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SUMMARYSARS-CoV-2, depends on host cell components for replication, therefore the identification of virus-host dependencies offers an effective way to elucidate mechanisms involved in viral infection. Such host factors may be necessary for infection and replication of SARS-CoV-2 and, if druggable, presents an attractive strategy for anti-viral therapy. We performed genome wide CRISPR knockout screens in Vero E6 cells and 4 human cell lines including Calu-3, Caco-2, Hek293 and Huh7 to identify genetic regulators of SARS-CoV-2 infection. Our findings identified only ACE2, the cognate SARS-CoV-2 entry receptor, as a common host dependency factor across all cell lines, while all other host genes identified were cell line specific including known factors TMPRSS2 and CTSL. Several of the discovered host-dependency factors converged on pathways involved in cell signalling, lipid metabolism, immune pathways and chromatin modulation. Notably, chromatin modulator genes KMT2C and KDM6A in Calu-3 cells had the strongest impact in preventing SARS-CoV-2 infection when perturbed. Overall, the network of host factors that have been identified will be broadly applicable to understanding the impact of SARS-CoV-2 on human cells and facilitate the development of host-directed therapies.IN BRIEFSARS-CoV-2, depends on host cell components for infection and replication. Genome-wide CRISPR screens were performed in multiple human cell lines to elucidate common host dependencies required for SARS-CoV-2 infection. Only ACE2, the cognate SARS-CoV-2 entry receptor, was common amongst cell lines, while all other host genes identified were cell line specific, several of which converged on pathways involved in cell signalling, lipid metabolism, immune pathways, and chromatin modulation. Overall, a network of host factors was identified that will be broadly applicable to understanding the impact of SARS-CoV-2 on human cells and facilitate productive targeting of host genes and pathways.HIGHLIGHTS- Genome-wide CRISPR screens for SARS-CoV-2 in multiple human cell lines- Identification of wide-ranging cell-type dependent genetic dependencies for SARS-CoV-2 infection- ACE2 is the only common host factor identified across different cell types

The de novo synthesis of fatty acids has emerged as a therapeutic target for various diseases including cancer. While several translational efforts have focused on direct perturbation of de novo fatty acid synthesis, only modest responses have been associated with mono-therapies. Since cancer cells are intrinsically buffered to combat metabolic stress, cells may adapt to loss of de novo fatty acid biosynthesis. To explore cellular response to defects in fatty acid synthesis, we used pooled genome-wide CRISPR screens to systematically map genetic interactions (GIs) in human HAP1 cells carrying a loss-of-function mutation in FASN, which catalyzes the formation of long-chain fatty acids. FASN mutant cells showed a strong dependence on lipid uptake that was reflected by negative GIs with genes involved in the LDL receptor pathway, vesicle trafficking, and protein glycosylation. Further support for these functional relationships was derived from additional GI screens in query cell lines deficient for other genes involved in lipid metabolism, including LDLR, SREBF1, SREBF2, ACACA. Our GI profiles identified a potential role for a previously uncharacterized gene LUR1 (C12orf49) in exogenous lipid uptake regulation. Overall, our data highlights the genetic determinants underlying the cellular adaptation associated with loss of de novo fatty acid synthesis and demonstrate the power of systematic GI mapping for uncovering metabolic buffering mechanisms in human cells.

A central focus of systems biology is the functional mapping of protein-protein interactions under physiological conditions. Here we describe MaGiCaL-BiFC, a lentivirus-based bimolecular fluorescence protein-fragment complementation approach for the high-throughput, genome-scale identification of protein-protein interactions in mammalian cells. After developing and validating this methodology using known protein-protein interaction pairs, we constructed genome-scale pooled BiFC libraries using the human ORFeome cDNA collection. These pooled libraries, containing ∼ 12,000 unique human cDNAs, were used to screen for candidate interaction partners of the mitochondrial transmembrane protein TOMM22. Following infection of cells with the TOMM22 bait and the pooled cDNA libraries, cells harboring candidate TOMM22 interacting proteins were isolated from the cell pool via fluorescence activated cell sorting, and identified via microarray analysis. This approach identified several known interaction partners of TOMM22, as well as novel physical and functional partners that link the mitochondrial network to proteins involved in diverse cellular processes. Notably, protein kinase CK2 was identified as a novel physical interaction partner of human TOMM22. We found that this association occurs preferentially during mitosis and involves direct phosphorylation of TOMM22, an event that may lead to attenuation of mitochondrial protein import. Together, this data contributes to the growing body of evidence suggesting eloquent coordination between cell cycle progression and mitochondrial physiology. Importantly, through high-throughput screening and focused validation, our study demonstrates the power of the MaGiCaL-BiFC approach to uncover novel functional protein-protein interactions, including those involving proteins with membrane-spanning domains, or of a transient nature, all within their native cellular environment.

The adaptation of CRISPR/Cas9 technology to mammalian cell lines is transforming the study of human functional genomics. Pooled libraries of CRISPR guide RNAs (gRNAs), targeting human protein-coding genes and encoded in viral vectors, have been used to systematically create gene knockouts in a variety of human cancer and immortalized cell lines, in an effort to identify whether these knockouts cause cellular fitness defects. Previous work has shown that CRISPR screens are more sensitive and specific than pooled library shRNA screens in similar assays, but currently there exists significant variability across CRISPR library designs and experimental protocols. In this study, we re-analyze 17 genome-scale knockout screens in human cell lines from three research groups using three different genome-scale gRNA libraries, using the Bayesian Analysis of Gene Essentiality (BAGEL) algorithm to identify essential genes, to refine and expand our previously defined set of human core essential genes, from 360 to 684 genes. We use this expanded set of reference Core Essential Genes (CEG2), plus empirical data from six CRISPR knockout screens, to guide the design of a sequence-optimized gRNA library, the Toronto KnockOut version 3.0 (TKOv3) library. We demonstrate the high effectiveness of the library relative to reference sets of essential and nonessential genes as well as other screens using similar approaches. The optimized TKOv3 library, combined with the CEG2 reference set, provide an efficient, highly optimized platform for performing and assessing gene knockout screens in human cell lines.