Methods in Enzymology 472 - Single Molecule Tools: Fluorescence Based Approaches

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

Author: Nils G. Walter

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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 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 2010 Copyright # 2010, 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: 978-0-12-374954-3 ISSN: 0076-6879 Printed and bound in United States of America 10 11 12 10 9 8 7 6 5 4 3 2 1

CONTRIBUTORS

John Abelson Department of Biochemistry and Biophysics, University of California, San Francisco, California, USA Ichiro Amitani Department of Microbiology, and Department of Molecular and Cellular Biology, University of California, Davis, California, USA William M. Atkins Department of Medicinal Chemistry, University of Washington, Seattle, Washington, USA Ronald J. Baskin Department of Molecular and Cellular Biology, University of California, Davis, California, USA Jaime J. Benı´tez Department of Chemistry and Chemical Biology, Cornell University, Ithaca, New York, USA Keith P. Bjornson Pacific Biosciences, Menlo Park, California, USA Mario Blanco Department of Chemistry, Single Molecule Analysis Group, and Program in Cellular and Molecular Biology, University of Michigan, Ann Arbor, Michigan, USA Mario Brameshuber Biophysics Institute, Johannes Kepler University Linz, Linz, Austria Adina R. Buxbaum Anatomy and Structural Biology and Gruss-Lipper Biophotonics Center, Albert Einstein College of Medicine, New York, USA Anirban Chakraborty Department of Chemistry and Chemical Biology, Waksman Institute, and Howard Hughes Medical Institute, Rutgers University, Piscataway, New Jersey, USA Bidhan P. Chaudhuri Pacific Biosciences, Menlo Park, California, USA

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Contributors

Peng Chen Department of Chemistry and Chemical Biology, Cornell University, Ithaca, New York, USA Yan Chen School of Physics and Astronomy, University of Minnesota, Minneapolis, USA Ronald L. Cicero Pacific Biosciences, Menlo Park, California, USA Ashok A. Deniz Department of Molecular Biology, The Scripps Research Institute, La Jolla, California, USA Christopher C. Dombrowski Department of Microbiology, and Department of Molecular and Cellular Biology, University of California, Davis, California, USA Richard H. Ebright Department of Chemistry and Chemical Biology, Waksman Institute, and Howard Hughes Medical Institute, Rutgers University, Piscataway, New Jersey, USA Yon W. Ebright Department of Chemistry and Chemical Biology, Waksman Institute, and Howard Hughes Medical Institute, Rutgers University, Piscataway, New Jersey, USA Margaret M. Elvekrog Department of Chemistry, Columbia University, New York, USA Michael T. Englander Department of Chemistry, and Integrated Program in Cellular, Molecular, and Biomedical Sciences, Columbia University, New York, USA Teresa Fazio Department of Applied Physics and Applied Mathematics, Center for Electron Transport in Molecular Nanostructures, NanoMedicine Center for Mechanical Biology, Columbia University, New York, USA Jingyi Fei Department of Chemistry, Columbia University, New York, USA Allan Chris M. Ferreon Department of Molecular Biology, The Scripps Research Institute, La Jolla, California, USA Benjamin A. Flusberg Pacific Biosciences, Menlo Park, California, USA

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Contributors

Yann Gambin Department of Molecular Biology, The Scripps Research Institute, La Jolla, California, USA Lori S. Goldner Department of Physics, University of Massachusetts, Amherst, Massachusetts, USA Ruben L. Gonzalez Jr. Department of Chemistry, Columbia University, New York, USA Jason Gorman Department of Biological Sciences, Columbia University, New York, USA Jeremy J. Gray Pacific Biosciences, Menlo Park, California, USA Eric C. Greene The Howard Hughes Medical Institute, and Department of Biochemistry and Molecular Biophysics, Columbia University, New York, USA Max Greenfeld Department of Chemical Engineering, and Department of Biochemistry, Stanford University, Stanford, California, USA ¨rgen Groll Ju DWI e.V. and Institute of Technical and Macromolecular Chemistry, RWTH Aachen University, Aachen, Germany Christine Guthrie Department of Biochemistry and Biophysics, University of California, San Francisco, California, USA Haralambos Hadjivassiliou Department of Biochemistry and Biophysics, University of California, San Francisco, California, USA Christopher Hart Helicos BioSciences Massachusetts, USA

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¨bler Thomas Haselgru Biophysics Institute, Johannes Kepler University Linz, Linz, Austria Bettina Heise Department of Knowledge-based Mathematical Systems, Johannes Kepler University Linz, Linz, Austria Daniel Herschlag Department of Chemical Engineering, and Department of Biochemistry, Stanford University, Stanford, California, USA

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Contributors

Clemens Hesch Biophysics Institute, Johannes Kepler University Linz, Linz, Austria David Holden Pacific Biosciences, Menlo Park, California, USA Ana M. Jofre Department of Physics and Optical Science, University of North Carolina, Charlotte, North Carolina, USA Jolene Johnson School of Physics and Astronomy, University of Minnesota, Minneapolis, USA Martin Kaltenbrunner Biophysics Institute, Johannes Kepler University Linz, Linz, Austria Aaron M. Keller Department of Chemistry and Chemical Biology, Cornell University, Ithaca, New York, USA Samuel Kim Department of Chemistry, Stanford University, Stanford, California, USA Peter Koo Department of Physics, Yale University, New Haven, Connecticut, USA Jonas Korlach Pacific Biosciences, Menlo Park, California, USA Stephen C. Kowalczykowski Department of Microbiology, and Department of Molecular and Cellular Biology; Biophysics Graduate Group, University of California, Davis, California, USA Manuela Lehner Center for Biomedical Nanotechnology, Upper Austrian Research GmbH, Linz, Austria Doron Lipson Helicos BioSciences Massachusetts, USA

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Bian Liu Department of Microbiology, and Department of Molecular and Cellular Biology; Biophysics Graduate Group, University of California, Davis, California, USA Patrick Macdonald School of Physics and Astronomy, University of Minnesota, Minneapolis, USA Daniel D. MacDougall Department of Chemistry, Columbia University, New York, USA

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Contributors

Patrice M. Milos Helicos BioSciences Massachusetts, USA

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Andrew D. Miranker Department of Molecular Biophysics and Biochemistry, Yale University, New Haven, Connecticut, USA Martin Moeller DWI e.V. and Institute of Technical and Macromolecular Chemistry, RWTH Aachen University, Aachen, Germany Crystal R. Moran Department of Molecular Biology, The Scripps Research Institute, La Jolla, California, USA Joachim D. Mueller School of Physics and Astronomy, University of Minnesota, Minneapolis, USA Abhinav Nath Department of Molecular Biophysics and Biochemistry, Yale University, New Haven, Connecticut, USA, and Department of Medicinal Chemistry, University of Washington, Seattle, Washington, USA Fatih Ozsolak Helicos BioSciences Massachusetts, USA

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Christian Paar Center for Biomedical Nanotechnology, Upper Austrian Research GmbH, Linz, Austria Hye Yoon Park Anatomy and Structural Biology and Gruss-Lipper Biophotonics Center, Albert Einstein College of Medicine, New York, USA Wolfgang Paster Department of Molecular Immunology, Center for Physiology, Pathophysiology, and Immunology, Medical University of Vienna, Vienna, Austria Zdeneˇk Petra´sˇek Biotec, TU Dresden, Dresden, Germany Dileep K. Pulukkunat Department of Chemistry, Columbia University, New York, USA Arjun Raj Department of Bioengineering, University of Pennsylvania, Philadelphia, Pennsylvania, USA

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Tal Raz Helicos BioSciences Massachusetts, USA

Contributors

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Elizabeth Rhoades Department of Molecular Biophysics and Biochemistry, and Department of Physics, Yale University, New Haven, Connecticut, USA Jonas Ries Biotec, TU Dresden, Dresden, Germany Ravi Saxena Pacific Biosciences, Menlo Park, California, USA ¨tz Gerhard J. Schu Biophysics Institute, Johannes Kepler University Linz, Linz, Austria Michaela Schwarzenbacher Biophysics Institute, Johannes Kepler University Linz, Linz, Austria Petra Schwille Biotec, TU Dresden, Dresden, Germany Robert H. Singer Anatomy and Structural Biology and Gruss-Lipper Biophotonics Center, Albert Einstein College of Medicine, New York, USA Alois Sonnleitner Center for Biomedical Nanotechnology, Upper Austrian Research GmbH, Linz, Austria Kathleen Steinmann Helicos BioSciences Massachusetts, USA

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Samuel H. Sternberg Department of Chemistry, Columbia University, New York, USA Hannes Stockinger Department of Molecular Immunology, Center for Physiology, Pathophysiology, and Immunology, Medical University of Vienna, Vienna, Austria Stefan Sunzenauer Biophysics Institute, Johannes Kepler University Linz, Linz, Austria Jianyong Tang Janelia Farm Research Campus, Howard Hughes Medical Institute, Ashburn, Virginia, USA

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Contributors

John Thompson Helicos BioSciences Massachusetts, USA

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Adam J. Trexler Department of Molecular Biophysics and Biochemistry, Yale University, New Haven, Connecticut, USA Stephen W. Turner Pacific Biosciences, Menlo Park, California, USA Sanjay Tyagi Public Health Research Institute, New Jersey Medical School-UMDNJ, Newark, New Jersey, USA Mari-Liis Visnapuu Department of Biochemistry and Molecular Biophysics, Columbia University, New York, USA Nils G. Walter Department of Chemistry, Single Molecule Analysis Group, University of Michigan, Ann Arbor, Michigan, USA Dongye Wang Department of Chemistry and Chemical Biology, Waksman Institute, and Howard Hughes Medical Institute, Rutgers University, Piscataway, New Jersey, USA Jiangning Wang Department of Chemistry, Columbia University, New York, USA Jeffrey Wegener Pacific Biosciences, Menlo Park, California, USA Julian Weghuber Biophysics Institute, Johannes Kepler University Linz, Linz, Austria Shalom Wind Department of Applied Physics and Applied Mathematics, Center for Electron Transport in Molecular Nanostructures, NanoMedicine Center for Mechanical Biology, Columbia University, New York, USA Bin Wu School of Physics and Astronomy, University of Minnesota, Minneapolis, and Albert Einstein College of Medicine, Bronx, New York, USA Richard N. Zare Department of Chemistry, Stanford University, Stanford, California, USA

PREFACE

Ever since Feynman’s suggestion in the early 1960s that ‘‘there’s plenty of room at the bottom’’, single-molecule tools have seen an exponential rise in popularity (note that exponentially increasing rates are characteristic of explosions!). One can hardly go to a Biophysical Society meeting these days without being impressed by the literally thousands of posters and seminars that show data exploiting the unique capabilities of single-molecule probing techniques. Among their benefits are that they (i) can directly observe events at the molecular level; (ii) reveal rare and/or transient species and heterogeneities along a reaction pathway, which are often lost in ensemble averages; (iii) can directly access the low copy numbers (typically 1–1000) of any specific biopolymer in a single cell; (iv) afford counting and nanometer-accuracy localization of molecules in spatially distributed samples such as a cell; (v) enable the ultimate miniaturization and multiplexing of biological assays such as DNA sequencing; (vi) allow for the direct measurement of the mechanical forces affecting and enacted by biopolymers; and (vii) yield standard populationaveraged information from the statistics of many single-molecule observations. A half-century of single-molecule tool development has yielded technical advances that have demonstrated each of these advantages, and more are sure to emerge. Yet in any field enjoying increasing popularity, there inevitably comes a crossroads, which inspired MIE volumes 472 and 475. To advance beyond being used or studied only by a limited (and eventually vanishing) group of specialists, a set of tools or area of research needs to find more widespread appreciation. Many methods that are commonplace in labs today—such as gel electrophoresis, PCR, and sequencing—made that transition from specialist’s art to general practitioner’s basic tool by a combination of being very appealing and becoming easy to master. The two MIE volumes are aimed to facilitate this transition by, often for the first time, revealing for a broad selection of single-molecule tools those details that pioneering specialists rarely have the space to cover in their research publications. Compiling methods from an emerging field is a daunting task, since new tools are developed nearly daily. The resulting selection is, by necessity, incomplete, limited by both the availability of contributors and my gaps in knowledge. Yet through the vigorous response to my solicitation of articles, what was planned as one volume became two, somewhat loosely organized by theme. While editing each of these works, I became increasingly impressed by the consistently superb quality of the contributions, in terms of both style and substance. I am therefore very grateful to John Abelson for xxi

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convincing me to take on the job as editor, and trusting me with it, to the phenomenal group of authors (some of which even made the deadline), and to the staff at Elsevier for allowing me to divide the contributions into two volumes and supporting me in numerous other ways. My hope is that the hard work by everyone involved bears fruit and helps spread the word and enthusiasm about the power of single-molecule tools. NILS G. WALTER

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

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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

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VOLUME 256. Small GTPases and Their Regulators (Part B: Rho Family) Edited by W. E. BALCH, CHANNING J. DER, AND ALAN HALL 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


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VOLUME 274. RNA Polymerase and Associated Factors (Part B) Edited by SANKAR ADHYA 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

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VOLUME 293. Ion Channels (Part B) Edited by P. MICHAEL CONN 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 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

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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 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


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VOLUME 345. G Protein Pathways (Part C: Effector Mechanisms) Edited by RAVI IYENGAR AND JOHN D. HILDEBRANDT 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

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VOLUME 362. Recognition of Carbohydrates in Biological Systems (Part A) Edited by YUAN C. LEE AND REIKO T. LEE 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


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VOLUME 381. Oxygen Sensing Edited by CHANDAN K. SEN AND GREGG L. SEMENZA 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

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VOLUME 400. Phase II Conjugation Enzymes and Transport Systems Edited by HELMUT SIES AND LESTER PACKER 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


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VOLUME 418. Embryonic Stem Cells Edited by IRINA KLIMANSKAYA AND ROBERT LANZA 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

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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 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


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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 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 VOLUME 461. Chemokines, Part B Edited by TRACY M. HANDEL AND DAMON J. HAMEL VOLUME 462. Non-Natural Amino Acids Edited by TOM W. MUIR AND JOHN N. ABELSON VOLUME 463. Guide to Protein Purification, 2nd Edition Edited by RICHARD R. BURGESS AND MURRAY P. DEUTSCHER VOLUME 464. Liposomes, Part F Edited by NEJAT DU¨ZGU¨NES,

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VOLUME 465. Liposomes, Part G Edited by NEJAT DU¨ZGU¨NES, VOLUME 466. Biothermodynamics, Part B Edited by MICHAEL L. JOHNSON, GARY K. ACKERS, AND JO M. HOLT VOLUME 467. Computer Methods Part B Edited by MICHAEL L. JOHNSON AND LUDWIG BRAND VOLUME 468. Biophysical, Chemical, and Functional Probes of RNA Structure, Interactions and Folding: Part A Edited by DANIEL HERSCHLAG VOLUME 469. Biophysical, Chemical, and Functional Probes of RNA Structure, Interactions and Folding: Part B Edited by DANIEL HERSCHLAG VOLUME 470. Guide to Yeast Genetics: Functional Genomics, Proteomics, and Other Systems Analysis, 2nd Edition Edited by GERALD FINK, JONATHAN WEISSMAN, AND CHRISTINE GUTHRIE VOLUME 471. Two-Component Signaling Systems, Part C Edited by MELVIN I. SIMON, BRIAN R. CRANE, AND ALEXANDRINE CRANE VOLUME 472. Single Molecule Tools, Part A: Fluorescence Based Approaches Edited by NILS G. WALTER

C H A P T E R

O N E

Star Polymer Surface Passivation for Single-Molecule Detection ¨rgen Groll and Martin Moeller Ju Contents 2 2 4

1. 2. 3. 4.

Introduction Surface Grafting of PEO and Protein Repellence The NCO–sP(EO-stat-PO) System Preparation of sP(EO-stat-PO)-Coated Substrates for Single-Molecule Experiments 5. Analysis of Protein Structure and Function on NCO–sP(EO-stat-PO) Surfaces Acknowledgments References

6 11 16 16

Abstract Poly(ethylene oxide) (PEO) is known as an excellent coating material to minimize nonspecific protein adsorption. For an examination of biomolecules attached to surfaces with sensitivities down to the single-molecule level, demands on the surface additionally comprise low-intrinsic fluorescence of the coating material and a possibility to immobilize biomolecules in their functional conformation. One strategy that combines the protein-resistant properties of PEO with chemical functionality is the use of star-shaped PEOs that allow for interpolymer crosslinking. Our system consists of six-arm PEO-based star polymers functionalized with reactive isocyanate groups at the ends of the polymer chain. The isocyante groups allow intermolecular cross-linking so that high grafting densities may be achieved, which render the surfaces extremely resistant to protein adsorption. Application by spin coating offers a simple procedure for the preparation of minimally interacting surfaces. The reactive end groups may be further biofunctionalized to recognize specific biomolecules such as streptavidin or His-tagged proteins in specific geometries or as single isolated molecules. These properties, together with the advantageous chemical properties of PEO, render the surfaces ideal for immobilizing proteins with detection limits down to the single molecule level. This chapter focuses on the preparation of substrates that DWI e.V. and Institute of Technical and Macromolecular Chemistry, RWTH Aachen University, Aachen, Germany Methods in Enzymology, Volume 472 ISSN 0076-6879, DOI: 10.1016/S0076-6879(10)72019-X

#

2010 Elsevier Inc. All rights reserved.

1

2

¨rgen Groll and Martin Moeller Ju

are suitable for single-molecule experiments. Besides a detailed description of surface preparation, two examples for the single-molecule detection of immobilized proteins, nucleosomes and RNase H, are presented that demonstrate the advantages of the star-polymer derived coatings over lineargrafted PEO.

1. Introduction Poly(ethylene oxide) (PEO) is a hydrophilic uncharged polymer that has been recognized as particularly efficient for achieving protein-resistant surfaces (Harris and Zalipsky, 1997). While most studies deal with the grafting of linear PEO chains to the material surface, changes in the molecular architecture of the polymer are beneficial for higher polymer segment density on the surface and a higher density of end-group-functionalities. In this chapter, we focus on star-shaped PEO molecules and especially on their use for the preparation of biofunctional surfaces that can be used for single-molecule experiments. Layers consisting of cross-linked, end-functionalized, six-armed, PEO-based star molecules were found to be as good as or better than linear-PEO-modified surfaces at reducing protein adsorption (Groll et al., 2004, 2005a). In contrast to the effort that is necessary to obtain surfaces with high grafting density by the surface grafting of linear PEO, such films can be prepared by simple spin or dip coating from aqueous solution, since chemical cross-linking ensures a high polymer segment density on the substrate (Gasteier et al., 2007). Since the reactive end-groups can be used for further functionalization, particular attention is paid to the ability to generate biofunctional films by a one-step preparation method through spin-casting. The experimental procedure for substrate preparation will be discussed in detail, and examples are given for single-molecule experiments demonstrating the negligible nonspecific interaction of proteins with the surface and the unperturbed function of proteins that are immobilized on such coatings.

2. Surface Grafting of PEO and Protein Repellence The general strategy to render surfaces inert toward proteins is to introduce a coating layer that prevents protein adsorption either thermodynamically, so that attractive surface interactions are overcompensated by repulsive interactions with the layer, or at least kinetically by creating a free energy barrier of sufficient height that cannot be overcome on relevant time scales (Halperin, 1999). An abundance of studies have shown that PEO-coated surfaces display exceptional protein resistance (Gasteier et al.,

Star Polymer Surface Passivation for Single-Molecule Detection

3

2007; Harder et al., 1998; Harris and Zalipsky, 1997; Kingshott et al., 2002; Malmsten et al., 1998; McPherson et al., 1998; Sofia et al., 1998; Unsworth et al., 2008). On substrates such as glass or silicon, protein-repellant coatings are frequently made from long, randomly coiling linear PEO chains terminally anchored to the surface. Only in the brush regime, the grafting density of linear chains is high enough that the attached polymer chains stretch out perpendicularly to the surface, thus avoiding unfavorable monomer–monomer interactions and maintaining optimal solvation. Consequently, the grafted chains provide adequate coverage and thickness to form a very effective steric barrier against protein adsorption (Szleifer and Carignano, 2000; Yang et al., 1999). Grafting density and chain length are thus the two essential experimental control parameters by which the degree of protein resistance is governed (Malmsten et al., 1998; McPherson et al., 1998; Unsworth et al., 2006). It has recently been shown that, for molecular weights between 600 and 2000 g/mol, a grafting density of 0.5 linear OH-terminal PEO chains/nm2 is the threshold for minimal protein adsorption (Unsworth et al., 2008). Star-shaped PEO molecules (star PEO) have a central core region from which the PEO arms extend. Due to this constraint, their density is higher than that of a linear chain, which offers the opportunity to produce PEO surfaces with higher grafting density (Douglas et al., 1990; Sofia et al., 1998). Moreover, the ends of the arms are preferentially located near the periphery due to the steric constraints in the interior of the star (Irvine et al., 1996). Therefore, the probability is increased for end-functionalized groups to bind to the surface. Star PEO systems thus appear an attractive choice to confer protein resistance to surfaces. Indeed, star PEO with 70 arms and a molecular weight of 5200 g/mol per arm have been reported to pack closely on the surface and to efficiently reduce protein adsorption, although the efficiency is reduced for small proteins such as cytochrome c (Sofia et al., 1998). In another study, star PEO with 24 arms and a molecular weight of 9700 g/mol per arm as well as star PEO with 72 arms and a molecular weight of 4500 g/mol per arm were surface grafted (Irvine et al., 1998). Atomic force microscopy and reflectivity measurements show that the hydrated star molecules are overlapping, and since the star segments are depleted near the substrate, the authors explain the residual adsorption by the diffusion of small proteins such as the 12,000 g/mol cytochrome c through the low PEO density seams between molecules and subsequent surface adsorption. As a result, surfaces obtained by grafting the smaller star PEO molecules prevent protein adsorption better since their packing on the surface is denser. By contrast, due to the spherical shape of the highmolecular-weight PEO stars, gaps remain between the stars that appear sufficiently large for small proteins to reach the surface and adsorb to it. From these protein-adsorption properties of surfaces obtained by the grafting of PEO stars with different sizes, two strategies become clear and these have to be followed in order to improve star PEO-derived surface

4


coatings. First, both the number and molecular weight of the arms have to be reduced. Smaller stars seem better for the modification of surfaces since their packing is denser on the surface. In addition, a more flexible core than the poly-divinylbenzene core used in the aforementioned studies would make the stars more flexible and, in combination with a smaller number of arms, less spherical. A second approach is to functionalize the stars with reactive groups at the ends of the arms that enable intermolecular crosslinking of the PEO stars. Covalently cross-linked stars on the surface will result in a more homogeneous lateral PEO density profile and higher surface coverage. Moreover, cross-linking would allow for a more variable control of the layer thickness and the preparation of layers that are thicker than monolayers, since the end-groups are not restricted to lateral reactions. A further advantage concerns the functionalization of stars with molecules that react with the end-groups. The spatial distribution of such molecules in the layer can be controlled on the nanoscale by attaching them to the stars before or after surface grafting (Maheshwari et al., 2000). In this way, either a random distribution or a nanoclustered ligand pattern can be achieved.

3. The NCO–sP(EO-stat-PO) System We followed both strategies mentioned in the last paragraph for the development of our six-arm, star-shaped molecules with terminal reactive functional groups. The backbone consists of a statistical copolymer of ethylene oxide and propylene oxide in a ratio of 4:1; each arm has a molecular mass of 2000 g/mol with low polydispersity and is attached to a sorbitol core (sP(EO-stat-PO)). The arms of the star molecules are initially terminated with OH and can be functionalized with various reagents to yield molecules with different reactivities. This chapter will concentrate on isocyanate (NCO–) terminated star molecules (NCO–sP(EO-stat-PO)) that are obtained through functionalization with isophorone diisocyanate (IPDI; Goetz et al., 2002). As IPDI is chemically attached to the star molecules without a catalyst, the primary, less reactive aliphatic isocyanate groups remain as functional groups at the ends of the arms, so that the NCO–sP (EO-stat-PO) molecules can be dissolved in water and coatings can be applied from aqueous solutions. When the NCO–sP(EO-stat-PO) material is dissolved in water, hydrolysis of the isocyanate groups lead to the formation of carbaminic acid which, at neutral pH, instantly decarboxylates to form amine groups. These amines react with unreacted isocyanate groups to form urea bridges between the NCO–sP(EO-stat-PO) molecules. Since the kinetics of amine addition to isocyanate is much faster than hydrolysis (Caraculacu and Coseri, 2001), urea bridge formation occurs preferentially until steric restrictions significantly lower the reaction probability.

5


The aqueous NCO–sP(EO-stat-PO) solution can be used for coating surfaces either by simple dip-, spin-, or spray-coating. However, due to the ongoing hydrolysis and aminolysis of isocyanate groups, a time window of maximum 20 min after the addition of water to NCO–sP(EO-stat-PO) should not be exceeded. After coating, the system requires at least 12 h for completion of the cross-linking reaction within the layer. During this time, all isocyanate groups hydrolyze and then either react with other isocyanate groups to form urea bridges or remain as free amino groups that can be further functionalized (Groll et al., 2005a,b,c). Figure 1.1 shows the chemical reactions that occur during film formation and presents a model of the resulting surface coatings. One particular advantage of the NCO–sP(EO-stat-PO) system is the change in reactivity from isocyanate groups, which are reactive toward nucleophilic groups, such as alcohols, amines, and thiols, to amine groups during the layer preparation and curing of the coating. Addition of watersoluble compounds that bear nucleophilic groups to the aqueous NCO–sP (EO-stat-PO) solution before coating thus results in covalent attachment of these molecules to the coating. It is important to emphasize that, after A NCO-sP(EO-stat-PO) EO-stat-PO RO

4 OR

R=

O m

IPDI

O O

n

NH

NCO

OR Mn = 2 kDa/arm; m = 0.8; n = 0.2 Cross-linking:

=

R

NH2

R2

NCO + H2N R

R2

-

NCO + H2O

-

R

O

N-C-N H H

R

B

Figure 1.1 Surface coating with star polymers. (A) Schematic of the chemical composition of the NCO–sP(EO-stat-PO) system and the cross-linking reaction induced by water. (B) Schematic of a cross-linked sP(EO-stat-PO) surface coating where all isocyanate groups are hydrolyzed or aminolyzed resulting in urea bridges between the stars (yellow) and free amino groups (green). Figure partially reprinted with permission from Heyes et al. (2007), copyright Royal Society of Chemistry.

6


complete hydrolysis of the isocyanate groups, the compounds that are covalently bound to the layers are embedded in a coating that inhibits nonspecific interactions with proteins and cells, so that the immobilized molecules can interact specifically. This feature is achieved in a one-step layer preparation without the use of further chemical blocking-agents. The remainder of this chapter will focus on the preparation of substrates for single-molecule experiments according to this layer preparation method; a broader overview of different strategies for functionalization and application of the NCO–sP(EO-stat-PO) system for cell culture and biomaterials has recently been given elsewhere (Gasteier et al., 2007).

4. Preparation of sP(EO-stat-PO)-Coated Substrates for Single-Molecule Experiments Fluorescence is among the most sensitive analytical tools available and has been extensively applied to study biomolecules. In order to achieve single-molecule detection on surfaces, it is of utmost importance that the substrates have extremely low background fluorescence. Consider that a standard wide field fluorescent microscope has a point spread function approximately half the wavelength of the emitted light, which is 300 nm for visible fluorophores. The fluorescent label has a diameter of 1 nm. Therefore, in order to observe a single molecule, the number of emitted photons from the fluorophore covering approximately a 1 1 nm2 area must be significantly higher than the integrated background fluorescence over the entire 300 300 nm2 area. This stringent requirement necessitates that all preparation steps are carried out either in a clean room, or under a laminar flow hood with an air-filtration system. Glass slides, chemicals, solvents, and especially, the aminofunctional material used to functionalize the substrate and the PEO polymers, must be of the highest purity possible. The substrates are prepared according to the following steps:

Ultrasonication in water for 2 min. Ultrasonication in isopropanol for 2 min. Cleaning and activation in a plasma oven or by UV/ozone treatment.

We have used different plasma machines, for example, the TePla 100-E system with 100 W at a process gas pressure of 0.5 mbar, with either oxygen or filtered air as flow gas, and process times between 10 and 15 min. For UV/ozone treatment, we have used a home-made device using a 40 W UV lamp (main emission 185 nm; UV-Technik Speziallampen GmbH) in an oxygen stream of 350 ml/min with a sample distance of 5 mm to the lamp for 10–15 min. Both processes result in clean substrates that were suitable for single-molecule experiments.


7

To covalently bind NCO–sP(EO-stat-PO) to the substrate, the surface must be functionalized with isocyanate-reactive groups, such as alcohols, amines, or thiols, as anchor points. Since the NCO–sP(EO-stat-PO) molecules cross-link on the substrates, the system tolerates a much lower number of functional groups on the surface than other systems that use classical grafting techniques. Furthermore, the cross-linking also results in a certain stability of the film against desorption from the surface in aqueous solution even without covalent attachment. For contact times with aqueous solutions of less than 10 h, films are sufficiently stable and may simply be coated on cleaned glass substrates. If covalent attachment is necessary, amino functionalization may be achieved by a variety of methods, for example, electrostatic adhesion of polyamines such as poly-L-lysine, chemical vapor deposition of 4-amino [2,20 ]-paracyclophanes, or aminosilanization. We have used aminosilanization according to the following protocol:

Cleaning and activation of the substrates as described earlier. Transfer of the substrates into a glove box under nitrogen atmosphere. Immersion into a solution of 3 ml N-[3-(trimethoxysilyl)propyl] ethylenediamine in 50 ml dry toluene for 2 h. Aminopropylsilane (APTES) may be used alternatively. Repeated rinsing of the substrates with dry toluene. Storage of the substrates in dry toluene until further use. Alternatively, the commercial reagent VectabondTM from Vector Labs may be used according to the detailed protocol provided by the supplier. While this method can be performed without the need of a glove box, it is important to use a new, unopened bottle of Vectabond each time, as it does not stay clean for long after it has been opened. Spin-coating of aqueous NCO–sP(EO-stat-PO) solutions provides precise control of the layer thickness via rotation speed and prepolymer concentration and results in homogeneous layers (Groll et al., 2005b). NCO–sP(EO-stat-PO) is preweighed in portions of typically 50 mg in nitrogen atmosphere and provided in airtight glass vials. For spin-coating, anhydrous THF is added to the vial to predissolve the prepolymer, so that upon the addition of water, a homogeneous mixture is formed immediately. Typically, THF is added to result in solutions with a concentration of 10–20 mg/ml NCO–sP(EO-stat-PO). Then, water is added until the aqueous solution is diluted to typically 1 mg/ml NCO–sP(EO-stat-PO). After gentle shaking to ensure homogeneous mixing, the solution is left to react for exactly 5 min. After this time, the solution is slightly opaque. In the meantime, the aminosilanized glass coverslip is placed on the spin coater. The solution is drawn up into a syringe, and a 0.02-mm membrane filter (Whatman Anotop 10) is attached to the syringe Luer connection. The solution is pressed through the filter directly onto the amino functional coverslip placed on the spin coater. The whole coverslip is homogeneously

8


covered with solution (0.5 ml is needed per 24 24 mm coverslip). It is important not to touch the coverslip with the syringe as this may cause problems with the homogeneity of the spin-coating. The spin coater is turned on and the substrate rotated at 2500 rpm for 45 s. After that, the coverslip is placed into a glass petri dish that has been cleaned either by plasma- or UV/ozone treatment. The petri dish is covered, sealed with parafilm, and stored at ambient conditions over night for cross-linking of the surface. Figure 1.2 presents a flow diagram for the layer preparation

1

2

3

4

5

Figure 1.2 Flowchart of the coating procedure for generation of NCO–sP(EO-statPO)-coated slides. Glass microscopy slides are cleaned by ultrasonication, activated either by oxygen plasma or UV/ozone treatment and, if long-term stability of the films on the substrates in aqueous conditions is required, subsequently aminofunctionalized (1). These substrates are fixed on a spin coater (2), ideally in dust-free or (not of) dust-reduced conditions, and dropwise covered with an aqueous solution of NCO–sP (EO-stat-PO) 5 min after dissolution of the star-shaped prepolymers in a typical concentration of 1 mg/ml. The solution is dropped onto the substrate from a syringe and filtered through 0.02 mm syringe filters (3). When the substrate is completely covered by the solution, spin-casting is initiated (4) with 2500 rpm and left rotating for 45 s. Afterward, the samples are carefully taken off the spin-coater using a teflon tweezer (5) and stored for 24 h in clean glass petri dishes under ambient conditions (ideally dust free or dust reduced) for cross-linking of the coating.


9

procedure. As hydrolysis and subsequent cross-linking between the starmolecules continuously proceed in solution, only a limited number of maximally five substrates can be produced from each solution. The remaining aqueous NCO–sP(EO-stat-PO) solution has to be discarded. It was shown using scanning confocal fluorescence microscopy with single-molecule detection sensitivity that the background fluorescence of cross-linked sP (EO-stat-PO) surfaces carefully prepared according to this protocol is low enough to detect the fluorescence of single molecules (Groll et al., 2004). The nonfouling (passivation) properties of sP(EO-stat-PO) coatings were compared to surfaces modified with linear methoxy-terminated PEO chains and BSA (Groll et al., 2004; Koopmans et al., 2008). In both studies, the sP (EO-stat-PO) films exhibited superior nonfouling properties (Fig. 1.3). For binding of proteins to such cross-linked sP(EO-stat-PO) films, ligands for specific immobilization have to be covalently linked to the polymer. One often-used coupling-system of proteins to surfaces relies on the complex formation between biotin and streptavidin. Streptavidin recognizes biotin with high specificity and affinity, binding with a Kd of 10 15 M. Streptavidin is tetravalent toward biotin and is able to subsequently bind a biotinylated protein of interest. Biotinylated surfaces may be prepared by the addition of biocytin, a biotin derivative that contains a free amine group, to the aqueous NCO–sP(EO-stat-PO) solution prior to spin coating. Experimentally, only one variation of the layer preparation protocol above is necessary. Instead of adding pure water to the NCO–sP(EOstat-PO) material dissolved in THF, an aqueous solution of biocytin is added. During the 5- min interval between mixing and spin-casting, the amine group of biocytin reacts with the isocyanate groups of the polymer. After spin-casting, the covalently linked biotin moieties are homogeneously distributed in the polymer film. The amount of biocytin that is dissolved in water determines the degree of layer functionality. Typically, 2 mg of biocytin are used per 50 mg NCO–sP(EO-stat-PO) prepolymer. In order to perform single-molecule measurements on such substrates, first streptavidin has to be bound to the biotin, followed by binding of the biotinylated and fluorescently labeled protein to the streptavidin. All these steps should be performed in aqueous solution, so that sequential flushing of solutions has to be enabled. This can be achieved by constructing substrate ‘‘sandwiches’’ following the procedure schematically shown in Fig. 1.4. One 32 24 mm coverlip and one 20 20 mm coverslip are required for each sandwich. At least one of the substrates has to be coated with a biotinylated cross-linked sP(EO-stat-PO) film, whereas the second one may be coated with a nonfunctionalized sP(EO-stat-PO) layer. The sandwiches are prepared by taking the large coverslip from the petri dish and placing two pieces of double-sided tape on the upside to leave a 2–3 mm channel in the center. Then, the small coverslip is placed on top of the tape. Care should be taken to ensure that the polymer-coated upside now faces

10

A


RNase H 1000 Background

Density of spots (mm−2)

100

Unspecific adsorption

10

1

0.1

0.01

sP(EO-stat-PO) B 100

Linear PEO5000

BSA

Nucleosomes sP(EO-stat-PO)

100

Linear PEO5000

100

75

75

75

50

50

50

25 0

5 mm

25 0

5 mm

25

BSA

5 mm

0

Figure 1.3 Quality of surface passivation. Nonspecific protein adsorption on crosslinked sP(EO-stat-PO) films is compared to that on grafted linear PEO5000 and physisorbed BSA using single molecules of Alexa Fluor 546 labeled RNase H (A, density of spots) and Cy3-ATTO647N labeled nucleosomes (B, fluorescence images and normalized fluorescence signal intensities). Significantly higher levels of nonspecific adsorption were observed on BSA than on PEO surfaces. sP(EO-stat-PO) surfaces showed negligible nonspecific adsorption. Figure partially reprinted with permission from Groll et al. (2004), copyright American Chemical Society and Koopmans et al. (2008), copyright Wiley-VCH Verlag GmbH& Co. KGaA.

down into the channel. The tape is cut along the edges of the coverslip and the sandwich is placed in a clean, sealed glass petri dish to transport to the microscope. For the experiments, the streptavidin solution (typically 20 mg/ml) and biotinylated/labeled protein (typically 200 pM) are flushed through the channel by adding a droplet of solution to one open side of the channel and waiting for 10 min each time before the removal of the droplet and addition of the next one.

11


A

1 B

C

2

4

3

5

Figure 1.4 Schematic of substrate preparation for single-molecule experiments. For optimal results, preparation should be carried out under clean room conditions. The substrate-sandwiches are prepared by taking the large coverslip (32 mm 24 mm; (1)) from the petri dish, and placing two pieces of double-sided tape (2) on the upside to leave a 2–3 mm channel in the center (A). Then, the small coverslip (20 20 mm; (3)) is placed on top of the tape with the coated side facing down toward the big coverslip (B). The tape is cut along the edges of the coverslip, and the sample can be placed in a clean, sealed glass petri dish to transport to the microscope. The channel between the two coated coverslips (4) allows for repeated flushing with solutions by adding a droplet at the edge of the small glass slide (5) and waiting for 10 min.

5. Analysis of Protein Structure and Function on NCO–sP(EO-stat-PO) Surfaces To take advantage of the applications of surface-immobilized proteins, for example, as biosensors, it is necessary to achieve: (i) high preference of specific adsorption over nonspecific adsorption, and (ii) binding of the protein in its native, functional structure. Ideally, the protein should completely refold into its native form if it is temporarily exposed to denaturing conditions. Maintenance of the folded state of the protein and its ability to refold after denaturation can be addressed using single-molecule fluorescence (or Fo¨rster) resonance energy transfer (FRET). More specifically, the labeling of proteins with two spectrally different fluorophores enables experiments in which the fluorophore with the higher excitation energy, the donor, is selectively excited. The energy is then nonradiatively transferred via dipole–dipole coupling to the lower energy fluorophore, the acceptor (Fo¨rster, 1948; Stryer and Haugland, 1967). Since the efficiency of this process is proportional to

12


R 6, where R is the distance between the two chromophores, structural information of the protein may be inferred from the FRET efficiency. In order to study single-molecule FRET of surface-immobilized molecules, scanning confocal microscopy or total internal reflection microscopy may be used to limit background fluorescence. A schematic representation on how FRET is used to infer the structural details of immobilized biomolecules is presented in Fig. 1.5. The surface is coated with a protein-resistant material, such as linear PEO or crosslinked sP(EO-stat-PO), which contains a bioactive group such as biotin (represented as a red antenna). In order to compare the cross-linked sP (EO-stat-PO) with other surface preparation techniques, linear-PEOcoated surfaces were prepared by grafting linear PEO (MW ¼ 5000 Da) with amine-reactive NHS end-groups from aqueous solution, of which a small fraction (1%) was also functionalized with biotin. Cross-linked sP (EO-stat-PO) surfaces were prepared as described earlier in a convenient, single-step layer preparation. Subsequent addition of streptavidin to these surfaces and then of biotinylated, FRET-labeled protein as described earlier allows specific immobilization of the protein. Maintenance of a functional protein structure can be followed through the FRET efficiency. Upon structural changes and unfolding of the peptide chain, the distance between the chromophores increases and the efficiency of energy transfer decreases so that an increased fluorescence of the donor dye can be detected. By this method, the binding specificity of biotinylated and FRET-labeled nucleosomes to three different surfaces and especially, the structural integrity of the surface-bound nucleosomes, were measured (Koopmans et al., 2008). On biotinylated BSA, binding specificity was only 2%, and only 28% of the immobilized nucleosomes retained structural integrity. On linear PEO5000, the values increased to 60% and 53%, respectively. Cross-linked sP(EO-stat-PO) films, by contrast, resulted in 90% specificity of binding, and 78% of the immobilized nucleosomes were bound in their intact structure. Spontaneous unwrapping of nucleosomal DNA, so called nucleosome breathing, was measured on the surfaceimmobilized nucleosomes and the dynamics of the process compared to that in solution. The lifetimes of both the closed and the open states are approximately fivefold faster on cross-linked sP(EO-stat-PO) films than the dynamics observed on the linear-PEO-coated surface (1.5 s closed state, 120 ms open state), and they perfectly agree with the breathing kinetics of nucleosomes in solution (Li et al., 2005). Thus, nucleosomes can be specifically immobilized on sP(EO-stat-PO) coatings while maintaining their structural integrity and their dynamic nature. In order to study the interaction of specifically bound proteins with the NCO–sP(EO-stat-PO) surface and ask whether immobilized proteins refold into their functional structure after temporary denaturation, biotinylated RNase H was labeled with Alexa Fluor 546 and Alexa Fluor 647 and

13


Alexa546

FRET

Alexa647

h•n h•n

h•n

h•n

Unfolding Refolding

6 M GdmCl

Buffer

sP(EO-stat-PO)

Buffer

0.5 1.0 0.0 0.5 1.0 0.0 0.5 1.0 FRET efficiency FRET efficiency FRET efficiency

0.0

0.5 1.0 0.0 0.5 1.0 0.0 0.5 1.0 FRET efficiency FRET efficiency FRET efficiency

Linear PEO

0.0

Figure 1.5 Schematic illustration of the FRET technique used to monitor structural information of immobilized proteins. In the folded state, the dye molecules, which are placed at specific sites on the protein, are close together. Upon excitation of the donor dye (green), a high transfer efficiency of the energy to the acceptor dye (red) occurs. If the protein is unfolded, the distance between the dyes increases and consequently, the energy transfer efficiency decreases. The distance dependence of the FRET efficiency can be used to infer details of the protein structure. The pictures show example scanning confocal fluorescence microscopy images of RNase H proteins immobilized on NCO–sP(EO-stat-PO)-coated surfaces and the resulting single-molecule FRET histograms of RNase H immobilized on NCO–sP(EO-stat-PO) and linear-PEO5000coated surfaces under buffer conditions, 6 M guanidinium chloride (GDmCl) and then subsequently reimmersed in buffer. The green fraction centered at zero FRET efficiency represents molecules that have no acceptor molecule due to incomplete labeling or dye photobleaching. The red fraction at high (0.9)-FRET efficiency are molecules in their folded state. The yellow fraction at low-to-intermediate FRET efficiency ( 0.4) represents molecules in their unfolded state. Figure partially reprinted with permission from Groll et al. (2004), copyright American Chemical Society.

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bound to the biotinylated NCO–sP(EO-stat-PO) layers via streptavidin. The FRET dye pair was chosen and placed at sites on the protein so that a high-FRET efficiency is observed as long as the protein maintains its folded state. If the protein loses its compact-folded structure, the average distance between the dyes increases and the FRET efficiency is reduced. RNase H was labeled with Alexa Fluor 546 and Alexa Fluor 647 (Molecular Probes, ˚ in buffer) at amino acids 3 and 135, respectively Eugene, OR, R0 ¼ 66 A (Kuzmenkina et al., 2006). As a result, when unfolding of the protein chain is induced, the distance between the dyes increases and the donor fluorescence becomes detectable. If the peptide chain is able to refold to its initial conformation, the energy is again transferred to the acceptor dye and the fluorescence of this chromophore dominates. Exemplary scanning confocal fluorescence microscopy images of single, specifically immobilized, FRET-labeled RNase H on cross-linked sP(EO-stat-PO) surfaces are shown in Fig. 1.5, together with histograms of the calculated FRET efficiency of many single molecules on both linear PEO and cross-linked sP (EO-stat-PO) surfaces. The histograms in Fig. 1.5 are colored, based on their FRET efficiency ranges, to indicate proteins that are folded (red) or unfolded (yellow) or contain no acceptor dye and thus, cannot be structurally interrogated (green). For RNase H immobilized on linear PEO surfaces under buffer conditions, it is evident that there is a large distribution of FRET efficiencies from molecule to molecule, indicating that the proteins adopt a wide range of structures (many of them in a low-to-intermediate (unfolded) FRET state), while on cross-linked sP (EO-stat-PO) surfaces, practically all molecules that contain both dyes are in a high-FRET state, indicating that the folded state of RNase H is maintained for most molecules (Amirgoulova et al., 2004; Groll et al. 2004). Upon exposure of immobilized RNase H on either linear or crosslinked sP(EO-stat-PO) surfaces to high concentrations of guanidinium chloride (GdmCl), a reduction in the FRET efficiency was observed, indicating that the molecules unfold. Upon exchanging the denaturant for normal buffer conditions once again, practically all the RNase H proteins immobilized on cross-linked sP(EO-stat-PO) surfaces were able to refold to their compact high-FRET state. In contrast, on the linear PEO surfaces, once the protein molecules completely unfolded, practically none were able to refold to their high-FRET folded state. Moreover, on the cross-linked sP (EO-stat-PO) surfaces, the unfolding–refolding of RNase H molecules was found to be completely reversible over at least 50 cycles of adding and removing GdmCl (Amirgoulova et al., 2004). In Fig. 1.6, the FRET state of the same single molecules before and after 50 cycles of adding and removing 6 M GdmCl was followed. The ability of the molecules to fold to the same high-FRET state after multiple denaturation–renaturation cycles is suggestive that the proteins are in or at least close to their native state. Further evidence stems from whether the protein is still able to function on the

15


B

A

C DNA RNA

Dye quenched Q Quencher

D

E

Fluorescence (a.u.)

Folded on sP(EO-stat-PO) Refolded on sP(EO-stat-PO) Enzyme in solution 0

100 200 Time (s)

300

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20

40

60

ka/s-1mM-1

Figure 1.6 Scanning confocal fluorescence microscopy image of RNase H molecules immobilized on cross-linked sP(EO-stat-PO) surfaces before (A) and after (B) 50 cycles of unfolding–refolding. The same molecules that were folded before the 50 cycles were shown to completely refold after, and are highlighted in both figures. There are always a fraction of molecules that have no acceptor dye but have a donor dye. These green molecules are ignored as we cannot infer structural information from them. In the right image, some of the molecules that were visible in the left frame are no longer visible in the right frame, due to photobleaching during the scanning. Panel (C) shows a schematic representation of the enzymatic assay of RNase H immobilized on cross-linked sP(EOstat-PO) surfaces. A fluorescently-quenched DNA–RNA hybrid dissociates upon RNA cleavage by the RNase H. (D) Increase in fluorescence of the dye following RNA cleavage with time upon exposure to RNase H immobilized on cross-linked sP(EO-stat-PO) both before and after an unfolding–refolding cycle. The refolding curve has been offset vertically for presentation purposes. (E) Calculated activity coefficients of the RNase H in solution, upon immobilization on cross-linked sP(EO-stat-PO), and following an unfolding– refolding cycle on the cross-linked sP(EO-stat-PO). Figure partially reprinted with permission from Heyes et al., 2007, copyright Royal Society of Chemistry.

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surface. The function of RNase H is to cleave RNA–DNA hybrids (Kanaya, 1998). An enzymatic assay for RNase H was previously developed that uses a fluorescently labeled RNA–DNA construct (Hogrefe et al., 1990). The hybrid contains a fluorescent dye and a quencher, so that it does not fluoresce in its uncleaved state. Once exposed to RNase H, the RNA is cleaved and the DNA–RNA hybrid dissociates. This cleavage separates the quencher from the dye, and the dye fluoresces. By following the increase in fluorescence over time for the DNA–RNA hybrid exposed to RNase H specifically immobilized on sP(EO-stat-PO) surfaces, one is able to determine the activity coefficient of the enzyme. The results of this assay are shown in Fig. 1.6. Compared to the enzyme in solution, the activity coefficient of the enzyme is both unaffected by immobilization and returns to the same value after unfolding and refolding on the sP (EO-stat-PO) surface. More details of these FRET experiments with surface-bound RNase H are described elsewhere (Heyes et al., 2007).

ACKNOWLEDGMENTS We thank G. Ulrich Nienhaus, Colin D. Heyes, Wiepke J. A. Koopmans, and John van Noort for their cooperation. This work was financially supported by the VW-foundation (project self-assembled hydrogel layers) and the German Science Foundation (DFG, graduate school 1035 ‘‘Biointerface’’ and Project B1 in the TR-SFB 37).

REFERENCES Amirgoulova, E. V., Groll, J., Heyes, C. D., Ameringer, T., Ro¨cker, C., Mo¨ller, M., and Nienhaus, G. U. (2004). Biofunctionalized polymer surfaces exhibiting minimal interaction towards immobilized proteins. ChemPhysChem 5, 552–555. Caraculacu, A. A., and Coseri, S. (2001). Isocyanates in polyaddition processes. Structure and reaction mechanisms. Prog. Polym. Sci. 26, 799–851. Douglas, J. F., Roovers, J., and Freed, K. F. (1990). Characterization of branching architecture through "universal" ratios of polymer solution properties. Macromolecules 23, 4168–4180. Fo¨rster, T. (1948). Zwischenmolekulare Energiewanderung und Fluoreszenz. Ann. Physik. 2, 55–75. Gasteier, P., Reska, A., Schulte, P., Salber, J., Offenhaeusser, A., Moeller, M., and Groll, J. (2007). Surface grafting of PEO-based star-shaped molecules for bioanalytical and biomedical applications. Macromol. Biosci. 7, 1010–1023. Goetz, H., Beginn, U., Bartelink, C. F., Gruenbauer, H. J. M., and Mo¨ller, M. (2002). Preparation of isophorone diisocyanate terminated star polyethers. Macromol. Mater. Eng. 287, 223–230. Groll, J., Amirgoulova, E., Ameringer, T., Heyes, C. D., Ro¨cker, C., Nienhaus, G. U., and Mo¨ller, M. (2004). Biofunctionalized, ultrathin coatings of crosslinked star-shaped poly (ethylene oxide) allow reversible folding of immobilized proteins. J. Am. Chem. Soc. 126, 4234–4239.


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Groll, J., Ademovic, Z., Ameringer, T., Klee, D., and Mo¨ller, M. (2005a). Comparison of coatings from reactive star shaped PEG-stat-PPG prepolymers and grafted linear PEG for biological and medical applications. Biomacromolecules 6, 956–962. Groll, J., Ameringer, T., Spatz, J. P., and Mo¨ller, M. (2005b). Ultrathin coatings from isocyanate-terminated star PEG prepolymers: Layer formation and characterization. Langmuir 21, 1991–1999. Groll, J., Haubensak, W., Ameringer, T., and Moeller, M. (2005c). Ultrathin coatings from isocyanate terminated star PEG prepolymers: Patterning of proteins on the layers. Langmuir 21, 3076–3083. Halperin, A. (1999). Polymer brushes that resist adsorption of model proteins: Design parameters. Langmuir 15, 2525–2533. Harder, P., Grunze, M., Dahint, R., Whitesides, G. M., and Laibinis, P. E. (1998). Molecular conformation in oligo(ethylene glycol)-terminated self-assembled monolayers on gold and silver surfaces determines their ability to resist protein adsorption. J. Phys. Chem. B 102, 426–436. Harris, J. M., and Zalipsky, S. (1997). Poly(ethylene glycol): Chemistry and Biological Applications. American Chemical Society, Washington, DC. Heyes, C. D., Groll, J., Moeller, M., and Nienhaus, G. U. (2007). Synthesis, patterning and applications of star-shaped poly(ethylene glycol) biofunctionalized surfaces. Mol. Biosyst. 3, 419–430. Hogrefe, H. H., Hogrefe, R. I., Walder, R. Y., and Walder, J. A. (1990). Kinetic analysis of Escherichia coli RNase H using DNA-RNA-DNA/DNA substrates. J. Biol. Chem. 265, 5561–5566. Irvine, D. J., Mayes, A. M., and Griffith-Cima, L. (1996). Self-consistent field analysis of grafted star polymers. Macromolecules 29, 6037–6043. Irvine, D. J., Mayes, A. M., Satija, K. S., Barker, G. J., Sofia-Allgor, S. J., and Griffith, L. G. (1998). Comparison of tethered star and linear poly(ethylene oxide) for control of biomaterials surface properties. Biomed. Mater. Res. 40, 498–509. Kanaya, S. (1998). Enzymatic activity and protein stability of E. coli ribonuclease HI. In ‘‘Ribonucleases H,’’ (R. J. Crouch and J. J. Toulme, eds.), INSERM, Paris. Kingshott, P., Thissen, H., and Griesser, H. (2002). Effects of cloud-point grafting, chain length, and density of PEG layers on competitive adsorption of ocular proteins. Biomaterials 23, 2043–2056. Koopmans, W. J. A., Schmidt, T., and van Noort, J. (2008). Nucleosome immobilization strategies for single-pair FRET microscopy. ChemPhysChem 9, 2002–2009. Kuzmenkina, E. V., Heyes, C. D., and Nienhaus, G. U. (2006). Single-molecule FRET study of denaturant induced unfolding of RNase H. J. Mol. Biol. 327, 313–324. Li, G., Levitus, M., Bustamante, C., and Widom, J. (2005). Rapid spontaneous accessibility of nucleosomal DNA. Nat. Struct. Mol. Biol. 12, 46–53. Maheshwari, G., Brown, G., Lauffenburger, A. D., Wells, A., and Griffith, L. G. (2000). Cell adhesion and motility depend on nanoscale RGD clustering. J. Cell Sci. 113, 1677–1686. Malmsten, M., Emoto, K., and Alstine, J. M. V. (1998). Effect of chain density on inhibition of protein adsorption by poly(ethylene glycol) based coatings. J. Colloid Interface Sci. 202, 507–517. McPherson, T., Kidane, A., Szleifer, I., and Park, K. (1998). Prevention of protein adsorption by tethered poly(ethylene oxide) layers: Experiments and single-chain mean-field analysis. Langmuir 14, 176–186. Sofia, S. J., Premnath, V., and Merrill, E. W. (1998). Poly(ethylene oxide) grafted to silicon surfaces: Grafting density and protein adsorption. Macromolecules 31, 5059–5070. Stryer, L., and Haugland, R. P. (1967). Energy transfer: A spectroscopic ruler. Proc. Natl. Acad. Sci. USA 58, 719–726.

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Szleifer, I., and Carignano, M. A. (2000). Tethered polymer layers: Phase transitions and reduction of protein adsorption. Macromol. Rapid. Commun. 21, 423–448. Unsworth, L. D., Tun, Z., Sheardown, H., and Brash, J. L. (2006). In situ neutron reflectometry investigation of gold-chemisorbed PEO layers of varying chain density: Relationship of layer structure to protein resistance. J. Colloid Interface Sci. 296, 520–526. Unsworth, L. D., Sheardown, H., and Brash, J. L. (2008). Protein-resistant poly(ethylene oxide)-grafted surfaces: Chain density-dependent multiple mechanisms of action. Langmuir 24, 1924–1929. Yang, Z., Galloway, J. A., and Yu, H. (1999). Protein interactions with poly(ethylene glycol) self-assembled monolayers on glass substrates: Diffusion and adsorption. Langmuir 15, 8405–8411.

C H A P T E R

T W O

Azide-Specific Labeling of Biomolecules by Staudinger– Bertozzi Ligation: Phosphine Derivatives of Fluorescent Probes Suitable for Single-Molecule Fluorescence Spectroscopy Anirban Chakraborty,*,†,1 Dongye Wang,*,†,1 Yon W. Ebright,*,† and Richard H. Ebright*,† Contents 20 21 21 22 23 25 25 26 26 27 27 28 28

1. Introduction 2. Materials and Methods 2.1. Materials 2.2. General methods 2.3. Synthesis of Alexa488-phosphine (Fig. 2.1) 2.4. Synthesis of Cy3B-phosphine (Fig. 2.2) ˚ 2.5. Synthesis of Alexa647-phosphine20 A (Fig. 2.3A) 24 A˚ 2.6. Synthesis of Alexa647-phosphine (Fig. 2.3B) 2.7. Azide-specific labeling 2.8. Quantitation of labeling efficiency 2.9. Quantitation of labeling specificity Acknowledgments References

Abstract We describe the synthesis of phosphine derivatives of three fluorescent probes that have a brightness and photostability suitable for single-molecule fluorescence spectroscopy and microscopy: Alexa488, Cy3B, and Alexa647. In addition, we describe procedures for use of these reagents in azide-specific, bioorthogonal * Department of Chemistry and Chemical Biology, Waksman Institute, Rutgers University, Piscataway, New Jersey, USA Howard Hughes Medical Institute, Rutgers University, Piscataway, New Jersey, USA 1 Contributed equally {

Methods in Enzymology, Volume 472 ISSN 0076-6879, DOI: 10.1016/S0076-6879(10)72018-8

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Anirban Chakraborty et al.

labeling through Staudinger–Bertozzi ligation, as well as procedures for the quantitation of labeling specificity and labeling efficiency. The reagents and procedures of this report enable chemoselective, site-selective labeling of azidecontaining biomolecules for single-molecule fluorescence spectroscopy and microscopy.

1. Introduction The Staudinger–Bertozzi ligation involves reaction between a first compound containing an azide moiety and a second compound containing a phosphine moiety with an adjacent methyl ester, and results in coupling of the compounds through an amide linkage (Kiick et al., 2002; Saxon and Bertozzi, 2000; reviewed in Kohn and Breinbauer, 2004; Sletten and Bertozzi, 2009). The reaction is bioorthogonal, since azides and phosphines are not present in natural biomolecules and since azides and phosphines do not react with moieties present in natural biomolecules. The reaction is biocompatible, since it proceeds in aqueous solution under mild conditions at moderate temperatures and moderate pH ranges. The reaction is efficient, and yields of 90% are achieved routinely. The bioorthogonality, biocompatibility, and high efficiency of the Staudinger–Bertozzi ligation render the reaction suitable for two applications: (i) biomolecule-specific labeling of engineered biomolecules containing randomly located azide moieties and (ii) biomolecule-specific, site-specific labeling of engineered biomolecules containing site-specifically incorporated azide moieties. In published work, the reaction has been used for labeling of engineered azide-containing biomolecules in vitro with single proteins, in vitro with mixtures of proteins, in vivo in living cells, and in vivo in living organisms (Kiick et al., 2002; Prescher et al., 2004; Saxon and Bertozzi, 2000). Multiple strategies have been reported for the incorporation of azides into biomolecules, providing potential targets for azide-specific, bioorthogonal labeling through use of the Staudinger–Bertozzi ligation. For example, azides have been randomly incorporated into carbohydrates and proteinlinked carbohydrates by supplying cells with azide-functionalized carbohydrate precursors (Chang et al., 2007; Dube et al., 2006; Hang et al., 2003; Hangauer and Bertozzi, 2008; Laughlin and Bertozzi, 2007; Laughlin et al., 2006; Prescher et al., 2004; Saxon and Bertozzi, 2000; Saxon et al., 2002; Vocadlo et al., 2003); azides have been randomly incorporated into proteins by supplying cells or organisms with azide-functionalized methionine (Kiick et al., 2002; Link and Tirrell, 2003; Link et al., 2004; Ngo et al., 2009); azides have been site-specifically incorporated into proteins in vitro by ligation with azide-functionalized farnesyl, lipoyl, or puromycin surrogates (Baruah et al., 2008; Gauchet et al., 2006; Humenik et al., 2007); and azides have been sitespecifically incorporated into proteins in vitro and in vivo by use of unnatural

Phosphine Derivatives of Fluorescent Probes

21

amino acid mutagenesis (Chin et al., 2002; Deiters et al., 2003; Krieg et al., 1986; Nguyen et al., 2009; Ohno et al., 2007; Tsao et al., 2005). Multiple phosphine derivatives suitable for azide-specific, bioorthogonal labeling through use of the Staudinger–Bertozzi ligation have been reported, including phosphine derivatives of the affinity probe biotin and phosphine derivatives of the fluorescent probes fluorescein, coumarin, tetraethylrhodamine, and Cy5.5 (Chang et al., 2007; Hangauer and Bertozzi, 2008; Lemieux et al., 2003; Saxon and Bertozzi, 2000; Wang et al., 2003). Single-molecule fluorescence spectroscopy requires fluorescent probes that have exceptionally high brightness and exceptionally high photostability (fluorescent probes of greater brightness and photostability than fluorescein, coumarin, and tetraethylrhodamine; reviewed in Ha 2001; Kapanidis and Weiss, 2002; Roy et al., 2008). Single-molecule fluorescence resonance energy transfer (FRET) experiments further require pairs of fluorescent probes capable of serving as an efficient donor/acceptor, wherein the fluorescence emission spectrum of the donor overlaps the fluorescence excitation spectrum of the acceptor. In FRET experiments, the lengths and flexibilities of the linkers between biomolecule and fluorescent probes can significantly affect results; therefore, maximum flexibility in experimental design requires sets of reagents that yield different lengths and flexibilities of linkers between biomolecules and fluorescent probes. Here we report the synthesis of phosphine derivatives of fluorescent probes that have a brightness and photostability suitable for single-molecule fluorescence spectroscopy (Alexa488, Cy3B, and Alexa647; Cooper et al., 2004; Leung et al., 2005; Panchuk-Voloshina et al., 1999), that have a spectral overlap suitable to serve as donor/acceptor pairs for FRET (Alexa488/Cy3B, Alexa488/Alexa647, and Cy3B/Alexa647), and that, in one case, yield alternatively either a moderate-length, flexible biomolecule-probe linker or a ˚ and 9 rotatable bonds longer, more flexible, biomolecule-probe linker (20 A ˚ vs. 24 A and 12 rotatable bonds; Figs. 2.1–2.3). In addition, we report procedures for the application of these reagents in azide-specific, bioorthogonal labeling through use of the Staudinger–Bertozzi ligation and procedures for the quantitation of labeling specificity and labeling efficiency. The reagents and procedures of this report enable chemoselective, site-selective labeling of azide-containing biomolecules for single-molecule spectroscopy.

2. Materials and Methods 2.1. Materials 1-Methyl-2-diphenylphosphinoterephthalate (MDPT) was synthesized as described in Kiick et al. (2002). Alexa Fluor 488 cadaverine, Alexa Fluor 647 cadaverine, Alexa Fluor 647 NHS ester, 1-ethyl-3-

22


H2N

SO3−

SO3−

O

I

NH2+

COOH

O

N H

H2N

MDPT EDAC/NHSS/DIPEA 3 h, 37 ⬚C H2N

SO3−

SO3−

O

NH2+

COOH

II O

H3COOC

N H

N H

O

PPh2

Figure 2.1 Synthesis of Alexa488-phosphine. Staudinger–Bertozzi ligation between ˚ linker between the compound II and an azide-containing biomolecule yields an 18 A biomolecule and the fluorophore (distance measured from first nitrogen atom of azide to fused ring system of fluorophore with fully extended conformation of linker).

(3-dimethylaminopropyl)-carbodiimide (EDAC), and N-hydroxysulfosuccinimide (NHSS) were purchased from Invitrogen (Carlsbad, CA). Cy3B-NHS was purchased from GE Healthcare (Piscataway, NJ). Monotrityl-ethelenediamine (acetic acid salt) was purchased from Novabiochem (Madison, WI). N-Trityl-1,2-ethanediamine (hydrobromide salt), N,N0 - trifluoroacetic acid (TFA), triethylamine (TEA), diisopropylethylamine (DIPEA), and N,N0 -dimethylformamide (DMF) were purchased from Sigma-Aldrich (Milwaukee, WI). Bio-Gel P30 was purchased from BioRad (Hercules, CA).

2.2. General methods Reversed-phase HPLC was performed on a Hitachi L7100 instrument using Supelco Discover Bio C18 column (25 cm 10 mm, 10 mm). All solutions for HPLC were deoxygenated by bubbling argon for 15 min. Flash chromatography was performed using silica gel (230–400 mesh, 60 A˚). MALDI-MS was performed on an Applied Biosystems MDS SCIEX 4800 instrument.

23


O SO3−

N-O

III

O

O

N+

N O

TrNH(CH2)2NH2 1 h, 25 ⬚C TrHN

IV

H N

SO3− O

N+

N O

20% TFA 1 h, 25 ⬚C H2N

V

H N

SO3− O

N+

N O

O N H

VI H3COOC

PPh2

MDPT EDAC/NHSS/DIPEA 3 h, 37 ⬚C SO3−

H N O

N+

N O

Figure 2.2 Synthesis of Cy3B-phosphine. Staudinger–Bertozzi ligation between com˚ linker between the pound VI and an azide-containing biomolecule yields an 15 A biomolecule and the fluorophore.

2.3. Synthesis of Alexa488-phosphine (Fig. 2.1) 2.3.1. Alexa488-carboyl-pentylenediaminyl-phosphine (Alexa488-phosphine; II) EDAC (4.2 mg; 21 mmol) in 50 ml degassed water and NHSS (4.2 mg; 16 mmol) in 50 ml degassed water were mixed, and MDPT (5.9 mg; 15 mmol) in 50 ml DMF was added. A precipitate was observed. Degassed water (50 ml) was added, followed by DMF (200 ml), resulting in dissolution of the precipitate. Compound I (Alexa Fluor 488 cadaverine; 1.0 mg; 1.5 mmol; Fig. 2.1) in 50 ml DMF was added, followed by DIPEA (5.6 ml; 31 mmol), and the reaction mixture was incubated for 3 h at 37 C. Product II was purified by reversed-phase HPLC (solvent A: 0.1% TFA in water; solvent B: 100% acetonitrile; gradient: 30–100% B in 30 min at 2 ml/min) and lyophilized. MS (MALDI): calculated, m/z 964.9 (MHþ); found 964.9.

24


A

-

(CH2)3SO3N

O3S(H2C)3 N+ -O

3

S

B

-

-O

SO3-

VII

O

NO

O

(CH2)3SO3-

O3S(H2C)3 N+

N

S

SO3-

3

XI

HN

O

O TrNH(CH2)2NH2 TEA 1 h, 25 ⬚C -O

3

N+

3

N

S

-O

SO3-

VIII HN

S

SO3-

3

HN

33% TFA 30 min, 25 ⬚C

-O

N+

XII

(CH2)3SO3N

O3S(H2C)3 N+

3S

(CH2)3SO3N

3S(H2C)3

-O

O

NHTr

-

MDPT EDAC/NHSS/DIPEA 3 h, 37 ⬚C

(CH2)3SO3-

S(H2C)3

-O

H2N

O

O H3COOC

N H PPh2

SO3-

IX HN

O

NH2 MDPT EDAC/NHSS/DIPEA 3 h, 37 ⬚C -O

(CH2)3SO3N

3S(H2C)3

-O

N+

3S

SO3-

X HN O

O

NH

PPh2 COOCH3 ˚

˚

Figure 2.3 Synthesis of Alexa647-phosphine20 A (A) and Alexa488-phosphine24 A (B). Staudinger–Bertozzi ligation between compound X or XII and an azide-contain˚ linker between the biomolecule ing biomolecule yields, respectively, an 20 or 24 A and the fluorophore.

25


2.4. Synthesis of Cy3B-phosphine (Fig. 2.2) 2.4.1. Cy3B-carboyl-ethylenediaminyl-trityl (IV) Mono-trityl-ethelenediamine (acetic acid salt; 23.5 mg; 65 mmol), compound III (Cy3B-NHS; 5.0 mg; 6.5 mmol), and TEA (60 ml; 430 mmol) were added, in turn, to 200 ml anhydrous DMF, and the reaction mixture was incubated for 1 h at room temperature. Product IV was purified by reversed-phase HPLC (solvent A: water; solvent B: 90% acetonitrile, 10% water; gradient 30–80% B in 30 min at 2 ml/min) and lyophilized. MS (MALDI): calculated, m/z 845.6 (MHþ); found, 845.6. 2.4.2. Cy3B-carboyl-ethylenediamine (V) TFA (50 ml; 0.65 mmol) was added to compound IV (4.2 mg; 5.0 mmol) in 200 ml chloroform, and the reaction mixture was incubated for 1 h at room temperature, and the solvent was evaporated. Product V was purified by reversed-phase HPLC (solvent A: 0.1% TFA in water; solvent B: 100% acetonitrile; gradient: 20–80% B in 30 min at 2 ml/min) and lyophilized. MS (MALDI): calculated, m/z 603.3 (MHþ); found, 603.3. 2.4.3. Cy3B-carboyl-ethylenediaminyl-phosphine (Cy3B-phosphine; VI) EDAC (12.5 mg; 65 mmol) in 50 ml DMF, NHSS (8.8 mg; 65 mmol) in 50 ml DMF, and MDPT (24 mg; 60 mmol) in 50 ml DMF were combined. Compound V (2.4 mg; 4.0 mmol) in 50 ml DMF was added, followed by DIPEA (23 ml; 130 mmol), and the reaction mixture was incubated for 3 h at 37 C. Product VI was purified by reversed-phase HPLC (solvent A: 0.1% TFA in water; solvent B: 100% acetonitrile; gradient: 30–100% B in 30 min at 2 ml/min) and lyophilized. MS (MALDI): calculated, m/z 948.5 (MHþ); found, 948.5. ˚

2.5. Synthesis of Alexa647-phosphine20 A (Fig. 2.3A) 2.5.1. Alexa647-pentanoyl-ethylenediaminyl-trityl (VIII) N-Trityl-1,2-ethanediamine (hydrobromide salt) (23 mg; 60 mmol) was added to compound VII (Alexa Fluor 647 NHS ester; 5.0 mg; 5.0 mmol) in 1 ml DMF. TEA (10.0 ml; 71 mmol) was added and the reaction mixture was incubated for 30 min at room temperature. The reaction mixture was dried under vacuum, redissolved in 0.5 ml ethanol and 20 ml ammonium hydroxide. Product VIII was isolated by flash chromatography and dried under vacuum. MS (MALDI): calculated, m/z 1143.4 (MHþ); found, 1143.4.

26


2.5.2. Alexa647-pentanoyl-ethylenediamine (IX) TFA (100 ml; 1.3 mmol) was added to compound VIII (5.0 mg; 4.4 mmol) in 200 ml chloroform, and the reaction mixture was incubated for 30 min at room temperature. The reaction mixture was dried under vacuum, and product IX was purified using flash chromatography. MS (MALDI): calculated, m/z 901 (MHþ); found, 901. 2.5.3. Alexa647-pentanoyl-ethylenediaminyl-phosphine ˚ (Alexa647-phosphine20 A; X) EDAC (21 mg; 110 mmol) in 250 ml degassed water, NHSS (21 mg; 78 mmol) in 250 ml degassed water, compound IX (5.0 mg; 5.5 mmol) in 200 ml DMF and 50 ml degassed water, and MDPT (30 mg; 75 mmol) in 250 ml DMF were combined. A precipitate was observed. DMF (700 ml) was added, resulting in dissolution of the precipitate. DIPEA (28 ml; 160 mmol) was added, and the mixture was incubated for 3 h at 37 C. Product X was purified by reversed-phase HPLC (solvent A: 0.1% TFA in water; solvent B: 100% acetonitrile; gradient: 30–100% B in 30 min at 2 ml/min) and dried under vacuum. MS (MALDI): calculated, m/z 1248.4 (MHþ); found, 1248.4.

2.6. Synthesis of Alexa647-phosphine24 A (Fig. 2.3B) ˚

2.6.1. Alexa647-pentanoyl-pentylenediaminyl-phosphine ˚ (Alexa647-phosphine24 A; XII) EDAC (21 mg; 110 mmol) in 250 ml degassed water, NHSS (21 mg; 78 mmol) in 250 ml degassed water, compound XI (Alexa Fluor 647 cadeverine; 5.0 mg; 5.5 mmol) in 200 ml DMF and 50 ml degassed water, and MDPT (30 mg; 75 mmol) in 250 ml DMF were combined. A precipitate was observed. DMF (700 ml) was added, resulting in dissolution of the precipitate. DIPEA (28 ml; 160 mmol) was added, and the mixture was incubated for 3 h at 37 C. The product was purified by reversed-phase HPLC (solvent A: 0.1% TFA in water; solvent B: 100% acetonitrile; gradient: 30–100% B in 30 min at 2 ml/min) and was dried under vacuum. MS (MALDI): calculated, m/z 1290.5 (MHþ); found, 1290.5.

2.7. Azide-specific labeling Reaction mixtures (3 ml) contained 20 mM P-azide (derivative of protein P containing a single azide moiety) and 200 mM probe phosphine ˚ (Alexa488-phosphine, ˚ Cy3B-phosphine, Alexa647-phosphine20A, or 24 A Alexa647-phosphine ) in 50 mM Tris–HCl, pH 7.9, 6 M guanidine– HCl, and 5% (v/v) glycerol. Reaction mixtures were incubated for 15 h at 37 C. Reaction mixtures were then applied to 10 ml columns of Bio-Gel


27

P30 preequilibrated in 50 mM Tris–HCl, pH 7.9, 6 M guanidine–HCl, and 5% (v/v) glycerol; columns were washed with 3 ml of the same buffer; and products were eluted in an additional 3 ml of the same buffer.

2.8. Quantitation of labeling efficiency The concentration of the product of the labeling reaction and the efficiency of labeling reaction are determined from UV/Vis-absorbance measurements and are calculated as A280 2F;280 ðA max =2F; max Þ 2P;280 A max =2F; max labeling efficiency ¼ 100% concentration of product

concentration of product ¼

where A280 is the measured absorbance at 280 nm, Amax is the measured absorbance at the long-wavelength absorbance maximum of fluorescent probe F (493, 559, and 652 nm for Alexa488, Cy3B, and Alexa647, respectively), 2P,280 is the molar extinction coefficient of protein P at 280 nm (calculated as in Gill and von Hippel, 1989), 2F,280 is the molar extinction coefficient of fluorescent probe F at 280 nm (8,030 M 1 cm 1, 10,400 M 1 cm 1, and 7,350 M 1 cm 1 for Alexa488, Cy3B, and Alexa647, respectively), and 2F,max is the extinction coefficient of fluorescent probe F at its long-wavelength absorbance maximum (73,000 M 1 cm 1 at 493 nm, 130,000 M 1 cm 1 at 559 nm, and 245,000 M 1 cm 1 at 652 nm for Alexa488, Cy3B, and Alexa647, respectively). Typical labeling efficiencies are 90%.

2.9. Quantitation of labeling specificity The specificity of labeling is determined from the efficiencies of labeling (see preceding section) of (i) the product of the labeling reaction with P-azide and (ii) the product of a parallel labeling reaction with P. The specificity of labeling is calculated as labeling specificity ¼ 100% f1 ½ðlabeling efficiency with PÞ ðlabeling efficiency with P-azideÞg Alternatively, the specificity of labeling can be determined from the fluorescence intensities at the emission maximum of fluorescent probe F (516 nm upon excitation at 493 nm, 570 upon excitation at 559 nm, or 672 nm upon excitation at 652 nm for Alexa488, Cy3B, and Alexa647, respectively) of (i) the product of the labeling reaction with P-azide and

28


(ii) an equal concentration of the product of a parallel labeling reaction with P. In this case, the specificity of labeling is calculated as labeling specificity ¼ 100% f1 ½ðfluorescence with PÞ ðfluorescence with P-azideÞg Typical labeling specificities are 90%.

ACKNOWLEDGMENTS We thank S. Weiss for suggesting identities of fluorescent probes suitable for single-molecule detection. This work was supported by NIH grants GM41376 and AI72766 and a Howard Hughes Investigatorship to R. H. E.

REFERENCES Baruah, H., Puthenveetil, S., Choi, Y. A., Shah, S., and Ting, A. Y. (2008). An engineered aryl azide ligase for site-specific mapping of protein-protein interactions through photocross-linking. Angew. Chem. Int. Ed. Engl. 47, 7018–7021. Chang, P. V., Prescher, J. A., Hangauer, M. J., and Bertozzi, C. R. (2007). Imaging cell surface glycans with bioorthogonal chemical reporters. J. Am. Chem. Soc. 129, 8400–8401. Chin, J. W., Santoro, S. W., Martin, A. B., King, D. S., Wang, L., and Schultz, P. G. (2002). Addition of p-azido-L-phenylalanine to the genetic code of Escherichia coli. J. Am. Chem. Soc. 124, 9026–9027. Cooper, M., Ebner, A., Briggs, M., Burrows, M., Gardner, N., Richardson, R., and West, R. (2004). Cy3B: Improving the performance of cyanine dyes. J. Fluoresc. 14, 145–150. Deiters, A., Cropp, T. A., Mukherji, M., Chin, J. W., Anderson, J. C., and Schultz, P. G. (2003). Adding amino acids with novel reactivity to the genetic code of Saccharomyces cerevisiae. J. Am. Chem. Soc. 125, 11782–11783. Dube, D. H., Prescher, J. A., Quang, C. N., and Bertozzi, C. R. (2006). Probing mucintype O-linked glycosylation in living animals. Proc. Natl. Acad. Sci. USA 103, 4819–4824. Gauchet, C., Labadie, G. R., and Poulter, C. D. (2006). Regio- and chemoselective covalent immobilization of proteins through unnatural amino acids. J. Am. Chem. Soc. 128, 9274–9275. Gill, S. C., and von Hippel, P. H. (1989). Calculation of protein extinction coefficients from amino acid sequence data. Anal. Biochem. 182, 319–326. Ha, T. (2001). Single-molecule fluorescence resonance energy transfer. Methods 25, 78–86. Hang, H. C., Yu, C., Kato, D. L., and Bertozzi, C. R. (2003). A metabolic labeling approach toward proteomic analysis of mucin-type O-linked glycosylation. Proc. Natl. Acad. Sci. USA 100, 14846–14851. Hangauer, M. J., and Bertozzi, C. R. (2008). A FRET-based fluorogenic phosphine for livecell imaging with the Staudinger ligation. Angew. Chem. Int. Ed. 47, 2394–2397. Humenik, M., Huang, Y., Wang, Y., and Sprinzl, M. (2007). C-terminal incorporation of bio-orthogonal azide groups into a protein and preparation of protein-oligodeoxynucleotide conjugates by Cu’-catalyzed cycloaddition. ChemBioChem 8, 1103–1106.


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Kapanidis, A. N., and Weiss, S. (2002). Fluorescent probes and bioconjugation chemistries for single-molecule fluorescence analysis of biomolecules. J. Chem. Phys. 117, 10953–10964. Kiick, K. L., Saxon, E., Tirrell, D. A., and Bertozzi, C. R. (2002). Incorporation of azides into recombinant proteins for chemoselective modification by the Staudinger ligation. Proc. Natl. Acad. Sci. USA 99, 19–24. Kohn, M., and Breinbauer, R. (2004). The Staudinger ligation–A gift to chemical biology. Angew. Chem. Int. Ed. 43, 3106–3116. Krieg, U. C., Walter, P., and Johnson, A. E. (1986). Photocrosslinking of the signal sequence of nascent preprolactin to the 54-kilodalton polypeptide of the signal recognition particle. Proc. Natl. Acad. Sci. USA 83, 8604–8608. Laughlin, S. T., and Bertozzi, C. R. (2007). Metabolic labeling of glycans with azido sugars and subsequent glycan-profiling and visualization via Staudinger ligation. Nat. Protoc. 2, 2930–2944. Laughlin, S. T., Agard, N. J., Baskin, J. M., Carrico, I. S., Chang, P. V., Ganguli, A. S., Hangauer, M. J., Lo, A., Prescher, J. A., and Bertozzi, C. R. (2006). Metabolic labeling of glycans with azido sugars for visualization and glycoproteomics. Methods Enzymol. 415, 230–250. Lemieux, G. A., De Graffenried, C. L., and Bertozzi, C. R. (2003). A fluorogenic dye activated by the Staudinger ligation. J. Am. Chem. Soc. 125, 4708–4709. Leung, W.-Y., Cheung, C.-Y., and Yue, S. (2005). Modified carbocyanine dyes and their conjugates. US Patent 6, 977, 305. Link, A. J., and Tirrell, D. A. (2003). Cell surface labeling of Escherichia coli via copper(I)catalyzed [3þ2] cycloaddition. J. Am. Chem. Soc. 125, 11164–11165. Link, A. J., Vink, M. K., and Tirrell, D. A. (2004). Presentation and detection of azide functionality in bacterial cell surface proteins. J. Am. Chem. Soc. 126, 10598–10602. Ngo, J. T., Champion, J. A., Mahdavi, A., Tanrikulu, I. C., Beatty, K. E., Connor, R. E., Yoo, T. H., Dieterich, D. C., Schuman, E. M., and Tirrell, D. A. (2009). Cell-selective metabolic labeling of proteins. Nat. Chem. Biol. 5, 715–717. Nguyen, D. P., Lusic, H., Neumann, H., Kapadnis, P. B., Deiters, A., and Chin, J. W. (2009). Genetic encoding and labeling of aliphatic azides and alkynes in recombinant proteins via a pyrrolysyl-tRNA synthetase/tRNA(CUA) pair and click chemistry. J. Am. Chem. Soc. 131, 8720–8721. Ohno, S., Matsui, M., Yokogawa, T., Nakamura, M., Hosoya, T., Hiramatsu, T., Suzuki, M., Hayashi, N., and Nishikawa, K. (2007). Site-selective post-translational modification of proteins using an unnatural amino acid, 3-azidotyrosine. J. Biochem. 141, 335–343. Panchuk-Voloshina, N., Haugland, R. P., Bishop-Stewart, J., Bhalgat, M. K., Millard, P. J., Mao, F., Leung, W.-Y., and Haugland, R. P. (1999). Alexa dyes, a series of new fluorescent dyes that yield exceptionally bright, photostable conjugates. J. Histochem. Cytochem. 47, 1179–1188. Prescher, J. A., Dube, D. H., and Bertozzi, C. R. (2004). Chemical remodelling of cell surfaces in living animals. Nature 430, 873–877. Roy, R., Hohng, S., and Ha, T. (2008). A practical guide to single-molecule FRET. Nat. Methods 5, 507–516. Saxon, E., and Bertozzi, C. R. (2000). Cell surface engineering by a modified Staudinger reaction. Science 287, 2007–2010. Saxon, E., Luchansky, S. J., Hang, H. C., Yu, C., Lee, S. C., and Bertozzi, C. R. (2002). Investigating cellular metabolism of synthetic azidosugars with the Staudinger ligation. J. Am. Chem. Soc. 124, 14893–14902. Sletten, E. M., and Bertozzi, C. R. (2009). Bioorthogonal chemistry: Fishing for selectivity in a sea of functionality. Angew. Chem. Int. Ed. 48, 6974–6998.

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Tsao, M. L., Tian, F., and Schultz, P. G. (2005). Selective Staudinger modification of proteins containing p-azidophenylalanine. ChemBioChem 6, 2147–2149. Vocadlo, D. J., Hang, H. C., Kim, E. J., Hanover, J. A., and Bertozzi, C. R. (2003). A chemical approach for identifying O-GlcNAc-modified proteins in cells. Proc. Natl. Acad. Sci. USA 100, 9116–9121. Wang, C. C., Seo, T. S., Li, Z., Ruparel, H., and Ju, J. (2003). Site-specific fluorescent labeling of DNA using Staudinger ligation. Bioconjug. Chem. 14, 697–701.

C H A P T E R

T H R E E

Preparation of Fluorescent Pre-mRNA Substrates for an smFRET Study of Pre-mRNA Splicing in Yeast John Abelson, Haralambos Hadjivassiliou, and Christine Guthrie Contents 1. Introduction 2. Identification of a Yeast Pre-mRNA with a Small Intron that is Spliced Efficiently In Vitro 3. Synthetic Fluorescent Ubc4 Pre-mRNA 4. Do the Dyes Affect the Efficiency of Splicing? 5. Mutant Pre-mRNAs 6. Tethering the Pre-mRNA to the Microscope Slide 7. Summary and Conclusion Acknowledgments References

32 32 33 37 37 38 39 40 40

Abstract The spliceosome is a complex small nuclear (sn)RNA–protein machine that removes introns from pre-mRNAs via two successive phosphoryl transfer reactions. For each splicing event, the spliceosome is assembled de novo on a premRNA substrate and a complex series of assembly steps leads to the active conformation. To comprehensively monitor pre-mRNA conformational dynamics during spliceosome assembly, we developed a strategy for single-molecule FRET (smFRET) that utilizes a small, efficiently spliced yeast pre-mRNA, Ubc4, in which donor and acceptor fluorophores are placed in the exons adjacent to the 50 and 30 splice sites. In this chapter, we describe the identification of Ubc4 pre-mRNA that is efficiently spliced in vitro and the methods we have developed for the chemical synthesis of fluorescent Ubc4 pre-mRNA for smFRET.

Department of Biochemistry and Biophysics, University of California, San Francisco, California, USA Methods in Enzymology, Volume 472 ISSN 0076-6879, DOI: 10.1016/S0076-6879(10)72017-6

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John Abelson et al.

1. Introduction An in vitro splicing system in yeast was developed almost 25 years ago, enabling the study of spliceosome assembly (Lin et al., 1985). Much has been learned about the steps in spliceosome assembly since that time, but little is known about the kinetics of spliceosome assembly, largely because no progress has been made on developing a well-defined in vitro system. Experiments are still done in a crude extract where multistep reversible processes are obscured by asynchronous progression along the pathway. In addition, in vitro splicing in a yeast extract is generally inefficient, leading to only a fraction of molecules undergoing one or both steps of splicing. As abundantly demonstrated in this volume, single-molecule fluorescence resonance energy transfer (smFRET) is a technique that could overcome these difficulties. Accordingly, we have set out to establish an smFRET assay for spliceosome assembly in the yeast system. In principle, spliceosome assembly could be monitored by transfer between donor and acceptor probes in two proteins, in two RNAs, in a single RNA or in a single RNA and a single protein. For the development of this system, we have elected to monitor FRET between donor and acceptor probes in the pre-mRNA. For the first experiments, we have located the donor probe in exon 1 near the 50 splice site and the acceptor in exon 2 near the 30 splice site. In the premRNA, these probes may be (depending on the secondary structure of the pre-mRNA) too far away from each other to result in smFRET, but in the spliced mRNA product, they should be brought into proximity producing an smFRET signal. This experiment, then, is designed to monitor the relative movement of the 50 and 30 splice sites during spliceosome assembly. We have elected to follow the FRET changes that occur during assembly at the single-molecule level (Abelson et al., 2010). This chapter describes the identification and synthesis of a pre-mRNA substrate that is suitable for these experiments.

2. Identification of a Yeast Pre-mRNA with a Small Intron that is Spliced Efficiently In Vitro We first had to identify a yeast pre-mRNA with a small intron that is spliced efficiently in the yeast in vitro splicing system. A small intron is required in order to efficiently assemble the fluorescent substrate from synthetic RNA molecules. Most yeast in vitro splicing experiments have utilized the actin pre-mRNA. The actin intron is 308 nucleotides, too long for easy synthesis via synthetic RNA molecules.

Preparation of Fluorescent Pre-mRNA Substrates

33

To find a pre-mRNA in yeast with a small intron that is spliced well in vitro, we employed the yeast temperature-sensitive mutant, prp2-1. In this mutant, splicing is blocked before the first catalytic step when cells are shifted to the nonpermissive temperature. This results in the efficient accumulation of yeast pre-mRNAs. RNA was extracted from prp2-1 cells that had been grown at the permissive temperature (30 C) and shifted to the nonpermissive temperature (37 C) for 30 min. Bulk RNA was extracted from these cells and used as substrate in an in vitro splicing reaction. The RNA was extracted from these reaction mixtures and analyzed by RNA microarray analysis. The Guthrie lab has established a microarray assay that specifically monitors intron and mRNA features of all of the 250 or so yeast transcripts that contain introns (Pleiss et al., 2007). The presence of mRNA is monitored by hybridization to an immobilized DNA fragment whose sequence spans the spliced junction. For this experiment, cDNA was prepared from the splicing reactions described earlier. The control RNA was from reactions that did not contain ATP and thus would not contain transcripts spliced during the period of growth at the nonpermissive temperature. A tabulation of the results is shown in Table 3.1. According to this analysis, the pre-mRNA for the ribosomal protein RPS6A is best spliced in vitro. The actin pre-mRNA is 20th on the list. Several candidates with small introns emerged from this analysis. Ubc4, with an intron of 95 nucleotides, is second on the list. We ultimately chose the pre-mRNA for Ubc4 as the substrate for our FRET analysis. We next determined the minimum exon size for efficient splicing in vitro. A number of 32P labeled UBC 4 pre-mRNAs, differing in the size of their exons, were transcribed in vitro from DNA templates by T7 RNA polymerase and used as substrates for in vitro splicing (Fig. 3.1). The Ubc4 pre-mRNA (with exon lengths of 47 nucleotides) is the best of these substrates, but a precursor with exon lengths of only 20 nucleotides was about 70% as active as the former. In a trade-off between ease of synthesis and activity as a substrate, we chose to develop as an smFRET substrate the UBC 4 pre-mRNA consisting of two 20 nucleotide exons and the 95 nucleotide intron for a total size of 135 nucleotides.

3. Synthetic Fluorescent Ubc4 Pre-mRNA The pre-mRNA was synthesized by joining two oligonucleotides synthesized by Dharmacon: I (the 50 76 nucleotides of the pre-mRNA) and II (the 30 59 nucleotides; Fig. 3.2). For dye-labeled pre-mRNA, allyl-amine uridine was substituted for uridine at the appropriate positions. Oligonucleotide I was coupled to Cy3 and II to Cy5. For a 0.2 mM synthesis of oligonucleotides in this size

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Table 3.1 Relative splicing efficiencies of yeast pre-mRNAs in vitroa Rank

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 a

Systematic name

Gene name

ORF length

Intron length

YPL090C YBR082C YDR471W YKL081W YNL050C YLR061W YDR424C YBL040C YML056C YPL143W YAL030W YBR048W YPL081W YBL059C-A YBR181C YKL186C YHR101C YLR344W YER133W YFL039C

RSP6A UBC4 RPL27B TEF4 Unknown RPL22A DYN2 ERD2 IMD4 RPL33A SNC1 RPS11B RPS9A CMC2 RPS6B MTR2 BIG1 RPL26A GLC7 ACT1

1105 542 795 1565 904 755 455 757 1983 849 467 982 1095 415 1063 792 1095 831 1464 1436

394 95 384 326 91 389 96 97 408 525 113 511 501 85 352 154 87 447 525 308

Shown are the top 20 pre-mRNAs (out of about 250 genes in yeast that contain introns) in descending order of splicing efficiency in vitro as assayed in a microarray assay. RNA was extracted from prp2-1 grown at the permissive temperature (2-1 RNA) and from in vitro splicing reactions in which the pre-mRNA added to the reaction mixture was RNA isolated from prp2-1 grown at the permissive temperature and then shifted to the nonpermissive temperature for 30 min. Splicing reactions containing 240 mg/ml of the RNA extracted from cells grown at the nonpermissive temperature were incubated for 30 min at room temperature with (þATP RNA) and without ATP (ATP RNA). cDNA synthesized from the 2-1 control RNA was labeled with Cy3 and cDNA from þATP RNA and ATP RNA with Cy5 as described (Pleiss et al., 2007). Splicing microarrays were hybridized with a mixture of 2-1 cDNA and þATP cDNA or 2-1 cDNA and ATP cDNA. After hybridization the microarrays were washed and analyzed for the ratio of ATP to 2-1. For this analysis we only considered hybridization to the set of oligonucleotides specific for the mRNAs of genes containing introns. The order of the genes in the table was determined by subtracting the rank orders of þATP/2-1 minus –ATP/2-1 for each gene (e.g., Ubc4 was in the 64th percentile in the (þ)ATP ratios and in the 0.8th percentile in the ()ATP ratios). Ubc4 pre-mRNA is second in this list and the canonical substrate for yeast in vitro pre-mRNA splicing, actin pre-mRNA, is 20th.

range, the yield is typically about 100 nmol. The quality of these oligonucleotides from Dharmacon is remarkable, given their length, but in order to obtain a homogeneous product, we first purify the deprotected oligonucleotides on a denaturing, 8 M urea, 6% polyacrylamide gel. The correct product has the slowest mobility and there is a streak of faster moving contaminants. The bands are visualized by UV shadowing or by staining

35


UBC4 30/30

30/20

30/10

20/20

20/10

20/30 10/10

10/20 10/30

0⬘ 15⬘ 30⬘

Figure 3.1 Exon length requirement for efficient splicing of Ubc4 pre-mRNA in vitro. DNA templates containing the T7 RNA polymerase promoter and the Ubc4 gene with different exon lengths were prepared by PCR. 32P-labeled T7 RNA polymerase RNA transcripts of the different Ubc4 constructs were incubated for 0, 15, and 30 min and assayed for splicing activity in a yeast extract.

20 nt Cy3

95 nt

−7

20 nt +4

I

II

76 nt

59 nt

Cy5

Figure 3.2 Design of Ubc4 pre-mRNA. Sequences of I and II: I ¼ 50 GAACUAAGUGAUCUAGAAAGGUAUGUCUAAAGUUAUGGCCACGUUUCAAAUGCGUGCUUUUUUUUUAAAACUUAUG; II ¼ 50 PCUCUUAUUUACUAACAAAAUCAACAUGCUAUUGAACUAGAGAUCCACCUACUUCAUGUT. To provide the proper substrate for RNA ligase the 50 end of II is phosphorylated and we make the last nucleotide in II a 20 -deoxy T in order to prevent circularization and in an attempt to give stability against exonucleolysis in cell extracts.

with toluidine blue and eluted from crushed gel slices overnight in 0.3 M sodium acetate pH 5.3, 1 mM EDTA and 0.1% SDS. Acrylamide is removed by phenol extraction, followed by chloroform extraction and ethanol precipitation. The precipitate is washed twice in 70% (v/v) ethanol, dried, and resuspended in water. The final yield after these steps is typically 25–30%. The activated succinimidyl esters of the Cy3 and Cy5 dyes are obtained from GE Healthcare. The content of a gel pack varies from lot to lot from 0.1 to 0.3 mg. The dye is resuspended in 20 ml of DMSO and mixed with 2–5 nmol of oligonucleotide in 0.1 M sodium bicarbonate buffer at pH 9.0. (Either fresh stocks of the bicarbonate buffer should be prepared or stocks should be frozen and the pH of the buffer checked before using.) The condensation is done at 60 C for 30 min. Four hundred microliters of

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John Abelson et al.

3⬘ A TATTT CATA C A ACTACA

P

5⬘...GU ACC GUAUAAA GUAUGUUGAUGU

3⬘ A ACB

5⬘U A

Acceptor

UCC

0.3 M Na-acetate, pH 5.3, is added and the derivitized oligonucleotides are precipitated with two volumes of ethanol by incubation for 20 min at 80 C. The precipitate is washed at least three times with 70% (v/v) ethanol until all of the free dye has been removed. The pellets are dried and resuspended in water at a concentration of 100 mM. Condensation of the dye with the precursor is usually about 50% efficient. The dye-labeled oligonucleotide can be separated from the uncoupled oligonucleotide by electrophoresis on a denaturing, 8 M urea, 20% polyacrylamide gel, but this is a step of low yield and we have usually used dye-coupled RNAs without further purification. The dye-coupled oligonucleotides were joined together by T4 RNA ligase 1. A DNA splint, partially complementary to the 30 end of oligonucleotide I and the 50 end of oligonucleotide II, loops out the ends of the RNA so that they resemble a nicked tRNA anticodon loop, a good substrate for T4 RNA ligase 1 (Stark et al., 2006; Fig. 3.3). We have also used T4 RNA Ligase 2 for the ligation of oligonucleotides (Ho and Shuman, 2002). In this case, the splint is exactly complementary to the donor and acceptor ends, producing a gapped substrate. Although we have less experience using T4 RNA Ligase 2, the efficiency of ligation for both ligases is generally 30–50%. The ligated pre-mRNA is separated from unligated oligonucleotides by electrophoresis on a denaturing, 8 M urea, 6% polyacrylamide gel (Fig. 3.4). The recovery of the ligated oligonucleotides from the gel at this stage is sometimes poor. We believe that this is because the hydrophobicity of the dye-labeled oligos leads to a loss of materials in the phenol extraction step. We have had better yields from the gel by employing electroelution of excised bands, using a device manufactured by International Biotechnologies Inc. (New Haven, CT). Because of the cumulative losses in the multiple steps involved in this procedure, the overall efficiency of labeled pre-mRNA synthesis is low, but because Dharmacon supplies us with nanomoles of synthetic oligonucleotide and femtomoles are required for a splicing assay, the yield is adequate. Of course far less material is required for the single-molecule assays.

Donor

A GCAGAUCAUGUUUUUUAAGCCG...3⬘ T CGTCTAGTACAAAAAAT 5⬘

Splint

Figure 3.3 Design of a ligation splint for T4 RNA ligase 1. The black line separating the two parts of the splint and opposite the looped out ends of donor and acceptor is a 9 carbon linker. Good ligation efficiency is obtained when the ratio of acceptor to donor to splint is 1:1:1.

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Cy5

Cy3

I–II I II

Figure 3.4 Ligation of oligonucleotides I and II to obtain Ubc4 pre-mRNA. Oligonucleotides I and II were ligated together with T4 RNA Ligase 1 employing the splint shown in Fig. 3.3. The ratio of I:II:splint was 1:1:1 (250 pmol of each). The reaction was incubated with 150 units T4 RNA ligase 1 (New England Biolabs) for 3 h at 37 C and the products were separated on a denaturing, 8 M urea, 6% polyacrylamide gel. The Typhoon Fluorimager scan of Cy5 is shown.

4. Do the Dyes Affect the Efficiency of Splicing? It is crucial to demonstrate that the dyes themselves do not inhibit the splicing reaction. We have prepared pre-mRNAs with dyes located at uridines in positions 7 in exon 1 and þ4 in exon 2, as well as in positions 12 and þ4, and 12 and þ10. All of these pre-mRNAs are spliced with the same efficiency and with an efficiency similar to that of 32P labeled premRNA not containing dyes (Fig. 3.5). The single-molecule experiments described in Abelson et al. (2010) have employed pre-mRNAs with dyelabeled uridines at position 7 and þ4.

5. Mutant Pre-mRNAs To validate the single-molecule FRET results, we have employed mutant pre-mRNAs that affect either the first or the second step of splicing. Fluorescent Ubc4 pre-mRNAs were synthesized with an A-to-C substitution in the branch point (b.p.) adenosine or a G-to-C substitution at the

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I7–II4

I12II4

− + + − + +

ATP

I12II10 − + +

Lariat-intron 2 Pre-mRNA

mRNA

I (76)

II (60)

−7

+4

Figure 3.5 The position of dyes in the pre-mRNA does not affect the efficiency of splicing. Synthetic Ubc4 pre-mRNA was prepared with dyes coupled to uridines at positions 7, þ 4, 12, þ4 and 12, þ 10. Splicing reactions were assayed by denaturing polyacrylamide gel electrophoresis of the RNAs and the gels were scanned with a Typhoon Fluorimager. The Cy5 scan is shown.

30 -splice site (30 ss). Figure 3.6 shows that the mutant pre-mRNAs behave as expected (Vijayraghavan et al., 1989). The 30 ss mutant is a substrate for the first step of splicing but is blocked in the second step and therefore accumulates the reaction intermediates. The b.p. mutant is blocked in the first step.

6. Tethering the Pre-mRNA to the Microscope Slide In our initial approach, we have tethered the Ubc4 pre-mRNA to the slide via a tether oligonucleotide that is complementary to exon 2 and contains a 50 biotin. The sequence of that oligonucleotide is 0

5 biotin-mAmAmCmAmUmGmAmAmGmUmAmGmGmUmGmGmA

39


+4

−7

UACUAAC

Cy3

C

UAG

C

Cy5

Cy5

wt.

3⬘ss

b.p. Lariat-ex II Pre-mRNA

mRNA

Figure 3.6 Pre-mRNA mutations inhibit splicing as expected. Ubc4 pre-mRNAs were synthesized with mutant changes in the branch point adenosine and the 30 splice site guanosine as shown. The fluorescent RNAs were assayed for splicing in vitro and the RNA products were separated by denaturing polyacrylamide gel electrophoresis. Shown is the Cy5 Typhoon Fluorimager scan of the gel.

This is a ribooligonucleotide in which all of the 20 -hydroxyls are methylated (m). This provides resistance to nuclease digestion. DNA tethers cannot be used in these experiments because in the splicing extract they will direct RNaseH cleavage of the substrate. Incorporation of 50 -biotin to the Ubc4 pre-mRNA is a preferable approach. We have shown that this alteration does not affect splicing (data not shown).

7. Summary and Conclusion We have described the identification of a yeast pre-mRNA splicing substrate, Ubc4, that contains a small intron facilitating its chemical synthesis. The synthetic pre-mRNA can be labeled with fluorescent dyes, providing a substrate for smFRET studies of spliceosomal assembly. The preliminary use of this substrate to study the dynamics of splicing in vitro has been described (Abelson et al., 2010; Blanco and Walter, 2010). Our laboratory is currently working on the development of fluorescent U6 and U2 small nuclear (sn) RNAs. These RNAs, synthesized from synthetic oligonucleotides as described earlier, can be incorporated into the (sn)RNA–protein complexes (snRNPs) in vitro by a method of reconstitution in which the (sn)RNA in the

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extract is inactivated by DNA-directed RNase H. In principle, spliceosome assembly can also be studied via the incorporation of dyes into spliceosomal proteins.

ACKNOWLEDGMENTS We acknowledge the participation of Dan Ryan, Jeffrey Pleiss, and Tommaso Villa in various stages of this project. The application of these substrates to the study of spliceosome assembly via smFRET has been a collaboration with Nils Walter’s laboratory at the University of Michigan. The work at UCSF was supported by an American Cancer Society Research Professor of Molecular Genetics award to C. G., by NIH grant GM021119 to C. G., and by a grant from the Agouron Institute to J. A.

REFERENCES Abelson, J., Blanco, M., Ditzler, M. A., Fuller, F., Aravamudhan, P., Wood, M., Villa, T., Ryan, D., Pleiss, J. A., Maeder, C., Guthrie, C., and Walter, N. G. (2010). Conformational dynamics of single pre-mRNA molecules during spliceosome assembly and splicing. Nat. Struct. Mol. Biol. 17, 1767–1775. Blanco, M., and Walter, N. G. (2010). Analysis of complex single molecule FRET time trajectories. Methods Enzymol. 472, 153–178. Ho, C. K., and Shuman, S. (2002). Bacteriophage T4 RNA ligase 2 (gp24.1) exemplifies a family of RNA ligases found in all phylogenetic domains. Proc. Natl. Acad. Sci. USA 99, 12709–12714. Lin, R. J., Newman, A. J., Cheng, S. C., and Abelson, J. (1985). Yeast mRNA splicing in vitro. J. Biol. Chem. 260, 14780–14792. Pleiss, J. A., Whitworth, G. B., Bergkessel, M., and Guthrie, C. (2007). Transcript specificit in yeast pre-mRNA splicing revealed by mutations in core spliceosomal components. PLoS Biol. 5, e90. Stark, M. R., Pleiss, J. A., Deras, M., Scaringe, S. A., and Rader, S. D. (2006). An RNA ligase-mediated method for the efficient creation of large, synthetic RNAs. RNA 12, 2014–2019. Vijayraghavan, U., Company, M., and Abelson, J. (1989). Isolation and characterization of pre-mRNA splicing mutants of Saccharomyces cerevisiae. Genes Dev. 3, 1206–1216.

C H A P T E R

F O U R

Nanovesicle Trapping for Studying Weak Protein Interactions by Single-Molecule FRET Jaime J. Benı´tez, Aaron M. Keller, and Peng Chen Contents 42 44 45 46 47 47 49

1. Introduction 2. Nanovesicle Trapping Approach 2.1. Lipid selection 2.2. Lipid nanovesicle preparation and protein trapping 3. smFRET Measurements of Weak Protein–Protein Interactions 3.1. Surface immobilization of nanovesicles 3.2. Control experiments 3.3. Application to weak interactions between intracellular copper transporters 4. Single-Molecule Kinetic Analysis of Three-State Protein–Protein Interactions 5. Further Developments 6. Concluding Remarks Acknowledgments References

51 54 57 58 59 59

Abstract Protein–protein interactions are fundamental biological processes. While strong protein interactions are amenable to many characterization techniques including crystallography, weak protein interactions are challenging to study because of their dynamic nature. Single-molecule fluorescence resonance energy transfer (smFRET) can monitor dynamic protein interactions in real time, but are generally limited to strong interacting pairs because of the low concentrations needed for single-molecule detection. Here, we describe a nanovesicle trapping approach to enable smFRET study of weak protein interactions at high effective concentrations. We describe the experimental procedures, summarize the application in studying the weak interactions between intracellular copper transporters, and detail the single-molecule kinetic analysis Department of Chemistry and Chemical Biology, Cornell University, Ithaca, New York, USA Methods in Enzymology, Volume 472 ISSN 0076-6879, DOI: 10.1016/S0076-6879(10)72016-4

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of bimolecular interactions involving three states. Both the experimental approach and the theoretical analysis are generally applicable to studying many other biological processes at the single-molecule level.

1. Introduction Protein–protein interactions are essential for cellular functions including protein folding, cell signaling, and metal trafficking (Gragerov et al., 1992; Hall, 1992; Huffman and O’Halloran, 2001). The strength of protein–protein interactions can vary widely depending on the proteins involved. Strong protein interactions can have equilibrium dissociation constants (KD) of a few picomolar (10 12M), for example antigen–antibody interactions, for which tight binding is crucial (Nooren and Thornton, 2003). Weak protein interactions can have KD’s of a few micromolar to millimolar (10 6–10 3M), for example, interactions between metallochaperones and their target proteins, for which dynamic binding and unbinding are necessary to have many interaction turnovers (Banci and Rosato, 2003; Cobine et al., 2006; Huffman and O’Halloran, 2001; Kim et al., 2008; Lutsenko et al., 2007; Rosenzweig, 2001; Strausak et al., 2003). For understanding their fundamental properties, strong protein interactions are amenable to characterization by ensemble measurements, as stable interaction complexes can form even at dilute solution conditions. Stable protein complexes can further be crystallized for structural determination down to atomic resolution. In contrast, weak protein interactions are challenging to characterize in ensemble measurements for several reasons: (1) they are dynamic and stochastic, making synchronization of molecular actions often necessary; (2) the steady-state concentrations of interaction intermediates are often low, making detection difficult; and (3) the presence of multiple interaction intermediates can complicate ensemble-averaged measurements. To study these weak protein interactions, single-molecule measurements offer several advantages: (1) no synchronization of molecular reactions is necessary; (2) the molecular reactions, including the formation, interconversion, and dissolution of interaction intermediates, are followed in real time; and (3) only one molecular state, be it an intermediate, is observed at any time point, enabling the resolution of complex reaction kinetics. Single-molecule fluorescence resonance energy transfer (smFRET), with its inherent distance dependence in the nanometer scale, is particularly suited for probing dynamic protein–protein interactions, which is accompanied by changes in protein–protein distances. There are challenges to overcome, however, before smFRET can be applied to study weak protein interactions. The primary challenge is the concentration limit. Single-molecule fluorescence measurements are generally done at low

Nanovesicle Trapping for Weak Protein Interactions

43

concentrations (10 6M) to favor complex formation. To overcome this concentration limit, one needs to decrease the effective detection volume to 10 19–10 21 l, so that at concentrations of up to 10 6–10 4M there is no more than one fluorophore on average found in it (Laurence and Weiss, 2003). This can be done by reducing the laser excitation volume or by confining molecules in space. For reducing the excitation volume, Webb, Craighead, and coworkers have fabricated zero-mode waveguides made of metal-clad wells on top of a silica substrate (Levene et al., 2003). The diameter of these wells is much smaller than the wavelength of the excitation light, and therefore, light shining at the silica substrate cannot propagate through the wells. Thisblockage of light propagation reduces the light excitation to an evanescent electromagnetic field close to the silica substrate surface, leading to reduction of the laser excitation volume to 10 21 l. Using this approach, Webb, Craighead, and coworkers have studied the reactions of individual DNA polymerase molecules that have substrate binding affinity in the micromolar range. As these zero-mode waveguides are open reaction containers, a big advantage is easy exchange of solutions for changing reaction conditions. A disadvantage is the proximity of a metal surface to the fluorophore; the metal surface can influence the fluorophore’s fluorescence properties, such as its intensity and fluorescence lifetime. To follow individual molecules over time, the molecules also have to be immobilized on the silica surface at the bottom of the wells, which can introduce nonspecific surface interactions. For confining molecules spatially, trapping with nanometer-sized lipid vesicles is an effective approach (Fig. 4.1), which was initially used in single-molecule studies of enzyme reactions (Chiu et al., 1999), protein folding (Boukobza et al., 2001; Haran, 2003; Rhoades et al., 2003, 2004), and nucleic acid conformation dynamics (Lee et al., 2005; Okumus et al., 2004). Because of the confined volume, the effective concentration of a single-molecule inside a nanovesicle can be as high as tens of micromolar, while the overall concentration of the nanovesicles can be kept low to maintain the single-molecule detection condition. Using this nanovesicle trapping approach combined with smFRET measurements, Ha and coworkers have studied dynamic protein–nucleic acid interactions (Cisse et al., 2007), and we have studied weak protein–protein interactions at high effective concentrations (Benitez et al., 2008, 2009). In this chapter, we describe in detail how nanovesicle trapping, combined with smFRET

44


D + A

Lipid bilayer/PEG/BSA Quartz

Biotin Streptavidin

Figure 4.1 Schematics of nanovesicle trapping of two proteins labeled with a FRET donor–acceptor pair for smFRET studies.

measurements, can be used to characterize weak, dynamic protein interactions at the single-molecule level. We also detail the single-molecule kinetic analysis of bimolecular interactions that show three FRET states.

2. Nanovesicle Trapping Approach Nanovesicle trapping is an effective approach in reducing the effective detection volume to enable high concentration studies at the single-molecule level. This approach also offers several other advantages: (1) the lipid membrane enclosure mimics biological environments inside cells or organelles; (2) the membrane prevents nonspecific interactions between the protein and the glass surface because molecule immobilization is done via tethering the nanovesicle (Fig. 4.1); nevertheless, nonspecific interactions with the lipid membrane may occur; control experiments must be performed to check this possibility (see below); (3) the diameter of vesicles can be varied from a few hundred nanometers down to 50 nm, covering effective concentrations of up to 24 mM for a single-molecule inside (Fig. 4.2); and (4) for protein–protein interaction studies, interactions between molecules of the same type, if occurring, can be selectively discarded in the data analysis stage by examining only the nanovesicles that contain molecules of different types.

45


Effective concentrations (mM)

100 10 1 0.1 0.01 250

500

750

1000

Vesicle diameter (nm)

Figure 4.2 Dependence of the effective concentration of a single molecule on the diameter of the nanovesicle. The solid symbols indicate a few commercial available membrane pore sizes for preparing nanovesicles.

In this section, we describe the experimental details of preparing nanovesicles to trap two different proteins for protein interaction studies. The procedures largely follow those of Haran and Ha (Boukobza et al., 2001; Okumus et al., 2004).

2.1. Lipid selection The lipids for forming the membrane bilayer of the nanovesicles contain two components: one major lipid (99%) that dominates the behavior of the membrane bilayer and the other minor lipid (1%) that contains a biotin group for surface immobilization. The chemical nature and the gel-to-liquid phase transition temperature (Tm) of the major lipid are important here. The lipid must not significantly interact with the proteins and perturb the protein interactions. A lipid with a net zero charge is preferred, as it is less likely to interact with soluble, largely hydrophilic proteins (Boukobza et al., 2001). Usually, the Tm of the major lipid should be much lower than the temperature for the single-molecule experiments, so the lipid bilayer stays in the fluidic liquid phase. A common major lipid used in single-molecule applications is Egg PC, extracted from egg yolk and 99% of which is L-aphosphatidylcholine. Its Tm is about 2 C (Silvius, 1983), so its bilayer is in the liquid phase at room temperature. Many other lipids with different Tm and charge properties are available and can be used for preparing vesicles (Silvius, 1983). For the biotinylated minor lipid, Biotinyl-cap PE (1,2dipalmitoyl-sn-glycero-3-phosphoethanolamine-N-(cap biotinyl)) is commonly used.

46


2.2. Lipid nanovesicle preparation and protein trapping The procedure consists of two major steps: (1) preparation of dry lipid film and hydration of the lipid film with buffer containing fluorescently labeled proteins to form vesicles and trap proteins inside and (2) extrusion of the formed vesicles through a polycarbonate membrane with well-defined pore diameters to make unilamellar vesicles of defined size. Using 100-nm pore-size membranes for extrusion, the multilamellar vesicles were estimated to be less than 2% (Hope et al., 1985). 2.2.1. Lipid film preparation and hydration 1. Prepare lipid stock solutions in chloroform at 100 mg ml 1 and store them at 20 C in a desiccator. The biotinylated lipid stock solution is prepared at 1 mg ml 1. 2. Transfer aliquots of lipid solutions into a clean glass test tube, forming a solution of 99% major lipid and 1% biotinylated minor lipid. Use enough amounts for a final total lipid concentration of 5 mg ml 1 upon hydration. Dry under a nitrogen flow until a thin lipid film is formed on the wall of the test tube. The lipid film can be further put under vacuum for 1–2 h to remove residual chloroform. 3. Hydrate the lipid film with the solution containing a mixture of the two labeled proteins under study. The concentration of each of the fluorescently labeled proteins should be close to the targeted effective concentration when the protein is trapped inside the nanovesicle. For example, for trapping a pair of protein molecules in 100 nm diameter nanovesicles, the concentration of each protein should be 3 mM, whereas for trapping in 200 nm diameter nanovesicles, use 400 nM concentration. The efficiency of cotrapping a pair of molecules can be increased if the hydration and trapping are done under conditions where the protein pair has maximum binding affinity for each other. 4. Briefly vortex the hydrated solution to detach the lipid film from the wall of the test tube. Incubate the solution for 10 min to 1 h at a temperature of at least 10 C above the Tm of the major lipid. The hydrated lipids will spontaneously form large multilamellar vesicles. Further freeze–thaw cycles (5–10 times) of the vesicle solution using liquid nitrogen and warm water can induce cracks in the membrane, which can improve entrapment of small molecules. Here, care must be taken that the freeze–thaw cycles do not denature the proteins; circular dichroism spectroscopy can be used to check the folding state of the protein. 2.2.2. Preparation of unilamellar nanovesicles via extrusion Unilamellar nanovesicles are formed by extrusion of the vesicle solution through a polycarbonate membrane with nanometer-sized pores (Hope et al., 1985; Johnson et al., 2002; MacDonald et al., 1991). Extrusion should


47

be performed at a temperature of at least 10 C above the Tm of the major lipid. The Avanti mini extruder (Avanti Polar Lipids, Inc.) is handy for this purpose. Polycarbonate membranes of different pore diameters are available, ranging from 50 nm to 1 mm. The nanovesicle diameter obtained after extrusion follows a Gaussian distribution, the width of which is dependent on the number of passes through the extruder; the more passes, the narrower the distribution (Hope et al., 1985; MacDonald et al., 1991). The diameter distribution can be checked using dynamic light scattering measurements. We normally perform tens of passes, significantly more than what is suggested by Avanti. The number of molecules trapped within the nanovesicles follows a Poisson distribution, the average occupation number depending on the protein/lipid ratio in the hydration step (Boukobza et al., 2001). The exact occupancy of each nanovesicle can be determined by single-molecule fluorescence imaging (see Section 3.2).

3. smFRET Measurements of Weak Protein–Protein Interactions The smFRET experiments consist of (1) immobilization of nanovesicles in a flow cell and (2) real-time imaging using total internal reflection fluorescence microscopy. The microscope is equipped with two-color detection for imaging the fluorescence of the FRET donor and acceptor simultaneously.

3.1. Surface immobilization of nanovesicles To follow the protein–protein interactions inside each nanovesicle over time, the nanovesicles need to be immobilized on a surface. Most commonly, a biotin–avidin linkage is used. Biotinylated lipids in the nanovesicle membrane are used to bind avidins (e.g., streptavidin or neutravidin), which in turn are bound to a biotin-modified surface. We have used three different schemes to modify the surface with biotins, all of which yield similar results: (1) coating the surface with a lipid bilayer containing biotinylated lipids, (2) coating with biotinylated bovine serum albumin (BSA), and (3) coating with partially biotinylated polyethylene glycol (PEG). 3.1.1. Lipid bilayer coating This surface modification scheme takes advantage of the spontaneous fusion of lipid vesicles onto clean quartz surfaces to form a lipid bilayer (Boxer, 2000; Brian and McConnell, 1984), over which the nanovesicles can be attached. The lipids used for this bilayer can be the same as those used for the nanovesicles, for example, 99% Egg PC and 1% Biotinyl-cap PE.

48


1. The procedure for lipid preparation is the same as described earlier. The lipid film is prepared first and then hydrated with buffer in the absence of proteins. 2. The hydrated solution is sonicated for 30 min to 1 h until clarity. The sonication here breaks large multilamellar vesicles to form small unilamellar vesicles, which can spontaneously fuse to clean quartz surfaces. The distribution of vesicle sizes is not important here. 3. Incubate the quartz substrate with the solution containing small unilamellar vesicles at a total lipid concentration of 1–5 mg ml 1 for 1 h. Wash out excess lipids from the quartz surface with buffer. 4. Vesicle preparation, surface coating, and washing should all be performed at a temperature of at least 10 C above the Tm of the major lipid. One problem with using Egg PC for the supported bilayer is that at room temperature the bilayer exists in the liquid phase, so the attached nanovesicles are mobile. The nanovesicle mobility can be reduced by increasing the percentage of biotinylated lipid so that each nanovesicle is anchored to the supported bilayer by multiple biotin–avidin linkages (Okumus et al., 2004). Nevertheless, many nanovesicles still remain mobile as we observed in our experiments. To alleviate this mobility problem, we have used another lipid, DPPC (1,2-dipalmitoyl-sn-glycero-3-phosphocholine), which has a Tm of 41 C. Because of its high Tm, DPPC exists in the gel phase at room temperature, resulting in a mostly immobile lipid support. 3.1.2. BSA coating BSA can bind to quartz surfaces strongly via nonspecific interactions (Rasnik et al., 2005), and therefore, biotinylated BSA can be used to coat the quartz surface to immobilize nanovesicles: 1. Prepare 1 mg ml 1 biotinylated BSA solution and incubate on the quartz substrate for 30 min to 1 h. 2. Wash out excess biotin–BSA with buffer. The BSA coating is easy to perform and can prevent rupture and fusion of nanovesicles to the quartz surface. (In case some bare patches on the glass surface exist because of incomplete coating with BSA, vesicle fusion to the glass surface can form patches of lipid bilayer to fill them up.) 3.1.3. PEG coating Covalent functionalization of a quartz surface with partially biotinylated PEG is another scheme for immobilizing nanovesicles. The quartz surface is first covalently functionalized with amine groups, which are then covalently linked to PEG via succinimidyl ester chemistry.


49

For amine modification: 1. Prepare a fresh solution of 1.5–2% amino silane reagent (Vectabond, Vector Laboratories) in acetone. (Other types of amino silane reagents work too, for example, 3-aminopropyltriethoxysilane.) 2. Drop 200 ml of the amino silane solution onto the quartz slide. 3. Incubate for 5 min and then wash extensively with ultra-filtered, deionized water for 1 min. Dry the slides with nitrogen and store under a dry environment. For PEG modification: 1. Prepare a solution of 98–99% m-PEG-SPA-5000 and 1–2% biotinPEG-NHS-3400 (Nektar Therapeutics, JenKem Technology Inc., or SunBio, USA) in 100 mM NaHCO3, pH 8.2. 2. Drop 200 ml of the PEG solution onto an amine-functionalized slide and sandwich it with another slide. Place parafilm spacers in between to prevent squeezing out the solution. Incubate for 4 h in the dark. 3. Wash slides thoroughly with nanopure water and dry with nitrogen for usage.

3.2. Control experiments 3.2.1. Lipid–protein interactions To check whether the fluorescently labeled proteins have nonspecific interactions with the lipid membrane, one can coat the quartz surface with a lipid bilayer and flow in solutions containing high concentrations (e.g., 100 nM) of labeled proteins. After washing the flow cell with fresh buffer and imaging the single-molecule fluorescence, the number of molecules that are immobilized on the lipid bilayer by nonspecific interactions can be counted. Comparing the number of nonspecifically bound molecules to the number of molecules detected using specific biotin–avidin immobilization of nanovesicles provides an estimate of the extent of nonspecific interactions between the protein and the lipid membrane (Benitez et al., 2008, 2009; Okumus et al., 2004). 3.2.2. Occupancy of nanovesicles The nanovesicle trapping procedure will result in a distribution of occupancy of individual nanovesicles. The nanovesicle occupation is important to verify when using smFRET to study weakly interacting pairs. Under normal smFRET measurements, only the FRET donor is continuously excited and exhibits fluorescence. The FRET acceptor emits ideally only when it is close to the donor-labeled protein (e.g., upon protein–protein interaction) and is excited via energy transfer. The possible presence of multiple acceptor-labeled proteins within a nanovesicle can adversely affect quantitative determination of protein–protein interaction kinetics. Control

50


experiments are necessary to determine the distribution of occupancy of nanovesicles under the trapping conditions. To do so, one can use two different lasers to excite the FRET donor and acceptor separately. For example, for the Cy3–Cy5 FRET pair, the Cy3 fluorescence can be directly imaged by excitation with a 532-nm laser and Cy5 fluorescence with a 637-nm laser. With the nanovesicles already loaded with fluorescent proteins and immobilized on the surface, the control experiments follow: 1. Directly excite the donor dye and record a movie of fluorescence intensity. 2. Switch to the second laser to excite the acceptor dye in the same area and record a fluorescence movie. 3. Analyze both movies to obtain fluorescence trajectories and positions of individual molecules. Use the number of photobleaching steps in the fluorescence intensity trajectory to determine the number of donor (or acceptor) molecules in the nanovesicle. 4. Check the position colocalization if the donor and acceptor dyes belong to the same nanovesicle. In our experience, incidental vesicle colocalization due to limited spatial resolution is minimal when the surface density of protein containing vesicles is smaller than 0.2 mm 2. For weakly interacting protein pairs, such as Hah1 and MBD4 (see Section 3.3), the cotrapping efficiency is low. Among 340 nanovesicles containing either Hah1–Cy5 or MBD4–Cy3, only 21 of them contain a Hah1–Cy5 and a MBD4–Cy3. The number of acceptor molecules can also be checked during normal smFRET measurements. One can first use the donor-exciting laser for smFRET while recording a fluorescence movie. In the later part of the movie, the acceptor-exciting laser is turned on to excite the acceptor dye until the acceptor photobleaches. The photobleaching events in the acceptor intensity will indicate the number of acceptor molecules in the nanovesicle. In this way, one is sure to examine only single pairs of protein molecules. 3.2.3. FRET differentiation of acceptor-blinked/bleached states from the dissociated state of protein interactions Organic fluorescent dyes show blinking behavior, that is, the fluorescence intensity sometimes switches off temporarily. Although fluorescence blinking can be suppressed significantly by using an oxygen scavenging system and triplet quenchers (e.g., Trolox; Rasnik et al., 2006), occasional blinking of the FRET acceptor is problematic, as it would result in an apparently low FRET efficiency (EFRET ¼ IA/(IA þ ID), where IA and ID are the acceptor and donor fluorescence intensities), which could be mistaken as that of the dissociated state of protein–protein interactions. Fortunately, using nanovesicle trapping and Cy3–Cy5 as the FRET pair,


51

the Cy5-blinked state has clearly lower EFRET than that of the dissociated state from control experiments (Benitez et al., 2008, 2009). As far as the apparent EFRET is concerned, the acceptor-blinked state is effectively the same as that in the absence of the acceptor and that of the acceptor photobleached state. Therefore, the apparent EFRET from nanovesicles that merely contain a donor molecule serves as a control for signal from the acceptor blinked state (Fig. 4.3A). The determined apparent EFRET with one Cy3 only is 0.04 0.05, which is the same as Cy5-blinked/bleached state of a Cy3–Cy5 pair (Fig. 4.3C). The dissociated state can be mimicked by a nanovesicle containing a free donor and a free acceptor (Fig. 4.3B), as the free dyes do not interact with each other. Here, the existence of both a donor and an acceptor must be confirmed by separate laser excitations (Fig. 4.3B). Under 532-nm excitation, the apparent EFRET is 0.15 0.14 (Fig. 4.3C); the larger value here compared with that of Cy5-blinked state is likely due to the residual direct excitation of Cy5 fluorescence by the 532-nm laser and some energy transfer of Cy3–Cy5 due to their confined coexistence inside the nanovesicle.

3.3. Application to weak interactions between intracellular copper transporters We applied the nanovesicle trapping approach to enable smFRET studies of the weak, dynamic interactions between the human intracellular copper chaperone Hah1 and the fourth metal-binding domain (MBD4) of the copper transporting ATPase Wilson disease protein (WDP) (Benitez et al., 2008, 2009). The interactions between Hah1 and WDP mediate the copper transfer from Hah1 to the MBDs of WDP, an essential process for safe trafficking of copper ions in human cells (Banci and Rosato, 2003; Cobine et al., 2006; Huffman and O’Halloran, 2001; Kim et al., 2008; Lutsenko et al., 2007; Rosenzweig, 2001; Strausak et al., 2003). Because of the low affinity of the Hah1–WDP interaction (KD 10 6 M), their interaction dynamics have been challenging to quantify in ensemble measurements. Nanovesicle trapping offers an ideal platform to examine their interactions at the single-molecule level using smFRET. We labeled Hah1 with the acceptor dye Cy5 and MBD4 with the donor dye Cy3, using maleimide chemistry at specific cysteine residues, and cotrapped them in 100-nm diameter nanovesicles. smFRET trajectories reveal their dynamic interactions (Fig. 4.4A). These trajectories show three different EFRET states: E0 (0.2) is the dissociated state, and E1 ( 0.5) and E2 ( 0.9) are two different interaction complexes. Transitions between E0 and E1 and between E0 and E2 correspond to the binding/ unbinding processes for forming complexes 1 and 2. The transitions between E1 and E2 correspond to the interconversions between the two

52


Intensity (a.u.)

A 30 k

Cy3 Cy5

15 k 0 0

50

100

150

Time (s) B

637 nm

Intensity (a.u.)

532 nm 20 k

Cy3 Cy5

10 k 0 0

50

100

150

Time (s)

Occurrence

C 60

20

30

10

0

0.0

0.3

0 0.6

EFRET

Figure 4.3 smFRET control experiments for acceptor blinked/bleached states and the dissociated state. (A) Two-color fluorescence intensity trajectories of a nanovesicle containing a single Cy3 molecule using 532-nm laser excitation. The Cy3 molecule photobleaches at the 62th second. (B) Two-color fluorescence intensity trajectories of a nanovesicle containing a single Cy3 and a single Cy5. The 532-nm laser is on throughout; the 637-nm laser was turned on at the 75th second. The Cy3 photobleaches at the 25th second; the Cy5 molecule photobleaches at 125th second. The first 25 seconds mimics the dissociated state of a Cy3–Cy5 pair. (C) Histograms of the apparent EFRET (¼IA/(IA þ ID); ID and IA are the fluorescence intensities of the donor and acceptor, respectively) for nanovesicles containing a single Cy3 (line patterned columns) and for nanovesicles containing a free Cy3 and Cy5 molecule (clear columns).

complexes. Figure 4.4B gives the interaction scheme between Hah1 and MBD4. The kinetic constants of all interaction processes can be extracted by analyzing the distributions of dwell times in each FRET state (Fig. 4.4C– H, Section 4). The direct observation of the interconversion dynamics between the two interaction complexes is particularly exciting here, as it enables determination of both the forward and the reverse interconversion rate constants (see Section 4)—ensemble characterization can often only

53


A Counts

B

Cy5-Hah1

Cy3-MBD4

20 k

1

(HAH1-MBD4) E1 k–1 HAH1 + MBD4 k k3 –3 E0 k2 k1

10 k

EFRET

0k 1.0

E2

0.5

E1 E0

0.0 0

10

C

20 Time (s)

20

(k1 + k2)[P] = 0.8 ± 0.1 s–1

0

40

15

2

t0 → 1

6

F

10

0

(k1 + k2)[P] = 1.0 ± 0.1 s–1

2

t1 → 0

6

10

k–1 + k3 = 1.4 ± 0.1 s–1

20

10

6

t0 → 2

10

0

2

6 t2 → 0

10

k–2 + k–3 = 1.7 ± 0.2 s–1

20 10

10 2

0

H 30

20

0

k–2 + k–3 = 2.1 ± 0.2 s–1

20

G

30

(HAH1-MBD4) E2

E k–1 + k3 = 1.2 ± 0.1 s–1

30

10

2

40

D 30

No of events

30

k–2

2

t1 → 2

6

10

0

2

6 t2 → 1

10

Figure 4.4 smFRET measurements of weak protein interaction dynamics in a nanovesicle. (A) Two-color fluorescence intensity (upper) and corresponding apparent EFRET (lower) trajectories of a Cy5–Hah1 and a Cy3–MBD4 trapped in a 100-nm nanovesicle. (B) Interaction scheme between Hah1 and MBD4. (C–H) Distributions of the six types of dwell times from the EFRET trajectories of Hah1–MBD4 interactions. Solid lines are exponential fits; insets give the exponential decay constants and their relations to the protein interaction rate constants in (B). [P] is the effective concentration ( 3 mM) of a single molecule in a 100-nm vesicle. The individual rate constants are k1 ¼ (1.6 0.2) 105 M 1 s 1, k 1 ¼ 0.88 0.04 s 1, k2 ¼ (1.4 0.2) 105 M 1 s 1, k 2 ¼ 1.3 0.1 s 1, k3 ¼ 0.42 0.04 s 1, and k 3 ¼ 0.7 0.1 s 1. Data in (A, C–H) adapted with permission from Benitez et al. (2008, 2009). Copyright 2008 American Chemical Society. (See Color Insert).

determine the sum of the forward and reverse rates for intermediate interconversion dynamics, as the interconversion dynamics are generally nonsynchronizable.

54


4. Single-Molecule Kinetic Analysis of Three-State Protein–Protein Interactions The interaction scheme between Hah1 and MBD4 can be generalized to that in Fig. 4.5A. An idealized EFRET trajectory showing three FRET states is given in Fig. 4.5B with different types of dwell times denoted. In this section, we derive the probability density functions of the dwell times involved in this three-state interactions, using single-molecule kinetic analysis (Benitez et al., 2008, 2009; Xie, 2001; Xu et al., 2009). We first consider the binding processes that occur during the dwell time t0 in the E0 state. Based on the interaction scheme shown in Fig. 4.5A, the processes occurring during t0 are summarized in Scheme 4.1. The ensemble rate equations for these kinetic processes are 0

d½A d½A 0 ¼ ¼ ðk1 þ k2 Þ½A½A dt dt

E1 B

A k1 k–1 A + A⬘ E0

(4.1a)

k2 k–2

k3

k–3 C E2

B

EFRET

1.0 t2→ 0 0.5

t0→ 2

t1→ 2

E2

t2→ 1 t1→ 0 t 0→ 1

E1 E0

0.0 0

100

50

150

Time (s)

Figure 4.5 Generic kinetic scheme of protein interactions and corresponding EFRET trajectories. (A) Generalized kinetic scheme of a single-interacting pair with three FRET states: one dissociated state, A þ A0 , with a FRET value of E0; and two interaction complexes, B and C, with FRET values of E1 and E2, respectively. (B) Idealized three-state EFRET trajectories of an interacting pair; all six types of dwell times are denoted.

55


k1

B

A + A⬘ k2

C

Scheme 4.1 Kinetic processes occurring during the dwell time t0 at the E0 state.

d½B 0 ¼ k1 ½A½A dt

(4.1b)

d½C 0 (4.1c) ¼ k2 ½A½A dt For the single-molecule reactions occurring in a nanovesicle, we have to consider the molecules in terms of their probabilities at time t, P(t). These rate equations then become

dP 0 ðtÞ dPA ðtÞ ¼ ðk1 þ k2 ÞPA ðtÞPv;A0 ;A ðtÞ ¼ A dt dt dPB ðtÞ ¼ k1 PA ðtÞPv;A0 ;A ðtÞ dt

(4.2a) (4.2b)

dPC ðtÞ (4.2c) ¼ k2 PA ðtÞPv;A0 ;A ðtÞ dt Here PA(t) is the probability of finding A at time t; PA0 (t), PB(t), and PC(t) are defined similarly; and PA(t) þ PB(t) þ PC(t) ¼ 1. Pv;A0 ;A ðtÞ is the conditional probability at time t of finding A0 within the same infinitesimal volume v where A is located, provided that A is found. Pv;A0 ;A ðtÞ is then Pv;A0 ;A ðtÞ ¼

PA0 ;A ðtÞ

(4.3) V Here PA0 ,A(t) is the conditional probability at time t of finding A0 within the entire space of the nanovesicle, provided that A is found; and V is the volume of the nanovesicle. Because whenever A is present, A0 is found, PA0 ,A(t) ¼ 1. Therefore, Pv;A0 ;A ðtÞ ¼ 1=V , which is the effective concentration (ceff) of one molecule inside the nanovesicle. We then have

dP 0 ðtÞ dPA ðtÞ ¼ ðk1 þ k2 Þceff PA ðtÞ ¼ A dt dt

(4.4a)

56


dPB ðtÞ ¼ k1 ceff PA ðtÞ dt

(4.4b)

dPC ðtÞ (4.4c) ¼ k2 ceff PA ðtÞ dt The initial conditions for solving these equations are PA(0) ¼ PA0 (0) ¼ 1, PB(0) ¼ 0, and PC(0) ¼ 0, with t ¼ 0 being the onset of each binding reaction. We can then evaluate the probability density f0(t) of the dwell time t0. The probability of finding a particular t0 is f0(t)Dt; and f0(t)Dt is equal to the sum of two probabilities: (1) the probability of molecule A and A0 to form B between t ¼ t and t þ Dt, which is DPB(t) ¼ k1ceffPA(t)Dt; and (2) the probability of molecule A and A0 to form C between t ¼ t and t þ Dt, which is DPC(t) ¼ k2ceffPA(t)Dt. In the limit of infinitesimal Dt, dðPB ðtÞ þ PC ðtÞÞ (4.5) ¼ ðk1 þ k2 Þceff PA ðtÞ dt Using the initial conditions to solve Eqs. (4.4a)–(4.4c) for PA(t), we get f0 ðtÞ ¼

R1

f0 ðtÞ ¼ ðk1 þ k2 Þceff exp½ðk1 þ k2 Þceff t

(4.6a)

Clearly, 0 f0 ðtÞdt ¼ 1, as expected. The dwell time t0 can be further separated into two types: one, t0!1, that ends with a transition to the E1 state and the other, t0!2, that ends with a transition to the E2 state. We can also evaluate the corresponding probability densities f0!1(t) and f0!2(t) of the dwell times t0!1 and t0!2. The probability of finding a particular t0!1 is f0!1(t)Dt; and f0!1(t)Dt is equal to the probability for A and A0 to form B between t ¼ t and t þ Dt, which is DPB(t) ¼ k1ceffPA(t)Dt. The probability of finding a particular t0!2 is f0!2(t)Dt; and f0!2(t)Dt is equal to the probability for A and A0 to form C between t ¼ t and t þ Dt, which is DPC(t) ¼ k2ceffPA(t)Dt. In the limit of infinitesimal Dt: f0!1 ðtÞ ¼

dPB ðtÞ ¼ k1 ceff exp½ðk1 þ k2 Þceff t dt

(4.6b)

f0!2 ðtÞ ¼

dPC ðtÞ ¼ k2 ceff exp½ðk1 þ k2 Þceff t dt

(4.6c)

Expectedly, f0!1(t) þ f0!2(t) ¼ f0(t). Note the exponential decay constants of f0!1(t) and f0!2(t) are the same as that of f0(t), all equal to (k1þk2) ceff, the sum of the two parallel kinetic processes in Scheme 4.1. The ratio between the total occurrence N0!1 of dwell time t0!1 and the total


57

occurrence N0!2 of dwell time t0!2 in the smFRET trajectories also carries important information: R1 f0!1 ðtÞdt k1 N0!1 ¼ R01 (4.6d) ¼ N0!2 k2 0 f0!2 ðtÞdt Similarly, we can derive the probability density function of the dwell time t1 on the E1 state, which can be separated into two types: t1!0 and t1!2, and that of the dwell time t2 on the E2 state, which can be separated into t2!0 and t2!1. The results are f1 ðtÞ ¼ ðk1 þ k3 Þexp½ðk1 þ k3 Þt

(4.7a)

f1!0 ðtÞ ¼ k1 exp½ðk1 þ k3 Þt

(4.7b)


(4.7c)

N1!0 k1 ¼ N1!2 k3

(4.7d)

f2 ðtÞ ¼ ðk2 þ k3 Þexp½ðk2 þ k3 Þt

(4.8a)


(4.8b)


(4.8c)

N2!0 k2 ¼ N2!1 k3

(4.8d)

Equations (4.6a)–(4.6d), (4.7a)–(4.7d), and (4.8a)–(4.8d) can be used to fit the corresponding experimental results to obtain the rate constants. The caption of Fig. 4.4C gives the determined rate constants for each of the kinetic steps in the Hah1–MBD4 interaction, from which the KD’s of the interaction complexes can be calculated. In ensemble-averaged measurements, if the two interaction complexes cannot be differentiated but are detectable, the measured effective dissociation constant (KD,eff) is related to the KD’s of the two complexes as 1/KD,eff ¼ 1/KD1 þ 1/KD2.

5. Further Developments A limitation of using Egg PC for forming nanovesicles is the enclosed environment that prevents facile exchange of solution. Being able to change the solution condition and introduce additional chemical reagents is highly

58


desired, however. Ha and coworkers have developed two strategies to make the nanovesicles porous to allow exchange of solution into the nanovesicles (Cisse et al., 2007): (1) using a lipid with a higher Tm and performing experiments at its Tm, which induces defects in the lipid membrane and (2) incorporating into the bilayer membrane the bacterial toxin a-hemolysin that forms pores. The first strategy is based on the fact that lipid bilayer membranes form packing defects at Tm, making the membrane permeable to small molecules (Chakrabarti and Deamer, 1992; Monnard, 2003). Ha and coworkers used the lipid DMPC (1,2-dimyristoyl-sn-glycero-3-phosphocholine), which has a Tm of 23 C. They showed that at 23 C, the nanovesicles made of DMPC lipid membranes are permeable to molecules as large as ATP, but not to macromolecules such as proteins and DNA. The second strategy uses the natural pore-forming ability of the membrane protein a-hemolysin, a heptameric transmembrane channel from Staphylococcus aureus. The monomers of a-hemolysin self-assemble into the heptameric channel structure in a lipid bilayer, forming a stable pore of 1.4–2.4 nm diameter and allowing exchange of most solution components (Song et al., 1996). The lipid membrane of the nanovesicles also provides a natural platform for studying protein interactions that involve membrane-bound or membrane-anchored proteins. To do so, one can incorporate or anchor one protein to the lipid membrane of the nanovesicle and trap the other protein inside. smFRET measurements can then be employed to monitor their interactions at high effective concentrations. The confined volume of the nanovesicles can also be exploited to probe the crowding effects on protein interactions by cotrapping a larger number of different types of unlabeled macromolecules inside, for example polysaccharides. This crowding effect arguably mimics the intracellular environment, offering an opportunity to study biomacromolecule dynamics in a controlled and confined environment in vitro.

6. Concluding Remarks Nanovesicle trapping is a convenient approach to enabling singlemolecule studies at high effective concentrations. This approach also offers easy surface immobilization and minimization of nonspecific interactions with glass surfaces. Coupled with smFRET measurements, dynamic events of protein interactions with weak affinity can be monitored in real time at the single-molecule level. Single-molecule kinetic analysis allows extraction of quantitative kinetics of the protein interactions, some of which are challenging to quantify with ensemble techniques. The lipid membrane also mimics the cellular environment, as well as provides a natural platform


59

for studying membrane-bound or membrane-anchored proteins. The confined volume can further be exploited to study crowding effects on macromolecule dynamics at the single-molecule level. With porous vesicles allowing solution exchange, many biological processes can be studied at high effective concentrations in situ. We expect that more biological studies using the nanovesicle trapping approach will emerge.

ACKNOWLEDGMENTS This research is supported by the National Science Foundation (CHE0645392), National Institute of Health (GM082939), the Wilson Disease Association, a Camille and Henry Dreyfus New Faculty Award, an Alfred P. Sloan Fellowship, and Cornell University. J. J. B. and A. M. K. are supported by Molecular Biophysics Traineeships from the National Institute of Health. We thank Profs. D. L. Huffman and A. R. Rosenzweig for their collaboration.

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Hall, A. (1992). Ras-related GTPases and the cytoskeleton. Mol. Biol. Cell 3, 475–479. Haran, G. (2003). Single-molecule fluorescence spectroscopy of biomolecular folding. J. Phys. Condens. Matter 15, R1291–R1317. Hope, M. J., Bally, M. B., Webb, G., and Cullis, P. R. (1985). Production of large unilamellar vesicles by a rapid extrusion procedure. Characterization of size distribution, trapped volume and ability to maintain a membrane potential. Biochim. Biophys. Acta 812, 55–65. Huffman, D. L., and O’Halloran, T. V. (2001). Function, structure, and mechanism of intracellular copper trafficking proteins. Annu. Rev. Biochem. 70, 677–701. Johnson, J. M., Ha, T., Chu, S., and Boxer, S. G. (2002). Early steps of supported bilayer formation probed by single vesicle fluorescence assays. Biophys. J. 83, 3371–3379. Kim, B.-E., Nevitt, T., and Thiele, D. J. (2008). Mechanisms for copper acqusition, distribution and regulation. Nat. Chem. Biol. 4, 176–185. Laurence, T. A., and Weiss, S. (2003). How to detect weak pairs. Science 299, 667–668. Lee, J. Y., Okumus, B., Kim, D. S., and Ha, T. (2005). Extreme conformational diversity in human telomeric DNA. Proc. Natl. Acad. Sci. USA 102, 18938–18943. Levene, M. J., Korlach, J., Turner, S. W., Foquet, M., Craighead, H. G., and Webb, W. W. (2003). Zero-mode waveguide for single-molecule analysis at high concentration. Science 299, 682–686. Lutsenko, S., LeShane, E. S., and Shinde, U. (2007). Biochemical basis of regulation of human copper-transporting ATPase. Arch. Biochem. Biophys. 463, 134–148. MacDonald, R. C., MacDonald, R. I., Menco, B. E., Takeshita, K., Subbarao, N. K., and Hu, L. R. (1991). Small-volume extrusion apparatus for preparation of large, unilamellar vesicles. Biochim. Biophys. Acta 1061, 297–303. Monnard, P.-A. (2003). Liposome-entrapped polymerases as models for microscale/nanoscale bioreactors. J. Membr. Biol. 191, 87–97. Nooren, I. M. A., and Thornton, J. M. (2003). Diversity of protein–protein interactions. EMBO J. 22, 3486–3492. Okumus, B., Wilson, T. J., Lilley, D. M. J., and Ha, T. (2004). Vesicle encapsulation studies reveal that single molecule ribozyme heterogeneities are intrinsic. Biophys. J. 87, 2798–2806. Rasnik, I., McKinney, S. A., and Ha, T. (2005). Surfaces and orientations: Much to FRET about? Acc. Chem. Res. 38, 542–548. Rasnik, I., McKinney, S. A., and Ha, T. (2006). Nonblinking and long-lasting single molecule fluorescence imaging. Nat. Methods 3, 891–893. Rhoades, E., Gussakovsky, E., and Haran, G. (2003). Watching proteins fold one molecule at a time. Proc. Natl. Acad. Sci. USA 100, 3197–3202. Rhoades, E., Cohen, M., Schuler, B., and Haran, G. (2004). Two-state folding observed in individual protein molecules. J. Am. Chem. Soc. 126, 14686–14687. Rosenzweig, A. C. (2001). Copper delivery by metallochaperone proteins. Acc. Chem. Res. 34, 119–128. Silvius, J. R. (1983). Thermotropic phase transitions of pure lipids in model membranes and their modifications by membrane proteins. In ‘‘Lipid–Protein Interactions,’’ (P. C. Jost and O. H. Griffish, eds.), pp. 239–281. Wiley, New York. Song, L., Hobaugh, M. R., Shustak, C., Cheley, S., Bayley, H., and Gouaux, J. E. (1996). Structure of staphylococcal-hemolysin a heptameric transmembrane pore. Science 274, 1859–1865. Strausak, D., Howies, M. K., Firth, S. D., Schlicksupp, A., Pipkorn, R., Multhaup, G., and Mercer, J. F. B. (2003). Kinetic analysis of the interaction of the copper chaperone Atox1 with the metal binding sites of the menkes protein. J. Biol. Chem. 278, 20821–20827. Xie, X. S. (2001). Single-molecule approach to enzymology. Single Mol. 2, 229–236. Xu, W., Kong, J. S., and Chen, P. (2009). Single-molecule kinetic theory of heterogeneous and enzyme catalysis. J. Phys. Chem. C 113, 2393–2404.

C H A P T E R

F I V E

Droplet Confinement and Fluorescence Measurement of Single Molecules Lori S. Goldner,* Ana M. Jofre,† and Jianyong Tang‡ Contents 1. Introduction 2. Methods for Droplet Generation 2.1. Emulsification 2.2. Injection 2.3. Microfluidics 3. Methods for Droplet Manipulation 3.1. Optical manipulation 3.2. Lab-on-chip methods for droplet manipulation 4. Droplet Coalescence and Mixing 5. Experimental Considerations for Single Fluorophore Detection 5.1. Protocol for aligning the apparatus 5.2. Protocol for preparation of emulsion samples 5.3. Protocol for droplet injection 6. Single-Molecule Measurements in Droplets 7. Future Prospects Acknowledgments References

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Abstract We describe a method for molecular confinement and single-fluorophore sensitive measurement in aqueous nanodroplets in oil. The sequestration of individual molecules in droplets has become a useful tool in genomics and molecular evolution. Similarly, the use of single fluorophores, or pairs of fluorophores, to study biomolecular interactions and structural dynamics is now common. Most often these single-fluorophore sensitive measurements are performed on molecules that are surface attached. Confinement via surface * Department of Physics, University of Massachusetts, Amherst, Massachusetts, USA Department of Physics and Optical Science, University of North Carolina, Charlotte, North Carolina, USA Janelia Farm Research Campus, Howard Hughes Medical Institute, Ashburn, Virginia, USA

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Methods in Enzymology, Volume 472 ISSN 0076-6879, DOI: 10.1016/S0076-6879(10)72015-2

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attachment permits molecules to be located and studied for a prolonged period of time. For molecules that denature on surfaces, for interactions that are transient or out-of-equilibrium, or to observe the dynamic equilibrium of freely diffusing reagents, surface attachment may not be an option. In these cases, droplet confinement presents an alternative method for molecular confinement. Here, we describe this method as used in single-fluorophore sensitive measurement and discuss its advantages, limitations, and future prospects.

1. Introduction The advent of techniques and instrumentation for measuring the fluorescence from single fluorophores has opened many new doors in scientific inquiry. Among these is the ability to directly visualize the structural transformations and reaction dynamics of individual biomolecules and biomolecular complexes. Using intrinsic fluorescence, or labeling biomolecules with an appropriate dye molecule or molecules, polarization or spectroscopic techniques can be used to elucidate molecular motion, structure, structural transformations, and binding. In contrast to ensemble measurements, single-molecule sensitive measurements can be compared directly with microscopic models. Single-molecule sensitive measurements of structural transformations, reaction dynamics, and binding all require that a molecule under study be measured for some amount of time. This requires a method for locating or distinguishing individual molecules, and for confining them in a detection region. Depending on the measurement scheme, various methods have been devised for distinguishing or localizing biomolecules, including surface binding (Ha et al., 1999; Noji et al., 1997; Wennmalm et al., 1997), surface adsorption (Bopp et al., 1997; Jia et al., 1999; Talaga et al., 2000; Wazawa et al., 2000), or confinement in a porous material (Dickson et al., 1997; Lu et al., 1998). Confinement to surface tethered liposomes has also been used and offers the advantage of a less perturbative and more reproducible environment for the confined molecule (Boukobza et al., 2001; Okumus et al., 2004; Yoon et al., 2006). Most recently, femtoliter and subfemtoliter droplets in oil have been used to confine single fluorescent molecules for measurement (Reiner et al., 2006; Tang et al., 2008). In addition to offering a simple and convenient alternative to other methods for confining or localizing molecules, droplets offer the distinct advantage that they can be made to coalesce on contact, without loss of hydrophilic contents, providing a convenient means for fast mixing. For droplets in the absence of surfactant coalescence is intrinsically fast, and the timing of mixing will be limited by diffusion in the droplets. Diffusional mixing can occur in less than 1 ms for subfemtoliter

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droplets. Combined with single-molecule sensitive fluorescence measurement, this opens new possibilities for the study of reaction dynamics or any out-of-equilibrium process that requires fast mixing. Coalescence also offers the possibility of assembling and studying short-lived molecular complexes as they undergo rapid assembly and dissociation, since the various components can be introduced in individual droplets and are all confined to a single slightly larger droplet after coalescence. The monodispersity, manipulability, repeatability, small size, and fast mixing afforded by aqueous nanodroplets in oil offer many opportunities for nanochemistry and observation of chemical reactions on a molecule-by-molecule basis. More generally, droplets offer convenient compartmentalization and localization useful in many applications in analytical chemistry and specifically enzymology. Unlike nature’s own cellular compartments, droplets can be engineered to be stable under conditions not commensurate with living systems. The use of emulsions makes massively parallel high-throughput measurement of bioreactions possible; a single microliter of sample can be aliquoted into 106–109 separate bioreactors. Confinement to a small reaction volume leads to higher reaction rates than in the bulk, both because reactant concentrations can be made arbitrarily high as droplets become arbitrarily small, and because diffusion-limited reaction rates increase as volume decreases. The utility of single aqueous droplets in oil for the study of single molecule reaction kinetics has long been recognized. Almost 50 years ago Rotman (1961) demonstrated that the activity of single b-D-galactosidase molecules confined to aqueous droplets in silicone oil could be measured by monitoring the increase in fluorescence of a fluorogenic substrate over time. While Rotman did not detect individual turnovers, his technique represents perhaps the first time that single enzyme kinetics could be measured using fluorescence. More recently, chymotrypsin kinetics have been studied using a similar technique (Lee and Brody, 2005). In both these works, droplets were used to confine individual molecules and indirectly study their kinetics using fluorogenic substrates. Here, we describe how the fluorescence from single droplet-confined molecules can be directly observed. Many applications have been found in recent years for droplet compartmentalization of biological reagents. Often these involve the use of single DNA templates in applications of directed evolution or gene sequencing. As many of the methodologies might be useful in detection of single biochemical interactions, we provide a brief outline here. More complete reviews can be found elsewhere in the literature (Griffiths and Tawfik, 2006; Kelly et al., 2007; Leamon et al., 2006; Song et al., 2006; Taly et al., 2007). A general method for expression and evolution of enzymes using droplet compartmentalization in bulk emulsions to link genotype and phenotype was first elucidated by Tawfik and Griffiths (1998). In this work and in subsequent works (Bernath et al., 2005; Cohen et al., 2004; Doi and

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Yanagawa, 1999; Ghadessy et al., 2001; Griffiths and Tawfik, 2003), much of which is reviewed in Griffiths and Tawfik (2006), a single gene is confined to individual droplets in an emulsion. Ghadessy et al. (2001) demonstrated the directed evolution of a polymerase in a droplet using a feedback loop whereby successful polymerases amplify their own single encoding gene inside a droplet. More recently, Courtois et al. (2008) demonstrated protein expression and detection on-chip from single DNA templates confined to droplets using a microfluidic technique introduced by Dittrich et al. (2005). In contrast to bulk emulsions, the use of microfluidic droplet generators make it possible to individually prepare, address, and analyze specific droplets on a single device. Compartmentalization using droplet fluidics, therefore, provides a particularly convenient method to link genotype and phenotype for in vitro molecular evolution. While PCR on a single gene confined to a droplet was demonstrated by Ghadessy et al. (2001) in the context of directed evolution of DNA polymerases, it was introduced specifically for single-molecule sensitive amplification by Nakano et al. (2003). Musyanovych et al. (2005) refined the technique to use a miniemulsion formulation that resulted in a more monodisperse distribution of droplets; they were able to demonstrate PCR in 200 nm emulsions where one-third of the droplets contained both a single DNA template and single DNA Taq polymerase. Emulsion PCR has been further refined for commercial deployment and used for gene sequencing by 454 Life Sciences (Margulies et al., 2005). Similar to an earlier protocol using magnetic beads (Dressman et al., 2003), the 454 technique uses droplet confinement to amplify single genomic fragments 107 times and to attach the copies to a single bead confined in the same droplet. In both the magnetic case, and the 454 protocol, beads are later purified for analysis. For more uniform droplet generation and therefore more uniform amplification, microfluidic devices have recently been adapted to generate monodisperse droplets for PCR in a similar application (Kumaresan et al., 2008). The invention of real-time quantification of PCR (Heid et al., 1996) and the use of microfluidic devices now means that PCR can be achieved and analyzed on-chip with nanoliter (Beer et al., 2007) or picoliter (Kiss et al., 2008) droplets providing isolation necessary to amplify individual nucleic acid templates. A recent review of microfluidic DNA amplification can be found in Zhang and Ozdemir (2009). More recently, droplet microfluidic devices have been adapted quite generally for droplet-confined chemistry. Microfluidics have the advantage of creating very monodisperse droplets, with rates of droplet formation of up to 3000/s now typical. Furthermore, by confining reactants to a droplet, dispersion that occurs by virtue of a parabolic flow field in continuous flow devices is eliminated. Many of the applications of droplet fluidic devices are discussed in pertinent reviews (Griffiths and Tawfik, 2006; Kelly et al., 2007; Leamon et al., 2006; Song et al., 2006; Taly et al., 2007).


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Finally, it is worth noting that single cells have similarly been confined to droplets. Huebner et al. (2007) showed protein expression could be detected inside single intact cells confined to droplets in a microfluidic device. The directed evolution work of Ghadessy et al. (2001) also used single bacterial cells to provide single gene templates, but in this technique, intact cells are lysed with the first PCR cycle.

2. Methods for Droplet Generation 2.1. Emulsification Commonly called nano- or miniemulsions, metastable suspensions of water-in-oil droplets less than a micron in size can be generated by a variety of methods (Mason et al., 2006; Solans et al., 2005). Many of these methods involve extreme shear generated by ultrasound or high-pressure homogenizers. Droplets as small as a few tens of nanometers in diameter (zeptoliter volumes) can be generated this way, but the droplet size and size distribution are difficult to control, and the agitation process is damaging to many biomolecules. For example, large DNA molecules are known to break under ultrasonication (Musyanovych et al., 2005). A protocol for the formation of emulsions using ultrasonication is given in Section 5 and a similar protocol is described in Reiner et al. (2006). Triton X-100 (Sigma) is used as a surfactant, and Fluorinert FC-40, FC-70, or FC-77 (3M) as the continuous phase. As discussed later, we use perfluorinated continuous phases for their low refractive index, which facilitates optical trapping of aqueous droplets. The surfactant facilitates formation and serves to make the droplet smaller; it does not, in this case, stabilize the droplets against coalescence. The droplets formed were generally smaller than 1 mm in size, and in some cases as small as 50 nm, as measured by dynamic light scattering. Perfluorinated compounds sold by 3M under the Fluorinert trade name have low solubility in water, 10 ppm or less, and only slightly higher water solubility. Evaporation of droplets is therefore not a serious problem. We have not investigated the consequences of small amounts of Fluorinert dissolved in the aqueous phase, but we generally expect it to be inert. The viscosity of the various Fluorinert fluids vary widely; FC-70 is nearly 20 times more viscous than FC-77 and requires a longer time in the ultrasonic cleaner to form an emulsion (several minutes) than does FC-77 (several seconds). A schematic of the measurement for molecules confined to droplets in emulsion is shown in Fig. 5.1, and details are given in Section 5. Droplets are optically trapped out of the emulsion by translating the sample stage and positioning a droplet in the trap, which is colocalized with the fluorescence excitation volume of a confocal microscope. Fluorescence from a molecule

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Emulsify

Trap and probe Fluorescent molecule

Detect Fluorescence excitation laser Photon counting detector

Fluorescence emission Aqueous nanodroplet in perfluorinated continuous phase

1064 nm trap laser

Figure 5.1 Overall scheme for single-molecule measurement in preformed emulsion droplets.

or molecules inside the droplet is collected through the microscope and detected at a high quantum-yield photon-counting detector. For droplets that are stable against coalescence, Tawfik and Griffiths (1998) used 4.5% (v/v) Span 80 (mineral oil) in their continuous phase, followed by 0.5% (v/v) Tween 80. They formed their emulsion by stirring, with a resulting mean droplet size of 2.6 mm. Ghadessy et al. (2001) used a similar protocol but they changed the surfactant concentrations and added a third surfactant, Triton X-100, with a reported average droplet diameter of 15 mm and improved stability to changes in temperature. Droplet size depends dramatically on the details of stirring. Musyanovych et al. (2005) explored different continuous phases and used ultrasonication to create a stable miniemulsion with resulting droplet average diameters from 100 to 1200 nm.

2.2. Injection Droplets formed in bulk emulsion have considerable limitations. First and foremost, there will be a distribution of sizes. Second, the experimental procedure requires the user to ‘‘hunt and trap’’ individual droplets, which can be time-consuming. A solution to these limitations is to use the piezoelectric droplet injector developed and described by Tang et al. (2009) and shown in Fig. 5.2. The injector (Fig. 5.2) is built around a piezoelectric tube (EBL Products Inc., type EBL 2, 3.175 mm OD 0.508 mm wall 25.4 mm length) with single inner and outer nickel electrodes. The tube is fitted with Macor endcaps MC1 and MC2 using either cyanoacrylate glue or epoxy. MC1 holds a sharpened microcapillary tube (also called micropipette) in place with a set screw, and MC2 serves as a structural base for the injector. MC2 is mounted onto an aluminum (Al) holder that is fixed on a three-dimensional

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s

MC2

Al holder

s PT

T

p

MC1

B

Figure 5.2 Schematic representation of the piezoelectric driven inertial injector showing the set screws (s) that hold the glass micropipette (p) in the front macor endcap (MC1) and the back macor endcap (MC2) in the Al holder. PT is the piezoelectric tube (Tang et al., 2009).

translation stage with micrometer adjusters. The sharpened end of the micropipette protrudes from the front of the injector and the microcapillary end extends out the back of MC2. The protocol for loading using the droplet injector is given in Section 5. After the injector has been loaded with sample, and the sample driven with a backing pressure to form a meniscus at the microcapillary tip, a sawtooth waveform is used to drive the piezoelectric tube and eject droplets on demand into the continuous phase. The waveform is generated by an HP function generator (model 33120A, 8 ms rise time typical with fall time 30) of shorter oligonucleotides (20 bases), each of which hybridize to a different portion of the target mRNA (Fig. 17.1). We label each of these oligonucleotides with a single fluorophore at its 30 end; thus, upon hybridization, a large number of fluors are all brought within close proximity of

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30-50 probes labeled on 3⬘ end Positions selected to optimize GC content

Open reading frame of target mRNA

Figure 17.1 Depiction of scheme for imaging individual mRNA molecules using singly labeled oligonucleotide probes. The placement of the probes is often nonuniform in order to maintain an optimal GC content for all probes, thus matching hybridization conditions between probes. See Raj et al. (2008) for all sequences used in this chapter.

the target. The presence of so many fluors in a single location results in enough fluorescence that the spot can be made out as a diffraction-limited spot in a widefield fluorescence microscope. Our method achieves its specificity and sensitivity owing to the large number of probes used. The rate of false negatives is low because even if the target RNA molecule has been partly degraded or is partly obscured by RNA binding proteins, at least some fraction of the probes will still bind to it, yielding a detectable signal. The rate of false positives is also low because one only detects a signal when a significant fraction of the probes are bound. Thus, off-target binding of individual probes will not yield much signal above background. Such false positives are particularly a concern in other methods consisting of the hybridization of a single probe followed by an enzymatic signal amplification; in such cases, it is impossible to distinguish a single nonspecific binding event from a legitimate interaction. Moreover, our method is straightforward and easy to implement, owing to the simplicity of the chemistries involved. Advances in oligonucleotide synthesis make it cost effective to purchase large numbers of singly functionalized probes, and the labeling procedure can be performed on a pooled set of these oligonucleotides, greatly reducing the effort required. Another feature of our method is that it can be combined with other methods like DNA FISH (Vargas et al., 2005) (Arjun Raj unpublished observations) and immunofluorescence (Raj et al., 2008). Furthermore, the fact that we see diffraction-limited spots allows us to precisely determine the location of the center of the spot beyond the optical diffraction limit (Yildiz et al., 2003), technically making our method a version of super-resolution imaging. One question that often arises is how we know that each fluorescent spot represents a single RNA molecule rather than a conglomeration of multiple target mRNAs. We have several pieces of evidence supporting the conclusion that each spot corresponds to a single RNA, mostly outlined in Vargas et al. (2005). In one experiment, we synthesized mRNAs prehybridized with two different fluorophores (effectively, we made ‘‘red’’ and ‘‘green’’ mRNAs). We then injected a mixture of these red

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and green mRNAs into single cells. If the mRNAs were in fact clumping, the spots would have contained both red and green mRNAs and would thus appear yellow. What we found, however, was that each spot was either red or green but never both, showing that each spot corresponded to individual red or green mRNA molecules. Moreover, the signal intensities from these synthetic mRNAs were roughly identical to those from endogenously transcribed mRNAs, indicating that endogenously transcribed mRNAs also do not form clumps. It is possible, of course, that certain other mRNAs form clumps, and a formal proof requires this procedure be followed for each particular mRNA under study, but at least this case is consistent with the null hypothesis that mRNAs do not form conglomerates. Another piece of evidence comes from examining the distribution of spot intensities (Raj et al., 2008; Vargas et al., 2005). If some of the spots were conglomerates of small numbers of mRNA, one would expect that some spots would consist of one mRNA, some of two, and so on. The distribution of spot intensities would then show multiple peaks, as observed with MS2 binding-site-tagged mRNAs, which are know to clump (Golding et al., 2005). Instead, we always see a single peak (Raj et al., 2008; Vargas et al., 2005), consistent with each spot representing single mRNA molecules. We also compared mRNA counts obtained with our method (specifically, average number of mRNA per cell) to those obtained by quantitative RT-PCR and found that the results compared favorably, coming within 30% of each other. These measurements not only bolster our claim to be detecting individual molecules, but also show that our fixation procedure does not result in the loss of a significant fraction of the mRNAs in the sample. Another potential issue could be the occlusion of the target RNA by various RNA-binding proteins; for example, cytoplasmic mRNAs being occluded by ribosomes. We doubt this factor is significant, though, partly because of the quantitative RT-PCR experiments described above. Also, we simultaneously labeled both the open-reading frame and the 30 UTR (upon which there should be no ribosomes) simultaneously but with differently colored probes, and we found a high degree of colocalization (80%), showing that at least ribosome binding is not a significant impediment to RNA detection. In this chapter, we describe the procedures involved in detecting individual RNA molecules in situ. These are (1) designing and synthesizing the fluorescently labeled oligonucleotides, (2) fixation of the biological specimen, (3) hybridization, (4) imaging on a fluorescence microscope, and (5) data analysis. None of these steps utilize any exotic chemicals, procedures or equipment, and we will indicate as needed any aspects of the application of our method that require any special attention.


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2. Design and Synthesis of Fluorescent Oligonucleotide Probe Sets 2.1. Design Our method involves the synthesis of a set of fluorescently labeled oligonucleotides (which we call the ‘‘probe set’’) that will hybridize along the length of target RNA molecule. There are a few general guidelines we typically follow when designing these oligonucleotides. Firstly, the probe sets typically consist of anywhere between 30 and 96 (typically 48) different 20mer DNA oligonucleotides, each complementary to a different region of the target RNA, with no less than two bases separating any two oligonucleotides (Fig. 17.1). We have found that one can sometimes obtain signals with less than 30 oligonucleotides, but the signals are often fainter. Forty-eight probes appear to be sufficient to generate a robust signal in most instances, and many synthesis companies sell parallel orders of oligonucleotides in batches of 48, which is why that is the default number of oligonucleotides we utilize in our probe sets. Another issue is that of the GC content of the individual oligonucleotides. Given that GC content can significantly alter the hybridization parameters, we consider it desirable to make the GC contents of the various oligonucleotides as uniform as possible, thus ensuring that as many probes as possible will bind at a given hybridization stringency. In order to design such probe sets, we have deployed a web-based program (http://www. singlemoleculefish.com) that, given a target RNA sequence, a desired number of probes and a target GC percentage, will generate a set of oligonucleotides whose GC contents are as uniform as possible. Of course, for shorter target RNAs, there is a tradeoff between the number of probes one can generate and the GC uniformity of those probes, but we have not systematically studied these effects. Anecdotally, we find that beyond around 35 probes, optimizing the GC content of the probes is probably more useful than squeezing more probes onto the target mRNA. As reference points, we note that we have seen decent signals using as few as 20 probes and excellent signals using just 30 probes, meaning that one can detect mRNAs as short as 500 bases.

2.2. Synthesis and purification Once the oligonucleotide sequences are generated, we order the oligonucleotides synthesized with a 30 amine group, which we use for coupling the fluorophore. The oligonucleotides we order are desalted and resuspended in water rather than TE, since Tris can interfere with subsequent aminecoupling reactions. Since the amount of oligonucleotide used for each hybridization is typically very small, one should have the oligonucleotides

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synthesized on the smallest scale possible. We order our oligonucleotides from Biosearch Technologies (Novato, CA) at a scale of 10 nmol per oligo, which are delivered to us in 100 ml of water. We have found that other means of labeling oligonucleotides (especially internal amino-dTs) have far lower coupling efficiencies. The next step is to couple the oligonucleotides to the desired fluorophore. We utilize succinimidyl ester derivatives to couple to the amine group at the 30 end of the oligonucleotides (we will discuss the choice of fluorophore shortly). Rather than coupling and purifying each oligonucleotide individually, we instead couple and purify the oligonucleotides en masse via reverse phase HPLC, significantly reducing the labor involved: 1. Combine the uncoupled oligonucleotides by pooling 1 nmole of each oligonucleotide (10 ml in our case) together. 2. Add enough volume of 1 M sodium bicarbonate (pH 8.0) so that the oligonucleotide pool contains 0.1 M sodium bicarbonate. 3. Meanwhile, dissolve the fluorophore in 50 ml of 0.1 M sodium bicarbonate (pH 8.0). Note that some fluorophores, such as tetramethylrhodamine (TMR), are more readily soluble in organic solvents; we first dissolve those fluorophores in around 5 ml of DMSO and then add 50 ml of 0.1 M sodium bicarbonate. 4. Add the fluorophore solution to the oligonucleotide solution. 5. Let the reaction sit in the dark overnight at room temperature. At this point, the tube will contain uncoupled fluorophore, uncoupled oligonucleotides, and coupled oligonucleotides. In order to remove the uncoupled fluorophores, we perform an ethanol (EtOH) precipitation: 6. Add 0.13 vol of 3 M sodium acetate (pH 5.2) and 2.5 vol EtOH to the reaction. 7. Store at 80 C for at least 1 h. 8. Spin in a 4- C microcentrifuge at maximum speed for 15 min. A colored pellet containing the coupled and uncoupled oligonucleotides should form at the bottom of the tube. 9. Carefully pipette off as much of the supernatant as possible. This supernatant contains the uncoupled fluorophore. In order to separate the uncoupled oligonucleotides from the coupled oligonucleotides, we purify the oligonucleotides by HPLC. The typically hydrophobic organic fluorophores cause a large increase in hydrophobicity of the coupled oligonucleotides as compared to the rather hydrophilic uncoupled oligonucleotides. The size of this increase is much larger than the variation in the hydrophobicity of the individual oligonucleotides, thus enabling us to purify the entire pool of oligonucleotides at once. This procedure requires an HPLC equipped with a C18 column (C18TP104) and a dual wavelength detector (or diode array detector) set to


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detect DNA absorption (260 nm) as well as the absorption of the coupled fluorophore (e.g., 555 nm for TMR). We have found it easiest to collect the desired fractions manually rather than automatically from the outflow. For our gradient, we use 0.1 M Triethyl ammonium acetate, pH 6.5 (Buffer A) and acetonitrile, pH 6.5 (Buffer B), ranging from 7% to 30% Buffer B over the course of 30 min at a flow rate of 1 mL per min (after this, be sure to run the column at 70% Buffer B for 10 min in order to clear the column of extraneous molecules and then equilibrate the column at 7% Buffer B for 10 min before running another sample). The specific gradient may depend on the exact nature of your HPLC setup, but should be at least similar to that we describe here. While the gradient is running, continuously monitor the absorption in the 260 and 555 nm channels. Initially, you will see a large set of peaks at 260 nm while the 555 nm absorption remains low. This peak contains the uncoupled oligonucleotide. After that peak passes, you will observe another set of peaks in which there is large absorption in both the 260 and 555 nm channels (Fig. 17.2). This peak contains the coupled oligonucleotides. Collect this fraction as it passes through the HPLC (the total volume collected will typically be between 2 and 6 mL). Be sure to collect the entire peak rather than just the ‘‘top.’’ This is important, because different parts of the peak will contain different oligonucleotides. It also bears mentioning that even labeled oligonucleotide can generate multiple peaks due to incomplete deprotection or dye-induced chemical variation. We do not think, though, that these issues lead to any serious problems in oligonucleotide purity. Once the fraction is collected, dry the samples in a lyophilizer or a speedvac rated for use with acetonitrile, then resuspend the fractions in 50–100 ml of Tris EDTA (TE), pH 8.0. This is the stock of your probe (concentration of roughly 0.1–1 mM) from which you can make working dilutions (1:10, 1:20, 1:50, 1:100) for your hybridizations. As for the choice of fluorophore, the ones we commonly use are TMR (Molecular Probes, Invitrogen), Alexa 594 (Molecular Probes, Invitrogen), and Cy5 (GE Amersham). Using appropriate filter sets (Table 17.1), we are able to independently image these three colors reliably in most samples we have examined with no bleedthrough between channels (Fig. 17.3). While it is possible that one can use fluorophores that absorb and emit at even shorter wavelengths (e.g., Alexa 488), we have found that background autofluorescence at these wavelengths is usually strong enough that it is difficult to make out the signals (although we have had success with Alexa 488 on occasion). Even the signals from TMR and to some extent Alexa 594 are sometimes marred by autofluorescent blobs that make the particles hard to distinguish. In such situations, one can get some idea of whether or not the signals are real by taking pictures of the sample using GFP/fluorescein filters—background autofluorescence typically has a broad emission spectrum and will often show up in multiple channels, whereas the organic dyes will not appear in the GFP channel. Reducing this background is often

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Figure 17.2 Sample HPLC chromatographs showing absorbance at 260 nm (blue) and 555, 594, and 650 nm (red; TMR, Alexa 594, and Cy5, respectively). The first 260 nm peak is the uncoupled oligonucleotides. The next peak appears in both the 260 nm and fluorophore absorbance channels, indicating that this is the coupled oligonucleotides. Collect the entire fraction between the gray dotted lines.

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Table 17.1 Optical filters for multiplex mRNA detection

TMR Alexa 594 Cy5

Excitation

Dichroic

Emission

Supplier

546DF10 590DF10 HQ620/60x

555DRLP 610DRLP Q660LP

580DF30 630DF30 HQ700/75m

Omega Omega Chroma

Details of the excitation, dichroic, and emission filters used for multiplex detection with TMR, Alexa 594, and Cy5. The nomenclature used is specific to the suppliers listed on the right (Omega Optical, Chroma). The first and second numbers refer to the center and width of the bandpass region, respectively.

difficult and is very sample dependent, with some cell lines and tissues exhibiting high levels of background, often related to cellular stress. Another factor to consider is the fact that Alexa 594 and especially TMR are fairly photostable and thus require no special care to be taken about photobleaching when imaging. Cy5, on the other hand, is notorious for being rapidly photobleached. In order to combat this, we use a glucose-oxidase (glox)-based oxygen scavenging mounting medium (described later in this chapter; adapted from Yildiz et al., 2003), which reduces the photobleaching rate of Cy5 to levels comparable to that of TMR. Given the low autofluorescent background at these far red wavelengths, Cy5 is an excellent choice for samples in which reduction in cellular autofluorescence is impossible.

3. Preparation of Samples for In Situ Hybridization In this section, we outline the procedures for fixation and permeabilization of various biological samples for use in in situ hybridization. These protocols are based on the protocols developed in the lab of Robert Singer (Femino et al., 1998; http://www.singerlab.org/protocols). While the specifics may change slightly from organism to organism, the fundamental procedure is roughly the same in all cases: fix the sample in 3.7% (v/v) formaldehyde (i.e., 10% formalin) in 1 phosphate buffered saline (PBS), then permeabilize in 70% ethanol, at which point samples can be stored at 4 C for weeks (even months) without degradation. Note that all solutions used postfixation should be made with nuclease-free water.

3.1. Fixation solutions 3.1.1. Fixation solution (3.7% formaldehyde/10% formalin, 1 PBS) 40 mL RNase free H2O (Ambion) 5 mL 37% (v/v) formaldehyde (100% formalin) 5 mL 10 PBS (RNase free, Ambion)

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Figure 17.3 Demonstration of three color mRNA detection. (A) Expression of FKBP5 (blue), PTGS2 (purple), and FAM105A (yellow) mRNAs in human carcinoma cell line A549. Scale bar is 5 mm long. (B–D) Examination of fluorescent spot bleedthrough. (B) Images of an FAM105A mRNA spot labeled with TMR as seen through the TMR, Alexa 594, and Cy5 filter channels. Linescans of fluorescent intensity corresponding to the line through the image are given below, with the different linescans corresponding to measurements taken at increasing z (0.25 mm spacing). The green linescan corresponds to the z-slice shown in the image itself. A similar analysis was performed for a PTGS2 mRNA spot labeled with Alexa 594 (C) and an FKBP5 mRNA particle labeled with Cy5 (D). All linescan intensity measurements had the camera background subtracted but range between 0 and 200 arbitrary fluorescence units.

3.1.2. Buffer B (1.2 M sorbitol, 0.1 M Potassium phosphate) 218 g sorbitol 17.4 g Potassium phosphate (dibasic) RNase free water to 1 L


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3.1.3. Spheroplasting buffer 10 mL Buffer B 100 ml 200 mM vanadyl ribonucleoside complex (New England Biolabs) 3.1.4. M9 5.8 g Na2HPO4 3.0 g KH2PO4 0.5 g NaCl 1.0 g NH4Cl Double-distilled ddH2O (ddH2O) to 1 L

3.2. Fixation protocols 3.2.1. Fixation of yeast cells 1. Grow yeast to an optical density (OD, at 260 nm) of around 0.1–0.2 in a 45-mL volume of minimal media. 2. Add 5-mL of 37% (v/v) formaldehyde directly to growth media and let sit for 45 min. 3. Wash 2 twice with 10 mL ice-cold Buffer B. 4. Add 1 mL of spheroplasting buffer, transferring to a microcentrifuge tube. 5. Add 1 ml of zymolyase and incubate at 30 C for 15 min. 6. Wash 2 twice with 1 mL ice-cold Buffer B, spinning at low speed (2000 rpm). 7. Add 1 mL of 70% (v/v) EtOH and leave at least overnight at 4 C. 3.2.2. Fixation of adherent mammalian cells 1. Grow cells on #1 coverglasses set in six-well culture dishes or in LabTek chambered coverglass (with #1 coverglass on the bottom; we have had bad results with #1.5 coverglass). 2. Aspirate growth medium. 3. Wash with 1 PBS. 4. Add fixation solution and incubate at room temperature for 10 min. 5. Wash 2 twice with 1 PBS. 6. Add 70% (v/v) EtOH and store at 4 C at least overnight. 3.2.3. Fixation of Caenorhabditis elegans larvae (L1–L4) 1. Grow larvae in a plate seeded with OP50. 2. Add 5 mL M9 buffer and swirl in plate to release worms from surface, then move worms to a 15 mL conical centrifuge tube.

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We often use DI water instead of M9 in this step and in step 4 and get fine results. Spin down worms and aspirate. Wash with 5 mL M9 buffer. Spin down worms and aspirate. Add 1 mL fixation solution, transfer to microcentrifuge tube, and incubate for 45 min. 7. Wash 2 with 1 mL 1 PBS. 8. Resuspend in 1 mL of 70% EtOH and leave for at least overnight at 4 C. We have sporadic reports that longer incubations at 4 C in EtOH (i.e., 5 days) can reduce autofluorescence, but we do not think it really matters. 3. 4. 5. 6.

3.2.4. Fixation of C. elegans embryos 1. Add 5 mL M9 buffer to a plate of gravid hermaphrodites and swirl to release worms from surface. Move worms to a 15-mL conical centrifuge tube. We often use DI water instead of M9 in this and subsequent steps and get fine results. 2. Spin down and add bleaching solution (40 mL H2O, 7.2 mL 5 N NaOH, 4.5 mL 6% NaHOCl). 3. Vortex for roughly 4–8 min until worms disappear and only embryos remain. 4. Spin down and aspirate, then wash 2 twice in M9 buffer. 5. Resuspend in 1-mL fixation solution and incubate at room temperature for 15 min. 6. Vortex and then immediately submerge tube in liquid nitrogen for 1 min to freeze crack the embryos’ eggshells. 7. Thaw in water at room temperature. 8. Once thawed, vortex and place on ice for 20 min. 9. Wash twice with 1 mL 1 PBS. 10. Resuspend in 1 mL of 70% (v/v) EtOH and store at least overnight at 4 C. 3.2.5. Fixation of Drosophila melanogaster wing imaginal discs 1. Submerge 3rd instar larvae in 1 mL 1 PBS and dissect to release wing imaginal discs. 2. Place discs at the bottom of a chambered coverglass. They should stick readily.


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3. Fix wing discs by aspirating PBS and adding 1 mL fixation solution; incubate at room temperature for 45 min. 4. Wash 2 twice with 1 mL 1 PBS to remove fixative. 5. Add 1 mL of 70% EtOH and leave at least overnight at 4 C. 3.2.6. Fixation of tissue sections 1. Freeze tissue section in optimal cutting temperature compound (OCT). We have heard reports that using sucrose-based cryoprotectants can lead to high background and so should be avoided. 2. Slice the tissue section into 4–10 micron sections using a cryotome and affix the sections to #1 coverslips; the sections can then be stored for months at 80 C. Notes: Although it is a more standard procedure, do not affix the tissue sections to slides, as this greatly hinders the visualization of the fluorescent spots. Also, the use of poly-L-lysine or some similar surface treatment may enhance the degree to which your tissue section sticks to the coverglass. 3. Thaw the section and immediately fix in fixation solution, either in a coplin jar or a six-well plate. Note: we perform this procedure by affixing a perfusion chamber (Grace Biolabs) to a 24-mm 50-mm coverglass and adding all solutions, etc. to this chamber. Using the perfusion chamber greatly reduces the amount of fixing/washing reagents required. 4. Wash twice with 1 mL 1 PBS to remove fixative. 5. Add 1 mL of 70% (v/v) EtOH and leave for 1 h at room temperature. Note: some researchers have reported trouble with their sections floating off of the coverslip when stored for prolonged periods of time in 70% EtOH; thus, we recommend beginning the in situ hybridization less than 1 h following fixation.

4. Hybridization Hybridization consists of a brief prehybridization followed by an overnight hybridization with the oligonucleotide probes. In the morning, two washes in a washing buffer remove the nonhybridized probes and the samples are essentially ready for imaging. There are three basic parameters involved in the hybridization. One is the concentration of the probes used in the hybridization. We typically determine the appropriate concentration empirically, but we have found that (generally) a concentration in the vicinity of 5–50 nM works. Moreover, we have found that there is a fairly

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significant range (roughly a factor of 2 or 3 in either direction) of concentrations over which the signals are similar and readily quantifiable. When possible, it is best to optimize the probe concentration rather than changing other factors in the hybridization, since multiplex detection requires shared hybridization conditions, which are easy to match when the only variable is different concentrations of probes. The other two parameters of the hybridization are related and concern the stringency of the hybridization itself: one is the temperature at which one hybridizes the probes, and the other is the concentration of formamide used in the hybridization and washes. Regarding the former, higher temperature generally leads to higher stringency, as fewer of the probes will bind (nonspecifically or specifically) as the temperature increases. We typically use either 30 C or room temperature, but rarely change this variable, especially since changing the formamide concentration is largely equivalent and is easier to control in a fine-grained manner. To adjust the stringency via formamide, the main point is that the higher the concentration of formamide, the higher the stringency. We typically use 10% (v/v) for most of our hybridizations, but sometimes probes with GC contents of 55–60% require the use of 25% (v/v) formamide. It is important, however, to note that more stringent conditions can lead to a dramatic rate of false negatives: one can only see a few faint looking spots, when in reality, there are many more mRNAs present. Thus, it is generally better to begin with the less stringent 10% conditions and then work up from there. Also, we have found that adding some wet paper towels in the hybridization chamber is NOT helpful and often causes a spotlike background.

4.1. Hybridization solutions 4.1.1. Hybridization buffer (10 mL) Dextran sulfate (1 g) Escherichia coli tRNA (10 mg) Vanadyl ribonucleoside complex (NEB) (100 ml of 200 mM stock) BSA (RNase free) (Ambion) (40 ml of 5 mg/mL) 20 SSC (nuclease free, Ambion) (1 mL) Formamide (deionized, Ambion) (1 mL for 10% final concentration, can increase formamide to increase stringency) Nuclease free (NF) water (Ambion) (to 10 mL final volume) First, mix the dextran sulfate in about 4 mL of water with gentle agitation at room temperature until dissolved (can take min to h, depending on the batch). Then add the other components. We then keep the hybridization solution in 0.5 mL aliquots at 20 C.


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4.1.2. Wash buffer (50 mL): Wash/prehybridization buffer: 40 mL RNase free water (Ambion) 5 mL Formamide (deionized, Ambion) 5 mL 20 SSC (RNase free, Ambion) Note: one can increase the stringency by increasing the amount of formamide. 4.1.3. Antifade buffer and enzymes: 10% (w/v) glucose in nuclease free water 2 M Tris–HCl, pH 8.0 20 SSC (Ambion) Nuclease free water (Ambion) Glox (Sigma) (diluted to 3.7 mg/mL stock in 50 mM sodium acetate, pH 5) Catalase (Sigma) Mix together 0.85 mL of NF water and add 100 ml of 20 SSC, 40 ml of 10% (w/v) glucose and 5 ml of 2 M Tris–HCl. Vortex and then transfer 100 ml of this ‘‘glox’’ buffer to another tube, to which one should add 1 ml of glox stock and 1 ml of (nicely vortexed) catalase suspension. The remainder will be used as an equilibration buffer.

4.2. Hybridization protocols 4.2.1. Hybridization in solution 1. Prepare the hybridization solution: to 100 ml of hybridization buffer, add 1–3 ml of probe at the appropriate concentration, then vortex and centrifuge. a. Be sure to warm the hybridization solution to room temperature before opening it. b. For the initial test of a set of probes, it is best to start four separate hybridization reactions by adding 1 ml each of the 1:10, 1:20, 1:50, and 1:100 working dilutions of probes to see which one is optimal. 2. Centrifuge the fixed sample and aspirate away the ethanol. 3. Resuspend in 1 mL wash buffer that contains the same percentage formamide as the hybridization buffer you will be using. Let stand for 2–5 min. 4. Centrifuge sample and aspirate wash buffer, then add hybridization solution. Incubate in the dark overnight at 30 C.

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5. In the morning, add 1 mL of wash buffer to the sample, vortex, centrifuge, and aspirate, then resuspend in another 1 mL of wash buffer and incubate at 30 C for 30 min. 6. Vortex, centrifuge, and aspirate the wash buffer, then resuspend in another 1 mL of wash buffer containing 5 ng/mL DAPI for nuclear counterstaining. Incubate at 30 C for 30 min. 7. If you are imaging without using glox antifade solution (e.g., if you are using TMR), then just resuspend in an appropriate volume (>0.1 mL) of 2 SSC and proceed to imaging. 8. If you are imaging with the glox antifade solution, aspirate the buffer and resuspend in the glox buffer without enzymes for equilibration; incubate for 1–2 min. 9. Aspirate the buffer and resuspend in the 100 ml of glox buffer to which the enzymes (glox and catalase) have been added. Proceed to imaging. 4.2.2. Hybridization for samples adhered to coverglass 1. Prepare the hybridization solution: to 100 ml of hybridization buffer, add 1–3 ml of probe at the appropriate concentration, then vortex and centrifuge. a. Be sure to warm the hybridization solution to room temperature before opening it. b. For the initial test of a set of probes, it is best to start four separate hybridization reactions by adding 1 ml each of the 1:10, 1:20, 1:50, and 1:100 working dilutions of probes to see which one is optimal. 2. Aspirate the 70% ethanol off of the sample. 3. Add 1 mL wash buffer that contains the same percentage formamide as the hybridization buffer you will be using. Let stand for 2–5 min. 4. Aspirate wash buffer and then add hybridization solution. Place a carefully cleaned coverslip over the sample to prevent drying of the hybridization solution during the incubation. Incubate in the dark overnight at 30 C. Note: if using perfusion chambers on a coverslip containing a tissue section, one can remove the perfusion chamber before performing the hybridization. 5. In the morning, add 1 mL of wash buffer to the sample, remove the coverslip, then incubate at 30 C for 30 min. a. Be sure to remove the coverslip very carefully so as not to disturb the cells underneath very much. b. For tissue sections, add 100 ml wash buffer to the edges of the coverslip and gently remove the coverslip. Then reaffix a perfusion chamber and proceed as usual. 6. Aspirate the wash buffer, then resuspend in another 1 mL of wash buffer containing 5 ng/mL DAPI for nuclear counterstaining. Incubate at 30 C for 30 min.


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7. If you are imaging without using glox antifade solution (e.g., if you are using TMR), then just add 1 mL of 2 SSC and proceed to imaging. 8. If you are imaging with the glox antifade solution, aspirate the buffer and resuspend in 2 SSC. 9. Aspirate the SSC and add the glox buffer without enzymes for equilibration; incubate for 1–2 min. 10. Aspirate the buffer and resuspend in the 100 ml of glox buffer to which the enzymes (glox and catalase) have been added. 11. Place a carefully cleaned coverslip over the sample. This will spread the glox buffer over the entire sample and also slow evaporation. 12. Proceed to imaging.

5. Imaging At this point, the samples are essentially ready for imaging. The microscopy equipment required is fairly standard.

5.1. Microscopy equipment 1. Standard widefield fluorescence microscope (e.g., Nikon TE2000 or Ti, Zeiss Axiovert). 2. Strong light source, such as a mercury or metal-halide lamp (e.g., ExFo Excite, Prior Lumen 200). We have found that the metal-halide lamps are generally brighter, especially for the far red dyes such as Cy5. 3. Filter sets appropriate for the fluorophores chosen (see Table 17.1). 4. Standard cooled CCD camera, ideally optimized for low-light level imaging rather than speed (13 mm pixel size or less is ideal; for example, Pixis, Princeton Instruments, CoolSNAP HQ). We have found that EMCCDs do not provide any additional signal-to-noise benefits over nongain amplified cameras. 5. High NA (>1.3) 100 DIC objective (be sure to check transmission properties when using far red dyes such as Cy5 or Cy5.5). We have also seen spots using an oil-immersion 60 objective, but the reduced spatial resolution makes the spots somewhat more difficult to identify computationally. Generally speaking, the imaging of single mRNAs using a widefield fluorescence microscope is relatively straightforward; see Fig. 17.4 for some examples. The only difference between this and many more standard applications of fluorescence microscopy is that the signals are much weaker than, say, a DAPI stain, thus requiring exposure times on the order of 2–3 s. We have found that widefield microscopy works best due to the relatively

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Figure 17.4 Imaging mRNAs in a variety of biological samples. (A) elt-2 mRNA molecules (red) in an early stage embryo (100 cell stage) from C. elegans; the nuclei have been counterstained with DAPI (blue). (B) elt-2 mRNA molecules in an L1 larva from C. elegans. Inside the blue box, a single focal plane is shown in which the intestinal track is visible. (C) A schematic depiction of dpp and engrailed expression in the imaginal wing discs of third instar larvae from D. melanogaster. (D) Image showing the locations of the computationally identified dpp mRNA molecules (light blue circles) and Engrailed expression detected by immunofluorescence (dark blue). (E) Image containing enhanced dpp mRNA molecule signals (light blue) and Engrailed protein expression detected by immunofluorescence (dark blue). (F) Image of FKBP5 mRNAs in human carcinoma cell line A549 induced with dexamethasone (nuclei in purple). (G–H) STL1 mRNA particles in both unperturbed cells (G) and cells subjected to a 10-mi 0.4 M NaCl salt shock (H), with nuclear DAPI counterstaining in purple. STL1 is one among a number of yeast genes whose expression is significantly upregulated by the addition of salt to the growth medium. All images except the boxed portion of (B) are maximum merges of a z-stack of fluorescent images, and all scale bars are 5 mm long.


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large amount of light gathered as compared to confocal imaging setups. That said, we have had some success using both spinning disk and laser scanning confocal microscopes, but it seems that one issue with their use is that the high intensity of the laser excitation rapidly bleaches samples. Since the total light collection is much lower than in a widefield microscope (per illumination), this bleaching limits the signal one can gather and is especially problematic when one takes multiple z sections to generate three-dimensional image stacks. However, the use of widefield microscopy places a tight limitation upon the thickness of the sample one can image, because thicker samples lead to far more out-of-focus light that can obscure the relatively faint mRNA signals. We have found that the single mRNA signals are most readily detectable when the sample is less than 7–8 microns thick. Some samples (notably C. elegans embryos and larvae) are considerably thicker than this limit, so we generally flatten them between two coverslips to reduce the z-extent of the sample considerably before imaging. For other samples, such as tissue sections and cell lines, the specimens are already sufficiently thin so as to obviate the requirement for flattening. Also, for imaging multiple slices, we recommend using at least a 0.2-mm z spacing between sections, and larger spacings such as 0.3 or even 0.4 mm are also probably fine. The main consideration is an empirical one: Aim for each RNA spot showing up in at least two adjacent optical sections. This gives confidence that the spots identified are legitimate. There are also some common microscopy practices that one should avoid when doing single molecule FISH. One of these is the use of commercial antifade mounting media. We have found that while these media do decrease the rate of photobleaching, they also lower the overall fluorescence of the sample and also introduce a strong background that interferes with the FISH signals (most likely from the glycerol included in many of these solutions). We recommend avoiding these entirely and just imaging with the antifade glox solution (or just 2 SSC if photobleaching is not a concern). Another thing to avoid is the use of nail polish to seal samples. This introduces a high background into the sample, again obscuring the FISH signals. We recommend sealing with silicone-based vacuum grease instead. Regarding the mounting of the samples, we use #1 coverglass to image all of our samples. We have found that our signals are better with #1 than with #1.5, even though our objectives (like most) are designed for use with #1.5 coverglass. Also, one should avoid having ones samples on a microscopy slide and then ‘‘covering’ them with coverglass. We have found that the subsequent layer of liquid between the top of the coverglass and the sample causes the signals to blur. If the target RNAs are stained properly, you will see clear diffractionlimited spots, such as those depicted in Fig. 17.4. The width of the spots is

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roughly 200–500 nm, depending on the dye and the imaging setup. While the intensities of the individual spots may vary, the spot size should be essentially identical. (An exception to this are active sites of transcription, at which many nascent mRNAs accumulate, resulting in a somewhat larger and significantly brighter spot (Femino et al., 1998; Raj et al., 2006; Vargas et al., 2005) Variability in the spot size is an indication that the spots are not actually target mRNAs but rather are some form of autofluorescent background. One way to check for this is to perform the hybridization without adding the probes to check if the allegedly nonspecific spots persist. Another way to see if the spots are merely autofluorescent background is to acquire images with different filter sets. Typically, the autofluorescent background will show up in multiple channels, owing to the rather broad spectral properties of cellular autofluorescence—with appropriate filters, there is essentially no bleedthrough between the different organic dyes used to label the oligonucleotides (Fig. 17.3) (Raj et al., 2008).

6. Image Analysis The analysis of images acquired using this method involves the computer-assisted identification of spots in a three-dimensional set of images (Fig. 17.5). Given that the spot-like signals are significantly brighter than the background, one might assume that a simple threshold would be sufficient. Unfortunately, due to out-of-focus light, the background itself often varies greatly throughout the image, making the simple application of a threshold impossible. To remove this (typically slowly varying) background, we employ Laplacian of Gaussian (LoG) filters (Fig. 17.5B). The LoG filter has essentially one parameter, which is the width of the filter. For any particular microscope/camera combination, we usually determine the optimal filter width by trial and error (theoretically, the width of the filter should be the same as the width of the spots one is trying to identify). We should note that we apply our filters in three-dimensions, thus using the three-dimensionality of the spots to further enhance the signals. Another option for removing the out-of-focus light is deconvolution software. We have found, though, that while the results from deconvolution are often nice, they seldom yield results that are better in terms of spot counting accuracy. Moreover, they are extremely expensive, both monetarily and computationally. For these reasons, we find our simple linear filtering approach to be more appropriate, especially for large data sets. After performing the filtering, one must select an appropriate threshold. We have found that this task is difficult to automate, since it is difficult to say a priori what the appropriate threshold is. Instead, we compute the number of spots detected for all possible thresholds. Upon graphing this relationship,


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Figure 17.5 Computational identification of mRNA spots. (A) Raw image data (maximum intensity merge) obtained from imaging FKBP5 mRNA particles in A549 cells induced with dexamethasone. (B) Image (maximum merge) obtained by running raw data through Laplacian of a Gaussian filter designed to enhance spots of the correct size and shape while removing the slowly varying background. (C) The number of spots (i.e., connected components) found upon thresholding the filtered image from (B) is plotted as a function of the threshold value, ranging from 0 to the maximum intensity of the filtered image (normalized to 1). The presence of a plateau indicates that there is a region over which the number of particles detected is fairly insensitive to the particular threshold chosen. The gray line represents the threshold used (within the plateau) for determining the actual number of mRNA in the image. (D) Image showing the results of using the threshold represented by the gray line in C on the filtered image in (B), with each distinct spot assigned a random color. The spots detected correspond very well with those identified by eye. All scale bars are 5 mm long. Adapted with permission from Supplementary Fig. 1 of Raj et al. (2008).

we found that there was a plateau region in the graph, which means that there is a broad region of thresholds over which the spot count does not vary significantly (Fig. 17.5C). This is generally the correct threshold to choose, as spots identified at those thresholds correspond nicely to those identified by eye (Fig. 17.5D). Our image processing pipeline is thus to first preprocess the data via filtering and applying all possible thresholds, then manually picking thresholds based on the graph (with some visual feedback). We find that this facilitates rapid processing of many images, allowing one to threshold hundreds of images in a matter of hours. Software demonstrating these algorithms (implemented in MATLAB and including some sample data) is free for download at: http://rajlab.seas.upenn. edu/pdfs/raj_nat_meth_2008_software.zip.

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ACKNOWLEDGMENTS Sanjay Tyagi acknowledges support from National Institutes of Health grant NIMH079197. Arjun Raj acknowledges support from National Science Foundation postdoctoral fellowship DMS-0603392 and a Burroughs-Wellcome Fund Career Award at the Scientific Interface.

REFERENCES Femino, A. M., Fay, F. S., Fogarty, K., and Singer, R. H. (1998). Visualization of single RNA transcripts in situ. Science 280, 585–590. Gall, J. G. (1968). Differential synthesis of the genes for ribosomal RNA during amphibian oo¨genesis. Proc. Natl. Acad. Sci. USA 60, 553–560. Golding, I., Paulsson, J., Zawilski, S. M., and Cox, E. C. (2005). Real-time kinetics of gene activity in individual bacteria. Cell 123, 1025–1036. Larson, D. R., Singer, R. H., and Zenklusen, D. (2009). A single molecule view of gene expression. Trends Cell Biol. 19, 630–637. Levsky, J. M., and Singer, D. (2003). Fluorescence in situ hybridization: Past, present and future. J. Cell Sci. 116, 2833–2838. Maamar, H., Raj, A., and Dubnau, D. (2007). Noise in gene expression determines cell fate in Bacillus subtilis. Science 317, 526–529. Maheshri, N., and O’shea, E. K. (2007). Living with noisy genes: How cells function reliably with inherent variability in gene expression. Ann. Rev. Biophys. Biomol. Struct. 36, 413–434. Raap, A. K., Van de corput, M. P., Vervenne, R. A., Van gijlswijk, R. P., Tanke, H. J., and Wiegant, J. (1995). Ultra-sensitive FISH using peroxidase-mediated deposition of biotinor fluorochrome tyramides. Hum. Mol. Genet. 4, 529–534. Raj, A., and Van oudenaarden, A. (2008). Nature, nurture, or chance: Stochastic gene expression and its consequences. Cell 135, 216–226. Raj, A., and Van oudenaarden, A. (2009). Single-molecule approaches to stochastic gene expression. Ann. Rev. Biophys. 38, 255–270. Raj, A., Peskin, C. S., Tranchina, D., Vargas, D. Y., and Tyagi, S. (2006). Stochastic mRNA synthesis in mammalian cells. PLoS Biol. 4, e309. Raj, A., Van den bogaard, P., Rifkin, S. A., Van oudenaarden, A., and Tyagi, S. (2008). Imaging individual mRNA molecules using multiple singly labeled probes. Nat. Methods 5, 877–879. Tautz, D., and Pfeifle, C. (1989). A non-radioactive in situ hybridization method for the localization of specific RNAs in Drosophila embryos reveals translational control of the segmentation gene hunchback. Chromosoma 98, 81–85. Vargas, D. Y., Raj, A., Marras, S. A., Kramer, F. R., and Tyagi, S. (2005). Mechanism of mRNA transport in the nucleus. Proc. Natl. Acad. Sci. USA 102, 17008–17013. Yildiz, A., Forkey, J. N., Mckinney, S. A., Ha, T., Goldman, Y. E., and Selvin, P. R. (2003). Myosin V walks hand-over-hand: Single fluorophore imaging with 1.5-nm localization. Science 300, 2061–2065. Zenklusen, D., Larson, D. R., and Singer, R. H. (2008). Single-RNA counting reveals alternative modes of gene expression in yeast. Nat. Struct. Mol. Biol. 15, 1263–1271.

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Single mRNA Tracking in Live Cells Hye Yoon Park, Adina R. Buxbaum, and Robert H. Singer Contents 388 389 391 391 392 393 394 394 395 396 396 397 398 399 401 402 403 403

1. Introduction 2. Significance of Tracking mRNA 3. Labeling mRNA in Living Cells 3.1. Selection of probes for SPT 3.2. The MS2-GFP system 3.3. Minimizing photobleaching and phototoxicity 4. Imaging mRNA Movements 4.1. Experimental considerations 4.2. Instrumentation 4.3. 3D tracking 5. Analyzing mRNA Motions 5.1. Localization algorithms 5.2. Tracking algorithms 5.3. Categories of single particle motion 5.4. Interpretation of mRNA tracking data 6. Conclusions Acknowledgments References

Abstract Asymmetric distribution of mRNA is a prevalent phenomenon observed in diverse cell types. The posttranscriptional movement and localization of mRNA provides an important mechanism to target certain proteins to specific cytoplasmic regions of their function. Recent technical advances have enabled real-time visualization of single mRNA molecules in living cells. Studies analyzing the motion of individual mRNAs have shed light on the complex RNA transport system. This chapter presents an overview of general approaches for single particle tracking and some methodologies that are used for single mRNA detection. Anatomy and Structural Biology and Gruss-Lipper Biophotonics Center, Albert Einstein College of Medicine, New York, USA Methods in Enzymology, Volume 472 ISSN 0076-6879, DOI: 10.1016/S0076-6879(10)72003-6

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1. Introduction Localization of mRNA is an important mechanism to generate cell polarity crucial in diverse cellular functions from motility to differentiation (for reviews, see Condeelis and Singer, 2005; Martin and Ephrussi, 2009; Shav-Tal and Singer, 2005). The asymmetrical distribution of mRNA provides a means for a cell to regulate the protein synthesis at high spatial and temporal resolution. Localized mRNAs can be translated repeatedly to produce high concentrations of proteins in specific subcellular compartments in response to local stimuli. To date, thousands of mRNAs are found to exhibit spatially distinct patterns in many different cell types, including budding yeast, fruit fly oocyte, fibroblasts, and neurons (Martin and Ephrussi, 2009). Technical developments in intracellular RNA imaging have been indispensable to increase our knowledge about the mechanisms of mRNA localization. When the localization of b-actin mRNA was first observed in the lamellipodia of fibroblasts (Lawrence and Singer, 1986), the mRNAs were hybridized with radioactive DNA probes and visualized by autoradiography, which required exposure times in the range of weeks. Now, it is possible to observe the movement of single mRNA molecules in living cells in real time (Bertrand et al., 1998; Fusco et al., 2003; Shav-Tal et al., 2004). Single particle tracking (SPT) is used in many different research fields to investigate the dynamics of individual objects by regarding them as punctate points while ignoring the internal conformations. By following the trajectories of particles, we can characterize the types of motion and measure the velocity or diffusion coefficient. Jean Perrin, probably in the first SPT akin to modern methods, observed the movements of gamboges with submicron precision (Perrin, 1913). His quantitative analysis of the trajectories supported Einstein’s microscopic theory of Brownian motion (Einstein, 1905). In cell biology, the use of SPT was pioneered by Barak and Webb (1982). They observed the motion of fluorescently labeled low-density lipoprotein (LDL) receptors on plasma membrane. De Brabander et al. (1985) microinjected colloidal gold particles of 20–40 nm in living cells, and visualized their motion using transmitted light To date, SPT has been extensively used to study complex cellular dynamics, including ligand–receptor interactions, membrane organization, secretory granules, locomotion of motor proteins, and transport within nuclei (reviewed in Kusumi et al., 2005; Levi and Gratton, 2007; Saxton and Jacobson, 1997; Wieser and Schutz, 2008). There are other optical techniques for measuring the lateral mobility. In the technique of fluorescence recovery after photobleaching, or FRAP (Axelrod et al., 1976), a region of interest is irreversibly photobleached by

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intense laser irradiation and then, recovering fluorescence in the area is recorded in time. From the recovery curve, one can derive the fraction and the diffusion coefficient D of mobile fluorescent molecules. Caution is required, however, in the presence of multiple species with distinct characteristics of mobility: FRAP data are an ensemble average of the total population, and the specific dynamics of a subpopulation may be hidden. SPT overcomes this limitation of FRAP by directly observing individual particles. Furthermore, the spatial resolution of SPT exceeds that of FRAP by more than an order of magnitude. SPT considers only the center of particles which can be determined with a precision of one to tens of nanometers, whereas the diffraction-limited focal volume dictates the minimum area in FRAP or fluorescence correlation spectroscopy (FCS). Consequently, SPT is suitable for high-resolution studies, far below the diffraction limit, of nanometer-scale displacements and structures, such as motor proteins and membrane microdomains. Here, we describe SPT techniques that have been applied to the studies of mRNA trafficking in living cells. Methods to label, visualize, and track single mRNA molecules are reviewed. The ‘‘MS2 system’’ (Beach et al., 1999; Bertrand et al., 1998) for labeling mRNA is emphasized, which has been established in our laboratory. Various analysis techniques are reviewed and the information obtained by combining SPT with the MS2 system is discussed toward the end of the chapter.

2. Significance of Tracking mRNA Many aspects of mRNA transport and localization have been discovered by single mRNA imaging and tracking. Whereas in situ hybridization shows the distribution of mRNA fixed at different stages, tracking of single mRNAs can reveal the in vivo dynamics that occur in the native environment. Tracking single mRNA particles in the cytoplasm of COS cells revealed that the movement of a reporter mRNA in the cytoplasm could be diffusive, static, corralled, and directed, with diffusive motion dominating (Fusco et al., 2003). The authors of this study were also able to show for the first time the movement of mRNA along cytoskeletal fibers. Interestingly, the addition of the b-actin 30 UTR to the construct, which contains a localization sequence necessary for the localization of b-actin mRNA, increased in the relative amount of directed movements and their average length. In a related study, single molecule tracking allowed the measurement of the diffusion coefficient of b-actin mRNA in different regions of the COS cells. b-actin mRNA was found to diffuse freely in the leading edge of the cell, however, in the perinuclear region, mRNA diffusion was restricted. Disruption of the actin cytoskeleton delocalized mRNA

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and increased the diffusion coefficient of mRNA in the perinuclear region, indicating that cytoskeletal barriers may play a role in the localization of b-actin mRNA (Yamagishi et al., 2009). In an additional study where SPT was critical to probing a mechanism of mRNA localization, Bertrand et al. (1998) employed single mRNA tracking to address the question of how ASH1 mRNA travels to the bud tip in yeast. It was known that SHE1/MYO4, a type V myosin, as well as an intact actin cytoskeleton were necessary for ASH1 mRNA localization, however, it was not clear whether ASH1 mRNA was actively transported to the bud tip or if myosin was transporting another protein necessary for ASH1 mRNA anchoring at the bud tip. Real-time imaging and particle tracking indicated that ASH1 was transported from mother to daughter yeast cell with a velocity consistent with motor-based transport and that mRNA particles colocalized with myosin. Single mRNA tracking in the nucleus was used to address the controversial question of how mRNA travels in the nucleus, revealing movements indicative of corralled diffusion (Shav-Tal et al., 2004). In this study, it was shown that mRNAs are not actively transported in the nucleus but passively diffuse. Zimyanin et al. (2008) also used live cell visualization and tracking of mRNA to address a controversy in the field of oskar mRNA localization in Drosophila oocytes. Prior to their study, it had been known that kinesin was necessary for posterior oskar mRNA localization, so seemingly oskar mRNA localization depended on kinesin-based transport; however, paradoxically, the microtubule network in the Drosophila oocyte lacks uniform polarity. Other theories postulated that cytoplasmic flow or exclusion from specific regions are responsible for oskar mRNA localization, with kinesin playing an indirect role. By direct observation of the mRNA, the authors showed that the mRNA moves along microtubules in many directions with a 14% bias toward the posterior region. Over time, this is sufficient to localize the mRNA to the correct region in the appropriate time frame. An interesting cellular model for active transport of mRNA is the study of mRNA localization in neuronal processes, as diffusion alone is insufficient to transport mRNA into long dendritic processes, thus, active transport is a necessity for mRNA to reach the distal regions of neurons. Live imaging of calcium/calmodulin kinase II alpha reporter mRNA revealed a kinesin and microtubule-dependent oscillatory movement of the mRNA in the dendrites. Following stimulation, there is an increase of mRNA movement in the anterograde direction, bringing mRNA granules into dendrites and increasing the probability of arriving at activated synapses (Rook et al., 2000). These representative examples emphasize the significant discoveries in the field of mRNA trafficking where live mRNA imaging and tracking played a pivotal role in understanding the mechanisms of mRNA localization.


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3. Labeling mRNA in Living Cells 3.1. Selection of probes for SPT A wide variety of probes have been used in SPT, including gold particles, quantum dots, small organic dyes, and fluorescent proteins. Colloidal gold particles of 20–40 nm in diameter have been used with bright field microscopy (De Brabander et al., 1985) or differential interference contrast (DIC) microscopy (Sheetz et al., 1989). A small number of ligands or Fab fragments of the antibody IgG for target molecules are conjugated to the gold particles. Labeling by gold is advantageous for longer duration of tracking because there is no photobleaching and little saturation. Also, it allows the manipulation of single particles by using an optical trap (Edidin et al., 1991; Kusumi et al., 1998). However, gold probes have artifacts such as nonspecific charge interactions and crosslinking (Kusumi et al., 2005) and have not been yet applied successfully to mRNA labeling in living cells. Fluorescent probes are more amenable to specific labeling. Simultaneous tracking of different species is readily achieved by multicolor imaging with diverse fluorescent tags. When using fluorescent probes, photostability and brightness are the primary figures of merit for SPT. Quantum dots have been widely used for SPT since they are 10- to 100-times brighter and 100to 1000-times more photostable than organic dyes (Smith et al., 2008). Another advantage of semiconductor nanocrystals is that the emission wavelength can be tuned by the size; larger quantum dots emit redder fluorescence. However, quantum dots exhibit intermittent emission, or ‘‘blinking’’ (Nirmal et al., 1996), which can complicate the analysis of SPT data. Using quantum dots, Ishihama and Funatsu observed the movement of single mRNAs for over 60 s with a time resolution of 30 ms (Ishihama and Funatsu, 2009). Organic dyes and fluorescent proteins have been predominantly used for labeling mRNAs (for reviews, see Querido and Chartrand, 2008; Rodriguez et al., 2007; Tyagi, 2009). To image total mRNA in live cells, nonspecific nucleic acid stains such as SYTO 14 can be used (Knowles et al., 1996). Visualization of specific mRNA has been typically achieved through the microinjection of fluorescently labeled RNAs (Ainger et al., 1993; Shan et al., 2003; for a review of fluorescent RNA cytochemistry, see Pederson, 2001). An alternate technique that allows the labeling of endogenous mRNA is a variation of FISH performed on live cells. Santangelo et al. (2009) describe a technique where the membranes of live cells are reversibly permeabilized with the Streptolysin O, which delivers fluorescently labeled oligonucleotides into cells. Finally, molecular beacons have also been used to visualize endogenous mRNAs in live cells (Bratu et al., 2003), where delivery also typically involves microinjection.

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3.2. The MS2-GFP system To label native mRNA with GFP in living cells, the MS2-labeling technique has been devised (Bertrand et al., 1998). High autofluorescence in the cytoplasm can significantly confound tracking single molecules in a live cell. In order to enhance the signal-to-background ratio, the system expresses mRNAs that contain multiple MS2 stem loops, to each of which a dimer of fluorescent protein-fused MS2 coat proteins (FP-MCP) specifically binds. We have empirically determined that 24 copies of the MS2 binding sites (MBS) binding up to 48 FP-MCPs are sufficient to visualize single mRNA molecules (Fusco et al., 2003; Shav-Tal et al., 2004). Plasmids containing multiple MBS cassettes and FP-MCP are available upon request at http:// singerlab.aecom.yu.edu/requests/. The benefit of using genetically encoded fluorescent proteins to label mRNAs is that the mRNA is transcribed and labeled in the nucleus, which should ensure proper binding of mRNA binding proteins, necessary for proper export, transport, and translation (Farina and Singer, 2002). Additionally, the MS2 system involves minimal perturbation to the cellular structure as opposed to other methods of delivery of exogenous mRNA such as microinjection of fluorescently labeled mRNAs or delivery through the perturbation of the plasma membrane. Many previous chapters have addressed the methodology using the MS2 system to fluorescently label mRNAs (Chao et al., 2008a; Grunwald et al., 2008b). This chapter will focus on technical considerations as opposed to specific instructions. An MS2-GFP labeling system should be designed properly with several considerations. It is important that the MS2-GFP construct includes appropriate untranslated regions (UTR), which play an essential role in the mRNA localization by regulating the mRNA’s interaction with the cytoskeleton or RNA binding proteins. Moreover, the MS2 repeats must be inserted in a carefully selected location. It is highly recommended to verify proper trafficking of mRNA using FISH in order to avoid potential problems. Other unknown elements not included in the reporter construct may be important for correct localization. Or the MS2 repeats may interfere with trafficking or induce nonsense-mediated degradation of the mRNA. Secondly, appropriate levels of expression are crucial. If both the reporter mRNA and the FP-MCP are overly expressed, they may form fluorescent aggregates in the cytoplasm of the cell. Overexpression of mRNA may also lead to abnormal localization, because RNA-binding proteins and transport machinery may exist in limiting amounts. Therefore, it is most desirable that the reporter constructs are expressed under their own promoters. Retrovirus or lentivirus infection is widely used for creating stably expressing cells. Because each cell will only contain a few copies of the transgene, this method not only eliminates the concern of overexpression but also reduces the cell-to-cell variations in expression.


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When performing live cell imaging using the MS2 system, multiple controls are essential to perform to verify the correct trafficking of the mRNA. MS2-tagged mRNAs should be visualized in combination with FISH to measure the relative abundance of labeled mRNAs, as in Fusco et al. (2003). Furthermore, FISH should be performed on cells that express the stem-loop-tagged mRNA in the absence and presence of the FP-MCP to ensure proper targeting of the mRNA with the stem loops and while bound to multiple fluorescent proteins. An additional necessary control is to express the FP-MCP in cells that do not contain the stemloop-tagged mRNA for the purpose of verifying that the expression of the coat protein does not lead to artifactual aggregation of fluorescent protein in the cells. In our laboratory, a transgenic mouse line with 24 MS2 repeats inserted into the 30 UTR of the b-actin gene has been created recently (manuscript in preparation). This system will allow the visualization and tracking of endogenous b-actin mRNA in various cell types, and moreover in vivo, which has not been achieved before. An orthogonal system for RNA labeling has also been developed using PP7 bacteriophage coat protein (Chao et al., 2008b), which will enable the tracking of multiple mRNA species.

3.3. Minimizing photobleaching and phototoxicity Ultimately, long time-lapse imaging experiments are limited by photobleaching and phototoxicity. The average number of photons emitted by a dye molecule before photobleaching is approximately 10,000–100,000. Photobleaching occurs by several complex mechanisms and strongly depends on the environmental conditions such as solvent polarity and temperature (Eggeling et al., 2005). The most notable mechanism for photobleaching is photooxidation. Fluorophores in triplet excited state react with ground-state triplet oxygen and generate singlet oxygen (1O2). The highly reactive singlet oxygen causes both photobleaching and phototoxicity. Several reagents such as ascorbic acid and enzymatic deoxygenation systems have been used to reduce the detrimental effects. However, the removal of oxygen can enhance or reduce the photobleaching effect depending on the experimental condition. This is because photooxidation processes cause both the ground-state recovery of the dyes and the formation of irreversible photoproducts. Therefore, the concentration of oxygen scavengers needs to be optimized for sufficiently long tracking experiments. Addition of triplet quenchers such as Trolox (a water-soluble analog of vitamin E) and mercaptoethylamine can also improve the photostability (Rasnik et al., 2006; Widengren et al., 2007).

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4. Imaging mRNA Movements 4.1. Experimental considerations In order to track single mRNA movement in real time, it is important to achieve high sensitivity for single molecule detection and fast image acquisition. In fluorescence microscopy, photobleaching phenomena inherently limit the number of photons available from the probe. Therefore, one needs to find a good balance in the image-acquisition protocol. First, the camera exposure time needs to be optimized to detect single molecules in motion. The precision to locate the center of a particle is proportional to the total number of collected photons (Bobroff, 1986). Once the imaging system is optimized for the highest signal-to-noise ratio, the exposure time needs to be long enough to locate particles with a desirable precision. On the other hand, the camera exposure has to be short enough to capture an image of a highly mobile object. If the particle travels a significant distance during the exposure time, it will show up as a streak or a blurred object, which impairs the detection of the object. Secondly, a high frame rate is desired to follow the trajectory of a diffusing particle. In order to identify the same particle in two successive image frames, it is ideal to meet the Nyquist criterion in temporal sampling, that is, the displacement during the time interval should be less than half the spatial resolution. The previously measured diffusion coefficients of messenger ribonucleoprotein particles (mRNPs) in living cells are 0.1–0.8 m2/s (Fusco et al., 2003; Shav-Tal et al., 2004), thus, the sampling time interval needs to be 5–40 ms. This requirement can be relaxed when the particle density in the image is sufficiently low. If the average distance between particles is much larger than the average particle displacement between frames, two successive images of an object can be linked to each other unambiguously. However, with increasing particle density, it becomes more difficult to solve the motion correspondence problem. Lastly, a sufficient tracking range is crucial to identify the type of motion. The total number of frames in the image sequence determines the statistical accuracy of the analysis (Qian et al., 1991; Saxton, 1997). Monte Carlo simulations can be performed without limitation on the tracking period to quantitatively estimate the deviations from Brownian motion. For instance, Saxton examined the statistical variation of the diffusion coefficient D by simulations (Saxton, 1997). In addition, longer observation enables the detection of motion-type transitions. Since it is difficult to meet all of these requirements with a limited number of photons, one needs to find a good compromise between the high acquisition rate and the total duration of the experiment.


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4.2. Instrumentation SPT may be performed in various forms of light microscopy, including widefield, confocal, and total internal reflection microscopy (TIRFM). A standard wide-field epi-illumination microscope has been successfully used to visualize single mRNA molecules labeled by the MS2 system. The microscope system should be optimized to observe single molecule dynamics in living cells. For a sensitive detection of weak fluorescence, the photon collection efficiency needs to be maximized while the background noise is minimized. Microscope objectives with higher NA are desirable to obtain a higher photon collection efficiency and tighter point-spread function. Large magnification may be beneficial to minimize the pixelation noise, as long as the particle under study does not travel beyond the field of view. When using multiple fluorophores with different emission colors, chromatic aberration must be appropriately corrected by using achromat or apochromat objectives. For colocalization of single molecules labeled with different fluorophores, multichannel image registration is also necessary (Churchman and Spudich, 2007). The most common light source for wide-field microscopy is either a mercury or xenon arc lamp. If the power of the lamp at the excitation wavelength is not sufficient to detect single molecules, a laser light source can be employed. Laser illumination provides not only higher power but also narrower excitation bandwidth in the subnanometer range, which reduces the excitation background (Grunwald et al., 2008b). Since the viability of the cell also needs to be ensured, the illumination power must be balanced to protect the specimen against photodamage and photobleaching. For single-molecule detection, there are many different types of cameras and spot detectors. The most commonly used detector for SPT is the electron-multiplying charge-coupled device (EMCCD). The electronmultiplying shift register increases the gain while keeping the noise level low. In order to achieve shot noise-limited detection, it is desirable to obtain maximum quantum efficiency and minimum camera noise. For higher quantum efficiency, back-illuminated type CCD chips are preferable. The dark noise of the CCD is due to the thermal fluctuation in the amount of charge in total darkness and can be reduced by cooling the chip down to 80 C. The readout noise increases approximately with the square root of the readout speed (Rasnik et al., 2007). Therefore, there is a tradeoff between the acquisition rate and the noise level. A frame-transfer feature alleviates this constraint and is highly desirable for sufficiently frequent acquisition. Finally, cells must be kept in physiological conditions to ensure that the dynamics observed is an appropriate representation of the behavior in vivo. For mammalian cells, the temperature should be maintained at 37 C.

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There are several commercial systems to keep the sample warm during imaging sessions. A simple economical method is to use heating elements for the specimen and the objective lens. However, there can be a thermal drift due to the cycles of heating and cooling. A more reliable method is to build an incubator around the microscope body. A custom-designed incubator that can enclose the majority part of the microscope can keep the system at a stable temperature and prevent thermal drift. Also, incubators are desirable to control the CO2 level and humidity for extended periods of time.

4.3. 3D tracking SPT has been mainly employed in two-dimensional systems such as cell surface or immobilized cytoskeletons in vitro. It is highly desirable to extend the technology into three-dimensional imaging since most biological processes occur within the 3D space of the cell. Kao and Verkman (1994) introduced a weak cylindrical lens in the detection optics of an epifluorescence microscope, which caused astigmatism in a particle image. Images of fluorescent beads are circular in the focus but become ellipsoidal when out of the focus. The major axis of the ellipsoid is rotated by 90 above and below the focus. They retrieved the x, y, and z positions by analyzing the shape, orientation, and position of the particle’s image. Simple defocusing methods have also been used for 3D tracking. Speidel et al. (2003) calibrated the radii of the ring patterns in the defocused image of a particle as a function of the axial position of the object. They found a linear dependence of the ring radii on the z-offset within an axial range of 3 mm. Toprak et al. (2007) employed a similar method but with simultaneous imaging of the focused and defocused planes, and improved the localization accuracy in 3D. 3D tracking is also demonstrated using a two-photon microscope by tracing the laser beam in four circular orbits surrounding the object (Levi et al., 2005). The position of the particle is calculated on the fly, and those coordinates are used to set the next scanning position.

5. Analyzing mRNA Motions A number of ideas and techniques for tracking objects in a sequence of images can be found in the context of fluid mechanics, computer vision, and radar surveillance. In cell biological applications, two types of tracking algorithms have typically been used. The first category detects the changes in particle positions by crosscorrelating consecutive frames. The second category generally consists of two steps: find the center of each particle in time-lapse images, and connect the positions to reconstruct the trajectory. Cheezum et al. (2001) compared the tracking algorithms quantitatively by

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simulations. They concluded that the crosscorrelation method performs better for particles larger than the wavelength. Conversely, for particles that are smaller than the emission wavelength, it is more accurate and precise to perform particle detection followed by trajectory linking. Since the size of the mRNPs is smaller than the visible light wavelength, we will consider the second category of the tracking method here.

5.1. Localization algorithms In light microscopy, an object that is smaller than the dimension of wavelength appears as a diffraction-limited spot. Because of the limited resolution, the details of the object cannot be discerned. However, the center of the object can be determined with a much better precision when a sufficient number of photons are collected from the particle. There are two major categories of algorithms to identify the location of single particles: searching for the intensity-weighted center of mass (centroid) or fitting image intensities by point-spread function. In a centroid method, the image is filtered to remove high-frequency noise, a binary mask is applied to exclude the background below threshold intensity, and the weighted center of mass of contiguous pixels is calculated (Ghosh and Webb, 1994). Gelles et al. (1988) demonstrated a localization precision of 1–2 nm by usingDIC images of plastic beads. They crosscorrelated the sequence of images with a kernel segment of a single bead image and computed the centroid of each particle. The centroid method is computationally efficient and valid for asymmetric particles. However, the precision and accuracy of the particle position found by centroid methods are highly dependent on the background threshold level (Cheezum et al., 2001). Alternatively, the fluorescent intensity distribution of a single particle can be fit with a 2D Gaussian function. It provides a higher localization precision and an accurate measure of the intensity (Anderson et al., 1992). Cheezum et al. (2001) compared the efficacy of the centroid and Gaussian fitting routines and concluded that a direct Gaussian fit to the intensity profile is superior in terms of both accuracy and precision. Thompson et al. (2002) derived an approximate equation for the localization precision: hðDxÞ2 i ¼

s2 þ a2 =12 8ps4 b2 þ 2 2 aN N

ð18:1Þ

where s is the standard deviation of the point-spread function, a is the pixel size, b is the background noise, and N is the photon number. In the shot noise limit (the first term in Eq. (18.1)), the localization error is inversely

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proportional to the square root of the number of photons. When the background noise dominates (the second term in Eq. (18.1)), the uncertainty scales as the inverse of the number of photons. They also introduced a simplified fitting algorithm called ‘‘Gaussian mask,’’ which is equivalent to a nonlinear least-squares fit to a Gaussian distribution ignoring the shot noise. In this method, the centroid is calculated in convolution with a Gaussian distribution around the candidate position, and iterated until the centroid position converges. When the number of photons originating from the molecule of interest is small, the Gaussian mask algorithm can be more robust than the full least-squares fit.

5.2. Tracking algorithms After the particles are located in a sequence of frames, the next step is to link a position in each frame with a corresponding position in the next frame. In general, the particles are not distinguishable from one another. With increasing particle density, it becomes more difficult to determine the next position of a given particle. Therefore, an important parameter to gauge the difficulty of particle tracking is the spacing-displacement ratio, which is the average distance between particles divided by the average particle displacement between two successive frames (Malik et al., 1993). If the spacing-displacement ratio is much larger than one, tracking can be reliably done by simple nearest-neighbor approaches (Anderson et al., 1992; Ghosh and Webb, 1994). However, it becomes more difficult to connect the trajectories as the spacing-displacement ratio becomes smaller. Because there are many possible pairs of particles between two images, it is necessary to find the most probable set of connection. Various algorithms have been developed to seek a unique solution to the motion correspondence problem, and they can be divided into two broad categories: deterministic and statistical methods (Yilmaz et al., 2006). Deterministic methods are also called combinatorial optimization techniques. They define a cost function of associating each spot in the previous frame to a single spot in the next frame. By minimizing the cost function, an optimal assignment can be obtained. For example, Crocker and Grier (1996) described a simple cost function to track noninteracting Brownian particles. If we consider an ensemble of indistinguishable noninteracting M particles, most probable set of linkages between two frames is obtained P the ! ! 2 when M ð j¼1 r j ði þ 1Þ r j ðiÞÞ is minimized. If the particles can be distinguished by additional information such as size, color, and intensity, these data can be treated as another dimension of the particles in the cost function. The algorithm is available at http://www.physics.emory.edu/ weeks/idl.


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If the scope of the tracking is extended to more than two image frames, it becomes a multidimensional optimal assignment problem (Sbalzarini and Koumoutsakos, 2005; for the associated ImageJ plugin, see http://www. mosaic.ethz.ch/Downloads/ParticleTracker). Most multiframe tracking algorithms are based on heuristic assumptions such as smoothness of the particle trajectories motion (Sage et al., 2005; for the associated ImageJ plugin, see http://bigwww.epfl.ch/sage/soft/spottracker/; Vallotton et al., 2003). By tracking objects across multiple frames, the history of the particle movement is considered. Therefore, these methods can resolve problems arising from crossing trajectories, temporary occlusion, blinking, and detection failure. However, multiframe tracking is computationally expensive and becomes difficult to solve as the frame number increases. Therefore, greedy search techniques and heuristic approaches are used to obtain approximate solutions (reviewed in Ja¨hne et al., 2007; Yilmaz et al., 2006). Statistical data association methods take the uncertainty of the position measurements into account and assign a probability density function for a particle state. The probability distribution propagates over time and is updated by the measurements in each frame. The simplest statistical tracking method is the Kalman filter. In a Kalman filter, the initial particle state and noise have a Gaussian distribution. The next position of a particle is predicted by a linear model of motion, and the actual observation in the predicted search region is used to adjust the particle state. Kalman filtering can also be extended to multiple frame processing. The multiple hypotheses tracking (MHT) algorithm defers the correspondence decision until several frames are examined (Reid, 1979). Probabilities for multiple hypotheses are calculated, and the most likely set of track is chosen. The MHT algorithm seeks the globally optimal solution by considering all particle positions at all time frames. However, it is computationally intense both in time and memory. Thus, various approximate solutions to MHT were developed and applied to SPT in living cells ( Jaqaman et al., 2008; Serge et al., 2008).

5.3. Categories of single particle motion It is not known whether molecular motion in biology is finite, but the effort to categorize it is well worthwhile for SPT. Random walk is one of a few simple and universal models in physics, which analytically describes unobstructed, or ‘‘normal,’’ diffusion. Therefore, it is natural in SPT that normal diffusion serves as a reference while complicated motions are treated as deviations from this null model. A molecule may exhibit one of the five modes of motion, depending on the nature of interactions; stationary, normal diffusion, anomalous subdiffusion, corralled diffusion, and directional movement by active transport. Moreover, it is also possible that an

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mRNA molecule makes transitions between the modes (Fusco et al., 2003). It was only after SPT was applied that researchers began to recognize the significance of nonBrownian microscopic motions in biology (Feder et al., 1996; Kusumi et al., 1993). A measurable parameter most commonly employed in SPT analysis is the mean-squared displacement (MSD) as a function of time. If we consider a trajectory ! r ðtÞ recorded every dt for N time steps, the MSD for a given time lag ndt is calculated by: hr 2 ðnÞi ¼

n X 1 N ! 2 ½! r ði þ nÞ r ðiÞ N n i¼1

The MSD curves for the different types of motion are shown in Fig. 18.1 and the analytical forms can be expressed as follows: hr 2 i < ðDxÞ2 hr 2 i ¼ 2dDt hr 2 i ¼ Gt a hr 2 i ¼ R2 1 A1 exp AR22t hr 2 i ¼ 2dDt þ v2 t2

stationary (Dx: localization precision) normal diffusion (d: spatial dimension) anomalous subdiffusion (a < 1) corralled diffusion (R: radius of the corral) directed motion with diffusion (v: speed)

Mean-squared displacement

Normal diffusion Directed motion Anomalous subdiffusion Corralled diffusion

Time

Figure 18.1 Mean-squared displacement as a function of time for various modes of motion.

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When fitting experimental MSD data with these analytical functions, one needs to add a constant to the fit-function because the localization precision Dx leads to an offset in the MSD plot (Wieser and Schutz, 2008). Another approach to analyze SPT trajectories is obtained by looking at the statistics of displacements, rather than the average. The probability distribution (Anderson et al., 1992), or equivalently, the jump-distance distribution (Grunwald et al., 2008a; Siebrasse et al., 2008), permits different perspectives from MSD. While ensemble MSD analysis measures an average of a population, jump-distance histogram detects different mobility populations. Jump distance analysis measures the probability P to find a particle ! recorded within a distance of ! r ði þ 1Þ from the initial position r ðtÞ after time t according to the following equation: ! ! 2 1 ð! r ði þ 1Þ r ðiÞÞ ! ! Pð r ði þ 1Þj r ðiÞ; tÞdV ¼ dV ; exp 4Dt ð4pDtÞd=2 normal diffusion The probability distribution is suited to distinguish subpopulations with multiple diffusion coefficients, which can be nontrivial to identify in MSD plots.

5.4. Interpretation of mRNA tracking data Upon successful labeling, imaging, and tracking of mRNAs, SPT data provide a rich source of information. Linking the quantitative analysis of mRNA movement to a biological process or function is another big challenge. SPT often yields observational information about the nature of mRNA movement. Observational reports about the travels of mRNA in the nucleus have utilized mean-squared displacement (Politz et al., 2006; Shav-Tal et al., 2004) as well as jump-distance histograms (Grunwald et al., 2008a; Siebrasse et al., 2008) to describe the nuclear environment that the mRNA encounters. In these reports, MSD measurements yielded an average diffusion coefficient, while mean jump distance was used to calculate the mean diffusion coefficient of discernable populations in unique compartments. While nuclear SPT of mRNA usually yields diffusion coefficients of mRNA in the various nuclear compartments or the entire nucleus, utilization of SPT of mRNA in the cytoplasm needs to distinguish between diffusing mRNAs and ones that are transported along cytoskeletal elements. The use of MSD to analyze SPT data is capable of comparing the distribution of distinct motility populations of mRNA in the cytoplasm of cells. For example, MSD has been used to compare the relative population of

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diffusing mRNAs compared to transported or static mRNAs of reporter constructs with and without the b-actin 30 UTR (Fusco et al., 2003). Alternatively, a specific aspect of active transport may be measured, such as the average velocity, maximum velocity, or the average length of transport path. Rook et al. (2000) measured a variety of aspects of active transport of CamKII alpha mRNA in the neuronal dendrites pre- and post-potassium chloride (KCl) stimulation. They measured the percent motile mRNA granules, distance traveled, average rate, and the maximum rate of active transport. The comparison of the motility of mRNA prior and following a treatment or knockdown of RNA-binding proteins is a direct way to measure cellular elements responsible for mRNA localization or means in which mRNA localization can be induced. In this study, it was shown that following KCl stimulation, there was a shift of movement from oscillatory to anterograde. In a more recent study of CamKII mRNA in dendrites, MSD was used to compare the relative abundance of actively transported and nonmotile mRNAs in wild type and FMRP knockout neurons. SPT of mRNA also allowed the measurement of the maximal and mean granule velocity in both the anterograde and retrograde directions in dendrites (Dictenberg et al., 2008). The measurement of mRNA velocity along the cytoskeleton is an important stepping stone toward understanding more about the nature of active transport in different cell types and situations. Because cytoskeletal filaments are required for active transport, studying the contribution of cytoskeletal elements and molecular motors on mRNA localization is often accomplished by chemical disruption of the cytoskeleton or overexpression of the dominant negative motors (Mingle et al., 2005; Sundell and Singer, 1991; Zhang et al., 1999). Conversely, live measurements of mRNA being actively transported can provide an insight into how cells actively facilitate the localization of mRNA to discrete locations.

6. Conclusions SPT is a useful tool for monitoring the behavior of individual molecules in living cells, providing new information about dynamic heterogeneity. Current technological advances in SPT used in conjunction with the MS2-labeling system have allowed more accurate and extended tracking of mRNAs in cells. Single mRNA tracking studies are now elucidating the mechanisms of mRNA transport and localization in various cell types. Despite the remarkable recent progress, many important questions remain to be answered. A clear picture of the cause-and-effect relationship between mRNA localization and cell physiology will likely emerge as the in vivo dynamics of mRNA is revealed. Furthermore, multicolor imaging of single


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mRNAs interacting with their diverse binding partners will provide a more comprehensive picture of the molecular pathways in live cells.

ACKNOWLEDGMENTS This work was supported by National Institutes of Health grant EB2060. H. Y. P. was also supported by National Research Service Awards 5T32 HL007675 and 1F32 GM087122.

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Single-Molecule Sequencing: Sequence Methods to Enable Accurate Quantitation Christopher Hart, Doron Lipson, Fatih Ozsolak, Tal Raz, Kathleen Steinmann, John Thompson, and Patrice M. Milos Contents 1. Introduction 2. Basic Principles of Single-Molecule Sequencing 3. Preparation of Genomic DNA for Single-Molecule Sequencing 3.1. DNA fragmentation and quantitation 3.2. Poly-A tailing 3.3. 30 end blocking 4. Bacterial Genome Sequencing 4.1. Preparation and sequencing of bacterial DNA 4.2. Assessment of coverage and lack of bias 5. Human Genome Sequencing and Quantitation 5.1. Copy number variation 6. Chromatin Immunoprecipitation Studies 6.1. Preparation of ChIP DNA 6.2. ChIP DNA poly-A tailing 6.3. ChIP DNA 30 blocking 7. Digital Gene Expression for Transcriptome Quantitation 7.1. Methodology for single-molecule sequencing digital gene expression 7.2. Demonstration of DGE counting reproducibility 8. Summary Acknowledgments References

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Abstract HelicosÒ Single-Molecule Sequencing provides a unique view of genome biology through direct sequencing of cellular and extracellular nucleic acids in an unbiased manner, providing both quantitation and sequence information. Using Helicos BioSciences Corporation, One Kendall Square, Cambridge, Massachusetts, USA Methods in Enzymology, Volume 472 ISSN 0076-6879, DOI: 10.1016/S0076-6879(10)72002-4

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a simple sample preparation, involving no ligation or amplification, genomic DNA is sheared, tailed with poly-A and hybridized to the flow-cell surface containing oligo-dT for initiating sequencing-by-synthesis. RNA measurements involving direct RNA hybridization to the flow cell allows for the direct sequencing and quantitation of RNA molecules. From these methods, a diverse array of applications has now been successfully demonstrated with the HelicosÒ Genetic Analysis System, including human genome sequencing for accurate variant detection, ChIP Seq studies involving picogram quantities of DNA obtained from small cell numbers, copy number variation studies from both fresh tumor tissue and formalin-fixed paraffin-embedded tissue and archival tissue samples, small RNA studies leading to the identification of new classes of RNAs, and the direct capture and sequencing of nucleic acids from cell quantities as few as 400 cells with our end goal of single cell measurements. Helicos methods provide an important opportunity to researchers, including genomic scientists, translational researchers, and diagnostic experts, to benefit from biological measurements at the single-molecule level. This chapter will describe the various methods available to researchers.

1. Introduction The revolution in genomic sequencing that is currently occurring in the scientific community is heralding an exciting era of biology where experiments can be performed at a scale that fully elucidates the genome, its corresponding architecture, and the resulting transcriptome (all RNA molecules transcribed from the genome), revealing amazing new findings (Kahvejian et al., 2008). This revolution is continuing as we move into the era of single-molecule sequencing where, for the first time, we are sequencing and measuring the actual molecules present in cells and tissues. This new era offers the promise of a better understanding of the fundamental basis of health and disease. Helicos single-molecule sequencing offers the opportunity to examine billions of DNA or RNA molecules in a highly parallel fashion, scalable to sequencing of an entire human genome (Harris et al., 2008; Ozsolak et al., 2009; Pushkarev et al., 2009). While other technologies may offer similar approaches, the simplicity and the scalability of single-molecule sequencing sets it distinctly apart from next-generation sequencing technologies. Further, these same principles contribute directly to the absolute quantitative nature of the technology. By eliminating cumbersome sample preparation steps, including complex ligations and polymerase chain reactions for amplification, single-molecule sequencing offers both sequence information and reliable quantitation for many different applications. Often referred to as ‘‘third-generation’’ sequencing (Hayden, 2009), the methods involved in single-molecule sequencing demonstrate these unique principles.

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This chapter describes the methodological details for a variety of genomic applications used by the research and translational biology communities, including preparation of genomic DNA for complete genomic sequencing, copy number variation detection and chromatin immunoprecipitation (ChIP) studies. Quantitative aspects of single-molecule measurements for RNA are also described for methods associated with digital gene expression.

2. Basic Principles of Single-Molecule Sequencing Helicos single-molecule sequencing utilizes sequencing-by-synthesis methodology, involving individual nucleic acid molecules that are initially fragmented in the case of genomic DNA, melted into single strands of DNA, and poly-A tailed. These DNA molecules are then captured as individual strands of DNA through deposition onto a glass HelicosÒ Flow Cell (Fig. 19.1B) surface coated with oligo-dT-50 oligonucleotides, which are then filled with dTTP and polymerase for the purpose of filling in any remaining nucleotides complementary to the poly-A tail. Following the fill, nucleic acid templates are locked in place by the addition of fluorescently labeled dCTP, dGTP, and dATP Virtual TerminatorTM nucleotides, which incorporate as a single complementary nucleotide and prohibit subsequent extension prior to terminator cleavage. This ‘‘fill and lock’’ step ensures that each template become available for the sequencing-by-synthesis reaction (Bowers et al., 2009; Harris et al., 2008). Following the fill and lock step, sequencing-by-synthesis is initiated through the addition of fluorescently labeled Virtual TerminatorTM nucleotides added one at a time. Nucleotide incorporation occurs at the complementary position in the individual growing strands of DNA, using a DNA polymerase. After incorporation, unincorporated nucleotides are rinsed through the flow cell. The flow-cell surface is then illuminated with a laser and incorporation is detected by the fluorescent emission of light. The HeliScope Sequencer captures the images via a CCD camera and records which strands have incorporated a nucleotide and records positional information as well as cycle information to ensure conversion of the image to the individual DNA molecules as well as the A, C, G, or T nucleotide sequence information. After the images are captured, the terminator moiety is cleaved from the incorporated nucleotide, allowing subsequent addition of the next complementary nucleotide. Once the thousands of images, which correspond to all the channels of the flow cell, have been recorded, the fluorescent label is cleaved from the nucleotide, allowing the instrument to continue incorporation of the next nucleotide in the addition cycle. In a standard run, the HeliScope Sequencer

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A

B

25 channels - 2 flow cells per run

Figure 19.1 (A) The HeliScopeÒ Single-Molecule Sequencer. A powerful genetic analyzer that performs single-molecule sequencing chemistry and captures images of single-molecule incorporation of fluorescently labeled nucleotides, producing accurate sequences of billions of templates at a time. (B) The HelicosÒ Flow Cell. Specifically designed for sequencing chemistry used with the Sequencer, two flow cells – each with 25 channels enable a multitude of applications all benefiting from Helicos proprietary chemistry.

completes 120 cycles of individual nucleotide additions. A representative visual image taken from the HeliScope Sequencer is shown in Fig. 19.2. At the end of the run, real-time image processing has converted all the images into a complete sequence file, recording both the DNA strand position and nucleotide string addition; scientists are then able to download the sequence file and begin the alignment to appropriate reference genomic or transcriptomic sequences. To date, numerous genomes have been sequenced using the HeliScope Sequencer, including genomes from M13 virus (Harris et al., 2008), bacterial species, yeast, and Caenorhabditis elegans (Bowers et al., 2009), culminating in the world’s first sequencing of a human genome using single-molecule sequencing (Pushkarev et al., 2009). The following will describe the basic methodologies one requires in order to prepare genomic templates for single-molecule DNA and cDNA sequencing.

3. Preparation of Genomic DNA for SingleMolecule Sequencing The basic principles involved in the preparation of genomic DNA for subsequent sequencing-by-synthesis involve DNA fragmentation and quantitation, poly-A tailing, and 30 end blocking to ensure that sequence obtained

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3 2 1

Position Cycle Cycle Cycle Cycle Cycle Cycle

1 2 3 4 5

1 C A C

2 C A -

3 G A T -

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Figure 19.2 Helicos Flow Cell Image and Virtual TerminatorÒ Nucleotide Incorporation. A true image derived from a section of the sequencing flow cell showing a closeup image of single molecules of DNA which have incorporated fluorescent Virtual TerminatorÒ nucleotides. The right insert shows a close-up view of the single molecules and the definition of the nucleotide incorporated at the positions 1, 2, or 3 during the cyclic addition of nucleotides.

from the 30 end of surface-bound oligoT is not contaminated with sequence from the 30 end of the hybridized DNA strands. Figure 19.3 outlines the process described in detail below.

3.1. DNA fragmentation and quantitation When quantities are not limiting, 1–3 mg of genomic DNA is typically used for single-molecule DNA sequencing of whole genomes, although much smaller quantities are also possible (see subsequent ChIP DNA Sequencing section). When the amount of DNA is low, care should be taken to use low-loss tubes and pipette tips. Addition of any type of carrier nucleic acid should be done cautiously as it could become a significant contaminant in sequencing. 3.1.1. DNA shearing 1. Prepare 1–3 mg of genomic DNA in a final volume of 120 ml 10 mM Tris 1 mM EDTA (1 TE). 2. Any method of DNA shearing can be used; however, if complete coverage is desired, the method chosen should cleave the DNA randomly and provide a 30 hydroxyl end for subsequent tailing. In the current protocol, ultrasonic shearing of the DNA is achieved using the Covaris

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Denature, terminal transferase + dATP AAAAAAAAAA3⬘

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True single molecule sequencing (tSMS)TM analysis

Figure 19.3 Depiction of DNA sequencing methodology. Illustration of the basic sample preparation steps of genomic DNA for single-molecule sequencing.

S2 instrument, resulting in fragmentation suitable for sequencing of the entire genomic sample. Conditions have been optimized by Covaris to allow for the use of genomic DNA ranging in length, at present, from 100 to 3000 base pairs (bp) so that the researcher can select the desired fragment size (Covaris, Woburn, MA; http://www.covarisinc.com). For typical genomic DNA sequencing using single reads, DNA is fragmented to an average size of 200–300 bp. For paired read sequencing in


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which two or more regions of the same DNA fragment are sequenced, fragmentation of 1500 bp is optimal to provide spacer gaps ranging from 100 to 700 nucleotides in length. 3. Conditions vary for the various fragmentation sizes: For example, to shear DNA to 200 bp, the DNA is sheared in Covaris microTubes using 3 cycles of 60 s, 10% duty cycle, intensity 5, and 200 cycles per burst. 4. Transfer the DNA to a clean 1.5-ml microtube. At this point, the DNA sample can be stored at 20 C. 3.1.2. DNA size selection The DNA sample is subsequently cleaned using Agencourt AMPureÒ beads to remove small nucleic acids, nucleotides, and salts that may be present in the sheared sample. 1. Adjust the DNA volume to 100 ml. 2. Warm AMPure Bead solution to room temperature (RT). Vortex to resuspend. 3. Transfer DNA sample to 1.5-ml tube and add water to bring each sample to 100 ml. Vortex the beads again and add 300 ml AMPure Bead slurry. 4. Incubate at RT for 30 min. Shake the tube every 10 min. 5. Briefly centrifuge at low speed, capture beads on DynalÒ magnetic stand for 5 min and carefully aspirate supernatant. 6. Wash beads twice with 700 ml freshly prepared 70% (v/v) ethanol. 7. Briefly centrifuge, place on magnet, remove ethanol, and dry pellet completely at RT for 5–7 min. Cracks will form when the pellet is dried sufficiently. 8. To elute the sheared DNA from the AMPure beads add 20 ml of water, pipette the beads and water up and down 20 times and place the tube back on the Dynal magnet. 9. Collect the 20 ml volume and transfer to a new 1.5-ml tube. 10. Repeat this process again to remove any remaining DNA on the AMPure beads. DNA will now be in the 40 ml volume. 3.1.3. Concentration estimation of 30 ends for subsequent poly-A tailing 1. In order to effectively tail the 30 ends of the genomic DNA, one must determine the approximate concentration of 30 ends, which requires a determination of the average fragment size of the sheared DNA obtained by running a 2-ml DNA aliquot on a 4–20% gradient Tris Borate EDTA (TBE) polyacrylamide gel. 2. DNA standards of 1000 and 25 bp ladders are included for size comparison.

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3. To estimate the size of the sheared product, compare the middle of the DNA smear to the size standards. An example gel is shown in Fig. 19.4. 4. Determine the double-stranded DNA concentration using a NanoDrop 1000 or 8000 spectrophotometer. Calculate the pmoles of the ends in the sample using the following formula. pmol 30 termini=ml ¼ XXng DNA=ml ð103 pg=ngÞ ðpmole=660 pgÞ ð1=average fragment size as determined from gelÞ 2ð30 termini=dsDNA moleculeÞ

1

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Figure 19.4 Example of gel sizing for sheared DNA. A 4–20% TBE gradient gel is used to assess the successful fragmentation of genomic DNA for subsequent poly-A tailing. Size standards of 1 kilobase ladder and 25 bp ladder are used to estimate average fragmentation length. Compare the average size in the middle of the sample smear to the size standards.


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3.2. Poly-A tailing The DNA fragments must be modified at their 30 ends with a poly-A tail to allow for efficient hybridization onto the oligonucleotide-coated Helicos Flow Cell. Conditions are optimized to allow the addition of 90–200 polyAs to the single-stranded DNA molecules. 1. Prepare a sample DNA Tailing Mix assuming a 3.0-pmole sample reaction. For one reaction—4 ml 10 Terminal Transferase buffer, 4 ml 2.5 mM CoCl2, 2 ml Terminal Transferase Enzyme (20 U/ml), 3.9 ml Helicos supplied Poly-A Tailing dATP and 1.1 ml deionized water (dH2O). Please note: For the Tailing Control Tube, adjust the Poly-A Tailing dATP to 1.3 ml and the dH2O to 3.7 ml. 2. Place the 3.0 pmole sheared DNA sample into a 200-ml PCR tube. 3. At the same time, prepare a separate 200-ml PCR tube with tailing control sample which consists of 0.8 pmoles of your DNA sample and 0.2 pmoles of tailing oligo control supplied by Helicos to monitor efficiency of tailing. 4. Denature the DNA by placing the sheared DNA and tailing oligo control tubes in a PCR Thermocycler, at 95 C for 5 min. Snap cool by placing tubes in an aluminum block prechilled on an ice slurry for 2 min to prevent reannealing of the denatured single-stranded DNA. 5. Add 15 ml of Sample Tailing Mix or Control Tailing Mix to each DNA tube. Mix by pipetting up and down 10 times. Collect liquid contents by centrifuging briefly. 6. Place the tubes in the thermocycler using the following conditions: 37 C for 60 min, 70 C for 10 min, maintain at 4 C until ready to proceed to next step. 7. Success of tailing is determined by monitoring the oligo control tailing. Twenty microliters of the oligo control is run on a 4–20% polyacrylamide gel in TBE alongside 100 and 25 bp ladders. An example of successfully sheared and tailed DNA is shown in Fig. 19.4. 8. Control-tailed oligos should migrate anywhere between 250 and 600 bp, indicating the sample is properly poly-A tailed with a desired tail length of between 90 and 200 dA.

3.3. 30 end blocking During flow-cell hybridization, the poly-A tail on the DNA sequencing templates may align imperfectly to the oligo-dT surface on the Helicos Flow Cell surface. This may result in the generation of a recessed 30 end that can serve as a substrate for the sequencing-by-synthesis reaction. To prevent the incorporation of fluorescent Virtual Terminator nucleotides at that end

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of the duplex, the 30 ends of sheared DNA molecules are modified with a dideoxy terminator, using the following protocol. 1. Following the poly-A tailing, heat denature the DNA at 95 C for 5 min in the thermocycler. Immediately remove and snap cool for a minimum of 2 min by placing in the ice-cooled aluminum block. 2. Add 0.3 ml of 500 mM Biotin ddATP to each tube. 3. Add 2 ml Terminal Transferase (20 U/ml) to each tube. Mix thoroughly by pipetting up and down 10 times. 4. Collect contents by brief centrifugation. 5. Return to the thermocycler and run the following conditions: 37 C for 60 min, 70 C for 10 min, maintain at 4 C until ready to proceed to next step. Samples are now ready for hybridization to the Helicos Flow Cell for subsequent sequencing-by-synthesis. DNA concentrations in the range of 150–300 pM are utilized for each Helicos Flow Cell Channel typically in a 20-ml loading volume.

4. Bacterial Genome Sequencing Helicos BioSciences has applied the above DNA sample preparation methodology to the sequencing of three bacterial genomes to demonstrate the principles of single-molecule sequencing—the simplicity of the sample preparation, the lack of amplification requirement, and the corresponding lack of G þ C biases (Dohm et al., 2008), as well as the evenness of coverage across a broad range of bacterial genomes, including Escherichia coli K12 MG1655, Staphylococcus aureus USA 3000, and Rhodobacter sphaeroides 2.4.1. The percentage of guanine and cytosine nucleotides (%GC) content of the genomes of these organisms represents the entire range of %GC content of kilobase-sized windows found in the human genome (Table 19.1). They have therefore been employed as reference genomes to test the ability of sequencing platforms to sequence the human genome. Achieving accurate and even coverage across these bacterial genomes demonstrates an absence of sequence content bias, which thus provides both sequence information as well as quantitative accuracy.

4.1. Preparation and sequencing of bacterial DNA 1. Shear and prepare 1 mg of bacterial DNA obtained from each species to 250–300 bp as described in Section 3. 2. Following sample preparation, load 150–300 pM of each bacterial DNA into individual flow-cell channels in a volume of 20 ml and

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Table 19.1 Reference bacterial genomes containing diverse genome sequence content

E. coli R. sphaeroides S. aureus

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Genomic size and G þ C content of bacterial genomes used for demonstration of high-throughput sequencing methodologies due to diverse genomic content.

sequence-by-synthesis for 120 nucleotide cycle additions via the HeliScope Sequencer in an 8-day run in which both flow cells are utilized. 3. Align the single-molecule sequence reads obtained at run completion to the corresponding bacterial reference genomes using the Helicos IndexDP Genomic aligner (available at Helicos HeliSphere Technology Center http://open.helicosbio.com/mwiki/index.php/Main_Page). 4. The resulting throughput yields 12–20 million aligned reads per flowcell channel or, given the two flow cells totaling 50 channels per run, 0.6–1 billion alignable reads per run. 5. A single channel provides upward of 80–120 coverage for these bacterial genomes, depending on the genome size, and represents some 3–4 more coverage than is required for accurate consensus calling. Figure 19.5 shows the alignment view of reads and coverage within a selected region of the E. coli genome, which allows one to compare the sequence reads mapped to the region of a 5-kilobase pairs (kbp) window against the background of varying GC content in this same region. Coverage of sequence reads remains evenly distributed. Figure 19.5 also shows the read alignment, demonstrating the accuracy of the sequence information obtained.

4.2. Assessment of coverage and lack of bias The ability to achieve consistent coverage across these genomes with special emphasis on regions of highly varying GC content is a hallmark of singlemolecule sequencing. To demonstrate consistent coverage across the genomic regions of the three bacteria, we have plotted in Fig. 19.6 the coverage depth of single-molecule sequence reads binned across the bacterial genomic sequence and similarly plotted their known GC content in the same windows alongside the reference genomes. The HeliScope Sequencer produces even coverage across the entire span of genomic sequence content within a genome, even in the case of very G þ C rich (R. sphaeroides) and highly A þ T rich (S. aureus) genomes.

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CGTGAAATACTGGCGCATCCGCTGGTGGGAGGGCTGATTCTCTTTACGCGTAACTATCATGATCCTGCCCAGTTACGTGAACTGGTGCGCCAGATCCGCG

Figure 19.5 Detailed view of reads and coverage within an arbitrary position within the E. coli genome. Top panel shows sequence read coverage across each 5 kb region of the E. coli genome along (red smooth line) with the regional GC coverage (green jagged line). In each case positional statistics are derived from a sampling of the 500 bp upstream and 500 bp downstream regions. Bottom panel shows sequence reads as they aligned to the genome within the region demarcated by the vertical black lines in the top panel.

5. Human Genome Sequencing and Quantitation Whole genome sequencing has been successfully achieved by scientists at Stanford University using Helicos single-molecule sequencing methods and the HeliScope Sequencer. Pushkarev et al. (2009) utilized 200 pM of poly-A tailed human genomic DNA per Helicos Flow Cell channel and loaded some 170 channels with the genomic DNA. The researchers obtained 148 Gigabases of raw sequence of, on average, 33-nt read length to achieve, on average, a 28 coverage of a human genome. Some 90% of the human genome was covered using this initial genome sequencing methodology. Sequence variants were identified as described in Pushkarev et al. (2009), which included data on copy number variation found within the human genome sequence.

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Figure 19.6 Comparison of genomic sequence coverage across differing G þ C content within bacterial genomes. (A) E. coli (51% G þ C). (B) S. aureus (32% G þ C). (C) R. sphaeroides (70% G þ C). Single molecule DNA sequencing provides minimal sequence bias across diverse genomic content. Sequence reads were mapped to each genome and the number of reads which map in discrete bins of the genome are plotted (red line) versus the expected bins if the mapping was perfect. Obtaining a signal as nearly identical to each other demonstrates the unique ability to sequence across diverse GC and AT rich regions. The analysis utilized a 200-bp sliding window, the local GC content and observed mean sequencing coverage were tabulated. Windows were then aggregated into GC-content bins ranging from 0 to 1 with a step size of 0.1. Plotted is the mean coverage (RED; Right Y axis) for each window within each of the aggregated GC content bins (BLACK; Left Y axis). A distinguishing feature of the Helicos SMS approach appears to be the minimal shifts in coverage across the vast majorities of sequence contexts.

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5.1. Copy number variation Copy number variation studies provide a methodology for detecting amplification and deletion of genomic regions across the human genome and often represent critically important knowledge of mutational events occurring in cancer genomes. Given the demonstration of evenness of sequence coverage in the bacterial strains representing the diversity of sequence found in the human genome, the use of single-molecule sequencing with the HeliScope Sequencer for an assessment of copy number variation represents an important, cost-effective method. 1. When available, prepare 1–2 mg of genomic DNA as described in Section 3. Less material may be utilized if sample is limited. This material may be obtained as genomic DNA prepared from tissue, blood, and formalin-fixed paraffin-embedded (FFPE) genomic DNA. 2. In the case of FFPE DNA, visualize the isolated DNA on a 1% agarose gel to determine the size of the genomic DNA. It is possible that, depending on the fixation of the tissue from which the DNA was obtained, the DNA still consists of high-molecular weight DNA and, if above 2–3 kbp, will require additional shearing as described in Section 3.1.1. 3. If the FFPE DNA falls below the size range of 2–3 kbp, proceed directly to Section 3.1.2 (DNA size selection) to ensure removal of small molecular weight DNA that can interfere with DNA sequence yields. 4. Following preparation of poly-dA tailed genomic DNA, load 150– 300 pM of genomic DNA on each Helicos Flow Cell channel for the HeliScope Sequencer. 5. Depending on the desired level of resolution required for localization of the regions of amplification and duplication, a decision will be required regarding the depth of sequence coverage desired. At present performance, one channel of the HeliScope Sequencer provides 0.2–0.3 coverage of the human genome. This allows you to group sequence reads by using ‘‘bins’’ which can be between 10 and 50-kilobase-sized segments of the human genome. This resolution allows sufficient coverage for detection of amplification and duplication events, including loss of heterozygosity and two- to threefold amplification across the entire human genome. Figure 19.7 summarizes the copy number variation data obtained from a human cancer cell line in which approximately 100 Mio sequence reads were mapped to the genome at a read bin size of 1 kbp intervals. These data are compared to existing comparative genomic hybridization data using an array technology. Peaks of amplification are easily detected, and the peak intensities reflect the extent of amplification. We refer also to the copy number variation data obtained from the first single-molecule human genome sequence (Pushkarev et al., 2009). To further demonstrate the power of single-molecule sequencing technology, data used for the comprehensive

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Figure 19.7 Detection of genomic amplification comparing Helicos single-molecule sequencing to comparative genomic hybridization. Genomic DNA from a breast cancer cell line was isolated, sheared, tailed, and sequenced according to the methods described in Section 5.1. Following sequencing, sequence reads were aligned to the human genome, binned into genomic bin sizes of 10 kb and bin sizes are plotted along the a 30 Megabase region chromosomal 20 (top panel). Regions of amplification are clearly detected in well described regions of Chr 20 previously identified using CGH arrays (bottom panel). (CGH Data: Courtesy of Genome Institute of Singapore).

view shown in Fig. 19.7 are replotted as individual channels of HeliScope Sequencer data and displayed in a 14-kbp region of the genome with 1-kbp smoothing of the read peaks (Fig. 19.8). These data reflect the consistency as well as the resolution achieved in single channels, allowing one to detect a region of five- to sevenfold amplification in this region.

6. Chromatin Immunoprecipitation Studies Helicos single-molecule sequencing technology is ideally suited also for another area of genomic science where accurate quantitation is key, ChIP studies (Goren et al., 2010). This method requires no ligation, amplification,

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Figure 19.8 Visualization of genomic amplification obtained from single HeliScope Sequencer Channels. Genomic reads used in Fig. 19.7 shown aligned to a segment of Chr 20 defining the boundary of amplification. Ten independent HeliScope Sequencer channels demonstrate the ability of a single channel of HeliScope Sequencer reads to clearly define the boundary of genomic amplification.

or complicated cleanup steps—all of which have the potential to induce sample loss and bias. The Helicos ChIP Seq methodology consists of a 1-h 30 poly-A tailing step followed by a 1-h 30 dideoxy-blocking step. Recommended starting material consists of 6–9 ng ChIP DNA (average fragment size 400–500 bp), although as little as 1–3 ng DNA prepared using this same method can be successfully employed. Typical yields obtained with the recommended 6–9 ng ChIP DNA from mouse or human studies allow one to load 3–6 Helicos Flow Cell Channels with a yield of 7–12 Million aligned sequence reads per channel.

6.1. Preparation of ChIP DNA 1. The quantity of ChIP DNA should first be determined with the Quant-iTTM PicoGreen dsDNA Reagent Kit (Invitrogen). 2. Samples should be free of RNA contamination and the use of the Qiagen Reaction Cleanup Kit (Qiagen) is recommended. 3. The micrococcal nuclease treatment used for fragmentation in some selected ChIP methods will generate phosphate groups on the 30 ends and thus will require end repair prior to initiating the ChIP tailing protocol. 4. One must also consider the alternative types of shearing used for fragmentation to ensure the 30 ends are amenable to direct poly-A tailing. Recommendations vary with shearing devices and one must check with the manufacturer on their advice for subsequent end repair.


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6.2. ChIP DNA poly-A tailing 1. Prepare a mix of 2 ml 10 Terminal Transferase buffer (NEB), 2 ml 2.5 mM CoCl2, ChIP DNA and Nuclease-free water 10.8 ml in a 200 ml PCR tube. 2. Place mixture in a thermocylcer and heat to 95 C for 5 min to denature the DNA. 3. Remove tube from the thermocylcer and quickly chill in an aluminum block held in an icy slurry to prevent renaturation. 4. Prepare a mix of 1 ml Terminal Transferase (1:4 diluted, 5 U/ml; NEB), 4 ml 50 mM dATP, and 0.2 ml BSA (NEB). 5. Add 5.2 ml mix to the denatured DNA on ice to bring total volume to 20 ml. 6. Place tube in the thermocycler and run the following program: 37 C for 1 h, 70 C for 10 min, maintain at 4 C until ready to proceed to next step.

6.3. ChIP DNA 30 blocking 1. Denature the 20 ml poly-A tailed ChIP DNA at 95 C for 5 min in the thermocycler, followed by immediate transfer to a prechilled aluminum block kept in an ice and water slurry. 2. Prepare a 10 ml mixture of 1 ml 10 Terminal Transferase buffer (NEB), 1 ml 2.5 mM CoCl2, 1 ml Terminal Transferase (1:4 diluted, 5 U/ml), 0.5 ml 200 mM Biotin-ddATP and 6.5 ml Nuclease-free water. 3. Add the 10 ml mixture to the denatured, poly-adenylated ChIP DNA mixture for a final volume of 30 ml. 4. Place the tube in a thermocycler and run the following program: 37 C for 1 h, 70 C for 20 min, followed by 4 C until ready to proceed to next step. 5. Add 2 pmol of a 50–80 nucleotide carrier oligonucleotide to the above terminal transferase reaction to minimize ChIP DNA loss during the sample loading steps. Since it does not contain a poly-A tail, the oligonucleotide will not hybridize to the Helicos Flow Cell. 6. Hybridize ChIP DNA sample to Helicos Flow Cell and sequence.

7. Digital Gene Expression for Transcriptome Quantitation Full transcriptome sequencing using high-throughput sequencing platforms (RNA Seq) has increased the sensitivity and accuracy of gene expression analysis. However, RNA Seq results in an inherent bias as a result of more reads from longer transcripts and thus has reduced the

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sensitivity for quantification of shorter transcripts (Oshlack and Wakefield, 2009). Further, assessing expression levels requires prior knowledge of transcript length for count normalization, which will not always be a reasonable demand, say in the case where there may be alternative splicing variants. Single-molecule sequencing digital gene expression (smsDGE) answers these difficulties and provides a route to quantitative analyses. smsDGE differs from RNA Seq in that only a single sequence read is generated per transcript molecule, regardless of its length. This permits short transcripts to be detected with the same sensitivity as long ones. Thus, whereas it would require 50 million RNA Seq reads to quantify 95% of the human transcriptome, with smsDGE 10 million reads will suffice (Lipson et al., 2009).

7.1. Methodology for single-molecule sequencing digital gene expression Sample preparation for smsDGE is minimal, requiring neither PCR amplification nor ligation. A summary of the method is shown in Fig. 19.9. Single-stranded cDNA is made directly from total RNA or poly-A þ RNA using poly-U primed reverse transcription. The RNA is then digested away using RNase, and a poly-A tail is added to the cDNA’s 30 end using terminal transferase. The sample can then be hybridized to the HeliScope flow-cell surface and sequenced (Lipson et al., 2009). 7.1.1. Single-stranded cDNA preparation 7.1.1.1. cDNA synthesis 1. Thaw RNA on ice (1–8 mg total RNA or 100–200 ng poly-Aþ RNA) preferably in 8 ml volume. 2. For sample: Prepare Master Mix A stock of 1 ml poly-U primer dTU25V (50 mM) and 1 ml dNTP nucleotide mix. Keep on ice. Prepare Master Mix B from Invitrogen SuperscriptIII kit as follows: 2 ml 10 Reverse Transcriptase buffer, 4 ml 25 mM MgCl2, 2 ml 0.1 mM DTT, 1 ml RNaseOUTTM and 1 ml Superscript III Reverse Transcriptase. 3. Aliquot 2 ml Master Mix A into a PCR tube. 4. Pipette 8 ml of RNA Sample into the PCR tube. Mix thoroughly by pipetting up and down. 5. Incubate the RNA at 65 C for 5 min. Snap cool by placing in aluminum block held in an ice water bath. 6. Add 10 ml Master Mix B Reverse Transcriptase enzyme and buffer to each tube. Mix well and spin down. 7. Place PCR tubes in the thermocycler. Incubate at 40 C for 5 min, 55 C for 50 min, 85 C for 5 min, maintain at 4 C until ready to proceed to next step.

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Figure 19.9 Overview of method utilized for single molecule sequencing digital gene expression. Principles employed in the single-molecule sequencing digital gene expression methodology described in Section 7.

7.1.1.2. RNA digestion

1. Add 1 ml RNase H (2 U/ml) to the cDNA Synthesis reaction. Mix well and incubate at 37 C for 15 min, maintain at 4 C until ready to proceed to next step.

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2. Add 1 ml USERTM (1 U/ml) enzyme. Mix well and incubate at 37 C for 15 min, maintain at 4 C until ready to proceed to next step. 3. Add 1 ml RNase I (50 U/ml) enzyme. Mix well and incubate at 37 C for 15 min, maintain at 4 C until ready to proceed to next step. 7.1.1.3. cDNA sample cleanup

1. Warm AMPure Bead solution to RT. Vortex to resuspend. 2. Transfer cDNA sample to a 1.5-ml tube and add water to bring each sample to 50 ml. Vortex the beads again and add 65 ml AMPure Bead slurry. 3. Incubate at RT for 30 min. Shake tube every 10 min. 4. Briefly centrifuge at low speed, capture beads on Dynal magnetic stand for 5 min and carefully aspirate supernatant. 5. Wash beads twice with 200 ml freshly prepared 70% (v/v) ethanol. 6. Briefly centrifuge, place on magnet, remove ethanol, and dry pellet completely at RT for 5–7 min. 7. Elute the cDNA sample from the beads with 20 ml distilled water twice. 8. Repeat entire cDNA sample cleanup once more. Final product will be in 40 ml volume. 7.1.1.4. cDNA quantification

1. Determine the concentration and yield for each cDNA sample preparation using a small volume spectrophotometer. If the sample concentration is likely below 2 ng/ml use the Quant-iTTM OliGreenÒ ssDNA Reagent Kit and obtain spectrofluorometer reads accordingly. 2. Store samples at 20 C to continue sample preparation the next day if desired. 7.1.2. Poly-A tailing of the cDNA 7.1.2.1. Poly-A tailing reaction 1. Obtain control oligonucleotides from HelicosÒ Digital Gene Expression Assay Reagent Kit. 2. Place 20–60 ng of cDNA into a PCR tube. Add water to bring each to 28 ml. 3. Add 7.5 ml of HelicosÒ Control Oligonucleotide. Mix well and store on ice. 4. Incubate at 95 C for 5 min. Snap cool on ice. Briefly centrifuge. 5. Prepare poly-A Tailing mix of 5 ml 10 Terminal Transferase buffer, 5 ml CoCl2, 2.5 ml HelicosÒ poly-A Tailing dATP, and 1.5 ml Terminal Transferase. Mix well. 6. Add 14 ml of poly-A Tailing Mix to the cDNA and pipette up and down.


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7. Incubate at 42 C for 60 min, 70 C for 10 min, and maintain at 4 C until ready to proceed to next step. 7.1.2.2. Determining the success of the tailing reaction

1. Success of the tailing reaction is determined by monitoring the oligo control tailing. Run an aliquot of the control oligonucleotide without poly-A tail addition and the control poly-A tailed oligonucleotide alongside your cDNA tailing reaction on a 4–20% gradient polyacrylamide gel in 1 TBE, together with a 25-bp ladder. 2. Since the cDNA molecules will be of a very broad size range, assess the length of the tail added to the control oligonucleotide as a measure of the tail added to the cDNA molecules. 3. Control-tailed oligos should migrate anywhere between 225 and 450 bp of the 25-bp ladder to ensure a proper poly-A tail with a desired length between 90 and 140 dA. 7.1.3. cDNA blocking 7.1.3.1. cDNA blocking reaction 1. Incubate the cDNA sample at 95 C for 5 min. Snap cool on ice to denature. 2. Add 0.3 ml biotin-ddATP and 1.5 ml of Terminal Transferase enzyme. Mix well and spin down. 3. Incubate at 37 C for 30 min, then 70 C for 10 min, and maintain at 4 C until ready to proceed to next step. 7.1.3.2. Poly-A tailing control oligonucleotide digestion

1. Add 1 ml USER Enzyme (1 U/ml) to the cDNA sample. Mix well and spin down. 2. Incubate at 37 C for 30 min, maintain at 4 C until ready to proceed to next step. 7.1.3.3. Sample cleanup

1. Transfer cDNA from digestion step above to a 1.5-ml tube. Add water to bring volume to 60 ml. 2. Mix cDNA with 60 ml AMPure Bead slurry and incubate at RT for 30 min. Shake every 10 min. 3. Capture the beads on Dynal magnetic stand for 5 min and carefully aspirate supernatant. 4. Wash beads twice with 200 ml freshly prepared 70% (v/v) ethanol.

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5. Dry pellet completely at RT for 5–7 min. 6. Elute cDNA sample from beads with 20-ml distilled water twice. Hybridize 150–300 pmol smsDGE cDNA in 20 ml volume to Helicos Flow Cell and sequence.

7.2. Demonstration of DGE counting reproducibility To assess smsDGE reproducibility, we independently prepared three brain samples from the same RNA (poly-A RNA, Ambion, Austin TX) and sequenced each sample in a single HeliScope flow-cell channel. The three channels yielded 15, 14, and 12 million transcriptome-aligned reads. Transcript abundance ranged from 0 to 370,000 transcripts per million (tpm) with the highest seen for mitochondrial transcripts (chromosome M). Of the 28,800 transcripts included in our reference (UCSC genome database), 18,700 were present at a level higher than 1 tpm (>12 mapped reads). Transcript count reproducibility between samples was high (r ¼ 0.99) with coefficient of variation (%CV) ranging from 4% at 100 tpm to 20% at 1 tpm (Fig. 19.10).

8. Summary Methods for single-molecule sequence analysis of nucleic acids provide a diverse repertoire for quantitative and qualitative investigation of the genome and transcriptome. As such, we have attempted to describe many of the simple sample preparation methods offered to the research community. We will continue to optimize our sample preparation protocols to allow preparation and sequencing from picogram quantities of nucleic acid (Ozsolak et al., 2010)—all important for maximizing researchers abilities to perform important biological experiments with limiting biological sample amounts. These methods will serve as the starting point for the next edition of methods for single-molecule sequencing.

ACKNOWLEDGMENTS Special thanks to the many individuals who have contributed to the success of Helicos BioSciences technology—for their scientific excellence and passions to develop a remarkable new technology and all its broad applications.

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Figure 19.10 Demonstration of transcript counting reproducibility obtained using smsDGE methods with human brain RNA. smsDGE transcript quantification of independently prepared human brain samples. (A) Transcript count comparison between two samples run on a single flow-cell channel each. Each sample represents a single transcript (r ¼ 0.99). (B) Coefficient of variation (%CV) across transcript abundance levels between three samples at 12, 14, and 15 million transcriptome-aligned reads per channel.

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REFERENCES Bowers, J., Mitchell, M., Beer, E., Buzby, P. R., Causey, M., Efcavitch, J. W., Jarosz, M., Krzymanska-Olejnik, E., Kung, L., Lipson, D., Lowman, G. M., Marappan, S., et al. (2009). Virtual terminator nucleotides for next generation DNA sequencing. Nat. Methods 6, 593–595. Dohm, J. C., Lottaz, C., Borodina, T., and Himmelbauer, H. (2008). Substantial biases in ultra-short read data sets from high-throughput DNA sequencing. Nucleic Acids Res. 36 (16), e105. Goren, A., Ozsolak, F., Shoresh, N., Ku, M., Adli, M., Hart, C., Gymrek, M., Zuk, O., Regev, A., Milos, P. M., and Bernstein, B. E. (2010). Chromatin profiling by directly sequencing small quantities of immunoprecipitated DNA. Nat. Methods 7(1), 47–49. Harris, T. D., Buzby, P. R., Babcock, H., Beer, E., Bowers, J., Braslavsky, I., Causey, M., Colonell, J., Dimeo, J., Efcavitch, J. W., Giladi, E., Gill, J., et al. (2008). Single-molecule DNA sequencing of a viral genome. Science 320(5872), 106–109. Hayden, E. (2009). Genome sequencing: The third generation. Nature 457, 768–769. Kahvejian, A., Quackenbush, J., and Thompson, J. F. (2008). What would you do if you could sequence everything? Nat. Biotechnol. 26, 1125–1133. Lipson, D., Raz, T., Kieu, A., Jones, D. R., Giladi, E., Thayer, E., Thompson, J. F., Letovsky, S., Milos, P., and Causey, M. (2009). Quantification of the yeast transcriptome by single-molecule sequencing. Nat. Biotechnol. 27, 652–658. Oshlack, A., and Wakefield, M. J. (2009). Transcript length bias in RNA-seq data confounds systems biology. Biol. Direct 4, 14. Ozsolak, F., Platt, A., Jones, D., Reifenberger, J., Sass, L. E., McInerney, P., Thompson, J. F., Bowers, J., Jarosz, M., and Milos, P. (2009). Direct RNA sequencing. Nature 461, 814–818. Ozsolak, F., Goren, A., Gymrek, M. A., Guttman, M., Regev, A., Bernstein, B. E., and Milos, P. M. (2010). Digital transcriptome profiling from attomole-level RNA samples. Genome Res. [Epub ahead of print]. Pushkarev, D., Neff, N. F., and Quake, S. R. (2009). Single-molecule sequencing of an individual human genome. Nat. Biotechnol. 27, 847–850.

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Real-Time DNA Sequencing from Single Polymerase Molecules Jonas Korlach, Keith P. Bjornson, Bidhan P. Chaudhuri, Ronald L. Cicero, Benjamin A. Flusberg, Jeremy J. Gray, David Holden, Ravi Saxena, Jeffrey Wegener, and Stephen W. Turner Contents 1. Introduction 2. Principle of Single-Molecule, Real-Time DNA Sequencing 3. Components of SMRT Sequencing 3.1. Zero-mode waveguides for observation volume confinement 3.2. ZMW surface derivatization for targeted enzyme immobilization 3.3. Phospholinked nucleotides for uninterrupted DNA polymerization 3.4. DNA polymerase—the sequencing ‘‘engine’’ 3.5. Instrument for highly parallel monitoring of sequencing reactions 3.6. DNA sequencing assay example 3.7. Data analysis 4. Single-Molecule DNA Polymerase Dynamics 4.1. Determination of single-molecule kinetic parameters 4.2. DNA polymerase pausing 5. Conclusions Acknowledgments References

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Abstract Pacific Biosciences has developed a method for real-time sequencing of single DNA molecules (Eid et al., 2009), with intrinsic sequencing rates of several bases per second and read lengths into the kilobase range. Conceptually, this sequencing approach is based on eavesdropping on the activity of DNA polymerase carrying out template-directed DNA polymerization. Performed in a Pacific Biosciences, Menlo Park, California, USA Methods in Enzymology, Volume 472 ISSN 0076-6879, DOI: 10.1016/S0076-6879(10)72001-2

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highly parallel operational mode, sequential base additions catalyzed by each polymerase are detected with terminal phosphate-linked, fluorescence-labeled nucleotides. This chapter will first outline the principle of this single-molecule, real-time (SMRTTM) DNA sequencing method, followed by descriptions of its underlying components and typical sequencing run conditions. Two examples are provided which illustrate that, in addition to the DNA sequence, the dynamics of DNA polymerization from each enzyme molecules is directly accessible: the determination of base-specific kinetic parameters from singlemolecule sequencing reads, and the characterization of DNA synthesis rate heterogeneities.

1. Introduction The ability to rapidly determine nucleic acid sequences has fundamentally transformed the biological sciences, both with respect to inquiries toward understanding biological processes and the approaches to manipulating them. Next-generation DNA sequencing methods have changed whole-genome sequencing projects into routine procedures (reviewed in Mardis, 2008) and have been adapted to other areas, such as transcriptome sequencing and epigenetics (Cloonan et al., 2008; Cokus et al., 2008; Fullwood et al., 2009; Maher et al., 2009; Yassour et al., 2009). However, despite their gains in sequencing throughput, these methods still fall short of providing the means to elicit fundamental changes in the fields of medical diagnostics, disease prevention, and treatment. Further improvements are required for higher quality and even more cost-effective sequencing of complete individual genomes and transcriptomes. DNA polymerases can be viewed as efficient DNA sequencers— engineered by nature—as they decode the sequence of a template strand by virtue of synthesizing its complementary strand. Over millions of years of molecular evolution, DNA polymerases have been optimized to rapidly and faithfully replicate genomes, and they have in turn developed many features attractive for artificial DNA sequencing methods. DNA polymerases can be very fast, with DNA synthesis rates reported in vitro as high as 750 bases per second (Tabor et al., 1987). Tens to hundreds of thousands of bases can be synthesized from a single polymerase binding event (Blanco et al., 1989). DNA polymerases can also be viewed as very frugal as only one nucleotide is consumed during each incorporation cycle. Error rates can be as low as one in 105 bases (Esteban et al., 1993) and even lower with associated proofreading activities. Finally, DNA polymerases are physically very small, enabling a high level of multiplexing on a small footprint.

Real-Time DNA Sequencing from Single Polymerase Molecules

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Exploiting all of these characteristics directly by using polymerase as the actual sequencing engine had not been commercially feasible until recently. We have overcome the underlying technical challenges by innovations in the fields of nanofabrication, surface derivatizations, nucleotide and protein chemistries, and optics, to enable the direct, real-time interrogation of individual polymerase activities (Eid et al., 2009). Essentially, DNA is sequenced by watching with base-pair resolution what normally constitutes DNA replication occurring in dividing cells.

2. Principle of Single-Molecule, Real-Time DNA Sequencing The Single-Molecule, Real-Time (SMRTTM) DNA sequencing concept is illustrated in Fig. 20.1. The two principal technological components that facilitate SMRT sequencing are (i) zero-mode waveguide (ZMW) confinement that allows single-molecule detection at concentrations of labeled nucleotides relevant to the enzyme, and (ii) fluorescence-labeled, phospholinked nucleotides that permit observation of uninterrupted DNA polymerization. ZMW nanostructures (Fig. 20.1A) consist of dense arrays of holes, 100 nm in diameter, fabricated in a 100-nm metal film deposited on a transparent substrate (e.g., silicon dioxide) (Foquet et al., 2008; Levene et al., 2003). Each ZMW becomes a nanophotonic visualization chamber for recording an individual polymerization reaction, providing a detection volume of just 100 zeptoliters (10 21 L). This volume represents a 1000-fold improvement over diffraction-limited confocal microscopy, making it possible to observe single nucleotide incorporation events against the background created by diffusing fluorescence-labeled nucleotides. In addition to reducing the number of labeled nucleotides present inside the observation volume, the highly confined volume results in drastically shorter diffusional visitation times. This enables better temporal differentiation between events involving diffusion of labeled nucleotides through the observation volume (now typically lasting only a few microseconds) and enzymatic nucleotide incorporation events (typically lasting several milliseconds for polymerases). The second important component is phospholinked nucleotides for which the fluorescent label is attached to the terminal phosphate rather than the base, typically via a linker (Fig. 20.1B). A 100% replacement of unmodified nucleotides by phospholinked nucleotides is achieved because the enzyme cleaves away the fluorophore as part of the incorporation process, leaving behind a completely natural, double-stranded nucleic acid

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Step 2

Step 3

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Template

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Figure 20.1 Principle of single-molecule, real-time (SMRT) DNA sequencing. (A) Single DNA polymerase molecules with bound DNA template are immobilized to the bottom of zero-mode waveguide (ZMW) nanostructure arrays. Polymerization of the complementary DNA strand is observed in real time by detecting enzymatic processing of fluorescent phospholinked nucleotides. (B) Molecular structure of phospholinked nucleotides. Alexa Fluor 568-aminohexyltriphosphate-dTTP is shown by example (Eid et al., 2009). The arrow indicates the a-b phosphodiester bond cleavage mediated by the DNA polymerase. (C) Schematics of reactions steps involved in SMRT DNA sequencing (top), and corresponding fluorescence intensity time trace (bottom). Step 1: The DNA template/primer/polymerase complex is surrounded by diffusing phospholinked nucleotides which probe the active site. Step 2: A labeled nucleotide makes a cognate binding interaction with the template base in the DNA. During the time it is bound in the active site (typically lasting tens of milliseconds) fluorescence is emitted continuously, giving rise to a detectable pulse in the fluorescence intensity time trace. The identity of the fluorescent dye indicates which base is incorporated. Step 3: The polymerase incorporates the nucleotide into the growing nucleic acid chain by cleaving the a-b phosphodiester bond, thereby subsequently releasing the pyrophosphatelinker-fluorophore. Step 4: The polymerase translocates to the next template position. Step 5: The process repeats.

product. In SMRT sequencing, each of the four different nucleobases is labeled with a distinct fluorophore to discriminate base identities during incorporation events, thus providing sequence determination of the complementary DNA template (Fig. 20.1C). During incorporation, the enzyme holds the labeled nucleotide in the ZMWs detection volume for several milliseconds, orders of magnitude longer than the average diffusing nucleotide is present. Fluorescence is emitted continuously from the fluorophore


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label during the incorporation process, causing a detectable pulse of increased fluorescence in the corresponding color channel. The pulse is terminated naturally by the polymerase releasing the pyrophosphatelinker-fluorophore group which diffuses out of the observation volume. The polymerase then translocates to the next base, and the process repeats.

3. Components of SMRT Sequencing 3.1. Zero-mode waveguides for observation volume confinement Fabrication of ZMWs with aluminum or gold as the metal cladding material was first described using a positive-tone, electron-beam lithography technique followed by reactive ion etching (Levene et al., 2003; Liu and Blair, 2003). Subsequently, other fabrication methods have been described, including negative-tone, electron-beam lithography followed by metallization and resist removal (Foquet et al., 2008; Miyake et al., 2008), focused ion beam milling (Rigneault et al., 2005), and photolithography (Foquet et al., 2008). Of these, photolithography is very attractive because of the lower cost of fabrication and its compatibility with high-volume manufacturing processes. We have recently improved the photolithographic process of ZMW fabrication, resulting in greater reproducibility, size uniformity, and ZMW shape control (Fig. 20.2). Detailed protocols for the different fabrication methods can be found in the references cited above.

3.2. ZMW surface derivatization for targeted enzyme immobilization The selective placement of an active polymerase molecule into a ZMW observation volume, immediately above the transparent ZMW floor, is an important prerequisite for efficient SMRT DNA sequencing. ZMWs put additional demands on the quality of surface preparations to achieve this because the functionalization target area is very small relative to the cladding surface area. At the same time, the surfaces should be well-passivated to prevent corrosion and nonspecific adsorption of phospholinked nucleotides which are used at much higher concentrations compared to conventional single-molecule assays. In addition, the employed surface coating reagents should exhibit low fluorescence levels, and should not interfere with enzymatic activities. For aluminum-clad ZMWs, we have developed protocols and reagent formulations meeting all of these criteria by exploiting an inherent feature of ZMW architecture in that the ZMW substrate and cladding are made of

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B

A

Frequency

C 900 800 700 600 500 400 300 200 100 0 80 85 90 95 100 105 110 115 120 ZMW diameter (nm)

Figure 20.2 Zero-mode waveguide (ZMW) fabrication. (A) Scanning electron micrograph of the top side and (B) transmission electron micrograph of the center cross-section of a ZMW fabricated by the described photolithography protocol. The desired ZMW shape exhibits vertical bottom walls and a slightly tapered opening toward the top midway up the cladding. Scale bars ¼ 100 nm. (C) Distribution of ZMW floor diameters over an array of 3000 ZMWs with nominal diameter of 100 nm. (mean ¼ 98.4 nm; standard deviation ¼ 5.8 nm).

different materials. It combines selective passivation of the cladding surfaces using polyphosphonate chemistries (Korlach et al., 2008b) with selective functionalization of the ZMW substrate using biotin polyethylene glycol (PEG) silane (Eid et al., 2009). It results in ZMW arrays that present biotin for specific enzyme immobilization only at the ZMW glass floor, above a layer of PEG to preserve enzyme activities (Fig. 20.3A). Using this procedure, we have achieved high contrast ratios of biotin functionalization (in excess of 100:1, Fig. 20.3B), with undetectable levels of biotin PEG silane on the aluminum surface, as measured by X-ray photoelectron spectroscopy (XPS). The specificity of protein binding was also in excess of 100:1 (Fig. 20.3C). For polymerase immobilization, depending on the ZMW diameter chosen for sequencing, the concentrations of streptavidin and polymerase are adjusted to yield optimal loading which is governed by Poisson statistics (Korlach et al., 2008b) (Section 3.6).

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SiO2

Al Selectivity (SiO2/Al) 110.7 ± 18.8

Polymerase/DNA complex

Aluminum cladding

C

-

Biotin block:

+

Specificity (SiO2/ SiO2biotin block) 102.4 ± 10.6

Glass substrate Polyphosphonates Biotin-PEG-silane

Streptavidin Native aluminum oxide

Figure 20.3 Surface derivatization for specific, selective immobilization of DNA polymerase in ZMWs. (A) The cladding surface is passivated with polyphosphonates, the ZMW substrate surface is functionalized with biotin PEG silane to mediate enzyme immobilization targeted to the ZMW floor. (B) Material selectivity of the surface derivatization, measured with 40 nm fluorescent neutravidin beads (Korlach et al., 2008b). The assay uses patterned substrates of 0.5 mm aluminum squares on fused silica. (C) Specificity of neutravidin binding to the glass surface. Specificity was determined by comparing neutravidin binding with a sample for which neutravidin was blocked with excess biotin before the immobilization step. Contrast means and standard deviations are for n ¼ 4 chips.

3.3. Phospholinked nucleotides for uninterrupted DNA polymerization Nucleotides with fluorescent labels attached to the terminal phosphate were first described as efficient substrates for Escherichia coli DNA-dependent RNA polymerase (Chatterji and Gopal, 1996; Schlageck et al., 1979; Yarbrough et al., 1979). Utilization of phospholinked dNTPs was subsequently demonstrated in conjunction with DNA polymerases and reverse transcriptases (Kumar et al., 2005; Mulder et al., 2005; Sood et al., 2005), but high concentrations had to be used because incorporation efficiencies were generally much lower than with unmodified dNTPs. It was observed that a linker containing one or more additional phosphate groups extending the triphosphate moiety proved beneficial for improving incorporation efficiencies (Kumar et al., 2005; Sood et al., 2005), presumably due to attenuation of steric hindrance effects of the bulky fluorophore proximal to the active site, and partial restoration of the negative charge lost by the linker conjugation at the g-phosphate. We have found that for f29 DNA polymerase, a linker that is extending the natural triphosphate by an additional two or three phosphates, followed by a short aminohexyl aliphatic

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chain, yields nucleotides that are incorporated as efficiently as unmodified, natural dNTPs with respect to synthesis rates and processivity (Korlach et al., 2008a). Depending on the specific DNA polymerase under study, the exact nature of the linker and number of extra phosphates may vary. An exemplary synthesis protocol for the phospholinked dNTP Alexa Fluor 488 aminohexyl-dG5P (Korlach et al., 2008a) is given below. Based on carbonyldiimidazole (CDI) activation, it builds the additional diphosphate moiety on an aliphatic linker, allowing for flexibility of dye conjugation as the final step. The aliphatic linker also allows a larger spatial separation between nucleotide and fluorophore. During the third CDI activation for coupling the linker-triphosphate to the nucleotide, MgCl2 is included, which significantly improves the yield (Kadokura et al., 1997). Fmoc-6-aminohexylphosphate 1. Coevaporate 1 g (2.94 mM) of Fmoc-6-aminohexanol 2 with 20 ml anhydrous acetonitrile, then suspend in 10 ml anhydrous triethylphosphate. 2. Add two equivalents (550 l, 5.88 mM) of phosphorus oxychloride to the stirring suspension (Yoshikawa et al., 1967). After 2 h, HPLC shows disappearance of the Fmoc-6-aminohexanol. 3. Quench the reaction by the addition of 100 ml 0.1 M triethylamine bicarbonate (TEAB) (pH 6.8) and stir for 30 min. Purify by reverse phase HPLC on a Waters Xterra C18 RP 30 100 column using an acetonitrile gradient in 0.1 M TEAB. 4. Evaporate the fractions containing product, followed by coevaporation with methanol (2). 5. Triturate the residue twice with 100 ml diethylether and dry under vacuum to give a white powder. Yield: 1.24 g, 68% as bis-triethylamine salt. Purity (HPLC): 98%. Fmoc-6-aminohexyldiphosphate 1. Coevaporate 200 mg (320 mM) of Fmoc-6-aminohexylphosphate twice with anhydrous acetonitrile, then suspend in 2 ml anhydrous DMF. 2. Add four equivalents of 1,10 -carbonyldiimidazole (CDI; 207 mg, 1280 mM) and stir at ambient temperature for 4 h (Hoard and Ott, 1965). 3. Add six equivalents of methanol (77 ml, 1920 mM) and stir for 30 min. 4. Add to the reaction 10 equivalents of tributylamine–H2PO4 (3200 mM; prepared by mixing equimolar amounts of tributylamine and 85% phosphoric acid, followed by coevaporation three times with anhydrous acetonitrile, and dissolved in 4 ml anhydrous DMF). Stir the reaction mixture for 16 h. HPLC shows 3% Fmoc-aminohexylphosphate remaining. 5. Dilute the reaction mixture to 50 ml with 0.1 M TEAB, and purify by RP HPLC on a Waters Xterra C18 RP 30 100 column using an acetonitrile gradient in 0.1 M TEAB.


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6. Evaporate the fractions containing product, followed by coevaporation with methanol (2). 7. Coevaporate the residue with anhydrous acetonitrile. Yield: 186 mg, 73% as Tris–TEA salt. Purity (HPLC): 96%. Aminohexyl-dG5P 1. Coevaporate 186 mg (233 mM) Fmoc-6-aminohexyldiphosphate twice with anhydrous acetonitrile, then suspend in 3 ml anhydrous DMF. 2. Add four equivalents of CDI (150 mg, 930 mM) and stir at ambient temperature for 4 h. 3. Add six equivalents of methanol (56 ml, 1400 mM) and stir for 30 min. 4. Coevaporate 1.5 equivalents dGTP (TEA salt, 350 mM) 3 with anhydrous acetonitrile, then suspend in 2 ml anhydrous DMF. 5. Add the Fmoc-aminohexyldiphosphoimidazolate reaction to the dGTP solution, followed by 10 equivalents of anhydrous MgCl2 (333 mg, 3500 mM) (Kadokura et al., 1997). Stir the reaction for 18 h. HPLC shows 28% of the Fmoc-aminohexyldiphosphate converted to Fmocaminohexyl-dG5P. 6. Dilute the reaction mixture to 125 ml with 0.1 M TEAB, and purify by RP HPLC on a Waters Xterra C18 RP 30 100 column using an acetonitrile gradient in 0.1 M TEAB. 7. Evaporate the fractions containing product, followed by coevaporation with methanol (2). 8. Take up the residue in 20 ml 10% TEA/water and stir for 16 h to remove the Fmoc protecting group from the amine on the linker. 9. Evaporate triethylamine, add water to 25 ml, and extract the solution three times with 25 ml diethyl ether. 10. Purify the product from the aqueous layer by anion exchange chromatography on Q sepharose FF using a TEAB gradient from 0.05 to 1 M. Yield: 42 mM, 18%. Purity (HPLC): 98%. Alexa Fluor 488-aminohexyl-dG5P 1. Dissolve 1 mM aminohexyl-dG5P in 200 ml of 50 mM NaHCO3, pH 8.7, and add to 1 mg Alexa Fluor 488-TFP ester (Invitrogen). Briefly sonicate the mixture. 2. After 4 h, HPLC showed no active ester remaining (the product is identified by characteristic PDA scan). Purify the compound by IEX on Q sepharose FF with a TEAB gradient from 0.05 to 1 M. Purify the product further by RP HPLC on a Waters Xterra RP C18 19 100 column using an acetonitrile gradient in 0.1 M TEAB. 3. Evaporate the fractions containing pure product, followed by coevaporation with methanol (2). 4. Dissolve the residue in water and quantitate by UV–Vis spectrophotometry. Yield: 370 nM, 37%. Purity (HPLC): 99%.

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In contrast to base-linked nucleotide derivatizations, this synthesis scheme proceeds identically for all four nucleobases, and for labeling with different fluorophores using the appropriate dye NHS esters. For phospholinked nucleotides containing a triphosphate linker (Eid et al., 2009) instead of the diphosphate moiety described here, Fmoc-aminohexyl-triphosphate is substituted for Fmoc-aminohexyl-diphosphate in the condensation reaction with nucleoside triphosphate. Demands on the purity of phospholinked nucleotides for accurate SMRT DNA sequencing are high, as even small traces of unlabeled nucleotides, when incorporated by the polymerase, could lead to missed bases in the sequencing read. Exposure of materials to ambient light should be minimized during the dye conjugation step to avoid fluorophore bleaching. In addition, in contrast to base-linked nucleotides, it is straightforward to subject phospholinked nucleotides to an additional enzymatic purification. For example, one can take advantage of the specificity of alkaline phosphatases which rapidly degrade unmodified dNTPs to the corresponding nucleoside, but are completely inactive on dNTPs that contain moieties coupled to the terminal phosphate (Sood et al., 2005; Yarbrough, 1978). Such post-chemical-synthesis purification can be carried out before using phospholinked nucleotides in SMRT sequencing reactions, or conveniently, the phosphatase can be included in the sequencing reaction.

3.4. DNA polymerase—the sequencing ‘‘engine’’ Various DNA polymerases can be used in conjunction with SMRT DNA sequencing, and the sequencing performance will depend on their specific properties. We have applied wild-type and mutant DNA polymerases from bacteriophage f29 to our SMRT DNA sequencing method, taking advantage of several favorable characteristics. f29 DNA polymerase is extremely processive (tens of kilobases), relatively fast (50–100 bases/s) and highly accurate (error rate of 10 5–10 6) (Baner et al., 1998; Blanco et al., 1989; Esteban et al., 1993). It is also very stable, maintaining constant enzymatic activities for up to several days (Dean et al., 2001; Nelson et al., 2002). The use of doublestranded DNA templates is possible by its efficient DNA strand displacement synthesis activity, thus simplifying sample preparation procedures. The following protocol outlines the expression and purification of f29N62D, a mutant with reduced 30 -50 exonuclease activity while maintaining essentially identical polymerizing properties (Blanco and Salas, 1996; de Vega et al., 1996). N-terminal Histidine (His) and GST tags were cloned into pET41 (Invitrogen, Carlsbad, CA) for ease of purification (Korlach et al., 2008a). 1. Overproduce polymerase in E. coli by addition of IPTG (1 mM) at midlog phase.


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2. Disrupt the cells using lysozyme (chicken egg white, Sigma-Aldrich, St. Louis, MO) in a buffer containing 50 mM Tris–HCl, pH 7.5, 7 mM 2-mercaptoethanol, and 5% glycerol (buffer B), and additionally containing 0.2 M NaCl for 30 min. Sonicate for 2 min with a sonication probe. Degrade DNA with DNase I (bovine pancreas, Sigma-Aldrich) for 30 min at room temperature while shaking. Remove cell debris by centrifugation for 30 min at 15,000g. 3. Adjust the supernatant to 0.5 M NaCl for purification on a 1-ml HisTrap FF column (Ni-resin, GE Healthcare, Piscataway, NJ), equilibrated with buffer B containing 0.5 M NaCl. Wash His-tagged polymerase retained on the HisTrap column with at least 50 column volumes, first using buffer B containing 1 M NaCl, 0.2% Tween-20, and 20 mM imidazole, followed by buffer B containing 0.5 M NaCl and 50 mM imidazole. 4. Elute the polymerase with buffer B containing 300 mM imidazole. Pool this ‘‘HisTrap’’ fraction and adjust it to 0.2 M NaCl using buffer C (50 mM Tris–HCl, pH 7.5, 1 mM EDTA, 7 mM 2-mercaptoethanol, 5% (v/v) glycerol). 5. Load the sample onto a Heparin-Sepharose CL-6B column (10 ml, GE Healthcare), equilibrated in buffer C. Elute polymerase with buffer C and a gradient of 0–1 M NaCl. Pool these ‘‘Heparin’’ fractions and concentrate using Centricon YM-50 (Millipore, Billerica, MA). 6. Adjust to the final storage buffer (50 mM Tris–HCl, pH 7.5, 0.2 M NaCl, 1 mM EDTA, 7 mM 2-mercaptoethanol, 50% (v/v) % glycerol). 7. Analyze protein fractions by sodium dodecyl sulfate—polyacrylamide gel electrophoresis (SDS–PAGE, 10% or 15% polyacrylamide). The purified polymerase is at least 97% homogenous. Determine protein concentrations both by measuring the absorbance at 280 nm, and by the Bradford method using known amount of BSA (Bio-Rad). Various strategies exist to mediate specific enzyme immobilization in ZMWs. They will depend on the particular coupling chemistry chosen. For a surface derivatization providing selectively biotinylated ZMW floors (described in Section 3.2), they include nonspecific biotinylation of the enzyme (Hermanson, 1996), introduction of specific biotin tags (Beckett et al., 1999), or fusion proteins (Nilsson et al., 1997).

3.5. Instrument for highly parallel monitoring of sequencing reactions As for all single-molecule fluorescence recording systems, optimization of light collection efficiencies is paramount for maximal signal-to-noise detection. For SMRT DNA sequencing, additional demands exist for simultaneously illuminating and monitoring many ZMWs containing immobilized DNA polymerase molecules. We have described the development of a

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highly parallel optical system that is capable of continuously analyzing thousands of concurrent sample locations (Lundquist et al., 2008) (Fig. 20.4). In this system, wavelength-specific holographic phase masks (Kress and Meyrueis, 2000) act as illumination multiplexers by dividing the laser beams into several thousand subbeams. Relay lens assemblies convert these beams into corresponding arrays of spots focused at a plane conjugate to the front focus of a microscope objective. After combining multiple wavelengths paths, all of the illumination light is transmitted through a common dichroic filter and brought to an array of diffraction-limited focal spots in the sample plane where it excites fluorescence in each ZMW observation volume. Multiple laser sources, coupled with demands for detecting several different fluorophores with single-molecule sensitivity, put stringent demands on the dichroic filter. We have found that better performance

Multiplex zero-mode waveguide array

Objective lens

Zero-mode waveguide array Monochrome detector Confocal pinhole array

Color separation

ZMW 1 ZMW 2 ZMW 3

Dichroic

ZMW 4 Prism

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Laser 2

ZMW 5

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Holographic phase masks

Figure 20.4 Schematics of an optical system for SMRT DNA Sequencing. This instrument provides simultaneous illumination of 3000 ZMWs with two different lasers, and wavelength-specific real-time detection of fluorescence from phospholinked nucleotides processed by DNA polymerase immobilized in the ZMWs. A photograph of an instrument (top cover removed) is shown on the bottom.


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with respect to narrow excitation bandwidths and high fluorescence throughput can be achieved by reversing the conventional positions of the illumination and collection paths. Upon reflecting off the dichroic filter, fluorescence light is first imaged onto a congruent array of confocal pinholes to reject stray light not originating from ZMW locations. It is subsequently reimaged through a prism dispersive element onto a monochrome, electron-multiplication charge-coupled device (EM-CCD) array. The compound prism serves to linearly disperse the wavelength content of the emitted light, transforming the image from each confocal volume element from a diffraction-limited spot into a ‘‘rainbow’’ pattern. Emitted fluorescence from different phospholinked nucleotides falls onto different spatial locations on the detector, thereby enabling identification of the type of nucleotide incorporated by the polymerase at any given time. A single camera thus collects both spatial and spectral information for the entire ZMW array. The prism assembly we have chosen allows for hightransmission, continuous color separation. The resulting opportunity for oversampling the fluorescence spectra in wavelength improves the accuracy of classification in cases of overlapping dye emission spectra. For example, in the implementation described in Lundquist et al., (2008), a three-wedge compound prism was optimized to provide linear angular dispersion of 1.25 mrad between the wavelengths of 490 and 730 nm, with a zero-deviation angle at 550 nm. With this choice, the system can be applied to a variety of fluorophore combinations. If resolution of highly overlapping emission spectra were a limitation, dispersion could be increased in the critical regions to improve spectral performance.

3.6. DNA sequencing assay example A typical protocol for performing a SMRT DNA sequencing reaction is described below. An oxygen scavenging system, consisting of protocatechuate dioxygenase (PCD) and its substrate protocatechuic acid (PCA), is used to remove oxygen and thereby suppress photophysical effects that might be deleterious to the polymerase (Aitken et al., 2008; Eid et al., 2009). A nitrobenzyl-based triplet state quencher, nitrobenzoic acid (NBA), is included to shorten the time fluorophores can reside in the dark triplet state (Dave et al., 2009). 1. Incubate DNA polymerase carrying an N-terminal biotin-tag (Beckett et al., 1999) with 1.5 molar excess of primed DNA template at 4 C for 10 min in a buffer containing 50 mM MOPS, pH 7.5, 75 mM potassium acetate, 5 mM dithiothreitol and 0.05% (v/v) Tween-20. 2. Simultaneously, incubate streptavidin (Invitrogen) at a twofold stoichiometric excess over polymerase in the same buffer at 22 C on the ZMW array. Wash the array five times with buffer.

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3. Immobilize polymerase/template complexes onto the arrays at 4 C for 15 min. Remove unbound complexes by washing five times with reaction buffer (50 mM ACES, pH 7.1, 75 mM potassium acetate, and 5 mM dithiothreitol). 4. Add the oxygen scavenging system (1 PCD, 4 mM PCA), triplet state quencher (6 mM NBA (all Sigma-Aldrich, St. Louis, MO), and all phospholinked dNTPs (250 nM final concentration each), except the one corresponding to the first base to be incorporated into the DNA template. 5. Initiate the sequencing reactions by simultaneous addition of the first phospholinked dNTP to be incorporated (250 nM) and manganese acetate (0.5 mM final concentration) (Korlach et al., 2008a; Kumar et al., 2005).

3.7. Data analysis Fluorescence pulse calling is performed by a threshold algorithm on the dye-weighted intensities using fluorescence emission calibration spectra for each of the phospholinked dNTPs (Horne, 1986). For base identification, light collected by the detector is summed over the duration of the pulse, allowing each fluorescent phospholinked nucleotide to be spectrally evaluated and classified. Automated classification is performed by least-squares fitting to the four known dye reference spectra. The spectrum that yields the minimum chi-squared difference when compared to the pulse spectrum identifies the pulse as a particular phospholinked dNTP. The degree of spectral cross talk between different fluorophore types depends on the specific dyes chosen and their intrinsic brightness. A typical set of dyes we have used in conjunction with SMRT DNA sequencing, with spectral separation between the emission maxima of the pairs of dyes excited with the same laser of 31 and 23 nm, respectively, showed misidentification rates of less than 1% using this method (Eid et al., 2009). A section of a typical sequencing read after such automated base calling is shown in Fig. 20.5A. DNA polymerase activity is marked by a train of pulses corresponding to phospholinked nucleotide incorporations. Incorporation signals from the four phospholinked nucleotides show fluorescence intensity ‘‘level setting’’ characteristics which are due to (i) the stationary location of the enzyme’s active site with respect to the illumination profile, and (ii) different excitation efficiencies and intrinsic fluorophore brightness of the four fluorescent dyes. High detector frame rates (e.g., 100 Hz; Eid et al., 2009) ensure that enzymatic turnovers are oversampled in time, allowing precise measurements

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Figure 20.5 SMRT DNA sequencing example. (A) Four-color time trace of dyeweighted fluorescence intensities with automated base annotations, along with definitions of pulse width (PW) and interpulse duration (IPD). While significant spectral overlap can be present from two dyes excited by one laser, its magnitude is known from the dye reference spectra and thus it does not affect misidentification rates. (B) Generalized enzymatic reaction cycle of DNA polymerization, with the red rectangle differentiating the steps which constitute the ‘‘bright’’ (PW) state. E: polymerase enzyme; D: DNA template; N: nucleotide.

of ‘‘on’’ and ‘‘off’’ times. The pulses exhibit stochastic intensity fluctuations because of counting statistics and dye photophysics. Hallmarks of singlemolecule fluorescent events are characteristic: single-frame rise and fall times at the start and end of the pulse, respectively ( 10 ms), which facilitate pulse detection and base calling even when pulses are close together. Single-molecule events corresponding to phospholinked dNTP incorporations manifest as fluorescent pulses whose variable duration and spacing directly reflect the underlying enzyme kinetics. In the generalized enzymatic DNA polymerization cycle (Fig. 20.5B), kinetic steps starting with phospholinked nucleotide binding, then proceeding through the transition from the ‘‘open’’ to the ‘‘closed’’ polymerase conformation, catalysis, reverse conformational transition, and up to the moment of pyrophosphate-linkerfluorophore release, have the nucleotide bound in the active site and thereby

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make up the duration of the fluorescence pulse (defined hereafter as pulse width (PW)). The time elapsing after release of the reaction product, translocation of the polymerase along the template by one base, and waiting time for the binding of the next incoming phospholinked nucleotide constitute the duration between successive pulses (interpulse duration (IPD)).

4. Single-Molecule DNA Polymerase Dynamics While the base sequence of the synthesized DNA strand constitutes the main output of the SMRT sequencing method, the real-time aspect of this approach generates unprecedented information about DNA polymerase kinetics. Because the system reports the kinetics of every base incorporation through PW and IPD, it can be used to investigate the dynamics of DNA polymerization with base-pair resolution, and to provide the distribution of kinetic parameters over many different sequence contexts in a single 5-min experiment. The method thereby allows direct assessments of static variation (differences in enzymatic activity between different molecules) and dynamic variation (fluctuation of catalytic rate constants over time for a single enzyme molecule).

4.1. Determination of single-molecule kinetic parameters From the multitude of nucleotide incorporations recorded for single DNA polymerases during a SMRT sequencing read, it is possible to determine effective kinetic parameters for each enzyme molecule. For certain polymerases and reaction conditions, a simplified model can successfully be used for which single steps limit the rates of transitions between the ‘‘bright’’ and ‘‘dark’’ states, as defined above (Fig. 20.5B). In this case, the kinetic cycle of DNA synthesis reduces to k1

k2

N þ E : D > E : D : N ! E : Dþ1 k1

with the ternary complex of enzyme, DNA, and nucleotide (E:D:N) now denoting all states for which the phospholinked nucleotide is bound in the active site. Here, the average fluorescence PW is determined by the summation of kinetic steps exiting the ‘‘bright’’ state PW ¼

1 1 ¼ kPW ðk2 þ k1 Þ

ð20:1Þ


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The IPD is governed by the combination of DNA polymerase translocation along the template and time to binding of the next nucleotide. For enzymes with fast translocation kinetics relative to nucleotide binding (e.g., below nucleotide substrate saturation concentrations), the latter becomes rate-limiting, and the average IPD is then given by IPD ¼

1 1 ¼ kIPD k1 ½N

ð20:2Þ

The two expressions are combined to yield a measurement of the Km for a single polymerase molecule from measured average PWs and IPDs: Km ¼

ðk2 þ k1 Þ IPD ¼ ½N k1 PW

ð20:3Þ

Base-specific Km values determined in this way for a 10-min, 2.4-kb sequencing read are depicted in Fig. 20.6. The single-exponential fits to the PW and IPD histograms indicate that this simplified, single rate-limiting kinetic model is a good approximation for the DNA polymerase employed in this experiment. Km values for this molecule are in good agreement with bulk data measuring the transient kinetics of single nucleotide turnovers using a stopped-flow instrument (KinTek), except for dTTP which has a lower Km for the single polymerase by a factor of 2.

4.2. DNA polymerase pausing The above-mentioned analysis does not account for transient changes in DNA polymerization dynamics during the course of DNA synthesis for a single enzyme. While the validity of the Michaelis–Menten equation has been demonstrated theoretically and experimentally in the presence of such dynamic variation (English et al., 2006; Kou et al., 2005; Min et al., 2006; Velonia et al., 2005), the extracted parameters do not inform about it, so a more detailed analysis is needed. DNA polymerases present a more complex case compared to other, single-substrate turnover enzymes, as there are four different nucleotides competing for one active site, several different enzymatic activities are possible in one protein, and the sequence of the DNA template introduces a large number of different sequence contexts. A detailed description of these phenomena is beyond the scope of this chapter, and only a few examples illustrating the richness of these singlemolecule data are given here. We have previously described polymerase pausing caused by hairpin formation in single-stranded DNA templates (Eid et al., 2009). Here, we extend our analysis to double-stranded DNA templates several hundred

Phospholinked nucleotide

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Figure 20.6 Determination of effective Km values from a SMRT sequencing read. Distributions from a 10-min, 2.4-kb read for pulse widths of, and interpulse duration before each of the four phospholinked nucleotides are fit to single exponential decay functions used to derive Km values (Eq. (20.3)). Values are compared to bulk measurements of single-turnover kinetics (gray).


449

bases in length, in conjunction with DNA strand displacement synthesis carried out by the polymerase. While double-stranded DNA is characterized by dramatically less secondary structure in comparison with singlestranded DNA, there still remains a degree of higher order structure due to different sequence contexts (Gimenes et al., 2008; Hagerman, 1990). In addition, the dynamics of strand displacement activity of the polymerase, separating the nontemplate strand from the template strand before its entry into the polymerase active site, is also likely influencing DNA polymerization rates (Kamtekar et al., 2004; Rodriguez et al., 2005). Single-molecule sequencing trajectories of template position over time allow a detailed view into polymerase-mediated DNA synthesis dynamics (Fig. 20.7). Variations in polymerization rates are apparent with respect to heterogeneity among different molecules for a given template position, allowing the creation of instantaneous rate distributions for every template position when analyzed over all molecules. Template sequence context effects over many time scales are apparent. For the specific example shown in Fig. 20.7A, the DNA synthesis rate roughly doubles after incorporation of 250 nucleotides. Analyzed over shorter time scales, a range of interpulse distances is observed, including occurrences of cessation of DNA synthesis activity on a time scale of many seconds, followed by resumption of DNA synthesis. Such polymerase pausing is specific to certain DNA template locations where it is common to several molecules (Fig. 20.7A, arrows). To rule out that such variations are caused by systematic effects of the instrumentation or reaction conditions, and instead represent dynamic changes of DNA polymerization caused by different DNA template sequence contexts, circular DNA templates can be employed (Eid et al., 2009). In this configuration, polymerases capable of strand displacement synthesis, such as f29 DNA polymerase (Blanco et al., 1989), will encounter the same DNA sequence on a template molecule multiple times. DNA synthesis trajectories encompassing multiple rounds of circular template sequencing (Fig. 20.7B) show that polymerases repeat the dynamic signatures upon consecutive encounters of the same DNA template sequence context. For example, the transition to the faster overall rate at around 250 nucleotides into the template (described above) can be discerned for each round of synthesis. Similarly, polymerase pausing occurs at the same DNA template site during each round of synthesis, albeit with variable IPDs (Fig. 20.7B, lower right panel, arrows). To within the resolution of the data in this experiment, the correlation between IPDs of the same sequence context in different molecules was the same as between different laps around the circular template carried out by the same molecule. IPD profiles from several hundred polymerases for multiple laps illustrate these phenomena further (Fig. 20.7C), showing the slower rate for the first half of the template due to overall increased IPDs, and highlighting template locations of increased pausing frequencies.

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ATTTAAAGATT AGATAAATGGA TGTTAAACAGT xxxxAAAxxxx TAGTAAACCCT TTACAAACACC

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CTACAGGTTTG ATACGGGTAAA xxACxGxTxxx AGACTGTTTAA

Figure 20.7 SMRT DNA synthesis dynamics. (A) DNA synthesis trajectories of template position over time for 33 polymerase molecules. The two dashed lines illustrate a transition to higher polymerization rates occurring at 250 bases into the DNA template. Arrows indicate common sites in the DNA template at which pausing occurs for several enzyme molecules. (B) Polymerization trajectories for four DNA polymerase molecules on circular DNA templates, showing multiple laps of continuous, processive DNA synthesis. The white dotted line indicates the same template position as in (A) where the speed transition occurs. Arrows in the lower right panel show an example of template locations at which the polymerase molecule pauses during each round of synthesis. (C) 90th percentile of the IPD versus template position for several hundred polymerases sequencing two successive laps around a circular DNA template. The arrows indicate the pause sites for which the sequences and consensus contexts (D) are given.

Analysis of DNA sequences for these pauses indicate common, relatively short consensus sequence contexts (Fig. 20.7D) which we have confirmed using templates from different sources (data not shown). While the mechanism and biological significance of these pausing signatures remains to be elucidated, the ‘‘AAA’’ sequence is reminiscent of the initiation mechanism by f29 DNA polymerase (characterized by multiple dATP incorporations and sliding-back movements; Mendez et al., 1992). We speculate that perhaps the polymerase has an increased propensity for slippage in this template sequence context, creating the pause signature before DNA synthesis resumes.

451


5. Conclusions SMRT DNA sequencing harnesses the intrinsic power of DNA polymerases, allowing their speed, processivity, efficiency, and fidelity to be exploited directly. Rapid intrinsic DNA synthesis rates translate to short sequencing run cycle times. Long continuous sequence reads preserve the molecular integrity of the DNA template, simplifying the downstream bioinformatics for genome assembly and analysis in the context of structural variations and allelic polymorphism linkages. Many sequencing-by-synthesis techniques employ DNA polymerase as a bulk reagent consumable, synchronizing its activity with various termination approaches (reviewed in Mardis, 2008). Such gating allows for an increase in multiplex and overall sequence throughput, but comes at a cost of long singlebase cycle times and relatively short read lengths due to incomplete cycle efficiencies. These methods utilize uniform protocols for each incorporation cycle and are therefore insensitive to sequence context effects on polymerization efficiencies, leading to variable systematic errors (Kong, 2009) and even inaccessible genomic regions. In contrast, sequencing by observing uninterrupted DNA polymerization allows the enzyme to spend variable amounts of

120 100

Frequency

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1 2 3 4 5 6 7 Instantaneous DNA synthesis rate (bases/s)

8

Figure 20.8 DNA polymerization rate variations over different sequence contexts. In this example, SMRT sequencing reads were recorded from 128 polymerase molecules. Instantaneous DNA synthesis rates for each position of the 1.1 kb DNA template were extracted for each molecule. Mean values from the rate distributions at each template position are used for the histogram. The coefficient of variation of DNA synthesis rate for this template is 70%.

452


time synthesizing different sequence contexts. Even when analyzed over many polymerase molecules, significant variation of DNA synthesis rates exists for different DNA template positions (Fig. 20.8). This dispersion of DNA synthesis rates as a function of sequence context suggests that in an ensemble sequencing-by-synthesis system, the ideal protocol for incorporation should vary by that same amount. This requirement is moot in a single-molecule, realtime method, as every incorporation is allowed precisely the correct amount of time, thus providing an intrinsic adjustment and optimal sequencing performance in every sequence context. Heterogeneities between enzymes (static variation) or in the catalytic rates for a single enzyme molecule (dynamic variation) have been observed for many enzymes (reviewed in Blank et al., 2009), and DNA polymerases are no exception. The information can be used advantageously to improve the quality of sequencing, and at the same time provide insights into the dynamics of DNA polymerization. Because polymerase kinetics is sensitive to biological perturbation, this information can be further developed for investigating DNA binding proteins, DNA polymerase inhibitors, and effects of base methylation.

ACKNOWLEDGMENTS We are indebted to the entire staff at Pacific Biosciences for their dedicated work that brings this technology to fruition. We also thank J. Puglisi, M. Hunkapiller, R. Kornberg, K. Johnson, D. Haussler, W. Webb, and H. Craighead for many helpful discussions. Aspects of this research were supported by National Human Genome Research Institute grant R01HG003710.

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Author Index

A Abelson, J., 31–40, 155, 156, 160, 162, 163, 170, 172–174 Aguzzi, A., 191 Ahn, K., 72, 73 Ainger, K., 391 Aitken, C. E., 78, 155, 443 Akiyama, B. M., 214 Alami, M., 91 Albright, L. M., 233 Alexeev, A., 264 Altschul, S. F., 243 Ames, B. N., 236 Amir, D., 188 Amirgoulova, E. V., 14 Amitani, I., 261–288, 308 Anderson, C. M., 397–398 Anderson, D. G., 264 Anderson, J. R., 121 Anna, S. L., 68 Antoun, A., 231 Aoki, H., 254 Arai, Y., 69 Ashkin, A., 69, 70 Atkinson, D., 91 Atkins, W. M., 89–112 Axelrod, D., 95, 139, 294–295, 388 B Baas, B., 97 Baba, T., 244 Bacia, K., 135, 186, 318 Bai, Y., 209 Baker, S., 92 Banci, L., 42, 51 Baner, J., 440 Barak, L. S., 388 Barrios-Rodiles, M., 134 Bartley, L. E., 216 Baruah, H., 20 Baskin, R. J., 261–288 Bastiaens, P. I., 242 Bateman, A., 160 Bauch, A., 134 Baum, D. A., 214 Bayburt, T. H., 90, 94 Beach, D. L., 389

Becker, W., 321–322 Beckett, D., 441, 443 Beer, N. R., 64 Benitez, J. J., 41–59 Benson, F. E., 264 Berland, K. M., 347 Bernard, A., 140 Bernath, K., 63 Bertozzi, C. R., 20, 21 Bertrand, E., 388–390, 392 Bianco, P. R., 262–265, 271, 281 Binkert, T., 328 Blair, S., 435 Blanchard, S., 91 Blanchard, S. C., 224, 226, 250, 252, 253 Blanco, L., 432, 440, 449 Blanco, M., 39, 153–176 Blank, K., 452 Block, S. M., 69, 70, 274, 278 Bobroff, N., 394 Bochner, B. R., 236 Bokinsky, G., 160, 161 Boldog, T., 91, 94 Bolen, D. W., 194 Bopp, M. A., 62 Borbat, P., 110 Bornholdt, S., 136 Boukobza, E., 43, 45, 47, 62, 214 Bowers, J., 409, 410 Boxer, S. G., 47, 297 Brameshuber, M., 133–148 Brandi, L., 236 Bratu, D. P., 391 Brau, R. R., 76 Breinbauer, R., 20 Brent, R., 229 Brewer, L. R., 262, 271 Brian, A. A., 47 Broder, Y. C., 135 Brody, J. P., 63 Bronson, J. E., 161, 163, 164, 167, 168 Brucale, M., 181, 200 Brundin, P., 110 Brunger, A., 96 Brustad, E. M., 188, 189 Bussell, R. Jr., 110, 195 Buxbaum, A. R., 387–403

457

458

Author Index C

Cai, L., 120 Cammack, K. A., 226 Campbell, M. J., 264 Caraculacu, A. A., 4 Carbon, J., 249, 250 Carignano, M. A., 3 Cavalcanti-Adam, E. A., 137 Celliers, P. M., 276 Chakrabarti, A. C., 58 Chakraborty, A., 19–28 Chambliss, G. H., 225 Chandra, S., 110 Chang, P. V., 20, 21 Chao, J. A., 392–393 Chartrand, P., 391 Chatterji, D., 437 Cheezum, M. K., 396–397 Chen, P., 41–59 Chen, Y., 345–361 Chen, Z., 264 Chiantia, S., 326 Chin, J. W., 21 Chiou, P. Y., 72 Chiu, D. T., 43 Cho, S. K., 72 Chugh, D., 72 Churchman, L. S., 395 Cianci, G. C., 360 Cisse, I., 43, 58 Clamme, J. P., 198 Clemens, M. J., 254 Cloonan, N., 432 Cobine, P. A., 42, 51 Cohen, A. E., 120 Cohen, H. M., 63 Cokus, S. J., 432 Condeelis, J., 388 Conia, J., 276 Conway, A. B., 264 Cookson, M., 109 Cooper, M., 21 Cormack, B. P., 81 Coseri, S., 4 Courtois, F., 64 Cremer, P. S., 297 Crick, S. L., 186 Crocker, J. C., 398 Cross, A. J., 80 Cruz, J. A., 206 Cui, B. X., 120 Curtis, J. E., 71 D Das, R., 206, 209 Datsenko, K. A., 244 Dave, R., 443

David, H., 249, 250 Davidich, M. I., 136 Davidson, W. S., 110, 195 Davis, R. W., 264 Daviter, T., 224 Davydov, D., 94, 97, 98 Dawson, P. E., 188, 190 Deamer, D. W., 58 Dean, F. B., 440 De Brabander, M., 388, 391 Deiters, A., 21 DeLano, W., 243 Denisov, I., 92, 94, 97, 98, 110 Deniz, A. A., 179–200 Denk, W., 347 Dertinger, T., 319, 325, 339–340 Desai, K. V., 83 de Vega, M., 440 Dickson, R. M., 62 Dictenberg, J. B., 402 Diez, M., 96 Digman, M. A., 135, 319, 323, 326, 347 Dillingham, M. S., 264 Dincbas-Renqvist, V., 232 Dirksen, A., 190 Dittrich, P. S., 64 Ditzler, M. A., 156, 160, 161, 217 Dixon, D. A., 264 Dohm, J. C., 416 Doi, N., 63 Dombrowski, C. C., 261–288 Dorsch, S., 136 Dorywalska, M., 214, 244 Douglas, J. F., 3 Draper, D. E., 206, 209 Drescher, M., 110 Dressman, D., 64 Dube, D. H., 20 Dubnoff, J. S., 227 Duckworth, B. P., 354 Dunker, A. K., 180 Dyson, H. J., 180 E Eaton, W. A., 180 Eberhard, M., 73 Ebright, R. H., 19–28 Ebright, Y. W., 19–28 Eddy, S. R., 160 Edidin, M., 391 Egea, P. F., 348 Eggeling, C., 393 Ehrenberg, M., 225 Eid, J., 433, 436, 440, 444, 447, 449 Eidne, K. A., 135 Einstein, A., 388 Elad, M., 102 Elbing, K., 229

459

Author Index

Elenko, M. P., 217 Eliezer, D., 110, 195 Elson, E. L., 318, 323, 330, 346, 359 Elvekrog, M. M., 221–254 Enderlein, J., 318, 350 Englander, M. T., 221–254 Englander, S. W., 78 English, B. P., 447 Ephrussi, A., 388 Ermolenko, D. N., 249 Erne, P., 73 Esteban, J. A., 432, 440 F Falke, J., 96 Farina, K. L., 392 Fazio, T., 293–314 Feder, T. J., 400 Fei, J., 221–254 Femino, A. M., 366, 373, 384 Fernando, H., 97 Ferreon, A. C., 96, 110, 179–200 Ferri, F., 329 Fields, S., 135 Field, Y., 310–311 Fiore, J. L., 156, 161 Fleming, G. R., 82 Fleury, S., 143 Fogarty, K., 120 Foquet, M., 433, 435 Forchhammer, K., 254 Forkey, J. N., 295 Fo¨rster, T., 11 Fourmy, D., 227 Frank, J., 222, 224, 253 Fredrick, K., 237 Freistroffer, D. V., 239 Fullwood, M. J., 432 Funatsu, T., 391 Fusco, D., 388–389, 392–394, 400, 402 G Gahagan, K. T., 71 Gallagher, S. R., 225, 230, 231 Galletto, R., 262, 264, 269, 286 Gall, J. G., 366 Gambin, Y., 179–200 Gao, F., 102, 105 Garcıá-Saéz, A. J., 96, 341 Garstecki, P., 68 Gasteier, P., 2, 3, 6 Gauchet, C., 20 Gautier, I., 349 Gell, C., 95 Gelles, J., 397 George, J., 110 Georgieva, E. R., 110, 198

Ghadessy, F. J., 64–66 Ghosh, I., 135 Ghosh, R. N., 397–398 Gill, S. C., 27 Gimenes, F., 449 Goedert, M., 109 Goetz, H., 4 Goldberg, R. B., 244 Golding, I., 368 Goldner, L. S., 61–83 Gonzalez, R. L., 221–254 Gopal, V., 437 Gorman, J., 293–314 Gragerov, A., 42 Grakoui, A., 148 Grane´li, A., 294, 297–298, 307 Gratton, E., 388 Greene, E. C., 293–314 Greenfeld, M., 205–218 Gregor, I., 350 Grier, D. G., 398 Griffiths, A. D., 63, 64 Grilley, D., 209 Grinkova, Y., 94 Groll, J., 1–16 Groves, J. T., 297 Grunwald, D., 392, 395, 401 Guengerich, F., 97, 98 Guthrie, C., 31–40 Guttenberg, Z., 72 H Haas, E., 188 Hadjivassiliou, H., 31–40 Hagerman, P. J., 449 Hall, A., 42 Halperin, A., 2 Halpert, J., 97, 98 Hamadani, K. M., 198 Handa, N., 262, 264, 268, 281, 286 Hangauer, M. J., 20, 21 Hang, H. C., 20 Hapke, B., 226 Haran, G., 43, 165 Haran, G., 193 Harder, P., 3 Harriman, P. D., 244 Harris, J. M., 2, 3 Harris, L. J., 130 Harris, T. D., 408–410 Hart, C., 407–429 Hartz, D., 233, 235–237 Haselgru¨bler, T., 133–148 Hase, M., 70 Ha, T., 21, 62, 154, 182, 206, 215, 222, 295 Haugland, R. P., 11, 182 Haupts, U., 353 Hayden, E., 408

460

Author Index

Hebda, J., 106 Hebert, B., 324 Heid, C. A., 64 Heikal, A. A., 82 Heise, B., 133–148 Helenius, A., 195 He, M. Y., 68 Hendler, R., 102 Hendrix, J., 354 Henzler-Wildman, K., 91 Hermanson, G. T., 441 Herschlag, D., 205–218 Hesch, C., 133–148 Hesse, J., 139, 148 Heurgue-Hamard, V., 232 Heyer, W. D., 264 Heyes, C. D., 5, 15, 16 Hilario, J., 262, 264, 266, 269, 270, 284–286, 288 Hillesheim, L. N., 350, 353–354, 357 Hinnebusch, A. G., 254 Hinz, H. J., 195 Hirokawa, G., 241 Hoard, D. E., 438 Ho, C. K., 36 Hodak, J. H., 214 Hoffmann, A., 229 Hogrefe, H. H., 15 Hohng, S., 198, 242 Holzen, T. M., 264 Hope, M. J., 46, 47 Horne, K., 444 Huang, B., 125 Huang, Z., 217 Hu, C. D., 135 Hu, D., 82 Huebner, A., 65, 83 Huffman, D. L., 42, 51 Humenik, M., 20 I Irvine, D. J., 3 Isacoff, E., 102 Ishihama, Y., 391 Ishii, Y., 155 Isin, E., 98 J Jacobson, K., 388 Jager, M., 188 Ja¨hne, B., 399 Jakes, R., 193 Jao, C., 110 Jaqaman, K., 399 Jares-Erijman, E. A., 135 Jelenc, P. C., 225 Jencks, W. P., 207 Jensen, P. H., 195

Jia, Y. W., 62 Jo, E., 110, 195 Jofre, A. M., 61–83 Johnson, J. M., 46, 345–361 Jones, E., 104 Jones, T. B., 72 Joo, C., 171, 180, 210, 215 Jorgenson, J. W., 124 Joseph, S., 237, 238 Jovin, T. M., 135, 242 K Kadokura, M., 438, 439 Kahvejian, A., 408 Kaler, K., 72 Kaltenbrunner, M., 133–148 Kamtekar, S., 449 Kanaya, S., 15 Kane, R. S., 139 Kao, H. P., 396 Kapanidis, A. N., 21, 155, 185 Kaplan, N., 310 Kapp, L. D., 254 Karstens, T., 276 Kask, P., 359 Kato, H., 278, 279 Katsura, S., 70 Keller, A. M., 41–59 Keller, R. A., 120 Kelly, B. T., 63, 64 Kent, S. B., 188 Kiick, K. L., 20, 21 Kijac, A., 94 Kim, B.-E., 42, 51 Kim, P. W., 147 Kim, S. A., 119–131, 318 Kingshott, P., 3 Kiss, M. M., 64 Klein, H. L., 264 Knight, J., 96, 106, 108, 109 Knowles, R. B., 391 Kobs, K., 276 Kochaniak, A., 308 Kohn, M., 20 Kong, Y., 451 Koo, P., 89–112 Koopmans, W. J. A., 9, 10, 12 Korennykh, A. V., 217 Korlach, J., 431–452 Korostelev, A., 242 Korsmeyer, T., 72 Koshland, D., 97 Kotani, N., 135 Koumoutsakos, P., 399 Kou, S. C., 447 Kowalczykowski, S. C., 261–288 Kozuka, J., 96 Kress, B., 442

461

Author Index

Krieg, U. C., 21 Krishnan, R., 191 Kruger, R., 193 Kumaresan, P., 64 Kumar, S., 437, 444 Kusumi, A., 388, 391, 400 Kuszak, A., 91 Kuzmenkina, E. V., 14 L Lakowicz, J. R., 95, 243, 348–349 Lampe, J., 98 Lang, P., 148 Larson, D. R., 366 Laughlin, S. T., 20 Laurence, T. A., 43 Lawrence, J. B., 388 Lawrence, R., 161 Leamon, J. H., 63 64 Lee, A. I., 63 Lee, J. Y., 43 Lee, N. K., 185, 198 Lee, T. H., 160, 224 Legler, D. F., 139 Lehner, M., 133–148 Leitz, A., 94 Lemieux, G. A., 21 Lemke, E. A., 198 Leung, W.-Y., 21 Levene, M. J., 43, 433, 435 Levitus, M., 96, 181 Levi, V., 388, 396 Levsky, J. M., 366 Li, G., 12 Li, H. T., 191 Li, L., 161, 163 Liljas, A., 222 Lindquist, S. L., 191 Lingwood, D., 339 Ling, Y., 106 Link, A. J., 20 Link, D. R., 68 Lin, M. Z., 139 Lin, R. J., 32 Li, P., 206 Lipman, E. A., 120, 198 Lipson, D., 407–429 Li, Q. J., 136, 146 Liu, B., 261–288 Liu, C., 236 Liu, S., 160 Liu, Y., 276, 435 Li, W., 224 Lorenz, R. M., 69, 71 Lorsch, J. R., 254 Lotharius, J., 110 Lu, H. P., 62, 82, 91 Lukacs, K. D., 124

Lundquist, P. M., 442, 443 Luo, J. K., 71, 72 Luo, Y., 129 Lutsenko, S., 42, 51 M Maamar, H., 366 Maar, D., 236 Macdonald, P., 345–361 MacDonald, R. C., 46, 47 MacDougall, D. D., 221–254 Magatti, D., 329, 339 Magde, D., 95, 184, 346 Maher, C. A., 432 Maheshri, N., 366 Maheshwari, G., 4 Malik, N. A., 398 Malmsten, M., 3 Mammen, M., 208 Mardis, E. R., 432, 451 Margulies, M., 64 Marshall, R. A., 222, 224, 244, 253 Martin, K. C., 388 Mason, T. G., 65 Maurel, D., 135 Mazin, A. V., 264 MCnnell, H. M., 47 McIntosh, T. J., 137 McKenna, S. A., 225, 226 McKinney, S. A., 160, 161, 163, 171, 216 McPherson, T., 3 Melin, J., 122 Mendez, J., 450 Meyrueis, P., 442 Michalet, X., 154, 180, 181, 183 Milligan, J. F., 225, 226 Milos, P. M., 407–429 Mingle, L. A., 402 Min, W., 156, 447 Miranker, A. D., 89–112 Mishra, R., 106 Miyake, T., 435 Modesti, M., 264 Moeller, M., 1–16 Moerner, W. E., 120, 180 Mohr, D., 237, 254 Monnard, P.-A., 58 Monod, J., 97 Moore, D. D., 234 Moore, S., 244 Mora, L., 232 Moran, C. R., 179–200 Morrissey, J., 91, 94 Mossman, K. D., 137 Mueller, J. D. 345–361 Muir, T. W., 190 Mukhopadhyay, S., 181, 183, 185, 186, 191–193, 197

462

Author Index

Mulder, B. A., 437 Muller, B., 328, 341 Mu¨ller, J. D., 357, 359, 361 Munro, J. B., 157, 163, 175, 253 Murakoshi, H., 96 Muralidharan, V., 190 Musyanovych, A., 64–66 N Nakano, M., 64 Nanga, R., 106 Nath, A., 89–112 Neher, E., 163 Nelson, J. R., 440 Neuman, K. C., 69, 70, 274, 278 Ngo, J. T., 20 Nguyen, D. P., 21 Nilsson, J., 441 Nimonkar, A. V., 262, 264, 268, 283, 288, 308 Nirmal, M., 391 Noji, H., 62 Noller, H. F., 206, 226, 237, 238 Noll, H., 226 Nooren, I. M.A., 42 O Odom, O. W., 249 Ogawa, T., 264 Ogle, J. M., 224 O’Halloran, T. V., 42, 51 O’Hare, H. M., 139 Ohashi, R., 91 Ohno, S., 21 Okamoto, K., 158 Okumus, B., 43, 45, 48, 49, 62, 214 Orrit, M., 180 Orte, A., 185 Orth, R. N., 137 O’Shea, E. K., 366 Oshlack, A., 424 Ott, D. G., 438 Ozdemir, P., 64 Ozsolak, F., 407–429 P Paar, C., 133–148 Pace, C. N., 194 Palmer, A. G. D., 346, 359 Palo, K., 353, 359 Panchunk-Voloshina, N., 21 Papin, J. A., 134 Park, H. Y., 91, 387–403 Park, S.-Y., 72 Paster, W., 133–148 Pathak, S., 308 Patino, M. M., 191

Pavlov, M. Y., 225 Pederson, T., 391 Pereira, M. J. B., 154, 163, 165, 171, 214 Perrin, J., 388 Perroud, T. D., 128 Peske, F., 241 Peterman, E., 91 Peterman, E. J. G., 276 Petersen, N. O., 347 Petra´ˇsek, Z., 317–341 Petrov, E. P., 321 Petruschke, R., 98 Petukhova, G., 264 Pfeifle, C., 366 Pfleger, K. D., 135 Pleiss, J. A., 33, 34 Plumbridge, J. A., 250 Politz, J. C. R., 401 Pollack, M. G., 72 Polymenidou, M., 191 Polymeropoulos, M. H., 193 Poritz, A. B., 160 Powers, T., 226 Prasad, T. K., 264, 306–309 Prentice, P. A., 71 Prescher, J. A., 20 Priest, C., 73 Protter, M., 102 Puig, O., 134 Pulukkunat, D. K., 221–254 Pushkarev, D., 408, 410, 418, 420 Q Qian, H., 346, 359, 394 Qin, F., 161, 163 Qin, Y., 254 Quake, S. R., 122 Querido, E., 391 R Raap, A. K., 366 Rabiner, A., 161 Raj, A., 365–385 Raleigh, E. A., 229 Ramakrishnan, V., 224 Ramm, P., 148 Rasnik, I., 48, 50, 78, 393, 395 Raz, T., 407–429 Recht, M. I., 226 Reid, D. B., 399 Reiner, J. E., 62, 65, 70, 71, 73, 79, 80 Reynolds, J. A., 195 Rhoades, E., 43, 89–112, 181 Ries, J., 317–341 Rigler, R., 318, 323, 330 Rigneault, H., 435 Ricˇka, J., 328

463

Author Index

Ritchie, T., 90, 92, 93 Robberson, D. L., 264 Roberts, A., 98 Robertson, J. M., 226 Robertson, R. B., 264 Rodriguez, A. J., 391 Rodriguez, I., 449 Roeder, R. G., 229 Roman, L. J., 264 Romano, V., 276, 279 Rook, M. S., 390, 402 Rosato, A., 42, 51 Rosenzweig, A. C., 42, 51 Rosgen, J., 195 Rotman, B., 63 Roy, R., 21, 95, 155–157, 181, 183, 185, 213, 215, 222 Ruan, Q., 319, 337 Rueda, D., 160, 161 S Saffarian, S., 353 Sage, D., 399 Sakmann, B., 163 Salas, M., 440 Sanchez, S., 92 Sandal, M., 181, 200 Santangelo, P. J., 391 Sasaki, K., 71 Sasse, J., 230 Satsoura, D., 324 Sattin, B., 206, 210, 214–218 Sauer, R. T., 244 Saxon, E., 20, 21 Saxton, M. J., 388, 394 Sbalzarini, I. F., 399 Schaffer, J., 82 Scha¨tzel, K., 327, 329 Schatz, P. J., 268 Schlageck, J. G., 437 Schlapak, R., 141 Schmitt, E., 227, 228 Schneider, R. J., 254 Schuette, J. C., 224 Schuler, B., 180, 181, 183, 193 Schultz, P. G., 188 Schuster–Bo¨ckler, B., 160 Schu¨tz, G. J., 133–148, 388, 401 Schuwirth, B. S., 242 Schwartz, J. A., 72 Schwarzenbacher, M., 133–148 Schwille, P., 96, 135, 186, 317–341, 350, 353 Segrest, J., 91, 93 Selmer, M., 223 Serge, A., 399 Serio, T. R., 191 Seshadri, A., 241 Shan, J. G., 391

Sharon, R., 195 Shastry, M. C.R., 73 Shav-Tal, Y., 388, 390, 392, 394, 401 Shaw, A., 94 Sheetz, M. P., 391 Sherman, E., 193 Shimizu, Y., 227 Shinohara, M., 264 Shorter, J., 191 Shrager, R., 102 Shuman, S., 36 Siebrasse, J. P., 401 Silverman, S. K., 214 Silvius, J. R., 45 Simonian, M. H., 230 Simon, S. A., 137 Singer, D., 366 Singer, R. H., 387–403 Skinner, J. P., 323, 332, 335 Slatko, B. E., 233 Sletten, E. M., 20 Sligar, S., 90 Small, D., 91 Smith, A. M., 391 Smith, G. J., 214 Smith, G. R., 264 Smith, J. A., 230 Soderberg, O., 136 Sofia, S. J., 3 Solans, C., 65 Solinger, J. A., 264 Solomatin, S. V., 214, 217 Sonenberg, N., 254 Song, H., 63, 64, 68 Song, L., 58 Song, O., 135 Sonnleitner, A., 133–148 Sood, A., 437, 440 Spahn, C. M., 254 Speidel, M., 396 Spies, M., 262, 264, 281 Spillantini, M. G., 193 Spudich, J. A., 395 Stagljar, I., 135 Stark, H., 224 Stark, M. R., 36 Stasiak, A., 264 St. Claire, R. L., 124 Steinmann, K., 407–429 Sternberg, S. H., 221–254 Stockinger, H., 133–148 Stone, M. D., 214 Strausak, D., 42, 51 Striker, G., 82 Stryer, L., 11, 154, 182 Subramanian, M., 97 Suchanek, M., 135 Sugiura, S., 69 Sundell, C. L., 402

464

Author Index

Sung, P., 264 Sunzenauer, S., 133–148 Superti-Furga, G., 134 Suzuki, K. G., 148 Svoboda, K., 69, 70 Swaminathan, R., 82 Swartzlander, G. A., 71 Szleifer, I., 3 T Tabor, S., 432 Tada, H., 72 Takamoto, K., 212 Talaga, D. S., 62, 162 Taly, V., 63, 64 Tanaka, M., 137 Tan, E., 214 Tanford, C., 195 Tang, J., 61–83 Tautz, D., 366 Tawfik, D. S., 63, 64 Taylor, A. F., 264 Tcherniak, A., 319, 323 Terabe, S., 125 Terazima, M., 158 Thews, E., 328, 341 Thompson, J. D., 243, 407–429 Thompson, N. L., 346 Thompson, R. E., 397 Thornton, J. M., 42 Thorsen, T., 68 Thummel, K., 96 Tirrell, D. A., 20 Tompa, P., 180 Toprak, E., 396 Torres, T., 96, 181, 186, 197 Trexler, A. J., 89–112, 181, 183, 198 Tsalkova, T., 98 Tsao, M. L., 21 Tyagi, S., 365–385, 391 U Ueda, K., 109 Uetz, P., 135 Ulbrich, M., 102 Ulmer, T. S., 110, 196 Umbanhowar, P. B., 69 Unger, M. A., 121 Unsworth, L. D., 3 Uptain, S. M., 191 Uskova, M. A., 82 Utada, A. S., 69 Uversky, V. N., 180 V Valentin, G., 135 Valle, M., 224

Vallotton, P., 399 Vandelinder, V., 198 van der Heijden, T., 264 van Dijk, 76 Van Orden, A., 120 Van Oudenaarden, A., 366 Vargas, D. Y., 367, 368, 384 Varshney, U., 241 Veldhuis, G., 181, 183, 197 Velev, O. D., 72 Velonia, K., 447 Verkman, A. S., 396 Veronese, F. M., 139 Vijayraghavan, U., 38 Villa, E., 224 Visnapuu, M. L., 293–314 Vocadlo, D. J., 20 Vogelsang, J., 105 Volkmer, A., 82, 349 von Hippel, P. H., 27 W Wade, H. E., 226 Wagner, E. G., 225 Wakefield, M. J., 424 Wall, J. D., 244 Walter, N. G., 39, 153–176, 180, 183 Wang, C. C., 21 Wang, D., 19–28 Wang, J., 221–254 Wanner, B. L., 244 Wasserman, L., 167 Wazawa, T., 62 Webb, W. W., 186, 388, 397–398 Weghuber, J., 133–148 Weinger, J. S., 238 Weinreb, P. H., 110, 193 Weiss, S., 21, 43, 154, 155, 198 Wennmalm, S., 62 Westhof, E., 206 Whorton, M., 91 Wickner, R. B., 191 Widengren, J., 349–350, 393 Wieser, S., 388, 401 Wilkinson, G., 96 Williamson, J. R., 208 Williams, P., 98 Wilson, D. N., 222 Wilson, K., 228 Wind, S., 293–314 Wintermeyer, W., 226 Wiseman, P. W., 326, 347 Wright, P. E., 180 Wu, B., 345–361 Wu, H., 120 Wu, M., 137 Wyatt, J. R., 225, 226

465

Author Index X Xie, J., 188 Xie, X. S., 54 Xu, W., 54 Y Yamada, R., 72 Yamagishi, M., 390 Yanagawa, H., 63 Yang, Z., 3 Yao, H., 71 Yarbrough, L. R., 437, 440 Yassour, M., 432 Yildiz, A., 367, 373 Yilmaz, A., 398–399 Yim, P. B., 80 Yoon, T. Y., 62

Yoshikawa, M., 438 Youngman, E. M., 239 Yu, J., 181, 200 Z Zaitsev, E. N., 264 Zalipsky, S., 2, 3 Zare, R. N., 119–131 Zavialov, A. V., 239, 241 Zeldin, R., 98 Zeng, J., 72 Zenklusen, D., 366 Zhang, H. L., 402 Zhang, Y. H., 64 Zhuang, X. W., 160, 161, 180, 183, 206, 214, 216, 227 Zimyanin, V. L., 390

Subject Index

A Alexa488-phosphine synthesis, 23–24 Alexa647-phosphine synthesis, 25–26 Amine labeling, 188 Aminosilanization, 7 Amylin. See Islet amyloid polypeptide (IAPP) Automatic DNA length measurement, 288 Azide-specific biomolecule labeling, 26–27. See also Staudinger–Bertozzi ligation, bioorthogonal labeling B Bait–prey interactions, 148. See also Proteinprotein interaction detection Biotinylated l DNA biotin and digoxigenin, 267 preparation, 265 Bovine serum albumin (BSA) separation, 125, 128 C Caenorhabditis elegans fixation, in situ hybridization, 375–376 gene sequencing, 410 sFCS, 334–335 Capillary electrophoresis (CE), 120. See also Microfluidics Carbonyldiimidazole (CDI), 438, 439 Chromatin immunoprecipitation (ChIP) DNA 30 blocking, 423 poly-A tailing, 423 preparation, 422 Coalescence, droplet, 62–63, 73 Complex barrier patterns, DNA curtains geometric patterns, 304–305 rack patterns double-tethered, 304, 305 linear barriers, 305 pentagons, 306 Complex single-molecule FRET time trajectories FRET state number selection, 167–168 hidden Markov analysis, 160–162 HMM software, 163–164 post-HMM processing and data visualization data condensation and visualization, 169–172 local correlation analysis, 168–170 yeast pre-mRNA splicing, 171, 173–174

preprocessing trajectories formatting, 165–166 outliers removal, 164–165 smoothing (noise reduction), 165 stitching trajectories, 166–167 QuB data preparation, 174 data visualization, 176 HMM analysis, 175 molecule selection, 174 postprocessing, 176 preprocessing, 175 simple trajectories analysis FRET state distribution, 158 kinetic analysis, 158–160 trajectories selection, 157–158 Confocal laser scanning microscope (CLSM), 320–322 Cy3B-phosphine synthesis, 23, 25 Cy3-labeled antibody, DNA substrate, 266–267 Cysteine labeling, 187–188 Cytochrome P450 3A4 (CYP3A4)–Nanodiscs, 96 allosterism, 97–98 CYP3A4 incorporation, 99–101 effectors, 98 Nile Red dye, 98–99 surface attachment, 101–102 D Dielectrophoresis, 72 1,2-Dimyristoyl-sn-glycero-3-phosphocholine (DMPC) lipid membranes, 58 Dipole force. See Gradient force DNA–bead complexes Cy3-labeled antibody binding, 267 DNA labeling, biotin and digoxigenin, 267 fluorescent secondary antibody, 266 preparation, 265–266 DNA curtains, single molecule imaging complex barrier patterns geometric patterns, 303–305 rack patterns, 305–306 DNA molecules aligment bilayer deposition, 298 buffer, 298 fluid bilayer, 297 procedure, 297–298

467

468

Subject Index

DNA curtains, single molecule imaging (cont.) manually etched diffusion barriers, 298, 299 nanofabricated barrier patterns ebeam lithography, 299–304 nanoimprint lithography, 299, 301, 303 TIRFM description, 295 flowcells and injection system, 295–297 simple prism-type, 295 trouble-shooting, 306–307 visualizing protein-DNA interaction ATP-dependent DNA translocation, 308–309 mismatch repair, 310, 312–314 quantum dots, 307–308 tagged nucleosomes, 310, 311 DNA fragmentation and quantitation 30 ends estimation, poly-A tailing, 413–414 shearing, 411–413 size selection, 413 DNA molecule aligment bilayer deposition, 298 buffer application, 298 fluid bilayer, 297 procedure, 297–298 DNA polymerization kinetic parameter determination, 446–448 polymerase pausing circular template sequencing, 449–450 consensus sequence contexts, 450 double-stranded DNA templates, 447, 449 IPD profiles, 449–450 sequencing engine, 440–441 DNA sequencing method. See Single-molecule, real-time (SMRT) DNA sequencing Drosophila melanogaster, 376–377 Dual-color fluorescence cross-correlation spectroscopy (FCCS), 328 Dual-color sFCS, 340–341 Dual-focus sFCS, 339–340 E Ebeam lithography, 299–304 Egg phosphatidylcholine lipid, 45, 47, 48, 57 Electrokinetic injection, 125–127 Electron-multiplying charge-coupled device (EMCCD), 295, 395 Electrowetting, 72 Emulsification, 65–66 Ensemble averaging, 156, 180, 217, 262 Escherichia coli-based in vitro translation system, smFRET elongation polypeptide synthesis assay, 238–239 primer-extension inhibition assay, 237–238 initiation assays GTP hydrolysis assay, 236–237

primer-extension inhibition assay, 233–236 mRNA preparation, 226–227 phylogenetic analysis/structural modeling, 243 ribosome labeling fluorescently labeled r-proteins, 247–248 mutant ribosomes preparation, 244–247 r-proteins reconstitution, 248–249 ribosome recycling, 241–242 ribosomes and ribosomal subunits, 226 termination elongation reaction, 239–240 polypeptide release assay, 239–241 release reactions, 240 RF1/2 activity determination, 240–241 translation factors cleavage reaction, 230 EF-G, 232 EF-Tu, 232 IF1, 230–231 IF3, 232 IF2g, 231–232 labeling, 252–253 Ni2þ-NTA affinity purification, 229–230 RF1 and RF2, 232 tris–polymix buffer, 225–226 tRNA labeling, 249–252 tRNA synthetase, 227–228 F FCS. See Fluorescence correlation spectroscopy (FCS) Figures of merit, protein interaction detection, 147–148 Flow cell design, 270–271 fabrication, 271–273 illustration, 262–263 Fluorescence correlation spectroscopy (FCS), 95. See also Scanning fluorescence correlation spectroscopy (sFCS) IDP, 186 microfluidics autocorrelation function, 127–128 immunocomplex formation, 130 multivalent antibody hypothesis, 130–131 parameters, 129, 130 TMR-labeled BSA and anti-BSA antibody, 128–129 rIAPP binding Nanodiscs, 107–109 Fluorescence fluctuation spectroscopy (FFS), 346 Fluorescence in situ hybridization (FISH), 383 Fluorescence quenching EGFP and protein X labeling, 348–349 environmental changes, 348 types, 348 Fluorescence recovery after photobleaching (FRAP), 388–389

469

Subject Index

Fluorescence resonance energy transfer (FRET). See also Single-molecule fluorescence resonance energy transfer (smFRET) measurement, 154–155 membrane proteins, 95 ratio, 154 a-synuclein (aS), Nanodiscs, 111–112 Fluorescent oligonucleotide probe design, 369 synthesis and purification Alexa 594, 373 HPLC samples, 370–372 oligonucleotide synthesis, 369–370 optical filters, 371, 373 three color mRNA detection, 371, 374 TMR, 370 Fluorescent pre-mRNA substrates, smFRET microscope slide, 38–39 pre-mRNA mutation, 37–39 spliceosome assembly, 32 splicing efficiency dyes, 37, 38 Ubc4 pre-mRNA, 33, 35 synthetic fluorescent Ubc4 pre-mRNA design, 35 oligonucleotide ligation, 36–37 precipitation, 35–36 purification, 33–34 yeast pre-mRNA in vitro splicing exon length requirement, 35 prp2–1 mutant, 33 relative splicing efficiency, 34 ribosomal protein RPS6A, 33 Fluorescent probes, 21. See also Staudinger–Bertozzi ligation, bioorthogonal labeling Fluorescent semiconducting nanocrystals. See Quantum dots Fluorescent spot, 367–368 Fo¨rster resonance energy transfer. See Fluorescence resonance energy transfer (FRET) FRET. See Fluorescence resonance energy transfer (FRET) G Gaussian mask algorithm, 398 Genomic DNA preparation DNA fragmentation and quantitation 30 end estimation, poly-A tailing, 413–414 shearing, 411–413 size selection, 413 30 end blocking, 415–416 poly-A tailing, 415 Gradient force, 69 GTP hydrolysis assay, 236–237

H Helicos single-molecule sequencer bacterial genome sequencing coverage assessment and lack of bias, 417, 419 preparation, 416–418 cDNA blocking, 427–428 poly-A tailing, 426–427 single-stranded, preparation, 424–426 chromatin immunoprecipitation (ChIP) DNA 30 blocking, 423 poly-A tailing, 423 preparation, 422 copy number variation assessment, 420 genomic amplification visualization, 421–422 vs. genomic hybridization, 421–422 DGE reproducibility, 428 genomic DNA preparation DNA fragmentation and quantitation, 411–414 30 end blocking, 415–416 poly-A tailing, 415 Helicos Flow Cell Image and Virtual TerminatorÒ , 410, 411 nucleotid incorporation, 409 principles, 409–410 real-time image processing, 410 sequencing-by-synthesis reaction, 410 a-Hemolysin self-assembly, 58 Hidden Markov model (HMM), FRET trajectories. See also QuB program, FRET trajectories data condensation and visualization complex trajectories, 172 POKIT, 171 TDP, 169–171 five-state system analysis, 161, 162 FRET state number selection, 167–168 local correlation analysis, 168–170 parameter sets, 160–161 preprocessing trajectories formatting trajectories, 165–166 outliers removal, 164–165 smoothing (noise reduction), 165 stitching trajectories, 166–167 software programs, 161, 162 features, 164 HaMMy, 163 QuB, 163 vb-FRET, 163–164 transition rate constant, 161–162 yeast pre-mRNA splicing, 171, 173–174 Homologous recombination (HR), 263

470

Subject Index I

L

IAPP. See Islet amyloid polypeptide (IAPP) IDP. See Intrinsically disordered proteins (IDPs) Imaging mRNA movement image-acquisition protocol, 394 microscopic system noise reduction, 395 physiological conditions, 395–396 three-dimensional tracking, 396 Injection, droplet loading protocol, 67 micropipettes, pulling protocol, 67–68 schematic representation, 66–67 In situ hybridization buffer B, 374 FISH, 383 fixation protocols adherent mammalian cell, 375 Caenorhabditis elegans, 375–376 Drosophila melanogaster wing imaginal discs, 376–377 freezed tissue sections, 377 yeast cells fixation, 375 fixation solution, 373–374 M9 salt, 375 spheroplasting buffer, 375 Intrinsically disordered proteins (IDPs) single-molecule fluorescence method dual-color single-molecule coincidence, 185–186 FCS, 186 smFRET, 182–185 site-specific labeling amine labeling, 188 cysteine labeling, 187–188 dual-labeling, FRET, 189–190 orthogonal chemical reactions, 189 protein ligation, 190 unnatural amino acid functional groups, 188–189 structure and dynamics a-synuclein, 193–199 yeast prion protein Sup35, 191–193 Islet amyloid polypeptide (IAPP) FCS measurement, 107–109 membrane interactions, 106–107 type II diabetes, 106 Isocyanate terminated star molecules (NCO–sP (EO-stat-PO)) biosensors, 11 protein structure and function immobilized biomolecule, 12–13 nucleosomes, 12 RNase H, 14–16 surface coating aqueous solution, 4–5 reactivity, 5–6

Lab-on-chip method, 71–72 Laplacian of Gaussian (LoG) filters, 384 Lipid nanovesicle preparation lipid film, 46 lipid selection, 45 unilamellar nanovesicles, 46–47 Living cell mRNA labeling MS2-GFP system, 392–393 photobleaching and phototoxicity limitation, 393 probe selection, SPT, 391 Low-density lipoprotein (LDL) receptors, 388 M Microbiochip, 138, 143–144, 146 Microcontact printing experimental design, 139–140 procedure, 141–142 Microfluidics detergent-assisted microchannel electrophoresis electrokinetic injection, 125–127 PDMS microchip, 124–125 separation buffer and sample preparation, 125 droplets, 64–65, 68–69 electrophoretic biomolecule separation, 120 FCS autocorrelation function, 127–128 immunocomplex formation, 130 multivalent antibody hypothesis, 130–131 parameters, 129, 130 TMR-labeled BSA and anti-BSA antibody, 128–129 laser-induced fluorescence detection, 123–124 laser trap microscope, proteins on DNA dual optical trap imaging system, 275–276 schematics, 274, 275 single optical trap imaging system, 273–275 microchip fabrication design drawing and photomask printing, 121–122 molding master fabrication, 122 PDMS chip fabrication, 122–123 single-molecule experiment, 120 Micropatterning technique advantages, 147–148 CD4-YFP protein interaction, 143 principle, 137–138 Mismatch repair (MMR), 310, 312–314 Mold master, 122 mRNA tracking, living cell. See also Quantum dots FRAP technique, 388–389 imaging mRNA movement image-acquisition protocol, 394

471

Subject Index

microscopic system, 395–396 three-dimensional tracking, 396 labeling MS2-GFP system, 392–393 photobleaching and phototoxicity limitation, 393 probe selection, SPT, 391 motion analysis data interpretation, 401–402 localization algorithms, 397–398 particle tracking, 398–399 single particle motion, 399–401 types, 396–397 significance distribution, COS cells, 389 localization, 390 single particle tracking (SPT), 388 technical development, 388 MS2-labeling technique, 392–393 Multiple hypotheses tracking (MHT) algorithm, 399 Multiple-tau method, 328–329 N Nanodiscs. See Phospholipid bilayer Nanodiscs Nanodroplet confinement cell biology, 83 compartmentalization, 63–64 droplet coalescence and mixing, 62–63, 73 droplet generation emulsification, 65–66 injection, 66–68 microfluidics, 68–69 lab-on-chip method dielectrophoresis, 72 electric field, 71–72 electrowetting, 72 surface acoustic wave, 72 microfluidics, 64–65 (see also Microfluidics) molecule confinement, 62–63 molecule reaction kinetics, 63 optical manipulation force, 69–70 optical tweezers, 70–71 optical vortices, 71 PCR, 64 single fluorophore detection acousto-optical modulators (AOMs), 76 apparatus alignment, 74, 76–77 droplet injection, 77–78 emulsion sample preparation, 77 filters, 75 polarizing beamsplitter (PC), 75 removable mirror (RM), 75 technique, 74–75 Ytterbium fiber laser, 73–74 single-molecule measurement FRET, RNA molecule, 80

photobleaching, dye molecule, 79–80 time-resolved fluorescence anisotropy, EGFP, 81–82 Nanofabricated barrier patterns, DNA curtains ebeam lithography, 299–304 nanoimprint lithography descum process, 301, 303 PMMA layers, 299, 301 preimprint phase, 301 Nanoimprint lithography, 299, 301, 303 Nanovesicle trapping, weak protein interactions advantages, 44 characteristics, 42 DMPC lipid membranes, 58 effective concentration vs. vesicle diameter, 45 Egg PC limitation, 57–58 a-hemolysin self-assembly, 58 lipid nanovesicle preparation lipid film preparation and hydration, 46 unilamellar nanovesicles, 46–47 lipid selection, 45 protein trapping, 46–47 single-molecule kinetic analysis conditional probability, 55 dissociation constant, 57 dwell time, 56–57 generic kinetic scheme, 54 kinetic rate equations, 54–55 probability density, 56 smFRET measurement acceptor-blinked/bleached states, 50–52 intracellular copper transporters, 51–53 lipid–protein interactions, 49 nanovesicle occupation, 49–50 nanovesicle surface immobilization, 47–49 schematics, 43–44 zero-mode waveguides, 43 Nile Red (NR) binded CYP3A4, 98–99, 103 O Optical distortions, 319 Optical trapping. See Optical tweezers Optical tweezers, 70–71 Optical vortices, 71 P PEO. See Poly(ethylene oxide) (PEO) surface passivation Phosphine Alexa488 synthesis, 22–23 Alexa647 synthesis, 24–26 biotin and fluorescent probes, 21 Cy3B synthesis, 23, 25 Phospholinked nucleotide principle fluorescence emission, 434–435 molecular structure, 434

472 Phospholinked nucleotide (cont.) SMRT sequence determination, 433–434 uninterrupted DNA polymerization Alexa Fluor 488-aminohexyl-dG5P, 439 aminohexyl-dG5P, 439 enzymatic purification, 440 Fmoc-6-aminohexyldiphosphate, 438–439 Fmoc-6-aminohexylphosphate, 438 linker, 437–438 unmodified dNTPs, 437–438 Phospholipid bilayer Nanodiscs application, 91 characteristics, 94 vs. conventional membrane, 91 cytochrome P450 3A4 (CYP3A4) allosterism, 97–98 effectors, 98 incorporation of, 99–101 Nile Red dye, 98–99 surface attachment, 100–102 HDL particles formation, 91–92 lipid–protein ratio, 93 POPC–MSP1D1 discs, 92–94 IAPP FCS measurement, 107–110 membrane interactions, 106–107 type II diabetes, 106 membrane protein study, 94 oligomerization, 94 self-assembly, 93 single-molecule techniques, 95–96 SVD based image filtering artifacts, photobleaching, 105 noise reduction, 102–104 pseudocode, 104–105 a-synuclein (aS) conformation, 110 smFRET measurement, 110–112 Photobleaching, 79–80, 319, 330–331 Photomask printing, 121–122 Photoresist, 122 Poly-A tailing cDNA, 426–427 ChIP DNA, 423 3’ ends estimation, 413–414 oligonucleotide digestion, 427 procedure, 415 Polymethylmethacrylate (PMMA), 300, 301 Poly(dimethylsiloxane) (PDMS) microfluidic chip fabrication, 122–123 microchannel electrophoresis, 124–125 Poly(ethylene oxide) (PEO) surface passivation end-functionalized groups, 3 grafting density, 3–4 linear vs. cross-linked PEO, 2 NCO-sP(EO-stat-PO) system protein structure and function, 11–16

Subject Index

surface coating, 4–6 PEO star size, 3–4 protein-repellant coatings, 2–3 quality, 10 sP(EO-stat-PO) substrate aminosilanization, 7 biotin and streptavidin formation, 9 layer precipitation procedure, 8–9 nonfouling properties, 9, 10 preparation, 6 schematics, 9–11 spin-coating, 7–8 POPC–MSP1D1 Nanodiscs characteristics, 94 oligomerization, 94 preparation, 92–94 Population-weighted and kinetically indexed transition density (POKIT), 171 Primer-extension inhibition assay EF-G(GTP), 238 IF1, 235–236 IF3, 236 IF2g activity, 235 initiation reaction, 234 Lys-tRNALys ternary complex, 238 Phe-tRNAPhe ternary complex, 237–238 primer labeling reaction, 233 Protein interactions and stoichiometry, living cells brightness classification fluorescent proteins, 354 single brightness state, 347–349 two brightness state, 349–353 brightness titration monomeric protein state, 355 normalized brightness values, 355–356 oligomeric state, 356 protein expression variability, 354 TR4-EGFP labeling, 355 cell selection bright-field imaging, 358 excitation powers, 360 morphology, 357–358 photobleaching, 359–360 signal-to-noise ratio, 360 thickness, 360–361 two-photon FFS mode, 358 control and calibration experiments fluorescent label EGFP, 356 normalized brightness measurement, EGFP2, 356–357, 359 Western blot gel, 357, 358 FFS parameter, 346 Protein ligation, 190 Protein-protein interaction detection applicability living cells, 136 plasma membrane proteins, 137 bait–prey interactions, 134–135, 148

473

Subject Index

capture ligand, 139 CD4-Lck interaction, 145–147 cellular expression system, 139 chip production, 139–140 dynamic range/sensitivity, 137 false negatives/false positives, 137 figures of merit, 147–148 high throughput capabilities, 137 instrumentation, 139 living cells, 135 micropatterning technique, 137–138 procedure cell incubation, micropatterned surface, 142–143 data analysis, 144–145 microcontact printing, 141–142 microscopy, 143–144 quantification, 136 resting state analysis, 148 signaling analysis, 148 weak interaction detection, 136 Protein repellant coating, 2–3 Proteins on DNA automatic DNA length measurement, 288 DNA substrate preparation biotinylated l DNA, 265 Cy3-labeled antibody, 266–267 DNA–bead complexes, 265–266 ensemble averaging, 262 flow cell design, 270–271 fabrication, 271–273 illustration, 262–263 fluorescent proteins preparation chemically modified fluorescent RecA/ Rad51 proteins, 269–270 Rad54/Tid1 labeling, 268–269 RecBCD labeling, 268 laser trap microscope and microfluidic system dual optical trap imaging system, 275–276 schematics, 274, 275 single optical trap imaging system, 273–275 RecA/Rad51, 264 RecBCD helicase/nuclease, 264 recombinational DNA repair, 263 single-molecule imaging DNA unwinding, 281 experimental steps, 280–281 Rad54/Tid1 translocation, 283–284 real-time Rad51 assembly, 284–285 real-time Rad51 disassembly, 285–286 RecAFAM/RecA-RFP/Rad51FAM filament formation, 286–287 RecBCD–nanoparticle translocation, 281–283 temperature determination and control, instruments schematics, 277

temperature control, 280 temperature determination, 276–279 thermal gradient, 279–280 two-dimensional Gaussian fitting, 288 Protein synthesis ribosome structure, 222, 223 smFRET studies (see Single-molecule fluorescence resonance energy transfer (smFRET)) Protein trapping, 46–47 Protocatechuate dioxygenase (PCD), 443 Protocatechuic acid (PCA), 443 Q Quantum dots, 391. See also mRNA tracking, living cell antibody conjugation, 308 disadvantage, 307 labeling strategy, 308 QuB program, FRET trajectories data preparation, distribution analysis and HMM, 174 data visualization, 176 HMM analysis, 175 molecule selection, 174 postprocessing, 176 preprocessing, 175 R Rad51 proteins, 264 assembly, 284–285 chemical modification, 269–270 disassembly, 285–286 Rad54/Tid1 proteins labeling, 268–269 translocation, 283–284 Raster image correlation microscopy (RICS), 326 RecA proteins, 264 chemical modification, 269–270 RecAFAM/RecA-RFP/Rad51FAM filament formation, 286–287 RecBCD enzyme DNA unwinding, 264, 281 labeling, 268 nanoparticle translocation, 281–283 RNase H, 14–16 RNA transcripts detection fluorescent oligonucleotide probe sets design, 369 synthesis and purification, 369–373 fluorescent spot, 367–368 hybridization protocol, 379–381 solution, 378–379 image analysis computational spot identification, 384–385 deconvolution software, 384

474

Subject Index

RNA transcripts detection (cont.) LoG filter, 384 microscopic imaging antifade mounting media, 383 single mRNA, various samples, 381–382 spot size variation, 384 staining method, 383–384 widefield microscopy, 381–383 oligonucleotide synthesis, 367 RNA binding protein, 368 in situ hybridization, 366 fixation protocols, 375–377 fixation solution, 373–375 target mRNAs probing, 366–367 S Scanning fluorescence correlation spectroscopy (sFCS) application Caenorhabditis elegans embryo, 325, 334–335 dual-color sFCS, 340–341 dual-focus sFCS, 339–340 perpendicular scan path, 337–339 small-circle sFCS, 335–337 correlation curves autocorrelation, 327 dual-color cross-correlation spectroscopy, 327–328 linear correlation, 329 multiple-tau method, 328–329 spatiotemporal cross-correlation, 329 data fitting autocorrelation function, 333 data points, 334 fitting parameters, 332 experimental steps, 320, 321 fluorescent background, 330 laser scanning microscope system, 322 measurement volume, 320–321 photobleaching, 330–331 photon counting detector, 321 principle, 318 scan paths calibration, 326–327 circular path, 324–325 double-line scan, 326 large-range scans, 323–324 membrane motion, 326 raster scan, 326 spatial heterogeneities, 331–332 uses, 319–320 Scan paths, sFCS calibration, 326–327 circular path, 324–325 double-line scan, 326 large-range scans correlation analysis, 324

spatiotemporal correlation, 323–324 membrane motion, 326, 338, 340 properties, 323 raster scan, 326 Scattering force, 69 Single brightness state, fluorescent molecules homoFRET, 349 quenching, 348–349 Single fluorophore detection, nanodroplet acousto-optical modulators (AOMs), 76 apparatus alignment, 74, 76–77 droplet injection, 77–78 emulsion sample preparation, 77 filters, 75 polarizing beamsplitter (PC), 75 removable mirror (RM), 75 technique, 74–75 Ytterbium fiber laser, 73–74 Single-molecule fluorescence resonance energy transfer (smFRET). See also Complex single-molecule FRET time trajectories elongation polypeptide synthesis assay, 238–239 primer-extension inhibition assay, 237–238 energetic coupling, tertiary RNA contacts cooperativity measurement, 217 design, single molecule construct, 212–215 identification, 210, 212 knocking out, 212 single molecule construct validation, 215–217 ensemble-averaging, 156 features, 156 fluorescent labeling, 224 fluorescently labeled translation components phylogenetic analysis/structural modeling, 243 ribosome labeling, 244–249 translation factor labeling, 252–253 tRNA labeling, 249–252 fluorescent pre-mRNA substrates microscope slide, 38–39 pre-mRNA mutation, 37–39 spliceosome assembly, 32 splicing efficiency, dyes, 37, 38 synthetic fluorescent Ubc4 pre-mRNA, 33–37 yeast pre-mRNA in vitro splicing, 33–35 fluorophores, 155–156 highly purified in vitro translation system, Escherichia coli mRNA preparation, 226–227 ribosomes and ribosomal subunits, 226 translation factors, 228–232 tris–polymix buffer, 225–226 tRNA synthetase, 227–228 IDP confocal format, 183, 185

Subject Index

protein dual-labeling, 189–190 protein ligation, 190 schematics, 184 a-synuclein, 193–199 TIRF format, 185 transfer efficiency, 182–183 yeast prion protein Sup35, 191–193 initiation assays GTP hydrolysis assay, 236–237 primer-extension inhibition assay, 233–236 instrumentation, 155 mRNA-encoded aa-tRNA, 224 protein structure and function FRET efficiency, 12–14 immobilized biomolecule, 12–13 nucleosomes, 12 RNase H, 14–16 ribosome labeling fluorescently labeled r-proteins, 247–248 mutant ribosomes preparation, 244–247 r-proteins reconstitution, 248–249 ribosome recycling, 241–242 termination, 239–241 weak protein interactions acceptor-blinked/bleached states, 50–52 advantages, 42 concentration limitation, 43 dynamic protein–protein interactions, 42 intracellular copper transporters, 51–53 lipid–protein interactions, 49 nanovesicle occupation, 49–50 nanovesicle trapping, 43–44 surface immobilization (see Surface immobilization, nanovesicle) Single-molecule fluorescence (SMF) spectroscopy bioorthogonal labeling (see Staudinger–Bertozzi ligation, bioorthogonal labeling) dual-color single-molecule coincidence, 185–186 fluorescence correlation spectroscopy (FCS), 186 microfluidics (see Microfluidics) Nanodiscs (see Phospholipid bilayer Nanodiscs) single-molecule fluorescence resonance energy transfer (smFRET), 182–185 (see also Single-molecule fluorescence resonance energy transfer (smFRET)) Single-molecule kinetic analysis, three-state protein interactions conditional probability, 55 dissociation constant, 57 dwell time, 56–57 generic kinetic scheme, 54 kinetic rate equations, 54–55 probability density, 56

475 Single-molecule, real-time (SMRT) DNA sequencing compound prism, 443 data analysis dye types, 444 enzymatic reaction cycle, 445 fluorescence pulse, 445–446 DNA polymerase, 440–441 DNA squencing assay, 443–444 dynamics DNA polymerase pausing, 447, 449–450 kinetic parameters determination, 446–448 optical system, DNA sequencing, 441–443 phospholinked dNTP Alexa Fluor 488-aminohexyl-dG5P, 439 aminohexyl-dG5P, 439 Fmoc-6-aminohexyldiphosphate, 438–439 Fmoc-6-aminohexylphosphate, 438 linker, 437–438 purity, 440 principle phospholinked nucleotide, 433–435 ZMW nanostructures, 433, 434 ZMW fabrication, 435, 436 surface derivatization, 435–437 Single particle tracking (SPT) method. See mRNA tracking, living cell Singular-value decomposition (SVD) based image filtering artifacts, photobleaching, 105 noise reduction, 102–104 pseudocode, 104–105 Spatiotemporal image correlation spectroscopy (STICS), 324 Spin casting, 2, 7–9 Spin coating flow diagram, 8–9 homogeneity, 7–8 Staudinger–Bertozzi ligation, bioorthogonal labeling ˚ Alexa647-phosphine20 A synthesis, 25–26 ˚ 24 A synthesis, 26 Alexa647-phosphine Alexa488-phosphine synthesis, 23 applications, 20 azide-specific labeling, 26–27 Cy3B-phosphine synthesis, 25 fluorescent probes, 21 materials, 21–23 phosphine derivatives, 21 quantitation labeling efficiency, 27 labeling specificity, 27–28 reaction, 20 reversed-phase HPLC, 22 strategies, 20–21 Surface grafting, 2–4 Surface immobilization, nanovesicle

476

Subject Index

Surface immobilization, nanovesicle (cont.) bovine serum albumin (BSA) coating, 48 lipid bilayer coating, 47–48 polyethylene glycol (PEG) coating, 48–49 a-Synuclein (aS) conformation, 110 disordered state GdnHCl-induced changes, 194–195 noncooperative protein transition, 195 Parkinson’s disease, 193 smFRET measurement, Nanodiscs, 111–112 sodium dodecyl sulfate (SDS) binding modes, 196–197 F conformation, 198, 199 labeling, 195–196 structural dynamics, 197–198 T Tertiary contacts, RNA folding cooperativity measurement, 217 folding equilibrium, 209–210 identification, 210, 212 ionic condition, 217–218 knocking out, 212 single molecule constructs design considerations, 212–213 equilibrium constant, FRET, 216 FRET pair incorporation, 213 heterogeneity, smFRET, 217 P4-P6 cooperativity, 215–216 surface tether, 214–215 synthetic RNA, 214 variability, 215 thermodynamic cooperativity complex chemical equilibrium, 207 free energy diagram, 208–209 generic thermodynamic cycle, 207–208 Testicular orphan receptor 4 (TR 4), 355 Tetramethylrhodamine (TAMRA), 107–109 Tetramethylrhodamine (TMR), 128, 370 Time-resolved fluorescence anisotropy, EGFP, 81–82 Toeprinting assays EF-G(GTP), 238 IF1, 235–236 IF3, 236 IF2g activity, 235 initiation reaction, 234

Lys-tRNALys ternary complex, 238 Phe-tRNAPhe ternary complex, 237–238 primer labeling reaction, 233 Total internal reflection fluorescence microscopy (TIRFM), 183, 395 description, 295 membrane proteins, 95–96 microfluidic flowcells and injection system, 295–297 simple prism-type, 295 Transcriptome quantitation, digital gene expression cDNA blocking, 427–428 poly-A tailing, cDNA determination, 427 reaction, 426–427 RNA Seq, 423–424 single-stranded cDNA preparation cDNA synthesis, 424 quantification, 426 RNA digestion, 425–426 sample cleanup, 426 smsDGE reproducibility, 428 Transition density plot (TDP), 163 Two brightness state flickering, 350, 351 long-lived states, 351–353 short-lived states and flickering, 350 Two-dimensional Gaussian fitting, 288 U Uridine, 33, 37, 38 Y Yeast prion protein Sup35, 191–193 Z Zero-mode waveguides (ZMW), DNA sequencing fabrication, 435, 436 principle, 433–434 surface derivatization, enzyme immobilization aluminum-clad, 435–436 biotin PEG silane, 437 neutravidin binding, 436–437

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