Potential Molecular Mechanisms and Remdesivir Treatment for Acute Respiratory Syndrome Corona Virus 2 Infection/COVID 19 Through RNA Sequencing and Bioinformatics Analysis

G Prashanth; Basavaraj Vastrad; Chanabasayya Vastrad; Shivakumar Kotrashetti

doi:10.1177/11779322211067365

Potential Molecular Mechanisms and Remdesivir Treatment for Acute Respiratory Syndrome Corona Virus 2 Infection/COVID 19 Through RNA Sequencing and Bioinformatics Analysis

Bioinform Biol Insights. 2021 Dec 23:15:11779322211067365. doi: 10.1177/11779322211067365. eCollection 2021.

Authors

G Prashanth¹, Basavaraj Vastrad², Chanabasayya Vastrad³, Shivakumar Kotrashetti³

Affiliations

¹ Department of General Medicine, Basaveshwara Medical College, Chitradurga, India.
² Department of Biochemistry, Basaveshwar College of Pharmacy, Gadag, India.
³ Biostatistics and Bioinformatics, Chanabasava Nilaya, Dharwad, India.

Abstract

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.

Keywords: ROC analysis; SARS-CoV-2 infection; differentially expressed genes; pathway enrichment analysis; protein-protein interaction.