Systemic analysis of tissue cells potentially vulnerable to SARS-CoV-2 infection by the protein-proofed single-cell RNA profiling of ACE2, TMPRSS2 and Furin proteases

  1. Lulin Zhou
  2. Zubiao Niu
  3. Xiaoyi Jiang
  4. Zhengrong Zhang
  5. You Zheng
  6. Zhongyi Wang
  7. Yichao Zhu
  8. Lihua Gao
  9. Hongyan Huang
  10. Xiaoning Wang
  11. Qiang Sun

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Abstract

Single-cell RNA profiling of ACE2, the SARS-CoV-2 receptor, had proposed multiple tissue cells as the potential targets of SARS-CoV-2, the novel coronavirus causing the COVID-19 pandemic. However, most were not echoed by the patients’ clinical manifestations, largely due to the lack of protein expression information of ACE2 and co-factors. Here, we incorporated the protein information to analyse the expression of ACE2, together with TMPRSS2 and Furin, two proteases assisting SARS-CoV-2 infection, at single cell level in situ , which we called protein-proofed single-cell RNA (pscRNA) profiling. Systemic analysis across 36 tissues revealed a rank list of candidate cells potentially vulnerable to SARS-CoV-2. The top targets are lung AT2 cells and macrophages, then cardiomyocytes and adrenal gland stromal cells, followed by stromal cells in testis, ovary and thyroid. Whereas, the polarized kidney proximal tubule cells, liver cholangiocytes and intestinal enterocytes are less likely to be the primary SARS-CoV-2 targets as ACE2 localizes at the apical region of cells, where the viruses may not readily reach. Actually, the stomach may constitute a physical barrier against SARS-CoV-2 as the acidic environment in normal stomach (pH < 2.0) could completely inactivate SARS-CoV-2 pseudo-viruses. These findings are in concert with the clinical characteristics of prominent lung symptoms, frequent heart injury, and uncommon intestinal symptoms and acute kidney injury. Together, we provide a comprehensive view on the potential SARS-CoV-2 targets by pscRNA profiling, and propose that, in addition to acute respiratory distress syndrome, attentions should also be paid to the potential injuries in cardiovascular, endocrine and reproductive systems during the treatment of COVID-19 patients.

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  1. Version published to 10.1101/2020.04.06.028522v3 on bioRxiv
  2. ScreenIT

    SciScore for 10.1101/2020.04.06.028522: (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.
    Cell Line Authenticationnot detected.

    Table 2: Resources

    Experimental Models: Cell Lines
    SentencesResources
    Cell culture, constructs and pseudovirus production: The HEK293T, 293T-ACE2 and Hela-ACE2 cells were maintained in DMEM (MACGENE Tech Ltd., Beijing, China) supplemented with 10% fetal bovine serum (Kang Yuan Biol, Tianjin, China) and 1% Penicillin-Streptomycin (MACGENE Tech Ltd., Beijing, China).
    HEK293T
    suggested: None
    293T-ACE2 cells and Hela-ACE2 cells were cultured in DMEM medium supplemented with 10% FBS and 1% PenStrep.
    293T-ACE2
    suggested: RRID:CVCL_YZ65)
    Hela-ACE2
    suggested: None
    Software and Algorithms
    SentencesResources
    Data Acquisition: For scRNA profiling, the raw gene expression matrices for single cells were downloaded from Gene Expression Omnibus (GEO) database(https://www.ncbi.nlm.nih.gov/geo/) and Human Cell Atlas Data Portal (https://data.humancellatlas.org/).
    Gene Expression Omnibus
    suggested: (Gene Expression Omnibus (GEO, RRID:SCR_005012)
    For tissue distribution of mRNA and protein expression profiles, data were obtained for target genes from the “TISSUE” categories of “THE HUMAN PROTEIN ATLAS” (http://www.proteinatlas.org/) (Uhlen et al., 2015).
    http://www.proteinatlas.org/
    suggested: (HPA, RRID:SCR_006710)
    Quality Control and Data Normalization: The raw count matrices of single-cell transcriptome were imported into R (version 3.6.1, https://www.r-project.org/) and processed by the Seurat R package(version3.1.4) (Stuart et al., 2019).
    https://www.r-project.org/
    suggested: (R Project for Statistical Computing, RRID:SCR_001905)
    Seurat
    suggested: (SEURAT, RRID:SCR_007322)

    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

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  3. Version published to 10.1101/2020.04.06.028522v2 on bioRxiv
  4. Version published to 10.1101/2020.04.06.028522v1 on bioRxiv