Gene Expression Profiling Reveals the Shared and Distinct Transcriptional Signatures in Human Lung Epithelial Cells Infected With SARS-CoV-2, MERS-CoV, or SARS-CoV: Potential Implications in Cardiovascular Complications of COVID-19

Abstract

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is the causative virus for the current global pandemic known as coronavirus disease 2019 (COVID-19). SARS-CoV-2 belongs to the family of single-stranded RNA viruses known as coronaviruses, including the MERS-CoV and SARS-CoV that cause Middle East respiratory syndrome (MERS) and severe acute respiratory syndrome (SARS), respectively. These coronaviruses are associated in the way that they cause mild to severe upper respiratory tract illness. This study has used an unbiased analysis of publicly available gene expression datasets from Gene Expression Omnibus to understand the shared and unique transcriptional signatures of human lung epithelial cells infected with SARS-CoV-2 relative to MERS-CoV or SARS-CoV. A major goal was to discover unique cellular responses to SARS-CoV-2 among these three coronaviruses. Analyzing differentially expressed genes (DEGs) shared by the three datasets led to a set of 17 genes, suggesting the lower expression of genes related to acute inflammatory response (TNF, IL32, IL1A, CXCL1, and CXCL3) in SARS-CoV-2. This subdued transcriptional response to SARS-CoV-2 may cause prolonged viral replication, leading to severe lung damage. Downstream analysis of unique DEGs of SARS-CoV-2 infection revealed changes in genes related to apoptosis (NRP1, FOXO1, TP53INP1, CSF2, and NLRP1), coagulation (F3, PROS1, ITGB3, and TFPI2), and vascular function (VAV3, TYMP, TCF4, and NR2F2), which may contribute to more systemic cardiovascular complications of COVID-19 than MERS and SARS. The study has uncovered a novel set of transcriptomic signatures unique to SARS-CoV-2 infection and shared by three coronaviruses, which may guide the initial efforts in the development of prognostic or therapeutic tools for COVID-19.

Keywords: COVID-19 and transcriptome analysis; MERS-CoV; SARS-CoV; SARS-CoV-2; cardiovasclar disease.

Figure 1

Gene expression profiles of the differentially expressed genes (DEGs) in human lung epithelial cells infected with coronaviruses. (A) Workflow of gene expression analysis. Selection process of eligible datasets for transcriptome analysis was based on datasets generated from infection of human lung epithelial cell in culture with SARS-CoV-2, MERS-CoV, or SARS-CoV. SARS-CoV-2, severe acute respiratory syndrome coronavirus 2; CoV, coronavirus; MERS-CoV, Middle East respiratory syndrome coronavirus; SARS-CoV, severe acute respiratory syndrome coronavirus and GEO, Gene Expression Omnibus. (B–D) Heatmaps of expression profiles for the top 25 increased and 25 decreased DEGs obtained from RNA-seq data analysis. Clustering of selected genes on the heatmap was performed by hierarchical clustering algorithm using Euclidean distance measure. (B) SARS-CoV-2, (C) MERS-CoV, and (D) SARS-CoV.

Figure 2

Shared transcriptional signatures between the three coronaviruses. (A) Venn diagram representing the shared and unique DEGs portion between three coronaviruses. (B) Heatmap representation of expression profiles for the common DEGs between coronaviruses. Clustering of selected genes on the heatmap was performed by hierarchical clustering algorithm using Euclidean distance measure. Expression scale: blue (low expression) to yellow (high expression). (C) coronavirus–gene network representing the shared and unique DEGs. Network was created between coronaviruses and their top 100 DEGs on cytoscape platform. Network core represents the coronaviruses (source nodes) and gene (target nodes). Inner circles of genes in the network are the shared ones, while outer circle genes are unique to each coronavirus.

Figure 3

Type 1 IFN response and apoptotic genes signature in three coronaviruses. (A) Heatmap representation of expression profiles for the type 1 IFN response genes (GO:0060337) between coronaviruses. (B) Heatmap representation of expression profiles for the apoptotic gene signatures (GO:0042981) between coronaviruses. Clustering of selected genes on the heatmap was performed by hierarchical clustering algorithm using Euclidean distance measure. Expression scale: blue (low expression) to yellow (high expression).

Figure 4

Downstream analysis of SARS-CoV-2–specific DEGs. (A) Overrepresentation of pathways and Gene Ontology categories in biological networks identified from DEGs unique to SARS-CoV-2. Significantly overrepresented biological processes based on GO terms were visualized in Cytoscape. The size of a node is proportional to the number of targets in the GO category. The color represents enrichment significance—the deeper the color on a color scale, the higher the enrichment significance. p values were adjusted using a Benjamini and Hochberg FDR correction. Analysis revealed the enriched pathways associated with immune responses and chemotaxis, blood coagulation, apoptosis signaling pathway, vasculature remodeling, and vascular cell proliferation. (B) Network-based analysis of hub DEGs. Interaction network of SARS-CoV-2 unique genes; red nodes represent increased and green nodes represent decreased DEGs. (C) Regulatory gene network analysis of the top 10 enriched kinases (green) and transcription factors (red) using SARS-CoV-2 specific DEGs. Yellow nodes represent the intermediate proteins in the regulatory network. Node size represents the significance of protein based on p value; the bigger the node size, the higher the significance value.