Single-cell analysis reveals bronchoalveolar epithelial dysfunction in COVID-19 patients

  1. Jiangping He
  2. Shuijiang Cai
  3. Huijian Feng
  4. Baomei Cai
  5. Lihui Lin
  6. Yuanbang Mai
  7. Yinqiang Fan
  8. Airu Zhu
  9. Huang Huang
  10. Junjie Shi
  11. Dingxin Li
  12. Yuanjie Wei
  13. Yueping Li
  14. Yingying Zhao
  15. Yuejun Pan
  16. He Liu
  17. Xiaoneng Mo
  18. Xi He
  19. Shangtao Cao
  20. FengYu Hu
  21. Jincun Zhao
  22. Jie Wang
  23. Nanshan Zhong
  24. Xinwen Chen
  25. Xilong Deng
  26. Jiekai Chen

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Abstract

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  1. Version published to 10.1007/s13238-020-00752-4
  2. ScreenIT

    SciScore for 10.1101/2020.05.23.20100024: (What is this?)

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

    Table 1: Rigor

    Institutional Review Board StatementIRB: Study approval: This study was approved by the Ethics Committee of the First Affiliated Hospital of Guangzhou Medical University with written consent form acquired from the patient.
    Consent: Study approval: This study was approved by the Ethics Committee of the First Affiliated Hospital of Guangzhou Medical University with written consent form acquired from the patient.
    RandomizationWe randomly permuted the cluster labels of all cells 1,000 times and determined the mean of the average receptor expression level of a cluster and the average ligand expression level of the interacting cluster.
    Blindingnot detected.
    Power Analysisnot detected.
    Sex as a biological variablenot detected.

    Table 2: Resources

    Antibodies
    SentencesResources
    Cells were then labeled for cell surface markers, fixed/ permeabilized with Cytofix/Cytoperm Solution (BD Biosciences), and labeled with anti-intracellular cytokine/protein antibodies.
    anti-intracellular cytokine/protein
    suggested: None
    The following anti-human monoclonal antibodies were used: The following Cytometric Bead Array (CBA) products were used to detect cytokines: Single-Cell RNA library preparation and sequencing: Cell suspensions were loaded onto a chromium single-cell chip to generate single-cell gel bead-in-emulsions (GEMs) aiming for 2,000-8,000 single cells per reaction.
    anti-human monoclonal
    suggested: None
    Software and Algorithms
    SentencesResources
    Flow cytometry data were acquired on a BD FACSVerse or a BD Aria III flow cytometer and analyzed using FlowJo software (Tree Star Inc.).
    FlowJo
    suggested: (FlowJo, RRID:SCR_008520)
    Amplified cDNA was purified using SPRIselect beads (Beckman Coulter) and sheared to 250-400 bp. cDNA quality control was performed using Qubit 3.0 Fluorometer and Agilent Bioanalyzer 2100.
    Agilent Bioanalyzer
    suggested: None
    Ligand-receptor interaction analysis: The ligand-receptor interacting patterns annotation were downloaded from iMEX consortium (http://www.imexconsortium.org/)
    http://www.imexconsortium.org/
    suggested: (IMEx - The International Molecular Exchange Consortium, RRID:SCR_002805)
    ) (Orchard et al., 2012) and CellPhoneDB (https://www.cellphonedb) (Vento-Tormo et al., 2018), we excluded from our analysis with only secreted, cytokines, growth factors, hormones, extracellular matrix, membrane, receptors and transporters according to uniport classification.
    CellPhoneDB
    suggested: (CellPhoneDB, RRID:SCR_017054)

    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.

  3. Version published to 10.1101/2020.05.23.20100024v1 on medRxiv