RESEARCH PROJECT 1

项目1：系统地识别主机网络 传染病发病机制 摘要 疾病控制和预防中心(CDC)估计，超过200万人感染了艾滋病 每年都有严重的抗药性细菌感染，造成至少23,000人死亡。这些数字将 随着多重耐药细菌频率的上升和感染在全球范围内的传播，这种情况急剧增加。 不幸的是，自20世纪60年代以来，新型抗生素的生产一直停滞不前，因此突显出 迫切需要开发可用于治疗感染的替代方法。已经有了 推动以宿主为导向的治疗传染病的新疗法的发展 预计不太容易产生抗药性。此外，最近的研究表明，虽然类似的 蛋白质可能不是不同病原体的靶标，相同的功能通路经常被劫持和 在感染过程中重新布线。因此，针对宿主途径的药物，而不是针对单个病原体的药物 因素，可能代表改善的治疗目标。出于这些原因，传染病的研究是 变得越来越依赖多种类型的宿主生物网络的知识，包括 蛋白质之间的物理相互作用，这允许功能通路的解构。 在这里，我们建议系统地识别驱动临床相关疾病发病机制的蛋白质网络。 模型系统。结合关键病原体-宿主的功能验证和高分辨率结构分析 相互作用和复杂性，我们也期待着对发病的潜在生物学的主要见解。 因为有可能揭开与治疗相关的新漏洞。 为此，我们瞄准了数百个结核分枝杆菌病原体编码基因， 金黄色葡萄球菌和沙眼衣原体，并对它们进行亲和纯化 在一组临床相关的免疫细胞系中进行光谱分析(AP-MS)(目标1)。为了补充这些数据，我们 将进行蛋白质组广泛的磷酸化、泛素化和蛋白质丰度的定量分析 病原体感染一段时间内的水平(目标2)。在目标3中，我们将使用一套结构 表征方法，包括X射线结晶学、低温电子显微镜(低温电子显微镜)和 交联质谱(XL-MS)用于治疗可操作蛋白质的结构表征 复合体和信令节点。这些目的将为体内宿主靶蛋白的选择提供信息 在AIM 4中的验证，在其中我们将产生基因敲除小鼠并使它们受到感染以测试增加的 对细菌病原体的抗性。这项工作的成功完成不仅将极大地丰富我们的 对宿主-病原体网络相互作用的了解有限，但它也将确定新的治疗方法 这三种病原体的机会。此外，该平台的开发将产生一个完整的 系统到结构的管道，可以扩展到许多病原体类型，并将有助于理性 以更高的精度和速度选择治疗靶点。 1

PROJECT 1: SYSTEMATIC IDENTIFICATION OF HOST NETWORKS IN INFECTIOUS DISEASE PATHOGENESIS SUMMARY The Centers for Disease Control and Prevention (CDC) estimates that more than 2 million people acquire a serious drug-resistant bacterial infections each year, with at least 23,000 deaths resulting. These numbers will increase dramatically as the frequency of multidrug resistant bacteria rise and infections spread worldwide. Unfortunately, the production of novel classes of antibiotics has stagnated since the 1960s, thus underscoring a critical need for the development of alternate approaches that can be used to treat infection. There has been a new push for the development of host-directed therapies for treatment of infectious diseases as they are expected to be less susceptible to drug-resistance. In addition, recent work has revealed that while similar proteins may not be targeted by different pathogens, the same functional pathways are often hijacked and re-wired during the course of infection. Thus, drugs that target host pathways, rather than individual pathogen factors, may represent improved targets for treatment. For these reasons, the study of infectious disease is becoming increasingly dependent on knowledge of host biological networks of multiple types, including physical interactions among proteins, which allow for deconstruction of functional pathways. Here we propose to systematically identify the protein networks that drive pathogenesis in clinically relevant model systems. Coupled with functional validation and high-resolution structural analysis of key pathogen-host interactions and complexes, we anticipate major insights into the underlying biology of pathogenesis, as well as the potential to unravel novel vulnerabilities of therapeutic relevance. To this end, we are targeting hundreds of pathogen encoded genes from Mycobacterium tuberculosis, Staphylococcus aureus, and Chlamydia trachomatis, and subjecting them to affinity purification mass spectrometry (AP-MS) in a panel of clinically relevant immune cell lines (Aim 1). To complement these data we will perform proteome wide quantitative profiling of phosphorylation, ubiquitylation and protein abundance levels over a time course of pathogen infection (Aim 2). In Aim 3, we will use a suite of structural characterization methods, including X-ray crystallography, cryogenic electron microscopy (cryo-EM) and cross-linking mass spectrometry (XL-MS) to structurally characterize therapeutically actionable protein complexes and signaling nodes. These aims will inform the selection of host target proteins for in vivo validation in Aim 4, in which we will generate knockout mice and subject them to infection to test for increased resistance to bacterial pathogens. Successful completion of this this work will not only significantly enrich our limited understanding of host-pathogen networks interactions, but it will also identify novel therapeutic opportunities for these three pathogens. Additionally, the development of this platform will yield an integrated systems-to-structure pipeline that can be extended to many pathogen types, and will aid in the rational selection of therapeutic targets with greater precision and speed. 1