Abstract
Severe acute respiratory syndrome corona virus 2 (SARS-CoV-2) is pandemic recently emerged and is rapidly spreading in humans. However, the precise molecular mechanisms of the advancement and progression of SARS-CoV-2 infection remain unclear. The current investigation attempted to identify and functionally analyze the differentially expressed genes (DEGs) between SARS-CoV-2 infection and mock by using comprehensive bioinformatics analyses. The GSE148729 expression profiling by high throughput sequencing was downloaded from the Gene Expression Omnibus (GEO) and analyzed using the limma package in R software to identify DEGs. Pathway and gene ontology (GO) enrichment analysis of the up and down regulated genes were performed in ToppGene. The HIPPIE database was used to evaluate the interactions of up and down regulated genes and to construct a protein-protein interaction (PPI) network using Cytoscape software. Hub genes were selected using the Network Analyzer plugin. Subsequently, extensive target prediction and network analyses methods were used to assess, target gene - miRNA regulatory network and target gene - TF regulatory network. Receiver operating characteristic (ROC) analysis was utilized for validation. A total of 928 DEGs (461 up regulated genes and 467 down regulated genes) were identified between SARS-CoV-2 infection and mock samples. The Pathway enrichment analysis results showed that these up and down regulated genes were significantly enriched in cytokine-cytokine receptor interaction, and ascorbate and aldarate metabolism. Several significant GO terms, including the response to biotic stimulus and oxoacid metabolic process, were identified as being closely associated with these up and down regulated genes. The top hub genes and target genes were screened and included JUN, FBXO6, PCLAF, CFTR, TXNIP, PMAIP1, BRI3BP, FAHD1, PROX1, CXCL11, SERHL2 and CFI. ROC curve analysis showed that messenger RNA levels of these ten genes (DDX58, IFITM2, IRF1, PML, SAMHD1, ACSS1, CYP2U1, DDC, PNMT and UGT2A3) exhibited better diagnostic efficiency for SARS-CoV-2 infection and mock. The current investigation identified a series of key genes and pathways that may be involved in the progression of SARS-CoV-2 infection, providing a new understanding of the underlying molecular mechanisms of SARS-CoV-2 infection.
Regulatory network of metformin on adipogenesis determined by combining high-throughput sequencing and GEO database
