Transcriptome Profiling of different types of human respiratory tract cells infected by SARS-CoV-2 Highlight an unique Role for Inflammatory and Interferon Response

  1. Minghui Yang
  2. Luping Lei
  3. Qiumei Cao
  4. Yang Yang
  5. Jun Wang
  6. Xiao Jiang
  7. Kun Huang
  8. Jinzhi Lai
  9. Ling Qing
  10. Yu Wang
  11. Yingxia Liu

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Abstract

The emergence of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) disease (COVID-19) at the end of 2019 has caused a large global outbreak and now become a major public health issue. Lack of data underlying how the human host interacts with SARS-CoV-2 virus. In the current study, We performed Venn-analysis, Gene ontology (GO), KEGG pathway analysis and Protein-protein interaction analysis of whole transcriptome studies with the aim of clarifying the genes and pathways potentially altered during human respiratory tract cells infected with SARS-CoV-2. We selected four studies through a systematic search of the Gene Expression Omnibus (GEO) database or published article about SARS-CoV-2 infection in different types of respiratory tract cells. We found 36 overlapping upregulated genes among different types of cells after viral infection. Further functional enrichment analysis revealed these DEGs are most likely involved in biological processes related to inflammatory response and response to cytokine, cell component related to extracellular space and I-kappaB/NF-kappaB complex, molecular function related to protein binding and cytokine activity. KEGG pathways analysis highlighted altered conical and casual pathways related to TNF, NF-kappa B, Cytokine-cytokine receptor interaction and IL17 signaling pathways during SARS-CoV-2 infection with CXCL1, CXCL2, CXCL3, CXCL8, CXCL10, IL32, CX3CL1, CCL20, IRF1, NFKB2 and NFKB1A up-regulated which may explain the inflammatory cytokine storms associated with severe cases of COVID-19.

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    SciScore for 10.1101/2020.11.15.383927: (What is this?)

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

    Table 1: Rigor

    NIH rigor criteria are not applicable to paper type.

    Table 2: Resources

    Software and Algorithms
    SentencesResources
    Study Search and RNA-Seq data collection: We searched for RNA-Seq experiments deposited in the Gene Expression Omnibus (GEO) database and NCBI Pubmed related to SARS-CoV-2 infection in different types of human respiratory tract cells (Calu-3, doi:10.3390/biology9090260; ACE2-A549,GSE154613; a lung organoid model driving by human pluripotent stem cells, GSE155241; Primary human bronchial epithelial cells, GSE150819) which carried out in human cells (ex vivo) or human cell lines (in vitro).
    Gene Expression Omnibus
    suggested: (Gene Expression Omnibus (GEO, RRID:SCR_005012)
    Pubmed
    suggested: (PubMed, RRID:SCR_004846)
    Functional analysis of differential expressed genes: The Go terms enrichment, KEGG pathways and protein-protein interaction analysis of the DEGs were performed using OmicsBean (http://www.omicsbean.cn) and Cytoscape v.
    KEGG
    suggested: (KEGG, RRID:SCR_012773)
    OmicsBean
    suggested: (OmicsBean, RRID:SCR_016322)
    Cytoscape
    suggested: (Cytoscape, RRID:SCR_003032)

    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: 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.

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  2. Version published to 10.1101/2020.11.15.383927 on bioRxiv