Microbiological Identification using MALDI-TOF and Tandem Mass Spectrometry

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. 1970–1985) 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(ε- 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 Drug–Cell Interactions and Prognosis 392 15.4 Applications of the Detection of Lipids and MALDI- MS in Alzheimer’s 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