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      Integrated multi-omics analyses identify key anti-viral host factors and pathways controlling SARS-CoV-2 infection

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          Abstract

          Host anti-viral factors are essential for controlling SARS-CoV-2 infection but remain largely unknown due to the biases of previous large-scale studies toward pro-viral host factors. To fill in this knowledge gap, we performed a genome-wide CRISPR dropout screen and integrated analyses of the multi-omics data of the CRISPR screen, genome-wide association studies, single-cell RNA-seq, and host-virus proteins or protein/RNA interactome. This study has uncovered many host factors that were missed by previous studies, including the components of V-ATPases, ESCRT, and N-glycosylation pathways that modulated viral entry and/or replication. The cohesin complex was also identified as a novel anti-viral pathway, suggesting an important role of three-dimensional chromatin organization in mediating host-viral interaction. Furthermore, we discovered an anti-viral regulator KLF5, a transcriptional factor involved in sphingolipid metabolism, which was up-regulated and harbored genetic variations linked to the COVID-19 patients with severe symptoms. Our results provide a resource for understanding the host anti-viral network during SARS-CoV-2 infection and may help develop new countermeasure strategies.

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          Most cited references54

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          Genomic characterisation and epidemiology of 2019 novel coronavirus: implications for virus origins and receptor binding

          Summary Background In late December, 2019, patients presenting with viral pneumonia due to an unidentified microbial agent were reported in Wuhan, China. A novel coronavirus was subsequently identified as the causative pathogen, provisionally named 2019 novel coronavirus (2019-nCoV). As of Jan 26, 2020, more than 2000 cases of 2019-nCoV infection have been confirmed, most of which involved people living in or visiting Wuhan, and human-to-human transmission has been confirmed. Methods We did next-generation sequencing of samples from bronchoalveolar lavage fluid and cultured isolates from nine inpatients, eight of whom had visited the Huanan seafood market in Wuhan. Complete and partial 2019-nCoV genome sequences were obtained from these individuals. Viral contigs were connected using Sanger sequencing to obtain the full-length genomes, with the terminal regions determined by rapid amplification of cDNA ends. Phylogenetic analysis of these 2019-nCoV genomes and those of other coronaviruses was used to determine the evolutionary history of the virus and help infer its likely origin. Homology modelling was done to explore the likely receptor-binding properties of the virus. Findings The ten genome sequences of 2019-nCoV obtained from the nine patients were extremely similar, exhibiting more than 99·98% sequence identity. Notably, 2019-nCoV was closely related (with 88% identity) to two bat-derived severe acute respiratory syndrome (SARS)-like coronaviruses, bat-SL-CoVZC45 and bat-SL-CoVZXC21, collected in 2018 in Zhoushan, eastern China, but were more distant from SARS-CoV (about 79%) and MERS-CoV (about 50%). Phylogenetic analysis revealed that 2019-nCoV fell within the subgenus Sarbecovirus of the genus Betacoronavirus, with a relatively long branch length to its closest relatives bat-SL-CoVZC45 and bat-SL-CoVZXC21, and was genetically distinct from SARS-CoV. Notably, homology modelling revealed that 2019-nCoV had a similar receptor-binding domain structure to that of SARS-CoV, despite amino acid variation at some key residues. Interpretation 2019-nCoV is sufficiently divergent from SARS-CoV to be considered a new human-infecting betacoronavirus. Although our phylogenetic analysis suggests that bats might be the original host of this virus, an animal sold at the seafood market in Wuhan might represent an intermediate host facilitating the emergence of the virus in humans. Importantly, structural analysis suggests that 2019-nCoV might be able to bind to the angiotensin-converting enzyme 2 receptor in humans. The future evolution, adaptation, and spread of this virus warrant urgent investigation. Funding National Key Research and Development Program of China, National Major Project for Control and Prevention of Infectious Disease in China, Chinese Academy of Sciences, Shandong First Medical University.
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            A SARS-CoV-2 Protein Interaction Map Reveals Targets for Drug-Repurposing

            SUMMARY The novel coronavirus SARS-CoV-2, the causative agent of COVID-19 respiratory disease, has infected over 2.3 million people, killed over 160,000, and caused worldwide social and economic disruption 1,2 . There are currently no antiviral drugs with proven clinical efficacy, nor are there vaccines for its prevention, and these efforts are hampered by limited knowledge of the molecular details of SARS-CoV-2 infection. To address this, we cloned, tagged and expressed 26 of the 29 SARS-CoV-2 proteins in human cells and identified the human proteins physically associated with each using affinity-purification mass spectrometry (AP-MS), identifying 332 high-confidence SARS-CoV-2-human protein-protein interactions (PPIs). Among these, we identify 66 druggable human proteins or host factors targeted by 69 compounds (29 FDA-approved drugs, 12 drugs in clinical trials, and 28 preclinical compounds). Screening a subset of these in multiple viral assays identified two sets of pharmacological agents that displayed antiviral activity: inhibitors of mRNA translation and predicted regulators of the Sigma1 and Sigma2 receptors. Further studies of these host factor targeting agents, including their combination with drugs that directly target viral enzymes, could lead to a therapeutic regimen to treat COVID-19.
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              MAGeCK enables robust identification of essential genes from genome-scale CRISPR/Cas9 knockout screens

              We propose the Model-based Analysis of Genome-wide CRISPR/Cas9 Knockout (MAGeCK) method for prioritizing single-guide RNAs, genes and pathways in genome-scale CRISPR/Cas9 knockout screens. MAGeCK demonstrates better performance compared with existing methods, identifies both positively and negatively selected genes simultaneously, and reports robust results across different experimental conditions. Using public datasets, MAGeCK identified novel essential genes and pathways, including EGFR in vemurafenib-treated A375 cells harboring a BRAF mutation. MAGeCK also detected cell type-specific essential genes, including BCR and ABL1, in KBM7 cells bearing a BCR-ABL fusion, and IGF1R in HL-60 cells, which depends on the insulin signaling pathway for proliferation. Electronic supplementary material The online version of this article (doi:10.1186/s13059-014-0554-4) contains supplementary material, which is available to authorized users.
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                Author and article information

                Contributors
                Journal
                Res Sq
                ResearchSquare
                Research Square
                American Journal Experts
                15 August 2022
                : rs.3.rs-1910932
                Affiliations
                University of Houston
                The University of Texas MD Anderson Cancer Center
                University of Texas Medical Branch
                University of Houston
                The University of Texas MD Anderson Cancer Center
                The University of Texas MD Anderson Cancer Center
                The University of Texas MD Anderson Cancer Center
                UTMB
                The University of Texas MD Anderson Cancer Center
                University of Texas Medical Branch
                University of Houston
                Author notes

                Authors’ Contributions

                Conception and Design: P. Shi, X. Xie, Y. Chen and W. Peng

                Acquisition of data (provided required animals, cells, patient samples, clinical information, etc.): J. Hou, J Zou, X. Xie, R. Jaffery and W. Peng

                Analysis and interpretation of data (statistical analysis and bioinformatics analysis): Y. Wei, S. Liang, C. Zheng, K. Chen, Y. Chen and W. Peng

                Writing and/or revision of the manuscript: J. Hou, Y. Wei, X. Xie, P. Shi, Y. Chen and W. Peng

                Study supervision: P. Shi, Y. Chen, X. Xie and W. Peng.

                Author information
                http://orcid.org/0000-0003-4200-2859
                http://orcid.org/0000-0002-9575-1522
                http://orcid.org/0000-0003-4013-5279
                http://orcid.org/0000-0001-5553-1616
                http://orcid.org/0000-0002-7706-7540
                http://orcid.org/0000-0003-0918-016X
                http://orcid.org/0000-0002-7785-6240
                Article
                10.21203/rs.3.rs-1910932
                10.21203/rs.3.rs-1910932/v1
                9413708
                36032971
                2a998c7f-430f-497a-95d4-17ecb7ef271c

                This work is licensed under a Creative Commons Attribution 4.0 International License, which allows reusers to distribute, remix, adapt, and build upon the material in any medium or format, so long as attribution is given to the creator. The license allows for commercial use.

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                genome-wide crispr screen,sars-cov-2,host factors
                genome-wide crispr screen, sars-cov-2, host factors

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