Modeling Host Responses to Understand Severe Human Virus Infections

这种全面和高度集成的系统生物学应用程序旨在描绘复杂的 决定潜在致命病毒感染结果的宿主反应。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）。技术核心将进行蛋白质组学，磷酸蛋白质组学， 脂质组学和代谢组学分析，而mRNA和miRNA分析将外包收费服务 基础此外，多个生物数据集，包括病毒学数据和蛋白质-蛋白质数据， 互动，将产生。所有数据将由计算建模核心进行分析， 整合不同的数据集并构建预测机制和网络模型，包括虚拟肺 肝脏模型基于这些分析，两个研究项目将开展全面的 体外和体内的验证研究（即，在敲除小鼠中）。OMIC研究（如上所述）来自 病毒感染的敲除小鼠和匹配的野生型小鼠将用于第二轮分析，从而 实现迭代采样、建模和验证的系统生物学范式。储存， 管理和交换大型和多样化的数据集，并向社区推广，将是 由数据管理和资源传播核心提供便利，而行政核心 将确保所有行政任务得到处理。总之，我们提出了一个全面和 交互式系统生物学计划，将加强传染病的预测建模，并确定 严重的人类病毒致病性的关键调节因子，可用于开发 治疗干预。

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.