Unbiased Functional Characterization of Enterovirus-Host Interactions

项目总结(见说明)： 在这项研究中，我们的目标是使用三种不同的肠道病毒(脊髓灰质炎病毒、EV71和柯萨奇病毒)从功能上询问宿主与病原体的关系。为此，我们将使用多种方法系统地生成病毒-宿主蛋白-蛋白质和遗传相互作用图。使用这些最初的、不偏不倚的方法产生的数据将在后续项目中推动更有针对性、更受假设驱动的研究。虽然我们打算跟进我们发现的最有趣、最意想不到的联系，但我们将密切监测与质量控制过程中涉及的主机因素的联系， 包括伴侣功能、蛋白质泛素化和蛋白质降解，这将把这项工作与项目2和3中描述的工作联系起来。我们将与Sumit Chanda(Burnham Institute)和John Young(Salk Institute)合作，利用RNAi方法在全球范围内评估宿主因素与三种肠道病毒致病机制(目标1)的遗传相关性。下一首, 为了表征肠道病毒-人类蛋白质-蛋白质的相互作用，我们打算与Al Burlingame(UCSF)合作，使用系统的亲和标签/净化-质谱学方法来鉴定病毒-宿主蛋白质复合体(目标2)。我们还打算利用质谱学在全球范围内确定蛋白质翻译后修饰对感染的影响(目标3)。最后，在AIM中 4，我们将利用一套生物信息学和可视化工具以有意义的方式整合数据集，以便与朱迪思·弗莱德曼(项目2)和劳尔·安迪诺(项目3)合作生成和测试关于质量控制过程的具体假设。这种综合的方法将利用多个小组的专业知识，包括技术核心的PI(Andrej Sali和Joe DeRisi)，以便可以识别和表征在感染期间被劫持的新宿主路径。 这些信息有望在抗病毒药物和疫苗方面取得突破。

PROJECT SUMMARY (See instructions): In this study, we aim to functionally Interrogate host-pathogen relationships using three different enteroviruses (poliovirus, EV71 and coxsackievirus). To this end, we will use a variety of methods to systematically generate viral-host protein-protein and genetic interaction maps. The data generated using these initial, unbiased approaches will fuel more targeted, hypothesis-driven research in the subsequent projects. Although we intend to follow up on the most Interesting, unanticipated connections we uncover, we will be closely monitoring for links to host factors involved in quality control processes, including chaperone function, protein ubiquitination and protein degradation, which will link this work to the work described in Projects 2 and 3. In collaboration with Sumit Chanda (Burnham Institute) and John Young (Salk Institute), we will utilize RNAI methodology to globally assess the genetic dependencies, both positive and negative, of host factors to the pathogenesis of the three enteroviruses (Aim 1). Next, to characterize the enterovlrus-human protein-protein interactions, we intend to collaborate with Al Burlingame (UCSF) to employ a systematic affinity tag/purlflcation-mass spectrometry approach to Identify the viral-host protein complexes (Aim 2). We also Intend to globally ascertain the effects of protein post-translational modifications upon infection using mass spectrometry (Aim 3). Finally, In Aim 4, we will utilize a suite of bioinformatic and visualization tools to integrate the data sets in a meaningful fashion so that specific hypotheses regarding quality control processes can be generated and tested in collaboration with Judith Frydman (Project 2) and Raul Andino (Project 3). This integrated approach will leverage the expertise from multiple groups, including Pis of the Technology Core (Andrej Sali and Joe Derisi), so that novel host pathways that are hijacked during Infection can be Identified and characterized. This information will hopefully lead to breakthroughs with anti-viral drugs and vaccines.