CRISPR screens for SARS-CoV-2 Host Factors

项目总结 我们将与Wilen博士(耶鲁大学)和Goujon博士(法国CNRS)合作，建立细胞系 建立模型并进行全基因组CRISPR筛查，以确定SARS-CoV-2所必需的宿主基因 感染。我们将首先使用非洲绿猴的Vero细胞，因为它们是一个成熟的模型 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 一旦模型得到充分验证，将立即进行筛查。在这些屏幕上，我们预计将 寻找感染所必需的宿主因子，例如病毒的表面结合靶点ACE2和 预计筛查将识别出额外的基因，当基因被敲除时，可以防止病毒性细胞病变 效果。此外，我们可以调节选择性压力，以确定当丢失时会使 细胞与SARS-CoV-2的关系，这将为宿主细胞生物学提供补充。同样，我们还将 进行CRISPR激活筛选，以确定当过度表达时提供保护的宿主基因 抗感染，这可能确定病毒必须克服的限制因素。主屏幕将是 用二级池进行验证，这也将允许测试更多条件和细胞类型的基因， 建立了结果的推广性。最后，进行组合筛选，生成 HIT基因的无偏遗传相互作用图，它可以识别被部分屏蔽的冗余 主要屏幕，以及跨路径的意外协同效应。有重点的、机械性的基因跟踪 这些屏幕所标识的内容不在本提案的范围内，但与Wilen和 古洪集团。

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.