CRISPR screens for SARS-CoV-2 Host Factors

项目摘要 与Wilen博士（耶鲁大学）和Goujon博士（法国CNRS）合作，我们将建立细胞系 模型，并进行全基因组CRISPR筛选，以确定SARS-CoV-2所必需的宿主基因 感染我们将首先使用来自非洲绿色猴的Vero细胞，因为它们是一种成熟的模型， 许多病原体，我们之前已经为这个物种建立了一个全基因组文库。初步数据 这表明我们也已经产生了可以作为有效模型系统的人类细胞系，这些细胞系 一旦模型得到充分验证，将立即进行筛选。通过这些屏幕，我们希望 找到感染所必需的宿主因子，如病毒的表面结合靶点ACE2， 预计筛选将确定其他基因，当敲除，防止病毒细胞病变， 方面的影响.此外，我们可以调节选择性压力，以确定当丢失时， 细胞SARS-CoV-2，这将提供对宿主细胞生物学的补充观点。同样，我们也将 进行CRISPR激活筛选，以确定宿主基因，当过度表达时， 这可以确定病毒必须克服的限制因素。主屏幕将 通过二级库进行验证，这也将允许在更多条件和细胞类型下测试基因， 建立结果的普遍性。最后，将进行组合筛选， 命中基因的无偏遗传相互作用图，它可以识别在一个 初级筛选，以及跨途径的意想不到的协同作用。有重点的、机械的基因跟踪 这些屏幕所识别的内容超出了本提案的范围，但Wilen和 古戎集团。

PROJECT SUMMARY In collaboration with Dr. Wilen (Yale University) and Dr. Goujon (CNRS, France), we will establish cell line models and conduct genome-wide CRISPR screens to identify host genes that are necessary for SARS-CoV-2 infection. We will first use Vero cells from the African Green Monkey, as they are a well-established model for many pathogens, and we had previously generated a genome-wide library for this species. Preliminary data suggest that we have also generated human cell lines that can serve as effective model systems, and these screens will be conducted as soon as the models are sufficiently validated. Across these screens, we expect to find host factors that are necessary for infection, such as the surface binding target for the virus, ACE2, and anticipate that the screens will identify additional genes that, when knocked out, prevent viral cytopathic effects. Additionally, we can modulate the selective pressure to identify factors that, when lost, sensitize the cells to SARS-CoV-2, which will provide a complementary view into host cell biology. Likewise, we will also conduct CRISPR activation screens to identify host genes that, when overexpressed, provide protection against infection, which may identify restriction factors that the virus must overcome. Primary screens will be validated with secondary pools, which will also allow for testing of genes across more conditions and cell types, establishing the generalizability of the results. Finally, combinatorial screens will be conducted to generate unbiased genetic interaction maps of hit genes, which can identify redundancies that are partially masked in a primary screen, as well as unexpected synergies across pathways. Focused, mechanistic follow-up of genes identified by these screens is outside the scope of this proposal, but is of immediate interest to the Wilen and Goujon groups.