Prevalence, Consequences and Mechanisms of Antibiotic Heteroresistance in Cystic Fibrosis

项目摘要 改善感染结果的进展取决于对削弱抗生素作用的因素的了解。 最近的研究表明，抗生素的异质性耐药可能是一个关键因素。异源耐药病原菌展示 种群水平的抗性异质性，这意味着它们包含高度抗性的亚群，而且通常 表现出不稳定的抗药性，这意味着一些细胞在没有抗生素的情况下生长时会迅速变得敏感。 这项建议侧重于这两种表型，因为它们被认为对易感性有重大影响。 测试和抗生素疗效。在这里，我们建议研究种群水平的抗性异质性和 囊性纤维化(CF)和慢性铜绿假单胞菌(PA)患者的不稳定耐药性 时断时续的感染患者吸入了妥布霉素。 Cf为这些研究提供了关键优势，因为它是一种具有统一表现的单基因疾病， 单一细菌物种对相同抗生素的反应可以在相当大的队列中进行研究，并且 存在基础设施，用于在抗生素使用期间从感染部位(痰)获取初级样本 “关”期。这些优势和我们在前期工作中开发的方法使我们能够测试 假设来自慢性感染患者的PA表现出显著的人群水平耐药性异质性 和不稳定的耐药性；考虑这些因素的参数预测治疗的临床反应； Cf pa的不稳定抗性是由于一套核心的基因扩增和适合度补偿 点突变。这项工作将产生关于抗生素异质性的基础知识， 提高对CF中抗生素治疗失败的认识，并提出新的精准医学方法 选择抗生素并改善结果。这些发现也可以指导未来在感染方面的工作， 异质性、病原体和治疗的多样性以及不发达的基础设施使研究变得更加困难。

Project Summary Progress in improving infection outcomes depends upon understanding factors that diminish antibiotic action. Recent work suggests antibiotic heteroresistance may be a key factor. Heteroresistant pathogens exhibit population-level resistance heterogeneity, meaning they contain highly resistant subpopulations, and often exhibit unstable resistance, meaning some cells become rapidly sensitive when grown without antibiotics. This proposal focuses on these two phenotypes as they are postulated to have major effects on susceptibility testing and antibiotic efficacy. Here we propose to study population-level resistance heterogeneity and unstable resistance in people with cystic fibrosis (CF) and chronic Pseudomonas aeruginosa (Pa) infections who cycle on and off inhaled tobramycin. CF offers key advantages for these studies as it is a monogenic disease with uniform manifestations, the responses of a single bacterial species to the same antibiotic can be studied in sizable cohorts, and infrastructure exists to procure primary specimens from the infected site (sputum) during antibiotic "on" and "off" periods. These advantages, and methods developed in our preliminary work enable us to test the hypotheses that Pa from chronically-infected patients exhibit marked population-level resistance heterogeneity and unstable resistance; that parameters accounting for these factors predict clinical responses to treatment; and that unstable resistance in CF Pa is due to a core set of gene amplifications and fitness-compensating point mutations. This work will generate foundational knowledge about antibiotic heteroresistance that could improve understanding of antibiotic treatment failure in CF, and suggest new precision medicine approaches to select antibiotics and improve outcomes. The findings could also guide future work in infections where patient heterogeneity, pathogen and treatment diversity, and less developed infrastructure make studies more difficult.