Systems Biology Analysis of Influenza A Virus and Ebola Virus

项目摘要(见说明)：感染高致病性禽流感H5N1甲型流感病毒(LAV)或埃博拉病毒(EBOV)会导致严重的呼吸道疾病或出血热，导致人类高死亡率。对这些病毒如何失调宿主反应的有限了解损害了对病毒引起的疾病的有效治疗。我们假设，比较宿主对H5N1 LAV、EBOV和一系列毒力突变的反应将有助于描述共同的和病毒特异性的免疫颠覆和致病机制。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一假设。我们将利用我们现有的来自感染H5N1亚型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，在目标1中，将为感染EBOV的细胞和小鼠获得类似的蛋白质组学和转录组数据集。此外，我们将对这两种病毒进行miRNA图谱、磷酸蛋白质组学、代谢组学和脂质组学分析；量化免疫细胞进入感染肺或肝脏组织的数量；收集从LAV感染肺分离的免疫细胞群的转录组数据；以及提供LAV和EBOV蛋白与宿主蛋白相互作用的全面数据。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为西尼罗河病毒(WNV)产生的数据相结合。计算建模核心将产生用于后续分析的优先调控靶标列表，在目标2中，靶标将使用结合宿主因子表达或活性扰动的体外系统进行实验验证。选定的靶点将在体内通过基因敲除(KO)小鼠的生成和KO基因对感染结果的影响的评估来验证。为了完善计算模型和完成系统生物学范式，我们还将从KO小鼠身上获取样本，用于迭代组学研究。总而言之，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性建模，并确定可能成为新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.