M. tuberculosis strain-dependent interactions with host cells

结核分枝杆菌与宿主细胞的菌株依赖性相互作用

• 批准号: 10653910
• 负责人: JEFFERY S COX
• 金额: $ 62.89万
• 依托单位: UNIVERSITY OF WASHINGTON
• 依托单位国家: 美国
• 财政年份: 2021
• 资助国家: 美国
• 起止时间: 2021-08-01 至 2026-05-31
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10653910
• 关键词: Alleles; Animal Model; Bacterial Genes; Bacterial Proteins; Bioinformatics; Biological Assay; CBL gene; CRISPR/Cas technology; Candidate Disease Gene; Cell Wall; Cells; Clinical; Collaborations; Complement; Cues; Data; Data Set; Defect; Diagnostic; Disease; Disease Outcome; Distal; ELF3 gene; Etiology; Family; Genes; Genetic; Genetic Variation; Genotype; Goals; Growth; Host resistance; Human; Immune; Immune response; Individual; Infection; Inflammatory Response; Innate Immune Response; Interferon Type I; Laboratories; M. tuberculosis genome; Macrophage; Mediating; Messenger RNA; Modification; Mutation; Mycobacterium tuberculosis; Network-based; Organism; Outcome; Pathogenesis; Pathogenicity; Pathway interactions; Permeability; Phagosomes; Phenotype; Population; Post-Translational Protein Processing; Predisposition; Prevalence; Protein Secretion; Proteins; Proteomics; Pulmonary Tuberculosis; Resistance; Scanning; Site; System; Technology; Testing; Tuberculosis; Ubiquitin; Variant; Vietnam; Vietnamese; Virulence; Work; bacterial genetics; causal variant; cohort; complex data; diverse data; genome wide association study; high resolution imaging; in vivo; innate immune pathways; insight; mouse model; mutant; pathogen; programs; recruit; repaired; response; transcriptomics; transmission process; ubiquitin ligase

Tuberculosis (TB) is a multifaceted disease that has extensive variation in clinical manifestations despite being the product of infection with a single pathogen, Mycobacterium tuberculosis. The extensive genetic diversity in human and Mycobacterium tuberculosis genomes responsible for differences in clinical outcomes represent modifications of host-pathogen interactions that are key to pathogenesis. Understanding the basis for these heterogenous responses will uncover new mechanisms of virulence and resistance and will impact treatment and diagnostics. Unfortunately, the challenges of studying the mechanisms of differential outcomes of infection in humans not only includes identification of correlations between host/pathogen genotypes with phenotypes in human populations, but also the subsequent identification of the mechanisms that are causal for disease which require studying them in the laboratory without the pathogen’s natural host organism. This Program takes advantage of unique, ongoing genome-wide association studies (GWAS) that have identified both human and pathogen variants that are associated with heterogenous clinical responses in two different human populations. To determine the mechanisms underlying these variations, we will employ a powerful set of experimental assays, including new proteomics-based scanning platform to probe host responses during experimental macrophage infection that is orthogonal to traditional mRNA profiling, in order to broadly search for changes in host innate immune pathways that correlate with disease outcomes associated with these clinical strains. Based on our preliminary data, we hypothesize that many of these interactions occur early during infection and are mediated by proteins secreted by M. tuberculosis. In this proposal, we focus primarily on correlations between two unique sets of clinical bacterial variants, strains that are associated greater transmission of pulmonary TB disease and strains that are more prone to dissemination to distal sites in the body. An unexpected theme from both of these sets of strains is the prevalence of TB proteins secreted by the ESX systems expressed in M. tuberculosis. Both the ESX-1 and ESX-5 secretion systems of M. tuberculosis are key virulence determinants required for intracellular growth and for eliciting distinct innate immune responses during macrophage infection. A central hypothesis is that the set of bacterial proteins that influence disease outcomes are enriched for secreted proteins that mediate interactions between pathogen and host macrophages. To test this hypothesis, we will collaborate with Cores A and B to use an integrative approach to combine genetic data from the M. tuberculosis GWAS datasets with genetic and proteomic screen to identify causal genes that mediate interactions with macrophages. We will use these same technologies to collaborate with Projects 2 and 3 to identify proteins/pathways responsible for host resistance and bacterial dissemination.

结核病（TB）是一种多面性疾病，尽管在临床表现上有广泛的差异