Omics for TB Disease Progression (OTB)

结核病进展组学 (OTB)

• 批准号: 8852535
• 负责人: ALAN A ADEREM
• 金额: $ 377.42万
• 依托单位: SEATTLE BIOMEDICAL RESEARCH INSTITUTE
• 依托单位国家: 美国
• 财政年份: 2013
• 资助国家: 美国
• 起止时间: 2013-06-21 至 2016-05-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/8852535
• 关键词: Affect; African; Bacterial Infections; Behavior; Bone Marrow; Candidate Disease Gene; Cessation of life; Clinical; Cohort Effect; Complex; Containment; Data; Data Collection; Data Set; Disease; Disease Progression; Evaluation; Gene Expression Profile; Genes; Genetic Screening; Human; Immune response; Infection; Instruction; Lung; Modeling; Mutant Strains Mice; Mycobacterium tuberculosis; Outcome; Proteins; RNA Interference; Regulon; Sampling; Symptoms; System; Systems Analysis; Systems Biology; Testing; Tuberculosis; cell type; combat; in vivo; macrophage; mutant; network models; novel; pathogen; repository; research study; response; tool

From initial infection to the onset of symptoms, tuberculosis (TB) is a remarkably complex disease. This proposal tests the concept that behaviors of host and pathogen are coordinated by interwoven regulatory networks, and that the outcome of infection (bacterial containment or active disease) is the product of many network-network interactions that vary both spatially and temporally. If so, then perturbing specific networks will both illuminate the topology of the larger network and allow us to define the steps and components critical to infection outcome. Our consortium of two projects and four Cores will test this hypothesis and reveal key features of TB disease progression in an iterative cycle: perturb carefully chosen subnetworks within both MTB and host; collect matched omics data sets; model, predict, and validate with new experiments. Project 1 exploits a vast repository of mutant mice to screen novel candidate genes derived from a unique South African clinical cohort for effects on TB disease progression. Project 2 begins with a novel in vivo genetic screen to identify MTB regulators that affect disease progression in lungs. In each case, once key regulators are identified, we will quantitate and characterize the changes in infected cell types and determine the specific points in disease progression where particular mutants show altered responses. For both projects, we leverage our extensive cache of preliminary data to perform detailed systems analyses of key genes and their predicted regulons using bone marrow macrophages infected ex vivo. We will collect host and MTB transcriptomes and global protein level changes from matched samples. We will also perform condition-specific ChlP-seq on key MTB regulators from within infected macrophages. These data will fuel modeling of both the bacterial and host response networks, predictions from which will drive a new round of mutant evaluation, omics-scale data collection and additional modeling. Our ultimate modeling Aim in this proposal is a novel integrated host/MTB network model, human relevance of which will be validated in primary human macrophages with mutant MTB and relevant host genes dis-regulated via RNAi.

从最初感染到出现症状，结核病 (TB) 是一种非常复杂的疾病。这 该提案测试了宿主和病原体的行为通过相互交织的监管来协调的概念 网络，感染的结果（细菌遏制或活动性疾病）是许多因素的产物 网络与网络之间的相互作用在空间和时间上都有所变化。如果是这样，则扰乱特定网络 将阐明更大网络的拓扑并允许我们定义步骤和组件 对感染结果至关重要。我们的两个项目和四个核心联盟将测试这个假设并 揭示迭代循环中结核病进展的关键特征：扰乱精心选择的子网络 在 MTB 和主机内；收集匹配的组学数据集；使用新的模型、预测和验证 实验。 项目 1 利用大量突变小鼠来筛选源自独特基因的新候选基因 南非对结核病进展影响的临床队列。项目2以体内小说开始 基因筛查以确定影响肺部疾病进展的 MTB 调节因子。在每种情况下，一旦密钥 确定调节因子后，我们将定量和表征受感染细胞类型的变化，并确定 疾病进展的特定点，其中特定突变体表现出改变的反应。 对于这两个项目，我们利用大量的初步数据缓存来执行详细的系统分析 使用离体感染的骨髓巨噬细胞对关键基因及其预测的调节子进行研究。我们将收集 匹配样本中宿主和 MTB 转录组以及整体蛋白质水平的变化。我们还将表演 对受感染巨噬细胞内的关键 MTB 调节因子进行条件特异性 ChLP-seq。这些数据将推动 对细菌和宿主反应网络进行建模，从中进行预测将推动新一轮的研究 突变体评估、组学规模数据收集和附加建模。我们的终极建模目标是 提案是一种新颖的集成主机/MTB 网络模型，其人类相关性将在 具有突变 MTB 的原代人类巨噬细胞和相关宿主基因通过 RNAi 失调。