Identification of ACE2 modifiers by CRISPR screening

  1. Emily J. Sherman
  2. Carmen Mirabelli
  3. Vi T. Tang
  4. Taslima G. Khan
  5. Andrew A. Kennedy
  6. Sarah E. Graham
  7. Cristen J. Willer
  8. Andrew W. Tai
  9. Jonathan Z. Sexton
  10. Christiane E. Wobus
  11. Brian T. Emmer

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Abstract

SARS-CoV-2 infection is initiated by binding of the viral spike protein to its receptor, ACE2, on the surface of host cells. ACE2 expression is heterogeneous both in vivo and in immortalized cell lines, but the molecular pathways that govern ACE2 expression remain unclear. We now report high-throughput CRISPR screens for functional modifiers of ACE2 surface abundance. We identified 35 genes whose disruption was associated with a change in the surface abundance of ACE2 in HuH7 cells. Enriched among these ACE2 regulators were established transcription factors, epigenetic regulators, and functional networks. We further characterized individual cell lines with disruption of SMAD4, EP300, PIAS1 , or BAMBI and found these genes to regulate ACE2 at the mRNA level and to influence cellular susceptibility to SARS-CoV-2 infection. Collectively, our findings clarify the host factors involved in SARS-CoV-2 entry and suggest potential targets for therapeutic development.

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  1. ScreenIT

    SciScore for 10.1101/2021.06.10.447768: (What is this?)

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

    Table 1: Rigor

    EthicsIACUC: 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).
    Sex as a biological variablenot detected.
    Randomizationnot detected.
    Blindingnot detected.
    Power Analysisnot detected.
    Cell Line Authenticationnot detected.

    Table 2: Resources

    Antibodies
    SentencesResources
    At 14 days post-transduction, a total of ∼200 million cells were harvested and stained for surface ACE2 abundance as previously described with ACE2 antibody (R&D Systems #MAB9332) at 1:50 dilution in FACS buffer (PBS supplemented with 2% FBS) and Alexa Fluor 647-conjugated goat anti-rabbit IgG secondary antibody (AlexaFluor647 goat anti-rabbit IgG (Fisher #A32733) at 1:500 dilution in FACS buffer.
    ACE2
    suggested: (LSBio (LifeSpan Cat# LS-C347-500, RRID:AB_1271966)
    anti-rabbit IgG
    suggested: (Thermo Fisher Scientific Cat# A32733, RRID:AB_2633282)
    The plates were then sealed, surface decontaminated, and transferred to BSL2 for staining with antibody against SARS-CoV-2 nucleocapsid protein (Antibodies Online, Cat# ABIN6952432) overnight at 4 ?
    SARS-CoV-2 nucleocapsid protein
    suggested: None
    C followed by staining with Alexa Fluor 647-conjugated secondary antibody (goat anti-mouse, Thermo Fisher, A21235) and DAPI (Thermo FIsher).
    anti-mouse
    suggested: (Molecular Probes Cat# A-21235, RRID:AB_2535804)
    Experimental Models: Cell Lines
    SentencesResources
    Design and synthesis of secondary CRISPR library: Candidate genes were selected from (i) top candidate genes identified in our primary genome-wide CRISPR screen for ACE2 surface abundance; (ii) genes identified in CRISPR screens as candidate modifiers of SARS-CoV-2 cytopathic effect (Daniloski et al., 2021; Gordon et al., 2020; Heaton et al., 2020; Hoffmann et al., 2021; Wang et al., 2021; Wei et al., 2021); (iii) genes whose expression was correlated with ACE2 surface abundance in HuH7 cells (Sherman and Emmer, 2021); (iv) genes in proximity to loci associated with COVID-19 susceptibility by GWAS (described below); (v) candidate genes identified in our own pilot CRISPR screens of ACE2 surface abundance in ACE2-overexpressing HEK293T cells or Caco2 cells or SARS-CoV-2 cytopathic effect in Caco2 cells; and (vi) hypothesis-driven manually selected genes.
    HEK293T
    suggested: CCLV Cat# CCLV-RIE 1018, RRID:CVCL_0063)
    Caco2
    suggested: CLS Cat# 300137/p1665_CaCo-2, RRID:CVCL_0025)
    Viral titers were determined by TCID50 assays in Vero E6 cells (Reed and Muench method) by microscopic scoring.
    Vero E6
    suggested: RRID:CVCL_XD71)
    For the infectivity assay, HuH7 were seeded at 3 × 105 cells per well in a 12-well plate and allowed to adhere overnight.
    HuH7
    suggested: None
    Recombinant DNA
    SentencesResources
    Lentiviral stocks were generated by cotransfection of the lentiviral plasmid pool with psPAX2 and pVSVG into HEK293T cells, harvesting of supernatants, and titering of virus stocks as previously described (Emmer et al., 2018).
    psPAX2
    suggested: RRID:Addgene_12260)
    Each individual gRNA was ligated into BsmBI-digested pLentiCRISPRv2(Sanjana et al., 2014) and lentiviral stocks generated and titered as previously described(Emmer et al., 2018).
    pLentiCRISPRv2
    suggested: RRID:Addgene_127644)
    Software and Algorithms
    SentencesResources
    Gene network analysis of secondary screen hits was performed using the STRING database (Szklarczyk et al., 2019) with default settings and visualized with Cytoscape (Shannon et al., 2003).
    STRING
    suggested: (STRING, RRID:SCR_005223)
    Cytoscape
    suggested: (Cytoscape, RRID:SCR_003032)
    Heatmaps were generated with log-transformed p-values from our study and from Schneider et al.(Schneider et al., 2021) using GraphPad Prism v9.1.0.
    GraphPad Prism
    suggested: (GraphPad Prism, RRID:SCR_002798)
    Plates were imaged with Thermo Fisher CX5 high content microscopes with a 10X/0.45NA LUCPlan FLN objective and analyzed with a Cell Profiler pipeline.
    Profiler
    suggested: (PROFILER, RRID:SCR_009339)

    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: We detected the following sentences addressing limitations in the study:
    An important caveat of our study is the focused nature of our library, limited to high-resolution functional testing of 833 candidate genes. Our initial attempts at genome-wide screening did nominate candidate ACE2 regulators that were included in our focused library, but these pilot studies were limited by an experimental bottleneck at the cell sorting stage with inadequate depth of coverage to support definitive conclusions about each gene tested. Nevertheless, for those genes interrogated by the focused library, several observations support a high degree of confidence in the functional significance of each gene to ACE2 surface abundance. First, the internal control ACE2-targeting gRNAs were clearly depleted in ACE2-positive cells. Second, the genes that were identified as regulating ACE2 abundance exhibited a robust statistical enrichment or depletion. Third, we observed a very high degree of concordance in the degree of enrichment or depletion observed for each gene between the independent screens of wild-type or ACE2-enriched HuH7 cells. Fourth, identified genes were highly enriched for related functional annotations and protein-protein interactions and exhibited significant overlap with previously identified modulators of HuH7.5 cellular susceptibility to ACE2-dependent coronaviruses. Finally, of the screen hits we selected for single gene validation testing, the vast majority (18 of 21) were confirmed to regulate ACE2 surface abundance. Given the sensitivity of our scr...

    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: Please consider improving the rainbow (“jet”) colormap(s) used on pages 40, 25, 38 and 39. At least one figure is not accessible to readers with colorblindness and/or is not true to the data, i.e. not perceptually uniform.

    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.

    Results from scite Reference Check: We found no unreliable references.

    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 10.1101/2021.06.10.447768v1 on bioRxiv