Abstract
BackgroundSevere acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is the causative agent of coronavirus disease 19 (COVID-19) that was emerged as a new member of coronaviruses since December 2019 in Wuhan, China and then after was spread in all continentals. Since SARS-CoV-2 has shown about 77.5% similarity to SARS-CoV, the transcriptome and immunological regulations of SARS-CoV-2 was expected to have high percentage of overlap with SARS-CoV.ResultsIn this study, we applied the single cell transcriptomics data of human bronchial epithelial cells (2B4 cell line) infected with SARS-CoV, which was annotated in the Expression Atlas database to expand this data to COVID-19. In addition, we employed system biology methods including gene ontology (GO) and Reactome pathway analyses to define functional genes and pathways in the infected cells with SARS-CoV. The transcriptomics analysis on the Expression Atlas database revealed that most genes from infected 2B4 cell line with SARS-CoV were downregulated leading to immune system hyperactivation, induction of signaling pathways, and consequently a cytokine storm. In addition, GO:0016192 (vesicle-mediated transport), GO:0006886 (intracellular protein transport), and GO:0006888 (ER to Golgi vesicle-mediated transport) were shown as top three GOs in the ontology network of infected cells with SARS-CoV. Meanwhile, R-HAS-6807070 (phosphatase and tensin homolog or PTEN regulation) showed the highest association with other Reactome pathways in the network of infected cells with SARS-CoV. PTEN plays a critical role in the activation of dendritic cells, B- and T-cells, and secretion of proinflammatory cytokines, which cooperates with downregulated genes in the promotion of cytokine storm in the COVID-19 patients.ConclusionsBased on the high similarity percentage of the transcriptome of SARS-CoV with SARS-CoV-2, the data of immunological regulations, signaling pathways, and proinflammatory cytokines in SARS-CoV infection can be expanded to COVID-19 to have a valid platform for future pharmaceutical and vaccine studies.
Highlights
Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is the causative agent of coronavirus disease 19 (COVID-19) that was emerged as a new member of coronaviruses since December 2019 in Wuhan, China and after was spread in all continentals
Gene Ontology (GO) Analysis In this analysis, the top ten gene ontology (GO) as a network were visualized that their gene products were attributed to some vital cellular functions of the infected 2B4 cell line with SARS-CoV
The p-value based on False Discovery Rate (FDR) < 0.05 as the significance cut-offs was applied in the GO analysis and Reactome pathway enrichment pathways in the evaluation of transcriptomic gene expression profiles by microarray assay in SARS-CoV infection, which has a potential to be expanded to CIVID-19
Summary
Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is the causative agent of coronavirus disease 19 (COVID-19) that was emerged as a new member of coronaviruses since December 2019 in Wuhan, China and after was spread in all continentals. The transcriptome of living organisms including RNA transcripts is studied by transcriptomics assays [1]. The outputs of RNA-Seq analysis can be validated by quantitative reverse transcription PCR (RTqPCR) as a complementary method in transcriptomics [4]. Two models, including cell lines for in vitro and animal models for in vivo assays are commonly considered for transcriptomics analysis of human responses to infectious agents [7]. In vitro and in vivo cell lines/animals interactions with pathogens and their host-specific responses to the pathogens can be evaluated by transcriptomics techniques. The interactions of the infected cell lines with immune system cellular components can be through recognition with specific T cells and natural killer (NK) cells as the crucial factors of the adaptive and innate immunity and reflected in the transcriptional responses [8,9,10]. The patterns of gene expression as a biomarker can be evaluated by transcriptomics techniques to discriminate the different stages of the infections and may influence physiological pathways
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