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Article: Natural selection plays a significant role in governing the codon usage bias in the novel SARS-CoV-2 variants of concern (VOC).

Tyagi, Neetu / Sardar, Rahila / Gupta, Dinesh

2022 Volume 10, Page(s) e13562

Abstract: The ongoing prevailing COVID-19 pandemic caused by SARS-CoV-2 is becoming one of the major global health concerns worldwide. The SARS-CoV-2 genome encodes spike (S) glycoprotein that plays a very crucial role in viral entry into the host ... ...

Abstract	The ongoing prevailing COVID-19 pandemic caused by SARS-CoV-2 is becoming one of the major global health concerns worldwide. The SARS-CoV-2 genome encodes spike (S) glycoprotein that plays a very crucial role in viral entry into the host cell
Language	English
Publishing date	2022-06-23
Publishing country	United States
Document type	Journal Article
ZDB-ID	2703241-3
ISSN	2167-8359
ISSN	2167-8359
DOI	10.7717/peerj.13562
Database	MEDical Literature Analysis and Retrieval System OnLINE

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Article: Machine Learning Assisted Prediction of Prognostic Biomarkers Associated With COVID-19, Using Clinical and Proteomics Data.

Sardar, Rahila / Sharma, Arun / Gupta, Dinesh

Frontiers in genetics

2021 Volume 12, Page(s) 636441

Abstract: With the availability of COVID-19-related clinical data, healthcare researchers can now explore the potential of computational technologies such as artificial intelligence (AI) and machine learning (ML) to discover biomarkers for accurate detection, ... ...

Abstract	With the availability of COVID-19-related clinical data, healthcare researchers can now explore the potential of computational technologies such as artificial intelligence (AI) and machine learning (ML) to discover biomarkers for accurate detection, early diagnosis, and prognosis for the management of COVID-19. However, the identification of biomarkers associated with survival and deaths remains a major challenge for early prognosis. In the present study, we have evaluated and developed AI-based prediction algorithms for predicting a COVID-19 patient's survival or death based on a publicly available dataset consisting of clinical parameters and protein profile data of hospital-admitted COVID-19 patients. The best classification model based on clinical parameters achieved a maximum accuracy of 89.47% for predicting survival or death of COVID-19 patients, with a sensitivity and specificity of 85.71 and 92.45%, respectively. The classification model based on normalized protein expression values of 45 proteins achieved a maximum accuracy of 89.01% for predicting the survival or death, with a sensitivity and specificity of 92.68 and 86%, respectively. Interestingly, we identified 9 clinical and 45 protein-based putative biomarkers associated with the survival/death of COVID-19 patients. Based on our findings, few clinical features and proteins correlate significantly with the literature and reaffirm their role in the COVID-19 disease progression at the molecular level. The machine learning-based models developed in the present study have the potential to predict the survival chances of COVID-19 positive patients in the early stages of the disease or at the time of hospitalization. However, this has to be verified on a larger cohort of patients before it can be put to actual clinical practice. We have also developed a webserver CovidPrognosis, where clinical information can be uploaded to predict the survival chances of a COVID-19 patient. The webserver is available at http://14.139.62.220/covidprognosis/.
Language	English
Publishing date	2021-05-20
Publishing country	Switzerland
Document type	Journal Article
ZDB-ID	2606823-0
ISSN	1664-8021
ISSN	1664-8021
DOI	10.3389/fgene.2021.636441
Database	MEDical Literature Analysis and Retrieval System OnLINE

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Article ; Online: Dataset of mutational analysis, miRNAs targeting SARS-CoV-2 genes and host gene expression in SARS-CoV and SARS-CoV-2 infections.

Sardar, Rahila / Satish, Deepshikha / Birla, Shweta / Gupta, Dinesh

Data in brief

2020 Volume 32, Page(s) 106207

Abstract: The identification of host-miRNAs targeting mutated virus genes is crucial to understand the miRNA mediated host-defense mechanism in virus infections. To understand the mechanism in COVID-19 infections, we collected genome sequences of SARS-CoV-2 with ... ...

Abstract	The identification of host-miRNAs targeting mutated virus genes is crucial to understand the miRNA mediated host-defense mechanism in virus infections. To understand the mechanism in COVID-19 infections, we collected genome sequences of SARS-CoV-2 with its metadata from the GISAID database (submitted till April 2020) and identified mutational changes in the sequences. The dataset consists of genes with mutation event count and entropy scores. We predicted host-miRNAs targeting the genes in the genomes and compared it with that in related viral species. We have identified 2284 miRNAs targeting MERS genomes, 2074 miRNAs targeting SARS genomes, and 1599 miRNAs targeting SARS-CoV-2 genomes, identified using the miRNA target prediction software miRanda. The host miRNAs targeting SARS-CoV-2 genes were further validated to be anti-viral miRNAs and their role in respiratory diseases through a literature survey, which helped in the identification of 42 conserved antiviral miRNAs. The data could be used to validate the anti-viral role of the predicted miRNAs and design miRNA-based therapeutics against SARS-CoV-2.
Keywords	covid19
Language	English
Publishing date	2020-08-21
Publishing country	Netherlands
Document type	Journal Article
ZDB-ID	2786545-9
ISSN	2352-3409 ; 2352-3409
ISSN (online)	2352-3409
ISSN	2352-3409
DOI	10.1016/j.dib.2020.106207
Database	MEDical Literature Analysis and Retrieval System OnLINE

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Article: Integrative analyses of SARS-CoV-2 genomes from different geographical locations reveal unique features potentially consequential to host-virus interaction, pathogenesis and clues for novel therapies.

Sardar, Rahila / Satish, Deepshikha / Birla, Shweta / Gupta, Dinesh

Heliyon

2020 Volume 6, Issue 9, Page(s) e04658

Abstract: We have performed an integrative analysis of SARS-CoV-2 genome sequences from different countries. Apart from mutational analysis, we have predicted host antiviral miRNAs targeting virus genes, PTMs in the virus proteins and antiviral peptides. A ... ...

Abstract	We have performed an integrative analysis of SARS-CoV-2 genome sequences from different countries. Apart from mutational analysis, we have predicted host antiviral miRNAs targeting virus genes, PTMs in the virus proteins and antiviral peptides. A comparison of the analyses with other coronavirus genomes has been performed, wherever possible. Our analysis confirms unique features in the SARS-CoV-2 genomes absent in other evolutionarily related coronavirus family genomes, which presumably confer unique infection, transmission and virulence capabilities to the virus. For understanding the crucial factors involved in host-virus interactions, we have performed Bioinformatics aided analysis integrated with experimental data related to other corona viruses. We have identified 42 conserved miRNAs that can potentially target SARS-CoV-2 genomes. Interestingly, out of these, 3 are previously reported to exhibit antiviral activity against other respiratory viruses. Gene expression analysis of known host antiviral factors reveals significant over-expression of
Keywords	covid19
Language	English
Publishing date	2020-08-20
Publishing country	England
Document type	Journal Article
ZDB-ID	2835763-2
ISSN	2405-8440
ISSN	2405-8440
DOI	10.1016/j.heliyon.2020.e04658
Database	MEDical Literature Analysis and Retrieval System OnLINE

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Article: Identification of Novel SARS-CoV-2 Drug Targets by Host MicroRNAs and Transcription Factors Co-regulatory Interaction Network Analysis.

Sardar, Rahila / Satish, Deepshikha / Gupta, Dinesh

Frontiers in genetics

2020 Volume 11, Page(s) 571274

Abstract: Understanding the host regulatory mechanisms opposing virus infection and virulence can provide actionable insights to identify novel therapeutics against severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). We have used a network biology ... ...

Abstract	Understanding the host regulatory mechanisms opposing virus infection and virulence can provide actionable insights to identify novel therapeutics against severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). We have used a network biology approach to elucidate the crucial factors involved in host responses involving host-microRNA (miRNA) interactions with host and virus genes using recently published experimentally verified protein-protein interaction data. We were able to identify 311 host genes to be potentially targetable by 2,197 human miRNAs. These miRNAs are known to be involved in various biological processes, such as T-cell differentiation and activation, virus replication, and immune system. Among these, the anti-viral activity of 38 miRNAs to target 148 host genes is experimentally validated. Six anti-viral miRNAs, namely, hsa-miR-1-3p, hsa-miR-17-5p, hsa-miR-199a-3p, hsa-miR-429, hsa-miR-15a-5p, and hsa-miR-20a-5p, are previously reported to be anti-viral in respiratory diseases and were found to be downregulated. The interaction network of the 2,197 human miRNAs and interacting transcription factors (TFs) enabled the identification of 51 miRNAs to interact with 77 TFs inducing activation or repression and affecting gene expression of linked genes. Further, from the gene regulatory network analysis, the top five hub genes
Keywords	covid19
Language	English
Publishing date	2020-10-14
Publishing country	Switzerland
Document type	Journal Article
ZDB-ID	2606823-0
ISSN	1664-8021
ISSN	1664-8021
DOI	10.3389/fgene.2020.571274
Database	MEDical Literature Analysis and Retrieval System OnLINE

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Article: Integrative analyses of SARS-CoV-2 genomes from different geographical locations reveal unique features potentially consequential to host-virus interaction, pathogenesis and clues for novel therapies

Sardar, Rahila / Satish, Deepshikha / Birla, Shweta / Gupta, Dinesh

Heliyon. 2020 Sept., v. 6, no. 9

2020

Abstract	We have performed an integrative analysis of SARS-CoV-2 genome sequences from different countries. Apart from mutational analysis, we have predicted host antiviral miRNAs targeting virus genes, PTMs in the virus proteins and antiviral peptides. A comparison of the analyses with other coronavirus genomes has been performed, wherever possible. Our analysis confirms unique features in the SARS-CoV-2 genomes absent in other evolutionarily related coronavirus family genomes, which presumably confer unique infection, transmission and virulence capabilities to the virus. For understanding the crucial factors involved in host-virus interactions, we have performed Bioinformatics aided analysis integrated with experimental data related to other corona viruses. We have identified 42 conserved miRNAs that can potentially target SARS-CoV-2 genomes. Interestingly, out of these, 3 are previously reported to exhibit antiviral activity against other respiratory viruses. Gene expression analysis of known host antiviral factors reveals significant over-expression of IFITM3 and down regulation of cathepsins during SARS-CoV-2 infection, suggesting its active role in pathogenesis and delayed immune response. We also predicted antiviral peptides which can be used in designing peptide based drugs against SARS-CoV-2. Our analysis explores the functional impact of the virus mutations on its proteins and interaction of its genes with host antiviral mechanisms.
Keywords	Severe acute respiratory syndrome coronavirus 2 ; antiviral properties ; bioinformatics ; cathepsins ; host-pathogen relationships ; immune response ; microRNA ; mutational analysis ; pathogenesis ; peptides ; virulence ; viruses
Language	English
Dates of publication	2020-09
Publishing place	Elsevier Ltd
Document type	Article
Note	NAL-AP-2-clean
ZDB-ID	2835763-2
ISSN	2405-8440
ISSN	2405-8440
DOI	10.1016/j.heliyon.2020.e04658
Database	NAL-Catalogue (AGRICOLA)

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Article: Dataset of mutational analysis, miRNAs targeting SARS-CoV-2 genes and host gene expression in SARS-CoV and SARS-CoV-2 infections

Sardar, Rahila / Satish, Deepshikha / Birla, Shweta / Gupta, Dinesh

Data in Brief. 2020 Oct., v. 32

2020

Abstract	The identification of host-miRNAs targeting mutated virus genes is crucial to understand the miRNA mediated host-defense mechanism in virus infections. To understand the mechanism in COVID-19 infections, we collected genome sequences of SARS-CoV-2 with its metadata from the GISAID database (submitted till April 2020) and identified mutational changes in the sequences. The dataset consists of genes with mutation event count and entropy scores. We predicted host-miRNAs targeting the genes in the genomes and compared it with that in related viral species. We have identified 2284 miRNAs targeting MERS genomes, 2074 miRNAs targeting SARS genomes, and 1599 miRNAs targeting SARS-CoV-2 genomes, identified using the miRNA target prediction software miRanda. The host miRNAs targeting SARS-CoV-2 genes were further validated to be anti-viral miRNAs and their role in respiratory diseases through a literature survey, which helped in the identification of 42 conserved antiviral miRNAs. The data could be used to validate the anti-viral role of the predicted miRNAs and design miRNA-based therapeutics against SARS-CoV-2.
Keywords	COVID-19 infection ; Severe acute respiratory syndrome coronavirus 2 ; computer software ; data collection ; databases ; entropy ; gene expression ; metadata ; microRNA ; mutation ; mutational analysis ; prediction ; surveys ; therapeutics ; viruses
Language	English
Dates of publication	2020-10
Publishing place	Elsevier Inc.
Document type	Article
ZDB-ID	2786545-9
ISSN	2352-3409
ISSN	2352-3409
DOI	10.1016/j.dib.2020.106207
Database	NAL-Catalogue (AGRICOLA)

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Article ; Online: Comparative analysis of codon usage patterns in SARS-CoV-2, its mutants and other respiratory viruses

Tyagi, Neetu / Sardar, Rahila / Gupta, Dinesh

bioRxiv

Abstract: The Coronavirus disease 2019 (COVID-19) outbreak caused by Severe Acute Respiratory Syndrome Coronavirus 2 virus (SARS-CoV-2) poses a worldwide human health crisis, causing respiratory illness with a high mortality rate. To investigate the factors ... ...

Abstract	The Coronavirus disease 2019 (COVID-19) outbreak caused by Severe Acute Respiratory Syndrome Coronavirus 2 virus (SARS-CoV-2) poses a worldwide human health crisis, causing respiratory illness with a high mortality rate. To investigate the factors governing codon usage bias in all the respiratory viruses, including SARS-CoV-2 isolates from different geographical locations (~62K) including two recently emerging strains from the United Kingdom (UK), i.e.,VUI202012/01 and South Africa (SA), i.e., 501.Y.V2 codon usage bias (CUBs) analysis was performed. The analysis includes RSCU analysis, GC content calculation, ENC analysis, di-nucleotide frequency and neutrality plot analysis. We were motivated to conduct the study to fulfil two primary aims: first, to identify the difference in codon usage bias amongst all SARS-CoV-2 genomes and secondly, to compare their CUBs properties with other respiratory viruses. A biased nucleotide composition was found as most of the highly preferred codons were A/U-ending in all the respiratory viruses studied here. When compared with human host, the RSCU analysis led to the identification of 11 over-represented codons and 9 under-represented codons in SARS-CoV-2 genomes. Correlation analysis of ENC and GC3s revealed that mutational pressure is the leading force determining the CUBs. The present study results yields a better understanding of codon usage preferences for SARS-CoV-2 genomes and discover the possible evolutionary determinants responsible for the biases found among the respiratory viruses, thus unveils a unique feature of the SARS-CoV-2 evolution and adaptation. To the best of our knowledge, this is the first attempt at comparative CUBs analysis on the worldwide genomes of SARS-CoV-2, including novel emerged strains and other respiratory viruses.
Keywords	covid19
Language	English
Publishing date	2021-03-03
Publisher	Cold Spring Harbor Laboratory
Document type	Article ; Online
DOI	10.1101/2021.03.03.433699
Database	COVID19

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Article ; Online: Comparative analyses of SAR-CoV2 genomes from different geographical locations and other coronavirus family genomes reveals unique features potentially consequential to host-virus interaction and pathogenesis

Sardar, Rahila / Satish, Deepshikha / Birla, Shweta / Gupta, Dinesh

bioRxiv

Abstract: The ongoing pandemic of the coronavirus disease 2019 (COVID-19) is an infectious disease caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV2). We have performed an integrated sequence-based analysis of SARS-CoV2 genomes from different ... ...

Abstract	The ongoing pandemic of the coronavirus disease 2019 (COVID-19) is an infectious disease caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV2). We have performed an integrated sequence-based analysis of SARS-CoV2 genomes from different geographical locations in order to identify its unique features absent in SARS-CoV and other related coronavirus family genomes, conferring unique infection, facilitation of transmission, virulence and immunogenic features to the virus. The phylogeny of the genomes yields some interesting results. Systematic gene level mutational analysis of the genomes has enabled us to identify several unique features of the SARS-CoV2 genome, which includes a unique mutation in the spike surface glycoprotein (A930V (24351C>T)) in the Indian SARS-CoV2, absent in other strains studied here. We have also predicted the impact of the mutations in the spike glycoprotein function and stability, using computational approach. To gain further insights into host responses to viral infection, we predict that antiviral host-miRNAs may be controlling the viral pathogenesis. Our analysis reveals nine host miRNAs which can potentially target SARS-CoV2 genes. Interestingly, the nine miRNAs do not have targets in SARS and MERS genomes. Also, hsa-miR-27b is the only unique miRNA which has a target gene in the Indian SARS-CoV2 genome. We also predicted immune epitopes in the genomes
Keywords	covid19
Publisher	BioRxiv; WHO
Document type	Article ; Online
DOI	10.1101/2020.03.21.001586
Database	COVID19

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Article: Integrative analyses of SARS-CoV-2 genomes from different geographical locations reveal unique features potentially consequential to host-virus interaction, pathogenesis and clues for novel therapies

Sardar, Rahila / Satish, Deepshikha / Birla, Shweta / Gupta, Dinesh

Heliyon

Abstract	We have performed an integrative analysis of SARS-CoV-2 genome sequences from different countries. Apart from mutational analysis, we have predicted host antiviral miRNAs targeting virus genes, PTMs in the virus proteins and antiviral peptides. A comparison of the analyses with other coronavirus genomes has been performed, wherever possible. Our analysis confirms unique features in the SARS-CoV-2 genomes absent in other evolutionarily related coronavirus family genomes, which presumably confer unique infection, transmission and virulence capabilities to the virus. For understanding the crucial factors involved in host-virus interactions, we have performed Bioinformatics aided analysis integrated with experimental data related to other corona viruses. We have identified 42 conserved miRNAs that can potentially target SARS-CoV-2 genomes. Interestingly, out of these, 3 are previously reported to exhibit antiviral activity against other respiratory viruses. Gene expression analysis of known host antiviral factors reveals significant over-expression of IFITM3 and down regulation of cathepsins during SARS-CoV-2 infection, suggesting its active role in pathogenesis and delayed immune response. We also predicted antiviral peptides which can be used in designing peptide based drugs against SARS-CoV-2. Our analysis explores the functional impact of the virus mutations on its proteins and interaction of its genes with host antiviral mechanisms.
Keywords	covid19
Publisher	WHO
Document type	Article
Note	WHO #Covidence: #723218
Database	COVID19

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Article: Natural selection plays a significant role in governing the codon usage bias in the novel SARS-CoV-2 variants of concern (VOC).

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Article: Machine Learning Assisted Prediction of Prognostic Biomarkers Associated With COVID-19, Using Clinical and Proteomics Data.

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Article ; Online: Dataset of mutational analysis, miRNAs targeting SARS-CoV-2 genes and host gene expression in SARS-CoV and SARS-CoV-2 infections.

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Article: Integrative analyses of SARS-CoV-2 genomes from different geographical locations reveal unique features potentially consequential to host-virus interaction, pathogenesis and clues for novel therapies.

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Article: Identification of Novel SARS-CoV-2 Drug Targets by Host MicroRNAs and Transcription Factors Co-regulatory Interaction Network Analysis.

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Article: Integrative analyses of SARS-CoV-2 genomes from different geographical locations reveal unique features potentially consequential to host-virus interaction, pathogenesis and clues for novel therapies

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Article: Dataset of mutational analysis, miRNAs targeting SARS-CoV-2 genes and host gene expression in SARS-CoV and SARS-CoV-2 infections

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Article ; Online: Comparative analysis of codon usage patterns in SARS-CoV-2, its mutants and other respiratory viruses

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Inter-library loan at ZB MED

Article ; Online: Comparative analyses of SAR-CoV2 genomes from different geographical locations and other coronavirus family genomes reveals unique features potentially consequential to host-virus interaction and pathogenesis

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Article: Integrative analyses of SARS-CoV-2 genomes from different geographical locations reveal unique features potentially consequential to host-virus interaction, pathogenesis and clues for novel therapies

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Inter-library loan at ZB MED