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.

从初始感染到症状发作，结核病（TB）是一种非常复杂的疾病。这 提案测试了一个概念，即宿主和病原体的行为是通过交织的调节协调的 网络，感染的结果（细菌遏制或活性疾病）是许多人的产物 网络网络交互在空间和时间上变化。如果是这样，那么扰动特定网络 都将照亮较大网络的拓扑，并允许我们定义步骤和组件 对感染结果至关重要。我们由两个项目和四个核心组成的财团将检验这一假设， 在迭代循环中揭示结核病进展的关键特征：敏捷的子网 在MTB和主机中；收集匹配的OMIC数据集；模型，预测和验证新的 实验。 项目1利用大量突变小鼠的存储库来筛选出源自独特的候选基因 南非临床队列对结核病疾病进展的影响。项目2从体内小说开始 遗传筛查以鉴定影响肺部疾病进展的MTB调节剂。在每种情况下，一次键 确定调节剂，我们将定量和表征感染细胞类型的变化，并确定 特定突变体显示反应改变的疾病进展中的特定点。 对于这两个项目，我们都利用大量的初步数据缓存来执行详细的系统分析 使用骨髓巨噬细胞感染的骨髓巨噬细胞的关键基因及其预测的调节。我们将收集 宿主和MTB转录组以及全局蛋白水平随匹配的样品而变化。我们也会表演 来自感染巨噬细胞内部的关键MTB调节剂的条件特异性CHLP-SEQ。这些数据将加剧 对细菌和宿主响应网络的建模，预测将驱动新的一轮 突变评估，OMICS规模数据收集和其他建模。我们的最终建模目标 提案是一种新颖的综合主机/MTB网络模型，其人类相关性将在 通过RNAi分离的具有突变体MTB和相关宿主基因的原代人巨噬细胞。