Identification of Drugs Blocking SARS-CoV-2 Infection using Human Pluripotent Stem Cell-derived Colonic Organoids

  1. Xiaohua Duan
  2. Yuling Han
  3. Liuliu Yang
  4. Benjamin E. Nilsson-Payant
  5. Pengfei Wang
  6. Tuo Zhang
  7. Jenny Xiang
  8. Dong Xu
  9. Xing Wang
  10. Skyler Uhl
  11. Yaoxing Huang
  12. Huanhuan Joyce Chen
  13. Hui Wang
  14. Benjamin tenOever
  15. Robert E. Schwartz
  16. David. D. Ho
  17. Todd Evans
  18. Fong Cheng Pan
  19. Shuibing Chen

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Abstract

The current COVID-19 pandemic is caused by SARS-coronavirus 2 (SARS-CoV-2). There are currently no therapeutic options for mitigating this disease due to lack of a vaccine and limited knowledge of SARS-CoV-2 biology. As a result, there is an urgent need to create new disease models to study SARS-CoV-2 biology and to screen for therapeutics using human disease-relevant tissues. COVID-19 patients typically present with respiratory symptoms including cough, dyspnea, and respiratory distress, but nearly 25% of patients have gastrointestinal indications including anorexia, diarrhea, vomiting, and abdominal pain. Moreover, these symptoms are associated with worse COVID-19 outcomes 1 . Here, we report using human pluripotent stem cell-derived colonic organoids (hPSC-COs) to explore the permissiveness of colonic cell types to SARS-CoV-2 infection. Single cell RNA-seq and immunostaining showed that the putative viral entry receptor ACE2 is expressed in multiple hESC-derived colonic cell types, but highly enriched in enterocytes. Multiple cell types in the COs can be infected by a SARS-CoV-2 pseudo-entry virus, which was further validated in vivo using a humanized mouse model. We used hPSC-derived COs in a high throughput platform to screen 1280 FDA-approved drugs against viral infection. Mycophenolic acid and quinacrine dihydrochloride were found to block the infection of SARS-CoV-2 pseudo-entry virus in COs both in vitro and in vivo , and confirmed to block infection of SARS-CoV-2 virus. This study established both in vitro and in vivo organoid models to investigate infection of SARS-CoV-2 disease-relevant human colonic cell types and identified drugs that blocks SARS-CoV-2 infection, suitable for rapid clinical testing.

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  1. ScreenIT

    SciScore for 10.1101/2020.05.02.073320: (What is this?)

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

    Table 1: Rigor

    Institutional Review Board StatementIACUC: All animal work was conducted in agreement with NIH guidelines and approved by the WCM Institutional Animal Care and Use Committee (IACUC) and the Institutional Biosafety Committee (IBC).
    Randomizationnot detected.
    Blindingnot detected.
    Power Analysisnot detected.
    Sex as a biological variableIn vivo transplantation and drug evaluation: hPSC-COs were harvested by cell scraper, mixed with 20 μl Matrigel (Corning) and transplanted under the kidney capsule of 7-9 weeks old male NSG mice.
    Cell Line Authenticationnot detected.

    Table 2: Resources

    Antibodies
    SentencesResources
    Secondary antibodies included donkey anti-mouse, goat, rabbit or chicken antibodies conjugated with Alexa-Fluor-488, Alexa-Fluor-594 or Alexa-Fluor-647 fluorophores (1:500
    goat
    suggested: None
    rabbit
    suggested: (Alomone Labs Cat# ANR-041-AG, RRID:AB_2876808)
    chicken antibodies conjugated with Alexa-Fluor-488 , Alexa-Fluor-594 or Alexa-Fluor-647 fluorophores ( 1:500
    suggested: None
    Primary antibodies were detected using Fluorophore-conjugated secondary goat anti-mouse (IRDye 680RD, 926-68070) and goat anti-rabbit (IRDye 800CW, 926-32211) antibodies.
    anti-mouse
    suggested: (LI-COR Biosciences Cat# 926-68070, RRID:AB_10956588)
    Experimental Models: Cell Lines
    SentencesResources
    HEK293T cells were grown to 80% confluency before transfection with pCMV3-SARS-CoV2-spike (kindly provided by Dr. Peihui Wang, Shandong University, China) using FuGENE 6 (Promega).
    HEK293T
    suggested: None
    Approximately 2.5 × 105 Vero E6 cells were pre-treated with the indicated compounds for 1 h prior to infection with SARS-CoV-2 at an MOI of 0.01 in DMEM supplemented with 2% FBS, 4.5 g/L D-glucose, 4 mM L-glutamine, 10 mM
    Vero E6
    suggested: RRID:CVCL_XD71)
    After reviewing the clusters, we merged four clusters that were likely from stem cell population into a single cluster (LGR5+ or BMI1+ stem cells) and kept the other four clusters (KRT20+ epithelial cells, MUC2+ goblet cells, EPHB2+ TA cells, and CHGA+ NE cells) for further analysis.
    TA
    suggested: RRID:CVCL_4315)
    Software and Algorithms
    SentencesResources
    Cell Lines: HEK293T (human [Homo sapiens] fetal kidney) and Vero E6 (African green monkey [Chlorocebus aethiops] kidney) were obtained from ATCC (https://www.atcc.org/).
    https://www.atcc.org/
    suggested: (ATCC, RRID:SCR_001672)
    Images were acquired using an LSM880 Laser Scanning Confocal Microscope (Zeiss) and processed with Zen or Imaris (Bitplane) software.
    Zen
    suggested: None
    Imaris
    suggested: (Imaris, RRID:SCR_007370)
    Antibody-mediated fluorescence was detected on a LI-COR Odyssey CLx imaging system and analyzed using Image Studio software (
    Image Studio
    suggested: (Image Studio Lite, RRID:SCR_013715)
    We normalized the gene expression UMI counts for each sample separately using a deconvolution strategy24 implemented by the R scran package (v.1.14.1).
    scran
    suggested: (scran, RRID:SCR_016944)
    The list of dissociation-related genes was originally built on mouse data26, we converted them to human ortholog genes using Ensembl BioMart.
    Ensembl
    suggested: (Ensembl, RRID:SCR_002344)
    We re-identified marker genes for the merged five clusters and selected the top 10 positive marker genes per cluster for heatmap plot using the DoHeatmap function in the R Seurat package25.
    Seurat
    suggested: (SEURAT, RRID:SCR_007322)

    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. Version published to 10.1101/2020.05.02.073320v1 on bioRxiv