Integrative Bioinformatics Analysis Provides Insight into the Molecular Mechanisms of 2019-nCoV

  1. Xiang He
  2. Lei Zhang
  3. Qin Ran
  4. Junyi Wang
  5. Anying Xiong
  6. Dehong Wu
  7. Feng Chen
  8. Guoping Li

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Abstract

The 2019-nCoV is reported to share the same entry (ACE2) as SARS-CoV according to the updated findings. Analyzing the distribution and expression level of the route of coronavirus may help reveal underlying mechanisms of viral susceptibility and post-infection modulation. In this study, we found that the expression of ACE2 in healthy populations and patients with underlying diseases was not significantly different, suggesting relatively similar susceptibility. Besides, based on the expression of ACE2 in smoking individuals, we inferred that long-term smoking might be a risk factor for 2019-nCoV. Analyzing the ACE2 in SARS-CoV infected cells suggested that ACE2 was more than just a receptor but also participated in post-infection regulation, including immune response, cytokine secretion, and viral genome replication. Moreover, we also constructed Protein-protein interaction (PPI) networks and identified hub genes in viral activity and cytokine secretion. Our findings may explain the clinical symptoms so far and help clinicians and researchers understand the pathogenesis and design therapeutic strategies for 2019-nCoV.

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  1. ScreenIT

    SciScore for 10.1101/2020.02.03.20020206: (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 Collection: Six independent studies (GSE37758, GSE73395, GSE89809, GSE63127, GSE97010, and GSE14700), covering healthy volunteers, COPD patients, asthma patients, smoking individuals were collected from GEO data repository (https://www.ncbi.nlm.nih.gov/geo/).
    https://www.ncbi.nlm.nih.gov/geo/
    suggested: (Gene Expression Omnibus (GEO, RRID:SCR_005012)
    GSEA was performed to analyze the possible biological processes related to ACE2 in healthy people using clusterProfiler (12).
    clusterProfiler
    suggested: (clusterProfiler, RRID:SCR_016884)
    PPI: All viral-related biological process and cytokine secretion-biological process proteins were extracted from the gmt file, Cytoscape v3.7.2 was used to construct the PPI network using BisoGenet application, the PPI sources include DIP, BIOGRID, HPRD, INTACT, MINT and BIND.
    Cytoscape
    suggested: (Cytoscape, RRID:SCR_003032)
    BisoGenet
    suggested: (BisoGenet, RRID:SCR_018502)
    BIOGRID
    suggested: (BioGrid Australia, RRID:SCR_006334)
    HPRD
    suggested: None
    MINT
    suggested: (MINT, RRID:SCR_001523)
    Hub proteins were identified using Cytoscape plugin CytoHubba.
    CytoHubba
    suggested: (cytoHubba, RRID:SCR_017677)

    Results from OddPub: We did not detect open data. We also did not detect open code. Researchers are encouraged to share open data when possible (see Nature blog).

    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: We did not find any issues relating to colormaps.

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

    About SciScore

    SciScore is an automated tool that is designed to assist expert reviewers by finding and presenting formulaic information scattered throughout a paper in a standard, easy to digest format. SciScore checks for the presence and correctness of RRIDs (research resource identifiers), and for rigor criteria such as sex and investigator blinding. For details on the theoretical underpinning of rigor criteria and the tools shown here, including references cited, please follow this link.

  2. Version published to 10.1101/2020.02.03.20020206v1 on medRxiv