Table Of ContentOmics Approaches and Technologies in COVID-19
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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
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Dedication
We dedicate the book to our mothers, mothers of our children,
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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
