesarman, E., 127, 128, 130, 134, 135, 137, 141, 153 Chaisuparat, R., 128 Chaleff, S., 78 Chamberlain, A. K., 269 Chan, C., 383 Chan, F. K.-M., 384 Chanda, S. K., 419 Chandraratna, R. A., 291 Chang, C. N., 361 Chang, Y., 127 Chappel, J., 60, 63 Charlton, M. H., 270 Charo, I. F., 92, 232, 358, 400 Charurat, M., 128 Chen, C. A., 162 Chen, D., 269, 270 Chen, H., 290, 291 Chen, J., 74, 107 Chen, M. C., 201 Chen, S., 92 Chen, S. C., 128, 153, 195, 196, 198, 203, 204 Chen, X., 78 Cheng, G., 239 Cheng, T., 60, 61 Cheng, X., 416 Cheng, Y., 130, 158 Chensue, S. W., 128, 153, 196 Cherezov, V., 264, 400 Chernosky, A., 92 Cheruku, S., 269 Cheson, B., 65 Cheung, M. C., 127 Chevillotte, M., 166 Chien, E. Y., 264 Chien, H. F., 92 Chien, P., 92 Chihara, K., 292 Childs, R., 80 Chiodoni, C., 118 Chiou, C. J., 134 Chiozzini, C., 128 Chlenski, A., 118 Choe, H., 60, 400 Choe, H. W., 264, 271 Choe, S., 361, 401 Choi, C. S., 200 Choi, E. J., 267, 269, 270, 272, 285 Choi, H. J., 264, 400 Choi, K. C., 292 Choi, U., 63 Chou, C. C., 33, 195, 198, 204

427

Author Index

Chou, C. J., 290, 291 Chow, K. Y., 60 Chow, K. Y. C., 317 Christophe, T., 364, 367 Christopher, M. J., 60, 63, 66 Christopoulos, A., 264, 271 Christopoulos, T. K., 353 Chu, C. C., 239 Chung, C. Y., 327, 328 Ciaramella, G., 24, 39, 40, 43, 44, 46 Cichy, J., 291, 305 Ciechanover, A., 414, 415 Cihak, J., 359, 361, 362, 364 Cinamon, G., 194 Cinatl, J., Jr., 152 Cioffi, M., 291 Cirillo, R., 210, 212 Ciruela, F., 380 Ciufo, D. M., 134 Clader, J. W., 21, 33, 45, 46 Clapham, P. R., 359, 361, 362, 364 Clapp, D. W., 61, 63, 64, 67, 76 Clark, C. J., 118 Clark, J. H., 383 Clark, P. C., 415 Clarke, W. P., 264, 271 Clark-Lewis, I., 60, 174, 175, 176, 184, 187, 194, 400, 401 Clawson, G. A., 348 Clotet, B., 359 Cobbs, C. G., 152 Cobbs, C. S., 152 Cohen, P., 307, 332 Cohn, S. L., 118 Colangeli, V., 127 Coleman, M. K., 342 Collier, G., 292 Collins, P. D., 174, 175, 176, 179, 181 Collins, S., 317 Colombat, P., 59 Colombo, M. P., 118 Colwill, K., 419 Colyer, C. L., 383 Combadiere, C., 19, 33 Comerford, I., 246, 251, 254, 255 Communi, D., 291 Conejo-Garcia, J. R., 107 Conlon, P. J., 178 Conn, P. M., 159 Connell, L., 239 Constantini, F., 196 Contreras, R., 226 Cook, D. N., 92, 213, 232, 233, 236, 238 Cooper, S., 61, 63, 64, 67, 73, 76 Copeland, N. G., 165 Coppack, S. W., 291 Coppens, J. M., 201 Corbau, R., 24, 36, 39

Cordon-Cardo, C., 401 Coronel, E. C., 198 Coso, O., 127, 128, 130, 137, 153 Coso, O. A., 139 Costantino, N., 165 Costes, A., 107, 117 Costes, B., 174 Cottler-Fox, M., 65 Couillault, C., 118 Coukos, G., 107 Coulombel, L., 73, 77 Court, D. L., 165 Coussens, L. M., 106, 107 Cox, K., 33 Crabtree, G. R., 136 Craft, T. P., 80 Creech, S., 67 Crnkovic, I., 165 Crowe, E., 92 Crowley, J., 65 Crown, S. E., 174, 211, 333 Crozier, P. S., 273 Cruz, J., 66 Crystal, R. G., 63 Cui, M., 92 Cullinan, C. A., 291 Culpepper, J., 127 Cyster, J. G., 198 D Dadke, D., 128, 137, 143 Dagis, A., 67 Dai, E., 209, 213 Dale, D. C., 63, 67 Dallas, W., 63, 359, 360 Damodaran, A., 232 Damotte, D., 107 Dandona, P., 290 D’Andrea, F., 291 D’Andrea, M., 359 Dar, A., 58, 59 Darkes, M., 29 Darling, A. J., 294, 296 Darzi, A., 107, 117 Dash, A. B., 10 da Silva, A. P., 118 Daub, H., 332, 333, 342 Daugherty, B. L., 157, 361 Davidson, M. W., 380 Davies, J. A., 290 Davis, C. B., 361, 401 Davis, J., 20, 38, 43, 48 Davis-Poynter, N. J., 165, 178, 180 Davis-Turner, J., 361 Deconto, R. M., 117 de Esch, I. J., 156, 160, 162 Defea, K., 358

428 Degerman, E., 307 de Graauw, M., 332 De Groot, C. J., 92 de Haan, G., 61, 66, 73 Deichmann, M., 401 de Kleine, R., 353 de las Rivas, J., 59 de la Torre, Y. M., 236 Delaunay, T., 10 del Canizo, M. C., 59 De Leener, A., 17 Delgado, M., 59 Delhaye, M., 361 Dell’Aquila, M., 333, 334 de Lys, P., 92 DeMartino, J. A., 361 de Mendonca, F. L., 270 Demirer, T., 65 Demuynck, H. M., 66 Deng, H., 401 den Hertog, J., 381 De Paoli, P., 359 Dephoure, N. E., 342 DeRavin, S. S., 63 Dertinger, S. K., 327 Desbois, I., 59 Detheux, M., 291 Dethmers-Ausema, B., 73 Dettwiler, S., 419 Deupi, X., 264, 271, 272 Deupree, J. D., 157 Devine, H., 68, 69, 80 Devine, S. M., 68, 69, 80 Devore, P., 66 Devreotes, P., 381 Dewchand, H., 200 Dewor, M., 60 Dexter, T. M., 61, 66 Dezube, B. J., 127 Dhanoa, D. S., 269 Dhillon, T., 127 Diaz, C., 273 Diaz, G. A., 63, 317 Di Carlo, E., 118 Dick, J. E., 77, 78 Diehlmann, A., 60 Dieli, F., 235, 239 Dierlamm, J., 67 Digel, M., 166 Dijkstra, I., 92 Dijkstra, I. M., 92 Di Liberto, D., 235, 239, 247 Dimarzio, P., 401 Dinter, H., 118 Dioszegi, M., 35, 44, 45 Di Paolo, S., 128 DiPersio, J. F., 57, 58, 59, 60, 61, 65, 67, 68, 69, 80

Author Index

Dirac, A. M., 415 DiSepio, D., 291 Dittmer, D. P., 128, 134 Divieti, P., 59 Dlubek, D., 61 Dobbs, S., 19, 20, 22, 24, 26, 29, 30, 33, 35, 36, 39, 40 Doebber, T. W., 291 Doedens, M., 78 Doitsidou, M., 401 Dollard, S. C., 127 Dombrowski, S., 92 Domenech, J., 59 Domon, B., 338 Doms, R. W., 17, 291 Doni, A., 232, 233, 236, 240, 241 Dontje, B., 61, 66 Doranz, B. J., 17, 361 Dorf, M., 239 Dorr, P., 17, 19, 20, 21, 22, 24, 26, 28, 29, 30, 33, 34, 35, 36, 38, 39, 40, 42, 43, 44, 46, 48 Dorrestein, P. C., 331 Dorries, J., 401 Dorrucci, M., 127 Dower, S. K., 178 Drabczak-Skrzypek, D., 61 Dragic, T., 401 Dragowska, W., 73 Drake, M. T., 414 Dreger, P., 66 Drexhage, H. A., 201 Driver, S. E., 294 Drobnjak, M., 401 Droese, J., 154 Dubois-Dalcq, M., 92 Dugani, C. B., 240 Dunbrack, R. L., Jr., 268 Duncan, R. C., 119 Dunn, G. P., 107 Dunn, R., 419 Dunning, L., 270 Dupor, J., 232, 233, 238 Dupuy, A., 63, 317 Duran, E. M., 128 Durell, S. R., 361 Durham, S. K., 198 Durrant, S., 66 Dutta, R., 92 Duvic, M., 291 Dykstra, B., 73 Dziejman, M., 60 Dziembowska, M., 92 E Eaves, A. C., 73, 74, 77 Eaves, C. J., 73, 74, 77, 78 Ebert, B. L., 143

429

Author Index

Eckstein, V., 60, 80 Edgar, C. E., 380, 381, 382, 384, 385, 386, 388, 391, 392, 395 Edinger, A. L., 291 Edwards, J. G., 240 Edwards, P. C., 264 Efstathiou, S., 174, 175, 176, 179, 194, 195 Ehlenbeck, C., 65 Ehlers, M. D., 240 Ehninger, G., 60, 66 Eisenmann, J. C., 66 Eisterer, W., 78 Eizirik, D. L., 197, 200, 201 Elcock, A. H., 270 Elliott, J. I., 200 Ellmeier, W., 401 Elstner, M., 264 Eltayeb, S., 92 Ema, H., 65, 76, 77 Emeis, J. J., 291 Endres, M., 33 Endres, M. J., 361 Eng, J., 340 Ensoli, B., 128 Entel, P., 264 Eramian, D., 266, 269 Ericsson-Dahlstrand, A., 92 Ernst, O. P., 264, 271 Eroles, P., 128 Esguerra, C. V., 401 Esposito, K., 291 Este, J. A., 359 Eswar, N., 266, 269 Eto, K., 290 Evans, B. J., 399 Evans, R. J., 61, 63 Eveno, E., 118 Evens, A. M., 59 Everett, H., 174 F Fabbri, M., 105, 236, 240, 241 Faber, A., 60 Facchetti, F., 291 Failenschmid, C., 333 Fajas, L., 292 Fakhari, F. D., 134 Falk, P., 67 Fallon, R., 60, 61 Fan, L., 213 Fang, X., 342 Fantuzzi, G., 290 Farrell, H. E., 155, 165 Farrens, D.L., 265, 271, 272 Farzan, M., 51, 60, 400 Fedarko, N. S., 118 Felberbaum, R., 414, 415 Feller, S. E., 273

Feng, S., 338 Feng, Y., 60, 401 Fenyk, J. R., Jr., 63 Ferketich, A. K., 69 Ferlazzo, G., 291 Ferminan, E., 59 Fernandes, P. A., 270 Fernandez, J. L., 353 Ferrant, A., 66 Ficarro, S. B., 338 Fichman, M., 267, 269 Fidock, M., 21, 24, 28, 30, 36, 39, 46 Field, J., 128, 137, 143 Filizola, M., 273 Finelli, M., 269, 270 Fingerle-Rowson, G., 60 Fire, A., 294 Fischer, J., 67 Fischer, R., 384 Fisher, G. H., 131 Fisher, I., 60 Fisher, L. W., 118 Fisher, N., 68, 69, 80 Fitzsimons, C. P., 153, 156, 160, 165 Flavell, R. A., 195 Flodstrom, M., 200 Flore, O., 134 Florens, L., 342 Floriano, W., 267, 270 Floriano, W. B., 267, 269, 270, 272, 285 Folsom, A. R., 290 Foote, S., 64 Forde, S. P., 59 Forsberg, E., 210 Forssell, J., 107, 108, 117 Forssmann, W. G., 291 Forster, R., 70, 72 Forster, T., 381 Foudi, A., 69 Foulis, A. K., 199 Fox, B. A., 44, 264, 400 Fox, J. M., 270 Fox, M. H., 384 Fra, A. M., 237, 239, 240, 246, 250, 254 Fraile-Ramos, A., 154, 159, 360 Francois, F., 63, 317 Frank, A., 340, 341 Franssen, J. D., 291 Frascaroli, G., 166 Fraser, A. D., 304 Fraser, A. R., 239 Fratantoni, S. A., 160 Freddolino, P., 267, 269, 270, 272, 285 Frederich, R., 291 Fredriksson, R., 60, 400 Freedman, N. J., 416, 421 Fremont, D. H., 174, 175, 176, 184, 194, 200, 204

430

Author Index

Frenette, P. S., 63, 198 Freud, A. G., 69 Freytes, C. O., 66 Frick, M., 67 Fricker, S. P., 29 Fridey, J., 67 Friedman, J. M., 290 Friend, D., 174 Friesner, R. A., 271, 274 Fruehauf, S., 80 Fryer, B. H., 128, 137, 143 Fuentes, M. E., 198 Fuery, M., 66 Fujii, N., 59, 399, 402, 408 Fujino, M., 367 Fujita, N., 270 Fukuda, S., 60, 62, 65, 74, 76, 80 Fuller, M. T., 58 Furtado, G. C., 198, 201, 204 G Gabriel, J., 68, 69, 80 Gadella, T. W. J., Jr., 381 Galisteo, R., 128, 141, 143 Gallagher, R., 317 Galliera, E., 236, 237, 238, 246 Gallo, R. C., 128, 317 Galon, J., 107, 117 Galun, E., 61, 62 Gan, O. I., 78 Gandhi, M. K., 65 Ganem, D., 127 Gao, J. L., 160 Gao, S. J., 128 Garbutt, M., 211 Garcia, B., 213 Garcia, J. L., 59 Garcia-Zepeda, E., 60, 61 Gariboldi, S., 118 Garin, A., 200, 204 Garlanda, C., 106, 107, 117 Garofalo, A., 59 Garton, A. J., 307 Gassmann, M., 142 Gavrilov, S., 21, 45, 46 Gazitt, Y., 66 Ge, N., 401 Geay, J. F., 69 Geer, L. Y., 342 Geiger, H., 61, 66 Geiser, T., 60 Gelb, B., 63 Gendelman, R., 128 Gentili, F., 291 Georget, M. T., 59 Georgiev, I., 60

Geras-Raaka, E., 127, 135 Gerhart, M., 174 Germing, U., 67 Gerritsen, W. R., 73 Gershengorn, M. C., 127, 128, 130, 135, 137, 153 Gertler, F. B., 210, 317, 318, 319 Gesualdo, L., 128 Geuze, H. J., 374 Ghosh, A., 271, 274 Ghosh, S., 143, 145 Ghosn, C., 291 Gibson, W., 154 Giebel, B., 65 Giershik, P., 165 Gifford, A. M., 118 Gill, J., 39 Gillespie, G. Y., 152 Gillette, M. A., 143 Gillies, S. D., 78 Gillis, S., 178 Ginsberg, H. N., 293 Girotti, M. R., 118 Gish, G., 419 Giugliano, D., 291 Giugliano, G., 291 Glabinski, A., 92 Glazer, A. N., 383 Glimm, H., 78 Glogauer, M., 118 Gnad, F., 342 Gobbi, M., 237, 239, 240 Goddard, W. A., 267 Goddard, W. A. III, 267, 268, 269, 270, 272, 285 Goddell, M. A., 65 Goedecke, M. C., 28 Gohda, K., 270 Goichberg, P., 59 Goldin, R., 107, 117 Golding, H., 416 Goldstone, A. H., 66 Golemis, E. A., 128, 137, 143 Golub, T. R., 143 Gomez, J., 359 Gomperts, B., 4, 118 Gong, B., 338 Gonsiorek, W., 33 Goodnough, L. T., 65 Goodwin, R. G., 174 Gooley, T., 65 Goralski, K. B., 289, 290, 291, 302, 304, 305, 306 Gorlin, R. J., 63, 317 Gorman, J. R., 49 Gossen, M., 202 Gotoh, M., 197

431

Author Index

Gott, B., 78 Goucher, D., 416 Gouldson, P. R., 273 Govaerts, C., 17, 291 Grabovsky, V., 60 Graham, G. J., 213, 232, 236, 237, 239, 240, 245, 246, 247, 248, 250 Graham, K. A., 174, 175, 176, 187 Graham-Evans, B., 61, 63, 64, 67, 76 Grammer, A. C., 384 Grandaliano, G., 128 Grande, F., 59 Granzow, M., 142 Graudens, E., 118 Grauls, G., 165 Grauls, G. E., 165 Gravot, A., 361 Gray, A., 34 Gray, P. W., 359 Graziano, M. P., 291 Green, M. D., 67 Greenlee, W. J., 33 Greenman, J., 59, 69, 72 Gregori, S., 200 Gregory, J. L., 60 Greiner, A. L., 118 Greiner, D., 78 Greiner, D. L., 78 Gremy, G., 118 Greten, F. R., 106 Grewal, I. S., 195 Grewal, K. D., 195 Griffin, N., 226 Griffin, P., 17, 19, 20, 22, 24, 26, 29, 30, 33, 35, 36, 39, 40 Griffith, M. T., 264 Grigg, A., 66, 67 Grimes, J. M., 174 Grisotto, M. G., 128, 201, 204 Gronborg, M., 332, 333 Groom, C. R., 400 Groom, J., 60 Grossfield, A., 273 Group, S. C., 58 Grove, E. A., 92 Gruijthuijsen, Y. K., 153, 160, 165 Grundner-Culemann, K., 332, 333, 342 Guerrero, L. J., 118 Guetta, E., 78 Guimond, M., 69 Guise, T. A., 401 Gulino, A. V., 63, 317 Gulizia, R. J., 24 Gunera-Saad, N., 317 Gunthel, C. J., 127 Guo, H. G., 128 Gupta, N., 341 Gupta, P. B., 10

Gutensohn, K., 67 Gutierrez, A., 359 Gutie´rrez, L., 239 Gutierrez, N. C., 59 Gutkind, J. S., 125, 127, 128, 130, 131, 132, 134, 135, 137, 138, 139, 140, 141, 143, 153 Guy, H. R., 361 Gygi, S. P., 342 Gysemans, C., 201 H Haas, R., 401 Haas, W., 342 Habler, L., 59 Hackett, N. R., 63 Hagen, D. C., 402 Hagen, H., 174 Hahn, G., 166 Halaas, J. L., 290 Hall, S. E., 267, 269, 270, 272, 273, 274, 285 Ham, A. J., 210, 315, 317, 318, 319 Hamada, J., 59 Hamilton, D., 46 Hammerschmidt, W., 165 Han, Y., 92 Hanahan, D., 198 Handel, T. M., 174, 194, 211, 212, 291, 305, 331, 333 Handgretinger, R., 78 Handyside, A., 49 Hanenberg, H., 77 Hangoc, G., 61, 63, 64, 67, 76 Hanniman, E. A., 290, 291, 302, 304, 305, 306 Hansell, C., 239 Hansell, C. A., 261 Hanson, M. A., 264, 400 Hanyaloglu, A. C., 359, 414 Hardan, I., 59 Hardwick, A., 66 Hardy, K., 49 Hargreaves, D. C., 198 Haribabu, B., 60, 236, 237, 238, 240, 241, 402, 408 Harirchian, P., 269, 270 Harkins, L., 152 Harriague, J., 60, 63, 317 Harris, L. N., 118 Harrison, D. E., 74, 76 Harrison, J. K., 211 Harrison, L. C., 200 Harrison, P., 39 Hartmann, T. N., 60 Harvey, R. P., 60 Haseloff, R. F., 338 Hattori, K., 63

432 Haug, J. S., 65 Havel, P. J., 290 Hawley, R. G., 65 Hawley, T. S., 65 Haworth, B., 21, 28, 30 Hayden, M. S., 143, 145 Haylock, D. N., 64, 65, 74 Hayter, P., 39 Hayward, G. S., 134 Hazelton, B., 65 He, L., 381, 384 He, T. T., 92 He, Y., 128, 131, 132, 134, 135 Heard, J. M., 60, 401 Hebert, C. A., 358, 400 Hedin, K. E., 379, 380, 381, 382, 384, 385, 386, 388, 391, 392, 395 Hedrick, J. A., 203 Heifetz, A., 267, 269 Heike, T., 78 Heissig, B., 63 Heitman, J., 402 Helenius, A., 364 Hellerstrom, C., 197 Henderson, A., 232, 239 Henderson, N., 48 Henderson, R., 264 Hendricks, D., 65 Hendy, J., 58, 60 Hengel, H., 166 Henon, P. R., 66 Henriksson, M. L., 107, 108, 117 Hensbergen, P., 332 Henson, G. W., 63, 67 Herbert, K. E., 64, 65, 74 Hermann, G. E., 92 Hermann, S., 60, 61 Hermans-Borgmeyer, I., 291 Hermey, G., 291 Hermine, O., 63, 317 Hernandez, J. M., 59 Hernandez, P. A., 63, 317 Herren, S., 210, 212 Herrmann, S. H., 60 Hershko, A., 414, 415 Hershkoviz, R., 78 Hersi, K., 419 Hess, D. A., 80 Hettich, R. L., 342 Hewgill, D., 381 Hewlett, L., 360, 368, 373 Hey, P. J., 291 Hibbitts, S., 359 Hibert, M., 267, 270 Hicke, L., 419 Hickman, I. J., 291 Hidalgo, A., 63 Higashino, F., 59

Author Index

Hildebrand, P. W., 264 Hill, C. M., 361, 401 Hill, D. A., 66 Hill, L. A., 160 Hillyer, T., 226 Hilsher, C., 128 Hilton, M. J., 60, 63, 66 Hioki, K., 78 Hipkin, R. W., 33, 195, 198, 204 Hiramatsu, H., 78 Hiramatu, K., 402, 408 Hiramoto, T., 270 Hirota, S., 60, 400 Hitchcock, C., 35 Hively, W. P., 131 Ho, A. D., 60 Ho, S., 70 Ho, S. N., 275 Ho, Y., 174, 184 Hochstrasser, M., 414, 415 Hoelig, K., 60 Hofmann, K. P., 264, 271 Hofmann, W., 51 Hogan, B., 196 Hogge, D. E., 73, 77 Hohm, S., 80 Holbrook, M., 19, 33, 34 Holig, K., 66 Holl, J., 153, 160, 162, 163, 165 Holland, E., 131 Holle, L., 66 Holm, C., 307 Holmes, K. L., 384 Holmes, W., 63, 359, 360 Holst, P. J., 162 Holt, M. S., 61, 67, 68, 69, 80 Holyoake, T. L., 78 Holzmann, S., 198 Homey, B., 128, 153, 196, 401 Hong, K. S., 292 Honjo, T., 63 Hooper, A. T., 128 Hooper, M., 49 Hopken, U. E., 154 Hopkins, A. L., 400 Hopkins, C. R., 371 Hopp, T. P., 178 Hori, T., 44, 264, 400 Horsch, K., 60 Hortobagyi, G. N., 416 Horton, R. M., 275 Horuk, R., 60, 92, 263, 264, 266, 358, 400 Hosokawa, M., 59 Hossfeld, D. K., 67 Hotamisligil, G. S., 291 Hou, Y., 33 Houtz, D. A., 154 Howard, C., 419

433

Author Index

Howley, P. M., 419 Hoxie, J. A., 63, 359, 360, 361 Hseuh, Y. P., 402 Hu, J., 128 Hu, T., 232 Huang, D., 92 Huang, W., 40 Huang, Y., 92, 401 Hubbard, M. J., 332 Hubbell, W. L., 265, 272 Hubel, K., 63, 67 Huber, T., 265 Huckle, W. R., 159 Hughes, R., 290 Hughes, S. H., 131 Hughes, T. L., 69 Huibregtse, J. M., 419 Hulshof, J. W., 160 Hummel, K., 67 Humphreys, T. D., 380, 381, 382, 384, 385, 386, 388, 391, 392, 395 Humphries, R. K., 74 Hunerliturkoglu, A., 67 Hung, M. C., 416 Hunt, D. F., 338 Hunt, H. D., 275 Hunter, S, 49 Hunter, T., 332, 381 Hutchins, C., 66 Huttenrauch, F., 362 Hylander, B. L., 118 I Igishi, T., 139 Iida, K., 292 Iizasa, H., 60, 400 Iizawa, Y., 367 Ijzerman, A. P., 264 Ikawa, M., 195 Illmer, T., 60 Imai, K., 59, 290 Imberti, L., 63, 317 Imhof, A., 240 Imoto, H., 367 Inbal, B., 267 Ince, T. A., 118 Infante, B., 128 Infantino, S., 60 Ingham, R. J., 419 Ingram, D. A., 73 Inoue, K., 270 Irvine, B., 17, 19, 20, 22, 24, 26, 29, 30, 33, 36, 39, 40, 46 Irvine, R., 24, 36, 39 Isaacs, N., 245 Isidro, I. M., 59 Isin, B., 273

Issafras, H., 361 Ito, M., 78 Ito, Y., 290 Itoh, H., 290 Itoh, K., 290 Ivanova, N., 61, 66 Iwashita, T., 65 Iyer, C. V., 61, 63 Izac, B., 77 J Jaakola, V. P., 264 Jackson, D. G., 240 Jacobe, H., 291 Jacobsen, S. E., 76 Jaffe, H. W., 127 Jagannath, S., 65 Jala, V. R., 236, 237, 238, 240, 241 Jalil, A., 69 James, I., 17 Jamieson, T., 213, 236, 247 Janetopoulos, C., 381 Janeway, C. A., Jr., 195 Jankowski, K., 60, 63 Jansson, C. C., 29 Jares-Erijman, E., 380, 383 Jarrier, P., 69 Javitch, J. A., 264, 271 Jeffery, R. W., 290 Jenh, C. H., 128, 153, 196 Jenkins, N. A., 165 Jenkinson, S., 33, 34 Jensen, K. K., 128, 195, 198, 203, 204 Jensen, O. N., 332, 333, 338, 339, 342 Jestice, K., 65 Jham, B. C., 128 Ji, C., 44, 45 Ji, H., 210, 211 Ji, Y., 128, 141, 143 Jiang, G., 381 Jiang, J., 213 Jiang, S. Y., 68 Jiang, X., 338 Jin, P., 80 Jin, T., 381 Joazeiro, C. A., 419 John, H., 291 Johnson, G. L., 159 Johnson, Z., 174, 194, 210, 211, 212 Johnston, D., 290 Johnston, J. B., 174 Jones, D., 60 Jones, M., 361 Jones, R., 20, 38, 43, 48 Jones, T. R., 153, 159 Jongejan, A., 154 Jordan, C. T., 74, 76

434

Author Index

Jorgensen, T. J., 338 Jovrin, T. M., 380, 383 Jowett, J., 292 Jun, H. S., 200 Jund, R., 404 Jung, A., 107, 108, 117 Jung, S., 239 Jung, Y., 59 K Kabisch, H., 67 Kadi, L., 92 Kaji, H., 292 Kajumo, F., 21, 45, 46 Kakonen, S. M., 401 Kalani, M. Y., 270 Kalid, O., 267 Kalinkovich, A., 59 Kall, L., 342 Kalume, D. E., 332 Kam, V. W. T., 270 Kamon, J., 290 Kandel, G., 66 Kang, Y., 401 Kanjanapangka, J., 269, 270 Kanz, L., 333, 401 Kanzaki, N., 367 Kao, W. M., 63 Kaplan, M., 128 Kappes, J. C., 326 Kaptein, S. J., 165 Karber, G., 296 Kardash, E., 60 Karin, M., 106, 107, 145 Karnoub, A. E., 10 Karpova, T. S., 384 Kaspler, P., 59 Kasuga, M., 292 Kataoka, Y., 60, 400 Katayama, Y., 63 Kato, I., 77 Katoh, K., 292 Katona, R., 166 Katz, A., 77 Kauer, J. A., 240 Kaufer, B., 165 Kauffman, M., 269 Kaufman, R. J., 51 Kawabata, K., 60, 400 Kawahata, M., 78 Kawai, T., 63 Kazmierski, W., 33, 34 Keane, M. P., 4, 118 Keen, J. H., 360, 415, 416, 417, 419, 420 Keighley, W., 39 Kelleher, S. P., 118 Kelley, K., 128

Kelvin, D. J., 174, 176, 187, 211 Kenakin, T., 33, 34 Kennedy, G., 66 Kennedy, P. E., 60, 401 Kenyon, J. C., 174 Kerjaschki, D., 232, 239, 361 Kerob, D., 63, 317 Kerscher, O., 414, 415 Kershaw, T., 357 Ketas, T., 21, 45, 46 Khan, A., 59, 69, 72 Khan, M. Z., 92 Kho, T., 200 Khorana, H. G., 51, 265, 272 Khuu, H., 80 Kidd, G., 92 Kidley, N. J., 273 Kiel, M. J., 58, 65 Kiger, A. A., 58 Kikutani, H., 60, 400 Kim, D. E., 353 Kim, J. B., 292 Kim, P. S., 134, 213 Kim, S., 341 Kim, Y. J., 264 King, A. G., 65, 74, 76 King, M., 78 King, P. H., 152 Kinsley, D., 198 Kinsley, D. J., 203 Kipps, T. J., 333, 334 Kirchhoff, F., 154 Kirilovsky, A., 107, 117 Kish, J., 92 Kishimoto, T., 60, 400 Kita, S., 290 Kitamura, Y., 60, 400 Kitazawa, R., 292 Kitazawa, S., 292 Kivisa¨kk, P., 92 Kiyoizumi, T., 197 Kjellen, L., 210 Klaege, K. L., 92 Klasse, P. J., 63, 359, 360 Kledal, T. N., 135, 153, 154, 155, 156, 159, 160 Kleinschmidt, A., 70, 72 Klemm, C., 338 Klemm, L., 63 Klip, A., 240 Klotman, M. E., 63, 317 Knight, M. C., 59 Knight, Z. A., 128 Knowles, D. M., 127, 134 Knutson, J. R., 384 Kobayashi, K., 78 Kobayashi, M., 59 Kobbe, G., 67

435

Author Index

Kobilka, B., 264, 271 Kobilka, B. K., 264, 271, 272, 400 Kobilka, T. S., 264, 400 Kochanny, M., 270 Koehne, G., 67 Koenen, R. R., 60 Koga, R., 290 Koh, A., 118 Kohara, H., 59 Kohn, W., 61, 63 Kohout, T., 360 Koh-Paige, A. J., 59 Kolattukudy, P. E., 154, 159 Kolb, H., 200 Kolb-Bachofen, V., 200 Kolchinsky, P., 51 Kollet, O., 58, 59, 78 Kominami, K., 195 Kondo, H., 65, 76, 77 Kondru, R., 44, 45 Kooi, M. L., 73 Kooistra, T., 60 Koovakat, S., 270 Kopp, J., 212 Koprunner, M., 401 Korbutt, G. S., 197 Korenstein-Ilan, A., 59 Kosco-Vilbois, M. H., 194, 210, 212 Koshimoto, T., 60 Kostas, S. A., 294 Kostenko, V., 92 Koszinowski, U. H., 165, 166 Kotb, M., 78 Kotchetkov, R., 152 Kottmann, A. H., 60, 400 Koup, R. A., 401 Kouyama, T., 264 Kowalak, J. A., 342 Koyanagi, Y., 78 Kozasa, T., 143 Krause, E., 338 Krauss, N., 264 Kremer, K. N., 379, 380, 381, 382, 384, 385, 386, 388, 391, 392, 395 Kremmer, E., 70, 72 Kriehuber, E., 232, 239 Kristiansen, K., 265 Krivacic, K., 92 Kroenke, M., 91 Kroger, N., 67 Krohn, R., 60 Kronenberg, H. M., 59 Kronenwett, R., 401 Kronheim, S. R., 178 Kroschinsky, F., 60, 66 Krystek, S., 266 Kucia, M., 60, 63 Kuhmann, S., 21, 45, 46

Kuhn, P., 264 Kuhnl, P., 67 Kuijpers, T. W., 92 Kuller, L. H., 290 Kumar, A., 379, 380, 381, 382, 384, 385, 386, 388, 391, 392, 395 Kumar, C., 342 Kumasaka, T., 44, 264, 400 Kunkel, S. L., 201, 204 Kuo, C. J., 60 Kuo, P. C., 118 Kuroda, M., 60, 400 Kurowska-Stolarska, M., 239 Kurrer, M. O., 240 Kutzleb, C., 291 Kwon, D., 361 Kwon, N. S., 200 L Labrecque, J., 29 Labroli, M. A., 33 Lachowicz, J., 33 Lacroute, F., 404 Lacy, L., 196 Lagace, D. C., 306 Lagane, B., 60, 63, 317 Lagerstrom, M. C., 60 Laghi, L., 105 Lagorce-Pages, C., 107, 117 Lahav, M., 59 Lahey, R., 80 Lai, M., 107 Lajemi, M., 118 Lakowicz, J. R., 381 Lakso, M., 49 Lalani, A. S., 174, 175, 176, 187, 211, 213 Landau, N. R., 232, 237 Lander, E. S., 143 Landua, S., 68 Landwehr, S., 166 Lane, J. R., 264 Lane, T. A., 66 Lane, T. E., 91 Laney, A. S., 127 Lang, J., 29 Langdon, S. P., 10 Lange, A., 61 Langston, M. A., 342 Lansdorp, P. M., 73, 74 La Perle, K. M., 128 Lapidot, T., 58, 60, 77, 78 Large, V., 307 Larochelle, A., 77 Larsen, M. R., 338, 339 Lassmann, H., 92 Latger-Cannard, V., 63, 317 Lau, E. K., 174, 194, 211, 212

436 Lau, G., 29 Lau, P., 92 Laub, L., 65 Laufs, S., 80 Laurent, L., 63, 153, 159, 317 Lauri, E., 232, 233 Law, P., 60, 62, 66 Lazarini, F., 92 Le, T. I., 264 Leach, M. W., 128, 153, 196 Lear, C. H., 117 Lebbe, C., 63, 317 Lebon, P., 92 Lee, B., 361 Lee, C. S., 342 Lee, E., 49 Lee, F., 127 Lee, H., 118 Lee, H. S., 200 Lee, J. C., 92 Lee, K., 78 Lee, L. S., 130 Lee, S. H., 200 Lefkowitz, R. J., 154, 237, 238, 264, 414, 419 Legler, D. F., 60, 401 Lehman, L. A., 160 Leiber, M., 142 Leibowitz, M. D., 291 Lemieux, M. E., 73 Lemischka, I. R., 61, 66 Leng, L., 60 Lepers, M., 66 Le Poul, E., 291, 361 Leslie, A. G., 264 Letafat, S., 39 Letexier, D., 307 Le Trong, I., 44, 400 Leung, H., 60 Leung, R. K., 294 Leung, T., 401 Leurs, R., 153, 154, 155, 156, 160, 162, 163, 165 Lever, R., 210, 212 Levesque, J. P., 58, 60, 63, 64, 65, 74 Levoye, A., 63, 317 Levy, F. O., 358 Lewin, A. C., 198 Lewis, B. C., 131 Lewis, M., 24, 40, 43, 44, 46 Ley, T. J., 67 Li, J., 264 Li, L., 80 Li, M., 60, 91, 92 Li, W., 419 Li, X., 61, 63, 64, 67, 76, 213 Li, Y., 128, 131, 132, 134, 135 Li, Y. M., 416 Liang, H., 66 Liang, M., 270

Author Index

Lider, O., 59 Lie, Y. S., 40 Lightfoot, S., 142 Li Jeon, N., 327 Like, A. A., 200 Liles, W. C., 61, 63, 64, 67, 76 Lilleby, K., 65 Lim, C. S., 419 Lim, H. D., 162 Limoli, K. L., 40 Lin, H., 21, 28, 30 Lin, K. K., 65 Linch, D. C., 66 Link, D. C., 60, 63, 66, 68, 69, 80 Link, H., 66 Linta, L., 166 Linton, G. F., 63 Lipp, M., 70, 72, 154, 198 Lipsky, P. E., 381, 384 Lira, S. A., 128, 153, 193, 195, 196, 198, 200, 201, 203, 204, 213, 232, 233, 236, 238 Littman, D. R., 60, 239, 361, 400 Litwin, V., 401 Liu, F., 60, 63, 66 Liu, G., 361 Liu, H., 342 Liu, J., 33 Liu, L., 92, 209, 213, 232 Liu, L. Y., 174, 175, 176 Liu, R., 401 Liu, S., 118 Liu, T., 342 Liu, Y., 317, 319, 326, 328, 380 Liu, Y. J., 70 Livak, K. J., 304 LiWang, P. J., 156, 160, 194 Llera, A. S., 118 Locati, M., 105, 107, 117, 231, 232, 233, 235, 236, 237, 238, 239, 240, 241, 246 Loetscher, M., 60, 401 Lofsness, K. G., 63 Lokeshwar, V. B., 119 Lollmann, B., 291 Lombardi, G., 239 Long, F., 60, 63, 66 Lopez, A., 92 Lopez, S., 68, 69, 80 Lopez, T., 198 Lortat-Jacob, H., 62, 63 Loskutoff, D. J., 290 Lou, Q., 61, 63 Louache, F., 69 Loverre, A., 128 Lu, B., 107 Lu, M., 92 Lu, Z., 60, 61 Lucas, A., 174, 175, 176, 209, 211, 213 Lucchinetti, C. F., 92

437

Author Index

Luckow, B., 359, 362, 364 Lu¨deke, S., 265 Lue, H., 60 Luescher, I., 388, 390 Luini, W., 291 Lukens, J. N., 63, 317 Luna-Vargas, M. P., 415 Lundin, L. G., 60 Luo, Y., 239 Luske, A., 165, 166 Lusso, P., 359 Luster, A. D., 60, 61, 185, 188 Luther, M. A., 63, 359, 360 Luther, S. A., 198 Lynch, D. M., 165 Lyons, B. L., 78 M Ma, Q., 60 Macartney, M., 17, 19, 20, 22, 24, 26, 29, 30, 33, 36, 39, 40, 46 Macauley, C., 209, 213 MacCoss, M. J., 342 Macdonald, G. A., 291 MacDonald, R., 388, 390 MacDougald, O. A., 292 Macek, B., 342 Macen, J. L., 174, 175, 176, 211 Macfarland, R., 67 MacGrath, M., 66 Mack, M., 210, 212, 359, 360, 361, 362, 364, 367, 371 Maddon, P. J., 401 Magerus, A., 59 Maggio, G., 128 Magid, M., 59 Maguer-Satta, V., 78 Mahabaleshwar, H., 60 Mahad, D., 92 Mahad, D. J., 92 Mahalingam, M., 265 Maher, D., 67 Mahmoud, N. G., 28 Maier, P., 80 Mailman, R. B., 264, 271 Majmudar, A., 92 Majorana, A., 291 Maki, T., 197 Malech, H. L., 63 Malhotra, M., 291 Malim, M. H., 63 Manders, P. M., 92 Mandrup, S., 292 Manfra, D. J., 128, 153, 196, 198, 203, 204 Manfredi, J. P., 402, 408 Mangada, J., 78 Manischewitz, J., 416

Mann, M., 332, 333, 342 Manning, B. D., 128 Manning, G., 332 Mansfield, R., 17, 19, 33, 34 Mantovani, A., 4, 105, 106, 107, 117, 231, 232, 233, 235, 236, 237, 238, 239, 240, 241, 246, 291 Many, A., 59 Mao, A., 269, 270 Mao, H. C., 69 Marantz, Y., 267, 269 Marburger, T. B., 69 Marcenaro, E., 291 March, C. J., 178 March, M., 364 Marchese, A., 60, 69, 360, 413, 414, 415, 416, 417, 419, 420 Marco, E., 105 Marcus, R. E., 65 Marfella, R., 291 Margalit, R., 59 Margulies, B. J., 154 Mariage-Samson, R., 118 Marincola, F. M., 80 Markey, S. P., 342 Marmon, S., 361, 401 Marrelli, S., 291 Marsh, M., 63, 154, 159, 357, 359, 360, 361, 362, 364, 365, 367, 368, 371, 373, 375 Marti, W., 175 Martin, A. P., 128, 193, 198, 200, 201, 204 Martin, D., 125, 128, 138, 141, 143 Martin, R. P., 59 Martin, S. R., 401 Martinez, A. C., 60 Martinez, M. A., 359 Martinez de la Torre, Y., 232, 233, 238, 247 Martinez-Mayorga, K., 273 Martinez-Munoz, L., 60 Martini, L., 162 Marullo, S., 361 Maruyama, M., 66 Masilamani, S., 341 Massague, J., 401 Massardi, L., 291 Massardi, M. L., 237, 239, 240, 291 Masuda, T., 290 Mathieu, C., 201 Mathys, S., 165 Matloubian, M., 198 Matsubara, A., 65, 76, 77 Matsuchima, K., 400 Matsuda, A., 419 Matsushima, K., 60, 201, 358, 400 Matsuura, H., 270 Matsuyama, T., 290 Matthiesen, R., 342 Mattison, K., 153, 165

438 Maurer, D., 232, 239 Mausbacher, N., 332, 333, 342 Maussang, D., 151, 153, 162, 163 Maynard, D. M., 342 Mayo, S. L., 268 Mazzolari, E., 63, 317 Mbamalu, G., 419 McAllister, S. S., 118 McCaffrey, G., 402 McCarthy, T. C., 290, 291, 302, 304, 305, 306 McCarty, J. M., 58, 59, 67, 68 McCauley, L. K., 59 McClanahan, T., 401 McCleland, M. L., 338 McCombie, S. W., 21, 33, 45, 46 McCoy, J., 60 McCredie, K., 317 McCulloch, C., 245 McCulloch, C. V., 246, 248, 249, 250, 251, 253, 256 McDonagh, E. M., 415 McDonald, I. K., 274 McFadden, G., 174, 175, 176, 184, 187, 188, 194, 209, 211, 212, 213 McFadyen, L., 20, 38, 43, 48 McFarland, K., 68, 69, 80 McGlauchlen, K., 68, 69, 80 McGrath, K. M., 67 McIlhinney, R. A., 154, 155 McIvor, D., 209 McKeating, J. A., 28 McKenzie, J. L., 78 McKimmie, C. S., 239 McKnight, A., 361 McKoy, J. M., 59 McLean, A. J., 361 McLean, K. A., 162 McLean, P., 213, 236, 245 McLeod, R. S., 306 McMaster, B. E., 60 McMillan, J., 292 McNally, J. G., 384 Mead, L. E., 73 Mealiffe, M., 66 Meatchi, T., 107 Meder, W., 291 Megill, J. R., 198 Meguro, K., 367 Meiser, A., 415 Melikian, A., 60 Mellado, M., 60 Mello, C. C., 294 Menge, W. M., 154 Menzel, W., 142 Meraviglia, S., 235, 239 Mernaugh, R. L., 210, 315, 317, 318, 319 Mertens, T., 153, 154, 160, 165, 166 Merzouk, A., 60, 62

Author Index

Meshel, T., 3 Mesirov, J. P., 143 Mesri, E. A., 127, 128, 130, 137, 140, 141, 153 Messerle, M., 165, 166 Mestas, J., 4, 118 Metcalf, D., 64 Methner, A., 291 Metzgar, R., 317 Meucci, O., 92 Meyer, D., 401 Meyer, M., 291 Miao, Z., 60 Micali, G., 127, 134 Michejda, C. J., 360 Michel, D., 151, 153, 160, 162, 163, 165 Michelson, S., 153, 159 Middleton, D., 20, 38, 43, 48 Migeotte, L., 291 Miki, T., 139 Mikolaenko, I., 152 Milano, S. K., 414 Milasta, S., 246, 251, 254, 255 Miller, C. L., 73 Miller, K., 17, 371 Miller, K. J., 264, 271 Miller, L., 65, 213 Miller, L. H., 358, 400 Miller, R. H., 92 Miller, R. J., 92 Miller, W. E., 154, 155 Miller, W. R., 10 Milligan, G., 246, 251, 254, 255, 361 Milligan, L. L., 134 Mills, J., 17, 24, 36, 39, 46 Milner, L. A., 59 Milotic, I., 165 Minina, S., 60 Minisini, R., 154, 165 Minokoshi, Y., 290 Minson, A. C., 174, 175, 176, 179, 194, 195 Miotti, S., 118 Mirjolet, J. F., 291 Mirolo, M., 105, 236, 240, 241 Mirzabekov, T., 51 Mirzadegan, T., 44, 45 Misteli, T., 348 Miyano, M., 44, 264, 400 Miyata, H., 139 Mlecnik, B., 107, 117 Moepps, B., 60, 154, 165 Mohanty, P., 269 Mohar, A., 401 Mohle, R., 333, 401 Mohler, K., 174 Mokros, T., 154 Molday, R. S., 51 Molidor, R., 107

439

Author Index

Molina, H., 332 Molinari, A. M., 291 Molineux, G., 61, 66 Molinolo, A., 128, 131, 132, 134, 135 Mollard, C., 118 Mollereau, C., 291 Monaco, A. P., 197 Monini, P., 127 Monk, M., 49 Montaner, S., 127, 128, 131, 132, 134, 135, 137, 138, 140, 141, 143 Montgomery, M., 65 Montgomery, M. K., 294 Moon, J., 63 Moore, C. A., 414 Moore, J. P., 401 Moore, M. A., 63, 401 Moore, P. S., 127 Mootha, V. K., 143 Moratto, D., 63, 317 Moretta, A., 291 Moretta, L., 291 Morgello, S., 92 Mori, J., 19, 20, 22, 24, 26, 29, 30, 33, 38, 40, 43, 44, 46, 48 Morimoto, J., 201 Morita, Y., 65, 76, 77 Moritz, T., 77 Morris, A., 107, 117 Morris, E. S., 66 Morris, K., 127 Morrison, S. J., 58, 65 Morrow, V., 246, 251, 254, 255 Mortensen, P., 342 Morton, J., 66 Moser, B., 60 Moser, K., 341 Mosi, R., 29 Mosier, D. E., 24 Mosley, A. L., 342 Mosley, M., 19, 24, 33, 34, 40, 43, 44, 46 Mossman, K., 174, 176, 187, 211 Motoshima, H., 44, 264, 400 Motoyama, A., 340 Moubayed, M., 66 Moukhametzianov, R., 264 Mourits, S., 201 Moyer, R. W., 174, 175, 176, 211, 213 Mozobil, 59, 67 Mueller, A., 28, 415 Mueller, L. N., 338 Mueller, M., 338 Mueller, O., 142 Mukherjee, S., 143 Mullen, M., 66 Mullen, P., 10 Muller, A., 401 Mu¨ller, M., 92

Mumby, M., 340, 341 Mundell, S. J., 60 Munuswamy-Ramanujam, G., 209 Murakami, M., 264 Muranyi, W., 165 Murdoch, B., 77 Murphy, E., 401 Murphy, P. M., 19, 33, 63, 118, 160, 174, 175, 176, 194, 358, 400 Murray, J. L., 402 Murrell-Lagnado, R. D., 240 Muruganandan, S., 290, 291, 302, 304, 305, 306 Mutlu, A. D., 128 Muzio, M., 106, 107 Muzio, V., 210, 212 Myszka, D. G., 35 N Nabors, L. B., 152 Nachtigal, M. W., 306 Nademanee, A., 67 Nador, R. G., 134 Naeem, R., 10 Nagasawa, T., 59, 60, 400 Nagashima, K. A., 401 Nagler, A., 59, 60, 61, 62, 78 Nagpal, S., 291 Nakahata, T., 78 Nakamoto, B., 62, 63 Nakamura, M., 290 Nakanishi, T., 195 Nakauchi, H., 65, 76, 77 Naor, Z., 267 Napier, C., 17, 19, 20, 22, 24, 26, 29, 30, 33, 34, 40 Nappo, F., 291 Narula, S. K., 128, 153, 196 Narumi, S., 201 Nasca, M. R., 127, 134 Nation, P., 211 Naumann, N., 63 Navenot, J. M., 402, 408 Navis, M., 153, 160 Navratilova, I., 17, 35 Nazareno, D., 33 Nazarian, S. H., 174 Neamati, N., 59 Nebuloni, M., 231, 232, 233, 235, 238, 239 Nedjai, B., 269, 270 Neel, N. F., 210, 315, 317, 318, 319 Negus, R., 107, 117 Nelson, C. A., 194 Nelson, C. D., 154 Nelson, D. L., 63, 317 Nelson, J., 65 Nelson, J. A., 153, 165 Nelson, P. J., 359, 362, 364

440

Author Index

Neptune, E. R., 327 Nerl, C., 70, 72 Nervi, B., 57, 60, 67 Ness, T. L., 174, 175, 176, 211 Netzer, N., 59 Neupogen, 66 Ni, J., 240 Nibbs, R. J., 213, 232, 236, 237, 239, 240, 245, 246, 247, 248, 251, 254, 255, 261 Nicastri, E., 127 Nicholas, J. F., 63 Nichols, A., 290, 291 Nichols, D. E., 264, 271 Nicolai, J., 92 Nicolaidou, V., 269, 270 Nicolas, J. F., 317 Nicolini, F., 78 Niedergang, F., 361 Niemann, D., 92 Nijman, S. M., 415 Nikolaev, O., 381 Nikolic, T., 201 Nilsson, M., 92, 107 Nishikawa, S., 60, 400 Nishikawa, Y., 367 Nishimune, Y., 195 Nishimura, O., 367 Niv, M. Y., 273 Nixon, C., 213, 236 Noble, W. S., 342 Noda, M., 59, 290 Noiman, S., 267, 269 Nolta, J. A., 80 Nomiyama, H., 4 Nonaka, Y., 270 Norton, J. A., 175 Notarangelo, L. D., 63, 317 Novotny, E. A., 137 Nudelman, R., 269 Nuovo, G. J., 69 O Oakley, C. L., 199 Oberg, A., 107, 108, 117 Oberlin, E., 60, 401 O’Bryan, S., 92 Ocio, E. M., 59 Oelschlaegel, U., 60, 66 Offermann, M. K., 127 Offord, R. E., 24 Ogawa, Y., 367 Ogbureke, K. U., 118 O’Hara, M., 237, 240 O’Hayre, M., 331, 333 Ohyama, T., 291, 305 Oikawa, Y., 201 Oishi, S., 399

Okabe, M., 195 Okada, T., 44, 264, 400 Okamoto, M., 367 Okamoto, Y., 49 Okayama, H., 162 Okimura, Y., 292 Okonogi, K., 367 Olafson, B. D., 268 Old, L. J., 107 Oldridge, J., 63, 359, 360 Olsen, D. B., 92 Olsen, J. V., 342 Olson, D. P., 59, 384 Olson, E. N., 136 Olsson, T., 92 Olszak, I., 60, 61 Omagari, A., 402, 408 Omatsu-Kanbe, M., 270 Ong, S. E., 332, 333, 342 Opalenik, S. R., 317 Oppenheim, J. J., 4, 358, 400 Oppermann, M., 154, 360, 362, 364, 367, 368, 373 Oprian, D. D., 51 Or, R., 59 Orci, L., 290 Ordemann, R., 66 O’Reilly, T., 60 Orimo, A., 10 Orlicky, D. J., 300 Orschell, C. M., 61, 63, 64, 67, 73, 76 Orsini, M. J., 60 Orsulic, S., 131 Orth, A., 419 Osman, N. I., 59 Osterrieder, N., 165 Otero, K., 63, 237, 239, 240, 317 Otto, C., 154 Otto, S., 338 Ou, C. Y., 127 Overvoorde, J., 381 P Paavola, C., 212 Pablos, J. L., 63, 317 Padovani-Claudio, D. A., 92 Pagani, M., 117 Page, C., 210, 212 Pages, F., 107 Paing, M. M., 69, 414 Palani, A., 21, 33, 45, 46 Palczewski, K., 44, 264, 400 Palframan, R. T., 239 Palike, H., 117 Palmer, P., 65 Palmieri, C., 127 Palmqvist, R., 107, 108, 117

Author Index

Pan, W. H., 348 Pan, Y., 416 Panageas, K. S., 107 Pandey, A., 332, 333 Pandey, M., 290 Paniyadi, J., 198 Pantanowitz, L., 127 Panzer, U., 48 Papayannopoulou, T., 58, 62, 63 Paradela, A., 333, 338, 341 Pardo, C. A., 92 Parent, D., 232, 239 Parent, J. L., 60 Parenza, M., 118 Parera, M., 359 Parish, C. R., 210 Park, H. S., 67 Park, J. H., 264 Park, L., 174 Park, M., 240 Parkin, N. T., 40 Parlee, S. D., 290, 291, 302, 304, 305, 306 Parmentier, M., 17, 291, 292, 361 Parnot, C., 271, 272 Parolin, C., 60, 400 Parolini, S., 291 Parry, C. M., 174, 175, 176, 179, 194, 195 Parry, N., 213 Pashenkov, M., 92 Pasqualini, F., 231 Pasvolsky, R., 60 Patel, A., 107 Patel, M. M., 127 Patel, S., 291 Patel, V., 127, 128, 137, 140, 141 Pati, S., 128 Patterson, G. H., 380 Paulovich, A., 143 Pawson, T., 419 Paxton, W. A., 401 Payne, S. H., 335, 340, 341, 342, 343 Pease, J. E., 156, 174, 263, 415 Pease, L. R., 275 Pece, S., 137, 140 Peck, D., 107, 117 Pedley, R. B., 226 Pei, G., 402, 408 Peiper, S. C., 60, 399, 401, 402, 408 Peired, A. J., 63 Pelchen-Matthews, A., 63, 154, 159, 359, 360, 361, 364, 367, 368, 371, 373, 375 Peled, A., 59, 61, 62, 78 Pellett, P. E., 127 Pellicer, A., 130 Peltonen, J. M., 28 Pelus, L. M., 60, 62, 65, 74, 76, 80 Penfold, M. E., 60 Peng, S. B., 61, 63

441 Penick, E. C., 240 Perkins, H., 24, 36, 39 Peroni, O., 307 Perros, M., 17, 20, 24, 26, 35, 36, 38, 39, 40, 42, 43, 44, 46, 48 Perruccio, F., 20, 24, 36, 38, 39, 43, 46, 48 Pessin, M. S., 127 Peterson, J. W., 92 Petit, I., 59, 78 Petit, S. J., 415 Petropoulos, C. J., 24, 40, 44, 46 Pevzner, P. A., 340, 341 Pezzotti, P., 127 Pflumio, F., 77 Phair, R. D., 348 Philipsen, S., 239 Phillips, J. C., 271 Philpott, N. J., 141 Piatier-Tonneau, D., 118 Picard, L., 24, 361 Picarella, D. E., 195 Picchio, G. R., 24 Pichel, J. G., 49 Pickart, C. M., 414, 415 Pickford, C., 24, 36, 39 Pickup, D. J., 174 Pierce, K. L., 414, 419 Pihlavisto, M., 28 Pike, L., 353 Pilaro, A. M., 226 Pioro, E. P., 92 Piret, J., 78 Pirovano, S., 63, 317 Pitman, M. C., 273 Pittelkow, M. R., 63 Piwnica-Worms, D., 67 Planchenault, T., 63, 317 Platzbecker, U., 60 Pleskoff, O., 153, 162, 163 Plett, P. A., 61, 63, 64, 67, 73, 76 Plowman, G. D., 332 Podhajcer, O. L., 118 Pohjanoksa, K., 29 Poignard, P., 24 Pojda, Z., 61, 66 Pollard, D., 117 Pollard, J. W., 107 Pollok-Kopp, B., 362 Polyak, K., 10 Pomeroy, S. L., 143 Ponath, P. D., 232, 239 Ponomaryov, T., 59 Poole, L. J., 134 Poppe-Thiede, K., 66 Porta, C., 4 Power, C. A., 48, 210, 211, 358, 361, 400 Prada, F., 118 Premont, R. T., 414, 419

442

Author Index

Prentice, C. R., 290 Prevo, B., 240 Priestley, G. V., 62, 63 Primrose, J. N., 290 Prince, H. M., 64, 65, 74 Prins, J. B., 291 Prior, J. L., 67 Pristera, T., 127 Proost, P., 201 Proudfoot, A. E., 17, 48, 92, 174, 194, 210, 211, 359, 360, 361, 362, 364, 367, 371 Pruenster, M., 239 Prusoff, W., 158 Psaroudakis, G., 273 Pugliese-Sivo, C., 33 Puigserver, P., 292 Pullen, J. K., 275 Pullen, S., 34 Pulley, S., 61, 63 Punzel, M., 65 Purton, L. E., 74, 75, 76, 77 Pusic, I., 68 Putz, M. M., 174 Pyo, R., 203, 204 Q Qamhieh, H. T., 290 Qian, D., 67 Qian, W. J., 342 Qin, S., 232, 239 Quitoriano, M. S., 63 R Raaijmakers, J., 419 Raaka, E. G., 127, 128, 130, 137, 153 Radford, K. W., 127 Rafii, S., 63, 401 Ragg, T., 142 Rahill, B., 159 Raiborg, C., 360, 414, 415, 416, 417, 419, 420 Rajarathnam, K., 174, 176, 187 Rall, G., 66 Raman, D., 210, 315, 317, 318, 319, 326, 328 Ramani, N., 198 Ramezani, A., 65 Ramirez, P., 57, 67 Ramirez, P. A., 61, 67, 68 Ramos, M. J., 270 Ramsdell, A. K., 128, 137, 138, 143 Randolph-Habecker, J. R., 159 Rani, M. R., 92 Rani, R. M., 92 Ranieri, E., 128 Ransohoff, R. M., 60, 91, 92, 232 Rao, P., 91 Rapp, C. S., 271, 274 Rasmussen, S. G., 264, 400

Ratajczak, J., 60, 63 Ratajczak, M. Z., 60, 63 Ratnal, V. R. P., 271, 272 Ravazzola, M., 290 Ravid, R., 92 Rawlinson, W. D., 165 Ray, H., 307 Ray, P. E., 128, 131, 132, 134, 135 Raz, E., 60, 401 Rebel, V. I., 73 Reca, R., 60, 63 Reddy, V. A., 419 Reeves, J. D., 359 Regele, H., 361 Rehm, A., 154 Reichman-Fried, M., 60, 401 Reinhardt, F., 118 Reinhart, T. A., 156 Reitz, M., 128 Ren, D., 92 Ren, J., 80 Repasky, E. A., 118 Resnick, I., 59 Rettig, M. P., 57, 59, 61, 63, 67, 68, 69, 80 Reynolds, C. A., 273 Rezza, G., 127 Ribeiro, S., 269, 270 Riboldi, E., 291 Riboldi-Tunnicliffe, A., 245 Richards, A. A., 291 Richardson, A. L., 10 Richardson, R. M., 60 Richmond, A., 118, 210, 315, 317, 318, 319, 326, 327, 328, 347, 348 Richter, R., 291 Rickett, G., 17, 19, 20, 22, 24, 26, 29, 30, 33, 34, 35, 36, 39, 40 Rieth, C., 67 Rintelen, F., 210, 211 Ritchey, J. K., 61, 67, 68, 69, 80 Ritchie, A., 10 Robas, N., 24, 36, 39, 46 Robb, L., 64 Robbins, K. C., 137 Roberts, A., 66 Roberts, A. W., 64 Robichaud, J., 184, 188 Robinson, P. J., 338, 339 Robinson, S. N., 65 Robson, L., 226 Rockey, W. M., 270 Roden, R. B., 107 Rodenhuis, S., 73 Roderburg, C., 60 Rodger, E., 63, 67 Roepstorff, P., 338 Rogers, R. C., 92 Rognan, D., 267, 270

443

Author Index

Roh, S. G., 292 Rollins, B. J., 92, 198, 239 Romantseva, T., 416 Romero, P., 388, 390 Rommel, C., 210, 211 Ronnstrand, L., 307 Root, H., 17 Rose, M., 210, 212 Rosen, E. D., 292 Rosenbaum, D. M., 264, 400 Rosenkilde, M. M., 63, 135, 152, 153, 154, 155, 162, 359, 360 Rosenthal, J., 67 Ross, F. P., 60, 63 Ross, J. S., 290, 291 Ross, M. M., 338 Rossi, D., 106 Rossini, A. A., 200 Rot, A., 59, 194, 213, 232, 236, 237, 239, 240, 246, 247, 248 Roth, B. L., 264, 271 Rotstein, D., 44, 45 Rovin, B. H., 159 Rowley, S., 65 Rowlings, P. A., 67 Roychowdhury, S., 69 Royle, S. J., 240 Rozenberg, F., 92 Ruchti, F., 153, 165 Rucker, J., 291 Ruckle, T., 210, 211 Ruiz-Arguello, M. B., 174, 184, 185, 188 Rukavina, D., 232, 233, 238 Rumio, C., 118 Ruscetti, F., 317 Ruse, C. I., 340 Russo, R. C., 231 Rutt, C., 66 Ruzsics, Z., 165 S Sabbe, R., 24 Sadowska, M., 128 Sadygov, R. G., 342 Saelzler, M. P., 118 Saffrich, R., 60 Sage, E. H., 118 Sai, J., 210, 315, 317, 318, 319, 326, 327, 328 Sakmar, T. P., 265 Salanga, C. L., 331, 333 Salari, H., 60, 62 Salassa, B., 127 Salcedo, R., 4 Sale, H., 19, 33, 34 Salerno, A., 235, 239 Sali, A., 266, 269 Sallusto, F., 358

Salowsky, R., 142 Salvatierra, E., 118 Salwen, H. R., 118 Samad, F., 290 Samanta, M., 152 Samatova, N. F., 342 Samjanovich, S., 380 Sampaio, K. L., 166 Samson, M., 291 Samuel, S., 59 Sanchez-Cabo, F., 107, 117 Sandbank, J., 59 Sanders, J., 65 Sandler, S., 200 Sangaletti, S., 118 Sankuratri, S., 44, 45 San Miguel, J. F., 59 Sano, G., 198 Santamaria, P., 200 Santini, F., 360, 415, 416, 417, 419, 420 Santomasso, B., 127, 128, 130, 137, 153 Santoro, A., 291 Saraiva, M., 174, 184 Saran, N., 415 Sardiu, M. E., 342 Sarmati, L., 127 Saruta, T., 201 Sasaki, S., 292 Sasaki, Y., 76 Sasse, M. E., 92, 232 Satomi, S., 197 Sauer, B., 48, 49 Sausville, E. A., 127, 128, 134, 137, 140, 141 Savelkouls, K. G., 165 Savino, B., 231, 236, 240, 241 Savola, J. M., 29 Sawada, H., 367 Sawai, E. T., 127, 128, 131, 132, 134, 135, 137, 138, 140, 141, 143 Scadden, D. T., 58, 60, 61, 74, 75, 76, 77 Schaack, J., 300 Schaer, C. A., 240 Schaer, D. J., 240 Scheerer, P., 264 Scheffner, M., 419 Scheinin, M., 28, 29 Schena, A., 128 Schena, F. P., 128 Schertler, G. F., 264 Schiffman, K., 65 Schinke, B., 291 Schioth, H. B., 60, 400 Schipani, E., 59 Schleuder, D., 291 Schlondorff, D., 359, 361, 362, 364 Schlyer, S., 264, 266, 270 Schmelzle, K., 335, 344 Schmidt, A., 198

444 Schmittgen, T. D., 304 Schmitz, N., 66 Schneider, A., 59 Schneider, P., 67 Schober, A., 60, 210, 213 Schoedon, G., 240 Scholten, D. J., 156 Schooley, K., 174 Schottelius, A. J., 118 Schreiber, A., 151, 332, 333, 342 Schreiber, R. D., 107 Schroeder, A., 142 Schubel, A., 70, 72 Schulte, G., 358 Schulten, K., 273 Schutyser, E., 317 Schwartz, O., 60, 401 Schwartz, R. A., 127, 134 Schwartz, T. W., 63, 128, 135, 153, 154, 155, 156, 159, 160, 162, 359, 360 Schwartzberg, L., 65 Schwarz, M. A., 195, 198, 204 Schwarz, M. K., 210, 211, 270 Schwede, T., 212 Schyler, S., 269, 270 Scolnick, E. M., 160 Scott, C., 64 Scott, M. A., 65 Scott Worthen, G., 160 Scuderi, L., 127, 134 Sechler, J. M., 63, 128 Seckinger, A., 60 Sedat, J. W., 327 Sedgwick, J. D., 198 Sedmak, D. D., 159 Seeger, T., 80 Seet, B. T., 174, 184, 188, 211, 212, 213 Segal, B., 91 Segal, D., 292 Segal, R. A., 60 Segerer, S., 361 Seibert, C., 21, 45, 46 Seita, J., 65, 76, 77 Selchau, V., 269, 270 Sellebjerg, F., 92 Selvaraju, R., 92 Semerad, C. L., 60, 63 Sempek, D. S., 68 Serabian, M. A., 226 Serrano-Vega, M. J., 264 Servant, G., 327 Servitja, J. M., 128, 137, 138, 143 Seto, M., 367 Setoh, P., 361 Sewing, A., 39 Sexton, P. M., 264, 271 Sgroi, D. C., 10

Author Index

Shabanowitz, J., 338 Shacham, S., 267, 269 Shalekoff, S., 70 Shaner, N. C., 380, 384 Shang, L., 193, 198 Shannon, W. D., 68, 69, 80 Shapira, M. Y., 59 Shapiro, S., 33 Sharadendu, A., 269 Shargill, N. S., 291 Sharif, W. W., 203 Sharma, S. K., 226, 270 Sharron, M., 291, 361 Shaw, J. P., 48 Shelenkov, A. A., 268 Shellam, G. R., 165 Shen, H., 60, 61 Shen, M. Y., 266, 269 Shen, R. F., 341 Shenk, T., 175, 176, 184 Shenoy, S. K., 414, 416, 421 Shepard, L. W., 143 Sheridan, W. P., 67 Shi, W., 342 Shieh, J. H., 63 Shigihara, T., 201 Shilton, B., 184, 188 Shimada, A., 201 Shimizu, S., 92 Shin, J. W., 80 Shinder, V., 59, 194 Shindo, M., 59 Shinobu, N., 59 Shipman, M., 371 Shiraishi, M., 367 Shire, D., 273 Shizuru, J. A., 65, 69 Shokat, K. M., 128 Short, B., 60, 63 Short, S. T., 317 Shoshan, S., 59 Shu, H., 340, 341 Shu, W., 401 Shulman, Z., 60 Shultz, L., 59 Shultz, L. D., 77, 78 Sica, A., 106, 107, 117 Siciliano, S. J., 157 Siebert, F., 265 Siegel, P. M., 401 Sierro, F., 60 Sigel, R. M., 384 Signorelli, P., 237, 238, 239, 240 Signoret, N., 63, 357, 359, 360, 361, 362, 364, 365, 367, 368, 371, 373 Sikora, K., 92 Silverstein, S., 130

Author Index

Simas, J. P., 174, 175, 176, 179, 194, 195, 198, 204 Simmons, G., 359, 361, 362, 364 Simmons, P. J., 58, 60, 63 Simone, J., 381 Simpson, C. V., 237, 240, 261 Sims, O. L., 379 Sinal, C. J., 289, 290, 291, 302, 304, 305, 306 Singh, R., 184, 188, 211, 212 Sinzger, C., 166 Sireci, G., 235, 239 Sironi, M., 237, 239, 240, 291 Sitkoff, D., 266 Sixma, T. K., 415 Skolnick, J., 270 Skrabanek, L., 273 Slot, J. W., 374 Smailbegovic, A., 210, 212 Smit, M. J., 151, 152, 153, 154, 155, 156, 160, 162, 163, 164, 165 Smith, A. L., 68 Smith, C. A., 174 Smith, D., 40 Smith, E., 67 Smith, G. L., 174, 175, 176, 178, 179, 181 Smith, L., 226 Smith, M. J., 154, 156 Smith, P., 153, 165 Smith, R. D., 342 Smith, T. D., 174 Smith, V. P., 174, 175, 176, 179, 184, 185, 188, 194, 195 Smith-Burchnell, C., 19, 20, 22, 24, 26, 29, 30, 33, 40, 43, 44, 46 Smits, R. A., 162 Smolak, P. J., 174 Smolka, M. B., 335, 340, 341, 342, 343 Smrcka, A. V., 136 Snyder, D., 67 Snyder, P. M., 416, 421 Snyderman, R., 60 Sobolik-Delmaire, T., 210, 317, 318, 319 Sodek, J., 118 Soderberg-Naucler, C., 152, 153, 165 Sodhi, A., 127, 128, 131, 132, 134, 135, 137, 138, 140, 141, 143 Sodroski, J., 51, 60, 400 Sohngen, D., 67 Sole, J., 290, 291 Solinas, G., 4 Soloway, M. S., 119 Somlo, G., 67 Song, S. H., 292 Song, T., 342 Srensen, T., 92 Srensen, T. L., 92 Soresina, R., 63, 317 Soria, G., 3, 4

445 Soto, H., 401 Sousa, S. F., 270 Sozzani, S., 60, 63, 106, 107, 117, 201, 237, 239, 240, 291, 317 Spaltro, J., 294, 296 Speck, S. H., 174, 175, 176, 194 Spedding, M., 264, 271 Spiegel, A., 60, 78 Spiegelman, B. M., 291, 292 Spira, T. J., 127 Spits, H., 69 Spodsberg, N., 291 Spradling, A. C., 58 Sprague, G. F., Jr., 402 Springer, M. S., 157, 361 Springer, T. A., 60, 400 Srour, E., 73 Stahl, R. A., 48 Stallone, G., 128 Stangassinger, M., 359, 361, 362, 364 Stauber, R. H., 360 Staugaitis, S. M., 92 Stebler, J., 401 Steen, H., 332, 333 Steensma, R. W., 33 Stehouwer, C. D., 291 Stein, A., 67 Stein, E. J., 92 Stein, J. V., 316 Steinbach, P. A., 384 Steinmetz, O. M., 48 Stenkamp, R. E., 44, 264, 400 Stenling, R., 107, 108, 117 Stenmark, H., 360, 415, 416, 417, 419, 420 Sternweis, P. C., 136 Stevens, M. J., 273 Stevens, R. C., 264, 400 Stewart, C. A., 174, 175, 176, 179, 194, 195 Stiff, P. J., 67 Stine, J. T., 359 Stinson, V. L., 290 Stockdale, M., 24, 40, 43, 44, 46 Stocker, S., 142 Stockerl-Goldstein, K. E., 68 Stockschlader, M., 67 Stoebenau-Haggarty, B., 361 Storb, R., 65 Stordeur, P., 291 Storelli, S., 156 Storey, J. D., 342 Strange, P. G., 21, 28, 30 Streblow, D. N., 153, 156, 165 Stremler, M., 327, 328 Strieter, R. M., 4, 92, 118 Strittmatter, E. F., 342 Strizki, J. M., 29, 30, 33 Stroncek, D. F., 80 Stropes, M. P., 154, 155

446

Author Index

Strupeck, J., 67 Struyf, S., 4 Stryer, L., 381, 382 Stuart, D. I., 174 Studts, J. M., 194 Stukenberg, P. T., 338 Stupple, P., 20, 38, 43, 48 Su, Y., 317 Subramanian, A., 143 Sudarsanam, S., 332 Sugamura, K., 78 Sugihara, M., 264 Sugiyama, T., 59 Sullivan, A., 10 Sullivan, L., 128, 153, 196 Sultan, H., 24, 36, 39 Summers, B. C., 60 Sun, C., 118 Sun, L., 153, 159 Sun, Y. Z., 59 Sung, J., 69 Sunnemark, D., 92 Sunshine, M. J., 60 Sutherland, H. J., 73 Sutton, R. E., 401 Suzue, K., 78 Swaminath, G., 271, 272 Swanberg, S. L., 60 Sweeney, E. A., 62, 63 Swerdel, M. R., 198 Swofford, R., 384 Symons, J. A., 174, 175, 176, 178, 179, 181 Sypula, J., 174 Szalkowski, D. M., 291 Szer, J., 66, 67 Szilvassy, S. J., 74 Szollosi, J., 380, 388, 390 T Tabellini, G., 291 Tachibana, K., 60, 400 Tadokoro, Y., 65, 76, 77 Tagat, J. R., 21, 29, 30, 33, 45, 46 Taichman, R. S., 59 Tajkhorshid, E., 273 Takahashi, K., 292 Takahashi, M., 292 Takahashi, Y., 292 Takakura, N., 60, 400 Takamatsu, Y., 58, 60 Takano, H., 65, 76, 77 Talbot, S., 361 Tallman, M. S., 59 Tamamura, H., 402, 408 Tamayo, P., 143 Tan, G., 290, 291 Tan, M., 416

Tan, W., 138 Tanaka, J., 59 Tanaka, M., 290 Tang, K., 92 Tani, M., 92 Taniuchi, I., 60, 400 Taniuchi, S., 63, 317 Tanner, S., 335, 340, 341, 342, 343 Tannous, B. A., 353 Tarasova, N. I., 360 Tartaglia, L. A., 290, 291 Tashiro, K., 63 Tassone, L., 63, 317 Taswell, C., 74 Tate, C. G., 264 Tateno, M., 63 Taubman, M. B., 203, 204 Taylor, L., 419 Taylor, R. C., 107 Tee, A., 39 Teleshova, N., 92 Teller, D. C., 44, 264, 400 Temple, B. R., 69, 414 Teng, M., 291 Tensen, C. P., 156 Teramoto, H., 139 Terhorst, C., 65, 386 Terstappen, L. W., 66 Tertoolen, L. G. J., 381 Thacker, J. D., 73 Tham, T. N., 92 Thelen, M., 60, 316, 332 Thian, F. S., 264, 400 Thiele, K. P., 67 Thingholm, T. E., 338, 339 Thomas, A., 24, 36, 39 Thomas, J., 361 Thomas, R. J., 270 Thomas, S. A., 63 Thompson, D. A., 24 Thornton, J. M., 274 Thrall, B. D., 342 Thusu, K., 290 Tian, H., 40 Tian, Y., 118 Tiemessen, C. T., 70 Tiffany, H. L., 19, 33, 174, 175, 176, 194 Tigue, C. C., 59 Timmerman, H., 153, 154, 156, 160 Tindle, S., 65 Ting, R., 317 Tirelli, U., 359 Tischer, B. K., 165 To, L. B., 67 Todd, G., 65 Todd, K., 24, 36, 39 Todt, L., 68, 69, 80 Toews, M. L., 157

447

Author Index

Tolner, B., 226 Toner, M., 327 Topf, M., 267 Torok-Storb, B., 159 Torrance, D., 174 Torre, Y., 232, 233, 238 Tosolini, M., 107, 117 Towers, P., 180 Trabanino, R., 267, 269, 270, 272, 285 Trabanino, R. J., 270 Tran, P. B., 92 Tran, T., 63, 359, 360 Trapp, B. D., 92 Trebst, C., 92 Trebst, D., 92 Trejo, J., 69, 414, 417 Tremblay, C., 33 Trent, J. O., 237, 238 Tricot, G., 65 Trifilio, S. M., 59 Trkola, A., 21, 45, 46 Troost, D., 92 Trowbridge, I. S., 371 Trujillo, J., 317 Trumpp, A., 58 Tsai, S., 317 Tsai, T. W., 66 Tsamis, F., 21, 45, 46 Tsien, R. Y., 384 Tsuji, K., 78 Tsukada, N., 333, 334 Tsung, K., 175 Tubo, R., 10 Tucky, B., 92 Tulone, C., 165 Turner, J. E., 48 Turner, P., 213 Tyldesley, R., 291 Tyrberg, B., 200 U Uberbacher, E., 342 Uchida, S., 290 Ueda, Y., 317 Ueki, K., 290 Ueyama, Y., 78 Ulbrich, A., 419 Unger, R. H., 290 Unutmaz, D., 361, 401 Upton, C., 211 Urban, J. D., 264, 271 Urdal, D. L., 178 Uy, G. L., 59, 63, 67, 68 V Vago, L., 232, 233, 238 Vaida, B., 165

Vaidehi, N., 263, 267, 269, 270, 272, 273, 274, 285 Vainchenker, W., 69, 77 Vakili, J., 361 Vally, H., 165 Vamosi, G., 380 van Berkel, V., 174, 175, 176, 194 Vance, P. J., 361 van Cleef, K. W., 165 van Dam, C. M., 162 Van Dam, J. G., 165 Van Damme, J., 4, 237 Vandercappellen, J., 4 van der Lelie, H., 73 Vanderplasschen, A., 174, 178, 180 van der Ryst, E., 17 van der Schoot, C. E., 73 Vanderwinden, J. M., 361 van de Water, B., 332 Van de Water, L., 327 van Dongen, G. A., 153, 162, 163 van Heteren, J., 154 van Heteren, J. T., 92 Van Meter, M. J., 92 van Os, R. P., 65, 73 van Walsum, M., 153, 162, 163 Van Zant, G., 61, 66 Varma, A., 127, 135 Varmus, H. E., 131 Varty, G., 33 Vassart, G., 17, 291, 361 Vassileva, G., 128, 198 Vecchi, A., 107, 232, 233, 235, 236, 237, 238, 239, 240, 291 Velds, A., 415 Vellenga, E., 61, 66 Venherle, S. J., 165 Venkataramanan, V., 416, 421 Verani, A., 359 VerBerkmoes, N. C., 342 Verhaegent, M., 353 Verhasselt, V., 291 Verheij, M. H., 160 Vermi, W., 291 Verola, O., 63, 317 Versnel, M. A., 201 Vervecken, W., 226 Verzijl, D., 153, 156, 160, 162, 163, 165 Vesole, D., 65 Victor, S. M., 307 Vieira, J., 153, 159, 165 Viejo-Borbolla, A., 173, 193 Vij, R., 68, 69, 80 Vilardaga, J. P., 381 Villa, C., 264 Vincent, L., 128 Vink, C., 165 Virelizier, J. L., 60, 153, 159, 401

448

Author Index

Virgin, H. I., 174, 175, 176, 194 Virgin, H. W., 194, 213 Vischer, H. F., 151, 154, 156, 160, 168 Viskari, P. J., 383 Vita, C., 153, 159 Vitry, S., 92 Vo, A. P., 10 Voermans, C., 73 Vogel, J. U., 152 Vogel, R., 265 Volk, A. L., 152 von Andrian, U. H., 239, 246 von Einem, J., 165, 166 von Kalle, C., 78 von Zastrow, M., 264, 271, 359, 414 Vormoor, J., 77 Voyno-Yasenetskaya, T., 143 Vriend, G., 269 Vulcano, M., 237, 291 W Wadden, T., 290 Wagner, L., 342 Wagner, M., 165 Wagner, N., 29, 30, 33 Wagner, S. N., 401 Wagner, W., 60, 80 Wai, P. Y., 118 Wakabayashi, E., 153, 165 Wakefield, J. K., 326 Waki, H., 290 Wald, H., 61, 62 Walder, K., 292 Waldhoer, M., 152, 154, 155, 156, 160, 360 Walker, B. D., 60 Walker, G., 326, 328 Walker, G. M., 327, 328 Walkey, C. J., 292 Wallstro¨m, E., 92 Wang, D., 175, 176, 184 Wang, E., 80 Wang, G., 341 Wang, H., 213 Wang, J., 59, 61, 63, 92, 416 Wang, J. C., 77 Wang, L. C., 340, 341 Wang, M. Y., 290 Wang, S., 67 Wang, W., 342 Wang, X., 134 Wang, Y., 60 Wang, Z., 399, 402 Warming, S., 165 Warne, J. P., 290 Warne, T., 264 Warshaviak, D., 267 Washburn, M. P., 342

Washington, R. H., 128 Watier, H., 59 Watkins, R., 33 Watson, C., 33, 34 Watt, S. M., 59 Wavre, S., 360, 368, 373 Wavre-Shapton, S. T., 357 Weaver, C., 65 Weaver, C. H., 65 Webb, B., 266, 269 Webb, L. M., 175, 184, 187 Weber, C., 210, 213 Weber, J. M., 59 Weber, M., 237, 240, 246, 247, 248, 249, 250, 251, 252, 253, 254, 255, 256 Webster, R., 19, 20, 22, 24, 26, 29, 30, 33, 40 Weersing, E., 61, 66 Weh, H. J., 67 Wehde, M., 65 Wei, K., 60 Wei, T., 92 Wei, Y., 416 Weibrecht, K. W., 59 Wein, F., 60 Weinberg, R. A., 10, 118 Weiner, O. D., 327 Weinhardt, S., 80 Weinstein, H., 264, 269, 271, 273 Weinstock, R., 290 Weis, W. I., 264, 400 Weiss, C., 210, 211 Weiss, I. D., 61, 62 Weissleder, R., 353 Weissman, A. M., 416, 421 Weissman, I. L., 65, 69 Wellen, K. E., 291 Wells, T. N., 48, 63, 92, 194, 210, 211 Wells, T. N. C., 359, 360, 361, 362, 364 Wendland, M., 291 Weninger, W., 239 Wenz, F., 80 Werb, Z., 106, 107 Wernet, P., 67 Wernstedt, C., 307 West, G., 66 West, W., 65 Westby, M., 17, 19, 20, 22, 24, 26, 29, 30, 33, 36, 38, 39, 40, 43, 44, 46, 48 Westervelt, P., 68, 69, 80 Westphal, H., 49 Whistler, J. L., 154, 155 Whitcomb, J. M., 24, 40, 44, 46 White, F. M., 335, 338, 341, 344 White-Carrington, S., 291 White-Cooper, H., 58 Whitehead, G. S., 247

449

Author Index

Whitehead, J. P., 291 Whitesides, G. M., 327 Whiting-Theobald, N. L., 63 Whittaker, M., 270 Whittaker, P. A., 294 Wiekowski, M., 128, 153, 196, 213, 236 Wiekowski, M. T., 195, 198, 203, 204 Wigler, M., 130 Wikswo, J., 317, 319, 326, 327, 328 Wilburn, B. P., 203 Wilhelm Doerr, H., 152 Wilken, J., 24 Wilkens, M., 61, 66 Wilkinson, D., 361 Williams, B. O., 131 Williams, D. A., 77 Williams, R. C., 383 Williams, T. J., 174, 175, 176, 179, 181, 415 Wilson, A., 58 Wilson, D., 60 Wilson, P. A., 117 Wilson, S. B., 201 Wind, P., 107, 117 Wing, R. R., 290 Winkler, I., 60, 63 Winkler, I. G., 58 Winslow, G. A., 40 Wirthlin, L., 80 Wise, E. L., 174, 269, 270, 415 Wittamer, V., 291, 292, 361 Woehl, B., 60 Wohlschlegel, J. A., 340 Wojciechowski, M., 270 Wojcik, L., 29, 30, 33 Wolf, C., 338 Wong, D., 60, 62 Wong, F. S., 195 Wood, B., 63, 67 Woolf, T. B., 273 Worth, D., 304 Worthen, G. S., 159 Wright, H. M., 292 Wright, M., 292 Wrin, T., 40 Wu, K. K., 290 Wu, L., 51 Wu, M., 291 Wu, T. C., 107 Wu, W. W., 341 Wu, X., 326, 381, 384 Wujek, J., 92 Wunder, E., 66 Wurdinger, T., 353 Wurster, S., 29 Wyatt, R., 51 Wylie, S. M., 232, 237 Wysoczynski, M., 60, 63

X Xia, W., 416 Xia, Z., 380 Xiao, K., 416, 421 Xiao, X. L., 77 Xiao, Y., 33 Xie, P., 143 Xie, T., 58 Xu, E., 107 Xu, H., 290, 291 Xu, J., 107 Xu, M., 342 Xu, Q., 60 Xu, S., 29, 30, 33, 294 Xu, T., 340 Xu, Y., 198 Xue, C., 402 Y Yamada, S., 201 Yamamoto, K., 290 Yamamoto, M., 44, 264, 400 Yamamoto, T., 270 Yamashita, S., 290 Yamauchi, T., 290 Yamazaki, S., 65, 76, 77 Yan, L. Z., 61, 63 Yang, D., 290, 291 Yang, J., 232, 237, 347, 348 Yang, K., 265, 272 Yang, L., 342 Yang, M., 143 Yang, O. O., 60 Yang, Q., 118, 290, 291 Yang, T. Y., 128, 153, 196 Yang, X., 342 Yao, X., 271, 272 Yao, X. J., 400 Yarchoan, R., 128 Yates, J. R. III, 340, 342 Yau, M., 335, 341, 342, 343 Ye, M., 338 Ye, R. D., 143 Yeaman, S. J., 307 Yeh, S. W., 383 Yeung, B., 419 Yilmaz, O. H., 65 Yim, J. H., 175 Yoder, M. C., 73 Yoneyama, H., 201 Yoon, J. W., 200 Yoshida, H., 59, 60, 400 Yoshida, N., 60, 400 Yoshie, O., 4 Young, D., 66 Yu, D., 416

450

Author Index

Yu, J., 107, 419 Yu, Y., 317 Yu, Y. H., 293 Yuan, R., 74 Yuan, W., 401 Yudkin, J. S., 291 Z Zabel, B. A., 290, 291, 302, 304, 305, 306 Zaborski, P., 118 Zacharias, D., 384 Zage, P., 118 Zaitseva, M., 416 Zaja-Milatovic, S., 317 Zalamea, P., 203 Zaman, G. J., 156 Zamanakos, G., 267, 269, 270, 272, 285 Zamboni, W. C., 66 Zander, A., 66 Zander, A. R., 67 Zandi, E., 340, 341 Zanussi, S., 359 Zaratin, P., 210, 212 Zeller, W., 67 Zeller, W. J., 80 Zerboni, R., 127 Zernecke, A., 60, 210, 213 Zhang, B., 291, 342 Zhang, J., 44, 45, 60, 63 Zhang, W. B., 402, 408 Zhang, Y., 69

Zhang, Z., 341 Zheng, J. C., 92 Zheng, W., 160 Zhong, R., 60, 62, 213 Zhong, R. K., 74, 76 Zhou, B. P., 416 Zhou, H., 335, 338, 340, 341, 342, 343 Zhou, X., 416 Zhou, Z. L., 92 Zhu, H., 293 Zhu, Y., 245 Ziccardi, P., 291 Ziegler, H., 165 Zimmer, K., 66 Zimmet, P., 292 Zinzindohoue, F., 107, 117 Zipeto, D., 153, 159 Ziprin, P., 107, 117 Zlotnik, A., 4, 106 Zohar, M., 127, 128, 137, 140, 141 Zohar, R., 118 Zolotaryov, F. N., 292 Zong, J. C., 134 Zou, H., 338 Zou, Y. R., 60, 400 Zsak, M., 59 Zuniga, L., 291, 305 Zvaifler, N. J., 333, 334 Zwahlen, R., 60 Zweerink, H., 239 Zybailov, B., 342

Subject Index

A Adipokine chemerin, see Chemerin functional overview, 290 AIP4, see Atrophin-interacting protein–4 Akt, activation assay via Kaposi’s sarcoma-associated herpesvirus-encoded G protein-coupled receptor, 137–138 Atrophin-interacting protein–4, CXCR4 ubiquitin ligase activity, 419–421 B Bacterial artificial chromosome mutagenesis, cytomegalovirus-encoded G protein-coupled receptor, 165–167 Biacore, see Surface plasmon resonance Breast cancer chemokine transfection in human cell lines cell culture, 8 cell preparation, 7–8 chemokine quantification, 9 materials, 6–7 microporation overview, 5–6 technique, 8 xenograft models human cell lines, 9–10 primary tumor formation using T47D cells inoculation, 12 materials, 11 mouse handling, 11 overview, 10 tumor cell preparation, 11–12 tumor growth and survival assays, 12 pulmonary metastasis model using MDA-MB–231 cells inoculation, 14 materials, 12–13 metastasis formation assay, 14–15 mouse handling, 14 tumor cell preparation, 14 C Calcium flux CCR5 signaling assay cell culture and transfection, 22–23 data analysis, 23 dye preparation and loading, 23

fluorescence measurement, 23 materials, 50 overview, 19, 22 cytomegalovirus-encoded G protein-coupled receptor signaling assay, 160 CCL3, colorectal cancer expression studies, 112, 114, 117 CCL4, colorectal cancer expression studies, 112, 114, 117 CCR1, ligand docking modeling of small molecule binding, 270–271 CCR5 antagonists, 20–22 antiviral assays antagonist resistance assay, 42–43 human immunodeficiency virus stock expansion and storage, 42 materials, 51 primary cell preparation monocyte-derived macrophages, 41 peripheral blood lymphocytes, 40–41 reverse transcriptase assay, 41–42 calcium signaling assay cell culture and transfection, 22–23 data analysis, 23 dye preparation and loading, 23 fluorescence measurement, 23 materials, 50 overview, 19, 22 cell lines for expression, 362–363 cognate ligands, 22 cyclic AMP response element-luciferase reporter gene assay data interpretation, 32–33 luminescence measurement, 32 materials, 51 plate preparation, 32 principles, 30–31 transient transfection, 31–32 degradation assays immunofluorescence microscopy, 370–371 Western blot, 369–370 detection techniques, 360–362 endocytosis electron microscopy cell surface replicas of whole-mount preparations, 372–372 immuno-gold labeling of cryosections, 374–375

451

452 CCR5 (cont.) membrane sheet preparation, 372–374 overview, 364, 371 flow cytometry, 363, 366 immunofluorescence microscopy, 363–365 mechanism, 360 GTP-associated inverse agonism assay, 28–30, 51 human immunodeficiency virus coreceptor, 359 gp160–CCR5-mediated cell–cell fusion assay, 38–40, 51 internalization assay cell culture, 24 clinical analysis of agonist-dependent functional receptor occupancy dosing and sampling regimen, 27 fluorescence-activated cell sorting, 28 principles, 25–26 data analysis, 25 fluorescence-activated cell sorting, 24–25 materials, 50 overview, 24 knockin human CCR5 mice overview, 48 vector construction, 48–49 embryonic stem cell transfection, 49 materials, 52 ligand-binding assays human immunodeficiency virus gp120-binding assays functional occupancy characterization in vitro, 37–38 gp120 assay, 36 materials, 51 overview, 35–36 time-resolved fluorescence immunoassay, 36–37 radioassays antagonist binding and dissociation, 34 chemokine ligands, 33–34 surface plasmon resonance antibody immobilization, 34 data analysis, 35 ligand binding, 35 materials, 51 ligand docking studies computer modeling, 43–44, 46–47 cyclic AMP response element-luciferase reporter gene assay, 46 materials, 51–52 site-directed mutagenesis, 45 structural model generation, 44–45 transfection of human embryonic kidney cells, 45–46 recycling assays flow cytometry, 368 immunofluorescence microscopy, 367

Subject Index

Chemerin cell model for adipogenesis and adipocyte metabolism, 292–293 functional overview, 291–292 receptor, see Chemokine-like receptor–1 RNA interference adenoviral vectors design, 294 testing, 298–299 titration, 294–296 adipocyte metabolism effects, 307–308 adipogenesis effects, 306–307 cell preparation and maintenance, 299–300 materials, 297–298 postdifferentiation knockdown studies, 304–306 predifferentiation knockdown studies, 300, 302 principles, 293–294 RNA isolation and quantification, 302–304 safety precautions, 298 Chemokine-binding proteins, see Viral chemokine-binding proteins Chemokine-like receptor–1 cell model for adipogenesis and adipocyte metabolism, 292–293 ligand, see Chemerin RNA interference adenoviral vectors design, 294 testing, 298–299 titration, 294–296 adipocyte metabolism effects, 307–308 adipogenesis effects, 306–307 cell preparation and maintenance, 299–300 materials, 297–298 postdifferentiation knockdown studies, 304–306 predifferentiation knockdown studies, 300, 302 principles, 293–294 RNA isolation and quantification, 302–304 safety precautions, 298 Chemokine receptors, see CCR1; CCR5; Chemokine-like receptor–1; CXCR2; CXCR4; CXCR7; D6; G protein-coupled receptors; Phosphoproteomics Chronic lymphocytic leukemia, CXCL12 signaling phosphoproteomics in cells cell isolation, 334 CXCL12 stimulation, 334–335 functional annotation of data, 344 high-performance liquid chromatography of phosphopeptides, 339–340 immobilized metal affinity chromatography enrichment of phosphopeptides bead preparation, loading, and elution, 337 C18 cartridge cleanup, 337

Subject Index

denaturation, reduction, and alkylation, 335–336 metals for elution, 338 sequential elution, 339 trypsin digestion, 336–337 lysate preparation, 335 principles, 333–334 protein classification with Database for Annotation, Visualization, and Integrated Discovery, 343 tandem mass spectrometry database search program selection considerations, 342–343 InsPecT identification of phosphopeptides, 340–342 running conditions, 339–340 CLL, see Chronic lymphocytic leukemia CMLKR1, see Chemokine-like receptor–1 Coimmunoprecipitation, CXCR2 and binding proteins, 321 Colorectal cancer chemokine and receptor expression studies CCL3, 112, 114, 117 CCL4, 112, 114, 117 cell culture and tissue collection/processing, 108 CXCL8 expression analysis, 112, 114, 117–118 correlation with osteopontin and secreted protein acidic and rich in cysteine expression, 116–119 regulation, 115 enzyme-linked immunosorbent assay, 110 low-density array analysis, 108–113 quantitative real-time polymerase chain reaction, 109, 112, 114 rationale, 107 statistical analysis, 110 inflammation and immune response, 106–107 Confocal microscopy CXCR2 and binding proteins, 322 D6, 234, 238, 253 knockout mice, 235–239 CR, see Colorectal cancer CRE, see Cyclic AMP response element CXCL8, colorectal cancer expression studies assays, 112, 114, 117–118 correlation with osteopontin and secreted protein acidic and rich in cysteine expression, 116–119 regulation, 115 CXCL12 phosphoproeomics of signaling in chronic lymphocytic leukemia cells cell isolation, 334 CXCL12 stimulation, 334–335 functional annotation of data, 344

453 high-performance liquid chromatography of phosphopeptides, 339–340 immobilized metal affinity chromatography enrichment of phosphopeptides bead preparation, loading, and elution, 337 C18 cartridge cleanup, 337 denaturation, reduction, and alkylation, 335–336 metals for elution, 338 sequential elution, 339 trypsin digestion, 336–337 lysate preparation, 335 principles, 333–334 protein classification with Database for Annotation, Visualization, and Integrated Discovery, 343 tandem mass spectrometry database search program selection considerations, 342–343 InsPecT identification of phosphopeptides, 340–342 running conditions, 339–340 receptor, see CXCR4 stem cell mobilization, see Hematopoietic stem cell CXCR2 chemosynapse overview, 317–318 proteomic screening for chemosynapse adaptor proteins, 318–320 protein–protein interactions coimmunoprecipitation, 321 colocalization in dHL–60 cells confocal microscopy, 322 polarization in Zigmond chamber, 321 glutathione S-transferase pulldown assays fusion protein constructs, 322–323 fusion protein production, 323 pull down, 324 site-directed mutagenesis of residues at interface, 324–325 radioactive phosphorylation of interacting proteins, 325–326 chemotaxis assays of ligand effects Boyden chamber, 326–327 micro fluidic gradient device, 327–328 CXCR4 central nervous system expression analysis with in situ hybridization color development, 98–99 complementary DNA cloning, 95–96 first-strand synthesis, 95 controls, 99–101 hybridization, 97–98 materials, 93–94 overview of chemokine receptor distribution, 92

454 CXCR4 (cont.) probe generation with in vitro transcription, 96–97 RNA purification, 94–95 tissue preparation, 94 washing, 98 endocytosis mechanism, 360 functional overview, 400–401 ligands, 60 stem cell mobilization approaches, 58–59 characterization of mobilized cells differentiation assays, 73 transmigration assays, 73–74 CXCL4/CXCR4 axis-mobilizing agents, 59–63 donor selection humans, 64–65 mice, 64 flow cytometry CXCR4 expression, 69–72 mobilized cell counting, 65 granulocyte colony-stimulating factor-induced mobilization human cells, 66–67 mouse cells, 66 plerixafor-induced mobilization human cells, 67–68 mouse cells, 67 transplantation assays immune-deficient mouse models, 77–80 limiting dilution competitive repopulation assay, 75–77 overview, 74–75 secondary transplantation, 77 T-cell receptor interaction analysis with fluorescence resonance energy transfer dye-linked monoclonal antibody probes advantages and limitations, 382–386 cell surface labeling, 386–387 chemokine treatment, 388 controls, 390–391 flow cytometry, 388 Jurkat T-cell findings, 388–391 methyl-b-cyclodextrin effects, 392 fluorescent protein fusion protein probes advantages and limitations, 384–386 emission spectra interpretation, 395 fluorescence spectroscopy, 395 Jurkat T-cell findings, 396 transient transfection, 392–395 principles, 380–381 therapeutic targeting, 401 WHIM syndrome defects, 63, 317 yeast expression of human protein for inverse agonist screening affinities of compounds, 408–410 constitutively active mutant utilization, 410

Subject Index

5-fluorouridine toxicity assay, 403–404 FUS1-HIS3 reporter, 402–403, 406 reporter gene system comparison, 404–407 vector, 403 CXCR7, central nervous system expression analysis with in situ hybridization color development, 98–99 complementary DNA cloning, 95–96 first-strand synthesis, 95 controls, 99–101 hybridization, 97–98 materials, 93–94 overview of chemokine receptor distribution, 92 probe generation with in vitro transcription, 96–97 RNA purification, 94–95 tissue preparation, 94 washing, 98 Cyclic AMP response element, luciferase reporter gene assay for CCR5 data interpretation, 32–33 luminescence measurement, 32 materials, 51 plate preparation, 32 principles, 30–31 transient transfection, 31–32 Cyclin D1, assay of cytomegalovirus-encoded G protein-coupled receptor-induced cell proliferation, 163–164 Cytomegalovirus-encoded G protein-coupled receptors bacterial artificial chromosome mutagenesis, 165–167 binding assays, 157–158 enzyme-linked immunosorbent assay, 156 genetic engineering, 154–156 internalization assays, 159 oncogenesis induction assays cyclin D1 assay of cell proliferation, 163–164 foci formation assay, 162–163 xenograft models, 164 signal transduction assays calcium flux, 160 inositol phosphate production, 159–160 reporter gene assays, 160, 162 subcellular localization, 156 types, 152–154 US28 receptor, 153 D D6 confocal microscopy of internalization, 253 flow cytometry receptor recycling, 253–254 chemokine uptake assays, 254–255

455

Subject Index

functional overview, 246–247 ligands, 232, 246 pull-down assay of binding, 259–260 purification large-scale production bell jar, 257 bioreactor, 257–258 nickel affinity chromatography, 258–259 solubilization, 258–259 transfection, 256–257 regulation under homeostatic and inflammatory conditions, 240–241 scavenging assays biotinylated chemokines, 250–251 detection, 251–252 kinetic analysis, 252 radiolabeled chemokines, 250 trichloroacetic acid precipitation, 251 transfection of expression constructs, 247–249 tuberculosis studies chemokine neutralization in vivo, 233 chemokine scavenging assay, 234 immune response overview, 239–240 immunohistochemistry of human lung lymph nodes, 232–233, 235, 239 mouse models, 233, 235–236 transfection and localization of Rab11 mutant–green fluorescent protein construct, 233–234, 236 Western blot analysis, 249–250 Database for Annotation, Visualization, and Integrated Discovery, 343 DAVID, see Database for Annotation, Visualization, and Integrated Discovery Diabetes, murine herpesvirus–68 M3 protein inhibition of development in mice, 199–202 DNA microarray, Kaposi’s sarcoma-associated herpesvirus-encoded G protein-coupled receptor signaling studies, 141–143 DOCK, ligand docking modeling of small molecule binding to G protein-coupled receptors, 270–271 E Electron microscopy, CCR5 internalization monitoring cell surface replicas of whole-mount preparations, 372–372 immuno-gold labeling of cryosections, 374–375 membrane sheet preparation, 372–374 overview, 364, 371 ELISA, see Enzyme-linked immunosorbent assay Enzyme-linked immunosorbent assay colorectal cancer chemokine and receptor expression studies, 110 cytomegalovirus-encoded G protein-coupled receptors, 156

F FlashPlate, viral chemokine-binding protein binding assays, 182–184 Flow cytometry CCR5 endocytosis assays, 24–25, 366 overview, 363 recycling assay, 368 CXCR4–T-cell receptor interaction analysis with fluorescence resonance energy transfer, 388 D6 studies chemokine uptake assays, 254–255 receptor recycling, 253–254 stem cell mobilization assays CXCR4 expression, 69–72 mobilized cell counting, 65 Fluorescence resonance energy transfer CXCR4–T-cell receptor interaction analysis dye-linked monoclonal antibody probes advantages and limitations, 382–386 cell surface labeling, 386–387 chemokine treatment, 388 controls, 390–391 flow cytometry, 388 Jurkat T-cell findings, 388–391 methyl-b-cyclodextrin effects, 392 fluorescent protein fusion protein probes advantages and limitations, 384–386 emission spectra interpretation, 395 fluorescence spectroscopy, 395 Jurkat T-cell findings, 396 transient transfection, 392–395 principles, 380–381 FRET, see Fluorescence resonance energy transfer FucS, stem cell mobilization, 62 G G-CSF, see Granulocyte colony-stimulating factor Glycosaminoglycan–chemokine interactions overview, 210–211 surface plasmon resonance of viral chemokine-binding protein binding binding assays, 188–189 chemokine competition assays, 187 GPCRs, see G protein-coupled receptors G protein-coupled receptors, see also Chemokine receptors crystal structures, 264–265 flexibility and ligand-induced conformational change computational modeling Liticon, 273–274 overview, 271–273 internalization, 358, 414 pathophysiology, 264 site-directed mutagenesis for model validation binding assays

456

Subject Index

G protein-coupled receptors, see also Chemokine receptors (cont.) chemotaxis assay, 282–284 direct binding assays, 281–282 radiolabeled ligands, 278–281 cell culture, 275–276 expression assay, 277–278 overview, 274–275 transient transfection, 276–277 small molecule binding computational modeling ab initio modeling, 267–270 homology modeling, 266–267 ligand docking, 270–271 therapeutic targeting, 400 viral chemokine receptors, see Cytomegalovirus-encoded G protein-coupled receptors; Kaposi’s sarcoma-associated herpesvirus-encoded G protein-coupled receptor Granulocyte colony-stimulating factor, stem cell mobilization, 61, 66–67 GTP, CCR5 inverse agonism assay, 28–30, 51 H Hematopoietic stem cell receptors, 58 stem cell mobilization approaches, 58–59 characterization of mobilized cells differentiation assays, 73 transmigration assays, 73–74 CXCL4/CXCR4 axis-mobilizing agents, 59–63 donor selection humans, 64–65 mice, 64 flow cytometry CXCR4 expression, 69–72 mobilized cell counting, 65 granulocyte colony-stimulating factor-induced mobilization human cells, 66–67 mouse cells, 66 plerixafor-induced mobilization human cells, 67–68 mouse cells, 67 transplantation assays immune-deficient mouse models, 77–80 limiting dilution competitive repopulation assay, 75–77 overview, 74–75 secondary transplantation, 77 HIV, see Human immunodeficiency virus Human herpesvirus–5, see Cytomegalovirusencoded G protein-coupled receptor Human herpesvirus–8, see Kaposi’s sarcoma-associated herpesvirus-encoded G protein-coupled receptor

Human immunodeficiency virus CCR5 assays antiviral assays antagonist resistance assay, 42–43 human immunodeficiency virus stock expansion and storage, 42 materials, 51 primary cell preparation, 40–41 reverse transcriptase assay, 41–42 gp120-binding assays functional occupancy characterization in vitro, 37–38 gp120 assay, 36 materials, 51 overview, 35–36 time-resolved fluorescence immunoassay, 36–37 gp160–CCR5-mediated cell–cell fusion assay, 38–40, 51 CXCR4 therapeutic targeting, 401 I InsPecT, identification of phosphopeptides, 340–342 ISH, see In Situ hybridization K Kaposi’s sarcoma-associated herpesvirus-encoded G protein-coupled receptor functional overview, 127–128 gene cloning, 128–129 Kaposi’s sarcoma features, 127 paracrine transformation induction, 134–135 signaling characterization activation of second messenger-generating systems, 136–137 Akt activation assay, 137–138 DNA microarray analysis of gene expression, 141–143 nuclear factor-kB activation assay, 143–144 binding assay, 144–145 translocation assay, 146–147 overview, 135 Rac1 pulldown assay bead preparation, 139 principles, 138–139 transfection and pulldown, 139–140 transcription factor activation, 141 Western blot of phosphoproteins, 140–141 targeted infection in vivo overview, 131–132 transgenesis, 132 viral production, 132–134 therapeutic targeting rationale, 129 transforming activity assays in vitro, 130 in vivo, 130–131

457

Subject Index L LDA, see Low-density array analysis Liticon, G protein-coupled receptor conformational modeling, 273–274 Low-density array, colorectal cancer chemokine and receptor expression studies, 108–113 M M3, see Murine herpesvirus–68 M3 protein Maraviroc, CCR5 antagonism and structure, 20 Mass spectrometry, tandem mass spectrometry for CXCL12 signaling phosphoproteomics database search program selection considerations, 342–343 InsPecT identification of phosphopeptides, 340–342 running conditions, 339–340 MembStruk, ab initio modeling of small molecule binding to G protein-coupled receptors, 267–270 Metastasis, see Breast cancer Microporation, see Breast cancer M-T7, see Myxoma virus M-T7 Multiple sclerosis, chemokine receptor expression, 92 Murine herpesvirus–68 M3 protein b cell expression studies chemokine-induced cell migration inhibition, 198–199 conditional transgenic expression system, 202–204 diabetes prevention in mice, 199–202 transgenic mouse generation, 195–198 overview, 194–195 prospects for study, 204 Myxoma virus M-T7 ascites assay, 219–220 cell adhesion assay, 216–217 gene discovery and identification, 211–212 inflammatory vasculopathic disease inhibition aortic transplant rat model studies anesthesia, 221 donor, 221 morphometric analysis of aortic plaque, 224–225 recipient, 221–222 staining of tissue, 223–224 statistical analysis, 225 overview, 213 membrane fluidity assay, 217–219 purification, 215–216 toxicity testing in preclinical studies, 225–227 viral constructs for expression, 213–215 N Nonobese diabetic/severe combined immunodeficient mouse, human stem cell

repopulation capacity characterization, 77–80 Nuclear factor-kB chemokine transcription modulation in tumorigenesis bioluminescent imaging of intratumor signaling in anesthetized mice firefly luciferase, 349 Gaussia luciferase reporter, 349–351 bioluminescent imaging of intratumor signaling in conscious mice, 353–354 kinase and transcriptional activity assays in vitro, 352 reporter model development, 349 functional overview, 348 Kaposi’s sarcoma-associated herpesvirus-encoded G protein-coupled receptor signaling characterization activation assay, 143–144 binding assay, 144–145 translocation assay, 146–147 O OPN, see Osteopontin Osteopontin, colorectal cancer expression, 116–119 P PAM, see Tumor-associated macrophage PCR, see Polymerase chain reaction Phosphoproteomics CXCL12 signaling in chronic lymphocytic leukemia cells cell isolation, 334 CXCL12 stimulation, 334–335 functional annotation of data, 344 high-performance liquid chromatography of phosphopeptides, 339–340 immobilized metal affinity chromatography enrichment of phosphopeptides bead preparation, loading, and elution, 337 C18 cartridge cleanup, 337 denaturation, reduction, and alkylation, 335–336 metals for elution, 338 sequential elution, 339 trypsin digestion, 336–337 lysate preparation, 335 principles, 333–334 protein classification with Database for Annotation, Visualization, and Integrated Discovery, 343 tandem mass spectrometry database search program selection considerations, 342–343

458

Subject Index

Phosphoproteomics (cont.) InsPecT identification of phosphopeptides, 340–342 running conditions, 339–340 overview of strategies, 332–333 Plerixafor, stem cell mobilization, 61, 67–69 Polymerase chain reaction, colorectal cancer chemokine and receptor expression studies low-density array analysis, 108–113 quantitative real-time polymerase chain reaction, 109, 112, 114 R Rac1, pulldown assay of Kaposi’s sarcoma-associated herpesvirus-encoded G protein-coupled receptor signaling bead preparation, 139 principles, 138–139 transfection and pulldown, 139–140 Rhodopsin, structure elucidation, 264 RNA interference chemerin/chemokine-like receptor–1 knockdown adenoviral vectors design, 294 testing, 298–299 titration, 294–296 adipocyte metabolism effects, 307–308 adipogenesis effects, 306–307 cell preparation and maintenance, 299–300 materials, 297–298 postdifferentiation knockdown, 304–306 predifferentiation knockdown studies, 300, 302 RNA isolation and quantification, 302–304 safety precautions, 298 principles, 293–294 S Scintillation proximity assay, viral chemokinebinding protein binding assays, 180–182 Secreted protein acidic and rich in cysteine, colorectal cancer expression, 116–119 Site-directed mutagenesis, see CXCR2; G protein-coupled receptors In Situ hybridization, chemokine receptor expression analysis in central nervous system color development, 98–99 complementary DNA cloning, 95–96 first-strand synthesis, 95 controls, 99–101 hybridization, 97–98 materials, 93–94 overview of chemokine receptor distribution, 92 probe generation with in vitro transcription, 96–97

RNA purification, 94–95 tissue preparation, 94 washing, 98 SPA, see Scintillation proximity assay SPARC, see Secreted protein acidic and rich in cysteine SPR, see Surface plasmon resonance Stem cell mobilization, see Hematopoietic stem cell Stromal cell-derived factor–1, see CXCL12 Surface plasmon resonance CCR5 binding assays antibody immobilization, 34 data analysis, 35 ligand binding, 35 materials, 51 viral chemokine-binding protein binding assays chemokine binding, 184–187 glycosaminoglycan binding, 188–189 glycosaminoglycan competition assays, 187 T T134, stem cell mobilization, 61, 63 T140, stem cell mobilization, 61, 63 T-cell receptor, CXCR4 interaction analysis with fluorescence resonance energy transfer dye-linked monoclonal antibody probes advantages and limitations, 382–386 cell surface labeling, 386–387 chemokine treatment, 388 controls, 390–391 flow cytometry, 388 Jurkat T-cell findings, 388–391 methyl-b-cyclodextrin effects, 392 fluorescent protein fusion protein probes advantages and limitations, 384–386 emission spectra interpretation, 395 fluorescence spectroscopy, 395 Jurkat T-cell findings, 396 transient transfection, 392–395 principles, 380–381 TCR, see T-cell receptor Transgenic mouse, see CCR5 Tumor-associated macrophage, chemokine regulation, 4 U Ubiquitination, chemokine receptors CXCR4 agonist treatment, 417 atrophin-interacting protein–4 as ubiquitin ligase, 419–421 cell culture, 416–417 immunoprecipitation, 418 overview, 414–416 transfection, 417

459

Subject Index

Western blot, 418–419 G protein-coupled receptor degradation, 414 US28, see Cytomegalovirus-encoded G protein-coupled receptors V vCKBPs, see Viral chemokine-binding proteins vGPCR, see Cytomegalovirus-encoded G protein-coupled receptors; Kaposi’s sarcoma-associated herpesvirus-encoded G protein-coupled receptor Viral chemokine-binding proteins, see also Murine herpesvirus–68 M3 protein; Myxoma virus M-T7 binding studies cell binding assay, 179 cross-linking, 176–178 FlashPlate assay, 182–184 ligand blot assay, 178–179

scintillation proximity assay, 180–182 surface plasmon resonance chemokine binding, 184–187 glycosaminoglycan binding, 188–189 glycosaminoglycan competition assays, 187 media preparation from virus-infected cell cultures, 175–176 overview, 174–175 W Western blot CCR5 degradation, 369–370 CXCR4 ubiquitination, 418–419 D6, 249–250 phosphoproteins in Kaposi’s sarcoma-associated herpesvirus-encoded G protein-coupled receptor signaling, 140–141

Methods in Enzymology Vol 460: Chemokines, Part A

Methods in Enzymology Vol 461: Chemokines, Part B

Numerical Computer Methods, Part E (Methods in Enzymology Vol 384)

Methods in Enzymology Vol 284: Lipases, Part A

Programmed Cell Death Part A (Methods in Enzymology, Vol 442)

Methods in Enzymology Vol 367: Liposomes, Part A

Methods in Enzymology Vol 36: Hormone Action Part B

Methods in Enzymology Vol 440: Nitric Oxide, Part F

Methods in Enzymology Vol 440: Nitric Oxide, Part F

Methods in Enzymology Vol.334, Hyperthermophilic Enzymes (Part C)

Methods in Enzymology Vol 42: Carbohydrate Metabolism, Part C

Methods in Enzymology Vol 441: Nitric Oxide, Part G

Recombinant DNA, Part H, Vol. 217 (Methods in Enzymology)

Methods in Enzymology Vol 131: Enzyme Structure Part L

Methods in Enzymology Vol 314: Antisense Technology, Part B

Methods in Enzymology Vol 39: Hormone Action Part D

Methods in Enzymology Vol 369: Combinatorial Chemistry, Part B

Methods in Enzymology 466 - Biothermodynamics, Part B

Methods in Enzymology 488 - Biothermodynamics, Part 3

Methods in Enzymology 465 - Liposomes, Part G

Methods in Enzymology Vol 387: Liposomes, Part D

Methods in Enzymology 464 - Liposomes, Part F

Methods in Enzymology 492 - Biothermodynamics, Part 4

Methods in Enzymology 455 - Biothermodynamics, Part 1

Methods in Enzymology Vol 307: Confocal Microscopy

Methods in Enzymology Vol 426: Integrins

METHODS IN ENZYMOLOGY - GLYCOBIOLOGY (Vol. 415)

Methods in Enzymology Vol 416: Glycomics

Methods in Enzymology Vol 417: Functional Glycomics

Methods in Enzymology Vol 43: Antibiotics

Methods in Enzymology Vol 450: Fluorescence Spectroscopy

Methods in Enzymology Vol 460: Chemokines, Part A

Methods in Enzymology Vol 461: Chemokines, Part B

Numerical Computer Methods, Part E (Methods in Enzymology Vol 384)

Methods in Enzymology Vol 284: Lipases, Part A

Programmed Cell Death Part A (Methods in Enzymology, Vol 442)

Methods in Enzymology Vol 367: Liposomes, Part A

Methods in Enzymology Vol 36: Hormone Action Part B

Methods in Enzymology Vol 440: Nitric Oxide, Part F

Methods in Enzymology Vol 440: Nitric Oxide, Part F

Methods in Enzymology Vol.334, Hyperthermophilic Enzymes (Part C)

Methods in Enzymology Vol 42: Carbohydrate Metabolism, Part C

Methods in Enzymology Vol 441: Nitric Oxide, Part G

Recombinant DNA, Part H, Vol. 217 (Methods in Enzymology)

Methods in Enzymology Vol 131: Enzyme Structure Part L

Methods in Enzymology Vol 314: Antisense Technology, Part B

Methods in Enzymology Vol 39: Hormone Action Part D

Methods in Enzymology Vol 369: Combinatorial Chemistry, Part B

Methods in Enzymology 466 - Biothermodynamics, Part B

Methods in Enzymology 488 - Biothermodynamics, Part 3

Methods in Enzymology 465 - Liposomes, Part G

Methods in Enzymology Vol 387: Liposomes, Part D

Methods in Enzymology 464 - Liposomes, Part F

Methods in Enzymology 492 - Biothermodynamics, Part 4

Methods in Enzymology 455 - Biothermodynamics, Part 1

Methods in Enzymology Vol 307: Confocal Microscopy

Methods in Enzymology Vol 426: Integrins

METHODS IN ENZYMOLOGY - GLYCOBIOLOGY (Vol. 415)

Methods in Enzymology Vol 416: Glycomics

Methods in Enzymology Vol 417: Functional Glycomics

Methods in Enzymology Vol 43: Antibiotics

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