Transcriptomic Signatures of Airway Epithelium Infected With SARS-CoV-2: A Balance Between Anti-infection and Virus Load

Abstract

COVID-19 pneumonia requires effective medical therapies. However, it is a challenge to find therapeutic drugs that not only inhibit viral replication, but also inhibit the accompanying cytokine storm and maintain an appropriate immune response. In this study, the effects of SARS-CoV-2 on gene expression in lung epithelial cells from patients with COVID-19 were systematically evaluated with bioinformatics analysis methods. Transcriptome expression specific to bystander (exposed but uninfected) and infected cells were found, and the vital pathways were identified by conducting differentially expressed gene analysis regarding the relationship between gene signatures of COVID-19 infection and disease severity. We found that a high viral load did not necessarily imply a low response of epithelial cells or a poor disease convalescence. The ability to distinguish the role of virus-correlated genes facilitates the development of potential new medicines and therapies for COVID-19 infection.

Comparative Analysis of Circulating Levels of SARS-CoV-2 Antibodies and Inflammatory Mediators in Healthcare Workers and COVID-19 Patients

“…A high viral load in epithelial cells was not implicated in a severe ARDS outcome or poor recovery. On the other hand, gene signatures related to increased viral load fall into the mild or moderate group [ 25 ].…”

“…It is challenging to find therapeutic drugs that inhibit viral replication and cytokine storms yet maintain an effective anti-viral immune response. A study by Meng L et al identified that a high viral load does not necessarily imply a low immune response [ 25 ].…”

An Integrative Bioinformatic Analysis of Microbiome and Transcriptome for Predicting the Risk of Colon Adenocarcinoma

“…To screen for the crucial survival-related factors, the DEGs from the two risk groups were analysed with Wilcoxon's test and were enriched for the KEGG pathway analyses (Figures 3(a) and 3(b) ). GSEA KEGG pathway analyses were done using webgestalt.org website [ 8 ]. Of those pathways, PPAR signaling was upregulated and the IL17 signaling was decreased in the high risk group (Figures 3(c) and 3(d) ).…”

“…Statistics investigations were carried out with R software (version 3.6.0). Kaplan-Meier tests and ROC analysis were performed as we described previously [ 8 , 9 ]. In brief, we utilized the “survivor” and “survROC” software packages in both analyses [ 10 ].…”

Use of Single Cell Transcriptomic Techniques to Study the Role of High-Risk Human Papillomavirus Infection in Cervical Cancer

“…Statistical analyses were carried out using R software (version 3.6.0). Kaplan-Meier tests and ROC analysis were performed as described previously ( 13 , 14 ). In brief, the “survivor” and “survROC” software packages were utilized for both types of analyses ( 15 ).…”