Overlapping host pathways between SARS-CoV-2 and its potential copathogens: An in silico analysis

BACKGROUND: SARS-CoV-2 coinfection with other viral and bacterial pathogens and their interactions are increasingly recognized in the literature as potential determinants of COVID-19 phenotypes. The aim of this study was to determine infection induced, host transcriptomic overlap between SARS-CoV-2 and other pathogens. MATERIALS AND METHODS: SARS-CoV-2 infection induced gene expression data were used for gene set enrichment analysis (GSEA) via the Enrichr platform. GSEA compared the extracted signature to VirusMINT, Virus and Microbe perturbations from Gene Expression Omnibus (GEO) in order to detect overlap with other pathogen induced host gene signatures. For all analyses, a false discovery rate (FDR) <0.05 was considered statistically significant. RESULTS: GSEA via Enrichr revealed several significantly enriched sub-signatures associated with HSV1, EBV, HIV1, IAV, RSV, P.Aeruginosa, Staph. Aureus and Strep. Pneumoniae infections, among other pathogens (FDR < 0.05). These signatures were detected in at least 6 infection-induced transcriptomic studies from GEO and involved both bronchial epithelial and peripheral blood immune cells. DISCUSSION: SARS-CoV-2 infection may function synergistically with other viral and bacterial pathogens at the transcriptomic level. Notably, several meta-analyses of COVID-19 cohorts have furthermore corroborated viral and bacterial pathogens reported herein as coinfections with SARS-CoV-2. The identification of common, perturbed gene networks outlines a common host targetome for these pathogens, and furthermore provides candidates for biomarker discovery and drug design.