Host Determinants of TB Disease Progression

项目总结(见说明)： 项目1将应用系统方法来确定宿主调控基因(HRG)网络，该网络确定无症状的结核分枝杆菌感染和结核病进展之间的平衡。我们的战略集中在我们最近识别的预测人类发展为活动性结核病(TB)的转录本签名。通过将我们对MTB疾病进展的人类转录信号与巨噬细胞天然免疫的网络模型相结合，我们已经确定了近200个候选的MTB感染HRGs。 利用我们获得大量和不断扩大的含有ENU诱导的偶然突变的小鼠的信息库，我们将在体内筛选改变的MTB诱导的先天和获得性免疫的HRG小鼠突变体。改变结核病进展的HRG突变将被提出进行详细的机制分析。结核分枝杆菌调节的先天免疫网络，以及管理先天免疫和获得性免疫之间的接口的网络，将通过系统水平的描述在体外和体内详尽地描述。我们将收集宿主和结核分枝杆菌的转录本，靶蛋白水平的变化，特定条件下的ChlP-seq，以及 来自匹配的感染巨噬细胞样本中的关键宿主调节因子的蛋白质组增强体谱。这些数据将推动细菌和宿主反应网络的建模，由此做出的预测将推动新一轮候选HRG评估、组学规模的数据收集和额外的建模。我们的最终建模目标：一个新的集成主机/MTB网络模型将使用来自人类的样本进行测试，候选突变细菌和特定的宿主基因都受到RNAi的调控。 近年来，我们为系统生物学所需的基础设施作出了重大贡献，包括开发用于数据生成、分析和建模的关键工具。我们已经生成了一个广泛的固有监管网络概要，将作为这里提出的MTB研究的基础。这个项目结合了免疫学、转录学、分子遗传学、ChlPseq、蛋白质组学和网络建模方面的不同进展，以产生一个实验上扎根和可验证的系统级

PROJECT SUMMARY (See instructions): Project 1 will apply systems approaches to identify Host Regulatory Gene (HRG) networks that determine the balance between asymptomatic MTB infection and TB disease progression. Our strategy is centered on our recent identification of transcriptomic signatures that predict progression to active tuberculosis (TB) in humans. By integrating our human transcriptomic signatures for MTB disease progression with network models of macrophage innate immunity, we have identified nearly 200 candidate HRGs of MTB infection. Leveraging our access to a vast and expanding repository of mice harboring ENU-induced incidental mutations, we will screen the HRG mouse mutants for altered MTB-induced innate and adaptive immunity in vivo. HRG mutants that alter TB disease progression will be advanced for detailed mechanistic analysis. MTB-regulated innate immunity networks, and networks governing the interface between innate and adaptive immunity will be exhaustively characterized in vitro and in vivo through systems-level profiling. We will collect host and MTB transcriptomes, targeted protein level changes, condition-specific ChlP-seq, and proteomic enhanceosome profiles of key host regulators from within matched samples of infected macrophages. These data will fuel modeling of both the bacterial and host response networks, predictions from which will drive a new round of candidate HRG evaluation, omics-scale data collection and additional modeling. Our ultimate modeling Aim: a novel integrated host/MTB network model will be tested using samples from humans, with both candidate mutant bacteria and specific host genes modulated by RNAi. In recent years, we have contributed substantially to the infrastructure needed for systems biology, including the development of key tools for data generation, analysis and modeling. We have generated an extensive compendium of innate regulatory networks that will serve as a foundation for the MTB studies proposed here. This project combines separate advances in immunology, transcriptomics, molecular genetics, ChlPseq, proteomics and network modeling to produce an experimentally grounded and verifiable systems-level