Detecting Pathogens in Food

Detecting pathogens in food Related titles from Woodhead’s food science, technology and nutrition list: Microbiologic...

Author: McMeekin

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Detecting pathogens in food

Related titles from Woodhead’s food science, technology and nutrition list: Microbiological risk assessment in food processing (ISBN: 1 85573 585 7) Microbiological risk assessment is one of the most important recent developments in improving food safety management. Edited by two leading authorities in the field, and with a distinguished international team of experts, this book reviews the key stages and issues in MRA. Foodborne pathogens (ISBN: 1 85573 454 0) As trends in foodborne disease continue to rise, the effective identification and control of pathogens becomes ever more important for the food industry. With its distinguished international team of contributors, Foodborne pathogens provides an authoritative and practical guide to effective control measures and how they can be applied in practice to individual pathogens. Hygiene in food processing (ISBN: 1 85573 466 4) Drawing on the expertise of the prestigious European Hygiene Equipment Design Group (EHEDG) and other experts in the field, this major new collection promises to be the standard work on good hygiene practice in food processing. The coverage is truly comprehensive and includes hygiene regulation and legislation for both Europe and the USA. It opens with an examination of the general principles of hygiene, moves on to cover plant design and construction as well as hygiene management principles and methods. It will be an invaluable guide for all food processors.

Details of these books and a complete list of Woodhead’s food science, technology and nutrition titles can be obtained by: • visiting our web site at www.woodhead-publishing.com • contacting Customer Services (email: [email protected]; fax: +44 (0) 1223 893694; tel.: +44 (0) 1223 891358 ext. 30; address: Woodhead Publishing Limited, Abington Hall, Abington, Cambridge CB1 6AH, England) If you would like to receive information on forthcoming titles in this area, please send your address details to: Francis Dodds (address, tel. and fax as above; e-mail: [email protected]). Please confirm which subject areas you are interested in.

Detecting pathogens in food Edited by Thomas A. McMeekin

Published by Woodhead Publishing Limited Abington Hall, Abington Cambridge CB1 6AH England www.woodhead-publishing.com Published in North America by CRC Press LLC 2000 Corporate Blvd, NW Boca Raton FL 33431 USA First published 2003, Woodhead Publishing Limited and CRC Press LLC ß 2003, Woodhead Publishing Limited The authors have asserted their moral rights. This book contains information obtained from authentic and highly regarded sources. Reprinted material is quoted with permission, and sources are indicated. Reasonable efforts have been made to publish reliable data and information, but the authors and the publishers cannot assume responsibility for the validity of all materials. Neither the authors nor the publishers, nor anyone else associated with this publication, shall be liable for any loss, damage or liability directly or indirectly caused or alleged to be caused by this book. Neither this book nor any part may be reproduced or transmitted in any form or by any means, electronic or mechanical, including photocopying, microfilming and recording, or by any information storage or retrieval system, without permission in writing from the publishers. The consent of Woodhead Publishing Limited and CRC Press LLC does not extend to copying for general distribution, for promotion, for creating new works, or for resale. Specific permission must be obtained in writing from Woodhead Publishing Limited or CRC Press LLC for such copying. Trademark notice: Product or corporate names may be trademarks or registered trademarks, and are used only for identification and explanation, without intent to infringe. British Library Cataloguing in Publication Data A catalogue record for this book is available from the British Library. Library of Congress Cataloging-in-Publication Data A catalog record for this book is available from the Library of Congress. Woodhead Publishing Limited ISBN 1 85573 670 5 (book); 1 85573 704 3 (e-book) CRC Press ISBN 0-8493-1756-8 CRC Press order number: WP1756 Cover design by The ColourStudio Project managed by Macfarlane Production Services, Markyate, Hertfordshire (e-mail: [email protected]) Typeset by MHL Typesetting Limited, Coventry, Warwickshire Printed by TJ International Limited, Padstow, Cornwall, England

Contents

Contributor contact details . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

xi

Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . T. McMeekin, University of Tasmania

xv

Part I General issues . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

1

1

2

Microbiological analysis and food safety management: GMP and HACCP systems . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . C. de W. Blackburn, Unilever R&D Colworth, UK 1.1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1.2 Food safety management systems . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1.3 Types of testing used in GMP and HACCP systems . . . . . . . . . 1.4 Microbiological analysis and GMP systems . . . . . . . . . . . . . . . . . . 1.5 Microbiological analysis and HACCP systems . . . . . . . . . . . . . . . 1.6 Future trends . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1.7 Sources of further information and advice . . . . . . . . . . . . . . . . . . . 1.8 References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Sampling techniques . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . D. Legan and M. H. Vandeven, Kraft Foods North America, USA 2.1 Introduction: common definitions . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2.2 The purpose of sampling . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2.3 Sampling and the problem of pathogen distribution . . . . . . . . . . 2.4 Acceptance sampling when the history of the material is not known . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

3 3 4 5 7 11 16 17 17 20 20 23 24 28

vi

Contents 2.5 2.6 2.7 2.8 2.9 2.10 2.11 2.12

3

4

5

Acceptance sampling when the history of the material is known . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Environmental sampling and tightened inspection/skip lot sampling . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Taking samples . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Maximizing the value of test results . . . . . . . . . . . . . . . . . . . . . . . . . Future trends . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Sources of further information and advice . . . . . . . . . . . . . . . . . . . Acknowledgements . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

Separation and concentration of samples . . . . . . . . . . . . . . . . . . . . . . . A. Sharpe, Filtaflex Limited, Canada 3.1 Introduction: the need for separation and concentration . . . . . . 3.2 General approaches to removal, separation and detection . . . . 3.3 ‘Primary’ microbial removal methods . . . . . . . . . . . . . . . . . . . . . . . . 3.4 Separation and concentration of cells once they have . . . . . . . . been removed . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3.5 Future trends . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3.6 References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Validating detection techniques . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . J. Debevere and M. Uyttendaele, University of Ghent, Belgium 4.1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4.2 Definition of performance characteristics . . . . . . . . . . . . . . . . . . . . 4.3 Validation protocols . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4.4 The application of validation schemes: immunological methods . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4.5 The application of validation schemes: molecular methods . . 4.6 The use of validated methods in accredited laboratories . . . . . 4.7 Future trends . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4.8 Sources of further information and advice . . . . . . . . . . . . . . . . . . . 4.9 References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Quality assurance of laboratory performance . . . . . . . . . . . . . . . . . . R. Wood, Food Standards Agency, UK and J. E. L. Corry, University of Bristol, UK 5.1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5.2 Legislation and codes of practice . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5.3 Legislation in the EU . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5.4 The Codex Alimentarius Commission . . . . . . . . . . . . . . . . . . . . . . . . 5.5 The UK Food Standards Agency . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5.6 Quality assurance requirements: accreditation . . . . . . . . . . . . . . . . 5.7 Internal quality control (IQC) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5.8 Proficiency testing . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

33 41 43 45 48 48 49 49 52 52 53 55 59 62 64 69 69 70 75 81 84 86 88 89 90 93

93 94 95 97 98 99 100 104

Contents 5.9 5.10 5.11 5.12 5.13 5.14 5.15

vii

Quality assurance requirements: analytical methods . . . . . . . . . Criteria for valid methods of analysis . . . . . . . . . . . . . . . . . . . . . . . . Method validation through proficiency testing . . . . . . . . . . . . . . . Measurement uncertainty for the microbiologist . . . . . . . . . . . . . Future trends . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Appendix: The ISO/IUPAC/AOAC International Harmonised Protocol for Proficiency Testing of Analytical Laboratories . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

115

Part II Particular techniques . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

121

6

7

8

Culture methods . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . P. Stephens, Oxoid Ltd, UK 6.1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6.2 Culture medium design . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6.3 Culture method design . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6.4 Examples of qualitative methods . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6.5 Examples of commercial kits . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6.6 Future trends . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6.7 Further reading . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6.8 References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Electrical methods . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . D. M. Gibson, BIODON International, UK 7.1 Introduction: principles . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7.2 Instruments . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7.3 Data presentation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7.4 Pathogen assays: introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7.5 Assays for Salmonella . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7.6 Assays for Enterobactericeae, Escherichia coli and coliforms . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7.7 Assays for other pathogens . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7.8 Accreditation of electrical methods . . . . . . . . . . . . . . . . . . . . . . . . . . 7.9 Conclusion and future trends . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7.10 References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

ATP bioluminescence . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . M. Griffiths and L. Brovko, Canadian Research Institute for Food Safety 8.1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 8.2 Principles of ATP bioluminescent assay . . . . . . . . . . . . . . . . . . . . . 8.3 Assay for testing the total bacterial count of food products . . 8.4 The use of assays for particular foods . . . . . . . . . . . . . . . . . . . . . . . 8.5 The use of assays for hygiene monitoring . . . . . . . . . . . . . . . . . . .

106 110 112 112 113 113

123 123 123 129 133 137 140 141 142 147 147 149 150 151 152 156 159 161 162 162 165

165 165 167 168 171

viii

Contents 8.6 8.7 8.8

9

10

11

12

The use of assays to detect particular pathogens . . . . . . . . . . . . . Instrumentation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

174 178 180

Microscopy techniques: DEFT and flow cytometry . . . . . . . . . . . . . R. Raybourne and M. Tortorello, US Food and Drug Administration 9.1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 9.2 Stains, fluorochromes and probes . . . . . . . . . . . . . . . . . . . . . . . . . . . . 9.3 Microscopy . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 9.4 The direct epifluorescent filter technique (DEFT) . . . . . . . . . . . . 9.5 Flow cytometry . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 9.6 Comparing detection techniques and future trends . . . . . . . . . . . 9.7 Sources of further information and advice . . . . . . . . . . . . . . . . . . . 9.8 References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

186

Immunological techniques: immunochromatography, enzyme linked immunofluorescent assays and agglutination techniques . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . C. L. Baylis, Campden and Chorleywood Food Research Association, UK 10.1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 10.2 Immunochromatography: lateral flow devices . . . . . . . . . . . . . . . . 10.3 Enzyme linked fluorescent assays (ELFA) . . . . . . . . . . . . . . . . . . . 10.4 Agglutination tests . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 10.5 Future trends . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 10.6 Sources of further information and advice . . . . . . . . . . . . . . . . . . . 10.7 References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Immunological techniques: ELISA . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . J. McCarthy, Unilever R&D Colworth, UK 11.1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 11.2 The basic principles of an ELISA . . . . . . . . . . . . . . . . . . . . . . . . . . . . 11.3 ELISA formats . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 11.4 Commercially-available ELISAs . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 11.5 Advantages and disadvantages in using ELISAs . . . . . . . . . . . . . 11.6 Future trends . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 11.7 References and further reading . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Appendix Manufacturers of ELISA kits . . . . . . . . . . . . . . . . . . . . . . . . . . . Genetic techniques: PCR, NASBA, hybridisation and microarrays . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . K. Sanderson and D. Nichols, University of Tasmania, Australia 12.1 Introduction: the polymerase chain reaction (PCR) . . . . . . . . . . 12.2 Nucleic acid sequence-based amplification (NASBA), . . . . . . . hybridisation and microarrays . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 12.3 Key principles . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

186 188 192 196 199 209 210 211

217 217 220 225 228 235 236 237 241 241 242 243 245 252 254 256 258

259 259 261 262

Contents 12.4 12.5 12.6 12.7 12.8 13

14

ix

Applications for particular pathogens and foods . . . . . . . . . . . . . Advantages and disadvantages . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Examples of commercial kits . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Future trends . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

263 265 267 268 268

Genetic techniques: molecular subtyping methods . . . . . . . . . . . . . . C. Fitzgerald and B. Swaminathan, Centers for Disease Control and Prevention, USA and A. Sails, Newcastle General Hospital, UK 13.1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 13.2 Approaches to molecular subtyping . . . . . . . . . . . . . . . . . . . . . . . . . . 13.3 PCR-based techniques . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 13.4 AFLP analysis and emerging methods . . . . . . . . . . . . . . . . . . . . . . . 13.5 Standardized molecular subtyping of pathogens . . . . . . . . . . . . . . 13.6 Interpreting molecular subtyping data . . . . . . . . . . . . . . . . . . . . . . . . 13.7 The future of molecular subtyping . . . . . . . . . . . . . . . . . . . . . . . . . . . 13.8 Sources of further information and advice . . . . . . . . . . . . . . . . . . . 13.9 References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

271

New biosensors for microbiological analysis of food . . . . . . . . . . . . G. Volpe and G. Palleschi, University of Rome, Italy and A. Turner, Cranfield University, UK 14.1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 14.2 Transducers used in biosensors and immunosensors . . . . . . . . . 14.3 Biosensors used to detect Salmonella . . . . . . . . . . . . . . . . . . . . . . . . 14.4 Biosensors used to detect Staphylococcus aureus . . . . . . . . . . . . 14.5 Biosensors used to detect Escherichia coli . . . . . . . . . . . . . . . . . . . 14.6 Biosensors used to detect algal toxins and aflatoxin . . . . . . . . . 14.7 DNA biosensors . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 14.8 Detecting microbial spoilage . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 14.9 Future trends . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 14.10 References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

15 The use of applied systematics to identify foodborne pathogens M. Uyttendaele and J. Debevere, Ghent University, Belgium 15.1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 15.2 Identification based on morphological, physiological . . . . . . . . and biochemical characteristics . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 15.3 Identification based on chemotaxonomy . . . . . . . . . . . . . . . . . . . . . 15.4 Identification based on genetic information . . . . . . . . . . . . . . . . . . 15.5 Applications: identifying the genus Aeromonas . . . . . . . . . . . . . . 15.6 Applications: identifying the genus Bacillus . . . . . . . . . . . . . . . . . 15.7 Applications: identifying the genus Campylobacter . . . . . . . . . . 15.8 Detecting virulence factors in foodborne pathogenic bacteria 15.9 Future trends . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

271 273 278 281 285 287 290 291 292 294

294 296 304 311 312 318 323 325 326 326 332 332 333 338 342 346 347 350 351 353

x

Contents 15.10 Sources of further information and advice . . . . . . . . . . . . . . . . . . . 15.11 Acknowledgements . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 15.12 References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

354 355 355

Index . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

360

Contributor contact details

Chapter 1 Dr C. de W. Blackburn Unilever R&D Colworth Colworth House Sharnbrook Bedfordshire MK44 1LQ UK

Dr M. H. Vandeven Kraft Foods North America 200 DeForest Avenue East Hanover New Jersey 07936 USA E-mail: [email protected]

Tel. +44 (0) 1234 222943 E-mail: [email protected]

Chapter 3 Chapter 2 Dr J. D. Legan Kraft Foods R&D Center 801 Waukegan Road Glenview IL 60025 USA E-mail: [email protected]

Dr A. Sharpe FILTAFLEX Ltd PO Box 1224 Almonte Ontario K0A 1A0 Canada Tel: +1 613 256 3066 Fax: +1 613 256 8681 E-mail: [email protected]

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Contributors

Chapters 4 and 15

Chapter 6

Dr M. Uyttendaele and Professor J. Debevere Lab of Food Microbiology and Food Preservation University of Ghent Coupure Links 653 9000 Gent Belgium

Dr P. Stephens R&D Manager Oxoid Ltd. Wade Road Basingstoke UK

E-mail: [email protected]

Tel: +44 1256 694277 Fax: +44 1256 463388 E-mail: [email protected]

Chapter 5

Chapter 7

Dr R. Wood Food Standards Agency c/o Institute of Food Research Norwich Research Park Colney Norwich NR4 7UA UK

Donald M. Gibson BIODON International 43 Brighton Place Aberdeen AB10 6RT UK

Tel: +44 (0) 1603 255231 Fax: +44 (0) 1603 507723 E-mail: [email protected] Dr J. Corry Division of Food Animal Science Department of Clinical Veterinary Science University of Bristol Langford Bristol BS40 5DT UK Tel: +44 (0) 117 928 9409 Fax: +44 (0) 117 928 9324 E-mail: [email protected]

Tel/Fax: +44 (0) 1224 322 777 E-mail: [email protected]

Chapter 8 Professor M. W. Griffiths and Dr L. Brovko Canadian Research Institute for Food Safety (CRIFS) University of Guelph Guelph Ontario N1G 2W1 Canada Tel: +1 519 824 4120 Fax: +1 519 763 0952 E-mail: [email protected] E-mail: [email protected]

Contributors

xiii

Chapter 9

Chapter 12

Dr R. Raybourne and Dr M. L. Tortorello MOD1 RM1013 HFS-326 8301 Muirkirk Rd Laurel MD 20708 USA

Dr K. Sanderson and Dr D. Nichols Centre for Food Safety and Quality School of Agricultural Science University of Tasmania Private Bag 54 Hobart TAS 7001 Australia

Tel: +1 301 827 8099 E-mail: [email protected] E-mail: [email protected]

Tel: +61 3 6226 6278 Fax: +61 3 6226 2642 E-mail: [email protected] E-mail: [email protected]

Chapter 10 Mr C. L. Baylis Manager Micro Methods Research Group Microbiology Department CCFRA Chipping Campden Gloucestershire GL55 6LD UK Tel: +44 (0) 1386 842073 Fax: +44 (0) 1386 842100 E-mail: [email protected]

Chapter 11 Dr J. McCarthy Lead Scientist – Human Safety SEAC – Safety and Environmental Assurance Centre Applied Science & Technology Group Unilever R&D Colworth Sharnbrook Bedfordshire MK44 1LQ UK Tel: +44 (0) 1234 26 4852 Fax: +44 (0) 1234 26 4744 E-mail: [email protected]

Chapter 13 Dr B. Swaminathan and Dr C. Fitzgerald Foodborne and Diarrheal Diseases Laboratory Section Centers for Disease Control and Prevention 1600 Clifton Road MS-C03 Atlanta GA 30333 USA Tel: +1 404 639 3669 Fax: +1 404 639 3333 E-mail: [email protected] E-mail: [email protected] Dr A. Sails Health Protection Agency Public Health Laboratory Institute of Pathology Newcastle General Hospital Westgate Road Newcastle-Upon-Tyne NE4 6BE UK E-mail: [email protected]

xiv

Contributors

Chapter 14 Professor A. P. F. Turner Cranfield University Silsoe Bedfordshire MK45 4DT UK Tel: +44 (0) 1525 863005 Fax: +44 (0) 1525 863360 E-mail: [email protected]

Professor G. Palleschi and Dr G. Volpe Universita` di Roma Tor Vergata Dipartimento di Scienze e Tecnologie Chimiche Via della Ricerca Scientifica 00133 Rome Italy Tel: +39 067 259 4423 Fax: +39 067 202 4342 E-mail: [email protected]

Introduction T. McMeekin, University of Tasmania

In the effort to ensure a safe food supply, it is difficult to think of an activity that is as all pervasive as the provision of reliable methods to detect pathogenic microorganisms in foods and food processing environments. This is illustrated well by the observation of Debevere and Uyttendaele (this volume) that: Microbiological tests are important in governmental food inspection to enforce legal regulations, in international trade to determine compliance with a microbiological standard, in commercial relationships between trade partners to control on agreed microbiological specifications, in the food industry to maintain quality control and process requirements, in academic laboratories for conducting research, and in reference laboratories to confirm the analyses of another laboratory and to provide surveillance data. The fundamental requirement to detect a target organism may appear to be a simple task, but the complexity of achieving the basic outcome increases markedly when the method is also required to meet other important requirements. The following criteria are adapted from Table 2.2 in Betts (2002): • perform with sensitivity, specificity, accuracy, precision, reproducibility and repeatability (see Debevere and Uyttendaele for definitions) • provide a result within an acceptable time frame, perhaps even in real time • have ease of use characteristics that allow routine application in industry, including being amenable to automation • undergo rigorous validation to allow comparison with ‘standard’ methods • meet the requirements of laboratory accreditation authorities and gain international acceptance

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Introduction

• be cost effective in terms of both capital outlay and running costs • provide a numerical estimate of the organism of concern. This volume is presented in two parts, the first dealing with general issues and the second with the development of particular methods. In the latter, the reader will gain a sense of excitement as researchers describe the latest developments in their fields, many of which arise from technological advances in areas such as molecular biology, microelectronics and information technology. The role of the first part is to put methods development into the framework of approaches to address food safety issues and to consider common requirements and common issues that may limit the efficacy of many methods. Chapter 1 sets the scene by describing the various roles for microbiological methods in modern food safety management, including prerequisite systems based around good manufacturing practice (GMP) and hazard analysis and critical control point (HACCP) systems. Chapters 2 and 3 deal with key preliminary issues in the use of any microbiological methods: what samples to collect, how to collect them and how to prepare them for analysis. The absolute requirement to understand the implications for adopting a particular sampling method is addressed in Chapter 2 by considering attributes plans and variables plans. The section on how to extract more value from historical test results will be of interest to many laboratories in both the public and private sectors. Chapter 3 reminds readers that many recently developed methods need levels of about 105 organisms/ml for reliable detection, indicating a continuing requirement for methods to remove and separate microorganisms from food and concentrate these in samples for analysis. The final two chapters in Part 1 address the very complex issue of providing a level playing field in selecting and judging effectiveness and fairness when the results of different methods, or the same protocol used in different laboratories, are compared. Part 2 reviews the range of microbiological methods used for detecting pathogenic microorganisms in food. The most traditional method is the use of cultures, discussed in Chapter 6. Samples are incorporated into a nutrient medium and incubated to allow microorganisms to grow to a level where they can be visually identified and counted. Culture methods are technically simple, very adaptable, sensitive and capable of identifying specific organisms. They also allow the analyst to quantify the number of microorganisms present and thus estimate the level of contamination of a sample. Their principal drawback is that they are labour-intensive and time-consuming. However, their ease of use, and the historical reliance of microbiologists on culture-based methods, has spawned a tradition in which they are still widely used in analytical laboratories and continue to provide a standard against which to measure newer techniques. The modern food industry needs techniques which match the sensitivity of culture methods and their specificity in identifying particular pathogens, but which are faster and capable of being used routinely in industry. The need to develop more rapid and automated methods has led to the emergence of a new generation of analytical techniques that are reviewed in the following chapters. Each method

Introduction

xvii

has its own particular strengths and weaknesses. Some methods may work poorly with certain foods or not be able to identify particular organisms. Some are quantitative, providing a measurement of the number of microorganisms in a sample, whilst others are qualitative, indicating only the presence or absence of a target organism. They also vary in speed and degree of automation in dealing with large numbers of samples and use without specialist microbiological expertise. Recognition of the need for improved detection technology has often been considered in the food microbiology literature and an account of the perceived needs 10 years ago was provided by Buchanan and Deroever (1993). In evaluating limits in assessing microbiological food safety, these authors highlighted the twin impediments of acquiring and analysing data on the epidemiology of foodborne diseases and limitations in detection methodology. Research into the two issues raised by Buchanan and Deroever, together with the issue of risk assessment, was supported by the US Government in the programme ‘Food Safety from Farm to Table’. This programme was reported in the September 1997 issue of Dairy, Food and Environmental Sanitation (Anon, 1997); for a comprehensive account of risk assessment as a food safety initiative the reader is referred to Brown and Stringer (2002). Amongst several recommendations for research in the US Government programme, ‘Improved Detection Methods’ figured prominently with specific activities including detection methods for Cyclospora, Campylobacter, Salmonella, Toxoplasma, Escherichia coli 0157:H7 and other Shiga-like toxin-producing E. coli, Cryptosporidium, hepatitis A and Norwalk viruses, and naturally occurring mycotoxins and marine toxins in foods. The issue of acquiring and analysing epidemiological data is addressed in Chapter 13 of this volume. This indicates the very marked influence of advances in molecular biology and information technology in providing detailed information on foodborne disease agents and foods involved in their transmission in a time frame allowing interventions to limit the course of an outbreak. This type of technology, also described by Swaminathan et al. (2001), will be a major weapon in dealing with the significant change in outbreak scenarios described by Tauxe (1997) with localised, acute events being replaced by diffuse, widespread outbreaks that may even cross national boundaries (Tauxe and Hughes, 1996). When considering the development of particular methods, Buchanan and Deroever (1993) judged that: Even though there has been substantial progress during the last 20 years in the development of rapid methods, no method for the detection of low numbers of pathogens has successfully eliminated the need for a 24 to 48 h enrichment. Although improvements continue, at least for the immediate future, the timeliness of microbiological analyses will remain a major limitation. Part 2 of this volume suggests that, in the decade since 1993, the pace of new method development has increased significantly and very recent trends indicate

xviii

Introduction

that the rate of this activity is likely to experience a further increase. The search for the ‘holy grail’ of real time detection of low numbers of pathogens in foods (referred to by Buchanan and Deroever as ‘timeliness’) will not just be driven by problems of foodborne disease per se. New impetus will be provided by the insidious threat of bioterrorism and how this threat could be delivered via contaminated food and water supplies. The international importance of such scenarios will undoubtedly lead to significant investment in research into methods to detect pathogens which will then rapidly be adapted for specific food industry applications. The bioterrorism imperative was very clearly identified in a report of the Institute of Food Technology, ‘Food Research Trends 2003 and Beyond’ (Mermelstein, 2002). In that report, 35 scientists responsible for peer review of research papers in IFT journals were given the role of ‘soothsayers’. The great majority of those who commented on developments in food microbiology foreshadowed rapid advances in detection methods using descriptive terms such as nanobiotechnology, genomics, proteomics, biosensors, microarrays, faster, rapid and real-time detection. Thus the impediment of lack of ‘timeliness’ of microbiological analyses will receive close scrutiny. This is further emphasised by the theme of the January 2003 meeting of the Society for Applied Microbiology (UK), ‘Lab on a chip: diagnosis and on-site testing’. In describing the content of that meeting, Coote (2002) noted that: The electronic chip, designed in the form of a biosensor, has opened up the possibility of comprehensive, simultaneous analysis for the presence of multiple pathogens or for parallel testing for the presence of specific drug resistance alleles. This multiplex system, when coupled to the miniaturisation of the chip components, has facilitated the development of portable hand-held devices for pathogen diagnoses in the clinical or environmental setting. Such devices, with characteristics described as ‘portability, speed and ease of detection, cost effectiveness and the need to fulfil the requirements of the enduser’ appear to be ideally suited to satisfy the requirements listed by Betts (2002) for effective detection of foodborne pathogens. Timeliness, in the accepted sense, is also an important factor contributing to the impact of a publication. A key objective of Detecting Pathogens in Food is to bring together leading researchers in their field to review the strengths and weaknesses of particular techniques and to put these into the context of food safety management systems and food safety regulation. Given advances in the last decade and projected developments, this volume is well timed to advise readers of the current status of detection methods and to provide an appreciation of the speed with which technological advances will open new vistas. One can anticipate the emergence of new methods not only delivering the traditional, non-negotiable outcomes of a standard method but also having a significant impact on currently intractable food safety issues that require resolution in a timely manner.

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References (1997) ‘Food Safety from Farm to Table. A national food-safety initiative report to the president.’ Dairy, Food and Environmental Sanitation, 17 555–74. BETTS R (2002) ‘Detecting pathogens in food’, pp. 13-45, in ‘Foodborne Pathogens: hazards risk analysis and control’. C de W Blackburn and PJ McClure, Editors, Woodhead Publishing Ltd., Cambridge. BROWN M and STRINGER M (eds) (2002) Microbiological Risk Assessment in Food Processing, Woodhead Publishing Ltd, Cambridge. BUCHANAN R L AND DEROEVER C M (1993) ‘Limits in assessing microbiological food safety’, Journal of Food Protection, 56 725–9. COOTE J (2002) ‘Lab on a chip: diagnosis and onsite testing’, Microbiologist (Magazine of the Society for Applied Microbiology), 3 24–27. MERMELSTEIN N H (2002) ‘Food Research Trends – 2003 and Beyond’, Food Technology, 56 30–49. SWAMINATHAN B et al. (2001) ‘Pulse Net: the molecular subtyping network for food borne bacterial disease surveillance, United States’, Emerging Infectious Diseases, 7 309–82. TAUXE R V (1997) ‘Emerging foodborne diseases: an evolving public health challenge’, Emerging Infectious Diseases, 3 425–33. TAUXE R V and HUGHES J M (1996) ‘International investigations of outbreaks of food borne disease: public health responds to the globalisation of food’, British Medical Journal, 313 1093–94. ANON

Acknowledgement Tom McMeekin is indebted to his long-time colleague and mentor, Dr June Olley, for her significant contribution in critically reading each of the chapters in this book.

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Part I General issues


1 Microbiological analysis and food safety management: GMP and HACCP systems C. de W. Blackburn, Unilever R&D Colworth, UK

1.1

Introduction

There are two different approaches to deliver food safety, Quality Control (QC) and Quality Assurance (QA). Both systems share tools, but the emphasis is very different. Both approaches are legitimate, but they need totally different organisations, structures, skills, resource and ways of working (Kilsby, 2001). QC is a reactive approach influenced by the pressures in the external world. In a QC organisation the emphasis is on measurement, which needs to be robust and statistically relevant, and the focus is on legal and commercial issues. In contrast, QA is a preventative approach driven by the company’s internal standards. The emphasis is on operational procedures, which must be robust and regularly reviewed, and the focus is on the consumer. There are several problems associated with relying on testing for product safety assurance (van Schothorst and Jongeneel, 1994). In order to apply any statistical interpretation to the results, the contaminant should be distributed homogeneously through the batch. As microbiological hazards are usually heterogeneously distributed, this means that there is often a major discrepancy between the microbiological status of the batch and the microbial test results (ICMSF, 1986). Even if the microbial distribution is homogeneous, it may still be prohibitive to test a sufficient number of sample units for all the relevant hazards to obtain meaningful information. Perhaps most significantly, microbiological testing detects only the effects and neither identifies nor controls the causes. As a consequence there has been an inexorable move from QC to QA in the management of microbiological hazards in food, with the focus on preventative control measures rather than finished product testing. Although microbiological analysis has subsequently borne the brunt of much denigrating,

4


it still has a vital role to play as part of a QA framework, albeit with a shift in application and emphasis.

1.2

Food safety management systems

Food safety management relies on the interplay of a number of fundamental elements, including: • knowledge • tools (e.g. risk assessment) • mechanisms (e.g. HACCP) (van Schothorst, 1998; Ross and McMeekin, 2002). At the centre lies the provision of safe food defined by a food safety objective (FSO), which is a statement of the frequency or maximum concentration of a microbiological hazard in a food considered acceptable for consumer protection. The mechanism by which the FSO is achieved is by application of a number of systems, which have been adopted by the food industry and are used in an integrated fashion. These include good manufacturing practice (GMP), good hygiene practice (GHP) and the hazard analysis critical control point (HACCP) system. HACCP is a food safety management system that uses the approach of identifying and evaluating hazards and controlling their fate at critical control points (CCPs) in the supply chain. The widespread introduction of HACCP has promoted a shift in emphasis from end-product inspection and testing to the preventative control of hazards during production, especially at the CCPs. It is generally agreed that the most successful implementation of HACCP is done within an environment of well-managed prerequisite programmes (PRPs) (Mortimore and Mayes, 2002). Although definitions vary, the concept of PRPs does not differ significantly from what may be termed GMP. GMP is concerned with the general (i.e. non-product specific) policies, practices, procedures, processes, and other precautions that are required to consistently yield safe, suitable foods of uniform quality. GHP is the part of GMP that is concerned with the precautions needed to ensure appropriate hygiene and as such tends to focus on the prerequisites required for HACCP. Generally, GMP/GHP requirements include the following: • • • •

the hygienic design and construction of food manufacturing premises the hygienic design, construction, proper use and maintenance of machinery cleaning and disinfection procedures for plant and equipment general hygienic and safety practices in food processing, including: – microbial quality of raw materials and supplier quality assurance – hygienic operation of each process step – hygiene of personnel and their training in hygiene and the safety of food – pest control – water and air control

Microbiological analysis and food safety management – – – –

5

product rework and recall procedures waste management labelling and traceability systems transportation (Brown, 2002; Mortimore and Mayes, 2002).

For steps in the manufacturing process that are not recognised as CCPs, the use of GMP is essential to provide assurance that suitable controls and standards are present. In turn, the identification and analysis of hazards within the HACCP programme will provide information to interpret GMP requirements and indicate staff training needs for specific products or processes (Brown, 2002). Although GMP cannot substitute for a CCP, collectively it can minimise the potential for hazards to occur, thus eliminating the need for a CCP. The implementation of effective GMP will control ‘general’ or ‘establishment’ hazards that would otherwise have to be controlled by a CCP. Failure to have GMP in place will inevitably lead to a large number of CCPs in the HACCP plan covering both ‘general/establishment’ hazards and product specific ones. Food safety management is required from ‘farm to fork’ and systems analogous to GMP have been developed throughout the food supply chain. These include systems targeted at food production: good agricultural practice; good working practices of animal husbandry (Johnston, 2002); and good aquacultural practice; as well as those targeted at food handlers and consumers: good catering practice; and good domestic kitchen practice (Griffith, 2002).

1.3

Types of testing used in GMP and HACCP systems

The types of tests that have a role in GMP and HACCP systems depend on the specific application and range from standard detection and enumeration methods through to the most sophisticated finger printing techniques. Although full details of these methods are covered elsewhere in this book, it is worth taking time to briefly consider the importance of tests for indicator organisms and the application of challenge tests and predictive microbiology models.

1.3.1 Pathogen vs. indicator testing The numbers of pathogenic microorganisms in most raw materials and food products are usually low and so pathogen tests may provide little information of use for the implementation and maintenance of GMP and HACCP systems. Instead, the enumeration of so-called ‘indicator organisms’ has an important role. Indicator organisms are groups of microorganisms that are indicative for the possible presence of pathogens. Although there is not necessarily a relationship between indicator and pathogen numbers, it can be generally assumed that the possible numbers of a pathogen are less than the numbers of the organisms indicative for it. It can also be assumed that reduction in the numbers of the indicator organisms will produce a similar reduction in the numbers of

6


any corresponding pathogen (Brown et al., 2000). For the same reasons indicator organisms can also provide a measure of post-pasteurisation contamination that might lead to pathogen contamination. As different indicator organisms imply the possible presence of different pathogens, there are several groups of tests that may be appropriate, e.g. total aerobic counts, coliforms, Enterobacteriaceae, E. coli, faecal streptococci and aeromonads (Brown et al., 2000).

1.3.2 Microbiological challenge testing and predictive microbiology When assessing the safety of a product and/or process the use of microbiological challenge testing may be required. This type of test can be helpful in determining the ability of a food to support the growth of pathogens and in the validation of processes that are intended to deliver a defined degree of lethality against a target organism (IFT, 2001). In essence microbiological challenge testing involves the inoculation of a food with specific microbial hazards and monitoring their growth, survival or death during storage and/or after specific process steps. However, there are a number of important factors that must be considered when designing and implementing a challenge test, including: • • • • • •

selection of appropriate challenge organisms inoculum level duration and number of analyses storage conditions and packaging methodology interpretation (Vestergaard, 2001).

This type of microbiological testing is expensive, time-consuming and is very product/process specific and therefore may have to be repeated if the product and/or process is modified. These factors have been some of the main drivers for developments in the field of predictive microbiology, the concept and history of which have been reviewed in detail by McMeekin et al. (2002). Mathematical microbiology models can help describe the growth, survival and death of microorganisms in food as affected by the intrinsic factors (characteristics of the food, e.g. pH, aW, preservatives) and extrinsic factors (characteristics of the environment, e.g. temperature). In addition to the numerous predictive microbiology models that have been published, several software systems incorporating microbiology models have been produced, some of which are commercially or freely available (Blackburn, 2000). Information about this software is provided at the end of this chapter. Predictive models have the potential for a range of safety and spoilage applications including shelf-life determination and extension, distribution and storage condition assessment, product formulation and reformulation, process design, risk assessment, GMP, HACCP, and as an alternative or adjunct to challenge testing (Vestergaard, 2001). However, the extent to which the application of predictive models can be relied upon has been the subject of considerable debate. The US Department of Agriculture Food Safety and Inspection Service

Microbiological analysis and food safety management

7

(USDA FSIS) has gone so far as to say that ‘it is not possible or appropriate to rely solely upon a predictive modelling program to determine the safety of foods and the effectiveness of processing systems’ (FSIS, 2002). The FSIS also state that predictive models do not replace the need for challenge testing. The Institute of Food Technologists (IFT) take a more balanced view, highlighting the value of combining predictive models with challenge tests and the potential for using challenge test data for model development and validation (IFT, 2001). Taking a pragmatic approach it is clear that predictive models can provide a powerful source of information and a tool for its practical application, whilst not completely negating the need for microbiological testing. Utilising predictions requires a considerable amount of knowledge of the food, the process, the microorganism of concern and the model itself, and therefore models do not replace the judgement of a trained and experienced microbiologist. Developments in information technology have also led to the construction of microbiological expert systems. Originating from the artificial intelligence field of research, expert systems are essentially computer programs that attempt to emulate the performance of human experts. As an example of what can be achieved, an expert system for ready-to-eat meals has been described (Adair and Briggs, 1993). The system contained databases on product design, manufacturing and microorganisms, and several predictive bacterial growth models. In response to user inputs a rule base was applied and the output comprised the required assembly and packaging conditions, the minimum thermal process and the maximum shelf-life to ensure a microbiologically safe product.

1.4

Microbiological analysis and GMP systems

GMP/GHP systems have been found to be effective provided that they are well documented with standard operating procedures (SOPs), are fully implemented, and include monitoring records and verification procedures (Kvenberg and Schwalm, 2000). There are several principal sources of microbial contamination of a product that require control: raw materials, equipment, process/production environment and people. The extent to which microbial testing plays a role, and the degree of sampling required, should reflect the category of risk associated with the particular raw material, area or operation. For example, a ‘high-risk’ raw material that is added to a product post-pasteurisation may require more testing to verify compliance with a specification than one added before pasteurisation. Also the food contact surfaces and air quality in a ‘high care/ hygiene’ area may require a higher level of sampling.

1.4.1 Determining the source and significance of hazards Whether GMP/GHP or HACCP eventually controls the hazards, hazard identification is an important first step to ensure safe food products. Microbiological testing can play an important role in identifying potential hazards as well as

8


linking them to a source, assessing their significance for the final product, and verifying that controls are effective and successfully implemented. For example, in a meat processing plant microbial testing demonstrated that the most important factor contributing to the microbial contamination of ground beef and retail cuts was from incoming raw materials obtained from different suppliers (Eisel et al., 1997). Environmental sources of contamination were shown not to be a significant source of overall microbial contamination, although it was highlighted that cleaning and sanitation programmes and safe handling were still important. In a similar way, predictive microbiology models have helped determine the significance of different microbiology hazards in establishing the shelf-life of pasteurised milk (Griffiths and Phillips, 1988). This exercise highlighted the importance of good hygienic processing to reduce the postpasteurisation contamination. The use of molecular characterisation techniques has further increased the microbiologist’s armoury and epidemiological tracking of strains can provide a more in-depth knowledge of the food process. This may enable the determination of sites of contamination helping to highlight where controls are required, whether they be through GHP or CCPs (Dodd, 1994).

1.4.2 Raw materials The quality of raw materials can affect the overall quality of the finished product. Microbiological testing may often be required to verify that raw materials are delivered to the agreed specification and as a means of monitoring or selecting suppliers. Although frequently covered as part of a HACCP study, raw material specifications may not be identified as a CCP, in which case they are usually covered by GMP/GHP. Testing may then involve confirming the absence of specific pathogens or that indicator organisms are within defined limits. Raw materials may also be the means of introducing contamination into the food processing or production environment. This is particularly important from the point of view of controlling contamination in animal husbandry. Although control is particularly difficult in a farm environment, prevention of feed contaminated with pathogens being introduced into e.g. broiler flocks, is an important control point. Here microbial testing can be an important means of verifying that pathogens are absent and that the batch conforms to agreed specifications.

1.4.3 Equipment Food contact surfaces are a particularly important potential source of contamination, and sanitation (cleaning and disinfection) is the major day-today control. When undertaken correctly, sanitation programmes have been shown to be cost effective and easy to manage, and, if diligently applied, can significantly reduce the risk of microbial contamination (Holah and Thorpe, 2002). In this regard microbial testing is useful in the validation of standard


9

sanitary operating procedures (SSOPs) and the verification that they have been carried out effectively. In general, the microbial tests used are indicator organisms such as TVC, coliforms, Enterobacteriaceae or yeasts and moulds. However, it is very easy to forget that visual examination can provide a valuable first step in validating and/ or verifying an SSOP and can save a lot of wasted effort and expense. Conventional methods for monitoring surface contamination include: • contact plates/dipslides (for flat surfaces) • swabbing and plating (ideal for more inaccessible areas) • sponges (for sampling larger areas) (Fraser, 2002). An estimate of the microbial load per unit of plant is obtained and can be compared with predetermined specifications. An aerobic colony count of 100 cfu/cm2 is often used as a standard and counts below that level are indicative of clean surfaces (Griffiths, 1997). In closed systems that are sanitised by cleaning in place (CIP) procedures, cleanliness is usually determined by analysing rinse water samples for microbial load. Although of value in validating and/or optimising an SSOP, verification of sanitation based on colony counting techniques can generally only be of use for trend analysis. However, the application of the ATP bioluminescence technique for hygiene monitoring now provides the advantages of immediate corrective action, which fits with the QA approach. There are now a plethora of different types of systems for measuring ATP based on the analysis of swabs, rinse waters, and determining ATP in situ, which is only really applicable to flat surfaces. ATP bioluminescence can be useful to help refine and improve SSOPs and optimise the use of chemicals and water and in some cases can lead to a reduction in sanitation costs. Although of great potential benefit the technique does have its limitations. In particular, some food products have naturally low levels of ATP. In these cases hygiene monitoring using ATP bioluminescence would not be an appropriate method. However, rapid tests for measuring other hygiene indicators, e.g. protein and catalase activity, have also been developed and may be more applicable where ATP analysis is not. Although a microbial surface may not be a source of contamination after sanitation, food residue on that surface during production can provide the opportunity for microbial growth, which could then be a source of recontamination to the product. With the production pressures to keep lines running as long as possible between SSOPs, microbial testing can provide valuable information to maximise line efficiency without compromising the microbial safety or quality of the product.

1.4.4 Environment The food production/process environment can be a source of general contamination. Many surfaces not directly in contact with food may harbour microorganisms, e.g. non-food contact equipment surfaces, walls, floors, drains,

10


overhead structures. These microorganisms can then be transferred to the food in the air via water droplets and dust. Sampling of this environment can provide information on the likely presence and incidence of pathogens, their distribution in relation to processing lines and thus the risk of product contamination (Cordier, 2002). This allows preventative measures to be established in the framework of GHP, such as layout of processing lines and zoning within the factory. Sampling the cleaning equipment is a very useful index of what is actually present in a production environment, because cleaning ‘collects’ dirt and bacteria from all parts of the factory, e.g. floor mops, brushes, vacuums (Fraser, 2002). In a similar way sampling of drains also gives a better chance of determining whether a particular pathogen is present in the production environment, e.g. Listeria. This can often be a better approach than sampling end products. In addition, other wet areas such as sinks, taps, cleaning cloths and brushes, and boot-washing baths should also be checked routinely. Aerosols can be created from such areas and contamination can find its way into products on the manufacturing line. Testing for indicator organisms generally gives the most useful information on the environmental hygiene, an exception to this being the testing for Listeria in high-hygiene environments. Air quality can be a good index of the overall sanitary condition of a production environment. Air can contain microbial contamination from both external and internal sources, depending on the set-up of the factory. For example, if filters and air-conditioning units are not properly maintained, microorganisms can enter the plant from outside. Internal contamination can occur from skin particles shed from factory personnel, dust particles from packaging materials, and aerosols created during either production or on-going cooling or cleaning processes. The records from the routing monitoring of air quality can build a picture of the general standard of air hygiene in a plant (and identify the areas/sources of highest contamination). Generally, the methods for measuring air quality are either settle plates or the use of a portable, batteryoperated, air sampler. Because airborne counts can fluctuate widely depending on activities around the area, it is important to note what is happening (e.g. cleaning, shift-change) in order to correlate data with events (Fraser, 2002). The temperature of the production environment can obviously affect microbial proliferation and here predictive microbiology can play a role in GMP/GHP. For example, a dynamic Temperature Function Integration (TFI) model was used jointly by regulators and processors to develop justifiable criteria for the management of refrigeration during the production of hot and warm-boned meat, the post-slaughter handling of ovine carcasses and the handling of offals (Armitage, 1997). Similarly, the use of predicted lag times and growth rates of coliform bacteria have been used to support a proposal to alter the temperature of cutting rooms for chilled meat carcasses as stipulated by public health authorities in several countries (Baker, 1995).


11

1.4.5 People/training Food production staff and food handlers are a potential source of contamination of food products. For this reason, it is important that adequate training is given, and that proper supervision ensures adherence to all hygiene measures, particularly hand washing. The use of microbiological testing should not be underestimated as a part of hygiene training. The impact of seeing agar plates covered in colonies that have been isolated from swabs taken from hands pre-washing or surfaces pre-cleaning and the reduction achieved following washing or sanitation can be significant. The rapid results achievable by ATP bioluminescence can be particularly useful for the motivation and training of sanitation and production staff by providing a means by which they can access their own performance and by demonstrating the importance of their work. Regular swabbing of hands can also help to reinforce hygiene procedures.

1.5

Microbiological analysis and HACCP systems

Successful implementation of a fully validated HACCP study means that the supposed reliance on microbiological testing, with all its sampling limitations, is relinquished and this should enable a significant reduction in the volume of testing. Some in the food industry went so far as to surmise that microbiological testing would become obsolete (Struijk, 1996). In reality, however, microbiology testing has continued albeit with a shift in application and emphasis and accompanying changes in the role of the microbiologist (Kvenberg and Schwalm, 2000). The HACCP process comprises seven principles, which are further broken down into stages, and microbiological analysis has an important role to play in several of them (Table 1.1), including: • • • •

hazard analysis determination of CCPs defining target values and critical limits verification.

Although, not defined as a separate stage, validation of the HACCP study is an essential verification activity and can benefit from microbiological test data. Validation is concerned with obtaining evidence that the elements of the HACCP plan are effective, i.e. ‘doing the right things’. This contrasts with other verification activities, which determine the effectiveness of the HACCP system once defined and implemented, i.e. ‘doing things right’. The extent and scope of microbial testing is likely to vary with differences in facilities and equipment, the scales of processes, and the types of products involved (Brown et al., 2000). In reality the HACCP process often starts with a product/process concept where design control points (DCPs) rather than CCPs are the output. At this point predictive models can be of particular value as the

12


Table 1.1 1 2 3 4 5 6 7

The seven principles of the HACCP system

Conduct a hazard analysis Determine the critical control points (CCPs) Establish limits for each CCP Establish a system to monitor control of each CCP Establish the corrective action to be taken when a critical limit is exceeded Establish procedures to verify that the HACCP system is working effectively Establish documentation for the HACCP system

product and/or process goes through a number of iterations for reasons of product development, marketing, production or safety.

1.5.1 Hazard analysis The first principle of the HACCP process is to conduct a hazard analysis. Hazard analysis is the process of collecting and evaluating information on hazards and conditions leading to their presence to decide which are significant for food safety and therefore which should be addressed in the HACCP plan. For each raw material and process step this includes consideration of the likely occurrence of the hazards, qualitative/quantitative evaluation of the hazards, survival or multiplication of the hazards and identification of appropriate preventative measures. Published sources of microbiological data, including epidemiological and surveillance data, together with knowledge gained through commercial experience, can provide the HACCP team with relevant information on the likely hazards associated with the product and process. However, when existing data is lacking microbiological testing is often needed (Kvenberg and Schwalm, 2000). This may involve determining the incidence of pathogens or indicator organisms in raw materials, the presence of pathogens (e.g. Listeria) in the environment, and microbial loads in foods and on equipment (Stier, 1993). Here the links with GHP are important. Validation of the technical accuracy of the hazard analysis and effectiveness of the preventative measures is important before the HACCP study is finalised and implemented. Examples where microbiological methods may be used for validation include pre-operation checks of cleaning and sanitising, screening of sensitive raw materials, challenge testing, and monitoring of critical sites for microbiological build-up during processing (Hall, 1994). Predictive models can be used to help assess the risk and determine the consequence of a microbiological hazard in food during the different process steps (Elliott, 1996). The advantage of using predictive models is that the effect of adjusting the product formulation and/or processing parameters can be rapidly assessed. To obtain predictions from most models a starting concentration of microorganisms is required and here information from microbial testing can be of value. Where predictive models are appropriate this may allow a reduction in, or negate the need for, challenge testing, which might otherwise be required


13

to provide this information. Predictive models have a particularly important role to play in obtaining information about microorganisms that require specialist facilities for data generation. For example, models for Clostridium botulinum have been used to predict the safe refrigerated shelf-life of sous vide-type food products (Baker and Genigeorgis, 1993) and vacuum-packed fish (Hyytia¨ et al., 1999). Even though the FSIS (2002) has stated that ‘generally, a microbial pathogen computer model (MPCM) would not be the only documentation relied upon to support an element of a HACCP plan’ it is conceded that ‘in certain circumstances, a microbiologist . . . may determine the MPCM program is the most appropriate (and sole) source of data’ and Cl. botulinum is used as an example.

1.5.2 CCPs A CCP is a step at which control can be applied (and is essential) to prevent or eliminate a food safety hazard or reduce it to an acceptable level. The second, third and fourth principles of HACCP involve determining CCPs, setting critical limits and establishing a system to monitor control of each CCP. Challenge testing and predictive models can provide useful information for both the determination of CCPs and the setting of critical limits (Baker, 1995; Elliott, 1996; Griffiths, 1997; Fujikawa and Kokubo, 2001; IFT, 2001; FSIS, 2002). This information is often required to set maximum times and temperatures for storage conditions and minimum times and temperatures for heat processes. Microbial testing can play a major role in the validation of CCPs to demonstrate their effectiveness (van Schothorst, 1998; Blackburn, 2000; Kvenberg and Schwalm, 2000). For safe product design a defined reduction of target microorganisms may be required, either in one CCP or over a series of process steps. Quantitative data may be required to demonstrate that the process can deliver the defined level of microbial kill or that the end product meets the specification for safety and/or stability. This is particularly true if unconventional or unique control measures and/or critical limits are used. Predictive microbiology models can be used for ‘what if’ scenarios to provide an indication of the severity of problems caused by process deviations or the complete breakdown of any of the CCPs (FSIS, 2002). They can also be used to provide useful information on the assessment of equivalence of HACCP plans (Fujikawa and Kokubo, 2001). In many cases it is still necessary to conduct challenge tests to validate CCPs as current models will not be appropriate for all situations that may be encountered in food production. Microbial methods, particularly molecular characterisation ones, can be useful in answering questions that may arise as part of the HACCP validation exercise. For example, if a hazardous organism appears in a product at a point in the production line beyond the CCP designed to control it, does this mean failure of the CCP, or does it indicate post-process contamination (Dodd, 1994). The HACCP process requires the establishment of systems to monitor all identified CCPs. In most cases it is not feasible to use microbial testing to

14


monitor CCPs due to the long analysis time, low method sensitivity and heterogeneous nature of pathogen contamination. However, there are some notable exceptions. The receipt of raw materials within defined microbiological specification is often identified as a CCP. As a consequence, preventative measures may include a Certificate of Analysis for selected contaminants and inhouse laboratory tests to confirm acceptability and when screening new suppliers. Here again, the use of indicator organisms testing is often used. ATP bioluminescence kits are widely used for checking the sanitation of equipment. As results from these methods can be obtained in only a few minutes, it allows sufficient time for equipment to be resanitised before production begins thus preventing contamination. Consequently, sanitation of equipment and monitoring using ATP bioluminescence may be identified as a CCP, although this is frequently covered as part of a GHP programme. Although limited in their availability, other ‘real-time’ methods such as flow cytometry have been proposed for CCP monitoring (Griffiths, 1997).

1.5.3 Verification The sixth HACCP principle involves the establishment of verification procedures to confirm that the HACCP system is working effectively. The traditional view is that verification does not need to include microbial testing because, in large part, it is accomplished by reviewing HACCP monitoring records (Kvenberg and Schwalm, 2000). However, it is clear that many companies use microbial testing in verification programmes for both incoming ingredients and finished products. This may involve pathogen testing, although quantitative indicators can provide a much more effective tool for verifying that HACCP is properly implemented (Swanson and Anderson, 2000). The choice of appropriate indicators is product and process specific. For example, testing for coliforms provides an effective verification technique for the pasteurisation of milk and water potability. However, in certain applications finished product testing for even indicator organisms provides no meaningful data (e.g. canned products). In theory, a well-functioning HACCP plan should only require occasional testing as part of the verification process. However, sometimes local legislation, customer requirements or the company’s own standards demand a higher level of testing (Stier, 1993). Microbiological data can provide valuable sources of information for trend analysis and statistical process control and for this purpose they are generally under-utilised. In this regard, quantitative tests are more informative to a processor than negative pathogen tests as trends can be examined and early warnings of problems or loss of control can be obtained. Loss of operation control may give rise to dramatic changes to microbiological test results, however it may manifest itself in much more subtle gradual changes in microbial counts only detectable via trend analysis. If microbiological data are examined proactively it is then conceivable for microbiological problems to be prevented making the exercise compatible with the QA approach to food safety.


15

The goal should be for data to be directed towards process improvement and microbiological analyses should not be done solely for the sake of generating data. Many organisations have test results and baseline data for indicator organisms collected over many years. New criteria that replace historic baselines must be carefully reviewed to ensure that the processor retains a solid understanding of the microbial profiles of their processes and products. For example, the implementation of a new test method can make previously developed baseline data worthless if the new testing protocol does not provide equivalent results. HACCP is a living system and therefore review of the HACCP plan is an important aspect to ensure that it remains fully valid and implemented. A formal review should be triggered if there is a change to the product or process, but if this is not the case then it should be reviewed at regular intervals, e.g. annually. In these reviews it may be decided that microbiological data are required to assess the significance of a new hazard or to ensure that the CCPs can still control the existing hazards in light of any proposed changes to the product or process.

1.5.4 Troubleshooting and forensic investigation It has been pointed out that in spite of meticulous adherence to HACCP-based good practices occasional human, instrumental or operational hiatuses can and will occur (Struijk, 1996). Microbiological methods are still required for troubleshooting and forensic investigation in order to identify the cause of the problem and rectify it. Usually the first action required is to identify and control the affected product, which may or may not be identified as having deviated from HACCP critical limits. Microbiological testing may be appropriate to determine, or confirm, whether there is a microbiological problem and, if so, whether it is a safety or spoilage incident. In combination with a review of the process records, particularly at CCPs, and any historical microbiological test data, it may be necessary to instigate a microbiological sampling and testing plan to determine how much product is affected. As speed is often critical, rapid microbiology methods can play an important role (Stier, 1993). In addition, predictions from microbiology models may help to determine the extent of the microbiological problem (Fujikawa and Kokubo, 2001). Once this information has been obtained, decisions can be made regarding segregation, blocking, recall and salvaging of affected batches and the status of further production. Microbiological analysis is often required to determine the cause or source of the problem and the type and extent of testing required will vary enormously depending on the situation. Rapid techniques like ATP bioluminescence can be useful troubleshooting tools to identify problem areas quickly. Tests ranging from indicator organisms, through specific pathogen detection methods to the genetic fingerprinting of strains may also be appropriate. Following this immediate action an assessment of the integrity of the HACCP plan is required. It has to be determined whether the HACCP has failed due to its validity or its

16


implementation. Here again, microbiological analysis may have a role to play in any subsequent review and revalidation.

1.6

Future trends

The food industry has responsibilities to produce safe and wholesome food and providing this assurance is ultimately the microbiological goal. A microbiology test that could analyse a batch of food non-destructively, on-line and with the required accuracy, sensitivity and specificity is the ‘Holy Grail’ and would provide this assurance. Our current technical capabilities, and even the likely developments in the foreseeable future, fall well short of this ideal situation and so food safety management using the QA approach is here to stay. As can be seen throughout this chapter the full range of existing methods have an important place in our armoury against the threats posed by microorganisms in food. Due to the diversity of applications and user requirements new method developments still have the potential to bring benefits. Methods that are faster, cheaper, easier to use, more accurate and/or more sensitive are likely to find welcome recipients. There is also a push to standardise methods and demonstrate equivalence to address the increasingly global market for food. The rapid monitoring of hygiene using ATP bioluminescence is probably the best example of a ‘microbiological’ test applied in a GHP/HACCP environment. It is likely that the range of other compounds that could be used to monitor hygiene will extend further. Increased use of genetic fingerprinting methods to better understand the microbial ecology of the factory, manufacturing line, and production process may also bring benefits in targeting better control of the hazards. Biosensor development for very rapid pathogen detection and indicator organism enumeration could also be of benefit for application within GHP and HACCP (Fung, 2002). A variety of biosensors are now commercially available to monitor microorganisms, but they are not yet suitable for routine testing in the food industry. It has been proposed that rapid alert kits for food spoilage and detection of food pathogens will be developed for catering and home use and that more developments in this area are needed (Fung, 2002). However, there is a danger that if these kits are marketed at the expense of hygiene training and education then we may fall into the trap of imposing a QC rather than a QA mentality on the food handler and consumer. The use of predictive models, particularly those based on probabilities, for GMP and HACCP has yet to be fully realised. It has been stated that their utility will be further enhanced when predictive microbiology is recognised as a rapid method (McMeekin et al., 2002). This will require an increased availability and applicability of models and improvements to the accuracy of predictions as well as greater understanding of the benefits and limitations by the user. The deviations between predictions from current models and observed data in foods that are seen are often due to a factor not included in the model (e.g. a preservative) or differences in the factors used (e.g. type of acid or humectant).


17

The physiological state of microorganisms in food, particularly if injured or preconditioned, can have a dramatic effect on their fate and growth or survival kinetics (Blackburn and Davies, 1994; McMeekin et al., 2002). Combining knowledge of microbial kinetics in food with an understanding of the underlying physiological processes offers great benefits for the management of food safety in the future. Ultimately, the combining of predictive models with rule bases in expert systems offers the potential for greater assurance for food safety, while still providing scope for innovation by food developers and producers.

1.7

Sources of further information and advice

Food MicroModel software and enquiry service are currently available from Leatherhead Food International, Randalls Road, Leatherhead, Surrey KT22 7RY, UK. Tel. +44 (0)1372 376761; Fax. +44 (0)1372 386228. http:// www.leatherheadfood.com Forecast service and ERH CALC software are available from Campden & Chorleywood Food Research Association, Chipping Campden, Gloucestershire GL55 6LD, UK. Tel. +44 (0)1386 842000; Fax. +44 (0)1386 842100. http:// www.campden.co.uk Food Safety and Inspection Service (FSIS) website. http://www.fsis.usda.gov Institute of Food Technologists website. http://www.ift.org MicroFit and DMfit are available from the Institute of Food Research Reading and can be downloaded from the Internet. http://www.ifr.bbsrc.ac.uk Pathogen Modeling Program is available from the USDA and can be downloaded from the Internet. http://www.arserrc.gov/mfs/pathogen.htm Seafood Spoilage Predictor is available from the Danish Institute of Fisheries Research and can be downloaded from the Internet. http://www.dfu.min.dk/ micro/ssp

1.8

References

and BRIGGS P A (1993) The concept and application of expert-systems in the field of microbiological safety, Journal of Industrial Microbiology, 12 263–7. ARMITAGE N H (1997) Use of predictive microbiology in meat hygiene regulatory activity, International Journal of Food Microbiology, 36 103–9. BAKER D A (1995) Application of modelling in HACCP plan development, International Journal of Food Microbiology, 25 251–61. BAKER D A and GENIGEORGIS C (1993) Predictive modeling, in Hauschild A H W and Dodds K L (eds) Clostridium botulinum: Ecology and Control in Foods, Marcel Dekker Inc., New York, pp. 343–406. ADAIR C

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(2000) Modelling shelf-life, in Kilcast D and Subramaniam P (eds) The Stability and Shelf-Life of Food, Woodhead Publishing Limited, Cambridge, pp. 55–78. BLACKBURN C DE W and DAVIES A R (1994) Effects of preconditioning on pathogenic bacteria in foods, Food Technology International Europe 1994, 37–40. BROWN M (2002) Safe process design and operation, in Blackburn C de W and McClure P J (eds) Foodborne Pathogens Hazards, Risk Analysis and Control, Woodhead Publishing Limited, Cambridge, pp. 197–228. BLACKBURN C DE W

BROWN M H, GILL C O, HOLLINGSWORTH J, NICKELSON II R, SEWARD S, SHERIDAN J J,

and ZINK D (2000) The role of microbiological testing in systems for assuring the safety of beef, International Journal of Food Microbiology, 62 7–16. CORDIER J-L (2002) Sampling and testing for pathogens essential in safe food manufacture, New Food, 2 37–40. DODD C E R (1994) The application of molecular typing techniques to HACCP, Trends in Food Science and Technology, 5 160–4. ELLIOTT P H (1996) Predictive microbiology and HACCP, Journal of Food Protection, Suppl. 48–53. EISEL W G, LINTON R H and MURIANA P M (1997) A survey of microbial levels for incoming raw beef, environmental sources, and ground beef in a red meat processing plant, Food Microbiology, 14 273–82. FRASER E (2002) Environmental monitoring in the food industry, New Food, 5 9–14. FSIS (2002) Use of microbial pathogen computer modelling in HACCP plans, USDA Food Safety and Inspection Service, Washington, DC, FSIS Notice 55-02. FUJIKAWA H and KOKUBO Y (2001) Practical applications of predictive microbiology software programs to HACCP plans, Journal of the Food Hygienic Society of Japan, 42 252–6. FUNG D Y C (2002) Predictions for rapid methods and automation in food microbiology, Journal of AOAC International, 85 1000–2. GRIFFITH C (2002) Good practices for food handlers and consumers, in Blackburn C de W and McClure P J (eds) Foodborne Pathogens Hazards, Risk Analysis and Control, Woodhead Publishing Limited, Cambridge, pp. 257–76. GRIFFITHS M W (1997) Rapid microbiological methods with hazard analysis critical control point, Journal of AOAC International, 80 1143–50. GRIFFITHS M W and PHILLIPS J D (1988) Modeling the relation between bacterial growth and storage temperature in pasteurised milks of varying hygienic quality, Journal of the Society of Dairy Technology, 41 96–102. HALL P A (1994) Scope of rapid microbiological methods in modern food production, in Patel P D (ed.) Rapid Analysis Techniques in Food Microbiology, Blackie Academic, Glasgow, pp. 255–67. HOLAH J and THORPE R (2002) Hygienic plant design and sanitation, in Blackburn C de W and McClure P J (eds) Foodborne Pathogens Hazards, Risk Analysis and Control, Woodhead Publishing Limited, Cambridge, pp. 151–95. ¨ E, HIELM S, MOKKILA M, KINNUNEN A and KORKEALA H (1999) Predicted and HYYTIA observed growth and toxigenesis by Clostridium botulinum type E in vacuumpackaged fishery product challenge tests, International Journal of Food Microbiology, 47 161–9. ICMSF (1986) Micro-organisms in food-sampling for microbiological analysis Principle and specific applications, Blackwell, Oxford. STEVENSON T, SUMNER J L, THENO D M, USBORNE W R


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(2001) Microbiological challenge testing, in Evaluation and Definition of Potentially Hazardous Foods, A Report of the Institute of Food Technologists for the Food and Drug Administration of the US Department of Health and Human Services, IFT/FDA Contract No. 223-98-2333. JOHNSTON M (2002) HACCP in farm production, in Blackburn C de W and McClure P J (eds) Foodborne Pathogens – Hazards, Risk Analysis and Control, Woodhead Publishing Limited, Cambridge, pp. 127–50. KILSBY D (2001) Personal communication. KVENBERG J E and SCHWALM D J (2000) Use of microbial data for hazard analysis and critical control point verification Food and Drug Administration perspective, Journal of Food Protection, 63 810–14. MCMEEKIN T A, OLLEY J, RATKOWSKY D A and ROSS T (2002) Predictive microbiology: towards the interface and beyond, International Journal of Food Microbiology, 73 395–407. MORTIMORE S and MAYES T (2002) The effective implementation of HACCP systems in food processing, in Blackburn C de W and McClure P J (eds) Foodborne Pathogens – Hazards, Risk Analysis and Control, Woodhead Publishing Limited, Cambridge, pp. 229–56. ROSS T and MCMEEKIN T (2002) Risk assessment and pathogen management, in Blackburn C de W and McClure P J (eds) Foodborne Pathogens Hazards, Risk Analysis and Control, Woodhead Publishing Limited, Cambridge, pp. 97–126. STIER R F (1993) Development and confirmation of CCP’s using rapid microbiological tests, Journal of Rapid Methods and Automation in Microbiology, 2 17–26. STRUIJK C B (1996) The Hamlet option in food microbiology: to analyze or not to analyze food specimens as marketed once HACCP implemented, Acta Alimentaria, 25 57– 72. SWANSON K M J and ANDERSON J E (2000) Industry perspectives on the use of microbial data for hazard analysis and critical control point validation and verification, Journal of Food Protection, 63 815–18. VAN SCHOTHORST M (1998) Principles for the establishment of microbiology food safety objectives and related control measures, Food Control, 9 379–84. VAN SCHOTHORST M and JONGENEEL S (1994) Line monitoring, HACCP and food safety, Food Control, 5 107–10. VESTERGAARD E M (2001) Building product confidence with challenge studies, Dairy, Food and Environmental Sanitation, 21 206–9. IFT

2 Sampling techniques D. Legan and M. H. Vandeven, Kraft Foods North America, USA

2.1

Introduction: common definitions

There are many good texts describing the statistics of sampling including some designed to address the specific needs of microbiologists (ICMSF, 1974, 1986, 2002; Jarvis, 1989, 2000). They will supply additional background information and explanation. We intend to review the art and science of sampling for pathogens in and around foods indicating when to use statistical methods for selecting the sampling plan and when to prefer other methods. We will use examples from some common sampling circumstances for illustration. We will describe the ‘attributes’ sampling plans advocated by The International Commission on Microbiological Specifications for Foods (ICMSF) since 1974 to show why they are the most practical solution to the problem for which they were developed, namely port-of-entry sampling of foods in international trade. We will demonstrate how these plans can be rescaled to perform in terms of concentration of organisms when the log counts from sampling follow a normal distribution, and how this can provide a quantitative approach to food safety management. We will indicate how variables sampling plans may allow more value to be extracted from the data derived from sampling when the result of testing gives countable numbers of organisms and the distribution of organisms in the foods is known. We will consider environmental sampling as part of a program of food safety management within a manufacturing facility. Finally we will make some suggestions on how to extract more value from the historical records of test results produced in quality control laboratories at great expense. Some terms that will appear frequently in this chapter that may not be familiar to all readers are explained below.

Sampling techniques

21

Accept. Allow the food to be used for its intended purpose. This decision is made about the lot, not about an individual test result. Acceptable. A lot that is suitable for its intended purpose. A sample that gives a ‘passing’ test result – at or below the maximum acceptable level specified. Acceptance-sampling plan. A pre-determined procedure to determine whether a lot is acceptable. Such a plan should include statements about the number, size and type of samples to take, the laboratory methods to be used for analysis, and the criteria for acceptability. Attribute. A property of the sample used to assign it to one of the classes in the sampling plan. c. See two-class plan and three-class plan, below. Class. One of the conditions, such as ‘acceptable’, ‘marginally acceptable’ or ‘defective’ defined by quantitative limits. Colony forming unit (cfu). A bacterial or yeast cell, or small group of joined cells, or a fungal spore, cell or fragment of mycelium that gives rise to a single colony when grown on a solid medium. Consumer’s risk. The probability of accepting in error a lot that is defective. Defective. A lot that is not suitable for its intended purpose. A sample that gives a ‘failing’ test result – above the maximum acceptable level specified. Food Safety Objective (FSO). The frequency or maximum concentration of a microbiological hazard in a food considered acceptable for consumer protection. Good Manufacturing Practice. A formal approach to managing food quality. HACCP. Hazard Analysis Critical Control Point. A formal tool for managing food safety by identifying hazards and taking steps to ensure that they are controlled. ICMSF. International Commission on Microbiological Specifications for Foods: an international expert body with the primary role of giving guidance on appraising and controlling the microbiological safety and quality of foods. Lot. A defined quantity of a food or ingredient. A lot can be large and with a limited history, e.g. a shipload of grain, or small and with a clear history, e.g. a quantity of product made by batch mixing ingredients and further processing, e.g. 500 loaves of bread, with traceable records of all the ingredients. Or it could be somewhere in between, e.g. a truck load of flour from a mill that we deal with frequently or product made on a single production line during a recorded period of time (e.g. one hour, one shift). m. See two-class plan and three-class plan, below. M. See three-class plan, below. Marginally acceptable. A sample that gives a test result greater than the limit defined by good manufacturing practice but less than the limit defined by safety. n. See two-class plan and three-class plan, below. Operating characteristic (OC) curve. A graph relating the probability of accepting the lot to a measure of the underlying condition of the lot such as

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proportion defective or mean concentration of organisms. Producer’s risk. The probability that an acceptable lot is rejected in error. Probability of acceptance (Paccept). The likelihood of accepting the lot (on the basis of the test results). Probability of rejection (Preject). The likelihood of rejecting the lot (on the basis of the test results). Reject. Do not allow the food to be used for its intended purpose. This does not imply that the food may not be used for some other purpose – for example diverted to animal feed or processed to destroy the organisms of concern and then used in a different product. Sample. One dictionary definition of a sample is ‘a portion, piece or segment that is representative of a whole’ (Anon, 1982). The critical concept is that the portion represents the whole – if this is not true, no useful decision can be made based on properties of the sample. When sampling for pathogens we can think of a hierarchy of samples. At the highest level, there is the ‘lot sample’. This is a collection of individual units taken from the lot. Statisticians tend to refer to this collection of units as the sample, whereas microbiologists tend to use sample to indicate the individual units. Throughout this chapter we will defer to the microbiologists and use ‘sample’ to indicate the individual unit and the ICMSF term ‘population sample’ to represent the collection of units. However, it is important to be aware of this potential for confusion in the dialogue between microbiologists and statisticians, a dialogue that we fully recommend. Sometimes we may need to take a ‘subsample’ from each individual sample. For example, when testing for a very non-uniformly distributed contaminant we may initially take a sample of several kilograms and mix it thoroughly to distribute the contaminant as uniformly as possible in the sample. We can then take a subsample for ease of handling and storage. This type of procedure is used in aflatoxin testing (FAO, 1993; Whitaker et al., 1994). There is another important term ‘analytical sample’ which may be the whole sample, or subsample or a small portion of either, but which represents the actual material processed through the laboratory testing procedure. Two-class plan. An acceptance-sampling plan in which results for individual samples are assigned to one of two classes, ‘acceptable’ or ‘defective’, depending on whether they exceed the acceptable limit (ICMSF term m). A number of samples, n, are tested and the lot is rejected if more than c samples exceed m (usually c 0). Three-class plan. An acceptance-sampling plan in which results for individual samples are assigned to one of three classes, ‘acceptable’, ‘marginally acceptable’ or ‘defective’, depending on whether they exceed the acceptable (ICMSF term m) or marginally acceptable (ICMSF term M) limit. A number of samples, n, are tested and the lot is rejected if more than c samples exceed m or if any exceed M. (c decreases as the required plan stringency increases.)

Sampling techniques

2.2

23

The purpose of sampling

The point of sampling is usually to allow us to make a decision about the lot based on properties of the sample(s). The decision will be sound only to the extent that the sample truly represents those properties of the lot that concern us. So before we begin to sample anything, we need to understand clearly what our purpose is. When detecting pathogens in food, we usually intend to ensure that the food is safe to eat. Historically we would randomly select a food product at the end of a production line, or from a retail store. We would test it for the presence and/or concentration of pathogens and, if the laboratory results were ‘acceptably low’, we would conclude that the food was safe. This approach leaves us unsure about how truly representative the sample was. Hence, we are uncertain about whether we made a good decision. In this situation a formal, statistically-based, acceptance-sampling plan can tell us a great deal about how likely we are to make the ‘right’ or the ‘wrong’ decision. We will discuss this in more detail later in the chapter. We may have the fundamentally different aim of ensuring that a food manufacturing process can consistently make safe products. In this case, our emphasis should be on managing the process to eliminate pathogens or reduce their incidence and/or concentration in the product to an acceptable level. Management focus is on controlling those points in the process that play a critical role in ensuring product safety. A HACCP plan is the tool that helps to identify those points, sets appropriate control limits, and ensures that they are under control by appropriate monitoring and verification. We may use sampling of incoming raw materials as part of this control scheme. A statistically-based sampling plan here may help us to understand how likely we are to make the ‘right’ or the ‘wrong’ decision about whether to accept the incoming material. We may also use environmental sampling within the plant to help us minimize the possibility of cross-contamination from the environment (everything in the plant that is not food) to the food. The environmental sampling protocol will be based on experience of which parts of the plant environment have most contact with the product and which are most likely to harbor pathogens. Hence, environmental sampling protocols are not statistical sampling plans, though they may have a statistical element. For example, the protocol may stipulate increased levels of sampling once a test result shows that a sampling site is ‘out of control’. Within the HACCP plan we may be sampling finished product, but this now serves simply to verify that the process is under control. By statistical analysis of historical data from the process, we can establish whether the process is, in fact, capable of the performance that we require (Harris and Richardson, 1996; Hubbard, 1996). Occasionally we may already know, or suspect, that a foodstuff has an unacceptable level of pathogen contamination. In this instance, product sampling is a waste of available resources since, at best, it confirms what we already know or suspect whilst at worst it may lead us to conclude, incorrectly, that the food is safe. Rather we are interested in investigating the source of

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contamination so that we may subsequently eliminate it. Another circumstance concerns the decision of whether or not to accept a delivery of a material when we have no knowledge of its history. For an individual manufacturer this may be a consignment of a commodity raw material. For a regulatory agency it may be one of the many consignments of internationally-traded foodstuffs unloaded daily at ports and airports throughout the world.

2.3

Sampling and the problem of pathogen distribution

Consider that we are concerned with a toxin-forming pathogen, e.g. Staphylococcus aureus, where we can tolerate a measurable population of, say, 104 colony-forming units (cfu) per gram and still have a substantial safety margin before any toxin will be formed in the food. What issues do we face in deciding whether a lot is acceptable? Example 1. Consider a hypothetical continuously stirred tank containing 100 l of milk contaminated with S. aureus at a mean concentration of 106 cfu/ml. The mixing disperses the cells so that the concentration of cells in any particular 1 ml of milk will be roughly the same as in any other (they are uniformly distributed). There is no particular difficulty with sampling since any 1 ml sample would yield a count of about 106 cfu/g, which is substantially higher than our acceptable level of 104 cfu/g (Fig. 2.1a) and we would reject the milk. Example 2. Imagine that we refill the same tank with fresh milk. It is still well stirred so that the S. aureus is (approximately) uniformly distributed, but now it contains a mean concentration of about 1 cfu/ml. Again, there is no particular difficulty because any sample will contain a concentration of S. aureus well below our acceptable level of 104 cfu/ml (Fig. 2.1b) and we would accept the milk. Example 3. Now imagine that we have replaced the milk with a heavy cream, turned off the stirrer and allowed the temperature to rise until bacterial growth can occur. Just 5000 isolated S. aureus cells contaminated the tank but cell growth and division occur until the mean concentration is 2000 cfu/g, still well below our acceptable level of 104 cfu/g. However, because the cream is viscous and not stirred those cells are contained in 5000 micro colonies, each of 4 104 cells and each much smaller than 1 ml (Fig. 2.1c). Now we have a considerable difficulty, because most of the cream (95,000 1 ml portions) would give a result well below our acceptable level of 104 cfu/g, but 5000 portions of 1 ml would give a count above the acceptable level. There is a significant chance that we will make the wrong decision based on the result from a single 1 ml sample. Example 4. If we were to turn on the stirrer to mix the cream from example 3, the S. aureus cells would begin to disperse throughout the cream. If we took samples shortly after beginning to stir we would find that the number of cells in

Sampling techniques

25

Fig. 2.1 Schematic illustration (not to scale) of the relationship between hypothetical distributions of microorganisms in foods, the pattern of test results on sampling them and a hypothetical acceptable limit.

individual 1 ml aliquots of cream varies, with a distribution skewed to the right (Fig. 2.1d). In this example, taking logs of the counts we see that the log cfu/ml approximately follows a normal distribution (Fig. 2.1e). We could express this by indicating that the results were ‘log-normally distributed. If we stirred for long enough the cells would eventually become uniformly distributed. But in a solid food the opportunity for continuous mixing does not exist and the lognormal distribution of microbial load is most commonly seen. These

26


examples are all idealized and ignore the element of randomness seen in any real system that would mean some distribution of results would be seen in all cases – albeit that the distribution would be very narrow in a well-mixed system. Now assume that we are not concerned about S. aureus, but instead about an infectious pathogen such as Salmonella where our acceptable level is very low. In fact, we would like to be able to say that Salmonella is not present at all. Example 5. For the situation in example 1, any sample from the tank would yield Salmonella and we would correctly reject the milk. Example 6. For the situation in example 2, although the mean concentration is 1 cfu/ml, there is no assurance that any particular 1 ml sample will contain any Salmonella and some samples may contain more than one. Now, if we take a single 1 ml sample we are at risk of making the ‘wrong’ decision and accepting the milk even though it contains a significant number of Salmonella. Example 7. For the situation in example 3, the risk of making the wrong decision to accept the cream is even greater than that in example 6 because most of the potential samples would test negative even though there is a significant level of Salmonella in the lot. Example 8. For the situation in example 4 we are now at less risk than in example 7 of making the wrong decision because the mixing means that most of the individual portions contain (small numbers of) Salmonella but the risk is still significant. So how do we improve our chances of making the ‘right’ decision? And can we understand the risk of making the ‘wrong’ decision? A statistically-based acceptance sampling plan is the answer – though even the best plan, short of total destructive testing of the entire quantity of food, which is never a realistic option, cannot guarantee the ‘right’ decision. In 1974, the ICMSF published guidance on the use of sampling plans and microbiological criteria for foods in international trade (ICMSF, 1974) that was later updated (ICMSF, 1986). The plans were designed for sampling at ports of entry, where the sampler knows little or nothing about the history of the food before sampling and may know nothing about the distribution of pathogens in the food. The ICMSF scheme for port of entry sampling uses ‘attributes’ sampling plans, so called because the microbiological test results are used to attribute the samples to one of a number of classes: ‘acceptable’ or ‘defective’ (in a two-class plan) or ‘acceptable’, ‘marginally acceptable’ or ‘defective’ (in a three-class plan) by comparison with predetermined criteria. The decision to accept or reject the product is indicated by the number of test sample results in each class. Over the years, the attributes plans advocated by the ICMSF have become widely accepted to the point that they now form the basis for microbiological specifications in many trading contracts, and are written into food law in some countries. The ICMSF advice has been further updated

Sampling techniques

27

(ICMSF, 2002) to include a more risk-based approach to food safety management, including situations where the history of the food is known and/ or the distribution of pathogens in the food is understood.

2.3.1 Sampling and the degree of risk Given that we are always constrained by the availability of resources, how do we put our sampling effort where it will do the most good? The ICMSF (1974, 1986, 2002) presented a comprehensive scheme for use of acceptance sampling plans based on degree of health risk associated with a food and the change in health risk that is expected to occur between sampling and consumption. There are five levels of risk and three condition levels, leading to 15 cases (Table 2.1). Plans are selected depending on the case. Three-class plans are not very stringent and are appropriate where health risk is relatively low (cases 1 to 9). The plans’ stringencies are adjusted by changing the number of samples, n, the Table 2.1 ICMSF cases based on factors influencing risk and recommended attributes plans (ICMSF, 1986; table 10, p. 74). Reproduced with permission from The University of Toronto Press Conditions in which food is expected to be handled and consumed after sampling, in the usual course of events Degree of concern Conditions reduce degree of concern relative to utility and health hazard

Conditions cause no change in concern

Conditions may increase concern

No direct health hazard Utility, e.g. shelflife and spoilage

Increase shelf-life

No change

Reduce shelf-life

Case 1

Case 2

Case 3

3-class, n 5, c 3

3-class, n 5, c 2

3-class, n 5, c 1

Reduce hazard

No change

Increase hazard

Case 4

Case 5

Case 6

3-class, n 5, c 3

3-class, n 5, c 2

3-class, n 5, c 1

Case 7

Case 8

Case 9

3-class, n 5, c 2

3-class, n 5, c 1

3-class, n 10, c 1

Moderate, direct, potentially extensive spread

Case 10

Case 11

Case 12

2-class, n 5 , c 0

2-class, n 10, c 0

2-class, n 20, c 0

Severe direct

Case 13

Case 14

Case 15

2-class, n 15, c 0

2-class, n 30, c 0

2-class, n 60, c 0

Health hazard Low, indirect (indicator)

Moderate, direct, limited spread

28


upper limit on the ‘acceptable level’, m, and the upper limit on the ‘marginally acceptable level’, M, and the maximum tolerable number of results, c, that exceed m (Table 2.1). Two-class plans with c 0 are usually used for situations where the health risk is significant and the decision-maker is simply interested in whether or not a pathogen is present in a lot of foodstuffs (cases 10 to 15). The result is that the greatest sampling effort can be placed against the greatest hazard. Imagine that we are concerned about Staphylococcus aureus in milk powder. S. aureus would be considered a moderate hazard: as a foodborne illness it is not usually life threatening and symptoms are usually of short duration and selflimiting. Hence it would be assigned to cases 7–9. If we were receiving the milk powder for use as an ingredient in a baking operation we can see that subsequent processing (baking) reduces the risk (because the baking step would kill the pathogen). Accordingly this would be assigned to case 7 where a three-class plan having n 5 and c 2 is called for. What if, instead, we were concerned about Salmonella in paˆte´? Salmonella is a serious hazard of moderate duration and would be assigned to cases 10–12. In the case of paˆte´ there is no process to kill the Salmonella but growth could occur during storage, increasing the risk. Thus we would assign this to case 12 which calls for a two-class plan with n 20, c 2.

2.3.2 Effect of lot size For acceptance sampling where there is no requirement for larger lots to meet a more stringent standard – which is usually the case in food inspection – the number of samples taken is independent of lot size. This is because the probability of acceptance, based on the proportion of defective units in the lot, barely changes with lot size unless the number of samples taken represents at least one-quarter to one-half of the lot – a circumstance exceedingly rare in food examination (ICMSF, 2002, p. 125). If the number of defective units in a lot is more important than the proportion defective then the sampling plans described in this chapter are not appropriate. If the aim of the sampling exercise is to estimate the proportion of defective units in the lot, rather than to make an accept/reject decision remember that the confidence limits on that estimate will become narrower as the number of sample units tested increases but, again, the plans described here were not designed for this purpose.

2.4 Acceptance sampling when the history of the material is not known The ICMSF guidance, which has stood the test of more than 30 years of practical experience, can help us to select the sampling plan to use. But how can we assess the risk of making a ‘wrong’ decision?

Sampling techniques

29

Fig. 2.2 The relationships between acceptable and defective log concentrations for a two-class plan and acceptable, marginally acceptable and defective concentrations for a three-class plan, when m 3:0; M 4:0 and the distribution of organisms has mean 3.0 and 0:8. Pa is the proportion of acceptable material, Pm is the proportion marginally acceptable and Pd is the proportion defective. (Reprinted from Legan et al., 2001, with permission from Elsevier Science.)

2.4.1 Plan operating characteristics We select the sampling plan according to the risk-based case, and choose the limits of acceptable, m, (and marginally acceptable, M) concentration of the pathogen. Figure 2.2 illustrates how the proportion defective relates to the limit of acceptability for a lot where the microorganisms are lognormally distributed. We can then calculate the probability of acceptance (or conversely of rejection). Legan et al. (2001) described the details of this calculation using the multinomial distribution, which can be generalized to either the binomial or trinomial as appropriate. We could use the binomial distribution for a two-class plan and the trinomial distribution for a three-class plan. When we plot the probability of acceptance against the proportion of defective samples in the lot (for a two-class plan) we create the operating characteristic (OC) curve, which shows us how well the plan discriminates between acceptable and defective material and what the decision risk is with different proportions of defective units in the lot (Fig. 2.3). Two-class plans The operating characteristic curve allows us to recognize two categories of decision risk. The ‘producer’s risk’ is the probability that the plan will indicate rejection of a lot of food that is truly acceptable, and the ‘consumer’s risk’ is the probability that the plan will indicate acceptance of a lot which is truly unacceptable. The ideal OC curve would give a Paccept of 1 at all defect rates up to the acceptable level and a Paccept of 0 at all defect rates above the acceptable level. All realistic sampling plans fail to meet this ideal. The

30


Fig. 2.3 Operating characteristic curves for two-class sample plans: (a) OC curves for an ideal plan for an acceptable defect rate of 10% and an approximation to the ideal defined by n 120; c 10 and (b) OC curves for practical plans with n 5; c 0 and n 10; c 2.

steepness of the OC curve and plan stringency both increase as the number of samples increases. Plan stringency decreases as c increases, so it is possible, in principle, to approach the ‘ideal’ curve for an acceptable defect rate by using a large number of samples to increase the steepness of the curve and setting c accordingly (Fig. 2.3a). This approach would be indicated where sampling and testing are fast and inexpensive, the costs to both parties of the wrong decision are very high and there is a tolerable defect rate. This situation is unlikely ever to occur when sampling foods for pathogens. Hence we are forced to consider the compromises involved in more realistic sampling plans (Fig. 2.3b). The operating characteristic curves of these plans differ dramatically from the ideal. They are much less steep, and hence less discriminating, and when c 0 there is

Sampling techniques

31

no ‘shoulder’, implying that the plan will occasionally indicate rejection of a lot with a defect rate so low that we may, in fact, consider it acceptable. Nevertheless, these plans offer a realistic compromise between the degree of protection required and the resources needed for sampling and testing. Two-class plans are used when sampling for pathogens that we want to be absent from the food. For example if concerned about Salmonella, we would consider the two-class plans associated with cases 10–15 depending on the conditions of use and target consumer. These plans would give n 5, n 10, n 20, n 15, n 30 and n 60 respectively, all with c 0. Three-class plans Three-class plans are useful when we have some tolerance for ‘marginally defective’ material, which implies material that is outside the limits achieved by good manufacturing practice, so long as it is not hazardous. Just as we created an operating characteristic curve for a two-class plan (Fig. 2.3) so we can represent the operating characteristics of a three-class plan in a diagram; but now we have three variables to consider. These are the proportion defective (Pd), the proportion marginally defective (Pm) and the proportion acceptable (Pa) (see Fig. 2.2b). By plotting the Paccept against Pd and Pm we create the operating characteristic surface. This gives an overview of the plan operating characteristics but it is difficult to estimate Paccept accurately at any particular point on the surface (Fig. 2.4a). We could plot slices through the surface as twodimensional OC curves appearing similar to Fig. 2.3b by fixing Pm and plotting Paccept against Pd or by fixing Pd and plotting Paccept against Pm. Alternatively, we can use a contour plot (Fig. 2.4b) that allows us to estimate accurately all the values of Pd and Pm that give a desired Paccept. Three-class plans can be used when sampling for a pathogen that we can tolerate in food at low levels. For example if we are concerned about S. aureus

Fig. 2.4 (a) Operating characteristic surface showing an overview of plan performance for a three-class plan with n 5; c 3, (b) Contour plot for the same sampling plan linking combinations of proportion marginally acceptable and proportion defective that give equal probabilities of acceptance. This plan would be recommended for case 1 or case 4 in the ICMSF scheme.

32


we would consider the three-class plans associated with cases 7–9. If the food may support the growth of S. aureus, thereby increasing the risk, we would be in case 9 (Table 2.1) and we could use a sampling plan where n 10 and c 1. If we could be sure that no growth would occur and hence there would be no increase in risk we could use the plan for case 8 where n 5 and c 1.

2.4.2 Setting m and M (acceptable and marginally acceptable levels) Setting the values of m (limit of acceptable count in two- and three-class plans) and M (limit of marginally acceptable count in three-class plans) plays a critical role in determining the final performance of the sampling plan. This judgment is normally somewhat subjective and is based on our best knowledge about the pathogen of concern, the nature of the food, the status of the intended consumer and the demands of any relevant laws or regulations. Fortunately there are many prior examples of expert judgment that we can use to guide us (ICMSF, 1974, 1986; Shapton and Shapton, 1991). In a two-class plan we have only to set m. We typically use two-class plans when we have no tolerable level for the pathogen of concern. Accordingly we set m at zero. We must realize, however, that the true value of m defaults to the sensitivity of the analytical method used. An enrichment culture method applied to a 25 g sample, as in Salmonella testing, has a maximum theoretical sensitivity of one cell in the entire 25 g, which is equivalent to a concentration of 0.04 cells/ g and m is then equivalent to a concentration < 0.04 cells/g. For other pathogens such as Staphylococcus aureus where we do have some tolerance we typically use a three-class plan. Now we set M to the maximum tolerable level based on the hazard. We set m to a value that shows the food was produced under conditions of good hygienic practice (GHP). Where we have access to plant records these can be used to establish directly the level of m. The value of m is always lower than the value of M (or we have created a two-class plan) but otherwise there need be no quantitative relationship between them when used for pathogens. When a three-class plan is used for spoilage organisms a procedure developed by Dahms and Hildebrandt (1998) to set the difference between m and M can improve the overall level of control if the sample test results follow a lognormal distribution of known standard deviation.

2.4.3 Beware of ‘retest’ results When testing detects a pathogen and a two-class plan indicates rejection of a lot, we may be tempted to repeat the test using a retained portion of the sample or using new samples taken from the lot. We wish only to ‘confirm’ that the original result was correct before causing the disruption that may be associated with rejection of the lot. However, there are many reasons why a retest may fail to detect the pathogen that was correctly detected initially (ICMSF, 2002, pp. 191–7; Flowers and Curiale, 1993). Some of these are connected with the distribution of organisms in foods that we have previously discussed. Others

Sampling techniques

33

may be connected with a low incidence of contaminated units within a batch or a change in the concentration of the pathogen in the food making it harder to detect, even though it is still present. Hence an initial positive result should not simply be discarded in favor of a negative retest result unless there is a clear indication of a laboratory or sampling error associated with the first result. Even when retest results are considered in addition to the original results it is important to understand the nature of the resulting sampling plan. For example, at a defect rate of 5% the two plans n 60, c 0 and n 95, c 1 give the same probability of acceptance (in this instance 0.05). However, if one positive result is obtained from 60 samples tested and another 35 samples are then examined and all test negative we have not, in fact, used the plan n 95, c 1 which would justify accepting the lot. Rather we have used the two-stage plan n1 60, c1 1 plus n2 35, c2 0 which gives a higher probability of acceptance (actually 0.07; ICMSF, 2002). Montgomery (1996) shows how to calculate probabilities for two-stage plans. Even if we selected a two-stage plan giving the same Paccept as the plan with n 60, c 0 we should not forget that the implications of the plans can still be different. The decision to accept when no pathogens have been detected allows the possibility that the lot truly contains no pathogens. The decision to accept when one sample out of a larger number tested contained a detectable pathogen does not.

2.5 Acceptance sampling when the history of the material is known The ICMSF continues to recommend attributes sampling plans for circumstances where we have no knowledge of product history and/or have no knowledge of the distribution of pathogens in the food. However, it is increasingly realized that preventative measures such as Good Hygienic Practice (GHP) and Hazard Analysis and Critical Control Point (HACCP) systems are much more effective tools for managing food safety than end product testing. ICMSF advocated the use of HACCP in 1988 (ICMSF, 1988). Later, ICMSF published its scheme for managing microbiological risks (ICMSF, 1997). In this scheme a sampling plan is used to assure that a food is safe only when this assurance cannot be provided more effectively, for example, when there is no knowledge that GHP and HACCP have been properly applied. This advice has been considerably expanded in the latest ICMSF guidance (ICMSF, 2002), which advocates a risk-based approach wherever feasible. The heart of this riskbased approach is the Food Safety Objective (FSO: van Schothorst, 1998), which provides a functional link between risk assessment and risk management. Developments in quantitative risk assessments in microbiology (Buchanan et al., 1997; Whiting and Buchanan, 1997) have made it possible to link the exposure assessment of a pathogen to likely public health outcomes. It is then for society, through public officials charged with policy, to decide how much risk is tolerable and hence how much protection is required.

34


The question of how to join the ‘traditional’ and familiar use of attributes plans with the risk-based approach then arises. Legan et al. (2001) proposed a rescaling of the operating characteristic curves of attributes plans to show probability of acceptance at different concentrations of organisms based on the assumption that the logarithm of test results from microbiological sampling follow a normal distribution. In manufacturing, or other ongoing circumstances such as a relationship with a particular supplier, historical data are often available. These data can allow us to understand the typical distribution of test results, including testing the assumption that test results are lognormally distributed, and to use this knowledge when designing sampling plans and setting criteria.

2.5.1 Determining the concentration of microorganisms controlled by attributes plans Expressing the performance of attributes plans in terms of concentration of organisms has been suggested several times. Foster (1971) wrote, ‘at very low levels of contamination it may be more meaningful to talk in terms of concentration per unit’. Later, Hildebrandt et al. (1995) and Dahms and Hildebrandt (1998) discussed the performance of three-class attribute sampling plans in relation to the variability of the lot and the chosen values for m and M, assuming a lognormal distribution of counts. Their approach clearly makes the connection between the distribution of organisms in the food and the probability of finding defective units by sampling. Legan et al. (2001) built on the approach of Hildebrandt et al. (1995) using a statistical distribution of microorganisms to establish the proportion of defective samples in a lot, then using the calculated proportion of defective samples to determine the probability of acceptance in the usual way (i.e. cumulative binomial or multinomial distribution). Assuming a normal distribution for the log concentration of microbes, the area under the normal density function below m is used to define the value for proportion acceptable (Pa; Fig. 2.2). The area between m and M defines the value for proportion marginally acceptable (Pm; Fig. 2.2b), and the area above M (or m for a two-class plan) defines the value for proportion defective (Pd). The statistical methods for calculating the values of Pa, Pm and Pd are detailed in Legan et al. (2001). Operating characteristic curves relating probability of acceptance (Paccept) to lot mean concentration were developed by fixing the standard deviation , and then ‘sliding’ the mean of a normal distribution through a range of values. Figure 2.5 illustrates this for a two-class plan with n = 5, c 0, m 1.0 log cfu/ g. Figure 2.5a shows a normal distribution with 0.8 and three different means. Material with mean levels of contamination above m in each position is defective. When m is fixed, each different mean level of contamination gives a different Pd. Figure 2.5b plots Pd for all mean levels of contamination in the range ÿ2.0 to 5.0 log10 cfu/g to show how it increases with mean log count. Finally the Paccept at each Pd was computed using the binomial distribution and

Sampling techniques

35

Fig. 2.5 Illustration of the rescaling from concentration to probability of acceptance for a two-class plan with n 5, c 0, m= log count/g of 1.0. a) The distributions have 0:8 but different means. All parts of each distribution above m are defective. b) The proportion defective in each distribution illustrates the relationship between mean log count and proportion defective. c) The probability of acceptance determined for the relevant proportion defective using the operating characteristic curve (illustrated for n 5; c 0 in Fig. 2.3) gives the probability of acceptance for each mean log count/g. (Reprinted from Legan et al., 2001, with permission from Elsevier Science.)

plotted in Fig. 2.5c to give the operating characteristic curve that relates probability of acceptance to mean concentration of microorganisms. The last step is equivalent to reading the proportion defective associated with each mean log count from Fig. 2.5b and finding the associated probability of acceptance from the n 5, c 0 curve in Fig. 2.3b. This approach allows microbiologists to assess easily the performance of the sampling plans in terms of the familiar units of concentration of organisms.

36


Even the most stringent practical sampling plan (case 15: n 60, c 0) will accept a defect rate of 2% on 30% of sampling occasions. In this case defective means containing an unacceptably high concentration of the pathogen of concern, and a 2% defect rate implies 200 potentially hazardous units in a batch of 10,000, yet the sampling plan would indicate acceptance of the batch nearly one time in three! In the context of an ongoing relationship, a rejection rate of two in three would create pressure that rapidly leads to an improvement in future performance, but in the short term the acceptance rate of one in three may not provide the protection that we require. Rescaling this plan in terms of concentration of organisms, when m = log10–1.4 (a concentration of 0.04 cfu/g, equivalent to one cell in 25 g) and using as 0.8 log10 cfu/g there is a Paccept of 0.04 when the concentration is log10–2.7 (equivalent to one cell in 500 g). In other words, testing 60 samples and getting no positives only leaves us 96% sure that the concentration is below 1 cfu in 500 g. To put this into a risk-based perspective, one of the performance criteria recommended for managing Listeria monocytogenes in frankfurters is that ‘the concentration of L. monocytogenes after cooking (within the manufacturing plant) shall be 1 cfu/kg’ (ICMSF, 2002, p. 298). In other words, the most stringent sampling plan (case 15: n 60, c 0) would detect a process failure allowing this performance criterion to be exceeded by a factor of two on 96% of sampling occasions. Rescaling OC curves into units of concentration shows vividly the relationship between all of the elements of the sampling plan and the mean population of microorganisms that can be controlled by sampling. It makes very clear how high these concentrations are with plans involving practicably small numbers of samples when the detection limit of the analytical method is not a limiting factor. When sampling for pathogens and the test sensitivity is an issue, the concentrations of organisms that can be controlled are far from zero. For control of quality, spoilage or safety where the concern relates to relatively high numbers of microorganisms, the plans can be effective. Examples would include high numbers of food spoilage organisms, or S. aureus where it is generally regarded that 104–105 cfu/g are needed before toxin is formed. The plans are less effective in circumstances where concern relates to low numbers of microorganisms unless stringent cases, involving large numbers of samples, are used. The emergence of foodborne pathogens with a very low infective dose, e.g. pathogenic Escherichia coli, makes the application of even stringent microbiological criteria unlikely to ensure the safety of food with respect to the presence of these organisms. When historical data are available we can easily estimate whether or not the microbial population is described by a normal distribution of log counts. If it is not, many other distributions could be used. For example, the negative binomial may be useful if the distribution is heavily skewed to the right and has been used to describe the distribution of aflatoxin in peanut lots (Whitaker et al., 1994). It follows that examination of baseline data for different product and/or raw material streams to confirm the assumption of lognormality and to obtain estimates of would facilitate selection of appropriate values of n, c, m (and M).

Sampling techniques

37

2.5.2 Variables sampling plans When we are concerned about the mere presence of a pathogen, as in Salmonella testing, we have no choice but to use a two-class attributes plan with c 0 and n selected to give the discrimination that we require. However, if we are concerned about spoilage organisms, or pathogens where we have some tolerance for countable numbers, such as S. aureus, we may have the option of using a variables plan. The key advantage of a variables plan is that it captures all of the information in the test results (recorded counts and variance between multiple samples), whereas in an attributes plan, results are judged to be above or below the critical limit(s) m and M and the information on by how much is lost, as is the between sample variance. For example, in a three-class plan with m 102 and M 103, all results between 101 and 999 will carry the same weight. This ability to capture more of the information in the test results may make variables plans more cost-effective to operate than attributes plans. Variables plans may also remain more discriminating than attributes plans as the standard deviation of the data increases (ICMSF, 2002). Variables plans are, however, fundamentally different from attributes plans and may not, therefore, give generally equivalent indications. Variables plans are constructed on the assumption that the distribution of results is known. If this is not true then a variables plan cannot be used. Also, the decision rule in a (lognormal) variables plan is sensitive to the magnitude of the standard deviation. If the standard deviation in the test lot is greater than that used to set up the plan then the plan will not perform as expected. Microbiological test results can often be transformed to follow a normal distribution by taking logs of the count: we can say that the results follow a lognormal distribution. In a manufacturing environment, or when there is an ongoing relationship with a particular supplier, we may have enough accumulated data to show that in the long run the results follow a lognormal distribution. It is still possible that the log counts within a single batch may not be normally distributed but it is hard to test the lot distribution unless the number of samples is large. The lognormal distribution is used as the basis of published variables plans for microorganisms in foods (Kilsby et al., 1979; Kilsby, 1982; Malcolm, 1984; ICMSF, 1986, 2002; Jarvis, 2000). Once the underlying distribution (of log counts) is known to be normal, and the standard deviation has been established, the variables plan can be defined. The critical limit (C), that defines the boundary between acceptable and unacceptable material, is set (some authors use V to indicate this quantity). The value of C is the safety (or quality) limit in log concentration. The proportion of values that exceed the critical limit then depends on the population distribution such that: C ÿ = k where is the population mean, is the population standard deviation and k is a quantity to be used with normal probability tables found in most introductory statistical methods books (e.g. Montgomery, 1996) to find the proportion of the population that exceeds the critical limit C (Table 2.2).

38


Table 2.2

Values of k for different proportions of a lot exceeding the critical limit, C

%>C

Approximate k

%>C

Approximate k

1 2 5 10 15 20 25 30 35 40 45

2.32 2.05 1.65 1.30 1.05 0.85 0.67 0.52 0.38 0.25 0.13

50 55 60 65 70 75 80 85 90 95 99

0 ÿ0.12 ÿ0.25 ÿ0.38 ÿ0.52 ÿ0.68 ÿ0.85 ÿ1.05 ÿ1.30 ÿ1.65 ÿ2.32

Since k becomes smaller as the proportion > C increases, small values of k imply high proportions > C and we would want to reject any lot where the value of k was smaller than the value corresponding to the acceptable proportion > C. However, we cannot directly establish and . We can, instead, estimate them using the sample mean (x) and standard deviation (s). This allows us to use x and s to estimate the proportion > C through the quantity k0 where: C ÿ x=s k0 The estimates x and s carry a degree of uncertainty and k0 is about equally likely to fall above as below k. To compensate for this uncertainty the tolerance intervals k1 (for defined probability of rejection: Table 2.3) and k2 (for defined probability of acceptance: Table 2.4) have been calculated (Malcolm, 1984). Plans can then be designed to accept or reject with suitable probabilities based on the tails of the distribution of test results. Variables plans for safety and quality limits To use the variables plan for managing a safety or quality limit we must decide on the Pd that we are willing to tolerate and the probability (Preject) that we require of rejecting lots with a higher Pd. It is likely that in this case Pd is low and Preject is high. We refer to appropriate tables (Table 2.3) to find the value of k1 that connects Preject, Pd, and the number of samples tested, n. Using the sample log counts we calculate the sample mean (x) and standard deviation (s). We then calculate x k1 s and if this is greater than C we reject the lot. Variables plans for good manufacturing practice limits We can also use the variables plan to control good manufacturing practice limits. In this case we will select some limit Cm that we know is achievable when the operation is running well. This limit is somewhat analogous to the ICMSF limit m in a three-class plan. Now we want a high probability that we will accept the lot (Paccept) so long as the proportion > Cm is acceptable. Now both Paccept

Sampling techniques

39

Table 2.3 Values of k1 calculated using the non-central t-distribution for safety/quality limits. Reject if x k1 s > C. (Adapted from Malcolm, 1984, with permission. ß The Society for Applied Microbiology) Probability of rejection (Preject)

Proportion exceeding C (Pd)

Number of replicates (n) 3

0.99

0.10 0.20 0.30 0.40 0.50

4

5

6

7

8

9

10

2.3

5.4 4.0 3.0 2.3 1.7

4.4 3.3 2.5 1.9 1.4

3.9 2.9 2.2 1.6 1.2

3.5 2.6 2.0 1.5 1.1

3.2 2.4 1.8 1.4 1.0

3.0 2.2 1.7 1.3 0.9

0.95

0.05 0.10 0.30 0.50

7.7 6.2 3.3 1.7

5.1 4.2 2.3 1.2

4.2 3.4 1.9 0.95

3.7 3.0 1.6 0.82

3.4 2.8 1.5 0.73

3.2 2.6 1.4 0.67

3.0 2.4 1.3 0.62

2.9 2.4 1.3 0.58

0.90

0.10 0.25

4.3 2.6

3.2 2.0

2.7 1.7

2.5 1.5

2.3 1.4

2.2 1.4

2.1 1.3

2.1 1.3

Table 2.4 Values of k2 calculated using the non-central t-distribution for good manufacturing practice limits. Accept if x k2 s < Cm . (Adapted from Malcolm, 1984, with permission. ß The Society for Applied Microbiology) Probability of acceptance (Paccept)

Proportion exceeding Cm (Pm)

Number of replicates (n) 3

4

5

6

7

8

9

10

0.95

0.10 0.20 0.30

0.33 0.44 0.52 0.57 0.62 0.66 0.69 0.71 ÿ0.13 0.02 0.11 0.17 0.22 0.26 0.29 0.32 ÿ0.58 ÿ0.36 ÿ0.24 ÿ0.16 ÿ0.10 ÿ0.06 ÿ0.02 0.00

0.90

0.05 0.10 0.20 0.30 0.40 0.50

0.84 0.92 0.98 1.03 1.07 1.10 1.12 1.14 0.53 0.62 0.68 0.72 0.75 0.78 0.81 0.83 0.11 0.21 0.27 0.32 0.35 0.38 0.41 0.43 ÿ0.26 ÿ0.13 ÿ0.05 0.01 0.04 0.07 0.10 0.12 ÿ0.65 ÿ0.46 ÿ0.36 ÿ0.30 ÿ0.25 ÿ0.21 ÿ0.17 ÿ0.16 ÿ1.09 ÿ0.82 ÿ0.69 ÿ0.60 ÿ0.54 ÿ0.50 ÿ0.47 ÿ0.44

0.75

0.01 0.05 0.10 0.25 0.50

1.87 1.90 1.92 1.94 1.96 1.98 2.00 1.25 1.28 1.31 1.33 1.34 1.36 1.37 0.91 0.94 0.97 0.99 1.01 1.02 1.03 0.31 0.35 0.38 0.41 0.42 0.44 0.45 ÿ0.47 ÿ0.38 ÿ0.33 ÿ0.30 ÿ0.27 ÿ0.25 ÿ0.24

2.01 1.38 1.04 0.46 0.22

40


Fig 2.6 Schematic standards diagram showing GMP and safety limits for a variables sampling plan. The safety/quality limit is defined such that a lot has a probability of rejection of at least Preject if more than a given proportion pd exceeds the limit C (see Table 2.3), i.e. the mean and standard deviation (s) of samples from the lot fall to the right of the safety/quality line. If the mean and standard deviation together fall to the left of the safety/quality line the lot will be accepted. But some quality improvement action will be taken unless the standard deviation and mean together fall to the left of the GMP line. The GMP line is defined so that the batch has a probability of acceptance of at least Paccept if less than the proportion pm exceeds the limit Cm (Table 2.4). The GMP line is not operative to the right of the quality/safety line. (Adapted from Kilsby et al. (1979) with permission. ß The Society for Applied Microbiology.)

and the proportion > Cm could be high. From Table 2.4, we find the value of k2 that connects Paccept, Pd and the number of samples tested, n. Now we use the sample mean (x) and standard deviation (s) to calculate x k2 s and if this is equal to Cm we accept the lot. Figure 2.6 shows how the safety and GMP limits can be used together. Lots falling to the left of both the safety and GMP limits are completely satisfactory and lots falling to the right of the safety limit must be rejected. When a lot falls between the two limits this triggers an action to return the process to full control and may indicate additional actions with respect to that particular lot.

2.5.3 The connection between sampling and risk management We could characterize the ‘old-fashioned’ approach to sampling as an attempt to ‘test in’ safety. The development of good manufacturing practice, good hygienic practice and HACCP methodology has moved us to the modern, proactive

Sampling techniques

41

approach to food safety management where we design and operate production systems to build in safety. Sampling then became a means of monitoring that the system was performing as expected and detecting any substantial failures. Looking forward, a movement towards risk-based food safety management is emerging. For foods in international trade, the ICMSF scheme for managing microbiological risks proposed the Food Safety Objective (FSO) as a functional link between risk assessment and risk management. The FSO is defined as ‘a statement of the frequency or maximum concentration of a microbiological hazard in a food considered acceptable for consumer protection’ (van Schothorst, 1998) and allows the equivalence of different control measures to be established. Control measures include killing microorganisms during processing, preventing them from growing, e.g. by formulation, or temperature control during storage, and excluding them using sampling together with appropriate microbiological criteria. In order to compare the equivalence of different control measures we must be able to relate their performance in terms of achieving an FSO. In other words, can they maintain the frequency or maximum concentration of a pathogen at, or below, the level required for consumer protection? Variables sampling plans, and attributes plans re-scaled in terms of concentration of organisms, enable the performance achieved by different control measures to be compared directly in terms of concentration.

2.6 Environmental sampling and tightened inspection/skip lot sampling Environmental sampling may be thought to be strictly outside the scope of detecting pathogens in foods. But environmental pathogens in a food manufacturing facility can potentially become foodborne through crosscontamination so we will consider briefly this aspect of pathogen sampling. For the purpose of this discussion we assume that our hypothetical food processing facility is following the principles of good hygienic practice (GHP) as outlined by Codex (1997). This implies that there are procedures in place to manage the risk of environmental pathogens by, for example, minimizing crosscontamination from raw materials to finished product, having equipment of suitable sanitary design, appropriately maintaining and sanitizing equipment, removing waste, and training personnel. Environmental sampling then becomes a tool to ensure that those procedures are working. More detailed discussion of environmental sampling can be found in Holah (1999), ICMSF (2002) and Tompkin (2002).

2.6.1 Routine inspection In routine environmental sampling we want to ensure that the operation remains under control by detecting any increase in the risk of cross-contamination. First we need to know something about the ‘normal’ risk of cross-contamination when

42


the operation is under control. We may, initially, be interested in a wide range of pathogens, indicators or even spoilage organisms but will likely select just one for ongoing monitoring. We would probably start by taking process flow samples at various stages of the operation to determine how the microbiological condition of the food changes within the process. Food residues (crumbs, shavings and the like) may be sampled as a kind of composite sample of the process flow at a particular location and a guide to the potential for recontamination from held-up product. Product contact surfaces may be sampled at points in the process flow using swabs or sponges to assess a large area. When appropriate, equipment should be shut down so that covers can be removed and samples taken from inside. Samples should be taken at different times (e.g. beginning, middle and end of each shift; before and after cleaning, etc.). Samples may also be taken from drains, cleaning equipment, joins between floors and process equipment, etc. These samples can indicate sources of ongoing contamination. Results from all the samples should be arranged so that the ‘normal’ state of different locations when the process is under control can be seen and the most sensitive locations (and marker organisms) identified. The normal state may show a degree of seasonal variability, which will only become apparent over a number of years and is impossible to detect during an initial sampling exercise Environmental sampling protocols are not statistically-based; rather they are designed to pay most attention to those areas known to pose the highest risk of product contamination. However, some statistical concepts are applicable. Trend analysis can indicate unfavorable changes over time, even if individual changes are small and differential inspection rates allow the frequency of inspection to alter in response to the history of particular sampling locations. It is common practice to designate a number of zones within the processing plant, where different zones have different levels of risk of contaminating the product. ICMSF (2002) considers four zones: • Zone 1 includes all product contact surfaces that can potentially directly contaminate the food. Even in zone 1, we are most concerned with surfaces that can recontaminate the food after any microbial kill step and before packaging so not all surfaces are created equal. • Zone 2 includes equipment that is close to the product flow and could indirectly contaminate the food. • Zone 3 includes items within the processing area that could harbor contamination and/or transmit contamination to items in Zones 1 or 2. • Zone 4 includes items outside the processing area that, if not appropriately maintained, could serve as a reservoir of infection to the other three zones. The exact balance of samples from the four zones is based on experience of the sites most likely to indicate that the operation is ‘out of control’ in terms of good hygienic practice. The selection of sites can shift over time as operation of the sampling protocol improves knowledge of the operation. Knowing when to sample can be as important as knowing where to sample. In some operations, the most critical time may be immediately after startup. In

Sampling techniques

43

others, control may be lost slowly over time. The frequency of sampling may be increased if evidence indicates an increased risk and special sampling can be implemented in response to known risk factors such as construction.

2.6.2 Investigating a problem We may start an investigation in response to information suggesting that a problem already exists. Here we probably want to know the source of the problem so that we can take steps to correct it. Random sampling is not an efficient approach to an investigation. Rather the investigator must apply knowledge of microbiology, process operations and equipment design, along with information gained from visual inspection of the operation and the trigger for the investigation to determine those sampling sites most likely to harbor the organism(s) of concern. Examples include, but are not limited to, those sites suggested to establish a baseline for a routine monitoring program. Even whilst applying this pre-existing knowledge, it is important not to jump to conclusions, particularly when resources are limited and time is constrained (as is usually the case). To maintain a degree of flexibility, investigational sampling is very likely to be iterative. For example, the pathogen of concern may seem to enter the process at a particular point. We can then go back to examine in more detail the influences between the last ‘point of absence’ and the first ‘point of detection’. Over time the investigation works towards identifying the source and this process can sometimes be very lengthy.

2.6.3 Tightened inspection/skip lot sampling When we have an ongoing relationship with a supplier, or other ongoing sampling situation, we can, over time, develop a level of confidence in the performance of that supplier. That may lead us to relax the rate of sampling, including skipping sampling of some lots altogether, using the freed sampling resources where they can be more beneficial. If, however, the reduced rate of sampling finds a ‘defective’ lot we will revert to the initial sampling rate, or even to a more stringent level of sampling, until we develop confidence that the supplier’s performance has returned to an acceptable level. Formal methods for establishing such plans are described by Schilling (1982) and Montgomery (1996).

2.7

Taking samples

The process of physically selecting and taking samples is outside the scope of this chapter. Nevertheless, it may be helpful to keep some principles in mind: • For acceptance sampling, where a key assumption is that samples are representative of the lot, sample units should be selected randomly using a pre-determined scheme. It is easiest to sample when material is in motion and therefore accessible.

44


• For investigations it is more efficient to use targeted sampling. • Samples should be taken aseptically, and anyone charged with sampling for microbiological analysis needs appropriate training. Sampling equipment must be sterile, and must not violate management policies for other aspects of the operation. For example, it is common for glass to be banned from food production facilities and, where this is so, glass sample jars, etc., should not be used. • All results should be traceable back to the original sample. Appropriate labeling and documentation should be used. • Where samples must be stored and/or transported for analysis, they must be protected from contamination and physical damage, and maintained to prevent or minimize changes in the microbial population present. Wet or perishable samples may need to be maintained at chill temperatures in a refrigerator and shipped in an insulated container with ice or freezer packs. Frozen samples may need to be packed with dry ice to prevent thawing in transit. • The analyzing laboratory, whether in-house or a contractor or consultant should be capable of performing the required analyses reliably. Laboratories should have some formal procedures in place to assure this reliability. Formal quality management systems include those based on the ISO 9000 series, ISO Guide 25 or the principles of Good Laboratory Practice (Wood et al., 1998). • Samples should be as large as reasonably practical to minimize the impact of the distribution of microorganisms within the sample. For packaged food products the sample unit will be one or multiple product units (more product units for smaller products). For unpackaged food products, food within process, or bulk raw materials such as flour, sugar, etc., sample units in the region of 200–500 g are reasonably practicable. For environmental samples taken from a processing plant it may only be possible to recover 1–2 g, for example if scraping material from a gasket in a piece of process equipment. If it seems important to sample the site based on pre-existing knowledge or observations, the small sample should still be taken. • The sample unit is usually larger than the amount actually analyzed (the analytical sample). Where the nature of the sample permits, it should be aseptically blended before removing the analytical unit. For example shaking or squeezing may blend liquids or powders in a container with some headspace. This mixing is best done immediately before removing the analytical sample. • In qualitative analysis for the presence of a pathogen, combining multiple analytical samples into the enrichment phase of an analysis can significantly reduce the total amount of work when it has been shown to give equivalent recovery to not compositing. This does not sacrifice the discriminating power of the sampling plan since, with a two-class sampling plan where c 0, a single positive result is enough to indicate rejection of the lot. The critical condition is whether the total mass of analytical samples contains at least one detectable pathogen. Compositing is generally not sound in quantitative

Sampling techniques

45

testing, whether by a two- or three-class plan, because it has the effect of averaging the count across all the samples. For further detailed discussion on this topic, see Chapter 3.

2.8

Maximizing the value of test results

It is common practice to use test results once only to support a decision based on the plan criteria, e.g. to accept or reject a lot. The historical value of individual data points is often overlooked. Consequently quality laboratories may have files containing microbiological test results generated at great expense. Some simple techniques for plotting and statistically analyzing those data may greatly improve the return on the initial investment in testing. These techniques come from the field of statistical process control (Montgomery, 1996), which is used to great effect in many manufacturing operations but is still rarely applied to microbiological data.

2.8.1 Control charts Control charts are sequential plots of the data or some derivative such as the mean, range, standard deviation, etc., to allow trends to be observed. Depending on the exact nature of the chart, various kinds of warning or action limits or tests can be established. Variables data The simplest kind of control chart is known as an ‘X’, or ‘individual measurement’, chart. It is just a sequential plot of numerical results (e.g. log counts of an indicator or spoilage organism) against order of testing. This chart can show trends that may otherwise be missed, potentially allowing appropriate intervention before the count becomes unacceptably high. Equally it may help to identify times when the process results are better than normal and there is the opportunity to investigate to determine the cause and permit an ongoing improvement (Fig. 2.7a). A ‘control limit’ can be determined using ‘expert judgment’ and be drawn on the chart to give an immediate visual indication of an ‘out of control’ event. This control limit is typically the count at which the result is considered marginally acceptable. The criterion defining ‘out of control’ is then based on the number of marginally acceptable results observed within a pre-determined period of time or number of samples analyzed. Figure 2.7a shows hypothetical test results for a spoilage organism in samples from a process that is showing a trend towards loss of control through January. The predetermined criterion of two sequential marginally acceptable results shows that control was first lost in late January, but no action is taken until the acceptable limit is breached by a large margin in mid February. That triggered an investigation of the cause and a corrective intervention in late February resulting

46


Fig. 2.7 Hypothetical examples of control charts for (a) individual measurements (‘X’) and (b) attributes.

in control being regained. Note that the intervention reduced the variability as well as the mean of the test results. Also note that a response to the first observation of two sequential marginally acceptable results, even though individually they only just exceeded the limit, would have prevented the more serious later breach of the limit. Attributes data When the test gives only a positive or negative result, as when testing for the presence of Salmonella, it is still possible to plot the results in sequence. Now the ‘out of control’ condition is indicated when more than a pre-determined number of positive results are observed in sequence (Fig. 2.7b). Since this type

Sampling techniques

47

of chart can only show the direction of a result (positive or negative) it responds only to the sequence. Hence an ‘out of control’ condition will only be identified after a delay. Figure 2.7b shows hypothetical results of daily Salmonella tests for a process with a 10% incidence of positive results when in control. On the basis of past experience, positive results from three sequential tests are considered to indicate loss of control. The chart shows that control was lost on day 50 but, because the test method introduces a delay, this was not detected until day 56 when corrective action was immediately implemented and control was regained. More sophisticated control charts use formal statistical rules to derive the control limits, although the limits can be modified subsequently in the light of experience. Their use for microbiological data has been described by Jarvis (2000) and ICMSF (2002) and their statistical principles discussed in detail by Montgomery (1996). Using these charts we can: • determine whether the process is capable of consistently delivering the required performance (e.g. food safety objective, trading specification) • estimate the probability of severely out of control conditions based merely on the process variability (Peleg, 2002) • access a number of additional decision rules to identify out of control conditions on the basis of trends in the data, even when the control limits are not breached. Of course, within the context of food safety management, the use of control charts need not be restricted to microbiological results. They can be used to show data for any type of measurement used to manage a critical control point within a HACCP program and Khongsak and Hourigan (2002) gave an example for critical control points in shell egg washing. A full discussion of these approaches is outside the scope of this chapter, but the reader is encouraged to investigate further.

2.8.2 Process variability reduction The variability in a sequence of data is, itself, an important source of information. After statistical analysis to determine the distribution that best describes the observed variability it is possible to estimate the future frequency of extreme events, though not to predict when they will occur (Peleg and Horowitz, 2000; Nussinovitch and Peleg, 2000; Engel et al., 2001; Peleg, 2002). It is apparent that results are likely to reach extreme values more frequently when processes have large variability than when the variability is small. Hence, management intervention that reduces the variability of a process also reduces the likelihood of an extreme event such as an outbreak of food poisoning. The information on variability is already present in our records of test results over time. Such approaches are widely used in engineering but they are still quite rare for microbiological control. For example, Reneau (2001) described the use of an individual measurement control chart to plot bulk tank somatic cell count (BTSCC) in milk from a Wisconsin dairy herd. The BTSCC correlates with milk

48


microbiological quality and other factors. The chart allowed the reduced variability in somatic cell count caused by a management intervention to be identified rapidly so that the improvement in milking practice could be captured.

2.9

Future trends

Consumers in all developed countries are increasingly aware of food safety. Particularly since the emergence of foodborne listeriosis in the 1980s and of pathogenic Escherichia coli in the 1990s this has increased the pressure for pathogen testing and seems likely to increase the total number of samples tested. However, industry and regulators have known for many years that it is impossible to ‘test in’ safety. Rather, food safety is ‘designed in’ to products and assured by appropriate control procedures. Thus it seems likely that we will continue to see sampling resources increasingly used to monitor or verify process controls and assure good hygienic practice. As this shift progresses we would expect that ‘foods’, certainly finished products, will represent a smaller proportion of all samples tested for pathogens during food safety management. The trend towards Food Safety Objectives as risk-based targets will maintain the tendency towards control of the process and distribution system. It will also, in time, drive a more quantitative understanding of food safety and encourage the use of quantitative sampling plans that help to demonstrate the equivalence of different control measures. There is clearly value in the re-use of data through charting techniques and we expect that this will become commonplace in time. Indeed this is an area that seems poised for growth, initially through the advocacy of a small number of influential groups and later gathering momentum as the power of these approaches becomes more widely recognized. In short, we expect sampling to remain a critical element of food safety management for the foreseeable future, but with a more quantitative and proactive role than in the past.

2.10


Advice on the risk-based approach to food safety management is given in ICMSF (2002). This book gives detailed guidance on most of the topics discussed in this chapter. Jarvis (1989, 2000) gives more detail on the underlying statistics of sampling from the perspective of an experienced microbiologist. Information on ICMSF members, programs and publications can be found at http://www.dfst.csiro.au/icmsf.htm. For more background on attributes plans we recommend ICMSF (1986). Now out of print, part two of this book, giving sampling plans and criteria for a wide range of foodstuffs, is available as a free download from the ICMSF website at http://dfst.csiro.au/icmsf/book2.htm. A Microsoft Excel workbook for exploring performance of ICMSF recommended plans in terms of concentration of microorganisms based on the approach of

Sampling techniques

49

Legan et al. (2001) can also be downloaded free at http://www.dfst.csiro.au/ icmsf/samplingplans.htm. Another Excel workbook, based on the same principles but taking a different approach to designing and improving sampling plans, is available with a review from Campden & Chorleywood Food Research Association (Goddard et al., 2001). Many statistical packages can be used to create control charts. An easier approach for some people might be to use the Microsoft Excel workbook and accompanying guide available from Campden & Chorleywood Food Research Association (Jewell et al., 2002).

2.11

Acknowledgements

We would like to thank Joe Meyer for helpful comments on the manuscript, Martin Cole for prompting us to work on acceptance sampling in the first place, Keith Jewell for thoughts on use of control charts for microbiological data, and Lynne Hare for support and encouragement.

2.12

References

(1982) The American Heritage Dictionary New College Edition. Houghton Mifflin Publishers, Boston. BUCHANAN, R.L., DAMERT, W.G., WHITING, R.C. and VAN SCHOTHORST, M. (1997) Use of epidemiologic and food survey data to estimate a purposefully conservative doseresponse relationship for Listeria monocytogenes levels and incidence of listeriosis. Journal of Food Protection, 60(8) 918–22. CODEX (1997) Codex Alimentarius Commission, Joint FAO/WHO food standards programme Codex committee on food hygiene, supplement to volume 1B- 1997. Recommended international code of practice, general principles of food hygiene. CAC/RCP-1-1969, Rev. 3. DAHMS, S. and HILDEBRANDT, G. (1998) Some remarks on the design of three-class sampling plans. Journal of Food Protection, 61(6) 757–61. ENGEL, R., NORMAND, M.D., HOROWITZ, J. and PELEG, M. (2001) A qualitative probabilistic model of microbial outbursts in foods. Journal of the Science of Food and Agriculture, 81 1250–62. FAO (FOOD AND AGRICULTURE ORGANISATION) (1993) Sampling plans for aflatoxin analysis in peanuts and corn. FAO Food and Nutrition Paper no. 55. FAO, Rome. FLOWERS, R.S. and CURIALE, M.S. (1993) Qualitative microbiological testing: discrepancies between original and retest results. Scope, 8 1–5. Silliker Laboratories, Homewood, IL. FOSTER, E.M. (1971) The control of Salmonellae in processed foods: a classification system and sampling plan. Journal of the AOAC, 54(2) 259–66. GODDARD, M., JEWELL, K., MORTON, R.S., PAYNTER, O., RUEGG, J. and VOYSEY, P.A. (eds) (2001) Designing and improving acceptance sampling plans – a tool. Review No. 27. Campden & Chorleywood Food Research Association, Chipping Campden, UK. HARRIS, C.S.M and RICHARDSON, P.S. (1996) Review of principles, techniques and benefits ANON

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of statistical process control. Review No. 4. Campden & Chorleywood Food Research Association, Chipping Campden, UK. ¨ HMER, L. and DAHMS, S. (1995) Three-class attributes plans in HILDEBRANDT, G., BO microbiological quality control: a contribution to the discussion. Journal of Food Protection, 58 784–90. HOLAH, J (ed.) (1999) Effective microbiological sampling of food processing environments. Report no. 20. Campden & Chorleywood Food Research Association, Chipping Campden, UK. HUBBARD, M.R. (1996) Statistical quality control for the food industry. Chapman & Hall, London. ICMSF (INTERNATIONAL COMMISSION ON MICROBIOLOGICAL SPECIFICATIONS FOR FOODS)

(1974) Microorganisms in Foods 2. Sampling for microbiological analysis; principles and specific applications. University of Toronto Press, Toronto. ICMSF (INTERNATIONAL COMMISSION ON MICROBIOLOGICAL SPECIFICATIONS FOR FOODS)

(1986) Microorganisms in Foods 2. Sampling for microbiological analysis; principles and specific applications (2nd edn). Roberts, T.A., Bryan, F.L., Christian, J.H.B., Kilsby, D., Olson, J.C. Jr. and Silliker, J.H. (eds). University of Toronto Press, Toronto. ICMSF (INTERNATIONAL COMMISSION ON MICROBIOLOGICAL SPECIFICATIONS FOR FOODS)

(1988) Microorganisms in Foods 4. Application of the hazard analysis critical control point (HACCP) system to ensure microbiological safety and quality. Blackwell Scientific Publications, Oxford. ICMSF (INTERNATIONAL COMMISSION ON MICROBIOLOGICAL SPECIFICATIONS FOR FOODS)

(1997) Establishment of microbiological safety criteria for foods in international trade. World Health Statistics Quarterly, 50 119–23. ICMSF (INTERNATIONAL COMMISSION ON MICROBIOLOGICAL SPECIFICATIONS FOR FOODS)

(2002) Microorganisms in foods 7. Microbiological testing in food safety management. Tompkin, R.B., Roberts, T.A., van Schothorst, M., Cole, M.B., Gram, L., Buchanan R.L. and Dahms S. (eds). Kluwer Academic/Plenum Publishers, New York. JARVIS, B. (1989) Statistical aspects of the microbiological analysis of foods. Progress in Industrial Microbiology, vol 21. Elsevier, Amsterdam. JARVIS, B. (2000) Sampling for microbiological analysis. In The microbiological safety and quality of Food, Vol 2. pp. 1691–733. Lund, B.M., Baird-Parker, T.C. and Gould, G.W. (eds). Aspen Publishers, Gaithersburg, MD. JEWELL, K., VOYSEY, P AND THE STATISTICS AND SAMPLING WORKING PARTY (2002) Statistical quality assurance: how to use your microbiological data more than once. Review No. 36. Campden & Chorleywood Food Research Association, Chipping Campden, UK. KHONGSAK, S. and HOURIGAN, J.A. (2002) The use of statistical process control (SPC) to enhance the validation of critical control points (CCPs) in shell egg washing. Food Control, 13 263–73. KILSBY, D. (1982) Sampling schemes and limits. In Brown, M.H. (ed.), Meat Microbiology, pp. 387–421. Applied Science Publishers, London. KILSBY, D., ASPINALL, L.J. and BAIRD-PARKER, A.C. (1979) A system for setting numerical microbiological specifications for foods. Journal of Applied Bacteriology, 46 591–9. LEGAN, J.D., VANDEVEN, M.H., DAHMS, M.H. and COLE, M.B. (2001) Determining the concentration of micro-organisms controlled by attributes sampling plans. Food Control, 12 137–47.

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(1984) A note on the use of the non-central t-distribution in setting numerical microbiological specifications for foods. Journal of Applied Bacteriology, 57 175–7. MONTGOMERY, D. (1996) Introduction to Statistical Quality Control, 3rd edn, John Wiley & Sons, New York. NUSSINOVITCH, A. and PELEG, M. (2000) Analysis of the fluctuating patterns of microbial counts in frozen industrial food products. Food Research International, 33 53–62. PELEG, M. (2002) Interpretation of the irregularly fluctuating microbial counts in commercial dairy products. International Dairy Journal, 12 255–62. PELEG, M. and HOROWITZ, J. (2000) On estimating the probability of aperiodic outbursts of microbial populations from their fluctuating counts. Bulletin of Mathematical Biology, 62 17–35. RENEAU, J.K. (2001) Somatic cell counts: measures of farm management and milk quality. National Mastitis Council Annual Meeting Proceedings (2001), 29–37. SCHILLING, E.G. (1982) Acceptance Sampling in Quality Control, Marcel Dekker, New York. SHAPTON, D.A. and SHAPTON, N.F. (1991) Principles and Practices for the Safe Processing of Foods. Butterworth-Heinemann Ltd., Oxford. TOMPKIN, R.B. (2002) Control of Listeria monocytogenes in the food-processing environment. Journal of Food Protection, 65 709–25. VAN SCHOTHORST, M. (1998) Principles for the establishment of microbiological food safety objectives and related control measures. Food Control, 9 379–84. WHITAKER, T.B., GIESBRECHT, F.G., WU, J., HAYLER, W.H. and DOWELL, F.E. (1994) Predicting the distribution of aflatoxin test results from farmer’s stock peanuts. Journal of AOAC International, 77 659–66. WHITING, R.C. and BUCHANAN, R.L. (1997) Development of a quantitative risk assessment model for Salmonella enteritidis in pasteurized liquid eggs. International Journal of Food Microbiology, 36, 111–25. WOOD, R., NILSSON, A. and WALLIN, H. (1998) Quality in the Food Analysis Laboratory, pp 16–35. Cambridge, RSC. MALCOLM, S.

3 Separation and concentration of samples A.N. Sharpe, Filtaflex Ltd, Canada

3.1

Introduction: the need for separation and concentration

To detect even 100 cells of microbial pathogens per gram of food or raw material within 30 minutes would be very useful, but if we could confirm the presence (or absence), of one viable cell in 25 g of food within 30 minutes we could reject shipments at loading bays, divert raw materials, monitor HACCP Critical Control Points, etc. The reality is that rapid detection of microbial pathogens in foods at limiting regulatory levels is confounded by our inability to detect their minute signals amid the noise presented by food components, including competing flora. The identification kits and systems that have proliferated recently are mainly immunological, DNA hybridization, or conductance methods needing levels of about 105 organisms/ml for reliable detection. Reaching this level from 1 cell/ 25 g means a concentration gain of about 107 or 22 doublings. This gain is similar to overnight enrichment, making new methods unlikely candidates for direct tests. DNA amplification cannot be applied directly to 25 g food samples. However, if we could extract the target into a suitably small sample aliquot and amplify it without noise, a five-minute Polymerase Chain Reaction cycle would achieve the necessary concentration gain in about two hours. Current analyses use time inefficiently because we take for detection only a small aliquot of the microbes we have slowly cultivated during enrichment. Using a larger fraction of enrichment (e.g. by immunomagnetic separations) speeds analyses. However, the volume which can be handled is still small and takes us only part way towards the real challenge of rapid detection at regulatory levels. The need to amplify microbial signals to detectable levels in relatively large volumes (10–100 L) thus remains a major barrier to more rapid detection.

Separation and concentration of samples 53 However, ease of detection of microbes depends not on number but rather their concentration, which affects the signal-to-noise ratio. Physical, chemical or immunological methods might achieve massive gains in efficiency, not by increasing microbial numbers but by separating them from the food components and reducing the volume of suspension in which they exist. We could then employ rapid identification procedures that currently are impractical owing to poor signal-to-noise. As an example, microscopes or cytometers can, if there is no interfering noise, identify volumes of 10ÿ12 L (i.e. single cells). The concentration gains (107) needed to improve microbial signal-to-noise ratios for direct detection are still out of reach. Even ‘DEFT-type’ enzyme/ surfactant/membrane filtration treatment – still one of the best separation methods and quite successful for spoilage organisms – needs improving by several orders of magnitude before it can be applied to direct pathogen detection at regulatory levels. The effectiveness of separation and concentration techniques may depend on whether target organisms can be brought into a free planktonic state or have to be dealt with whilst still attached to larger particles.

3.2

General approaches to removal, separation and detection

Approaches to directly detecting pathogens in foods include: • extracting whole cells then identifying them after suitable concentration steps • using the cell’s phenotypy (serological or enzymological properties) • chemical extraction (e.g. DNA or RNA) to provide consistent analytical starting bases • detecting targets directly in product by confering on target cells some property (light emission, radioactivity, etc.) detectable against the background. This discussion is based on an assumption that for the forseeable future it will be necessary to first remove microorganisms from samples into liquid suspension, then concentrate them. Reliable pathogen detection then depends on two fundamental processes: 1. 2.

removing them (quantitatively?), from the sample into a primary suspension moving them quantitatively from this primary suspension into the detection device.

There is a pressing need for new methods to generate primary suspensions. With present technology (rinses, stomachers, blenders, etc.), one cannot suspend a high proportion of microorganisms from foods without producing large volumes of suspension (100–250 ml). Yet the powerful separation techniques (IMS, flow cytometers, etc.), cannot handle more than a few millilitres of suspension. Moreover, microbial capture reagents are prohibitively costly for large volumes. The most important (and most difficult) problem to solve or

54

Novel food packaging techniques

avoid is that of reducing a primary suspension to a volume of a few millilitres or less. It is the most difficult because • the primary suspension has a very variable composition, and • it cannot be attacked with expensive materials because of its volume. Once a suspension has been reduced to a few millilitres one can consider more ‘sophisticated’ techniques to concentrate the target further.

3.2.1 How efficiently must pathogens be extracted from foods? This question affects the credibility of any method not dependent on microbial multiplication. Any detection method based on separation will be measured against the performance of traditional methods, for which single viable cells can be detected given sufficient time and suitable enrichment conditions, even if organisms exist in the food in a tightly bound or protected state. The test of a novel (separation-based) method is not when there are >100 cells/g, but when there is only a single viable cell in the analytical sample. If it does not find that single cell it will prove inferior to the traditional method. Either it must be capable of collecting and detecting every cell of the target organism, or the probability of analytical samples containing this limiting concentration of cells must be low. For example, if the target occurs in a lot as sporadic colonies of a few million cells, the statistical distribution of local contamination levels will be such that samples tend to be either ‘clean’ or else heavily contaminated (i.e. only a very small proportion of samples will contain target cells at the limit of detectability of the rapid method). For such samples it will not matter if the novel method only detects samples containing >100 cells/g. However, if the target is distributed uniformly through a lot at a level of 1 cell/g (i.e. all samples are positive but each contains only a few target cells), then a separation-based method might perform poorly. Clearly, much depends on the statistics of the distribution of target cells in a typical lot. For the time being we should aim to develop techniques capable of detecting all target organisms in the conventional sample, or (preferably), techniques that provide an even better chance of detecting the target than do traditional methods.

3.2.2 Separation efficiency, speed and multiplexed separations Conventional detachment methods (blenders, etc.), yield large suspension volumes throughout which the target cells are distributed. To concentrate target cells they must be contacted by whatever means is effecting their separation, so it is vital to make rapid contact (‘hits’) with all the target cells. Unless one uses a ‘capture means’ (filter, column, beads, etc.), having a surface area and volume commensurate with the volume being processed, the hit rate is low and the method slow. How, at affordable costs, can we quickly capture target cells from large volumes? One can show that concentration processes will be faster if they are broken down into several smaller steps, each of lesser efficiency.

Separation and concentration of samples 55 In a single-stage concentration process a capture element (in reality, the final volume), passes through a sample N times greater in volume, until it has gone through the whole sample to capture the target from it. If it takes t s (specific sweep time) for the capture element to pass through its own volume in the sample (this factor remaining constant during the capture pass), one can show (Sharpe, 1991) that for single-stage, two-stage, three-stage, or p-stage, processes, the minimum times required for separation vary in the ratios: N ÿ 1; N 1=2 ; N 1=3 ; and N 1=p : To give perspective, imagine concentrating pathogens from 1,000 ml of sample suspension into a volume of 110ÿ9 ml (one high-power field), for microscopy, ignoring practicalities such as the need to prepare the product of one stage for introduction to the next. A value of t 0:001 s can be assumed for membrane filtration (other processes such as sweeping antibody-coated beads through samples will have different specific sweep times). Using this value for all steps used in reaching the required concentration gain we find that, for single-, two- and three-stage processes, total concentration times would be 1109 s (32 years), 2103 s (33 min), and 30 s, respectively. Even allowing for different specific sweep times of different processes one can appreciate that if we expect too much of any one stage the overall process is likely to slow down, and that multiplexing separations steps could yield dramatic improvements in speed.

3.3

‘Primary’ microbial removal methods

3.3.1 Swabs Of early techniques only the ‘Total Object Swab’ (Mossel and Buchli, 1964), or ‘Danish Swab Method’ (Olgaard, 1977) yielded reproducible fractions of surface counts provided by more rigorous methods, and only a few (using cellulose sponges or polyester-bonded cloths), permitted sampling the larger areas needed for environment sampling (Silliker and Gabis, 1975; Quevedo et al., 1977; Kirschner and Puleo, 1979). Ingram and Roberts (1976), found a ‘wet and dry’ swab method (a wet swab followed by rubbing down the area with a dry one), for carcasses and carcass meats gave summed counts from the two swabs ranging from 1–24 per cent (average 10) for fresh beef carcass, 27–52 per cent (average 37) for fresh mutton, 13–67 per cent (average 44) for fresh pork, and 25–89 per cent (average 39) for chilled pork belly, compared with counts from the excised, blended surface. Gill et al. (2001) showed that for fresh beef and pork carcasses, swabbing with cotton and wool recovered 30 per cent and gauze 10 per cent of counts compared with excision/stomaching, rising somewhat as carcasses aged. Palumbo et al. (1999) found that, for pork carcasses, a three-site swab method yielded the same incidence of E. coli as an excision method, while a one-site swab yielded rather less than half the positives. Thus, while swabs yield minimal debris, microbial removal is usually below the required efficiency.

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3.3.2 Is there is a ‘mass action’ effect? Data by Price (1938), Lillard (1938), and others, and my own (unpublished) observations, indicate that bacteria detach from surfaces until they reach a limiting concentration in suspension. The effect is important to rinsing, swabbing, stomaching, blending, etc. One explanation is that as rinsing, blending or stomaching continues, more and more food particles are released into suspension, so that rapid re-attachment of microbes to previously uncontaminated particles reduces their countability and minimizes further count increases. For example, Price (1938) had subjects scrub their hands, rinse them and repeat the process several times, counting the bacteria in each rinse and, using curves plotted from serial scrubbings, determined total skin bacterial counts. Fifty per cent of the skin’s bacterial population was removed after six minutes of scrubbing and the decrease on successive washes followed a first order reaction kinetic; other workers (Pohle and Stuart, 1940; Cade, 1952; Ulrich, 1961; Sheena and Stiles, 1983) confirmed or disagreed with these conclusions. Attenuation of the count per wash/rinse is of a similar order of magnitude to effects found for meat-based products: Leistner and Szentkuti (1970) reported a constant proportion of bacteria removed (17–24%), during each of six rinses of roosters; Carson et al. (1987) found rinsing poultry skin up to 30 times with saline only removed 90 per cent of Salmonella typhimurium; and Lillard (1988) found a continual strong removal by stomachings for up to 40 rinses of chicken skin, showing that even blending does not give a representative count. We can infer that bacterial removal techniques that are only as good as blending might not yield, say, the number of Salmonella positives as techniques where the whole specimen is first incubated in broth, and that novel techniques are needed to pull, say, >90 per cent of the organisms off a carcass. While not wishing to suggest that bacteria communicate with one another while being removed from foods, one has to wonder whether some sort of ‘mass action’ effect determines detachment of cells. If ‘mass action’ actually exists, a means for quickly capturing detached target cells, (reducing their suspension concentration to zero) could improve detachment methods. We normally think of dispersing all microbial cells, then trying to concentrate them, but just as chemical reactions can be driven to one side of the equation by removing the reaction product, if we could apply a ‘sink’ for the target organism to the sample we could ignore the remaining flora. If ‘mass action’ exists, the high concentration of removed microbes built up at a swab/sample interface would inhibit further removal, and inability to distribute removed microbes uniformly through the small quantity of diluent in the swab could explain the inefficient and variable swab performance. To test the idea of treating surfaces with a larger swab diluent volume and distributing and diluting the removed organisms throughout that volume, Sharpe developed the ‘Rotorinser’. It held 10 ml of diluent in an open-cell urethane foam cylinder; compressions and rotations of the cylinder against it pumped liquid repeatedly through the foam to bring microbes from the test surface into equilibrium with the diluent. On pork skin and beef carcass surfaces it proved more efficient at

Separation and concentration of samples 57 removing microbes than excision followed by stomaching (Sharpe et al., 1996), but did not become available commercially. 3.3.3 Paddle-type blenders and the PulsifierÕ By causing less tissue disruption than bladed blenders, paddle-type blenders (originally the StomacherÕ by Seward Medical, London, England) are useful in separating and concentrating microbes from foods. One should be concerned as to whether stomaching removes the majority of target cells from the food. The original Stomacher evaluation (Sharpe and Jackson, 1972, 1975) used saline or peptone diluent, but later studies recommended addition of 1 per cent Tween 80 to cope with foods containing fat (Sharpe and Harshman, 1976). In general, paddle-type blenders yield about the same count as bladed blenders and, until recently, this was assumed to yield the closest representation of the actual microbe content. A recent advancement is the PulsifierÕ (Sharpe, 2001), available through Microgen Bioproducts Ltd. (Surrey, UK). Instead of kneading and crushing samples, it applies a combination of shock waves and intense agitation. The Pulsifier yielded counts of total aerobes, coliforms and E. coli biotype 1 as high as or higher than a Stomacher. Significantly for separation technology, ‘pulsificates’ contained much less food debris unless the sample already was highly comminuted. For example, for celery and carrot Pulsifier : Stomacher total count ratios were 1.3 and 2.5, respectively, but pulsificates were clear while stomachates contained enough debris to interfere with pipetting (Fung et al., 1998) and membrane filtration rates were up to 12 times greater (Sharpe et al., 2000).

3.3.4 Sticky tapes There are many descriptions (even patents) using adhesive tapes for removing microbial cells from surfaces for direct microscopy or for plating and incubating in the manner of an agar contact technique (e.g., Thomas, 1961; Fung et al., 2000; Saika et al., 2001). An interesting publication (Imam and Gould, 1990) describes adhesion of amylolytic bacteria (Arthrobacter spp.) to a starch-based film – killed or inactivated cells did not adhere, suggesting that adhesion required cell viability and that surfaces might be tailored for binding specific microbes. Kyogashima et al. (1989) describe glycolipid receptors (N-glycolylsialoparagloboside, etc.) to bind E. coli K99, and several kits or patents have been based on similar compounds (Krivan et al., 1993; Ginsburg et al., 1996). Hydroxyapatite surfaces also specifically bind bacteria (Schilling and Doyle, 1995).

3.3.5 Sprays Sprays are relatively non-destructive and yield low debris levels, yet will remove bacteria from surfaces. In fact, they are used to reduce carcass bacterial

58


loads, though a common combination of sanitizing agents with sprays clouds the issue of just how many they actually remove. Anderson et al. (1977) found 99.9 per cent reductions in count when samples were washed with three per cent acetic acid at a pressure of 14 kg/cm2 and Roberts (1980) quoted carcass spray pressures of 228 and 1,137 kPa as removing 50–80 per cent of the bacterial contamination. In view of the inefficiency of unsanitized high-pressure sprays, some older reports seem surprising. Clark (1963) reported higher counts of Pseudomonas fluorescens by spraying inoculated chicken skin, lean beef and pork fat with diluent at a pressure of 35–207 kPa over sample surfaces, than either a blender or swabbing; favorable reports were given by Baumgart and Kussmann (1975), Hess and Lott (1970), Leistner (1979) and Reuter et al. (1979). Interest in sprays during that era was high enough that a commercial unit – the PASS (Portable Automatic Spray System, Pool Bioanalysis Italiana, Milan, Italy) – could be purchased. What would be the effect of jets of much higher pressure, such as are used to cut rocks? Pressure pulse immunization guns vaccinate through skin without other mechanical contact. Some foods obviously would not be suited, but skin would probably resist the cutting action of quite strong jets, while attached bacteria might be removed, even from crevices. A device that might be worth trying is the dental hygiene system ‘Water-Pik’ (Teledyne Water-Pik, Fort Collins, CO, USA); its use to remove bacteria from human skin was described by Staal and Noordzij (1978).

3.3.6 Ultrasound There are few studies on insonation for removal of microbes from foods. An ultrasonic tank gave good recovery for peas and beans, was less effective for intact meat pieces which clumped together to hide surfaces from the energy source, and worse with comminuted meat; however, it yielded suspensions with very low debris content (Sharpe and Kilsby, 1970). Dispersive (even chemical) effects of insonation occur only at intensity levels high enough to cause cavitation, which is quickly lethal to bacteria – sonication conditions must be a compromise between effectiveness and lethality. Several workers describe the use of ultrasound to move suspended particles around (e.g. Coakley et al., 1989; Grundy et al., 1989; Whitworth et al., 1991) and particle size, concentration, and other factors affecting efficiency were described by Miles et al. (1995). The idea of detaching cells from test surfaces and moving them off to a place of collection by using the same ultrasonic forces is tempting.

3.3.7 Gas bubbles Gas bubbles expanding from nuclei dislodge materials from surfaces. ‘Household Hints’-type books often suggest soaking stubborn deposits in Coca-Cola, and the advertising for some cleaning fluids suggests the same effect

Separation and concentration of samples 59 occurs. Perhaps more credible evidence – in electrolytic cleaning of metals – ‘gas scrubbing’ is very effective in removing scale and other unwanted surface material, and it is more effective when the metal part is the cathode because the volume of hydrogen liberated there is twice that of oxygen from the anode. Could this be applied to foods? The closer organisms are to the nucleation site of a bubble the greater the force they would experience. Catalase-positive organisms might be a good subject for study – they would be right at the spot. Could they be lifted off with dilute H2O2? Would it be possible to ‘aim’ catalase at target organisms by conjugating it to specific antibodies? It might not be necessary to use lethal levels of H2O2 – lower levels, followed by sudden evacuation of the vessel to cause outgassing might be sufficient.

3.4 Separation and concentration of cells once they have been removed Once an extraction method has detached cells from the food into suspension they must be brought into a more handleable state. Centrifugation and membrane filtration are absolute methods, in that all the target can be brought into the ultimate volume or area; other techniques may not collect the target so completely. The most important factor in trapping microbes from suspension to effect a concentration gain is the true state of those microbes. We have little idea when we blend, stomach, vortex stir, rinse, or otherwise suspend microbes, whether suspended microbes exist as single (or clumped) cells, or are still attached to tissue cells. While tissue cells may still be small enough to stay in suspension when we pipette in conventional plating procedures, they are many times larger than microbes. We can expect an enormous difference in the performance of capture systems, depending on whether bacteria are freely floating 1 m particles or 1 m particles attached to 20 m particles. Even if target bacteria were on the outside of such particles the forces needed to capture large composites must be many times greater (many times less probable) than for free bacteria.

3.4.1 Membrane filtration While the right pore size removes all target cells from a suspension, the success of membrane filters depends strongly on the filterability of food suspensions. Suspensions of unprocessed foods (raw meats, fish, vegetables) filter easily. With increasing levels of processing, addition of gums, fillers, etc., food suspensions become less filterable, and dairy products usually present problems. Filtration problems can be overcome: much work on the filtration of foods (temperature, pressure, flow direction, inclusion of Tween 80, and enzyme treatments, etc.) was carried out during development of the hydrophobic grid membrane filter (ISO-GRID HGMF, Neogen Inc., Lansing, MI, USA) (Sharpe et al., 1979; Peterkin and Sharpe, 1980, 1981; Entis et al., 1982). Around the

60


same time Pettipher and co-workers settled on trypsin/Triton X-100 digestion for milks and other foods as a means of removing unwanted debris while developing the Direct Epifluorescent Filter Technique (DEFT) (Cousins et al., 1979; Pettipher and Rodrigues, 1982; Pettipher, 1989; Rodrigues and Kroll, 1985). A complete discussion of enzyme treatments can be found in Sharpe and Peterkin (1988).

3.4.2 Centrifugation Despite being inconvenient, centrifugation has a major role in microbial separation. Centrifugation at 2000 g for 10 s prior to estimating biomass by ATP measurement removed virtually all meat particles without decrease in bacterial count (Stannard and Wood, 1983). Density gradient centrifugation removed food debris without loss of bacterial count in 15 min using colloidal silica (Basel et al., 1983) and the automated density gradient apparatus of the Bactoscan instrument (Foss Electric, Hillerod, Denmark) allows concentration of foodrelated microbes (Linhardt, 1987). Sedimentation Field-Flow Fractionation separated pure bacterial cultures – cells were injected into an open, unpacked channel, first sedimented by a low (5–10 RCF) centrifugal field, then fractionated by the parabolic fluid-velocity field as diluent passed through the chamber (Sharma et al., 1993). The method is probably applicable to foods.

3.4.3 Immunomagnetic separations (IMS) Microbes can be made ferromagnetic or paramagnetic by adsorbing submicron particles of magnetic iron oxides on their surfaces, treating them with Er3+ ions (Zborowski et al., 1993) or precipitating ferromagnetic ions on their surfaces (Ellwood et al., 1992). However, the popular methods involve immobilizing them, in suspension, on paramagnetic polystyrene beads (Dynabeads, Dynal, UK) or primed, silanized magnetic iron oxide particles (BioMag, Metachem Diagnostics Ltd, UK) by means of lectins or antibodies. The attraction lies in the speed and simplicity with which target species may be separated by a powerful magnet. Techniques may be as simple as collecting a pellet of magnetic cells, washing them by resuspending and recollecting, or more sophisticated processes such as thin-layer magnetophoresis (Payne et al., 1992; Safarik et al., 1995). Separated cells may be detected by plating on normal growth media, electrical impedance, or PCR where immunomagnetic separation can remove inhibitory materials (Fluit et al., 1993; Olsvik et al., 1991; Widjojoatmodjo et al., 1991) or ELISA (Krusell and Skovgaard, 1993). IMS can capture microbes that are dead or severely damaged and undetectable by standard culture techniques (Mansfield and Forsythe, 1993). In general, separation works best with high levels of immunomagnetic particles. For Salmonellae and E. coli O157:H7 particle concentrations of 106– 107/ml have been used (Skjerve et al., 1990; Vermunt et al., 1992; Fratamico et al., 1992). Incubations of 10–60 min are required, and attachment increases with

Separation and concentration of samples 61 time; however, with unduly long incubation non-specific attachment and heavy contamination with non-target microbes reduces the selectivity of immunomagnetic beads; surfactants such as Tween-20 or protamine reduce non-specific attachment. The utility of immunomagnetic beads is limited by the small volume treatable because of the short range of magnetic fields and a tendency for less-than-quantitative attachment even with great excesses of bead to target cell. Plate counts from immobilized microbes tend to be lower than the actual number of cells owing to a tendency for multiple attachment of cells; a common rule is that one colony may represent up to six target organisms (Skjerve et al., 1990; Skjerve and Olsvik, 1991). There are now hundreds of papers, techniques and kits related to IMS for separating suspended microbes, either directly from initial suspensions or after short enrichments. Just a small sample of current literature is indicated by descriptions of detection of Vibrio parahaemolyticus from shellfish (Hara-Kudo et al., 2001); E. coli O157:H7 from sprouts (Weagant and Bound, 2001), carcasses (Kang et al., 2001) or raw meats or milks (Chapman et al., 2001; Coia et al., 2001); Listeria monocytogenes and Salmonella from foods (Hsih and Tsen, 2001; Hudson et al., 2001); and Campylobacter jejuni from foods (Waller and Ogata, 2000).

3.4.4 Dielectrophoresis When an electric field is applied between plate and pin electrodes, conducting particles suspended in liquid in the non-uniform field migrate to or from the pin electrode, the direction depending on the relative conductivities of particle and liquid. Unlike electrophoresis, dielectrophoresis occurs in both AC or DC fields. Electrode assemblies are barely larger than the cells they are used with and may be fabricated on silicon semiconductor chips. Complex electrode arrays can also rotate cells, and since particles modify applied fields one can make some electronic analysis (Huang et al., 1992). While the small size of dielectrophoresis units prohibits their use for processing primary suspensions, the ability to combine them with electronic signal processing and control will make them useful for final microbe separations.

3.4.5 Biphasic partitioning Bacteria, viruses and other bodies partition themselves between the phases of aqueous biphasic systems (e.g. of polysaccharide and gelatin mixtures) permitting some degree of separation (Magnusson and Stendahl, 1985; Mattiason, 1983; Betts, 1993). Not only can Salmonella and E. coli be separated, but also rough/smooth mutants of Salmonella typhimurium (Stendahl et al., 1973). Practical applications in food microbiological analysis have not been described.

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3.4.6 Ion-exchange columns and sponges In general, microorganisms can only be separated from other material if they make contact with the separating element. In the 1980s considerable interesting work on separation by ion-exchange bead columns was described by the Leatherhead Food Research Association (Surrey, UK) in their in-house reports, though little seems to have been published in the regular journals. The advantage of bead columns is that target microorganisms are never more distant from a trapping surface than the maximum interbead spacing, optimizing the probability of hits. Disadvantages are that void volumes are relatively small so there is need for continuous flow (short contact times) to treat reasonable suspension volumes; they block easily; and bound microorganisms must be removed by a somewhat voluminous elution mixture. The ‘physical negative’ of a bead column is an open-cell sponge. I have not seen descriptions of the use of sponges in microbial separations, yet they have many potential attractions. Some sponge materials (e.g. the polyurethane used in the Filtaflex Ltd ‘FiltaTips’) have void volumes of about 97 per cent, superb flexibility, and are non-toxic to most species. Sponges suitably treated with binding receptors could permit: • initial separation of target from debris by the inherent filter effect of the sponge • treating of much larger suspension volumes per given volume of separating element – filled sponges could be left alone for extended periods, to optimize trapping • distances of target from trapping surface as close as with beads • compressibility to a fraction of the initial volume prior to adding eluting agent • ability to compress the sponge even further to express the liberated microorganisms. Thus, sponges might permit both separation and concentration in one operation.

3.5

Future trends

If HACCP procedures do manage to control pathogens to low levels in foods, an increasingly important goal of microbial separation should be to improve the efficiency of sampling procedures. Microorganisms generally are not distributed uniformly through lots or over surfaces. If they are distributed relatively uniformly but in low numbers, statistics dictates whether any particular sample does, or does not, contain a detectable target organism. Even when numbers are high, microbes may be present as a few colonies of many cells each. In either case, the microbiologist’s success in detecting the target depends considerably on the luck of sampling the right area at the right time. Statistics exerts a dismal effect on our probability of accepting or not accepting lots that contain appreciable proportions of defectives; the effect is well illustrated in Table 3.1.

Separation and concentration of samples 63 Table 3.1

Probability of accepting a lot for two-class attribute plans with c 0

Proportion of defectives

5

10

0.0000 0.0001 0.001 0.002 0.01 0.05 0.1 0.5

1.00 1.00 1.00 0.99 0.95 0.77 0.59 0.03

1.00 1.00 0.99 0.98 0.90 0.60 0.35 >0

Number of samples taken 20 60 1.00 1.00 0.98 0.98 0.82 0.36 0.12

1.00 1.00 0.94 0.89 0.55 0.05 >0

200

2000

1.00 1.00 0.82 0.94 0.40 >0

1.00 0.98 0.14 0.09 >0

Adapted from data in ICMSF (1986).

It is not possible to guarantee the microbiological status of a lot without taking 100 per cent of that lot for examination. Similar situations occur locally when levels of contamination are low or fluctuate. For example, an animal’s fur may remain contaminated after pathogen excretion stops; a rinsewater that was temporarily contaminated may be free of pathogen by the time it is sampled; or a low level of pathogen may be missed through swabbing the wrong area of a carcass. The traditional way of collecting samples places an upper limit on the reliability of any detection procedure. Given that there is a limit to the size of sample that can be sent off to the microbiology lab, are there ways to improve the probability of the analytical sample containing the target – for example, by increasing the apparent volume of product sampled or the duration of the sampling period? There may be advantages to changing the way we think about microbiological testing. For example, we may speak of ‘screening for a pathogen in 48 h . . .’. This actually means that the test method detects (or does not) its presence within 48 h of a sample reaching the lab. The irony is that the pathogen may be in the test environment (cattle pen, truck, crate, fruit, lettuce, conveyor, grinder, mixer, floor) hours or days before samples are taken, but analysis only begins when samples reach the lab, so this other lifetime of the pathogen is lost as far as the analysis is concerned. If we could begin the separation process before the traditional start time we might shorten the lab time needed to get the answer. The Microbe TrapÕ, jointly under development by Pharmacon Research, Inc. (Ottawa, ON, Canada) and Filtaflex Ltd, comprises a self-adhesive flexible substrate coated with binding receptors specific to microbial targets. It can be placed in the test site and left to capture target cells for any length of time before being removed to the laboratory. For example, it can be attached to cattle pens, cows’ tails, lettuce plants, apples, linemen’s overalls, plant equipment, grocery store chill cabinets, domestic kitchen counters, cutting boards, refrigerators, etc. The Microbe Trap attacks the sampling problem because it has more time, and more patience, to spend on its task than a human inspector (anyone who has

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fished for lobster will appreciate the difference in catch between dangling a net over the side of a boat during the time available, compared with leaving a baited trap on the sea floor for several days). But it also attacks the speed problem since, at the lab, non-selectively attached materials can be removed by rinsing, leaving the target in a relatively purified state suitable for rapid detection. The Microbe Trap is the subject of various patent applications.

3.6

References

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(1986), Microorganisms in Foods 2. Sampling for microbiological analysis; principles and specific applications (2nd). University of Toronto Press, Toronto. IMAM, S H and J M GOULD (1990), ‘Adhesion of an amylolytic Arthrobacter spp. to starchcontaining plastic films’, Appl Environ Microbiol, 56 872–6. INGRAM, M and T A ROBERTS (1976), ‘The microbiology of the red meat carcass and the slaughterhouse’, Roy Soc Health J, 96 270–6. KANG, D H, G A BARKOCY-GALLAGHE, M KOOHMARAIE and G R SIRAGUSA (2001), ‘Screening bovine carcass sponge samples for Escherichia coli O157 using a short enrichment coupled with immunomagnetic separation and a polymerase chain reaction-based (BAX), detection step’, J Food Prot, 64 1610–12. KIRSCHNER, L E and J R PULEO (1979), ‘Wipe-rinse technique for quantitating microbial contamination on large surfaces’, Appl Environ Microbiol, 38 466–70. KRIVAN, H C, V GINSBURG and D D ROBERTS (1993), ‘Carbohydrate receptor for bacteria and method for use thereof’, United States Patent 5,217,715.

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4 Validating detection techniques J. Debevere and M. Uyttendaele, University of Ghent, Belgium

4.1 Introduction Microbiological tests are important in governmental food inspection to enforce legal regulations, in international trade to determine compliance with a microbiological standard, in commercial relationships between trade partners to exercise control on agreed microbiological specifications, in the food industry to maintain quality control and process requirements, in academic laboratories for conducting research, and in reference laboratories to confirm the analyses of another laboratory and to provide surveillance data. The results of these tests should be reliable, making it important to determine the performance characteristics of a particular method. Apart from these technical characteristics it is important that all parties involved agree with and accept the methods employed. Mutual recognition of test methods in international trade facilitates commerce. Standardized methods have been elaborated by international, national or trade organizations such as ISO (International Standards Organization), AOAC International (formerly Association of Official Analytical Chemists), CEN (Comite´ Europeén de Normalisation), NMKL (Nordisk Metodikkomitte´ fo¨r Livsmeddel), AFNOR (Association Franç aise de Normalisation), NNI (Nederlands Normalisatie Instituut), DIN (Deutsches Institut fu¨r Normung), IDF (International Dairy Federation) etc. (Bertram-Drogatz et al., 2000).These standardized methods for detection of microbiological contaminants in foods are usually classical methods, primarily because the intention is to provide the users of these methods with a reliable and internationally accepted method which enables them to obtain equivalent results in different laboratory settings without having exclusivity of materials related to one manufacturer. Although, in

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essence, these standardized methods serve only as guidelines for reliable microbial analysis of foods, historically in many countries governmental agencies and trading agencies recommend or accept them as official methods for detection or enumeration of microorganisms in foods. They are considered as the reference methods (Hitchins, 1996; Lahellec, 1998). During the last decade several alternative (rapid) methods have been introduced for the detection and/or enumeration of microorganisms in foods as a result of recent developments in immunology, biotechnology and instrumentation. These alternative methods are often more rapid, user-friendly and open to automation and are thus of great interest to the food industry and control laboratories. Therefore, they are often preferred for daily use than the classical reference methods. Before alternative (rapid) methods can be used and accepted by the interested parties, it should be shown that the method is fit for its purpose by an independent organization. In practice, a method validation study needs to be performed to demonstrate that the intrinsic technical performance of these new procedures are acceptable. The increasing need for validated methods is also due to the concept of official laboratories which must be accredited according to the requirements of ISO 17025 and thus need to use either official (standardized) methods, validated alternative methods or, if using a modified standardized method or own developed alternative method, perform a proper validation. On the other hand it is evident that standardized or validated methods can only give reliable results if used in a food microbiology laboratory with an overall Quality Assurance programme in place. Section 4.2 defines a number of technical performance characteristics which are commonly determined in a validation study. Section 4.3 gives an overview of the validation protocols in use or suggested by AOAC International and the European validation procedures developed under the MicroVal project, and discusses a number of issues that need to be addressed in the preparation of a solid validation scheme. Some examples of performed validation studies of new techniques are discussed in Sections 4.4 and 4.5 to illustrate the abovementioned issues. Section 4.6 focuses on the need for the commitment to quality assurance of the laboratory management in order to provide controlled conditions to execute microbiological analytical procedures using validated methods. Finally Section 4.7 looks at future trends.

4.2

Definition of performance characteristics

Validation is the demonstration that the technical performance of the method is comparable to the existing standard method in order to provide confidence to the end user that a method has proven ability to detect or enumerate the organism or group of organisms specified. Validation should include one or a combination of the following procedures

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• determination of the performance of the method using reference materials or if not available well characterized pure cultures of relevant test strains • a methods comparison study • an inter-laboratory study • testing to determine the effect of the variables, e.g. period of incubation, food matrix, etc. on the performance of the method. Validation studies typically determine some or all of the following parameters.

4.2.1 Trueness (bias) (quantitative methods) The closeness of agreement between the true value or, if not known, the accepted reference value and the mean result which is obtained when the experimental procedure is applied a large number of times is known as the systematic error (Ellison et al., 2000; ISO, 2002). The trueness can be obtained by the analysis of certified reference materials (CRMs), derived from a certifying body (e.g. the Community Bureau of Reference (BCR) of the European Commission (EC)). The production of reference materials is based on spray drying bacteria suspended in milk. The highly contaminated milk powder obtained is mixed with sterile milk powder and treated for homogeneity and stability and filled into gelatine capsules. Based on microbial analysis by multiple laboratories with a high level of experience, a number of reference materials were subjected to BCR certification. Based on the BCR certificate, user tables are produced presenting the 95 per cent confidence limits for the number of capsules likely to be examined in practice (In ‘t Veld, 1998; In ‘t Veld et al. 1999). However, only a limited number of CRMs are available for microbiological purposes. Non-certified reference materials having known values are available from different organizations for more, if not all, microbial parameters. In microbiology, where almost no stable reference material is available, the analysis of spiked materials (recovery studies) can be performed as an alternative. ‘Known values’ can also be obtained after many replicated measurements with naturally contaminated samples using the reference method which is independent from the method to be validated. However, under these conditions the true value is not defined precisely and it is not possible to estimate correctly the trueness. An almost accurate approximation can be arrived at by measuring the same subsamples with the reference method and the alternative method. Participitation in proficiency testing schemes can also help in assessing the laboratory performance for the parameter of trueness.

4.2.2 Precision (quantitative methods) Precision may be defined as the closeness of agreement between independent test results obtained by applying the experimental procedure several times on the same sample under stipulated conditions ( random error) (Ellison et al., 2000; Notermans et al., 1997). The measure of precision is usually expressed in terms

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of imprecision and calculated as a standard deviation of the test results. Less precision is reflected by a larger standard deviation. Checks of precision in routinely used methods should be made to ensure that the result does not change with time as a result of changes in reagents, equipment, staff, etc. Distinction is made between: • repeatability: indicates the variability observed within a laboratory, over a short time, using a single operator, the same apparatus on identical test material • reproducibility: inter-laboratory reproducibility indicates the variability observed when different laboratories analyse the same sample by use of the same method and may be estimated directly by inter-laboratory study. Intra-laboratory reproducibility relates to the variation in results observed when one or more factors, such as time, equipment and operator, are varied within a laboratory.

4.2.3 Accuracy (qualitative and quantitative methods) Accuracy is the closeness of agreement between a test result and the true value, or if not known, the accepted reference value. Accuracy is a qualitative concept and involves a combination of random components and a common systematic error. For microbiological analyses the term ‘relative accuracy’ is sometimes used, defined as the degree of correspondence between the response obtained by the reference method and the response obtained by the alternative method on identical samples. The term ‘relative’ implies that the reference method does not automatically provide the accepted reference value (ISO, 2002).

4.2.4 The detection limit (qualitative and quantitative methods) The detection limit is the smallest number of culturable microorganisms that can be reliably detected in the sample. For qualitative methods it can be defined as the smallest number of culturable microorganisms that can be detected on 50 per cent of occasions by the alternative and reference methods. For quantitative methods the detection limit is higher than the critical level, the latter being the lowest level of culturable microorganisms that can be reliably enumerated, for instance, the average of a blank sample plus three times the standard deviation of the blank and can be determined by analysing a relatively high number of blank samples (ISO, 2002).

4.2.5 Linearity (quantitative methods) Linearity is the ability of the method when used with a given matrix to give results that are in proportion to the amount of analyte present in the sample. That is an increase in analyte produces a linear or proportional increase in results (ISO, 2002).


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4.2.6 Sensitivity and specificity (qualitative methods) Both sensitivity and specificity relate to the degree to which a method responds uniquely to the specified target organism or group of organisms and relate to the number of false positive and false negative results that are found with the validated method. Various definitions for sensitivity and specificity have been proposed (Notermans et al., 1997). The sensitivity of a method is the proportion of target organism that can be detected; it can be calculated using the following equation: sensitivity (per cent)

number of true positives P 100 P number of false negatives

A failure to detect the target when present is a false negative result and will lower the sensitivity of a test. In food microbiology only a very low frequency of false negative results can be tolerated for safety reasons. The specificity of a method is the ability to discriminate between the target organism and other organisms; it can be calculated using the formula: number of true negatives (N ) 100 specificity (per cent) N number of false positives A positive result in the absence of the target is a false positive result and will lower the specificity of a method. For rapid screening methods, a higher false positive frequency may be acceptable, as positive screening tests are followed by confirmation tests. In addition to the specificity and sensitivity as described above, also the inclusivity and exclusivity of a qualitative method may be determined, inclusivity being the ability of the validated method to detect a wide range of strains belonging to the target organism, exclusivity being the lack of detection with the validated method of a relevant range of non-target strains (ISO, 2002).

4.2.7 Robustness/ruggedness (qualitative and quantitative methods) Robustness may be defined as the sensitivity of the method for (small) changes in environmental conditions or method parameters during execution, e.g. time and temperature of incubation, sources of supplies, purity and shelf-life of reagents, etc. (Andrews, 1996).

4.2.8 Practicality Other considerations which can be important for adopting a new method and are generally referred to as practicality include (Andrews, 1996): • the safety hazards associated with the procedure • whether the procedure is quick and easy to perform and shows possibilities for automation • the need for the analyst to follow extensive training programmes

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• the availability of the method and the reputation of the manufacturer (services, quality system covering the production line).

4.2.9 Performance characteristics and standardized methods Determination of the performance characteristics of a method by validation will facilitate acceptance of the test results by international, national or regional regulators and trade partners. Standardized methods which are published by international, national or regional standardization organizations or trade organizations are considered as validated. In this case the laboratory has to demonstrate that criteria for validation indicated in the standard can be achieved. However, these standardized methods are not necessarily validated methods. In contrast to IDF and AOAC methods, which have gone through a validation study before acceptance, only recently a number of ISO methods have been submitted to a validation scheme by order of the European Commission (Standards, Measurement and Testing Fourth Framework Programme Project SMT4-CT962098). The performance characteristics of six ISO methods were determined, namely Bacillus cereus (enumeration), Listeria monocytogenes (detection and enumeration), Staphylococcus aureus (enumeration), Clostridium perfringens (enumeration) and Salmonella (detection) and will shortly be published in the corresponding ISO methods (Schulten et al., 2000; Scotter et al., 2001a,b). Nevertheless, ISO methods have historically been considered as internationally accepted standard methods, because they are the outcome of an open discussion between experts of the different participitating nations (recommended by the national committees) in dedicated working groups (ISO/TC34/SC9 for Microbiology) (Lahellec, 1998). Although these standardized methods are regularly revised to include improvements that have been made in classical methods this process is laborious and time-consuming and subsequently these methods are not always up-to-date with new developments. If any modification is made to a standardized method by the user, e.g. change in period of incubation, restriction in the number or use of other culture media or confirmation tests, a limited validation study should be performed. Recently numerous new methods have been developed which either generate results more rapidly than the classical culture methods and/or are easier to perform and open to automation. These methods can be developed ‘in-house’ or are available as a commercial test kit. An extensive validation study should be performed if the method is used on a routine basis in a control (official) laboratory applying for accreditation. Where an alternative method is used on a routine basis for internal laboratory use without the requirement to meet (higher) external criteria of quality assurance, e.g. in autocontrol or applied research laboratories, a less stringent comparative validation of the alternative method may be appropriate.


4.3

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Validation protocols

An appropriate procedure for a validation study should be developed for each proposed method. The validation protocol will differ for a qualitative or a quantitative method and the stringency of the criteria set for the technical characteristics of the method will depend upon the application of the method, e.g. rapid screening method in a HACCP programme or analytical procedure to detect the cause of a foodborne outbreak, and the scope of the method, e.g. type of microorganism and type of food involved. In the past different countries have developed different validation schemes. Several standardization organizations such as AOAC, IDF, AFNOR, NMKL, etc. have expanded their activities and started up a validation protocol for alternative methods. This has frustrated kit manufacturers, as they have to undertake a number of different validations in different countries, in order to get widespread acceptance of their test. There is a need of harmonization in validation schemes. In 2002, the European standard ‘Protocol for the validation of alternative methods’ was accepted by the CEN. This standard is the outcome of the MicroVal project which started in 1993 with the aim of setting up a European validation procedure (MicroVal Secretariat, 1998; Rentenaar, 1996). As such the first goal, to establish an international accepted protocol for validation of alternative microbiological methods through standardization, has been achieved. Through the CEN/ISO ‘Vienna agreement’ this European Standard will also be adopted as an ISO standard (ISO 16140) and agreements have been made with AOAC International for mutual recognition of the different validation schemes. The ISO 16140 has been prepared by Technical Committee CEN/TC 275 ‘Food analysis – Horizontal methods’ in collaboration with Technical Committee ISO/TC 34 ‘Agricultural food products’. A European organization for independent certification of alternative methods based on the European standard is set up (second goal of the MicroVal project) and pilot validation studies are ongoing (MicroVal Secretariat, 1998; Rentenaar 1996). The proposed ISO 16140 standard for validation of alternative methods describes a technical protocol for the validation of qualitative methods and a technical protocol for the validation of quantitative methods which both include a methods comparison study and an inter-laboratory study. Specific recommendations are given relating to the experimental setup of the measurement protocol and the calculation and interpretation of the data obtained using appropriate statistics. Standardization of the validation scheme as provided by the MicroVal is an important step towards consistent validation requirements. Nevertheless, the acceptance criteria are not clearly defined in the protocol. Results of the alternative method should be ‘comparable’ to those of the reference method. The actual criteria will depend on the type of method and the circumstances under consideration. AOAC International is an organization that has a long tradition in the validation of methods. The collaborative study forms the essence of the

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AOAC validation process. In this study, competent, experienced analysts, working independently in different laboratories, use a specified method to analyse homogeneous samples for a particular microorganism. Although no standardized protocol is available for the setup of the collaborative study, a number of recommendations are given regarding the minimum number of food types to be tested and the number of samples to be analysed for each food type. An Associate Referee, under the guidance of the General Referee and assisted by a statistical consultant, is responsible for the actual development of the protocol for the collaborative study which should be approved through the Methods Committee on Microbiology and Extraneous Materials. The Associate Referee also conducts ruggedness testing and a precollaborative study to determine the applicability of the method for detection of the target organism(s) in a wide range of food matrices and conditions. The Associate Referee is required to be an expert in a particular target organism or a particular type of method or a food matrix or a combination of these. The General Referee must be a recognized authority in the field of interest (De Smedt, 1998; Andrews, 1996). A number of issues need to be addressed in the preparation of a solid validation scheme.

4.3.1 Choice of reference method The reference method should be an internationally accepted method. Usually an internationally standardized method is chosen (ISO method, AOAC International accepted method, IDF method) or, if not available, certain national recognized methods or a method that has been published in a scientific journal and has been used succesfully for several years by several laboratories but without official recognition (ISO, 2002; Andrews, 1996). The choice of the reference method is of importance as it is supposed to give the true result. Indeed, for qualitative methods, the alternative method under validation is considered to produce a false positive result if a positive result is obtained while the reference method shows a negative result. This implies that the reference method should reveal all contaminated samples as true positives. For example for validation studies of rapid diagnostic kits for detection of Salmonella, the ISO method can be chosen as a reference method. However, as it has been shown that for certain food matrices a modified ISO method using a semi-solid medium such as Diassalm (LabM, Lancashire, England) or modified semi-solid Rappaport-Vassiliadis medium (MSRV, Oxoid, Basingstoke, England) instead of selective enrichment in a broth leads to a higher number of confirmed Salmonella positive samples than the original ISO method (De Zutter et al., 1991; Van Der Zee et al., 2002), this modified ISO method presents a good alternative to function as reference method in methods comparison studies (Poppe and Duncan, 1996).


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4.3.2 Number of food types to be tested and number of samples to be analysed The results of the method under validation are inherently affected by the type of food product under examination. The numbers, character and biochemical activities of the normal accompanying flora (background flora) in the food product affect the behaviour of the target organism(s). In addition the intrinsic and extrinsic properties (pH, aw, temperature, atmosphere, naturally occurring or added antimicrobial components) of the food product under consideration and the nature and intensity of processing to which it was submitted inflict sublethal injury on the target organism(s) and may reduce its recovery by the proposed method (Struijk, 1996). Moreover, the composition of the food itself can complicate the assay further because of the presence of a number of constituents that can directly interfere with the assay procedure itself as is often noted with PCR methods (Wilson, 1997). The number of food types to be included depends on the applicability of the method. If the method is to be validated for all foods, usually five categories of foods are included in the validation study. Food categories are predominantly determined by the origin of the product, e.g. meat products, poultry, fish and seafood, fruits and vegetables, dairy products, chocolate/bakery products and others (dressings and mayonnaise, egg products, cereals, etc.). Animals feeds and veterinary samples or environmental samples should be regarded as a separate category. Additionally the modes of processing to increase shelf-life, e.g. raw, heat processed, cured/salted, fermented, frozen, etc., may further be used to select food types within a category of foods (ISO, 2002). The types of food chosen should be relevant to the type of target organism(s) sought. For example validation studies for Bacillus cereus might include samples of rice, spices, raw and heat processed dairy products, heat processed vegetable-based products, whereas validation studies for Campylobacter might include raw poultry and meat, raw seafood, raw milk. However, if the applicability of the method is restricted the number of food categories may be reduced, e.g. the detection of Vibrio parahaemolyticus in fish and seafood products. The outcome of the validation study will recommend the acceptance of the method in the latter case for a particular type or otherwise for all types of foods. Whenever a method is validated for the detection of a particular target organism in all foods, questions arise as to whether the method is really effective with each individual type of food associated with that particular type of microorganism (Andrews, 1996). In the validation study only a limited number of food types are implied. If, for example, a validated method for Listeria monocytogenes indeed produces reliable results for five food types from each of five categories of foods (e.g. sliced prepacked cooked ham (heat processed meat product), raw milk based soft cheese (raw dairy product), smoked salmon (processed fish product), salad (raw vegetable product) and pasta (other products)), does this guarantee that the validated method will efficiently detect the presence of L. monocytogenes in raw milk, pasteurized cheeses, raw poultry, frozen fish, pate´, fermented meat, bakery yeast, etc.? This is still an open question and therefore the validation report

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should clearly state exactly which types of food were implicated in the validation study. Although the fact that a method is officially validated is an indication of good functioning of the detection or enumeration characteristic, the user of the method should always demonstrate that the method is producing reliable results if applied to its particular type of food matrix by a in-house limited validation study. With regard to the number of samples to be included in the validation study, a sufficient number of identical samples should be analysed by both the reference method and the method under validation in order to generate sufficient data to allow the use of appropriate statistics for interpretation. Examples of numbers of samples included in the validation study protocols proposed by MicroVal and used by AOAC International are shown in Table 4.1. It should be mentioned, however, that these numbers of samples are valid for an extended validation study of a commercial kit. The validation of an internal method in food control laboratories, industrial laboratories or applied research laboratories may include variable numbers of samples depending on the type and the scope of the method. This is further illustrated in Sections 4.4 and 4.5. It is recommended that the food samples in a methods comparison study come from as wide a distribution as possible in order to reduce any bias from local or seasonal factors and broaden the range of validation. It is desirable for qualitative methods to obtain approximately 50 per cent of positive results and 50 per cent of negative results for the same food type although this may not always be feasible when analysing naturally contaminated samples for foodborne pathogens. The reference method and the method under validation should be performed with, as far as possible, exactly the same sample. For example if the first stage of the two methods is the same (the same pre-enrichment broth or the same primary dilution) than take subsamples after this first step (ISO, 2002). Effective comparison of pathogen detection methods often requires testing at around the detection limit, where differences between methods are likely to be apparent. In this case it may be impossible to generate paired samples, where it is known that the number in one sample of the pair is accurately reflected in the other (Baylis et al., 2001).

4.3.3 Naturally contaminated food samples versus artificially contaminated food samples Whenever possible naturally contaminated samples should be used in methods comparison studies as these represent best real-life encountered samples with the target organism(s) present as a minority (if pathogenic bacteria) in a vast majority of other bacteria and in a non-optimal (stressed) condition due to the intrinsic properties of the food and the storage and processing conditions. Naturally contaminated samples can be collected from products analysed on a routine basis by the organizing laboratory or other laboratories. Storage should be minimized in order to prevent changes in both numbers of target organism present or the stress it is subjected to. Contamination should again be confirmed by the reference method before or during the validation study (ISO, 2002).

Table 4.1

Comparison of validation schemes suggested by MicroVal and AOAC International

MicroVala Qualitative method Inclusivity 50 strains Exclusivity 30 strains Methods comparison study Five categories of foods 60 samples per food category (minimum 3 food types) Detection limit 5 food types (5 food categories) 3 inocula levels: – control (uninoculated) – low (near the detection limit) – high (10 detection limit) 6 replicates each Inter-laboratory study at least 10 laboratories 1 to 3 food types 3 inocula levels 8 to 10 replicates each a b

ISO (2002), Scotter et al., 2001a, b. Andrews et al., (1998).

Quantitative method

AOAC Internationalb Qualitative method

Quantitative method

Inclusivity 30 strains Exclusivity 20 strains Methods comparison study Five categories of foods 5 levels of target organism(s) 2–10 replicates Detection and quantification limit Five categories of foods 6–10 blank samples

Inclusivity 100–200 strains Exclusivity 20–30 strains Precollaborative study 20 food types 3 inocula levels (single strain): – control (uninoculated) 5 replicates – low (near the detection limit) – high (10 detection limit) 20 replicates each

Inclusivity 30–40 strains Exclusivity 10–20 strains Precollaborative study 20 food types 4 inocula levels – control (uninoculated) – low – medium – high 5 replicates each

Inter-laboratory study at least 8 laboratories 1 to 3 food types 4 inocula levels at least 2 replicates each

Collaborative study at least 15 laboratories 5 food types 3 inocula levels 5 replicates each

Collaborative study at least 8 laboratories 5 food types 4 inocula levels 2 replicates each

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If it is not possible to acquire a sufficient number of naturally contaminated foods for each of the food categories implicated in the validation study, artificially contaminated samples (spiked samples) can be allowed. However, it is recommended that no more than 80 per cent of the samples should be artificially contaminated (Andrews, 1998). When artificially contaminated samples are used, the levels of inoculation and the preparation of the inocula to achieve these levels of inoculation should be similar to those expected to be found in naturally contaminated samples. For example, a protocol for preparation of stressed (sublethally injured) organisms should be defined (e.g. cold storage, freeze-stress, acid stress) (Baylis et al., 2001) and the degree of stress demonstrated at the time of inoculation, e.g. by comparison of the lagphase and/or the numbers of the stressed culture to the lag-phase and/or the numbers obtained for an optimal culture on a non-selective and/or selective culture medium (Baylis et al., 2001; Restaino et al., 2001; Uyttendaele et al., 2001). Also the background flora (numbers, distribution and ecology) of the samples used for artificial inoculation should be representative for the accompanying flora normally found in naturally contaminated samples (Andrews, 1996).

4.3.4 The source and number of inoculum strains Reference materials, containing appropriate but well defined levels of target organism in a stable but stressed state, may be used for spiking samples. However, for qualitative studies their use is limited when only a few strains or serotypes of food origin of the target organism are available as reference materials. Strains that have been isolated from the same type of food product are preferred over clinical isolates for spiking. If not possible, then inocula should be fully characterized (reference) cultures (Andrews, 1996; ISO, 2002). In the selection of strains to test inclusivity and exclusivity the majority of the strains should originate from the type of foods used in the validation study and cover the recognized range of the target organism with respect to the geographical distribution, incidence and diversity of the identification characteristics, its biochemical activity, serotype, phage type, etc. If the proposed method detects a defined target organism at the genus level, a range of species from that genus and if possible all species of the genus should be included, as well as a number of representative species from a range of genera within the same family. If the proposed method detects at the species level, a range of strains from that species should be included originating from different sources as well as representative strains from a range of species within the same genus. A number of representative strains of non-target organisms known to be part of the background flora of the type of foods included in the validation study could be included in the testing of selectivity of the method (ISO, 2002).


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4.4 The application of validation schemes: immunological methods Examples of the experimental design used for the evaluation of rapid methods in a number of studies are given here to illustrate the points made in the previous section. Because food manufacturers and regulators need quick and reliable information on the presence of foodborne pathogens in the food supply, numberous rapid or user-friendly methods for detection of foodborne pathogens (particular for Salmonella, Listeria monocytogenes and Escherichia coli O157:H7) are continuously introduced to the market. Consequently, the majority of the methods comparison studies performed and published concern qualitative methods for these pathogenic bacteria. The examples mentioned here include both immunological (Section 4.4) and molecular (Section 4.5) methods, and were chosen on the basis of their wide application and/or potential in food microbiological laboratories throughout the world. These examples are intended simply to illustrate the methodology applied for evaluation or validation of the alternative methods, and therefore no judgement on the actual performance should be made on the basis of these data, as more recent information on the actual methods’ performance may be available.

4.4.1 The VIDAS Listeria enzyme-linked fluorescent immunoassay The VIDAS Listeria (LIS) (BioMe´rieux, Marcy l’Etoile, France) is a qualitative enzyme-linked fluorescent immunoassay (ELFA) performed in the automated VIDAS instrument for the detection of Listeria spp. This method allows rapid screening for the presence of Listeria spp. in food and environmental samples after a 44–48 h prior enrichment step. Positive results must be confirmed by standard culture methods. The test kit’s performance was reviewed by the AOAC Research Institute’s Performance Tested Methods Programme and found to perform to the manufacturer’s specifications. Inclusivity and exclusivity were demonstrated with 206 strains of Listeria and 50 strains of non-Listeria microorganisms. In a precollaborative study including 980 samples consisting of uninoculated, inoculated and naturally contaminated samples representing 17 different foods, the test was shown to be as good or better than culture method tests (FDA-BAM 8th Edition) of the same samples. The collection of food matrices included dairy products, seafoods, vegetables, raw meats and poultry and cooked and processed meats and poultry. A number of environmental surfaces were also subject to testing. Subsequently, the VIDAS LIS method and the traditional culture method (FDA-BAM 8th Edition) were evaluated in a collaborative study. Nineteen laboratories participated in the study. Six food types (ice cream, cheese, green beans, fish, roast beef and ground turkey) were selected for the study. Ice cream, green beans and cheese were each inoculated with a different serovar of L. monocytogenes, roast beef was inoculated with a strain of L. innocua, and fish

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were inoculated with L. welshimeri. Ground turkey samples were naturally contaminated with Listeria. Each food type was divided into three portions; the first two were inoculated (1–5 cells/25 g for the low inoculation level and 10–50 cells/25 g for the high inoculum) and the third served as uninoculated (negative) control. Cheese samples were stabilized by storage for five days at 4ºC. All other samples were stabilized by storage for five days at ÿ20ºC. Each collaborator received a set of 15 samples for each food product (five replicates of each inoculum level and negative control). Of 1558 samples tested, 935 were positive: 839 by the VIDAS method and 809 by standard culture method tests. Overall false negative rates were 10.3 and 13.5 per cent for the VIDAS LIS and culture methods, respectively. The false positive rate for the VIDAS LIS assay was 1.4 per cent based on nine VIDAS LIS positive assays that did not confirm positive by isolation of Listeria. The agreement between the VIDAS LIS and culture methods for all samples tested was 86 per cent. Results for each food type and each contamination level were as good or better than those obtained with the traditional culture method (Gangar et al., 2000). On the basis of these studies the VIDAS LIS method for detection of Listeria spp. was recommended for Official First Action. The recommendation was approved by the Methods Committee on Microbiology and Extraneous Materials, and was adopted by the Official Methods Board of AOAC International. The VIDAS LIS kit also received an AFNOR validation certificate (No. Bio 12/2–06/94) for the rapid detection of Listeria spp. in all food products. Inclusivity and exclusivity (indicated as specificity by the AFNOR certificate) were demonstrated with 217 strains of Listeria (207 were isolated from food and 10 were L. monocytogenes collection samples) and 35 strains of non-Listeria microorganisms. The intrinsic detection limit defined as the number of Listeria required to obtain a positive response with the VIDAS LIS kit was between 104 and 105 cfu/ml obtained on four pure strains of Listeria. The detection limit was performed using four different types of food (meat, vegetables, milk products and seafood), each artificially contaminated with four strains of Listeria at five different contamination levels: 0, 1–10, 2–20, 5–50 and 10–100 bacteria per 25 g. Agreement between the two methods was found to be 96.4 per cent (80/ 83). The three false readings involved levels of two or three bacteria per 25 g. Accuracy was determined by a methods comparison study of the VIDAS LIS method with the reference method (ISO 11290-1) using 204 samples (various products) of which 88 were naturally contaminated and 116 uncontaminated. All samples were tested in duplicate by both the VIDAS LIS method and the reference method. Overall the concordance between the VIDAS LIS kit and the reference technique was catalogued as good by AFNOR (eight false negatives were obtained with the VIDAS LIS kit and five false negatives with the reference method). Precision data were determined during an inter-laboratory assay involving 13 laboratories. Analyses were performed using pasteurized milk samples artificially contaminated with a L. monocytogenes strain at four different levels: 0, 1–10, 5–50 and 10–100 cells per 25 g. All the results were concordant with expected results. The method was shown to be reliable.


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4.4.2 Dynabeads anti-Salmonella Dynabeads anti-Salmonella (Dynal, Oslo) employs magnetizable particles coated with specific antibodies to concentrate all Salmonella serovariants selectively from foods and environmental samples. The technique which takes 15–20 minutes, may replace or enhance the performance of the 18–48 h conventional selective enrichments. The originally described protocol included immunomagnetic separation (IMS) from buffered peptone water (BPW) enriched food samples followed by plating (IMS-plating). The direct plating of bead-bacteria complexes onto solid media is suitable for processed foods or samples known to have a history of very low resident flora. For raw food samples, for example raw poultry, in some instances IMS-plating resulted in the overgrowth of target salmonellae by competitive enteric flora on the plating media. A modified IMS protocol consisting of the standard pre-enrichment of samples in BPW followed by IMS and subsequent selective enrichment of the bead-bacteria complexes in Rappaport-Vassiliadis Soya Peptone broth before plating on selective media (IMS-RVS-plating) was evaluated as an alternative to the traditional culture method for detection of Salmonella. The performance of both the IMS-plating and the IMS-RVS-plating protocol was compared to the conventional ISO 6579 method using ten food samples (powdered skimmed milk, mayonnaise, cake-mix, raw chicken meat, cooked sausage, cheese, pepper, meat balls, lasagne, casein) inoculated with 20 different Salmonella serotypes (two serotypes for each food sample) at low (1–5 cfu/25 g) and medium (10– 50 cfu/25 g) level before pre-enrichment. All inoculated samples were frozen for one month before being examined. A 100 per cent concordance was achieved between the direct IMS-plating and IMS-RVS-plating for the ten diverse food samples (processed and raw) but the latter protocol assisted in the formation of well isolated near pure cultures of salmonellae on the plates. The IMS method showed respectively a 90 per cent and 95 per cent concordance with the ISO method and isolated respectively two and one more Salmonella positive sample than the conventional ISO method at the low and medium inoculum level. In an evaluation of both IMS protocols using 100 naturally contaminated samples (50 poultry carcasses, 20 cloacal and/or faecal swabs, 15 chicken liver samples, 15 chicken breast meat samples, and 10 poultry feed samples) the advantage of the IMS-RVS-plating method (39 positive samples detected) compared to the conventional ISO 6579 reference method (31 positive samples detected) and the IMS-plating method (only 20 positive samples detected) was clearly demonstrated (Cudjoe and Krona, 1997). The IMS separation method has been successfully combined with the ELISA technique as the end-detection method for the recovery of Salmonella Enteritidis from eggs and skimmed milk powder. However, studies of raw chicken using a combined IMS and ELISA technique gave a significant number of false negative results because of high levels of competing flora. A study was performed to evaluate a modified IMS-ELISA method involving the resuspension of the beadbacteria complexes and incubation in GN broth at 42ºC for 6 h prior to ELISA analysis. The present study is, however, an example of a study with a (too)

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limited experimental setup. In the first part only two food types, animal feed and raw chicken, artificially inoculated, not in the food matrix but in the BPW preenrichment broth, using rather high inoculum levels (2000, 200 and 20 cfu per ml) and only three serotypes of Salmonella were involved (18 samples in total) to demonstrate that direct application of IMS-ELISA failed most of the time although RV-XLD (conventional culture method) and IMS-XLD succeeded in detecting Salmonella. The second part was even more restricted and stated the improved detection of Salmonella using IMS-GN-ELISA compared to the conventional RV-XLD methodology on the basis of 15 samples (triplet raw chicken pre-enrichment broths artificially inoculated with S. Enteritidis at 5 inoculum levels) (Mansfield and Forsythe, 2001).

4.5

The application of validation schemes: molecular methods

4.5.1 The ProbeliaTM Salmonella PCR system Recently, the polymerase chain reaction (PCR) has emerged as an increasingly important diagnostic tool in food microbiology. The ProbeliaTM Salmonella PCR amplification and detection kits (Bio-Rad, Marnes la Coquette, France) have received AFNOR approval for detection of Salmonella in foodstuffs. The ProbeliaTM Salmonella PCR system is based on the amplification of the iagA gene (involved in the bacterial invasion process) of Salmonella spp. by PCR followed by probe hybridization in a 96-well format for colorimetric detection. In an independent study (Wan et al., 2000) the ProbeliaTM PCR system was evaluated for rapid and specific detection of Salmonella spp. in dairy products and compared to the Australian Standard Method. Using bacterial DNA preparations derived from ten-fold serial dilutions of a pure culture of Salmonella Agona, the intrinsic detection limit of ProbeliaTM was determined as being between 8 and 79 cfu/ml, equivalent to 0.2–2 cfu per PCR reaction. Next, a methods comparison study was performed using artificially inoculated (with S. Agona) skim milk powder at 5–10 cfu/g and subjected to analysis immediately and after storage for two up to four to six weeks at 5, 15 or 25ºC (five replicates at each sampling point). A second food type was included: artificially inoculated ricotta cheese at 1–2, 10–20 and 100–200 cfu per 25 g (three replicates each). For all of the 40 milk powder samples and 12 ricotta cheese samples, the ProbeliaTM results were consistent with those of the Australian Standard Method. The present study was restricted to dairy products: two food types were included, however, only one Salmonella strain was involved, S. Agona. Naturally contaminated samples were not included. Recently the ProbeliaTM Salmonella PCR system was replaced by the manufacturer by a real-time PCR based kit iQ-Check Salmonella, applying a fluorescent probe hybridizing to the generated amplified products and measuring fluorescence directly in the tubes during the PCR annealing step.


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4.5.2 The TaqmanTM Salmonella PCR system The Taqman assay is a fluorogenic PCR-based format enabling real-time detection of PCR products. The assay utilizes the 50 nuclease activity of Taq DNA polymerase to hydrolyse an internal fluorogenic probe for monitoring the amplification of DNA target (the Salmonella invA gene). Studies were performed to elucidate the specificity and sensitivity of the assay for pure cultures of Salmonella and for Salmonella-contaminated foods (Chen et al., 1997). A total of 164 Salmonella strains representing all the subspecies of Salmonella enterica were detected while 52 non-Salmonella strains were not detected. The intrinsic detection limit of the PCR assay was 2 cfu per PCR reaction when 10-fold serial dilutions of a pure culture of S. Typhimurium were used (PCR assays conducted in duplicate and replicated on different days). An appropriate sample preparation protocol was selected for the isolation of PCRamplifiable DNA from foods. A detection limit of 3–7 cfu/PCR reaction was obtained using post-enrichment spiked food samples (ground beef, ground pork) inoculated with 10-fold dilutions of the S. Typhimurium strain and ca. 3 cfu per 25 g were detected when foods (raw milk, ground beef, ground pork) were inoculated with 2-fold dilutions of the same Salmonella strain and pre-enriched overnight. In both experiments no replicates were involved. Finally naturally contaminated foods (50 chicken carcass rinses and 60 raw milk samples) were examined for Salmonella using both the fluorogenic TaqmanTM assay and the MSRV culture method which was used as the reference method. The concordance between the two methods was over 98 per cent. Two samples were Salmonella positive by the PCR assay but negative by the MSRV method.

4.5.3 A PCR-ELISA test for detection of Shiga toxin-producing Escherichia coli (STEC) In the last few years, STEC and particularly strains of serogroup O157, have emerged as food-poisoning pathogens. A study was performed to evaluate the sensitivity and specificity of an in-house developed PCR-ELISA test for detection of STEC in dairy products using pure cultures, spiked and naturally contaminated samples (Fach et al., 2001). Specificity of the PCR-ELISA was determined with 94 STEC strains (including a large range of STEC serotypes isolated from humans and animals) and 84 non-STEC strains. The sensitivity was determined using duplicates of three individual STEC strains suspended and 10-fold diluted from approximately 106 to 1 cfu/ml. The detection limit in dairy products was carried out on five different pasteurized cheeses artificially contaminated with individual STEC strains (three strains) at four levels of contamination (0,10, 100 and 1000 cfu per 10 g, ca. 30 replicates each except for the highest inoculum level using ca. 15 replicates) and immediately subjected to testing. Finally a comparative study of the PCR-ELISA with vero cytotoxicity testing as the reference method was conducted involving 527 naturally contaminated samples (raw milk samples, unpasteurized cheeses, pasteurized cheeses and dairy environment samples). Of the 527 samples tested, both the PCR-ELISA and the vero cell assay detected

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STEC in 30 samples. Only one sample which cause a cytotoxic effect on vero cells was PCR negative. PCR-ELISA detected STEC in an additional 74 samples. Regarding these results, the PCR-ELISA and the vero cell assay were not in total accordance. The overall percentage of agreement (negative or positive by both methods) was 85.8 per cent.

4.5.4 PCR/restriction enzyme analysis (PCR/REA) for identification of thermophilic Campylobacter species Thermophilic Campylobacter species (Campylobacter jejuni, C. coli, C. lari, and C. upsaliensis) are recognized as the most common bacterial agents responsible for gastroenteritis in humans in industrialized countries. The use of traditional phenotypic tests for the differentiation and species identification of campylobacters is often hampered by the fact that these bacteria are fastidious, asaccharolytic and possess few distinguishing biochemical characteristics. An in-house PCR/REA method was compared with standard phenotypic tests for the identification of these thermophilic campylobacters. In total 182 presumptive thermophilic campylobacters from 12 different animal species were tested by both PCR/ELISA and standard phenotypic tests. By PCR/REA, 95 per cent of isolates were identified as either one of the four thermophilic Campylobacter species or as not belonging to these organisms at all. By standard phenotyping, 174 of the 182 isolates were initially identified as either C. jejuni, C. coli, C. lari or C. upsaliensis. The PCR/REA and standard phenotypic tests resulted in only 67 per cent concordant species identifications. However, for the majority of the isolates who received discrepant species identifications with PCR/REA and standard phenotyping (52 isolates), additional tests could explain the discrepancies and prove the accuracy of the PCR/REA. For example 19 biochemically hippurate negative isolates initially phenotypically identified as C. coli but considered C. jejuni by PCR/REA were verified as C. jejuni by positive hippuricase gene PCR (Engvall et al., 2002).

4.6

The use of validated methods in accredited laboratories

The confidence in the results produced by a microbiological analytical procedure relies on the goodness of the analytical method (determined by a validation study) but also on the competence of the laboratory to provide accurate, reliable and repeatable test results under controlled conditions. Accreditation of laboratories carrying out microbiological food analysis provides to those relying on its services the assurance of the reliability of the test results. Accreditation of a laboratory is the formal approval given by a national authorized body (linked by the European cooperation for Accreditation of Laboratories (EAL)) that the laboratory is competent to carry out specific methods of analysis and has a commitment to quality assurance in the laboratory (Bowles, 2000). A detailed account of the requirements that testing laboratories


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have to meet are described in ISO 17025:1999 (ISO, 1999). The criteria required are divided into: • management requirements: – organization – quality system – document control – review of requests, tenders and contracts – subcontracting of tests and calibrations – purchasing services and supplies – service to the client, complaints – corrective and preventive actions – control of records – internal audits, management review • technical requirements: – personnel – accommodation and environmental conditions – test methods and validation, measurement of uncertainty – equipment – measurement of traceability, control of data, sampling – reporting of results. It is clear that to comply with the requirements of ISO 17025:1999, the laboratory should use validated methods which are documented in standard operating procedures, and needs a systematic approach to quality control (Bolton, 1998; Lightfoot and Maier, 1998). For example: • The performance of culture media should be tested before use. For solid media the modified Miles-Misra method can be used. Detailed information can be found in the recommendations of the IUMS-ICFMH’s Working Party on Culture Media (Corry, 1995). • The performance of the equipment should be checked by daily monitoring and working out schedules for regular cleaning and maintenance This can include, for example, the monitoring of the temperature of an incubator using calibrated thermometers. Recently, in the framework of the European FOOD-PCR project a biochemical test was developed to check the efficiency of the thermocycler for performing PCR reactions. • Defined internal quality control procedures should be used including first, second and third lines of control. The first line of control is quality control checks performed by the analyst during each series of tests executed under similar conditions, and can include the analysis of blank samples (no test organism) or positive (target organism) and negative controls (non-target organism) using reference materials or spiked samples. The results of the positive controls can be used to produce control charts to give an indication of the overall performance and consistency of the results in time.

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The second line of control is performed less frequently. It includes checks which are initiated by the quality manager of the laboratory and need to be performed by the various analysts of the laboratory, e.g. testing of an identical sample (naturally contaminated or artificially inoculated) or interpretation of incubated culture media by more than one analyst. Results can be used to determine the intra-laboratory reproducibility. The third line of control comprises the participation of the laboratory in approved proficiency testing schemes and aims to compare the overall performance of the laboratory with others. The results can be used by the laboratory to determine the parameter ‘trueness’ for the microbiological analytical procedure implied. The data obtained by the internal quality control along with the data from in-house validation studies can be used to estimate the uncertainty of measurement of a microbiological analytical method. • Of major importance for laboratory accreditation is an appropriately qualified staff competent to perform the microbiological tests and supported in its continuing professional development. The introduction of a quality system as a requirement of laboratory accreditation enables tight control over the laboratory’s activities and enhances the confidence in the results produced. Formal accreditation of laboratories performing microbiological testing in the food industry is demanded increasingly by food manufacturers and government representatives.

4.7

Future trends

Dialogue between the international organizations which are involved in the development and validation of microbiological methods is of major importance in order to achieve uniformity and should ensure the acceptance of microbiological results by governmental inspection laboratories and laboratories in the food trade, thus facilitating international commerce. International cooperation is a fact which is illustrated by International Symposia and Workshops jointly organized by ISO, CEN, AOAC International and IDF to create a forum for the exchange of ideas and experiences between microbiologist colleagues. Meetings of ISO TC 34/SC9 and CEN TC 275/WG6 are held annually in the same week and at the same location in order to facilitate good coordination between the two groups. Experts from AOAC International and IDF also attend these meetings. This should result in the adoption of more harmonized standardized protocols although this is not always easy to obtain due to the wide variation in interests and experiences (Andrews, 1996; Hitchins, 1996; Lahellec, 1998). For alternative methods it is in the commercial interest of the suppliers and users of novel test methods to agree on harmonization in protocols for validation of these alternative methods. In 2002 the European standard ‘Protocol for the validation of alternative methods’ was accepted by the


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CEN and will also be adopted as an ISO standard (ISO 16140). Agreements have been made with AOAC International for mutual recognition of the different validation schemes. This should lead to harmonization of validation procedures within Europe and, it is hoped, also acceptance in other countries. It will certainly help the unification of the food trade in Europe. The use of validated methods is only part of providing a reliable result. Of equal importance is the execution of the method by qualified staff with validated equipment and utensils in a laboratory committed to quality assurance. In addition there should be recognition that the result of an analytical method, particularly near the detection limit, is not absolutely defined as presence or absence of a target organism (in the case of qualitative methods) or as a single number of colony forming units of target organisms (in the case of quantitative methods). The outcome of an analytical method is subject to an uncertainty of measurement which should be known and within the precision characteristics of the method as determined during the validation study. The present ISO standard for accreditation of testing laboratories (ISO 17025:1999) explicitly refers to the necessity of determining the uncertainty of measurement of a microbiological analytical method. The uncertainty of measurement can be estimated by the utilization of validation data (external or in-house validation studies) and quality control data (obtained as part of the accreditation scheme). Many important decisions are based on the results of microbial analytical procedures. The use of validated methods in accredited laboratories leads to reliable results and provides confidence in the data obtained. Interpretation of these results, however, demands knowledge of the sampling procedure applied, appropriate definition of the goal (the purpose) of the microbial analysis, and a good knowledge of the ecology of the food product involved and the technology used for processing in order to set realistic criteria for interpretation of the test results. Apart from good analytical skills to perform the microbial analyses, also a broad knowledge of food microbiology, food technology and food chemistry is required for interpretation of the test results.

4.8


Information concerning the definitions of the technical performance characteristics, the determination of these parameters and the measurement of uncertainty can be found in the Eurachem/CITAC guide (2000) on Quantifying Uncertainty in Analytical Measurement as well as in the appropriate ISO 5725 Accuracy (trueness and precision) of measurement methods and results. For more details on the design of an appropriate validation protocol, see CCFRA (Campden and Chorleywood Food Research Association) Guidelines for Establishing the Suitability of Food Microbiology Methods (2001), the special issue of Food Control (1996 Vol. 7, No. 1) on the validation of rapid methods in food microbiology and ISO 16140 Microbiology of food and animal feeding stuffs – Protocol for the validation of alternative methods (ISO, 2002).

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On the accreditation of laboratories and quality assurance, see the actual ISO 17025 General requirements for the competence of testing and calibration laboratories, and the book by Lightfoot and Maier (1998) Microbiological Analysis of Food and Water – Guidelines for Quality Assurance, published by Elsevier Science.

4.9

References

(1996) Validation of modern methods in food microbiology by AOAC International collaborative study. Food Control, 7(1), 19–29. ANDREWS W H (1998) Validation of rapid methods in microbiology. De Ware(n) Chemicus, 28 30–1. BAYLIS C L, JEWELL K, OSCROFT C A and BROOKS F L (2001) Guideline No. 29. Guidelines for establishing the suitability of food microbiology methods, Campden Gloucestershire, Campden & Chorleywood food Research Association (CCFRA). ANDREWS W H

¨ NEWALD C, FANDKE BERTRAM-DROGATZ PA, WILBORN F, SCHEU P, PARDIGOL A, KOOB C, GRO

and BERGHOF K (2000) PCR-based commercial tests for pathogens. In: Robinson R K, Batt C A and Patel P D (eds) Encyclopedia of Food Microbiology, Academic Press, London, pp. 1638–40. BOLTON F J (1998) Quality assurance in food microbiology – a novel approach. Int. J. Food Microbiol, 45 7–11. BOWLES C (2000), Laboratory management accreditation schemes. In: Robinson R K, Batt C A and Patel P D (eds) Encyclopedia of Food Microbiology, Academic Press, London, pp. 1128–33. M, GASCHE A

CHEN S, YEE A, GRIFFITHS M, LARKIN C, YAMASHIRO C T, BEHARI R, PASZKOKOLVA C, RAHN K

and DEGRANDIS S A (1997) The evaluation of a fluorogenic polymerase chain reaction assay for the detection of Salmonella species in food commodities. Int. J. Food Microbiol, 35(3), 239–50. CORRY J E L (1995), Reviews from the sixth symposium of the Working Party for Culture Media. Int. J. Food Microbiol. 26 1–131. CUDJOE K S and KRONA R (1997) Detection of Salmonella from raw food samples using Dynabeads anti-Salmonella and a conventional reference method. Int. J. Food Microbiol, 37 55–62. DE SMEDT J M (1998) AOAC Validation of qualitative and quantitative methods for microbiology in foods. Int. J. Food Microbiol. 45 25–8. DE ZUTTER L, DE SMEDT J M, ABRAMS R, BECKERS H, CATTEAU M, DE BORCHGRAVE J, DEBEVERE J, HOEKSTRA J, JONKERS F, LENGERS J, NOTERMANS S, VAN DAMME L, VANDERMEERSCH R, VERBRAEKEN R and WAES G (1991) Collaborative study on the use of motility enrichment on modified semisolid Rappaport-Vassiliadis medium for the detection of Salmonella from foods. Int. J. Food Microbiol, 13 11–20. ELLISON S L R, ROSSLEIN M and WILLIAMS A (2000) Quantifying uncertainty in analytical measurement, London, Eurachem/CITAC ¨ NDSTRO ¨ M B, GUNNARSSON A, MO ¨ RNER T, WAHLSTRO ¨ M H and FERMER C ENGVALL E O, BRA (2002) Validation of a polymerase chain reaction/restriction enzyme analysis method for species identification of thermophilic campylobacters isolated from domestic and wild animals. J. Appl. Microbiol, 92 47–54. FACH P, PERELLE F, DILASSER F and GROUT J (2001) Comparison between a PCR-ELISA


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test and the vero cell assay for detecting Shiga toxin-producing Escherichia coli in dairy products and characterization of virulence traits of the isolated strains. J. Appl. Microbiol, 90 809–18. Õ GANGAR V, CURIALE M S, D’ONORIO A and SCHULTZ A (2000) VIDAS Enzyme-linked immunofluorescent assay for detection of Listeria in foods: collaborative study. J. AOAC Int., 83(4), 903–18. HITCHINS A D (1996) The International Dairy Federation’s procedure for the validation of microbiological analytical methods for dairy foods. Food Control, 7(1), 13–18. IN ’T VELD P H (1998) The use of reference materials in quality assurance programmes in food microbiology laboratories. Int. J. Food Microbiol. 45 35–41. IN ’T VELD P H, HAVELAAR A H and VAN STRIJP-LOCKEFEER, N G W M (1999) The certification of a reference material for the evaluation of methods for the enumeration of Bacillus cereus. J. Appl. Microbiol, 86(2), 266–74 INTERNATIONAL STANDARDS ORGANIZATION (ISO) (1994) ISO 5725:1994 (Parts 1–6) Accuracy (trueness and precision) of measurement methods and results, Geneva, ISO. INTERNATIONAL STANDARDS ORGANIZATION (ISO) (1999) ISO/IEC 17025:1999 General requirements for the competence of calibration and testing laboratories, Geneva, ISO. INTERNATIONAL STANDARDS ORGANIZATION (ISO) (2002) ISO/FDIS 16140:2002 Microbiology of food and animal feeding stuffs protocol for the validation of alternative methods, Geneva, ISO. LAHELLEC C (1998) Development of standard methods with special reference to Europe. Int. J. Food Microbiol, 45 13–16. LIGHTFOOT N F and MAIER E A (1998) Microbiological analysis of food and water: Guidelines for quality assurance, Amsterdam, Elsevier Science. MANSFIELD P L and FORSYTHE S J (2001) The detection of Salmonella serovars from animal feed and raw chicken using a combined immunomagnetic separation and ELISA method. Food Microbiol, 18 161–366. MICROVAL SECRETARIAT (1998) MicroVal: a European approach to the certification of new microbiological methods. Int. J. Food Microbiol, 45, 17–24. NOTERMANS S, BEUMER R and ROMBOUTS F (1997) Detecting foodborne pathogens and their toxins: conventional versus rapid and automated methods. In: Doyle P, Beuchat L R and Montville T J (eds) Food Microbiology Fundamentals and Frontiers, ASM Press, Washington, pp. 705–8. Õ POPPE C and DUNCAN C L (1996) Comparison of detection of Salmonella by the Tecra Unique Salmonella test and the modified Rappaport Vassiliadis medium. Food Microbiol, 13, 75–81. RENTENAAR, I M F (1996) MicroVal, a challenging Eureka project. Food Control, 7(1), 31– 6. RESTAINO L, FRAMPTON E W and SPITZ H (2001) Repair and growth of heat- and freezeinjured Escherichia coli O157:H7 in selective enrichment broths. Food Microbiol, 18(6), 617–29. SCHULTEN S M, IN ’T VELD P H, NAGELKERKE N J D, SCOTTER S, DE BUYSER M L, ROLLIER P and LAHELLEC C (2000) Evaluation of the ISO 7932 standard for the enumeration of Bacillus cereus in foods. Int. J. Food Microbiol, 57(1–2), 53–61 SCOTTER S L, LANGTON S, LOMBARD B, SCHULTEN S, NAGELKERKE N, IN ’T VELD P H, ROLLIER P

and LAHELLEC C (2001a) Validation of ISO method 11290 Part 1 Detection of Listeria monocytogenes in foods. Int. J. Food Microbiol, 64, 295–306.

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SCOTTER SL, LANGTON S, LOMBARD B, LAHELLEC C, SCHULTEN S, NAGELKERKE N, IN ’T VELD P H and ROLLIER P (2001b) Validation of ISO method 11290 Part 2. Enumeration of Listeria monocytogenes in foods. Int. J. Food Microbiol, 70, 121–9. STRUIJK C B (1996) Guidelines for method validation techniques used in the microbiological examination of food samples. Food Control, 7(1), 53–8. UYTTENDAELE M, BAGAMBOULA C F, DE SMET E, VAN WILDER S and DEBEVERE J. (2001) The evaluation of culture media for enrichment and isolation of Shigella sonnei and S. flexneri. Int. J. Food Microbiol, 70, 255–65. VAN DER ZEE H, WIT B and DE BOER E (2002) Validation of the semi-solid media MSRV and Diassalm vs. ISO 6579 combined with the use of incubated pre-enrichment after refrigeration for 24 and 48 hours. Proceedings Salmonella & Salmonellosis Congress, Ploufragan, 129–30. Õ WAN J, KING K, CRAVEN H, MCAULEY C, TAN S E and COVENTRY M J (2000) Probelia PCR system for rapid detection of Salmonella in milk powder and ricotta cheese. Lett. Appl. Microbiol, 30, 267–71. WILSON I G (1997) Inhibition and facilitation of nucleic acid amplification. Appl. Environ. Microbiol, 63(10), 3741–51.

5 Quality assurance of laboratory performance R. Wood, Food Standards Agency, UK and J. E. L. Corry, University of Bristol, UK

5.1

Introduction

It is now universally recognised as essential that a laboratory produces and reports data which are fit-for-purpose, that is fit for the intended use by the customer of the laboratory. For a laboratory to produce consistently reliable data it must implement an appropriate programme of quality assurance measures. Such measures are now required in the European Union (EU) by virtue of legislation for food control work, by the Codex Alimentarius Commission for laboratories involved in the import/export of foodstuffs and, in the case of the United Kingdom (UK) Food Standards Agency, in the requirements for contractors undertaking survey work. Thus customers now demand of providers of analytical data that their data meet established quality requirements. These are described below. The significance of the measures identified are then described and the future of analytical methods within the food laboratory is then discussed. ‘Food analysis’ is generally understood to refer to chemical or physical tests, assays or measurements, and could include a wide variety of tests, such as determination of water, fat, fibre, nitrite or nitrate content, and measurement of mycotoxins, pesticide or herbicide residues. Microbiological tests usually involve determination of presence or absence of pathogenic microbes, or estimation of numbers of pathogenic, indicator, ‘total’ numbers or various species of spoilage organism. Analysis of the microbiological quality of food is sometimes referred to as ‘food examination’ and has been treated separately from food analysis. In the UK a distinction is made between chemical analysis and microbiological examination for the purposes of the Food Safety Act 19901

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and Regulations made under the Act. This is unusual in that most countries do not make this distinction and for them ‘analysis’ embraces both chemical and microbiological analyses. Thus, in the EU general analysis legislation is taken to refer to both chemistry and microbiology. It is important that this is appreciated when non-UK analytical documents are considered. One reason for this distinction in the UK has been the recognition that it has been considered more difficult to apply quality control systems to microbiological tests. This is because microbes are heterogeneously distributed in many foods, because it is much more difficult to prepare stable control samples, and also perhaps because microbiology has traditionally been considered to some degree an art – the results depending to some extent on the particular skill of individual microbiologists. This has been particularly true for the detection/isolation of pathogens such as salmonellas, which relied on the ability to spot one or a few suspect salmonella colonies among hundreds of non-salmonella competitors, and contrasted with analytical methods which invariably rely on a more objective measurement, such as weight, volume or absorbance. Although many official laboratories still use traditional (colony-count type) microbiological methods, more rapid methods, often partly or wholely mechanised, more akin to those used in chemical analyses, are gradually gaining popularity. Development of better traditional-type methods including selective media with better indicator systems (e.g. chromogenic substrates), or immunological or PCRtype tests applied after enrichment, have also made microbiological testing less subjective than in the past. In addition, it is becoming increasingly clear that similar quality control systems can and should be applied to microbiological as to analytical tests, even though the variability of the results can be much higher. Chapter 5 deals with most of the microbiological aspects of quality assurance systems. This chapter will outline the legislative aspects of assurance of food laboratory performance, applied in the first instance to chemical analyses, highlighting differences with respect to microbiological examination.

5.2

Legislation and codes of practice

Methods of analysis have been prescribed by legislation for a number of foodstuffs since the UK acceded to the European Community in 1972. However, the Community now recognises that the quality of results from a laboratory is equally as important as the method used to obtain the results. This is best illustrated by consideration of the Council Directive on the Official Control of Foodstuffs (OCF) which was adopted by the Community in June 1989.2 This, and the similar Codex Alimentarius Commission requirements, are described below. As a result of this general recognition there is a general move away from the need to prescribe analytical methods in detail towards the prescription of the general quality systems within which the laboratory must operate. This allows greater flexibility to the laboratory without detracting from the quality of results that it will produce.

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Although such an approach is relatively easy to appreciate in the chemistry area, it is less so in the microbiology area where the experimental result is frequently dependent on the method of analysis used – i.e. it is empirical. It is all the more surprising, therefore, that until comparatively recently, although the EU laid down microbiological criteria in Directives for various foods (e.g. egg products, live and cooked shellfish, milk and milk products, including cheeses of various types, meat preparations and minced meat) the methods to be used were not precisely defined. In the last few years policy on this has changed, however, and the Member States of the EU have taken the lead in the development of new standard methods and the revision of old ones via CEN (European Committee for Standardisation), ISO (International Organization for Standardisation) and IDF (International Dairy Federation). New and revised standard methods include sections on their repeatability and reproducibility, and there are standards completed and in preparation concerned with general quality systems – e.g. Methods for microbiological examination of food and animal feeding stuffs. General laboratory practices3 and Guidelines on quality assurance and performance testing of culture media.4 An EU Regulation on microbiological criteria for foodstuffs is in draft,5 which will specify ISO standard methods to be used for checking specifications previously laid down. It will also permit alternative methods to be used, that have been validated according to the EN/ ISO protocol for method validation.

5.3

Legislation in the EU

5.3.1 Official Control of Foodstuffs Directive (OCF) 1989 The Council Directive on the Official Control of Foodstuffs (OCF) which was adopted by the Community in 19892 looked forward to the establishment of laboratory quality standards, by stating that ‘In order to ensure that the application of this Directive is uniform throughout the Member States, the Commission shall, within one year of its adoption, make a report to the European Parliament and to the Council on the possibility of establishing Community quality standards for all laboratories involved in inspection and sampling under this Directive’ (Article 13).

5.3.2 Additional Measures concerning the Official Control of Foodstuffs (AMFC) Directive 1993 Following that the Commission, in September 1990, produced a Report which recommended establishing Community quality standards for all laboratories involved in inspection and sampling under the OCF Directive. Proposals on this were adopted by the Community in the 1993 Directive on Additional Measures Concerning the Official Control of Foodstuffs (AMFC).6 In Article 3 of the AMFC Directive it states:

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Detecting pathogens in food 1.

2.

3.

4.

Member States shall take all measures necessary to ensure that the laboratories referred to in Article 7 of Directive 89/397/EEC2 comply with the general criteria for the operation of testing laboratories laid down in European standard EN 450017 supplemented by Standard Operating Procedures and the random audit of their compliance by quality assurance personnel, in accordance with the OECD (Organisation of Economic Cooperation and Development) principles Nos. 2 and 7 of good laboratory practice as set out in Section II of Annex 2 of the Decision of the Council of the OECD of 12 Mar 1981 concerning the mutual acceptance of data in the assessment of chemicals.8 In assessing the laboratories referred to in Article 7 of Directive 89/ 397/EEC Member States shall: (a) apply the criteria laid down in European standard EN 45002;9 and (b) require the use of proficiency testing schemes as far as appropriate. Laboratories meeting the assessment criteria shall be presumed to fulfil the criteria referred to in paragraph 1. Laboratories which do not meet the assessment criteria shall not be considered as laboratories referred to in Article 7 of the said Directive. Member States shall designate bodies responsible for the assessment of laboratories as referred to in Article 7 of Directive 89/397/EEC. These bodies shall comply with the general criteria for laboratory accreditation bodies laid down in European Standard EN 45003.10 The accreditation and assessment of testing laboratories referred to in this article may relate to individual tests or groups of tests. Any appropriate deviation in the way in which the standards referred to in paragraphs 1, 2 and 3 are applied shall be adopted in accordance with the procedure laid down in Article 8.’

and in Article 4, it states: Member States shall ensure that the validation of methods of analysis used within the context of official control of foodstuffs by the laboratories referred to in Article 7 of Directive 89/397/EEC comply whenever possible with the provisions of paragraphs 1 and 2 of the Annex to Council Directive 85/591/EEC of 23 December 1985 concerning the introduction of Community methods of sampling and analysis for the monitoring of foodstuffs intended for human consumption.11 As a result of the adoption of the above Directives, legislation is now in place to ensure that there is confidence not only in national laboratories but also those of the other Member States. As one of the objectives of the EU is to promote the


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concept of mutual recognition, this is being achieved in the laboratory area by the adoption of the AMFC Directive. In addition it is important that there is dialogue and co-operation by the laboratory with its customers. This is also required by virtue of the EN 45001 Standard at paragraph 6, and will be emphasised even more in future revised versions of EN 45001 and ISO/IEC Guide 25.12 This Directive is currently undergoing revision, but it is not expected that the laboratory requirements will be any less stringent than is the current legislation.

5.4

The Codex Alimentarius Commission

The decisions of the Codex Alimentarius Commission (CAC) are becoming increasingly important because of the acceptance of Codex Standards in World Trade Organisation (WTO) agreements. They can be regarded as being semi-legal in status. Thus, on a world-wide level, the establishment of the WTO and the formal acceptance of the Agreements on the Application of Sanitary and Phytosanitary Measures (SPS Agreement) and Technical Barriers to Trade (TBT Agreement) have dramatically increased the status of Codex as a body. As a result, Codex Standards are now seen as de facto international standards and are increasingly being adopted by reference into the food law of both developed and developing countries. Because of the status of the CAC described above, the work that it has carried out in the area of laboratory quality assurance must be carefully considered. One of the CAC Committees, the Codex Committee on Methods of Analysis and Sampling (CCMAS) has developed criteria for assessing the competence of testing laboratories involved in the official import and export control of foods. These were recommended by the Committee at its Twenty-first Session in March 199713 and adopted by the Codex Alimentarius Commission at its Twenty-second Session in June 1997;14 they are intended to assist countries in their fair trade in foodstuffs and to protect consumers. They mirror the EU recommendations for laboratory quality standards and methods of analysis. The criteria for laboratories involved in the import and export control of foods, now adopted by the Codex Alimentarius Commission are: • to comply with the general criteria for testing laboratories laid down in ISO/ IEC (The International Electrotechnical Commission) Guide 25: 1990 ‘General requirements for the competence of calibration and testing laboratories’;12 (i.e. effectively accreditation) • to participate in appropriate proficiency testing schemes for food analysis which conform to the requirements laid down in ‘The International Harmonised Protocol for the Proficiency Testing of (Chemical) Analytical Laboratories’,15 (already adopted for Codex purposes by the CAC at its 21st Session in July 1995) • to use, whenever available, methods of analysis which have been validated according to the principles laid down by the CAC, and

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• to use internal quality control procedures, such as those described in the ‘Harmonised Guidelines for Internal Quality Control in Analytical Chemistry Laboratories’.16

In addition, the bodies assessing the laboratories should comply with the general criteria for laboratory accreditation, such as those laid down in the ISO/IEC Guide 58:1993: ‘Calibration and testing laboratory accreditation systems – General requirements for operation and recognition’.17 Thus, as for the European Union, the requirements are based on accreditation, proficiency testing, the use of validated methods of analysis and, in addition, the formal requirement to use internal quality control procedures which comply with the Harmonised Guidelines. Although the EU and Codex Alimentarius Commission refer to different sets of accreditation standards, the ISO/IEC Guide 25: 1990 and EN 45000 Series of Standards are similar in intent. It is only through these measures that international trade will be facilitated and the requirements to allow mutual recognition to be fulfilled will be achieved. They both aim to facilitate international trade by enabling mutual recognition of efficient analytical laboratories. However, all of these Standards have effectively been replaced by the ISO/IEC Standard 17025.

5.5

The UK Food Standards Agency

5.5.1 Surveys The Food Standards Agency undertakes food survey exercises. It has developed information for potential contractors on the analytical quality assurance requirements for food chemical surveillance exercises. These requirements are outlined below; they emphasise the need for a laboratory to produce and report data of appropriate quality. The requirements are divided into three parts dealing with: Part A: quality assurance requirements for surveillance projects provided by potential contractors at the time tender documents are completed and when commissioning a survey. Here information is sought on: • the formal quality system in the laboratory if third party assessed (e.g. if UKAS accredited or GLP compliant) • the quality system if not accredited • proficiency testing • Internal Quality Control • Method Validation Part B: information to be defined by the FSA customer once the contract has been awarded – to be agreed with contractor, e.g. the sample storage conditions to be used, the methods to be used and a copy of Standard Operating Procedures (SOPs) where accredited, the internal quality control (IQC) procedures to be used, the measurement limits (i.e. limit of detection (LOD): limit of determination/quantification (LOQ); reporting limits and the measurement uncertainty).


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Part C: information to be provided by the contractor on an on-going basis once the contract is awarded – to be agreed with the customer to ensure that the contractor remains in ‘analytical control’.

5.5.2 Contractual research The procedures employed by the UK Food Standards Agency have recently been reviewed by a Working Group chaired by Sir John Arbuthnott and his Report published in 2001.18 That Report recommends that the quality systems employed by the Agency’s research contractors be reviewed with a view to the introduction of formal third-party assessed system by 2006.

5.6

Quality assurance requirements: accreditation

The effect of the AMFC (Additional Measures Concerning the Official Control of Foodstuffs) Directive is that organisations must consider the following aspects within the laboratory: its organisation, how well it actually carries out analyses, and the methods of analysis used in the laboratory. All these aspects are inter-related, but in simple terms may be thought of as: • becoming accredited to an internationally recognised Standard; such accreditation is aided by the use of internal quality control procedures, • participating in proficiency schemes, and • using validated methods. The AMFC Directive requires that food control laboratories should be accredited to the EN 45000 series of Standards as supplemented by some of the OECD GLP principles. In the UK, Government Departments have nominated the United Kingdom Accreditation Service (UKAS) to carry out the accreditation of official food control laboratories for all the aspects prescribed in the Directive. However, as the accreditation agency will also be required to comply to EN 45003 Standard and to carry out assessments in accordance with the EN 45002 Standard, any other accreditation agencies that are members of the European Co-operation for Accreditation of Laboratories (EA) may also be nominated to carry out the accreditation. Similar procedures will be followed in the other Member States, all having or developing equivalent organisations to UKAS. It is the normal practice for UKAS to accredit laboratories on a method-by-method basis although the accreditation of generic protocols (i.e. instrumental procedures) is becoming increasingly more frequent. In the UK, official food control laboratories undertaking microbiological examination are accredited on a method-by-method basis for the detection and/ or enumeration of pathogenic indicators and organisms routinely determined in food, including aerobic colony count, Enterobacteriaceae or coliforms, E. coli (including serotype 0157), Staphylococcus aureus, Bacillus cereus, Clostridium perfringens, Salmonella species, Listeria monocytogenes and Campylobacter

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species. Where legislation prescribes the methods to be used, any official laboratory which intends to use such methods must be accredited to use them. If not prescribed by statute, then methods published by ISO, CEN, AOAC INTERNATIONAL or other methods which have been validated may be used. Microbiological examinations for which there are no approved standard methods may be undertaken where the laboratory has in place a series of accredited specific methods or accredited generic protocols dealing with, for example: sample preparation, colony counting, impedimetric techniques, immunological procedures, gene probe methods, PCR and electron or other microscopy techniques. It will be necessary for laboratories to be able to demonstrate quality control procedures to ensure compliance with the EN 45001 Standard,7 an example of which would be compliance with the ISO/AOACI/ IUPAC (International Union of Pure and Applied Chemistry) Guidelines on Internal Quality Control in Analytical Chemistry Laboratories.16 For both of these legislative requirements it is the ISO Standard 17025 which is now applicable. This is similar in intent to the ISO/IEC Guide 2512 and the equivalent EN Standards, but does lay more emphasis on method validation, measurement uncertainty and traceability than did the previous Standards/ Guides. Requirements for accreditation of microbiological laboratories are summarised by the European Co-operation for Accreditation (E.A.).19

5.7

Internal quality control (IQC)

Although the legislative requirements apply only to food control laboratories, the effect of their adoption is that other food laboratories are advised to achieve the same standard in order for their results to be recognised as equivalent and accepted for ‘due diligence’ purposes. In addition, the Codex requirements affect all organisations involved in international trade and thus provide an important ‘quality umbrella’. As shown above, these include the requirements for a laboratory to be thirdparty assessed to international accreditation standards, to demonstrate that it is in statistical control by using appropriate internal quality control procedures, to participate in proficiency testing schemes which provide an objective means of assessing and documenting the reliability of the data it is producing and to use methods of analysis which are ‘fit-for-purpose’. These requirements may be summarised as follows and then described in greater detail later in this chapter: IQC is one of a number of concerted measures that analytical chemists can take to ensure that the data produced in the laboratory are of known quality and certainty. In practice this is determined by comparing the results achieved in the laboratory at a given time with a standard. IQC therefore comprises the routine practical procedures that enable the analyst to accept a result or group of results or reject the results and repeat the analysis. IQC is undertaken by the inclusion of particular reference materials, ‘control materials’, into the analytical sequence


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and by duplicate analysis. IQC for food microbiology is discussed in Chapter 6. ISO, IUPAC and AOAC INTERNATIONAL have co-operated to produce agreed protocols on the ‘Design, Conduct and Interpretation of Collaborative Studies’20 and on the ‘Proficiency Testing of (Chemical) Analytical Laboratories’.15 The Working Group that produced these protocols has prepared a further protocol on the internal quality control of data produced in analytical laboratories. The document was finalised in 1994 and published in 1995 as the ‘Harmonised Guidelines For Internal Quality Control In Analytical Chemistry Laboratories’ (IQC protocol).16 The use of the procedures outlined in the Protocol should aid compliance with the accreditation requirements specified above. Internal quality control in microbiology laboratories differs somewhat from the procedures in analytical laboratories, mostly because the analyte is less stable. However, ‘Standard’ or ‘reference’ materials can be used, as can replicate testing and replicate evaluation of test results and the spiking of samples with appropriate standard strains of organisms (see Chapter 6).

5.7.1 Basic concepts The IQC protocol sets out guidelines for the implementation of internal quality control (IQC) in analytical laboratories. IQC is one of a number of concerted measures that analytical chemists can take to ensure that the data produced in the laboratory are fit for their intended purpose. In practice, fitness for purpose is determined by a comparison of the accuracy achieved in a laboratory at a given time with a required level of accuracy. Internal quality control therefore comprises the routine practical procedures that enable the analytical chemist to accept a result or group of results as fit for purpose, or reject the results and repeat the analysis. As such, IQC is an important determinant of the quality of analytical data, and is recognised as such by accreditation agencies. Internal quality control is undertaken by the inclusion of particular reference materials, called ‘control materials’, into the analytical sequence and by duplicate analysis. The control materials should, wherever possible, be representative of the test materials under consideration in respect of matrix composition, the state of physical preparation and the concentration range of the analyte. As the control materials are treated in exactly the same way as the test materials, they are regarded as surrogates that can be used to characterise the performance of the analytical system, both at a specific time and over longer intervals. Internal quality control is a final check of the correct execution of all of the procedures (including calibration) that are prescribed in the analytical protocol and all of the other quality assurance measures that underlie good analytical practice. IQC is therefore necessarily retrospective. It is also required to be as far as possible independent of the analytical protocol, especially the calibration, that it is designed to test. Ideally both the control materials and those used to create the calibration should be traceable to appropriate certified reference materials or a recognised

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empirical reference method. When this is not possible, control materials should be traceable at least to a material of guaranteed purity or other wellcharacterised material. However, the two paths of traceability must not become coincident at too late a stage in the analytical process. For instance, if control materials and calibration standards were prepared from a single stock solution of analyte, IQC would not detect any inaccuracy stemming from the incorrect preparation of the stock solution. In a typical analytical situation several, or perhaps many, similar test materials will be analysed together, and control materials will be included in the group. Often determinations will be duplicated by the analysis of separate test portions of the same material. Such a group of materials is referred to as an analytical ‘run’. (The words ‘set’, ‘series’ and ‘batch’ have also been used as synonyms for ‘run’.) Runs are regarded as being analysed under effectively constant conditions. The batches of reagents, the instrument settings, the analyst, and the laboratory environment will, under ideal conditions, remain unchanged during analysis of a run. Systematic errors should therefore remain constant during a run, as should the values of the parameters that describe random errors. As the monitoring of these errors is of concern, the run is the basic operational unit of IQC. A run is therefore regarded as being carried out under repeatability conditions, i.e., the random measurement errors are of a magnitude that would be encountered in a ‘short’ period of time. In practice the analysis of a run may occupy sufficient time for small systematic changes to occur. For example, reagents may degrade, instruments may drift, minor adjustments to instrumental settings may be called for, or the laboratory temperature may rise. However, these systematic effects are, for the purposes of IQC, subsumed into the repeatability variations. Sorting the materials making up a run into a randomised order converts the effects of drift into random errors. Spiked samples of the food being examined microbiologically can be used. There are a number of difficulties/uncertainties with this approach, however. Firstly, unless the food has been sterilized, it is not possible to be quite sure that it does not already contain the target organism. Secondly, if the food is sterile (e.g. by autoclaving or (preferably) irradiating) then there will be no competitive flora. Thirdly, the wild strains sought may have different properties from the control strain used to spike the food and may also differ in their physiological state. The first difficulty is relatively easily overcome by using a relatively rare strain that can easily be recognised when isolated. This is also a useful precaution in case of accidental cross-contamination from the ‘positive control’ to the test culture(s). For instance, cultural methods for isolating Salmonella species are extremely sensitive, such that even one organism per 25 g sample can be detected with relative ease. The consequences of reporting a sample of processed food positive for Salmonella can be extremely serious involving recall of large quantities of product and potential losses of millions of pounds.


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5.7.2 Recommendations Specific recommendations are given in the guidelines which represent integrated approaches to IQC that are suitable for many types of analysis and applications areas. Managers of laboratory quality systems will have to adapt the recommendations to the demands of their own particular requirements. Such adoption could be implemented, for example, by adjusting the number of duplicates and control material inserted into a run, or by the inclusion of any additional measures favoured in the particular application area. The procedure finally chosen and its accompanying decision rules must be codified in an IQC protocol that is separate from the analytical system protocol. The practical approach to quality control is determined by the frequency with which the measurement is carried out and the size and nature of each run. The use of control charts and decision rules are covered in Appendix 1 to the guidelines. By following the guidelines laboratories would introduce internal quality control measures which are an essential aspect of ensuring that data released from a laboratory are fit-for-purpose. If properly executed, quality control methods can monitor the various aspects of data quality on a run-by-run basis. In runs where performance falls outside acceptable limits, the data produced can be rejected and, after remedial action on the analytical system, the analysis can be repeated. The guidelines stress, however, that internal quality control is not foolproof even when properly executed. Obviously it is subject to ‘errors of both kinds’, i.e., runs that are in control will occasionally be rejected and runs that are out of control occasionally accepted. Of more importance, IQC cannot usually identify sporadic gross errors or short-term disturbances in the analytical system that affect the results for individual test materials. Moreover, inferences based on IQC results are applicable only to test materials that fall within the scope of the analytical method validation. Despite these limitations, which professional experience and diligence can alleviate to a degree, internal quality control is the principal recourse available for ensuring that only data of appropriate quality are released from a laboratory. When properly executed it is very successful. The guidelines also stress that the perfunctory execution of any quality system will not guarantee the production of data of adequate quality. The correct procedures for feedback, remedial action and staff motivation must also be documented and acted upon. In other words, there must be a genuine commitment to quality within a laboratory for an internal quality control programme to succeed, i.e., the IQC must be part of a complete quality management system.

5.7.3 Quality control of media Almost all microbiological tests require the use of media, most of which are not chemically defined, but contain mixtures of nutrients, and frequently selective agents, designed to inhibit unwanted microbes, as well as indicator systems

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designed to identify colonies of the microbes sought. The proper performance of these media is therefore essential if a laboratory is to obtain reliable results of testing. Although recipes with detailed lists of ingredients and instructions for preparation are provided in standard test protocols, few laboratories prepare their media from basic ingredients. Most buy them in dehydrated form, which need only to be mixed with the correct quantity of water and sterilised. Heat labile ingredients are added after sterilisation of the basal media and are also available commercially ready to use. Medium manufacturers test the functioning of the ingredients of their media (e.g. gelling properties of agar, composition of peptones, inhibitory effect of bile salts, brilliant green) and also the functioning of the complete medium. Nevertheless, laboratories should check the functioning of each new lot of medium they buy. This is normally done by use of test inocula of target and (in the case of selective media) unwanted (competitive) microflora.21 The choice of test organisms may include recent isolates which reflect ones most likely to be encountered in future, as well as standard strains, and possibly strains known to be particularly sensitive to suboptimal media. Methods of testing can be quantitative (comparison of colony counts on control versus test media) or semi-quantitative (standardised streaking or ‘ecometry’). The appearance and size, as well as the number of colonies should be checked. Methods have also been devised for liquid media. Standard methods are in preparation on this topic.4, 22 Less detailed tests (e.g. a qualitative streak-plate) should also be set up for each batch of medium sterilised.

5.8

Proficiency testing

Participation in proficiency testing schemes provides laboratories with an objective means of assessing and documenting the reliability of the data they are producing. Although there are several types of proficiency testing schemes they all share a common feature: test results obtained by one laboratory are compared with those obtained by one or more testing laboratories. The proficiency testing schemes must provide a transparent interpretation and assessment of results. Laboratories wishing to demonstrate their proficiency should seek and participate in proficiency testing schemes relevant to their area of work. A proficiency testing scheme is defined as a system for objectively checking laboratory results by an external agency. It includes comparison of a laboratory’s results at intervals with those of other laboratories, the main object being the establishment of trueness. In addition, although various protocols for proficiency testing schemes have been produced the need now is for a harmonised protocol that will be universally accepted; the progress towards the preparation and adoption of an internationally recognised protocol is described below. Various terms have been used to describe schemes conforming to the draft protocol (e.g. external quality assessment, performance schemes etc.), but the preferred term is ‘proficiency testing’.


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Proficiency testing schemes are based on the regular circulation of homogeneous samples by a co-ordinator, analysis of samples (normally by the laboratory’s method of choice) and an assessment of the results. However, although many organisations carry out such schemes, there has been no international agreement on how this should be done – in contrast to the collaborative trial situation. In order to rectify this, the same international group which drew up collaborative trial protocols was invited to prepare one for proficiency schemes (the first meeting to do so was held in April 1989). Other organisations, such as CEN, are also expected to address the problem.

5.8.1 Microbiological proficiency testing schemes Currently there are no internationally or nationally recognised standards for proficiency testing schemes for the microbiological examination of food. The available proficiency testing schemes for food examination will therefore be recognised by the FSA on a case by case basis. Schemes that satisfy the requirements will be recognised and food examination laboratories wishing to be recognised as official control laboratories will be required to participate in the relevant parts of one or more of the recognised schemes. The FSA requires that schemes recognised for the purposes of the AMCF must comply with the general principles of the International Harmonised Protocol for Proficiency Testing of (Chemical) Analytical Laboratories15 in as far as they are appropriate. Proficiency test samples should mirror routine situations likely to be encountered when examining foods in the UK under the AMCF. There should be at least 12 distributions per year. Each distribution may contain a number of test materials. Each test material may contain a single organism, a mixture of organisms or may be devoid of organisms of significance. Detection and/or determination of specific pathogenic organisms and indicators are required at least once each year. Where quantitative determinations are assessed, schemes should treat the results statistically to determine whether performance is satisfactory, for example by converting counts to log10 values and then applying the procedures which have been developed in the International Harmonised Protocol for Proficiency Testing of (Chemical) Analytical Laboratories. Recognised proficiency testing schemes for the microbiological examination of food shall also include a procedure for the recognition of unsatisfactory qualitative results. Currently there are no nationally or internationally recognised protocols for assessing satisfactory performance in qualitative (presence/absence) food examinations. Nevertheless, it is proposed that, in assessing performances, schemes should take due account of false positive and false negative results. Proficiency test results which fall outside acceptable confidence intervals prescribed for the schemes are unsatisfactory. In such cases it will be necessary for laboratories to demonstrate to UKAS that appropriate remedial action has been taken. The performance of official laboratories in proficiency testing schemes recognised as suitable for official control laboratories will be monitored

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by UKAS on behalf of the FSA. Official food control laboratories must therefore consent to UKAS reporting to the FSA on their performance.

5.8.2 Why proficiency testing is important Participation in proficiency testing schemes provides laboratories with a means of objectively assessing, and demonstrating, the reliability of the data they produce. Although there are several types of scheme, they all share a common feature of comparing test results obtained by one testing laboratory with those obtained by other testing laboratories. Schemes may be ‘open’ to any laboratory or participation may be invited. Schemes may set out to assess the competence of laboratories undertaking a very specific analysis (e.g. lead in blood) or more general analysis (e.g. food analysis). Although accreditation and proficiency testing are separate exercises, it is anticipated that accreditation assessments will increasingly use proficiency testing data.

5.8.3 Accreditation agencies attitude to proficiency testing It is now recommended by ISO/IEC Standard 17025,12 the prime standard to which accreditation agencies now operate, that such agencies require laboratories seeking accreditation to participate in an appropriate proficiency testing scheme before accreditation is gained. There is now an internationally recognised protocol to which proficiency testing schemes should comply; this is the IUPAC/AOAC/ISO Harmonised Protocol. Because of the importance of proficiency testing the Protocol is outlined in the Annex to this Chapter. The elements of the Protocol apply equally to microbiological as well as to chemical measurements.

5.8.4 Blind PT schemes It should be recognised by laboratories that the use of blind proficiency testing, i.e. where the laboratory receives a sample for analysis from a customer who knows the characteristics of the sample but does not inform the laboratory of that, is becoming more frequent. This is because some customers wish to assess for themselves the effectiveness of their contractors.

5.9

Quality assurance requirements: analytical methods

Methods should be validated as being fit for purpose before use by a laboratory. Laboratories should ensure that, as a minimum, the methods they used are fully documented, laboratory staff trained in their use and control mechanisms established to ensure that the procedures are under statistical control. The development of methods of analysis for incorporation into International Standards or into foodstuff legislation was, until comparatively recently, not


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systematic. However, the EU and Codex have requirements regarding methods of analysis and these are outlined below. They are followed by other International Standardising Organisations (e.g. AOAC INTERNATIONAL (AOACI) and the European Committee for Standardization (CEN)).

5.9.1 Codex Alimentarius requirements This was the first International Organisation working at the government level in the food sector which laid down principles for the establishment of its methods. That it was necessary for such guidelines and principles to be laid down reflects the confused and unsatisfactory situation in the development of legislative methods of analysis that existed until the early 1980s in the food sector. The ‘Principles For The Establishment Of Codex Methods Of Analysis’23 are given below; other organisations which subsequently laid down procedures for the development of methods of analysis in their particular sector followed these principles to a significant degree. They require that preference should be given to methods of analysis the reliability of which have been established in respect of the following criteria, selected as appropriate: • specificity • accuracy • precision; repeatability intra-laboratory (within laboratory), reproducibility inter-laboratory (within laboratory and between laboratories) • limit of detection • sensitivity • practicability and applicability under normal laboratory conditions • other criteria which may be selected as required.

5.9.2 EU requirements The EU is attempting to harmonise sampling and analysis procedures in an attempt to meet the current demands of the national and international enforcement agencies and the likely increased problems that the open market will bring. To aid this the Union issued a Directive on Sampling and Methods of Analysis.11 The Directive contains a technical annex, in which the need to carry out a collaborative trial before it can be adopted by the Community is emphasised. The criteria to which Community methods of analysis for foodstuffs should now conform are as stringent as those recommended by any International Organisation following adoption of the Directive. The requirements follow those described for Codex above, and are given in the Annex to the Directive. However, the current draft of the revised Official Food Control Directive states that methods should comply with the following: Methods of analysis which are to be considered for adoption under the provisions of this Regulation shall be examined with respect to the

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following criteria: • • • • •

• • • • •

Accuracy Applicability (matrix and concentration range) Limit of detection Limit of determination Precision; repeatability intra-laboratory (within laboratory), reproducibility inter-laboratory (within and between laboratories) but generated from collaborative trial data rather than measurement uncertainty considerations Recovery Selectivity Sensitivity Linearity Other criteria that may be selected as required.

The precision values referred to in 1(5) shall be obtained from a collaborative trial which has been conducted in accordance with an internationally recognised protocol on collaborative trials (e.g. ISO 5725:199424 or the IUPAC International Harmonised Protocol). The repeatability and reproducibility values shall be expressed in an internationally recognised form (e.g. the 95% confidence intervals as defined by ISO 5725:1994 or IUPAC). The results from the collaborative trial shall be published or freely available. Methods of analysis which are applicable uniformly to various groups of commodities should be given preference over methods which apply only to individual commodities. In situations where methods of analysis can only be validated within a single laboratory then they should be validated in accordance with IUPAC Harmonised Guidelines. Methods of analysis adopted under this Regulation should be edited in the standard layout for methods of analysis recommended by the International Organisation for Standardisation. The above provisions are equally applicable to microbiological examination as chemical analyses, for which they were originally developed

5.9.3 Other organisations – CEN and AOACI There are other International Standardising Organisations, most notably the European Committee for Standardization (CEN) and AOACI, which follow similar requirements. Although CEN methods are not prescribed by legislation, the European Commission does place considerable importance on the work that CEN carries out in the development of specific methods in the food sector; CEN has been given direct mandates by the Commission to publish particular methods, e.g. those for the detection of food irradiation. Because of this some of


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the methods in the food sector being developed by CEN are described below. CEN, like the other organisations described above, has adopted a set of guidelines to which its Methods Technical Committees should conform when developing a method of analysis. The guidelines are: Details of the interlaboratory test on the precision of the method are to be summarised in an annex to the method. It is to be stated that the values derived from the interlaboratory test may not be applicable to analyte concentration ranges and matrices other than given in annex. The precision clauses shall be worded as follows: Repeatability: ‘The absolute difference between two single test results found on identical test materials by one operator using the same apparatus within the shortest feasible time interval will exceed the repeatability value r in not more than 5% of the cases. The value(s) is (are): . . .’ Reproducibility: ‘The absolute difference between two single test results on identical test material reported by two laboratories will exceed the reproducibility value R in not more than 5% of the cases. The value(s) is (are): . . .’ There shall be minimum requirements regarding the information to be given in an Informative Annex, this being: Year of interlaboratory test and reference to the test report (if available) Number of samples Number of laboratories retained after eliminating outliers Number of outliers (laboratories) Number of accepted results Mean value (with the respective unit) Repeatability standard deviation (sr) (with the respective unit) Repeatability relative standard deviation (RSDr) (%) Repeatability limit (r) w(with the respective units) Reproducibility relative standard deviation (sR) (with the respective unit) Reproducibility relative standard deviation (RSDR) (%) Reproducibility limit (R) (with the respective unit) Sample types clearly described Notes if further information is to be given

5.9.4 Validation requirements of official bodies Consideration of the above requirements confirms that in future all methods must be fully validated if at all possible – i.e. have been subjected to a collaborative trial conforming to an International recognised Protocol. In addition

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this, as described above, is now a legislative requirement in the food sector of the European Union. The concept of the valid analytical method in the food sector, and its requirements, is described below.

5.10

Criteria for valid methods of analysis

It would be simple to say that any new method should be fully tested for the criteria given above. However, the most ‘difficult’ of these is obtaining the accuracy and precision performance criteria.

5.10.1 Accuracy Accuracy is defined as the closeness of the agreement between the result of a measurement and a true value of the measurand.25 It may be assessed by the use of reference materials. However, in microbiological analysis, there is a particular problem. In many instances the numerical value of a characteristic (or criterion) in a Standard, or whether the organism is present or not, is dependent on the procedures used to ascertain its value. This illustrates the need for the [sampling and] analysis provisions in a Standard to be developed at the same time as the specification in the Standard is negotiated to ensure that the characteristics are related to the methodological procedures prescribed.

5.10.2 Precision Precision is defined as the closeness of agreement between independent test results obtained under prescribed conditions.26 In a standard method the precision characteristics are obtained from a properly organised collaborative trial, i.e. a trial conforming to the requirements of an International Standard (the AOAC/ISO/IUPAC Harmonised Protocol or the ISO 5725 Standard). Because of the importance of collaborative trials, and the resource that is now being devoted to the assessment of precision characteristics of analytical methods before their acceptance, they are described in detail below:

5.10.3 Collaborative trials As seen above, all ‘official’ methods of analysis are required to include precision data. These may be obtained by subjecting the method to a collaborative trial conforming to an internationally agreed protocol. A collaborative trial is a procedure whereby the precision of a method of analysis may be assessed and quantified. The precision of a method is usually expressed in terms of repeatability and reproducibility values. Accuracy is not the objective. Recently there has been progress towards a universal acceptance of collaboratively tested methods and collaborative trial results and methods, no matter by whom these trials are organised. This has been aided by the


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publication of the IUPAC/ISO/AOAC Harmonisation Protocol on Collaborative Studies.20 That Protocol was developed under the auspices of the International Union of Pure and Applied Chemists (IUPAC) aided by representatives from the major organisations interested in conducting collaborative studies. In particular, from the food sector, the AOAC International, the International Organisation for Standardisation (ISO), the International Dairy Federation (IDF), the Collaborative International Analytical Council for Pesticides (CIPAC), the Nordic Analytical Committee (NMKL), the Codex Committee on Methods of Analysis and Sampling and the International Office of Cocoa and Chocolate were involved. The Protocol gives a series of 11 recommendations dealing with: • • • • • • • •

The Components That Make Up A Collaborative Trial Participants Sample Type Sample Homogeneity Sample Plan The Method(s) to be Tested Pilot Study/Pre-trial The Trial Proper

5.10.4 Statistical analysis It is important to appreciate that the statistical significance of the results is wholly dependent on the quality of the data obtained from the trial. Data which contains obvious gross errors should be removed prior to statistical analysis. It is essential that participants inform the trial co-ordinator of any gross error that they know has occurred during the analysis and also if any deviation from the method as written has taken place. The statistical parameters calculated, and the outlier tests performed are those used in the internationally agreed Protocol for the Design, Conduct and Interpretation of Collaborative Studies.20

5.10.5 Alternative validation procedures In the microbiology sector there will be an interest in alternative validation procedures, most notably for ‘Test Kits’. Such procedures are currently being prepared by both AOAC International and CEN.

5.10.6 Single laboratory method validation There is concern in the food analytical community that although methods should ideally be validated by a collaborative trial, this is not always feasible for economic or practical reasons. As a result, IUPAC guidelines are being developed for in-house method validation to give information to analysts on the acceptable procedure in this area. These guidelines have recently been published27 and point readers to protocols/guidelines in the area.

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5.11


Method validation through proficiency testing

The prime objective of proficiency testing is to assess the ‘quality’ of the laboratory. However, in some proficiency testing schemes a significant number of laboratories will use the same method of analysis. This is particularly the situation for microbiology proficiency testing schemes. As a result there are initiatives to develop procedures for the validation of methods of analysis using the results from proficiency testing schemes when this situation occurs.

5.12

Measurement uncertainty for the microbiologist

5.12.1 Introduction It is increasingly being recognised by both laboratories and the customers of laboratories that any reported analytical result is an estimate only and the ‘true value’ will lie within a range around the reported result. The extent of the range for any analytical result may be derived in a number of different ways, e.g. using the results from method validation studies or, determining the inherent variation through different components within the method, i.e. estimating these variances as standard deviations and developing an overall standard deviation for the method. There is some concern within the food analytical community as to the most appropriate way to estimate this variability.

5.12.2 Microbiology laboratories Few laboratories until recently indicated their uncertainty of measurement when quoting test results, even when these were expressed as numbers of colonyforming units. The reasons given for this included that the distribution of microbes in the substrates examined (particularly solids, such as foods) was inherently heterogeneous, microbes are often present in clumps that break up to varying degrees during sampling, mixing, diluting and plating, reference materials with exactly known numbers of microbes cannot be made. This attitude has changed recently, partly because the results of standard tests are sometimes used to assess whether a food complies with statutory microbial limits, and partly as a result of widespread introduction of quality assurance and accreditation systems into microbiology laboratories. As with chemical analysis, overall errors can be estimated by investigating individual errors within the method (weighing, pipetting, etc., bias from different individuals counting the colonies), but the method generally favoured is to estimate overall uncertainty by determining repeatability and reproducibility of the method concerned. Uncertainty is minimised by quality assurance systems that minimise errors within the method (e.g. temperature, time of incubation, weighing, measurement of pH, productivity and selectivity of culture media, accuracy of volume measurement). However, these cannot be completely eliminated, and other sources of uncertainty are inherent – numbers of microbes in replicate samples


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are generally distributed according to the Poisson distribution, so there is inherently greater uncertainty than found in chemical testing. Uncertainty of measurement can be estimated by replicate testing done within the laboratory as well as from results obtained by participation in proficiency testing schemes. Uncertainty will be affected by factors such as the food substrate being tested, and the method used, so needs to be determined for each food/method combination. In general, selective colony-count methods have greater uncertainty than non-selective ‘total’ colony count methods, counts from liquids are less uncertain than from solid foods. There are a number of useful publications and draft standards on this topic.22,28–35

5.13

Future trends

For the microbiological laboratory, as for all laboratories, it is likely that the most significant developments will be the need to demonstrate the quality of their work. For survey work that is readily achieved through accreditation. However the requirement to demonstrate quality, possibly through a third-party assessment, is likely to be adopted by the major funding agencies in the UK. Such a requirement would have a major impact on the work of the laboratory.

5.14 1. 2. 3. 4.

5. 6. 7.

8.

9.

10.

References ‘Food Safety Act, 1990’, HMSO, London, 1990, 16. Council Directive 89/397/EEC on the Official Control of Foodstuffs, O.J. L186 of 30.6.1989. ISO 1996 BS 5763-0:1996, ISO 7218:1996 Methods for microbiological examination of food and animal feeding stuffs. General laboratory practices ISO (draft) 2000 Microbiology of food and animal feeding stuffs – guidelines on quality assurance and performance testing of culture media. Part 1: General guidelines on quality assurance of culture media in the laboratory. DD ENV ISO 11133-1: 2000. EU MICROBIOLOGICAL CRITERIA PROPOSAL. EUROPEAN UNION Council Directive 93/99/EEC on the Subject of Additional Measures Concerning the Official Control of Foodstuffs, O.J. L290 of 24.11.1993. EUROPEAN COMMITTEE FOR STANDARDIZATION, General Criteria for the Operation of Testing Laboratories – European Standard EN 45001, Brussels, CEN/ CENELEC, 1989. ORGANISATION FOR ECONOMIC CO-OPERATION AND DEVELOPMENT, Decision of the Council of the OECD of 12 Mar 1981 concerning the mutual acceptance of data in the assessment of chemicals, Paris, OECD, 1981. EUROPEAN COMMITTEE FOR STANDARDIZATION, General Criteria for the Assessment of Testing Laboratories – European Standard EN45002, Brussels, CEN/ CENELEC, 1989. EUROPEAN COMMITTEE FOR STANDARDIZATION, General Criteria for Laboratory Accreditation Bodies – European Standard EN45003, Brussels, CEN/CENELEC, 1989. EUROPEAN UNION,

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11.

EUROPEAN UNION,

12.

13.

14. 15.

16.

17.

18. 19. 20.

21.

22.

23. 24.

25. 26. 27.

28.

Council Directive 85/591/EEC Concerning the Introduction of Community Methods of Sampling and Analysis for the Monitoring of Foodstuffs Intended for Human Consumption, O.J. L372 of 31.12.1985. INTERNATIONAL ORGANIZATION FOR STANDARDIZATION, General Requirements for the Competence of Calibration and Testing Laboratories – ISO/IEC Guide 25, Geneva, ISO, 1990. CODEX ALIMENTARIUS COMMISSION, Report of the 21st Session of the Codex Committee on Methods of Analysis and Sampling – ALINORM 97/23A, Rome, FAO, 1997. CODEX ALIMENTARIUS COMMISSION, Report of the 22nd Session of the Codex Alimentarius Commission – ALINORM 97/37, Rome, FAO, 1997. INTERNATIONAL UNION OF PURE AND APPLIED CHEMISTRY, The International Harmonised Protocol for the Proficiency Testing of (Chemical) Analytical Laboratories, ed. Thompson M and Wood R, Pure Appl. Chem., 1993 65 21232144 (Also published in J. AOAC International, 1993 76 926–40). INTERNATIONAL UNION OF PURE AND APPLIED CHEMISTRY, Guidelines on Internal Quality Control in Analytical Chemistry Laboratories, ed. Thompson M and Wood R, Pure Appl. Chem., 1995 67 649–66. INTERNATIONAL ORGANIZATION FOR STANDARDIZATION, Calibration and Testing Laboratory Accreditation Systems – General Requirements for Operation and Recognition – ISO/IEC Guide 58, Geneva, ISO, 1993. A Review of the Food Standards Agency’s Research Portfolio and Research Management Systems, Published by the Food Standards Agency, July 2001. EUROPEAN CO-OPERATION FOR ACCREDITATION, Accreditation for Microbiological Laboratories EA-04/10 2002 (http://www.european-accreditation.orgl). HORWITZ W: ‘Protocol for the Design, Conduct and Interpretation of Method Performance Studies’, Pure Appl. Chem, 1988 60 855–64. (Revision published 1995). CORRY, J.E.L., CURTIS, G.D.W. and BAIRD, R.M. 2003 Handbook of Culture Media for Food Microbiology (2nd Edition). Progress in industrial microbiology, Volume 37, Amsterdam: Elsevier. ISO (draft) 2002a Microbiology of food and animal feeding stuffs – Guidelines on quality assurance and performance testing of culture media. Part 2: Practical guidelines on performance testing of culture media (ISO/DTS 11133-2: 2002). CODEX ALIMENTARIUS COMMISSION, Procedural Manual of the Codex Alimentarius Commission – Tenth Edition, Rome, FAO, 1997. INTERNATIONAL ORGANIZATION FOR STANDARDIZATION, Precision of Test Methods – Standard 5725, Geneva, ISO, 1981 [revised 1986 with further revision in preparation]. INTERNATIONAL ORGANIZATION FOR STANDARDIZATION, International Vocabulary for Basic and General Terms in Metrology – 2nd Edition, Geneva, ISO, 1993. INTERNATIONAL ORGANIZATION FOR STANDARDIZATION, Terms and Definitions used in Connection with Reference Materials – ISO Guide 30, Geneva, ISO, 1992. Harmonised guidelines for single-laboratory validation of methods of analysis, Michael Thompson, Stephen L R Ellison and Roger Wood, Pure Appl. Chem., 2002, 74(5), 835–55. NMKL (1999) Procedure No 8 Measurement of Uncertainty in Microbiological Examination of Foods. Nordic Committee on Food Analysis, Oslo, Norway (www.nmkl.org).

Quality assurance of laboratory performance 29.

30. 31.

32.

33. 34.

35.

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and JEWELL, K. 1999 Uncertainty Associated with Microbiological Measurement, Project no 29732, Campden and Chorleywood Food Research Association Review no 15, CCFRA, Chipping Campden, UK. UKAS (United Kingdom Accreditation Service) 2000 The Expression of Uncertainty in Testing Edition 1, UKAS Publication ref: LAB 12, London. ISO (draft) 2001a Milk and milk products – Quality control in the microbiological laboratory Part 1: Analyst performance assessment for colony counts ISO/CD 14461-1| IDF 169-1. ISO (draft) 2001b Milk and milk products – Quality control in the microbiological laboratory Part 2: Determination of the reliability of colony counts of parallel plates and subsequent dilution steps ISO/CD 14461-2|IDF 169-2. ISO (draft) 2002b Microbiology – determination of measurement uncertainty. (doc ISO/TC 34/SC9 N 558). ISO (draft) 2002c Statistics of analytical data Protocol for the establishment of precision characteristics of microbiological quantitative methods by interlaboratory studies, 1st draft, ISO/TC 34/SC 9 N 543. ¨ , S.I., 2002 Uncertainty of quantitative determinations derived by NIEMELA cultivation of microorganisms. 2nd Edition. Centre for Metrology and Accreditation, Advisory Commission for Metrology, Chemistry Section, Expert Group for Microbiology, Helsinki, Finland, Publication J3/2002. VOYSEY, P.A.

5.15 Appendix: the ISO/IUPAC/AOAC International Harmonized Protocol for Proficiency Testing of Analytical Laboratories The International Standardising Organisations, AOACI, ISO and IUPAC have co-operated to produce an agreed ‘International Harmonised Protocol for Proficiency Testing of (Chemical) Analytical Laboratories’.11 That protocol is recognised within the food sector of the European Community and also by the Codex Alimentarius Commission. The protocol makes the following recommendations about the organisation of proficiency testing, all of which are important in the food sector: 5.15.1 Framework Samples must be distributed regularly to participants who are to return results within a given time. The results will be statistically analysed by the organiser and participants will be notified of their performance. Advice will be available to poor performers and participants will be kept fully informed of the scheme’s progress. Participants will be identified by code only, to preserve confidentiality. The scheme’s structure for any one analyte or round in a series should be: • • • • •

samples prepared samples distributed regularly participants analyse samples and report results results analysed and performance assessed participants notified of their performance

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• advice available for poor performers, on request • co-ordinator reviews performance of scheme • next round commences.

5.15.2 Organization The running of the scheme will be the responsibility of a co-ordinating laboratory/organization. Sample preparation will either be contracted out or undertaken in house. The co-ordinating laboratory must be of high reputation in the type of analysis being tested. Overall management of the scheme should be in the hands of a small steering committee (Advisory Panel) having representatives from the co-ordinating laboratory (who should be practising laboratory scientists), contract laboratories (if any), appropriate professional bodies and ordinary participants.

5.15.3 Samples The samples to be distributed must be generally similar in matrix to the unknown samples that are routinely analysed (in respect of matrix composition and analyte concentration range). It is essential they are of acceptable homogeneity and stability. The bulk material prepared must be effectively homogeneous so that all laboratories will receive samples that do not differ significantly in analyte concentration. The co-ordinating laboratory should also show the bulk sample is sufficiently stable to ensure it will not undergo significant change throughout the duration of the proficiency test. Thus, prior to sample distribution, matrix and analyte stability must be determined by analysis after appropriate storage. Ideally the quality checks on samples referred should be performed by a different laboratory from that which prepared the sample, although it is recognised that this would probably cause considerable difficulty to the co-ordinating laboratory. The number of samples to be distributed per round for each analyte should be no more than five.

5.15.4 Frequency of sample distribution Sample distribution frequency in any one series should not be more than every 2 weeks and not less than every 4 months. A frequency greater than once every 2 weeks could lead to problems in turn-round of samples and results. If the period between distributions extends much beyond 4 months, there will be unacceptable delays in identifying analytical problems and the impact of the scheme on participants will be small. The frequency also relates to the field of application and amount of internal quality control that is required for that field. Thus, although the frequency range stated above should be adhered to, there may be circumstances where it is acceptable for a longer time scale between sample distribution, e.g. if sample throughput per annum is very low. Advice on this respect would be a function of the Advisory Panel.


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5.15.5 Estimating the assigned value (the ‘true’ result) There are a number of possible approaches to determining the nominally ‘true’ result for a sample but only three are normally considered. The result may be established from the amount of analyte added to the samples by the laboratory preparing the sample; alternatively, a ‘reference’ laboratory (or group of such expert laboratories) may be asked to measure the concentration of the analyte using definitive methods or thirdly, the results obtained by the participating laboratories (or a substantial sub-group of these) may be used as the basis for the nominal ‘true’ result. The organisers of the scheme should provide the participants with a clear statement giving the basis for the assignment of reference values which should take into account the views of the Advisory Panel.

5.15.6 Choice of analytical method Participants can use the analytical method of their choice except when otherwise instructed to adopt a specified method. It is recommended that all methods should be properly validated before use. In situations where the analytical result is method-dependent the true value will be assessed using those results obtained using a defined procedure. If participants use a method which is not ‘equivalent’ to the defining method, then an automatic bias in result will occur when their performance is assessed.

5.15.7 Performance criteria For each analyte in a round a criterion for the performance score may be set, against which the score obtained by a laboratory can be judged. A ‘running score’ could be calculated to give an assessment of performance spread over a longer period of time.

5.15.8 Reporting results Reports issued to participants should include data on the results from all laboratories together with participant’s own performance score. The original results should be presented to enable participants to check correct data entry. Reports should be made available before the next sample distribution. Although all results should be reported, it may not be possible to do this in very extensive schemes (e.g. 800 participants determining 15 analyses in a round). Participants should, therefore, receive at least a clear report with the results of all laboratories in histogram form.

15.5.9 Liaison with participants Participants should be provided with a detailed information pack on joining the scheme. Communication with participants should be by newsletter or annual

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report together with a periodic open meeting; participants should be advised of changes in scheme design. Advice should be available to poor performers. Feedback from laboratories should be encouraged so participants contribute to the scheme’s development. Participants should view it as their scheme rather than one imposed by a distant bureaucracy.

5.15.10 Collusion and falsification of results Collusion might take place between laboratories so that independent data are not submitted. Proficiency testing schemes should be designed to ensure that there is as little collusion and falsification as possible. For example, alternative samples could be distributed within a round. Also instructions should make it clear that collusion is contrary to professional scientific conduct and serves only to nullify the benefits of proficiency testing.

5.15.11 Statistical procedure for analysis of results The first stage in producing a score from a result x (a single measurement of analyte concentration in a test material) is to obtain an estimate of the bias, thus: bias x ÿ X where X is the true concentration or amount of analyte. The efficacy of any proficiency test depends on using a reliable value for X. Several methods are available for establishing a working estimate of X^ (i.e. the assigned value): In the case of microbiological results, they are log transformed. Formation of a z-score Most proficiency testing schemes compare bias with a standard error. An obvious approach is to form the z-score given by: z x ÿ X^ = where is a standard deviation. could be either an estimate of the actual variation encountered in a particular round (~s) estimated from the laboratories’ results after outlier elimination or a target representing the maximum allowed variation consistent with valid data. A fixed target value for is preferable and can be arrived at in several ways. It could be fixed arbitrarily, with a value based on a perception of how laboratories should perform. It could be an estimate of the precision required for a specific task of data interpretation. could be derived from a model of precision, such as the ‘Howitzer Curve’.15 However, while this model provides a general picture of reproducibility, substantial deviation from it may be experienced for particular methods.


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5.15.12 Interpretation of z-scores If X^ and are good estimates of the population mean and standard deviation then z will be approximately normally distributed with a mean of zero and unit standard deviation. An analytical result is described as ‘well behaved’ when it complies with this condition. An absolute value of zjzj greater than three suggests poor performance in terms of accuracy. This judgement depends on the assumption of the normal distribution, which, outliers apart, seems to be justified in practice. As z is standardised, it is comparable for all analyses and methods. Thus values of z can be combined to give a composite score for a laboratory in one round of a proficiency test. The z-scores can therefore be interpreted as follows: jzj < 2 ‘Satisfactory’: will occur in 95% cases produced by ‘well behaved results’ 2 < jzj < 3 ‘Questionable’: but will occur in 5% of cases produced by ‘well behaved results’ jzj > 3 ‘Unsatisfactory’: will only occur in 0.1% of cases produced by ‘well behaved results’

5.15.13 Combination of results within a round of the trial There are several methods of combining the z-scores produced by a laboratory in one round of the proficiency test described in the Protocol. They are: The sum of scores, SO = Rz The sum of squared scores, SSZ = Rz2 The sum of absolute values of the scores, SAZ = jzj All should be used with caution however. It is the individual z-scores that are the critical consideration when considering the proficiency of a laboratory.

5.15.14 Calculation of running scores Similar considerations apply for running scores as apply to combination scores above.


Part II Particular techniques


6 Culture methods P. Stephens, Oxoid Ltd, UK

6.1

Introduction

Culture methods for detecting pathogens in food have existed for more than a century. To this day, culture methods still form the foundation of nearly all methods for detecting pathogens in food. In fact, in the majority of situations, culture methods still form the detection method in its entirety. In a recent survey of 312 food testing laboratories within Europe more than 99 per cent of respondents said they were using conventional culture methods for the isolation of most food pathogens (Chris Baylis, personal communication). In the same survey, respondents listed universal acceptance, cost effectiveness, reliability and ease of use as the main reasons for choosing culture methods. In this chapter, the key components of culture medium design will be reviewed. The principles of culture method structure, both quantitative and qualitative, will be discussed and examples given. Recent, continuing and future innovations in culture methods will be presented.

6.2

Culture medium design

6.2.1 Basic culture medium components Culture methods, according to their definition, are methods that involve the growing or keeping alive of a collection of microorganisms in or on a nutrient medium. In the most basic sense nutrient media comprise up to six key components disolved in water: • amino-nitrogen compounds • energy sources

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buffer salts mineral salts and metals growth promoting factors gelling agents.

Amino-nitrogen compounds (peptones, other protein hydrolysates, infusions or extracts) Relatively few microorganisms can utilise heated and denatured protein as a source of amino-nitrogen as this would depend on the excretion of extracellular proteolytic enzymes. Therefore, pre-digested or acid-hydrolysed protein, or aqueous infusions/extracts of protein rich materials are used. Peptones are watersoluble mixtures of polypeptides, oligopeptides and single amino acids, together with the other water-soluble compounds present in the original proteinaceous substrate. The peptides formed are of varying chain lengths and amino acid sequences, which depend on the protein substrate and the process of hydrolysis. Proteolytic enzymes hydrolyse proteins by splitting specific peptide bonds, thus producing characteristic peptones. It follows, therefore, that a wide variety of peptones can be made by allowing different proteolytic enzymes to act on different proteins. Commercially, only three enzymes are generally used: papain, pancreatin and pepsin. The variety of protein sources, however, is large including meat (fresh, frozen, dried), casein (precipitated from milk with lactic or hydrochloric acids), gelatin, fish (fresh, dried), keratin (horn, feather), soya and many types of vegetable derived material. Energy sources (e.g. glucose) The most common components used for this purpose are glucose or similar easily utilised carbohydrates intended to provide a readily accessible source of energy. Media that do not contain an identifiable carbohydrate source provide peptones or similar compounds, which are utilised by the organisms as sources of carbon and energy. Buffer salts (e.g. soluble phosphate salts, acetates and citrates) Buffering agents are commonly added to media supplemented with energy sources, to maintain pH stability if fermentation is likely to take place. They are also used to prevent adverse shifts in pH when sample materials such as food are added to the medium. Mineral salts and metals (phosphates, sulphates, calcium, magnesium, iron, manganese and trace metals) Essential metals are normally present as contaminants in other medium components, at adequate levels to improve growth. Specific supplements are often not made, unless to overcome the chelating effects of competing compounds in the medium. A common reason for the use of these additives is to enhance and identify a particular biochemical reaction. In these circumstances they act as indicator substances, e.g. iron and sulphites (Wilson, 1923).

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Growth promoting factors (blood, serum, vitamins, NADH, etc.) There is a diverse assortment of complex, often heat-labile substances, essential for the growth of fastidious or particularly demanding microorganisms, which are not present in unsupplemented media. These essential factors are not always solely acting in a nutritional role, e.g. blood in culture media for the isolation of Campylobacter also acts as a protective agent against reactive oxygen species and influences dissolved oxygen levels (Bolton et al., 1984). Gelling agents (agar, gelatin, alginate, gums, etc.) Agar is the predominant gelling agent used to provide a solid matrix for the visualisation of growing microorganism colonies. It is rarely a pure ingredient and it contributes metals and minerals as well as exerting a significant effect on water availability. Gelling agents can also be used as selective components by controlling the movements of motile microorganisms (De Smedt et al., 1986).

6.2.2 Selective culture medium components In food microbiology, when detecting specific pathogens in a sample containing many different species, it is often essential to incorporate one or many selective features into a culture medium in addition to the basic components listed above. Selective agents preferentially or selectively allow for the growth of the target group from a sample. Healthy bacteria of the target group should be resistant to the selective compounds at the concentrations used. The more common selective agents of choice can be divided into four groups: • • • •

inorganic salts dyes surface-active agents antibiotics.

Inorganic salts Examples include sodium azide active against Gram negative bacteria (Mossel et al., 1957), bismuth sulphite active against coliforms (Wilson and Blair, 1926), lithium chloride active against Gram negatives and enterococci (van Netten et al., 1989), potassium tellurite active against Gram negatives (Baird-Parker, 1962), tetrathionate active against Gram positives and coliforms (Knox et al., 1943), and sodium selenite active against Gram positives and coliforms (Leifson, 1936). Dyes Acridines and triphenylmethane dyes have been known, since the beginning of the last century, to possess outstanding powers of bacteriostasis. Examples include acriflavine (van Netten et al., 1989), crystal violet (Jasper and Dellinger, 1967), brilliant green (Moats and Kinner, 1974) and malachite green (van Schothorst and Renaud, 1985).

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Surface-active agents MacConkey first used bile in culture media in 1905. The active components of bile, bile salts, are more chemically defined and used more frequently in the medium formulations of today (Leifson, 1935). Other surface-active components include cetrimide (Brown and Lowbury, 1965), lauryl sulphate (Mallmann and Darby, 1941) and a range of proprietary surfactants such as Tergitol (Chapman, 1947). Antibiotics Because of the numbers of different antibiotics available and the differing spectra of activity antibiotics provide for targeted selectivity. Antibiotics as selective agents are in use as single selective agents, as mixtures with other antibiotics, and even in conjunction with the more conventional chemical selective agents listed above.

6.2.3 Differential culture medium components In addition to selecting for microorganisms of the target species, it is also common to use components that allow the differentiation of the target species from other species using differences in their biochemistry. Indicator dyes (e.g. phenol red, neutral red, bromocresol purple) These dyes are added to indicate pH changes in media following growth of microorganisms, particularly when carbohydrates have been added to the formulation. Colour changes as a result of alkaline changes in pH are also used. Specific substrate indicators (e.g. chromogens, fluorogens) Chromogens are indicator compounds that act as substrates for specific enzymes and change colour due to the action of the enzyme. The chromogenic enzyme substrates generally comprise a specific enzyme substrate such as a sugar or amino acid linked to a chromophore. The compound remains colourless until utilised when the chromophore is released giving rise to coloration of the medium and/or cells. The ability to detect specific enzymes using the appropriate substrates has led to the development of a great number of new media for the identification of pathogens (Manafi, 2000). Fluorogens are similar in principle but, following enzyme action, a fluorophore is released that can be detected when observed under UV illumination. The action of the targeted microbial enzyme on a single substrate can achieve much greater specificity than indicator systems based on changes in pH. The greatest gains are made, however, when combinations of chromogens and pH indicators are used, each targeting a different enzyme system. Much more information can be gained sooner regarding the identity of the microorganisms present in the original sample using media containing these combinations. Most developments have evolved around chromogenic enzyme substrates for detecting activity from -galactosidase (Ley et al., 1993), -glucuronidase

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(Feng and Hartman, 1982), -glucosidase (Manafi and Sommer, 1993), caprylate esterase (Humbert et al., 1989) and phospholipase C (Restaino et al., 1999). The successful use of chromogens is dependent on the correct enzyme expression that might require the presence of the appropriate inducers in the medium. Careful medium design must also take into consideration that some released indicators diffuse freely into the medium causing coloration of neighbouring cells, or the indicator might be pH sensitive and not produce the correct colour. Other diagnostic features (e.g. virulence factors) Culture media have been designed to incorporate diagnostic features that detect the presence/activity of key virulence factors that can be used in the isolation and identification of the target microorganism species. Haemolysin activity has long been detected by the inclusion of blood into media (Turner and Pickard, 1980). Egg yolk emulsion (Baird-Parker, 1962) and lecithin (Chrisope et al., 1976) have been included for the detection of phospholipase activity, and rabbit plasma fibrinogen (Beckers et al., 1984) has been used to detect coagulase activity.

6.2.4 Incubation conditions (e.g. pH, temperature and gaseous atmosphere) Use of buffer salts to resist adverse changes in pH in order to allow growth of the desired microorganism has been discussed above. Control of pH is important to allow other medium components to function optimally, e.g. antibiotic potency, precipitation of bile salts and metal complexes. Additionally, control of pH at low and high values can be used to selectively favour the growth of the target microorganism at the expense of competing species (van Schothorst and Renaud, 1985). Likewise, incubation temperature can be used to select for rapid growth of the target microorganism as well as restricting the growth of competing species. Selective incubation temperature can be lower (Hao et al., 1987), as was the case for many early isolation methods for Listeria monocytogenes, as well as higher (van Schothorst and Renaud, 1985). Incubation temperature may also be critical for the optimum expression of certain diagnostic features including antigens, e.g. L. monocytogenes and flagella expression at 30ºC but not at 37ºC (Peel et al., 1988). Control of gaseous environment is also important to provide the optimum conditions for growth of the target microorganism. This is particularly relevant for the isolation of microaerophilic species such as Campylobacter. Control of oxygen concentration is typically achieved through the use of controlled atmosphere incubation in jars and cabinets. It can also be achieved through the use of oxygen consuming medium ingredients. In some instances the dynamic interaction of many factors can be important in the function of culture media. In Campylobacter isolation the control of oxygen concentration is not only affected by the external control of atmospheric conditions but also the growth of

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competing microorganisms that will significantly affect the dissolved oxygen content. Anaerobic conditions can be beneficial for the resuscitation of stressed pathogens such as Salmonella, L. monocytogenes and Escherichia coli O157 (see Section 6.2.5). Such conditions would also provide a selective benefit by restricting the growth of aerobic competing species such as Pseudomonas.

6.2.5 Resuscitation conditions (e.g. supplements and medium design) Pathogens present in food may be injured and as a result more exacting in their growth requirements. Such microorganisms can be difficult to detect because they are sensitive to the selective agents used traditionally in culture media. Stressed microorganisms can be sensitive to low levels of reactive oxygen species (ROS) that can exist in culture media, and stressed microorganisms have extended lag times during which repair of damage takes place. To ensure the detection of injured pathogens culture media can be supplemented with components to quench the toxicity from selective agents and ROS. Medium components can be chosen that are known to be low in toxicity and methods can be constructed that allow for complete resuscitation before exposure to selective agents (see Section 6.3). Recent developments in recovering injured cells have focussed on defining the time needed for repair of individual cells within a population (Stephens et al., 1997) and in formulating resuscitation media and/or conditions to avoid exposing cells to oxidative stress (Stephens et al., 2000). Two sources of ROS exist for injured microorganisms recovering in a non-selective culture medium (Stephens et al., 2000). Firstly, the medium itself can be a source of ROS, primarily as a result of photo-oxidation reactions of medium components with light, and secondly as a result of auto-oxidation reactions of medium components at ambient and high temperatures used for sterilisation. Levels of ROS in culture media are very low and are usually not inhibitory to uninjured microorganisms. Reactive oxygen species can be prevented from forming by careful medium design or quenched after they have been produced through the use of specific medium components such as blood (Bolton et al., 1984), pyruvate (Baird-Parker, 1962), catalase (Mackey and Seymour, 1987), superoxide dismutase (Hoffman et al., 1979) and cysteine (Knabel and Thielen, 1995). Beneficial effects have been reported in many foodborne pathogens including E. coli O157 (Mizunoe et al., 1999), Camp. jejuni (Bolton et al., 1984), Salm. typhimurium (Mackey and Derrick, 1986), Staphylococcus aureus (BairdParker, 1962) and L. monocytogenes (Patel and Beuchat, 1995). The second source of ROS is the aerobic metabolism of injured microorganisms. Through a variety of possible mechanisms, injured cells metabolising aerobically suffer oxidative stress as a result of increased intracellular levels of ROS (Stephens et al., 2000). By encouraging these microorganisms to metabolise anaerobically, as might be the case following ingestion, they are prevented from producing further undesirable ROS. The use

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of anaerobic conditions to improve recovery of stressed cells has been reported widely for Salmonella (Xavier and Ingham, 1993), Listeria (Linton et al., 1992), E. coli O157 (Bromberg et al., 1998) and Staph. aureus (Ugborogho and Ingham, 1994). Strictly anaerobic conditions are usually achieved using the Hungate technique (Hungate, 1969) or by working entirely within an anaerobic cabinet. Neither of these is suitable for routine microbiological work. An alternative method of achieving anaerobiosis is to use a crude membrane preparation from E. coli that can be added to liquid media to scavenge oxygen with high affinity (Adler et al., 1981). A membrane preparation known as Oxyrase is now available commercially (Adler, 1990). By using a combination of a peptone medium low in ROS and Oxyrase, significant improvements in the detection of Salmonella in spiked ice cream and milk powder have been reported (Baylis et al., 2000a).

6.3

Culture method design

Culture methods for detecting pathogens in food fall into two categories, those for quantitative (enumeration) analysis and those for qualitative (presence/ absence) analysis.

6.3.1 Quantitative methods (enumeration) The number of viable cells of a target species in a specified sample can be counted by the spread-plate method, the pour-plate method and the most probable number method (MPN). The spread-plate method can be used with opaque media and avoids exposing the inoculum to mild heat stress as occurs with the pour-plate method. Many differential features of media may only be displayed correctly by the spreadplate technique whereby surface colonies are growing under the appropriate gaseous conditions. Similarly, it is easier to subculture surface colonies for subsequent identification/confirmation. Only a small inoculum, typically 100 l, can be used on a spread-plate in a standard 90 mm Petri dish. Where low counts are expected larger Petri dishes can be used to spread up to 1ml of sample. Where high counts are expected the sample must be serially diluted with each dilution used to inoculate a separate spread-plate. Alternatively the drop-plate method or Miles Misra technique can be used (Hedges et al., 1978). Enumeration by spread plating can also be achieved using a spiral plater whereby a decreasing volume of inoculum is deposited in the form of a spiral over the agar medium from the centre to the edge of the plate (Donnelly et al., 1976). This procedure allows a range of up to four decimal dilutions to be counted from a single plate. With the pour-plate technique, a larger inoculum volume, typically 1 ml, can be used. The sample is added directly to an empty Petri dish and tempered medium is poured into the dish and the sample and medium mixed before the

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medium solidifies. Precise cooling of the medium prior to mixing is essential to prevent loss of viability during mixing. Solidified pour-plates are often overlaid with a thin layer of the same medium to prevent the spreading of colonies on the surface of pour-plates. Numerous strategies have been used to avoid underestimating microbial numbers in samples likely to contain stressed cells. These include formulating the medium to minimise any inhibitory effects on injured target microorganisms and performing a resuscitation treatment to allow repair of injury before inoculation on/into a selective medium. There are few examples of the first option in current use. Baird-Parker agar (Baird-Parker, 1962) supports good recovery of Staph. aureus cells damaged by drying, freezing or heating but there are not many other examples of such media. Where inhibitory selective media cannot be avoided, resuscitation on solid or in liquid media is needed. Solid medium repair is the method of choice where quantitative estimates of viable numbers are needed. This can be achieved by spreading cells on the surface of a non-selective agar medium and, after allowing for repair to occur, overlaying with a selective medium (Speck et al., 1975). A more satisfactory method is to incubate cells on a membrane filter on a non-selective medium before transferring the membrane filter to selective agar (Holbrook et al., 1980). Recently, this approach has been used for the enumeration of E. coli O157 in foods (McCarthy et al., 1998). Thin polycarbonate membranes were used that facilitated transfer of the pH indicator into the developing colony, thus allowing the fermentation reaction to be easily visualised on the surface of the membrane. Both these approaches have the advantage that should growth of uninjured cells take place during the resuscitation period this will not lead to a falsely high count as the early growth will only contribute to the development of a single colony. Agar ‘underlay’ methods for the enumeration of stressed L. monocytogenes (Kang and Fung, 1999) and Salm. typhimurium (Kang and Fung, 2000) have also been developed. In this method, the selective medium is overlaid with nonselective medium immediately before the sample containing stressed cells is plated onto the surface of the upper non-selective layer. Initially the upper layer remains non-selective allowing resuscitation to take place. Selective agents then diffuse into the upper layer from the selective medium thus suppressing the growth of competing bacterial species. Some success has been reported from the addition of ‘recovery supplements’ to selective agars to aid the resuscitation of stressed cells in the presence of selective agents. The addition of egg yolk emulsion to Oxford and PALCAM agar formulations has improved the recovery of stressed L. monocytogenes (Wood et al., 1996). The MPN method of enumeration is particularly useful when low counts are expected, when the amount of material to be tested is too large for the spreadand pour-plating methods, when testing particulate samples and when there is concern over the presence of injured cells in the sample material. In the MPN method, counts are estimated from examining multiple cultures prepared from multiple aliquots of a dilution series, and determining the proportions of such

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cultures that show growth. The multiple tube count is the commonest form of MPN enumeration. A liquid enrichment medium is chosen that will support the recovery and growth of the target species. The determination of growth of the target species is made according to the production of an appropriate reaction in the medium, e.g. pH change, indole production, gas production, etc. In some instances an MPN procedure can involve processing each aliquot in accordance with a full qualitative test including primary enrichment, selective enrichment and plating. The number of aliquots and the range of dilutions required are dependent on the expected level of contamination and the precision required from the estimated count. Reference to probability tables or the use of probability equations obtains the MPN estimate. A disadvantage of the MPN method is that it is labour intensive and the precision is poor unless the number of replicate tubes per dilution is very large.

6.3.2 Qualitative methods (presence/absence) Depending on the level of sensitivity required there are up to four sequential stages in a qualitative culture method for detecting pathogens in food: • • • •

primary enrichment (pre-enrichment) selective enrichment plating confirmation.

Primary enrichment Direct inoculation of injured cells into selective media can result in the loss of viability of some or all of them, the latter giving rise to a false negative result. A period of time in a non-selective, or reduced selectivity, medium allows the repair and growth of any sublethally injured microorganisms prior to their exposure to the selective components of selective enrichment. Numbers of target cells must be reached that ensure both their transfer on subculture to a selective medium and their survival in the selective medium in sufficient numbers that their growth is ensured (van Leusden et al., 1982). A non-selective primary enrichment culture will allow the growth of the majority of the microorganisms present in a food sample; these microorganisms may overgrow the target species. By the time repair has occurred, other uninjured or less-injured microorganisms may form the dominant species. When the dominant species enter their own stationary phase, they may inhibit the further growth of all other species present, including the target species that may still be in such small numbers that their detection after the selective enrichment stage is uncertain. Jameson (1962) first described this stationary phase inhibition. The early and/or progressive introduction of selective agents to the primary enrichment medium helps overcome the Jameson Effect. The use of short primary enrichment incubation (e.g. six hours) is not sufficient to allow recovery and multiplication of all injured cells (Stephens et

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al., 1997). The existing incubation times of 16 to 20 hours are a compromise between a longer incubation time that may allow better recovery of severely damaged cells, and the increased risk of overgrowth from competing microorganisms. Certain foods require specific treatments for primary enrichment (Andrews and Hammack, 1998). When testing dehydrated products controlled rehydration of the sample is important to minimise osmotic shock to damaged cells. When testing herbs and spices their natural antimicrobial constituents require extra dilution, up to 1:1000, to provide conditions in which cells of the target species can grow. Milk solids might be added to cocoa rich samples to neutralise toxicity and thiosulphate might be added as a quenching agent to preservativerich food samples. Selective enrichment The purpose of selective enrichment is to provide a ratio of target species to competing microorganisms that allows for successful detection. Selective agents and incubation conditions of the type described above are used to suppress the growth of as many competing microorganisms as possible whilst allowing growth of the target species. A 1:10 or 1:100 dilution of the primary enrichment medium is followed typically by an incubation period of 24 to 48 h. Following primary enrichment it is probable that the target species will still be in the minority because of the low selectivity that exists in primary enrichment media. In a selective enrichment broth culture inoculated with a mixture of microorganisms, competitive growth occurs between all species able to tolerate and use the selective conditions. Rarely from a heterogeneously contaminated sample does any selective enrichment allow the growth of the target species alone. Diagnostic indicators might be included in the selective enrichment medium but they are unlikely to be sufficiently sensitive or specific to provide a confirmed result. Plating Plating forms the detection phase of a conventional culture method for pathogen detection in food. Theoretically, plating is one of the most sensitive detection techniques in routine use. Typically a 10 l aliquot is transferred to the plating medium. The presence of one typical colony is sufficient to suggest contamination of the initial sample being analysed. Assuming no loss of viability upon plating and complete inhibition of competing microorganisms, then plating could detect as few as 100 cells/ml of the enrichment broth. Realistically there is some loss of viability upon plating, and growth of competing microorganisms is likely, reducing the sensitivity by up to 100fold. If competing microorganism growth outnumbers the target microorganism by >1000:1 then the presence of the target microorganisms will be masked entirely and the sample falsely recorded as negative. To maximise the chance of isolating the target microorganism from an enrichment broth upon subculture to selective agar, an appropriate streaking

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technique must be employed. The principle is that ever-decreasing numbers of cells are spread over an increasing surface area of the medium to obtain discrete, well-separated colonies that fully exhibit the diagnostic features of the medium. Semisolid plating media exist and they use the migration of motile target bacteria through or over the medium as an additional selection process (De Smedt et al., 1986). The concentration of the gelling agent is critical to the performance of such media Confirmation Few selective and differential plating media are wholly specific. For both quantitative and qualitative methods colonies displaying the correct typical appearance must still be confirmed to be the target microorganism before the analysis could be considered complete. Confirmation can take the form of a series of biochemical tests, antigenic tests or nucleic acid analysis. Purification of the suspect colonies might be required prior to confirmation by means of further subculture onto a differential plating medium.

6.4

Examples of qualitative methods

Across the world and across trade organisations there are often many different methods of analysis for the same microorganism of concern. The International Organisation for Standardisation (ISO) technical committee 34/sub-committee 9 is responsible for compiling standardised horizontal microbiological methods of analysis for all food and animal feeding stuffs. The standardised methods published by this committee represent an international consensus of opinion on the most appropriate method for the intended purpose. The standardised methods are not necessarily the most sensitive or the simplest to operate but act as reference methods to facilitate international trade without endangering the consumer. It might be considered that as Salmonella, L. monocytogenes, Campylobacter and E. coli O157 are pathogens that can contaminate food that their methods of analysis would be similar. However, their standardised methods of analysis differ not only in specific media, as would be expected, but differ considerably in their structure and design. The first attempts to compile an international standard method for the detection of Salmonella in foods were made by ISO more than three decades ago. The method has had several technical changes made to it since then but the method in place today is similar in structure to the very first standard method (Fig. 6.1) (Anon, 2002). There is more performance data available for culture methods for Salmonella isolation than for any other pathogen. For this reason, and the ubiquitous nature of Salmonella contamination of food, the standardised method for its detection is the most thorough of all the pathogen methods. Samples are first incubated in an entirely non-selective primary enrichment (pre-enrichment) medium to facilitate resuscitation of stressed cells. This is then subcultured into two selective enrichment media. Two

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Fig. 6.1

ISO 6579:2002 (Anon, 2002). Microbiology of food and animal feeding stuffs – horizontal method for the detection of Salmonella spp.

media are necessary because of the biological diversity of the Salmonella group, and the need to maximise the chance of detecting all strains. Similarly, it is necessary to utilise two different selective plating media. Because of the close relatedness of Salmonella and some other species of the Enterobacteriaceae it is important that the proper plating and confirmation methods are followed. Following much activity in the early 1990s regarding L. monocytogenes method development, ISO published their standardised method in 1996 (Fig. 6.2) (Anon, 1996). Listeria monocytogenes does not compete well in mixed

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Fig. 6.2 ISO 11290-1:1996 (Anon, 1996). Microbiology of food and animal feeding stuffs – horizontal method for the detection and emuneration of Listeria monocytogenes. Part 1. Detection method.

cultures where the dominant microflora are Enterobacteriaceae. To reduce the risk of a false negative result due to overgrowth of competing microorganisms it is necessary to include some selective agents in the primary enrichment medium. This is at the expense of not resuscitating all stressed cells. Unlike Salmonella, not all species of the Listeria genus are of concern. However, because of their close relatedness it is difficult to devise a mix of selective agents that preferentially enriches L. monocytogenes and not members of the other Listeria species (Scotter et al., 2001).

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Fig. 6.3

ISO 10272:1995 (Anon, 1995). Microbiology of food and animal feeding stuffs – horizontal method for the detection of thermotolerant Campylobacter.

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The method is due for modification with changes proposed to the selective plating media. The first-choice medium of Oxford agar, which is unable to differentiate the pathogenic L. monocytogenes from the other Listeria spp. is to be replaced with a more differential chromogenic medium. The ISO standardised method for Campylobacter detection has two different protocols depending on whether it is to be used for detection in foods heavily contaminated with competing microorganism species or detection of low levels of stressed cells (Fig. 6.3) (Anon, 1995). The protocol for heavily contaminated foods involves direct selective enrichment in a medium containing four antimicrobial compounds and incubation at 42ºC. The protocol for use with foods, where the detection of low levels of stressed cells is of concern, involves a delayed introduction of antimicrobial compounds and a gradual increase in incubation temperature. The method is due for modification with changes proposed to the enrichment protocols, with the inclusion of Bolton Broth (Baylis et al., 2000b), and the choice of plating media. The first ISO standardised method for the detection of E. coli O157 was published in 2001 (Fig. 6.4) (Anon, 2001). The method differs to the other three described above in that it does not include a non-selective or reduced selectivity primary enrichment step. Although reflecting the need to produce a prompt standardised method, following the rapid emergence of this pathogen, and the fact that the main food type likely to be contaminated is raw meat, it is still seen as a weakness of the method that it is unsuitable for the detection of low levels of stressed cells (Stephens and Joynson, 1998). A second difference of the method is the incorporation of an immunomagnetic separation step (Chapman et al., 1994). In the three methods described above the main selective challenges have been to distinguish between the target species and microorganisms from other species, albeit closely-related species. In the detection of E. coli O157 it is necessary to distinguish a specific serogroup of E. coli from all other E. coli as well as numerous closely-related species. This is aided by exploiting the antigenic differences within the E. coli spp.

6.5

Examples of commercial kits

6.5.1 Cold water setting gels The rehydratable film product (e.g. PetrifilmTM, 3M; CLONdiscTM, BD Biosciences) is a simple to use version of the traditional pour-plate method (Ginn et al., 1986). It comprises two plastic films coated with adhesive, powdered culture medium constituents and a dehydrated cold water soluble gelling agent. In use the top film of the plate is lifted and a 1 ml sample is added to the centre of the bottom film. The top film is released and a spreading device is used to press down the top film. Rehydratable film products are available for total viable counts and enumeration of indicator organisms with the only pathogen enumeration product being for Staphylococcus aureus.

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Fig. 6.4

ISO 16654:2001 (Anon, 2001). Microbiology of food and animal feeding stuffs – horizontal method for the detection of Escherichia coli O157.

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Products similar in principle are available as Compact Dry (Scil Diagnostics) (Ellis and Meldrum, 2002) and SANITA-KUN (Chisso). The RedigelTM product (3M) is a pectin gel method similar to agar pour-plate techniques (Roth, 1988). Pre-sterilised medium containing the pectin gel is added to specially treated Petri dishes whereby the base of the dish has been coated with divalent cations to cause solidification of the gelling agent. The RedigelTM products can also be used in the spread-plate technique. At present there are no RedigelTM products available for pathogen detection.

6.5.2 Selective motility The Oxoid Salmonella Rapid Test combines liquid and semi-solid enrichment stages and liquid indicator media (Holbrook et al., 1989). Motile salmonellae migrate through the selective medium under the influence of chemoattractants. The test is performed in a disposable culture vessel containing two tubes with porous bases. Each of the tubes contains two culture media separated by a further porous disc. The media in the bottom halves of the tubes are selective for Salmonella and the media in the top halves contain indicators for Salmonella.

6.5.3 Delayed addition SalmosystÕ (Merck) is a manual delayed addition method whereby selective agents are added to a primary enrichment sample in the form of a tablet after a pre-determined time period (six to eight hours) (Pignato et al., 1995). SPRINT Salmonella is a combined primary enrichment and secondary enrichment method whereby selective agents are automatically released directly into the primary enrichment medium after a pre-determined time (4-6 hours) from delayed-release capsules (Baylis et al., 2000a). The primary enrichment medium is optimised for the rapid resuscitation of stressed cells so that by the time the medium is turned selective all stressed cells have begun growing. Selective agents are packaged in capsules that are sealed with a hydrogel plug. The plugs rehydrate in the primary enrichment medium, swelling at a controlled rate until a point where they are forced from the end of the capsules releasing selective agents into the medium. Both methods are only available for Salmonella detection.

6.5.4 MPN The hydrophobic grid membrane filter (HGMF) (e.g. ISO-GRIDTM, Neogen) method uses a membrane filter imprinted with a hydrophobic grid that divides the filter surface into 1600 equal compartments (Sharpe and Michaud, 1974). When a sample is filtered through the HGMF, microorganisms are randomly distributed into the filter compartments. The filter is placed onto a selective differential agar medium to enable identification of colonies of the target

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species. The number of compartments occupied by colonies is determined and an MPN estimate is calculated. The HGMF method can also be used as a qualitative method by filtering selective enrichment broths and using the appropriate selective differential plating medium. The hydrophobic grid is then used to separate colonies to maximise the chances of detecting the target species in a mixed culture. The HGMF method is available for Salmonella, L. monocytogenes, E. coli O157 and Staph. aureus. The SimPlateÕ system (BioControl) is a pre-moulded circular plastic dish with microwells (Beuchat et al., 1998). The sample is mixed with the culture medium prior to pouring into the dish. Fluorescent enzyme substrates in the medium are hydrolysed by the target bacteria during the incubation period. After incubation the number of fluorescent microwells is noted and the MPN estimated. The product is available for performing total viable counts, enumeration of indicator microorganisms and Campylobacter enumeration. ColilertÕ and Quanti-TrayÕ (IDEXX Laboratories) are proprietary products for broth-based MPN enumeration (Yakub et al., 2002). Each product comprises a moulded device with multiple self-contained chambers into which a mixture of sample and culture medium is poured. Chromogens, fluorogens and gas production are used as indicators for the presence of the target microorganism. After incubation the number of positive chambers is noted and the MPN estimated. The products are available for the enumeration of indicator microorganisms in water samples but could be used on diluted samples of food although no products are available for pathogen detection. Similar products, such as ColiTrakÕ (BioControl) are available for qualitative testing.

6.5.5 Specific substrate media Patent protection for culture media formulations was relatively unknown until the advent of specific substrate media. There are many proprietary products for enrichment and plating that contain the novel use of an existing chromogenic or fluorogenic substrate, or a novel compound in itself (Manafi, 2000). Many products are available for the detection of E. coli O157, Salmonella, L. monocytogenes, Bacillus cereus, Staph. aureus and Clostridium perfringens.

6.6

Future trends

Despite the long existence of culture methods there is still great potential for further significant improvements. Products with increased specificity and sensitivity will be brought about by improvements in medium components, such as new chromogens that reduce the requirement for confirmation and chromogens with enhanced properties such as strength of colour thus enabling faster visualisation. New medium components will include new types of selective agent that act in a more targeted fashion based on enzyme expression without toxicity to stressed cells of the target species. New medium components

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for improved resuscitation of stressed cells are likely. Products will be made simpler enabled by improvements in presentation and design of products. The emergence of new pathogens, e.g. detection of all VTEC in foods, will bring about the development of new culture methods. Changes in testing requirements, e.g. enumeration of Campylobacter spp. in poultry products, will also lead to the development of new culture methods. Culture media will be specifically designed that are compatible with rapid end-point technologies. As in the past where media have been designed with impedance techniques in mind (Druggan et al., 1993), media in the future will be designed that are optimised for techniques such as PCR (Knutsson et al., 2002). New diagnostic features will be built into culture methods. New principles for culture detection will be designed, e.g. bacteriophage amplification, targeted responsive liposomes. Finally, there will be increased harmonisation of standardised culture methods with more cross-border recognition of national and international standardised culture methods. Much is now understood about the complex interactions of culture medium components. Commercially produced media in dehydrated and ready-to-use forms are of very high standard often giving more reliable and reproducible performance than media prepared from individual components in the user’s laboratory. Continuing innovations in medium components will lead to faster, simpler to use and more sensitive products. Although, in comparison with newer alternative technologies, they are time-consuming and require a moderate degree of skill to operate culture methods still dominate the field of detecting pathogens in food. Culture methods have universal acceptance, are lower in cost, are highly specific and highly sensitive and often have a long history of good reliable performance. Even with the introduction of alternative technologies culture methods will continue to form the heart of the method fulfilling the essential roles of resuscitation, growth and selectivity.

6.7

Further reading

Bridson EY (1990) Media in microbiology. Rev Med Microbiol 1, 1–9. Harrigan WF (1998) Laboratory Methods in Food Microbiology, 3rd Edition. London: Academic Press. Manafi M (2000) New developments in chromogenic and fluorogenic culture media. Int J Food Microbiol 60, 205–18. Corry JEL, Curtis GDW and Baird RM (1995) Culture Media for Food Microbiology (Volume 34 in the Progress in Industrial Microbiology Series). Amsterdam: Elsevier Science.

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6.8

References

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injured Salmonella typhimurium. Int J Food Microbiol 54, 127–32. and THIELEN SA (1995) Enhanced recovery of severely heat-injured, thermotolerant Listeria monocytogenes from USDA and FDA primary enrichment media using a novel, simple, strictly anaerobic method. J Food Prot 58, 29–34. KNOX R, GELL PGH and POLLOCK MR (1943) The selective action of tetrathionate in bacteriological media. J Hyg Camb 43, 147–58. KNUTSSON R, FONTANESI M, GRAGE H and RADSTROM P (2002) Development of a PCRcompatible enrichment medium for Yersinia enterocolitica: amplification precision and dynamic detection range during cultivation. Int J Food Microbiol, 72(3), 185– 201. LEIFSON E (1935) New culture media based on sodium desoxycholate for the isolation of intestinal pathogens and for the enumeration of the colon bacillus in milk and water. J Path Bact 40, 581–99. LEIFSON E (1936) New selenite enrichment media for the isolation of typhoid and paratyphoid (salmonella) bacilli. Amer J Hyg 24, 423–32. LEY AN, BARR S, FREDENBURGH D, TAYLOR M and WALKER N (1993) Use of 5–bromo-4– chloro-3–indolyl- -D-galactopyranoside for the isolation of -D-galactosidasepositive bacteria from municipal water supplies. Can J Microbiol 39, 821–5. LINTON RH, WEBSTER JB, PIERSON MD, BISHOP JR and HACKNEY CR (1992) The effect of sublethal heat shock and growth atmosphere on the heat resistance of Listeria monocytogenes Scott A. J Food Protect 55, 84–87. MACKEY BM and DERRICK CM (1986) Peroxide sensitivity of cold-shocked Salmonella typhimurium and Escherichia coli and its relationship to minimal medium recovery. J Appl Bacteriol 60(6), 501–11. MACKEY BM and SEYMOUR DA (1987) The effect of catalase on recovery of heat-injured DNA-repair mutants of Escherichia coli. J Gen Microbiol 133, 1601–10. MALLMANN WL and DARBY CW (1941) Use of a lauryl sulfate tryptose broth for the detection of coliform organisms. Am J Publ Health 31, 127–34. MANAFI M (2000) New developments in chromogenic and fluorogenic culture media. Int J Food Microbiol 60, 205–18. MANAFI M and SOMMER R (1993) Rapid identification of enterococci with a new fluorogenic-chromogenic assay. Wat Sci Tech 27, 271–4. MCCARTHY J, HOLBROOK R and STEPHENS PJ (1998) An improved direct plate method for the enumeration of stressed Escherichia coli O157:H7 from food. J Food Protect 61, 1093–7. MOATS WA and KINNER JA (1974) Factors affecting selectivity of brilliant green-phenol red agar for salmonellae. Appl Microbiol 27(1), 118–23. MIZUNOE Y, WAI SN, TAKADE A and YOSHIDA S. (1999) Restoration of culturability of starvation-stressed and low-temperature-stressed Escherichia coli O157 cells by using H2O2-degrading compounds. Arch Microbiol 172(1), 63–67. MOSSEL DAA, DIEPEN HMJ VAN and BRUIN AS DE (1957) The enumeration of faecal streptococci in foods, using Packer’s crystal violet sodium azide blood agar. J Appl Bact 20, 265–72. PATEL JR and BEUCHAT LR (1995) Enrichment in Fraser broth supplemented with catalase or Oxyrase, combined with the microcolony immunoblot technique, for detecting heat-injured Listeria monocytogenes in foods. Int J Food Microbiol 26(2), 165–76. PEEL M, DONACHIE W and SHAW A (1988) Temperature dependent expression of flagella of Listeria monocytogenes studied by electron microscopy, SDS-PAGE and western blotting. J Gen Microbiol 143, 2171–8. KNABEL SJ

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and GIAMMANCO G (1995) Evaluation of new culture media for rapid detection and isolation of salmonellae in foods. Appl Environ Microbiol 61(5), 1996–9. RESTAINO L, FRAMPTON EW, IRBE RM, SCHABERT G and SPITZ H (1999) Isolation and detection of Listeria monocytogenes using fluorogenic and chromogenic substrates for phosphatidylinositol-specific phospholipase C. J Food Prot 62(3), 244–51. ROTH JN (1988) Temperature-independent pectin gel method for aerobic plate count in dairy and non-dairy food products: collaborative study. J Assoc Off Anal Chem 71(2), 343–9. PIGNATO S, MARINO AM, EMANUELE MC, IANNOTTA V, CARACAPPA S

SCOTTER SL, LANGTON S, LOMBARD B, SCHULTEN S, NAGELKERKE N, IN’T VELD PH, ROLLIER P

and LAHELLEC C (2001) Validation of ISO method 11290 part 1 – detection of Listeria monocytogenes in foods. Int J Food Microbiol 64(3), 295–306. SHARPE AN and MICHAUD GL (1974) Hydrophobic grid-membrane filters: new approach to microbiological enumeration. Appl Microbiol 28, 223–5. SPECK ML, RAY R and READ JR. RB (1975) Repair and enumeration of injured coliforms by a plating procedure. Appl Microbiol 29, 549–50. STEPHENS PJ, JOYNSON JA, DAVIES KW, HOLBROOK R, LAPPIN-SCOTT HM and HUMPHREY TJ (1997) The use of an automated growth analyser to measure recovery times of single heat-injured Salmonella cells. J Appl Microbiol 83, 445–55. STEPHENS PJ and JOYNSON JA (1998) Direct inoculation into media containing bile salts and antibiotics is unsuitable for the detection of acid/salt stressed Escherichia coli O157:H7. Lett Appl Microbiol 27, 147–51. STEPHENS PJ, DRUGGAN P and NEBE-VON CARON G (2000) Stressed Salmonella are exposed to reactive oxygen species from two independent sources during recovery in conventional culture media. Int J Food Microbiol 60, 269–85. TURNER WH and PICKARD DJ (1980) A new haemolysin from Staphylococcus aureus which lyses horse erythrocytes. J Gen Microbiol 116(1), 237–41. UGBOROGHO TO and INGHAM SC (1994) Increased D-values of Staphylococcus aureus resulting from anaerobic heating and enumeration of survivors. Food Microbiol 11, 275–80. VAN LEUSDEN FM, VAN SCHOTHORST M and BECKERS HJ (1982) The standard Salmonella isolation method. In Isolation and Identification Methods for Food Poisoning Organisms, eds Corry JEL, Roberts D and Skinner FA pp. 35–49. SAB Symposium Series No. 17. London: Academic Press. VAN NETTEN P, PERALES I, VAN DE MOOSDIJK A, CURTIS GD and MOSSEL DA (1989) Liquid and solid selective differential media for the detection and enumeration of L. monocytogenes and other Listeria spp. Int J Food Microbiol 8(4), 299–316. VAN SCHOTHORST M and RENAUD AM (1985) Malachite green pre-enrichment medium for improved salmonella isolation from heavily contaminated samples. J Appl Bacteriol 59(3), 223–30. WILSON WJ (1923) Reduction of sulphites by certain bacteria in media containing a fermentable carbohydrate and metallic salts. J Hyg Camb 21, 392–8. WILSON WJ and BLAIR EM MCV (1926) Combination of bismuth and sodium sulphite affording enrichment and selective medium for typhoid-paratyphoid groups of bacteria. J Path Bact 29, 310–11. WOOD M, HOLBROOK R and STEPHENS P (1996) Enhanced recovery of stressed Listeria monocytogenes on Oxford and Palcam agars. Proceedings of the Symposium on Food Associated Pathogens, Uppsala, May 1996 pp. 216–17. Uppsala: SLU.

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XAVIER IJ

YAKUB GP, CASTRIC DA, STADTERMAN-KNAUER KL, TOBIN MJ, BLAZINA M, HEINEMAN TN, YEE

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GY

7 Electrical methods D. Gibson, BIODON International, UK

7.1

Introduction: principles

The application of direct electrical methods in analytical microbiology has a long history, extending over 100 years when ‘electricity’ was being applied to every conceivable scientific problem. Stewart (1899) is generally credited with the first methods, derived from his physiological studies on the circulation of blood in man. However, it is apparent that while he identified some of the problems and proposed valid conclusions, he did not provide a rapid method, experiments extending for many days, and it is difficult with hindsight to decide what he was really measuring. But the principle remains. The modern interest was rekindled in the 1970s when two instruments were described at the First Symposium on Rapid Methods and Automation in Microbiology and Immunology (Heden and Illeni, 1975). Within a short time there were three instruments competing in the market; now there are four – Bactometer, Malthus, RABIT and BacTrac, each with unique characteristics, operating systems and data presentation but capable of handling multiple samples simultaneously. These electrical methods are concerned with measuring the response of microbial cultures to alternating electrical current (AC) at specific frequencies. There were some developments using direct electrical current (DC) but these were not commercialized. With high currents, the growth medium electrolyses and kills the microbes, and at low currents, mediators such as lipoic acid are needed and the developments have proceeded as biosensors. All types require electrodes to be immersed in the growth medium or food homogenate. The parameters of importance are impedance and conductance, either alone or in combination. Put simply, impedance is the AC equivalent of resistance to a

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DC current. At any frequency (cycles per second, Hz), impedance has two components: capacitance and conductance. Capacitance relates more to the properties and changes at the electrode and conductance to the solution or gel between the electrodes. Resistivity is the reciprocal of conductance. Pure water and solutions of salts have no capacitance and so their impedance is solely conductance. Most microbiological media have capacitance due to their macromolecular content as well as contributions from the inoculum such as food. Changes in impedance are a measure more of the change in biomass in the assay, and conductance changes are due to the effects of metabolism on the charge-carrying capacity of the medium. Large molecules are broken down to small ones which are much better charge carriers; for example amines and ammonia from proteins, lactic acid from carbohydrates, polymers reduced to monomers. Each growth medium therefore has an impedance value that depends on its composition of defined chemicals and components, and the composition of the inoculum. Salts have a major effect and the operating range of every type of instrument is limited by lack of response to ‘high salt’ media, and salty foods if not diluted. As some conventional media incorporate high salt levels as selective agents, indirect methods have to be used. Impedance has a high temperature coefficient, about 2 per cent per degree. For sensitive and therefore fast responses to any change, the assay temperature has to be controlled. Manufacturers have different solutions. Bactometer use an uninoculated control alongside the test and measure both. Malthus and RABIT, derived from the same original work and patent, control temperature to within a few thousandths of a degree and make an absolute measurement. BacTrac use four electrodes (terminals) two of which act as controls. All instruments take readings of their chosen parameter(s) every few minutes and store the data or manipulated data on a computer. All instruments are simple to operate. Microbiologically, they have the unique advantage over other technologies as being hands on/walk away. An extract is prepared from the food source, placed in the test cell with media, and the instrument takes regular readings and announces when the criteria for a positive have been exceeded. They are very economical with trained staff time and effort. They have been on the market for more than 25 years but have not had the uptake experienced by equivalent instruments in automated chemistry. The reasons for this are obscure even allowing for the perceived lack of reliability of early machines when continuous performance of both the ‘microbiological’ and ‘computer’ parts of the instruments were pushing the design limits of the technologies. There was an innate resistance of microbiologists to new technologies and industry was not ready for significant capital expenditure in microbiology testing laboratories, being accustomed only to high recurrent costs on media and consumables. There was also the problem of acceptability of the data. Users wanted methods to be approved but were unwilling to participate in the approval system as they faced the costs of running parallel assays, the novel and their conventional assays, and the additional labour was not available.

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Despite these problems, electrical tests are probably the most used automated systems in applied microbiology and have been granted approval by most of the leading method accreditation organizations worldwide and are also accepted by laboratory accreditation bodies. Important reviews include articles by Bolton and Gibson (1994), Silley and Forsythe (1996) and Gibson (2001).

7.2

Instruments

Bactometer (bioMerieux UK Ltd, Grafton Way, Basingstoke RG22 6HY, UK) was one of the first on the market. It was described at the First Symposium on Rapid Methods and Automation in Microbiology and Immunology, Stockholm, 1973 (Cady, 1975) along with the Biobridge (Ur and Brown, 1975), which is no longer produced. It measures overall impedance, capacitance and/or conductance. Samples are held in disposable plastic modules holding eight 2 ml assays and control samples in air incubators. The frequency used for measurement, 2 kHz, favours capacitance more than conductance and so electrode effects predominate. This gives an advantage over other instruments for detecting yeasts and moulds, but in the present context, as pathogenic fungi are rarely measured in foods (their toxins are assayed chemically), there is no advantage. Malthus (Malthus Instruments Ltd, IDG plc, Topley House, 52 Wash Lane, Bury BL9 6AU, UK) developed from work carried out at the Torry Research Station, Aberdeen and the University of Aberdeen, UK (Richards et al., 1978). The author was part of the team. The work derived from experience devising and developing electrical gadgets for measuring fish quality. The Malthus measures purely conductance, minimizing contributions from capacitance by the choice of frequency (10 kHz), and the samples are held in water incubators whose temperature is controlled accurately to within ±0.005ºC. While capacitance was minimized by the use of platinum electrodes in the prototypes (and inert metals in production models), experimental data showed that the conductance changed sooner than capacitance in assays after inoculation with extracts containing bacteria, and conductance was not affected by debris from the inoculum. The fish quality meters use four-terminal electrodes but it was decided that for the size of the changes in conductance of interest there was no advantage and it introduced unnecessary complications to the instrumentation. The RABIT (Rapid Automated Bacterial Impedance Technique, Don Whitley Scientific Ltd, 14 Otley Road, Shipley BD17 7SE, UK) is also based on the Aberdeen work. It uses solid metal block incubators instead of the water baths and close fitting electrode cells to maintain good contact with the metal block. It measures at 2 kHz and thus has more capacitance included than the Malthus. The BacTrac (Sy Lab GMBH, Purkensdorf, Austria) uses four-terminal measurements and offers medium and electrode impedance measurements but does not reveal the electrode composition. They also have a small capacity conductance instrument.

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All instruments can handle multiple samples simultaneously – up to 500 – with free access to the incubator and thus infinite start times for each assay, or in the case of the Bactometer each module of eight assays. The integral computers display the status of each assay and also when assays have exceeded the parameters chosen for a positive result or when the time limit for a negative result has been exceeded. A major advantage of these electrical methods is that they do not require optically clear inocula or media. They can make measurements on cloudy solutions containing particles such as hamburger homogenates without any clarification. The only dilution factor is that required to reduce any antimicrobial factors in the foodstuff, for example as with fresh milk or blood. For example, large quantities, representing 10–20 g of food and 90 ml of liquids, can be inoculated into large Malthus bottles. Where debris might coat electrodes as with the Bactometer and RABIT where the electrodes protrude from the base, the electrodes can be coated with a weak agar gel without affecting the speed of response. At the end of the assay, the test cell can be sampled for further confirmation tests. Indeed, one manufacturer of molecular methods praised the electrical methods to the author as a means of screening out negatives before using expensive reagents for further studies.

7.3

Data presentation

The electrical parameter selected is initially presented as a plot of the change in parameter with time. Data gathered in the first 20–30 min of the assay are often discarded as the assay solution is equilibrating to the set temperature of the incubator. The plot resembles a growth curve but with many more points than is possible by traditional microbiological techniques. Numerous studies have shown good correlations between the microbial count of cultures and the conductance and impedance changes with time since inoculation. Thus, the electrical methods are regarded as an alternative to counts methods. A critical parameter is the point on the curve where it deviates from the baseline. Ideally, baselines are linear and flat, but a certain amount of deviation is tolerated, based on experience with the assay. When viewing a complete growth curve it is easy to see, in retrospect, when the curve deviated and this point is termed the ‘detection time’, the time when growth was first reliably detected. Detection times can be defined empirically, for example when there has been a change in conductance or >10 S after the first reading following temperature equilibration. Plots of detection times against the logarithm of microbial numbers in the inocula are linear. Thus after calibrating the tests against conventional microbiology, detection times can be used as a measure of numbers or counts. This has been shown to have wide ranging validity and the reproducibility of the electrical assay is better as there is less sample manipulation, for example as there is no need to prepare a dilution series.

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For assays in selective media after a pre-enrichment stage, the recoding of a detection time means that the target microorganism is present. It is not possible to relate the count at detection time to the numbers of microbes in the original food sample, but there is a normal relationship to the numbers inoculated from the pre-enrichment. When large volume flasks are used, low numbers of bacteria can be detected – perhaps 1 microbe per inoculum which can be >10 g. As mentioned earlier, positive cultures are often subjected to confirmation tests. Using cultures from electrical tests, the physiological state of the culture can be estimated from the progress of the growth curve, and the cell concentration estimated. This can be useful for some tests when it is useful to know that the sample taken is not dead. Stationary cultures containing many dead cells or cells coated in slime may give poor results in some secondary tests.

7.4

Pathogen assays: introduction

Electrical assays are growth assays and growth depends on the culture obtaining nutrients and energy from the medium and assay environment. Thus all assays are based on traditional methods and conventional information about the growth requirements and characteristics of the culture. The difference lies in the interpretation of the knowledge base. In conventional microbiology, the end point is usually visual detection of a colony on the surface of an agar plate or in the medium, or turbidity of a broth. In the former, clearly separated, welldefined colonies are the aim, with little interference from debris from the food homogenate. In electrical assays, the only consideration is good metabolism of electrically neutral substrates into charge carriers. Dehydrated media of a single type can yield quite different conductance responses from a named organism that has the same colony appearance. Not all peptones and tryptones are the same and media manufacturers do select particular batches for particular purposes or for defined media. This is known in the microbiology community when aliquots from the same batch of media are often distributed to participants in collaborative trials. One UK manufacturer tests media components for conductance response even when the end use is conventional microbiology as it was found that uniformity from production batch to batch was enhanced. With the introduction of ISO 17025 for laboratory media, manufacturers can take the responsibility for quality control of batches of media and so divert lots with good electrical responses to customers with conductance/impedance instruments. The initial capacitance and/or conductance reading of the media in the test cell must be within the measuring range of the instrument. This is a limiting factor as some assays for Salmonella, Listeria, Staphylococcus, etc. utilize media with high salt contents. It is known from physico-chemical studies that the relationship between chemical concentration and conductivity is better at low concentrations (approaching infinite dilution) than at high where doubling the concentration of an ion has little effect. The solution to this problem has been the development of indirect conductance methods (Owens et al., 1989).

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Table 7.1

Conductance and impedance methods for pathogens associated with foods

Microorganism

Reference

Salmonella spp.

Easter and Gibson (1985) Gibson (1987b) Arnott et al. (1988) Ogden (1988) Pugh et al. (1988) Bullock and Frodsham (1989) Pless et al. (1995) Quinn et al. (1995) Gibson et al. (1984) Dupont et al. (1994) Colquhoun et al. (1995) Dupont et al. (1996) Timms et al. (1996) Gibson (1997) Edminston and Russell (1999, 2000) Petitt (1983) Wood and Williams (2000) Gibson (1987a) Dromigny et al. (1997) Philips and Griffiths (1989) Bolton and Gibson (1994) Neaves et al. (1988)

Escherichia coli and coliforms

Enterobacteriaceae Clostridium spp. Listeria spp. Faecal streptococci

During metabolism, all cells produce CO2 (and water). The first CO2 produced dissolves in the medium. As the concentration increases, there is soon a significant level in the headspace above the culture medium and in equilibrium with it. In indirect conductance, the electrodes are placed in an alkaline solution within the assay so that the CO2 can diffuse into the solution, and react to form carbonates, which produce a change in conductance. In theory, every conventional medium could be used as the primary medium and growth detected in the secondary medium. In practice users prefer the direct assay. The most widely used tests for pathogens and indicator organisms in foods are those for Salmonella spp., Enterobacteriaceae, Escherichia coli and coliforms, vibrios, Listeria spp., and to some extent Campylobacter spp. The scope of the assays for pathogens is shown in Table 7.1. The performance of many of the media discussed here are given by Bolton and Gibson (1994).

7.5

Assays for Salmonella

There have been many assays devised for Salmonella spp. in foods: indeed they have been the driving force for the adoption of the conductance methods because the economic case for investment in instruments was easier to justify than for

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other organisms. Also, the reduction in assay time was significant and made salmonella testing worthwhile as recalls based on positive results were feasible and could be complete before the food had reached the retailers and been consumed. The assays are based on more traditional media than some of the current popular growth media because they can contain either active compounds that do not give much of a conduction/impedance change or ion concentrations fall outside the range of measurement of the instruments. The sensitivity and assay times for conductance assays are on a par with those using molecular methods especially when the time for initial cultures are taken into consideration (Gibson, 1998).

7.5.1 Easter-Gibson medium Easter and Gibson (1985) devised their medium based on their work on fish spoilage. They had noted that trimethylamine-N-oxide, an osmoregulator in fish, acted as an electron acceptor during the growth of bacteria, being reduced to trimethylamine, which has the odour of stale fish, and that this reduction was accompanied by a large change in conductance. The substrate is a neutral compound with no net charge and the product is as basic as ammonia. Trimethylamine-N-oxide was added to many commercially available media. These were inoculated with Salmonella spp., recent isolates from foods in a local public health laboratory, and their electrical responses in a prototype Malthus recorded. By far the best response was obtained with Liefson’s selenite-cysteine medium and this was further developed. The recipe is shown in Table 7.2. Conductance changes of >700 S were obtained; in development work for spoilage bacteria, changes of ~100 S were regarded as ‘good’. Many other strains of bacteria from the same source were tested; the only false positives were from some strains of Citrobacter freundi. As it can cause some gastrointestinal infection, it was not regarded as a serious false positive. Liefson used 0.2, 0.4 and 0.8 per cent sodium selenite in his medium depending on the source of the sample. While Easter and Gibson found that 0.4 Table 7.2

Recipe for Easter and Gibson’s Salmonella detection medium

Ingredient

Quantity per litre

Peptone Na2HPO4.2H2O Dulcitol Trimethylamine oxide dihydrate* Sodium biselenite

5 10 5 5.6 4

The pH is adjusted to pH 7.2. The medium is steamed for 10 min. Immediately before use, 10 ml of L-cystine stock (0.1 g in 15 ml N-NaOH made up to 100 ml with water) is added to each litre. * Originally, the hydrochloride salt was used. It was extremely acidic and caused problems if technicians forgot to adjust the pH of the medium. The dihydrate is now widely available and is neutral.

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per cent selenite was best in their studies, they said that users should test the other concentrations for particular applications. One major factor is the concentration of phosphate as Liefson had shown that the toxicity of selenite was greatly increased in the presence of phosphate. Besides the presence of phosphate in some foods, even the fortuitous addition of phosphate in buffers used in sample preparation can have an effect making the medium toxic even for Salmonella spp. The source of the peptone can have an effect on the response of the medium. Easter and Gibson originally used a batch of Evan’s peptone and obtained excellent assay results. Media manufacturers had some difficulty reproducing the responses and had to test many batches of peptones to reproduce the results. For traditional growth assays where the endpoint is a visible colony on the surface of a plate or turbidity in a broth, the precise peptone used is usually of little importance. But in electrical assays, careful selection is important and users may well find that it is better to buy commercially prepared media rather than to make it in their own laboratory. The author has since heard that media manufacturers put considerable effort into the preparation and selection of peptones for specific media and that the lack of reproducibility of results with published media may be due to the particular properties of the constituents of the medium used in the originators’ laboratory. Under the provisions of ISO 17025, manufacturers can ensure the quality of complete batches of media reducing the need for quality control checks by the user. Easter and Gibson’s medium has been modified. Gibson (1987b) substituted mannitol for dulcitol with excellent results. Dulcitol-negative strains of Salmonella spp. are very rare. Mannitol is a better inducer of the enzymes of dulcitol metabolism than dulcitol itself. He also used dimethylsulphoxide as electron acceptor. This was a very efficient and a cheap ingredient but the odour of the endproduct, dimethyl sulphide, proved to be too obnoxious for general use. Some customers reported to media suppliers some false positives from some products, especially some meats. Antibiotic mixes have been devised to reduce their incidence, rather than modifying the medium by varying the concentration of selenite or the selenite/phosphate ratio. An example is given in Table 7.3. Such mixtures are better obtained from suppliers than prepared in the user’s laboratory as testing their selectivity and stability can be onerous. Positive results from pre-enriched cultures are often seen after 6 h incubation. Generally, incubation times of 16 h are used with a maximum of 30 h. A positive result after 48 h was reported to the author some years ago. Extended incubation Table 7.3 Selective agents used in Salmonella media Novobiocin Cefsulodin Additional sodium selenite

0.01 mg/ml Not disclosed 1–2 g/l

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times are generally not productive and better use can be made of the instrument by increasing the number of samples tested. The medium is not toxic to Salmonella spp., after growth is complete. Subcultures can be taken for further testing. In the early days, technicians were reluctant to report a positive result without carrying out confirmation tests in case they activated an expensive product recall in error. With the adoption of the precautionary principle, this may change especially as there are rapid confirmatory tests on the market.

7.5.2 Ogden’s lysine decarboxylase test Ogden (1988) developed his medium to be complementary to the Easter-Gibson medium especially with respect to dulcitol-negative strains and citrobacters. At the time a few strains of the former had been reported although the published incidence was 106) of S. enteritidis and of Shigella sonnei would interfere with the enumeration. As such numbers are highly unlikely to be

Electrical methods Table 7.5

159

Ogden’s GT conductance medium for E. coli (g/l)

Lactalbumin hydrolysate Trimethylamine-N-oxide.2H 2O NaCl K2HPO4 MgSO4.7H2O NH4Cl Na D-glucuronic acid

5 5 5 1 1 0.5 5

found in poultry samples and should result in rejection of the lot, E. coli detection and enumeration on poultry by conductance methods was regarded as a satisfactory method. There have been reports of additions to conductance media to give optical changes useful for confirmation of the species present. Thus methyl umbelliferyl glucuronide has been added as an assay for -glucuronidase. This approach can be developed further.

7.7

Assays for other pathogens

7.7.1 Listeria There have been many attempts to develop media for testing foods for Listeria spp., in particular L. monocytogenes. A major difficulty has been the transition from laboratory studies with pure cultures to assays on real foods, preferably naturally contaminated but more usually spiked, as the methods used in the conventional microbiological tests for comparison are problematic. The indirect conductance method has been used with some success by Bolton (1990) as some of the more recently proposed conventional media use high concentrations of salts as selective agents such that the media are outside the normal measurement range of the instruments. Also some media have included a mixture of antibiotics; these work well with pure laboratory cultures but the presence of foods or food extracts can affect the results. One successful approach was that of Bolton for Malthus. From the taxonomic descriptions of listeria, he incorporated hippuric acid as the key differentiation substrate of the medium with excellent results, both in the microbiological and conductance sense. Bolton and Gibson (1994) discuss the results further. In brief the results from electrical assays are as good as those from conventional tests in that no single method seems able to distinguish all positives, probably in part due to the low numbers of listeria in food samples and their irregular distribution. However, the ‘hands off’ approach of the electrical methods allow for far more samples to be analysed and the resulting cultures are ideal for confirmatory tests, both conventional and molecular biological.

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7.7.2 Campylobacter All manufacturers offer media for campylobacters. One problem is the lack of an approved method for comparison. Another is the use of special gas atmospheres. Bolton found that when he filled the Malthus tubes to the brim with his Preston medium, the medium contained suitable levels of the required gases. His experience, and that of others, is that the conductance methods are suitable for screening foods for campylobacters and give more positives, later confirmed by alternative means, than conventional testing. The protocol is given by Bolton and Gibson (1994).

7.7.3 Clostridia Gibson (1987a) showed that the growth of Clostridium botulinum in pork slurries could be monitored using conductance measurements. Dromigny et al. (1997) devised a medium for detecting clostridia in foods. One problem encountered by many researchers is that the signal breaks up due to the copious production of gas bubbles by some clostridia. This means that there is not a typical growth curve. As the production of gas in the selective media is a characteristic of these microbes, the time taken to break up of signal is a measure of the numbers present and occurs sooner in the assay than the visible appearance of gas.

7.7.4 Vibrios Gibson et al. (1984) showed that vibrios were detected in low salt TCBS ahead of any enteric bacteria. By virtue of their extremely rapid growth relative to any competing bacteria, they were easily detected. They ran the assays along with a coliform assay. When the detection times were shorter in the coliform assay than the TCBS tube, coliforms were present and not vibrios. It should be remembered that many of the differential media are not wholly selective for a particular species of group, and detection within a specified time can give excellent screening results.

7.7.5 Yersinia While Yersinia are not normally assayed in foods except for epidemiological purposes, Walker’s (1989) medium is noteworthy in that hydrolysis of urea is a key feature and this reaction gives a relatively large conductance change, the urea having no charge and the ammonia a very high charge. The trimethylamineN-oxide/trimethylamine couple gives a greater change.

7.7.6 Gram positive bacteria Electrical assays have not been so well developed and used for Gram positives. For example, none of the traditional assays for Staphylococcus aureus have

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really converted well to conductance assays but some are slightly better in impedance assays. Work needs to be done on determining the best concentration(s) of selective agent(s) and inhibitors of competing flora. However, with near sterile products where any contamination is likely to be Stap. aureus suitable assays have been devised. The problem lies with the lack of a universal medium for general food use and this was also the case for many years with traditional approaches. Provided that their metabolism can be tweaked to give copious amounts of CO2, the indirect method should be suitable for detecting most microbes. In practice, it seems that the bacteria with the most active decarboxylases are those easily detected by direct assay.

7.8

Accreditation of electrical methods

The Malthus system for Salmonella spp. in all foods was the first pathogen assay using electrical methods to obtain an international approval, in this case from the AOAC International, the independent US approvals body (Gibson et al., 1992), and Final Action Status was later granted on the basis that there was satisfaction and no complaints from users. This was a landmark, in that it was the first automated hands-off system to be approved. The approval is ring-fenced and applies only to the Malthus system. It involves using the two media, TMAOdulcitol-based and Ogden’s lysine media after pre-enrichment. Positive results require, for AOAC purposes, to be confirmed by their conventional procedures. In retrospect, a single medium assay is all that is needed. Because there were a few reports at the time of dulcitol-negative salmonellas, the company played safe by using the lysine medium in tandem. Since then, there have been so few isolates of such bacteria, that it would be better to use the capacity of the instruments to double the number of samples as the heterogeneity of the distribution of salmonellas in food is a greater risk for missing them than the occurrence of a dulcitol-negative strain. The Salmonella system has since been approved for all conductance assays by the International Standards Organization (ISO) and many of its component bodies. The International Dairy Federation (IDF) ran a large trial with instruments from different manufacturers and gave the assay approval. Some details of the trials have been published (Prentice et al., 1990). The shellfish assays for enteric bacteria are used by the official bodies for monitoring bivalves in France. Many laboratories using electrical methods have been granted accredited status by their national authorities. In addition, such laboratories are normally members of proficiency testing programmes and their results on distributed samples have been within the norm expected.

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7.9

Conclusions and future trends

Of all the rapid automated methods in food microbiology the electrical methods have come of age. They are accepted by their users and their customers and the brand names are quoted in scientific conversation as understood by all. There has been a dearth of recent publications describing methods but this is mainly due to the maturity of the existing methods as practised in thousands of laboratories worldwide servicing the public demand for safe food. The plot of the change of conductance with time can yield a wealth of information. Jason and Jason (1998) have devised algorithms to identify species and subspecies from the data from E.coli growth curves. This approach – detection and identification in a single assay – deserves further study. Linkage with other evolving technologies both at the preliminary stages of the assays such as separating and concentrating the target microorganisms with selective magnetic beads, and confirmation of positive screening assays with molecular biological methods are to be encouraged. No other hands-off screening method yields such a mass of cells for further work.

7.10

References

and GRIFFITHS, J.L. (1988) ‘Detection of salmonellas in confectionery products by conductance’. Journal of Applied Bacteriology, 64, 409–20. BOLTON, F.B. (1990) ‘An investigation of indirect conductimetry for detection of some foodborne bacteria’. Journal of Applied Bacteriology, 69, 655–61. BOLTON, F.B. and GIBSON, D.M. (1994) ‘Automated electrical techniques in microbiological analysis’. In: Rapid Analysis Techniques in Food Microbiology, ed. P. Patel. London, Blackie, pp. 131–69. BULLOCK, R.D. and FRODSHAW, D. (1989) ‘Rapid impedance detection of salmonellas in confectionery using modified LINCR broth.’ Journal of Applied Bacteriology, 66, 385–91. CADY, P. (1975) ‘Rapid automated bacterial identification by impedance measurements’. In: New Approaches to the Identification of Microorganisms, eds C.G. Heden and T. Illeni. London, Wiley, pp. 74–99. COLQUHOUN, K.O., TIMMS, S. and FRICKER, C.R. (1995) ‘Detection of Escherichia coli in potable water using direct impedance technology’. Journal of Applied Bacteriology, 79, 635–9. DROMIGNY. E., BOURRION, F., RUGRAF, Y., BOLTON, F.J. and LEDEN, N. (1997) ‘New media for detection and counting of Clostridia in foods’. Letters in Applied Microbiology, 24, 19–22. DUPONT, J., MENARD, D., HERVE, C. and MINIER, B. (1994) ‘Analytical procedure for use of conductance measurements to estimate Escherichia coli in shellfish’. Journal of Applied Bacteriology, 77, 296–302. DUPONT, J., MENARD, D., HERVE, C., CHEVALIER, F., BELIAEFF, F. and MINIER, B. (1996) ‘Rapid estimation of Escherichia coli in live bivalve shellfish using automated conductance measurement’. Journal of Applied Bacteriology, 80, 81–90. ARNOTT, M.L., GUTTERIDGE, C.S., PUGH, S.J.

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and GIBSON, D.M. (1985) ‘Rapid and automated detection of salmonella by electrical measurements’. Journal of Hygiene (Cambridge), 94, 245–62. EDMINSTON, A.L. and RUSSELL, S.M. (1999) ‘Evaluation of a conductance method for enumerating Escherichia coli on chicken, pork, beef and milk’. Journal of Food Protection, 62, 1260–5. EDMINSTON, A.L. and RUSSELL, S.M. (2000) ‘Specificity of a conductance assay for the enumerating Escherichia coli from broiler carcass rinse samples containing genetically similar species’. Journal of Food Protection, 63, 264–7. GIBSON, A.M. (1987a) ‘Use of conductance measurement to detect growth of Clostridium botulinum in a selective medium’. Letters in Applied Microbiology, 5, 19–21. GIBSON, D.M. (1987b) ‘Some modifications to the media for rapid automated detection of salmonellas’. Journal of Applied Bacteriology, 63, 299–304. GIBSON, D.M. (1997) ‘Bacteriological classification of shellfish by Malthus conductance measurements’. In: Fish Inspection, Quality Control and HACCP, eds. R.E. Martin, R.L. Collette and J.W. Slavin. Technomic, Lancaster, USA, pp 342–9. GIBSON, D.M. (1998) ‘Sensitivity of rapid tests for Salmonella in foods’. Letters in Applied Microbiology, 27, 384. GIBSON, D.M. (2001) ‘Conductance/impedance techniques for microbial assay’. In: Instrumentation and Sensors for the Food Industry, 2nd edn, eds E. Kress-Rogers and C.J.B. Brimelow. Woodhead, Cambridge, pp. 484–517. GIBSON, D.M., COOMBES, P.C. and PIMBLEY, D.W. (1992) ‘Automated conductance method for the detection of Salmonella in foods: collaborative study’. Journal of AOAC International, 75, 293–302. GIBSON, D.M., OGDEN, I.D. and HOBBS, G. (1984) ’Estimation of the bacteriological quality of fish by automated conductance measurements’. International Journal of Food Microbiology, 1, 127–34. HEDEN, C.G. and ILLENI, T. (1975) Automation in Microbiology and Immunology. Wiley, New York. JASON, D. and JASON, A.C. (1998) ‘Automated typing of bacterial isolates’. Letters in Applied Microbiology, 25, 431–4. NEAVES, P., WADDELL, M.J. and PRENTICE. G.A. (1988) A medium for the detection of Lancefield Group D cocci in skimmed milk powder by measurement of conductance changes. Journal of Applied Bacteriology, 65, 437–48. OGDEN, I.D. (1988) ‘A conductance medium to distinguish between Salmonella and Citrobacter spp.’. International Journal of Food Microbiology, 7, 287–97. OGDEN, I.D. (1993) ‘A conductance assay for the detection and enumeration of Escherichia coli.’ Food Microbiology, 10, 321–7. OGDEN, I.D., BROWN, G.C., GALLACHER, S., ET AL. (1998) ‘An interlaboratory study to find an alternative to the MPN technique for enumerating Escherichia coli in shellfish’. International Journal of Food Microbiology, 40, 57–64. OGDEN, I.D., MACRAE, M. HEPBURN, N.F. and STRACHAN, N.J.C. (2000) ‘Improved isolation of Escherichia coli O157 using large enrichment volumes for immunomagnetic separation’. Letters in Applied Microbiology, 31, 338–41. OWENS, J.D., THOMAS, D.S., THOMSON, P.S. and TIMMERMAN, J.W. (1989) ‘Indirect conductimetry: a novel approach to the conductrimetric enumeration of microbial populations’. Letters in Applied Microbiology, 9, 245–9. PETIT, S.B. (1983) ‘Detection of ‘‘coliforms’’ and Enterobacteriaceae’. Journal of Applied Bacteriology, 55, vii. PHILIPS, J.D. and GRIFFITHS, M.W. (1989) ‘An electrical method for detecting Listeria spp.’. EASTER, M.C.

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Letters in Applied Microbiology, 9, 129–32. and GSCHWANDTER, A. (1995) ‘Rapid detection of Salmonellae by means of a new impedance-splitting technique’. Journal of Food Protection, 57, 369–76. PRENTICE, G.A., NEAVES, P. and JERVIS, D.I. (1990) ‘An interlaboratory evaluation of an electrical method for detection of salmonellas in milk powders’. In: Rapid Microbiological Methods for Foods, Beverages and Pharmaceuticals, eds C. Stannard, S.B. Pettit and F.J. Skinner. Blackwell, Oxford. pp. 155–64. PUGH, S.J., GRIFFITHS, J.L., ARNOTT, M.L. and GUTTERIDGE, C.S. (1988) ‘A complete protocol using conductance for rapid detection of salmonellas in confectionery’. Letters in Applied Microbiology, 7, 23–7. QUINN, C., WARD, J., GRIFFIN, M., YEARSLEY, D. and EGAN, J. (1995) ‘A comparison of conventional culture and three rapid methods for the detection of Salmonella in poultry feeds and environmental samples’ Letters in Applied Microbiology, 20, 89– 91. RICHARDS, J.C.S., JASON, A.C., HOBBS, G., GIBSON, D.M. and CHRISTIE, R.H. (1978) ‘Electronic measurement of bacterial growth’. Journal of Physics E: Scientific Instruments, 11, 560–8. SILLEY, P. and FORSYTHE, S.J. (1996) ‘Impedance microbiology – a rapid change for microbiologists’. Journal of Applied Bacteriology, 80, 233–43. STEWART, G.N. (1899) ‘The changes produced by the growth of bacteria in the molecular concentrations and the electrical conductivity of culture media’. Journal of Experimental Medicine, 4, 235–47. TIMMS, S., COLQUHOUN, K.O. and FRICKER, C.R. (1996) ‘Detection of Escherichia coli in potable water using indirect impedance technique’. Journal of Microbiological Methods, 26, 125–32. UR, A. and BROWN, D.F.J. (1975) ‘Monitoring bacterial activity by impedance measurements’. In: New Approaches to the Identification of Microorganisms, eds C.G. Heden and T. Illeni. London, 61–71. WALKER, S.J. (1989) ‘Development of an impedimetric medium for the detection of Yersina enterocolitica in pasteurised milk. IDF Seminar on Modern Microbiological Methods, Santander, Spain. WOOD, A.D. and WILLIAMS, P.E.V. (2000) Quantitative analysis of Enterobacteriaceae in the determination of animal feed hygiene. Society for Applied Microbiology Summer Conference, p 48. PLESS, P., FUTSCHIK, K.

8 ATP bioluminescence M. Griffiths and L. Brovko, Canadian Research Institute for Food Safety

8.1

Introduction

The food industry is increasingly adopting food safety and quality management systems that are more proactive and preventative than those used in the past which have tended to rely on endproduct testing and visual inspection. The regulatory agencies in many countries are promoting one such management tool, Hazard Analysis Critical Control Point (HACCP), as a way to achieve a safer food supply and as a basis for harmonization of trading standards. For HACCP to be effective, rapid methods for monitoring and verifying performance are desirable. Monitoring usually relies on surveillance of physical or chemical parameters of a process such as time and temperature of heating or pH, whereas validation of HACCP performance requires testing for the absence of specific pathogens such as Salmonella, Escherichia coli O157:H7, Campylobacter jejuni, Listeria monocytogenes and others. There is some controversy as to whether microbiological tests can be used to monitor critical control points (CCPs) because of the length of time needed to generate results and the sampling strategy required to obtain meaningful results. However, considerable advantages may accrue if verification can be achieved quickly. Of all the rapid microbiological tests currently available, the only one that comes close to offering real-time results is ATP bioluminescence.

8.2

Principles of ATP bioluminescent assay

The ATP bioluminescence technique for cell detection was first described in the 1960s by NASA scientists who were interested in clinical applications as well as

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Fig. 8.1 Scheme of ATP-based bioluminescent reaction.

determining if life existed on other planets (Chappelle and Levin, 1968). It makes use of the fact that all living cells contain adenosine triphosphate (ATP), which is the universal energy donor for metabolic reactions. However, after cell death, the ATP content decreases sharply, allowing the intracellular ATP concentration to serve as a measure of biomass and cell viability. An enzymesubstrate complex, luciferase-luciferin, present in firefly tails converts the chemical energy associated with ATP into light by a stoichiometric reaction (Fig. 8.1). The amount of light emitted is proportional to the concentration of ATP present and can be quantified using light detecting devices. Because the quantum yield of this bioluminescent reaction is 0.88 (Seliger and McElroy, 1960), almost 1 photon is emitted per reaction cycle. As instruments are available that can detect even single photons, the theoretical sensitivity of the bioluminescent ATP assay is extremely high (1 amol). The level of ATP in a cell remains relatively constant; thus, the light produced during the luciferaseluciferin catalyzed reaction is directly related to the number of metabolically active cells present in the assay. Assuming that the ATP content of an average bacterial cell is about 1–10 amol, even single cells should be detectable using this method. Sharpe et al. (1970) were the first to apply the method to the detection of microorganisms in food but the high level of ATP from nonmicrobial sources reduced the sensitivity substantially. Although there continued to be an interest in the application of ATP bioluminescence for assessing microbial contamination of food, it was not until the early 1990s that the technique came of age in the food industry (Griffiths, 1993; 1995; Kyriakides and Patel, 1994). In an attempt to improve the sensitivity of ATP bioluminescence, Squirrell and Murphy (1995) proposed the use of the enzyme adenylate kinase (AK) as a cell marker. AK is a key intracellular enzyme found in both prokaryotic and eukaryotic cells that equilibrates AMP, ADP and ATP by the reaction: MgATP AMP , MgADP ADP When excess ADP is used as the substrate, ATP will be produced in an amount proportional to the concentration of AK present. This ATP can be assayed using the luciferin-luciferase system. From the turnover number and the cellular ratio of AK to ATP it was predicted that, with 1 minute incubation, 40–50 times more ATP would be available for bioluminescent detection than in assays for ATP alone. This would correspond to a limit of detection between 20 and 25 bacterial cells. The bioluminescent AK assay of bacteria retained the simplicity of ATP

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assay and had better sensitivity. However, in practice the instability of ADP and the presence of relatively high admixtures of ATP, even in highly purified ADP preparations, does not allow this theoretical detection limit to be reached.

8.3

Assay for testing the total bacterial count of food products

ATP bioluminescence assays have been developed to estimate the total microbial load in a number of products. As ATP in food can be present in somatic cells, as free ATP, or in microorganisms, microbial ATP must be separated from other sources before assay. The original ATP techniques relied on selective lysis of somatic cells with a non-ionic detergent, such as Triton X100, followed by enzymatic or chemical destruction of the released ATP. Microbial ATP was subsequently extracted with a cationic detergent and assayed with luciferase-luciferin. The number of cells present was calculated from standard curves relating ATP concentration (or emitted light in Relative Light Units (RLU) to cell count (cfu/ml)). While convenient and rapid, this format suffered from inherent insensitivity (Griffiths, 1991). More recently researchers have utilized ways of concentrating microorganisms from foods before performing the ATP assay. These have consisted of filtration (ATP-F Test, Lumac BV, Landgraaf, The Netherlands; Milk Microbial ATP Kit, Biotrace Ltd., Bridgend, UK) or centrifugation (Enliten reagent, Promega, Madison, Wis.) followed by release of microbial ATP and quantification. The necessity of a two-step procedure for bioluminescent microbial detection was determined by certain instability of luciferase in lysis reagent. Recently a novel single-step bioluminescent reagent was proposed by Promega Corporation (Creswell et al., 2002). This has been made possible by using a mutant form of firefly luciferase that was developed through directed evolution to be robust to lytic agents. The stable luciferase was used in the reagent that combined the lytic agent with luciferin-luciferase making possible new simplified assay formats. For filterable solutions, another approach was introduced by Millipore Corporation (MicroStarTM system) that provides quantitative results in minutes for yeast, and a few hours for bacteria. The assay protocol involves filtering a sample through a specialized membrane that retains and distributes microorganisms evenly across the membrane. The system enables detection of single yeast cells immediately after filtration. Bacterial detection requires a brief incubation of the membrane on the surface of an appropriate nutrient medium. The incubation time required is typically a quarter to one third the time needed for regular plate counts. An ATP releasing agent is sprayed onto the filter and, after a short drying period, bioluminescent reagent is added that produces ‘light spots’ (photons) corresponding to each yeast cell or bacterial microcolony. Emitted photons are detected by a fast-scan charge-coupled device (CCD camera), and a membrane image with spatial distribution of the light spots is produced. Total photon detection time is two minutes. The system can detect as

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few as 1 to 200 cfu per sample. The obtained results are directly comparable with standard plate counts.

8.4

The use of assays for particular foods

8.4.1 Raw milk ATP bioluminescence assays for the determination of microbial load in raw milk within 10 min have been described (Bautista et al., 1992; Griffiths, 1991; Reybroek and Schram, 1995; Sutherland et al., 1994; Frudzhyan et al., 1999; Brovko et al. 1999; Samkutty et al., 2001). The milk is incubated in the presence of a somatic cell-lysing agent and then filtered through a bacteria-retaining membrane. The microorganisms retained on the filter are then lysed and the lysate assayed for ATP activity. Microbial populations as low as 104 cfu/ml can be detected and the methods have a greater precision than the plate count. The technique is useful for screening incoming tanker milk at processing sites and monitoring quality during prolonged storage. Although the detection limit achieved by these modifications may be sufficient for practical use, the accuracy of analysis was not significantly improved. The reported values for accuracy estimates for cfu/ml in raw milk (Sxy) by the bioluminescent methods were in the range of 0.27–0.87 log units. The main reason for this inaccuracy was the error in estimation of cfu/ml introduced due to bacterial clumping which was dependent on both the level of bacterial contamination and composition of the milk itself. To improve correlation between ATP and cfu, it may be more appropriate to obtain separate correlation curves for milk samples from different sources with relatively stable bacterial populations (Brovko et al., 1999). The accuracy of the ATP bioluminescence assay of bacterial quality of raw milk can also be improved by the introduction of a preliminary incubation of the raw milk sample at 15.6ºC for 18 h (Samkutty et al., 2001). This approach assumes that low-temperature incubation of milk allows the growth of only the psychrotrophic microflora and the normal flora of the udder will not grow. Coefficient of linear regression of ATP bioluminescent assay versus standard plate counts improved significantly after incubation from 0.58 to 0.80. A ‘concentrating’ reagent, Enliten, has been described that clarifies milk and allows the removal of microorganisms by centrifugation. Combination of this treatment with an ATP assay enabled detection of microbial levels down to 2104 cfu/ml to be detected within 6–7 min (Pahuski et al., 1991). However, this method has not found wide application in comparison with the filtration techniques mentioned above. Incorporating a pre-incubation step before the ATP assay provides a useful 25 h test for the keeping quality of pasteurized milk (Griffiths, 1993). This principle was used in the Rapid Pasteurized Milk Screen and Shelf Life Determination test from Celsis Inc. (Evanston IL, USA). ATP bioluminescence can also be used for sterility testing of UHT products, saving two to five days over conventional methods (Griffiths, 1993). A sensitive and rapid (1.5 h) test

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for antibiotics in milk has also been described that relies on the detection of the growth of Streptococcus thermophilus in milk by ATP bioluminescence (Hawronskyj et al., 1993).

8.4.2 Drinking water, brewing, beverage, fruit and fruit juice ATP bioluminescence provides a very fast alternative (< 5 min) for detection of bacteria in drinking water in comparison with the conventional plate count technique that takes up to seven days (Deininger and Lee, 2001). Spoilage of beer is mainly brought about by yeasts and Lactobacillus spp. Yeasts contain about 100 times more ATP than bacterial cells and, thus, can be detected at lower numbers. However, beer contains high levels of non-microbial ATP as well as components that quench the light reaction, so a filtration step is necessary before the luciferaseluciferin reaction can be applied (Kyriakides and Patel, 1994). Simpson et al. (1989) described such a method for the sensitive detection of microorganisms in filtered, unpasteurized beer that could be performed in 60 min. They suggested that the method could be carried out on continuous in-line filters providing a rapid indication of process efficiency. Takashi et al. (2000) applied MicroStarTM-RMDS (Millipore Corp.) for detecting beer-spoilage bacteria (Lactobacillus brevis). Judging from the detection time and detection limit, 16–24 h of cultivation for the RMD System corresponded to 40–96 h of cultivation for the standard plate count method. Unlike beer, carbonated beverages generally contain low levels of nonmicrobial ATP. Since they can be easily filtered and spoilage is mainly due to yeasts, ATP bioluminescence assays are a useful indication of product quality (Kyriakides and Patel, 1994). A filtration system using vortex mixing filtration technology, the Haemocell Rapid Microbial Quality Assurance (RMQA) system (GEM Biomedical, Inc., Hamden, Conn.) achieves rapid and gentle filtration by creating a turbulent flow across a dimpled membrane. The final sample can be retrieved into a disposable syringe by back washing the filter with ATP-free water. When combined with an ATP bioluminescence assay, the filtration system allowed low-level microbial contamination of brewing products to be detected in 60 min (Davies et al., 1995). The RMQA system in conjunction with ATP bioluminescence has also been applied successfully to carbonated beverages (Heying, 1995). Biotrace Ltd. produces a reagent kit (Bev-TraceTM) designed to detect rapidly the presence or absence of spoilage contaminants in all filterable beverages that are pasteurized or sterile filtered. According to the developed protocol, the required volume of beverage is first filtered through a 47 mm sterile filter with 0.2–1.2 m pore size followed by a rinsing step. To concentrate and increase microbial contamination, an initial filtration step is followed by an enrichment phase on a suitable growth medium. After enrichment, the membrane is treated with ATPase for 60 min to remove non-microbial ATP. Extraction and detection of microbial ATP with luciferin-luciferase reagent takes another two minutes. If the light output registered from the test sample is three times higher than for the control (sterile) sample, it indicates the presence of microorganisms.

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An ATP bioluminescence assay was used for estimating total plate counts of surface microflora of whole cantaloupe and determining efficacy of washing (Ukuku et al., 2001). A high correlation (r2 0:995) was observed between bioluminescence and aerobic plate count of unwashed and washed (with water) cantaloupe. A reliable minimum detection level obtained with the bioluminescent method was 104 cfu/cm2, but that was not sufficient for evaluation of cantaloupe washed with hypochlorite or hydrogen peroxide. Attempts have been made to apply ATP bioluminescence to fruit juices, with varying results. Problems are encountered due to high non-microbial ATP levels associated with pulp cells, and the low pH of the products. When reconstituted orange juice concentrate was analyzed immediately, the results were poor, but they improved after storage of the reconstituted product at 25ºC for 24 h (Kyriakides and Patel, 1994). A rapid method for the microbiological assessment of fruit juices and fruit concentrates marketed by Celsis-Lumac involves 48 h pre-incubation of product at 28–30ºC, followed by treatment with a nucleotide-releasing solution (F-NRS) to lyse somatic cells and with a hydrolytic enzyme (Somase) that destroys ATP released from these somatic cells prior to assay of microbial ATP with luciferase-luciferin.

8.4.3 Poultry Bautista et al. (1995b) have described a method for the enumeration of surface contamination of poultry carcasses by ATP bioluminescence. Chicken carcass rinse water was treated with a somatic cell-lysing agent containing lipase. The treated solution was then filtered, first through a coarse filter and then through a bacteria-retaining filter. The cells trapped on the filter were lysed and assayed for ATP. Good correlations were obtained with plate count and levels of 5 104 cfu/ml of rinse water (corresponding to about 2 103 cfu/g carcass weight) could be detected in less than 15 min. A simplified version of the poultry carcass ATP test was used to monitor CCPs identified at a poultry processing plant. The test, which involved swabbing and then extracting and assaying the ATP on the swab, took about two minutes to complete. ATP levels were elevated on carcasses directly after evisceration but dropped to low levels after the pre-chill and chill tanks. This work suggests that this simple test may provide a way for microbiological monitoring of CCPs in poultry processing operations (Bautista et al., 1996). A rapid ATP bioluminescence test to monitor the microbial load in poultry processing waters within 15 minutes has also been described (Bautista et al., 1994). This provides a near real-time indication of water quality and allows water use in the plant to be minimized.

8.4.4 Meat Siragusa and co-workers at the US Department of Agriculture’s Meat Animal Research Laboratories in Nebraska have developed ATP bioluminescence

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assays for beef and pork carcasses (Siragusa and Cutter, 1995; Siragusa et al., 1995). A 500 cm2 area of beef carcass or a 50 cm2 area of pork carcass were swabbed using an ATP-free, sterile, microbiological sampling sponge moistened with saline and Tween 80. After swabbing, the liquid was removed from the sponge and the somatic cell ATP was extracted and removed using a special filtration device, the Filtravette (New Horizons Diagnostics, Columbia, Md.). The bacteria were retained in the device, which could then be placed in the luminometer (New Horizons Diagnostics), where the microbial ATP was extracted and assayed. The assay could be performed in about 5 min and the lower limits for detection were 1 102 cfu/cm2 and 1.6 103 cfu/cm2 for beef and pork carcasses, respectively. An ATP bioluminescence method for assessing the microbiological quality of beef carcasses sampled by excising a 5 cm 5 cm area of the surface has been described. The excised sample was rinsed and processed in somatic cell extractant containing lipase. The bacteria were removed by filtration and their ATP content determined. Microbial numbers down to 4 104 cfu/cm2 on the beef carcass were detectable in 15 min (Bautista et al., 1995a). The sensitivity could be improved dramatically by sampling a larger area. If the same area sampled in the USDA study had been used in the latter study, the sensitivity would be about 2 103 cfu/cm2. A similar approach was used by Celsis-Lumac (Netherlands) for screening the total microbial contamination level of beef and pork carcasses. The developed method allows testing of total bacterial contamination of beef and pork carcasses within 10 min with a sensitivity of 100 cfu/cm2 and 500 cfu/cm2, respectively (Zwartkruis et al., 1999). The reported correlation of the method with the plate count technique was 0.95 and 0.93 for beef and pork, respectively. A method for assessing the bacterial contamination of minced meat was developed by Frudzhyan et al. (2002). Due to the high level of non-bacterial ATP in raw minced meat that corresponds to 107–108 bacterial cells per g of meat, a novel method for its elimination was proposed. Treatment with pancreatin – Neonol mixture at 45ºC for 60 min followed by filtration through a FiltravetteTM (New Horizons Diagnostics, Columbia, Md.) was used to destroy somatic ATP from the sample and allowed detection of 103–105 cfu/g of minced meat. The correlation with standard plate count was 0.99 and the analysis time was 2 h in comparison to 48–72 h required for the traditional method.

8.5

The use of assays for hygiene monitoring

ATP bioluminescent techniques are increasingly used for measuring the efficiency with which surfaces and utensils are cleaned. A survey of 500 food manufacturing businesses in the UK revealed that 48 per cent of respondents used swabbing followed by bacterial culture, while 27 per cent used ATP bioluminescence (Davidson et al., 1999). To adequately sanitize a food contact surface, it must first be washed to remove any food residues that could act as a nutrient source for subsequent growth of microorganisms. Following washing,

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the surface is sanitized to kill the residual microflora. If either process is not done properly, food particles and/or microorganisms could remain on the surface and may constitute a risk to the quality and safety of foods to be processed afterward. Normal swabbing and plate counting procedures would detect only microbial contamination of the surface and may not tell you whether the surface has been cleaned properly. However, ATP bioluminescence detects contamination from both sources within two minutes and is a more reliable indicator of the overall hygienic condition of the area tested (Hawronskyj and Holah, 1997). Several studies have compared the results obtained by standard microbiological techniques and ATP bioluminescence for assessing surface cleanliness. Some reported a good correlation between these methods (Seeger and Griffiths, 1994; Kyriakides et al., 1991; Bautista et al., 1992). Others have obtained a poor correlation (Griffith et al., 1997; Poulis et al., 1993; Carrick et al., 2001). Such discrepancy in findings could be explained either by the different nature of the surface and surface contamination (presence of spores, for example) or inability/ inconsistency of swabs to pick up microorganisms effectively. Loss in bacterial viability during drying could also have an impact on both ATP bioluminescence and plate count results. In addition, the presence of detergents, sanitizers or other chemicals may interfere with bioluminescent reaction (Velazquez and Feirtag, 1997) leading to false positive or false negative results. Despite these difficulties ATP bioluminescence has been used successfully as an initial step in hygiene monitoring, especially within HACCP plans. Most of the ATP-based reagent kits produced for rapid surface cleanliness (EnlitenÕ Total ATP rapid biocontamination detection kit, Promega, WI; Clean-TraceTM Rapid Cleanliness kit, Biotrace, UK) tests rely on the use of a baseline cut-off value that should be determined for every tested environment. Protocols have been proposed for evaluation of ATP-based hygiene monitoring systems and they were tested for three different single-shot systems manufactured by Biotrace Ltd (UNILITE Xcel), Charm Sciences (Luminometer K, PocketSwab) and IDEXX (LightNING) (Colquhoun et al., 1998). It was anticipated that a described test protocol could be the first tier of a more extensive assessment programme which could include, in addition to sensitivity and accuracy, also direct surface swabbing comparison and the effect of sanitizers on system responses. Although the existing ATP bioluminescent assays are sufficient for the needs of 90 per cent of the food industry, in certain situations there is a demand to detect low levels of bacteria that may still be present. For these cases, an ATP recycling system that uses a cocktail of enzyme to amplify low ATP levels was developed (Hawronskyj et al., 1994). The amplification reagent consists of a mixture of firefly luciferase, myokinase and pyruvate kinase together with their substrates (luciferin, AMP and phosphoenolpyruvate), which effectively ‘amplifies’ all AMP to ATP (Fig. 8.2). The time for the reaction to reach half of the maximum light output is directly related to the log of ATP and can be used as an indicator of cleanliness. A combined index of ATP, AMP and RNA was proposed by Sakakibara et al. (1999) for hygiene monitoring. Simultaneous bioluminescent detection of all

ATP bioluminescence

Fig. 8.2

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Reaction scheme for ATP amplification.

these metabolites was achieved by coupling the reaction catalyzed by pyruvate orthophosphate dikinase (PPDK) with firefly luciferase (Fig. 8.3). The sensitivity of the detection of food residues on surfaces was several-hundredfold better than with usual methods using ATP as an index. Adenylate kinase (AK) amplification of ATP bioluminescence was also used for hygiene monitoring in the food industry (Corbitt et al., 2000). It was shown

Fig. 8.3 Reaction scheme for bioluminescence cycling assay for ATP and AMP.

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that AK could be used not only as a bacterial cell marker as proposed by Squirrell and Murphy (1995), but as a marker of food residues as well. The technique is particularly applicable to the meat and vegetable industry and to certain dairy products (milk, yogurt, cottage cheese). Further research is required to implement this method in a fruit processing environment.

8.6

The use of assays to detect particular pathogens

Despite the fact that ATP bioluminescence has been used for bacterial detection for a long time, it is only recently that this technique has been adapted for detection of specific pathogens. The developed protocols include, as a first step, the recognition of the target bacteria followed by its lysis and ATP assay. Recognition of the bacteria can be achieved by specific antibodies or by specific bacteriophages.

8.6.1 Antibody-based bioluminescent methods for detection of bacterial pathogens Most of the traditional methods for pathogen detection that are based on the recognition of specific bacterial antigens by antibodies are able to detect the presence of target organisms in complex mixtures. However, on average, these systems detect from 104 to 106 cells per ml (Niroomand and Lord, 1994; Huang and Chang, 1996). Even the introduction of firefly luciferase, one of the most sensitive labels, as a label for the secondary antibody did not improve the sensitivity of Bioluminescent Enzyme ImmunoAssay (BLEIA) significantly (Fukuda et al., 2000). As a result, in order to detect 50 cfu/ml of, for example, Staph. aureus a 5 h enrichment step is necessary. The introduction of a step involving specific concentration of bacteria using a biosorbent substantially decreases the analysis time (Blais et al., 1997). One such method, immunomagnetic separation (IMS) is based on the use of magnetic beads coated with a target cell-specific antibody for capturing the cells. Methods incorporating IMS have gained widespread acceptance for the detection of foodborne pathogens in recent years. In addition to concentrating target bacteria in a small volume and, thus, avoiding a long enrichment step, biosorbents also permit removal of all food components from the sample which otherwise could interfere with analysis. Coupling of IMS with ATP bioluminescence resulted in the development of methods for enumeration of E. coli O157:H7 (Tu et al., 2000; Aytac et al., 2001). It was shown that addition of glucose to the solution increased the ATP content of free as well as captured cells (Tu et al., 1999), providing a better assay sensitivity. According to the developed experimental protocol, beef hamburger patties spiked with different levels of E. coli O157:H7 were incubated for 6 h in specific media at 37ºC. After incubation E. coli cells were captured by IMS, washed and resuspended in glucose-containing buffers. Since the meat samples might contain extracellular ATP from damaged beef

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muscles and other bacteria, luciferin-luciferase mixture was added to the sample before the extractant solution in order to consume non-bacterial ATP in the bioluminescent reaction. After that bacterial extractant was added, only the intracellular ATP associated with bacterial cells was detected. The presence of less than 1 cfu of E. coli O157:H7 per ml of beef hamburger suspension could be detected after 6 h enrichment. Commercial magnetic beads coated with antibodies against Salmonella spp., E. coli O157:H7 and Listeria spp. are available from Dynal Inc. (Oslo, Norway); however no method has been published describing coupling of IMS with ATP bioluminescence for detection of Salmonella and Listeria. The sensitivity and specificity of bioluminescent IMS assays for particular pathogens depend to a great extent on the specificity and affinity of the antibody towards the live bacterial cell. The efficiency of bacterial capture is a function of antibody properties as well as environmental conditions, such as pH, media composition, osmomolarity and water activity. Screening of available antibodies and optimal conditions for cell capturing is an essential part of IMS method development. Either ATP bioluminescence or in vivo bioluminescence can be used as a tool for assessing the efficiency of IMS (Sun et al., 2002). The sensitivity of detection of captured cells by ATP bioluminescence was improved by one log unit when this approach was used to optimize IMS capture of E. coli O157:H7.

8.6.2 Phage-based bioluminescent assays Phage-based biosorbents are an attractive alternative to immunosorbents due to their greater specificity and faster binding. Bacteriophages are also cheaper to mass-produce than antibodies. A phage-based biosorbent consisting of a Salmonella-specific phage passively immobilized on a polysterene membrane has been used to specifically separate Salmonella from a food matrix (Bennet et al., 1997). However, the efficiency of cell capture was poor. Biotinylation of phage head protein and construction of biosorbents by coating magnetic beads with phage via the biotin-streptavidin interaction significantly increased capturing efficiency (Sun et al., 2001). Another advantage of using bacteriophage as a biosorbent for bacterial pathogens is that it allows combination of both concentration and detection steps. The target bacterial cells can be captured by phage-based biosorbent and the resulting cell lysis can then be detected by ATP bioluminescence (Sanders, 1994a, b), providing a way to enumerate captured bacteria. Using the AK bioluminescent assay instead of ATP in phage-based pathogen detection assays was proposed by Blasco et al. (1998). It was expected that sensitivity would be improved significantly due to the higher sensitivity of the AK-based bacterial enumeration assay (see Section 8.2). However, this approach allowed only about 104 cfu/ml of E. coli and Salmonella to be detected within 1 and 2 h, respectively. Evidently phage-mediated AK release was not optimized and did not reach a maximum level. It has been shown that the multiplicity of infection (MOI) influenced the amount of AK released by lysis and this consequently affected the sensitivity of the whole assay (Wu et al., 2001). At

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optimal MOI (10–100), the amount of phage-released AK reached almost 100 per cent and allowed specific detection of E. coli and Salmonella in mixed culture with a sensitivity of approximately 103 cfu/ml for both cultures, corresponding to detection of 25 cells per 25 l sample within 2 h. Combination of IMS and phage-mediated AK release was used by Squirrell et al. (2002) for rapid and specific detection of bacteria. The obtained sensitivity using bioluminescent AK assay as a detection method was around 102 cells per ml for E. coli O157:H7. Depending on the level of specificity, the assay took from five minutes to just under an hour. Another approach describing how bioluminescence can be used for detection of specific bacteria was first suggested by Ulitzur and Kuhn (1987, 1989). They put the genes encoding a bacterial luciferase (lux genes) into phages specific for E. coli. The phages are not able to express the genes, so they remain dark. However, when the phage infects the host cell, the luciferase is synthesized and the E. coli cells light up and can be detected with a luminometer. This is represented schematically in Fig. 8.4. Bioluminescent reporter bacteriophages were constructed for detection of Enterobactereaceae (Kodicara et al., 1991), Listeria monocytogenes (Loessner et al., 1996, 1997), Salmonella (Stewart and Williams, 1992; Turpin et al., 1993; Chen and Griffiths 1996), and Mycobacterium tuberculosis (Riska et al., 1997). Bioluminescent phage-based methods for enumeration of pathogens were tested for detection of Salmonella in eggs (Chen and Griffiths, 1996) and environmental samples such as water, soil and sewage sludge (Turpin et al., 1993). Pre-incubation for a short period of time (6 h) resulted in a reliable detection of as low as 10 cfu of Salmonella per ml of original sample. The system allowed Salmonella cells to be detected in artificially contaminated whole eggs. After incubation for 24 h, eggs inoculated with 102–103 cfu per egg became luminescent (Fig. 8.5) (Chen and Griffiths, 1996). A phage-based bioluminescent test for Listeria identified viable pathogen cells in ricotta cheese, chocolate pudding and cabbage at a level of less then one cell per g of food after a 20 h pre-incubation (Loessner et al., 1996). In foods having a large and complex microbial background flora, such as minced meat and soft cheese, at least ten Listeria cells per g of product were necessary to produce a positive bioluminescent signal. An additional advantage of recombinant phage technology for pathogen detection is that it can be performed under field conditions using a simple photographic film-based device for light detection (Riska et al., 1999). In the earlier publications mentioned above, insertion of lux genes into the phage genome was performed by transposition using a transposon with a selectable marker such as antibiotic resistance. This method is rapid but rather hit or miss. If the phage lacks non-essential genes or packaging limits of the phage head are very strict, then the addition of several kilobases may lead to the loss of its viability. In this situation it is preferable to gain some knowledge of the molecular structure of the phage to allow non-essential sites to be identified for cloning the reporter genes into the phage DNA. Kuhn et al. (2002a) cloned and sequenced part of genome of Felix 01 phage that is considered the best

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Fig. 8.4

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Schematic presentation of bacteriophage-based bioluminescent method for bacteria detection.

choice with regard to Salmonella due to its ability to lyse almost all Salmonella strains. This information was used by the same authors (Kuhn et al., 2002b) while developing recombinant phage reagent for Salmonella. A non-essential gene discovered earlier allowed substitution of foreign DNA in a way that neither increased the size of the phage genome nor allowed loss of the insert by recombination. Some concerns have arisen recently regarding the possible ‘release’ of recombinant bacteriophages in nature. A way to avoid possible dispersal of recombinant phages was proposed by Kuhn et al. (2002b).

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Fig. 8.5 Bioluminescent image of the egg inoculated with 103 cfu of Salmonella sp and incubated at 37ºC for 24 h. Recombinant phage was added to the egg and bioluminescence was monitored using BIQ Image Quantifier 30 min after infection.

Simultaneously with insertion of lux genes one of the essential phage genes responsible for phage particle assembly was removed from its genome. This did not prevent the expression of bioluminescent proteins upon infection of target bacteria, but at the same time the phage cannot multiplicate. To propagate such bacteriophage only specially constructed host bacteria strains carrying complementary plasmid with the missing essential gene should be used.

8.7

Instrumentation

Three main groups of instruments capable of measuring low level luminescence are available on the market – tube luminometers, luminescent plate readers and

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Table 8.1 ATP bioluminescent reagent/instrument systems available for use as hygiene monitors and microbial contamination control in food industry Type of system

Manufacturer

Trade name and system description

Bioluminometers and selfcontained swab kits

Biotrace Inc. (www.biotrace.com)

Clean-TraceÕ – surface hygiene test and Aqua_TraceÕ – water hygiene test with luminometers Uni-LiteÕ or Uni-LiteÕXCEL Celsis-Lumac SystemSURE with Advance luminometer PocketSwabÕ – surface hygiene kit with luminometers LUM-T or Firefly IDEXX LightningÕ

Celsis (www.celsis.com) Charm Sciences (www.charm.com) Biocontrol Systems Inc. (www.rapidmethods.com) CCD camera and filtering Millipore Corporation system with bioluminescent (www.millipore.com) reagent kit Swab-based system for hygiene monitoring

Promega Corporation (www.promega.com)

MicroStarTM System for detection of microbial contamination in filterable samples ENLITENÕ total ATP Rapid Biocontamination Detection Kit (could be used with most commercial luminometers)

imaging devices. The latter are able to measure luminescence in tubes, multiwell plates or from an object of irregular shape and size such as Petri dishes, blotting membranes etc. (Berthold et al., 2000). The application determines the choice of a suitable instrument. Detailed surveys of commercially available instruments for bioluminescent detection are published on a regular basis by Stanley (1999, 2000). Tube luminometers are designed to measure luminescence intensity in single tubes using mostly photomultiplier tubes (PMT) as light detectors. There are multipurpose tube luminometers that can accommodate a wide range of sample formats. Another group of tube luminometers is designed specifically for certain experimental protocols and can be used only with tubes and reagents designated for the instrument. Such portable, battery-driven luminometers have been developed for industrial microbiology applications. Examples of reagent/instrument systems for hygiene monitoring are presented in Table 8.1. Because of the popularity of microplates, automatic plate luminometers have found a considerable market for high throughput bioluminescent analysis. Measuring luminescence from microplates presents some unique design challenges, especially in performance parameters of the plate such as so-called cross-talk between the wells (Berthold et al., 2000). Because of the close

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proximity of neighbouring sample wells, the light transmitted from adjoining wells may add to the background signal. To reduce this cross-talk, white microplates with clear bottoms are considered the better choice. These plates show cross-talk values up to three orders of magnitude less than completely clear ones; in addition the efficiency of light detection is increased due to higher reflection from the white walls of the well. Black microplates exhibit the least cross-talk values (10 times lower than for white plates). However, they have low efficiency due to absorption of light by the black walls and are recommended only for samples with high luminescence intensity. For particular applications, besides the luminescence intensity, information about spatial resolution is required. For this purpose semiconductor array detectors are used. Charge-coupled device (CCD) cameras dominate the market as imaging detectors. The most important technologies used for luminescent imaging are slow-scan cooled CCD cameras, intensified CCD cameras and video cameras with intensifier (Berthold et al., 2000). The benefits of cooled slow-scan CCDs are high image quality, sensitivity and broad dynamic range. However, they cannot operate at video rate, e.g. a chip of 512 512 pixels can be read out within about 5 s. Intensified CCD cameras operate at higher readout rates and are used in cases when fast image acquisition is necessary. In highquality, commercial imaging systems, the software controls image acquisition, correction and processing, thus providing an opportunity for quantitative analysis. Raw data in all types of luminometers are presented in relative light units (RLU). RLU is not a scientifically defined unit but rather a measure of relative light output from a sample. To compare readings for the same sample on different luminometers each instrument has to be calibrated individually using a known analyte concentration or specially calibrated light sources (O’Kane and Lee, 2000).

8.8

References

AYTAC S A , MERCANOGLU B,

and OZBAS ZY (2001), ‘Enumeration of Escherichia coli O157:H7 by using immunomagnetic separation and ATP bioluminescence in buffer solution’, Archiv fu¨r Lebensmittelhygiene 52, 113–14. BAUTISTA D A, MCINTYRE L, LALEYE L, and GRIFFITHS M W (1992), ‘The application of ATP bioluminescence for the assessment of milk quality and factory hygiene’, J. Rapid 091 Methods Automat. Microbiol. 1, 179–93. BAUTISTA D A, CLARKE R, VAILLANCOURT J P, RENWICK S, and GRIFFITHS M W (1994), ‘Adenosine triphosphate bioluminescence as a method to determine microbial levels in scald and chill tanks at a poultry abattoir’, Poultry Sci. 73, 1673–78. BAUTISTA D A, JERICHO K W F, and GRIFFITHS M W (1995a), ‘Evaluation of adenosine triphosphate (ATP) bioluminescence for estimating bacteria on surfaces of beef carcasses’, in Beef Research Update, 1994, ed. J Buchanan-Smith, University of Guelph, Guelph, Ont., Canada, pp. 54–7. BAUTISTA D A, VAILLANCOURT J-P, CLARKE R, RENWICK S, and GRIFFITHS M W (1995b), ‘The

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9 Microscopy techniques: DEFT and flow cytometry R. Raybourne and M. Tortorello, US Food and Drug Administration

9.1

Introduction

The food microbiologist has two questions when considering pathogen contamination of foods: is the pathogen present? and, if it is present, how much is there? There are many more methods for answering the first question than the second one. The reason is clear. Detection (is the pathogen present?) is often all that is needed in practice, because in most cases, the mere presence of the pathogen in a food is sufficient cause for concern and reason for action. Most of the rapid assay kits that have been commercialized for pathogen analysis in foods are detection methods, and the options available are many and varied. However, accurate enumeration (how much is there?) is needed for a variety of determinations: growth and survival of pathogens, their incidence in foods, human exposure levels and the efficiency of control methods. These quantitative determinations can also contribute to the development of accurate risk assessments for pathogens in foods. For enumeration, the technical options available to the food microbiologist are quite limited. This chapter will focus on two specific approaches for the microscopic detection and enumeration of foodborne microbial pathogens: microscopic methods including the direct epifluorescent filter technique known as DEFT and flow cytometry (FC). These techniques share in common a utilization of optical technology, combined with specific or non-specific staining of the organisms in question with fluorescent dyes. There are numerous differences between the two methods, however, and each possesses unique strengths and weaknesses. DEFT recalls the basic foundation of microbiology in that it relies on the direct microscopic observation of organisms. FC is a technique that combines optical, fluidic and electronic technologies for the detection and characterization of

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single cells or other small particles. Some flow cytometers are also capable of sorting, or physically isolating cells or particles with definable characteristics. FC technology was a commercially available technology by the 1970s (Hulett et al., 1969; Van Dilla et al., 1969) and evolved rapidly with the primary emphasis on lymphoid cell analysis. Microbiological analysis has developed more slowly. Although the potential use of FC in microbiology was recognized relatively early (Bailey et al., 1977), the technology has been slow to be adapted or widely accepted by many microbiologists. As is the case with most technologies, widespread adaptation depends on the development of at least one indispensable method uniquely dependent on the technique. It is debatable whether or not FC is a true microscopic technique because enhancement of the apparent size of the organism and direct observation by the human eye are not necessarily involved in this technique. FC shares with DEFT the use of optics and fluorescent dyes to distinguish microorganisms. Both methods also offer the promise of direct detection and enumeration of foodborne pathogens. The aspect of direct detection is especially significant in that organisms need not be cultured in order to be enumerated, as is the case with traditional microbial colony counting. This not only eliminates the need for incubation of agar plates, thus contributing to rapidity of the methods, but also allows for detection of organisms that cannot be cultured such as stressed bacteria or protozoan pathogens such as Cryptosporidium spp. In order to detect specific pathogenic species or strains, both methods are dependent on the availability of high-quality antibody or nucleic acid probes. Analysis of samples by both methods requires adequate sample preparation that ensures the removal of potentially interfering particulates. The problems encountered in trying to analyze foods for the presence of pathogens are well known. The pathogen usually exists in much smaller numbers than the indigenous microbial populations in the food, which makes detection difficult. Also, the complex food matrix is likely to interfere with detection. Most pathogen detection methods include a procedure to alleviate these problems, the most common being enrichment culture. Enrichment culture provides conditions that allow the pathogen to increase in number while inhibiting the growth of indigenous microorganisms. The food sample is added to an enrichment medium and incubated to provide optimal growth conditions for the pathogen. Enrichment culture, followed by colony isolation and identification on selective and differential agar media, has been the standard method for detection of pathogens in foods for many years. Commercial rapid assay kits generally include enrichment as a first step, which compromises the speed of the assay. Nevertheless, the ability to proceed directly from enrichment culture to detection result via a rapid assay, thereby circumventing lengthy colony isolation/identification procedures, greatly improves the speed of analysis. Enrichment, however, destroys the ability to enumerate the pathogen in the food, except when it is used in the most probable number procedure, a lengthy, tedious and laborious method for determining pathogen counts in foods

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DEFT and other true microscopic methods are primarily manual and can be tedious. A skilled observer is also required. These factors offer both pros and cons: they tend to limit the number of samples that can be analyzed, however, few automated methods can equal the discriminating power of the trained eye. FC, as an automated technique, offers advantages in the area of speed, and potential automation of the process, thereby increasing sample throughput. Flow cytometers can analyze in excess of 1000 particles, or events, per second. Events can be tabulated at the time of analysis, or can be stored as archival data. FC data is also quantitative, involving the analysis of many thousands of individual particles, not possible manually. Problems can arise in relation to signal versus noise when attempting to detect rare cells amidst a high number of background cells or particles. This problem may be better addressed by direct observation of the cells (or bacteria) of interest by a trained observer. Because of the strengths of both methods, it is not surprising that some hybrid methods have been developed more recently. These methods combine the quantitative data collection and analysis features of FC with the slide or filter-based microscopic approach (Darzynkiewicz et al., 1999). The capability to visually observe cells of interest may also be a feature of these instruments.

9.2

Stains, fluorochromes and probes

Most microbial cells require some type of staining to provide sufficient contrast for visualization of the cells against the background medium. Some exceptions include pigmented microorganisms, e.g. the toxigenic dinoflagellates, and the pathogenic protozoan Cyclospora, which produces naturally autofluorescent oocysts. A huge variety of staining procedures have been described over the years.

9.2.1 Conventional stains Categories of conventional stains include direct stains, differential stains and structural stains (Bier et al., 2001). Direct staining is useful for broadly classifying microbial groups (bacteria, yeasts, molds, protozoa) and for morphological descriptions (rods, cocci, spirals, hyphal segmentation). Identifications of certain molds can be made solely on the basis of morphologies of their spore-forming structures. Differential staining procedures allow distinctions between groups of microorganisms based on a particular property. In Gram staining, perhaps the most commonly used differential stain, bacteria may be broadly grouped as Gram positive or Gram negative, based on their reaction to the four-step staining procedure, a consequence of fundamental differences in cell wall structure. Structural staining procedures highlight a particular structure of the microbial cell, e.g. endospores, flagella, inclusion granules, and are helpful for identification purposes.


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9.2.2 Fluorochromes Some procedures such as DEFT and FC may require the use of fluorescent dyes to distinguish cells of interest (bacteria or protozoa) from other particulates. These fluorochromes can be used in two ways: by taking advantage of their chemical properties to interact directly with cellular targets such as DNA, RNA, lipids or proteins, or by using them as labels for molecular probes such as antibodies or oligonucleotides. All of the fluorochromes share the common characteristic of the ability to absorb and emit specific wavelengths of light. A detailed discussion of the physics of absorption and emission of light energy from fluorescent compounds is beyond the scope of this chapter. Briefly, fluorochromes absorb energy in the form of light, resulting in an excited state in which electrons are shifted to a higher energy level. This state is unstable and the electrons eventually return to their unexcited state. In this process, energy is released in the form of emitted light. Based on its molecular structure, each fluorochrome has unique light absorption and emission properties. Common to all, however, is the property that the energy released when electrons return to their ground state is at a lower level than the energy absorbed. The practical effect is that the light wavelength used to excite a fluorochrome is always shorter (higher energy) than the wavelength of the emitted light (lower energy). The difference between the two wavelengths is known as the Stokes shift, and is characteristic for each fluorochrome. These properties occur in the form of spectra with specific absorption and emission wavelength maxima for each. The broadness of the spectra and the magnitude of the Stokes shift can differ greatly between fluorochromes with important implications for their usefulness as probes or labels. There is important interplay between the properties of fluorochromes and instrumentation. The characteristics of available fluorochromes often dictate the configuration of the instrumentation used in measurements. This is particularly true in the case of flow cytometers because the source of excitation is usually a laser. Unlike the illumination lamps of most fluorescent microscopes that emit a broad range of potential excitation wavelengths, lasers are typically limited to one or two wavelengths or laser lines of emission. The most common laser source, the argon laser, was originally chosen for use in early flow cytometers because its 488 nm emission was close to the absorption maximum of Fluorescein, a fluorochrome that was (and still is) widely used for labeling antibodies. The widespread use of the argon laser has, on the other hand, spawned the discovery and development of a number of fluorochromes with absorption spectra compatible with the 488 nm emission, but with distinct emission peaks that can be separated optically. This has led to the important capability of simultaneous analysis of multiple fluorochromes using a single excitation wavelength. Were it not for the early and widespread adaptation of the argon laser in flow cytometry, it is likely that none of these developments would have occurred because they would be unnecessary for fluorescence microscopy where mercury or xenon lamps can produce multiple excitation wavelengths. Thus, there are some fluorochromes, such as rhodamine, and some dyes that excite in the ultraviolet range that are used

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almost exclusively in microscopy methods and rarely in FC. Fluorochromes are used either as direct probes for cellular components, or as reporters for the binding of some type of molecular probe. Examples of the former include nucleic acid binding dyes and viability stains. In many cases, nucleic acid binding dyes can function as viability stains. Comprehensive lists of fluorochromes, their spectral properties and uses can be found in most general references (Givan, 2001a; Haugland, 1996; Robinson, 1998).

9.2.3 Viability stains The traditional determinant of microbial cell viability is colony formation. Not all viable cells can be grown in culture, however. Of practical consideration to food microbiologists are sublethally injured cells, which may not be able to grow on selective agar media (Ray, 1979). Microscopic methods may be used as an alternative tool for demonstrating cell viability. Various viability stains, based on different aspects of the nature of cellular viability, have been described and reviewed (Roszak and Colwell, 1987; McFeters et al., 1995; Porter et al., 1995; Haugland, 1996; Breeuwer and Abee, 2000; Takeuchi and Frank, 2001a). Acridine orange is a fluorescent dye which has an affinity for nucleic acids. Binding to single-stranded RNA or double-stranded DNA results in red-orange or green fluorescence, respectively, and this differential binding was the basis for its use as a viability stain (Hobbie et al., 1977; McFeters et al., 1995). However, the color differentiation was found to depend on the medium in which the cells were suspended, and did not always display predictably in cells exposed to various processing treatments; thus the stain is no longer regarded as a reliable indicator of viability (Kepner and Pratt, 1994). It is, however, commonly used in DEFT for quantification of the total microbial population in a food sample. Redox probes constitute another category of viability indicators, based on the presence of a functioning electron transport system (Haugland, 1996). Redox probes accept electrons from the electron transport system components in respiring cells and accumulate within the cell as insoluble chromogens or fluorescent derivatives. Fluorescent antibody staining has been coupled with the redox probe CTC (cyanoditolyl tetrazolium chloride) to specifically count viable cells of E. coli O157:H7 (Pyle et al., 1995). Many viability stains are based on cell membrane integrity (Haugland, 1996). Exclusion of certain dyes by an intact membrane is an indication of viability, while permeation of the dye shows that the membrane has been damaged and the cell is not viable. For example, staining of cells by the fluorescent dye propidium iodide has been used to show their nonviable state. Staining of cells by fluorescein diacetate is based on two properties related to cell viability: enzyme activity and membrane integrity. This nonpolar, nonfluorescent compound can diffuse across an intact membrane. However, when esterase enzymes cleave the compound, the fluorescein released cannot pass the membrane and accumulates within the cell as a fluorescent indicator of viability.


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Other nucleic acid binding dyes such as the SYTO series (Molecular Probes) and thiazol orange are permeant to intact cell membranes. Nucleic acid binding dyes in association with their viability indicator properties have been employed extensively in microbial methods of FC. The exploitation of these properties for analytical purposes will be discussed as they apply to specific methods.

9.2.4 Molecular probes Fluorochromes are used as labels primarily for antibody or oligonucleotide probes. Unlike conventional stains, which have little discriminating power, molecular probes allow for specific identifications to be made by microscopy or FC. Microbial cells may be distinguished at various taxonomic levels, e.g. genus, species, strain, depending on the specificity of the probe. An antibody binds to an antigen specifically, through non-covalent molecular interactions as a result of conformational features in protein structure, in a way similar to the interaction between an enzyme and its substrate. This specificity allows antibodies to be used as probes for the presence of a particular antigen, e.g. a unique microbial cell component. Antibody-based immunofluorescence methods involve some form of stable chemical coupling of the fluorochrome to antibody molecules directed against a cellular or bacterial target protein. Fluorescent antibody staining is the basis of an official method for detection of Salmonella in foods (AOAC International, 1997b). Oligonucleotides are short polymers of nucleotides, the structural components of DNA and RNA. These short nucleotide chains can bind to specific nucleic acid sequences by complementary base pairing (adenine:thymine and cytosine:guanine), which involves formation of hydrogen bonds between the bases. Like antibodies, oligonucleotides may be labeled with a fluorochrome, and as such, can function as fluorescent probes for specific nucleic acid sequences. Oligonucleotides are less expensive and easier to produce than antibodies, because they can be synthesized chemically. Identification of the molecular target for the probe that uniquely belongs to a particular microbial group (genus, species, strain, etc.) is the first consideration in designing the probe. Also to be considered is the relative abundance of the target in the cell. Antigens are usually present in the microbial cell in amounts sufficient for direct detection by microscopy; however biosynthesis of some antigens may be environmentally regulated, and they may not be expressed at all times by the cell. Nucleic acid sequences, on the other hand, are usually always present regardless of environmental conditions, but in amounts too low for direct microscopic detection. A notable exception is the relatively abundant level of ribosomal RNA present in actively growing cells. Fluorescent oligonucleotides specific for ribosomal RNA sequences have been applied as ‘phylogenetic stains’ for detection and identification of groups of microorganisms (DeLong et al., 1989). Their use for detection and tracking of microbial populations by fluorescence in situ hybridization (FISH) has been demonstrated for a variety of natural samples, from drinking water to intestinal tissue (Manz et al., 1993;

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Poulsen et al., 1994). Methods have also been developed for use of fluorescent oligonucleotide probes in FC analysis of microorganisms (Amann et al., 1990; Fuchs et al., 1998; Porter and Pickup, 2000). In the area of flow cytometric methods applied to microbial pathogens in food, few, if any, such methods have been developed. Fluorescent antibodies are easy to use, involving a simple process of adding them to a suspension of microbial cells, allowing them to react for a few minutes, then washing away the excess, unbound fluorescent antibodies before microscopic observation. The antibody probes are generally directed against some type of cell surface component and can bind immediately, therefore no preliminary treatment of the cells is required. The antibody-antigen reaction occurs at the cell surface. Use of oligonucleotide probes, on the other hand, usually requires some type of pre-treatment of the cells to allow the probe to pass across the cell wall to reach the nucleic acid component. In addition, heating and chemical treatment steps are necessary for hybridization of the oligonucleotide to the target nucleic acid sequence. Gene sequences for proteins that fluoresce or luminesce can be spliced into the genome of a microorganism by recombinant DNA techniques or incorporated into the cell as a plasmid component. Unlike fluorescent antibodies or oligonucleotides, these molecular markers are not used to detect or identify naturally occurring microbial cells. Rather, they are helpful for determining microbial growth and survival, after inoculation of the marked strain into a food. Firefly luciferase and green fluorescent protein are two light-emitting markers that have been used commonly (Fratamico et al., 1997). The commercial availability of the gene sequences for these markers has contributed to the popularity of these types of studies. For example, strains marked with the green fluorescent protein have been used to study survival of Salmonella (Gandhi et al., 2001) and E. coli O157:H7 (Takeuchi and Frank, 2001b) in produce, and bioluminescent strains have been used to study sublethal injury in Salmonella (Ellison et al., 1991; Chen and Griffiths, 1996) and penetration of Campylobacter into egg shells (Allen and Griffiths, 2001).

9.3

Microscopy

Microscopy is a powerful tool for analysis of microbial populations, because it allows us to see things at the microbial level, below the detection limit of the human eye, in a direct way that cannot be matched by other techniques. Two essential features of the microscope are its magnification and resolving power, which are inherent properties of its optical lens system. Magnification is the ability to make objects appear larger than they are. Resolving power is the ability to distinguish two closely-placed objects as distinct and separate. As the magnifying power of a lens system increases, resolving power generally decreases. The usefulness of a microscope obviously depends on the quality of the lens system with regard to both magnification and resolving power.


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For food microbiological analysis, microscopy offers advantages, but also has disadvantages in comparison to other analytical methods. As a direct method of analysis, microscopy is difficult to match for its speed of detection; however, the food matrix is a major interfering factor. Because such a small sample size is analyzed in microscopy, its sensitivity is often less than that of other methods. However, microscopy may be combined with separation/concentration techniques to relieve food matrix interferences and to improve the sensitivity of detection. Specificity can be a problem, because microbial cells generally cannot be differentiated microscopically. However, staining techniques that employ molecular probes, such as antibodies and oligonucleotides, may be used specifically to identify microorganisms in the sample. Microscopy provides one of the best technical options available for rapid enumeration of microorganisms. The other standard methods of enumeration, viable counts in agar media and the most probable number procedure, are more sensitive than microscopy but require one to several days to complete. Microscopic enumeration, by comparison, can be completed within an hour. The speed of analysis not only makes microscopy useful for research studies but also for practical applications in food analysis. Often microscopy is used for identification procedures, after enrichment culture and isolation of the microorganism from the food. In these applications, direct analysis of the food is not a goal. Furthermore, microbial enumeration cannot be performed because the microbial population has been allowed, via enrichment culture, to increase in number beyond its original level. Nevertheless, such uses of microscopy provide unique capabilities, and, in many cases, may help to shorten the time required to identify the microorganism. In summary, microscopy is a versatile technology, capable of allowing both rapid detection and enumeration of microorganisms in foods, or when used in identification procedures, improving the time of analysis. A number of procedures for the microbiological analysis of foods involve microscopy in various forms.

9.3.1 Bright field microscopy Bright field microscopy is readily available in food testing laboratories and is useful for microbial identification procedures, such as Gram staining, endospore visualization, and fungal morphology characterization. Certain quantitative procedures also employ bright field microscopy. In the Howard Mold Count, for example, product quality determinations are based on the number of mold fragments in a sample deposited onto a special type of slide (AOAC International, 1997c). In milk grading, microbial counts are obtained from microscopic examination of the milk prepared as a stained, dried film on a microscope slide (Packard et al., 1992). Bright field techniques usually involve fixation and staining of the sample, to provide sufficient contrast or visualization of the microbial cell against the background.

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9.3.2 Fluorescence microscopy Fluorescence involves the excitation of a substance (i.e. the fluorochrome) by exposure to short wavelength light, causing emission of longer wavelength light by the fluorochrome. In fluorescence microscopy, various types of fluorochromes may be used as stains for visualization of microbial cells. The excitation and emission wavelengths are controlled and separated by appropriate filters positioned within the microscope. The design of a fluorescence microscope is based on either of two types of illumination, that is, transmitted or incident light. For food microbiological analysis, the most practical and widely used is the epifluorescence microscope, which features illumination of the sample by incident light (Fig. 9.1). There are two primary advantages afforded by epifluorescence or incident light illumination. First, it yields superior performance at the high magnifications needed for microbial cells. Second, because the light originates from above the sample, causing illumination from the sample surface, epifluorescence provides the ability to analyze the thick or opaque specimens that transmission fluorescence microscopy does not allow. The direct epifluorescent filter technique (DEFT, discussed below) takes advantage of these features of the epifluorescence microscope and is one of the most rapid methods known for enumerating microbial cells. The incorporation of molecular probes in the DEFT increases its utility, to allow rapid enumeration of specific microorganisms.

9.3.3 Confocal laser scanning microscopy The capacity of the epifluorescence microscope for analysis of thick specimens, such as foods, is limited. In epifluorescence, the incident light illuminates the entire thickness of the specimen, causing out-of-focus fluorescent emissions to reach the eye and blur the image. In confocal laser scanning microscopy (CLSM), these out-of-focus emissions are removed, thus allowing sharp, highcontrast imaging of objects deep within a structure. The specimen is illuminated by rastering an intense beam of light across the plane of focus. A computer collects and stores the data, and when several focal planes are analyzed, highcontrast three-dimensional images may be created. Thus, CLSM allows analysis of thick specimens that would require sectioning and staining in other microscopic techniques. It provides the capability to study pathogens in situ in foods, without fixation or other sample preparation procedures that might give rise to artifacts. Biofilm work has been particularly advanced by CLSM. However, the cost and complex instrumentation of CLSM make it primarily a research technology, and not generally applicable for routine use in detection or enumeration of microorganisms in foods. For a review of CLSM applications in food microbiology, see Takeuchi and Frank (2001a).

9.3.4 Electron microscopy Like CLSM, electron microscopy is basically a research tool, and not useful for routine analysis of microorganisms in foods. Two types of electron microscopy,


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Fig. 9.1 Components of the epifluorescence microscope. In epifluorescence microscopy, light from (A) is passed through an excitation filter (B) which directs selected wavelengths to a dichroic mirror (C; also known as a dichromatic beam splitter), placed at a 45º angle to the vertical axis of the microscope. The dichroic mirror reflects (shorter) excitation wavelenghts and transmits (longer) fluorescence wavelengths. The reflected light from C is focused onto the specimen through the objective lens (D), which collects the fluorescent emissions for transmission back up to the eyepiece through C and the barrier filter (E). Only the fluorescent wavelengths of the fluorochrome in use are transmitted to the eyepiece. A filter set (B, C, E) is usually assembled for use with a particular fluorochrome and may be exchanged for another set within the microscope housing when use of a different fluorochrome is desired.

transmission (TEM) and scanning (SEM), have been of use in microbiological research. TEM has tremendous magnification and resolving power, and with detection limits in the nanometer range, it can provide details of subcellular structures of microorganisms. Although artifacts may be generated as a result of extensive sample preparation procedures required in sectioning and staining of the specimen, it has been a workhorse for studies of microbial cell ultrastructure. The mechanisms of cell inactivation of food processing treatments have been investigated using TEM (Calderon-Miranda et al., 1999; Dutreux et al., 2000). In SEM, the specimen is coated with a thin film of a heavy metal, and a beam of

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electrons is scanned across it. The technique gives a three-dimensional image of the surface of the specimen and has been useful for studies of microorganisms in their natural environments, for example attachment of pathogens to foods and equipment surfaces (Fett, 2000; Woody et al., 2000; Han et al., 2000; Lindsay and von Holy, 1999).

9.3.5 Microscopic enumeration of microorganisms One of the most powerful applications of the microscope in food microbiology is its potential for counting microorganisms directly and rapidly. In fact, the examination of a food film dried onto a microscope slide is among the oldest techniques described in food microbiology. Originally developed and used for the grading of milk (Breed, 1911; Packard et al., 1992), microscopic enumeration of microorganisms in thin films has also been applied to other foods (Bryce and Poelma, 1995; AOAC International, 1997a). A known quantity of the sample is applied to the slide, and the number of microbial cells counted per microscope field is converted into numbers per gram based on the area of the field, as described below. The microscope slide used for dried film analysis has a 1 cm2 circular area imprinted on it, which is used to contain the sample in a defined area. A 0.01 ml quantity of the sample is spread within the circle, dried, fixed and stained. The number of microbial cells is counted in 10–100 fields, and the average count per field is calculated. To obtain the concentration of cells in the food, the Microscope Factor (MF), which is unique for every lens, must be determined. The MF is the number of microscope fields in the 1 cm2 slide area, divided by the quantity of sample (0.01 ml) applied. The formula for the area of a circle (r2 ) is used to determine the area of the microscope field for a particular lens; r is determined by measuring the field diameter using a stage micrometer and dividing by two. The MF is obtained by dividing the slide sample area (1 cm2) by the field area to obtain the number of microscope fields in the slide area; and then dividing this quantity by 0.01 ml. Finally, the concentration of microorganisms in the food is calculated by multiplying the average count per field by the MF.

9.4

The direct epifluorescent filter technique (DEFT)

The dried film technique can be used for enumeration only when microbial cell densities are quite large, because of the small sample size examined. Greater sensitivity (i.e. lower detection limit) can be achieved by including a sample concentration step, as in the direct epifluorescent filter technique (DEFT). In the DEFT, membrane filtration of the sample improves sensitivity by several orders of magnitude. When the sample is passed through the filter, the microbial cells are concentrated and collected on the filter, which provides the surface on which the microscopic analysis is performed. Incident light illumination (epifluorescence) is used to examine the filter surface.


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The DEFT had its origins in microbiological studies of natural aquatic systems (Collins, 1957; Francisco et al., 1973). Well-acquainted with the failings of conventional culture media to recover microorganisms from environmental samples, microbial ecologists looked to microscopy for direct analysis of the systems under study. Use of the acridine orange stain, with its affinity for nucleic acids, allowed microscopists to distinguish biological (i.e. cellular) matter from detritus. Considering all things that might be present and visible in a microscopic sample, this was a significant technological advance. For sample concentration, black membrane filters were used, which provided contrast between the fluorescent cells and background. Later, the development of polycarbonate membranes of uniform pore size provided improved microbial counts compared to cellulosic filters, due to greater capture of cells on the filter surface, as opposed to within the depths of the filter. Food microbiologists explored the method’s use originally for counting microorganisms in milk, as a more sensitive alternative to the dried film method (Cousins et al., 1979; Pettipher et al., 1980). To effect filtration through the 0.6 m pore filter, the milk was pre-treated with protease, surfactant and mild heat. Homogenized foods, including meat, fish, vegetables, and spices, were next, and the term ‘direct epifluorescent filter technique’, or DEFT, was coined (Pettipher and Rodrigues, 1982a). For these samples, a preliminary step of prefiltration through a 5 m pore nylon filter was added to the procedure to facilitate passage of the food through the analytical filter. A digital camera attached to the microscope with linkage to an image analysis system showed the potential to automate the technique (Pettipher and Rodrigues, 1982b). The speed of the DEFT for direct enumeration of microorganisms was unmatched, and it compared favorably with other techniques with respect to sensitivity and precision (Pettipher, 1986). Evaluations were performed to support its use as a standard method for the microbiological analysis of meats (Ovist and Jakobsen, 1985; Shaw et al., 1987; Boisen et al., 1992). The following procedure has been recommended for the microbiological analysis of raw milk by the DEFT (Pettipher et al., 1980; Bier et al., 2001). All reagents, buffers and solutions for use in the DEFT must be passed through 0.22 m pore sterilization filters to remove contaminating microorganisms that would be visible microscopically and influence counting results. The milk sample (2 ml) is mixed together with 0.5 ml trypsin and 2 ml Triton X-100 (each at 0.5% w/v), and incubated at 50ºC for 10 min. The somatic cells and lipid micelles in the milk are lysed by this procedure, facilitating filtration. The lysed mixture is then added to a previously warmed filter assembly holding a 25 mm diameter, 0.6 m pore black polycarbonate membrane filter (shiny side up). A vacuum is applied to the filter assembly, which is then rinsed with 5 ml Triton X-100 (0.1% w/v). The vacuum is disconnected, and the membrane filter is overlayed with 2 ml acridine orange stain (available commercially, or prepared as a 0.025% w/v solution in 0.1 M citrate-NaOH buffer, pH 6.6). After staining for 2 min, the membrane filter is rinsed under vacuum with 2.5 ml 0.1 M citrateNaOH buffer, pH 3, followed by 2.5 ml 95% ethyl alcohol. The membrane filter

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is air-dried, then mounted on a glass microscope slide in a drop of nonfluorescent immersion oil. Finally, a cover slip is applied for examination of the membrane filter by epifluorescence microscopy, using a 450–490 nm wide-bandpass filter appropriate for acridine orange fluorescence. It is best to choose the microscope objective lens that provides the widest field of view for scanning the filter for the presence of fluorescent cells. For detecting and counting bacteria, the 100X oil immersion lens, which is the lens with the smallest field of view, is generally necessary. However, other microorganisms, e.g. yeasts or protozoa, may be detectable using lower power lenses which provide larger fields of view. During a preliminary scan of the membrane, a rough estimate of the number of cells per field is made; if there are typically more than 100 cells per field, the sample should be diluted before counting is attempted. Fluorescent cells in randomly selected fields across the membrane filter are then counted. The number of fields that should be analyzed depends on the microbial cell density, recommended as follows: if there are 0–10 cells per field, 15 fields are analyzed; for 11–25 cells per field, 10 fields are analyzed; for 26–50 cells, 6 fields; for 51–75 cells, 3 fields; for 76–100 cells, 2 fields. Calculation of the number of cells per ml of milk is done as for the dried film procedure (above), by multiplying the average number of cells per field by the MF; however, in the DEFT the area of the membrane filter is factored (membrane filter microscope factor, MFMF). The MFMF is the area of the membrane filter divided by the area of the microscope field. The concentration of microbial cells in the sample is calculated by multiplying the average number of cells per field by the MFMF, then dividing by the volume of material filtered. Any dilution of the original sample should be factored into the calculation. Adaptations of the DEFT have been made to extend its functionality. Determination of viable cells has been performed by incubation of the membrane filters for several hours on agar media after sample filtration, followed by staining and examination of the microcolonies formed by epifluorescence microscopy (Rodrigues and Kroll, 1988, 1989). The microcolony technique was further modified to include the use of fluorescent antibodies as staining reagents, allowing for specific identification of viable cells. The potential for rapid detection of viable cells of Salmonella (Rodrigues and Kroll, 1990) and Listeria (Sheridan et al., 1991) in raw meats was demonstrated by the microcolonyfluorescent antibody method. Fluorescent antibodies were also applied directly in the DEFT without microcolony formation, as an alternative to acridine orange staining, for rapid specific detection and enumeration of microorganisms. The antibody-direct epifluorescent filter technique (Ab-DEFT) allowed specific enumeration of E. coli O157:H7 in milk and juice samples within one hour (Tortorello and Gendel, 1993). The sensitivity of the Ab-DEFT for detection of E. coli O157:H7 in beef compared favorably with a conventional enrichment culture technique, and it was shown to be useful for measurement of growth of the pathogen in beef (Tortorello and Stewart, 1994). The Ab-DEFT was evaluated as an alternative to


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the most probable number method for enumeration of Listeria in vegetables (Tortorello et al., 1997). In a variation of fluorescence in situ hybridization (FISH), application of fluorescent oligonucleotides in the DEFT has been demonstrated, but their use has been reported more frequently by microbial ecologists than by food microbiologists. The usual target of oligonucleotide probing is ribosomal RNA, because its abundance in the cell allows for a fluorescent signal sufficiently large to be detectable by microscopic observation. Depending on the level of specificity, oligonucleotides complementary to ribosomal RNA sequences may function as group- or species-specific probes for microbial cells in a sample. Direct enumeration of E. coli in water, various beverages and vegetable sprouts was demonstrated by using a fluorescent oligonucleotide in the DEFT (Tortorello and Reineke, 2000). The detection limit of the DEFT is in the order of 103 cells/ml (Pettipher, 1986). Although the detection limit of the Ab-DEFT for E. coli O157:H7 in beef was reported as approximately 16 cfu/g, it was achieved by passing up to 100 ml of homogenate through the filter and by scanning hundreds of microscope fields (Tortorello and Stewart, 1994). In comparison to the recommended DEFT parameters for sample volume and number of fields analyzed (discussed above), the Ab-DEFT report represented a significantly greater effort. Furthermore, the excellent quality of the fluorescent antibody, which provided an intense fluorescent signal, was an important factor which contributed to the sensitivity of detection, for it allowed visualization of the fluorescent cells within a dense, complex background. These conditions may not be feasible or available for the routine application of the DEFT. Modifications to the DEFT have been explored to improve its sensitivity for pathogen detection. A short period of sample enrichment prior to the Ab-DEFT, for example, substantially reduced microscope scanning time by allowing cells to multiply to readily detectable levels, thereby improving sensitivity (Restaino et al., 1996). This modification resulted in a 10 h screening assay, which, although it no longer allowed enumeration, resulted in a detection limit (0.1 cfu/ g) comparable to that of standard cultural methods. The same report demonstrated the use of immunomagnetic separation (IMS) for confirmation of Ab-DEFT-positive samples within 24 h (Restaino et al., 1996). The ease and speed of the combined screening and confirmation protocol represented a substantial saving in time and effort for screening of beef for the presence of E. coli O157:H7. In comparison to other rapid methods (e.g., IMS-polymerase chain reaction and flow cytometry), the Ab-DEFT provided the quickest detection of E. coli O157:H7 in enrichments of apple juice inoculated at 0.1 cfu/ ml (Tortorello et al., 1998a).

9.5

Flow cytometry

Numerous excellent books and extensive review articles have been written on the technical aspects of FC including microbial analysis by FC (Davey and Kell,

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1996; Givan, 2001a; Shapiro, 2000; Steen, 2000). The following is intended as a brief overview for those unfamiliar with the technology of flow cytometry with particular emphasis on the problems associated with analysis of microbial organisms.

9.5.1 Basic principles and instrumentation This section will focus on FC as an off-the-shelf technology and not deal with custom, one of a kind instruments, or with proprietary instrumentation such as those designed specifically for the food industry. In a typical commercially available FC instrument, particles (cells, bacteria, nuclei, beads) move in an aqueous stream that intersects a focused, stable, high intensity beam of light, usually produced by a laser (Fig. 9.2). Some instruments may utilize two or more lasers. The primary laser is usually an argon laser, producing a 488 nm excitation beam. In order to achieve uniform light exposure of the cells, they must be stabilized at a uniform distance in relation to the focused excitation beam. This is accomplished by a laminar flow technique in which a narrow sample stream, or sample core, containing the cells or other particles is stabilized within a larger stream known as the sheath. By maintaining a precise pressure differential between the sample stream and the sheath, cells move through the laser beam in a single file line fixed at the focal point of the beam. This process is known as hydrodynamic focusing. Depending on the instrument, the intersection of laser and stream may occur in air (stream in air), within an optical quartz flow cell (stream in quartz), or on the surface of a cover slip (stream on surface). Each of these configurations offers certain strengths and

Fig. 9.2 Overview of signal and data pathways in flow cytometry. Scattered and emitted fluorescence light signals from cells passing the laser are converted to electronic pulses by PMTs. Pulses are converted to digital values, processed by the computer, and used to produce data displays. (Adapted from Becton Dickinson Immunocytometry Systems.)


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weaknesses to be discussed later. When the cells pass through the laser, the light that is scattered is collected by detectors configured to detect light at a low angle in the direction of the laser beam path (forward light scatter) or light that is emitted at approximately 90º to the beam path (side scatter, or 90º light scatter). Forward light scatter (FSC) is correlated roughly with cell size, while side scatter (SSC) correlates with internal structure such as granularity, or with surface roughness. This relationship between physical properties of cells, including microorganisms, and light scatter provides an additional determinant for characterizing cells, exclusive of fluorescent probes. FSC and SSC as well as light emitted by fluorescent probes bound to the cells are collected by a series of focusing lenses and distributed to detectors along an optical pathway that includes appropriate wavelength transmitting or blocking filters. This results in each detector being specific for one light signal or parameter. The detectors are photomultiplier tubes (PMTs) for SSC and fluorescence emissions, and usually a photodiode for FSC. Both types of detectors convert photons into an electrical current. The current from the PMTs are then passed through linear and/or logarithmic amplifiers. Linear amplification is useful for analyzing particles of similar size or fluorescence (such as beads), whereas logarithmic amplification is suited to analysis of particles that are more broadly distributed with respect to a particular parameter. In general, where a high level of discrimination may be needed, such as light scatter, linear amplification is used. The amplified pulses are then processed and converted from analog to a digital number, typically from 1–1000 mV. These numbers are then used to generate a variety of data plots (Fig. 9.2). It is necessary to be able to distinguish cells of interest from debris and electronic noise. In order to accomplish this, a threshold level is established for one of the signals. Typically, light scatter signals are used for this purpose, because all cells, even in a sample that may contain non-fluorescently labeled cells, will produce a scatter signal. If the signal from the cell or particle is above this level, then the instrument is triggered to collect all other signals derived from the same cell or particle. This is the basis of a most important aspect of FC: multi-parameter data is generated on individual cells. FS, SSC, and fluorescence data are stored in the computer as correlated data for each cell (listmode data). This allows for the generation of data plots based on single or multiple parameters. Plotting the data in this way gives rise to populations of cells based on the accumulated single cell data. These populations can be included within graphically represented regions that can function as regions and gates. Data regarding other parameters linked to the cells that fall within the gate can then be derived. Multiple gates can be used to further define cell populations. Data saved on the computer as listmode can be re-analyzed as necessary to generate new data plots and additional information. The same gates can also be used to define populations of cells for sorting if the cytometer has that capability. Sorted cells can then be subjected to further analysis.

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9.5.2 Flow cytometry of microorganisms If the world of FC is large, the world of FC of microorganisms is fairly small, but growing. Since its inception, the potential usefulness of FC for the study of microorganisms has been considered; however, microbiologists have been relatively slow to adopt the technology for the study of bacterial populations. Studies using FC instruments to analyze bacteria were first published in the late 1970s (Bailey et al., 1977). The clear advantage of FC for bacterial analysis lies in the ability to collect correlated data on single cells as described above and in other comprehensive articles (Davey and Kell, 1996; Shapiro, 2001). This capability represents a potential conceptual breakthrough from viewing bacterial populations as monolithic entities. Questions regarding variations in the antigenic, reproductive and physiologic state of individual cells in a large population can be addressed. Nevertheless, as pointed out by Harald Steen, one of the pioneers in the field of microbial analysis: ‘No one seemed to realize that they had hit a scientific goldmine . . . even now, the majority of bacteriologists are not aware of the possibilities that flow cytometry offers for acquiring knowledge about bacteria which is difficult, if not impossible, to obtain by other methods’ (Steen, 2000). The list of potential parameters that could be measured in microorganisms is lengthy (Shapiro, 2000). The reasons for this relatively underdeveloped state of knowledge may lie both in the fact that most microbiologists are unfamiliar with FC and that no area of information about bacterial populations has arisen from multiparameter FC that is considered to be unique and indispensable to microbiologists. In other words, there is no ‘killer application’ that makes FC universally essential to microbiologists. By way of analogy, the development of multiparameter lymphocyte phenotyping quickly made FC an integral part of almost every immunology and hospital clinical laboratory. A second handicap faced by microbiologists has been a lack of readily available reagents for specific identification of microorganisms. To extend the analogy with lymphocyte phenotyping, the widespread use of FC in immunology is both driven by and supports the development of a huge variety of commercially available FC reagents. This problem is particularly acute in the area of pathogen detection, where identification may depend on specific antibody or DNA probes. Within the past few years, some commercially available reagent kits for FC of bacteria have become available, such as the BacLightTM kit (Molecular Probes) for distinguishing live and dead bacteria (as in Raybourne, 1997). The most basic information on microbial analysis by FC comes from research on organisms grown in culture in the laboratory. Applied applications have focused in the areas of clinical, food and primarily environmental microbiology. Most of the information gained from analysis of bacteria in pure culture or the environment is also relevant to detection of microbial pathogens in foods. Indeed, there is a direct relationship between environmental microbiology and food especially in the area of pathogens that may be generally considered waterborne, but can also be transmitted due to exposure of food to contaminated water. Of special interest in this area are FC methods related to the protozoan


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Cryptosporidium spp. (Vesey et al., 1994; Valdez et al., 1997). While the list of foodborne microbial pathogens includes this and other protozoans, the focus here will be on bacteria. The basic FC principles outlined above apply generally to analysis of microorganisms such as bacteria. However, these organisms do present some special problems. One such problem is due to the relatively small size of bacteria. Most commercially available flow cytometers are designed for analysis of particles in the size range of eukaryotic cells, for example lymphocytes, which are roughly ten times the diameter (or 1000 times the volume) of most bacteria. This problem is most critical in the detection of FSC and SSC signals. In many commercial flow cytometers FSC of bacteria may be difficult to separate from noise. The noise may come from electronic, optical and particulate sources (Hoffman, 1997). The latter is due to small particulates in the sheath fluid or the sample medium and can be dealt with by careful filtration of the sheath and other solutions involved in the experiment. Electronic noise becomes a problem when increasing amounts of voltage and/or amplification are applied to the FSC and SSC detectors. Optical noise is detected when signals derived from the laser excitation source are present in the absence of sample particles. The optical and electronic problem is particularly acute with FSC, since many commercial instruments use a photodiode, which is less sensitive (but adequate for eukaryotic cells) as the FSC detector. As with any FC analysis, the objective is to achieve optimal separation between the signals of interest and the threshold, below which noise occurs. Because, as previously mentioned, FSC is commonly used as the threshold or triggering signal, lack of separation between signal and noise can result in spurious accumulation of noise in all other parameters. Some degree of FSC noise is always present due to dust, particulates, stray laser light, and even room light, usually making it necessary to maintain some threshold at all times. As an example, this might be a threshold level of 50 channels out of 1000. The FSC amplification necessary to resolve lymphocytes, for example, would result in almost no noise above the threshold of 50. As one attempts to resolve smaller and smaller particles, it becomes necessary to increase the degree of amplification of the FSC signal. Eventually this results in significant noise appearing above the threshold of 50. Of course, one could increase the threshold, but this strategy will only be successful if the signal of interest is not overlapping the threshold to a significant degree. Thus, analyzing bacteria using FSC as the threshold requires careful optimizing of signal to noise. Some factors that can help in this are careful optical alignment of the instrument, cleaning of optical filters and lenses and reduction of ambient light. Some cytometer optical configurations achieve better FSC resolution and sensitivity than others. Of the most widely distributed commercial instruments, those with stream in quartz configurations are superior to stream in air (Shapiro, 2001; Harkins, 1999). This is due to increased scattering of light from the sheath fluid when the laser interacts with the stream in air. Steen and colleagues (Steen, 2000) developed the stream on open surface configuration in which FSC is

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collected using microscope optics. In this system, the FSC detector is a photomultiplier tube rather than a photodiode. This unique system configuration achieves resolution down to 0.2 M. This type of instrument has been used to produce unique light scatter profiles as a means of rapidly characterizing bacterial populations. This characterization was further improved with the addition of DNA content as a parameter (Allman et al., 1992). Using this instrument, in conjunction with a specific antibody probe, it could be demonstrated that E. coli O157:H7 had enhanced FSC over background microbial flora in a beef enrichment culture (Raybourne, 1997). Additional strategies have also been developed to resolve bacteria on mass marketed flow cytometers lacking sensitive, high resolution light scatter detection. One approach is the use of SSC as the threshold or triggering parameter (Harkins, 1999; Alsharif and Godfrey, 2001). The SSC detector is typically a PMT which gives this parameter increased sensitivity over the photodiode detector typically used for FSC. In addition, this PMT is not in the direct light path of the laser as in the case of the FSC detector, reducing the tendency for optical noise. Additionally, log amplification of the SSC and/or FSC results in increased sensitivity. The emphasis on FSC and SSC as threshold parameters can be avoided entirely in favor of a fluorescence parameter by the use of a fluorochrome labeled probe or other fluorochrome to distinguish particles of interest from particulate noise (Nebe-von-Caron et al., 2000; Pinder et al., 1990; Porter, 1999). This strategy is based on the assumption that all particles of interest, i.e. bacteria or other cells, will take up the dye and become more fluorescent than particulate debris. Dyes that bind to cellular structures such as nucleic acids (Davey and Kell, 1996) are commonly used for this purpose. Nucleic acid binding dyes that increase their fluorescence upon binding to DNA are particularly useful. Success also depends on the dye penetrating all the cells. To achieve this may require the use of a dye that is cell membrane permeant such as thiazole orange (Givan, 2001b), acridine orange, or Syto 9 (Molecular Probes, Eugene OR, USA). Even though these dyes are permeant in eukaryotic cells, they may have difficulty being taken up by bacteria. Treatment of the cells with EDTA to deplete the Lipopolysaccharide (LPS) can facilitate bacterial labeling (Alsharif and Godfrey, 2001). If there is no need to retain viability of the cells, treatment such as fixation by heat or other toxic method can be used to render the cells permeable to normally impermeable nucleic acid binding dyes, such as propidium iodide or ethidium bromide. This increases the number of possible fluorochromes that can be used for this purpose (Pinder et al., 1990; Davey and Kell, 1996).

9.5.3 Microbial pathogens in food Detection of microbial pathogens such as bacteria in foods presents some additional challenges to those outlined above. These problems relate primarily to the complexity of the food matrix and the need to identify bacteria with some specificity. Many foods are fairly complex and require some processing to


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release bacteria into a suitable medium for further analysis. The processes for doing this (grinding, etc.) often result in the presence of particulates that can be extremely troublesome for FC analysis. Even liquid foods may require some processing. Foods are also generally not sterile and usually contain a presence of background bacterial flora or spoilage organisms that are not pathogens and are of little interest for regulatory purposes. Thus, the challenge becomes specific identification of pathogenic strains. Under ideal circumstances, measurement of some of the markers listed above (DNA staining, FSC, SSC) may help identify certain bacteria, but it is likely that a specific marker such as an antibody or nucleic acid probe will be needed. The availability and standardization of antibodies of appropriate specificity can then become a limitation. In addition, the pathogens of concern in foods often have very low presumptive infectious doses making it necessary to be able to detect as few as 10–100 cells of the organism of interest per gram of food, in the presence of a large number of bacteria of no regulatory interest. In spite of these potential difficulties, there is a significant potential payoff in the use of FC in food microbiology in the areas of rapid detection and high throughput, and in the ability to identify organisms of interest through multi-parameter single cell analysis. In terms of rapid detection, FC produces real-time and archival data that may be particularly important for critical control point monitoring (Wang and Slavik, 1999). Flow cytometers equipped with cell sorting capability can also be used to isolate bacteria of potential interest for further culture and analysis. FC can also detect non-viable as well as so-called viable non-culturable bacteria (Nebe-von-Caron et al., 2000) that can be of regulatory significance. A number of studies that have focused on detection of potentially pathogenic bacteria in food are summarized in Table 9.1. Excluded from Table 9.1 are studies that exclusively involve detection of specific pathogens derived from pure broth cultures (Goodridge et al., 1999; Clarke and Pinder, 1998; Kusunoki et al., 1998; McClelland and Pinder, 1994a), although the use of pure cultures is a necessary step in the development of methods applicable to a food matrix. There are several common elements to all of the studies listed in Table 9.1. These elements will be considered below. Experimental details can usually be found in the references cited. A more detailed protocol is also available (Raybourne, 1999) for studies with E coli O157:H7 in food.

9.5.4 Sample processing and enumeration of bacteria Comparison with conventional agar plate counts is generally used as the standard for counting bacteria by FC. As a starting point for method development, target organisms can be diluted in a filtered diluent such as PBS. Aliquots can then be taken for FC counting and plating. These simple suspensions are useful for instrument standardization. Many investigators then proceed to spiking of a food extract with dilutions of bacteria followed by parallel FC counting and plating. Because such food extracts often contain large

Table 9.1 Some studies utilizing flow cytometry for detection of microbial pathogens in food Organism

Food matrix-microbiological methods

FC methods

Reference

Listeria monocytogenes

Milk (selective enrichment from)

Donnelly and Baigent (1996)

Salmonella typhimurium Salmonella montevideo

Milk (direct detection after clearing and non-selective enrichment)

Salmonella typhimurium

Eggs and milk (direct detection after clearing and non-selective enrichment) Ground beef (non-selective enrichment) FC vs. Ab-DEFT comparison

CytofluorografTM: DNA (PI) Immunofluoresence Light Scatter (SSC) Custom-built cytometer: Nucleic acids (Ebr) immunifluorescence (FITC & R = PE) Light Scatter (FSC) Custom-built cytometer: Nucleic acids (Ebr) Immunofluorescence (FITC) Light Scatter (FSC) EPICS EliteTM and Bryte HSTMImmunofluorescence (FITC) Light Scatter (FSC) Sorting Bryte HSTMImmunofluorescence (FITC) Light Scatter (FSC)

McClelland and Pinder (1994b)

FACSortTMImmunofluorescence (FITC) Light Scatter (FSC)

Wang and Slavik (1999)

FACScanTM and FACSCaliburTM: Nucleic acid (SYTO BC) Light Scatter (FSC and SSC) Viability (PI) Sorting

Gunasekara et al. (2000)

Escherichia coli O157:H7

Escherichia coli O157:H7 Salmonella typhimurium

Total bacteria (Escherichia coli and Staphylococcus aureus)

Apple juice (non-selective enrichment) Comparison of six methods vs. time Washes from processed poultry (direct detection and selective enrichment) Immunomagnetic separation Milk (direct detection after clearing)

McClelland and Pinder (1994a)

Tortorello et al. (1998b)

Tortorello et al. (1998a)


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amounts of particulate matter, some type of filtration step is necessary to avoid clogging of the flow cytometer. Filtration of the extract or enrichment culture through a 5.0 m porosity filter has proven to be adequate to remove harmful large particulates (Tortorello et al., 1998b). If immunofluorescence is being used to identify the pathogen of interest, the samples must be stained before FC analysis. This is accomplished by addition of a predetermined optimal concentration of fluorescent antibody probe to the samples, followed by incubation and washing (Tortorello et al., 1998b). Some studies (Tortorello et al., 1998a; McClelland and Pinder, 1994a; Pinder and McClelland, 1994) use a killing step, which can be important as a safety consideration when working with biosafety 2 level pathogens because FC can generate aerosols. This would obviously not be practical in studies in which sorting and subsequent culture are planned. However, most flow cytometers capable of cell sorting have provisions for aerosol control due to the common use of these instruments to sort cells from infectious human samples (e.g. HIV infected blood). One advantage of a killing step is that it can facilitate the use of some nucleic acid staining dyes that are not normally membrane permeable. This can be used as a means to distinguish the bacterial cells in a sample from non-cellular debris and can thus aid in the identification of the entire bacterial population. In multiparameter analysis nucleic acid stains have been combined with fluorochrome-labeled antibodies to identify specific pathogens of interest in mixed bacterial populations (Donnelly and Baigent, 1986; McClelland and Pinder, 1994b; McClelland and Pinder, 1994a). Identification of the organisms of interest amongst a high background population is a significant practical consideration and can be addressed experimentally by spiking the food matrix with mixtures of the concerned pathogen and an irrelevant bacterial strain at various ratios (Pinder and McClelland, 1994), or by using similar mixtures in PBS (Tortorello et al., 1998b). One approach to the problem of pathogen enumeration by FC involves determination of the volume of sample that has passed through the detection point of the instrument. If the instrument uses a microsyringe with controlled flow, the volume of sample, the number of events (bacteria) in the region of interest, and hence the concentration of bacteria, can be determined directly. In the studies listed, only the custom built cytometer and the Bryte HS have this capability. In most commercially-available instruments, it is necessary to estimate the sample volume based on flow rate and time (Gunasekera et al., 2000; Wang and Slavik, 1999). Another approach is to include in the sample fluorescent microspheres (beads) at a known concentration. These beads have light scatter and fluorescence properties that are distinct from the bacteria. The concentration of the bacteria of interest (e.g., FITC-stained E. coli O157:H7) can then be calculated as a function of the ratio of beads detected by FC vs. the known concentration. When investigated in parallel, the microsyringe and ratiometric methods produced equivalent results (Tortorello et al., 1998b). It is interesting to observe that, despite all of the numerous variables between these studies, all of them achieved a consistent lower limit

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of detection of the pathogen of approximately 104 ml in various foods and in the presence of high levels of background flora compared to the ‘gold standard’ of viable counts. The level of sensitivity and resolution for detection by FC seems unlikely to be improved to a level sufficient to detect directly pathogens that may be of regulatory concern at concentrations of less that 100 organisms per 25 g of food. It is for this reason that great emphasis has been placed on the use of enrichment procedures for detection of low numbers of pathogens. The simple idea of enrichment is to culture an extract of the contaminated food in microbial growth medium to a point where the pathogen can be detected directly. This can be done using a medium that selectively promotes the growth of the pathogen (selective enrichment) or a permissive medium (non-selective enrichment). The experimental procedure involves spiking of food with known numbers of the pathogen down to very low levels of about 1 organism per ml or less. At this point, one approach is to add a competing strain of bacteria at various ratios to the strain of interest in order to simulate background flora in some foods (milk and eggs; McClelland and Pinder, 1994b). Alternatively, if the food has a high inherent background (e.g., ground beef or chicken washes) a substantial natural background bacterial flora will grow during the course of enrichment (Tortorello et al., 1998b; Wang and Slavik, 1999). Enrichment cultures can than be analyzed by both FC and plating at a fixed time point, or a series of enrichment cultures can be analyzed at various time points. This allows for the determination of the minimum enrichment time required to detect a given starting level of pathogen (Tortorello et al., 1998a; Wang and Slavik, 1999), an important consideration in a rapid method. With enrichments, enumeration by FC is relatively unimportant. The analysis is simply a positive or negative result with the detection limit extrapolated back to the original number of organisms added prior to enrichment.

9.5.5 Applications in food processing In addition to pathogen detection, FC methods have been developed for use in food processing and quality control. Multiparameter FC analysis of dairy starter and probiotic products revealed the presence of populations of culturable, metabolically active but not culturable and permeabilized (non-viable) lactic acid bacteria (Bunthof and Abee, 2002). This approach serves to better characterize the microbial properties of such products than culture alone. FC studies were also conducted on L. monocytogenes subjected to high hydrostatic pressure as a potential food preservation technique (Ritz et al., 2001). Analysis of metabolic activity based on fluorescein diacetate, membrane permeability based on propidium iodide and light scatter were used to assess the morphological and physiological state of treated cells.


9.6

209

Comparing detection techniques and future trends

Reliance on enrichments to detect low numbers of pathogens is not unique to FC, and is commonly used in other rapid methods. We compared FC, Ab-DEFT, direct plating, and immunomagnetic separation combined with direct plating or polymerase chain reaction (IMS-PCR) for their ability to detect several strains of E. coli O157:H7 in apple juice (Tortorello et al., 1998a). The standard for comparison was the enrichment time required for detection of the slowest growing strain at various levels of contamination. At the lowest level (0.1 cfu/ ml), Ab-DEFT proved to be the most rapid (8 h), followed by IMS-PCR (16 h), FC (24 h), IMS-direct plating, (32 h), and direct plating alone (48 h). In this direct comparison, FC and Ab-DEFT compared favorably with IMS-PCR, without the additional step of IMS. If the time required for each analysis were included it is likely that FC would be capable of analyzing many more samples per hour than other methods, since the approximate time for analysis of each FC sample is about 1 min.

9.6.1 Dedicated instruments One major drawback to the use of FC as a detection method is the relatively high cost of the instrumentation that has kept the technology primarily in the realm of a research tool. Commercially available research flow cytometers minimally cost approximately $100,000 and require one skilled key operator to maintain the instrument. The capabilities of these instruments may be beyond what is needed for analysis in the arena of food microbiology. These factors have led to efforts to develop dedicated instrumentation, based on FC technology, designed for specific applications that may be less expensive and less complex to operate. One such instrument is the BactoscanÕ which is essentially a flow cytometer with limited measurement parameters. This instrument has been used in conjunction with acridine orange staining to measure the number of microorganisms in raw milk (Rapposch et al., 2000). It has not been shown to be effective for probe-based detection of specific pathogens.

9.6.2 Laser scanning cytometry Laser scanning cytometry (LSC)Õ is a technology related to FC and to confocal laser scanning microscopy in which the laser beam rasters across a sample which is stationary on a microscope stage (similar to confocal laser scanning). As in FC, the signals emitted from particles in the sample are transmitted to PMTs, converted to electrical pulses, and digitized for computer analysis (Darzynkiewicz et al., 1999). The result is an output of single and multiple parameter histograms and dot plots similar to FC. One unique feature of this technology is the ability to re-locate particles (e.g. potential pathogens) of interest on the microscope stage for visual confirmation. As with FC, this technology is a relatively sophisticated tool with many applications in research. A dedicated instrument based on similar

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technology (ChemScanRDITM, Chemunex) has been developed and used in combination with IMS to detect small numbers of E. coli O157:H7 in ground beef and water (Pyle et al., 1999). In this study, liquid samples were concentrated by filtration using a polycarbonate nuclear etched membrane filter. This approach has the potential advantage of allowing for concentration of large volumes containing relatively small numbers of bacteria. In this way, it is somewhat similar to DEFT and has the potential to greatly increase sensitivity over conventional FC.

9.6.3 Application to counter-terrorism An unfortunate reality of today’s world is that incidents of contamination of food or water might not be accidental. The possible use of food as a vehicle for bio-terrorism might involve classical pathogens such as Salmonella or E. coli O157:H7, or the use of more exotic pathogens such as Bacillus anthracis or Francisella tularensis. In either case, the high throughput potential of FC might be of value in the event of such an incident, where numerous potentially contaminated samples might have to be analyzed rapidly. As outlined above, methods exist for FC detection of Salmonella and E. coli O157:H7 in foods. Methods have also been described for FC-based detection of B. anthracis spores (Stopa, 2000) using FITC-labeled antibodies. Some problems with crossreactivity to related species were reported, but could probably be overcome with more specific antibody probes. A method has also been reported for FC detection of F. tularensis (Grunow et al., 1998). It seems likely that these methods could be adapted for use in food analysis.

9.7


Current Protocols in Cytometry, edited by J.P. Robinson, published by John Wiley and Sons, New York in 1998. This is a compendium of detailed methods for flow cytometry and image analysis. It is in loose-leaf form and is updated regularly. Flow Cytometry, First Principles, second edition, by A.L. Givan, published by Wiley Liss, New York in 2001. An introduction to flow cytometry. ‘Flow cytometry and cell sorting of heterogeneous microbial populations: the importance of single cell analyses’, Davey, H.M. and Kell D.B. (1996) Microbiological Reviews 60: 641–96. A comprehensive review of flow cytometry of microorganisms. International Society for Analytical Cytology (ISAC). www.isac.org A professional organization for scientists interested in flow cytometry and related technologies Cytometry: Official publication of ISAC Handbook of Fluorescent Probes and Research Chemicals, by R.P. Haugland, published by Molecular Probes, Inc., www.molecularprobes.com. Part reference manual, part catalogue. Molecular Expressions Microscopy Primer. Michael W. Davidson, Mortimer Abramowitz, Olympus America, Inc. and The Florida State University. http:// www.microscopy.fsu.edu/primer/index.html. An educational website devoted to


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all aspects of microscopy. Includes interactive tutorials, virtual microscopes, photo gallery, references and links to web resources, both educational and commercial. Introduction to Light Microscopy, S. Bradbury and B. Bracegirdle. The Royal Microscopy Society, Microscopy Handbook Series, Volume 42. (1997) Springer, New York. The Royal Microscopical Society. International society of professional microscopists, publishes Journal of Microscopy and a series of technical handbooks providing practical instruction in microscopical techniques. Fluorescence Microscopy, by F.W.D. Rost, published by Cambridge University Press, Cambridge (1992 and 1995), two-volume set. Fluorescent and Luminescent Probes for Biological Activity, edited by W.T. Mason, published by Academic Press Ltd, London in 1993.

9.8

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Appl Environ Microbiol 60, 3553–9. and STEWART, D.S. (1997). Comparison of antibody-direct epifluorescent filter technique with the most probable number procedure for rapid enumeration of Listeria in fresh vegetables. J AOAC Int 80, 1208–14. TORTORELLO, M.L., REINEKE, K.F., STEWART, D.S. and RAYBOURNE, R.B. (1998a). Comparison of methods for determining the presence of Escherichia coli O157:H7 in apple juice. J Food Prot 61, 1425–30. TORTORELLO, M.L., STEWART, D.S. and RAYBOURNE, R.B. (1998b). Quantitative analysis and isolation of Escherichia coli O157:H7 in a food matrix using flow cytometry and cell sorting. FEMS Immunol Med Microbiol 19, 267–74. VALDEZ, L.M., DANG, H., OKHUYSEN, P.C. and CHAPPELL, C.L. (1997). Flow cytometric detection of Cryptosporidium oocysts in human stool samples. J Clin Microbiol 35, 2013–17. VAN DILLA, M.A., TRUJILLO, T.T., MULLANEY, P.F. and COULTER, J.R. (1969). Cell microfluorometry: a method for rapid fluorescence measurement. Science 163, 1213–14. VESEY, G., HUTTON, P., CHAMPION, A., ASHBOLT, N., WILLIAMS, K.L., WARTON, A. and VEAL, D. (1994). Application of flow cytometric methods for the routine detection of Cryptosporidium and Giardia in water. Cytometry 16, 1–6. WANG, X. and SLAVIK, M.F. (1999). Rapid detection of Salmonella in chicken washes by immunomagnetic separation and flow cytometry. J Food Prot 62, 717–23. WOODY, J.M., WALSH, R.A., DOORES, S., HENNING, W.R., WILSON, R.A. and KNABEL, S.J. (2000). Role of bacterial association and penetration on destruction of Escherichia coli O157:H7 in beef tissue by high pH. J Food Prot 63, 3–11. TORTORELLO, M.L., REINEKE, K.F.

10 Immunological techniques: immunochromotography, enzyme-linked immunofluorescent assays and agglutination techniques C.L. Baylis, Campden and Chorleywood Food Research Association, UK

10.1

Introduction

Developments and technological advances in the field of microbiological test methods have resulted in the availability of a wide range of commercial kits and new techniques for the microbiologist. More recently there has been a gradual adoption of molecular biology methods into food testing, although lack of knowledge of these methods, the perceived greater costs associated with their use compared with traditional culture methods and lack of universal acceptance, currently restricts the widespread uptake of molecular methods. By comparison immunological methods which rely on the interaction between specific antibodies to selectively capture, label and detect antigens associated with the target organism are widely used and accepted for the detection and confirmation of specific microorganisms and certain toxins. The antigen of interest may be a cellular component of the target organism, such as a specific lippopolysaccharide on the outer cell wall, a protein on the flagella of certain motile bacteria, or a product or toxin produced by the organism during growth. The choice of antigen is particularly important as this will determine the specificity of the test. Antigens present on flagella can provide greater specificity, whilst some somatic antigens can be shared by a wide range of bacteria besides the target organism. A good example of such an antigen is the somatic O-antigen of E. coli O157. Although detection of this antigen provides a convenient and relatively specific method for detecting or confirming this pathogen, other bacteria share

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similar lipopolysaccharide structures, the most common being Escherichia hermanii and Citrobacter freundii. However, somatic antibody cross-reactions have also reported for some strains of Yersinia enterocolitica and Brucella species (Borczyk et al., 1987; Perry and Bundle, 1990; Bettelheim et al., 1993). Consequently, rapid immunological tests, although relatively specific, cannot be used alone to confirm the presence of a particular organism. For this reason, results from immunological detection methods are regarded as presumptive until they have been confirmed by conventional cultural isolation and subsequent confirmation of the target organism. Moreover, whilst immunological methods such as agglutination tests have become an integral part of some confirmation procedures, for example those used for Salmonella and E. coli O157, these too require supplementary characterisation tests such as biochemical tests to be performed to fully identify and confirm the presence of the target organism. In addition to the target antigen, the choice and type of antibodies used can markedly affect the specificity of the method and selection requires careful consideration by those developing immunology-based kits. Whilst optimising binding conditions for monoclonal antibodies is relatively straightforward, this can be more difficult for polyclonal antibodies which have a variety of epitopes which may each require different binding conditions. However, the choice and number of antibodies used will depend on the target analyte and the required specificity needed for the test. It should be remembered that a certain degree of method specificity is also provided by the growth media and conditions used before detection or isolation. Although certain organisms may potentially crossreact with the chosen antibodies, the careful choice of selective agents and growth conditions can effectively reduce the risk of false positive results. Moreover, during confirmation procedures, complementary characterisation tests should be used to eliminate non-target organisms. Probably the most widely used methods for detection of specific microorganisms in foods are those based on the enzyme-linked immunosorbent assay (ELISA) technique which is explained in more detail in Chapter 11. In addition, magnetic beads coated with antibodies have become popular for the separation of the target organism from food homogenates or enrichments containing interfering food particles and competitor organisms using the immunomagnetic separation (IMS) technique. This technique is commonly used to aid the detection of E. coli O157 in foods and has become an integral part of conventional and some rapid methods for this pathogen (Scotter et al., 2000; Baylis et al., 2001; Chapman et al., 2001). Consequently, the widespread use and acceptance of immunology-based methods has resulted in a plethora of commercial test kits for the detection of the common foodborne bacteria in foods including those belonging to the genera Salmonella, Listeria and Campylobacter, and more recently the specific detection of E. coli O157:H7. For the subsequent confirmation of suspect isolates there is also a wide range of agglutination tests available which again rely on detection of a particular antigen by monoclonal or polyclonal antibodies. In addition to the common foodborne pathogens, there are kits available for the

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detection and confirmation of less common bacteria, protozoans and specific toxins. Many of these kits are currently aimed at the clinical microbiology market, but with time and greater demand some may ultimately find their way into the food microbiology sector. However, despite the advances and developments in microbiological methods and the higher specificity and rapidity of results offered by many end-point detection systems, their dependence on conventional cultural enrichment still remains the most important limiting feature of the majority of microbiological methods. The minimum limit of detection of many methods, including those based on immunological or molecular approaches, is 104 log10 cfu per ml (Jay, 2000) and a particular pathogen in a food is likely to be found in low numbers. It is therefore still necessary to increase the level of the target organism using enrichment techniques. Moreover, the organism of interest is not likely to be homogeneously distributed throughout the food and is likely to be present together with higher numbers of other closely-related microorganisms which may retard or totally inhibit the growth of the organism of interest (De Medici et al., 1998; Baylis et al., 2000) resulting in a negative assay result. These competitor organisms may also give rise to cross-reactions with the antibodies used in some detection systems and confirmation tests, resulting in false positive results. Furthermore, cells in a food may have sustained sublethal injury from either the treatments used in food processing or from the effects of intrinsic factors such as low pH, high salt content, and the effect of preservatives or other inhibitory properties associated with the food concerned. Such damaged cells are often susceptible to the selective agents used in culture media and commonly exhibit extended lag phases and are less likely to grow rapidly, even under optimum growth conditions (Stephens et al., 1997; Blackburn and McCarthy, 2000). Selective enrichment, which is often required to inhibit or restrict the growth of competitor organisms, may also have a detrimental effect on the target organism. To overcome this, a pre-enrichment step is often necessary, but this adds additional time to the method. Having enriched the target organism to detectable levels, the microbiologist is faced with a vast array of rapid detection methods. As mentioned previously, the ELISA technique, but especially the microtitre plate format, has become an extremely popular method for routinely screening food samples following enrichment. Traditionally these assays, although rapid to perform, are labour intensive and rely on multiple stages for the washing of microtitre plates and addition of reagents prior to reading the result. Typically these assays take between 1–2 hours, depending on the format of the test and number and length of incubation steps. The introduction of automated plate washers and readers has reduced the hands-on time associated with performing many of the tasks required for these tests, but assay times still remain relatively long because of the multiple stages required. Fully automated systems based on the enzymelinked immunofluorescent assay technique (ELFA), which are covered later in this chapter, also provide reduced hands-on time whilst retaining the rapidity

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and specificity of the traditional ELISA techniques. By comparison immunochromatography techniques such as lateral flow devices (see Section 10.2) may require no instrumentation and results are often available within 15–20 minutes following the addition of a portion of enriched sample to the device. Consequently these tests have become an attractive alternative to the traditional ELISA test.

10.2

Immunochromatography: lateral flow devices

The introduction of membrane-based assays which rely on the immunochromatography principle has had a major impact on rapid end-point testing. This is particularly true in clinical diagnosis where immunochromatographic devices are routinely used for the detection of a wide range of analytes including specific components of urine, blood and other biological fluids, hormones, therapeutic drugs and drugs of abuse, viruses and other agents of disease and infection. This technology has now been applied to food testing and other nonclinical applications, resulting in a wide range of commercial kits for the detection of antibiotic residues, hormones and common foodborne pathogens. The most common format for immunochromatographic devices is the lateral flow or dipstick design. Although commercial assays are available in a diverse assortment of housings and designs, lateral flow devices generally share the same common composition and performance characteristics. A lateral flow device typically comprises a porous membrane, typically nitrocellulose, onto which is immobilised a capture protein for the target analyte. In most devices, it is common for the capture protein to be an antibody which specifically binds and captures a particular antigen if present in the sample (Fig. 10.1). A portion of sample is applied to the sample pad, often composed of paper, through an inlet in the housing, commonly referred to as the sample window. Below the sample pad is the conjugate pad, commonly composed of glass fibre, which is attached to the membrane. This pad contains a dried conjugate comprising particles adsorbed with antibodies or antigens specific to the analyte being detected. For some commercial kits, the conjugate contains gold particles, for example the visual immunoprecipitate (VIP) range of tests from BioControl Inc, Reveal tests from Neogen Inc, the Immunocard STAT! E. coli O157:H7 test from Meridian Diagnostics and the Singlepath range of LFDs from Merck. By comparison, with other commercial kits such as the Listeria Rapid Test (Oxoid Ltd), the conjugate contains coloured latex particles. When a sample is applied to the sample pad, the liquid migrates by capillary diffusion through the conjugate pad, re-hydrating the conjugate. Specific interaction between the conjugate and the sample analyte occurs, resulting in the formation of a complex which proceeds to move onto the membrane and migrate towards the capture binding protein where it becomes immobilised. This process, which is dependent on the flow rate of the fluid through the microporous membrane, typically takes 15–20 minutes for many commercial devices, and produces a distinct band or


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Fig. 10.1 Components of a typical lateral flow device.

line in the test window of the device, which is indicative of a positive result for the analyte of interest. Excess conjugate continues to migrate up the membrane where it is immobilised at another point on the membrane, producing a second line, commonly referred to as the control line, which indicates that the test is complete and the device has functioned properly (Fig. 10.2). In the absence of the target analyte, i.e. a negative result, only the control line will appear. Whilst the principle of lateral flow devices appears straightforward and relatively simple, in reality there are a number of problems that manufacturers of these devices must consider and overcome if these devices are to give the desired sensitivity and performance. The many interactions and problems associated with nitrocellulose membranes are covered in detail elsewhere (Jones, 1999a, 1999b). Whilst it may not be necessary for the user to concern themselves with these aspects of lateral flow devices, an appreciation of the potential causes of poor performance or unexpected results can be valuable when using these devices for the first time or with different food matrices. Among the important forces involved in protein binding to nitrocellulose membranes are hydrophobic and electrostatic interactions and hydrogen bonding. Each of these must be carefully considered by developers of LFDs in order to optimise binding of proteins to a particular membrane. The wicking movement of a sample through the membrane is the result of capillary action, which is a function of cohesion forces. To achieve lateral flow and wicking of the liquid through the membrane, the differential between the surface energies of

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Fig. 10.2 Example of a lateral flow device showing test and control lines (Courtesy Merck KGaA).

the solid substrate and the fluid sample needs to be overcome without mechanical assistance. To improve the flow of fluid through the membrane, the surface energy of a fluid must be decreased. Optimum wicking is achieved by reducing the surface tension of a fluid so that it is less than the surface energy of the surface to be wetted (Meathrel et al., 2001). Manufacturers achieve this by using physical and chemical treatment of plastics. Surfactants can also be used to reduce the surface energy of a fluid. For this purpose they are sometimes used to reduce the surface energy of the fluid directly or they are incorporated into adhesives and coatings used in the construction of these devices. For certain LFD tests or target proteins, it may be necessary to dilute the sample in a buffer before applying it to the device. For some tests this is required to ensure good solubility of the protein of interest or to maintain it in a stable form when presenting it to the device. If proteins in the sample precipitate before being applied to the membrane the amount of protein available for attachment to the membrane can be substantially reduced or the pores of the membrane can become clogged. Consequently, the performance of the device can be greatly reduced and results could be unreliable. The use of a buffer with such devices can overcome these problems, although many popular LFDs used for food testing enable food homogenates to be applied directly to the device. Although there are many commercial LFDs used for clinical applications, e.g. the ImmunoCard STAT! (Meridian Diagnostics Inc.), there are some commercially available LFDs that have been subjected to independent evaluations or collaborative studies to compare their performance against other similar devices or against conventional culture methods for the detection of specific


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Table 10.1 Examples of commercially available detection tests based on immunochromatography (lateral flow devices) Kit name

Manufacturer

Target analyte

VIP Salmonella VIP Listeria VIP EHEC

BioControl Inc

Salmonella Listeria spp E. coli O157

Reveal Salmonella Reveal Listeria Reveal E. coli O157:H7

Neogen Corp

Salmonella Listeria spp E. coli O157

Singlepath Singlepath Singlepath Singlepath

Merck KGaA

Salmonella Listeria spp E. coli O157 Campylobacter

Salmonella Listeria E. coli O157 Campylobacter

Duopath Verotoxins

VT1 and VT2*

Listeria Rapid test (Clearview)

Oxoid Ltd

Listeria spp (excluding L. murrayi)

NOWTM E. coli O157 and O157:H7

Binax Inc

E. coli O157

E. coli O157 Path-Stik Salmonella Path-Stick ImmunoCard STAT

Celsis Ltd

E. coli O157:H7 Salmonella E. coli O157

Meridian Diagnostics

* VT1 and VT2 refer to verocytotoxins (Shiga toxins).

pathogens in foods. Examples of commercially available LFDs used for foods are presented in Table 10.1 and details of specific kits are given below. In addition, there have been some commercial kits that have been included in validation and collaborative studies for food testing under the scheme operated by the Association of Official Analytical Chemists (AOAC) in the United States. LFDs approved for use with foods and specific sample types include the popular VIP (BioControl Inc.) range of kits for the detection of E. coli O157:H7 in selected foods (Feldsine et al., 1997a, b) Listeria monocytogenes in selected foods (Feldsine et al., 1997c), and from environmental samples (Feldsine et al., 2002) and Salmonella in foods (Feldsine et al., 2000). A second commercial LFD subjected to collaborative studies under the AOAC scheme is the Reveal test for E. coli O157:H7, manufactured by Neogen Corp. In addition to the LFD which is used for end-point detection, the manufacturers of this device have developed two enrichment media to selectively increase the amount of target organisms in the food sample to detectable levels. The first is an eight-hour test which has been subjected to collaborative study for detection of E. coli O157:H7 in raw ground beef, beef cubes and lettuce rinse (Bird and Hoerner, 2001b) and a 20-hour test for detection of this pathogen in selected foods and environmental swabs (Bird and Hoerner, 2001a). Other commercial LFDs approved by the AOAC for food testing include the PATH-STIK Salmonella test (Celsis), Reveal

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Salmonella test (Neogen Corp.) and Listeria Rapid test (Oxoid Ltd). These tests have all received performance-tested status by the AOAC after independent laboratory validation of the performance claims. As well as the AOAC scheme, there have been independent studies performed to compare the performance of LFDs against each other, against conventional culture methods and against other rapid methods. In a recent independent study (Chapman et al., 2001), both Reveal 8 h and 20 h test and VIP test were compared with a polymerase chain reaction (PCR) method and a conventional culture method incorporating IMS, for the detection of E. coli O157 in various naturally contaminated meats and meat products. It was reported that both LFDs were simple and rapid to use, giving results within 24 h. However, the sensitivity of both devices was less than that of the conventional culture method. In particular, the Reveal 8 h test performed poorly. This was attributed to the short incubation period and incubation temperature of 43ºC which may have been insufficient to recover stressed cells to a detectable level by the Reveal test. In food enrichments containing high levels of closelyrelated competitor organisms, growth of the target organisms can be severely retarded (Baylis et al., 2000). In a previous study (Power et al., 2000), the Reveal test (Neogen Corp.) and SafePath microwell ELISA method (SafePath Laboratories) were compared with a cultural method for the detection of E. coli O157 in bovine faeces and on meat carcasses. The latter method, which incorporated IMS, was regarded as the reference method. For the detection of E. coli O157:H7 on beef carcasses, the study revealed that both LFD and ELISA showed similar high specificity, being 99 per cent and 100 per cent, respectively. However, the sensitivity of both was low at 50 per cent, although this was based on low numbers of contaminated carcass samples. However, for individual faecal samples, the ELISA showed a much higher sensitivity (70 per cent) compared with the LFD (46 per cent). The authors concluded that both the ELISA and LFD showed promise as rapid carcass monitoring tests although more field testing would be necessary to estimate their sensitivity. For the detection of Listeria species in foods, the Listeria Rapid test (Oxoid Ltd), launched in 1994, has been reported to give comparable performance to conventional culture methods in a number of studies and trials (Roberts, 1994). The kit relies on the detection of ‘B’ flagella antigen which is common among Listeria species with the exception of L. grayi (formerly L. grayi subsp grayi and murrayi). In the device one of the monoclonal antibodies raised against flagellin protein is bound to blue-dyed polystyrene latex particles. The principle of the test is similar to the general format described above and shown in Fig 10.1. If the target antigen is present in the food sample, the antibody-antigen complex will migrate up the membrane and become immobilised by antibodies on the membrane, forming a blue line. Excess latex labelled antibodies continue to migrate up the membrane where they meet another line of immobilised polyclonal antibodies raised against mouse IgG, resulting in a second line that shows that the test has performed correctly.


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In two independent evaluations (Barbuti et al., 1995; Jones et al., 1995), the sensitivity of the test was reported to be between 103 and 106 cfu/ml, although this can be influenced by the serotype and strain as well as the growth conditions prior to using the device. Whilst this test is not designed to detect Listeria grayi which lacks the target antigen, conditions such as medium and incubation temperature may affect flagella formation and consequently reduce the yield of target antigen, resulting in false negative results (Jones et al., 1995). False negative results may also occur in certain foods containing low levels of stressed cells that may also fail to yield detectable levels of antigen after enrichment (Barbuti et al., 1995). However, this same situation can occur with any test that relies on multiplication of the target organism and the provision of sufficient amounts of target, be it antigen, DNA or cells, that will be detected by the test device. For the majority of foods, the Listeria Rapid Test has shown good correlation with traditional culture methods but with the advantage of reducing the time for a presumptive positive or negative result from 96 to 48 h.

10.3

Enzyme-linked fluorescent assays (ELFA)

Whilst LFDs provide simplicity and rapidity of results without the need for expensive equipment to perform and read the tests, traditional ELISA tests using microtitre plates remain popular and have become universally accepted methods for detection of pathogens in foods. More recently there has been a move towards greater automation of ELISA tests, which not only reduces the hands-on time but also improves the reproducibility and standardisation of each step of the assay. Whilst many ELISA-based methods rely on chromogenic substrates for end-point detection of the target antigen, enzyme-linked fluorescent assays (ELFA) employ fluorescence for end-point detection. A good example of commercial assays based on the ELFA principle are those developed by bioMe´rieux to run on their automated instrument the Vitek Immuno Diagnostic Assay System (VIDAS). In addition to producing assays for the clinical market, bioMe´rieux also produces a range of assays for the food microbiology sector which are performed on the VIDAS. These include assays for Salmonella, Campylobacter, Listeria species, Listeria monocytogenes, E. coli O157 and staphylococcal enterotoxins (A, B, C1, C2, C3, D and E). All of these assays are based on the ELFA principle and the steps described below are all performed automatically by the VIDAS instrument. In the same way that conventional ELISA tests are based on the specific binding of the target antigens to a capture antibody, ELFAs use the same principle except that the second antibody is conjugated to an enzyme which produces a fluorescent reaction upon addition of the enzyme substrate. Assays that are performed on the VIDAS typically comprise two parts. The first of these is a pipette tip-like disposable device, termed the solid phase receptacle (SPR), which is coated with antibodies specific to the target antigen. The SPR serves as both a pipette for the assay and as a solid phase onto which the antibodies are

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Fig 10.3 Cross-section of a VIDAS reagent strip (Modified from an image supplied by bioMe´rieux).

coated. The second is the reagent strip, comprising a polypropylene strip consisting of ten wells covered with a foil seal (Figs 10.3 and 10.4). All the reagents necessary for the assay are contained within specific wells in the strip. These include wash solutions, conjugate comprising of alkaline phosphatase labelled antibodies, which can be polycolonal or monoclonal depending on the assay, and the substrate 4-methyl-umbelliferyl phosphate. Following cultural enrichment of the sample in appropriate liquid media, an aliquot of boiled enrichment sample is placed into the first well of the reagent strip, which is placed in the VIDAS instrument. During the assay, the sample is

Fig. 10.4 Example of a VIDAS reagent strip (Courtesy bioMe´rieux).


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cycled in and out of the SPR for a specific length of time. If the target antigen is present in the sample it will bind to the antibodies coated to the interior of the SPR. Unbound sample components are removed by subsequent washing steps. The conjugate, which consists of antibodies labelled with alkaline phosphatase also binds to the antigen portion of the immune complex whereas unbound conjugate is removed by a final wash step. The fluorogenic substrate used by the assay, 4-methyl-umbelliferyl phosphate, is converted to the fluorescent product 4-methyl-umbelliferone by bound enzyme remaining on the SPR. The last well in the strip is an optically clear curvette in which intensity of fluorescence is measured by the optical scanner in the instrument. As with other immunoassays, any positive results for pathogens are regarded as presumptive and require cultural isolation and subsequent confirmation of the target organism. In previous studies, the VIDAS assays have been compared with conventional culture methods, including those incorporating IMS as well as other rapid methods for the detection of E. coli O157 (Vernozy-Rozand et al., 1997; Grif et al., 1998; Vernozy-Rozand et al., 1998), Listeria spp (Gangar et al., 2000; Kerdahi and Istafanos, 2000), L. monocytogenes (Vaz-Velho et al., 2000) and Salmonella (Curiale et al., 1997). In addition to the conventional assays that can be performed on the VIDAS, the Salmonella and E. coli O157 assays can both be used with an additional stage incorporating immunoconcentration. These procedures are termed immunoconcentration Salmonella (ICS) and immunoconcentration E. coli (ICE), respectively. Whilst similar in principle to manual IMS techniques, where the target organism is concentrated before screening with a rapid method such as an ELISA, or plating onto an isolation media, VIDAS immunoconcentration techniques provide a fully automated method of concentrating target organisms. Conventional ELFA for Salmonella detection using the VIDAS typically involves enrichment followed by the assay and end-point detection of the target antigen. The immunoconcentration assays both use a SPR device for the solid phase and a strip comprising of wells containing the necessary reagents for this procedure. However, unlike the conventional ELFA run on the VIDAS, the sample is not heat treated and living cells instead are captured by specific antibodies coated on the inside of the SPR. After different washing stages to remove other organisms non-specifically absorbed onto the SPR, a novel release process then enables the captured cells to be released and concentrated in solution in the first well in the strip. This process typically takes 40 min and the solution containing the concentrated cells can either be collected and used for isolation on appropriate media, or it can be used for detection using the ELFA strip. For Salmonella detection, the method requires pre-enrichment followed by selective enrichment, which typically takes 48 h prior to performing the assay. The ICS procedure replaces the selective enrichment stage so the assay can be performed after 16–24 h pre-enrichment, giving presumptive results on the second day. Alternatively selective media can be inspected for presumptive

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Salmonella colonies on the second day after using the ICS plating technique. For E. coli O157, the ICE is used to aid confirmation of positive samples according to the conventional ELFA. This automated immunoconcentration procedure has the additional benefit of reducing test times but also of improving the specific concentration and isolation of target organisms (De Medici et al., 1998; Vernozy-Rozand et al., 2002).

10.4

Agglutination tests

Owing to the specificity provided by antibody-antigen reactions, immunological methods have become increasingly popular for the detection of foodborne pathogens and toxins. Another application exploiting this interaction between antigen and antibody is serological confirmation and the use of agglutination tests. The term agglutination is used to describe the reaction of an antigen with its corresponding antibody in vivo producing macroscopic clumping. This reaction is generally rapid, does not dissociate and shows high affinity. Agglutination tests have been used extensively in clinical diagnosis of infection and for serological classification of bacteria for many years. As far back as 1896, techniques for testing patient serum for Salmonella antibodies in cases of typhoid fever were developed using agglutination of Salmonella O and H antigens to aid diagnosis. In addition to this application, which also extends to the diagnosis of other clinical infections, the use of antigenic typing schemes has become another important aspect of epidemiology and classification in microbiology. Probably the most well known of these typing schemes is the Kauffmann-White Antigenic Scheme used for identifying salmonellae. Traditionally serotypes of Salmonella are defined based on the antigenic structure of the somatic or cell wall (O) heat-stable antigens followed by the flagella (H) heat-labile antigens which are usually associated with motility. Whilst one somatic antigen may be common to a group of salmonella strains and thus identify a serogroup, other antigens may be shared among several serogroups. Furthermore, with a serogroup there will be specific antigens that together with the flagella (H) antigens enable a Salmonella to be identified to a particular serotype based on the combinations of O and H antigens present. Using this approach, over 2300 serotypes of Salmonella have been identified. However, with the increased use of genomics and improvements in molecular biology techniques, it has been realised that Salmonella serotypes are not different species, but that they all belong to two DNA hybridisation groups. Consequently, the nomenclature of Salmonella has again changed and now all of the Salmonella serovars belong to two species, namely S. bongori which contains 18 serovars and S. enterica which contains the remaining 2300+ serovars divided among six subspecies (Threlfall et al., 1999), Typically a laboratory would initially use polyvalent antisera that cover the Salmonella O Groups Poly A through to Poly G. If agglutination occurs, individual Salmonella O Group factor antisera would be used to determine to


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which specific serogroup the isolate belongs. Cross-reactions with Salmonella O factor antisera are possible because serogroups may share non-major group antigens. Furthermore, cross-reactions with organisms outside the genus can occur and for this reason both morphological and biochemical identification should be used to support any serological identification. Flagella (H) antigens, including analysis of phase 1 and phase 2 antigens, are also identified using a combination of polyvalent and single complex H antisera. However, to fully serotype and identify Salmonella requires time, expertise and a complete range of antisera to be kept by the laboratory. Consequently, whilst some laboratories may identify Salmonella biochemically and confirm the presence of O and H antigens using polyvalent antisera, or even use antisera to identify a particular serogroup, it is more common for such isolates to be sent to a specialist laboratory for complete identification involving full serotyping, phage typing or the use of genetic typing methods. Compared with specialist laboratories performing serology on routine isolates, food testing laboratories will need to confirm the identity of a suspect isolate quickly to enable appropriate action to be taken should contamination of a food product be suspected. Confirmation tests, particularly biochemical and basic serological identification or confirmation of a particular antigen, have become an integral part of some methods, in particular those for Salmonella and E. coli O157:H7. Although traditional antisera are available, in recent years there has been an increase in the introduction of rapid agglutination tests that are more convenient to use and easier to interpret. More recently, the use of blood cells or latex particles labelled with antibodies are particularly common formats, which not only allow for easy interpretation of clumping, but require less antigenic material to yield visible precipitation compared to conventional agglutination tests using antisera. Although many kits have primarily been developed for clinical diagnosis, many can be and have been adopted for identification of food isolates.

10.4.1 Agglutination tests for confirmation of bacteria Agglutination tests for Staphylococcus aureus Probably one of the most common foodborne organisms identified by commercial agglutination tests is Staphylococcus aureus. Traditionally, the tube coagulase test which involves confirmation of free coagulase using rabbit plasma is regarded as the ‘gold standard’ for the identification of S. aureus. This test is labour and materials intensive and requires regular readings up to 4 h, but it may require up to 24 h to obtain a positive result, which is characterised by clotting of plasma in the tube. Although conventional antiserum is available, owing to the complex antigenic structure of S. aureus, they are not commonly used in food testing laboratories for S. aureus identification. For epidemiological studies, typing with bacteriophages has proved to be a more useful approach. Food microbiologists on the other hand rely predominantly on confirmation of coagulase or heat stable nuclease (thermonuclease), but to distinguish S. aureus

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from other coagulase positive staphylococci, notably S. hyicus and S. intermedius, the coagulase test must also be accompanied by biochemical identification. Furthermore, although uncommon, some strains of free-coagulase negative S. aureus have also been reported (Luijendijk et al., 1996) which further supports the importance of not relying on one test, but instead, using a combination of tests to aid with the identification and confirmation of suspect isolates. Whilst the tube coagulase test may be used to detect free coagulase, a rapid version, the slide test, detects bound coagulase or fibrinogen affinity factor (clumping factor). This test is favoured because it is quick and easy to perform, involving emulsification of a colony in water on a slide, adding plasma and observing clumping which should occur within seconds. However, this technique is not recommended for colonies directly from selective media, particularly media containing high concentrations of salt which can give rise to autoagglutination and false positive results. Furthermore, if isolates autoagglutinate, these and those giving rise to negative results by slide agglutination test, generally require re-testing using the tube test. Consequently, commercial agglutination tests, which are simple and easy to use and interpret, and can provide results within seconds of testing a colony directly from an isolation medium, have proved popular alternatives to traditional tube and slide tests for routine identification of S. aureus. Two of the most common targets for commercial agglutination kits used for the identification of S. aureus are clumping factor and protein A. Some kits may detect clumping factor alone and others may also detect protein A. In clinical microbiology, identification of methicillin-resistant S. aureus (MRSA) is of particular importance. However, many MRSA strains possess capsular polysaccharide which can mask other cell components such as clumping factor and protein A. Consequently, many of these strains can give rise to negative results using agglutination tests targeted specifically at these or other cell surface antigens (Hsueh et al., 1999). To overcome this problem some of the earlier commercial agglutination kits have been modified whilst newer ones already include additional targets, such as specific surface antigens and polysaccharides, to improve detection of MRSA strains (Smole et al., 1998). Some of the earlier tests consisted of erythrocytes sensitised with fibrinogen for the detection of clumping factor. Subsequent commercial kits have employed coated latex particles and/or sensitised sheep erythrocytes for the simultaneous detection of clumping factor and protein A. For example, the Slidex Staph kit (bioMe´rieux) is an agglutination test based on a combination of latex and haemagglutination. The reagent contains blood cells sensitised with fibrinogen to detect bound coagulase and latex particles sensitised with specific monoclonal antibodies to detect protein A by the Fc fragment of IgG, as well as antigens on the bacterial surface. In contrast the BBL Staphyloslide kit (Beckton Dickenson) is a test based only on haemagglutination and detects the activity of the cell wall polypeptide clumping factor, which binds to fibrinogen sensitised sheep erythrocytes, resulting in visual clumping.


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Whilst S. aureus produces both free and bound coagulase, some other species of coagulase negative staphylococci have been found to produce clumping factor. These include S. lugdunensis and S. schleiferi, which although negative by traditional coagulase tube test, has been reported to give rise to positive results with agglutination tests that detect clumping factor (Personne et al., 1997; Zbinden et al., 1997; van Griethuysen et al., 2001). Moreover, even agglutination tests that detect polysaccharides and other surface antigens can give rise to positive results from coagulase negative species, for example S. haemolyticus (van Griethuysen et al., 2001) and S. epidermidis (Blake and Metcalfe, 2001). Agglutination tests for Escherichia coli O157 Another example of a foodborne pathogen which is routinely screened for and identified with the aid of agglutination tests is E. coli O157. As with S. aureus there is a plethora of commercial agglutination tests available to the microbiologist to aid with screening of suspect isolates. However, these agglutination tests also have limitations and require supplementary tests to be performed if an accurate positive identification is to be obtained. Screening foods for E. coli O157 commonly involves enrichment in a suitable selective medium which increases the target organism to levels that can be detected by a suitable end-point test or isolation on a suitable plating medium. Fortunately, the O antigen of the E. coli O157 serogroup provides a specific and convenient target for immunological methods. This can involve detection of the O157 antigen using ELISA, ELFA and LFD tests and the incorporation of IMS to increase recovery of cells from foods which may contain high levels of closely-related background flora. Following plating onto suitable selective plating media, it is usual to screen a selection of colonies exhibiting typical colony morphology for the presence of O157 antigen. Subsequent identification then usually requires biochemical identification to establish that the isolate is E. coli, although E. coli O157:H7/H- do not ferment sorbitol rapidly, if at all, unlike typical strains of E. coli. Furthermore, the majority of E. coli O157 strains lack -glucuronidase activity, which, again, is atypical for most strains of E. coli and is often a useful characteristic used to differentiate E. coli O157 from other E. coli strains. As discussed previously, antibodies used for the detection of O157 antigen can cross-react with the lipopolysaccharide (LPS) of other bacteria. Consequently, certain immunoassays can give rise to false positive results and commercial latex agglutination tests can also yield positive results with bacteria besides E. coli O157. In one evaluation of three commercial latex agglutination test kits cross-reactions with strains of Citrobacter freundii and Salmonella O group N were reported (Sowers et al., 1996). In addition to these, Escherichia hermanii is another bacterium that exhibits serological cross-reactivity with O157 (Borczyk et al., 1987; Perry and Bundle, 1990). Moreover, like E. coli O157 it too does not ferment sorbitol rapidly, if at all and therefore gives rise to similar colony morphology to E. coli O157 on sorbitol MacConkey medium,

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which is routinely used for the isolation of E. coli O157. It also shares the absence of -glucuronidase activity and therefore resembles presumptive E. coli O157 even further. However, biochemical tests can help to distinguish these bacteria, in particular, the ability of E. hermanii to ferment rhamnose. Once a laboratory has confirmed the presence of O157 antigen the isolate is still presumptive until the results from supporting tests such as the biochemical profile confirms the isolate to be E. coli. In addition the isolate will require testing to confirm its ability to produce verocytotoxins or the possession of the toxin genes and associated virulence determinants. These tests, together with full typing, including serology, phage typing and toxin typing, would normally be performed by a specialist laboratory. Furthermore, owing to the potential for severe infection and the low infective dose by these bacteria, including reports of laboratory acquired infection, strains of verocytotoxin-producing E. coli (VTEC) have been re-categorised to Hazard Group 3. This therefore requires that all work with known cultures of VTEC and samples highly likely to contain these organisms must be conducted in a Containment Level 3 Laboratory. Agglutination tests for Salmonella In routine laboratories, Salmonella confirmation generally involves confirmation of Salmonella somatic O and flagella H antigens supported by biochemical confirmation that the isolate is Salmonella. In some laboratories the isolate may be serotyped to a particular O Group but full serology is often performed by a specialist laboratory. The basic serology is often performed using polyvalent antisera. However, there are some commercial latex agglutination kits that can be used to aid with the screening and presumptive identification of suspect isolates. For screening purposes the Salmonella Latex kit (Oxoid Ltd) can provide a useful test to confirm isolates for the presence of Salmonella antigen. The test is based on latex particles coated with polyclonal antibodies targeted against flagella H antigens which are detected by agglutination. In addition to this test, others have been developed for screening isolates from clinical samples and for detection of particular Salmonella serotypes. For example a latex particle agglutination test has been developed to specifically identify cultured Salmonella Enteritidis (Thorns et al., 1994). This test is based on the use of two monoclonal antibody-coated latex reagents, one of which detected the recently discovered SEF14 fimbriae expressed predominantly by S. Enteritidis and S. Dublin organisms, while the second reagent detected the H0 p0 antigen of S. Dublin flagella. In a series of field trials 141 out of 142 strains of S. Enteritidis from 18 phage types were correctly identified by the latex test. A further 175 Salmonella isolates representing 35 serotypes were tested and only two false positives (S. Dublin) in the latex test were recorded. This test represents one of the first rapid serotype specific tests to be developed for S. Enteritidis and highlights the potential advantage of using fimbrial antigens as novel diagnostic antigens of the future.


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In addition to using latex agglutination tests for screening purposes, one commercial kit (Spectate), developed by R-Biopharm Rhoˆne Ltd, also establishes which Salmonella serogroup the isolate belongs to, using a combination of coloured latex particles. The kit consists of two reagents each being a mixture of red, blue and green latex particles. In the first reagent the red latex particles have an antibody attached which is specific to group B salmonellas and in the second reagent the red latex is specific to the Salmonella Vi antigen. With two reagents and three coloured latex particles targeted at different antigens, this test is able to identify serogroups B, C, D, E or G and the Vi antigen. This test can be used directly on colonies and also on broth cultures, although the latter requires heat treatment to remove any capsular material that could potentially mask any underlying antigens from detection. Although limited to a narrow range of serogroups, this test has been shown to provide a useful confirmation step using heat treated aliquots remaining from samples tested by ELISA (Cheesbrough and Donnelly, 1996). In addition to the bacteria mentioned above, latex agglutination tests have been developed for a wide range of organisms of clinical importance. For the food microbiologist rapid latex agglutination tests offer a convenient and quick method of screening suspect isolates. However, in addition to using latex agglutination as a method of screening and confirming certain organisms, techniques have also been developed for detection of a range of important toxins in foods.

10.4.2 Agglutination tests for the detection of toxins Although it is important to be able to detect and confirm the presence of a particular toxin-producing pathogen in a food, it may on some occasions be more appropriate to detect the toxin. This is especially true if the food being tested has undergone cooking and the toxin responsible for food poisoning is heat stable. A good example is S. aureus enterotoxins (SET) which can remain active in a food even after heat treatment, even though the numbers of viable cells of S. aureus have been substantially reduced or completely destroyed. In this situation, an enumeration test for S. aureus would not reveal the risk associated with the food. If a microbiologist does suspect previous contamination, either because the food has been implicated in a case of food poisoning showing characteristic symptoms associated with toxins, or if viable S. aureus cells are present in the food post cooking, detection of the toxins would be an important test to perform. Furthermore, confirmation of a particular toxin also provides further evidence of the disease causing potential of an isolate and in some cases the test may be an integral part of the confirmation procedure. An example would be confirmation of the toxins produced by verocytotoxin producing E. coli including E. coli O157. This group of pathogenic E. coli are characterised by their ability to produce two distinct toxins termed verocytotoxins (VT1 and VT2), which are otherwise known by the term shiga toxins (ST1 and ST2). In

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this situation these pathogens cause disease by infection and although the toxins play a role in pathogenesis, the toxins alone are not responsible for the symptoms, unlike toxins produced by other organsisms such as S. aureus, Bacillus cereus and Clostridium botulinum. Recently it has become increasingly popular to detect specific toxin genes in a culture or an enriched food sample using molecular techniques such as the polymerase chain reaction (PCR). However, there is a range of commercial kits that use latex particles coated with antibodies to detect toxins. Unlike traditional agglutination tests which rely on the interaction between soluble antibody and a particulate antigen such as a bacterial cell, resulting in visual clumping, these tests rely on antibody attached to an inert carrier such as latex particles. The latex particles in this technique are described as passive because they do not play an active role in the antibody-antigen reaction. If the target antibody is present in solution it will bind to the antibodies attached to the latex particles, resulting in the formation of a lattice structure due to cross-linking of particles, which is visible to the naked eye as agglutination. The test is performed in V-well microtitre plates and results are available after 20 to 24 h incubation at room temperature. If the target antigen is absent or below the detection limit of the test, the lattice structure does not form and the coated latex particles collect in the base of the well resulting in a tight ‘button’ of latex particles. Oxoid Ltd provides a range of RPLA kits for the detection of different toxins. Kits that are appropriate for testing foods include the SET-RPLA kit that detects staphylococcal enterotoxins A, B, C and D, and the BCET-RPLA which detects Bacillus cereus enterotoxin (diarrhoeal type). The VTEC-RPLA, which detects VT1 and VT2 individually, is another kit that can be used on sample filtrates or more commonly on cultures to confirm VT. A similar kit (VTEC Screen) produced by Denka Seiken, Japan detects both VT combined and can be used to test food samples directly following enrichment in appropriate media and subsequent toxin extraction procedures. These kits provide rapid and convenient methods of detecting toxins, which for B. cereus diarrhoeal toxin and VT traditionally rely on cell cytotoxicity assays. However, whilst RPLA provides a rapid and convenient test format, cell cytotoxicity assays are generally more sensitive, requiring less toxin for cell death compared with the amount required for a positive RPLA result. This finding has been reported for both the BCET RPLA test (Fletcher and Logan, 1999) and VTEC Screen (Chart et al., 2001). However, for VT testing, the RPLA tests provide a rapid and easy to use alternative to the Vero cell assay. For the rapid screening and identification of VTEC the VTEC-RPLA (Oxoid Ltd) has been combined successfully with a plating method for the detection of entrohaemolysin (Beutin et al., 1996). More recently, the VTEC Screen (Denka Seiken) has been used with a method of identifying heat-labile enterotoxinproducing E. coli to enable rapid screening for VTEC and provision of results within a working day (Bettelheim, 2001).


10.5

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Future trends

Over the past three decades immunological methods have become widely accepted and used for detection of specific pathogens in foods. The ELISA has become a common format for detection methods and there are now a plethora of commercial kits available to choose from. In recent years, greater automation of ELISA tests and fully automated systems such as VIDAS have become increasingly popular. With automation comes the added benefit of reducing hands-on time and freeing up staff for other duties or enabling fewer staff to run high numbers of tests. By comparison immunochromatography methods, particularly LFDs, have gained in popularity because of their simple format which requires no additional equipment to perform or interpret these tests. This is particularly attractive to smaller laboratories or those that perform pathogen testing infrequently. The use of immunological methods for confirmation of isolates is not a new concept either, and, in addition, the use of labelled antibodies, particularly latex particles, has become a widespread format for rapid agglutination tests. However, whilst antigen–antibody reactions provide a relatively high degree of specificity, there can be other organisms besides the target organism that share similar antigenic structures. Consequently both detection methods and agglutination tests can give rise to false positive results. For this reason, samples giving positive results with detection tests are still regarded as presumptive and are confirmed using conventional culture procedures. Agglutination tests are used together with other characterisation tests to aid identification of suspect isolates. More recently there has been a larger uptake of molecular methods which offer greater specificity and rapidity compared with many immunological methods. Lack of knowledge of these techniques, the need for trained staff and the expense of these tests still restrict their uptake. Moreover, tests such as PCR still require sufficient numbers of target cells to obtain a positive result, which still makes them dependent on cultural enrichment, and the food matrix interference can affect these tests. Despite molecular techniques becoming more user-friendly, there are still advances with tests that rely on antigen–antibody reactions. To start with, many manufacturers have increased the range of organisms detected by a particular assay. More recently, Merck KGaA has increased its Singlepath range of LFDs to include pathogenic Campylobacter species and they have just developed an LFD called Duopath that detects both verocytotoxins VT1 and VT2 (Fig. 10.2). In addition to increasing the range of target analytes detected, researchers have also looked at ways of combining lateral flow with other technologies. These include combining lateral flow immunoassay with amperometry and hydrogen peroxide consumption to enable the sensitive detection of low numbers of microorganims (Cowell et al., 2002) and detection of the protozoan Cryptosporidium parvum using lateral flow chromatography combined with reverse transcription PCR (Kozwich et al., 2000). There has also been a move towards improving the sensitivity and

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interpretation of lateral flow devices using paramagnetic particles instead of latex particles or colloidal gold (LaBorde and O’Farrell, 2002). Perhaps the one area of biology that has been advanced further by molecular biology than any other is identification and classification of microorganisms. Although immunological methods such as agglutination tests are useful for screening and aiding identification of isolates, molecular methods such as PCR and nucleic acid probes provide greater discrimination and accuracy. Moreover, the increased activity in the field of genomics and bioinformatics has had a huge impact on the understanding of microbial evolution and classification. DNA and microarrays have become increasingly popular for screening isolates for virulence determinants and specific genes which can aid clinical diagnosis, and show great potential for improving the knowledge of the role of some organisms in pathogenesis. Agglutination tests, however, remain popular and one example of a change to the conventional format is the Dryspot range from Oxoid Ltd, which includes tests for S. aureus and E. coli O157. Whereas traditional agglutination tests rely on the antibodies and antigen being in suspension, the Dryspot range comprises sensitive blue latex reagents dried onto the surface of specially designed reaction cards or test sticks. The advantage of this format is the reduced risk of splashes and these kits have improved shelf-life stability and can be stored at room temperature. Despite this move towards molecular methods many techniques such as pulse field gel electrophoresis and ribotyping are still confined to specialist laboratories. Therefore, easy to use and rapid agglutination tests will remain popular tests in many routine food testing laboratories for the foreseeable future.

10.6


Publications • Baylis, C. L. (2000) Catalogue of Rapid Methods (Review No.1) Campden & Chorleywood Food Research Association. Comprehensive listing of rapid methods and test kits, including their validation status, test times and manufacturers details, including web site addresses. • (1994) Rapid Methods and Automation in Microbiology and Immunology (R.C. Spencer, E.P. Wright, S. W. B. Newsom, eds) Intercept Ltd, Andover. • IVD Technology Monthly journal for those interested in the development and manufacture of rapid methods and diagnostics tests. Many useful articles on LFDs, microarrays and biosensors. For direct access to the journal online and for additional information see www.devicelink.com/ivdt. Useful web sites • www. AOAC.org


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Full details on the Institute and its validation schemes, including listings of approved kits • www.devicelink.com/ivdt Information and news for those interested in the development and manufacture of rapid methods, including LFDs, microarrays, DNA chip technology and other diagnostics technologies. Web site addresses for rapid method companies BioControl Systems Inc.: www.rapidmethods.com bioMe´rieux: www.biomerieux.com Binax Inc: www.binax.com Becton Dickinson: www.bd.com Celsis Ltd: www.celsis.com Denka Seiken Co. Ltd: www.denka-seiken.co.jp Merck KGaA: www.merck.de/microbiology Neogen Corp: www.neogen.com Oxoid Ltd: www.oxoid.com R-Biopharm Rhoˆne Ltd: www.r-biopharmrhone.com

10.7

References

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and KERR, D. E. (2000). ‘Equivalence of Visual Immunoprecipitate Assay (VIP) for Salmonella for the detection of motile and nonmotile Salmonella in all foods to AOAC culture method: collaborative study’. Journal of AOAC International 83(4), 888–902. FLETCHER, P. and LOGAN, N. A. (1999). ‘Improved cytotoxicity assay for Bacillus cereus diarrhoeal enterotoxin’. Letters in Applied Microbiology 28(5), 394–400. GANGAR, V., CURIALE, M. S., D’ONORIO, A., SCHULTZ, A., JOHNSON, R. L. and ATRACHE, V. (2000). ‘VIDAS enzyme-linked immunofluorescent assay for detection of Listeria in foods: collaborative study’. Journal of AOAC International 83(4), 903–18. GRIF, K., DIERICH, M. P. and ALLERBERGER, F. (1998). ‘Dynabeads plus 3M Petrifilm HEC versus Vitek Immunodiagnostic Assay System for detection of E. coli O157 in minced meat’. Letters in Applied Microbiology 26(3), 199–204. HSUEH, P. R., TENG, L. J., YANG, P. C., PAN, H. J., CHEN, Y. C., WANG, L. H., HO, S. W. and LUH, K. T. (1999). ‘Dissemination of two methicillin-resistant Staphylococcus aureus clones exhibiting negative staphylase reactions in intensive care units’. Journal of Clinical Microbiology 37(3), 504–9. JAY, J. M. (2000). Modern Food Microbiology. Gaithersburg, Aspen Publishers, Inc. JONES, K. D. (1999a). ‘Troubleshooting protein binding in nitrocellulose membranes. Part 1: Principles’. IVD Technology 5(2), 32–41. JONES, K. D. (1999b). ‘Troubleshooting protein binding in nitrocellulose membranes. Part 2: Common problems’. IVD Technology 5(3), 26–35. JONES, K. L., MACPHEE, S., TURNER, A. J. and BETTS, R. P. (1995). An evaluation of the Oxoid Listeria rapid test (incorporating Clearview) for the detection of Listeria from foods, Campden & Chorleywood Food Research Association, R&D Report 19. KERDAHI, K. F. and ISTAFANOS, P. F. (2000). ‘Rapid determination of Listeria monocytogenes by automated enzyme-linked immunoassay and nonradioactive DNA probe’. Journal of AOAC International 83(1), 86–8. KOZWICH, D., JOHANSEN, K. A., LANDAU, K., ROEHL, C. A., WORONOFF, S. and ROEHL, P. A. (2000). ‘Development of a novel, rapid integrated Cryptosporidium parvum detection assay’. Applied and Environmental Microbiology 66(7), 2711–17. LABORDE, R. T. and O’FARRELL, B. (2002). ‘Paramagnetic-particle detection in lateral flow assays’. IVD Technology 8(3), 36–41. LUIJENDIJK, A., VAN BELKUM, A., VERBRUGH, H. and KLUYTMANS, J. (1996). ‘Comparison of five tests for identification of Staphylococcus aureus from clinical samples’. Journal of Clinical Microbiology 34(9), 2267–9. MEATHREL, W. G., HAND SNR, H. M. and SU, L. H. (2001). ‘The effects of hydrophilic adhesives on sample flow’. IVD Technology 7(6), 56–66. PERRY, M. B. and BUNDLE, D. R. (1990). ‘Antigenic relationships of the lipopolysaccharides of Escherichia hermannii strains with those of Escherichia coli O157:H7, Brucella melitensis, and Brucella abortus’. Infection and Immunity 58(5), 1391–5. PERSONNE, P., BES, M., LINA, G., VANDENESCH, F., BRUN, Y. and ETIENNE, J. (1997). ‘Comparative performances of six agglutination kits assessed by using typical and atypical strains of Staphylococcus aureus’. Journal of Clinical Microbiology 35(5), 1138–40. FELDSINE, P. T., MUI, L. A., FORGEY, R. L.

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species in foods and environmental samples’. Microbiology Europe 2(5), 18–21. and CAPPS, K. (2000). ‘Validation of a method for the detection of E. coli O157:H7 in foods’. Food Control 11, 85–95. SMOLE, S. C., ARONSON, E., DURBIN, A., BRECHER, S. M. and ARBEIT, R. D. (1998). ‘Sensitivity and specificity of an improved rapid latex agglutination test for identification of methicillin-sensitive and -resistant Staphylococcus aureus isolates’. Journal of Clinical Microbiology 36(4), 1109–12. SOWERS, E. G., WELLS, J. G. and STROCKBINE, N. A. (1996). ‘Evaluation of commercial latex reagents for identification of O157 and H7 antigens of Escherichia coli’. Journal of Clinical Microbiology 34(5), 1286–9. STEPHENS, P. J., JOYNSON, J. A., DAVIES, K. W. and HOLBROOK, R. (1997). ‘The use of an automated growth analyser to measure recovery times of single heat-injured Salmonella cells’. Journal of Applied Microbiology 83, 446–55. THORNS, C. J., MCLAREN, I. M. and SOJKA, M. G. (1994). ‘The use of latex particle agglutination to specifically detect Salmonella enteritidis’. International Journal of Food Microbiology 21(1–2), 47–53. THRELFALL, J., WARD, L. and OLD, D. (1999). ‘Changing the nomenclature of salmonella’. Communicable Disease and Public Health 2(3), 156–7. VAN GRIETHUYSEN, A., BES, M., ETIENNE, J., ZBINDEN, R. and KLUYTMANS, J. (2001). ‘International multicenter evaluation of latex agglutination tests for identification of Staphylococcus aureus’. Journal of Clinical Microbiology 39(1), 86–9. VAZ-VELHO, M., DUARTE, G. and GIBBS, P. (2000). ‘Evaluation of mini-VIDAS rapid test for detection of Listeria monocytogenes from production lines of fresh to cold-smoked fish’. Journal of Microbiological Methods 40(2), 147–51. VERNOZY-ROZAND, C., MAZUY, C., RAY-GUENIOT, S., BOUTRAND-LOEI, S., MEYRAND, A. and RICHARD, Y. (1997). ‘Detection of Escherichia coli O157 in French food samples using an immunomagnetic separation method and the VIDAS E. coli O157’. Letters in Applied Microbiology 25(6), 442–6. VERNOZY-ROZAND, C., MAZUY, C., RAY-GUENIOT, S., BOUTRAND-LOEI, S., MEYRAND, A. and RICHARD, Y. (1998). ‘Evaluation of the VIDAS methodology for detection of Escherichia coli O157 in food samples’. Journal of Food Protection 61(7), 917– 20. SCOTTER, S., ALDRIDGE, M.

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11 Immunological techniques: ELISA J. McCarthy, Unilever R&D Colworth, UK

11.1

Introduction

Conventional cultural methods used for detecting microorganisms in foods are well established, simple, inexpensive and can be used in both quantitative or qualitative testing. However, there are some disadvantages to using conventional methods, particularly when applied to pathogen detection. These methods rely on the growth of the target microorganisms in one or more nutrient media, detection of growth by visual assessment and confirmation of the presence of a pathogen, usually involving a combination of biochemical and serological tests. The various stages can be extremely labour intensive, interpretation of results subjective and for some pathogens, the total test time can be many days. A typical protocol for the detection of Salmonella in foods involves incubation of the food homogenate in a non-selective pre-enrichment broth (20 h), transfer and incubation in two separate selective broths (24 h), isolation on selective agars (24 or 48 h), followed by visual assessment and purification of presumptive positive colonies on non-selective agars (24 h). Shorter test times and reduced labour requirements can be achieved by adopting alternative or rapid methods. In recent years, there have been remarkable advances in rapid methodology, and improvements in the performance, quality and commercial availability of these methods has led to them being widely adopted and accepted. Presently, rapid methods cannot completely replace conventional methods and in pathogen detection they are usually adopted to replace one stage of the total isolation, detection or identification procedure, resulting in conventional and rapid methods being used in combination. The term ‘rapid methods’ encompasses numerous technologies including those based on microscopy, measurement of adenosine triphosphate (ATP),

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monitoring of metabolic activity by electrical measurement, nucleic acids and immunology. Also referred to as immunoassays or antibody-based, immunological methods form the basis of a range of tests that can be applied to the detection of foodborne pathogens, determination of the species of origin of meat and identifying chemical contaminants and toxins. The enzyme-linked immunosorbent assay (ELISA) is a widely used immunological-based assay for the detection of foodborne pathogens. The technique is designed to replace the detection or isolation stage on agar; it is relatively easy to perform, can be applied to a range of pathogens, can be semiautomated and gives a rapid result. The scope of an ELISA can be designed to detect a genus, species or serotype. However, a positive result obtained by an ELISA is presumptive and must be confirmed using conventional tests. The greatest advantage of this technique therefore is in negative screening and including an ELISA test in a microbiological detection procedure has potential to greatly increase the number of samples per day which can be screened for the presence of a particular pathogen, assuming there are acceptable levels of false negative results. In this chapter, an overview of the principles of the technique, examples of different types of ELISA, examples of commercially-available kits and some advantages and disadvantages of using the technique are discussed.

11.2

The basic principles of an ELISA

11.2.1 Antibodies and antigens All immunological techniques utilise the highly specific binding reaction between antibodies and antigens, and this interaction is also the key to an ELISA. Antibodies are proteins produced by the white blood cells of animals that have been invaded by a foreign molecule or microorganism. Antibodies attach to areas on the invading foreign body referred to as antigens. This attachment is highly specific and immunological tests exploit this phenomenon to detect specific microorganisms, proteins or toxins. Two types of antibody can be used in an ELISA; monoclonal and polyclonal. If the invading foreign body is a large molecule, such as a protein or microorganism, there can be many different antigenic sites and polyclonal antibodies are produced during the immune response of the host. Monoclonal antibodies are produced using tissue culture techniques, procured from a single antigenic site, using a single white blood cell.

11.2.2 Labels In order to determine if any binding between antibody and antigen has taken place, a system for visualising or measuring the interaction is required. To achieve this, a ‘label’ is attached to the antibody. Labels can be of various types including fluorescent agents, luminescent chemicals, radioisotopes or enzymes. In an ELISA, the term ‘enzyme-linked’ indicates the labelling system is enzyme

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mediated. In most systems, the enzyme catalyses the conversion of a colourless substrate, resulting in a coloured product. The endpoint of the test can then easily be visualised by eye or by a spectrophotometer, depending on the type of test. Typical enzyme-substrate complexes used in ELISAs include alkaline phosphatase (enzyme) with para-nitrophenyl phosphate (substrate) and horseradish peroxidase (enzyme) with tetramethylbenzidine (substrate); both complexes produce a yellow coloured product.

11.2.3 Solid supports The reactions that take place during an ELISA require some form of physical, solid support. In the acronym ELISA, the term ‘immunosorbent’, implies that antibodies are absorbed onto a surface. Microtitre plates are most commonly used primarily because they are convenient, cheap to produce and allow for high numbers of tests per assay, having 96 wells per plate. Other solid supports used include paper membranes and polystyrene dipsticks.

11.3

ELISA formats

The first stage of an ELISA involves coating a solid support with specific antibodies or antigens. If the assay uses a static support, e.g. microtitre plate, the test sample and various reagents are added to the well in a series of multiple stages throughout the procedure. With dipstick formats, the principle of coating a solid phase with antibodies to the target antigen is again used, however, with these tests, the solid phase is designed to be transferable. The format is often a paddle or elongated stick; hence the term ‘dipstick’. With these devices, it is possible to transfer any captured antigens into different media to enhance growth thereby increasing target cell numbers. When transferred to a solution of substrate, the enzyme label, attached to the dipstick, causes it to change colour.

11.3.1 Sandwich ELISAs The sandwich ELISA has the simplest format and is most commonly used in commercially-available kits. The word ‘sandwich’ indicates that the assay uses two antibodies which trap or sandwich the target antigen. During the procedure, the antigen is first captured then detected. The capture antibody, specific to the target antigen, is attached to the surface of the solid support, e.g. microtitre well. An enriched food sample is added to the well and if the target antigen is present, it will bind to the antibodies. After a washing procedure, to remove food debris and unbound material, a second ‘detection antibody’ is added to the well. This antibody has an enzyme label attached. Again, the antibody will bind to the target antigen creating the ‘antibody sandwich’. More washing procedures are carried out to remove any unbound antibodies, followed by the addition of a colourless substrate which the enzyme converts to a coloured product. Finally, a

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stop solution is added to prevent any further enzyme activity and any change in colour is measured. The total test time for a sandwich ELISA is typically between two and three hours. It is possible to use this format in quantitative tests by calibrating the concentration of antigen against colour intensity. In the detection of foodborne pathogens, however, the sandwich ELISA is usually used for qualitative purposes, indicating the presence or absence of a pathogen. All sandwich ELISAs require an enriched food sample as a starting point. The enrichment procedure depends on the food type and pathogen being detected. The main stages involved in a sandwich ELISA are shown in Fig. 11.1.

Fig. 11.1

The main steps of a sandwich ELISA.


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11.3.2 Indirect sandwich ELISA In the indirect sandwich ELISA, the detection antibody does not carry the enzyme label. These antibodies carry a marker molecule which will specifically bind to another molecule, e.g. a protein. Biotin is often used as a marker with avidin as the protein binding site. The result is a biotin-avidin, enzyme labelled antibody. This enzyme will again catalyse the conversion of a colourless substrate to a coloured product.

11.3.3 Competitive ELISA In this format, the test well is coated with antigen, rather than antibody. The sample and labelled antibodies are then added to the test well simultaneously. If target antigens are not present in the sample, the labelled antibodies will bind to the antigen coated on the wells. When the substrate is added, the enzyme will catalyse a colour change as in the sandwich ELISA. However, if target antigens are present in the sample, the antibodies will bind with them, in addition to those attached to the well. During the washing stage, any antibody-antigen complexes in solution are removed. Therefore, any change in colour at the end of the test is due solely to the antibody-antigen complex on the surface of the well. The intensity of the endpoint colour will therefore be low. If the level of antigen in the sample is high, more antibodies will bind in solution, resulting in fewer antibodies available to bind to the surface of the well. In these circumstances, the endpoint will be an extremely weak colour or colourless. The competitive ELISA gives a reverse result to the sandwich, in that a coloured product indicates a negative result and a colourless (or weak coloured) product indicates a positive result. Competitive ELISAs can be direct or indirect, as in the sandwich format and can also be used in quantitative tests by calibration of antigen concentration against colour intensity. This type of ELISA is often used to detect small molecules that may not easily be detected using the sandwich format, which requires two binding sites. The main stages involved in the competitive ELISA are given in Fig. 11.2.

11.4

Commercially-available ELISAs

Numerous ELISA kits for the detection of a wide range of foodborne pathogens, including Salmonella spp., Listeria spp., Escherichia coli O157:H7, Campylobacter spp., staphylococcal enterotoxins, Bacillus diarrhoeal enterotoxin, verocytotoxins and Clostridium botulinum neurotoxins are now commercially available. The format of the kits varies but most are based on the sandwich ELISA using microtitre plates as the solid support. The design of the plates usually includes removable wells, allowing the user the flexibility to test for a desired number of samples without the need to use a complete 96 well plate each assay. Kits are typically provided with the solid support pre-coated with capture antibodies against a specific pathogen, wash concentrates, freeze-dried

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Fig. 11.2

The main steps of a competitive ELISA.

labelled detection antibodies (also referred to as conjugate), freeze-dried substrate, various diluents together with positive and negative controls. The endpoint of some systems can be measured by eye, assessing the degree of colour change against a colour chart, while others require the use of a spectrophotometer or microtitre plate reader. The washing steps are crucial in an ELISA and some manufacturers recommend the use of an automated microtitre plate washer. Few kits are suitable for manual washing (e.g. using a wash bottle) and in those that are, this stage needs to be carried out with great care. The automation of ELISAs has developed rapidly in recent years. Some systems are simply automated versions of the standard microtitre plate format, incorporating robotics for dispensing reagents and automated washing and reading


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procedures. These types of systems require minimal manual input and are most suitable for high throughput screening. Other manufacturers have developed novel formats, and some have incorporated an additional immunological-based stage to increase the specificity of the test and reduce incubation time during the enrichment procedure. This additional stage is known as immunoconcentration or immunocapture and is a means of separating or capturing bacterial cells in culture. The principle is simple and, as in all immunological-based methods, involves antibodies binding to target antigens. A solid support is required and one frequently used is magnetic beads. The beads are coated with capture antibodies, mixed and incubated with the test culture, then collected by application of a magnetic field. Any target antigen binds onto the antibodies on the beads, resulting in them being concentrated and separated from the food matrix and competitive flora. Antigen in this concentrated format is then used as the starting point for an ELISA. Immunoconcentration is also incorporated into certain dipstick assays, with the solid support being the antibody coated dipstick itself. This also acts as the solid support during the ELISA. From the numerous commercial kits available, information on three is provided in this section. These are manufactured by TECRA, bioMe´rieux and Foss Electric. Each manufacturer produces kits for detection of more than one pathogen. Therefore, for the purposes of this chapter, the procedure for the detection of Salmonella is described for each. It should be noted that these methods were chosen purely as examples of typical kits with quite different formats and protocols, and not as any form of endorsement of one kit over another. A list of other commercially-available pathogen detection ELISA kits is provided in Table 11.1. Each kit listed offers certain advantages and disadvantages, depending on the individual user requirements. 11.4.1 TECRA UNIQUETM The TECRA UNIQUETM, is an example of a manual-based, dipstick format sandwich ELISA, that incorporates an immunocapture stage. The UNIQUETM kits are presently available for detection of Salmonella spp. and Listeria spp. Other kits, including those with a microtitre plate format, are available from this company and full details can be obtained from the manufacturer (Table 11.1). The main stages of the UNIQUETM Salmonella are outlined below: • A food sample is incubated in a pre-enrichment broth, for 16 h at 37ºC. • An aliquot of pre-enriched sample is then transferred to the first of six ‘test tubes’, housed in a self-contained module. Simultaneously, an antibodycoated, ‘paddle-shaped’ dipstick, is added to the first test tube. During a short incubation period (20 min), any salmonellae present in the sample are captured onto the surface of the dipstick. The dipstick is then transferred into tube two, which contains a wash solution. • The dipstick is washed by inverting the module several times. It is then transferred to tube three, which contains a nutrient medium.

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Table 11.1 Partial list of commercially-available ELISA for the detection of foodborne pathogens Organism or toxin

Trade name

Manufacturer

Bacillus cereus diarrhoeal enterotoxin

Bacillus diarrhoeal enterotoxin EiaFoss Camplylobacter VIA BoNT EHEC-TeK Assurance E. coli O157 VIA Premier O157 E. coli O157:H7 E. coli Rapitest Transia card Premier EHEC Ridascreen Verotoxin E. coli ST Listeria-TeK Listeria VIA UNIQUE Listeria Assurance Transia Listeria Pathalert EiaFoss Salmonella-TeK Salmonella VIA UNIQUE Salmonella EQUATE BacTrace LOCATE Assurance Salmonella Transia Bioline S. aureus VIA SET-EIA Staphylococcal Enterotoxin VIA Transia SE RIDASCREEN

TECRA

Campylobacter Clostridium botulinum neurotoxin Escherichia coli O157

Shiga toxin Listeria

Salmonella

Staphylococcus aureus staphylococcal enterotoxin

Foss Electric TECRA Rhoˆne-diagnostics bioMe´rieux BioControl TECRA Meridian Binax Microgen Transia Meridian R-Biopharm Oxoid bioMe´rieux TECRA TECRA BioControl Transia Merck Foss Electric bioMe´rieux TECRA TECRA Binax KPL Rhoˆne-diagnostics BioControl GEM Biomedical Transia Bioline TECRA Toxin Technology TECRA Transia R-Biopharm

Adapted from Bacteriological Analytical Manual, Appendix 1 (2001)

• During a four-hour incubation in tube three, any captured salmonellae multiply. After incubation, the dipstick is transferred to tube four. • In tube four, the dipstick is incubated for 30 min in a solution of labelled detection antibodies. This is followed by transfer to a further wash solution in tube five.


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• The dipstick is again washed by inverting the module several times then transferred to a solution of substrate in tube six. • In tube six, after a 10 min incubation period, a presumptive positive result is expressed as a purple colour on the lower half of the dipstick. Negative and positive controls are built-in on the upper and lower ends of the dipstick. The total test time for this method is 22 hours. Any presumptive positive results must be confirmed as Salmonella using conventional methodology. All stages of the test are contained in the module, are extremely easy to perform and require minimal manual manipulations. However, this format is designed for low sample numbers and would not be suitable for high sample throughput. The UNIQUETM Salmonella test has been evaluated extensively against a variety of food types and overall results indicate at least equivalence to standard conventional methods (Hughes et al., 2001; de Paula et al., 2002).

11.4.2 Salmonella-Tek The Salmonella-Tek is manufactured by bioMe´rieux and uses a sandwich ELISA with microtitre plate format. This system can be used with or without an immunocapture stage, using magnetic beads (DynabeadÕ). Two different enrichment protocols are recommended for use with the Salmonella-Tek; one for samples expected to have low levels of competitive flora (e.g. processed foods) and one for samples with high levels of competitors (e.g. raw foods). Both procedures are shown in Fig. 11.3. The endpoint of both enrichment protocols is heat treated M broths (with novobiocin) and this is regarded as the starting point for the ELISA. The main stages of the Salmonella-Tek ELISA are outlined below. • An aliquot (100 l) of an enriched food sample (see Fig. 11.3) is added to a test well on the microtitre plate. This is then incubated for 30 min at 37ºC to allow any antigen to bind to the antibodies coated onto the surface of the well. • The wells are then washed six times in a wash solution followed by addition of 100 l of labelled detection antibodies. • The plate is then incubated for a further 30 min at 37ºC to allow these antibodies to also bind with the antigen. • After incubation, a further six washes are carried out. • After the second washing procedure, 100 l of substrate is added and the plate is incubated at 20–25ºC for 30 min. • After incubation, 100 l of a stop solution is added to each well and any colour change is measured using a microtitre plate reader. Negative and positive controls are provided with the kit and three wells must be allocated for their use, each time an ELISA is carried out. The test time for the ELISA is approximately two hours but the total test time, including the enrichment procedure, is approximately 46 and 52 hours for

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Fig. 11.3 Procedures recommended for use with the Salmonella-Tek ELISA.


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processed and raw foods, respectively. Any positive Salmonella-Tek ELISA results are presumptive and must be confirmed using standard methods. The total test time for the Salmonella-Tek can be reduced by including an immunocapture stage using DynabeadsÕ. The trade name of the combined immunocapture and ELISA system is Salmonella Capture-TekTM. The starting point for this is a pre-enriched food sample which has been incubated in a suitable pre-enrichment broth, for a minimum of 16 h at 37ºC. An aliquot (1 ml) of this is mixed in a capture tube with a solution of DynabeadsÕ for 10 min. During this period, any salmonellae present are captured by the antibodies coated onto the surface of the beads. The capture tube is placed into a magnetic particle concentrator allowing the beads to be immobilised and washed. The beads are then incubated in M-broth for five hours before being heat treated. The heated M-broth (containing the beads) is then used as the starting point for the Salmonella-Tek ELISA. By including this immunocapture stage, the total test time is reduced to approximately 24 hours for both processed and raw foods. Again, any positive results are presumptive and require confirmation. bioMe´rieux also manufacture kits for the detection of Listeria spp. (ListeriaTek) and E. coli O157 (EHEC-Tek). The Salmonella-Tek and Salmonella Capture-Tek have both shown good correlation with conventional methods having been evaluated against a range of food types by different workers (Chapman and Siddons, 1996; Eckner et al., 1994; Tveld and Notermans, 1992). These ELISAs are comparatively labour intensive, having numerous pipetting stages and washing steps. However, the SalmonellaTek is suitable for high sample throughput and can be semi-automated.

11.4.3 EiaFoss The EiaFoss, manufactured by Foss Electric, is a fully automated ELISA system that incorporates an immunocapture stage using magnetic beads. Kits are available for the detection of Salmonella spp., Listeria spp., E. coli O157 and Campylobacter spp. The EiaFoss is novel in that the magnetic beads used for the immunocapture of the target antigen, also act as the solid support stage for the ELISA. All of the reactions take place inside an ‘assay tube’ and all transfers of reagents, washing steps, immobilisation of magnetic beads and reading of endpoints are carried out automatically by the EiaFoss analyser. The starting point of the EiaFoss Salmonella is an enriched food sample. Two EiaFoss Salmonella enrichment broths are available (SEB I and SEB II) the use of which depends on the food type. The incubation period is also dependent on the type of food, most foods requiring 24 h (at 37ºC), but for those which could contain injured cells or inhibitory substances, e.g. spices, 48 hours would be required. The test time of the automated ELISA is two hours resulting in a total test time of 24 hours for most foods. As with other ELISA kits, any positive results require confirmation using conventional tests. This system has been thoroughly evaluated against a variety of foods and results have been shown to correlate well with conventional methods (Kleiner

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and Weisswange, 2000; Masso and Oliva, 1997; Krusell and Skovgaard, 1993). Manual manipulation is minimal with the EiaFoss and as the system can test between one and 27 samples in each assay (or 108 per working day), it would be suitable for low and high sample numbers. The EiaFoss analyser can also be used with the Listeria, E. coli O157 and Campylobacter kits.

11.5

Advantages and disadvantages in using ELISAs

11.5.1 Sensitivity The sensitivity of most ELISAs is approximately 105 cells/ml. This relatively low sensitivity level is one of the main disadvantages to using these types of assays. A requirement for the food microbiologist is often to detect a single pathogen in a 25 g sample of food. It is therefore necessary to enrich the food sample prior to a detection method such as an ELISA. This enrichment stage is crucial and the performance of the ELISA is dependent on it. Not only is it necessary for the increase in target cell numbers, but also to reduce unwanted competitive flora, dilute any inhibitory substances that may be present in the food matrix and allow for the resuscitation of any injured cells. Cell injury can occur as a result of processes such as heating, freezing, low pH and chemical preservation. The ability of methods to detect sublethally injured cells is an important consideration in all pathogen methodology, but particularly in E. coli O157 and Campylobacter detection methods due to the potential low infectious dose of these organisms, thought to be as low as 109 copies in approximately 90 minutes. The reaction occurs isothermally at 41ºC so thermocycling equipment is not required. NASBA can be used to selectively amplify RNA sequences in the presence of DNA since DNA strands are not melted out, unlike RT-PCR.

12.2.1 Hybridisation Hybridisation is the process whereby single stranded nucleotides anneal together. The similarity of the two sequences determines their degree of hybridisation. Membrane-based hybridisation methods were developed in the late 1980s and remain a standard method for the detection and quantification of nucleic acids. Two different but similar protocols, Northern blotting and Southern blotting, are used depending on whether DNA or RNA is being analysed. Both procedures involve separating the nucleic acid by electrophoresis. This is then transferred to and immobilised on a support membrane (e.g. nitrocellulose or nylon). The membrane is probed with a labelled probe to detect the sequences of interest. After detection, the nucleotides that have hybridised to the labelled probe are revealed as bands. Hybridisation can also be assayed in solution, thereby avoiding the timeconsuming steps of gel electrophoresis and membrane transfer and probing. Solution hybridisation colorimetric endpoint detection (PCR ELISA) facilitates the specific and sensitive detection of PCR amplification products.

262


12.2.2 Microarrays Microarrays or gene chips provide a miniaturised system for the simultaneous analysis of hybridisation to an array of oligonucleotide probes immobilised on a support such as glass or a synthetic membrane. The format enables the analysis of a large number of genetic features in a single hybridisation experiment. Microarrays are a powerful tool for the quantitative study of gene expression and are increasingly being considered as a tool for detecting and describing complex microbial communities.

12.3

Key principles

12.3.1 Probe and primer design The primary requirement for a probe or primer pair is that it is specific for the organism(s) of interest. That is that the gene sequence is only found in the target, and under the assay conditions the probe or primer pair does not give nonspecific reactions. It is difficult to generalise about the choice of target sequence since it depends so much on the target organism. In general the choice of a nucleotide sequence present on extrachromosomal DNA or mobile elements would not be recommended due to the increased possibility of lateral gene transfer to other microorganisms (false positive results) and the possibility of false negative results from isolates that had lost the target sequence. Pathogenicity determinants e.g. toxin genes are an obvious choice as targets since they are often well characterised and are a diagnostic feature of the pathogen. However, not all pathogenic determinants are restricted to a particular genus or species. A large number of PCR assays have been developed for the detection of E. coli O157:H7 based on conserved regions of shiga toxin (stx1 and stx2) and intimin (eaeA) genes, yet these genes are not unique to serotype O157:H7 (Chizhikov et al., 2001). Indeed there have been some reports of shiga toxin-like genes in non-enterics such as Aeromonas (Haque et al., 1996) and that not all serotype O157:H7 isolates contain these genes (Galland et al., 2001). Genes used as molecular taxonomic markers (see Chapter 13) such as ribosomal DNA genes (Tsen et al., 2000) and DNA gyrase (Venkateswaran et al., 1998) have also been used as targets for probe and primer pair design. These genes are particularly suitable for detecting pathogens were pathogenicity is species specific. While some pathogens can be detected on the basis of a single nucleotide sequence, detection of pathogens with a complex pathotype or that are genetically similar to other pathogens, such as the pathotypes of E. coli or serovars of Salmonella, require complex assay procedures such as multiplex PCR or microarray analysis of both general pathogenic determinants and serotype or strain specific determinants (Chizhikov et al., 2001). Increasingly, comparison of genomic data or detailed subtractive hybridisation studies are being used to identify novel genes for the detection of pathogens. In addition to providing new targets, such as the single locus that appears to be restricted to

Genetic techniques: PCR, NASBA, hybridisation and microarrays

263

Salmonella enterica Serovar Enteriditis (Agron et al., 2001), they also offer a more rational strategy for the choice of target sequences.

12.3.2 Extraction and isolation of DNA from food The usefulness of molecular methods may be limited by the presence of substances that inhibit the reactions (Lantz et al., 1994). A wide variety of foods and compounds present in foods have been reported to inhibit PCR reactions including collagen, heme, acidic polysaccharides, humic substances, cheese and bean sprouts (Lantz et al., 1994; Kim et al., 2000). Some of these compounds co-purify with the DNA so extensive DNA purification may be required before samples can be assayed. Separation of the pathogens from the food matrix prior to DNA isolation should prevent the carry-over of inhibitors into the reaction since these compounds are associated with the food matrix. Many methods of physical separation have been described including centrifugation, filtration, ion exchange resins and immunomagnetic separation. While these methods improve the sensitivity of detection, none has broad applicability for all foods and the methods need to be optimised for each product or product/pathogen combination (Lantz et al., 1994; Lucore et al., 2000). Simple physical separation or direct DNA extraction often lacks the sensitivity required to detect low numbers of pathogens in food samples. A brief cultural enrichment, followed by physical separation of the organisms from the culture has the benefits of separating the pathogen from the food matrix, diluting the concentration of inhibitory compounds and increasing the number of the target organisms (Lucke and ten Bosch, 1998). This approach has been almost universally adopted, where it is applicable, due to the marked increase in sensitivity (from ca. 102–103 cells to 100–101) given by even a brief (6–12 h) enrichment. Clearly this is not possible for microorganisms that are difficult to cultivate or are nonculturable.

12.4

Applications for particular pathogens and foods

12.4.1 Viruses in seafood Contamination of shellfish growing/harvesting waters with sewage can result in shellfish accumulating human enteric viruses. As shellfish are often consumed raw or after minimal heat treatment, consumption of virus contaminated shellfish poses a hazard to human health. Viruses of particular concern are members of the family Caliciviridae (Norwalk-like or small round structured viruses and Caliciviruses) and hepatitis A virus. These viral enteric pathogens cannot be cultivated in vitro. Some other enteric viruses (rotavirus, enteric adenoviruses and certain astroviruses) can be cultured with some difficulty; however, diagnostic technology is insufficiently developed to permit their routine isolation (CDC, 1990). Molecular methods of detection are therefore the only available technique for detecting the presence of these viruses.

264


Reported levels of shellfish contamination are low, ranging from 0.3 to 200 plaque forming units (pfu) per 100 grams of shellfish (Sobsey et al., 1991; Rose and Sobsey, 1993). Early attempts to detect these RNA viruses were based on hybridisation with virus specific probes. However, the sensitivity of that approach (limit of detection 103–104 pfu) is not always able to detect the low concentration of virus particles typically found in shellfish (Jean et al., 2001; Romalde et al., 2002). Recent attention has focused on the development of RTPCR and NASBA-based assays. Detection is made difficult by the low concentration of virus and the presence of glycogen and acidic polysaccharides in shellfish that inhibit amplification. Detection protocols therefore rely on recovery of intact virus (e.g. by immunocapture) or virus RNA prior to amplification. In a comparison of seven methods for the extraction of hepatitis A virus from shellfish it was found that methods based on the extraction of RNA were the most effective and suitable for routine diagnostic testing (Arnal et al., 1999). Studies of the bioaccumulation of viruses by shellfish have shown that virus is accumulated in the digestive tract (stomach and hepatopancreas) of shellfish. Dissection and extraction of these tissues results in increased sensitivity of detection compared with extraction of whole shellfish (Romalde et al., 2002). After more than a decade of development current protocols provide rapid, robust, specific and sensitive detection of enteric viruses in shellfish. Two possible limitations of the techniques are that they cannot distinguish between infective and inactivated viruses and they are not quantitative. Although the infectious dose of these viruses is not known, it is thought to be as low as 10– 100 virions. Therefore detection of these viruses is of public health concern whether the amount can be quantified or not.

12.4.2 Listeria monocytogenes in food Listeria are widespread in nature and are commonly found in soil, vegetation and sewage. One species, Listeria monocytogenes, is a potentially lethal foodborne bacterial pathogen. It is often present in milk, meats, soft cheese, vegetables and seafood and has the potential to grow on such products even under proper refrigerated storage. Serotypes 1/2a, 1/2b and 4b constitute more than 95 per cent of human clinical isolates although a definitive pathotype has yet to be identified. Detection of L. monocytogenes in foods is complicated by the presence of the closely-related but non-pathogenic species L. innocua. Conventional species specific identification procedures are labour intensive and time-consuming. In addition isolates with major differences in the key biochemical criteria have been reported, making the utility of these tests uncertain (Bubert et al., 1999). Thus there is clear potential for the development of rapid molecular methods for the specific detection of L. monocytogenes. A variety of PCR assays have been developed for L. monocytogenes based on a number of genes. Most assays include a brief culture enrichment step to increase sensitivity and to remove compounds inhibitory to amplification. Soft


265

cheeses in particular pose difficulties because of inhibitors. The assays have demonstrated that L. monocytogenes can be detected in the presence of high numbers of other Listeria species (Stewart and Gendel, 1998). However, there is a potential problem with culture enrichment prior to PCR as L. innocua can suppress the growth of L. monocytogenes during co-culture in commonly used enrichment media, which may result in false negative results (Norton et al., 2001). The presence of certain foods during enrichment may also inhibit the growth of L. monocytogenes. It has been reported that the minimum level at which L. monocytogenes spiked onto carrots could be detected was 100-fold higher than for other vegetables, presumably due to the presence, in the carrots, of substances inhibitory to the growth of Listeria (Shearer et al., 2001). Immunocapture has been used successfully to circumvent the need for culture enrichment but limits the possibilities for improving the sensitivity of the assay (Hudson et al., 2001) as the immunocapture step has a detection limit of approximately 102 organisms/ml (Oberst et al., 1998). In general molecular methods of detection show good correlation with conventional culture techniques and provide results in 1–2 days compared with 4–7 days for conventional methods.

12.5

Advantages and disadvantages

12.5.1 PCR PCR by itself is a way of amplifying a nucleotide sequence. Following amplification the presence of an amplicon still needs to be detected. The most commonly used research technique for this is gel electrophoresis which reveals the PCR products as bands on a gel. This does not show the specificity of the PCR product as it merely demonstrates whether a band of the expected size is obtained or not. The band could be due to a non-specific reaction product that happened to be the same size as the expected product. Hybridisation with diagnostic probes or sequencing are required to prove that the expected amplicon is obtained. Gel-based systems also lack sensitivity for detecting low levels of PCR product. Their advantages are that they are cheap to set up and run and can readily show the presence of unexpected bands.

12.5.2 Hybridisation Hybridisation is, in general, less sensitive and more time-consuming than amplification-based assays. An additional limitation of membrane hybridisation is the difficulty associated with multiple probe analysis. To detect more than one message, it is usually necessary to strip the initial probe before hybridising with a second probe. This process can be time-consuming and problematic, since harsh treatment is required to strip conventional probes from blots. The use of microarrays removes the need for reprobing as many targets can be detected at once. Microarrays are also suited for automation although at a higher capital cost.

266


12.5.3 Contamination Amplification techniques are susceptible to in-lab contamination with PCR amplicons resulting in false positive results. This is especially true for nested PCR due to the extra handling step between the two PCR reactions. This problem can be minimised by controlling the work flow so that sample preparation areas are physically separated from PCR and PCR product detection areas. An additional level of protection is provided by using dUTP rather than dTTP in the amplification reaction. Samples are pre-treated with uracil Nglycosylase (UNG) which specifically degrades nucleotides containing dUTP before amplification thereby removing any contaminants. The use of a heat labile UNG allows this to be done in the same tube as the PCR reaction itself (Schwab et al., 2001). As noted earlier, if an RT-PCR assay is designed to be specific for a RNA target then it is essential that no contaminating DNA is present in the sample as this will be amplified as well. Treatment with DNAase is normally sufficient to ensure samples are free of DNA. All RNA-based methods are susceptible to false negative results due to degradation of RNA during isolation. If RNA samples are even slightly degraded the quality of the data and particularly the ability to quantitate results are severely compromised. RNase-free reagents and techniques are essential and often a dedicated RNA work area is required. A further consideration for RNA-based microbial assays is that it is important that the target gene is either expressed constitutively or under those conditions present on the food or in the enrichment culture since, if the gene is not expressed, there will be no RNA to detect.

12.5.4 Viable and non-viable organisms One often cited disadvantage of molecular methods is their inability to discriminate between viable and non-viable cells. RNA-based methods are believed to be less prone to this disadvantage as RNA is quickly degraded upon the death of microbial cells. However, it has been reported that residual microbial DNA and mRNA could be detected by PCR and NASBA, respectively, for up to 30 h post-thermal death. The authors concluded that a single quantitative measurement based on nucleic acid amplification did not permit unequivocal determination of cell viability (Birch et al., 2001). In practice, the magnitude of the problem will depend on how the microbial cells were killed, the physical medium they are in and the number of dead cells present. Greater than 106 dead cells/25 g of sample was required to give a false positive result with the Probelia Salmonella kit (Fach et al., 1999) due to the enrichment stage which effectively dilutes this to ca. five dead cells per assay. Since most microbial assays include a culture enrichment stage the presence of low numbers of non-viable cells is unlikely to result in false positive results.


12.6

267

Examples of commercial kits

While there are many commercially available options for the basic components of molecular assays there are only a small number of complete molecular-based detection kits available commercially. Table 12.1 lists the most widely used of these kits. Three of the kits are PCR-based (Probelia, BAX and TaqManÕ) while the other is a hybridisation assay (Gene-Track). All kits rely on a culture preenrichment step. For the PCR based kits this is 16–24 h, while for the GeneTrack a 40–48 h enrichment is used. All the kits use ready-prepared reagents so there is minimal preparation required by the user. For Probelia, detection involves a colorimetric reaction in a microplate format following PCR. TaqManÕ and the automated BAX system are a microplate format that incorporates both PCR and detection in the same unit. BAX is also available as a manual system where results are obtained by gel electrophoresis of the PCR reactions. Gene-Track is based on a colorimetric detection system following hybridisation with labelled probes. There are no reports of comparisons between these systems with literature reports being confined to comparison of these assays with conventional culture (e.g. Oberst et al., 1998 TaqManÕ; Stewart and Gendel, 1998 BAX; Fach et al., 1999 Probelia). These reports show that with minor limitations these assays are comparable in sensitivity to culture-based methods. Although in one report it was noted that both BAX and culture assay were unable consistently to detect low numbers of E. coli O157:H7 from alfalfa sprouts (Shearer et al., 2001).

Table 12.1 Partial list of commercially available, nucleic acid-based assays used in the detection of foodborne bacterial pathogens Trade Name

Organism

Format

Manufacturer

BAX

E. coli O157:H7 L. monocytogenes Listeria spp. Salmonella

PCR

DuPont Qualicon http://www.qualicon.com/

Gene-Trak

L. monocytogenes Listeria spp. Salmonella

probe

Neogen Corporation http://www.neogen.com

Probelia

Campylobacter Listeria E. coli O157:H7 Salmonella

PCR

BioRad http://www.biorad.com

TaqManÕ

E. coli O157:H7 Salmonella

PCR

Applied Biosystems http://www.appliedbiosystems.com

268

12.7


Future trends

Molecular methods are available that enable the rapid, sensitive and cost effective detection of microbial pathogens in foods. These have been adopted quickly by the research community as the technology can easily be adapted and customised for particular research needs, resulting in a proliferation of different methods for the detection of particular pathogens based on different genes and different chemistries. This proliferation has probably been a detrimental factor slowing the adoption of molecular methods in diagnostic laboratories. Publication of a method in the scientific literature does not automatically make that method usable in a commercial setting. In this increasingly litigious world and in a climate where the presence of microbial pathogens in a product can be used as a barrier to trade, commercial laboratories are obliged to use standard, approved methods for detecting pathogens in food. Proliferation of methodologies does nothing to help standardisation. Lack of standardisation increases the difficulty of gaining approval from national regulatory bodies, the latter being a bottleneck for the adoption of any new technology or methodology. In contrast the availability of commercial molecular-based kits for the detection of microbial pathogens should facilitate the adoption of this methodology in commercial laboratories as the manufacturers have already established them as standard methods and in many cases gained acceptance from some national regulatory bodies. Future trends in the development of molecular methods will be focused on improving the sensitivity of direct detection without the requirement for culture enrichment and on the simultaneous detection and identification of several pathogens. The latter will rely increasingly on microarray technologies which are becoming more commonplace in laboratories.

12.8

References

AGRON, P. G., WALKER, R. L., KINDE, H., SAWYER, S. J., HAYES, D. C., WOLLARD, J.

and (2001), ‘Identification by subtractive hybridization of sequences specific for Salmonella enterica serovar Enteritidis’, Applied and Environmental Microbiology, 67, 4984–91. ARNAL, C., FERRE´-AUBINEAU, V., BESSE, B., MIGNOTTE, B., SCHWARTZBROD, L. and BILLAUDEL, S. (1999), ‘Comparison of seven RNA extraction methods on stool and shellfish samples prior to hepatitis A virus amplification’, Journal of Virological Methods, 77, 17–26. BIRCH, L., DAWSON, C. E., CORNETT, J. H. and KEER, J. T. (2001), ‘A comparison of nucleic acid amplification techniques for the assessment of bacterial viability’, Letters in Applied Microbiology, 33, 296–301. BUBERT, A., HEIN, I., RAUCH, M., LEHNER, A., YOON, B., GOEBEL, W. and WAGNER, M. (1999), ‘Detection and differentiation of Listeria spp. by a single reaction based on multiplex PCR’, Applied and Environmental Microbiology, 65, 4688–92. CDC (1990), ‘Viral agents of gastroenteritis: public health importance and outbreak ANDERSEN, G. L.


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management’, Morbidity and Mortality Weekly Report, 39, 1–24. and LEVY, D. D. (2001), ‘Microarray analysis of microbial virulence factors’, Applied and Environmental Microbiology, 67, 3258– 63. FACH, P., DILASSER, F., GROUT, J. and TACHE, J. (1999), ‘Evaluation of a polymerase chain reaction-based test for detecting Salmonella spp. in food samples: Probelia Salmonella spp.’ Journal of Food Protection, 62, 1387–93. GALLAND, J. C., HYATT, D. R., CRUPPER, S. S. and ACHESON, D. W. (2001), ‘Prevalence, antibiotic susceptability, and diversity of Esherichia coli O157:H7 isolates from a longitudinal study of beef cattle feedlots’, Applied and Environmental Microbiology, 67, 1619–27. HAQUE, Q. M., SUGIYAMA, A., IWADE, Y., MIDORIKAWA, Y. and YAMAUCHI, T. (1996), ‘Diarrheal and environmental isolates of Aeromonas spp. produce a toxin similar to Shiga-like toxin 1’, Current Microbiology, 32, 239–45. HUDSON, J. A., LAKE, R. J., SAVILL, M. G., SCHOLES, P. and MCCORMICK, R. E. (2001), ‘Rapid detection of Listeria monocytogenes in ham samples using immunomagnetic separation followed by polymerase chain reaction’, Journal of Applied Microbiology, 90, 614–21. JEAN, J., BLAIS, B., DARVEAU, A. and FLISS, I. (2001), ‘Detection of hepatitis A virus by the nucleic acid sequence-based amplification technique and comparison with reverse transcription-PCR’, Applied and Environmental Microbiology, 67, 5593–600. KIM, S., LABBE, R. G. and RYU, S. (2000), ‘Inhibitory effects of collagen on the PCR for detection of Clostridium perfringens’, Applied and Environmental Microbiology, 66, 1213–15. LANTZ, P. G., HAHN-HAGERDAL, B. and RADSTROM, P. (1994), ‘Sample preparation methods in PCR-based detection of food pathogens’, Trends in Food Science and Technology, 5, 384–9. LUCKE, F. K. and TEN BOSCH, C. (1998), ‘Advantages of and limits to application of the polymerase chain reaction (PCR) to detection and typing of food-borne pathogenic bacteria’, Deutsche Lebensmittel-Rundschau, 94, 182–7. LUCORE, L. A., CULLISON, M. A. and JAYKUS, L. A. (2000), ‘Immobilization with metal hydroxides as a means to concentrate food-borne bacteria for detection by cultural and molecular methods’, Applied and Environmental Microbiology, 66, 1769–76. NORTON, D. M., MCCAMEY, M. A., GALL, K. L., SCARLETT, J. M., BOOR, K. J. and WIEDMANN, M. (2001), ‘Molecular studies on the ecology of Listeria monocytogenes in the smoked fish processing line’, Applied and Environmental Microbiology, 67, 198– 205. CHIZHIKOV, V., RASOOLY, A., CHUMAKOV, K.

OBERST, R. D., HAYS, M. P., BOHRA, L. K., PHEBUS, R. K., YAMASHIRO, C. T., PASZKO-KOLVA, C.,

and GILLESPIE, J. R. (1998). ‘PCR-Based DNA amplification and presumptive detection of Escherichia coli O157:H7 with an internal fluorogenic probe and the 5’ nuclease (TaqManÕ) assay’, Applied and Environmental Microbiology 64, 3389–96. FLOOD, S. J. A., SARGEANT J. M.

ROMALDE, J. L., AREA, E., SANCHEZ, G., RIBAO, C., TORRADO, I., ABAD, X., PINTO, R. M., BARIJA, J. L. and BOSCH, A. (2002), ‘Prevalence of enteroviruses and hepatitis A virus in bivalve molluscs from Galicia (Spain): inadequacy of the EU standards of microbial quality’, International Journal of Food Microbiology, 74, 119–30. ROSE, J. B. and SOBSEY, M. D. (1993), ‘Quantitative risk assessment for viral contamination of shellfish and coastal waters’, Journal of Food Protection, 56, 1043–50. SCHWAB, K. J., NEILL, F. H., LE GUYADER, F., ESTES, M. K. and ATMAR, R. L. (2001),

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‘Development of a reverse transcription-PCR-DNA enzyme immunoassay for detection of ‘Norwalk-like’ viruses and hepatitis A virus in stool and shellfish’, Applied and Environmental Microbiology, 67, 742–9. SHEARER, A. E. H., STRAPP, C. M. and JOERGER, R. D. (2001), ‘Evaluation of a polymerase chain reaction-based system for detection of Salmonella enteritidis, Escherichia coli O157:H7, Listeria spp., and Listeria monocytogenes on fresh fruits and vegetables’, Journal of Food Protection, 64, 788–95. SOBSEY, M., COLE, M. and JAYKUS, L. A. (1991) In Comprehensive Literature Review of Indicators in Shellfish and their Growing Waters (eds, Pierson, M. D. and Hackney, C. R.), Pierson Associates, Inc. STEWART, D. and GENDEL, S. M. (1998), ‘Specificity of the BAX polymersase chain reaction system for the detection of the foodborne pathogen Listeria monocytogenes’, Journal of AOAC International, 81, 817–22. TSEN, H. Y., CHEN, M. L., HSIEH, Y. M., SHEU, S. J. and CHEN, Y. L. (2000), ‘Bacillus cereus group strains, their hemolysin BL activity, and their detection in foods using a 16S RNA and hemolysin BL gene-targeted multiplex polymerase chain reaction system’, Journal of Food Protection, 63, 1496–502. VENKATESWARAN, K., DOHMOTO, N. and HARAYAMA, S. (1998), ‘Cloning and nucleotide sequence of the gyrB gene of Vibrio parahaemolyticus and its application in detection of this pathogen in shrimp’, Applied and Environmental Microbiology, 64, 681–7.

13 Genetic techniques: molecular subtyping methods C. Fitzgerald and B. Swaminathan, Centers for Disease Control and Prevention, USA and A. Sails, Newcastle General Hospital, UK

13.1

Introduction

The ability to discriminate or subtype foodborne pathogens below the level of species has been applied successfully to aid the epidemiological investigation of outbreaks of gastrointestinal disease. Reliable, sensitive and informative subtyping methods are required to recognize outbreaks of infection, match case isolates with those from potential vehicles of infection and discriminate these from unrelated strains. Sensitive and discriminatory subtyping methods also are required for surveillance programs to identify new or emergent strains or clones that may present a new risk to public health. These methods also are fundamental to epidemiological research projects to identify potential reservoirs of strains that cause disease in humans, identify routes of transmission and improve our understanding of the epidemiology of foodborne disease (Swaminathan et al., 2001). The criteria used to evaluate subtyping methods include: • typability: the ability of the method to produce an unambiguous result for all strains of a particular species • reproducibility: the ability of the method to produce the same result when a particular strain is tested repeatedly (this includes both intra- and interlaboratory reproducibility) • discriminatory power: how well the method discriminates between unrelated strains of the same species • ease of use: technical difficulty and expertise necessary to perform the test • ease of interpretation: how easily results can be interpreted and compared between laboratories • time and cost factors: time taken to obtain a result and the cost per isolate.

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In the absence of a definitive ‘gold standard’, new subtyping methods must be vigorously evaluated using sets of well-characterized isolates whose relatedness has been unequivocally determined previously. Phenotypic subtyping methods include biotyping, which discriminates between strains on the basis of specific biochemical reactions, and their ability to grow in the presence of certain chemicals, pH gradients, temperatures or gaseous atmospheres. Biotyping is often used to identify isolates to species level, but the method has poor discriminatory power and a limited ability to differentiate between isolates below the level of species. Serotyping, which is based on the reaction of antigenic determinants on the cell surface with specific antibodies or antisera, is relatively rapid and technically easy to perform, and is considered to be one of the classic tools for the epidemiological discrimination of organisms such as Salmonella, Escherichia coli and Listeria monocytogenes. Certain serotypes have well-established associations with particular clinical syndromes, such as the association between haemolytic-uremic syndrome and E. coli O157:H7. Phage typing is based on the presence or absence of a phage receptor on the exposed bacterial surface and has been used to subtype a number of foodborne pathogens, including Salmonella, L. monocytogenes, Campylobacter jejuni and E. coli O157:H7. For some organisms phage typing has poor reproducibility, and typability can range from good to moderate with significant numbers of strains lacking phage receptors and being untypable. Despite this, phage typing notably has been of value for the phenotypic characterization of S. Enteritidis, S. Typimurium and E. coli O157:H7. Phage typing also requires constant quality control of the phage suspensions and significant expertise to perform and interpret the results. These factors often limit its use to reference laboratories. Phenotypic methods such as serotyping and phage typing have been used effectively for the subtyping of many foodborne pathogens, and for some pathogens many years of historical data have been generated. However, these methods do have limitations. Many phenotypic methods are not universally applicable and are useful only for the species for which they were developed. Variability in gene expression and the acquisition or loss of DNA-carrying genes, which encode phenotypic traits, can lead to changes in the phenotype displayed by the strain. This can lead to closely-related strains exhibiting different phenotypic traits and unrelated strains exhibiting indistinguishable subtypes. In addition, serotyping and phage typing require the production and maintenance of large panels of reagents, which is time-consuming and laborious. For example, approximately 350 antisera are required to detect the 2,523 recognized serotypes of Salmonella, therefore limiting identification of all serotypes to reference laboratories. In addition, specific reagents may not be available for some serotypes or phage types, leading to significant numbers of strains being untypable using these methods. The limitations of phenotypic subtyping methods and the rapid growth of molecular biological techniques have led to the development of a range of molecular subtyping methods. Molecular subtyping methods target genotypic variation within the DNA sequence of the organism, which may reduce or

Genetic techniques: molecular subtyping methods

273

eliminate problems encountered with untypability, theoretically providing 100 per cent typability. Molecular approaches are often both more universally applicable and useful for a wide range of organisms. Plasmid profiling was the first molecular typing to be described. However, many strains may contain no plasmids, or may gain or lose plasmids, making this method an unreliable marker for routine surveillance. One of the most useful molecular subtyping techniques to emerge in the last ten years is pulsed-field gel electrophoresis of macrorestricted chromosomal DNA (PFGE). Rare cutting restriction enzymes cleave the DNA into 10–800 kb fragments, which are then separated by gel electrophoresis to produce a PFGE ‘fingerprint’ containing between 5 and 30 bands. This technique is highly discriminatory and is a proven tool for epidemiological investigations (Swaminathan et al., 2001). Some molecular methods are based on the polymerase chain reaction (PCR), which provides results in less than a day. Many of the currently available molecular subtyping methods rely on the electrophoretic separation of DNA fragments of different sizes using gel electrophoresis. The resulting pattern of bands can be complex and difficult to interpret, and often provide results that are difficult to compare between laboratories or individual gels. The rapid progress of DNA sequencing technology has made this method increasingly more available and cost-effective. This in turn has led to the sequencing of the complete genome of a number of foodborne pathogens and is facilitating the discovery of new targets for molecular subtyping methods, which may provide more precise information on strain relatedness. A comparison of the utility of phenotypic and genotypic subtyping methods for C. jejuni and L. monocytogenes is presented in Table 13.1. In this chapter we will review the most commonly used molecular typing methods for foodborne pathogens and describe their potential advantages and disadvantages for epidemiological typing.

13.2

Approaches to molecular subtyping

Since many laboratories have limited resources and time yet handle large numbers of strains, a single typing method to determine strain relatedness would be optimal in the absence of a currently available definitive ‘gold standard’ typing technique applicable to all foodborne pathogens. In the next section we describe some of the methods currently used for bacterial subtyping and discuss some of the advantages and limitations of each method. The subtyping method of choice for a particular foodborne pathogen is ultimately determined by the nature of the microbiological question being asked.

13.2.1 Restriction endonuclease analysis One of the first techniques to be described for molecular subtyping of bacteria species was the restriction endonuclease analysis (REA) of chromosomal

Table 13.1 Comparison of the utility of phenotypic and genotypic subtyping methods for C. jejuni and L. monocytogenes Method and organism

Typability (%)

Reproducibility

Discriminatory power (DI)c

Ease of use

Ease of interpretation

Time and costs

C. jejunia Serotyping Phage typing

80 80

Good Fair

Average Fair

Fairly simple Fairly simple

Fairly simple Requires expertise

RAPD AFLP

80 100

Low Good

Average Good

Fairly simple Difficult Complex method Complex

Ribotyping

100

Good

Poor

Complex method Difficult

PFGE

100

Good

Good

Moderately complex

Requires normalization of data

97 per cent 16S rDNA sequence similarity to each other. Precise species identity must be confirmed by DNA-DNA hybridization or (for routine laboratories) by performing appropriate differentiating phenotypic tests between closely-related species showing > 97 per cent 16S rDNA sequence similarity with the unknown strain. Although, 16S rDNA sequencing is one of the basic modern techniques for identification of unknown isolates, these facilities are reserved to dedicated molecular biology laboratories. In addition, it is not an adequate technique to identify large numbers of strains, unless partial sequencing of the 16S rRNA gene up to about 500 bp is performed using one or two sequencing primers. 16S rDNA sequencing is especially useful to determine the position of an unknown isolate which cannot be allocated by simple and rapid phenotypic testing or chemotaxonomic methods to a defined species. For a well-studied genus or species, genus or species-specific primers from the 16S rDNA sequence may be selected to construct a PCR for identification purposes with the advantage that it is feasible to examine many strains. In addition these universal and variable bacterial sequences in the 16S rRNA molecule are under various conditions present in the viable cell and thus allow in situ detection and identification of individual cells without cultivation.

15.4.2 DNA-DNA hybridization To fully determine the inclusion of an unknown organism to a defined species or to establish the isolate as a new species, comparisons of the total genomic DNA of the isolate and two or more type strains of related species (showing >97 per cent 16S rDNA sequence similarity) should be performed. Description of a new species involves the determination of the mean mole GC content of the genome

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and the study of the total genomic sequence similarities by DNA-DNA hybridization. The value of 70 per cent or greater DNA/DNA homology has been proposed as the borderline of species designation (Wayne et al., 1987). However, it seems to be only indicative rather than absolute. Phenotypic characteristics have to support this definition. Preferentially a number of simple and straightforward tests should support species determination based on DNADNA hybridizations (Vandamme et al., 1996). As recently proposed, taxonomists are encouraged to also use other genomic methods in species descriptions provided that there is sufficient degree of congruence between the technique used and DNA-DNA reassociation (Stackebrandt et al., 2002c). Phenotypically identical but genotypically distinct groups of strains are referred to as genospecies. As a typical example, the taxonomy of the genus Aeromonas has evolved from a complex mixture of phenotypic and genotypic data. For this reason, biochemically distinct Aeromonas species are referred to as phenospecies, whereas distinct DNA hybridization groups (HGs) are usually called genospecies. Several of the genospecies are difficult to separate biochemically or have not yet been named because of lack of phenotypic characteristics that correlate well with DNA/DNA hybridization data (Huys et al., 1994; Carnahan and Altwegg, 1996). In other cases, DNA-DNA hybridization values conflicted with data from other analyses. Strains of Escherichia coli and Shigella dysenteriae are extremely closely related and exhibit DNA-DNA hybridization values as high as 89 per cent. Nevertheless for epidemiological purposes the two taxa are not considered strains of the same species and even represent two different genera in the Enterobacteriaceae. On the other hand, certain strains of Clostridium botulinum are remotely related only by 16S rDNA analysis, they share less than 10 per cent DNA homology as measured by DNA-DNA hybridization and they are more closely related to other Clostridium species than they are among themselves. However, as all of them express a botulinum toxin they are classified in one species (Stackebrandt, 2002a).

15.4.3 DNA-based typing methods The introduction of molecular biological techniques into microbiology yielded a large variety of DNA-based typing methods. Compared to the classical phenotypic typing techniques, molecular typing techniques have several advantages such as general applicability and a high discriminatory power. The currently available molecular techniques can be classified according to their working principles as follows. • PCR-mediated typing techniques (random amplification of polymorphic DNA or RAPD, rep-PCR) • typing techniques combining PCR with restriction analysis of a gene sequence showing variation (amplified ribosomal DNA restriction analysis or ARDRA, flaA typing of C. jejuni)

The use of applied systematics to identify foodborne pathogens

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• typing techniques based on chromosomal restriction fragment length polymorphisms (e.g. ribotyping, pulsed field gel electrophoresis or PFGE) • typing techniques combining restriction digestion with selective amplification (amplified fragment length polymorphism or AFLP) • plasmid analysis (Heyndrickx et al., 2001; Vandamme et al., 1996). Although most of these methods are particularly useful for discriminating strains of the same species and determining infraspecific relationships, some of these molecular typing methods can be applied to identify strains at the species level. For example, the results of the AFLP technique applied to Aeromonas species suggests its potential usefulness at the species and subspecies levels, as well as for the fine typing of individual strains (Huys et al., 1996). Also an extended database of ARDRA fingerprints of Bacillus sp. was constructed which can be used for identification purposes (Heyndrickx et al., 1996). Several molecular typing techniques have been shown to provide the possibility of Salmonella serovar identification and thus can replace the classical serotyping (Heyndrickx et al., 2001). Obviously the potential for identification of an unknown organism by DNA-based typing methods is restricted to a particular combination of ‘taxon-typing method’ and sufficient fingerprinting data of strains belonging to this taxon are needed to assess the usefulness of the typing method for reliable identification. PCR-based typing methods with random or repetitive elements as primers have been applied to strain characterization in a wide variety of bacteria. In several of these studies species-specific DNA fragments were generated. These specific DNA fragments may be useful as probes to rapidly screen and identify other isolates (Vandamme et al., 1996). Analysis of the PCR fingerprints obtained for thermophilic campylobacters revealed that besides isolate-specific fragments, species-specific DNA fragments were generated which could be used as species-specific probes for Campylobacter jejuni, C. coli and C. lari (Giesendorf et al., 1993). Recently Gevers et al. (2001) demonstrated that repPCR fingerprinting using the (GTG)5 primer is a valuable tool for differentiation of a wide range of food-associated lactobacilli at the species, subspecies and potentially up to the strain level. Although DNA-based typing methods may be a valuable tool in identification of microorganisms with a difficult taxonomic position, they are primarly applied for infraspecific characterization and comparison and grouping of large numbers of strains at the genetic level. A merit is that the dendogram generated by cluster analysis of the DNA fingerprints allows the selection of representative strains for further characterization. Ultimately further phenotypic testing of well-chosen strains can be used to determine the physiological, ecological or pathogenic relevance of these strains. In addition these selected strains can be subjected to 16S rDNA sequencing or DNA-DNA hybridization to determine their identity or phylogenetic position.

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15.5


Applications: identifiying the genus Aeromonas

Microbiological analysis of foodborne pathogens usually involves selective culture media. These media are frequently complex mixtures of nutrients, selective inhibitors (e.g. antibiotics), chemicals (bile salts, azide, selenite, tellurite) and dyes (brilliant green, crystal violet) and indicator systems, designed to inhibit unwanted organisms while permitting the sought organisms to grow. Colonies of sought organisms are sometimes distinguished by use of colour reactions, such as pH indicator to show acid production from a sugar, or production of a coloured product from a colourless one (Bolton, 1998). Usually classical phenotypic characteristics such as morphological, physiological and biochemical features are implied as confirmation tests. However, sometimes the development of simple and restricted confirmation schemes may not be feasible to provide a reliable identification of the foodborne pathogen, especially for particular genera or species that are not susceptible to being characterized by traditional phenotypic tests, e.g. Aeromonas sp., Bacillus sp., Campylobacter sp., pathogenic strains of Escherichia coli and other foodborne pathogenic species. The following will illustrate the application of information and techniques used in systematic studies to reach accurate identification of these foodborne bacterial pathogens. Aeromonas is a Gram negative facultatively anaerobic rod-shaped organism that is ubiquitous in virtually all types of freshwater worldwide but which has also been isolated from human and animal clinical specimens and from food including fish, raw meat and vegetables (Neyts et al., 2000; Palumbo, 1996). There is evidence that Aeromonas species can grow and produce different virulence factors not only at optimal growth temperature (28C), but at refrigeration temperatures as well (Merino et al., 1995). This may be of importance to raw food products that are kept at refrigeration temperatures and have an extended shelf-life at this temperature. Although still controversial, some strains of Aeromonas are considered as opportunistic pathogens causing gastrointestinal diseases in immunocompromised individuals (Joseph, 1996). Modern Aeromonas taxonomy is based on the so-called ‘four-speciesconcept’ described by Popoff in Bergey’s Manual of Systematic Bacteriology (1984) including the mesophilic motile A. hydrophila complex, the A. caviae complex, the A. sobria complex and the psychrophilic, non-motile species A. salmonicida. Each of these mesophilic complex groups were found to contain two or more DNA hybridization groups (HGs), some of which have meanwhile obtained the species status as a result of extensive phenotypic characterization and the introduction of chemotaxonomic and genotypic methods. Currently, the genus Aeromonas comprises at least 15 Aeromonas species including A. hydrophila (HG1 and HG3), A. bestiarum (HG2), A. salmonicida (HG3, including five subspecies), A. caviae (HG4 and HG5), A. media (HG5), A. eucrenophila (HG6), A. sobria (HG7), A. veronii biovar sobria and biovar veronii (HG8/10), A. jandaei (HG9), A. encheleia (HG11), A. schubertii (HG12), A. trota (HG13), A. allosaccharophila, A. popoffii, and A. culcicola.


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However, the taxonomy of the genus is continuously changing because of new findings. As such, the Aeromonas genus is a good example of a taxon where classical phenotypic testing lacks the potential for accurate identification. The application of advanced more discriminative methods can aid in addressing the current taxonomic and pathogenic problems in the genus of Aeromonas. Rapid phenotypic testing to identify a suspected Aeromonas isolate leads to misidentification because the current morphological, physiological and biochemical tests lack the taxonomic resolution compared to chemotaxonomic, genotypic and phylogenetic methods currently used to construct the taxonomic framework of the genus Aeromonas. Application of molecular methods showed several genospecies which are difficult to separate biochemically or have not been named yet because of lack of phenotypic characteristics that correlate well with DNA-DNA hybridization data. For instance, the motile A. hydrophila-like members of HG3 still await proper naming and can still be genotypically confused with the physiologically distinct subspecies of A. salmonicida. Data by biotyping (Valera and Esteve, 2002) and multilocus enzyme electrophoresis (Tonolla et al., 1991) correlated well with DNA-DNA hybridization data. However, these techniques are time-consuming and require too many reagents to be of practical use in routine analyses. FAME profiles are rather similar between Aeromonas species, although minor quantitative variations could be used to differentiate the majority of the phenospecies and/ or hybridization groups in the genus Aeromonas. Hybridization groups that constituted the Aeromonas hydrophila complex, the Aeromonas caviae complex, and the Aeromonas sobria complex were basically grouped into distinct FAME clusters. Rapid identification of unknown aeromonads can be performed by using the database of FAME fingerprints constructed for Aeromonas and related genera. It should be noted that comparison of FAME data with the established database can only be performed if these were achieved by highly standardized cultivation and extraction procedures and specialized software like the Microbial Identification System (MIDI, Microbial ID, Inc., Newark, Del.) (Huys et al., 1994). From the molecular methods used in Aeromonas taxonomy, the genomic fingerprinting technique AFLP (Amplified Fragment Length Polymorphism) can be considered as one of the most powerful techniques to differentiate all currently recognized taxa in the genus. Numerical analysis of the digitized AFLP fingerprints revealed AFLP clusters which, in general, clearly supported the current Aeromonas taxonomy derived from DNA homology data (Huys et al., 1996).

15.6

Applications: identifying the genus Bacillus

15.6.1 Bacillus spoilers The classical genus Bacillus encompasses the Gram positive spore forming rodshaped aerobic bacteria and comprised, in 1993, more than 60 validly described species (Priest, 1993). The classical genus Bacillus is phenotypically

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heterogeneous, with members exhibiting a wide range of nutritional requirements and growth conditions and occupying a variety of habitats. An extensive list of morphological, physiological and biochemical properties of most members of the genus have been compiled and procedures for isolation and tentative identification of typical strains of Bacillus species are available. However, identification of Bacillus species using classical phenotypic testing is not an easy task. Indeed DNA hybridization studies and 16S rRNA gene sequencing have revealed the genetic heterogeneity of the genus, and in fact intrageneric heterogeneity is as great as exists in most bacterial families, e.g. Enterobacteriacae (Slepecky and Hemphill, 2002). It is thus understandable that the genus has been subjected to reclassification. Reclassification of the genus Bacillus started in 1991 with the work of Ash et al. (1991). By comparative analysis of rRNA gene sequences of a collection of 51 Bacillus species they were able to group them into five distinct clusters. These studies, followed by others, have led to the creation of several new Bacillus-derived genera: Alicyclobacillus, Paenibacillus, Aneurinibacillus, Brevibacillus, Virgibacillus, Gracilibacillus, Salibacillus (Joung and Coˆte´, 2002) and it is expected that more new genera and species will be described in the near future. A miniaturized rapid identification system wherein many standardized biochemical assessments can be made along with some supplementary classical determinants (spore shape, presence of swollen sporangium, etc.) can be used for identification of the commonly encountered Bacillus species provided the corresponding correct species names are included in the database. A variety of techniques have been employed to find a simple and rapid approach to identify Bacillus species with a difficult taxonomic position. A first simple technique to assign Bacillus strains to groups is fatty acid methyl ester (FAME) analysis although it is not useful for exact species identification (Ka¨mpfer, 1994). Also, a standardized method for amplified ribosomal DNA restriction analysis (ARDRA) has been described and numerical analysis of the ARDRA patterns allows the strains to be grouped. In general, the clustering of the Bacillus strains corresponds well with the known species delineations (Heyndrickx et al., 1996). Alternatively, SDS-PAGE of whole cell proteins can be performed. Preferably two or more methods should be used for identification. When large sets of isolates have to be identified, a first classification of the isolates can be performed with, for example, ARDRA, FAME or PAGE, after which one representative of each cluster or group in the classification (usually represented in a dendrogram) can be identified by 16S rDNA sequencing (Heyndrickx et al., 1998). This polyphasic approach integrating different kinds of techiques and information was used for identification of aerobic spore-forming Bacillus species in feed concentrates for dairy cattle (Vaerewijck et al., 2001). Feed concentrate for dairy cattle contains known as well as yet unknown species of Bacillus and related genera with properties which might be relevant to the dairy sector. Indeed, in the last decade a highly heat-resistant sporeformer has been reported to cause spoilage problems in UHT milk. The above-mentioned approach needed to be applied to determine the Bacillus species responsible. In


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1996 the predominant thermoresistant spoiling sporeformer was taxonomically described as a new species Bacillus sporothermodurans. Besides B. sporothermodurans, other highly heat resistant Bacillus species have been found to contaminate milk. Often these species cannot be identified (or classified if unknown species are implied) by the normal classical phenotypic methodology. PCR assays were developed for rapid and simple detection of Bacillus sporothermodurans (Herman et al., 1997; Scheldeman et al., 2002).

15.6.2 Bacillus cereus Bacillus cereus is a foodborne pathogen and part of the B. cereus group including also B. anthracis, B. mycoides and B. thuringiensis. Most procedures for the isolation and enumeration of B. cereus involve direct plating on mannitol-egg yolk-polymyxin agar followed by a restricted number of confirmation tests. The members of the B. cereus group can be differentiated only on the basis of highly mutable characteristics. B. anthracis can be separated from B. cereus based on non-haemolytic activity and non-motility. For B. mycoides, rhizoid growth is the definitive characteristic. On the other hand, B. thuringiensis can be distinguished from B. cereus by its ability to produce an insecticidal crystal inclusion inside the cell during sporulation. As these definitive characteristics are often located in plasmids which are transferable, they become indistinguishable when strains lose plasmids. In fact, recent studies suggested that B. cereus and B. thuringiensis should be regarded as one species. For this reason, molecular methods are preferred for the specific identification of strains of the B. cereus group. In the case of differentiation of B. cereus from B. thuringiensis specific primers targeting the variable region of 16S rDNA or the gyrB genes can be used to design a discriminatory PCR reaction (Chen and Tsen, 2002). Apart from the problem of identification there is also discussion concerning the risk that the species belonging to the B. cereus group pose for food safety. Only B. cereus sensu stricto is an established foodborne pathogen. From epidemiological studies it is known that B. cereus is one of the major causes of bacterial foodborne gastroenteritis but because of the acute but self-limiting character of the disease it is underreported. B. cereus is a Gram positive sporeformer which is often (in limited numbers) found in numerous pasteurized foods, e.g. pasteurized milk, ready-to-eat pasteurized meals, rice dishes and pastas. In the case of temperature abuse the pathogen grows rapidly to high numbers (> 105/g) and produces toxin. B. cereus is the most important microbiological hazard in these types of food. Nevertheless, B. thuringiensis strains have also recently been found to produce enterotoxin profiles similar to those of B. cereus and may be present in pasteurized vegetable pureés. It is thus recommended to determine, apart from the identity of the strain, also the toxic potential of the isolate. Standard procedures to detect the toxic potential are cytotoxicity studies (cell tissue cultures). However, these procedures are laborious and demand a dedicated infrastructure. Furthermore, the demon-

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stration of the toxic potential uses either PCR detection or an ELISA kit, but these are focused on the diarrheal toxins and not available for the emetic toxin (Batt, 2000; Beattie and Williams, 2000). PCR detection is simple and easy to perform, but only indicates the presence of the toxin genes in the B. cereus strains without revealing any information regarding the expression of these genes during growth.

15.7

Applications: identifying the genus Campylobacter

The Campylobacteriaceae comprises a group of Gram negative, nonsaccharolytic bacteria with microaerobic growth requirements and a low GC content. A slender spiral ‘corkscrew-like’ morphology is typical. However, it has been documented for the thermophilic campylobacters (C. jejuni, C. coli, C. lari and C. upsaliensis) that they readily lose this morphology upon aging and cells incubated longer than 24 h will transform into bent rods or straight rods and finally become virtually completely coccoı¨d and non-culturable (Vandamme et al., 1996). The genus Campylobacter initially included a wide assembly of species which were characterized by their biochemical inertness. Indeed, classical phenotypic tests routinely used for the identification of clinically significant campylobacters often yield negative results or yield variable results within species and do not allow a reliable differentiation of the species, especially for phenotypic aberrant strains. The biggest problems are found in the identification of C. jejuni and C. coli. The single discriminatory test is hippurate hydrolysis. Strains which were identified biochemically as C. coli (hippurate hydrolysis negative) have been shown by PCR to possess the hippuricase gene unique to C. jejuni. Detection of the hippuricase gene by PCR provides a more useful test for confirmatory identification of C. jejuni. Also problems are encountered for objective evaluation of the sensitivity to cephalothin and nalidixic acid. Reliable identification of Campylobacter spp. should be supplemented with a molecular method (Steinhauserova et al., 2001; Engvall et al., 2002). Sequence comparison of 16S rRNA gene sequences revealed a considerable genotypic heterogeneity among the species of the initial Campylobacter genus described, and three major clusters (rRNA homology groups) were recognized. Subsequently, the initial genus Campylobacter was divided into three distinct groups, each corresponding to a separate genus: Campylobacter, Arcobacter and Helicobacter. Information derived from 16S or 23S rDNA sequencing has been used successfully to design species- or genusspecific primers and probes. Applied in a PCR assay these primers and probes offer valuable alternatives for the identification of these bacteria belonging to the family of the Campylobacteriaceae (Vandamme et al., 1996). Whole-cell protein analysis by SDS-PAGE has proved to be a valuable tool to identify unusual or atypical campylobacters. As with other bacteria, strains with highly similar protein patterns share high DNA hybridization values and therefore belong to the same species. The suitability of cellular fatty acid


351

analysis for the differentiation of the species is genus dependent; poor discriminatory power was found in Campylobacter species, whereas most Arcobacter species were easily differentiated (Vandamme et al., 1996).

15.8 Detecting virulence factors in foodborne pathogenic bacteria 15.8.1 Pathogenic Escherichia coli Escherichia coli is a commensal bacterium in the human and animal gastrointestinal tract. However, some E. coli strains show pathogenic potential because of the acquisition of virulence factors. These are known as pathogenic E. coli (EC) and there are six major groups: enteropathogenic (EPEC), enterotoxigenic (ETEC), enterohemorrhagic (EHEC), enteroinvasive (EIEC), enteroaggregative (EAEC), and diffusely adherent (DAEC) E. coli. Like typical E. coli, strains in most pathogenic groups ferment lactose and are not affected by the elevated incubation temperature of 44ºC normally applied for E. coli. Hence, they can still be distinguished from other enteric bacteria using the standard methods for E. coli. Exceptions, however, are EIEC, which do not ferment lactose, and EHEC O157, which can be inhibited by the elevated incubation temperature (Feng, 2001). E. coli O157 is an example of an organism that probably became virulent through the acquisition of a novel genetic element. Over time, genetic changes take place in a population at a regular rate leading to genetic diversity among specific cells in the population. Many types of genetic variability have been documented for E. coli by molecular typing methods. There have been claims that some E. coli strains are significantly more acid tolerant (McClure and Hall, 2000). This may be clinically important, since the capability to overcome the acid barrier of the stomach is facilitated. The first outbreak of infections caused by E. coli O157 was observed in 1982. This E. coli lineage is probably an example of a strain that acquired a Shiga-like toxin gene from an enteric organism that normally harbours this toxin (such as Shigella dysenteriae) as a secondary virulence factor, possibly through bacteriophage transduction into an already cytoadherent type of E. coli. Gene sequence comparisons have illustrated that insertion of foreign DNA into the E. coli chromosome occurs regularly (Finlay and Falkow, 1997; Van Belkum et al., 2001). Some type strains in these pathogenic E. coli groups, such as O157:H7, are widely recognized by their serotype, but mainly the pathogenic E. coli group are recognized solely on the basis of their pathogenicity and no unique test is available to differentiate pathogenic E. coli from normal intestinal E. coli. The detection of pathogenic E. coli clearly demands the combination of classical phenotypic methods for isolation and identification of the E. coli species and molecular-based methods for the demonstration of potential pathogenicity of the E. coli strain. There appears to be a clear association between the presence or absence of certain genetic elements and bacterial virulence. DNA-based

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methods for analysis of their virulence characteristics is required for definitive identification of each group of pathogenic E. coli. In the case of E. coli O157:H7, the most notorious foodborne pathogenic E. coli, the search for virulence factors includes the detection of the stx-genes (encoding cytotoxins known as Shiga-like toxins or verotoxins), the chromosomal eaeA-gene (encoding the intimin protein involved in attachment) and the ehxA gene (encoding for enterohemolysin). At present virulence factors are detected either by colony hybridization studies with specific probes or PCR tests with specific primer pairs. Recently DNA chips were introduced to map virulence gene patterns of pathogenic E. coli (Call et al., 2001; Chizhikov et al., 2001). As an alternative cytotoxicity for cells of tissue cultures can be determined or immunological detection of the Shiga-like toxins can be performed.

15.8.2 Pathogenic Yersinia enterocolitica, Vibrio parahaemolyticus and Listeria monocytogenes In food microbiology numerous taxonomic species are indicated as foodborne pathogens although only a limited number of strains, carrying virulence factors have the potential to cause infections. As well as E. coli, as mentioned above, some commonly known foodborne pathogenic species also include non-virulent as well as virulent strains, e.g. Yersinia enterocolitica, Vibrio parahaemolyticus or Listeria monocytogenes. The practice of judging food, based on total counts or detection of the taxonomic species as such without consideration of the virulence factors being present, is not always appropriate. As mentioned above virulence genes can be detected by DNA-based methods. However, if virulence factors are associated with phenotypic traits testing these can also be included as confirmation tests in the classical procedure. Historically, this has been included in some of the classical pathogen detection schemes, although at the time of their introduction the association between the phenotypic characteristic and the responsible virulence gene was not established. For Yersinia enterocolitica the initial event subsequent to infection is invasion of intestinal epithelial cells. This is connected with the presence of chromosomal genes termed the inv and ail loci in Y. enterocolitica. In addition, the presence of plasmid-encoding determinants play a major role in the overall virulence of pathogenic Yersinia. All pathogenic strains of Y. enterocolitica possess a 70 kbp plasmid carrying essential virulence genes, e.g. genes for the temperature inducible Yersinia outer membrane proteins (yop), and the gene for the adhesin (YadA). The virulence plasmid is well conserved among the pathogenic species; however, loss of the plasmid results in the loss of pathogenicity. Virulence of Y. enterocolitica can be determined by detection of the above-mentioned virulence genes and can be linked to phenotypic classical tests such as Congo red binding (Bhaduri, 2001). A thermostable direct haemolysin (tdh) and tdh-related haemolysin (trh) are considered to be the major virulence factors of Vibrio parahaemolyticus and respectively encoded by tdh gene and trh gene. They are very common in


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clinical strains and less so in environmental strains – estimated to be present in approximately 1 per cent of environmental isolates and up to 99 per cent of clinical isolates. Presence of tdh is correlated with the Kanagawa reaction on agar containing fresh human red blood cells, known as Wagatsuma agar (production of tdh causes beta-hemolysis). The presence of the trh correlated with a positive urease test (Tamplin, 2001). Not all strains of L. monocytogenes are pathogenic. Wiedmann et al. (1997) characterized 133 isolates of L. monocytogenes according to ribotype and virulence gene analysis. These authors found that L. monocytogenes strains could be clustered into three distinct lineages. Within lineage 1 resided all strains isolated during outbreaks of listeriosis. In contrast, lineage 3 contained no human isolates, indicating that strains in this grouping may have reduced virulence. The production of sulfhydryl-activated hemolysin, listeriolysin O (encoded by the hlyA gene), is associated with the pathogenic potential of L. monocytogenes. The loss of hemolysin production was shown to be associated with loss of virulence in a mouse model. An extracellular protein (p60) may be involved in the process of attachment and invasion of L. monocytogenes (encoded by the iap gene) and has been shown to be produced by all virulent L. monocytogenes strains (Donnelly, 2001). The potential use of fragments of these genes as a L. monocytogenes speciesspecific probe was demonstrated, and a multiple PCR assay was developed for rapid detection of L. monocytogenes targeting the hlyA or iap gene (Scheu et al., 1998).

15.9

Future trends

In the last ten years spectacular developments have been made in the field of sequencing of rRNA and genes coding for rRNA (rDNA). Sequence analysis of rRNA has become a rapid standard technique and the sequences generated have a very low error rate. These techniques revolutionized the insights in the phylogeny and taxonomy of bacteria and led to reclassification of numerous bacteria (Stackebrandt, 2002a). The molecular approach has facilitated classification and subsequently identification of unknown organisms and speeded up comprehension of the complex bacterial relations. But it has also raised questions about the approach to classification and subsequently identification using morphological, biochemical and physiological characteristics. However, although it is generally accepted that bacterial classification should reflect as closely as possible the natural relationships between bacteria as determined by their genetic relatedness, a taxon should be characterized by a certain degree of phenotypic consistency. Although genomic and chemotaxonomic methods may allow on some occassions a more accurate identification than the classical phenotypic identification tests, there is a need for phenotypic characterization of the isolates as well to evaluate their physiological and ecological functions.

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It is interesting that increased automation and democratization of these advanced chemotaxonomic and molecular-based techniques facilitated access to these methodologies for identification purposes. Classical phenotypic methods will remain internationally the reference methods and first approach in identification of foodborne microorganisms. Nevertheless several of the methods mentioned here may be valuable tools for reliable identification particularly of genus or species with a difficult taxonomic position. They represent a list of methods which can provide information on the unknown isolate on a different level. Whereas classical identification tests supply information on a wide range of expressed features, chemotaxonomic and genomic methods supply information on DNA base composition and heterogeneity, RNA sequence, protein or lipid composition. These advanced techniques should be regarded as complementary to the current classical phenotypic identification schemes in use. Primarily, it is of interest to understand at which level these methods carry information, to realize their technical complexity and to know whether it is applicable to a particular taxon (Vandamme et al., 1996). For all of these techniques it is necessary to obtain a pure culture. This requires preliminary isolation steps (sample preparation techniques and manipulation of culture media) according to a rationale which is primarily defined by the food matrix and the level and type of microorganism under consideration and needs the expertise of a food microbiologist. It is expected that these advanced techniques will be introduced increasingly in food microbiological laboratories. PCR methods and DNA-based typing methods are already accepted as rapid, simple and reliable methods for identification and typing of foodborne pathogens and rDNA sequencing has proven to be useful in identification of problematic isolates. It is of increasing importance to use a multidisciplinary approach in the identification of foodborne microorganisms in order to acquire a reliable and accurate identification. However, interpretation and application of these advanced methods should be supported by classical phenotypic characteristics and sustained ecologically.

15.10


For more details on systematics and defining a taxonomic rank the reader is referred to Bergey’s Manual of Systematic Bacteriology Volume 2 (Sneath P H A, Mair N S, Sharpe M E, Holt J G, eds), Williams & Wilkins, Baltimore, and The Prokaryotes (Dworkin M, (ed.)), Springer-Verlag, New York (www.prokaryotes.com). The concept of polyphasic taxonomy and overview of the multiple techniques which can be used for classification and/or identification of bacteria is explained by Vandamme et al. (1996). More details on molecular detection and typing of foodborne bacterial pathogens can be found in a review by Heyndrickx et al. (2001).


15.11

355

Acknowledgements

The authors appreciate the help of Dr Geert Huys of the Laboratory of Microbiology, Faculty of Sciences, Ghent University, Dr Marc Heyndrickx of the Department for Animal Product Quality and Transformation Technology, Center for Agricultural Research, Ghent and Willy Zorzi, Benaı¨ssa Elmoualij and Virginie Ruelle of the Lab of Histology, Faculty of Medicine, University of Lie`ge for their contribution and comments to the topics concerning respectively the genus Aeromonas, the genus Bacillus, and MALDI-TOF. Mieke Uyttendaele is indebted to the National Fund for Scientific Research (Belgium) for a position as Postdoctoral Research Fellow.

15.12

References

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Index

acceptable level 26, 29, 32 acceptance 21 probability of (Paccept) 22, 29, 31, 34–6, 38–40, 62–3 acceptance sampling 43 when history is known 33–41 when history is not known 28–33 acceptance sampling plans 21, 26–8 plan operating characteristics 29–32 accreditation 99–100, 106 accredited laboratories and validated methods 70, 86–8 electrical methods 161 accreditation agencies 106 accuracy 72, 110 acoustic/piezoelectric transduction 296, 301–3 acridine orange 190, 197 Additional Measures concerning the Official Control of Foodstuffs (AMFC) Directive 95–7 adenosine triphosphate (ATP) 166 see also ATP bioluminescence adenylate kinase (AK) 166–7, 173–4 adhesive tapes 57 Aeromonas (genus) 346–7 aflatoxin M1 (AFM1) 318, 322–3 agar 125 agar ’underlay’ methods 130 agglutination tests 228–34, 235, 236 confirmation of bacteria 229–33

detection of toxins 233–4 air quality 10 algal toxins 318–22 amino-nitrogen compounds 124 ammonia optodes 301 amnesic shellfish poisoning (ASP) 318, 320 amperometric biosensors 312, 313–18 amperometric transduction 296–8 amplification of ATP 172, 173 amplified fragment length polymorphism (AFLP) 274, 276, 281–2, 347 analytical methods choice of and proficiency testing 117 quality assurance requirements 106–10 analytical runs 102 analytical sample 22, 44 antibiotics 126 antibodies 217–18, 242 molecular probes 191–2 see also immunological techniques antibody-based bioluminescent methods 174–5 antibody-direct epifluorescent filter technique (Ab-DEFT) 198–9, 209 antigenic typing schemes 228–9 antigens 217–18, 242 see also immunological techniques AOAC International (AOACI) 75–6, 78, 79, 88–9, 108–9, 111, 161 harmonised protocol on proficiency testing 105, 106, 115–19

Index applied systematics see identification arbitrarily primed polymerase chain reaction (AP-PCR) 278–9 Arcobacter 350–1 argon laser 189 Arnott’s lysine medium 156 artificially contaminated samples 78–80, 102 assigned value 117 ATP bioluminescence 9, 16, 165–85 antibody-based methods 174–5 assays for testing total bacterial count 167–8 hygiene monitoring 171–4 instrumentation 178–80 particular foods 168–71 particular pathogens 174–8 phage-based assays 175–8 principles 165–7 attributes 21, 46–7 attributes sampling plans 26–8 avidin 245 Bacillus anthracis 349 cereus 248, 349–50 identifying the genus 347–50 MALDI-TOF approach 341–2 mycoides 349 spoilers 347–9 sporothermodurans 348–9 thuringiensis 349 bacteriophage-based bioluminescent assays 175–8 Bactometer 147, 148, 149–50 Bactoscan 209 BacTrac 147, 148, 149–50 basic culture media 123–5 BAX 267 BBL Staphyloslide kit 230 BCET-RPLA test 234 bead columns 62 Bev-Trace 169 beverages 169 bias 71, 118 biochemical characteristics 333–8 biological warfare agents 326 biosensors 16, 294–331 algal toxins and aflatoxin 318–23 DNA biosensors 323–4 Escherichia coli 312–18, 325, 325–6 future trends 326 microbial spoilage 325–6 Salmonella 304–11

361

Staphylococcus aureus 311–12 transducers used in 296–303 biotin 245 biotinylated thiol 315–16 biotyping 272 biphasic partitioning 61 blind proficiency testing 106 BOX sequence 280 brewing 169 bright field microscopy 193 buffer salts 124 Bullock and Frodsham’s LINCR medium 155–6 Caliciviridae 263–4 calorimetric transduction 296, 303 Campylobacter 248 coli 286, 350 electrical methods 160 identification of genus 350–1 jejuni 274, 286, 350 PCR/REA for thermophilic species 86 standardised culture method 136, 137 Campynet 286 capture line 220–1 carbon dioxide optodes 300–1 cellular fatty acids 339–40 CEN (European Committee for Standardisation) 75, 88–9, 95, 108–9 centrifugation 60 Certificate of Analysis 14 certified reference materials (CRMs) 71 challenge testing 6–7 charge-coupled device (CCD) cameras 180 chemotaxonomy 338–42 ChemScanRDI 209–10 chromogens 126–7 classification 332–3 see also identification cleaning equipment 10 Clostridium botulinum 160, 248, 344 clumping factor 230–1 cluster analysis 335 coagulase 280, 281 codes of practice 94–5 Codex Alimentarius Commission (CAC) 93, 97–8, 107 cold water setting gels 137–9 coliforms 156–9 Colilert 140 collaborative trials 110–11 collaborative typing networks 286, 291

362

Index

collusion 118 colony forming unit (cfu) 21 combination scores 119 commercial kits alternative validation procedures 111 culture methods 137–40 ELISAs 245–52 galleries of tests for identification 334–5 genetic techniques 267, 268, 276, 277, 291 LFDs 223–5 comparative DNA sequencing-based subtyping 283, 289 competitive ELISA 245, 246, 319 compositing 44–5 concentration attributes sampling plans 34–6 sample separation and concentration see separation and concentration conductance 147–8 see also electrical methods conductimetric transduction 296 confirmation 133 agglutination tests 229–33 confocal laser scanning microscopy (CLSM) 194 consumer’s risk 21, 29 contamination 266 contractual research 99 control charts 45–7 control limits 45–7 control materials 101–2 co-ordinating laboratory 116 costs 253 counter-terrorism 210, 326 critical control points (CCPs) 4, 5, 11, 13–14 critical limit 37–8 Cryptosporidium parvum 324 culture media 123–9, 141 basic culture media components 123–5 differential culture media components 126–7 incubation conditions 127–8 resuscitation conditions 128–9 selective culture media components 125–6 culture methods 123–46 commercial kits 137–40 culture media design see culture media culture method design 129–33 examples of 133–7, 138 future trends 140–1

data analysis 287–90, 291–2 data presentation 150–1 dedicated instrumentation 209 delayed addition 139 detection limit 72 detection time 150–1, 253 diarrhetic shellfish poisoning (DSP) 318, 322 dielectrophoresis 61 differential culture media 126–7 differential strains 188 direct epifluorescent filter technique (DEFT) 186, 187, 188, 194, 196–9 direct selective enrichment 252 direct stains 188 dipsticks 243 discriminatory power 271 distribution of pathogens 54 sampling and 24–8 DNA extraction and isolation from food 263 see also genetic techniques DNA biosensors 323–4 DNA-DNA hybridisation 343–4 DNA microarrays 290–1 DNA sequencing-based subtyping 283, 289 domoic acid (DA) 318, 320–2 drains 10 dried film technique 196 drinking water 169 Dryspot range 236 Duopath LFD 235 dyes 125, 126 Dynabeads anti-Salmonella 83–4 Easter-Gibson medium 153–5 EiaFoss 251–2 electrical methods 147–64 accreditation 161 Campylobacter 160 Clostridia 160 data presentation 150–1 Enterobacteriaceae, E. coli and coliforms 156–9 future trends 162 gram positive bacteria 160–1 instruments 149–50 Listeria 159 pathogen assays 151–2 principles 147–9 Salmonella 152–6, 161 vibrios 160 Yersinia 160

Index electrochemical biosensors 306–11, 312, 313–18, 319–20, 322–3, 324 electrochemical transduction 296–8 electron microscopy 194–6 electron transfer mediators 297–8 EN 45000 series of standards 99, 100 endogenous peroxidase 253 endproduct testing 295 energy sources 124 Enliten 168 enrichment 187, 208, 219, 263 ELISA 254–5 primary enrichment 131–2 selective enrichment 132, 208, 252 Enterobacteriaceae 156–9 enterobacterial repetitive intergenic consensus (ERIC) sequences 280 Enterococcus serolicida 325 enumeration culture method design 129–31 flow cytometry 207–8 microscopy 193, 196 environment 9–10 environmental sampling 41–3 enzyme amplification 313–16 enzyme-linked fluorescent assays (ELFA) 219–20, 225–8 enzyme-linked immunomagnetic electrochemistry (ELIME) 306–7, 308 enzyme-linked immunosorbent assay (ELISA) 218, 219, 235, 241–58, 318–19 advantages and disadvantages 252–3 basic principles 242–3 biosensor for Salmonella 307–11 commercially-available ELISAs 245–52 E. coli 224 formats 243–5, 246 future trends 254–6 IMS-ELISA 83–4, 247, 251, 254–5 manufacturers of ELISA kits 258 PCR-ELISA 85–6, 255, 261 enzyme-substrate complexes 243 epidemiological studies 271, 287–90 see also molecular subtyping epifluorescence microscope 194, 195 equipment 8–9 Escherichia coli (E. coli) 248, 287, 344 agglutination tests 231–2 biosensors used to detect 312–18, 325, 325–6 electrical methods 156–9

363

immunological techniques 223–4, 227–8, 231–2 standardised culture method 137, 138 STEC 85–6, 232, 233–4, 248, 262 virulence factors 351–2 European Co-operation for Accreditation (EA) 99, 100 European Union 93, 158 AMFC Directive 95–7 legislation 94–7 OCF Directive 94, 95, 107–8 quality assurance requirements 107–8 expert systems 7, 17 FAD 297–8 falsification of results 118 fatty acid methyl ester (FAME) profiles 339–40, 347 fatty acids 339–40 ferrocene 298 fibre optic sensors 299–301, 311–12 firefly luciferase 173, 192 flagellin 280, 281 flow cytometry (FC) 186–7, 188, 199–208, 209, 210 applications in food processing 208 microbial pathogens in food 204–5, 206 of microorganisms 202–4 principles and instrumentation 200–1 sample processing and enumeration 205–8 flow injection analysis (FIA) biosensors 304–6, 307–11, 316–18 fluorescein diacetate 190 fluorescence microscopy 194, 195 fluorescence resonance energy transfer (FRET) 260, 261 fluorochromes 189–90, 204 fluorogens 126 food processing 208 Food Safety Act 1990 93–4 food safety management 3–19, 295 future trends 16–17 microbiological analysis and GMP systems 7–11 microbiological analysis and HACCP systems 11–16 sampling and 40–1, 48 systems 4–5 types of testing used in GMP and HACCP 5–7 food safety objectives (FSOs) 4, 21, 33, 41, 48

364

Index

Food Standards Agency (FSA) 93, 98–9, 105, 106 food types 77–8 forensic investigation 15–16 forward light scatter (FSC) 200, 201, 203–4 Fourier transform infrared (FTIR) spectroscopy 342 fruit 170 fruit juices 170 gas bubbles 58–9 gaseous environment 127–8 gel electrophoresis 265 gelling agents 125 gene amplification method 324 Gene-Trak 267 genetic diversity 288–9 genetic techniques 16, 259–70 advantages and disadvantages 265–6 applications 263–5 commercial kits 267, 268, 276, 277, 291 extraction and isolation of DNA from food 263 future trends 268 hybridisation 261, 265, 275–6, 313–16 identification based on genetic information 342–5 key principles 262–3 microarrays 262, 265, 290–1 molecular subtyping see molecular subtyping NASBA 261 PCR see polymerase chain reaction probe and primer design 262–3 genospecies 344 glucose 124 glucose biosensor 298 glucose oxidase enzyme (GOD) 312 good hygiene practice (GHP) 4–5, 33, 41 good manufacturing practice (GMP) 4–5, 21 microbiological analysis and GMP systems 7–11 types of testing used in 5–7 variables plans for GMP limits 38–40 gram positive bacteria 160–1 green fluorescent protein 192 growth promoting factors 125 Haemocell Rapid Microbial Quality Assurance (RMQA) system 169 hand washing 11

‘Harmonised Guidelines for Internal Quality Control in Analytical Chemistry Laboratories’ (IQC Protocol) 101, 103 hazard analysis 11, 12–13 hazard analysis critical control point (HACCP) 4–5, 21, 33, 165, 295 HACCP plan 23 microbiological analysis and HACCP systems 11–16 types of testing used in 5–7 hazard identification 7–8 Helicobacter 350 hepatitis A viruses 263–4 high performance liquid chromatography (HPLC) 318 hybridisation 261, 265, 313–16 molecular subtyping 275–6 hydrodynamic focusing 200 hydrogen peroxide electrode 297, 298 hydrophobic grid membrane filter (HGMF) method 139–40 hygiene monitoring 171–4 identification 236, 332–59 Aeromonas genus 346–7 Bacillus genus 347–50 based on genetic information 342–5 Campylobacter genus 350–1 chemotaxonomy 338–42 detecting virulence factors 351–3 future trends 353–4 morphological, physiological and biochemical characteristics 333–8 identification tables 335, 336, 337 IFREMER system for E. coli 157–8 imaging devices 180 immunocapture (immunoconcentration) 227–8, 247, 251, 254–5 immunochromatography 220–5, 235 immunofiltration 316–18 immunological techniques 217–40 agglutination tests 228–34, 235, 236 application of validation schemes 81–4 ELFA 219–20, 225–8 ELISA see enzyme-linked immunosorbent assay future trends 235–6 immunochromatography 220–5, 235 immunomagnetic separations (IMS) 60–1, 218 coupled with ATP bioluminescence 174–5 Dynabeads anti-Salmonella 83–4

Index ELIME 306–7 IMS-PCR 209 incorporated into ELISA 83–4, 247, 251, 254–5 immunosensors algal toxins and aflatoxin 318–23 E. coli 316–18 transducers used in 296–303 see also biosensors impedance 147–8 see also electrical methods in-house method validation 111 incubation conditions 127–8 indicator dyes 126 indicator organisms 5–6 indirect conductance methods 151–2 indirect sandwich ELISA 245 individual measurement chart 45–6 inorganic salts 125 instrumentation ATP bioluminescence 178–80 dedicated 209 electrical methods 149–50 flow cytometry 200–1, 209 internal quality control (IQC) 87–8, 100–4 basic concepts 101–2 quality control of media 103–4 recommendations 103 International Commission on Microbiological Specifications for Foods (ICMSF) 21, 26–7, 33 international cooperation 88–9 International Dairy Federation (IDF) 88, 95, 161 ‘International Harmonised Protocol for Proficiency Testing of (Chemical) Analytical Laboratories’ 105, 106, 115–19 International Standardisation Organisation (ISO) 88–9, 95, 111, 161 harmonised protocol for proficiency testing 105, 106, 115–19 standard 16140 75 standard 17025 87, 89, 98, 100, 106 standardised methods 74, 133–7 investigations 15–16, 43 ion-exchange columns and sponges 62 IUPAC/ISO/AOAC Harmonisation Protocol on Collaborative Studies 111 IUPAC/ISO/AOAC Harmonised Protocol on Proficiency Testing 105, 106, 115–19

365

killing step 207 labels 242–3 lactate 325 laser scanning cytometry (LSC) 209–10 lateral flow devices (LFDs) 220–5, 235–6 latex agglutination tests 232–3 legislation 94–7 LINCR medium 155–6 linearity 72 Listeria 248 electrical methods 159 innocua 264, 265 monocytogenes see Listeria monocytogenes Rapid test 224–5 VIDAS LIS method 81–2 Listeria monocytogenes detecting virulence factors 353 genetic techniques 264–5, 274, 276, 277, 286, 287 standardised culture method 134–7 log-normal distribution 25 lot sample 22 lot size 28 luciferase 173, 192 lysine-based media 155–6 lysine decarboxylase test 155 magnification 192 Malthus 147, 148, 149–50 marginally acceptable level 26, 29, 32 ‘mass action’ effect 56–7 mass spectrometry 341–2 matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF MS) 341–2 measurement uncertainty 112–13 meat ATP bioluminescence 170–1 biosensors for Salmonella 307–11 media: quality control of 103–4 mediators, electron transfer 297–8 membrane filter microscope factor (MFMF) 198 membrane filters 59–60, 130 metals 124 methicillin-resistant Staphylococcus aureus (MRSA) 230 microarrays (gene chips) 262, 265, 290–1 Microbe Trap 63–4 microbial metabolism biosensors 325–6 microbial spoilage 325–6 microbiological challenge testing 6–7

366

Index

microbiological expert systems 7, 17 microelectromechanical system (MEMS) technology 313–16 micromachining 315 microscope factor (MF) 196 microscope slides 196 microscopy techniques 186–216 application to counter-terrorism 210 comparing detection techniques 209–10 DEFT 186, 187, 188, 194, 196–9 flow cytometry 186–7, 188, 199–208, 209, 210 forms of 192–6 probes 191–2 stains 188–91 MicroStar system 167–8 microtitre plates 219, 243, 245 MicroVal 75, 78, 79 milk, raw 168–9, 197–8 mineral salts 124 miniaturized test systems 334–5 molecular beacon probes 260–1 molecular imprinting polymer (MIP) 322 molecular marker 289–90 molecular methods 84–6 molecular probes 191–2 molecular subtyping 271–93 AFLP analysis and emerging methods 281–4 approaches to 273–8 data interpretation 287–90 future trends 290–1 and identification of pathogens 344–5 PCR-based techniques 273, 278–81, 289, 344, 345 standardised molecular subtyping 285–7 monoclonal antibodies 242, 253 morphological characteristics 333–8 most probable number method (MPN) 130–1, 139–40 mouse time to death bioassay (MBA) 318 multilocus enzyme electrophoresis (MLEE) 283 multilocus sequence typing (MLST) 283, 290 multilocus variable number tandem repeat analysis (MLVA) 283–4 multiple count tube 131 multiplexed separations 54–5 mussels 321–2 mycotoxin 318, 322–3

NADH 298 naturally contaminated food samples 78–80 nested PCR 260, 266 neurotoxic shellfish poisoning (NSP) 318 non-selective enrichment 208 non-viable cells 266 Northern blotting 261 nucleic acid binding dyes 204 nucleic acid sequence-based amplification (NASBA) 261 numerical identification 335–8 Official Control of Foodstuffs (OCF) Directive 94, 95, 107–8 Ogden’s assay for E. coli 158, 159 Ogden’s lysine decarboxylase test 155 oligonucleotide microarrays 262, 265, 290–1 oligonucleotide probes 191–2 operating characteristic (OC) curves 21–2, 29–30 and concentration of microorganisms 34–6 operating characteristic (OC) surface 31 optical transduction 296, 299–301, 302 see also fibre optic sensors ’optimal’ species 333 outbreak investigations 287–90 oxadaic acid (OA) 322 Oxoid Salmonella Rapid Test 139 Oxoid Simple Pre-enrichment and Rapid Isolation New Technology (SPRINT) 139, 255 oxygen electrodes 296–7 oxygen optodes 299–300 Oxyrase 129 paddle-type blenders 57 paralytic shellfish poisoning (PSP) 318, 319 PATH-STIK Salmonella test 223–4 pathogen vs indicator testing 5–6 people 11 peptones 124, 154 performance characteristics 70–4 and standardised methods 74 performance criteria 117 peroxidase, endogenous 253 pH 127 pH optodes 300 phage-based bioluminescent assays 175–8 phage typing 272, 274 phenogram 335

Index phenotyping subtyping methods 272, 274 see also serotyping physiological characteristics 333–8 piezoelectric biosensors 304–6, 311 piezoelectric quartz crystal (PQC) biosensors 313, 314, 322 piezoelectric/acoustic transduction 296, 301–3 plasmid profile analysis 273, 275 plate luminometers 179–80 plating 132–3 polyacrylamide gel electrophoresis (PAGE) 340 polyclonal antibodies 242, 253 polymerase chain reaction (PCR) 259–61, 295 advantages and disadvantages 265 application of validation schemes 84–6 IMS-PCR 209 PCR-based molecular subtyping techniques 273, 278–81, 289, 344, 345 PCR-ELISA 85–6, 255, 261 PCR/REA 86 PCR-RFLP 280–1 PCR-SSCP 281 REP-PCR 280 RT-PCR 260, 266 polymorphic genes 280–1 population sample 22 potentiometric transduction 296 pour-plate method 129–30 practicality 73–4 poultry 170, 309–11 precision 71–2, 110 predictive microbiology (predictive models) 6–7, 12–13, 16–17 prerequisite programmes (PRPs) 4 presence/absence methods 131–3 examples 133–7, 138 primary enrichment (pre-enrichment) 131–2 primary suspension 53–4 primers 259 design 262–3 probability of acceptance (Paccept) 22, 29, 31, 34–6, 38–40, 62–3 probability of rejection (Preject) 22, 38, 39 Probelia 267 Salmonella PCR system 84, 266 process variability reduction 47–8 processing plant zones 42 producer’s risk 22, 29

367

product testing 295 proficiency testing 104–6 ISO/IUPAC/AOAC harmonised protocol 105, 106, 115–19 method validation through 112 protein A 230, 311–12 pulsed-field gel electrophoresis of macrorestricted chromosomal DNA (PFGE) 273, 274, 277–8, 287, 288 PulseNet 286, 290 Pulsifier 57 pyrosequencing 290–1 pyruvate orthophosphate dikinase (PPDK) 173 qualitative methods culture method design 131–3 examples of culture methods 133–7, 138 validation 72, 73 quality assurance (QA) 3–4, 93–119 accreditation 99–100, 106 analytical methods 106–10 Codex Alimentarius Commission 97–8 criteria for valid methods of analysis 110–11 EU legislation 94–7 future trends 113 internal quality control 87–8, 100–4 legislation and codes of practice 94–5 measurement uncertainty 112–13 method validation through proficiency testing 112 proficiency testing see proficiency testing requirements 99–100, 106–10 UK Food Standards Agency 93, 98–9, 105, 106 quality control (QC) 3–4 laboratories and internal quality control 87–8, 100–4 quality limits 38, 39, 40 Quanti-Tray 140 quantitative methods culture method design 129–31 validation 71–2, 73 see also enumeration quartz crystal microbalance (QCM) 313, 322 RABIT 147, 148, 149–50 Raman spectroscopy 342

368

Index

random amplification of polymorphic DNA (RAPD) 278–9, 289 rapid alert kits 16 rapid methods 241–2 Rapid Microbial Quality Assurance (RMQA) system 169 raw materials 8 raw milk 168–9, 197–8 Rayleigh surface wave 302–3 reactive oxygen species (ROS) 128–9 real-time PCR 260–1 recovery supplements 130 ‘red tides’ 318 Redigel 139 redox probes 190 reference materials (control materials) 101–2 reference method, choice of 76 rehydratable film products 137–9 rejection 22 probability of (Preject) 22, 38, 39 repeatability 72, 109 repetitive extragenic palindromic PCR (REP-PCR) 280 reporting results 117 reproducibility 72, 109, 271 resolving power 192 restriction endonuclease analysis (REA) 273–5 restriction enzyme analysis (REA) 86 restriction fragment length polymorphisms (RFLP) 275–6 PCR-RFLP 280–1 resuscitation conditions 128–9 resuscitation treatments 130 retest results 32–3 Reveal test kits 223–4 reverse transcriptase polymerase chain reaction (RT-PCR) 260, 266 RiboPrinter system 276, 277 ribosomal RNA (rRNA) restriction analysis 275–6 ribosomal RNA (rRNA) sequences 343 ribotyping 274, 275–6, 277 risk management and sampling 40–1 sampling and degree of 27–8 RNA 260, 266 robustness (ruggedness) 73 Rotorinser 56–7 routine inspection 41–3 RPLA kits 234 running scores 117, 119 runs, analytical 102

safety 48 see also food safety management; food safety objectives safety limits 38, 39, 40 Salmonella 28, 102, 287 agglutination tests 228–9, 232–3 ATP bioluminescence 176, 178 biosensors 304–11 current official enumeration method 294–5 Dynabeads anti-Salmonella 83–4 electrical methods 152–6, 161 ELFA 227–8 ELISA kits 247–52 LFDs 223–4 Probelia PCR system 84, 266 Rapid test 139 serotyping 338–9 SPRINT 139, 255 standardised culture method 133–4 Taqman PCR system 85 Salmonella Capture-Tek 251 Salmonella Latex kit 232 Salmonella-Tek 249–51 Salmosyst 139 sample distribution frequency 116 samples harmonised protocol for proficiency testing 116 number to be analysed in validation study 77–8, 79 processing for flow cytometry 205–7 separation and concentration see separation and concentration types of 22 sampling 20–51 acceptance sampling when history is known 33–41 acceptance sampling when history is not known 28–33 environmental sampling 41–3 future trends 48 maximising value of test results 45–8 and problem of pathogen distribution 24–8 purpose of 23–4 and risk management 40–1 taking samples 43–5 tightened inspection/skip lot sampling 43 sandwich ELISAs 243–4 Sanitary and Phytosanitary Measures (SPS) Agreement 97 sanitation programmes 8–9

Index Sauerbrey equation 301–2 saxitoxin (STX) 318, 319–20 scanning electron microscopy (SEM) 195–6 screen printed electrodes (SPE) 319, 320–2 selective culture media 125–6, 346 selective enrichment 132, 208 direct 252 selective motility 139 self-assembled monolayers (SAMs) 313–16 sensitivity 73, 252 separation and concentration 52–68 of cells after removal 59–62 future trends 62–4 general approaches to removal, separation and detection 53–5 need for 52–3 ‘primary’ microbial removal methods 55–9 separation efficiency, speed and multiplexed separations 54–5 series piezoelectric quartz crystal sensor (SPQC) 313, 314 serotyping 228–9, 272, 274, 338–9 SET-RPLA 234 shellfish 331–2 biosensors used to detect toxins 318–23 IFREMER system for E. coli 157–8 viruses in 263–4 Sherlock microbial identification system 340 shiga toxin-producing E. coli (STEC) 85–6, 232, 233–4, 248, 262 Shigella dysenteriae 344 side scatter (SSC) 200, 201, 203, 204 SimPlate system 140 single nucleotide polymorphisms (SNPs) 290 single strand conformation polymorphism (SSCP) typing 281 Singlepath LFDs 235 16S rRNA gene sequencing 343 skip lot sampling 43 slide test 230 Slidex Staph kit 230 sodium azide 253 sodium dodecyl sulphate-polyacrylamide gel electrophoresis (SDS-PAGE) 340 solid medium repair 130 solid supports 243

369

Southern blot analyses 261, 276 species 332 specific substrate indicators 126–7 specific substrate media 140 specificity 73, 252–3, 262 Spectate 233 speed of detection 54–5, 193 spiked samples 78–80, 102 spoilage, microbial 325–6 sponges 62 sprays 57–8 spread-plate method 129 SPRINT 139, 255 stains 188–91 conventional 188 viability stains 190–1 standard sanitary operating procedures (SSOPs) 8–9 standardised methods 69–70, 268 culture methods 133–7, 138 molecular subtyping 285–7 performance characteristics and 74 Staphylococcus aureus 28, 36, 248 agglutination tests 229–31 biosensors 311–12 electrical methods 160–1 Staphylococcus aureus enterotoxins (SET) 233, 234, 248 statistical analysis 111 harmonised protocol for proficiency testing 118–19 sticky tapes 57 Stokes shift 189 Stomacher 57 strains 332 source and number of inoculum strains 80 streptavidin 315–16 structural stains 188 substrate indicators, specific 126–7 substrate media, specific 140 subsample 22 surface acoustic wave (SAW) devices 302–3 surface-active agents 126 surface plasmon resonance (SPR) 301, 302 surveillance projects 287–90 surveys 98–9 swabs 55 tachypleus amebocyte lysate (TAL) 313 TaqMan kits 260–1, 267 Taqman Salmonella PCR system 85

370

Index

Technical Barriers to Trade (TBT) Agreement 97 TECRA UNIQUE 247–9, 254 temperature 10, 127 terrorism 210, 326 test results, maximizing value of 45–8 thermophilic Campylobacter species 86 three-class plans 22, 26, 27–8, 32 plan operating characteristics 29, 31–2 tightened inspection 43 time, test 150–1, 253 total bacterial count 167–8 toxin detection 233–4 aflatoxin M1 318, 322–3 algal toxins 318–22 training 11 transduction 296–303 calorimetric 296, 303 electrochemical 296–8 optical 296, 299–301, 302 piezoelectric/acoustic 296, 301–3 see also biosensors transmission electron microscopy (TEM) 195 trimethylamine-N-oxide 153 troubleshooting 15–16 ‘true’ result 117 trueness (bias) 71, 118 tube coagulase test 229–30 tube luminometers 179 two-class plans 22, 26, 27, 28, 32, 62–3 plan operating characteristics 29, 29–31 typability 271 type strain 332 ultrasound 58 uncertainty, measurement 112–13 United Kingdom Accreditation Service (UKAS) 99, 105–6 United Kingdom Food Standards Agency 93, 98–9, 105, 106 universal pre-enrichment broth (UP) 255 validation 69–92 application of validation schemes 81–6 criteria for valid methods of analysis

110–11 definition of performance characteristics 70–4 future trends 88–9 of HACCP study 11 immunological methods 81–4 molecular methods 84–6 through proficiency testing 112 protocols 75–80 requirements of official bodies 109–10 use of validated methods in accredited laboratories 86–8 variability reduction 47–8 variable number tandem repeats (VNTRs) 283–4 variables sampling plans 37–40 verification 11, 14–15 verocytotoxin-producing E. coli (VTEC) 85–6, 232, 233–4, 248, 262 viability stains 190–1 viable cells 266 vibrios 160 Vibrio parahaemolyticus virulence factors 352–3 VIDAS Listeria enzyme-linked fluorescent immunoassay (VIDAS LIS) 81–2 VIP LFD kits 223 virulence factors 127, 351–3 viruses 263–4 Vitek Immuno Diagnostic Assay System (VIDAS) 81–2, 225–8 VTEC-RPLA 234 VTEC Screen 234 water, drinking 169 whole-cell fatty acid analysis 339–40 whole-cell protein analysis 340 World Trade Organisation (WTO) 97 Yersinia 160 enterocolitica 352 z-scores 118 interpretation 119 zones 42

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Bacteriophages in the Control of Food- And Waterborne Pathogens

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Tracing Pathogens in The Food Chain (Woodhead Publishing Series in Food Science, Technology and Nutrition)

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International Handbook of Foodborne Pathogens (Food Science and Technology)

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Foodborne Microbial Pathogens: Mechanisms and Pathogenesis (Food Science Texts Series)

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