Systems Biology Approaches to Viral Pathogenesis and Immunity

该项目建立在Katze实验室在基因组学、蛋白质组学和生物信息学方面的优势之上， 发展病毒-宿主相互作用以及病毒和宿主遗传决定因素的系统水平观点， 控制和决定感染的结果。为了实现这一目标，我们将与调查人员密切合作， 来自北卡罗来纳州大学（项目3.1）和威斯康星州大学（项目3.2），他们将 使用SARS-CoV、流感和埃博拉病毒的感染模型。除了大量的 我们将收集这些感染模型的微阵列数据，我们将整合蛋白质组学， 代谢组学和脂质组学数据，这些数据也可用于选定的感染模型。在目标1中，我们 使用基因表达数据在400个筛选中获得表达数量性状基因座（eQTL）定位 基因不同的小鼠，比较感染结果与SARS冠状病毒，流感和埃博拉病毒。 目标2从更详细的动物模型中生成病毒毒力和疾病进展的系统水平视图 数据集成是优化利用基因组和蛋白质组数据以更好地 了解基因和蛋白质的功能，以及辨别基因表达和蛋白质丰度 这些变化与先天性和适应性免疫反应以及最终的疾病结果相关。在目标3中， 将使用基因组方法提供宿主基因表达变化的全面视图， 在项目3.2中描述的埃博拉病毒免疫方案中发生。这些数据可以 提示保护性免疫的基因组标记或指示动物对特定疾病的易感性。 对免疫和随后的挑战作出反应。这些目标共同提供了一种综合方法 这显著增强了合作项目之间的协同作用，使我们和我们的合作者能够 将实验结果置于更全面的感染过程的背景下。在 此外，我们的高通量研究可能提供预测保护性的分子特征， 免疫学或病理学、用于诊断或预后测定的候选生物标志物，以及 改善抗病毒治疗或疫苗策略。

This Project builds upon the strengths of the Katze laboratory in genomics, proteomics, and bioinformatics to develop systems level views of the virus-host interactions and viral and host genetic determinants that regulate and determine the outcome of infection. To achieve this goal, we will work closely with investigators from the University of North Carolina (Project 3.1) and the University of Wisconsin (Project 3.2) who will be using infection models of SARS-CoV, influenza, and Ebola viruses. In addition to the extensive amount of microarray data that we will be collecting on these infection models, we will integrate proteomics, metabolomics, and lipidomics data that will also be available for selected infection models. In Aim 1, we will use gene expression data to obtain expression quantitative trait loci (eQTL) mapping in screens of 400 genetically distinct mice, comparing the infection outcomes with SARS-CoV, influenza, and Ebola viruses. Aim 2 generates a systems level view of viral virulence and disease progression from more detailed animal models; data integration is a key aspect to make optimal use of genomic and proteomic data for better understanding gene and protein function, as well as discerning how gene expression and protein abundance changes correlate with innate and adaptive immune responses and eventual disease outcome. In Aim 3, we will use genomic approaches to furnish a comprehensive view of the changes in host gene expression that occur in response to the Ebola virus immunization regimens described in Project 3.2. These data may suggest genomic markers of protective immunity or indicate the predisposition of an animal to a particular response to immunization and subsequent challenge. Together, these aims provide an integrated approach that markedly enhances synergy among the collaborating projects by allowing us and our collaborators to place experimental findings in the context of a more comprehensive picture of the infection process. In addition, our high-throughput studies are likely to provide molecular signatures that predict protective immunity or pathology, candidate biomarkers for diagnostic or prognostic assays, and a rational basis for improvements to antiviral therapies or vaccine strategies.