Microbiological Identification using MALDI-TOF and Tandem Mass Spectrometry

Industrial and Environmental Applications

Inbunden, Engelska, 2023

AvHaroun N. Shah,Saheer Gharbia,Ajit J. Shah,Erika Y. Tranfield,K. Clive Thompson

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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 Spectrometry fulfills 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 Spectrometry covers sample topics such as: Oil microbiology, marine and freshwater ecosystems, agricultural and food microbiology, and industrial waste microbiologyBioremediation 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 methodsRecent developments which are set to transform the use of MS from its success in clinical microbiology to a wide range of commercial and environmental usesBridging 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.

Produktinformation

Utgivningsdatum2023-04-27
Mått170 x 244 x 35 mm
Vikt1 219 g
FormatInbunden
SpråkEngelska
Antal sidor560
FörlagJohn Wiley & Sons Inc
ISBN9781119814054

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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 Thompson is Chief Scientist at ALS, Life Sciences, UK, an analytical testing organisation in the UK and Ireland.

List of Contributors xixPreface xxiii1 Progress in the Microbiological Applications of Mass Spectrometry: from Electron Impact to Soft Ionization Techniques, MALDI- TOF MS and Beyond 1Emmanuel Raptakis, Ajit J. Shah, Saheer E. Gharbia, Laila M.N. Shah, Simona Francese, Erika Y. Tranfield, Louise Duncan, and Haroun N. Shah1.1 Introduction 11.1.1 Algorithms Based upon Traditional Carbohydrate Fermentation Tests 11.1.2 Dynamic Changes in the Chemotaxonomic Era (c. 1970–1985) through the Lens of the Genus Bacteroides 21.1.3 Microbial Lipids as Diagnostic Biomarkers; Resurgence of Interest in MALDI- TOF MS with Advances in Lipidomics 31.2 The Dawn of MALDI- TOF MS: Establishing Proof of Concept for Diagnostic Microbiology 71.2.1 Development of a MALDI- TOF MS Database for Human Infectious Diseases 101.2.2 The Dilemma with Clostridium difficile: from Intact Cells to Intracellular Proteins, MALDI- TOF MS Enters a New Phase 131.3 Linear/Reflectron MALDI- TOF MS to Tandem Mass Spectrometry 151.3.1 Tandem MALDI- TOF Mass Spectrometry 171.3.2 Electrospray- based Mass Analysers 181.3.3 Tandem Mass Spectrometry 181.3.4 Mass Spectrometry- based Proteomics 191.3.5 Case Study: LC- MS/MS of Biothreat Agents, Proteomes of Pathogens and Strain- level Tying Using Bottom- up and Top- down Proteomics 191.3.6 Discovery Proteomics 211.3.7 Targeted Proteomics 221.3.8 Top- down Proteomics 231.3.9 Targeted Protein Quantitation 241.4 The Application of MALDI- MS Profiling and Imaging in Microbial Forensics: Perspectives 251.4.1 MALDI- MSP of Microorganisms and their Products 261.5 Hydrogen/Deuterium Exchange Mass Spectrometry in Microbiology 271.6 The Omnitrap, a Novel MS Instrument that Combines Many Applications of Mass Spectrometry 29References 352 Machine Learning in Analysis of Complex Flora Using Mass Spectrometry 45Luis Mancera, Manuel J. Arroyo, Gema Méndez, Omar Belgacem, Belén Rodríguez-Sánchez, and Marina Oviaño2.1 Introduction 452.2 An Improved MALDI- TOF MS Data Analysis Pipeline for the Identification of Carbapenemase- producing Klebsiella pneumoniae 472.2.1 Motivation 472.2.2 Materials and Methods 472.2.3 Spectra Acquisition 502.2.4 Results 512.2.5 Discussion 542.3 Detection of Vancomycin- Resistant Enterococcus faecium 552.3.1 Motivation 552.3.2 Materials and Methods 562.3.3 Results and Discussion 592.4 Detection of Azole Resistance in Aspergillus fumigatus Complex Isolates 592.4.1 Introduction 592.4.2 Material and Methods 602.4.3 Results 602.4.4 Discussion 642.5 Peak Analysis for Discrimination of Cryptococcus neoformans Species Complex and their Interspecies Hybrids 642.5.1 Motivation 642.5.2 Material and Methods 652.5.3 Results and Discussion 652.6 Conclusions 66References 673 Top- down Identification of Shiga Toxin (and Other Virulence Factors and Biomarkers) from Pathogenic E. coli using MALDI- TOF/TOF Tandem Mass Spectrometry 71Clifton K. Fagerquist3.1 Introduction 713.2 Decay of Metastable Peptide and Protein Ions by the Aspartic Acid Effect 723.3 Energy Deposition during Desorption/Ionization by MALDI 753.4 Protein Denaturation and Fragmentation Efficiency of PSD 763.5 Arginine and its Effect on Fragment Ion Detection and MS/MS Spectral Complexity 793.6 Inducing Gene Expression in Wild- type Bacteria for Identification by Top- Down Proteomic Analysis 823.7 Top- down Proteomic Identification of B- Subunit of Shiga Toxin from STEC Strains 833.8 Furin- digested Shiga Toxin and Middle- down Proteomics 853.9 Top- down Identification of an Immunity Cognate of a Bactericidal Protein Produced from a STEC Strain 873.10 Lc- Maldi- Tof/tof 883.11 Conclusions 89References 944 Liquid Atmospheric Pressure (LAP) – MALDI MS(/MS) Biomolecular Profiling for Large- scale Detection of Animal Disease and Food Adulteration and Bacterial Identification 97Cristian Piras and Rainer Cramer4.1 Introduction 974.2 Background to LAP- MALDI MS 984.3 Bacterial Identification by LAP- MALDI MS 1024.4 Food Adulteration and Milk Quality Analysis by LAP- MALDI MS 1054.5 Animal Disease Detection by LAP- MALDI MS 1084.6 Antibiotic Resistance Detection of Microbial Consortia by Lap- Maldi Ms 1104.7 Future Directions for LAP- MALDI MS Applications 113References 1145 Development of a MALDI- TOF Mass Spectrometry Test for Viruses 117Ray K. Iles, Jason K. Iles, and Raminta Zmuidinaite5.1 Introduction 1175.2 Understanding the Systems Biology of the Virus and Viral Infections 1205.3 Understanding the Nature of Viral Proteins and Molecular Biology 1215.4 Virion Protein Solubilization and Extraction 1235.5 Sampling and Virion Enrichment 1235.6 Peak Identification: Quantification and Bioinformatics 1255.7 Promise and Pitfalls of Machine Learning Bioinformatics 1265.8 Accelerating MALDI- TOF Assay Protocol Development Using Pseudotypes/ pseudoviruses 1285.9 Understanding the Operational Parameters of your MALDI- TOF MS 1305.10 Understanding the Operational Requirements of the Clinical Testing Laboratory: Validation and International Accreditation 1315.10.1 Limitation and Advantages of CLIA LDTs 1315.11 MALDI- TOF MS Screening Test for SARS- CoV- 2s 1325.11.1 Prepare Positive Control 1325.11.2 Prepare Gargle- saliva Samples 1325.11.3 Viral Particle Enrichment 1325.11.4 Dissolution of Virions and Solubilization of Viral Proteins 1335.11.5 Maldi- Tof Ms 1335.12 CLIA LDT Validation of a MALDI- TOF MS Test for SARS- CoV- 2 1335.12.1 Limit of Detection 1345.12.2 Interfering Substances and Specificity 1345.12.3 Clinical Performance Evaluation 1365.12.3.1 Establishing Operational Cut- off Values 1375.12.3.2 Direct comparison with an RT- PCR SARS- CoV- 2 test 1385.12.3.3 Internal Sampling Quality Control 1385.12.3.4 Daily System Quality Control 1385.12.4 Reproducibility 1395.12.5 Stability 1395.12.6 Validation Disposition 1415.12.6.1 Global Biosecurity 141References 1426 A MALDI- TOF MS Proteotyping Approach for Environmental, Agricultural and Food Microbiology 147Hiroto Tamura6.1 Introduction 1476.2 Serotyping of Salmonella enterica Subspecies enterica 1516.3 Discrimination of the Lineages of Listeria monocytogenes and Species ofListeria 1616.4 Discrimination of the Bacillus cereus Group and Identification of Cereulide 1676.5 Identification of Alkylphenol Polyethoxylate- degrading Bacteria in the Environment 1716.6 Conclusions and Future Perspectives 173References 1757 Diversity, Transmission and Selective Pressure on the Proteome of Pseudomonas aeruginosa 183Louise Duncan, Ajit J. Shah, Malcolm Ward, Radhey S. Gupta, Bashudev Rudra, Alvin Han, Ken Bruce, and Haroun N. Shah7.1 Introduction: Diversity 1837.1.1 P. aeruginosa: from ‘Atypical’ to Diverse 1837.1.2 Phenotypical Diversity in Isolates from Different Environments 1837.1.2.1 Clinical Isolates 1837.1.2.2 Environmental Isolates 1847.1.2.3 Veterinary Isolates 1847.1.2.4 Comparing P. aeruginosa Phenotypical Profiles from Different Environments 1847.1.2.5 Antibiotic Resistance in P. aeruginosa from Different Environments 1867.1.3 The Relationship Between Phenotypical and Proteomic Diversity 1867.1.4 Techniques and Practical Considerations for Studying Proteomic Diversity 1867.1.5 Proteomic Diversity and MS Applications 1897.2 Transmission 1897.2.1 The History of P. aeruginosa Transmission 1897.2.2 Proteomics and P. aeruginosa Transmission 1917.2.3 The Impact of Proteomic Diversity on Transmission 1917.3 Selective Pressures on the Proteome 1927.3.1 Tandem MS Systems for Studying Selected Proteomes 1927.3.2 Microenvironment Selection 1927.3.2.1 The Human Body and CF Lung 1927.3.2.2 The Natural Environment 1927.3.3 Antimicrobial Selection 1937.4 Conclusions on Studies of the Proteome 1937.5 Genomic Studies on Pseudomonas aeruginosa Strains Revealing the Presence of Two Distinct Clades 1957.5.1 Phylogenomic Analysis Reveals the Presence of Two Distinct Clades WithinP. aeruginosa 1967.5.2 Identification of Molecular Markers Distinguishing the Two P. aeruginosaClades 1987.6 Final Conclusions 201References 2018 Characterization of Biodegradable Polymers by MALDI- TOF MS 211Hiroaki Sato8.1 Introduction 2118.2 Structural Characterization of Poly(ε- caprolactone) Using Maldi- Tof Ms 2128.3 Biodegradation Profiles of a Terminal- modified PCL Observed by Maldi- Tof Ms 2168.4 Bacterial Biodegradation Mechanisms of Non- ionic Surfactants 2188.5 Advanced Molecular Characterization by High- resolution MALDI- TOF MS Combined with KMD Analysis 2218.6 Structural Characterization of High- molecular- weight Biocopolyesters by High- resolution MALDI- TOF MS Combined with KMD Analysis 225References 2289 Phytoconstituents and Antimicrobiological Activity 231Philip L. Poole and Giulia T.M. Getti9.1 Introduction to Phytochemicals 2319.2 An Application to Bacteriology 2339.2.1 Allicin Leads to a Breakdown of the Cell Wall of Staphylococcus aureus 2349.3 Applications to Parasitology 2399.3.1 Drug Discovery 2399.3.2 Parasite Characterization 2409.4 A Proteomic Approach: Leishmania Invasion of Macrophages 2409.5 Intracellular Leishmania Amastigote Spreading between Macrophages 2439.6 Potential Virus Applications 244Acknowledgements 246References 24610 Application of MALDI- TOF MS in Bioremediation and Environmental Research 255Cristina Russo and Diane Purchase10.1 Introduction 25510.2 Microbial Identification: Molecular Methods and MALDI- TOF MS 25710.2.1 PCR- based Methods 25810.2.2 Maldi- Tof Ms 26010.3 Combination of MALDI- TOF MS with Other Methods for the Identification of Microorganisms 26110.4 Application of MALDI- TOF MS in Environmental and Bioremediation Studies 26310.4.1 The Atmospheric Environment 26310.4.2 The Aquatic Environment 26310.4.3 The Terrestrial Environment 26510.4.4 Bioremediation Research Applications 26610.5 Microbial Products and Metabolite Activity 26810.6 Challenges of Environmental Applications 27010.7 Opportunities and Future Outlook 27110.8 Conclusions 272References 27311 From Genomics to MALDI- TOF MS: Diagnostic Identification and Typing of Bacteria in Veterinary Clinical Laboratories 283John Dustin Loy and Michael L. Clawson11.1 Introduction 28311.2 Genomics 28411.3 Defining Bacterial Species Through Genomics 28611.4 Maldi- Tof Ms 28711.5 Combining Genomics with MALDI- TOF MS to Classify Bacteria at the Subspecies Level 29011.6 Data Exploration with MALDI- TOF MS 29211.7 Validation of Typing Strategies 29411.8 Future Directions 294References 29512 MALDI- TOF MS Analysis for Identification of Veterinary Pathogens from Companion Animals and Livestock Species 303Dorina Timofte, Gudrun Overesch, and Joachim Spergser12.1 Veterinary Diagnostic Laboratories and the MALDI- TOF Clinical Microbiology Revolution 30312.1.1 MALDI- TOF MS: Reshaping the Workflow in Clinical Microbiology 30412.1.2 Identification of Bacterial Pathogens Directly from Clinical Specimens 30512.1.3 Prediction of Antimicrobial Resistance 30712.1.4 Impact in Veterinary Hospital Biosecurity and Epidemiological Surveillance 30812.2 Identification of Campylobacter spp. and Salmonella spp. in Routine Clinical Microbiology Laboratories 30912.2.1 General Aspects on the Importance of Species/Subspecies and Serovar Identification of Campylobacter spp. and Salmonella spp. 30912.2.2 General Aspects on Influence of Media/Culture Environment on Bacterial Species Identification by MALDI- TOF MS 31112.2.3 Possibilities and Limits of Identification of Campylobacter spp. by Maldi- Tof Ms 31212.2.3.1 Thermophilic Campylobacter spp. 31212.2.3.2 Human- hosted Campylobacter Species 31312.2.3.3 Campylobacter spp. of Veterinary Importance 31312.2.4 Possibilities and Limits of Identification of Salmonella spp. by Maldi- Tof Ms 31412.3 Identification and Differentiation of Mycoplasmas Isolated from Animals 31612.3.1 Animal Mycoplasmas at a Glance 31612.3.2 Laboratory Diagnosis of Animal Mycoplasmas 31712.3.3 MALDI- TOF MS for the Identification of Animal Mycoplasmas 318References 32213 MALDI- TOF MS: from Microbiology to Drug Discovery 333Ruth Walker, Maria E. Dueñas, Alan Ward, and Kaveh Emami13.1 Introduction 33313.2 Microbial Fingerprinting 33413.2.1 Environmental 33513.2.1.1 Actinobacteria 33513.2.1.2 Aquatic Microorganisms 33513.2.2 Terrestrial Microbiology 33713.2.3 Food and Food Safety 33813.2.3.1 Food Storage Effect on Identification 33813.2.3.2 Insects 33913.3 Mammalian Cell Fingerprinting 33913.3.1 Differentiation of Cell Lines and Response to Stimuli 33913.3.2 Cancer Diagnostics 34113.3.3 Biomarkers 34213.4 Drug Discovery Using MALDI- TOF 34213.4.1 Enzymatic Assays 34313.4.1.1 Targeting Antibiotic Resistance Using MALDI- TOF MS Enzymatic Assays 34313.4.2 Cellular- based Assays for Drug Discovery 34413.4.3 Automation in Drug Discovery 34513.4.4 Assay Multiplexing 34513.4.5 MS Imaging in Drug Discovery 34613.4.6 Maldi- 2 34613.5 Limitations/Challenges, Future Outlook, and Conclusions 34713.5.1 Sample Preparation Limitations 34713.5.1.1 Matrix 34713.5.1.2 Interference from Low- molecular- mass Matrix Clusters 34813.5.1.3 Buffer Compatibility 34813.5.1.4 TOF Mass Resolution Limitations 34813.5.2 Data Analysis and Application of Machine Learning 34813.6 Future Outlook/Conclusions 349References 35014 Rapid Pathogen Identification in a Routine Food Laboratory Using High- throughput MALDI- TOF Mass Spectrometry 359Andrew Tomlin14.1 Introduction 35914.2 MALDI- TOF MS in Food Microbiology 35914.3 Review of Existing Confirmation Techniques and Comparison to Maldi- Tof Ms 36214.4 Strain Typing Using MALDI- TOF MS 36414.5 Verification Trial 36514.6 Limitations of MALDI- TOF MS Strain Typing and Future Studies 36914.7 Listeria Detection by MALDI- TOF MS 37014.8 Trial Sample Preparation Procedure 37014.9 Initial Trial 37414.10 Limit of Detection Trial 37514.11 Method Optimization, Further Prospects, and Conclusions 376References 37915 Detection of Lipids in the MALDI Negative Ion Mode for Diagnostics, Food Quality Control, and Antimicrobial Resistance 381Yi Liu, Jade Pizzato, and Gerald Larrouy-Maumus15.1 Introduction 38115.2 Applications of Lipids in Clinical Microbiology Diagnostics 38215.2.1 Use of Cell Envelope Lipids for Bacterial Identification 38215.2.2 Detection of Cell Envelope Lipids and their Modifications to Determine Bacterial Drug Susceptibility 38415.2.3 Detection of Lipids in MALDI Negative Ion Mode for Fungal Identification 38715.2.4 Detection of Lipids in MALDI Negative Ion Mode for Parasite Identification 38715.2.5 Detection of Lipids in MALDI Negative Ion Mode for Virus Identification 38815.3 Applications of the Detection of Lipids in Negative Ion Mode MALDI- MS in Cancer Studies 38815.3.1 Lipids and MALDI Negative Ion Mode for Diagnosis of Lung Cancer 38915.3.2 Lipids and MALDI Negative Ion Mode for the Diagnosis of Breast Cancer 39015.3.3 Lipids and MALDI Negative Ion Mode for Diagnosis of Other Cancers 39115.3.4 Lipids and MALDI Negative Ion Mode for Drug–Cell Interactions and Prognosis 39215.4 Applications of the Detection of Lipids and MALDI- MS in Alzheimer’s Disease Studies 39215.5 Applications of MALDI in Negative Ion Mode and the Detection of Lipids in Toxicology 39315.6 Lipids and MALDI Negative Ion Mode for Food Fraud Detection 39415.7 Conclusions and Future Development of Lipids and their Detection in MALDI in Negative Ion Mode 395Acknowledgments 395References 39716 Use of MALDI- TOF MS in Water Testing Laboratories 405Matthew Jones, Nadia Darwich, Rachel Chalmers, K. Clive Thompson, and Bjorn Nielsen16.1 Introduction 40516.2 Application in a Drinking Water Laboratory 40816.2.1 Introduction 40816.2.2 Method Validation 40916.2.2.1 Reference Database Validation 41016.2.2.2 Method Comparison 41116.2.2.3 Agar Assessment 41216.2.3 Application Within Drinking Water Laboratory 41216.3 Application in Water Hygiene and Environmental Laboratory Testing 41316.3.1 Introduction 41316.3.2 Legionella Testing 41416.3.3 Wastewater and Sewage Sludge Microbiology 41516.3.4 Healthcare Water Testing 41616.3.5 Investigative Analysis 41716.3.6 Method Validation 41716.3.6.1 Characterization of Intended Use 41716.3.6.2 Library Assessment 41816.3.6.3 Assessment of Variables 41816.3.6.4 Comparison Assessment 41916.3.6.5 Ongoing Verification 42016.3.7 Conclusion on Suitability for Use in an Environmental Testing Laboratory 42216.4 Potential Application for Cryptosporidium Identification 423References 42517 A New MALDI- TOF Database Based on MS Profiles of Isolates in Icelandic Seawaters for Rapid Identification of Marine Strains 431Sibylle Lebert, Viggó Þór Marteinsson, and Pauline Vannier17.1 Introduction 43117.2 Selection and Cultivation of the Strains 43217.3 Genotypic Identification 43317.4 MALDI- TOF MS Data Acquisition and Database Creation 43817.5 Verification of the Accuracy of the Home- made Database 44117.6 Conclusions 448Funding 448References 44918 MALDI- TOF MS Implementation Strategy for a Pharma Company Based upon a Network Microbial Identification Perspective 453Lynn Johnson, Christoph Hansy, and Hilary Chan18.1 Introduction 45318.1.1 Microbial Identifications from a Pharmaceutical Industry Perspective 45318.1.2 Historical Evolution 45318.2 Regulatory Requirements/Guidance for Microbial Identification 45518.3 Strategic Approaches to MALDI- TOF Implementation Within the Modern Microbial Methods Framework 45518.3.1 Incorporation of MALDI- TOF into a Technical Evaluation Roadmap 45518.3.2 Initial Implementation Planning Stage 45618.3.2.1 Roles and Responsibilities (Global/Local, Partners/IT, Stakeholders) 45618.3.2.2 Considerations When Selecting a Vendor/Model 45718.3.2.3 Overall Identification Process Flow and MALDI- TOF as the Defined Application 45818.3.2.4 Benefits of an In- house System for Pharmaceutical Companies Compared with Outsourcing 45818.3.2.5 The Center of Excellence (CoE) Approach 46018.3.2.6 Building a Business Case for the MALDI- TOF as a Network Strategy 46118.3.3 Implementation Strategy – From Feasibility Studies to Global Deployment 46318.3.3.1 Pilot Trials/Feasibility 46318.3.3.2 Risk Assessment/Risk- based Validation Approach 46318.3.3.3 Network Validation Approach 46418.4 Conclusions 46718.a Appendix 468References 47019 MALDI- TOF MS – Microbial Identification as Part of a Contamination Control Strategy for Regulated Industries 473Christine E. Farrance and Prasanna D. Khot19.1 Industry Perspective 47319.1.1 Introduction to Regulated Industries 47319.1.2 Contamination Control Strategy 47419.1.3 Tracking and Trending EM Data 47419.1.4 Drivers for Microbial Identification 47619.1.5 Level of Resolution of an Identification 47619.1.6 Global Harmonization 47719.1.7 Validation Requirements for Regulated Industries 47719.1.8 Summary 47819.2 Technical Perspective 47819.2.1 Identification Technologies 47819.2.2 Phenotypic Systems 47919.2.3 Proteotypic Systems 47919.2.4 Genotypic Systems 47919.2.5 The Importance of the Reference Database 48019.2.6 MALDI- TOF in Regulated Industries 48019.2.7 Outsourcing 48019.2.8 Summary 48119.3 MALDI- TOF MS Microbial Identification Workflow at a High- throughput Laboratory 48119.3.1 MALDI- TOF MS Principles for Microbial Identification 48119.3.2 Organism Cultivation for Microbial Identification with MALDI- TOF MS 48219.3.3 Sample Preparation for Microbial Identification with MALDI- TOF MS 48219.3.4 Sample Processing Workflow for Microbial Identification 48219.3.5 Data Interpretation 48319.3.6 Importance of a Sequence- based Secondary (or Fall- through) Identification System 48419.4 MALDI- TOF MS Library Development and Coverage 48519.4.1 Importance of Library Development Under a Quality System 48519.4.2 Targeted Library Development for Gram- positive Bacteria and Water Organisms 48819.4.2.1 Case Study 1: Impact of MALDI- TOF MS Library Coverage for Organisms of the Family Bacillaceae 48819.4.2.2 Case Study 2: Impact of MALDI- TOF MS Library Coverage for Organisms Recovered from Water Systems 48919.4.3 Supplemental and Custom MALDI- TOF MS Libraries 48919.5 Comparison of MALDI- TOF MS with Other Microbial Identification Methods 49019.6 Future Perspectives 490References 49120 Identification of Mold Species and Species Complex from the Food Environment Using MALDI- TOF MS 497Victoria Girard, Valérie Monnin, Nolwenn Rolland, Jérôme Mounier, and Jean-Luc Jany20.1 Fungal Taxonomy 49720.1.1 Defining What Is a Fungal Species 49720.1.2 Fungal Speciation within a Food Context 49820.1.3 Delimiting Species 49820.1.4 Foodborne Fungi within the Fungal Tree of Life 49920.2 Impact of Molds in Food 50020.2.1 Filamentous Fungi in Fermented Foods 50020.2.2 Filamentous Fungi with Undesirable Impacts on Food Quality and Safety 50020.3 Identification of Fungi 50520.4 Identification of Foodborne Molds Using MALDI- TOF MS 50620.4.1 Sample Preparation 50620.4.2 Database Building and Performance of MALDI- TOF for Identification of Foodborne Molds 50720.4.2.1 Database Building 50720.4.2.2 Performance of Foodborne Mold Database 508References 509Index 515