Human Embryonic Stem Cell-derived Lung Organoids: a Model for SARS-CoV-2 Infection and Drug Test

  1. Rongjuan Pei
  2. Jianqi Feng
  3. Yecheng Zhang
  4. Hao Sun
  5. Lian Li
  6. Xuejie Yang
  7. Jiangping He
  8. Shuqi Xiao
  9. Jin Xiong
  10. Ying Lin
  11. Kun Wen
  12. Hongwei Zhou
  13. Jiekai Chen
  14. Zhili Rong
  15. Xinwen Chen

Reviewed by

Read the full article See related articles

Listed in

Log in to save this article

Abstract

The coronavirus disease 2019 (COVID-19) pandemic is caused by infection with the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), which is spread primary via respiratory droplets and infects the lungs. Currently widely used cell lines and animals are unable to accurately mimic human physiological conditions because of the abnormal status of cell lines (transformed or cancer cells) and species differences between animals and humans. Organoids are stem cell-derived self-organized three-dimensional culture in vitro and model the physiological conditions of natural organs. Here we demonstrated that SARS-CoV-2 infected and extensively replicated in human embryonic stem cells (hESCs)-derived lung organoids, including airway and alveolar organoids. Ciliated cells, alveolar type 2 (AT2) cells and rare club cells were virus target cells. Electron microscopy captured typical replication, assembly and release ultrastructures and revealed the presence of viruses within lamellar bodies in AT2 cells. Virus infection induced more severe cell death in alveolar organoids than in airway organoids. Additionally, RNA-seq revealed early cell response to SARS-CoV-2 infection and an unexpected downregulation of ACE2 mRNA. Further, compared to the transmembrane protease, serine 2 (TMPRSS2) inhibitor camostat, the nucleotide analog prodrug Remdesivir potently inhibited SARS-CoV-2 replication in lung organoids. Therefore, human lung organoids can serve as a pathophysiological model for SARS-CoV-2 infection and drug discovery.

Article activity feed

  1. ScreenIT

    SciScore for 10.1101/2020.08.10.244350: (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
    The SARS-CoV-2 isolate was obtained and titrated by plaque assay on Vero E6 cells.
    Vero E6
    suggested: RRID:CVCL_XD71)
    Software and Algorithms
    SentencesResources
    Differentially expressed genes were obtained using DESeq2 (version 1.10.1)8, a cutoff of Q-value < 0.05 and log2 (fold-change) > 1 was used for identify differentially expressed genes.
    DESeq2
    suggested: (DESeq, RRID:SCR_000154)
    NIS-Elements software was used to render Z-stack three-dimensional images.
    NIS-Elements
    suggested: (NIS-Elements, RRID:SCR_014329)
    All of the statistical analyses in this study were done with GraphPad Prism 8 software.
    GraphPad Prism
    suggested: (GraphPad Prism, RRID:SCR_002798)

    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.

    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. ScreenIT

    SciScore for 10.1101/2020.08.10.244350: (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

    No key resources detected.

    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 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.

    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 10.1101/2020.08.10.244350v1 on bioRxiv