Systems Biology Analysis of Influenza A Virus and Ebola Virus

项目总结（见说明）：高致病性禽流感病毒H5 N1 A型流感病毒（IAV）或埃博拉病毒（EBOV）感染可引起严重的呼吸道疾病或出血热，在人类中具有高死亡率。对这些病毒如何失调宿主反应的有限理解损害了对病毒诱导的疾病的有效治疗。我们假设比较宿主对H5 N1 IAV、EBOV和一系列毒力突变体的反应将允许描绘免疫颠覆和致病性的共同和病毒特异性机制。在这里，我们提出了一个高度集成的系统生物学方法来解决这个假设。我们将利用我们现有的来自感染H5 N1病毒和突变病毒的细胞和小鼠肺的转录组和蛋白质组数据，在Aim 1中，将获得EBOV感染细胞和小鼠的类似蛋白质组和转录组数据集。此外，我们将对两种病毒进行miRNA谱分析、磷酸化蛋白质组学、代谢组学和脂质组学分析;量化进入感染的肺或肝组织的免疫细胞运输;收集从lAV感染的肺分离的免疫细胞群体的转录组学数据;并提供lAV和EBOV蛋白与宿主蛋白相互作用的综合数据。数据集将在几个核心的协助下获得，用于样本处理，统计和计算分析，并与本合同第二个研究项目下的西尼罗河病毒（WNV）生成的数据整合。计算建模核心将产生优先的监管目标清单，用于后续分析，在目标2中，将使用体外系统结合宿主因子表达或活性的扰动对目标进行实验验证。然后通过产生敲除（KO）小鼠并评估基因KO对感染结果的影响来在体内验证选定的靶标。为了改进计算模型和完成系统生物学范式，我们还将从KO小鼠中获得样品用于迭代OMIC研究。总的来说，这一策略有望促进与严重的人类病毒病原体相关的疾病状态的预测建模，并确定可能成为新型干预策略目标的病毒发病机制的重要调节因子。

PROJECT SUMMARY (See instructions): Infections with highly pathogenic avian H5N1 influenza A viruses (lAV) or Ebola viruses (EBOV) cause severe respiratory disease or hemorrhagic fever with high mortality rates in humans. The limited understanding of how these viruses dysregulate the host response impairs effective treatments for virus induced disease. We hypothesize that comparing host responses to H5N1 lAV, EBOV and a range of virulence mutants will allow delineation of common and virus-specific mechanisms of immune subversion and pathogenicity. Here, we propose a highly integrated systems biology approach to address this hypothesis. We will leverage our existing transcriptome and proteome data from cells and mouse lungs infected with H5N1 lAV and mutant viruses, and in Aim 1, similar proteomics and transcriptomics datasets will be acquired for EBOV-infected cells and mice. In addition, we will perform miRNA profiling, phosphoproteomics, metabolomics and lipidomics analyses for both viruses; quantify immune cell trafficking into infected lung or liver tissues; collect transcriptomics data for immune cell populations isolated from lAV infected lungs; and provide comprehensive data for lAV and EBOV protein interactions with host proteins. Datasets will be acquired with the assistance of several Cores for sample processing, statistical and computational analyses, and integration with data generated for West Nile virus (WNV) under the second Research Project of this contract. The Computational Modeling Core will produce prioritized regulatory target lists for follow-up analysis, and in Aim 2, targets will be experimentally validated using in vitro systems coupled with perturbation of host factor expression or activity. Selected targets then will be validated in vivo by generation of knockout (KO) mice and assessment of the effects of gene KO on the outcome of infection. To allow refinement of computational models and completion of the systems biology paradigm, we will also obtain samples from KO mice for iterative OMICs studies. Collectively, this strategy is expected to facilitate predictive modeling of disease states associated with severe human viral pathogens and identify important regulators of viral pathogenesis that may be targeted for novel intervention strategies.