Parallel phenotyping to dissect genetic determinants of bacterial strain diversity

项目总结 所有病原体都具有遗传多样性，可以影响临床相关的表型，如毒力， 药物敏感性和疫苗效力。在后基因组时代，我们对微生物基因类型进行分类的能力 已经远远超出了我们分析微生物表型的能力。这限制了我们构建基因的能力-- 为感兴趣的性状绘制表型图，并阻碍广泛有效的新抗菌剂的开发， 疫苗和公共卫生干预。为了应对这一挑战，我开发了一种分子条形码 一种允许在单个体外或体外对数百个细菌临床分离株进行并行适合度表型分析的方法 活体实验。我开发并验证了这一新方法在结核分枝杆菌病原体中的应用 以及在感染期间和接种疫苗后细菌适合性的不同菌株之间的差异 老鼠模型。在这里，我建议使用这个新的工具来询问表型的遗传基础 一种相关分枝杆菌病原体的异质性，鸟分支杆菌(MAC)。Mac是一位环保人士 可导致慢性和治疗顽固性感染的微生物，其发病率正在增加。一位少校 MAC疾病管理中的挑战是病程和治疗结果的变异性，以及 这种变异性的细菌决定因素尚不清楚。在这里，我将利用我的应变条形码方法 以及这种微生物的自然生物多样性，以阐明遗传决定因素和分子机制 Mac的致病性和抗生素反应。这些努力将为改进诊断的发展提供信息 以及治疗这种和其他慢性细菌感染的药物。更广泛地说，这项工作将提供一种 用于揭示传染性疾病异质性生物学基础的智能框架和实验工具包 疾病表型。

PROJECT SUMMARY All pathogens possess genetic diversity that can impact clinically relevant phenotypes such as virulence, susceptibility to drugs, and vaccine efficacy. In the post-genomic era, our ability to catalog microbial genotypes has far outstripped our capacity to profile microbial phenotypes. This limits our ability to build genotype- phenotype maps for traits of interest and hinders the development of broadly effective new antimicrobials, vaccines, and public health interventions. To address this challenge, I developed a molecular barcoding approach that permits parallel fitness phenotyping of hundreds of bacterial clinical isolates in a single in vitro or in vivo experiment. I developed and validated this novel approach in the pathogen Mycobacterium tuberculosis and uncovered strain-specific differences in bacterial fitness during infection and following vaccination in the mouse model. Here, I propose to use this novel tool to interrogate the genetic basis of phenotypic heterogeneity in a related mycobacterial pathogen, Mycobacterium avium (MAC). MAC is an environmental microbe that can cause chronic and treatment-recalcitrant infections and is increasing in incidence. A major challenge in the management of MAC disease is the variability in disease course and treatment outcome, and the bacterial determinants of this variability are unknown. Here, I will leverage my strain barcoding approach and the natural biodiversity of this microbe to elucidate genetic determinants and molecular mechanisms of MAC pathogenicity and antibiotic response. These efforts will inform the development of improved diagnostics and therapeutics for this, and other, chronic bacterial infections. More broadly, this work will provide an intellectual framework and experimental toolkit to uncover the biological basis of heterogeneity in infectious disease phenotypes.