Omics Approaches and Technologies in COVID-19

1st Edition - December 1, 2022
Imprint: Academic Press
Editors: Debmalya Barh, Vasco Ariston De Car Azevedo
Language: English
Paperback ISBN:
9 7 8 - 0 - 3 2 3 - 9 1 7 9 4 - 0
eBook ISBN:
9 7 8 - 0 - 3 2 3 - 9 8 6 2 1 - 2

The COVID-19 pandemic has affected the entire world in an unprecedented way since 2019. However, novel and innovative applications of various omics, computational, and smart te… Read more

Omics Approaches and Technologies in COVID-19

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The COVID-19 pandemic has affected the entire world in an unprecedented way since 2019. However, novel and innovative applications of various omics, computational, and smart technologies have helped manage the pandemic of the 21st century in a very effective manner. Omics approaches and technologies in COVID-19 presents up-to-date knowledge on omics, genetic engineering, mathematical and computational approaches, and advanced technologies in the diagnosis, prevention, monitoring, and management of COVID-19.

This book contains 26 chapters written by academic and industry experts from more than 15 countries. Split into three sections (Omics; Artificial Intelligence and Bioinformatics; and Smart and Emerging Technologies), it brings an overview of novel technologies under omics such as, genomic, metagenomic, pangenomic, metabolomics and proteomics in COVID-19. In addition, it discusses hostpathogen interactions and interactomics, management options, application of genetic engineering, mathematical modeling and
simulations, systems biology, and bioinformatics approaches in COVID-19 drug discovery and vaccine development.

This is a valuable resource for students, biotechnologists, bioinformaticians, virologists, clinicians, and pharmaceutical, biomedical, and healthcare industry people who want to understand the promising omics and other technologies used in combating COVID-19 from various aspects.

Cover
Title page
Table of Contents
Copyright
Dedication
Contributors
About the editors
Preface
Section A: Omics
Chapter 1: Omics approaches in COVID-19: An overview
Abstract
1: Introduction
2: Genomics, meta-genomics, and pan-genomics approaches
3: Genotype-phenotype correlations in COVID-19
4: Proteomics in COVID-19
5: Host-pathogen protein—Protein interactions and interactomics
6: Currently available COVID-19 management options
7: Transcriptomic approaches in COVID-19: From infection to vaccines
8: miRNAomics in COVID-19
9: Epigenetic implementations in COVID-19
10: Nutrigenomics and nutrition aspects in COVID-19
11: COVID-19 and phenomics
12: Metabolomics in COVID-19
13: Applications of genetic engineering in COVID-19
14: CRISPR-based assays for rapid detection of SARS-CoV2
15: Approaches to understand the emergence and dynamics of COVID-19 and future pandemics
16: Artificial intelligence (AI) in COVID-19
17: Applications of mathematical modeling and simulation in COVID-19
18: In silico disease modeling for COVID-19
19: System biology applications in COVID-19
20: Computational approaches in COVID-19 drug discovery
21: Computational approaches in COVID-19 vaccine development
22: Applications of multiomics data in COVID-19
23: Publicly available resources in COVID-19 research and their applications
24: Emerging technologies for COVID-19 diagnosis, prevention, and management
25: Applications of digital and smart technologies to control SARS-CoV2 transmission, rapid diagnosis, and monitoring
26: Technologies for prediction of a patient’s health condition and outcomes from COVID-19
27: Conclusion and overall implications
References
Chapter 2: Genomics, metagenomics, and pan-genomics approaches in COVID-19
Abstract
1: Introduction
2: Metagenomic analysis
3: Covid-19 pangenome dynamics
4: Application and advancement of pan genome-derived data in therapeutics
5: Implementations of SARS-CoV-2 genomics, metagenomics, and pan-genomics approaches
6: Conclusion and future perspectives
References
Chapter 3: Genotype and phenotype correlations in COVID-19
Abstract
1: Introduction
2: Structure and lifecycle of coronavirus
3: COVID-19 susceptibility genes identified by GWASs and implications of these genes in developing COVID-19 disease subphenotypes
4: The cellular pathway of these SNPs/genes leading to COVID-19 subphenotypes
5: Genetic variations associated with susceptibility and severity to COVID-19
6: Epigenetic mechanisms of SARS-CoV-2 infection and associated comorbidities
7: Genetic variations and impact on diagnosis and treatment
8: Implementations of genotype-phenotype correlations in COVID-19
9: Other implementations
References
Chapter 4: Proteomic understanding of SARS-CoV-2 infection and COVID-19: Biological, diagnostic, and therapeutic perspectives
Abstract
1: Introduction
2: Proteome of the SARS-CoV-2 virus
3: Host-pathogen protein-protein interactions in COVID-19
4: Proteomics in COVID-19 patients
5: Posttranslational modifications in COVID-19
6: Proteomics tools and applications for COVID-19
7: Implementations of SARS-CoV-2 and COVID-19 proteomics
8: Critical analyses of the present achievements and future perspectives
References
Chapter 5: Metabolites and metabolomics in COVID-19
Abstract
1: Introduction
2: Metabolites and metabolomics in viral infection
3: Metabolomics in SARS-CoV-2
4: Implementation of metabolites/metabolomics in COVID-19
5: Conclusions and future perspectives
References
Chapter 6: Host-pathogen protein-protein interactions and interactomics in COVID-19
Abstract
1: Introduction
2: Comparative interactomics: How the SARS-CoV-2 PPI differs from SARS-CoV-1 and other viruses
3: PPI-based pathway interactions in COVID-19
4: Interactome datasets and tools available to the community on COVID-19
5: Implementations of SARS-CoV-2 and human PPI/translational interactomics
6: The search for druggable targets through ACE2 protein-protein interaction networks (PPINs)
7: Bioinformatics-based HPI and their implementations
8: Comparative coronavirus interactomics and host targets
9: Drug repurposing
10: Understanding the mechanism of multiorgan injuries and their sequels
11: Critical analyses of the present achievements
12: Conclusion and future perspectives
References
Chapter 7: Currently available COVID-19 management options
Abstract
1: Introduction
2: General treatment strategies
3: Specific treatments
4: Antiviral therapies
5: Anti-SARS-CoV-2 neutralizing antibody products
6: Immunomodulatory agents
7: Ventilation management and oxygenation in COVID-19
8: Management of critical cases
9: Supplementation
10: Vitamin D
11: Vitamin C
12: Zinc
13: Magnesium
14: Vitamin B12
15: Alpha-lipoic acid
16: Management of postinfection complications
17: Conclusions and future perspectives
References
Chapter 8: Transcriptomic approaches in COVID-19: From infection to vaccines
Abstract
1: Introduction
2: The structural basis of SARS-CoV-2 transcriptome
3: Transcriptional host responses to SARS-CoV-2 infection
4: Implementations of transcriptomics in COVID-19
5: Single-cell transcriptomics in COVID-19
6: Conclusions and perspectives
References
Chapter 9: miRNAomics in COVID-19
Abstract
1: Introduction
2: miRNA expression profile in COVID-19
3: Interactions of SARS-CoV-2 miRNA/small RNAs and host miRNA
4: SARS-CoV-2 encoded miRNAs/small RNAs in SARS-CoV-2 infection and COVID-19 pathology
5: Host miRNA/small noncoding RNAs and COVID-19 pathology/severity/host response
6: miRNA perspective of comorbid conditions and long-haul COVID
7: Implementations of miRNAs in
8: List of miRNA therapeutics in clinical trials
9: Conclusion and future perspectives
References
Chapter 10: Epigenetic features, methods, and implementations associated with COVID-19
Abstract
1: Introduction
2: Epigenetic landscape alteration and epigenetic mechanisms in respiratory viral infections
3: Cutting-edge epigenetics and epigenomics technology applied in COVID-19
4: Epigenetic landscape and mechanism in SARS-CoV-2 entry and infection
5: Interactions between human epigenetic factors and SARS-CoV-2 proteins
6: Epigenetic biomarkers for COVID-19 risk and severity
7: Epitranscriptome profiling, technology, outcomes, and implementations in COVID-19
8: Epitherapy and epidrug repurposing in COVID-19 clinical trials
9: Implementations of SARS-CoV-2 epigenetics/epigenomics
10: Conclusion and future perspectives
References
Chapter 11: Nutrigenetics and nutrition aspects in COVID-19
Abstract
1: Introduction of nutrigenetics
2: Gene-diet interaction and precision nutrition in COVID-19
3: Various diet components and their cellular and molecular effects on COVID-19
4: Recent updates of nutrigenomic studies in COVID-19
5: Link of COVID-19 to low mortality of Asians compared to Americans and Europeans
6: Conclusions and future perspectives
References
Chapter 12: COVID-19 phenomics
Abstract
1: Introduction to phenomics in the context of viral disease
2: Phenomic approaches to COVID-19
3: Applications of phenomics to COVID-19
4: Concluding remarks
References
Chapter 13: Applications of genetic engineering in COVID-19
Abstract
Conflict of interest
1: Introduction
2: SARS-CoV-2 protein production during the lifecycle emphasizes important posttranslation modifications
3: Application of subunit spike protein production
4: Production of recombinant virus and virus-like particles
5: Genetically engineered models
6: Synthetic biology of SARS-CoV-2
7: Concluding remarks
References
Chapter 14: CRISPR-based assays for rapid detection of SARS-CoV-2
Abstract
1: Introduction
2: SHERLOCK—CRISPR-Cas13a enzyme-based COVID-19 detection assay
3: DETECTR—CRISPR-Cas12a enzyme-based detection assay
4: AIOD-CRISPR—All-in-one dual CRISPR-Cas12a assay
5: CRISPRENHANCE—Enhanced analysis of nucleic acids with crRNA extensions assay
6: CASdetec—CRISPR-Cas12b-mediated DNA detection assay
7: FELUDA—CRISPR-Cas9 enzyme-based detection assay
8: Conclusion
References
Section B: Artificial intelligence and bioinformatics
Chapter 15: Emergence and dynamics of COVID-19 and future pandemics
Abstract
1: Differentiating the disease and infection
2: The weight of preconceived ideas
3: The example of COVID-19
4: The “medical approach”
5: The “environmental approach”
6: The “laboratory leak narratives”
7: The “Circulation” model and the evolution of viruses in the human population
8: The genetic accident
9: The societal accident
10: An intermediate summary
11: What can be performed to prevent the occurrence of further pandemics?
12: Conclusion: The solution is in the societal management
References
Chapter 16: Artificial intelligence in COVID-19
Abstract
1: Introduction
2: Background
3: AI implementations for COVID-19
4: Conclusion
References
Chapter 17: Applications of mathematical modeling and simulation in COVID-19
Abstract
1: The basic principles and applications of mathematical modeling and simulation in pandemics
2: Data sets and various mathematical models applied to COVID-19
3: Implementations of modeling and simulation
4: Limitations and potential challenges of modeling and simulation in COVID-19
5: Conclusions and future perspectives
References
Chapter 18: In silico disease modeling for COVID-19
Abstract
1: Introduction: COVID-19 models
2: In silico modeling of infectious disease: Types of models and biological implications
3: In silico modeling of SARS-COV-2 dynamics within the host
4: Implementations of in silico modeling of COVID-19
5: Conclusions
References
Chapter 19: Systems biology in COVID-19
Abstract
1: Introduction
2: Strategies, tools, DBs, and other publicly available resources for COVID-19 systems biology and phenomics
3: Implementations of systems biology in COVID-19 in basic and translational research
4: Systems pharmacology approaches in identifying the targetome, therapeutics, and prophylactic agents for COVID-19
5: Other implementations: Big data, phenomics, and radiomics
6: Critical analyses of the present achievements
7: Conclusion and future perspectives
References
Chapter 20: Computational approaches for drug discovery against COVID-19
Abstract
1: Introduction
2: Computational approaches to identify drug targets in SARS-CoV-2 and humans
3: In silico approaches to identify candidate drugs
4: Potential anti-COVID drugs based on computational approaches
5: Identification of prophylaxis and COVID-19 management agents (such as NO etc.) using in silico approaches
6: In silico disease (COVID-19) modeling for testing the efficacy of candidate therapeutics
7: Critical analyses of the present achievements
8: Conclusion and future perspectives
References
Chapter 21: Computational approaches in COVID-19 vaccine development
Abstract
1: Why is the vaccine the best way to fight COVID-19?
2: Steps in the development of conventional vaccines and their difficulties and disadvantages
3: How the computational approaches speed up the vaccine design and development process
4: The concept of computational immunology and the available resources
5: Computational immune proteomics approach in COVID vaccine design and outcomes
6: Reverse vaccinology-based approach in COVID vaccine design and outcomes
7: Identified epitope and multiepitope-based peptide vaccines against COVID-19
8: Computer-aided mRNA vaccine design against COVID-19
9: Computer-aided DNA vaccine design against COVID-19
10: Artificial intelligence and systems biology approaches in COVID-19 vaccine development
11: Computational approaches for rapid design, development, and testing the efficacy of COVID-19 vaccines
12: Computational approaches applied in various vaccine development platforms for COVID-19
13: The currently available vaccines and the computational approaches behind these vaccines
14: Computational approaches to validate the efficacy of the developed vaccines against COVID-19
15: Tools and applications used in tracking the COVID-19 vaccination regime
16: Publicly available resources for COVID-19 vaccine discovery
17: Critical analyses of the present achievements
18: Conclusion and future perspectives
References
Chapter 22: Applications of multiomics data in COVID-19
Abstract
1: Omics and multiomics approaches: Data, data integration, and analysis
2: Multiomics approaches to decode SARS-CoV-2 infection biology
3: Multiomics approaches to understand how nCoV hijacks the host cell machinery
4: Multiomics approaches to understand the comorbid conditions and COVID-19 interactions
5: Multiomics approaches for personalized and targeted therapy and care to COVID-19 patients
6: Early diagnosis and multiomics-based screening of biomarkers for the COVID-susceptible population
7: Developing a preventive strategy and multiomics approach toward the formulation of prophylaxis agents/strategies
8: Developing therapeutics and management for mild and severe COVID-19 cases
9: Multiomics approaches toward multiple organ injury and response because of COVID-19
10: Multiomics-based prediction of long-term health consequences and their treatment options in recovered patients
11: Conclusion
References
Chapter 23: Publicly available resources in COVID-19 research and their applications
Abstract
1: Introduction
2: Literature resources
3: Epidemiology resources
4: SARS-CoV-2-specific genomic databases and tools for analysis
5: SARS-CoV-2-specific proteomic databases and tools for analysis
6: SARS-CoV-2-specific epigenetic databases and tools for analysis
7: SARS-CoV-2-specific transcriptomic databases and tools for analysis
8: In vivo and clinical trial databases for COVID-19 drugs
9: Bioinformatics tools and databases for SARS-CoV-2 drug designing and vaccine developments
10: Toxicogenomic databases and tools for SARS-CoV-2 research
11: Resources and tools for clinicians
12: Mobile apps for tracking the pandemic
13: Conclusion and future perspectives
References
Section C: Smart and emerging technologies
Chapter 24: Emerging technologies for COVID-19, diagnosis, prevention, and management
Abstract
1: Introduction
2: Emerging technologies for diagnosing SARS-CoV-2
3: Emerging technologies for studying the COVID-19 epidemiology
4: Technologies for prevention and control the SARS-CoV-2 transmission
5: Emerging technologies for therapeutic and vaccine development
6: Conclusion and future perspectives
References
Chapter 25: Applications of digital and smart technologies to control SARS-CoV-2 transmission, rapid diagnosis, and monitoring
Abstract
1: Introduction
2: Digital and smart technologies used in the COVID pandemic
3: Implementation of digital and smart technologies in COVID-19
4: Technologies for Integration of various sectors (clinical, environmental, public and private, hospitals, health care centers to the individual public, etc.)
5: Emerging smart and digital tech for research purposes
6: Comparison of smart and digital techs implemented for pandemic management between first and third world economic countries
7: Advantages, disadvantages, and risks of the currently used smart and digital technologies in the COVID pandemic
8: Ethical perspective and steps to ensure data safety
9: Conclusion and future perspectives
References
Chapter 26: Application of big data analytics in the COVID-19 pandemic: Selected problems
Abstract
Acknowledgments
1: Introduction
2: Challenges in COVID-19 and big data
3: Recommendations
4: Conclusion
References
Index

Debmalya Barh

Dr. Debmalya Barh is currently a Visiting Full Professor (Titular, Grade-E) in Bioinformatics and Precision Health at the Department of Genetics, Ecology, and Evolution, ICB, Federal University of Minas Gerais, Brazil and honorary scientist of the Institute of Integrative Omics and Applied Biotechnology (IIOAB), India. With over 20 years of experience, he has led academic, healthcare, molecular diagnostic, and bioinformatics industry endeavors. He works with more than 400 scientists from 100+ top ranked organizations across 40+ countries and has 220+ publications and a branded editor for 10+ cutting-edge omics related reference books. He is an expert in in precision/personalized health and integrative omics-based biomarker and target discovery in infectious and complex lifestyle diseases.

Affiliations and expertise

Federal University of Minas Gerais, Belo Horizonte, Brazil

Vasco Ariston De Car Azevedo

Dr. Vasco Azevedo is a full professor at the Department of Genetics, Ecology, and Evolution, Institute of Biological Sciences, Federal University of Minas Gerais, Brazil. He is a CNPq (Conselho Nacional de Desenvolvimento Científico e Tecnológico) researcher 1A, member of the Brazilian Academy of Sciences, Commander of the Order of Scientific Merit of the MCTI of the genetics advisory committee and the public policy working group on biotechnology and genetic resources of COBRG/CNPq, coordinator of the Associated International Laboratory Bactinfl from INRAE and UFMG, and vice-president of the Brazilian Association of Bioinformatics and Computational Biology. He holds a degree in veterinary medicine from the School of Veterinary Medicine of the Federal University of Bahia (1986), a master's degree (1989), a doctorate (1993) in the genetics of microorganisms from the Institut National Agronomique Paris Grignon, and a doctorate in bioinformatics from UFMG (2017). He did his postdoctorate work with the Department of Microbiology, School of Medicine, University of Pennsylvania, United States (1994). He was a professor at the Institute of Biomedical Sciences of the University of São Paulo (2004). He is an expert in genetics and bioinformatics and his work mainly focuses on genomics, transcriptomics, proteomics, metabolomics, vaccine development, diagnostics, and the development of next generation probiotics. He has more than 600 scientific publications, 14 books, and 60 chapters as well as 12 patents.

Affiliations and expertise

Professor, Institute of Biological Sciences, Federal University of Minas Gerais (UFMG), Brazil

Life Sciences

Physical Sciences & Engineering

Social Sciences & Humanities

Health