Morphological cell profiling of SARS-CoV-2 infection identifies drug repurposing candidates for COVID-19

  1. Carmen Mirabelli
  2. Jesse W. Wotring
  3. Charles J. Zhang
  4. Sean M. McCarty
  5. Reid Fursmidt
  6. Carla D. Pretto
  7. Yuanyuan Qiao
  8. Yuping Zhang
  9. Tristan Frum
  10. Namrata S. Kadambi
  11. Anya T. Amin
  12. Teresa R. O’Meara
  13. Jason R. Spence
  14. Jessie Huang
  15. Konstantinos D. Alysandratos
  16. Darrell N. Kotton
  17. Samuel K. Handelman
  18. Christiane E. Wobus
  19. Kevin J. Weatherwax
  20. George A. Mashour
  21. Matthew J. O’Meara
  22. Arul M. Chinnaiyan
  23. Jonathan Z. Sexton

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Abstract

Since its emergence in China in December 2019, SARS-CoV-2 has caused a global pandemic. Repurposing of FDA-approved drugs is a promising strategy for identifying rapidly deployable treatments for COVID-19. Herein, we developed a pipeline for quantitative, high-throughput, image-based screening of SARS-CoV-2 infection in human cells that led to the identification of several FDA-approved drugs and clinical candidates with in vitro antiviral activity.

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  1. Version published to 10.1073/pnas.2105815118
  2. Version published to 10.1101/2020.05.27.117184v4 on bioRxiv
  3. Version published to 10.1101/2020.05.27.117184v3 on bioRxiv
  4. Version published to 10.1101/2020.05.27.117184v2 on bioRxiv
  5. ScreenIT

    SciScore for 10.1101/2020.05.27.117184: (What is this?)

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

    Table 1: Rigor

    Institutional Review Board StatementIACUC: All experiments using SARS-CoV-2 were performed at the University of Michigan under Biosafety Level 3 (BSL3) protocols in compliance with containment procedures in laboratories approved for use by the University of Michigan Institutional Biosafety Committee (IBC) and Environment, Health and Safety (EHS)
    Randomizationnot detected.
    Blindingnot detected.
    Power Analysisnot detected.
    Sex as a biological variablenot detected.
    Cell Line Authenticationnot detected.

    Table 2: Resources

    Antibodies
    SentencesResources
    The plates were then sealed, surface decontaminated, and transferred to BSL2 for staining with the optimized fluorescent dye-set: anti-nucleocapsid protein (anti-NP) SARS-CoV-2 antibody (Antibodies Online, Cat# ABIN6952432) overnight treatment at 4 °C followed by staining with secondary antibody Alexa-647 (goat anti-mouse, Thermo Fisher, A21235)
    anti-nucleocapsid protein ( anti-NP ) SARS-CoV-2
    suggested: None
    anti-mouse
    suggested: (Molecular Probes Cat# A-21235, RRID:AB_2535804)
    Staining protocol for the iAEC2s differed slightly with the addition of an anti-acetylated tubulin primary antibody (Cell Signaling, 5335), instead of HCS CellMask Orange, and the use of an additional secondary Alexa 488 antibody (donkey anti-rabbit, Jackson ImmunoResearch, 711-545-152)
    anti-acetylated tubulin primary antibody ( Cell Signaling , 5335
    suggested: None
    anti-rabbit
    suggested: (Jackson ImmunoResearch Labs Cat# 711-545-152, RRID:AB_2313584)
    Cells were counterstained with Hoechst 33342 and anti-S protein antibody (Spike antibody 1A9, GeneTex, Cat Nr.
    anti-S protein
    suggested: None
    Experimental Models: Cell Lines
    SentencesResources
    Viral titer determination: Vero E6, Caco-2, LNCaP and Huh7 cells were seeded in a 48-well plate at 2×104 cells/well and incubated overnight at 37°C with 5% CO2.
    Caco-2
    suggested: None
    Huh7
    suggested: None
    Viral Binding assay: Huh-7 cells were plated in 48-well plates at 100,000 cells per well and allowed to adhere overnight.
    Huh-7
    suggested: None
    Multi-cycle cytopathogenic effect (CPE) reduction assay: Vero E6 were allowed to adhere overnight in 96-well cell culture plates.
    Vero E6
    suggested: None
    Software and Algorithms
    SentencesResources
    Statistical methods and hypothesis testing: Dose-response curves were fit and pairwise differences between experimental conditions were tested using Prism (Graphpad Software, San Diego, CA, USA).
    Prism
    suggested: (PRISM, RRID:SCR_005375)
    Graphpad
    suggested: (GraphPad, RRID:SCR_000306)
    Dose response curves were fit with Graphpad Prism using a semilog 4-parameter variable slope model.
    Graphpad Prism
    suggested: (GraphPad Prism, RRID:SCR_002798)

    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.

  6. Version published to 10.1101/2020.05.27.117184v1 on bioRxiv