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Omics Approaches and Technologies in COVID-19 This page intentionally left blank Omics Approaches and Technologies in COVID-19 Edited by Debmalya Barh Institute of Biological Sciences, Federal University of Minas Gerais (UFMG), Belo Horizonte, Brazil Institute of Integrative Omics and Applied Biotechnology (IIOAB), Nonakuri, Purba Medinipur, West Bengal, India Vasco Azevedo Institute of Biological Sciences, Federal University of Minas Gerais (UFMG), Belo Horizonte, Brazil Academic Press is an imprint of Elsevier 125 London Wall, London EC2Y 5AS, United Kingdom 525 B Street, Suite 1650, San Diego, CA 92101, United States 50 Hampshire Street, 5th Floor, Cambridge, MA 02139, United States The Boulevard, Langford Lane, Kidlington, Oxford OX5 1GB, United Kingdom Copyright © 2023 Elsevier Inc. All rights reserved. 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Practitioners and researchers must always rely on their own experience and knowledge in evaluating and using any information, methods, compounds, or experiments described herein. In using such information or methods they should be mindful of their own safety and the safety of others, including parties for whom they have a professional responsibility. To the fullest extent of the law, neither the Publisher nor the authors, contributors, or editors, assume any liability for any injury and/or damage to persons or property as a matter of products liability, negligence or otherwise, or from any use or operation of any methods, products, instructions, or ideas contained in the material herein. ISBN: 978-0-323-91794-0 For information on all Academic Press publications visit our website at https://www.elsevier.com/books-and-journals Publisher: Stacy Masucci Acquisitions Editor: Rafael E. Teixeira Editorial Project Manager: Franchezca A. Cabural Production Project Manager: Swapna Srinivasan Cover Designer: Mark Rogers Typeset by STRAIVE, India Dedication We dedicate the book to our mothers, mothers of our children, and mother of the universe, who are our source of powers and inspirations. This page intentionally left blank Contents Contributors xix 6. Currently available COVID-19 About the editors xxiii management options 7 Preface xxv 7. Transcriptomic approaches in COVID-19: From infection to vaccines 7 7.1 Identification of target using RNA sequencing from patients’ blood, Section A nasopharyngeal swab, and other Omics tissues 7 7.2 Single cell sequencing to identify 1. Omics approaches in COVID-19: genetic changes in COVID-19 An overview patients 8 8. miRNAomics in COVID-19 8 Amit K. Maiti 9. Epigenetic implementations in 1. Introduction 3 COVID-19 8 2. Genomics, meta-genomics, and 9.1 Whole genome methylation pan-genomics approaches 4 profiling of COVID-19 patients 8 2.1 Genomic approaches to covid-19 4 9.2 Other epigenetic approaches 8 2.2 Metagenomic approaches 4 10. Nutrigenomics and nutrition aspects 2.3 Pan-genomics 4 in COVID-19 8 3. Genotype-phenotype correlations in 10.1 Role of vitamins and other COVID-19 5 nutritional factors 8 3.1 COVID-19 susceptibility genes 10.2 Involvement of gut as an important identified by Genome-Wide part of COVID-19 complications 9 Association Studies 5 10.3 Microbial sequencing to identify 3.2 Protein coding SNPs associated with gut microbes in COVID-19 COVID-19 5 patients 9 3.3 Regulatory SNPs associated with 11. COVID-19 and phenomics 9 COVID-19 6 12. Metabolomics in COVID-19 9 3.4 Implications of these genes in 12.1 Metabolomic approaches to developing COVID-19 disease COVID-19 detection and subphenotypes 6 prediction 9 3.5 The path to develop disease 13. Applications of genetic engineering in prediction, detection, and COVID-19 10 therapeutic target 6 14. CRISPR-based assays for rapid 4. Proteomics in COVID-19 6 detection of SARS-CoV2 10 4.1 Identification of protein level 15. Approaches to understand the changes in various tissues 6 emergence and dynamics of COVID-19 4.2 Identification therapeutic targets 6 and future pandemics 10 5. Host-pathogen protein—Protein 16. Artificial intelligence (AI) in interactions and interactomics 6 COVID-19 11 5.1 Interaction of SARS-CoV2 proteins 17. Applications of mathematical modeling with host proteins 6 and simulation in COVID-19 11 5.2 Implication of protein interactions in 18. In silico disease modeling for developing therapy 7 COVID-19 11 vii viii Contents 19. System biology applications in 4.3 Reverse vaccinology and drug targets 29 COVID-19 11 4.4 Tools for therapeutics development 19.1 Cellular pathway involved against COVID-19 30 for genes that are genetically 5. Implementations of SARS-CoV-2 associated with COVID-19 11 genomics, metagenomics, and 19.2 Other genes that are identified pan-genomics approaches 30 using proteomic or interactomic 5.1 Decoding SARS-CoV-2 infection studies 12 biology 30 20. Computational approaches in 5.2 Biomarkers development for early COVID-19 drug discovery 12 diagnosis and screening of COVID-19 21. Computational approaches in susceptible population 31 COVID-19 vaccine development 12 5.3 Developing preventive strategy and 22. Applications of multiomics data in formulation against SARS-CoV-2 31 COVID-19 13 5.4 Developing therapeutics and 23. Publicly available resources in management for mild and severe COVID-19 research and their COVID-19 cases 32 applications 13 5.5 Individualized/personalized and 24. Emerging technologies for COVID-19 targeted therapy and care to diagnosis, prevention, and management 13 COVID-19 patients 33 25. Applications of digital and smart 5.6 Mechanism of multiorgan injuries technologies to control SARS-CoV2 and their squeal 34 transmission, rapid diagnosis, and 5.7 Predicting the long-term health monitoring 14 consequences and their treatment 26. Technologies for prediction of options in recovered patients 34 a patient’s health condition and 5.8 Other implementations 35 outcomes from COVID-19 15 6. Conclusion and future perspectives 35 27. Conclusion and overall implications 15 References 35 References 15 3. Genotype and phenotype 2. Genomics, metagenomics, correlations in COVID-19 and pan-genomics approaches K.R. Anu, Subham Das, and Alex Joseph in COVID-19 1. Introduction 41 Maaz Waseem, Amina Basheer, Farha Anwer, 2. Structure and lifecycle of coronavirus 41 Fatima Shahid, Tahreem Zaheer, and Amjad Ali 3. COVID-19 susceptibility genes identified 1. Introduction 23 by GWASs and implications of these 1.1 Genomic diversity 23 genes in developing COVID-19 disease 1.2 Structural proteins 23 subphenotypes 43 1.3 Accessory proteins 25 4. The cellular pathway of these SNPs/ 2. Metagenomic analysis 25 genes leading to COVID-19 subphenotypes 44 2.1 Metagenomic next generation 4.1 Protein coding SNPs 44 sequencing analysis 25 4.2 Regulatory SNPs 45 2.2 Mutational, recombinational, and 4.3 SNPs in microRNAs and Linc RNAs 46 phylogenetic analysis 26 5. Genetic variations associated with 3. Covid-19 pangenome dynamics 26 susceptibility and severity to COVID-19 46 3.1 Statistics-WG sequencing-databases- 5.1 Virus genome variation 46 CNBC-NCBI 26 5.2 Human genetic changes and COVID-19 46 3.2 Pangenome diversity, genomic 5.3 Inborn errors and congenital variation in the region 26 conditions and their associations with 4. Application and advancement of pan COVID-19 48 genome-derived data in therapeutics 28 5.4 Other factors 48 4.1 Immunoinformatics 28 6. Epigenetic mechanisms of SARS-CoV-2 4.2 Reverse genetic systems 28 infection and associated comorbidities 51 Contents ix 7. Genetic variations and impact on 7. Implementations of SARS-CoV-2 and diagnosis and treatment 52 COVID-19 proteomics 76 8. Implementations of genotype- 7.1 Targeting the spike-ACE2 interaction 76 phenotype correlations in COVID-19 52 7.2 Targeting other SARS-CoV-2 proteins 77 8.1 Decoding infection biology 52 7.3 Targeting the host response 77 8.2 COVID-19 and therapeutic treatment 52 8. Critical analyses of the present 8.3 Individualized/personalized care to achievements and future perspectives 77 patients 54 References 77 8.4 Multiorgan failure 54 8.5 Short-term and potential long-term 5. Metabolites and metabolomics in effects 54 COVID-19 9. Other implementations 54 Damodara Gowda, Adithi Kellarai, Pramukh 9.1 Conclusion and future perspectives 55 References 56 Subrahmanya Hegde, Megha Bhat Agni, Kenneth Lundstrom, and Debmalya Barh 4. Proteomic understanding of 1. Introduction 87 SARS-CoV-2 infection and 1.1 From metabolites to metabolomics 87 COVID-19: Biological, diagnostic, 2. Metabolites and metabolomics in viral and therapeutic perspectives infection 88 2.1 Metabolomics and metabolites in Fares Al-Ejeh, Maysaloun Merhi, Mariam Al-Muftah, Zika virus, dengue virus, and Queenie Fernandes, Lobna Al-Zaidan, Takwa SARS-CoV infections 89 Bedhiafi, Sarra Mestiri, Dina Moustafa, Nassiba 2.2 Metabolome and metabolites in Taib, Varghese Inchakalody, Afsheen Raza, SARS-CoV-2 89 Shahab Uddin, and Said Dermime 3. Metabolomics in SARS-CoV-2 89 1. Introduction 61 3.1 Metabolomics studies with different 2. Proteome of the SARS-CoV-2 virus 62 biofluids and important findings 3. Host-pathogen protein-protein related to COVID-19 90 interactions in COVID-19 62 3.2 The relevance of saliva and gut 3.1 Proteomic profiling of SARS-CoV-2- metabolome for COVID-19 90 infected host cells 62 3.3 The unique metabolic signature of 3.2 Protein-protein interactions 63 SARS-CoV-2 as compared to other 4. Proteomics in COVID-19 patients 66 viral infections 91 4.1 Blood proteomes of COVID-19 3.4 Metabolic signature of asymptotic, patients 66 mild, and severe COVID-19 91 4.2 Blood proteomic predictors of 4. Implementation of metabolites/ COVID-19 severity or outcome 66 metabolomics in COVID-19 92 4.3 Proteomics of childhood with 4.1 Biomarker development for early multisystem inflammatory syndrome 70 diagnosis and screening of COVID 4.4 Proteomics landscape of end organs susceptible populations 92 or autopsy 71 4.2 Developing preventive strategies and 5. Posttranslational modifications in formulation of prophylactic agents/ COVID-19 72 strategies 94 5.1 Phosphorylation 73 4.3 Development of therapeutics and 5.2 Glycosylation 73 management for mild and severe 5.3 Ubiquitination 73 COVID-19 cases 94 5.4 Other modifications 74 4.4 Understanding the mechanism of 6. Proteomics tools and applications for multiorgan injuries and their sequelae 95 COVID-19 74 4.5 Predicting long-term health 6.1 Detection of SARS-CoV-2 infection 74 consequences and treatment options 6.2 Early detection of COVID-19 in recovered patients 96 disease 75 5. Conclusions and future perspectives 96 6.3 Target identification tools 76 References 97