Modeling Host Responses to Understand Severe Human Virus Infections

这一全面和高度集成的系统生物学应用程序试图描绘出复杂的 决定感染潜在致命性病毒结果的宿主反应。为了实现这一目标， 细胞和小鼠将感染野生型和突变型甲型流感病毒、埃博拉病毒和西尼罗河病毒 各种样本集(这些活动将由两个流感研究项目和 埃博拉病毒或西尼罗河病毒)。技术核心将执行蛋白质组学、磷酸蛋白质组学、 脂肪组学和代谢组学分析，而mRNA和miRNA分析将以服务费的形式外包 基础。此外，包括病毒学数据和蛋白质-蛋白质数据在内的多种生物数据集 互动，将会产生。所有数据将由计算建模核心进行分析，该核心将 整合不同的数据集，构建预测性的机械模型和网络模型，包括虚拟肺 和肝脏模型。基于这些分析，两个研究项目将全面开展 在体外和体内(即，在基因敲除小鼠中)的验证研究。组学研究(如上所述)来自 病毒感染的敲除小鼠和配对的野生型小鼠将被用于第二轮分析，从而 实现迭代采样、建模和验证的系统生物学范式。存储， 大型和多样化数据集的管理和交换，以及与社区的接触将是 由数据管理和资源传播核心推动，而行政核心 将确保所有行政任务都得到解决。总而言之，我们提出了一个全面和 交互式系统生物学计划，将增强传染病的预测性建模并识别 严重的人类病毒致病性的关键调节因子，可用于开发 治疗性干预。

This comprehensive and highly integrated systems biology application seeks to delineate the complex host responses that determine the outcome of infections with potentially lethal viruses. To achieve this goal, cells and mice will be infected with wild-type and mutant influenza A, Ebola, and West Nile viruses to collect a variety of sample sets (these activities will be carried out by two Research Projects for influenza and Ebola or West Nile virus, respectively). A Technical Core will perform proteomics, phosphoproteomics, lipidomics, and metabolomics profiling, whereas mRNA and miRNA profiling will be out-sourced on a fee-for-service basis. In addition, multiple biological datasets, including virological data and data on protein-protein interactions, will be generated. All data will be analyzed by a Computational Modeling Core, which will integrate the diverse datasets and build predictive mechanistic and network models, including virtual lung and liver models. Based on these analyses, the two Research Projects will carry out comprehensive validation studies in vitro and in vivo (i.e., in knock-out mice). OMICs studies (as described above) from virus-infected knock-out and matched wild-type mice will be used for a second round of analysis, thereby achieving the systems biology paradigm of Iterative sampling, modeling, and validation. Storage, management, and exchange of the large and diverse datasets, and outreach to the community, will be facilitated by a Data Management and Resources Dissemination Core, whereas an Administrative Core will ensure that all administrative tasks are addressed. In summary, we propose a comprehensive and interactive systems biology program that will enhance predictive modeling of infectious disease and identify critical regulators of severe human virus pathogenicity that may be exploited for the development of therapeutic interventions.