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Genome-wide CRISPR screens identify GATA6 as a proviral host factor for SARS-CoV-2 via modulation of ACE2.

Nature communications | 2022

The global spread of SARS-CoV-2 led to major economic and health challenges worldwide. Revealing host genes essential for infection by multiple variants of SARS-CoV-2 can provide insights into the virus pathogenesis, and facilitate the development of novel therapeutics. Here, employing a genome-scale CRISPR screen, we provide a comprehensive data-set of cellular factors that are exploited by wild type SARS-CoV-2 as well as two additional recently emerged variants of concerns (VOCs), Alpha and Beta. We identified several host factors critical for SARS-CoV-2 infection, including various components belonging to the Clathrin-dependent transport pathway, ubiquitination, Heparan sulfate biogenesis and host phosphatidylglycerol biosynthesis. Comparative analysis of the different VOCs revealed the host factors KREMEN2 and SETDB1 as potential unique candidates required only to the Alpha variant. Furthermore, the analysis identified GATA6, a zinc finger transcription factor, as an essential proviral gene for all variants inspected. We show that GATA6 directly regulates ACE2 transcription and accordingly, is critical for SARS-CoV-2 cell entry. Analysis of clinical samples collected from SARS-CoV-2 infected individuals shows elevated levels of GATA6, suggesting a role in COVID-19 pathogenesis. Finally, pharmacological inhibition of GATA6 resulted in down-modulation of ACE2 and inhibition of viral infectivity. Overall, we show GATA6 may represent a target for the development of anti-SARS-CoV-2 therapeutic strategies and reaffirm the value of the CRISPR loss-of-function screens in providing a list of potential new targets for therapeutic interventions.

Pubmed ID: 35469023 RIS Download

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This is a list of tools and resources that we have found mentioned in this publication.


Addgene (tool)

RRID:SCR_002037

Non-profit plasmid repository dedicated to helping scientists around the world share high-quality plasmids. Facilitates archiving and distributing DNA-based research reagents and associated data to scientists worldwide. Repository contains over 65,000 plasmids, including special collections on CRISPR, fluorescent proteins, and ready-to-use viral preparations. There is no cost for scientists to deposit plasmids, which saves time and money associated with shipping plasmids themselves. All plasmids are fully sequenced for validation and sequencing data is openly available. We handle the appropriate Material Transfer Agreements (MTA) with institutions, facilitating open exchange and offering intellectual property and liability protection for depositing scientists. Furthermore, we curate free educational resources for the scientific community including a blog, eBooks, video protocols, and detailed molecular biology resources.

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RRID:SCR_003199

Software package for interpreting gene expression data. Used for interpretation of a large-scale experiment by identifying pathways and processes.

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RRID:SCR_003485

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Database of known and predicted protein interactions. The interactions include direct (physical) and indirect (functional) associations and are derived from four sources: Genomic Context, High-throughput experiments, (Conserved) Coexpression, and previous knowledge. STRING quantitatively integrates interaction data from these sources for a large number of organisms, and transfers information between these organisms where applicable. The database currently covers 5''214''234 proteins from 1133 organisms. (2013)

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RRID:SCR_005375

THIS RESOURCE IS NO LONGER IN SERVICE. Documented on May 5,2022.Tool that predicts interactions between transcription factors and their regulated genes from binding motifs. Understanding vertebrate development requires unraveling the cis-regulatory architecture of gene regulation. PRISM provides accurate genome-wide computational predictions of transcription factor binding sites for the human and mouse genomes, and integrates the predictions with GREAT to provide functional biological context. Together, accurate computational binding site prediction and GREAT produce for each transcription factor: 1. putative binding sites, 2. putative target genes, 3. putative biological roles of the transcription factor, and 4. putative cis-regulatory elements through which the factor regulates each target in each functional role.

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RRID:CVCL_0574

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Software tool to identify important genes from genome-scale CRISPR-Cas9 screens. Used for prioritizing single-guide RNAs, genes and pathways in genome-scale CRISPR/Cas9 knockout screens.

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