The transcriptomic profiling of SARS-CoV-2 compared to SARS, MERS, EBOV, and H1N1

  1. Alsamman M. Alsamman
  2. Hatem Zayed

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Abstract

The SARS-CoV-2 (COVID-19) pandemic is a global crisis that threatens our way of life. As of November 18, 2020, SARS-CoV-2 has claimed more than 1,342,709 lives, with a global mortality rate of ~2.4% and a recovery rate of ~69.6%. Understanding the interaction of cellular targets with the SARS-CoV-2 infection is crucial for therapeutic development. Therefore, the aim of this study was to perform a comparative analysis of transcriptomic signatures of infection of SARS-CoV-2 compared to other respiratory viruses (EBOV, H1N1, MERS-CoV, and SARS-CoV), to determine a unique anti-SARS-CoV-2 gene signature. We identified for the first time that molecular pathways for heparin-binding, RAGE, miRNA, and PLA2 inhibitors were associated with SARS-CoV-2 infection. The NRCAM and SAA2 genes, which are involved in severe inflammatory responses, and the FGF1 and FOXO1 genes, which are associated with immune regulation, were found to be associated with the cellular gene response to SARS-CoV-2 infection. Moreover, several cytokines, most significantly IL-8 and IL-6 , demonstrated key associations with SARS-CoV-2 infection. Interestingly, the only response gene that was shared among the five viral infections was SERPINB1 . The protein-protein interaction (PPI) analysis shed light on genes with high interaction activity that SARS-CoV-2 shares with other viral infections. The findings showed that the genetic pathways associated with rheumatoid arthritis, the AGE-RAGE signaling system, malaria, hepatitis B, and influenza A were of high significance. We found that the virogenomic transcriptome of infection, gene modulation of host antiviral responses, and GO terms of SARS-CoV-2 and EBOV were more similar than to SARS, H1N1, and MERS. This work compares the virogenomic signatures of highly pathogenic viruses and provides valid targets for potential therapy against SARS-CoV-2.

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  1. Version published to 10.1371/journal.pone.0243270
  2. ScreenIT

    SciScore for 10.1101/2020.05.06.080960: (What is this?)

    Please note, not all rigor criteria are appropriate for all manuscripts.

    Table 1: Rigor

    Institutional Review Board Statementnot detected.
    Randomizationnot detected.
    Blindingnot detected.
    Power Analysisnot detected.
    Sex as a biological variablenot detected.

    Table 2: Resources

    Software and Algorithms
    SentencesResources
    Data Analysis: The identification of the differentially expressed genes (DEGs) in the transcription profile was analyzed using GEO2R tool (Barrett et al. 2012) and differential expression analysis using DESeq2 and DEApp (Li and Andrade 2017) using default parameters.
    GEO2R
    suggested: (GEO2R, RRID:SCR_016569)
    DESeq2
    suggested: (DESeq, RRID:SCR_000154)
    The evaluation of the protein interactions and gene ontology (GO) enrichment was conducted with the STRING database (Szklarczyk et al. 2016).
    STRING
    suggested: (STRING, RRID:SCR_005223)
    Cytoscape software has been used to visualize the structures of protein-protein networks (Shannon et al. 2003).
    Cytoscape
    suggested: (Cytoscape, RRID:SCR_003032)
    The Circos software (Krzywinski et al. 2009) was used to represent gene expression and gene ontology analysis of the host response to viral infections based on human genome data (GRCh38)..
    Circos
    suggested: (Circos, RRID:SCR_011798)

    Results from OddPub: Thank you for sharing your data.

    Results from LimitationRecognizer: An explicit section about the limitations of the techniques employed in this study was not found. We encourage authors to address study limitations.

    Results from TrialIdentifier: No clinical trial numbers were referenced.

    Results from Barzooka: We did not find any issues relating to the usage of bar graphs.

    Results from JetFighter: Please consider improving the rainbow (“jet”) colormap(s) used on page 6. At least one figure is not accessible to readers with colorblindness and/or is not true to the data, i.e. not perceptually uniform.

    Results from rtransparent:
    • Thank you for including a conflict of interest statement. Authors are encouraged to include this statement when submitting to a journal.
    • No funding statement was detected.
    • No protocol registration statement was detected.

    About SciScore

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  3. Version published to 10.1101/2020.05.06.080960v1 on bioRxiv