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Host Determinants of TB Disease Progression

结核病进展的宿主决定因素

基本信息

批准号：
8577272
负责人：
ALAN A ADEREM
金额：
$ 78.73万
依托单位：
SEATTLE BIOMEDICAL RESEARCH INSTITUTE
依托单位国家：
美国
项目类别：
财政年份：
2013
资助国家：
美国
起止时间：
2013-06-21 至 2018-05-31
项目状态：
已结题

来源：
https://reporter.nih.gov/project-details/8577272
关键词：
Aerosols Affect Bacteria Bacterial Infections Behavior Bone Marrow Cells Cessation of life Containment Cues Data Data Collection Data Set Dendritic Cell Pathway Dendritic Cells Dendritic cell activation Development Disease Disease Progression Equilibrium Ethylnitrosourea Evaluation Foundations Gene Expression Gene Expression Profile Gene Mutation Generations Genes Human Immune response Immunology In Vitro Infection Instruction Lung Modeling Molecular Genetics Mus Mutant Strains Mice Mutation Mycobacterium tuberculosis Natural Immunity Nature Outcome Pathway interactions Phenotype Proteins Proteomics RNA Interference Regulator Genes Research Infrastructure Sampling Shapes System Systems Analysis Systems Biology T cell response T-Lymphocyte Testing Time Transgenic Organisms Tuberculosis Virulence adaptive immunity advanced system base cohort combat in vivo macrophage monocyte mutant network models novel pathogen predictive modeling repository research study residence tool transcriptomics

项目摘要

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

项目概述（见说明）：