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Potential Molecular Mechanisms and Remdesivir Treatment for Acute Respiratory Syndrome Corona Virus 2 Infection/COVID 19 Through RNA Sequencing and Bioinformatics Analysis
INTRODUCTION: Severe acute respiratory syndrome corona virus 2 (SARS-CoV-2) infections (COVID 19) is a progressive viral infection that has been investigated extensively. However, genetic features and molecular pathogenesis underlying remdesivir treatment for SARS-CoV-2 infection remain unclear. Her...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
SAGE Publications
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8725226/ https://www.ncbi.nlm.nih.gov/pubmed/34992355 http://dx.doi.org/10.1177/11779322211067365 |
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author | Prashanth, G Vastrad, Basavaraj Vastrad, Chanabasayya Kotrashetti, Shivakumar |
author_facet | Prashanth, G Vastrad, Basavaraj Vastrad, Chanabasayya Kotrashetti, Shivakumar |
author_sort | Prashanth, G |
collection | PubMed |
description | INTRODUCTION: Severe acute respiratory syndrome corona virus 2 (SARS-CoV-2) infections (COVID 19) is a progressive viral infection that has been investigated extensively. However, genetic features and molecular pathogenesis underlying remdesivir treatment for SARS-CoV-2 infection remain unclear. Here, we used bioinformatics to investigate the candidate genes associated in the molecular pathogenesis of remdesivir-treated SARS-CoV-2-infected patients. METHODS: Expression profiling by high-throughput sequencing dataset (GSE149273) was downloaded from the Gene Expression Omnibus, and the differentially expressed genes (DEGs) in remdesivir-treated SARS-CoV-2 infection samples and nontreated SARS-CoV-2 infection samples with an adjusted P value of <.05 and a |log fold change| > 1.3 were first identified by limma in R software package. Next, pathway and gene ontology (GO) enrichment analysis of these DEGs was performed. Then, the hub genes were identified by the NetworkAnalyzer plugin and the other bioinformatics approaches including protein-protein interaction network analysis, module analysis, target gene—miRNA regulatory network, and target gene—TF regulatory network. Finally, a receiver-operating characteristic analysis was performed for diagnostic values associated with hub genes. RESULTS: A total of 909 DEGs were identified, including 453 upregulated genes and 457 downregulated genes. As for the pathway and GO enrichment analysis, the upregulated genes were mainly linked with influenza A and defense response, whereas downregulated genes were mainly linked with drug metabolism—cytochrome P450 and reproductive process. In addition, 10 hub genes (VCAM1, IKBKE, STAT1, IL7R, ISG15, E2F1, ZBTB16, TFAP4, ATP6V1B1, and APBB1) were identified. Receiver-operating characteristic analysis showed that hub genes (CIITA, HSPA6, MYD88, SOCS3, TNFRSF10A, ADH1A, CACNA2D2, DUSP9, FMO5, and PDE1A) had good diagnostic values. CONCLUSION: This study provided insights into the molecular mechanism of remdesivir-treated SARS-CoV-2 infection that might be useful in further investigations. |
format | Online Article Text |
id | pubmed-8725226 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | SAGE Publications |
record_format | MEDLINE/PubMed |
spelling | pubmed-87252262022-01-05 Potential Molecular Mechanisms and Remdesivir Treatment for Acute Respiratory Syndrome Corona Virus 2 Infection/COVID 19 Through RNA Sequencing and Bioinformatics Analysis Prashanth, G Vastrad, Basavaraj Vastrad, Chanabasayya Kotrashetti, Shivakumar Bioinform Biol Insights Original Research INTRODUCTION: Severe acute respiratory syndrome corona virus 2 (SARS-CoV-2) infections (COVID 19) is a progressive viral infection that has been investigated extensively. However, genetic features and molecular pathogenesis underlying remdesivir treatment for SARS-CoV-2 infection remain unclear. Here, we used bioinformatics to investigate the candidate genes associated in the molecular pathogenesis of remdesivir-treated SARS-CoV-2-infected patients. METHODS: Expression profiling by high-throughput sequencing dataset (GSE149273) was downloaded from the Gene Expression Omnibus, and the differentially expressed genes (DEGs) in remdesivir-treated SARS-CoV-2 infection samples and nontreated SARS-CoV-2 infection samples with an adjusted P value of <.05 and a |log fold change| > 1.3 were first identified by limma in R software package. Next, pathway and gene ontology (GO) enrichment analysis of these DEGs was performed. Then, the hub genes were identified by the NetworkAnalyzer plugin and the other bioinformatics approaches including protein-protein interaction network analysis, module analysis, target gene—miRNA regulatory network, and target gene—TF regulatory network. Finally, a receiver-operating characteristic analysis was performed for diagnostic values associated with hub genes. RESULTS: A total of 909 DEGs were identified, including 453 upregulated genes and 457 downregulated genes. As for the pathway and GO enrichment analysis, the upregulated genes were mainly linked with influenza A and defense response, whereas downregulated genes were mainly linked with drug metabolism—cytochrome P450 and reproductive process. In addition, 10 hub genes (VCAM1, IKBKE, STAT1, IL7R, ISG15, E2F1, ZBTB16, TFAP4, ATP6V1B1, and APBB1) were identified. Receiver-operating characteristic analysis showed that hub genes (CIITA, HSPA6, MYD88, SOCS3, TNFRSF10A, ADH1A, CACNA2D2, DUSP9, FMO5, and PDE1A) had good diagnostic values. CONCLUSION: This study provided insights into the molecular mechanism of remdesivir-treated SARS-CoV-2 infection that might be useful in further investigations. SAGE Publications 2021-12-23 /pmc/articles/PMC8725226/ /pubmed/34992355 http://dx.doi.org/10.1177/11779322211067365 Text en © The Author(s) 2021 https://creativecommons.org/licenses/by-nc/4.0/This article is distributed under the terms of the Creative Commons Attribution-NonCommercial 4.0 License (https://creativecommons.org/licenses/by-nc/4.0/) which permits non-commercial use, reproduction and distribution of the work without further permission provided the original work is attributed as specified on the SAGE and Open Access pages (https://us.sagepub.com/en-us/nam/open-access-at-sage). |
spellingShingle | Original Research Prashanth, G Vastrad, Basavaraj Vastrad, Chanabasayya Kotrashetti, Shivakumar Potential Molecular Mechanisms and Remdesivir Treatment for Acute Respiratory Syndrome Corona Virus 2 Infection/COVID 19 Through RNA Sequencing and Bioinformatics Analysis |
title | Potential Molecular Mechanisms and Remdesivir Treatment for Acute
Respiratory Syndrome Corona Virus 2 Infection/COVID 19 Through RNA Sequencing
and Bioinformatics Analysis |
title_full | Potential Molecular Mechanisms and Remdesivir Treatment for Acute
Respiratory Syndrome Corona Virus 2 Infection/COVID 19 Through RNA Sequencing
and Bioinformatics Analysis |
title_fullStr | Potential Molecular Mechanisms and Remdesivir Treatment for Acute
Respiratory Syndrome Corona Virus 2 Infection/COVID 19 Through RNA Sequencing
and Bioinformatics Analysis |
title_full_unstemmed | Potential Molecular Mechanisms and Remdesivir Treatment for Acute
Respiratory Syndrome Corona Virus 2 Infection/COVID 19 Through RNA Sequencing
and Bioinformatics Analysis |
title_short | Potential Molecular Mechanisms and Remdesivir Treatment for Acute
Respiratory Syndrome Corona Virus 2 Infection/COVID 19 Through RNA Sequencing
and Bioinformatics Analysis |
title_sort | potential molecular mechanisms and remdesivir treatment for acute
respiratory syndrome corona virus 2 infection/covid 19 through rna sequencing
and bioinformatics analysis |
topic | Original Research |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8725226/ https://www.ncbi.nlm.nih.gov/pubmed/34992355 http://dx.doi.org/10.1177/11779322211067365 |
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