Unbiased Functional Characterization of Enterovirus-Host Interactions

项目总结（见说明）： 在这项研究中，我们的目的是功能性地询问主机病原体的关系，使用三种不同的肠道病毒（脊髓灰质炎病毒，EV 71和柯萨奇病毒）。为此，我们将使用各种方法系统地生成病毒-宿主蛋白质-蛋白质和遗传相互作用图谱。使用这些初始的、无偏见的方法生成的数据将在后续项目中推动更有针对性的、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， 包括伴侣蛋白功能，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。与Sumit Chanda（Burnham研究所）和John Young（Salk研究所）合作，我们将利用RNAi方法在全球范围内评估宿主因素对三种肠道病毒发病机制的遗传依赖性（阳性和阴性）。下一个是 为了表征肠道病毒-人蛋白质-蛋白质相互作用，我们打算与Al Burlingame（UCSF）合作，采用系统的亲和标签/纯化-质谱法来鉴定病毒-宿主蛋白质复合物（目的2）。我们还打算使用质谱法全面确定蛋白质翻译后修饰对感染的影响（目标3）。最后，In Aim 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Judith Frydman（项目2）和Raul Andino（项目3）合作生成和测试有关质量控制过程的特定假设。这种综合方法将利用多个小组的专业知识，包括技术核心的Pis（Andrej Sali和Joe Derisi），以便识别和表征感染期间被劫持的新宿主途径。 这些信息有望导致抗病毒药物和疫苗的突破。

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.