Microbiological Identification using MALDI-TOF and Tandem Mass Spectrometry

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Bibliografische Daten
ISBN/EAN: 9781119814078
Sprache: Englisch
Umfang: 560 S., 31.85 MB
Auflage: 1. Auflage 2023
E-Book
Format: EPUB
DRM: Adobe DRM

Beschreibung

Microbiological Identification using MALDI-TOF and Tandem Mass Spectrometry

Detailed resource presenting the capabilities of MALDI mass spectrometry (MS) to industrially and environmentally significant areas in the biosciences

Microbiological Identification using MALDI-TOF and Tandem Mass Spectrometryfulfills a need to bring the key analytical technique of MALDI mass spectrometric analysis into routine practice by specialists and non-specialists, and technicians. It informs and educates established researchers on the development of techniques as applied to industrially significant areas within the biosciences. Throughout the text, the reader is presented with recognized and emerging techniques of this powerful and continually advancing field of analytical science to key areas of importance.

While many scientific papers are reporting new applications of MS-based analysis in specific foci, this book is unique in that it draws together an incredibly diverse range of applications that are pushing the boundaries of MS across the broad field of biosciences.

Contributed to by recognized experts in the field of MALDI MS who have been key players in promoting the advancement and dissemination of authoritative information in this field,Microbiological Identification using MALDI-TOF and Tandem Mass Spectrometrycovers sample topics such as: Oil microbiology, marine and freshwater ecosystems, agricultural and food microbiology, and industrial waste microbiology Bioremediation and landfill sites microbiology, microbiology of inhospitable sites (e.g. Arctic and Antarctic, and alkaline and acidic sites, and hot temperatures) Veterinary, poultry and animals, viral applications of MS, and antibiotic resistance using tandem MS methods Recent developments which are set to transform the use of MS from its success in clinical microbiology to a wide range of commercial and environmental uses

Bridging the gap between measurement and key applications, this text is an ideal resource for industrial and environmental analytical scientists, including technologists in the food industry, pharmaceuticals, and agriculture, as well as biomedical scientists, researchers, clinicians and academics and scientists in bio-resource centers.

Autorenportrait

Haroun N. Shah led the establishment of unique laboratory capabilities, transforming Public Health Laboratory Services identification of new and emerging threats through mass spectrometry combined with molecular technologies between 1999-2015. After his retirement, he continued to provide expert advice and training to industry and academia to advance innovations and embed new applications of proteomics across biosciences.

Saheer E. Gharbia is the Deputy Director of Gastrointestinal Infection and Food Safety for the UK Health Security Agency and has led the COVID-19 Genomics Programme to support the response to the COVID-19 pandemic. She continues to develop tools for the analysis and interpretation of complex biological and pathogenic traits and works across the One Health Scientific Community to embed common surveillance mechanisms to detect and track emerging threats.

Ajit J. Shah is a Professor in Bioanalytical Science in the Department of Natural Science, Middlesex University, UK.

Erika Y. Tranfield is Scientific Affairs Manager Microbiology at Bruker.

K. Clive Thompsonis Chief Scientist at ALS, Life Sciences, UK, an analytical testing organisation in the UK and Ireland.

Inhalt

List of Contributors xix

Preface xxiii

1 Progress in the Microbiological Applications of Mass Spectrometry: from Electron Impact to Soft Ionization Techniques, MALDI- TOF MS and Beyond 1
Emmanuel Raptakis, Ajit J. Shah, Saheer E. Gharbia, Laila M.N. Shah, Simona Francese, Erika Y. Tranfield, Louise Duncan, and Haroun N. Shah

1.1 Introduction 1

1.1.1 Algorithms Based upon Traditional Carbohydrate Fermentation Tests 1

1.1.2 Dynamic Changes in the Chemotaxonomic Era (c. 19701985) through the Lens of the Genus Bacteroides 2

1.1.3 Microbial Lipids as Diagnostic Biomarkers; Resurgence of Interest in MALDI- TOF MS with Advances in Lipidomics 3

1.2 The Dawn of MALDI- TOF MS: Establishing Proof of Concept for Diagnostic Microbiology 7

1.2.1 Development of a MALDI- TOF MS Database for Human Infectious Diseases 10

1.2.2 The Dilemma with Clostridium difficile: from Intact Cells to Intracellular Proteins, MALDI- TOF MS Enters a New Phase 13

1.3 Linear/Reflectron MALDI- TOF MS to Tandem Mass Spectrometry 15

1.3.1 Tandem MALDI- TOF Mass Spectrometry 17

1.3.2 Electrospray- based Mass Analysers 18

1.3.3 Tandem Mass Spectrometry 18

1.3.4 Mass Spectrometry- based Proteomics 19

1.3.5 Case Study: LC- MS/MS of Biothreat Agents, Proteomes of Pathogens and Strain- level Tying Using Bottom- up and Top- down Proteomics 19

1.3.6 Discovery Proteomics 21

1.3.7 Targeted Proteomics 22

1.3.8 Top- down Proteomics 23

1.3.9 Targeted Protein Quantitation 24

1.4 The Application of MALDI- MS Profiling and Imaging in Microbial Forensics: Perspectives 25

1.4.1 MALDI- MSP of Microorganisms and their Products 26

1.5 Hydrogen/Deuterium Exchange Mass Spectrometry in Microbiology 27

1.6 The Omnitrap, a Novel MS Instrument that Combines Many Applications of Mass Spectrometry 29

References 35

2 Machine Learning in Analysis of Complex Flora Using Mass Spectrometry 45
Luis Mancera, Manuel J. Arroyo, Gema Méndez, Omar Belgacem, Belén Rodríguez-Sánchez, and Marina Oviaño

2.1 Introduction 45

2.2 An Improved MALDI- TOF MS Data Analysis Pipeline for the Identification of Carbapenemase- producing Klebsiella pneumoniae 47

2.2.1 Motivation 47

2.2.2 Materials and Methods 47

2.2.3 Spectra Acquisition 50

2.2.4 Results 51

2.2.5 Discussion 54

2.3 Detection of Vancomycin- Resistant Enterococcus faecium 55

2.3.1 Motivation 55

2.3.2 Materials and Methods 56

2.3.3 Results and Discussion 59

2.4 Detection of Azole Resistance in Aspergillus fumigatus Complex Isolates 59

2.4.1 Introduction 59

2.4.2 Material and Methods 60

2.4.3 Results 60

2.4.4 Discussion 64

2.5 Peak Analysis for Discrimination of Cryptococcus neoformans Species Complex and their Interspecies Hybrids 64

2.5.1 Motivation 64

2.5.2 Material and Methods 65

2.5.3 Results and Discussion 65

2.6 Conclusions 66

References 67

3 Top- down Identification of Shiga Toxin (and Other Virulence Factors and Biomarkers) from Pathogenic E. coli using MALDI- TOF/TOF Tandem Mass Spectrometry 71
Clifton K. Fagerquist

3.1 Introduction 71

3.2 Decay of Metastable Peptide and Protein Ions by the Aspartic Acid Effect 72

3.3 Energy Deposition during Desorption/Ionization by MALDI 75

3.4 Protein Denaturation and Fragmentation Efficiency of PSD 76

3.5 Arginine and its Effect on Fragment Ion Detection and MS/MS Spectral Complexity 79

3.6 Inducing Gene Expression in Wild- type Bacteria for Identification by Top- Down Proteomic Analysis 82

3.7 Top- down Proteomic Identification of B- Subunit of Shiga Toxin from STEC Strains 83

3.8 Furin- digested Shiga Toxin and Middle- down Proteomics 85

3.9 Top- down Identification of an Immunity Cognate of a Bactericidal Protein Produced from a STEC Strain 87

3.10 Lc- Maldi- Tof/tof 88

3.11 Conclusions 89

References 94

4 Liquid Atmospheric Pressure (LAP) MALDI MS(/MS) Biomolecular Profiling for Large- scale Detection of Animal Disease and Food Adulteration and Bacterial Identification 97
Cristian Piras and Rainer Cramer

4.1 Introduction 97

4.2 Background to LAP- MALDI MS 98

4.3 Bacterial Identification by LAP- MALDI MS 102

4.4 Food Adulteration and Milk Quality Analysis by LAP- MALDI MS 105

4.5 Animal Disease Detection by LAP- MALDI MS 108

4.6 Antibiotic Resistance Detection of Microbial Consortia by Lap- Maldi Ms 110

4.7 Future Directions for LAP- MALDI MS Applications 113

References 114

5 Development of a MALDI- TOF Mass Spectrometry Test for Viruses 117
Ray K. Iles, Jason K. Iles, and Raminta Zmuidinaite

5.1 Introduction 117

5.2 Understanding the Systems Biology of the Virus and Viral Infections 120

5.3 Understanding the Nature of Viral Proteins and Molecular Biology 121

5.4 Virion Protein Solubilization and Extraction 123

5.5 Sampling and Virion Enrichment 123

5.6 Peak Identification: Quantification and Bioinformatics 125

5.7 Promise and Pitfalls of Machine Learning Bioinformatics 126

5.8 Accelerating MALDI- TOF Assay Protocol Development Using Pseudotypes/ pseudoviruses 128

5.9 Understanding the Operational Parameters of your MALDI- TOF MS 130

5.10 Understanding the Operational Requirements of the Clinical Testing Laboratory: Validation and International Accreditation 131

5.10.1 Limitation and Advantages of CLIA LDTs 131

5.11 MALDI- TOF MS Screening Test for SARS- CoV- 2s 132

5.11.1 Prepare Positive Control 132

5.11.2 Prepare Gargle- saliva Samples 132

5.11.3 Viral Particle Enrichment 132

5.11.4 Dissolution of Virions and Solubilization of Viral Proteins 133

5.11.5 Maldi- Tof Ms 133

5.12 CLIA LDT Validation of a MALDI- TOF MS Test for SARS- CoV- 2 133

5.12.1 Limit of Detection 134

5.12.2 Interfering Substances and Specificity 134

5.12.3 Clinical Performance Evaluation 136

5.12.3.1 Establishing Operational Cut- off Values 137

5.12.3.2 Direct comparison with an RT- PCR SARS- CoV- 2 test 138

5.12.3.3 Internal Sampling Quality Control 138

5.12.3.4 Daily System Quality Control 138

5.12.4 Reproducibility 139

5.12.5 Stability 139

5.12.6 Validation Disposition 141

5.12.6.1 Global Biosecurity 141

References 142

6 A MALDI- TOF MS Proteotyping Approach for Environmental, Agricultural and Food Microbiology 147
Hiroto Tamura

6.1 Introduction 147

6.2 Serotyping of Salmonella enterica Subspecies enterica 151

6.3 Discrimination of the Lineages of Listeria monocytogenes and Species of

Listeria 161

6.4 Discrimination of the Bacillus cereus Group and Identification of Cereulide 167

6.5 Identification of Alkylphenol Polyethoxylate- degrading Bacteria in the Environment 171

6.6 Conclusions and Future Perspectives 173

References 175

7 Diversity, Transmission and Selective Pressure on the Proteome of Pseudomonas aeruginosa 183
Louise Duncan, Ajit J. Shah, Malcolm Ward, Radhey S. Gupta, Bashudev Rudra, Alvin Han, Ken Bruce, and Haroun N. Shah

7.1 Introduction: Diversity 183

7.1.1 P. aeruginosa: from Atypical to Diverse 183

7.1.2 Phenotypical Diversity in Isolates from Different Environments 183

7.1.2.1 Clinical Isolates 183

7.1.2.2 Environmental Isolates 184

7.1.2.3 Veterinary Isolates 184

7.1.2.4 Comparing P. aeruginosa Phenotypical Profiles from Different Environments 184

7.1.2.5 Antibiotic Resistance in P. aeruginosa from Different Environments 186

7.1.3 The Relationship Between Phenotypical and Proteomic Diversity 186

7.1.4 Techniques and Practical Considerations for Studying Proteomic Diversity 186

7.1.5 Proteomic Diversity and MS Applications 189

7.2 Transmission 189

7.2.1 The History of P. aeruginosa Transmission 189

7.2.2 Proteomics and P. aeruginosa Transmission 191

7.2.3 The Impact of Proteomic Diversity on Transmission 191

7.3 Selective Pressures on the Proteome 192

7.3.1 Tandem MS Systems for Studying Selected Proteomes 192

7.3.2 Microenvironment Selection 192

7.3.2.1 The Human Body and CF Lung 192

7.3.2.2 The Natural Environment 192

7.3.3 Antimicrobial Selection 193

7.4 Conclusions on Studies of the Proteome 193

7.5 Genomic Studies on Pseudomonas aeruginosa Strains Revealing the Presence of Two Distinct Clades 195

7.5.1 Phylogenomic Analysis Reveals the Presence of Two Distinct Clades Within

P. aeruginosa 196

7.5.2 Identification of Molecular Markers Distinguishing the Two P. aeruginosa

Clades 198

7.6 Final Conclusions 201

References 201

8 Characterization of Biodegradable Polymers by MALDI- TOF MS 211
Hiroaki Sato

8.1 Introduction 211

8.2 Structural Characterization of Poly(- caprolactone) Using Maldi- Tof Ms 212

8.3 Biodegradation Profiles of a Terminal- modified PCL Observed by Maldi- Tof Ms 216

8.4 Bacterial Biodegradation Mechanisms of Non- ionic Surfactants 218

8.5 Advanced Molecular Characterization by High- resolution MALDI- TOF MS Combined with KMD Analysis 221

8.6 Structural Characterization of High- molecular- weight Biocopolyesters by High- resolution MALDI- TOF MS Combined with KMD Analysis 225

References 228

9 Phytoconstituents and Antimicrobiological Activity 231
Philip L. Poole and Giulia T.M. Getti

9.1 Introduction to Phytochemicals 231

9.2 An Application to Bacteriology 233

9.2.1 Allicin Leads to a Breakdown of the Cell Wall of Staphylococcus aureus 234

9.3 Applications to Parasitology 239

9.3.1 Drug Discovery 239

9.3.2 Parasite Characterization 240

9.4 A Proteomic Approach: Leishmania Invasion of Macrophages 240

9.5 Intracellular Leishmania Amastigote Spreading between Macrophages 243

9.6 Potential Virus Applications 244

Acknowledgements 246

References 246

10 Application of MALDI- TOF MS in Bioremediation and Environmental Research 255
Cristina Russo and Diane Purchase

10.1 Introduction 255

10.2 Microbial Identification: Molecular Methods and MALDI- TOF MS 257

10.2.1 PCR- based Methods 258

10.2.2 Maldi- Tof Ms 260

10.3 Combination of MALDI- TOF MS with Other Methods for the Identification of Microorganisms 261

10.4 Application of MALDI- TOF MS in Environmental and Bioremediation Studies 263

10.4.1 The Atmospheric Environment 263

10.4.2 The Aquatic Environment 263

10.4.3 The Terrestrial Environment 265

10.4.4 Bioremediation Research Applications 266

10.5 Microbial Products and Metabolite Activity 268

10.6 Challenges of Environmental Applications 270

10.7 Opportunities and Future Outlook 271

10.8 Conclusions 272

References 273

11 From Genomics to MALDI- TOF MS: Diagnostic Identification and Typing of Bacteria in Veterinary Clinical Laboratories 283
John Dustin Loy and Michael L. Clawson

11.1 Introduction 283

11.2 Genomics 284

11.3 Defining Bacterial Species Through Genomics 286

11.4 Maldi- Tof Ms 287

11.5 Combining Genomics with MALDI- TOF MS to Classify Bacteria at the Subspecies Level 290

11.6 Data Exploration with MALDI- TOF MS 292

11.7 Validation of Typing Strategies 294

11.8 Future Directions 294

References 295

12 MALDI- TOF MS Analysis for Identification of Veterinary Pathogens from Companion Animals and Livestock Species 303
Dorina Timofte, Gudrun Overesch, and Joachim Spergser

12.1 Veterinary Diagnostic Laboratories and the MALDI- TOF Clinical Microbiology Revolution 303

12.1.1 MALDI- TOF MS: Reshaping the Workflow in Clinical Microbiology 304

12.1.2 Identification of Bacterial Pathogens Directly from Clinical Specimens 305

12.1.3 Prediction of Antimicrobial Resistance 307

12.1.4 Impact in Veterinary Hospital Biosecurity and Epidemiological Surveillance 308

12.2 Identification of Campylobacter spp. and Salmonella spp. in Routine Clinical Microbiology Laboratories 309

12.2.1 General Aspects on the Importance of Species/Subspecies and Serovar Identification of Campylobacter spp. and Salmonella spp. 309

12.2.2 General Aspects on Influence of Media/Culture Environment on Bacterial Species Identification by MALDI- TOF MS 311

12.2.3 Possibilities and Limits of Identification of Campylobacter spp. by Maldi- Tof Ms 312

12.2.3.1 Thermophilic Campylobacter spp. 312

12.2.3.2 Human- hosted Campylobacter Species 313

12.2.3.3 Campylobacter spp. of Veterinary Importance 313

12.2.4 Possibilities and Limits of Identification of Salmonella spp. by Maldi- Tof Ms 314

12.3 Identification and Differentiation of Mycoplasmas Isolated from Animals 316

12.3.1 Animal Mycoplasmas at a Glance 316

12.3.2 Laboratory Diagnosis of Animal Mycoplasmas 317

12.3.3 MALDI- TOF MS for the Identification of Animal Mycoplasmas 318

References 322

13 MALDI- TOF MS: from Microbiology to Drug Discovery 333
Ruth Walker, Maria E. Dueñas, Alan Ward, and Kaveh Emami

13.1 Introduction 333

13.2 Microbial Fingerprinting 334

13.2.1 Environmental 335

13.2.1.1 Actinobacteria 335

13.2.1.2 Aquatic Microorganisms 335

13.2.2 Terrestrial Microbiology 337

13.2.3 Food and Food Safety 338

13.2.3.1 Food Storage Effect on Identification 338

13.2.3.2 Insects 339

13.3 Mammalian Cell Fingerprinting 339

13.3.1 Differentiation of Cell Lines and Response to Stimuli 339

13.3.2 Cancer Diagnostics 341

13.3.3 Biomarkers 342

13.4 Drug Discovery Using MALDI- TOF 342

13.4.1 Enzymatic Assays 343

13.4.1.1 Targeting Antibiotic Resistance Using MALDI- TOF MS Enzymatic Assays 343

13.4.2 Cellular- based Assays for Drug Discovery 344

13.4.3 Automation in Drug Discovery 345

13.4.4 Assay Multiplexing 345

13.4.5 MS Imaging in Drug Discovery 346

13.4.6 Maldi- 2 346

13.5 Limitations/Challenges, Future Outlook, and Conclusions 347

13.5.1 Sample Preparation Limitations 347

13.5.1.1 Matrix 347

13.5.1.2 Interference from Low- molecular- mass Matrix Clusters 348

13.5.1.3 Buffer Compatibility 348

13.5.1.4 TOF Mass Resolution Limitations 348

13.5.2 Data Analysis and Application of Machine Learning 348

13.6 Future Outlook/Conclusions 349

References 350

14 Rapid Pathogen Identification in a Routine Food Laboratory Using High- throughput MALDI- TOF Mass Spectrometry 359
Andrew Tomlin

14.1 Introduction 359

14.2 MALDI- TOF MS in Food Microbiology 359

14.3 Review of Existing Confirmation Techniques and Comparison to Maldi- Tof Ms 362

14.4 Strain Typing Using MALDI- TOF MS 364

14.5 Verification Trial 365

14.6 Limitations of MALDI- TOF MS Strain Typing and Future Studies 369

14.7 Listeria Detection by MALDI- TOF MS 370

14.8 Trial Sample Preparation Procedure 370

14.9 Initial Trial 374

14.10 Limit of Detection Trial 375

14.11 Method Optimization, Further Prospects, and Conclusions 376

References 379

15 Detection of Lipids in the MALDI Negative Ion Mode for Diagnostics, Food Quality Control, and Antimicrobial Resistance 381
Yi Liu, Jade Pizzato, and Gerald Larrouy-Maumus

15.1 Introduction 381

15.2 Applications of Lipids in Clinical Microbiology Diagnostics 382

15.2.1 Use of Cell Envelope Lipids for Bacterial Identification 382

15.2.2 Detection of Cell Envelope Lipids and their Modifications to Determine Bacterial Drug Susceptibility 384

15.2.3 Detection of Lipids in MALDI Negative Ion Mode for Fungal Identification 387

15.2.4 Detection of Lipids in MALDI Negative Ion Mode for Parasite Identification 387

15.2.5 Detection of Lipids in MALDI Negative Ion Mode for Virus Identification 388

15.3 Applications of the Detection of Lipids in Negative Ion Mode MALDI- MS in Cancer Studies 388

15.3.1 Lipids and MALDI Negative Ion Mode for Diagnosis of Lung Cancer 389

15.3.2 Lipids and MALDI Negative Ion Mode for the Diagnosis of Breast Cancer 390

15.3.3 Lipids and MALDI Negative Ion Mode for Diagnosis of Other Cancers 391

15.3.4 Lipids and MALDI Negative Ion Mode for DrugCell Interactions and Prognosis 392

15.4 Applications of the Detection of Lipids and MALDI- MS in Alzheimers Disease Studies 392

15.5 Applications of MALDI in Negative Ion Mode and the Detection of Lipids in Toxicology 393

15.6 Lipids and MALDI Negative Ion Mode for Food Fraud Detection 394

15.7 Conclusions and Future Development of Lipids and their Detection in MALDI in Negative Ion Mode 395

Acknowledgments 395

References 397

16 Use of MALDI- TOF MS in Water Testing Laboratories 405
Matthew Jones, Nadia Darwich, Rachel Chalmers, K. Clive Thompson, and Bjorn Nielsen

16.1 Introduction 405

16.2 Application in a Drinking Water Laboratory 408

16.2.1 Introduction 408

16.2.2 Method Validation 409

16.2.2.1 Reference Database Validation 410

16.2.2.2 Method Comparison 411

16.2.2.3 Agar Assessment 412

16.2.3 Application Within Drinking Water Laboratory 412

16.3 Application in Water Hygiene and Environmental Laboratory Testing 413

16.3.1 Introduction 413

16.3.2 Legionella Testing 414

16.3.3 Wastewater and Sewage Sludge Microbiology 415

16.3.4 Healthcare Water Testing 416

16.3.5 Investigative Analysis 417

16.3.6 Method Validation 417

16.3.6.1 Characterization of Intended Use 417

16.3.6.2 Library Assessment 418

16.3.6.3 Assessment of Variables 418

16.3.6.4 Comparison Assessment 419

16.3.6.5 Ongoing Verification 420

16.3.7 Conclusion on Suitability for Use in an Environmental Testing Laboratory 422

16.4 Potential Application for Cryptosporidium Identification 423

References 425

17 A New MALDI- TOF Database Based on MS Profiles of Isolates in Icelandic Seawaters for Rapid Identification of Marine Strains 431
Sibylle Lebert, Viggó Þór Marteinsson, and Pauline Vannier

17.1 Introduction 431

17.2 Selection and Cultivation of the Strains 432

17.3 Genotypic Identification 433

17.4 MALDI- TOF MS Data Acquisition and Database Creation 438

17.5 Verification of the Accuracy of the Home- made Database 441

17.6 Conclusions 448

Funding 448

References 449

18 MALDI- TOF MS Implementation Strategy for a Pharma Company Based upon a Network Microbial Identification Perspective 453
Lynn Johnson, Christoph Hansy, and Hilary Chan

18.1 Introduction 453

18.1.1 Microbial Identifications from a Pharmaceutical Industry Perspective 453

18.1.2 Historical Evolution 453

18.2 Regulatory Requirements/Guidance for Microbial Identification 455

18.3 Strategic Approaches to MALDI- TOF Implementation Within the Modern Microbial Methods Framework 455

18.3.1 Incorporation of MALDI- TOF into a Technical Evaluation Roadmap 455

18.3.2 Initial Implementation Planning Stage 456

18.3.2.1 Roles and Responsibilities (Global/Local, Partners/IT, Stakeholders) 456

18.3.2.2 Considerations When Selecting a Vendor/Model 457

18.3.2.3 Overall Identification Process Flow and MALDI- TOF as the Defined Application 458

18.3.2.4 Benefits of an In- house System for Pharmaceutical Companies Compared with Outsourcing 458

18.3.2.5 The Center of Excellence (CoE) Approach 460

18.3.2.6 Building a Business Case for the MALDI- TOF as a Network Strategy 461

18.3.3 Implementation Strategy From Feasibility Studies to Global Deployment 463

18.3.3.1 Pilot Trials/Feasibility 463

18.3.3.2 Risk Assessment/Risk- based Validation Approach 463

18.3.3.3 Network Validation Approach 464

18.4 Conclusions 467

18.a Appendix 468

References 470

19 MALDI- TOF MS Microbial Identification as Part of a Contamination Control Strategy for Regulated Industries 473
Christine E. Farrance and Prasanna D. Khot

19.1 Industry Perspective 473

19.1.1 Introduction to Regulated Industries 473

19.1.2 Contamination Control Strategy 474

19.1.3 Tracking and Trending EM Data 474

19.1.4 Drivers for Microbial Identification 476

19.1.5 Level of Resolution of an Identification 476

19.1.6 Global Harmonization 477

19.1.7 Validation Requirements for Regulated Industries 477

19.1.8 Summary 478

19.2 Technical Perspective 478

19.2.1 Identification Technologies 478

19.2.2 Phenotypic Systems 479

19.2.3 Proteotypic Systems 479

19.2.4 Genotypic Systems 479

19.2.5 The Importance of the Reference Database 480

19.2.6 MALDI- TOF in Regulated Industries 480

19.2.7 Outsourcing 480

19.2.8 Summary 481

19.3 MALDI- TOF MS Microbial Identification Workflow at a High- throughput Laboratory 481

19.3.1 MALDI- TOF MS Principles for Microbial Identification 481

19.3.2 Organism Cultivation for Microbial Identification with MALDI- TOF MS 482

19.3.3 Sample Preparation for Microbial Identification with MALDI- TOF MS 482

19.3.4 Sample Processing Workflow for Microbial Identification 482

19.3.5 Data Interpretation 483

19.3.6 Importance of a Sequence- based Secondary (or Fall- through) Identification System 484

19.4 MALDI- TOF MS Library Development and Coverage 485

19.4.1 Importance of Library Development Under a Quality System 485

19.4.2 Targeted Library Development for Gram- positive Bacteria and Water Organisms 488

19.4.2.1 Case Study 1: Impact of MALDI- TOF MS Library Coverage for Organisms of the Family Bacillaceae 488

19.4.2.2 Case Study 2: Impact of MALDI- TOF MS Library Coverage for Organisms Recovered from Water Systems 489

19.4.3 Supplemental and Custom MALDI- TOF MS Libraries 489

19.5 Comparison of MALDI- TOF MS with Other Microbial Identification Methods 490

19.6 Future Perspectives 490

References 491

20 Identification of Mold Species and Species Complex from the Food Environment Using MALDI- TOF MS 497
Victoria Girard, Valérie Monnin, Nolwenn Rolland, Jérôme Mounier, and Jean-Luc Jany

20.1 Fungal Taxonomy 497

20.1.1 Defining What Is a Fungal Species 497

20.1.2 Fungal Speciation within a Food Context 498

20.1.3 Delimiting Species 498

20.1.4 Foodborne Fungi within the Fungal Tree of Life 499

20.2 Impact of Molds in Food 500

20.2.1 Filamentous Fungi in Fermented Foods 500

20.2.2 Filamentous Fungi with Undesirable Impacts on Food Quality and Safety 500

20.3 Identification of Fungi 505

20.4 Identification of Foodborne Molds Using MALDI- TOF MS 506

20.4.1 Sample Preparation 506

20.4.2 Database Building and Performance of MALDI- TOF for Identification of Foodborne Molds 507

20.4.2.1 Database Building 507

20.4.2.2 Performance of Foodborne Mold Database 508

References 509

Index 515

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