Metagenomics

Metagenomics: Perspectives, Methods, and Applications, second edition, provides thorough coverage of the growing field of metagenomics. A diverse range of chapters from international experts offer an introduction to the field and examine methods for metagenomic analysis of microbiota, metagenomic computational tools, and recent metagenomic studies in various environments and clinical settings. The emphasis on application makes this text particularly useful for applied researchers, practitioners, clinicians, and students seeking to employ metagenomic approaches to advance knowledge in the biomedical and life sciences. Case study-based application chapters include topics ranging from metagenome tools, metagenomics in oral disease and health, metagenomic insights into the human gut microbiome and metabolic syndromes, and more.

This new edition has been fully updated to address the rapid growth and development of metagenomics applications, featuring expert discussion of recent developments and fresh case studies. Newly added chapters instruct in methods and implications of metagenomics in areas of growing focus, such as microbiome research, clinical diagnosis, metagenomic epidemiology, and plant microbe interaction. Data analysis is explained in simple terms for effective use of computational tools, software, and sequencing pipelines.

Metagenomics
Cover image
Title page
Table of Contents
Copyright
Contributors
About the editor
Preface
Acknowledgments
1 Metagenomics: A paradigm shift in microbiology
Abstract
Keywords
1 The birth of metagenomics
2 Function- and sequencing-based metagenomics
3 An overview of methods used in sequencing-based metagenomics
4 Interplay of single-cell genomics and metagenomics
5 Contribution of metagenomics to the recent expansion of the microbial tree of life
6 Concluding remarks
References
2 Metagenomic protocols and strategies
Abstract
Keywords
Acknowledgments
1 Introduction
2 Wet-lab techniques for sample collection, preservation, and transport
3 Wet-lab techniques for sample pretreatment and nucleic acid extraction (DNA)
3.1 Sample handling for superficial sea- and freshwater sample treatment
3.2 Sample handling for solid and sediment sample treatment
3.3 Isolation of high-quality DNA by phenol: Chloroform method followed by DNA cleaning
3.4 Isolation of high-quality DNA by the hexadecyltrimethylammonium bromide method
3.5 Isolation of high-quality DNA by commercial kits
3.6 Handling instructions for the isolation of high-quality genomic DNA from acidic samples
3.7 Isolation of high-quality DNA from fecal samples
3.8 Rapid amplification of DNA using Phi29 DNA polymerase
4 Wet-lab techniques for RNA isolation
5 Metataxonomy through 16S rRNA gene: From wet-lab techniques to bioinformatics
5.1 Wet-lab techniques for amplification and sequencing of 16S rRNA
5.2 Bioinformatic and statistical analysis of 16S rRNA amplicons
5.3 Presentation and interpretation of results
6 Metagenomics: Sequencing methods and bioinformatics
6.1 Sequencing methods for community DNA and cDNA analysis
6.2 Bioinformatic analysis of shotgun sequencing data from metagenomic samples
6.3 Metagenomes databases
7 Metagenomic: Wet-lab techniques for clone library construction
References
Further reading
3 Strategies for taxonomic and functional annotation of metagenomes
Abstract
Keywords
1 Introduction
2 Assessing taxonomic composition using metagenomic data
3 Metagenomic assembly
4 Detection and quantification of ecosystem processes using metagenomics
5 Comparing communities and estimating diversity
6 Computational “pipelines” for metagenomic analyses
7 Conclusions and outlook
References
4 Computational and statistical considerations in the analysis of metagenomic data
Abstract
Keywords
1 Introduction
2 Computational challenges in the analysis of shotgun metagenomics
2.1 Choosing a suitable read mapper
2.2 Analysis workflows and computational resources
2.3 Existing big data frameworks for gene quantification
2.4 A remark on the reproducibility in shotgun metagenomics
3 Statistical aspects of the analysis of shotgun metagenomic data
3.1 Normalization of gene abundance data
3.2 Identification of differentially abundant genes
4 Conclusions
References
5 Data science to biologists: Insights into microbiomics
Abstract
Keywords
Acknowledgments
1 Microbiome research
2 Prerequisites for microbiome research and data analysis
2.1 Study design
2.2 Sample size and type
2.3 Metadata collection
2.4 Nucleic acid extraction and library preparation
2.5 Sequencing platform and 16S rRNA primers
2.6 Unequal sample sizes and data normalization
2.7 Knowledge about commonly used tools in microbiome data analysis
2.8 Computational facilities and expertise
2.9 Basic programming skills (R and Python language)
2.10 Interpretation of results
2.11 Web tools
3 Key challenges in microbiome research
4 Biases in microbiome research
4.1 Strategies to minimize bias in microbiome research and associated comparative analysis
4.2 Developing standard data reporting forms to report microbiome data from all sources
5 Benchmarking the protocols used for microbiome research
5.1 Developing the best practice protocols for microbiome data analysis process to help the biologists
6 Applications of machine learning and deep learning in microbiome research
7 Future prospective in the microbiome studies
8 Conclusion
References
6 Meta-omic and machine learning approaches to understand microbial cross talks
Abstract
Keywords
1 Introduction
2 Machine learning and community data analysis
2.1 Data-driven approaches
2.2 Exploring molecular-level interactions using meta-omics data
2.3 Unsupervised multiple-variable approach used for marker-gene analysis
2.4 Supervised machine learning methods for microbial ecology study
3 Machine learning vs traditional statistics for microbiome analysis
4 Evaluating and interpreting estimator performance
5 Applications in environmental monitoring prediction and classification
6 Conclusion
References
7 Measuring microbiome diversity and diversity-scaling analysis with Hill numbers
Abstract
Keywords
1 Introduction
2 Rediscovering Hill numbers and the partition of Beta-diversity
3 Measuring phylogenetic diversity
4 Community similarity measures and their phylogenetic generalizations
5 Rarefaction interpolation and prediction extrapolation with Hill numbers
6 Additional Hill numbers-based metrics
7 Diversity-scaling analysis with Hill numbers: DAR (diversity-area relationship), DTR (diversity-time relationship) and DTAR (diversity-time-area relationship)
References
8 16S rRNA-based taxonomy profiling in the metagenomics era
Abstract
Keywords
1 16S rRNA: The gold standard for the phylogeny of prokaryotes
2 Targeted amplification of 16S rRNA gene
3 Biases in targeted approaches
4 Choosing the appropriate target region
5 Third-generation sequencing technologies
6 Maximum output of sequencers and why it matters
7 Taxonomic classification: The growth of 16S rRNA databanks
8 Methods for the estimation of taxonomic abundance
9 From taxonomy to metagenomics: Is it reasonable?
10 Taxonomy in nontargeted approaches
11 Taxonomy via 16S rRNA assembling: The issue of genomic complexity
12 Ribosomal read recruitment from nontargeted approaches
13 Experiment repositories and analysis pipelines
14 Concluding remarks
References
9 Metagenomics and neurodegenerative diseases
Abstract
Keywords
1 Introduction
2 Databases and web servers in metagenomics
3 Metagenomics for ascertaining neurological diseases
4 Metatranscriptomics
5 Our case study on Parkinson's disease
6 Conclusions and way forward
References
10 Metagenomics-guided reengineering of the gut microbiome
Abstract
Keywords
1 Introduction
2 Association of gut microbiome with various disorders
2.1 Gastrointestinal (GI) disorders
2.2 Non-GI disorders
2.3 Non-GI autoimmune disorders
2.4 Neuropsychiatric
2.5 Clostridium difficile infection (CDI)
2.6 Atopic asthma
3 Need for metagenomics in reengineering the gut microbiome
4 Approaches to reengineer gut microbiome
4.1 Fecal microbiota transplant
4.2 Microbial consortia
4.3 Pre/pro/synbiotics
4.4 Postbiotics
4.5 Bioengineered organisms
5 Future directions
References
11 Metagenomics: Implications in oral health and disease
Abstract
Keywords
Acknowledgments
1 Humans and microbes: A perpetual interplay
2 An overview of the oral microbiome
3 Evolution of oral microbiome
4 Oral microbiome composition
4.1 Virus
4.2 Protozoa
4.3 Archaea
4.4 Fungi
4.5 Bacteria
5 Human oral microbiome database
6 The commensal residents of oral cavity
7 Oral microbiome-associated diseases
8 Dysbiosis of the oral microbiota
8.1 Dental caries
8.2 Periodontal diseases
8.3 Endodontic infections
9 Oral cancer
9.1 Pregnancy complications
9.2 Oral microbiome and SARS-Cov-2
9.3 Oral microbiome-associated systemic infections
9.4 Cardiovascular disease
9.5 Alzheimer's disease
9.6 Diabetes mellitus
10 Conclusion
References
12 Exploring microbiome-based interventions in periodontitis: The role of prebiotics and postbiotics in oral health management
Abstract
Keywords
1 Prebiotics and postbiotics
2 Host-microbiome interaction
2.1 Interaction of microbiome with soft-tissue cells and hard-tissue cells
3 Action of prebiotic in periodontitis
4 Symbionts
5 Action of postbiotic on periodontitis
6 Discussion
7 Limitation and future perspective
8 Conclusion
References
13 Understanding the resistome of the human microbiome: A metagenomic approach
Abstract
Keywords
Conflict of interest
1 Introduction
2 Mechanisms of antibiotic resistance
2.1 Limiting drug uptake
2.2 Modification of drug targets
2.3 Drug inactivation
2.4 Efflux pump
3 The human resistome
3.1 Types of resistome—Intrinsic and mobile
3.2 Factors affecting the human resistome
4 Methods to identify antibiotic resistance in microbial communities
4.1 Culture-based methods to identify antibiotic resistance
4.2 Tracking antimicrobial resistance using metagenomics
4.3 Antibiotic resistance databases
5 Conclusion, challenges, and future directions
References
14 SARS-CoV-2 and variants: Alternative therapies to avert COVID-19
Abstract
Keywords
1 Introduction
2 SARS-CoV-2 epidemiology
3 Metagenomics and COVID-19
4 SARS-CoV-2 genetic variants of concern
5 Alpha (B.1.1.7)
6 Beta (B.1.351)
7 Gamma (P1)
8 Delta (B.1.617.1) variant
9 Omicron (B.1.1.529)
10 Strategies to combat COVID-19
11 Prevention and control of COVID-19
12 Surveillance and avoiding bats
13 Monitoring and surveillance of companion, pet, and zoo animals
14 One Health approach vis-à-vis COVID-19
15 Herbal supplements and phytochemicals
16 Lipid-based therapies
17 Microbial interventions and probiotic therapies
18 Outlook and challenges
19 Conclusions
References
15 AMR surveillance in bacteria using metagenomics
Abstract
Keywords
1 An overview of AMR
2 Metagenomics can redeem the threat of AMR on public health
3 Metagenomics has added new dimensions to AMR surveillance
4 Conclusion
References
16 An overview of the metagenomics-based assessment of ecosystem toxicology
Abstract
Keywords
1 Introduction
2 Conventional biomarkers for toxicity in soil and aquatic environment
3 Metagenomic approaches
4 Toxicological assessment of aquatic ecosystem
5 Toxicological assessment of soil
6 Toxicological assessment of other ecosystems
7 Challenges and prospects of metagenomics in toxicology evaluation
8 Conclusion
References
17 Metagenomic approaches to analyze earthworm-microbial interactions to maintain sustainable agroecosystem
Abstract
Keywords
1 Introduction
2 Metagenomic approaches to analyze microbial diversity
3 Challenges in metagenomic study of soil samples
4 Contribution of microbial diversity to agro-ecosystem
4.1 Microorganisms influencing phosphorus release in soils
4.2 Microbial strategy for release of unavailable forms of phosphorus
4.3 Mechanisms of action of KSB (potassium-solubilizing bacteria) in solubilizing potassium
5 Composition of microbial diversity in earthworm gut and nearby soil
6 Microbial evolution
7 Taxonomic evolution of microbial community in soil ecosystem
8 Effect of conservation agricultural practices in soil microbial diversity
9 Conclusions
References
18 Plant health in the era of metagenomics: Current state and future prospects
Abstract
Keywords
Conflict of interest
1 Introduction
2 Roles of microorganisms associated with plant phyllosphere, endosphere, and rhizosphere on plant health
3 Overview of metagenomics in plant health
3.1 Metabarcoding
3.2 Shotgun metagenomics
3.3 Application of metagenomics in plant health management
4 Taxonomic and functional annotation of the plant-associated microbiome
4.1 Taxonomic classification of the plant-associated microbiome
4.2 Functional annotation of the plant microbiome
5 Current challenges
6 Limitation
7 Conclusion and future prospects
References
19 The Agave and Cacti microbiome: Models for a planet under global warming
Abstract
Keywords
Acknowledgments
1 Introduction
2 Experimental design
3 Composition and diversity of microbial communities associated with Agaves and Cacti
4 Factors affecting the assembly of microbial communities in Agaves and Cacti
5 The core microbiome of Agaves and Cacti
6 Network analyses of microbial communities associated with Agaves and Cacti
6.1 Bulk soil
6.2 Belowground communities
6.3 Aboveground communities
7 Metagenomics of the soil, rhizosphere, and phyllosphere associated with Agaves and Cacti
7.1 Functional differentiation of the prokaryotic communities associated with the soil, rhizosphere, and phyllosphere of Agaves and Cacti
7.2 Phototrophy
7.3 Biofilm production and quorum sensing
7.4 Carbon utilization
7.5 Specialized metabolism
7.6 Xenobiotic metabolism
8 Toward synthetic communities
9 Conclusions
References
20 Marine invertebrate-microbe interactions: An insight into immunogenomics through metagenomic approach
Abstract
Keywords
Conflict of interest
1 Introduction
2 Ocean sampling day
3 Metagenomics in holobiont research
4 Microbial invertebrate symbiosis
5 Metagenomic approach to explore the unculturable microbial world
6 Isolation of eDNA
7 Metagenomic library construction
8 Screening of metagenomic clones
9 Metaproteomics and targeted metagenomics
10 Proteome analysis
11 Single-cell genomics
12 Microbiome and immunogenomics of marine invertebrates
13 Sponge
14 Coral
15 Annelid
16 Mollusk
17 Echinoderm
18 Conclusions
References
21 Advances of functional metagenomics in harnessing thermozymes
Abstract
Keywords
Acknowledgments
1 Introduction
2 Methodologies for functional metagenomics: Library construction and screening
2.1 Sampling
2.2 DNA extraction
2.3 Vector choice
2.4 DNA cloning
2.5 Functional screening
3 Concluding remarks and perspectives
References
Index

Life Sciences

Physical Sciences & Engineering

Social Sciences & Humanities

Health

Metagenomics

Perspectives, Methods, and Applications

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Muniyandi Nagarajan