Molecular Detection of Foodborne Pathogens

MOLECULAR DETECTION OF FOODBORNE PATHOGENS

MOLECULAR DETECTION OF FOODBORNE PATHOGENS EDITED BY

DONGYOU LIU

Boca Raton London New York

CRC Press is an imprint of the Taylor & Francis Group, an informa business

CRC Press Taylor & Francis Group 6000 Broken Sound Parkway NW, Suite 300 Boca Raton, FL 33487-2742 © 2010 by Taylor and Francis Group, LLC CRC Press is an imprint of Taylor & Francis Group, an Informa business No claim to original U.S. Government works Printed in the United States of America on acid-free paper 10 9 8 7 6 5 4 3 2 1 International Standard Book Number: 978-1-4200-7643-1 (Hardback) This book contains information obtained from authentic and highly regarded sources. Reasonable efforts have been made to publish reliable data and information, but the author and publisher cannot assume responsibility for the validity of all materials or the consequences of their use. The authors and publishers have attempted to trace the copyright holders of all material reproduced in this publication and apologize to copyright holders if permission to publish in this form has not been obtained. If any copyright material has not been acknowledged please write and let us know so we may rectify in any future reprint. Except as permitted under U.S. Copyright Law, no part of this book may be reprinted, reproduced, transmitted, or utilized in any form by any electronic, mechanical, or other means, now known or hereafter invented, including photocopying, microfilming, and recording, or in any information storage or retrieval system, without written permission from the publishers. For permission to photocopy or use material electronically from this work, please access www.copyright.com (http://www.copyright.com/) or contact the Copyright Clearance Center, Inc. (CCC), 222 Rosewood Drive, Danvers, MA 01923, 978-750-8400. CCC is a not-for-profit organization that provides licenses and registration for a variety of users. For organizations that have been granted a photocopy license by the CCC, a separate system of payment has been arranged. Trademark Notice: Product or corporate names may be trademarks or registered trademarks, and are used only for identification and explanation without intent to infringe. Library of Congress Cataloging-in-Publication Data Molecular detection of foodborne pathogens / [edited by] Dongyou Liu. p. ; cm. Includes bibliographical references and index. ISBN 978-1-4200-7643-1 (hard back : alk. paper) 1. Foodborne diseases--Molecular diagnosis. 2. Food--Microbiology. I. Liu, Dongyou. II. Title. [DNLM: 1. Food Contamination--analysis. 2. Food Poisoning--microbiology. 3. Molecular Diagnostic Techniques--methods. WA 701 M718 2009] QR201.F62M65 2009 615.9’54--dc22 Visit the Taylor & Francis Web site at http://www.taylorandfrancis.com and the CRC Press Web site at http://www.crcpress.com

2009017320

This book is dedicated to my parents, Jiaye Liu and Yunlian Li, whose unselfish sacrifice and unrelenting love have been a constant source of inspiration in my pursuit of knowledge and betterment.

Contents Preface........................................................................................................................................................................................xiii Editor........................................................................................................................................................................................... xv Contributors...............................................................................................................................................................................xvii Chapter 1. Molecular Detection: Principles and Methods......................................................................................................... 1 Lisa Gorski and Andrew Csordas

Section I  Foodborne Viruses Chapter 2. Adenoviruses.......................................................................................................................................................... 23 Charles P. Gerba and Roberto A. Rodríguez Chapter 3. Astroviruses........................................................................................................................................................... 33 Edina Meleg and Ferenc Jakab Chapter 4. Avian Influenza Virus............................................................................................................................................ 49 Giovanni Cattoli and Isabella Monne Chapter 5. Hepatitis A and E Viruses...................................................................................................................................... 63 Hiroshi Ushijima, Pattara Khamrin, and Niwat Maneekarn Chapter 6. Noroviruses............................................................................................................................................................ 75 Anna Charlotte Schultz, Jan Vinjé, and Birgit Nørrung Chapter 7. Rotaviruses............................................................................................................................................................. 91 Dongyou Liu, Larry A. Hanson, and Lesya M. Pinchuk Chapter 8. Sapoviruses...........................................................................................................................................................101 Grant S. Hansman Chapter 9. Slow Viral Diseases..............................................................................................................................................113 Takashi Onodera, Guangai Xue, Akikazu Sakudo, Gianluigi Zanusso, and Katsuaki Sugiura

Section II  Foodborne Gram-Positive Bacteria Chapter 10. Bacillus................................................................................................................................................................. 129 Noura Raddadi, Aurora Rizzi, Lorenzo Brusetti, Sara Borin, Isabella Tamagnini, and Daniele Daffonchio

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Chapter 11. Clostridium.......................................................................................................................................................... 145 Annamari Heikinheimo, Miia Lindström, Dongyou Liu, and Hannu Korkeala Chapter 12. Enterococcus........................................................................................................................................................ 157 Teresa Semedo-Lemsaddek, Rogério Tenreiro, Paula Lopes Alves, and Maria Teresa Barreto Crespo Chapter 13. Helicobacter..........................................................................................................................................................181 Norihisa Noguchi Chapter 14. Kocuria................................................................................................................................................................. 201 Edoardo Carretto and Daniela Barbarini Chapter 15. Listeria................................................................................................................................................................. 207 Dongyou Liu and Hans-Jürgen Busse Chapter 16. Micrococcus......................................................................................................................................................... 221 Friederike Hilbert and Hans-Jürgen Busse Chapter 17. Mycobacterium..................................................................................................................................................... 229 Irene R. Grant and Catherine E.D. Rees Chapter 18. Staphylococcus..................................................................................................................................................... 245 Paolo Moroni, Giuliano Pisoni, Paola Cremonesi, and Bianca Castiglioni Chapter 19. Streptococcus....................................................................................................................................................... 259 Mark van der Linden, Romney S. Haylett, Ralf René Reinert, and Lothar Rink

Section III  Foodborne Gram-Negative Bacteria Chapter 20. Aeromonas............................................................................................................................................................ 273 Germán Naharro, Jorge Riaño, Laura de Castro, Sonia Alvarez, and José María Luengo Chapter 21. Arcobacter............................................................................................................................................................ 289 Kurt Houf Chapter 22. Bacteriodes........................................................................................................................................................... 307 Rama Chaudhry, Anubhav Pandey, and Nidhi Sharma Chapter 23. Brucella.................................................................................................................................................................317 Sascha Al Dahouk, Karsten Nöckler, and Herbert Tomaso Chapter 24. Burkholderia.........................................................................................................................................................331 Karlene H. Lynch and Jonathan J. Dennis

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Chapter 25. Campylobacter..................................................................................................................................................... 345 Aurora Fernández Astorga and Rodrigo Alonso Chapter 26. Enterobacter......................................................................................................................................................... 361 Angelika Lehner, Roger Stephan, Carol Iversen, and Seamus Fanning Chapter 27. Escherichia........................................................................................................................................................... 369 Devendra H. Shah, Smriti Shringi, Thomas E. Besser, and Douglas R. Call Chapter 28. Klebsiella.............................................................................................................................................................. 391 Beatriz Meurer Moreira, Marco Antonio Lemos Miguel, Angela Christina Dias de Castro, Maria Silvana Alves, and Rubens Clayton da Silva Dias Chapter 29. Plesiomonas......................................................................................................................................................... 405 Jesús A. Santos, Andrés Otero, and María-Luisa García-López Chapter 30. Proteus..................................................................................................................................................................417 Antoni Róz∙alski and Paweł Sta˛ czek Chapter 31. Pseudomonas........................................................................................................................................................431 Olga Zaborina and John Alverdy Chapter 32. Salmonella............................................................................................................................................................ 447 Charlotta Löfström, Jeffrey Hoorfar, Jenny Schelin, Peter Rådström, and Burkhard Malorny Chapter 33. Serratia................................................................................................................................................................. 459 Zhi-Qing Hu, Wei-Hua Zhao, and Zhuting Hu Chapter 34. Shigella................................................................................................................................................................. 471 Benjamin R. Warren, Keith A. Lampel, and Keith R. Schneider Chapter 35. Vibrio.................................................................................................................................................................... 485 Asim K. Bej Chapter 36. Yersinia................................................................................................................................................................. 501 Mikael Skurnik, Peter Rådström, Rickard Knutsson, Bo Segerman, Saija Hallanvuo, Susanne Thisted Lambertz, Hannu Korkeala, and Maria Fredriksson-Ahomaa

Section IV  Foodborne Fungi Chapter 37. Alternaria............................................................................................................................................................. 521 Dongyou Liu, Stephen B. Pruett, and Cody Coyne Chapter 38. Aspergillus............................................................................................................................................................ 529 Giancarlo Perrone, Antonia Gallo, and Antonia Susca

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Chapter 39. Candida................................................................................................................................................................ 549 P. Lewis White, Samantha J. Hibbitts, Michael D. Perry, and Rosemary A. Barnes Chapter 40. Debaryomyces...................................................................................................................................................... 565 Juan J. Córdoba, Maria J. Andrade, Elena Bermúdez, Félix Núñez, Miguel A. Asensio, and Mar Rodríguez Chapter 41. Fusarium.............................................................................................................................................................. 577 Antonio Moretti and Antonia Susca Chapter 42. Penicillium........................................................................................................................................................... 593 Joëlle Dupont Chapter 43. Rhodotorula......................................................................................................................................................... 603 Diego Libkind and José Paulo Sampaio Chapter 44. Saccharomyces......................................................................................................................................................619 Franca Rossi and Sandra Torriani

Section V  Foodborne Protozoa Chapter 45. Acanthamoeba...................................................................................................................................................... 639 Hélène Yera, Pablo Goldschmidt, Christine Chaumeil, Muriel Cornet, and Marie-Laure Dardé Chapter 46. Cryptosporidium.................................................................................................................................................. 651 Una Ryan and Simone M. Cacciò Chapter 47. Cyclospora........................................................................................................................................................... 667 Dongyou Liu, G. Todd Pharr, and Frank W. Austin Chapter 48. Entamoeba........................................................................................................................................................... 677 Damien Stark and John Ellis Chapter 49. Encephalitozoon and Enterocytozoon................................................................................................................. 691 Jaco J. Verweij and Dongyou Liu Chapter 50. Giardia................................................................................................................................................................. 701 Yaoyu Feng and Lihua Xiao Chapter 51. Isospora.................................................................................................................................................................717 Somchai Jongwutiwes and Chaturong Putaporntip

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Chapter 52. Sarcocystis........................................................................................................................................................... 731 Benjamin M. Rosenthal Chapter 53. Toxoplasma...........................................................................................................................................................741 Chunlei Su and J.P. Dubey

Section VI  Foodborne Helminthes Chapter 54. Anisakis................................................................................................................................................................ 757 Stefano D’Amelio, Marina Busi, Sofia Ingrosso, Lia Paggi, and Elisabetta Giuffra Chapter 55. Clonorchis............................................................................................................................................................ 769 Heinz Mehlhorn, Boris Müller, and Jürgen Schmidt Chapter 56. Diphyllobothrium . .............................................................................................................................................. 781 Jean Dupouy-Camet and Hélène Yera Chapter 57. Fasciola................................................................................................................................................................ 789 Xing-Quan Zhu, Qing-Jun Zhuang, Rui-Qing Lin, and Wei-Yi Huang Chapter 58. Heterophyidae...................................................................................................................................................... 795 Ron Dzikowski and Michael G. Levy Chapter 59. Metagonimus........................................................................................................................................................ 805 Jae-Ran Yu and Jong-Yil Chai Chapter 60. Opisthorchis......................................................................................................................................................... 813 Paiboon Sithithaworn, Thewarach Laha, and Ross H. Andrews Chapter 61. Paragonimus........................................................................................................................................................ 827 Kanwar Narain, Takeshi Agatsuma, and David Blair Chapter 62. Taenia................................................................................................................................................................... 839 Akira Ito, Minoru Nakao, Yasuhito Sako, Kazuhiro Nakaya, Tetsuya Yanagida, and Munehiro Okamoto Chapter 63. Trichinella............................................................................................................................................................ 851 Edoardo Pozio and Giuseppe La Rosa Index.......................................................................................................................................................................................... 865

Preface Foodborne pathogens are microorganisms (e.g., bacteria, viruses, fungi, and parasites) that are capable of infecting humans via contaminated food and/or water. In recent years, diseases caused by foodborne pathogens have become an important public health problem worldwide, resulting in significant morbidity and mortality. Currently, there are over 250 known foodborne diseases. Due to the introduction of pathogens to other geographic regions through population movement and globalization of the food supply, new foodborne infections are continuously emerging. Furthermore, pathogen evolution, changes in human immune status and life-style as well as food manufacturing practices also contribute to increased incidences of foodborne ­illnesses. As a consequence, large outbreaks of foodborne diseases have been reported with alarming frequencies. It is well known that one of the most effective ways to control and prevent human foodborne infections is to implement a surveillance system that includes a capability to rapidly and precisely detect, identify, and monitor foodborne pathogens at the nucleic acid level. The purpose of this book is to bring out an all-encompassing volume on the detection and identification of major foodborne bacterial, fungal, viral, and parasitic pathogens using state-of-art molecular techniques. Each chapter includes a concise review of the pathogen concerned with respect to its biology, epidemiology, and pathogenesis; a summary of the molecular detection methods available; a description of clinical/food sample collection and preparation procedures; a selection of robust, effective, step-wise molecular detection protocols for each pathogen; and a discussion on the challenges and continuing research needs to further extend the utility and performance of molecular diagnostic methods for foodborne diseases. With each chapter written by scientists with expertise in their respective foodborne pathogen research, this book provides comprehensive coverage of the molecular methodologies for the detection and identification of major foodborne pathogens. It is an indispensable tool for clinical, food, and industrial laboratory scientists involved in the diagnosis of foodborne diseases; a convenient textbook for prospective undergraduate and graduate students intending to pursue a career in food microbiology and medical technology; and a reliable reference for upcoming and experienced laboratory scientists wishing to develop and polish their skills in the molecular detection of major foodborne pathogens. Given the number of foodborne pathogens covered, and the breadth and depth of the topics discussed, an inclusive book like this is undoubtedly beyond the capacity of an individual’s effort. It is my fortune and honor to have a large panel of international scientists as chapter contributors, whose willingness to share their technical insights on foodborne pathogen detection has made this book possible. Moreover, the professionalism and dedication of senior editor, Steve Zollo, and other editorial staff at CRC Press have contributed to its enhanced presentation. I hope the readers will find it as stimulating and rewarding as I do through reading this book, which by presenting relevant background information and ready-to-run molecular detection protocols will serve to save readers’ time and patients’ lives. Dongyou Liu, PhD

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Editor Dongyou Liu, PhD, is currently a member of the research faculty in the Department of Basic Sciences, College of Veterinary Medicine at Mississippi State University in Starkville. In 1982, he graduated with a veterinary science degree from Hunan Agricultural University in China. After one year of postgraduate training under the supervision of Professor Kong Fangyao at Beijing Agricultural University (presently China Agricultural University) in China, he completed his PhD study on the immunological diagnosis of human hydatid disease due to the parasitic tapeworm Echinococcus granulosus in the laboratory of Drs. Michael D. Rickard and Marshall W. Lightowlers at the University of Melbourne School of Veterinary Science in Australia in 1989. During the past two decades, he has worked in several research and clinical laboratories in Australia and the United States, with an emphasis on molecular microbiology, especially in the development of nucleic acid-based assays for species- and virulence-specific determination of microbial pathogens such as ovine footrot bacterium (Dichelobacter nodosus), dermatophyte fungi (Trichophyton, Microsporum, and Epidermophyton), and listeriae (Listeria species). He is the editor of the Handbook of Listeria monocytogenes and the Handbook of Nucleic Acid Purification, both of which have been published recently by Taylor & Francis/CRC Press.

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Contributors Takeshi Agatsuma Department of Environmental Health Sciences Kochi Medical School Nankoku City, Kochi, Japan Rodrigo Alonso Departamento de Inmunología, Microbiología y Parasitología Facultad de Farmacia Universidad del Pais Vasco/Euskal Herriko Unibertsitatea Vitoria-Gasteiz, Spain Sonia Alvarez Department of Animal Health University of León León, Spain John Alverdy Center for Surgical Infection Research and Therapeutics University of Chicago Chicago, Illinois Maria Silvana Alves Faculdade de Farmácia e Bioquímica Universidade Federal de Juiz de Fora Minas Gerais, Brazil Paula Lopes Alves Instituto de Biologia Experimental e Tecnológica (IBET) Av. da República, Quinta do Marquês Oeiras, Portugal M.J. Andrade Higiene y Seguridad Alimentaria Facultad de Veterinaria Universidad de Extremadura Cáceres, Spain Ross H. Andrews School of Pharmacy and Medical Sciences University of South Australia Adelaide, Australia M.A. Asensio Higiene y Seguridad Alimentaria Facultad de Veterinaria Universidad de Extremadura Cáceres, Spain

Aurora Fernández Astorga Departamento de Inmunología, Microbiología y Parasitología Facultad de Farmacia Universidad del Pais Vasco/Euskal Herriko Unibertsitatea Vitoria-Gasteiz, Spain Frank W. Austin Department of Basic Sciences College of Veterinary Medicine Mississippi State University Mississippi State, Mississippi Daniela Barbarini Bacteriology Laboratory Infectious Diseases, Laboratories of Experimental Researches Fondazione “IRCCS Policlinico San Matteo” Pavia, Italy Rosemary A. Barnes Department of Medical Microbiology Cardiff University University Hospital of Wales Cardiff, Wales, United Kingdom Asim K. Bej Department of Biology University of Alabama at Birmingham Birmingham, Alabama E. Bermúdez Higiene y Seguridad Alimentaria Facultad de Veterinaria Universidad de Extremadura Cáceres, Spain Thomas E. Besser Department of Veterinary Microbiology and Pathology College of Veterinary Medicine Washington State University Pullman, Washington David Blair School of Marine and Tropical Biology James Cook University Townsville, Australia Sara Borin Department of Food Science and Microbiology University of Milan Milan, Italy xvii

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Contributors

Lorenzo Brusetti Department of Food Science and Microbiology University of Milan Milan, Italy

Jong-Yil Chai Department of Parasitology and Tropical Medicine Seoul National University College of Medicine Seoul, Korea

Marina Busi Department of Public Health Science Sapienza University of Rome Rome, Italy

Rama Chaudhry Department of Microbiology All India Institute of Medical Sciences New Delhi, India

Hans-Jürgen Busse Institute of Bacteriology, Mycology and Hygiene University of Veterinary Medicine Vienna, Austria

Christine Chaumeil Laboratoire du Centre National d’Ophtalmologie des Quinze-Vingts Paris, France

Simone M. Cacciò Department of Infectious, Parasitic and Immunomediated Diseases Istituto Superiore di Sanità Rome, Italy

J.J. Córdoba Higiene y Seguridad Alimentaria Facultad de Veterinaria Universidad de Extremadura Cáceres, Spain

Douglas R. Call Department of Veterinary Microbiology and Pathology College of Veterinary Medicine Washington State University Pullman, Washington

Muriel Cornet Laboratoire de Microbiologie Hôpital Hôtel-Dieu Paris, France

Edoardo Carretto Bacteriology Laboratory Infectious Diseases, Laboratories of Experimental Researches Fondazione “IRCCS Policlinico San Matteo” Pavia, Italy Bianca Castiglioni Institute of Agricultural Biology and Biotechnology Italian National Research Council Milan, Italy Angela Christina Dias de Castro Instituto de Microbiologia Universidade Federal do Rio de Janeiro Rio de Janeiro, Brazil Laura de Castro Department of Animal Health University of León León, Spain Giovanni Cattoli Istituto Zooprofilattico Sperimentale delle Venezie Research and Development Department OIE/FAO and National Reference Laboratory for Newcastle Disease and Avian Influenza OIE Collaborating Center for Epidemiology, Training and Control of Emerging Avian Diseases Legnaro, Padova, Italy

Cody Coyne Department of Basic Sciences College of Veterinary Medicine Mississippi State University Mississippi State, Mississippi Paola Cremonesi Institute of Agricultural Biology and Biotechnology Italian National Research Council Milan, Italy Maria Teresa Barreto Crespo Instituto de Biologia Experimental e Tecnológica (IBET) Av. da República, Quinta do Marquês Oeiras, Portugal Andrew Csordas Institute for Collaborative Biotechnologies University of California, Santa Barbara Santa Barbara, California Daniele Daffonchio Department of Food Science and Microbiology University of Milan Milan, Italy Sascha Al Dahouk Department of Internal Medicine III RWTH Aachen University Aachen, Germany

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Contributors

Stefano D’Amelio Department of Public Health Science Sapienza University of Rome Rome, Italy

Yaoyu Feng School of Resource and Environmental Engineering East China University of Science and Technology Shanghai, People’s Republic of China

Marie-Laure Dardé Laboratoire de Parasitologie-Mycologie CHU Limoges, France

Maria Fredriksson-Ahomaa Institute of Hygiene and Technology of Food of Animal Origin Ludwig-Maximilian University Munich, Germany

Jonathan J. Dennis Department of Biological Sciences University of Alberta Edmonton, Alberta, Canada Rubens Clayton da Silva Dias Division of Infectious Diseases and Immunity School of Public Health University of California Berkeley, California J.P. Dubey United States Department of Agriculture, Agricultural Research Service Animal and Natural Resources Institute Animal Parasitic Diseases Laboratory Beltsville, Maryland Joëlle Dupont Muséum National d’Histoire Naturelle Département Systématique et Evolution Paris, France Jean Dupouy-Camet Laboratoire de Parasitologie-Mycologie Hôpital Cochin AP-H Université Paris Descartes Paris, France Ron Dzikowski Department of Microbiology & Molecular Genetics The Kuvin Center for the Study of Infectious and Tropical Diseases The Institute for Medical Research Israel-Canada The Hebrew University–Hadassah Medical School Jerusalem, Israel John Ellis Department of Medical and Molecular Biosciences University of Technology Sydney Broadway, Australia Seamus Fanning Centre for Food Safety, School of Agriculture, Food Science and Veterinary Medicine Veterinary Sciences Centre University College Dublin Dublin, Ireland

Antonia Gallo Institute of Sciences of Food Production National Research Council (ISPA-CNR) Bari, Italy María-Luisa García-López Department of Food Hygiene and Food Microbiology University of León León, Spain Charles P. Gerba Department of Soil, Water and Environmental Science University of Arizona Tucson, Arizona Elisabetta Giuffra Parco Tecnologico Padano Lodi, Italy Pablo Goldschmidt Laboratoire du Centre National d’Ophtalmologie des Quinze-Vingts Paris, France Lisa Gorski Produce Safety and Microbiology Research Unit United States Department of Agriculture Agricultural Research Service Western Regional Research Center Albany, California Irene R. Grant School of Biological Sciences Queen’s University Belfast Belfast, Northern Ireland, United Kingdom Saija Hallanvuo Department of Animal Diseases and Food Safety Research Finnish Food Safety Authority Evira Helsinki, Finland Grant S. Hansman Department of Virology II National Institute of Infectious Diseases Musashi-murayama Tokyo, Japan

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Larry A. Hanson Department of Basic Sciences College of Veterinary Medicine Mississippi State University Mississippi State, Mississippi Romney S. Haylett Institute of Immunology RWTH Aachen University Hospital Aachen, Germany Annamari Heikinheimo Department of Food and Environmental Hygiene University of Helsinki Helsinki, Finland Samantha J. Hibbitts Department of Obstetrics and Gynaecology Cardiff University University Hospital of Wales Cardiff, Wales, United Kingdom Friederike Hilbert Institute of Meat Hygiene, Meat Technology and Food Science University of Veterinary Medicine Vienna, Austria Jeffrey Hoorfar National Food Institute Technical University of Denmark Søborg, Denmark Kurt Houf Department of Veterinary Public Health and Food Safety Ghent University Merelbeke, Belgium Zhi-Qing Hu Department of Microbiology and Immunology Showa University School of Medicine Tokyo, Japan Zhuting Hu Department of Biology International Christian University Tokyo, Japan

Contributors

Akira Ito Department of Parasitology Asahikawa Medical College Asahikawa, Japan Carol Iversen Centre for Food Safety, School of Agriculture, Food Science and Veterinary Medicine Veterinary Sciences Centre University College Dublin Dublin, Ireland Ferenc Jakab Department of Genetics and Molecular Biology Institute of Biology, Faculty of Sciences University of Pécs Pécs, Hungary Somchai Jongwutiwes Molecular Biology of Malaria and Opportunistic Parasites Research Unit Department of Parasitology Chulalongkorn University Bangkok, Thailand Pattara Khamrin Aino Health Science Center Aino University Tokyo, Japan Rickard Knutsson Department of Bacteriology National Veterinary Institute Uppsala, Sweden Hannu Korkeala Department of Food and Environmental Hygiene University of Helsinki Helsinki, Finland Thewarach Laha Department of Parasitology Liver Fluke and Cholangiocarcinoma Research Center Khon Kaen University Khon Kaen, Thailand

Wei-Yi Huang Department of Veterinary Medicine College of Animal Science and Technology Guangxi University Nanning, Guangxi, People’s Republic of China

Susanne Thisted Lambertz Research and Development Department National Food Administration Uppsala, Sweden

Sofia Ingrosso Department of Public Health Science Sapienza University of Rome Rome, Italy

Keith A. Lampel Food and Drug Administration Division of Microbiology College Park, Maryland

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Contributors

Angelika Lehner Institute for Food Safety and Hygiene University of Zurich Zurich, Switzerland

Burkhard Malorny Federal Institute for Risk Assessment National Salmonella Reference Laboratory Berlin, Germany

Michael G. Levy Department of Population Health and Pathobiology College of Veterinary Medicine North Carolina State University Raleigh, North Carolina

Niwat Maneekarn Department of Microbiology, Chiang Mai University Chiang Mai, Thailand

Diego Libkind Laboratorio de Microbiología Aplicada y Biotecnología Instituto de Investigaciones en Biodiversidad y Medio Ambiente (INIBIOMA) Universidad Nacional del Comahue CRUB – Consejo Nacional de Investigaciones Científicas y Tecnológicas (CONICET) Bariloche, Río Negro, Argentina Rui-Qing Lin Laboratory of Parasitology College of Veterinary Medicine South China Agricultural University Guangzhou, Guangdong, People’s Republic of China Mark van der Linden Institute of Medical Microbiology and National Reference Center for Streptococci RWTH Aachen University Hospital Aachen, Germany Miia Lindström Department of Food and Environmental Hygiene University of Helsinki Helsinki, Finland Dongyou Liu Department of Basic Sciences College of Veterinary Medicine Mississippi State University Mississippi State, Mississippi Charlotta Löfström National Food Institute Technical University of Denmark Søborg, Denmark

Heinz Mehlhorn Department of Parasitology Heinrich Heine University Düsseldorf, Germany Edina Meleg Department of Biophysics Faculty of Medicine University of Pécs Pécs, Hungary Marco Antonio Lemos Miguel Instituto de Microbiologia Universidade Federal do Rio de Janeiro Rio de Janeiro, Brazil Isabella Monne Istituto Zooprofilattico Sperimentale delle Venezie Research and Development Department OIE/FAO and National Reference Laboratory for Newcastle Disease and Avian Influenza OIE Collaborating Center for Epidemiology, Training and Control of Emerging Avian Diseases Legnaro, Padova, Italy Beatriz Meurer Moreira Instituto de Microbiologia Universidade Federal do Rio de Janeiro Rio de Janeiro, Brazil Antonio Moretti Institute of Sciences of Food Production National Research Council (ISPA-CNR) Bari, Italy

José María Luengo Department of Biochemistry and Molecular Biology University of León León, Spain

Paolo Moroni Department of Veterinary Pathology Hygiene and Public Health University of Milan Milan, Italy

Karlene H. Lynch Department of Biological Sciences University of Alberta Edmonton, Alberta, Canada

Boris Müller Department of Parasitology Heinrich Heine University Düsseldorf, Germany

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Contributors

Germán Naharro Department of Animal Health University of León León, Spain

Lia Paggi Department of Public Health Science Sapienza University of Rome Rome, Italy

Minoru Nakao Department of Parasitology Asahikawa Medical College Asahikawa, Japan

Anubhav Pandey Department of Microbiology All India Institute of Medical Sciences New Delhi, India

Kazuhiro Nakaya Laboratory Animals for Medical Research Asahikawa Medical College Asahikawa, Japan

Giancarlo Perrone Institute of Sciences of Food Production National Research Council (ISPA-CNR) Bari, Italy

Kanwar Narain Regional Medical Research Centre, N.E. Region Indian Council of Medical Research Dibrugarh, Assam, India

Michael D. Perry NPHS Microbiology Cardiff University Hospital of Wales Cardiff, Wales, United Kingdom

Karsten Nöckler Federal Institute for Risk Assessment Berlin, Germany Norihisa Noguchi Department of Microbiology School of Pharmacy Tokyo University of Pharmacy and Life Sciences Hachioji, Tokyo, Japan Birgit Nørrung Department of Veterinary Pathobiology University of Copenhagen Frederiksberg C, Denmark F. Nuñez Higiene y Seguridad Alimentaria Facultad de Veterinaria Universidad de Extremadura Cáceres, Spain Munehiro Okamoto Department of Parasitology School of Veterinary Medicine Tottori University Tottori, Japan Takashi Onodera Department of Molecular Immunology, School of Agricultural and Life Sciences University of Tokyo Bunkyo-ku, Tokyo, Japan Andrés Otero Department of Food Hygiene and Food Microbiology University of León León, Spain

G. Todd Pharr Department of Basic Sciences College of Veterinary Medicine, Mississippi State University Mississippi State, Mississippi Lesya M. Pinchuk Department of Basic Sciences College of Veterinary Medicine Mississippi State University Mississippi State, Mississippi Giuliano Pisoni Department of Veterinary Pathology Hygiene and Public Health University of Milan Milan, Italy Edoardo Pozio Department of Infectious, Parasitic and Immunomediated Diseases Istituto Superiore di Sanità Rome, Italy Stephen B. Pruett Department of Basic Sciences College of Veterinary Medicine, Mississippi State University Mississippi State, Mississippi Chaturong Putaporntip Molecular Biology of Malaria and Opportunistic Parasites Research Unit Department of Parasitology Chulalongkorn University Bangkok, Thailand

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Contributors

Noura Raddadi Department of Food Science and Microbiology University of Milan Milan, Italy

Franca Rossi Dipartimento di Biotecnologie Universita degli Studi di Verona Verona, Italy

Peter Rådström Applied Microbiology Lund Institute of Technology Lund University Lund, Sweden

Antoni Róz∙ alski Institute of Microbiology and Immunology University of Łódz´ Łódz´, Poland

Catherine E.D. Rees School of Biosciences University of Nottingham Sutton Bonington Campus Leicestershire, England, United Kingdom Ralf René Reinert Wyeth Vaccines Research Paris la Défense, France Jorge Riaño Department of Animal Health University of León León, Spain Lothar Rink Institute of Immunology RWTH Aachen University Hospital Aachen, Germany Aurora Rizzi Department of Food Science and Microbiology University of Milan Milan, Italy M. Rodríguez Higiene y Seguridad Alimentaria Facultad de Veterinaria Universidad de Extremadura Cáceres, Spain Roberto A. Rodríguez Department of Environmental Science and Engineering University of North Carolina Chapel Hill, North Carolina Giuseppe La Rosa Department of Infectious, Parasitic and Immunomediated Diseases Istituto Superiore di Sanità Rome, Italy Benjamin M. Rosenthal United States Department of Agriculture Agricultural Research Service Animal Natural Resources Institute Animal Parasitic Diseases Laboratory Beltsville, Maryland

Una Ryan Division of Health Sciences School of Veterinary and Biomedical Science Murdoch University Perth, Australia Yasuhito Sako Department of Parasitology Asahikawa Medical College Asahikawa, Japan Akikazu Sakudo Department of Virology, Research Institute for Microbial Diseases Osaka University Suita, Osaka, Japan José Paulo Sampaio Centro de Recursos Microbiológicos Departamento de Ciências da Vida Universidade Nova de Lisboa Caparica, Portugal Jesús A. Santos Department of Food Hygiene and Food Microbiology University of León León, Spain Jenny Schelin Applied Microbiology Lund Institute of Technology Lund University Lund, Sweden Jürgen Schmidt Department of Parasitology Heinrich Heine University Düsseldorf, Germany Keith R. Schneider Food Science and Human Nutrition Department University of Florida Gainesville, Florida Anna Charlotte Schultz National Food Institute Technical University of Denmark (DTU) Søborg, Denmark

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Contributors

Bo Segerman Department of Bacteriology National Veterinary Institute Uppsala, Sweden

Roger Stephan Institute for Food Safety and Hygiene University of Zurich Zurich, Switzerland

Teresa Semedo-Lemsaddek Universidade de Lisboa Center for Biodiversity Functional and Integrative Genomics (BioFIG) Edifício ICAT, Campus da FCUL, Campo Grande Lisbon, Portugal

Chunlei Su Department of Microbiology University of Tennessee Knoxville, Tennessee

Devendra H. Shah Department of Veterinary Microbiology and Pathology College of Veterinary Medicine Washington State University Pullman, Washington Nidhi Sharma Department of Microbiology All India Institute of Medical Sciences New Delhi, India Smriti Shringi Department of Veterinary Microbiology and Pathology College of Veterinary Medicine Washington State University Pullman, Washington Paiboon Sithithaworn Department of Parasitology Liver Fluke and Cholangiocarcinoma Research Center Khon Kaen University Khon Kaen, Thailand Mikael Skurnik Department of Bacteriology and Immunology Infection Biology Research Program, Haartman Institute, University of Helsinki Helsinki, Finland and Helsinki University Central Hospital Laboratory Diagnostics Helsinki, Finland

Katsuaki Sugiura Food and Agricultural Materials Inspection Centre Chuo-ku, Saitama-shi Saitama, Japan Antonia Susca Institute of Sciences of Food Production National Research Council (ISPA-CNR) Bari, Italy Isabella Tamagnini Department of Food Science and Microbiology University of Milan Milan, Italy Rogério Tenreiro Universidade de Lisboa Center for Biodiversity Functional and Integrative Genomics (BioFIG) Edifício ICAT, Campus da FCUL, Campo Grande Lisbon, Portugal Herbert Tomaso Friedrich Loeffler Institute Institute of Bacterial Infections and Zoonoses Jena, Germany Sandra Torriani Dipartimento di Scienze, Tecnologie e Mercati della Vite e del Vino Università degli Studi di Verona Verona, Italy

Paweł Sta˛ czek Institute of Microbiology and Immunology University of Łódz´ Łódz´, Poland

Hiroshi Ushijima Aino Health Science Center Aino University Tokyo, Japan

Damien Stark Division of Microbiology, SydPath St. Vincent‘s Hospital Darlinghurst, Australia

Jaco J. Verweij Department of Parasitology Leiden University Medical Center Leiden, the Netherlands

xxv

Contributors

Jan Vinjé Division of Viral Diseases Center for Disease Control (CDC) Atlanta, Georgia

Jae-Ran Yu Department of Environmental and Tropical Medicine Konkuk University School of Medicine Seoul, Korea

Benjamin R. Warren Research, Quality, & Innovation ConAgra Foods, Inc. Omaha, Nebraska

Olga Zaborina Center for Surgical Infection Research and Therapeutics University of Chicago Chicago, Illinois

P. Lewis White NPHS Microbiology Cardiff University Hospital of Wales Cardiff, Wales, United Kingdom Lihua Xiao Division of Parasitic Diseases Centers for Disease Control and Prevention Atlanta, Georgia Guangai Xue Department of Molecular Immunology School of Agricultural and Life Sciences University of Tokyo Bunkyo-ku, Tokyo, Japan Tetsuya Yanagida Department of Parasitology Asahikawa Medical College Asahikawa, Japan Hélène Yera Laboratoire de Parasitologie-Mycologie Hôpital Cochin AP-HP Université Paris Descartes Paris, France

Gianluigi Zanusso Department of Neurological Sciences University of Verona Verona, Italy Wei-Hua Zhao Department of Microbiology and Immunology Showa University School of Medicine Tokyo, Japan Xing-Quan Zhu Laboratory of Parasitology College of Veterinary Medicine South China Agricultural University Guangzhou, Guangdong, People’s Republic of China Qing-Jun Zhuang Laboratory of Parasitology College of Veterinary Medicine South China Agricultural University Guangzhou, Guangdong, People’s Republic of China

Detection: 1 Molecular Principles and Methods Lisa Gorski

United States Department of Agriculture

Andrew Csordas

University of California

Contents 1.1 Introduction........................................................................................................................................................................... 1 1.2 Detection Methods................................................................................................................................................................ 3 1.2.1 Pathogen Detection in Complex Matrices—Sample Preparation.............................................................................. 3 1.2.2 Nucleic Acid Based Detection................................................................................................................................... 3 1.2.2.1 PCR............................................................................................................................................................. 3 1.2.2.2 Isothermal Amplification............................................................................................................................ 7 1.2.2.3 Microarray Detection.................................................................................................................................. 8 1.2.3 Fluorescence in situ Hybridization (FISH)................................................................................................................ 8 1.2.4 Immunological Detection Methods........................................................................................................................... 8 1.2.5 Combined Detection Methods................................................................................................................................... 9 1.2.6 Foodborne Pathogen Typing...................................................................................................................................... 9 1.2.7 Microfabrication and Microfluidics........................................................................................................................... 9 1.2.8 Other Molecular Detection Approaches.................................................................................................................... 9 1.2.9 Assay Design and Data Analysis Software.............................................................................................................. 10 1.3 Detection Targets................................................................................................................................................................. 10 1.3.1 Viral Targets............................................................................................................................................................ 10 1.3.1.1 RNA Targets.............................................................................................................................................. 11 1.3.1.2 Viral Structural Genes.............................................................................................................................. 11 1.3.1.3 Other Viral Targets.................................................................................................................................... 11 1.3.2 Nonviral Targets...................................................................................................................................................... 11 1.3.2.1 Ribosomal RNA Genes . .......................................................................................................................... 11 1.3.2.2 Cytoskeleton Proteins................................................................................................................................ 12 1.3.2.3 Virulence and Toxin Genes....................................................................................................................... 12 1.3.2.4 Unique Genes and Sequences................................................................................................................... 12 1.3.2.5 Insertion Elements..................................................................................................................................... 13 1.3.2.6 Mitochondrial Genes................................................................................................................................. 13 1.3.2.7 Genes for Surface Expressed Markers...................................................................................................... 13 1.3.3 Using Multiple Targets............................................................................................................................................. 14 1.4 Validation............................................................................................................................................................................ 14 1.5 Conclusions.......................................................................................................................................................................... 14 Acknowledgments........................................................................................................................................................................ 15 References.................................................................................................................................................................................... 15

1.1  Introduction While the vast majority of our food supplies are nutritious and safe, illness due to foodborne pathogens still affects millions if not billions of people each year. It is estimated that up to 30% of the population in industrialized nations suffer

from foodborne illness each year.1 In the U.S. there are an estimated 76 million cases each year that result in 325,000 hospitalizations, and 5000 deaths.2 Estimates of the number of cases in developing countries are difficult to obtain due to differences in reporting of cases in different countries; however, the rates of illness are expected to be higher.1,3,4 1

2

Molecular Detection of Foodborne Pathogens

Diarrheal diseases, a high number of which result from foodborne contamination, kill an estimated 1.8 million children worldwide.3 Table 1.1 summarizes the statistics of U.S. foodborne illness outbreaks for the year 2006 broken down by etiology. An outbreak is constituted by more than one person becoming ill by the same strain of an organism. The list displays only outbreaks from known etiologies of bacterial, viral, parasitic, and helminthic origin, and does not take into account outbreaks where an etiology could not be assigned. Nor does it take into account sporadic cases of illness, which far outnumber outbreak cases. Most of these sporadic cases are not reported to any official health tracking agency because they are not severe, or cultures are never obtained.1 An even greater number of people with sporadic cases of foodborne illness do not seek medical attention. Whether an illness is mild or severe, the underlying message from the statistics is that millions or billions of servings of food are contaminated with a pathogen or a toxin each year. Table 1.1 illustrates that the types of foods implicated is broad and comprises meats, dairy, produce, grains, processed foods, and water. While many cases of foodborne illness result from human cross-contamination in restaurants or in the home, a large amount results from foods that arrive

into the kitchen already contaminated. These organisms can contaminate the foods directly by association with feed animals or plants prior to or during processing, through contaminated water used for watering or washing, and through handling by infected people. One of the most difficult and fundamental issues in food safety is the detection of foodborne pathogens. The problem is terribly complex with a multitude of factors and variables with which to contend. With the infectious dose of some of the pathogens as low as 90%) among species demonstrated by DNA–DNA hybridization,14 due to identical 16S rRNA sequences among all Brucella species,106 and because more than 90% of all genes share >98% sequence identity.107 Nevertheless, various methods have been established for molecular subtyping of Brucella strains, e.g., AP-PCR (arbitrary primed-PCR),108 ERIC-PCR (enterobacterial repetitive intergenic consensus sequence-PCR), REPPCR (repetitive intergenic palindromic sequence-PCR),109,110 RAPD-PCR (random amplified polymorphic DNA-PCR),111 PCR-RFLP (PCR-restriction fragment length polymorphism) of different genetic loci,112 AFLP (amplified fragment length polymorphism),113 SNP114,115 and MLST (multi locus sequence typing).116 However, most of these tests lack reproducibility, show a limited capability to differentiate single strains, are more demanding than simple PCR typing methods or are not appropriate for routine typing. Recently, the genomes of B. melitensis 16M,117 B. suis 1330118 and B. abortus strain 9-941107 have been sequenced completely. DNA sequence variability required for subtyping or epidemiological trace-back of Brucella strains can now be deduced by direct comparison of genome sequences. Hence, tandem repeat loci predicted to display size polymorphism

323

Brucella

could be identified. Variable number tandem repeats (VNTRs) which are commonly used for DNA fingerprinting in forensic applications also exist in bacterial genomes and seem to be highly discriminatory markers, even when the pathogens investigated belong to monomorphic species such as Brucella.119–121 Tandem repeats are composed of perfect or imperfect copies of an elementary unit and various alleles can be observed in different bacterial strains within a species. Fingerprints resulting from analysis of multiple loci can be highly discriminating or even unique. Multiple locus variable number tandem repeats analysis (MLVA) has proven to be highly discriminatory among unrelated Brucella isolates that could not be differentiated by classical microbiological methods. The hypervariability found by MLVA is in contrast to the well-known genetic homogeneity of the genus. However, tandem repeats generally mutate at different rates.122 Some loci cluster Brucella isolates in accordance with the identified species, presumably because they mutate slowly and have a relatively low homoplasy rate. Others have a higher discriminatory index and Brucella isolates originating from a restricted geographical area can still be discriminated indicating the potential of VNTRs as an epidemiological tool.119 The hypermutability of VNTR loci has already been exploited for Brucella strain typing in large panels of animal isolates.120–124 Based on simple PCR techniques, Brucella-MLVA is accessible to a wide range of users. The alleles (PCR amplicons) can be analyzed by simple agarose gel electrophoresis or automatic high-throughput procedures. Standardization and quality control are easy to achieve. Especially in an outbreak setting including a great number of cases high-throughput screening is possible without manipulation of the living agent. Last but not least, the MLVA data can be easily coded and exchanged by the repeat copy numbers for each locus and strain. Currently, MLVA is the most suitable molecular method for subtyping brucellae which fulfils all the recommended performance criteria of a typing assay, i.e., typeability, reproducibility, stability, discriminatory power, concordance with other typing techniques and epidemiological concordance.123

fresh milk and tissue, and also from paraffin-embedded tissue samples.80,126 Queipo-Ortuno et al. evaluated seven commercially available DNA extraction kits using human serum samples and obtained the best results with the UltraCleanTM DNA BloodSpin Kit (MO BIO Laboratories Inc., Carlsbad, CA),127 which was also successfully used by Navarro et al.128 However, comprehensive evaluation studies on DNA extraction methods in animal and food samples are still missing.

23.2.2  Detection Procedures 23.2.2.1  Multiplex PCR A previously described AMOS-PCR is highly effective for differentiation of B. abortus, B. melitensis, B. ovis and B. suis96 (Table 23.2). This PCR employs one primer (IS711) for binding with the insertion sequence IS711, which is present in all Brucella species, and four primers for recognizing the speciesspecific regions downstream of this insertion sequence, leading to formation of variable sizes of amplicons from the four Brucella species, and facilitating their identification (Figure 23.1). Table 23.2 Primers for AMOS-PCR Primer BA BM BS BO IS711

Sequence 5´-GAC GAA CGG AAT TTT TCC AAT CCC-3´ 5´-AAA TCG CGT CCT TGC TGG TCT GA-3´ 5´-GCG CGG TTT TCT GAA GGT TCA GG-3´ 5´-CGG GTT CTG GCA CCA TCG TCG-3´ 5´-TGC CGA TCA CTT AAG GGC CTT CAT-3´

23.2  Methods

B. melitensis

B. suis

Both specificity and sensitivity of the most commonly used bcsp31 PCR have proven to be high at least in colony material.99,125 The limit of detection can be lower than 20 fg of DNA when determined on the basis of purified DNA obtained from colonies. In contrast, the low number of bacteria usually present in clinical samples may be a limiting factor for real-time PCR assays. Due to the small number of brucellae in clinical specimens, special methods for DNA preparation are required to reduce inhibitory effects caused by matrix components and to concentrate the DNA. Blood, milk, diary products, tissue, semen, and vaginal swabs can be valuable specimens for direct detection of Brucella DNA. Commercial kits such as the QIAampTM DNA Mini Kit (Qiagen Inc., Valencia, CA) can be used to extract DNA from

B. abortus

23.2.1  Sample Collection and Preparation

Figure 23.1  Identification and differentiation of B. abortus, B. melitensis, and B. suis using AMOS-PCR based on the repetitive DNA sequence IS711. (From Bricker, B.J. and Halling, S.M., J. Clin. Microbiol., 11, 2660, 1994.)

324

Molecular Detection of Foodborne Pathogens

Table 23.3 Primers for Brucella Multiplex PCR Primers BMEI0998f BMEI0997r BMEI0535f BMEI0536r BMEII0843f BMEII0844r BMEI1436f BMEI1435r BMEII0428f BMEII0428r BR0953f BR0953r BMEI0752f BMEI0752r BMEII0987f BMEII0987r Bmispec f Bmispec r

Sequence

Amplicon Size (bp)

5´-ATC CTA TTG CCC CGA TAA GG-3´ 5´-GCT TCG CAT TTT CAC TGT AGC-3´ 5´-GCG CAT TCT TCG GTT ATG AA-3´ 5´-CGC AGG CGA AAA CAG CTA TAA-3´ 5´-TTT ACA CAG GCA ATC CAG CA-3´ 5´-GCG TCC AGT TGT TGT TGA TG-3´ 5´-ACG CAG ACG ACC TTC GGT AT-3´ 5´-TTT ATC CAT CGC CCT GTC AC-3´ 5´-GCC GCT ATT ATG TGG ACT GG-3´ 5´-AAT GAC TTC ACG GTC GTT CG-3´ 5´-GGA ACA CTA CGC CAC CTT GT-3´ 5´-GAT GGA GCA AAC GCT GAA G-3´ 5´-CAG GCA AAC CCT CAG AAG C-3´ 5´-GAT GTG GTA ACG CAC ACC AA-3´ 5´-CGC AGA CAG TGA CCA TCA AA-3´ 5´-GTA TTC AGC CCC CGT TAC CT-3´ 5´-AGA TAC TGG AAC ATA GCC CG-3´ 5´-ATA CTC AGG CAG GAT ACC GC-3´

1,682 450 (1,320 in Brucella strains isolated from marine mammals) 1,071 794 587 272 218 152 510

BMEI and BMEII numbers designate loci in the B. melitensis genome; BR numbers designate loci in the B. suis genome; f, forward; r, reverse.

Table 23.4 Multiplex PCR Cycling Program Cycles 1 25

23.2.2.2  Real-Time PCR Real-time PCR assays targeting bcsp31 described by Probert et al. and Al Dahouk et al. can be recommended for the detection of Brucella for screening purposes (Tables 23.1 through 23.6).99,102 Assays for the species-specific identification of B. melitensis described by Redkar et al. and Probert et al. are also very sensitive (Table 23.8).99,100,102 Assays designed for the detection of B. abortus by Redkar et al., Probert et al., and Newby et al. only detected biotypes 1, 2, and 4, because of the more distant relatedness of other biotypes (Table 23.7).100–102 A real-time PCR assay specific for B. suis biotype 1 was also established by Redkar et al.100

B. microti

B. ceti

B. pinnipedialis

B. neotomae

To identify all Brucella species and the vaccine strains, B. abortus RB51, B. abortus S19, and B. melitensis Rev1, another multiplex PCR assay97 can be applied. Use of primers and PCR conditions shown in Tables 23.3 and 23.4 will result in the amplification of distinct bands from all Brucella species (Figure 23.2).97

B. canis

1

B. ovis

15 min 30 sec 90 sec 120 sec 10 min

B. melitensis

Time

95 94 58 72 72

B. suis

Temperature (°C)

B. abortus

Initial denaturation Denaturation Annealing Extension Last extension

Figure 23.2  Identification and differentiation of all Brucella species by a multi-locus multiplex PCR. (From García-Yoldi, D. et al., Clin. Chem., 52, 779, 2006.)

Hybridization probes technology offers melting curve analysis which provides typical signals for specific amplification products. 5′-exonuclease assays are very useful for large scale screening as they can be performed on platforms including 96 or 384 tests in parallel. Since real-time PCR assays for the detection of biologic agents can be easily transferred from one technical platform to another,129 diagnostic laboratories are able to choose between hybridization probes technology and 5′-exonuclease assays to meet

325

Brucella

Table 23.5 Real-Time PCR Assay Targeting bcsp31 for the Specific Detection of the Genus Brucella A. PCR mixture makeup Reagent

Stock Concentration (pmol/µl=µM)

Brucella spp. (bcsp31)

Water 25 mM MgCl2 10 × concentrated Reaction mix

LightCycler FastStart DNA Master Hybridization Probes Cat. No. 2 239 272

Primers and probes (5´-3´) B4 B5 Bru FL Bru LC Lambda F Lambda R Lambda FL Lambda LC Phage lambda DNA* Sample DNA

TGGCTCGGTTGCCAATATCAA CGCGCTTGCCTTTCAGGTCTG AGGCAACGTCTGACTGCGTAAAGCC LC Red 640-ACTCCAGAGCGCCCGACTTGATCG ATGCCACGTAAGCGAAACA GCATAAACGAAGCAGTCGAGT GGTGCCGTTCACTTCCCGAATAAC X LC Red 705-CGGATATTTTTGATCTGACCGAAGCG p Plasmid DNA

µl Per Reaction

Final Concentration (in 20 µl)

9.8 1.2

2.5 mM

2

20 pmol/µl 20 pmol/µl 8 µM 8 µM 20 pmol/µl 20 pmol/µl 8 µM 8 µM

0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 1 2

0.5 µM 0.5 µM 0.2 µM 0.2 µM 0.5 µM 0.5 µM 0.15 µM 0.15 µM

Temperature (°C)

Time

Slope (°C/s)

Acquisition Mode

95

10 min

20

None

95 55 72 95 55 95 40

10 sec 10 sec 12 sec 0 30 sec 0 30 sec

20 20 20 20 20 0.1 20

None Single None None None Continuous None

B. PCR Parameter Parameter Activation of Fast Start Taq DNA polymerase Amplification (45 cycles)

Melting curve analysis Cooling

The assay specifically detects all brucellae but no other organisms with a detection limit of 16 fg DNA in buffer. *Inclusion of an internal amplification control is especially useful for clinical samples (Al Dahouk, S. et al., Clin. Chem. Lab. Med., 45, 1464, 2007).

their demands. Ready to use protocols for the detection of Brucella and the identification of the most relevant species by means of real-time PCR assays are given in the Tables 23.5 through 23.8.

23.3 Conclusions and Future Perspectives In the diagnosis of brucellosis time-consuming culture and phenotypic characterization of the isolate is the “gold standard.” The low yield of Brucella cultures, however, often results in diagnostic delay and the late initiation of appropriate countermeasures. Serology is a more effective means of diagnostic, although cross-reactivity in the setting of other bacterial infections is still a major problem. PCR has proven to be a valuable tool when culture fails or serological results are inconclusive, and in addition, a test result can be available within a few hours. PCR assays targeting more than one gene of the Brucella genome may enhance the likelihood of detection. Genus-specific primers and probes

should always be included in a diagnostic scheme to detect infrequently isolated Brucella species and atypical strains. However, a positive result in a genus-specific real-time PCR has to be specified by a species-specific assay. Serological tests should be performed in parallel to further consolidate the diagnosis as the number of constantly seronegative animals is low. There has been controversial discussion about the preferred clinical specimen, the best method of DNA extraction, and the PCR assays with the lowest limit of detection. Most results were not reproducible in different laboratories which demonstrate the complexity of PCR procedures including DNA extraction from clinical specimens. PCR assays targeting different genes may help to exclude false positive results due to contamination. In order to determine inhibitory effects of the matrix an internal amplification control should be integrated in all assays. Since practical experiences may vary between laboratories concerning optimal DNA preparation and PCR assays, results obtained with molecular methods generally have to be evaluated in

326

Molecular Detection of Foodborne Pathogens

Table 23.6 Real-time 5′-Exonuclease Assay Targeting bcsp31 for Large Scale Screening of the Genus Brucella A. PCR Mixture Makeup Reagent

Stock Concentration (pmol/µl=µM)

Brucella spp. (bcsp31)

5.5

Water Reaction buffer

µl Per Reaction

TaqMan Universal MasterMix (uMM) Applied Biosystems Cat. No. 4304447

2×

Final Concentration (in 25 µl)  

12.5

1 ×

Primers and probes (5´-3´) Brucella spp fw GCTCGGTTGCCAATATCAATGC

10 µM

0.75

0.3 µM

Brucella spp rev

GGGTAAAGCGTCGCCAGAAG

10 µM

0.75

0.3 µM

Brucella spp. Taq

6FAM-AAATCTTCCACCTTGCCCTTGCCATCA-DB

10 µM

0.5

0.2 µM

Sample DNA

5 B. PCR parameter Temperature (°C)

Time

Cycle 1

Decontamination

50

2 min

Initial denaturation

95

10 min

1

Denaturation

95

15 sec

45

Annealing

57

1 min

The assay specifically detects all brucellae but no other organisms with a detection limit of 16 fg DNA in buffer. Source:  Probert, W.S. et al., J. Clin. Microbiol., 42, 1290, 2004.

Table 23.7 Real-Time PCR Assay Targeting alkB/IS711 for the Specific Detection of B. abortus Designed as 5′-Exonuclease Assay for Large Scale Screening A. PCR Mixture Makeup Reagent

Brucella abortus alkB/IS711

Stock Concentration (pmol/µl=µM)

Water Reaction buffer

TaqMan Universal MasterMix (uMM) Applied Biosystems

2×

µl Per Reaction

Final Concentration (in 25 µl)

5.5

 

12.5

1 ×

Primers and probes (5´-3´) B. abortus fw GCGGCTTTTCTATCACGGTATTC

10 µM

0.75

0.3 µM

B. abortus rev

CATGCGCTATGATCTGGTTACG

10 µM

0.75

0.3 µM

B. abortus Taq

6FAM-CGCTCATGCTCGCCAGACTTCAATG-DB

10 µM

0.5

0.2 µM

Sample DNA

5 B. PCR Parameter Temperature (°C)

Time

Cycle

Decontamination

50

2 min

1

Initial denaturation

95

10 min

1

Denaturation

95

15 sec

45

Annealing

57

1 min

This assay specifically detects B. abortus bv 1, 2, and 4, but other biotypes cannot be detected reliably. The detection limit is 18 fg DNA in buffer. Source:  Probert, W.S. et al., J. Clin. Microbiol., 42, 1290, 2004.

327

Brucella

Table 23.8 Real-Time PCR Assay Targeting BMEI1162/IS711 for the Specific Detection of Brucella melitensis Designed as 5′-Exonuclease Assay for Large Scale Screening A. PCR Mixture Makeup Reagent

Stock Concentration (pmol/µl=µM)

Brucella Melitensis BMEI1162/IS711

Water Reaction buffer

TaqMan Universal MasterMix (uMM) Applied Biosystems

2×

Primers and probes (5´-3´) B. melitensis fw AACAAGCGGCACCCCTAAAA

µl Per Reaction

Final Concentration (in 25 µl)

5,5

 

12.5

1 ×

10 µM

0.75

0.3 µM

B. melitensis rev

CATGCGCTATGATCTGGTTACG

10 µM

0.75

0.3 µM

B. melitensis Taq

6FAM-CAGGAGTGTTTCGGCTCAGAATAATCCACA-DB

10 µM

0.5

0.2 µM

Sample DNA

5 B. PCR Parameter Temperature (°C)

Time

Cycle

Decontamination

50

2 min

1

Initial denaturation

95

10 min

1

Denaturation

95

15 sec

45

Annealing

57

1 min

This assay specifically detects all B. melitensis isolates but no other organisms with a detection limit of 16 fg DNA in buffer. Source:  Probert, W.S. et al., J. Clin. Microbiol., 42, 1290, 2004.

the context of other diagnostic tests. Currently, it seems to be unlikely that conventional or real-time PCR will supersede microbiological methods for detection of Brucella in clinical samples. For instance, O’Leary et al. obtained positive real-time PCR results only in a small proportion of culture-positive milk (44%) and supramammary lymph tissue samples (75%) in cattle naturally infected with B. abortus.80 Debeaumont et al. tested serum samples of brucellosis patients for their bacterial DNA load by a quantitative bcsp31-based real-time PCR.130 Approximately 25–650 genomic copies per 5 µl of DNA extract were found. QueipoOrtuno et al. were able to detect one bacterial cell in a serial dilution spiked with B. abortus B19 in 200 µl serum.131 Hence, the small sample volume (2–5 µl) used in real-time PCR systems may also be a serious disadvantage. The main reasons why PCR results in the diagnosis of brucellosis have always been variable when compared to serology and bacteriology are (i) the stage of infection which may influence the number and location of bacteria, (ii) the presence of large amounts of host genomic DNA that may have inhibitory effects on the PCR assay, (iii) the method of DNA extraction which may be crucial for the detection of the bacterium by molecular methods. Most real-time PCR assays developed for the detection of Brucella can detect less than ten bacteria per reaction, which is close to the technical limit of this method. Additionally, a variety of DNA purification methods has been established to

eliminate inhibitory components of the matrix. Limitations are the small number of brucellae in clinical specimens of infected animals and the small amount of DNA used in PCR assays. Due to these biological and technical limitations, no significant advantage of PCR methods compared to standard serological and bacteriological methods could have been demonstrated so far.

References



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8. Al Dahouk, S. et al. Laboratory-based diagnosis of brucellosis – a review of the literature. Part I: techniques for direct detection and identification of Brucella spp. Clin. Lab., 49, 487, 2003. 9. Alton, G.G. et al. Techniques for the Brucellosis Laboratory. Institut National de la Recherche Agronomique, Paris, 1988. 10. Corbel, M.J. and Brinley-Morgan, W.J. Genus Brucella. In Bergey’s Manual of Systematic Bacteriology, vol. 1, p. 370. Krieg, N.R. and Holt, J.G. (Eds.). Williams & Wilkins, Baltimore, MD, 1984. 11. Cloeckaert, A. et al. Classification of Brucella spp. isolated from marine mammals by DNA polymorphism at the omp2 locus. Microbes Infect., 3, 729, 2001. 12. Foster, G. et al. Brucella ceti sp. nov. and Brucella pinnipedialis sp. nov. for Brucella strains with cetaceans and seals as their preferred hosts. Int. J. Syst. Evol. Microbiol., 57, 2688, 2007. 13. Scholz, H.C. et al. Brucella microti sp. nov., isolated from the common vole Microtus arvalis. Int. J. Syst. Evol. Microbiol., 58, 375, 2008. 14. Verger, J.M. et al. Brucella, a monospecific genus as shown by deoxyribonucleic acid hybridization. Int. J. Syst. Bacteriol., 35, 292, 1985. 15. Osterman, B. and Moriyón, I. International Committee on Systematics of Prokaryotes Subcommittee on the Taxonomy of Brucella. Minutes of the meeting, 17 September 2003, Pamplona, Spain. Int. J. Syst. Evol. Microbiol., 56, 1173, 2006. 16. Moreno, E. and Moriyón, I. Brucella melitensis: a nasty bug with hidden credentials for virulence. Proc. Natl. Acad. Sci. USA, 99, 1, 2002. 17. Lapaque, N. et al. Brucella lipopolysaccharide acts as a virulence factor. Curr. Opin. Microbiol., 8, 60, 2005. 18. Porte, F. et al. Role of the Brucella suis lipopolysaccharide O antigen in phagosomal genesis and in inhibition of phagosome-lysosome fusion in murine macrophages. Infect. Immun., 71, 1481, 2003. 19. Forestier, C. et al. Brucella abortus lipopolysaccharide in murine peritoneal macrophages acts as a down-regulator of T cell activation. J. Immunol., 165, 5202, 2000. 20. Roop II, R.M. et al. Adaptation of the brucellae to their intracellular niche. Mol. Microbiol., 52, 621, 2004. 21. Boschiroli, M.L. et al. The Brucella suis virB operon is induced intracellularly in macrophages. Proc. Natl. Acad. Sci. USA, 99, 1544, 2002. 22. Celli, J. and Gorvel, J.P. Organelle robbery: Brucella interactions with the endoplasmic reticulum. Curr. Opin. Microbiol., 7, 1, 2004. 23. Köhler, S. et al. The analysis of the intramacrophagic virulome of Brucella suis deciphers the environment encountered by the pathogen inside the macrophage host cell. Proc. Natl. Acad. Sci. USA, 99, 15711, 2002. 24. Köhler, S. et al. What is the nature of the replicative niche of a stealthy bug named Brucella? Trends Microbiol., 11, 215, 2003. 25. Al Dahouk, S. et al. Quantitative analysis of the intramacrophagic proteome of the pathogen Brucella suis reveals metabolic adaptation to the late stage of cellular infection. Proteomics, 8, 3862, 2008. 26. Miller, M.A. and Paige, J.C. Other food borne infections. Vet. Clin. North Am. Food Anim. Pract., 14, 71–89, 1998. 27. Bercovich, Z. Maintenance of Brucella abortus-free herds: a review with emphasis on the epidemiology and the problems in diagnosing brucellosis in areas of low prevalence. Vet. Quart., 20, 81, 1998.

Molecular Detection of Foodborne Pathogens 28. Brew, S.D. et al. Human exposure to Brucella recovered from a sea mammal. Vet. Rec., 144, 483, 1999. 29. McDonald, W.L. et al. Characterization of a Brucella sp. strain as marine-mammal type despite isolation from a patient with spinal osteomyelitis in New Zealand. J. Clin. Microbiol., 44, 4363, 2006. 30. Sohn, A.H. et al. Human neurobrucellosis with intracerebral granuloma caused by a marine mammal Brucella sp. Emerg. Infect. Dis., 9, 485, 2003. 31. Cooper, C.W. Risk factors in transmission of brucellosis from animals to humans in Saudi Arabia. Trans. R. Soc. Trop. Med. Hyg., 86, 206, 1992. 32. Yagupsky, P. and Baron, E.J. Laboratory exposures to Brucellae and implications for bioterrorism. Emerg. Infect. Dis., 8, 1180, 2005. 33. Saltoglu, N. et al. Fever of unknown origin in Turkey: evaluation of 87 cases during a nine-year-period of study. J. Infect., 48, 81, 2004. 34. Young, E.J. An overview of human brucellosis. Clin. Infect. Dis., 21, 283, 1995. 35. Colmenero, J.D. et al. Complications associated with Brucella melitensis infection: a study of 530 cases. Medicine (Baltimore), 75, 195, 1996. 36. Gür, A. et al. Complications of brucellosis in different age groups: a study of 283 cases in southeastern Anatolia of Turkey. Yonsei Med. J., 44, 33, 2003. 37. Peery, T.M. and Belter, L.F. Brucellosis and heart disease. II. Fatal brucellosis: a review of the literature and report of new cases. Am. J. Pathol., 36, 673, 1960. 38. Food andAgriculture Organization-World Health Organization, Joint FAO/WHO Expert Committee on Brucellosis (sixth report). In WHO Technical Report Series, No. 740, p. 56. World Health Organization, Geneva, 1986. 39. Godfroid, J. Brucellosis in wildlife. Rev. Sci. Tech., 21, 277, 2002. 40. Godfroid, J. and Käsbohrer, A. Brucellosis in the European Union and Norway at the turn of the twenty-first century. Vet. Microbiol., 90, 135, 2002. 41. Taleski, V. et al. An overview of the epidemiology and epizo­ otology of brucellosis in selected countries of Central and Southeast Europe. Vet. Microbiol., 90, 147, 2002. 42. Paton, N.I. et al. Visceral abscesses due to Brucella suis infection in a retired pig farmer. Clin. Infect. Dis., 32, 129, 2001. 43. Teyssou, R. et al. About a case of human brucellosis due to Brucella suis biovar 2. Mèd. Mal. Infect., 19, 160, 1989. 44. Chomel, B.B. et al. Changing trends in the epidemiology of human brucellosis in California from 1973 to 1992: A shift toward foodborne transmission. J. Infect. Dis., 170, 1216, 1994. 45. Wise, R.I. Brucellosis in the United States: Past, present, and future. JAMA, 244, 2318, 1980. 46. Corbel, M.J. Brucellosis: An overview. Emerg. Infect. Dis., 3, 213, 1997. 47. Pappas, G. et al. Medical Progress – Brucellosis. N. Engl. J. Med., 352, 2325, 2005. 48. De Massis, F. et al. Correlation between animal and human brucellosis in Italy during the period 1997–2002. Clin. Microbiol. Infect., 11, 632, 2005. 49. Fosgate, G.T. et al. Time-space clustering of human brucellosis, California, 1973–1992. Emerg. Infect. Dis., 8, 672, 2002. 50. Al Dahouk, S. et al. Changing epidemiology of human brucellosis, Germany, 1962–2005. Emerg. Infect. Dis., 13, 1895, 2007. 51. Eriksen, N. et al. Brucellosis in immigrants in Denmark. Scand. J. Infect. Dis., 34, 540, 2002.

Brucella 52. White Jr. A.C. and Atmar, R.L. Infections in Hispanic immigrants. Clin. Infect. Dis., 34, 1627, 2002. 53. Memish, Z.A. and Balkhy, H.H. Brucellosis and international travel. J. Travel Med., 11, 49, 2004. 54. Troy, S.B., Rickman, L.S. and Davis, C.E. Brucellosis in San Diego. Epidemiology and species-related differences in acute clinical presentations. Medicine, 84, 174, 2005. 55. Farrell, I.D. The development of a new selective medium for the isolation of Brucella abortus from contaminated sources. Res. Vet. Sci., 16, 280, 1974. 56. Castaneda, M.R. A practical method for routine blood cultures in brucellosis. Proc. Soc. Exp. Biol. Med., 64, 114, 1947. 57. Barham, W.B. et al. Misidentification of Brucella species with use of rapid bacterial identification systems. Clin. Infect. Dis., 17, 1068, 1993. 58. Al Dahouk, S. et al. Laboratory-based diagnosis of brucellosis – a review of the literature. Part II: Serological tests for brucellosis. Clin. Lab., 49, 577, 2003. 59. OIE (World Organisation for Animal Health). Bovine brucellosis. In OIE Manual of Diagnostic Tests and Vaccines for Terrestrial Animals, 5th ed. OIE, Paris, 2004. 60. Gall, D. and Nielsen, K. Serological diagnosis of bovine brucellosis: A review of test performance and cost comparison. Rev. Sci. Technol., 23, 989, 2004. 61. OIE (World Organisation for Animal Health). Caprine and ovine brucellosis (excluding Brucella ovis). In OIE Manual of Diagnostic Tests and Vaccines for Terrestrial Animals, 5th ed. OIE, Paris, 2004. 62. Godfroid, J. et al. How to substantiate eradication of bovine brucellosis when aspecific serological reactions occur in the course of brucellosis testing. Vet. Microbiol., 90, 461, 2002. 63. Nielsen, K. Diagnosis of brucellosis by serology. Vet. Microbiol., 90, 447, 2002. 64. Pouillot, R. et al. The brucellin skin test as a tool to differentiate false positive serological reactions in bovine brucellosis. Vet. Res., 28, 365, 1997. 65. Saergerman, C. et al. Diagnosis of bovine brucellosis by skin test: conditions for the test and evaluation of its performance. Vet. Rec., 145, 214, 1999. 66. Morgan, W.J.B. et al. The rose bengal plate agglutination test in the diagnosis of brucellosis. Vet. Rec., 85, 636, 1969. 67. Patterson, J.M., Deyoe, B.L. and Stone, S.S. Identification of immunoglobulins associated with complement fixation, agglutination, and low pH buffered antigen tests for brucellosis. Am. J. Vet. Res., 37, 319, 1976. 68. Rose, J.E. and Roepke, M.H. An acidified antigen for detection of nonspecific reactions in the plate-agglutination test for bovine brucellosis. Am. J. Vet. Res., 18, 550, 1957. 69. Alton, G.G. et al. The serological diagnosis of bovine brucellosis: an evaluation of the complement fixation, serum agglutination and Rose Bengal tests. Aust. Vet. J., 51, 57, 1975. 70. Stemshorn, B.W. et al. A comparison of standard serological tests for the diagnosis of bovine brucellosis in Canada. Can. J. Comp. Med., 49, 391, 1985. 71. Jones, L.M., Hendricks, J.B. and Berman, D.T. The standardization and use of the complement fixation test for the diagnosis of bovine brucellosis, with a review of the literature. Am. J. Vet. Res., 24, 1143, 1963. 72. Nicoletti, P. and Muraschi, T.F. Bacteriologic evaluation of serologic test procedures for the diagnosis of brucellosis in problem cattle herds. Am. J. Vet. Res., 27, 689, 1966. 73. Nielsen, K. et al. Improved competitive enzyme immunoassay for the diagnosis of bovine brucellosis. Vet. Immunol. Immunopathol., 46, 285, 1995.

329 74. Nielsen, K.H. et al. Comparison of enzyme immunoassays for the diagnosis of bovine brucellosis. Prev. Vet. Med., 26, 17, 1996. 75. Nielsen, K. et al. A homogeneous fluorescence polarisation assay for detection of antibody to Brucella abortus. J. Immunol. Methods, 195, 161, 1996. 76. Samartino, L. et al. Fluorescence polarization assay: Appli­ cation to the diagnosis of bovine brucellosis in Argentina. J. Immunoassay, 20, 115, 1999. 77. Nielsen, K. et al. Fluorescence polarization assay for the diagnosis of bovine brucellosis: adaptation to field use. Vet. Microbiol., 80, 163, 2001. 78. Bricker, B.J. PCR as a diagnostic tool for brucellosis. Vet. Microbiol., 90, 435, 2002. 79. Leal-Klevezas, D.S. et al. Single-step PCR for detection of Brucella spp. from blood and milk of infected animals. J. Clin. Microbiol., 12, 3087, 1995. 80. O’Leary, S., Sheahan, M. and Sweeney, T. Brucella abortus detection by PCR assay in blood, milk and lymph tissue of serologically positive cows. Res. Vet. Sci., 81, 170, 2006. 81. Romero, C. and López-Goni, I. Improved method for purification of bacterial DNA from bovine milk for detection of Brucella spp. by PCR. Appl. Environ. Microbiol., 65, 3735, 1999. 82. Romero, C. et al. Evaluation of PCR and indirect enzymelinked immunosorbent assay on milk samples for diagnosis of brucellosis in dairy cattle. J. Clin. Microbiol., 33, 3198, 1995. 83. Gallien, P. et al. Detection of Brucella species in organs of naturally infected cattle by polymerase chain reaction. Vet. Rec., 142, 512, 1998. 84. Serpe, L. et al. Single-step method for rapid detection of Brucella spp. in soft cheese by gene-specific polymerase chain reaction. J. Dairy Res., 66, 313, 1999. 85. Tantillo, G. et al. Polymerase chain reaction for the direct detection of Brucella spp. in milk and cheese. J. Food. Prot., 64, 164, 2001. 86. Tantillo, G.M., Di Pinto, A. and Buonavoglia, C. Detection of Brucella spp. in soft cheese by semi-nested polymerase chain reaction. J. Dairy Res., 70, 245, 2003. 87. Hamdy, M.E.R. and Amin, A.S. Detection of Brucella species in the milk of infected cattle, sheep, goats and camels by PCR. Vet. J., 163, 299, 2002. 88. Leal-Klevezas, D.S. et al. Use of polymerase chain reaction to detect Brucella abortus biovar 1 in infected goats. Vet. Microbiol., 75, 91, 2000. 89. Herman, L. and De Ridder, H. Identification of Brucella spp. by using the polymerase chain reaction. Appl. Environ. Microbiol., 58, 2099, 1992. 90. Romero, C. et al. Specific detection of Brucella DNA by PCR. J. Clin. Microbiol., 3, 615, 1995. 91. Rijpens, N.P. et al. Direct detection of Brucella spp. in raw milk by PCR and reverse hybridization with 16S-23S rRNA spacer probes. Appl. Environ. Microbiol., 62, 1683, 1996. 92. Leal-Klevezas, D.S., Lopéz-Merino, A. and Martínez-Soriano, J.P. Molecular detection of Brucella spp.: Rapid identification of B. abortus biovar 1 using PCR. Arch. Med. Res., 26, 263, 1995. 93. Ouahrani, S. et al. Identification and sequence analysis of IS6501, an insertion sequence in Brucella spp.: Relationship between genomic structure and the number of IS6501 copies. J. Gen. Microbiol., 139, 3265, 1993. 94. Ouahrani-Bettache, S., Soubrier, M.P. and Liautard, J.P. IS6501-anchored PCR for detection and identification of Brucella species and strains. J. Appl. Bacteriol., 81, 154, 1996.

330 95. Baily, G.G. et al. Detection of Brucella melitensis and Brucella abortus by DNA amplification. J. Trop. Med. Hyg., 95, 271, 1992. 96. Bricker, B.J. and Halling, S.M. Differentiation of Brucella abortus bv. 1, 2, and 4, Brucella melitensis, Brucella ovis, and Brucella suis bv. 1 by PCR. J. Clin. Microbiol., 11, 2660, 1994. 97. García-Yoldi, D. et al. Multiplex PCR assay for the identification of all Brucella species and the vaccine strains Brucella abortus S19 and RB51 and Brucella melitensis Rev1. Clin. Chem., 52, 779, 2006. 98. Al Dahouk, S. et al. The detection of Brucella spp. using PCR-ELISA and real-time PCR assays. Clin. Lab., 50, 387, 2004. 99. Al Dahouk, S. et al. Evaluation of genus-specific and speciesspecific real-time PCR assays for the identification of Brucella spp. Clin. Chem. Lab. Med., 45, 1464, 2007. 100. Redkar, R. et al. Real-time detection of Brucella abortus, Brucella melitensis and Brucella suis. Mol. Cell. Probes, 15, 43, 2001. 101. Newby, D.T., Hadfield, T.L. and Roberto, F.F. Real-time PCR detection of Brucella abortus: A comparative study of SYBR green I, 5´-exonuclease and hybridization probe assays. Appl. Environ. Microbiol., 69, 4753, 2003. 102. Probert, W.S. et al. Real-time multiplex PCR assay for detection of Brucella spp., B. abortus, and B. melitensis. J. Clin. Microbiol., 42, 1290, 2004. 103. Foster, J.T. et al. Real-time PCR assays of single-nucleotide polymorphisms defining the major Brucella clades. J. Clin. Microbiol., 46, 296, 2008. 104. Mukherjee, F. et al. Multiple genus-specific markers in PCR assays improve the specificity and sensitivity of diagnosis of brucellosis in field animals. J. Med. Microbiol., 56, 1309, 2007. 105. van Belkum, A. High-throughput epidemiologic typing in clinical microbiology. Clin. Microbiol. Infect., 9, 86, 2003. 106. Gee, J.E. et al. Use of 16S rRNA gene sequencing for rapid confirmatory identification of Brucella isolates. J. Clin. Microbiol., 42, 3649, 2004. 107. Halling, S.M. et al. Completion of the genome sequence of Brucella abortus and comparison to the highly similar genomes of Brucella melitensis and Brucella suis. J. Bacteriol., 187, 2715, 2005. 108. Fekete, A. et al. Amplification fragment length polymorphism in Brucella strains by use of polymerase chain reaction with arbitrary primers. J. Bacteriol., 23, 7778, 1992. 109. Mercier, E. et al. Polymorphism in Brucella strains detected by studying distribution of two short repetitive DNA elements. J. Clin. Microbiol., 5, 1299, 1996. 110. Tscherneva, E. et al. Repetitive element sequence based polymerase chain reaction for typing of Brucella strains. Vet. Microbiol., 51, 169, 1996. 111. Tscherneva, E. et al. Differentiation of Brucella species by random amplified polymorphic DNA analysis. J. Appl. Microbiol., 88, 69, 2000. 112. Al Dahouk, S. et al. Identification of Brucella species and biotypes using polymerase chain reaction-restriction fragment length polymorphism (PCR-RFLP). Crit. Rev. Microbiol., 31, 191, 2005. 113. Whatmore, A.M. et al. Use of amplified fragment length polymorphism to identify and type Brucella isolates of medical and veterinary interest. J. Clin. Microbiol., 43, 761, 2005.

Molecular Detection of Foodborne Pathogens 114. Marianelli, C. et al. Molecular characterization of the rpoB gene in Brucella species: New potential molecular markers for genotyping. Microbes Infect., 8, 860, 2006. 115. Scott, J.C. et al. Multiplex assay based on single-nucleotide polymorphisms for rapid identification of Brucella isolates at the species level. Appl. Environ. Microbiol., 73, 7331, 2007. 116. Whatmore, A.M., Perrett, L.L. and MacMillan, A.P. Characterisation of the genetic diversity of Brucella by multilocus sequencing. BMC Microbiol., 7, 34, 2007. 117. DelVecchio, V.G. et al. The genome sequence of the facultative intracellular pathogen Brucella melitensis. Proc. Natl. Acad. Sci. USA, 99, 443, 2002. 118. Paulsen, I.T. et al. The Brucella suis genome reveals fundamental similarities between animal and plant pathogens and symbionts. Proc. Natl. Acad. Sci. USA, 99, 13148, 2002. 119. Al Dahouk, S. et al. Evaluation of Brucella MLVA typing for human brucellosis. J. Microbiol. Methods, 69, 137, 2007. 120. Le Flèche, P. et al. Evaluation and selection of tandem repeat loci for a Brucella MLVA typing assay. BMC Microbiol., 6, 9, 2006. 121. Whatmore, A.M. et al. Identification and characterization of variable-number of tandem-repeat markers for typing of Brucella spp. J. Clin. Microbiol., 44, 1982, 2006. 122. Vergnaud, G. and Denoeud, F. Minisatellites: Mutability and genome architecture. Genome Res., 10, 899, 2000. 123. Bricker, B.J. and Ewalt, D.R. Evaluation of the HOOF-print assay for typing Brucella abortus strains isolated from cattle in the United States: Results with four performance criteria. BMC Microbiol., 5, 37, 2005. 124. Bricker, B.J., Ewalt, D.R. and Halling, S.M. Brucella ‘HOOF-prints’: Strain typing by multi-locus analysis of variable number tandem repeats (VNTRs). BMC Microbiol., 3, 15, 2003. 125. Casanas, M.C. et al. Specificity of a polymerase chain reaction assay of a target sequence on the 31-kilodalton Brucella antigen DNA used to diagnose human brucellosis. Eur. J. Clin. Microbiol. Infect. Dis., 20, 127, 2001. 126. Kattar, M.M. et al. Development and evaluation of real-time polymerase chain reaction assays on whole blood and paraffin-embedded tissues for rapid diagnosis of human brucellosis. Diagn. Microbiol. Infect. Dis., 59, 23, 2007. 127. Queipo-Ortuno, M.I. et al. Comparison of seven commercial DNA extraction kits for the recovery of Brucella DNA from spiked human serum samples using real-time PCR. Eur. J. Clin. Microbiol. Infect. Dis., 27, 109, 2008. 128. Navarro, E. et al. Use of real-time quantitative polymerase chain reaction to monitor the evolution of Brucella melitensis DNA load during therapy and post-therapy follow-up in patients with brucellosis. Clin. Infect. Dis., 42, 1266, 2006. 129. Christensen, D.R. et al. Detection of biological threat agents by real-time PCR: Comparison of assay performance on the R.A.P.I.D., the LightCycler, and the Smart Cycler platforms. Clin. Chem., 52, 141, 2006. 130. Debeaumont, C., Falconnet, P.A., and Maurin, M. Realtime PCR for detection of Brucella spp. DNA in human serum samples. Eur. J. Clin. Microbiol. Infect. Dis., 24, 842, 2005. 131. Queipo-Ortuno, M.I. et al. Rapid diagnosis of human brucellosis by SYBR green I-based real-time PCR assay and melting curve analysis in serum samples. Clin. Microbiol. Infect., 11, 713, 2005.

24 Burkholderia

Karlene H. Lynch and Jonathan J. Dennis University of Alberta

Contents 24.1 Introduction.....................................................................................................................................................................331 24.1.1 Burkholderia pseudomallei, Burkholderia mallei, and the BCC......................................................................331 24.1.1.1 Burkholderia pseudomallei and Burkholderia mallei......................................................................331 24.1.1.2 BCC.................................................................................................................................................. 332 24.1.2 Burkholderia gladioli pathovar cocovenenans................................................................................................. 333 24.1.2.1 Taxonomy......................................................................................................................................... 333 24.1.2.2 Epidemiology................................................................................................................................... 333 24.1.2.3 Pathogenesis..................................................................................................................................... 334 24.1.2.4 Biology............................................................................................................................................. 335 24.1.2.5 Conventional Diagnosis................................................................................................................... 336 24.1.2.6 Molecular Diagnosis........................................................................................................................ 337 24.2 Methods.......................................................................................................................................................................... 337 24.2.1 Reagents and Equipment................................................................................................................................... 337 24.2.2 Burkholderia gladioli pathovar cocovenenans Sample Collection and Preparation........................................ 338 24.2.2.1 Bacterial Isolation, Propagation, and Storage.................................................................................. 338 24.2.2.2 Toxin Extraction............................................................................................................................... 338 24.2.3 Burkholderia gladioli pathovar cocovenenans Detection Procedure............................................................... 338 24.3 Conclusions and Future Perspectives............................................................................................................................. 339 References.................................................................................................................................................................................. 340

24.1  Introduction The genus Burkholderia is an incredibly diverse group of Gram-negative β-proteobacteria. Although there are currently at least 60 species and proposed species in this genus, very few of these have been studied extensively.1 Much of the research to date has focused on the Burkholderia cepacia complex (BCC), Burkholderia pseudomallei, Burkholderia mallei, and Burkholderia gladioli. BCC organisms are pathogens that cause serious infections in plants, animals, and humans.2–4 However, they can also be beneficial as they fix nitrogen, produce antibiotics and antifungals, and degrade organic compounds.5–7 B. pseudomallei causes melioidosis, a disease with a wide variety of symptoms, while B. mallei causes glanders, a condition usually found in horses that can also affect humans.8 Since 2003, B. gladioli has been divided into four pathovars: gladioli, alliicola, agaricicola, and cocovenenans.9 The first three groups are primarily plant pathogens.10,11 However, in addition to being phytopathogenic, members of these pathovars can also infect patients with chronic granulomatous disease (CGD), cystic fibrosis (CF), and acquired immune deficiency syndrome (AIDS).9,12,13 The taxonomic description of B. gladioli pvs. gladioli, alliicola, and agaricicola published in 2003 indicates that they do not produce toxins that are harmful to humans, although some strains have since been shown to synthesize toxoflavin (discussed below).9,14

The fourth pathovar, B. gladioli pv. cocovenenans, is genetically similar to the first three pathovars, but distinct with regards to both its epidemiology and pathogenicity. Although other Burkholderia species can be found in food and water supplies (including B. pseudomallei, B. mallei, and the BCC), B. gladioli pv. cocovenenans is the only division of the Burkholderia genus that is characterized as a foodborne pathogen. In an analogous fashion to Clostridium botulinum, these bacteria cause disease indirectly through the production of toxins that permeate contaminated foods. This chapter will briefly discuss the literature regarding the presence of B. pseudomallei, B. mallei, and the BCC in food and water supplies and the potential for transmission from these sources, followed by an extensive review of B. gladioli pv. cocovenenans epidemiology, pathogenesis, biology, and diagnostics.

24.1.1 Burkholderia pseudomallei, Burkholderia mallei, and the BCC 24.1.1.1 Burkholderia pseudomallei and Burkholderia mallei B. pseudomallei causes melioidosis, a potentially fatal condition with a variety of symptoms including pneumonia, skin lesions, and septic shock.8 Most melioidosis cases are seen in 331

332

Southeast Asia (especially Thailand) and northern Australia, although they can also be found in areas such as Brazil.8,15 Although the first cases of melioidosis were described in 1913, there remains some debate as to how B. pseudomallei is transmitted to humans.16,17 It is thought that most infections occur following either inoculation of broken skin or inhalation.18 Historically, it was considered that melioidosis was also spread through the consumption of contaminated food and water, as it could be transmitted in this manner to guinea pigs, rabbits, and rats.16,19 However, B. pseudomallei has not been definitively shown to spread to humans by this route. A report published in 1998 described the development of melioidosis in five adults in northwestern Australia.20 Using pulsed-field gel electrophoresis (PFGE) typing, it was determined that all five patients were infected with the same PFGE type and that this type was identical to that of B. pseudomallei isolates found in the area’s drinking water. Although this association suggests that these cases developed due to ingestion of the waterborne microbe, the possibility exists that these persons may have been infected via a different route.20 B. pseudomallei can also be isolated from drinking water in areas where melioidosis is not endemic. Zanetti et al. showed that B. pseudomallei could be isolated from 7.1% of drinking water samples taken in Bologna, Italy.21 In these samples, the levels of B. pseudomallei ranged from 1020 to 15000 colony forming units (CFU) per 100 ml sample. Treatment of water with chlorine will kill B. pseudomallei (as well as B. mallei) in an experimental setting, but various factors in the environment (including attachment and nutrient limitation) may affect this susceptibility.22 B. mallei causes glanders, a disease of horses that can also be transmitted to humans. The symptoms vary ­depending on the route of transmission, but can include pneumonia, skin lesions, and septic shock (similar to melioidosis).23 Horses generally become infected following ingestion of B. ­mallei introduced into their food and water by other infected ­horses.23 It is thought that humans may also become infected via ingestion.24 As a result of stringent measures introduced to control the spread of glanders, this condition has not been seen in Western countries since 1939 (except following accidental laboratory exposure).25,26 However, there are concerns that both B. pseudomallei and B. mallei could be released as bioterrorism agents.27 Both of these species have been identified as food defense concerns.28 This categorization indicates that these species, both of which are Category B biological agents based on Centers for Disease Control classification, could be purposely introduced into the food supply in an act of terrorism.27,28 This is in contrast with normal concerns over food safety in which organisms such as Streptococcus may lead to accidental contamination of the food supply.28 24.1.1.2  BCC The BCC is currently made up of 15 (atleast 17) closely related Burkholderia species.1 These bacteria cause potentially fatal infections in susceptible patients, particularly those with CF and CGD.29,30 Whereas both melioidosis and glanders can have a wide range of symptoms that affect many different

Molecular Detection of Foodborne Pathogens

systems of the body, BCC infections tend to be ­limited to the lungs. These infections may be asymptomatic, may cause a patient’s condition to worsen over time, or may develop into a rapidly fatal pneumonia accompanied by damage to the lung tissue and septicemia.4 This group of bacteria is found more commonly in food and water supplies than either B. pseudomallei or B. mallei. They can be isolated from the rhizospheres of rice, corn, wheat, soybean, and alfalfa plants.31,32 BCC bacteria have also been found associated with Pleurotus ostreatus, the oyster mushroom, which is the second-most cultivated mushroom in the United States.33,34 BCC organisms may cause spoilage in foods as diverse as onions, Swiss cheese, and Parma ham.2,35,36 However, these bacteria can also prevent food spoilage: a BCC strain isolated from Washington navel oranges was found to prevent fungal infection of these fruits during storage when they were treated with this strain.37 Because of the ability of BCC organisms to produce such antifungals and antibiotics (in addition to their ability to fix nitrogen), there has been a great deal of interest in developing these species into agricultural products. However, because of the potential risk to susceptible persons, the United States Environmental Protection Agency (EPA) has placed strict limitations on the production and use of BCC bacteria since 2003.38 Despite their wide distribution in food products, when Moore et al. assessed the prevalence of BCC bacteria in a variety of foods (including bakery items, onions, cheese, ham, and oranges), they were only able to isolate these organisms from unpasteurized milk.39 BCC species have also been isolated from unpasteurized milk by Uraz and Çitak and Munsch-Alatossava and Alatossava.40–43 It is unknown how the milk becomes contaminated, but it has been suggested that it is due to transfer of BCC organisms from the soil to the cow udder and/or to milk storage tanks.44 Berriatua et al. found that the BCC species Burkholderia cenocepacia and Burkholderia vietnamiensis were responsible for causing subclinical mastitis (inflammation of the udder) in milking sheep.3 However, when Moore et al. examined milk samples taken from cows with mastitis to determine if this condition was responsible for the contamination, they were unable to isolate BCC organisms.44 It is important to note that, despite the contamination of raw milk, these bacteria are not found in commercially available dairy products and are effectively killed by pasteurization.39,44 Like B. pseudomallei, BCC organisms can also be isolated from drinking water. Zanetti et al. found that 3.5% of drinking water samples in Bologna, Italy contained BCC bacteria.21 The counts in these samples were very low compared to B. pseudomallei, containing between 1 and 19 CFU per 100 ml sample. Pegues et al. examined a BCC isolate from a water jug at a CF summer camp.45 They found that the ribotype of this isolate was different from the ribotypes taken from patients infected at the camp, indicating that this water was not the source of infection. The presence of BCC organisms in these samples may be due to their propensity to form biofilms in water supply systems.46 In contrast to these

Burkholderia

findings, examination of samples taken either by Moore et al. or Vermis et al. were unable to detect BCC organisms in a variety of drinking water sources, including bottled, tap, well, and spring water.39,47 Although it is generally considered that BCC organisms do not spread through ingestion, it remains a possibility that if these bacteria are present in the mouth and throat following the consumption of contaminated food or water, they may subsequently enter the lungs.39 Therefore, it is recommended that patients with CF should not consume unpasteurized milk products or food from buffets and should thoroughly wash and dry produce.39,48,49 To date, only one study has suggested a link between food consumption and BCC infection in CF patients. Fisher et al. found that BCC isolates taken from cucumber, lettuce, and cauliflower purchased from salad bars and food stores near two CF centers were of the same ribotype that was most commonly isolated from the patients in these centers.50 However, it is not possible to discern from these findings whether or not these foods acted as sources of infection.

24.1.2 Burkholderia gladioli pathovar cocovenenans

24.1.2.1  Taxonomy The taxonomy of the bacteria currently named B. gladioli pv. cocovenenans is relatively complicated and incredibly plastic. Despite the publication of several articles defining the nomenclature of this group, the naming remains inconsistent in the current literature. van Veen and Mertens published the first studies on this bacterium, which they isolated from contaminated tempe bongkrek, an Indonesian fermented coconut cake.51 This organism was named Pseudomonas cocovenenans (cocos=coconut, veneno=to poison) and this nomenclature was retained in early studies.52–54 Around this time, another bacterium was isolated from contaminated fermented corn flour in China.55 Similar isolates were studied extensively in the Chinese literature, but were not described in an English journal until 1988. Here, the organism is identified as Flavobacterium farinofermentans sp. nov.56 However, in the Chinese literature, these bacteria had been called by this name since 1980, and had already been renamed Pseudomonas farinofermentans by the mid-1980s.57,58 Comparisons of F. farinofermentans sp. nov. and P. cocovenenans (published in Chinese in 1987 and cited in the English literature in 1989) suggested that F. farinofermentans sp. nov. be renamed P. cocovenenans subspecies farinofermentans.59,60 A similar conclusion was reached following a separate set of comparisons published in 1988 and 1990, first in Chinese and then in English. After assessing a variety of characteristics (including cell and colony morphology, substrate utilization, antibiotic resistance, DNA hybridization, and antibody cross-reactivity), Zhao et al. determined that P. farinofermentans and P. cocovenenans belonged to the same species.58,61 However, they suggested that, because there were slight differences observed between P. farinofermentans and P. cocovenenans isolates

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with respect to substrate utilization and antibiotic resistance, P.  farinofermentans should be renamed P. cocovenenans biovar farinofermentans. In 1992, seven Pseudomonas species were reclassified and assigned to the new genus Burkholderia (including B. pseudomallei, B. mallei, B. cepacia, and B. gladioli).62 Following analysis of the type strain LMG 11626/NCIB 9450/ATCC 33664 (a strain isolated from tempe bongkrek), P. cocovenenans was subsequently assigned to this genus in 1995, becoming Burkholderia cocovenenans comb. nov.63 This transfer was confirmed later that year using 16S rDNA sequencing using NCIMB 12451 (a fermented corn flour poisoning isolate).64 In this paper, this strain was described as P. cocovenenans (as opposed to P. cocovenenans bv. farinofermentans), thus discontinuing the use of the biovar designation. In 1997, Vandamme et al. found that, when SDS-PAGE of whole-cell proteins was performed using B. gladioli and B. cocovenenans strains, the resulting protein patterns were very similar.65 To confirm the relatedness of these two species, this group performed further experiments using SDSPAGE, DNA hybridization, and biochemical tests.66 Their results led to the reclassification of B. cocovenenans as a member of B. gladioli. The most recent change to this taxonomy has been the addition of a fourth pathovar to B. gladioli that encompasses the former B. cocovenenans strains and isolates, called B. gladioli pathovar cocovenenans. The three existing pathovars of B. gladioli (gladioli, alliicola, and agaricicola) are all phytopathogenic.10,11 These pathovars can be differentiated from pathovar cocovenenans because they do not produce bongkrekic acid (discussed below) and have slightly different substrate utilization patterns (Table 24.1).9 Despite the publication of the papers described here, discrepancies in taxonomy remain in the current literature, particularly with regards to Chinese publications where use of the name P. cocovenenans subsp. farinofermentans remains common.67–70 24.1.2.2  Epidemiology B. gladioli pv. cocovenenans intoxications occur in two areas of the world due to the consumption of two different locally-produced fermented foods. The first of these foods, from which the bacterium was initially isolated, is tempe (or tempeh) bongkrek (also referred to as semaji or bongkrek). Tempe refers to a group of foods made by fermentation of plant material (such as soybeans and coconut) using mould.71 Tempe bongkrek is made using coconut presscake (a byproduct of processing coconut to remove the oil) or coconut milk residue.71,72 This material is then fermented using Rhizopus oligosporus, a fungus that grows on the surface of and throughout the tempe.73 The finished product is a white cake with a thickness of one inch or less.74 Tempe bongkrek that is properly made and fully fermented tends to be very safe.74 However, when it is made in the home (often by those who have little knowledge or experience regarding proper production methods), insufficient fungal growth may allow bacteria—including B. gladioli pv. cocovenenans—to multiply.74

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Molecular Detection of Foodborne Pathogens

Table 24.1 Differential Characteristics Among Pathovars of B. gladioli B. gladioli Pathovar gladioli NCPPB 1891

Pathovar agaricicola NCPPB 3580

Pathovar alliicola NCPPB 947

Pathovar cocovenenans ATCC 33664 and 6 Strains

Gladiolus – +

Mushroom – –

Onion – +

Coconut, fermented corn 100% (7/7)* 100% (7/7)

Growth at 4°C Nitrate reduction

+

+

–

0% (0/7)

–

–

+

100% (7/7)

Xylitol Gentiobiose N-Acetyl-D-galactosamine Acetic acid L-Pyroglutamic acid Maltose D-Raffinose Sucrose Glycyl-L-aspartic acid

– + + + – – – – –

Assimilation – + + – + + – – –

– + + + + – + + +

100% (7/7) 0% (0/7) 0% (0/7) 86% (6/7) 100% (7/7) 0% (0/7) 0% (0/7) 0% (0/7) 0% (0/7)

Characteristics Source Bongkrekic acid production Growth at 41°C

* % of positive strains; +: positive or weak positive reaction, –: negative reaction. Source: Jiao, Z. et al., Microbiol. Immunol., 47, 915, 2003. Reproduced with permission from Wiley-Blackwell Publishing.

Most tempe bongkrek poisonings occur in the Banjumas province in Central Java, Indonesia.74 Here, tempe is an important food source because it is inexpensive and highly nutritious, containing both protein and vitamin B12.52,71 The first reports of tempe bongkrek poisoning date back to 1895.75 Since then, poisonings have been relatively frequent, with 7216 cases and 850 deaths occurring between 1951 and 1975.74,76 Despite the banning of tempe bongkrek by the government in 1988 (and the threat of prison time), Indonesians continue to make and consume this food.71,77 Although there have been no reports of intoxications in surrounding countries, this is not necessarily an indication that they have not occurred.72 The second product that can cause B. gladioli pv. cocovenenans intoxications is fermented corn flour (FCF). FCF is produced by grinding corn that has been immersed in water for between 2 and 4 weeks. This flour is then used to make other foods, including breads and noodles.78 B. gladioli pv. cocovenenans can grow in the flour during storage.73 Cooking or baking of contaminated foods does not prevent illness as the toxins produced by the bacteria are heat-stable.74 FCF is commonly made in northeastern China, including the provinces of Heilongjiang, Jilin, and Liaoning.78 Intoxications due to B. gladioli pv. cocovenenans occur relatively frequently, with 226 outbreaks identified in these provinces between 1953 and 1975. Of the 1842 patients affected, 703 died (38.2% mortality). Most intoxications occurred in the summer months, between July and September. There was no effect of age or sex on whether or not those who ate contaminated FCF became ill or died. These effects were instead related to the amount of toxic material that had been eaten.78 A second,

less common source of B. gladioli pv. cocovenenans intoxications in China (and other Asian countries) is Tremella fuciformis, an edible mushroom. It has been found that up to half of these mushrooms may be contaminated with B. gladioli pv. cocovenenans.64 Following consumption of food contaminated with B. gladioli pv. cocovenenans, intoxication occurs rapidly, usually within 1–10 h.78 The classical symptoms are hyperglycemia followed by hypoglycemia, spasms, loss of consciousness, and death.74 Following autopsy, the liver, kidneys, brain, heart, lungs, gastrointestinal tract, and spleen all show signs of damage, particularly the first three organs.78 When food contaminated with B. gladioli pv. cocovenenans is fed to dogs, they develop spasms, enter comas and die within 2–3 h.78 Dogs and rhesus monkeys fed B. gladioli pv. cocovenenans culture supernatants die within 6–33 h and 15.5–35 h, respectively.56 When mice are fed the B. gladioli pv. cocovenenans toxin bongkrekic acid, all animals die within 45 minutes.9 24.1.2.3  Pathogenesis Although B. pseudomallei, B. mallei, and BCC species express a wide variety of virulence factors (including exopolysaccharide, type III secretion systems, and lipopolysaccharide), no single factor has been shown to have a predominant effect.8,23,79 This is in contrast to B. gladioli pv. cocovenenans, an organism whose pathogenicity is mediated solely by toxins. When mice are administered either live or heat-killed bacteria, adverse effects are not observed, as opposed to when they are administered culture supernatants or partiallypurified toxin.56,9 B. gladioli pv. cocovenenans produces two

Burkholderia

toxins, toxoflavin (also called xanthothricin) and bongkrekic acid (also called bongkrek acid or flavotoxin A). Toxoflavin has the chemical formula C7H7N5O2. This toxin is not restricted to B. gladioli pv. cocovenenans, as it is also produced by Streptomyces, Burkholderia glumae, Burkholderia plantarii, and phytopathogenic B. gladioli.80–82,14 In mice, the LD50 for injected toxoflavin is 1.7 mg/kg, while for the ingested toxin it is 8.4 mg/kg.83 This compound has a bright yellow color, a melting point of approximately 170°C, and a UV absorption maximum of 258 nm.54 Tempe bongkrek with a yellow color is particularly dangerous as it has been permeated by this toxin and likely by bongkrekic acid as well.72,84 However, both toxins may still be present even if there is no change in coloration.84 Several papers have been published describing the chemical synthesis of toxoflavin.85–87 This substance is toxic because it acts as an electron carrier, resulting in the production of hydrogen peroxide. Under normal conditions, NADH, and FADH2 produced during glycolysis and the citric acid cycle (in the cytosol and mitochondrial matrix, respectively) transfer their electrons to a series of carriers in the inner mitochondrial membrane, including cytochromes, which are organized into Complex I–IV.88 The electrons are shuttled down this chain based on redox potential, and the energy released is used to pump protons into the intermembrane space of the mitochondria. This transport creates a proton gradient that powers the ATP synthase, which produces the majority of ATP used by the cell in a process called oxidative phosphorylation.88 It was discovered by Latuasan and Berends that toxoflavin can interfere with this process.89 When antimycin A, which blocks Complex III of the electron transport chain, is added to yeast, respiration is inhibited.88,89 However, when antimycin A and toxoflavin are added together, no inhibitory effects are observed. Similarly, the addition of potassium cyanide, which blocks Complex IV, inhibited respiration, but not in the presence of toxoflavin.88,89 These results suggest that toxoflavin allows for cytochrome-independent electron transfer.89 Toxoflavin also exhibits electron-transferring activity independent of the mitochondrion. Latuasan and Berends showed that this toxin was able to stimulate oxygen uptake by both a mitochondria-free yeast cell extract and a yeast strain that lacks cytochrome proteins.89 When NADH is combined with toxoflavin in a yeast cell extract, electrons are transferred from NADH to toxoflavin and toxoflavin is reduced. Toxoflavin then transfers these electrons to oxygen, producing hydrogen peroxide. It is predicted that the toxic effect of toxoflavin is due to the action of the hydrogen peroxide and not due to interference with the electron transport chain.89 Yeast cells (which exhibit very high catalase activity) do not show growth defects in the presence of toxoflavin (even though their electron transport system is altered), which would be expected if interference with the mitochondria were contributing to toxicity.89 Although toxoflavin is highly toxic, it is not generally the key agent in B. gladioli pv. cocovenenans intoxications. Instead, the toxin with the greatest clinical relevance is

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bongkrekic acid (especially in the case of tempe bongkrek), as it is both more toxic and present in higher concentrations in contaminated foods.83,84 The LD50 in mice is 1.4 mg/kg when injected and 3.16 mg/kg when ingested.83,60 This compound has the chemical formula C28H38O7. Several papers have been published that have determined the properties and structure of bongkrekic acid.83,90–92 This compound is toxic because it inhibits oxidative phosphorylation by binding to the adenine nucleotide transporter (responsible for the shuttling of ADP and ATP across the inner mitochondrial membrane). The mechanism of action of bongkrekic acid was first examined in 1960. While the addition of toxoflavin to a cell homogenate sharply increases oxygen consumption, addition of bongkrekic acid has the opposite effect.89,93 Tests performed on isolated rat heart mitochondria by Welling et al. indicated that the oxidation of pyruvate (the end product of glycolysis), α-ketoglutarate, and malate (two citric acid cycle intermediates) were inhibited by bongkrekic acid.93 The mechanism behind this inhibition was not elucidated until 1970. Henderson and Lardy found that, when rat liver mitochondria were treated with bongkrekic acid, these organelles were no longer able to take up 14C-labeled ADP or ATP, suggesting that bongkrekic acid blocks the mitochondrial adenine nucleotide transporter.94 Further experiments indicated that bongkrekic acid binds to the transporter when it is in the matrix or m-state (the conformation in which the ADP/ATP binding site faces inwards towards the matrix).95 Because bongkrekic acid inhibits oxidative phosphorylation, the only way for cells to generate ATP is through anaerobic glycolysis.96 This metabolic change is responsible for the symptoms of intoxication. Glycogen stores are broken down to allow for an increased level of glycolysis, leading to hyperglycemia and increased lactic acid levels, but these stores are soon depleted, resulting in hypoglycemia and an inability to regenerate ATP.93 It is the ATP depletion that is fatal and not the hypoglycemia, as the injection of glucose is insufficient to prevent death.93 24.1.2.4  Biology B. gladioli pv. cocovenenans cells are motile, aerobic, nonspore­-forming, nonencapsulated Gram-negative rods. These bacteria form smooth, round colonies (on potato dextrose agar [PDA]) that are yellow pigmented due to the production of toxoflavin. Growth can occur between 6 and 41°C, but is optimal between 30 and 37°C.61,97 Most toxin production occurs between 22 and 30°C.97 Both catalase and oxidase tests are positive, but the oxidase reaction is extremely weak. Other characteristics of these bacteria (along with other B. gladioli pathovars) are summarized in Table 24.1. Two important aspects of the biology of B. gladioli pv. cocovenenans that affect its viability and toxin production in food are its susceptibility to pH and salt concentration. These bacteria cannot grow at a pH of 4.5 or in a salt concentration of 6%.61 As such, measures to decrease the pH or increase the salt content of foods such as tempe bongkrek have been suggested as a means to make them safer. However, some of these methods have been met with resistance. For example,

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addition of the acidic leaves of Oxalis spp. (a flowering plant) to the raw material for making tempe bongkrek decreases the pH to approximately 5.5, inhibiting bacterial growth. However, this addition changes the color of the cake, which has made this preventive measure relatively unpopular.84 Buckle and Kartadarma found that the production of both toxins was inhibited to different degrees following alteration of the pH and salt content by the addition of acetic acid and sodium chloride.84 After 48 h incubation in coconut culture medium (CCM, discussed below) at a pH of 4.5 or less, a salt concentration of 2% or greater, or a combination of pH 5.5 and 1% salt, toxoflavin was not produced. However, only the combination of decreased pH and higher salt concentration (5.5 and 1%, respectively) was sufficient to inhibit the production of bongkrekic acid in this medium. In laboratorysynthesized tempe bongkrek, a pH of 4.5 and 2% salt concentration was sufficient to inhibit the production of both toxoflavin and bongkrekic acid by three B. gladioli pv. cocovenenans strains. R. oligosporus growth was not inhibited under these conditions. Another important aspect of B. gladioli pv. cocovenenans biology with regards to its ability to produce toxin is its response to lipid content. Garcia et al. found that B. gladioli pv. cocovenenans could grow on rich coconut media (RCM) from which lipids had been extracted, but it did not produce bongkrekic acid until coconut fat was added to a level of 20%.72 When individual fatty acids were added to the media, bongkrekic acid was only produced in the presence of the saturated lauric acid (12:0), myristic acid (14:0), and palmitic acid (16:0), as well as the unsaturated oleic acid (18:1), linoleic acid (18:2), and linolenic acid (18:3). The three saturated fatty acids comprise over 70% of the total fatty acids present in coconut oil.72 Although bongkrekic acid production is affected by lipid content, toxoflavin production does not appear to be similarly affected, as it was synthesized even in the lipid-extracted RCM with no added fat.72 Therefore, intoxications that result from consuming contaminated foods with a lower fat content (including FCF and T. fuciformis) may be due to the action of toxoflavin more so than bongkrekic acid.72 However, it has also been suggested that, because corn oil has high oleic acid content, FCF may support the production of bongkrekic acid despite its relatively low lipid content.72 24.1.2.5  Conventional Diagnosis Because these intoxications have been limited to resource-poor areas and are relatively uncommon in comparison with many other foodborne pathogens, few detection measures for B. gladioli pv. cocovenenans have been described. Conventionally, these bacteria are isolated on CCM or a variant thereof. The following protocol, described by Ko et al., produces a medium that, when inoculated with R. oligosporus, approximates the properties of tempe bongkrek in a laboratory setting.98 (1) Remove 100 g meat from a fresh coconut (white layer). (2) Add 150 ml water (60–70°C).

Molecular Detection of Foodborne Pathogens

(3) Blend 2 min. Remove 200 ml liquid (using hydraulic handpress or other method). (4) Add 200 ml water (60–70°C). Repeat step 3. (5) Autoclave 60 g cakes 20 min at 110°C. In order to inoculate the cakes with mould, R. oligosporus spore suspensions (made in sterile water) are mixed with 60 g CCM cakes, poured into Petri dishes (approximately 20 g of media per dish), and incubated at 30°C for 48 h. B. gladioli pv. cocovenenans can be propagated on both CCM and laboratory-made tempe bongkrek.98 When toxoflavin is produced by bacteria growing on either of these, the media will turn a yellow color, which is a useful diagnostic criterion.84 However, the differential properties of these types of media are somewhat limited because other bacteria can produce toxoflavin and because not all B. gladioli pv. cocovenenans strains produce detectable levels of toxoflavin under laboratory conditions.14,80–82,84 However, because these intoxications have such a limited range (both with respect to the geographic area and the types of food involved), bacterial growth and toxin production on CCM or laboratory-made tempe bongkrek can be useful for propagation and preliminary analysis of B. gladioli pv. cocovenenans in food outbreaks. B. gladioli pv. cocovenenans can be identified using commercial test kits such as the Biolog GN2 system.9,42 This method, used to identify aerobic Gram-negative organisms, measures the ability of a bacterium to use a variety of carbon sources. This test can be used to differentiate pathovar cocovenenans from the other pathovars of B. gladioli.9 However, these commercial systems may give negative or conflicting results when used with these bacteria. Segonds et al. found that, using the API 20NE system, B. gladioli pv. cocovenenans could not be identified.99 Similarly, when isolates from raw milk were compared using the Biolog GN2 and API 20NE systems, one isolate was identified as B. cocovenenans by the first system and Pseudomonas fluorescens by the second.42 An effective method to detect and determine the concentration of toxins produced by B. gladioli pv. cocovenenans is high pressure liquid chromatography (HPLC). Most protocols for toxoflavin and bongkrekic acid detection are based on the methods developed by Voragen et al.100 In this protocol, toxoflavin and bongkrekic acid are extracted separately from tempe bongkrek. The UV absorbance is measured for bongkrekic acid at 267 nm and for toxoflavin at 258 nm. The extracted samples are compared to reference standards. Using this protocol, bongkrekic acid concentrations from either 2–160 µg/ml or 0.5–80 µg/ml (depending on injection volume) and toxoflavin concentrations from 1 to 300 µg/ml could be detected.100 This system effectively quantifies the levels of toxins and can detect the presence of each toxin even if they are present in a mixture. However, this method is time-consuming (as the toxins need to be extracted from the sample prior to analysis) and, more importantly, requires expensive and specialized equipment. Because these infections occur in economically-poor areas, detection methods for B. gladioli pv. cocovenenans should ideally be as simple and cost-effective as possible.

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Burkholderia

Because there is currently no selective medium for these ­bacteria, molecular techniques that can be used for rapid and effective detection during outbreaks of food intoxication are extremely important. 24.1.2.6  Molecular Diagnosis Although 16S rDNA sequencing is a useful molecular method for differentiating many bacteria, this procedure tends to be very unsuccessful for identifying members of the Burkholderia genus. For BCC species, these sequences are over 97.7% identical, which does not allow for species-level differentiation.101 Similarly, B. pseudomallei and B. mallei cannot be distinguished using this method because they have the exact same 16S rDNA sequence.102 Zhao et al. sequenced a 291 base pair segment of the 16S rDNA and found that there was a six base pair difference between B. gladioli pv. cocovenenans NCIMB 12451 and B. gladioli EY 3258.64 Viallard et al. found that the 16S sequences of the B. gladioli pv. gladioli and B. gladioli pv. cocovenenans type strains (ATCC 10248 and ATCC 33664, respectively) were 99.9% identical when a 1484 base pair region was sequenced.103 When Jiao et al. sequenced a segment with a similar length (1291 base pairs), they found that the sequence was between 99.4 and 99.7% identical between pathovar gladioli and pathovar cocovenenans strains and 98.2–99.6% identical among pathovar cocovenenans strains.9 In addition, B. gladioli pvs. gladioli and cocovenenans sequences had very high homology to those of both B. glumae and B. plantarii (98.0–99.4%). When 16S sequencing was used to identify isolates from CF patients in France, the sequence from one isolate identified as B. gladioli had only a one base pair change from the B. gladioli pv. cocovenenans reference sequence.104 These results indicate that the sequence similarity between the 16S rDNA sequences of the B. gladioli pathovars is too high to allow for adequate differentiation. As such, many studies that have identified B. gladioli in clinical specimens using this technique have not specified the pathovar to which these isolates belong.104–106 Despite this drawback, 16S sequencing has been used to putatively identify B. gladioli pv. cocovenenans in clinical isolates. In a 25-year-old patient from Thailand who produced anti-interferon γ autoantibodies, bacteria were isolated from various sites in the body, including lymphadenoid tissue and the lungs. The 16S rDNA sequences of these isolates were determined and they were identified as Burkholderia cocovenenans.107,108 To the best of our knowledge, these are the only reports in the literature of B. gladioli pv. cocovenenans causing this type of disease. Capillary electrophoresis–single-strand conformation polymorphism (CE–SSCP) analysis is a second technique that uses 16S rDNA sequence to identify B. gladioli pv. cocovenenans.109 In this method, 16S rDNA sequences are amplified using PCR primers with fluorescent labels. Capillary gel electrophoresis is performed using an automated DNA sequencer following denaturation of the PCR product. The resulting electropherograms differ based upon the conformation of the two labeled single-strand products. Using this protocol, B. gladioli pvs. cocovenenans, gladioli, and alliicola, B. glumae,

and B. plantarii all produced very similar electropherograms (which would be expected based upon the strong homology of their 16S rDNA sequences) and could be differentiated from other Gram-negative nonfermenters but not from one another. Yet another technique that uses 16S rDNA sequence to identify B. gladioli pv. cocovenenans is microarray analysis. Jin et al. developed a microarray with probes for eubacteria, for Gram-positive and Gram-negative organisms, and for specific pathogens based on their 16S sequences.110 Bacterial 16S rDNA was amplified using fluorescently-labeled primers and hybridized to the probes on the microarray. Although the microarray in this paper included a probe designed to recognize B. gladioli pv. cocovenenans, the array was not tested with this pathovar’s 16S rDNA. In a later paper, this group tested their microarray using three B. gladioli pv. cocovenenans strains and found that the microarray could successfully differentiate these strains from other foodborne pathogens.111 However, because this microarray was not tested with nonfoodborne B. gladioli, it is unknown if the other three pathovars would cross-react using this assay. Probe-based cell fishing is a technique that was developed to analyze the members of a microbial community without culturing them.112 In the first stage, biotinylated RNA probes hybridize in situ to the 23S rRNA. The cells are then incubated with paramagnetic streptavidin-coated beads. When the bacteria are run through a column in a magnetic field, cells in which the probes hybridized will stay bound, while those with no hybridized probe will not. Using the probe DIIIBcep, Stoffels et al. were able to detect the type strain of B. gladioli pv. cocovenenans.112 However, this probe was relatively nonspecific, as it also hybridized with B. cepacia, B. vietnamiensis, B. gladioli, and B. plantarii. Although several novel methods for B. gladioli detection have been developed since 1999, not all of these procedures were tested for their ability to identify food intoxication isolates.113–115 One of the protocols that was tested with B. gladioli pv. cocovenenans strains used primers specific for the gyrB gene in a multiplex PCR protocol.116 These primers amplify a 479 base pair fragment from B. gladioli pvs. cocovenenans, gladioli, alliicoli, and agaricicola, but not from B. glumae, B. plantarii, or B. cepacia. Therefore, this protocol is more specific than either CE–SSCP or probe-based cell fishing with respect to the detection of B. gladioli pv. cocovenenans. Although this method does not specifically identify this pathovar, it can still be a useful diagnostic tool. Because the cocovenenans pathovar is found in such a narrow range of foods, a positive result in this assay using bacteria isolated from a suspect food would be strong evidence for the presence of B. gladioli pv. cocovenenans.

24.2  Methods 24.2.1  Reagents and Equipment Table 24.2 describes the reagents and equipment required for the B. gladioli pv. cocovenenans detection procedure described in Section 24.2.3.

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Table 24.2 List of Reagents and Equipment Required Reagents -Sterile distilled water -10 × PCR buffer -MgCl2 -dNTPs -Primer sets P1–P3 (Section 24.2.3) -Taq polymerase -Agarose -Gel electrophoresis buffer

Equipment -DNA thermal cycler -Gel electrophoresis apparatus -Ultraviolet light box

-Ethidium bromide

24.2.2 Burkholderia gladioli pathovar cocovenenans Sample Collection and Preparation 24.2.2.1  Bacterial Isolation, Propagation, and Storage Because it is the toxins that cause the illness and not the bacteria themselves, B. gladioli pv. cocovenenans isolates are generally collected from the suspect food instead of from the patient (although in some cases they may be collected from vomit).117 These strains can be isolated from food material on a simple nutrient medium such as PDA.56 Other media commonly used for propagation include Luria-Bertani and trypticase soy agar.9 Colonies on PDA appear white or gray and produce a diffusible yellow pigment (toxoflavin).56,64 When the bacteria are grown on CCM, cell numbers reach 1010 within 2 days of incubation at 30–37°C.97 To quantify the bacteria in a sample, 1 g of CCM is blended with 100 ml 0.9% saline solution for 1 min and serial dilutions are made from this mixture.97 Bacteria can be stored at –80°C in 25% (v/v) glycerol.9 24.2.2.2  Toxin Extraction The following procedure for toxoflavin extraction was described by van Damme et al.54 (1) Propagate cells in 2% glycerol, 1% peptone, and 0.5% NaCl or 0.6% KCl 48 h at 28°C. (2) Add a saturating amount of ammonium sulphate at room temperature. (3) Centrifuge 15 min and filter. Extract three times with chloroform (1/2 filtrate volume). (4) Concentrate to 1% of the original culture volume. Centrifuge and filter solution. (5) Add 5/3 filtrate volume of light petroleum. Extract four times with water (1/4 volume). (6) Dilute to 7.5% of the original culture volume. Repeat steps 2 and 3. Evaporate chloroform. (7) Add 1–2% of the original culture volume of n-propanol at 55°C. Filter and incubate at –5°C. (8) The toxoflavin is now crystallized. Wash crystals with propanol and dry ether and dry.

The following procedure for bongkrekic acid extraction was described by Nugteren and Berends.53 (1) Propagate cells in 1 kg modified CCM. (2) Cover with petroleum ether, incubate 1 day at room temperature, and filter. Repeat. (3) Extract with 50 ml aliquots of 2% sodium bicarbonate. (4) Add 2 N H2SO4 until the extract reaches pH 3 and extract with 250 ml peroxide-free ether. Wash 2 × with 100 ml water. Extract with 25 ml aliquots of 2% sodium bicarbonate until no optical activity is measured. This extract (~150 ml volume) contains fatty acids (including capronic and caprylic acids) and approximately 2 g of bongkrekic acid. The bongkrekic acid can then be further purified using a chromatopile apparatus.53

24.2.3 Burkholderia gladioli pathovar cocovenenans Detection Procedure As discussed above, most of the molecular detection procedures developed that recognize B. gladioli pv. cocovenenans are limited by the fact that they simultaneously detect the other pathovars of B. gladioli (and occasionally other species such as B. glumae and B. plantarii) as part of this group. The following procedure, developed by Clode et al., was developed prior to the reclassification of B. cocovenenans as part of B. gladioli.118 In the testing performed by this group, this protocol successfully differentiates the B. gladioli pv. cocovenenans type strain LMG 11626 from the B. gladioli pv. gladioli strains ATCC 25417, ATCC 10247, and type strain ATCC 10248/NCTC 12378, B. glumae strain LMG 1277, and B. plantarii strain LMG 10908. This method uses three sets of primers in a multiplex PCR reaction. These primers are designed to amplify a 323 base pair region of BCC 23S rRNA (primer set P1), a 209 base pair region of BCC 16S rRNA (primer set P2), and a 274 base pair 16S–23S rRNA internal transcribed spacer (ITS) region of B. gladioli (primer set P3). At the time that this paper was written, the BCC was not yet divided into 15 (atleast 17) species, so the primers specific for “B. cepacia” were designed to amplify and tested with the BCC species B. cepacia, B. cenocepacia, B. stabilis, B. vietnamiensis, and B. lata. Primer sequences

Primer set P1 Primer set P2 Primer set P3

PC1 GCTGC GGATG CGTGC TTTGC PC2 GCCTT CTCCA ATGCA GCGAC PSR1 TTTCG AGCAC TCCCG CCTCT CAG PSL1 AACTA GTTGT TGGGG ATTCA TTTC PG1 TTCAA TGACA AACGT TCGGG PG2 GCTTT CGCTT GACAG GCC

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Burkholderia

Multiplex PCR protocol (1) To isolate chromosomal DNA, transfer five colonies (following incubation on solid media for 48 h) to 100 µl sterile distilled water. Vortex and centrifuge 5 min at 13000 × g. Transfer 3 µl of the supernatant to 12 µl sterile distilled water. (2) Set up PCR reactions containing 2.5 µl 10 × PCR buffer, 50 pmol MgCl2, 2.5 mol of each dNTP, 100 pmol of each primer (PC1, PC2, PSR1, PSL1, PG1, and PG2), 1.25 U of Taq polymerase, and the chromosomal DNA prepared in the previous step. (3) Amplify in a DNA thermal cycler under the following conditions: one cycle of 96°C for 5 min; 24 cycles of 96°C for 15 sec, 63°C for 30 sec, 72°C for 90 sec; one cycle of 70°C for 5 min (4) Separate PCR products on a 1.5% (wt/vol) agarose gel at 100 V for 1.5 h. The authors tested this protocol with characterized strains of the BCC (B. cepacia, B. cenocepacia, B. stabilis, B. vietnamiensis, and B. lata), B. gladioli pvs. gladioli and cocovenenans, B. glumae, B. plantarii, Burkholderia andropogonis, Burkholderia caryophylli, Burkholderia vandii, Ralstonia pickettii, Ralstonia solanacearum, and Pseudomonas aeruginosa. Of all of these strains, only the amplification of B. gladioli pv. cocovenenans strain LMG 11626 DNA generated PCR products approximately 274 and 323 base pairs in size (Figure 24.1). Only this DNA was amplified by both the P1 and P3 primer sets, thus differentiating B. gladioli pv. cocovenenans from all other

1.47 Kb 738 bp 369 bp 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21

123 bp

Figure 24.1  Multiplex PCR with three primer sets and reference strains of Burkholderia spp. and other species. Lane 1: B. cepacia NCTC 10661; lane 2: B. cenocepacia NCTC 10744; lane 3: B. cenocepacia ATCC 25610; lane 4: B. gladioli pv. gladioli ATCC 10248/NCTC 12378; lane 5: B. gladioli pv. gladioli ATCC l0248/ NCTC 12378; lane 6: B. gladioli pv. gladioli ATCC 25417; lane 7: R. pickettii NCTC 11149; lane 8: B. gladioli pv. cocovenenans LMG 11626; lane 9: R. solanacearum LMG 2295; lane 10: B. caryophylli LMG 2155; lane 11: B. vandii LMG 16020; lane 12: B. glumae LMG 1277; lane 13: B. vietnamiensis LMG 6998; lane 14: B. plantarii LMG 10908; lane 15: B. andropogonis LMG 2126; lane 16: P. aeruginosa NCTC 10332; lane 17: P. aeruginosa NCTC 10662; lane 18: Acinetobacter baumannii; lane 19: S. maltophilia; lane 20: water blank; lane 21: 123 bp size markers. (From Clode, F.  E. et al., J. Clin. Pathol., 52, 173, 1999. Reproduced/amended with permission from the BMJ Publishing Group.)

Table 24.3 Reactions of Reference Strains of Burkholderia and Ralstonia with Primer Sets Species B. cepacia B. cenocepacia B. vietnamiensis B. cenocepacia B. stabilis B. lata B. cenocepacia B. cenocepacia B. gladioli pv. gladioli B. gladioli pv. gladioli B. gladioli pv. gladioli B. gladioli pv. gladioli B. glumae B. plantarii B. vietnamiensis B. vandii R. solanacearum B. andropogonis B. caryophylli B. gladioli pv. cocovenenans R. pickettii P. aeruginosa

Strain NCTC 10661 NCTC 10744 ATCC 29424 ATCC 25608 ATCC 27515 ATCC 17460 ATCC 25610 ATCC 17765 NCTC 12378 ATCC 25417 ATCC 10247 ATCC 10248 LMG 1277 LMG 10908 LMG 6998 LMG 16020 LMG 2295 LMG 2126 LMG 2155 LMG 11626 NCTC 11149 NCTC 10332

P1*

P2*

P3*

+ + + + + + + + – – – – – – + + + – – + – –

+ + + + + + + + – – – – + – – + – – + – – –

– – – – – – – – + + – + – – – – – – – + – –

*Primers as in Section 24.2.3. Source: Clode, F. E. et al., J. Clin. Pathol., 52, 173, 1999. Reproduced/ amended with permission from the BMJ Publishing Group.

species tested (Table 24.3). When 177 clinical isolates putatively identified as “B. cepacia” were tested with these primer sets, none of them formed products with both P1 and P3, suggesting that reaction with these sets is relatively specific to B. gladioli pv. cocovenenans. Although further testing is required to verify the sensitivity and specificity of the amplification, this protocol appears to effectively identify B. gladioli pv. cocovenenans and differentiate it from B. gladioli pv. gladioli, B. glumae, and B. plantarii.

24.3 Conclusions and Future Perspectives Although B. gladioli pv. cocovenenans is a relatively unknown foodborne pathogen, it causes significant morbidity and mortality in certain parts of the world. There are substantial challenges involved in identifying these bacteria, both with respect to the biology of the organism and the socioeconomic conditions of the affected regions. Appropriate detection methods for B. gladioli pv. cocovenenans should be specific enough to differentiate it from related organisms such as B. glumae, B. plantarii, and the other pathovars of B. gladioli, but should be carried out using relatively inexpensive materials and equipment. Most molecular detection methods developed to date, including CE–SSCP, microarray analysis,

340

and probe-based cell fishing, are deficient in one or both of these areas. Testing performed by Clode et al. suggests that an effective and simple method for the detection of B. gladioli pv. cocovenenans is a multiplex PCR based on amplification of rDNA and internal transcribed spacer sequences.118 However, further studies are required to verify the effectiveness of this protocol. Research into novel diagnostic measures for these organisms, particularly the development of a selective medium, could be instrumental in preventing and responding to future outbreaks and intoxications.

References













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Molecular Detection of Foodborne Pathogens 15. Bezerra Rolim, D. et al. Melioidosis, northeastern Brazil. Emerg. Infect. Dis., 11, 1458, 2005. 16. Whitmore, A. An account of a glanders-like disease occurring in Rangoon. J. Hyg., 13, 1, 1913. 17. Dance, D. A. B. Ecology of Burkholderia pseudomallei and the interactions between environmental Burkholderia spp. and human-animal hosts. Acta Trop., 74, 159, 2000. 18. Suputtamongkol, Y. et al. The epidemiology of melioidosis in urban Ratchatani, northeast Thailand. Int. J. Epidemiol., 23, 1082, 1994. 19. Stanton, A. T. and Fletcher, W. Studies from the Institute for Medical Research, Federated Malay States, No. 21: Melioidosis. John Bale, Sons & Danielsson, Ltd., London, 1932. 20. Inglis, T. J. J. et al. Dry-season outbreak of melioidosis in Western Australia. Lancet, 352, 1600, 1998. 21. Zanetti, F., De Luca, G. and Stampi, S. Recovery of Burkholderia pseudomallei and B. cepacia from drinking water. Int. J. Food. Microbiol., 59, 67, 2000. 22. Rose, L. J. et al. Chlorine inactivation of bacterial bioterrorism agents. Appl. Environ. Microbiol., 71, 566, 2005. 23. Whitlock, G. C., Mark Estes, D. and Torres, A. G. Glanders: off to the races with Burkholderia mallei. FEMS Microbiol. Lett., 277, 115, 2007. 24. Gilad, J. et al. Burkholderia mallei and Burkholderia pseudomallei as bioterrorism agents: national aspects of emergency preparedness. Israel Med. Assoc. J., 9, 499, 2007. 25. Wilson, G. S. and Miles, A. Topley and Wilson’s Principles of Bacteriology, Virology and Immunity, 6th Edition. Edward Arnold, London, 1975. 26. Srinivasan, A. et al. Glanders in a military research microbio­ logist. New Engl. J. Med., 345, 256, 2001. 27. Rotz, L. D. et al. Public health assessment of potential biological terrorism agents. Emerg. Infect. Dis., 8, 225, 2002. 28. Takhistov, P. and Bryant, C. M. Protecting the food supply. Food Technol., 60, 34, 2006. 29. Rosenstein, B. J. and Hall, D. E. Pneumonia and septicemia due to Pseudomonas cepacia in a patient with cystic fibrosis. Johns Hopkins Med. J., 147, 188, 1980. 30. Bottone, E. J. et al. Association of Pseudomonas cepacia with chronic granulomatous disease. J. Clin. Microbiol., 1, 425, 1975. 31. Zhang, L. and Xie, G. Diversity and distribution of Burkholderia cepacia complex in the rhizosphere of rice and maize. FEMS Microbiol. Lett., 266, 231, 2007. 32. Ramette, A. and Tiedje, J. M. Multiscale responses of microbial life to spatial distance and environmental heterogeneity in a patchy ecosystem. Proc. Natl. Acad. Sci. USA, 104, 2761, 2007. 33. Yara, R. et al. A bacterium belonging to the Burkholderia cepacia complex associated with Pleurotus ostreatus. J. Microbiol., 44, 263, 2006. 34. Cohen, R., Persky, L. and Hadar, Y. Biotechnological applications and potential of wood-degrading mushrooms of the genus Pleurotus. Appl. Microbiol. Biot., 58, 582, 2002. 35. Smith, D., Mikolajcik, E. and Lindamood, J. Causative organisms and chemical nature of the Swiss cheese rind rot defect. Cult. Dairy Prod. J., 22, 9, 1987. 36. Blanco, D. et al. Study of “potato defect” of raw dry-cured ham. Ind. Conserv., 69, 230, 1994. 37. Huang, Y. et al. Biocontrol of postharvest orange diseases by a strain of Pseudomonas cepacia under semi-commercial conditions. Postharvest Biol. Tec., 3, 293, 1993.

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341 57. Research Group for Pathogenesis of Fermented Corn Flour Poisoning. A new species of food poisoning bacteria – Flavobacterium farinofermentans sp. nov. Acta Acad. Med. Sincae, 2, 77, 1980. Cited in Zhao, N. X. et al. Comparative description of Pseudomonas cocovenenans (van Damme, Johannes, Cox, and Berends 1960) NCIB 9450T and strains isolated from cases of food poisoning caused by consumption of fermented corn flour in China. Int. J. Syst. Bacteriol., 40, 452, 1990. 58. Zhao, N. X. et al. Comparative study on Pseudomonas cocovenenans and Pseudomonas farinofermentans. Chin. J. Microbiol. Immunol., 8, 151, 1988. 59. Meng, Z. et al. Comparing studies on Flavobacterium farinofermentans sp. nov. (tentative name) and Pseudomonas cocovenenans (NCIB 9450). J. Hyg. Res., 16, 17, 1987. 60. Hu, W. J. et al. Fermented corn flour poisoning in rural areas of China. III. Isolation and identification of main toxin produced by causal microorganisms. Biomed. Environ. Sci., 2, 65, 1989. 61. Zhao, N. X. et al. Comparative description of Pseudomonas cocovenenans (van Damme, Johannes, Cox, and Berends 1960) NCIB 9450T and strains isolated from cases of food poisoning caused by consumption of fermented corn flour in China. Int. J. Syst. Bacteriol., 40, 452, 1990. 62. Yabuuchi, E. et al. Proposal of Burkholderia gen. nov. and transfer of seven species of the genus Pseudomonas homology group II to the new genus, with the type species Burkholderia cepacia (Palleroni and Holmes 1981) comb. nov. Microbiol. Immunol., 36, 1251, 1992. 63. Gillis, M. et al. Polyphasic taxonomy in the genus Burkholderia leading to an emended description of the genus and proposition of Burkholderia vietnamiensis sp. nov. for N2-fixing isolates from rice in Vietnam. Int. J. Syst. Bacteriol., 45, 274, 1995. 64. Zhao, N. et al. Phylogenetic evidence for the transfer of Pseudomonas cocovenenans (van Damme et al. 1960) to the genus Burkholderia as Burkholderia cocovenenans (van Damme et al. 1960) comb. nov. Int. J. Syst. Bacteriol., 45, 600, 1995. 65. Vandamme, P. et al. Occurrence of multiple genomovars of Burkholderia cepacia in cystic fibrosis patients and proposal of Burkholderia multivorans sp. nov. Int. J. Syst. Evol. Microbiol., 47, 1188, 1997. 66. Coenye, T. et al. Burkholderia cocovenenans (van Damme et al. 1960) Gillis et al. 1995 and Burkholderia vandii Urakami et al. 1994 are junior synonyms of Burkholderia gladioli (Severini 1913) Yabuuchi et al. 1993 and Burkholderia plantarii (Azegami et al. 1987) Urakami et al. 1994, respectively. Int. J. Syst. Bacteriol., 49, 37, 1999. 67. Qiu, M., Liu, X. and Yang, R. Study on the molecular epidemiology characteristics of Pseudomonas cocovenenans subsp. farinofermentans isolated from China with rDNA fingerprinting. J. Hyg. Res., 27, 57, 1998. 68. Qiu, M. and Liu, X. Relationship between the toxigenicity and ribotype distribution of Pseudomonas cocovenenans subsp. farinofermentans. J. Hyg. Res., 27, 119, 1998. 69. Jiao, Z. et al. Sequencing and analysis of 16S rDNA sequences for P. cocovenenans subsp farinofermentans. J. Hyg. Res., 28, 232, 1999. 70. Jiao, Z. et al. Determination of DNA-DNA homology among Pseudomonas cocovenenans subsp. farinofermentans with microdilution plate hybridization method. Acta Microbiol. Sinica, 41, 70, 2001. 71. Adams, M. R. and Moss, M. O. Food Microbiology, 2nd Ed. Royal Society of Chemistry, Cambridge, UK, 2000.

342 72. Garcia, R. A., Hotchkiss, J. H. and Steinkraus, K. H. The effect of lipids on bongkrekic (Bongkrek) acid toxin production by Burkholderia cocovenenans in coconut media. Food Addit. Contam., 16, 63, 1999. 73. Jay, J. M., Loessner, M. J. and Golden, D. A. Modern Food Microbiology, 7th Ed., Springer, New York, 2005. 74. van Veen, A. G. The bongkrek toxins, pp. 43–50. In R. I. Mateles and Wogan, G. N. (ed.), Biochemistry of Some Foodborne Microbial Toxins. MIT Press, Cambridge, UK, 1966. 75. Arbianto, P. Bongkrek Food Poisoning in Java. Proc. GIAM-V, 371, 1979. 76. Mujimanto, Memeragi Bongkrek. Topic, 75, 24, 1975. Cited in Arbianto, P. Bongkrek food poisoning in Java. Proc. GIAM-V, 371, 1979. 77. Indonesian Embassy. Tempe, the unique health food of Indonesia [online], http://www.kbri-islamabad.go.id/index. php?option=com_content&task=view&id=30&Itemid=1, 2008. 78. Meng, Z. et al. Studies on fermented corn flour poisoning in rural areas of China. I. Epidemiology, clinical manifestations, and pathology. Biomed. Environ. Sci., 1, 101, 1988. 79. Mahenthiralingam, E., Urban, T A. and Goldberg, J. B. The multifarious, multireplicon Burkholderia cepacia complex. Nat. Rev. Microbiol., 3, 144, 2005. 80. Machlowitz, R. A. et al. Xanthothricin, a new antibiotic. Antibiot. Chemother., 4, 259, 1954. 81. Jeong, Y. et al. Toxoflavin produced by Burkholderia glumae causing rice grain rot is responsible for inducing bacterial wilt in many field crops. Plant Dis., 87, 890, 2003. 82. Sato, Z. et al. Toxins produced by Pseudomonas glumae. Ann. Phytopathol. Soc. Jpn., 55, 353, 1989. Cited in Maeda, Y. et al. Phylogenetic study and multiplex PCR-based detection of Burkholderia plantarii, Burkholderia glumae and Burkholderia gladioli using gyrB and rpoD sequences. Int. J. Syst. Evol. Microbiol., 56, 1031, 2006. 83. Lijmbach, G. W. M., Cox, H. C. and Berends, W. Elucidation of the chemical structure of bongkrekic acid. I. Isolation, purification and properties of bongkrekic acid. Tetrahedron, 26, 5993, 1970. 84. Buckle, K. A. and Kartadarma, E. Inhibition of bongkrek acid and toxoflavin production in tempe bongkrek containing Pseudomonas cocovenenans. J. Appl. Bacteriol., 68, 571, 1990. 85. Daves Jr., G. D., Robins, R. K. and Cheng, C. C. The total synthesis of toxoflavin. J. Am. Chem. Soc., 83, 3904, 1961. 86. Levenberg, B. and Linton, S. N. On the biosynthesis of toxoflavin, an azapteridine antibiotic produced by Pseudomonas cocovenenans. J. Biol. Chem., 241, 846, 1966. 87. Yoneda, F., Shinomura, K. and Nishigaki, S. A convenient synthesis of toxoflavins and toxoflavin-n-oxides. Tetrahedron Lett., 13, 851, 1971. 88. Voet, D., Voet, J. G. and Pratt, C. W. Fundamentals of Biochemistry, Upgrade Edition. John Wiley & Sons, Inc., New York, 2002. 89. Latuasan, H. E. and Berends, W. On the origin of the toxicity of toxoflavin. Biochim. Biophys. Acta, 52, 502, 1961. 90. Lijmbach, G. W. M., Cox, H. C. and Berends, W. Elucidation of the structure of bongkrekic acid. II. Chemical structure of bongkrekic acid and study of the UV, IR, NMR and mass spectra. Tetrahedron, 27, 1839, 1971. 91. de Bruijn, J. et al. The structure of bongkrekic acid. Tetrahedron, 29, 1541, 1973. 92. Hu, W. J., Zhang, G. S. and Chu, F. S. Purification and partial characterization of flavotoxin A. Appl. Environ. Microbiol., 48, 690, 1984.

Molecular Detection of Foodborne Pathogens 93. Welling, W., Cohen, J. A. and Berends, W. Disturbance of oxidative phosphorylation by an antibioticum produced by Pseudomonas cocovenenans. Biochem. Pharmacol., 3, 122, 1960. 94. Henderson, P. J. and Lardy, H. A. Bongkrekic acid: an inhibitor of the adenine nucleotide translocase of mitochondria. J. Biol. Chem., 245, 1319, 1970. 95. Buchanan, B. B., Eiermann, W. and Riccio, P. Antibody evidence for different conformational states of ADP,ATP translocator protein isolated from mitochondria. Proc. Natl. Acad. Sci. USA, 73, 2280, 1976. 96. Schwerdt, G. et al. Inhibition of mitochondria prevents cell death in kidney epithelial cells by intra- and extracellular acidification. Kidney Int., 63, 1725, 2003. 97. Ko, S. D. Growth and toxin production of Pseudomonas cocovenenans, the so-called ‘bongkrek bacteria’. ASEAN Food J., 1, 78, 1985. 98. Ko, S. D., Kelholt, A. J. and Kampelmacher, E. H. Inhibition of toxin production in tempe bongkrek. Proc. GIAM-V, 375, 1979. 99. Segonds, C. et al. Differentiation of Burkholderia species by PCR-restriction fragment length polymorphism analysis of the 16S rRNA gene and application to cystic fibrosis isolates. J. Clin. Microbiol., 37, 2201, 1999. 100. Voragen, A. G. J., De Kok, H. A. M. and Kelholt, A. J. Determination of bongkrek acid and toxoflavin by high pressure liquid chromatography. Food Chem., 9, 167, 1982. 101. Coenye, T. et al. Taxonomy and identification of the Burkholderia cepacia complex. J. Clin. Microbiol., 39, 3427, 2001. 102. Bauernfeind, A. et al. Molecular procedure for rapid detection of Burkholderia mallei and Burkholderia pseudomallei. J. Clin. Microbiol., 36, 2737, 1998. 103. Viallard, V. et al. Burkholderia graminis sp. nov., a rhizospheric Burkholderia species, and reassessment of [Pseudomonas] phenazinium, [Pseudomonas] pyrrocinia and [Pseudomonas] glathei as Burkholderia. Int. J. Syst. Bacteriol., 48, 549, 1998. 104. Ferroni, A. et al. Use of 16S rRNA gene sequencing for identification of nonfermenting gram-negative bacilli recovered from patients attending a single cystic fibrosis center. J. Clin. Microbiol., 40, 3793, 2002. 105. Boyanton Jr., B. L. et al. Burkholderia gladioli osteomyelitis in association with chronic granulomatous disease: Case report and review. Pediatr. Infect. Dis. J., 24, 837, 2005. 106. Lynch, K. H. and Dennis, J. J. Development of a species-specific fur gene-based method for identification of the Burkholderia cepacia complex. J. Clin. Microbiol., 46, 447, 2008. 107. Höflich, C. et al. Naturally occurring anti-IFN-γ autoantibody and severe infections with Mycobacterium cheloneae and Burkholderia cocovenenans. Blood, 103, 673, 2004. 108. Halle, E. et al. Melioidosis-like disease: infection with Burkholderia cocovenenans as rare differential diagnosis for lymphadenitis colli. Laryngo-Rhino-Otol., 86, 287, 2007. 109. Ghozzi, R. et al. Capillary electrophoresis-single-strand conformation polymorphism analysis for rapid identification of Pseudomonas aeruginosa and other Gram-negative nonfermenting bacilli recovered from patients with cystic fibrosis. J. Clin. Microbiol., 37, 3374, 1999. 110. Jin, L. Q. et al. Detection and identification of intestinal pathogenic bacteria by hybridization to oligonucleotide microarrays. World J. Gastroentero., 11, 7615, 2005. 111. Wang, X. W. et al. Development and application of an oligonucleotide microarray for the detection of food-borne bacterial pathogens. Appl. Microbiol. Biot., 76, 225, 2007.

Burkholderia 112. Stoffels, M., Ludwig, W. and Schleifer, K. H. rRNA ­probe-based cell fishing of bacteria. Environ. Microbiol., 1, 259, 1999. 113. Brisse, S. et al. Distinguishing species of the Burkholderia cepacia complex and Burkholderia gladioli by automated ribotyping. J. Clin. Microbiol., 38, 1876, 2000. 114. Whitby, P. W. et al. Species-specific PCR as a tool for the identification of Burkholderia gladioli. J. Clin. Microbiol., 38, 282, 2000. 115. Furuya, N. et al. Specific oligonucleotide primers based on sequences of the 16S-23S rDNA spacer region for the detection of Burkholderia gladioli by PCR. J. Gen. Plant Pathol., 68, 220, 2002.

343 116. Maeda, Y. et al. Phylogenetic study and multiplex PCR-based detection of Burkholderia plantarii, Burkholderia glumae and Burkholderia gladioli using gyrB and rpoD sequences. Int. J. Syst. Evol. Microbiol., 56, 1031, 2006. 117. Jakarta Post. Burkholderia cocovenenans foodborne illness – Indonesia (Central Java) [online], http://www.promedmail. org/pls/otn/f?p=2400:1202:3714406431165003::NO::F240 0P1202_CHECK_DISPLAY,F2400_P1202_PUB_MAIL_ ID:X,38630, 2007. 118. Clode, F. E. et al. Evaluation of three oligonucleotide primer sets in PCR for the identification of Burkholderia cepacia and their differentiation from Burkholderia gladioli. J. Clin. Pathol., 52, 173, 1999.

25 Campylobacter

Aurora Fernández Astorga and Rodrigo Alonso Basque Country University

Contents 25.1 Introduction.................................................................................................................................................................... 345 25.1.1 Classification..................................................................................................................................................... 345 25.1.2 Biology.............................................................................................................................................................. 346 25.1.3 Pathogenesis...................................................................................................................................................... 346 25.1.3.1 Virulence Factors............................................................................................................................. 346 25.1.3.2 Animal Models................................................................................................................................ 348 25.1.4 Isolation and Detection..................................................................................................................................... 348 25.1.4.1 Traditional Methods......................................................................................................................... 348 25.1.4.2 Rapid Methods................................................................................................................................. 349 25.1.4.3 Molecular Methods.......................................................................................................................... 349 25.2 Methods.......................................................................................................................................................................... 353 25.2.1 Reagents and Equipment................................................................................................................................... 353 25.2.2 Sample Preparation and DNA Extraction......................................................................................................... 353 25.2.3 Detection Procedures........................................................................................................................................ 354 25.2.3.1 Multiplex PCR................................................................................................................................. 354 25.2.3.2 Duplex Real-Time PCR................................................................................................................... 355 25.3 Conclusion and Future Perspectives............................................................................................................................... 355 Acknowledgments...................................................................................................................................................................... 356 References.................................................................................................................................................................................. 356

25.1  Introduction 25.1.1  Classification Members of the genus Campylobacter are classified into the epsilon class of proteobacteria, in the order Campylobacteriales. They share a close taxonomic framework and biological and clinical characteristics which complicates the species-specific identification in some cases. The genus Campylobacter, first described by Véron and Chatelain1 in 1973, comprises Gram-negative, nonspore-forming bacilli that have a curved or spiral shape with tapering ends. Cells possess a polar flagellum at one or both ends of the cells which is responsible of the characteristic corkscrew-like motility. They are generally microaerophilic requiring modified atmospheres with 3–15% oxygen and 2–10% carbon dioxide for optimal growth conditions. Further, they are unable to ferment nor to oxidize carbohydrates and to degrade complex substances instead they obtain energy from amino acids, or tricarboxylic acid cycle intermediates.2,3 At present, the genus includes at least 16 species, and six subspecies, of which Campylobacter jejuni subsp. jejuni, C. jejuni subsp. doylei, Campylobacter coli, Campylobacter lari, Campylobacter upsaliensis, and Campylobacter helveticus form a genetically closed group of species4 classed as thermophilic owing its optimal growth at 42°C. Thermophilic

campylobacters infect both human and warm-blooded animals. Although primarily occurring as commensals in a wide range of domestic and wild birds and animals, thermophilic campylobacters (except C. jejuni subsp. doylei) can also cause diseases being the most commonly isolated from human and animal diarrhea.4–6 As animal pathogens they are long related to diarrhea in cattle and septic abortion in both cattle and sheep,7 however, it was not until the 1970s that they were successfully associated to human enteritis (for an historical account, see Skirrow8). Human infection is termed campylobacteriosis, and ranges from self-limiting gastroenteritis to more serious systemic infections, i.e., bacteriaemia or hemolytic uraemic syndrome.6,9 Post-infectious complications are rare but demyelinating disorders as Guillian–Barré syndrome (GBS) and Miller Fisher syndrome (MFS) are now recognized as sequelae of Campylobacter infection.10 The epidemiology of Campylobacter infection is complex since the organism is widely distributed in the environment and throughout the food chain. These human pathogens are commonly found in the environment and on many raw foods, of both plant and animal origin. Campylobacters are considered to be part of the normal intestinal biota of a wide range of domestic and wild animals. Fecal contamination of meat often occurs during slaughtering, and human infection 345

346

is usually acquired through the consumption of undercooked contaminated meat or other cross-contaminated food products. Bacterial numbers can be very high on certain key foods like raw poultry meat. The risks to human health vary between the different animal species and will also be different between countries often due to variations in food preparation and consumption patterns.6 With incidences in developed countries two to seven times more frequent than infections with Salmonella species, Shigella species, or Escherichia coli O157:H79 campylobacteriosis is now considered to be one of the most important foodborne diseases worldwide.6 A range of food of mainly animal origin is involved in human transmission but it is of general acceptance that consumption and handling of poultry11 are the major sources of Campylobacter infection even though other sources like unpasteurized milk,12,13 contaminated water,14,15 and contact with pets especially birds and cats16 are also common. Although some outbreaks have been reported17–19 most campylobacteriosis cases are normally sporadic, affecting children and young adults in developed countries and mainly infants and young children in developing countries.9 Owing to the incidence, thought to be an estimated 1% of the population per year in developed countries and even higher in developing countries, as well as the spectrum of disease with chronic sequelae and the food risks, it is not surprising that the health and social burden of campylobacteriosis could be larger than estimated.20 Among the etiological agents of human campylobacteriosis it is worth highlighting C. jejuni which accounts for more than 95% of bacteria isolated from diarrheal stool samples.21–23 Therefore C. jejuni is a pathogen of considerable clinical and economic importance and requires easy and rapid detection to facilitate precautionary food safety measures. The conventional microbiological methods, however, usually include multiple subcultures and biotype or serotype-identification steps and, thus are laborious and timeconsuming. As a consequence, this chapter concentrates on both well-established aspects and recent advances in the characterization of C. jejuni and the alternative methods for its identification in food.

25.1.2  Biology C. jejuni was first described by Jones et al.24 in 1931, who named it Vibrio jejuni because of its similarity to so-called V. fetus (current Campylobacter fetus) found in aborting cattle.7 Within the species C. jejuni two subspecies, ssp. doylei and ssp. jejuni, can be distinguished on the basis of nitrate reduction, cephalothin susceptibility and catalase activity. With the pathogenic role of the ssp. doyley yet not defined,3 hereafter in this chapter C. jejuni will refer to C. jejuni ssp. jejuni. C. jejuni cells have a classic spiral morphology, 0.2–0.8 µm wide and 0.5–5.0 µm long. In old cultures or under stressed conditions they tend to spherical morphology (coccoid forms) with a diameter of approximately 1 µm. Cells are motile by means of unipolar or bipolar unsheathed flagella. The insertion of the flagellum in a cone-like depression allows its

Molecular Detection of Foodborne Pathogens

rotation in a characteristic corkscrew-like manner providing an extremely rapid, spinning motion to the cell.25 Due to this ability C. jejuni can move in very viscous media and can easily colonize and pass through the mucous layer in the intestinal tract of humans and animals.26 The genome of C. jejuni is a 1.6–1.7-Mbp adenine and thymine AT-rich DNA and contains a low G + C ratio, 30 mol% on average.27,28 This is a relatively small genome compared with other enteropathogens such as Escherichia coli (4.5 Mbp), and Salmonella enterica (4.9 Mbp). Some of the remarkable biochemical characteristics, i.e., their inability to ferment nor to oxidize carbohydrates and to degrade complex substances as well as their requirement for complex media for growth, stem from the small size of the genome.28 The small size of the genome has facilitated additional genome sequencing since the first NCTC 11168 C. jejuni genome sequence data were available in 2000.29 At present, a total of eight C. jejuni whole-genomes are available on the website of the National Center for Biotechnology Information (NCBI), http://www.ncbi.nlm.nih.gov. Of note are the hypervariable regions found in the C. jejuni genome which might be important both in survival30 and pathogenesis of the organisms.31,32 The genome sequence, however, contains no transposons, phage remnants, or insertion sequence elements and very few repeat sequences,29 making C. jejuni almost unique among sequenced bacterial pathogens.33 Typically microaerophilic and moderately capnophilic, the organisms require lower O2 and higher CO2 concentrations than the ambient atmosphere and may be cultured in atmospheres with 5–10% O2 supplemented with 2–10% CO2. However, C. jejuni also grows fairly well in humidified CO2 incubators ranging from 5 to 14% CO2 as claimed by Gaynor et al.34 The range of growth temperatures is narrow from 30 to 44ºC, with an optimal temperature of 37 and 42ºC. Even at optimal conditions the growth is quite slow and subsequently the times for primary isolation are long, 2–5 days.

25.1.3  Pathogenesis A reasonable understanding of the general clinical, microbiological, and epidemiological aspects of Campylobacter infection has been achieved. However, the molecular mechanisms involved in pathogenesis are still poorly understood. Few of the virulence determinants involved in Campylobacter pathogenesis are known or have a proven role. The virulence factors are generally not well characterized and some are rather controversial. In association with food or water, campylobacters enter the host intestine via the stomach acid barrier and colonize the distal ileum and colon. After colonization of the mucus and adhesion to intestinal cell surfaces, campylobacters perturb the absorptive capacity of the intestine by damaging epithelial cell function. 25.1.3.1  Virulence Factors Chemotaxis and motility. Effective colonization requires chemotaxis. Genome sequence analysis has shown that the C. jejuni genome encodes most features of the E. coli chemotaxis

Campylobacter

system.29,35 C. jejuni displays chemotactic motility towards mucin, L-serin, and L-fucose, amino acids that are found in the chicken gastrointestinal tract and mucus components.36 Mutants which lack either of the chemotaxis receptors DocB or Cj0262c show decreased chick colonization.37 Several other components of the chemotaxis system of C. jejuni have been identified, including CheY, CheV, CetA, and CetB.38 Motility of Campylobacter spp. necessitates the production of flagellum, the best characterized virulence determinant of campylobacters. Flagella and flagellar motility are vital to host colonization, virulence in ferret models, secretion, and host-cell invasion.38 The flagella of C. jejuni consists of an unsheathed polymer of flagellin subunits, which are encoded by the adjacent flaA and flaB genes. Both genes are subjected to antigenic and phase variation. Mutants of flaA, the primary structural gene for flagella, are unable to colonize chicks and cannot invade human intestinal epithelial cells in vitro.39 Adhesion and invasion are dependent on both motility and flagella expression, as C. jejuni mutants with reduced motility show reduced adherence and no invasion. This indicates that, while flagella are involved in adherence, other adhesins are involved in subsequent internalization.40 Adhesion and invasion. Adhesion by bacterial pathogens is often mediated by fimbrial structures. Genome annotations of several C. jejuni strains do not include obvious pilus or pilus-like ORFs. However, several proteins contribute to C. jejuni adherence to eukaryotic cells. CadF mediates adhesion by binding to the cell matrix protein fibronectin.41 CadF is required for maximal binding and invasion by C. jejuni in vitro, and cadF mutants are unable to bind fibronectin and did not colonize chicks.42 Another characterized adhesin, JlpA, is a surface exposed lipoprotein that has been shown to bind to Hsp90α on Hep-2 cells. This binding resulted in activation of NF-κB and p38 mitogen-activated protein kinase, both of which contribute to the inflammatory response.43,44 The lipoprotein CapA, a putative autotransporter, has been described as a possible adhesin that plays a role in adhesion and invasion of Caco-2 cells. Additionally, CapA-deficient mutants have decreased colonization and persistence in a chick model.45 Another reported adhesin is Peb1, a periplasmic ABC binding protein that is required for adherence to HeLa cells and for intestinal colonization of mice.46 C. jejuni is generally considered to be invasive,47 although the mechanism of uptake into epithelial cells remains vague. There are no specialized type III secretion systems similar to those of other enteric pathogens that mediate invasion into epithelial cells. Instead, the flagella appears to function as a type III secretion organelle that secretes a number of proteins, some of which are reported to affect invasion. The Cia proteins (for Campylobacter invasion antigens) are secreted through the flagella filament and affect invasion of some strains of C. jejuni.48,49 Although CiaB is internalized into epithelial cells, the mechanism by which CiaB mediates invasion has not been detailed.32 CiaB and other secreted Cia proteins (Cia A–H) require a functional flagellar export apparatus for their secretion.49 As well as the Cia proteins, this flagellar export apparatus secretes FlaC, which is also required for

347

invasion. Thus, the flagellar export apparatus is an ­important secretion mechanism in C. jejuni and is required for hostcell invasion.38 The ability to cross the epithelial cell barrier either through epithelial cell invasion or via tight junctions, allows the bacterium to move to the basolateral surface. At this point, it can reinvade the epithelial cell or be taken up into macrophages.32 It has been shown that C. jejuni can replicate intracellularly in macrophages and induce apoptosis.50 Interactions of C. jejuni with epithelial cells, dendritic cells and macrophages can release chemokines and cytokines that contribute to both inflammatory diarrhea and clearance of infection.32 The exact mechanisms by which C. jejuni induces disease remains unknown; symptoms could be a result of cytolethal distending toxin (CDT)-induced host cell death and subsequent inflammatory responses.51 CDT. The best characterized virulence factor present in the genome of C. jejuni is CDT. CDT consists of three subunits (CdtA, -B, and -C) encoded by a three-gene operon cdtABC,52 and isogenic C. jejuni cdt mutants lost all CDT activity.53 The role of CDT in C. jejuni pathogenesis remains unclear, but its mechanism of action is becoming understood.38 CDT is a tripartite toxin in which CdtB is the active subunit and CdtA and CdtC comprise the binding components. Once the toxin is bound to the cell, CdtB is transported to the nucleus where it acts as DNase and arrests the cell in the G2 phase of the cell cycle.54 CDT activity causes certain cell types (such as HeLa cells and Caco-2 cells) to become slowly distended, which progresses into cell death.40 Also, CDT induces IL-8 secretion from epithelial cells, which would contribute to inflammatory diarrhea.55 Although all C. jejuni strains tested contain cdt genes, there is a profound variation in CDT titers.56,57 Glycosylation system. Recently, the long-accepted dogma that bacteria only express nonglycosylated protein has been disproved.52,58 In 1989, Logan et al. provided clear evidence that Campylobacter flagellin was post-translationally modified.59 Today it is known that Campylobacter contains both a general N-linked protein glycosylation pathway (responsible for post-translational modification on at least 30 proteins) and an O-linked system (responsible for flagellar glycosylation).60 Both systems have been involved in C. jejuni virulence. Studies about the biological role for N-linked glycosylation clearly links it to bacterial virulence; a pglH mutant showed reduced ability to adhere/invade human epithelia and colonize chicks.61 It has been shown that O-linked glycosylation is essential for successful flagellin assembly and motility hence influencing adhesion, invasion, and virulence in vivo.62 Capsule and lipooligosaccharide (LOS). Genome sequences and DNA microarray data have demonstrated that C. jejuni genome contains about 22 variable regions on the chromosome. The most variable chromosomal regions are those involved in biosynthesis of surface carbohydrate structures, all of which play a role in virulence: the LOS core, a polysaccharide capsule (CPS), and the locus for O-linked glycosilation.32 The C. jejuni polysaccharide capsule is important for serum resistance, the adherence and invasion of

348

epithelial cells, chick colonization and virulence.63 Another study utilizing a capsule-deficient mutant suggested that contribution of bacterial CPS to host-pathogen interactions may be species-dependent.64 The C. jejuni LOS are highly variable due to differences in monosaccharide linkage and composition. Various LOS structures resemble human neuronal gangliosides. This molecular mimicry is thought to lead to autoimmune disorders, including GBS and MFS syndromes.38 The C. jejuni LOS and flagella have been shown to be sialylated, which is thought to be responsible for the ganglioside mimicry leading to GBS.40,65 Mutations in the various genes that are involved in LOS biosynthesis affect serum resistance, and adherence/ invasion of INT 407 cells.66 25.1.3.2  Animal Models Despite its global importance and the progress that has been made in recent years, there are still large gaps in our knowledge on basic aspects of the mechanisms of C. jejuni pathogenicity and host responses to infection.38 Many questions regarding its biology and pathogenic properties remain unanswered, in particular it is still unclear how C. jejuni causes diarrhea.32,38,67 One of the major obstacles to solve these problems is the lack of a suitable small animal model of infection that closely mimics human disease.68,69 We can find many references in the literature about the use of animal models for C. jejuni infection, but all of them have major disadvantages in terms of disease reproducibility or inadequate biological characterization. Nonhuman primates,70 mice,71,72 ferrets,73 piglets,74 hamsters,75 rabbits76, and chickens77 have been used as models for C. jejuni pathogenesis. Chicken models of commensal infection, mainly chick models, are of interest for the extensive and asymptomatic colonization of the gut. However, these models are limited by the poorly defined immune system of the chick and its unsuitability for genetic manipulation, thereby limiting the understanding of the enteric infection mechanism.67,69 They are used for investigations of the colonization factors with wild and mutant strains66 as well as for testing vaccine efficacy.78–80 Recently new and promising murine models have been developed. Using mice with limited enteric biota81 or immunodeficient mice82–84 some of these limitations can be overcome. Mice, in these models, develop colonization, severe inflammation in the lower intestine and pathological lesions similar to those reported in humans. In spite of many attempts, there is as yet no particular model as suitable for the study of Campylobacter infection in mammals. Other than animal models, polarized intestinal epithelial lines85 as well as human intestinal tissue86 are also used to investigate the pathogenic properties of C. jejuni and the immune response of host. They include INT 407,55 Caco-2,87 and T84 cells,88 and ex vivo organ culture.89

25.1.4  Isolation and Detection 25.1.4.1  Traditional Methods The microbiological analyses of a food are critical to determine the presence of any pathogen organism in order to

Molecular Detection of Foodborne Pathogens

ensure the safety of consumers. Food samples must be ­carefully examined in terms of the isolation of foodborne pathogens. Both false positive (isolated organisms which are not responsible of the specific illness) and false negative (unfounded organisms which are responsible for the specific illness) are important problems in microbiological food analysis. The complex matrix together with the high levels of commensal microbiota in the food may represent larger challenges than just their isolation in clinical samples. Pathogens in clinical samples are normally present as major or unusual microbiota. In contrast, the target microorganism in foods may be present in very low numbers or may be seriously injured by processing and conservation procedures such as freezing, cooling, heating, and salting.90 Even with improved culture methods it could be very difficult to detect these small numbers of foodborne pathogens amid large numbers of indigenous microbiota in a complex sample matrix like foods. The conventional methods based on culture techniques, although very valuable and constantly improving, are both time and material consuming as well as laborious and may be unsuitable in outbreak investigations and for positive release. Positive release involves testing the products to show that they are pathogen-free before they are put in the food chain.6 With some exceptions, the conventional microbiological methods for detection of bacteria in food samples usually include multiple subcultures and biotype or serotypeidentification steps. The presumptive detection requires an overnight pre-enrichment before the enrichment period of 24–48 h, followed by an additional 24–48 h incubation in selective agar plates. Afterwards, the colonies showing an expected morphology must be confirmed, species differentiated and sometimes subtyped by phenotypic characterization based mainly on biochemical and immunological tests. With species identification relying on just a few biochemical tests, in many cases inconclusive, it is not surprising that these conventional methods may sometimes lead to equivocal results and errors in taxonomy. All of that is applicable for the practical totality of the foodborne bacterial pathogens but it accounts especially for those considered fastidious owing the slow growth, susceptibility to environmental factors and restrictive culture conditions such as C. jejuni. The media that are used for isolating C. jejuni from foods are derived from those originally designed for isolating the pathogen from human stool samples.91–94 These media allow the recovery of C. jejuni from fecal samples by direct plating onto selective media. However, due to the predicted low numbers present in foods, selective enrichment broths are also required for the isolation of C. jejuni in foods. Thus, the time to confirm the presence of C. jejuni in food samples can exceed five working days. A standard procedure for the isolation of the organisms includes a pre-enrichment period in a selective broth for 4–6 h at 37ºC to promote the recuperation of the sub-lethally damaged cells; and then an enrichment period in the same medium for 42–44 h at 42ºC to promote specific growth. Afterwards, adequate dilutions of the culture must be spread onto selective agar plates and incubated for an additional 48-h period at 42ºC. Confirmation of the suspected

Campylobacter

colonies can be achieved by minimal standards which are colony morphology, Gram stain, motility, and oxidase test.95 Isolation of the colonies in separate plates requires additional incubations in selective agar plates for species differentiation and typing. All incubations must be under microaerophilic conditions using microaerobic-atmosphere-generating systems. Both solid and liquid selective media are normally achieved by using antibiotics. Typically, these are cefoperazone, cycloheximide, trimethoprim, rifampicin, vancomycin, polymyxin B, and amphotericin or nystatin, combined in different manners.96 Most current media use a combination of cefoperazone and amphotericin B, active against Grampositive bacteria and fungi respectively, together with vancomycin or trimethoprim, but depending on the food examined this cocktail can vary. In addition, selective media usually contain sheep or horse sterile lysed blood to neutralize the toxic effects of compounds formed in the presence of light and oxygen. The need to use lysed blood on media is another critical issue of the traditional methods to be applied in food analyses. It is expensive, easily contaminated and cannot be stored for long periods at the laboratory. Instead of, or in addition to, the lysed blood, charcoal, hematin, and a combination of ferrous sulphate, sodium metabisulfite and sodium pyruvate (FBP supplement) can be used as oxygenquenching ingredients. Attempts to improve oxygen protection include lysed blood and FBP supplement in the same selective media.96 There is little consensus on methods for isolating Campylobacter from foods and water and a number of different isolation methods are used worldwide. However, as with other foodborne bacterial pathogens, it is likely that no single method is ideal for the entire range of foods requiring testing. The 8th edition of the FDA Bacteriological Analytical Manual97 and the online revisions at http://www.foodinfonet. com/publication/fdaBAM.htm give a detailed description of the isolation of Campylobacter from food and water. Data suggest that Bolton broth as enrichment and the modified blood-free mCCDA medium as selective agar give the highest isolation rates for C. jejuni.98 Identification of Campylobacter species is based on biochemical tests such as nitrate/nitrite reduction, hippurate hydrolysis, catalase, and oxidase tests. However, the genus include closely related bacteria that share many biochemical characteristics which makes species differentiation difficult. By way of an example, the hippurate hydrolysis is thought only positive in C. jejuni.99 However, some C. jejuni isolates are hippuricase-negative, making it impossible to differentiate C. coli from hippuricase-negative C. jejuni using purely biochemical tests.39,100 In addition to the inherent difficulties in the detection of C. jejuni such as they may be lost among a background of indigenous microbiota, there is the fact that it can enter a viable but nonculturable state (VBNC) under adverse conditions. The former can be minimized by using pre-enrichment periods but VBNC cells are living cells unable to grow or divide in these media.101 Since ability to enter the VBNC

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state in C. jejuni cells was first described by Rollins and Colwell,102 a number of studies have been developed in order to explain the nature of such cells and the potential public health hazards they present. It has been found that, as culturable cells, they retain spiral morphology103 and metabolic activity.104,105 It has been also suggested that this dormant-like state is an adaptation to survival in adverse environments not supporting growth of Campylobacter, as during transmission or storage.102,106 However, the significance in transmission of disease is today uncertain, as the resuscitation back to the actively growing state of VBNC-forms of Campylobacter cells is still controversial. While several authors have reported C. jejuni resuscitation from the VBNC state after passage in embryonated eggs107 or experimental animals,108–110 there are others who referred their inability to resuscitate.111–113 The resuscitation of the VBNC cells is a key issue for considering the presence of these forms as true health hazards when found in food or water. Owing to the difficulties in finding an adequate animal model for studying the C. jejuni pathogenesis, the differences on resuscitation issues can be explained on the basis of this factor as well as derived for the different strains used in the studies. Although not conclusive, these results show that the presence of C. jejuni VBNC cells in food is of special concern, at least for certain strains, because traditional culture methods cannot elucidate. 25.1.4.2  Rapid Methods From a public health perspective, faster detection times are essential to prevent the spread of infectious diseases or the identification of a continuing source of infection. With the implementation of the HACCP system for control of the process line at CCPs (Critical Control Points), the demand for rapid, sensitive, and accurate methods to detect biological contaminants has also increased. In the past two decades, therefore, large efforts have been made to develop methods for ‘rapid diagnoses’ of foodborne pathogens. Rapid diagnoses include a wide range of novel testing procedures which can significantly reduce the reporting time compared with conventional bacterial culture.114 Following advances in molecular biology techniques and technologies, rapid methods such as antibody-based tests,115,116 simple miniaturized biochemical assays, physicochemical tests (e.g., Fourier transform infrared spectroscopy),117,118 and highly specific nucleic acid-based methods,119–124 have been developed for the specific detection, identification, and typing of microorganisms. The advent of whole-genome based methods, such as DNA microarrays, has generated new opportunities to detect pathogens in foods.125 In particular, methods targeting nucleic acids, both DNA and RNA, are intrinsically more precise and less affected by natural variation than the phenotypic methods. An extensive overview of genetic methods affecting detection and identification of C. jejuni in foods is presented below; the assay principles and some of the detailed procedures are also discussed. 25.1.4.3  Molecular Methods (i) DNA-based methods: DNA-based methods use PCR as the most versatile and widely used amplification technique.

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PCR is an in vitro enzymatic amplification of DNA or RNA, that requires a DNA template, short DNA fragments or primers (usually 20–30 nucleotides long), a thermo stable DNA polymerase like Taq polymerase and a thermocycler. The amplification is directed at short regions of the genome where the primers bind to their complementary bases. It is a cyclical process temporary divided in three thermal steps: (i) denaturization of the DNA template, accomplished by heating to 90–96ºC to open the double-strand of the template into single-strand; (ii) annealing of the primers to their complementary bases on the single-strand template; (iii) and DNA synthesis by the thermostable DNA polymerase to extend the DNA product. The whole process is repeated 25–30 times (cycles) so that within a short period (usually 1 h) there is enough DNA target to detect. A single copy of DNA template can turn into billions of copies in less than 2 h. The products of PCR are normally separated by electrophoresis in agarose gel and detected by a DNA stain. Alternatively, it can be detected by hybridization with labeled probes126 or nucleotide sequencing analysis.127 The hazards of cross-contamination with the PCR products have promoted the development and wide use of the realtime PCR.128 This technique combines PCR methodology with hybridization allowing the amplification and the detection of the products in a single reaction vessel. Detection is based either on fluorescent labeled probes or fluorescent dyes as SYBR green both binding to the PCR products as fast as they are synthesized by the DNA polymerase. The detection is achieved by a fluorimether combined with the thermocycler and recorded during the exponential phase of the amplification without post-PCR handling. This allows for direct detection and quantification as the number of cycles required to reach the threshold value can be directly correlated with the initial numbers of cells in the sample. In comparison, real-time PCR is faster than conventional PCR and may be carried out in automated devices that require less expertise.114 Both techniques can be used as multiplex PCR by including various primer sets within a single reaction. Multiplex PCR may be useful for identification of the pathogens by combining genus- and species-specific genes as targets129–131 as well as in epidemiological studies where a wide range of items may be analyzed.132 However, the selection of the primers should be done carefully. All of them must have similar annealing temperatures, absence of complementarity and enough difference in size for ensuring electrophoresis separation and accurate detection. Regarding C. jejuni, there is a large variety of PCR assays proposed to detect and to identify this species. Most of them are assayed with pure cultures or are developed for human stool samples. In contrast, the range of the applications of these methods for direct detection of C. jejuni in foods is narrow. A summarized description of some of those applied to C. jejuni detection in foods is given in Table 25.1. The consensus major advantages of the PCR-based detection is the speed, together with high specificity and sensibility. One of the main disadvantages, is the presence of false negative assay due to the presence of inhibitory substances

Molecular Detection of Foodborne Pathogens

in the food products which can affect primer binding or Taq ­activity. Part of this undesirable effect reflects the need for a short enrichment period, as much of the methods include, but also reducing the extreme sensitivity of the PCR reaction determined by pure culture when testing foods. Isolation of the DNA to be used in the amplification by in-house methods or commercial kits also minimizes this limitation. The selection of the genetic target to be amplified is one of the more critical aspects when designing a PCR method. As PCR selectively amplifies targets, depending on the specificity, different regions of the genome may be amplified. This is shown in the variety of gene targets used in the PCR-based methods for the detection of C. jejuni. The rRNA presents highly conserved regions in the species of the genus, which is used for Campylobacter spp. detection. In addition, the high numbers of copies per cell provide a naturally amplified target thus increasing the analytic accuracy. The 16S rRNA genes are the most suitable for this purpose and so they are widely used for Campylobacter spp. detection. However, not all the PCRs targeting the 16S rRNA are directed to the same position into the gene sequence. Other genetic targets are selected amid genes exclusively found in a particular species. Such genes are used for differentiating C. jejuni from the other species in the genus. An example of this is the hippurate gene, hipO, coding for the hippurate hydrolase which is found exclusively in C. jejuni species. Since hippurate negative strains were detected, this gene is no longer used in the identification of C. jejuni. Instead, interest has turned to the species-specific fragments of common genes suitable for discriminating between very closed related C. jejuni and C. coli. As an example, the ceuE gene coding a virulence determinant is present in both species but by choosing adequate primers, a specific fragment for each one may be obtained.163 The primers described by Gonzalez et al., for C. coli identification, are used later by a number of authors within different PCR methods.131,156,164 As a result, the test methods and primers used are heterogeneous, and validation and optimization of in-house assays requires further study.114 A major disadvantage concerning the DNA-based methods is the question whether or not they are detecting DNA from dead cells. Due to the long persistence of DNA in cells post-death, the correlation between presence of DNA and viability is not cleared.165 However, this is irrelavant for those methods using a pre-enrichment period. (ii) RNA-based methods: The most commonly used techniques for RNA amplification are reverse PCR (RT-PCR) and nucleic acid sequence-based amplification (NASBA). Both of these have been used to determinate the viability of the molecular targets165 but only NASBA has been also used for Campylobacter detection in food (see Table 25.1). The NASBA technique is a cycling transcriptional process in which single-stranded RNA sequences are targeted and amplified.166 The amplification involves the simultaneous use of three enzymes which mimic the retroviral replication, in a one-step process. Enzymes are, an avian myeloblastosis virus reverse transcriptase (AMV-RT), RNase H, and

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Campylobacter

Table 25.1 Identification of Campylobacter Species by Molecular Methods Target

Matrix

C. jejuni (cadF)

Chicken rinses

C. jejuni (ORF-C sequence)

Raw chicken, offal, shellfish, raw meat, milk Chicken rinses

Thermotolerant campylobacters (16S rRNA) C. jejuni (cadF)

Isolation Procedure Real-Time PCR SE (Mueller-Hinton Broth containing cefoperazone and growth supplements) SE (Bolton broth)

PCR Product Detection

Reference

Melting peak análisis

133

Taqman probe

134

SE (Bolton broth)

Taqman probe

135

Chicken skin

SE (Bolton broth)

Melting peak análisis

136

C. jejuni, C. coli, C. lari (16Sr RNA); C. jejuni (hipO)

Chicken samples

SE (Preston broth)

137

C. jejuni (cadF)

Chicken skin, pork, milk

SE (Bolton broth)

Lightcycler probe (16S rRNA) and melting peak analysis (hipO) Melting peak análisis

Campylobacter spp (16S rRNA)

Chicken rinses

Buoyant density separation

Lightcycler probe

139

Campylobacter spp (16S rRNA)

Chicken skin

SE (Bolton broth)

Taqman probe

140

C. jejuni (VS1 sequence)

Chicken rinses

Direct detection

Taqman probe

141

C. jejuni (gyrA)

Chicken samples

Buoyant density separation

Melting peak análisis

142

Thermotolerant campylobacters (16S rRNA) C. jejuni (hipO), C. coli (ceuE) C. jejuni (Cj 0414)

Chicken rinses

Buoyant density separation

Lightcycler probe

143

Chicken carcasses Chicken carcasses

Direct detection Direct detection

Taqman probe Taqman probe

144 145

C. jejuni and C. coli (cadF)

Chicken carcasses

Qualitative PCR Direct detection

Gel electrophoresis

146

C. jejuni and C. coli (intergenic flaA-flaB sequence) C. jejuni (putative lipoprotein)

Minced beef, chicken, pork Chicken rinses

Rosef broth

Gel electrophoresis

147

Buoyant density separation

Gel electrophoresis

148

C. jejuni, C. coli, C. lari (16S rRNA) Campylobacter spp (16S rRNA)

Chicken skin, whole milk

Immunomagnetic separation

Biotin-avidin capture assay

149

Brocccoli, crabmeat,mushroom, raw milk, and raw oyster rinses Chicken samples

SE (blood-free enrichment broth)

Gel electrophoresis

150

SE (Preston broth)

Gel electrophoresis

151

Chicken samples

SE (Preston broth)

Gel electrophoresis

152

Raw meat and offal (poultry, porcine, ovine, and bovine), raw shellfish, milk Carcass rinse

SE (Campylobacter Enrichment Broth)

PCR ELISA DIG detection kit and two biotinylated capture probes

153

Campylobacter spp (16S rRNA), C. jejuni (mapA), C. coli (ceuE) Campylobacter spp (16S rRNA) C. jejuni and C. coli (ccoN)

C. jejuni and C. coli (ceuE)

Thermotolerant campylobacters Chicken carcass (16S rRNA) Thermophilic campylobacters Chicken legs, ground (23S rRNA), and C. jejuni (ceuE) beef, fermented sausage, roast beef, pork chops, turkey breast, chicken wieners, beef wieners Campylobacter spp (16S rRNA); Poultry samples C. jejuni (mapA), C. coli (ceuE) C. jejuni, C. coli (lpxA) Chicken rinses

138

Direct detection

PCR ELISA DIG detection kit

154

SE (Bolton broth)

Gel electrophoresis

155

SE (Bolton broth)

Gel electrophoresis

156

Direct detection and SE (Preston broth)

Gel electrophoresis

131

SE (Oxoid anaerobe basal broth)

Gel electrophoresis

157 (Continued)

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Molecular Detection of Foodborne Pathogens

Table 25.1  (Continued) Target

Matrix

Isolation Procedure

PCR Product Detection

Reference

C. jejuni, C. coli

Chicken rinses

DNA Array SE (Oxoid anaerobe basal broth)

Oligonucleotide probes (70mer)

157

Campylobacter spp (16S rRNA)

Chicken product

DNA FISH SE (Preston broth)

Oligonucleotide probe

152

Campylobacter spp (16S rRNA), thermophilic campylobacters (23S rRNA)

Chicken

SE (Preston broth)

Oligonucleotide probe

158

C. jejuni, C. coli, C. lari (16S rRNA)

Poultry products, dairy products, red meats, vegetables Chicken skin

NASBA SE (Preston broth)

ELGA

159

Direct detection and SE (Preston broth)

ELGA

160

Buoyant density separation

ELGA

161

Direct detection

Molecular beacon

162

C. jejuni, C. coli, C. lari (16S rRNA) C. jejuni (16S rRNA)

C. jejuni, C. coli (16S rRNA)

Poultry products, meat products, dairy products, water Poultry breast

Note:  SE, selective enrichment; ELGA, enzyme-linked gel assay.

T7 RNA polymerase. In contrast to PCR, the enzymes in NASBA work under isothermal conditions (41ºC) so a thermocycler is not necessary. The molecular target is singlestranded RNA and both ribosomal and messenger RNA may be amplified by NASBA. The amplification product is also single-stranded RNA but antisense to the original target. NASBA offers several advantages over PCR and RT-PCR. The number of copies generated by NASBA is higher than that of PCR and in a shorter time than RT-PCR. Cycles in NASBA exponentially increase the number of RNA copies so the sensibility is highest. Of special interest is that the background DNA does not interfere with the NASBA reaction. The likelihood of amplification of the contaminating DNA is prevented by the low temperature as NASBA reactions cannot exceed 41ºC without risk of enzyme denaturalization.167 Some disadvantages nevertheless are intrinsic to the NASBA reaction. It is not possible to control the extent of the reaction by adjusting the number of cycles because NASBA is isothermal. As a consequence the likelihood of nonspecific reactions increases and the product reaction can contain RNA fragments other than the specific copies of the target RNA. This creates the need of post-NASBA handling steps which increases both the time to identify the specific RNA product and the likelihood of molecular contamination. The product of NASBA reaction may be detected by gel electrophoresis followed by ethidium bromide staining, but a confirmatory step is needed to ensure product specificity. Enzyme-linked gel assay (ELGA) has been reported as a suitable method to identify the NASBA products by using a specific oligonucleotide probe (ELGA probe) 5′-end labeled with horseradish peroxidise.159,160 With the development of the real-time NASBA reactions this limitation was overcome.162,168 Real-time NASBA is based on beacon probes

which are small, single-stranded nucleic acids, ­hairpin probes that brightly fluoresce when they are bound to their targets.169 When NASBA is performed in combination with molecular probes, the target RNA products are detected in a sealed reaction tube, which simplifies analysis and eliminates an important source of assay contamination. Real-time NASBA has been used to detect C. jejuni in food samples with a high specificity and sensibility.162,168 In addition it was suitable to establish the viability of the molecular targets as 16S rRNA genes.162 (iii) Whole-genome-based methods: The whole-genomebased methods have been developed from the microarray technology that offers the possibility of depositing a high density of different specific probes on a very small area. They are also known as biochip, DNA chip, DNA microarray, and gene array. The DNA microarray consists of a series of samples spotted on a solid support, most commonly glass or silicon. Each spot contains DNA fragments or oligonucleotides as probes.170,171 Probes appear as spots in the final image where each spot represents a unique probe sequence and spots are usually 100–200 µm in size and located within 200–500 µm of each other. The targets are labelled with fluorescent dyes before to be applied to the microarray and the probe-target hybridization can be detected and quantified by fluorescence-based detection.172 Depending on the objective, targets may be PCR products, genomic DNA, total RNA, mRNA, cDNA, plasmid DNA, or oligonucleotides.173 The uses of the DNA arrays are likely unlimited as it can combine the amplification of nucleic acids with its massive screening capability. Simultaneous detection or level of expression of thousands of specific DNA can be achieved in a single DNA microarray, resulting in sensitivity, specificity, and highthroughput capacity.

353

Campylobacter

Two main types of arrays are produced: genomic arrays and oligonucleotide arrays. The genomic microarrays comprise either whole genome, genomic fragments from a cDNA library, or open reading frames from a bacterial strain. These arrays are useful for comparative phylogenetic studies and genetic diversity by determining constant and variable genes among the isolates. The oligonucleotide arrays, containing probes from 18 to 70 nucleotides long, 174 are useful for genomic analysis because these arrays can consist of multiple sequence variants of a target gene and can be adapted for pathogen detection in different environments. Although efforts to apply microarrays in food safety are important for detecting foodborne pathogens such as E. coli, Listeria, and others,175–177 Campylobacter detection in foods has not been well documented.178 To the best of our knowledge only one approach has been published157 that was suitable for specific identification of Arcobacter bultzleri, C. coli

Sample Preparation and DNA Extraction Preston Campylobacter Selective Enrichment Broth (Oxoid), containing Nutrient Broth No. 2, Preston Campylobacter Selective Supplement SR0117, Campylobacter Growth Supplement SR0232 and 5% (v/v) Lysed Horse Blood SR0048 Sterile plastic bags Orbital shaker 1.5 ml microcentrifuge tubes Micropipets and filter tips NucleoSpin Tissue kit (Macheray Nagel, Germany) 100% Ethanol ND-1000 Spectrophotometer (NanoDrop)

package liquid from whole chicken carcasses was labeled and hybridized to the microarray with and without enrichment. C. jejuni was detected efficiently both in package liquid from whole chicken carcasses and in enrichment broths.

25.2  Methods First, we describe a method for extracting DNA from Campylobacter spp. for PCR analysis. This method is suitable for extracting DNA directly from food samples. Extracting DNA with a commercial kit reduces the probability of contamination of the DNA with PCR inhibitors. Second, two PCR-based methods for detection of C. jejuni and C. coli are described: (i) multiplex PCR, and (ii) real-time duplex PCR.

25.2.1  Reagents and Equipment

PCR Amplification 5 U/µl Taq DNA polymerase (Invitrogen). The enzyme is supplied with 50 mM MgCl2 and 10 × reaction buffer (200 mM Tris pH 8.4, 500 mM KCl

100 mM stocks of each deoxyribonucleotide triphosphate (dNTPs; Bioline). dNTPS working stock solutions containing 10 mM of each dNTP The oligonucleotide primers and probes are listed in Table 25.2 Sterile ultrapure water 0.2 ml PCR tubes Thermal cycler Robocycler gradient 96 (Stratagene) Molecular grade agarose 10 × TBE buffer: 0.9 M Tris-HCl pH 8.3, 0.9 M boric acid, 0.02 M EDTA Agarose gel sample loading buffer: 40% sucrose, 0.25% bromophenol blue Agarose gel staining solution: 0.5 µg/ml (w/v) ethidium bromide in distilled water HyperLadder IV DNA molecular weight marker (Bioline) Standard apparatus for horizontal electrophoresis of agarose gels and power supply Gel documentation system ChemiDoc (BIO-RAD) Real-time thermocycler ABI PRISM 7000 Sequence Detection System (Applied Biosystems) MicroAmp optical tubes and optical caps (Applied Biosystems) 2 × Taqman Universal Master Mix kit (Applied Biosystems), containing AmpliTaq Gold DNA polymerase, dNTPs, Passive reference 1 (ROX), and optimized buffer components

and C. jejuni present in retail chicken samples using a DNA microarray without prior PCR as well as C. jejuni genotyping based on LOS class. The approach contains a comprehensive set of 70-mer oligonucleotide probes targeting genes implicated in metabolism or pathogenicity of those pathogens. Total genomic DNA isolated from the microbiota in the

25.2.2  Sample Preparation and DNA Extraction DNA is extracted using a commercial kit and follows the manufacturer’s instructions. The NucleoSpin Tissue kit (Macheray Nagel, Germany) is proposed as a method that provides a high grade of purity, and is suitable for

354

Molecular Detection of Foodborne Pathogens

PCR-based methods in Campylobacter detection from food samples. (1) Rinse 25 g of food sample in 100 ml of Preston broth and mix in an orbital shaker for 10 min at 200 rpm. (2) Centrifuge 1 ml culture for 10 min at 6,000 × g and discard the supernatant. (3) Resuspend the pellet in 180 μl Buffer T1. Add 25 μl proteinase K solution. Vortex vigorously and incubate at 56ºC in a shaking incubator until complete lysis is obtained (at least 30 min). (4) Add 200 μl Buffer B3, vortex vigorously and incubate at 70ºC for 10 min. (5) Add 210 μl 100% ethanol to the sample and vortex vigorously. (6) Place one NucleoSpin® Tissue Column into a collection tube. Apply the sample to the column. Centrifuge for 1 min at 11,000 × g. Discard the flow-through and place the column back into the Collection tube. (7) Add 500 μl Buffer BW. Centrifuge for 1 min at 11,000 × g. Discard flow-through and place the column back into the collection tube. (8) Add 600 μl Buffer B5 to the column and centrifuge for 1 min at 11,000 × g. Discard flow-through and place the column back into the collection tube. (9) Centrifuge the column for 1 min at 11,000 × g. (10) Place the NucleoSpin® Tissue Column into a 1.5-ml microcentrifuge tube and add 150 μl prewarmed Elution Buffer BE (70°C). Incubate at 70ºC for 1 min. Centrifuge 1 min at 11,000 × g.

(11) Determine DNA concentration in each sample using absorbance spectrophotometry. (12) Take an aliquot of the DNA suspension and dilute to give a stock template DNA concentration of 20 ng/µl. DNA suspensions may be stored at 4ºC or –20ºC.

25.2.3  Detection Procedures 25.2.3.1  Multiplex PCR The PCR conditions are those proposed by Denis et al.164 with minor modifications concerning the dNTPs concentration and 16S rRNA gene primer concentration.131 Multiplex PCR amplification for specific detection of the 16S rRNA (Campylobacter spp), mapA (C. jejuni), and ceuE (C. coli) genes is performed with the three primer sets described in Table 25.2. (1) Prepare PCR mixture (30-µl) containing 1 × PCR buffer, 1.5 mM MgCl2, 0.2 mM dNTPs, 0.6 U Taq polymerase, 0.5 µM of MD16S1 and MD16S2 primers, and 0.42 µM of MDmapA1, MDmapA2, COL3, and MDCOL2 primers (Table 25.3), and 100 ng of template DNA. (2) Run the PCR in a conventional thermal cycler using the following parameters: one cycle of 95ºC for 10 min; 35 cycles of 95ºC for 30 sec, 59ºC for 1 min 30 sec, 72ºC for 1 min; and one cycle of 72ºC for 10 min. (3) Mix 10 µl of the PCR product with 2 µl of gel loading buffer and put them into wells of 2% TBEagarose gel. In a parallel well, dispense 5 µl of the HyperLadder IV DNA molecular weight marker.

Table 25.2 Oligonucleotide Primers and Probes used for PCR Amplification and Detection Target

16S rRNA mapA ceuE

mapA

Name

MD16S1 MD16S2 MDmapA1 MDmapA2 COL3 MDCOL2

mapA-F mapA-R mapA-probe

ceuE

ceuE-F ceuE-R ceuE-probe

Sequence (5′→3′) Multiplex PCR ATCTAATGGCTTAACCATTAAAC GGACGGTAACTAGTTTAGTATT CTATTTTATTTTTGAGTGCTTGTG GCTTTATTTGCCATTTGTTTTATT AATTGAAAATTGCTCCAACTATG TGATTTTATTATTTGTAGCAGCG Duplex Real-Time PCR CTGGTGGTTTTGAAGCAAAGA CAATACCAGTGTCTAAAGTGCGTTTAT fam-TTGAATTCCAACATCGCTAATGTATAAAAGC CCTTT-tamra AAGCTCTTATTGTTCTAACCAATTCTAACA TCATCCACAGCATTGATTCCTAA vic-TTGGACCTCAATCTCGCTTTGGAATCATT-tamra

Note:  5′ fluorescent reporter dyes and 3′ quenchers underlined.

Size

Reference

857 bp

129

589 bp

179

462 bp

163

95 bp

180

102 bp

180

Campylobacter

(4) Subject to electrophoresis at 90 V for approx 1.5–2h in 1 × TBE buffer. (5) Remove gel and submerge in an ethidium bromide DNA staining solution (0.5 µg/ml) for 30 min. (6) Wash the gel with distilled water and visualize the DNA amplicons by exposure to a UV-transilluminator. (7) Expected product sizes are as follows: an 857-bp Campylobacter specific fragment of the 16S rRNA gene, and two species-specific fragments of 589 and 462-bp corresponding to C. jejuni and C. coli, respectively. 25.2.3.2  Duplex Real-Time PCR Duplex real-time PCR amplification for specific detection of the mapA (C. jejuni) and ceuE (C. coli) genes is performed with the two primer sets and Taqman probes described in Table 25.2. The protocol published by Best et al.180 involves a ceuE probe quantity higher (0.1 µM) than that employed by us (0.05 µM). Reducing the probe quantity to 0.05 µM significantly increases the specificity of the PCR. (1) Prepare PCR mixture (20-µl) containing 1 × Taqman Universal Master Mix, 0.3 µM of each primer, and 0.1 µM of mapA probe, 0.05 µM of ceuE probe (Table 25.2) and 100 ng of template DNA. (2) Add the PCR premix and DNA template to the MicroAmp optical tubes, and cap the tubes. (3) Perform PCR amplification in the thermocycler ABI PRISM 7000 with an initial denaturation/ enzyme activation at 95ºC for 10 min, followed by 40 cycles of two-step PCR consisting of 15-sec denaturation at 95ºC and 60-sec annealing/extension at 60ºC. (4) As with traditional PCR methods, include positive and negative controls for each pair of primers used. (5) After the run, detect PCR products directly by the Taqman machine monitoring the increase in fluorescence where a numerical value, the CT value (threshold cycle), is assigned. This indicates the cycle number at which measured fluorescence increased above calculated background fluorescence, identifying amplification of the target sequence.

25.3 Conclusion and Future Perspectives C. jejuni is now recognized as an important foodborne pathogen which is responsible of most bacterial gastroenteritis worldwide; its incidence is higher than those of infections caused by Salmonella species, Shigella species, or E. coli O157:H7. Despite its global importance insights into C. jejuni are limited compared to Salmonella and E. coli. As a consequence much effort has been directed toward an improved understanding of C. jejuni, its epidemiology and pathogenic mechanisms; however, many questions are yet to be answered.

355

C. jejuni is typically microaerophilic and moderately capnophilic which largely reduces the risk of growth in food products. However, human infections are usually acquired through the consumption of undercooked contaminated meat, water or other cross-contaminated food products, the foods of poultry origin being the most common sources of infections. How these organisms in both the environment and the food chain survive is an unanswered question. As they can enter a VBNC state under adverse conditions it has been suggested that this VBNC state can be a survival strategy in environments not supporting growth of Campylobacter. However, the significance of the VBNC-forms in transmission of disease is today uncertain, as the resuscitation back to the actively growing state is still controversial. Human infection, particularly in children, can be severe and normally associated with bloody diarrhea. Postinfectious complications are rare but debilitating long-term sequelae are associated with C. jejuni infections. Unlike most other foodborne pathogens C. jejuni is far less associated with general outbreaks. A variety of virulence factors have been identified, among them LOS structures resembling human neuronal gangliosides and CDT. But there is general agreement that C.  jejuni is unique in not having an identifiable enterotoxin as a mechanisms to cause diarrhea. The mechanism that causes diarrhea remain unclear. This limited understanding on C. jejuni pathogenesis is partly because of the lack of a suitable small animal model of infection that closely mimics human disease. Despite the progress that has been made in recent years, further research is required to provide the clues of how this pathogen survives in the environment and food as well as how it interacts with human cells. As exogenous microbiota C. jejuni can occur in small numbers in food and even with improved culture methods it could be very difficult to detect amid large numbers of indigenous microbiota in a complex sample matrix like food. Therefore, C. jejuni detection in foods by traditional culture methods, pre-enrichment and enrichment periods in selective media are absolutely neccessary. Further selective agar plating is also needed for colony isolation as well as species identification. In addition, there exist some VBNC-forms that are unable to grow on culture media. All of these contribute to the laborious and time-consuming features of the traditional culture ­methods as well as their inability to elucidate the VBNC-forms. Alternative rapid diagnoses including a wide range of novel testing procedures can significantly reduce the reporting time compared with conventional bacterial culture. In particular, methods targeting the nucleic acids, both DNA and RNA, are intrinsically more precise and less affected by natural variation than the phenotypic methods. In the past two decades, large numbers of both PCR-based methods (DNA amplification) and NASBA methods (RNA amplification) have been developed for C. jejuni detection; but the range of the applications of these methods for direct detection of C. jejuni in foods is narrow. The advent of whole-genome based methods, such as DNA microarrays, has generated new opportunities to detect pathogens in food.

356

Molecular Detection of Foodborne Pathogens

Although rapid, sensitive, and accurate the molecular methods also suffer from some disadvantages mainly when they are applied to the detection of pathogens in food. The complex matrix of the foods may interfere with both isolation and amplification of the target nucleic acid. The presence of inhibitory substances in the food products can affect primer binding or enzyme activity then resulting in false negative assays. Isolation of the DNA and RNA by in-house methods or commercial kits minimizes this limitation. The selection of the target to be amplified is another critical aspect when designing a molecular method. The target must be chosen on the basis of well established biological and genetic characteristics of the bacterium; data bases in the public domain from whole-genome sequencing are useful in that regard. However, a major disadvantage concerning molecular based methods is the question whether or not they are detecting nucleic acid from dead cells. As a result, validation, and optimization of in-house assays need further attention in the future. The uses of the DNA arrays are likely unlimited as it can combine the amplification of nucleic acids with its massive screening capability. Extending future research to this area should allow the identification of improved epidemiological markers which in turn should allow a rapid increase in the knowledge of the ecology, epidemiology, and pathogenesis of C. jejuni as well as future tools to reduce—if not eliminate—this important pathogen from the food chain.



Acknowledgments



Work in the authors’ laboratory is supported by grants from Spanish Government (AGL2005-08162-C02-01) and Basque Government (GIC07/52-IT-308-07).











References





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Campylobacter 112. Hald, B.K. et al. Study of the infectivity of saline-stored Campylobacter jejuni for day-old chicks. Appl. Environ. Microbiol., 67, 2388, 2001. 113. Ziprin, R.L. and Harvey, R.B. Inability of cecal microflora to promote reversion of viable non-culturable Campylobacter jejuni. Avian Dis. 48, 647, 2004. 114. Abubakar, I. et al. A systematic review of the clinical, public health and cost-effectiveness of rapid diagnostic tests for the detection and identification of bacterial intestinal pathogens in faeces and food. Health Technol. Assess., 11 (36), 2007. 115. Tolcin, R. et al. Evaluation of the Alexon-trend ProSpecT Campylobacter microplate assay. J. Clin. Microbiol., 38, 3853, 2000. 116. Dediste. A. et al. Evaluation of the ProSpecT microplate assay for detection of Campylobacter: a routine laboratory perspective. Clin. Microbiol. Infect., 9, 1085, 2003. 117. Mouwen, D.J.M. et al. Discrimination of enterobacterial repetitive intergenic consensus PCR types of Campylobacter coli and Campylobacter jejuni by Fourier Transform Infrared Spectroscopy. Appl. Environ. Microbiol., 71, 4318, 2005. 118. Mouwen, D.J.M. et al. Artificial neural network based identification of Campylobacter species by Fourier transform infrared spectroscopy. J. Microbiol. Methods, 67, 131, 2006. 119. Cook, N, The use of NASBA for the detection of microbial pathogens in food and environmental samples. J. Microbiol. Methods, 53, 165, 2003. 120. Lubeck, P.S. et al. Toward an international standard for PCRbased detection of food-borne thermotolerant Campylobacters: assay development and analytical validation. Appl. Environ. Microbiol., 69, 5664, 2003. 121. Alonso, R. et al. PCR-restriction fragment length polymorphism assay for detection of gyra mutations associated with fluoroquinolone resistance in Campylobacter coli. Antimicrob. Agents Chemother., 48, 4886, 2004. 122. Amar, C.F. et al. Blinded application of microscopy, bacteriological culture, immunoassays and PCR to detect gastrointestinal pathogens from faecal samples of patients with community-acquired diarrhoea. Eur. J. Clin. Microbiol. Infect. Dis., 23, 529, 2004. 123. Alonso, R. et al. MAMA-PCR assay for the detection of point mutations associated with high-level erythromycin resistance in Campylobacter jejuni and Campylobacter coli strains. J. Microbiol. Methods, 63, 99, 2005. 124. Jensen, A.N. et al. Development of real-time PCR and hybridization methods for detection and identification of thermophilic Campylobacter spp. in pig faecal samples. J. Appl. Microbiol., 99, 292, 2005. 125. Kostic, T. et al. A microbial diagnostic microarray technique for the sensitive detection and identification of pathogenic bacteria in a background of nonpathogens. Anal. Biochem., 360, 244, 2007. 126. O’Sullivan, N.A. et al. Detection and differentiation of Campylobacter jejuni and Campylobacter coli in broiler chicken samples using a PCR/DNA probe membrane based colorimetric detection assay. Mol. Cell. Probes, 14, 7, 2000. 127. Nayak, R., Stewart, T.M., and Nawaz, M.S. PCR identification of Campylobacter coli and Campylobacter jejuni by partial sequencing of virulence genes. Mol. Cell. Probes, 19, 187, 2005. 128. Heid, C.A. et al. Real time quantitative PCR. Genome Res., 6, 986, 1996.

359 129. Linton, D. et al. PCR detection, identification to ­species level, and fingerprinting of Campylobacter jejuni and Campylobacter coli direct from diarrheic samples. J. Clin. Microbiol., 35, 2568, 1997. 130. On, S.L., and Jordan, P.J. Evaluation of 11 PCR assays for species-level identification of Campylobacter jejuni and Campylobacter coli. J. Clin. Microbiol., 41, 330, 2003. 131. Mateo, E. et al. Evaluation of a PCR assay for the detection and identification of Campylobacter jejuni and Campylobacter coli in retail poultry products. Res. Microbiol., 156, 568, 2005. 132. Martinez, I. et al. Detection of cdtA, cdtB, and cdtC genes in Campylobacter jejuni by multiplex PCR. Int. J. Med. Microbiol., 296, 45, 2006. 133. Cheng, Z. and Griffiths, M.W. Rapid detection of Campylobacter jejuni in chicken rinse water by melting-peak analysis of amplicons in real-time polymerase chain reaction. J. Food Prot., 66, 1343, 2003. 134. Sails, A.D. et al. A real-time PCR assay for the detection of Campylobacter jejuni in foods after enrichment culture. Appl. Environ. Microbiol., 69, 1383, 2003. 135. Josefsen, M.H., Jacobsen, N.R. and Hoorfar, J. Enrichment followed by quantitative PCR both for rapid detection and as a tool for quantitative risk assessment of food-borne thermotolerant campylobacters. Appl. Environ. Microbiol., 70, 3588, 2004. 136. Oliveira, T.C., Barbut, S. and Griffiths, M.W. Detection of Campylobacter jejuni in naturally contaminated chicken skin by melting peak analysis of amplicons in real-time PCR. Int. J. Food Microbiol., 104, 105, 2005. 137. Abu-Halaweh, M., Bates, J. and Patel, B.K. Rapid detection and differentiation of pathogenic Campylobacter jejuni and Campylobacter coli by real-time PCR. Res. Microbiol., 156, 107, 2005. 138. Oliveira, T.C., Barbut, S. and Griffiths, M.W. A robotic DNA purification protocol and real-time PCR for the detection of Campylobacter jejuni in foods. J. Food Prot., 68, 2131, 2005. 139. Wolffs, P. et al. Quantification of Campylobacter spp. in chicken rinse samples by using flotation prior to real-time PCR. Appl. Environ. Microbiol., 71, 5759, 2005. 140. Krause, M. et al. Comparative, collaborative, and on-site validation of a TaqMan PCR method as a tool for certified production of fresh, campylobacter-free chickens. Appl. Environ. Microbiol., 72, 5463, 2006. 141. Debretsion, A. et al. Real-time PCR assay for rapid detection and quantification of Campylobacter jejuni on chicken rinses from poultry processing plant. Mol. Cell Probes, 21, 177, 2007. 142. Fukushima, H. et al. Rapid separation and concentration of food-borne pathogens in food samples prior to quantification by viable-cell counting and real-time PCR. Appl. Environ. Microbiol., 73, 92, 2007. 143. Wolffs, P.F.G. et al. Simultaneous quantification of pathogenic Campylobacter and Salmonella in chicken rinse fluid by a flotation and real-time multiplex PCR procedure. Int. J. Food Microbiol., 117, 50, 2007. 144. Hong, J. et al. Quantification and differentiation of Campylobacter jejuni and Campylobacter coli in raw chicken meats using a real-time PCR method. J. Food Prot., 70, 2015, 2007. 145. Ronner, A.C. and Lindmark, H. Quantitative detection of Campylobacter jejuni on fresh chicken carcasses by real-time PCR. J. Food Prot., 70, 1373, 2007.

360 146. Konkel, M.E. et al. Identification of the enteropathogens Campylobacter jejuni and Campylobacter coli based on the cadF virulence gene and its product. J. Clin. Microbiol., 37, 510, 1999. 147. Waage, A.S. et al. Detection of small numbers of Campylobacter jejuni and Campylobacter coli cells in environmental water, sewage, and food samples by a seminested PCR assay. Appl. Environ. Microbiol., 65, 1636, 1999. 148. Wang, H. et al. Improved PCR detection of Campylobacter jejuni from chicken rinses by a simple sample preparation procedure. Int. J. Food Microbiol., 52, 39, 1999. 149. Waller, D.F. and Ogata, S.A. Quantitative immunocapture PCR assay for detection of Campylobacter jejuni in foods. Appl. Environ. Microbiol., 66, 4115, 2000. 150. Thunberg, R.L., Tran, T.T. and Walderhaug, M.O. Detection of thermophilic Campylobacter spp. in blood-free enriched samples of inoculated foods by the polymerase chain reaction. J. Food Prot., 63, 299, 2000. 151. Denis, M. et al. Campylobacter contamination in French chicken production from farm to consumers. Use of a PCR assay for detection and identification of Campylobacter jejuni and Campylobacter coli. J. Appl. Microbiol., 91, 255, 2001. 152. Moreno, Y. et al. Direct detection of thermotolerant campylobacters in chicken products by PCR and in situ hybridization. Res. Microbiol., 152, 577, 2001. 153. Bolton, F.J. et al. Detection of Campylobacter jejuni and Campylobacter coli in foods by enrichment culture and polymerase chain reaction enzyme-linked immunosorbent assay. J. Food Prot., 65, 760, 2002. 154. Hong, Y. et al. Rapid detection of Campylobacter coli, C. jejuni, and Salmonella enterica on poultry carcasses by using PCR-enzyme-linked immunosorbent assay, Appl. Environ. Microbiol., 69, 3492, 2003. 155. Josefsen, M.H. et al. Validation of a PCR-based method for detection of food-borne thermotolerant campylobacters in a multicenter collaborative trial. Appl. Environ. Microbiol., 70, 4379, 2004. 156. Bohaychuk, V.M. et al. Evaluation of detection methods for screening meat and poultry products for the presence of foodborne pathogens. J. Food Prot., 68, 2637, 2005. 157. Quinones, B. et al. Detection and genotyping of Arcobacter and Campylobacter isolates from retail chicken samples by use of DNA oligonucleotide arrays. Appl. Environ. Microbiol., 73, 3645, 2007. 158. Schmid, M.W. et al. Development and application of oligonucleotide probes for in situ detection of thermotolerant Campylobacter in chicken faecal and liver samples. Int. J. Food Microbiol., 105, 245, 2005. 159. Uyttendaele, M. et al. Detection of Campylobacter jejuni added to foods by using a combined selective enrichment and nucleic acid sequence-based amplification (NASBA). Appl. Environ. Microbiol., 61, 1341, 1995. 160. Uyttendaele, M., Bastiaansen, A. and Debevere, J. Evaluation of the NASBA nucleic acid amplification system for assessment of the viability of Campylobacter jejuni. Int. J. Food Microbiol., 37, 13, 1997. 161. Uyttendaele, M., Debevere, J. and Lindqvist, R. Evaluation of buoyant density centrifugation as a sample preparation method for NASBA–ELGA detection of Campylobacter jejuni in foods. Food Microbiol., 16, 575, 1999.

Molecular Detection of Foodborne Pathogens 162. Churruca, E. et al. Detection of Campylobacter jejuni and Campylobacter coli in chicken meat samples by real-time nucleic acid sequence-based amplification with molecular beacons. Int. J. Food Microbiol., 117, 85, 2007. 163. Gonzalez, I. et al. Specific identification of the enteropathogens Campylobacter jejuni and Campylobacter coli using a PCR test based on the ceuE gene encoding a putative virulence determinant. J. Clin. Microbiol., 35, 759, 1997. 164. Denis, M. et al. Development of a m-PCR assay for simultaneous identification of Campylobacter jejuni and C. coli. Lett. Appl. Microbiol., 29, 406, 1999. 165. Keer, J.T., and Birch, L. Molecular methods for the assessment of bacterial viability. J. Microbiol. Methods, 53, 175, 2003. 166. Kievits, T. et al.,. NASBA isothermal enzymatic in vitro nucleic-acid amplification optimized for the diagnosis of HIV-1 infection. J. Virol. Methods, 35, 273, 1991. 167. Tai, J.H. et al. Development of a rapid method using nucleic acid sequence-based amplification for the detection of astrovirus. J. Virol. Methods, 110, 119, 2003. 168. Cools, I. et al. Development of a real-time NASBA assay for the detection of Campylobacter jejuni cells. J. Microbiol. Methods, 66, 313, 2006. 169. Tyagi, S. and Kramer, F.R. Molecular beacons: probes that fluoresce upon hybridization. Nat. Biotechnol., 14, 303, 1996. 170. Al-Khaldi, S.F. et al. DNA microarray technology used for studying foodborne pathogens and microbial habitats: minireview. J. AOAC Int., 85, 906, 2002. 171. Ramsay, G. DNA chips: state-of-the art. Nat. Biotechnol., 16, 40, 1998. 172. Vora, G. J. et al. Nucleic acid amplification strategies for DNA microarray-based pathogen detection. Appl. Environ Microbiol., 70, 3047, 2004. 173. Call, D.R., Borucki, M.K. and Loge, F.J. Detection of bacterial pathogens in environmental samples using DNA microarrays. J. Microbiol. Methods, 53, 235, 2003. 174. Bryant, P.A. et al. Chips with everything: DNA microarrays in infectious diseases. Lancet, 4, 100, 2004. 175. Delaquis, P. et al. Application of DNA microarrays for the identification and tracking of E. coli O157:H7 and Listeria monocytogenes in food production systems. In Meeting of Agriculture and Agri-Food Canada Food Network, Lacombe, Alberta, 2002, p. 23 [Abstr. 8]. 176. Wilson, W.J. et al. Sequence-specific identification of 18 pathogenic microorganisms using microarray technology. Mol. Cell. Probes, 16, 119, 2002. 177. Hong, B. et al. Application of oligonucleotide array technology for the rapid detection of pathogenic bacteria of foodborne infections. J. Microbiol. Methods, 58, 403, 2004. 178. Kostrzynska, M. and Bachand, A. Application of DNA microarray technology for detection, identification, and characterization of food-borne pathogens. Can. J. Microbiol., 52, 1, 2006. 179. Stucki, U. et al. Identification of Campylobacter jejuni on the basis of a species-specific gene that encodes a membrane protein. J. Clin. Microbiol., 33, 855, 1995. 180. Best E.L. et al. Applicability of a rapid duplex real-time PCR assay for speciation of Campylobacter jejuni and Campylobacter coli directly from culture plates. FEMS Microbiol. Lett., 229, 237, 2003.

26 Enterobacter

Angelika Lehner and Roger Stephan University of Zurich

Carol Iversen and Seamus Fanning University College Dublin

Contents 26.1 Introduction.................................................................................................................................................................... 361 26.1.1 Classification..................................................................................................................................................... 361 26.1.2 Epidemiology and Pathogenesis....................................................................................................................... 361 26.1.3 Diagnosis........................................................................................................................................................... 362 26.1.3.1 Conventional Procedures................................................................................................................. 362 26.1.3.2 Molecular Procedures...................................................................................................................... 363 26.2 Methods.......................................................................................................................................................................... 364 26.2.1 Sample Preparation........................................................................................................................................... 364 26.2.2 Detection Procedures........................................................................................................................................ 365 26.2.2.1 PCR Identification .......................................................................................................................... 365 26.2.2.2 Real-Time PCR Identification.......................................................................................................... 365 26.3 Conclusions and Future Perspectives............................................................................................................................. 365 References.................................................................................................................................................................................. 365

26.1  Introduction 26.1.1 Classification The Enterobacter genus represents a large and heterogeneous group within the Enterobacteriaceae family. It once had 21 taxonomically valid species, however recent taxonomic studies have led to the transfer of three Enterobacter species to alternative genera (E. intermedius=Kluyvera intermedia, E. agglomerans=Pantoea agglomerans, E. sakazakii=Cronobacter spp.). Additionally, E. taylorae has been recognized as a heterotypic synonym of E. cancerogenus and Enterobacter dissolvens has been reassigned to Enterobacter cloacae as E. cloacae subspecies dissolvens comb. nov. Thus, the genus Enterobacter currently contains 16 distinct species.1–3 Species closely related to E. cloacae, having a DNA relatedness of over 60% to E. cloacae and/or differing by only one biochemical trait have been subsumed in the so-called E. cloacae-complex. These are considered the main species that are frequently isolated from clinical samples.4 Members of the genus Enterobacter can be found in natural environments (soil, water, sewage, vegetables) and sometimes appear as commensals of the animal and human gut. Only one species—Enterobacter sakazakii—is recognized as a foodborne pathogen and therefore we will focus in this chapter mainly on this species. E. sakazakii, previously known as “yellow-pigmented Enterobacter cloacae,” was

described as a new species in 1980 by Farmer et al.5 when the presence of certain biochemical traits, antibiotic susceptibilities and DNA relatedness provided sufficient evidence to distinguish the species from E. cloacae. However, from the beginning, members of this species were described as quite heterogeneous at the microbiological as well as at the molecular level.5–7 Updating the original taxonomy of E. sakazakii by using a polyphasic approach has resulted in the definition of at least five new species based on extensive geno- and phenotypic evaluations.8,9 In order to facilitate their continued inclusion in schemata for the diagnosis and the microbiological criteria for foodstuffs, it has been proposed that these species be moved to a novel genus, Cronobacter 9,10 with the novel genus being synonymous with E. sakazakii. A further study based on multilocus sequence analysis (MLSA) of several house keeping genes present in E. sakazakii supports the classification of these organisms as a new genus (Kuhnert et al., in submission).

26.1.2 Epidemiology and Pathogenesis Although isolated with varying frequency from the natural, domestic, and food production environments, as well as from various types of food, E. sakazakii attracted special attention as an (occasional) contaminant of powdered infant formula (PIF).11–13 Multiple cases of infections have occurred in neonatal intensive care units (NICU) and a number of outbreaks 361

362

have been traced back to the presence of these pathogens in reconstituted infant formula milk and/or their persistence in/ on food preparation equipment.14–16 A summary of reported cases has been provided by Mullane et al.17 Enterobacter sakazakii can cause meningitis, necrotizing enterocolitis (NEC) and bacteremia especially in neonates and infants.16,18–20 The International Commission for Microbiological Specification for Foods (ICMSF, 2002) has ranked E. sakazakii as “Severe hazard for restricted populations, life threatening or substantial chronic sequelae or long duration.” Although it is possible for infection to be acquired by previously healthy newborn infants in the home environment,21,22 the majority of reported cases have occurred in NICU. A retrospective study of 46 infants indicated that meningitis is more prevalent in infants of normal gestational age and birth weight with onset of disease usually occurring within the first week following birth. In contrast low birth weight, premature infants were more likely to develop bacteremia with no progression to CNS disease and the age of onset was usually over 1 month.23 A higher mortality rate and adverse sequelae in survivors were associated with meningitis cases. The bacterium causes cystic changes, abscesses, fluid collection, dilated ventricles and infarctions. Cronobacter meningitis leads to cerebral abscess similar to those due to Citrobacter koseri infections, therefore a similarity in the cascade of pathogenic events induced by the two organisms has been suggested.24 Some Cronobacter infections occur in neonates born by Cesarean section.18,25–27 Therefore, it is thought risk of infection is related to ingestion, exacerbated by poor hygiene practices, and not through vertical transmission from the mother.26 Prolonged and repeated use of enteral feed bags are identified as risk factors28,29 with the possibility of biofilm formation leading to increased oral dose. Muytjens et al.18 re-evaluated Enterobacter strains from blood and CSF and uncovered several cases of meningitis and bacteremia due to Cronobacter infection suggesting that the organism had been under reported. The first known cases of meningitis due to Cronobacter occurred in England.25 No source for the infection was identified although the report does not mention epidemiological investigation of infant formula or feed preparation equipment. Since then cases have been reported worldwide. Cronobacter has been isolated from a wide range of clinical sources including a stethoscope5 and nursery food preparation equipment.14,27,30 Smeets et al.31 used pulsed-field gel electrophoresis (PFGE) to confirm the epidemiological evidence that a contaminated dish brush used for cleaning bottles was the source of three cases in 1981. In Iceland three cases were reported linked to milk formula contaminated with Cronobacter 32 Two groups14,15 reported on four neonates with Cronobacter infections in Tennessee. The organism was isolated from all four patients, a used can of infant formula milk and the blender (which had heavy growth of the organism). In this outbreak identical biotypes, antibiograms, and plasmid profiles were obtained for patients and environmental isolates. There was evidence of prolonged incubation in bottle heaters between 35–37°C before use. Nazarowec-White and Farber33 studying three isolates

Molecular Detection of Foodborne Pathogens

obtained from one hospital over 11 years showed that they had indistinguishable ribotype patterns indicating possible persistence in the environment. In 1994 an outbreak occurred in France involving 17 neonates. Cronobacter isolates were obtained from various anatomical sites, prepared feeds and unused infant formula. PFGE analysis described four clusters, two of which contained isolates from neonates who ranged from asymptomatic colonized individuals to case fatalities. One other cluster contained isolates from the prepared feed, an asymptomatic neonate and a neonate with mild digestive problems. The fourth cluster comprised the isolates from the unused powdered formula. In this case no link could be made between the powdered formula and the outbreak and it is possible that the prepared feed became contaminated via an alternate source.34 A further outbreak occurred in France in 2004 involving 13 infants, nine were asymptomatically colonized, two developed bacterial meningitis, one had conjunctivitis and one suffered hemorrhagic colitis. The outbreak was investigated using automated ribotyping (using restriction endonucleases EcoRI, PstI, and PvuII) and by PFGE using the enzymes Xba1 and Spe1. A total of nine isolates from eight neonates were found to have undistinguishable ribotypes and PFGE patterns. These isolates were undistinguishable from isolates obtained from four separate lots of infant formula, thus establishing a clear link between the outbreak and the product.79 NEC is much more common in babies fed formula milk compared with those fed breast milk.35 The pathogenesis is associated with neonatal intestinal ischemia, microbial colonization of the gut, and excess protein substrate in the intestinal lumen (the latter being associated with formula feeding). In a study of 125 neonates with NEC, Enterobacter spp. were the most common organisms, being isolated from 29% of patients.36 As with cases of meningitis, NEC due to Cronobacter traditionally has a high case fatality rate (10–55%). Van Acker et al.16 described 12 cases of NEC in neonates that occurred in 1998. Eleven strains of Cronobacter were isolated from patient samples and 14 strains were isolated from infant milk preparations. Arbitrary primed PCR (AP-PCR) was used to type all the Cronobacter isolates and determine common sources of the outbreak. Three AP-PCR profiles were obtained for patient and milk isolates with the 14 milk isolates matching the profile from three patients. Four years earlier E. sakazakii had been isolated from a gastrostomy tube of a neonate fed the same type of milk. This original isolate was subsequently shown to have an AP-PCR profile almost identical to the 14 milk and patient isolates, thus demonstrating a persistent contamination problem.

26.1.3  Diagnosis 26.1.3.1  Conventional Procedures In 2002, the Food and Drug Administration (FDA) published a method for detection of E. sakazakii which included a ­pre-enrichment step in buffered peptone water (BPW), enrichment in Enterobacteriaceae Enrichment (EE) broth, plating on Violet Red Bile Glucose agar (VRBG) and picking

Enterobacter

of five typical colonies onto tryptone soy agar (TSA) plates.37 After incubation at 25°C for 48–72 h, yellow pigmented colonies on TSA plates are confirmed using the API 20E system. The main weak points of this procedure are the inability of some target strains to grow in the selective EE broth, the lack of discrimination between Enterobacteriaceae strains on VRBG, and the variation in intensity of the pigmentation, with occasional observation of nonpigmented strains.5,10 Guillaume-Gentil et al.38 published an alternative procedure based on selective enrichment in a modified lauryl sulphate tryptose broth (mLST), incorporating 0.5 M NaCl, and 10 mg/ml vancomycin hydrochloride. This method was further improved by the replacement of VRBG, with a chromogenic agar and forms the basis of the ISO Technical Specification for detection of E. sakazakii in milk-based infant formula.13 Various chromogenic and fluorogenic agar media have been described in recent years for detection of E. sakazakii.39–43 These are based mainly on the enzyme α-glucosidase, which is constitutively expressed in E. sakazakii. However, other organisms also produce presumptive colonies on these agars, notably the newly described species E. helveticus, E. turicensis, and E. pulveris.2,3 These species can be found in the same ecological niches as E. sakazakii, such as dried food products and factory environments and present a challenge to both culture-based as well as molecular isolation and identification methods. It has been established that some isolates of E. sakazakii do not grow well in enrichment broths currently proposed for isolation of this organism.44,45 As some E. sakazakii strains cannot grow in these broths, a sample containing only such strains would give a false negative result and therefore the enrichment procedure should be improved. In a recent study a Cronobacter Screening Broth (CSB), has been developed to identify samples potentially contaminated with Cronobacter (E. sakazakii).46 The broth is designed to circumvent the problems encountered with selective enrichment media for these organisms and to be complementary to current available chromogenic media in order to improve overall sensitivity and selectivity of Cronobacter (E. sakazakii) detection. An alternative method to avoid the difficulties of selective broths is the MATRIX PSAK50 Method (Matrix MicroScience Ltd, UK), which uses cationic paramagnetic particle capture to concentrate contaminating microorganism in a pre-enriched sample before plating directly onto isolation agar.47 Currently the AOAC® Official Methods ProgramSM is in the process of assessing rapid methods for the detection of E. sakazakii. These include two enzyme-linked immunoassays (EIAs): the Assurance for Enterobacter sakazakii (BioControl Systems, USA) and the TECRA HELIX E. sakazakii Method (TECRA International, Australia). 26.1.3.2  Molecular Procedures (i) Species-specific detection and identification: In comparison with labor-intensive methods, the recently developed fluoro- and chromogenic, differential (selective) media decrease the time for isolation of E. sakazakii.39–42,44

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However, due to the obvious heterogeneity within these organisms and/or the fact that expression of phenotypical/ biochemical features may vary, the phenotypic identification of E. sakazakii with available commercial systems may be difficult.45 Molecular methods revealed that several strains identified as E. sakazakii by commercial biochemical kits belonged to distinct species.7,42,48 Restaino et al.42 recommended using more than one differentiation system. Several conventional and real-time PCR methods have been developed that enable (quantitative), sensitive, specific, and rapid detection from infant formula, enrichment broths and media. Targets for conventional PCR systems include the 16S rRNA gene,6,49,50 the ompA gene51 the gene coding for the 1,6 α-glucosidase in E. sakazakii52 and a gene encoding a zinc-containing metalloprotease.53 Of the “real-time”-assays that have been described so far, three of them target the 16S rRNA gene,54–56 one is based on the region located between the 16S rRNA and the 23 rRNA genes,57 another targets the region between the tRNA-glu and 23S rRNA genes58 and one targets the dnaG gene.48,59 To date, only two PCR based methods have been evaluated on a broad panel of target as well as nontarget strains and both of these proved to be 100% sensitive and specific for E. sakazakii. These methods will be described in detail in the methods section of this chapter. Genetic-based systems include the BAX® Assay for the Detection of Enterobacter sakazakii (Dupont Qualicon,USA) and the foodproof® Enterobacteriaceae plus E. sakazakii Detection System (BIOTECON Diagnostics, Germany). The latter qualitatively detects Enterobacteriaceae DNA while simultaneously identifying the presence of E. sakazakii. To avoid false-positive PCR results the DNA of dead bacterial cells in the sample is eliminated using a light sensitive reagent that only penetrates the cell membranes of dead cells and covalently binds to DNA preventing amplification. The US FDA have also developed a revised BAM Method involving a short enrichment step, centrifugation, and a PCR assay. Another commercially available PCRbased identification system is the TaqMan® Enterobacter sakazakii Detection Kit (Applied BioSystems, USA). The VIT® (vermicon identification technology, Munich, Germany) represents an alternative to the DNA-targeted PCRbased detection and identification systems for E. ­sakazakii. It is based on fluorescently labeled gene probes targeting specified regions on the ribosomal RNA of the bacteria, therefore only live cells are detected by the system. The test is performed on 1 ml of overnight culture of enrichment broth or rich media broth (e.g., BHI, LB) after inoculation with presumptive colony material according to the instructions of the manufacturer. The method has successfully been used in a comparative study evaluating cultural and molecular identification systems for E. sakazakii 44. (ii) Subtyping: The determination of clonality or polyclonality of isolates is necessary during investigations of E. sakazakii infection outbreaks and also for trace-back studies in production environments.

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PFGE. PFGE is a nonamplified technique that separates long strands of DNA molecules (larger than 15–20 kb) previously digested with restriction enzyme(s). Periodical switching of the voltage in three directions results in the reorientation of DNA moving through the gel in a size dependent manner, which facilitates a finer resolution as it aligns and realigns to the applied electrical field. Nazarowec-White and Farber (1999)33 were the first to describe a PFGE method for the subtyping of E. sakazakii isolates and used two different enzymes (XbaI and SpeI). Recently, two factory surveillance studies have employed a PFGE method for tracing E. sakazakii isolates within infant food manufacturing facilities (Iversen et al., in submission and Mullane et al.60). These studies were based on the protocol of Nazarowec-White and Farber33 and used XbaI. In 2008, a collaborative study was undertaken by several international laboratories, in conjunction with the PulseNet Programme at the Centres for Disease Control and Prevention (CDC) in the US, to develop a standard protocol for E. sakazakii PFGE typing. Ribotyping. Ribotypes are generated by probing restriction fragments of genomic DNA for the highly conserved genes coding for the 16S and 23S rRNA. Small variations between strains occur in the less conserved, flanking genes and intergenic sections of the genome resulting in fragments of unequal size. These are separated using gel electrophoresis, transferred to a membrane and the individual strain fingerprints revealed by hybridization of chemiluminescent probes. The automated RiboPrinter Microbial Characterization System (Dupont Qualicon, USA) has been used to speciate and characterize a large number of E. sakazakii isolates.8 Isolates were grown on TSA (18 h, 37°C) and prepared according to standard procedures61 using the EcoR1 restriction enzyme. Riboprint patterns are analyzed based on the number, size, and signal intensity of the detected fragments. Comparison to existing entries in a riboprint database allows species-and subspecies-level identification. Random amplification of polymorphic DNA (RAPD). RAPD typing has been used to analyze clonal relationships between E. sakazakii strains in a number of independent studies (Iversen et al., in submission).33,48,62–65 NazarowecWhite and Farber33 developed protocols for the molecular subtyping of E. sakazakii by ribotyping, RAPD, and PFGE. The authors showed that RAPD and PFGE were the most discriminatory subtyping schemes for E. sakazakii followed by ribotyping and two microbiological typing methods— biotyping and antibiograms. In addition, Clementino et al.62 comparatively assessed the usefulness of the tRNA intergenic spacer, 16S–23S internal transcribed spacer and randomly amplified DNA for discrimination of E. sakazakii and E. cloacae isolates. BOX-PCR and REP-PCR. Proudy et al.66 examined the discriminative power of the 154 bp BOX element against the sequencing of the fliC gene and PFGE using 27 E. sakazakii strains from clinical and environmental sources. The BOXPCR results showed 92% agreement with PFGE results indicating the potential of this typing method for ­epidemiological investigation, whereas fliC gene sequencing was poorly

Molecular Detection of Foodborne Pathogens

discriminative. The application of BOX-PCR genotyping in a factory environment was demonstrated in a follow-up study.67 More recently the discriminative power of the repPCR (repetitive extragenic palindromic (REP) has been compared to PFGE.68 Using Simpson’s index of diversity, values of 0.974 and 0.998 were calculated for rep-PCR and PFGE, respectively at a similarity cut-off of 95% demonstrating good correlation with a high degree of genetic heterogeneity among the isolates. Multi-locus VNTR analysis (MLVA). Variable number tandem repeat (VNTR) motifs represent sources of genetic polymorphisms. These DNA sequence elements are often maintained within a bacterial species, with individual strains displaying different copy numbers. The length of a tandem repeat at a specific locus can vary as a consequence of DNA slippage during replication or unequal crossover elements. These differences can be analyzed by amplification of the region and sizing of the resulting amplicons.69 The high degree of polymorphism at these loci is particularly useful as a target for strain discrimination within bacterial species. MLVA is a subtyping method that involves amplification and fragment size comparison of polymorphic VNTR regions and has successfully been used to type Enterobacteriaceae.70–72 The availability of a complete E. sakazakii genome sequence (http://genome/wustl.edu/pub/organism/Microbes/Enteric_ Bacteria/Enterobacter_sakazakii/assembly/Enterobacter_ sakazakii-4.0/) enabled the identification of VNTR motifs within E. sakazakii. Subsequently an MLVA subtyping scheme was developed and applied on a genotypically and phenotypically diverse collection of E. sakazakii isolates in a study by Mullane et al.73 Amplified fragment length polymorphisms (AFLP). The AFLP technique has been employed in plant and microbiological research to describe the molecular ecology of various niches and can be used to determine inter- and intraspecies relatedness.74–76 Mougel et al.77 found that members of the same genomic species cluster consistently using AFLP analysis and suggested that future genomic delineation of bacterial species could be based on this approach. This technique was included in a study by Iversen et al.8 to clarify the taxonomic relationship of over 200 strains previously identified as E. sakazakii and gave discriminatory results comparable to DNA–DNA hybridization.

26.2  Methods 26.2.1 Sample Preparation Aliquots of matrices to be tested are pre-enriched in 9 × volume of BPW for 24 h at 37°C. A 100-fold dilution (0.1 ml in 10 ml) is transferred into CSB (CSB: 18 g/l Bromocressol purple broth, Sigma B2676; 10 g/l sucrose and 10 mg/l vancomycin hydrochloride, Sigma V2002)46 or alternative enrichment broths as e.g., mLST.13 Fermentation of the carbohydrate results in a colour change from purple to yellow. After incubation at 41.5°C for up to 24 h, positive (yellow) broths are streaked onto chromogenic media,

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Enterobacter

e.g., Brilliance Enterobacter sakazakii agar (CM1055, Oxoid, UK), Enterobacter sakazakii Isolation Agar (ESIA, AES Cheminux, France), Enterobacter sakazakii Screening Plate (ChromID Sakazakii, bioMérieux, France), or equivalent. For DNA extraction from broth cultures, commercially available kits e.g., the Qiagen Blood and Tissue Kit (Qiagen, Germany) are recommended. PCR and real-time PCR assays are set up using standard molecular handling procedures and by applying appropriate equipment and using standard instruments.

26.2.2  Detection Procedures 26.2.2.1  PCR Identification In a study by Lehner et al.52 the molecular basis of the α-glucosidase activity in E. sakazakii was determined and the potential of this PCR system targeting the 1,6-αglucosidase for the specific identification of E. sakazakii was evaluated in two studies.10,44 Presumptive colonies from agar plates are inoculated into 5 ml BHI broth and grown overnight at 37°C. DNA is extracted using a simple “boiling method,” i.e., harvesting cells from 1 ml overnight culture by centrifugation (5  min at 7500 × g), resuspension of cells in 100 µl distilled water, lysis of cells by heating the suspension at 100°C for 10 min and final separation of DNA from cellular debris by centrifugation for 2 min at 10000 × g. Alternatively, DNA can be extracted using a commercially available kit (e.g., Qiagen Blood and Tissue Kit, Germany). The α-glucosidase (gluA) gene is amplified using the following primers: EsAgf: 5′-TGAAAGCAATCGACAAGAAG-3′ and EsAgr: 5′-ACTCATTACCCCTCCTGATG-3′ generating a product of 1680 bp in size. The reaction mixture contains 5 pmol of forward and reverse primers, 100 μM dNTPs, 1x Taq DNA polymerase buffer and 2 U Taq DNA polymerase (Promega) in a total volume of 50 μl. The initial denaturation step is 94°C for 2 min, followed by 29 cycles of 94°C for 30 sec, 60°C for 60 sec and 72°C for 90 sec. Cycling is completed by a final elongation step at 72°C for 5 min. The amplification products are analyzed by electrophoresis in a 1% agarose gel and visualized with a fluorescent stain. The gluA_short fragment is amplified using primers EsAg5f: 5′-TATCAGATCTACCCGCGC-3′ and EsAg5_5r: 5′-TTGATGCCAAGCTGTTGC-3′ resulting in a 105-bp amplicon. The PCR cycling conditions are as described above except annealing is at 62°C for 30 sec and extension at 72°C for 30 sec. The amplification products are analyzed in a 2% agarose gel. 26.2.2.2 Real-Time PCR Identification A real-time PCR assay targeting the dnaG gene, which is a component of the macromolecular synthesis operon, was originally developed by Seo and Brackett.59 The method was modified by Drudy et al.48 using the TaqMan probe (6-FAMACAGAGTAGTAGTTGTAGAGGCCGTGCTTCC-TMR). To confirm identification of E. sakazakii, total genomic DNA is purified from presumptive colonies as outlined

above. The following primers are used for amplification: Fwd: 5′-GGGATATTGTCCCCTGAAACAG-3′ and Rev: 5′-CAGGAATAAGCCGCGATT-3′.59 Amplification of the target region is performed in a final volume of 20 μl, using 200 μM deoxynucleoside triphosphates, 4.0 mM MgCl2, 2.0 μl of 10 × reaction buffer, 10 mM of each primer, 2.5 mM of probe, 1 U Taq DNA polymerase, and 2 µl DNA template (containing approximately 100 ng of DNA). The recommended reaction conditions are: 95°C for 15 min followed by 40 cycles of 95°C for 15 sec and 60°C for 50 sec. In the study by Drudy et al.48 the RT-PCR was performed on a Corbett Research Rotor-Gene RG 3000 instrument.

26.3 Conclusions and Future Perspectives To date, there are only two molecular identification methods for E. sakazakii for which extensive evaluation data is publically available. Both methods are designed to target all species of the newly described genus Cronobacter (E. sakazakii) and both methods perform equally well in terms of sensitivity and specificity. Considering the new taxonomic description for Cronobacter, there is perhaps a need for the development of methods for the species-specific identification of organisms within this genus. This can be facilitated by the publication of the complete E. (Cronobacter) sakazakii genome sequence, as well as the genome sequence of a second type strain—Cronobacter turicensis 3032—which will be available in the near future. Genomic analysis will provide deeper insights into the genetic organization of Cronobacter species and will enable the identification of potential targets for molecular methods that will allow accurate discrimination of species. An interesting approach into the direction of molecular based serotyping of E. sakazakii was published recently by Mullane et al.78 In this study nucleotide polymorphism in the O-antigen coding locus rfb was determined and a PCR assay targeting the genes specific for the two prominent serotypes in E. sakazakii was developed. Last but not least, there are several efforts undergoing to improve the cultural detection method for Cronobacter spp., which might also lead to an improvement in the performance and application of the molecular identification methods.

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5. Farmer, J.J. et al. Enterobacter sakazakii: a new species of Enterobacteriaceae isolated from clinical species. Int. J. Syst. Evol. Bacteriol., 30, 569, 1980. 6. Lehner, A., Tasara, T. and Stephan, R. 16S rRNA gene based analysis of Enterobacter sakazakii strains from different sources and development of a PCR assay for identification. BMC Microbiol., 4, 43, 2004. 7. Iversen, C., Waddington, M. and Forsythe, S.J. Identification and phylogeny of Enterobacter sakazakii relative to Enterobacter and Citrobacter species. J. Clin. Microbiol., 42, 5368, 2004. 8. Iversen, C. et al. The taxonomy of Enterobacter sakazakii: proposal of a new genus Cronobacter gen. nov., and descriptions of Cronobacter sakazakii comb. nov., Cronobacter sakazakii subsp. sakazakii, comb. nov. Cronobacter sakazakii subsp. malonaticus subsp. nov., Cronobacter turicensis sp. nov., Cronobacter muytjensii sp. nov. Cronobacter dublinensis sp. nov. and Cronobacter genomospecies 1. BMC Evol. Biol., 7, 64, 2007. 9. Iversen, C. et al. Cronobacter gen. nov., a new genus to accommodate the biogroups of Enterobacter sakazakii, and proposal of Cronobacter sakazakii gen. nov. comb. nov., C. malonaticus sp. nov., C. turicensis sp. nov., C. muytjensii sp. 3 nov., C. dublinensis sp. nov., Cronobacter genomospecies 1, and of three subspecies, C. dublinensis sp. nov. subsp. dublinensis subsp. nov., C. dublinensis sp. nov. subsp. lausannensis subsp. nov., and C. dublinensis sp. nov. subsp. lactaridi subsp. nov. Int. J. Syst. Evol. Microbiol., 58, 1442, 2008. 10. Iversen, C. et al. Identification of Cronobacter spp. (Enterobacter sakazakii). J. Clin. Microbiol., 45, 3814, 2007b. 11. Anonymous, FAO-WHO. Enterobacter sakazakii and other microorganisms in powdered infant formula: meeting report. MRA Series 6, WHO, Geneva, 2004. 12. Anonymous, FAO-WHO. Enterobacter sakazakii and Salmonella in powdered infant formula, Second Risk Assessment Workshop. 16–-20th January, WHO Rome, Italy, 2006. 13. Anonymous, Technical Specification ISO/TS 22964. 2006. Milk and milk products – detection of Enterobacter sakazakii. ISO/TS 22964:2006(E) and IDF/RM 210:2006(E).210, 2006(E), First Edition. 14. Simmons, B.P. et al. Enterobacter sakazakii infections in neonates associated with intrinsic contamination of powdered infant formula. Infect. Control Hosp. Epidemiol., 10, 398, 1989. 15. Clark, N.C. et al. Epidemiologic typing of Enterobacter sakazakii in two neonatal nosocomial outbreaks. Diagn. Microbiol. Infect. Dis., 13, 467, 1990. 16. Van Acker, J. et al. Outbreak of necrotizing enterocolitis associated with Enterobacter sakazakii in powdered milk formula. J. Clin. Microbiol., 39, 293, 2001. 17. Mullane, N. et al. Enterobacter sakazakii: and emerging bacterial pathogen with implications for infant health. Minerva Pediatr., 59, 137, 2007. 18. Muytjens, H.I. et al. Analysis of eight cases of neonatal meningitis and sepsis due to Enterobacter sakazakii. Appl. Environ. Microbiol., 70, 5692, 1983. 19. Nazarowec-White, M. and Farber, J.M. Enterobacter sakazakii: a review. Int. J. Food Microbiol., 34, 103, 1997. 20. Lehner, A. and Stephan, R. Microbiological, epidemiological, and food safety aspects of Enterobacter sakazakii. J. Food Prot., 67, 2850, 2004. 21. Adamson, D.H. and Rogers, J.R. Enterobacter sakazakii meningitis with sepsis. Clin. Microbiol. Newslett., 3, 19, 1981.

Molecular Detection of Foodborne Pathogens 22. Kleimann, M.B. et al. Meningoencephalitis and compartmentalization of the cerebral ventricles caused by Enterobacter sakazakii. J. Clin. Microbiol., 14, 352, 1981. 23. Bowen, A.B. and Braden, C.R. Invasive Enterobacter sakazakii disease in infants. Emerg. Infect. Dis., 12, 1185, 2006. 24. Willis, J. and Robinson, J.E. Enterobacter sakazakii meningitis in neonates. Pediatr. Infect. Dis. J., 7, 196, 1988. 25. Urmenyi, A.M.C. and Franklin, A.W. Neonatal death from pigmented coliform infection. Lancet, 1, 313, 1961. 26. Muytjens, H.L. and Kollee, L.A.A. Enterobacter sakazakii meningitis in neonates: causative role of formula. Pediatr. Infect. Dis. J., 9, 372, 1990. 27. Bar-Oz, B. et al. Enterobacter sakazakii infection in the newborn. Acta Paediatr., 90, 356, 2001. 28. J. Levy, J. et al. Contaminated enteral nutrition solutions as a cause of nosocomial bloodstream infection: a study using plasmid fingerprinting. J. Parent. Enter. Nutr. 13, 228, 1989. 29. Oie, S. and Kamiya, A. Comparison of microbial contamination of enteral feeding solution between repeated use of administration sets after washing with water and after washing followed by disinfection. J. Hosp. Infect., 48, 304, 2001. 30. Noriega, F.R. et al. Nosocomial bacteremia caused by Enterobacter sakazakii and Leuconostoc mesenteroides resulting from extrinsic contamination of infant formula. Pediatr. Infect. Dis., 9, 447, 1990. 31. Smeets, L.C. et al. Genetische karakterisatie van Enterobacter sakazakii-isolaten van Nederlandse patiënten met neonatale meningitis. Ned. Tijdschr. Med. Microbiol.. 6, 113, 1998. 32. Biering, G. et al. Three cases of neonatal meningitis caused by Enterobacter sakazakii in powdered milk. J. Clin. Microbiol., 27, 2054, 1989. 33. Nazarowec-White, M. and Farber, J.M. Phenotypic and genotypic typing of food and clinical isolates of Enterobacter sakazakii. J. Med. Microbiol., 48, 559, 1999. 34. Townsend, S., Hurrell, E. and Forsythe, S. Virulence studies of Enterobacter sakazakii isolates associated with a neonatal intensive care unit outbeak. BMC Microbiol., 8, 64, 2008. 35. Lucas, A., and Cole, T.J. Breast milk and neonatal necrotizing enterocolitis. Lancet, 336, 1519, 1990. 36. Chan, K.L. et al. A study of preantibiotic bacteriology in 125 patients with necrotizing enterocolitis. Acta Paediatr. (Suppl.), 396, 45, 1994. 37. Anonymous, U.S. Food and Drug Administration. Isolation and enumeration of Enterobacter sakazakii from dehydrated powdered infant formula, 2002. [Online] http://www.cfsan. fda.gov~comm/mmesakaz.html. 38. Guillaume-Gentil, O. et al. A simple and rapid cultural method for detection of Enterobacter sakazakii in environmental samples. J. Food Prot., 68, 64, 2005. 39. Iversen, C., Druggan, P. and Forsythe. S.J. A selective differential medium for Enterobacter sakazakii. Int. J. Food Microbiol., 96, 133, 2004. 40. Leuschner, R.G.K. and Bew, J. A medium for the presumptive detection of Enterobacter sakazakii in infant formula: interlaboratory study. J. AOAC Int., 87, 604, 2004. 41. Oh, S.W. and Kang, D.H. Fluorogenic selective and differential medium for isolation of Enterobacter sakazakii. Appl. Environ. Microbiol., 70, 5692, 2004. 42. Restaino, L. et al. A chromogenic plating medium for the isolation and identification of Enterobacter sakazakii from foods, food ingredients and environmental sources. J. Food Prot., 69, 315, 2006.

Enterobacter 43. Song, K.Y. et al. Evaluation of a chromogenic medium supplemented with glucose for detecting Enterobacter sakazakii. Microbiol. Biotechnol., 18, 579, 2008. 44. Lehner, A. et al. Comparison of two chromogenic media and evaluation of two molecular based identification systems for Enterobacter sakazakii detection. BMC Microbiol., 6, 15, 2006. 45. Iversen, C. and Forsythe, S. Comparison of media for the isolation of Enterobacter sakazakii. Appl. Environ. Microbiol., 73, 48, 2007. 46. Iversen, C. et al. Development of a novel screening method for the isolation of Cronobacter spp. (Enterobacter sakazakii). Appl. Environ. Microbiol., 74, 2550, 2008. 47. Mullane, N.R. et al. Detection of Enterobacter sakazakii in dried infant milk formula by cationic magnetic bead capture. Appl. Environ. Microbiol., 72, 6325, 2006. 48. Drudy, D. et al. Characterization of a collection of Enterobacter sakazakii isolates from environmental and food sources. Int. J. Food Microbiol., 110, 127, 2006. 49. Witthuhn, R.C., Kemp, F. and Britz, T.J. Isolation and PCR detection of Enterobacter sakazakii in South African food products, specifically infant formula milks. World J. Microbiol. Biotechnol., 23, 151, 2007. 50. Hassan, A.A. et al. Characterization of the gene encoding the 16S rRNA of Enterobacter sakazakii and development of a species-specific PCR method. Int J. Food Microbiol., 116, 214, 2007. 51. Nair Mohan. K.M. and Ventkitanarayanan K.S. Cloning and sequencing of the ompA gene of Enterobacter sakazakii and development of an ompA targeted PCR for rapid detection of Enterobacter sakazakii in infant formula. Appl. Environ. Microbiol., 72, 2539, 2006. 52. Lehner, A. et al. Molecular characterization of the alpha glucosidase activity in Enterobacter sakazakii reveals the presence of a putative gene cluster for palatinose metabolism. Syst. Appl. Microbiol., 29, 609, 2006. 53. Kothary, M.M. et al. Characterization of the zinc-containing metalloprotease encoded by zpx and development of a species-specific detection method for Enterobacter sakazakii. Appl. Environ. Microbiol., 73, 4142, 2007. 54. Malorny, B. and Wagner, M. Detection of Enterobacter sakazakii strains by real-time PCR. J. Food Prot., 68, 1623, 2005. 55. Lehmacher, A., Fiegen, M. and Hansen, B. Real-time PCR von Enterobacter sakazakii in Säuglingsanfangsnahrung. J. Verbr. Lebensm., 2, 218, 2007. 56. Kang S.E., Nam, Y.S. and Hong, K.W. Rapid detection of Enterobacter sakazakii using TaqMan real-time PCR assay. Microbiol. Biotechnol., 17, 526, 2007. 57. Liu, Y. et al. Real time PCR using TaqMan and SYBR Green for detection of Enterobacter sakazakii in infant formula. J. Microbiol. Methods, 65, 21, 2006. 58. Derzelle, S. and Dilasser, F. A robotic DNA purification protocol and real-time PCR for the detection of Enterobacter sakazakii in powdered milk formulae. BMC Microbiol., 6, 100, 2006. 59. Seo, K.H. and Brackett, R.E. Rapid, specific detection of Enterobacter sakazakii in infant formula using a real time PCR assay. J. Food Prot., 68, 59, 2005. 60. Mullane, N.R. et al. Application of pulsed-field gel ­electrophoresis to characterise and trace the prevalence of Enterobacter sakazakii in an infant formula processing facility. Int. J. Food Microbiol., 116, 73, 2007.

367 61. Bruce, J. Automated system rapidly identifies and characterizes microorganisms in food. Food Technol., 50, 77, 1996. 62. Clementino, M.M. et al. PCR analyses of tRNA intergenic spacer, 16S–23S internal transcribed spacer, and randomly amplified polymorphic DNA reveal inter and intraspecific relationships of Enterobacter cloacae strains. J. Clin. Microbiol., 39, 3865, 2001. 63. Babalola, O.O. et al. Characterization of potential ethyleneproducing rhizosphere bacteria of Striga-infested maize and sorghum. Afr. J. Biotechnol., 1, 67, 2003. 64. Sanjaq, S. et al. Improvement and validation of RAPD in comparison to PFGE analysis of Enterobacter sakazakii strains. Int. J. Med. Microbiol., 297, 97, 2007. 65. Kim, K. et al. Prevalence and genetic diversity of Enterobacter sakazakii in ingredients of infant foods. Int. J. Food Microbiol., 122, 196, 2008. 66. Proudy, I. et al. Genotypic characterization of Enterobacter sakazakii isolates by PFGE, BOX-PCR and sequencing of the fliC gene. Appl. Environ. Microbiol., 104, 26, 2008. 67. Proudy, I. et al. Tracing of Enterobacter sakazakii isolates in infant milk formula processing by BOX-PCR genotyping. J. Appl. Microbiol., 2008. 68. Healy, B. et al. Evaluation of an automated rep-PCR system for subtyping Enterobacter sakazakii. J. Food Prot., 71, 1372, 2008. 69. Keim, P. et al. Multiple-locus variable–number tandem-repeat analysis reveals genetic relationship within Bacillus anthracis. J. Bacteriol., 182, 2928, 2000. 70. Le Fleche, P. et al. A tandem repeats database for bacterial genomes: application to the genotyping of Yersinia pestis and Bacillus anthracis. BMC Microbiol., 1, 2, 2001. 71. Lindstedt, B.A. et al. DNA fingerprinting of Shiga-toxin producing Escherichia coli O157 based on multiple-locus variable-number tandem-repeats analysis (MLVA). Ann. Clin. Microbiol. Antimicrob., 2, 12, 2003. 72. Lindstedt, B.A. et al. Multiple-locus variable-number tandem-repeats analysis of Salmonella enterica subsp. enterica serovar Typhimurium using PCR multiplexing and multicolor capillary electrophoresis. J. Microbiol. Methods, 59, 163, 2004. 73. Mullane, N.R. et al. Development of multiple-locus variable tandem repeat analysis for the molecular subtyping of Enterobacter sakazakii. Appl. Environ. Microbiol., 74, 1223, 2008. 74. Vos, P. et al. AFLP: a new technique for DNA fingerprinting. Nucleic Acids Res., 23, 4407, 1995. 75. Mueller, U.G. and Wolfenbarger, L.L. AFLP genotyping and fingerprinting. Tree, 14, 389, 1999. 76. Rademaker, J.L. et al. Comparison of AFLP and rep-PCR genomic fingerprinting with DNA-DNA homology studies: Xanthomonas as a model system. Int J. Syst. Evol. Microbiol., 50, 665, 2000. 77. Mougel, B. et al. A mathematical method for determining genome divergence and species delineation using AFLP. Int. J. Syst. Evol. Microbiol, 52, 573, 2002. 78. Mullane, N. et al. Molecular analysis of Enterobacter ­sakazakii O-antigen gene locus. Appl. Environ. Microbiol., 74, 3783, 2008. 79. Institut de Veille Sanitaire. Infections à Enterobacter sakazakii associées à la consommation d’une préparation en poudre pour nourrissons. France, octobre à décembre 2004. Rapport d’investigation, 2006.

27 Escherichia

Devendra H. Shah, Smriti Shringi, Thomas E. Besser, and Douglas R. Call Washington State University

Contents 27.1 Introduction.................................................................................................................................................................... 369 27.1.1 Occurrence and Epidemiology......................................................................................................................... 369 27.1.2 Pathogenesis and Virulence Traits.................................................................................................................... 370 27.1.3 Conventional Diagnostic Techniques................................................................................................................ 371 27.1.3.1 Culture and Isolation........................................................................................................................ 371 27.1.3.2 Latex Agglutination Test.................................................................................................................. 373 27.1.3.3 Enrichment and Immunomagnetic Separation................................................................................ 373 27.1.3.4 ELISA.............................................................................................................................................. 374 27.1.4 Molecular Diagnostic Techniques.................................................................................................................... 375 27.1.4.1 PCR.................................................................................................................................................. 375 27.1.4.2 Real-Time PCR................................................................................................................................ 377 27.1.4.3 Reverse Transcriptase PCR............................................................................................................. 380 27.1.4.4 Microarray....................................................................................................................................... 380 27.2 Methods.......................................................................................................................................................................... 381 27.2.1 Reagents and Equipment................................................................................................................................... 382 27.2.2 Sample Preparation .......................................................................................................................................... 382 27.2.3 Detection Procedure......................................................................................................................................... 382 27.3 Concluding Remarks...................................................................................................................................................... 383 Acknowledgments...................................................................................................................................................................... 383 References.................................................................................................................................................................................. 383

27.1  Introduction Escherichia coli O157:H7 (hereafter referred to as O157:H7) is an important foodborne pathogen and a causative agent of diarrhea, hemorrhagic colitis (HC) and a life threatening post-diarrheal sequela called hemolytic uremic syndrome (HUS).1,2 The genus Escherichia covers a number of Gramnegative, non-spore forming bacterial species in the family Enterobacteriaceae, of which Escherichia coli is one of the most numerous aerobic commensal species in the gastrointestinal tracts of humans and animals. While many E. coli strains are harmless, some, such as serotype O157:H7, can cause serious illnesses in humans. Clinically, HC is characterized by severe abdominal pain and bloody diarrhea. Approximately 10–15% of children below 10 years of age with HC progress to HUS, which is characterized by hemolytic anemia, thrombocytopenia, oliguria-anuria, acute renal failure and, rarely, seizures.3,4 In general, immunocompromised individuals, the very young and very elderly individuals are more susceptible to severe disease or death following O157:H7 infection. Ingestion of contaminated food and water is the major source of infection, but direct contact with infected humans or animals is also known to transmit infection to susceptible individuals.5 Serotype O157:H7 belongs to a group of diarrheagenic E. coli commonly referred as enterohemorrhagic E. coli (EHEC).

EHEC strains cause disease due to their ability to attach intimately to the intestinal mucosa and cause attaching-effacing lesions and also by their ability to produce Shiga-like toxins (Stx) that are responsible for inducing HC and HUS. Therefore, EHEC strains are also classified as subset of Stx producing E. coli (STEC) that are pathogenic to humans. While STEC is the term used for all Shiga toxin ­producing E. coli, it is not considered a defined E. coli pathovar.2 Nevertheless, the terms EHEC and STEC have been used interchangeably in the literature.

27.1.1 Occurrence and Epidemiology More than 100 serotypes of Shiga-toxin producing E. coli are associated with human infections6 and resultant illness is similar to that of O157:H7 infection.1,7 Nonetheless, O157:H7 is the most frequently isolated serotype from cases of bloody diarrhea and HUS.5 E. coli O157:H7 was first isolated in the US in 1982 during an outbreak of HC in which 47 individuals ingested contaminated hamburgers at a fast food chain in Michigan and Oregon.8 A retrospective examination of more than 3,000 isolates obtained between 1973 and 1982 revealed only one isolate of O157:H7 that was originally recovered from a 50-year-old woman who had experienced acute bloody diarrhea in 1975.8 Thereafter, sporadic cases 369

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as well as outbreaks due to O157:H7 infection have been reported increasingly in the US, UK, Europe, and other developed parts of the world.9–15 Between 1982 and 2002, a total of 350 outbreaks of O157:H7 infections were reported from 49 states in the US, representing 8,598 cases; resulting in 1,493 (17%) hospitalizations, 354 (4%) HUS cases, and a total of 40 (0.5%) deaths.5 In 2006, the Center for Disease Control FoodNet surveillance program reported 590 cases of O157:H7 infection in humans with an overall annual incidence of 1.31 cases per 100,000 people in the US.16 In the UK, the Health Protection Agency has reported that there were 70,603 food poisoning notifications in 2006. Of these, 1,003 (1.4%) were caused by O157:H7.15 The majority of outbreaks in North America are caused by typical O157:H7 isolates that can be distinguished from most of the other E. coli by their inability to rapidly (within 24 h) ferment sorbitol and by their inability to produce β-glucuronidase. There are also atypical strains that are non-motile (O157:NM) or that can rapidly ferment sorbitol and these have been associated with HUS and HC in Germany and other European countries.17,18 There has been a recent increase in the reported incidence of human infections associated with non-O157 STEC. A survey in the US found that a total of 940 non-O157 STEC were isolated from individuals with sporadic illnesses between 1982 and 2002.7 Out of 76 different serogroups isolated from these outbreaks, the most common O-antigen types included O26 (22%), O111 (16%), O103 (12%), O121 (8%), O45 (7%) and O145 (5%). In Europe, non-O157 serotypes are more commonly isolated than O157:H7.10,19–21 Recent reports from certain parts of the US (Montana, Washington, and Connecticut) show that non-O157 STEC are isolated at a frequency similar to that of O157:H7.22–24 In general, however, the relative isolation rates of non-O157 isolates vary from study to study and are influenced by geographical areas and methods employed for sampling and testing. Unlike O157:H7, the incidence, trends, and epidemiology of pathogenic non-O157 STEC are not well understood.7 It is also important to note that most strains of non-O157 STEC do not cause human illness, and some nonO157 STEC isolates recovered from diarrheal stool may not be pathogens.7,25 Moreover, pathogenic non-O157 E. coli are often biochemically indistinguishable from nonpathogenic E. coli and the identification of these bacteria requires complex biochemical, serological, and molecular testing that are not routinely performed by clinical microbiology laboratories. Contaminated food is one of the most important sources of O157:H7 infection, although contaminated water or direct contact with infected humans or animals are also reported as vehicles for transmission of infection.5 O157:H7 is ubiquitous on cattle operations in North America and has been isolated from the majority, if not all, operations studied longitudinally26,27 and estimates of point-in-time prevalence at the herd level have been as high as 63–100%.28–30 Fecal testing of cattle worldwide revealed a wide range of prevalence rates for O157:H7 in both dairy (0.2–48.8%) and beef (0.2–27.8%) cattle operations.31,32 Global assessments of contamination rates of O157:H7 in retail beef products during the last three decades showed that the prevalence of O157:H7 ranged from

Molecular Detection of Foodborne Pathogens

0.1 to 54.2% in ground beef, 0.1–44% in sausage, 1.1–36% in various retail cuts, and 0.01–43.4% in whole carcasses,25 suggesting that the high contamination rate of beef products corresponds to the wide-spread prevalence in cattle operations. A summary of O157:H7 associated outbreak investigations between 1982 and 2002 revealed that contaminated food accounted for 183 (52%) out of 350 outbreaks and 61% of 8,598 outbreak related cases, respectively, and that the contaminated beef products were reported as the primary source of infection in the majority (86 out of 183) of food related outbreaks.5 While there is a link between prevalence in cattle operations, contamination of retail beef products and subsequent infection of humans, the ecology and epidemiology of O157:H7 in cattle are complex and remain poorly understood.33–37 Although the majority of O157:H7 illnesses are related to consumption of contaminated beef, several outbreaks have been associated with other food commodities including lettuce, apple cider, salad, coleslaw, melons, sprouts, grapes, cheese, butter, and raw milk.4,5 Out of 350 outbreaks reported in the US between 1982 and 2002, direct contact with infected animals or humans and contaminated water (both recreational and drinking) were identified as a source of infection in 93 (26.5%) outbreaks, whereas the source of infection could not be traced in 116 (33%) outbreaks,5 indicating a complex ecology, and distribution O157:H7 in the environment and foods. Due to the ubiquitous nature of O157:H7, the development of portable and robust methods for its detection from different food and environmental matrices remains a challenging task. Consequently, most of the efforts in last three decades have been primarily directed towards the development of rapid and sensitive methods (both conventional and molecular) for the detection of O157:H7 from different types of foods and environment.

27.1.2  Pathogenesis and Virulence Traits O157:H7 is highly infectious for human beings with an estimated infectious dose being very low (~10–100 organisms).38 Unfortunately, there are no animal models that completely reflect O157:H7 infections in humans and thus, mechanisms of pathogenesis are not completely understood. Nevertheless, several virulence traits have been identified and their roles in the causation of disease have been elucidated. One important feature of O157:H7 infection is its ability to attach intimately to the intestinal epithelium and cause intestinal attaching and effacing (A/E) lesions. The other hallmark of O157:H7 pathogenicity is its ability to cause systemic effects via one or more Shiga-like toxins (Stx1, Stx2, and their variants). The genes encoding Stx1 and Stx2 are located on lambdoid bacteriophages that are integrated in the genome of O157:H7.39,40 Surveys have shown that the vast majority of North American O157:H7 isolates associated with HUS possess Stx2 alone or in combination with Stx1 and that only a small fraction possess Stx1 alone.41,42 Stx are composed of 5 B subunits and a single A subunit. The B subunits bind to glycophospholipid receptors (Gb3) on the surface of eukaryotic cells and the A subunit is an N-glycosidase, which inhibits protein synthesis and disrupts the large eukaryotic ribosomal subunit.43 These

Escherichia

toxins bind to and damage endothelial cells in the intestine, kidney, and brain.2,3 Although Stx1 is relatively homogeneous, two subtypes (Stx1c and Stx1d) have been described.44,45 Five subtypes of Stx2 have been identified, and these include Stx2c, Stx2d, Stx2e, Stx2f, and Stx2g.43,46 Epidemiological studies have indicated that stx2 is more associated with severe human disease than stx147 and among stx2 variants, stx2, and stx2c are frequently found in strains isolated from patients with HUS, while strains producing stx2d are usually isolated from cases of uncomplicated diarrhea.48 Typical O157:H7 strains possess other virulence factors encoded by the chromosomally located enterocyte effacement (LEE) pathogenicity island (PAI) and a large (~90 kb) virulence plasmid referred to as pO157. The LEE is integrated adjacent to either selC, pheV or pheU tRNA loci and consists of three functional modules.39,40 The first set (sepA to sepI) encode a type III secretion system (TTSS) that exports effector molecules. The second set (espA to espD) encode structural proteins of the TTSS, and the third set (eaeA and tir) encode the outer membrane adhesin, intimin, and its receptor Tir, which is translocated into the host cell plasma membrane via the TTSS apparatus.49 The LEE enables the bacteria to efficiently colonize the intestine of the host by binding between intimin, the product of eae gene, and its receptor Tir. Binding of LEE positive bacteria to the intestinal cells results in a characteristic A/E phenotype.3,50 The C′ terminus of the eaeA gene is highly variable. Based on the sequence and antigenic differences in the C′ terminus of eaeA several distinct types of intimin (α, β, γ, δ, ζ, η, θ, ι, and κ) have been identified of which γ intimin is generally produced in O157:H7 and several other non-O157 serotypes.51 In vitro studies that test adherence to cultured cells have identified a non-LEE adherence related gene, iha.52 In addition, the pO157 plasmid harbors several genes that are suspected to play a role in disease. These genes include hlyA (encoding hemolysin), katP (encoding catalase-peroxidase), espP (encoding serine protease) and toxB.3,53 The hlyA and toxB gene are present in almost all isolates of O157:H7 while the katP and espP genes can be detected in two thirds of the isolates.53 Additionally, the genome of O157:H7 contains 16 loci encoding genes involved in biosynthesis of other putative adhesins including fimbriae or pili.39,40 Currently, it is unclear how many of these are functional and necessary to induce disease. Several other (PAIs) and putative virulence associated genes have been described,54 but their role in pathogenesis of O157:H7 is not fully understood. Regardless of their functional status, these real or putative virulence-related genes provide targets for development of rapid, sensitive, and specific molecular methods for O157:H7, including assays based on PCR and various hybridization platforms.

27.1.3 Conventional Diagnostic Techniques 27.1.3.1  Culture and Isolation Conventional methods for isolation of O157:H7 include a combination of selective plating, enrichment procedures, and immunomagnetic separation (IMS) that is usually followed by confirmation via biochemical and serological

371

testing (Figure 27.1). Typical O157:H7 strains differ from most other E. coli strains in several ways. Over 95% of all E. coli strains rapidly (within 24 h) ferment sorbitol and produce β-glucuronidase, whereas typical O157:H7 strains do not ferment sorbitol within 24 h and fail to produce functional β-glucuronidase.55–58 O157:H7 strains do not ferment rhamnose on agar plates whereas 60% of nonsorbitol-fermenting E. coli strains belonging to serogroups other than O157:H7 will ferment rhamnose.59 These features have been exploited to develop sorbitol-MacConkey’s agar (SMAC) for isolation and differentiation of O157:H7 strains from several other serogroups of E. coli.56,60 The selectivity of SMAC was later improved by the addition of sub-inhibitory concentrations of cefixime (0.05 µg/ml) and 0.5% (w/v) rhamnose to make CR-SMAC agar,61 and cefixime and potassium tellurite to make CT-SMAC, agar.62 SMAC, CR-SMAC, and CT-SMAC media contain 1% sorbitol instead of 1% lactose with the standard MacConkey’s medium base. Cefixime was added to inhibit the growth of Proteus spp. and tellurite was added to inhibit the growth of Providentia, Aeromonas, Morganella, and Plesiomonas spp., which are prevalent in the feces of cattle and humans. The majority of E. coli of the fecal flora can ferment sorbitol within 24 h and yield pink colonies, whilst nonsorbitol fermenting E. coli O157 produce pale or colorless colonies on CT-SMAC agar. CT-SMAC is by far the most commonly used selective plating media for isolation of O157:H7. This system is not perfect, however, as false positives are possible from non-O157 isolates, and tellurite-sensitive and rapidly sorbitol-fermenting atypical strains of O157:H7 have been reported and thus will not be detected by these media.63 Moreover, colony characteristics of many organisms other than O157:H7, especially other sorbitol nonfermenting serogroups of E. coli, Proteus spp., Morganella spp., and Hafnia spp., appear identical to O157:H7 when grown on CT-SMAC. Several other chromogenic/fluorogenic selective media have also been developed including Rainbow agar O157 (RB O157; Biolog Inc., Hayward, CA), Biosynth culture media O157:H7 (BCM O157:H7; Biosynth Staad, Switzerland), Fluorocult O157:H7 (HC, Merck, Darmstadt, Germany), CHROMagar O157 (CHROMagar, Paris, France), and O157:H7 ID-F agar (O157 H7 ID-F; bioMerieux SA, Marcyl’Etoile, France). The efficacy of these media has been tested for the isolation and differential detection of O157:H7 from foods as well as clinical samples. RB O157 capitalizes on the inability of O157:H7 to produce β-glucuronidase. The addition of selective agents for E. coli and chromogenic substrates for β-glucuronidase and β-galactosidase allows selective detection. Most O157:H7 isolates are glucuronidase-negative and galactosidase-positive and their colonies appear as black or gray on this medium, whereas commensal E. coli strains produce β-glucuronidase and hence appear as pink colonies. Some non-O157 strains overproduce β-galactosidase relative to β-glucuronidase and produce intermediate (purple or magenta) colored colonies. One study examined 585 isolates of E. coli including typical and atypical strains of O157:H7 and several non-O157 STEC serogroups isolated from clinical

372

Molecular Detection of Foodborne Pathogens

Feces/food/environmental samples

Selective enrichment (6–24 h) Immunomagnetic separation (1–2 h)

ELISA (Stx and/or O157, H7) Direct plating on CT-SMAC and/or any other chromogenic medium (16–24 h) No O157:H7-like colonies Possible false negative Go to enrichment step

Prepare DNA for PCR (15–30 min)

Typical O157:H7 colonies

Serotyping and biochemical typing

PCR or/and microarray (2–4 h) (rfbE, fliC, stx1, stx2, eaeA, uidA, and hlyA)

rfbE+, fliC+, stx1+, stx2+, eaeA+, uidA+, and hlyA+ rfbE+, fliC+, stx1–, stx2+, eaeA+, uidA+, and hlyA+ rfbE+, fliC+, stx1+, stx2–, eaeA+, uidA+, and hlyA+ Typical or atypical O157:H7

rfbE–, fliC–, stx1±, stx2±, eaeA±, uidA–, and hlyA± Non-O157 E. coli?

rfbE+, fliC+, stx1–, stx2–, eaeA+, uidA+, and hlyA+ nonpathogenic O157:H7?

rfbE–, fliC+, stx1±, stx2±, eaeA±, uidA–, and hlyA± Other E. coli?

Proceed for molecular fingerprinting (e.g., PFGE)

Proceed for further confirmation by biochemical and serological testing

rfbE+, fliC–, stx1±, stx2±, eaeA±, uidA–, and hlyA± Other O157 E. coli?

Figure 27.1  A schematic of tiered microbiological and PCR scheme used to detect virulence factors and serotype-specific markers of O157:H7 from different sample matrices.

and environmental sources from Africa, Asia, Australia, Europe, and North America.64 This work showed that, in addition to O157:H7 isolates, several non-O157 STEC strains also produced a characteristic black colonies on RB agar and were indistinguishable from O157:H7 strains.64 Some nonO157 STEC strains produced characteristic mauve, red or pink colonies and were distinguishable from non-shiga toxin producing E. coli. In a separate study, Bettelheim65 used a collection of 585 isolates of E. coli to test the reliability of CHROMagar for the differential detection of O157:H7 and observed that although >90% of O157:H7/NM strains could be readily isolated and recognized by the characteristic pink colored colonies, several non-O157 STEC also produced similar colonies and were indistinguishable from O157:H7/ NM isolates. Reliability of a recently available ID-F agar, which contains carbohydrates, two chromogenic substrates to detect β-galactosidase and β-glucuronidase, and sodium deoxycholate to increase selectivity of Gram-negative rods, was also tested for the differential detection of O157:H7/NM strains.66 Out of 63 O157:H7/NM strains, 59 (93.7%) strains produced characteristic green colored colonies and out of the four O157:NM strains that failed to produce typical colonies, three were identified as Shiga-toxin negative. In addition, three non-O157 strains including one O55:H7 also produced

green colored colonies not distinguishable from O157:H7, whilst 284 non-O157 STEC or Shiga-toxin negative E. coli produced purple colonies and could be readily distinguished from O157:H7/NM strains.66 Recently, the performance of CHROMagar was compared with that of SMAC agar for the specific detection of O157:H7 from clinical specimens.67 A total of 3,116 stool specimens were tested, of which 27 generated culture positive results for O157:H7. CHROMagar was reported to have a higher sensitivity (96.3%) and negative predictive value (100%) than SMAC while specificity (100%) and positive predictive values (100%) were similar for both media.67 These authors also reported that the diagnostic efficiency of CHROMagar was better than SMAC due to the significant reduction in the numbers of false positive colony picks needed for further confirmation by serological and biochemical testing, thereby reducing labor and material costs.67 In another study, reliability of four chromogenic/fluorogenic media (RB, BCM, Fluorocult HC and SMAC) was evaluated for differential detection of O157:H7 from pure cultures and food samples such as ground beef and raw milk.68 Examination of 34 reference strains of O157:H7/NM showed false negative results with BCM (3%), RB (8.8%), HC, and SMAC (5.9%), whereas one out of 12 (8.3%) non-O157 E. coli strains generated false

Escherichia

positive results with BCM, RB, and SMAC, but no false positives were detected with HC agar.68 Examination of 60 food samples led to isolation of 466 Gram-negative bacteria of different genera including non-O157 E. coli, of which 57.3%, 6.2%, 3.3%, and 2.1% isolates produced false positive results on SMAC, HC, BCM, and RB agar, respectively.68 Collectively, studies of efficiency of different media for the differential detection of O157:H7 have indicated that although currently available plating media provide a valuable tool for the specific and sensitive detection of O157:H7, but the false positive as well as false negative results may be produced and therefore, further testing of the suspect colonies using conventional serological and biochemical typing is generally required for definitive identification. 27.1.3.2 Latex Agglutination Test (LAI) Confirmation of E. coli O157:H7 requires testing for the O157 somatic and H7 flagellar antigens. Several latex agglutination test (LAT) kits are commercially available. These are composed of latex particles coated with antiserum against O157 and H7 antigens for screening and detection of suspect colonies of O157:H7. Evaluation of performance of three commercial LATs for the specific detection of O157 and one LAT for the specific detection of H7 antigens revealed 100% correlation of commercial O157 kits with CDC reference antisera.69 The H7 reagent had a diagnostic sensitivity of 96% and diagnostic specificity of 100% compared with the CDC antisera.69 A study that compared four commercial LAT kits for their efficacy to detect O157 and H7 antigens revealed diagnostic sensitivities and specificities of 99–100%, respectively, for all kits.70 Nevertheless, special precautionary measures have been suggested with the use of these LAT test kits. False positive interpretations could arise if the latex controls were not routinely used or due to the cross reactivity of O157 antisera with strains of Citrobacter freundii and Salmonella O group N. Many O157:H7 strains may generate false negative reactions with H7 antisera and require several passages through motility medium for their accurate detection. In addition, atypical strains (O157:NM) will generate negative reactions due to the lack of the H7 antigen and hence require further biochemical testing. Recently developed PCR based methods for the detection of rfbE gene encoding O157 somatic antigen and fliC gene encoding H7 flagellar antigen can be used to detect both motile and non-motile strains of O157:H7 and offer a rapid, sensitive, specific, and more reliable alternative to LAT test (see below). 27.1.3.3 Enrichment and IMS Several factors influence the detection threshold of O157:H7 from clinical material, food, and cattle feces. In human patients, the recovery of O157:H7 declines from >90% during the first 6 days of illness to 33% for stools collected at a later date.71 The concentration at which E. coli O157 is shed in cattle feces varies from 102 to 105 CFU/g, but most adult cattle (61–85%) excrete less than 100 CFU of O157:H7 per gram of feces with high titers of background microflora.72–75 The numbers of O157:H7 can vary greatly from sample to

373

sample within the same fecal pat.76,77 Studies have indicated that beef products may contain as little as 0.3–15 CFU of O157:H7 per gram78,79 and certain acidic foods, such as apple cider, may contain acid injured O157:H7 that require special recovery procedures.80 Consequently, selective enrichment followed by IMS of O157:H7 is often necessary prior to plating on selective media.75,77,81-83 Several protocols have been described for isolating O157:H7 from food, environmental, and clinical matrices.84 Variables such as the type of enrichment broth (trypticase soy broth; TSB, E. coli broth; EC or buffered peptone water; BPW), the selective agents (bile salts and antibiotics such as cefixime, cefsulodine, and vancomycin), the incubation temperature (35–37ºC), and the duration of incubation period (6–24 h) may influence the sensitivity of detection from different sample matrices.85 The comparison of efficacy of different enrichment protocols used by different authors was recently reviewed by Vimont et al.;84 the general consensus is that, compared to direct plating on selective media, enrichment procedures improve detection threshold of O157:H7 by 10- to 100-fold. For instance, direct plating of cattle fecal samples on CT-SMAC was compared to enrichment in trypticase soy broth containing selective antibiotics followed by plating on CT-SMAC. In this case, enrichment increased the detection limit from 251 CFU/g by direct plating to 13–16 CFU/g by enrichment.86 IMS has greatly improved the detection sensitivity of O157:H7 from enrichment cultures of different matrices. IMS uses commercially available magnetic beads coated with antibody against E. coli O157 antigen (e.g., Dynabeads anti-E. coli O157; Dynal, Inc., Lake Success, N.Y.) for separation and concentration of O157:H7 from mixed cultures. Conventional IMS procedure consist of mixing a sample (usually enriched cultures) with antibody coated paramagnetic beads in a microcentrifuge tube. Once the target organism (O157:H7) is captured by the antibody coated beads, a magnet is applied to the sides of the tube to hold magnetic beads and the liquid sample that contains most of the background flora is removed from the tube. The beads are then washed to remove the additional background material and resuspended in a small volume of buffer followed by plating onto selective or differential media. Several studies have shown the usefulness of enrichment and IMS methods for a range of clinical, food, and environmental samples.2,3 For instance, a study that compared direct plating of bovine feces on CT-SMAC with that of enrichment and IMS procedures prior to plating on CT-SMAC showed that this combination of procedures improved the detection sensitivity of O157:H7 by 10- to 100-fold as compared to direct plating of bovine feces.75 Several modifications of the standard IMS procedure have been made, including modifications in apparatus, sample volume, bead sizes, and washing procedures.87–90 Although, conventional IMS procedures are not technically complex, the process is labor intensive and not amenable to high sample throughput. Consequently, an automated IMS method with an integrated ELISA (EiaFoss, Foss Electric A/S, Hillerod, Denmark) has also been developed that

374

allows rapid automated sample processing. The EiaFoss automatically carries out an immunomagnetic concentration of E. coli O157:H7 organisms and subsequently carries out an ELISA. Twenty-seven samples can be processed during one run, with an analysis time of about 100 min. Reinders et al.88 compared the sensitivity of an automated EiaFoss IMS procedure to that of conventional IMS for the detection of O157:H7 from milk. They reported that both methods were equally sensitive, but automated IMS provided a rapid and efficient alternative for manual IMS procedure. A recent modification of IMS procedure includes the use of an intrasolution magnetic particle separation device, called PickPen (BioNobile, Turku, Finland). The PickPen is available as the eight channel device that enables higher throughput processing of samples in 96-well format and offers a significant advantage over the single-tube IMS procedure. Nou et al.91 evaluated the usefulness of PickPen IMS for the detection of O157:H7 from enrichment cultures of cattle feces, hides, carcasses, and ground beef and compared this procedure with conventional IMS. They reported that PickPen IMS was significantly more sensitive than conventional IMS and that the PickPen IMS procedure greatly increased the throughput of IMS testing. Although enrichment and IMS procedures have improved the detection sensitivity of conventional culture procedures, these procedures are tedious and take an additional 16–24 h prior to plating onto selective media. Hence, a combination of pre-enrichment, IMS, and plating on selective media followed by screening of suspect O157:H7 colonies by conventional biochemical and serological testing may take several days (about a week) before the confirmatory detection of O157:H7 can be achieved. Recent studies have shown that the alternative approaches that combine molecular techniques such as PCR and microarrays with that of selective enrichment and IMS procedures can reduce the time required for confirmatory detection of O157:H7, and can also improve the detection sensitivity and specificity. 27.1.3.4 ELISA During the last two decades, several immunological methods (e.g., ELISA/EIA, colony blot, passive agglutination assays) have been developed for the detection of O157:H7 from multiple sample matrices. A number of these immunological assays are now available as commercial “ready to use test kits” for routine testing in clinical as well as food microbiological laboratory settings. These tests detect either the presence of Shiga toxins in stool samples and culture supernatants or detect bacterial antigens such as O157 and H7 from stools, food, and environmental samples. A commercially available Premier EHEC (Meridian Bioscience, Inc., Cincinnati, OH) ELISA is designed to detect Stx1 and Stx2 from diarrheal stool specimens or broth cultures of clinical isolates. This is a rapid 96-microwell enzyme immunoassay that uses monoclonal anti-Shiga toxin antibody absorbed to microwells. Addition of supernatant solution from test samples to the microwells permits binding of Stx to the monoclonal antibodies. This step is followed

Molecular Detection of Foodborne Pathogens

by the addition of an enzyme conjugated anti-Stx polyclonal antibody and a substrate for the colorimetric detection of Stx toxin. The Premier EHEC test has been evaluated by several researchers for the detection of Shiga toxins produced by E. coli including O157:H7 from clinical specimens.92–99 Most of these studies reported good sensitivity and specificity of the test, although one limitation at the microbial community level is that it is not possible to link presence of Stx toxin to any strain or serovar. Thus, this test at best provides rapid tool for screening of clinical specimens for the presence of Stx producing E. coli (including O157:H7) and further confirmation of O157:H7 by microbiological testing is often required. Although Premier EHEC test is a good presumptive test for Stx producing E. coli from clinical stool specimens, Hyatt et al.100 evaluated its performance on bovine feces and reported that this test had a poor sensitivity for detection of O157:H7 from these samples. It has also been reported that this test can produce false positive results with Pseudomonas aeruginosa isolates101 and may require overnight incubation of some strains to detect these toxins.102 The ability of Premier EHEC test to detect variants of Shiga toxins other than Stx1, Stx2, and Stx2c has not been explored. Another commercially available test is ProspecT Shiga toxin (STEC) microplate assay (Lexon-Trend, REMEL, Lenexa, KS). This assay is similar to the Premier EHEC except that the microtiter wells are coated with a polyclonal anti-Stx1 and Stx2 antibody and the secondary antibody is a horse radish peroxidase conjugated monoclonal anti-Stx1 and Stx2 antibody. Gavin et al.103 evaluated the performance of ProspecT assay for the detection of Shiga toxin producing E. coli in stool samples and reported that this assay was 100% sensitive and specific for detection of E. coli O157 in stools compared with SMAC. In addition, the ProspecT assay detected twice as many STEC as SMAC. This test has not been validated for detection of all known variants of Stx1 and Stx2. The Ridascreen assay (R-biopharm, Darmstadt, Germany) is also commercially available for detection of Stx toxins produced by STEC isolated from various sources. Bonardi et al.104 compared the performance of Ridascreen assay with that of vero cell test, PCR, and EIA ELISA using 34 strains of O157:H7 strains isolated from bovine feces and carcasses. These authors reported that Ridascreen assay was as sensitive as PCR, with less time required and simpler execution. This assay was also used successfully to investigate a multistate outbreak of E. coli O26:H11 in Germany.105 Recently, the Ridascreen assay was reported to detect strains producing Stx1 and variants Stx1c and Stx1d, as well as Stx2 and variants Stx2d1, Stx2d2, Stx2e, Stx2d, Stx2-O118 (Stx2d-ount), Stx2-NV206, Stx2f, and Stx2g.106 This assay showed a relative sensitivity of 95.7% and a relative specificity of 98.7%. Some of the Stx2-O118, Stx2e, and Stx2g producing STEC were not detected. Although the above immunoassays are not specific for the detection of O157:H7, they provide a straightforward approach for the presumptive identification of virtually all Shiga toxin producing E. coli (including O157:H7) in clinical samples. From a clinical perspective, administration of potentially deleterious

375

Escherichia

antimicrobial or antimotility treatments would be avoided due to the rapid detection of STEC in patients suffering from HC and HUS.107 Rapid immunological assays for the detection of O157 and/or H7 antigens have also been developed. One such assay is O157 ELISA (LMD Laboratories, Inc., Carlsbad, CA) that uses microwell test strips coated with anti-E. coli O157 polyclonal antibody to detect O157 antigen from clinical samples. Dylla et al.108 and Park et al.109,110 compared this O157 ELISA assay with culture for the detection of E. coli O157:H7 from human stool samples and reported that, as compared to SMAC plating, this assay was a highly sensitive and specific method for screening stool samples for O157:H7 and required 5 × 103/gb

Pure culture

TSB (37ºC/ OD600=0.8)

Boiling

4 × 103/ml

Ground beef

mTSBn100, c10, v8, cf0.05 (37ºC/6 h)

QIAamp tissue kit (Qiagen) or DNA-ER solution (Perkin-Elmer)

≥104/gc

Pure culture

mTSBn100, c10, v8, cf0.05 (37ºC/4–8 h) or (followed by IMS) mECn20 (37ºC/4–8 h)   or (followed by IMS)

Sample

Beef

mTSBn20 (37ºC/6 h)

Cattle feces Pure culture

mTSBn20 (37ºC/6 h) TSB (37ºC/18 h)

Reference 148

150

≥103/ml or (102/ml)c

≥103/ml or (102/ml)c InstaMatrix (BioRad)+boiling

3/gb

151

1.2/gb 2 × 104/ml

Multiplex SYBR Green I assay

stx1 and stx2

Pure culture

NA

DNeasy mini kit (Qiagen)

1 cfu

193

Molecular beacon assay

rfbE

Apple juice

mECn20 (37ºC/11 h)

InstaMatrix (BioRad)+boiling

1/mlb

155

Milk Pure culture

mECn20 (37ºC/6h) mEC (37ºC/overnight)

Pure culture

NA

Human feces

None

Feces

mTSB (37ºC/16 h)

Ground beef Pure culture

mTSB (37ºC/16 h) mTSB (37ºC/16 h)

Feces

mTSB (37ºC/16 h)

Ground beef

mTSB (37ºC/16 h)

Soil

mLBc10, v8, cf0.05 (37ºC/16 h)

Soil, feces, and waste water

None

Multiplex molecular beacon assay

Fluorogenic TaqMan assay

Multiplex TaqMan assay

Multiplex assay

stx1 and stx2

eaeA

stx1 and stx2

eaeA, stx1, and stx2

1/mlb 5 × 103/ml ID-DNA extraction kit (Infectio Diagnostics, Canada)

10–50 cfu

147

105/gb Lysis+boiling+Qia Quick PCR purification kit (Qiagen)

15/gb

194

1.5/gb 103/ml Lysis+boiling+QIA Quick PCR purification kit (Qiagen)

1.2–12/gb

1.2/gb UltraClean soil, fecal, and water DNA kits (MO BIO, Inc., Solana Beach, CA)

1–10/gb

156

≥3.5 × 104/gb

Multiplex fluorogenic assay

stx1 and stx2

Pure culture

NA

Lysis+boiling

5 × 102 cfu

149

Multiplex assay

eaeA and hlyA

Pure culture

NA

Lysis+boiling

5 × 102 cfu

149

Multiplex TaqMan assay

eaeA, stx1, and stx2

Cattle feces

GN+TSB (37ºC/16 h)

Lysis+boiling+Qia Quick PCR purification kit (Qiagen)

2.5–25/gb

157

103/ml

Pure culture Fluorogenic assay

eaeA

Groung beef

IMS without enrichment

Lysis+heating

1.3 × 104/gb

152

Multiplex TaqMan assay

rfbE and stx2

Feces and apple juice

None

Boiling+QIAamp stool kit (Qiagen)

104 cfub

195 (Continued)

379

Escherichia

Table 27.1  (Continued) Real-Time PCR

Target Gene

Sample

Growth/Enrichment Conditionsa

Beef and milk Milk Apple juice Pure culture

None TSB (37ºC/4 h) TSB (37ºC/10 h) TSB

DNA Preparation Method

Detection Limit (cfu)

Reference

103 cfub 10/mlb 10/mlb 103/ml

Fluorogenic TaqMan assay

eaeA

Sandy loam soil

None

FastPrep FP120 bead beating system (Bio-101, Vista, CA) followed by PCI

1.3 × 105/gb

153

Fluorogenic assay

eaeA

Ground meat

Two step enrichment in TSB (37ºC/2 h followed by 37ºC/3 h)

Membrane capture+PrepMan Ultra reagent (Applied biosystems, CA)

102/25gb

154

Fluorogenic TaqMan assay

eaeA/stx1/ stx2

Dairy wastewater

LB (37ºC/24 h)

AquaPure genomic DNA kit (Bio-Rad)

104/ml

158

a

b c

IMS, immunomagnetic separation; PCI, phenol chloroform isoamylalcohol; GN+TSB, Gram negative+trypticase soy broth; mEB, modified E. coli broth; mTSB, modified trypticase soy broth; mLB, modified luria broth; None, no growth or enrichment; NA, not applicable; v, vancomycin; c, cefsulodin; cf, cefixime; n, novobiocin; the numbers indicate concentration of each antibiotic (mg/ml). Detection limit is the actual numbers of bacteria present in the samples (either artificially spiked or natural sample) prior to enrichment. Detection limit is the actual numbers of bacteria present in the final enrichment sample.

result that quencher and reporter dye are no longer in close proximity of each other leading to emission of fluorescence. The use of MB in R-PCR offers supplementary level of specificity in which no increase in fluorescence is observed even with the presence of target strand that contains only a single nucleotide mismatch146. Most of the R-PCR assays that have been developed for the identification of O157:H7 are based on the detection of genes encoding Stx toxins,147–149 intimin,150–154 and O-antigen.155 These R-PCR assays offer the opportunity to quantify the absolute and relative amounts of O157:H7 in complex sample matrices (Table 27.1). Most of these assays target single genes, however, and therefore lack diagnostic specificity by themselves, which could lead to problems of cross reactivity (false positives) with other closely related organisms. For instance, R-PCR assays that target stx genes may cross react with other non-O157 STEC and fail to discriminate between O157:H7 and other E. coli. Some published reports have shown that the specificity and sensitivity of R-PCR assays can be improved by using a combination of two or more primer sets (multiplex-R-PCR assay) in one reaction156–158 although in practice is it not possible to multiplex more than four markers due to the limits of overlapping excitation of emission spectra of available fluorphores. Furthermore, several factors such as the initial numbers of O157:H7 in the sample, the type and volume of sample, presence of nontarget background microflora, PCR inhibitors and protocols used for the template DNA preparation may have significant influence on the sensitivity of the R-PCR assays used for the detection of O157:H7. As a result, the detection sensitivities of several published R-PCR assays for unenriched foods, feces, and environmental samples has been reported to be very low (>103–105 CFU; Table 27.1).

PCR inhibition is a common problem with DNA isolated from food, environmental, and clinical samples because of presence of substances such as heme in blood and meat samples and heavy metals and complex humic acids and fulvic substances in feces and soils, and polyphenolic compounds in acidic foods such as apple cider.155,159–164 Inhibitors can also squelch fluorescent signal from fluorophores used in these assays.165 The problems of PCR inhibitors can be partially dealt with further cleanup of DNA extracts and by spiking samples with internal PCR amplification controls such as those encoding green fluorescent protein (gfp) or targeting other sequences not present in O157:H7.147,166 Detection sensitivities of most R-PCR applications depend not only on the efficiency of nucleic acid extraction method, but can be improved by enrichment procedures that also increase likelihood of detection of viable cells. The enrichment step not only increases template numbers, but has the effect of diluting inhibitory substances. As with conventional PCR, the length of enrichment affects the detection sensitivity of R-PCR assays. Fortin et al.155 reported that when combined with selective enrichment step, R-PCR assay could detect as few as 1 CFU of O157:H7 organisms per ml in raw milk after 6 h of enrichment whereas for apple juice samples, the sensitivity of detection was much lower and a minimum of 11 h of enrichment was needed to achieve the same detection levels in raw milk. Similar results were obtained by Hu et al.136 who reported the sensitivity of the R-PCR assay to be 10 CFU/ml for milk samples and apple cider enriched for 4 h and 10 h, respectively. Sharma et al.151 reported that the sensitivity of R-PCR assay to detect O157:H7 from enriched cultures of beef samples was adversely affected by both the length of enrichment and the presence of non-target background microflora. They found that the detection sensitivity of

380

R-PCR assay improved from 3 × 103 CFU/ml in 2 h enriched cultures to 3 CFU/ml when cultures were enriched for 6–18 h prior to PCR analysis even when beef samples harbored 103 CFU/ml of background flora. When background flora increased to 108 CFU/ml, the detection sensitivity of R-PCR assay was reduced by 100-fold. 27.1.4.3 Reverse Transcriptase PCR Reverse transcriptase (RT)-based assays have been developed for the detection of viable O157:H7 in foods and environmental samples. Conventional PCR and R-PCR assays rely upon a DNA template for amplification. This DNA can, theoretically, persist in the sample even after cell death thereby leading to positive detection of nonviable cells.167 This could be a significant disadvantage and could be construed as false detection events because nonviable bacteria present no health risks.168 Thus, detection of O157:H7 from food and environmental samples by conventional or R-PCR is generally followed by isolation and confirmatory identification of the pathogen with conventional procedures. An alternative approach relies on RT to convert mRNA templates to cDNA for subsequent PCR amplification. mRNA is present only in actively growing cells and unlike DNA, mRNA tends to degrade rapidly (half-life of mRNA varies from 40 s to 20 min) in dead cells, thus allowing detection of only viable cells in a sample.169 Yaron and Matthews168 tested the utility of RT-PCR for detecting several genes (rfbE, fliC, stx1, stx2, mobA, eaeA, hlyC, hlyA, and 16S rRNA) as an indicator of viability of O157:H7. They found that 16S rRNA, and mRNA of rfbE, stx1, and hly were detected in cells harvested during all growth phases whereas other mRNAs including stx2 were variable in different growth phases. The authors suggested that rfbE and stx1 mRNAs were more suitable targets for detecting both viable as well as nonculturable cells because these mRNAs were more stable in the viable cells, while having a very short half-life in the heat killed cells. They also reported that at least 107 CFU of O157:H7 are required if the RT-PCR is to be used to detect viable cells without enrichment, and that the conventional PCR was more sensitive than RT-PCR. McIngvale et al.170 showed that the ability of RT-PCR to detect stx2 mRNA from viable O157:H7 cells was influenced by growth conditions with the best detection of stx2 mRNA found with late log- and early stationaryphase cells incubated at 37ºC compared with cells incubated at 32ºC. They also reported that with an initial inoculum of 1 CFU/g of beef samples, detection of stx2 mRNA was possible after 12 h of enrichment. RNA extraction from heat killed cells produced no bands from RT-PCR, while PCR of stx2 DNA consistently produced bands following cell death. While the RT-PCR assays targeting rfbE,168 stx2170 or a combination of stx1 and stx2171 are suitable for the rapid and sensitive detection of viable O157:H7 cells, these assays can produce false positive results for those E. coli strains that harbor either stx1 or stx2 or that possess O157-type O antigen. As a result, Sharma et al.172 developed a RT-realtime multiplex RT-PCR assay (rRT-mPCR) targeting mRNA encoded by rfbE and eaeA genes for the specific detection of

Molecular Detection of Foodborne Pathogens

O157:H7 in a single step. This assay allowed specific detection of O157:H7 at a concentration of as low as 1 CFU/g of bovine feces (initial inoculum) using RNA prepared from 5 h enrichment cultures of artificially seeded bovine feces. The only pitfall of this assay was that it did not include the stx1 and stx2 alleles and therefore would require further confirmation. Another rRT-mPCR assay was designed to detect and identify O157:H7 using three combinations of primers and probes targeting eaeA, rfbE, and stx2 mRNAs.173 Although this assay did not include primers to amplify stx1 mRNA, these authors reported that rRT-mPCR assay was effective in differentiating E. coli O157:H7, non-O157 STEC and non-E. coli pathogens from 100 strains isolated from clinical patients and the environment. They also reported that the sensitivity of rRT-mPCR for detection of O157:H7 from various foods (milk, alfalfa sprots, and ground beef), feces and pure cultures without enrichment or prior treatment ranged from 103 to 106 CFU. When combined with enrichment and IMS procedure, the assay could detect as few as 10 CFU/ ml (initial inoculum) of O157:H7 from pure culture, foods, and stool. Finally, a sensitive RT-PCR method for specific detection of viable O157:H7 cells, including viable but nonculturable (VBNC) cells, in water samples was developed by Liu et al.174 The VNBC cells were generated through starvation of O157:H7 in deionized water and confirmed by culture and viability staining using Live/Dead BacLight bacterium viability kit (Molecular Probes, Europe, Leiden, The Netherlands). This method involved capture of the bacterial cells on a low-protein-binding membrane and direct extraction and purification of RNA followed by RT-PCR and electronic microarray detection of rfbE and fliC from O157:H7. This assay was reported to detect as few as 1 CFU of O157:H7 in diluted cultures, 3 to 4 CFU/liter in tap water, 7 CFU/liter in river water, and 50 VBNC cells in 1 liter of river water, demonstrating the best limit of detection reported to date for VBNC cells in environmental water samples. The success of RT-PCR requires that the target mRNA molecule has a short half-life and that the target mRNA is constitutively expressed in viable cells, including healthy, dormant, injured or otherwise nonculturable cells. Furthermore, the expression of bacterial virulence factors is often influenced by various environmental and stress conditions that organisms may encounter in different food matrices and environments. For instance Stx production has been shown to be reduced with reduced aeration and reduced growth temperature (32ºC).170,175 Therefore, to use RT-PCR as a means of specifically identifying bacteria, care must be taken to ensure abundant and dependable expression of target mRNA. 27.1.4.4  Microarray Nucleic acid microarrays have also been employed for detection and genotyping of bacterial pathogens.176,177 Microarrays are well known for their application in the whole genome expression profiling of bacterial pathogens and several reviews of gene expression studies have been published.178–180 From food safety perspective, microarrays can also be used for bacterial gene identification as well as pathogen

381

Escherichia

surveillance.165,181–185 For these applications, labeled nucleic acid targets (PCR products, genomic DNA, rRNA, etc.) are hybridized to a microarray chip whereupon target:probe duplexes are typically detected using some type of direct or indirect fluorescent signal system. The relative signal from each probe (also called a spot or feature) is detected and quantified by using a confocal laser or filtered light scanner. In this way, the presence or absence of specific gene can be detected. The major advantage of the microarray assay over agarose gel analysis of the PCR products is that microarray do not rely on the length of the PCR products for identification, but require that the internal sequences of the target genes to be complementary to the probes spotted onto the chip. Such hybridization methods are generally sensitive to sequences mismatches >10% from the target sequence depending on the type of probe and position of the mismatch sequences. While microarrays are commonly coupled with m-PCR assays, there are situations where they can be used independent of target amplification and thereby avoid limitations in the number of genes that can be detected. Furthermore, when used to detect sequence polymorphisms in sequences that are “universally” present (e.g., 16S rDNA), microarrays can simultaneously distinguish between many different bacterial pathogens.186,187 As a proof of concept Chizhikov et al.183 constructed a microarray chip to detect six virulence genes common to Shigella spp., O157:H7 and enterovirulent E. coli. The presence or absence pattern of the six virulence genes (eaeA, stx1, stx2, fliC, rfbE, and ipaH) was used to test unidentified isolates. Fluorescent dyes were directly incorporated into products via m-PCR assay and hybridized to 25 bp single-stranded oligonucleotides spotted on a glass slide. The authors reported that the assay was relatively fast, flexible, and more reliable for detecting genetic markers as compared with m-PCR alone.183 Jin et al.184 designed a multi-pathogen detection microarray by incorporating multiple genes for the simultaneous detection of O157:H7 (stx1, stx2, and uidA genes) and Vibrio cholerae (ctxA, tcpA, and LPSgt genes) isolates. Using a recombinant plasmid and target pathogens, they reported bench top analytical sensitivities of 102 copies and 103 CFU/ml per reaction, respectively. For the samples with fewer O157:H7, culture enrichment prior was required to avoid false negatives. Call et al.181 designed a nucleic acid microarray composed of 25–30-mer oligonucleotide probes complementary to four target gene sequences (eaeA, stx1, stx2, and hlyA). Target DNA was amplified by m-PCR using biotinylated primers and PCR products were hybridized to the array without further modification or purification. When coupled with enzymatic amplification the array was reportedly 32-fold more sensitive than gel electrophoresis and the benchtop analytical sensitivity of the assay was