Deciphering the role of the Pancreatic Secretome in Covid-19 associated Multi-Organ Dysfunctions

  1. Ekta Pathak
  2. Rajeev Mishra

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Abstract

Emerging evidence indicates an intricate relationship between the SARS-CoV-2 infection and Multi-Organ Dysfunctions (MODs). Here, we have investigated the role of the Secretome of the SARS-CoV-2 infected pancreas and mechanistically linked it with the multi-organ dysfunction using the scRNA-seq analysis. We found that acinar-specific PRSS2, REG3A, REG1A, SPINK1 , and ductal-specific SPP1, MMP7 genes are upregulated in alpha, beta, delta, and mesenchyme cells. Using extensive documented experimental evidence, we validated the association of upregulated pancreatic Secretome with coagulation cascade, complement activation, renin angiotensinogen system dysregulation, endothelial cell injury and thrombosis, immune system dysregulation, and fibrosis. Our finding suggests the influence of upregulated Secretome on multi-organ systems such as Nervous, Cardiovascular, Immune, Digestive, and Urogenital systems. In addition, we report that the secretory proteins IL1B, AGT, ALB, SPP1, CRP, SERPINA1, C3, TFRC, TNFSF10, and MIF are associated with diverse diseases. Thus, suggest the role of the pancreatic Secretome in SARS-CoV-2 associated MODs.

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  1. ScreenIT

    SciScore for 10.1101/2021.09.22.461447: (What is this?)

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

    Table 1: Rigor

    Ethicsnot detected.
    Sex as a biological variablenot detected.
    Randomizationnot detected.
    Blindingnot detected.
    Power Analysisnot detected.

    Table 2: Resources

    Software and Algorithms
    SentencesResources
    scRNA-seq data of ex vivo SARS-CoV-2 infected human pancreas were retrieved from Gene Expression Omnibus(GSE159556)(Tang et al., 2021).
    Gene Expression Omnibus(GSE159556)
    suggested: None
    Clustree package was used to choose the final resolution (Zappia and Oshlack, 2018).
    Clustree
    suggested: (clustree, RRID:SCR_016293)
    Enrichment analysis: We used g:Profiler for GO enrichment analysis, Biological pathway enrichment analysis using KEGG, Reactome, WikiPathways.
    KEGG
    suggested: (KEGG, RRID:SCR_012773)
    WikiPathways
    suggested: (WikiPathways, RRID:SCR_002134)
    The disease phenotypes enrichment analysis was performed using Human Phenotype Ontology)(Raudvere et al., 2019) ClueGO, a Cytoscape plug-in, was used to identify the functionally grouped GO and pathway(Bindea et al., 2009).
    ClueGO
    suggested: (ClueGO, RRID:SCR_005748)
    Cytoscape
    suggested: (Cytoscape, RRID:SCR_003032)
    Pheatmap package was used for generating heatmap(Kolde and Kolde, 2015).
    Pheatmap
    suggested: (pheatmap, RRID:SCR_016418)

    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.

    Results from scite Reference Check: We found no unreliable references.

    About SciScore

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  2. Version published to 10.1101/2021.09.22.461447v1 on bioRxiv