Collateral Consequences of Enabler Genotypes in Antibiotic Treatment Failure.

项目2：Enabler基因分型在抗生素治疗失败中的附带后果 抗生素治疗失败(ATF)具有重要的医学意义，因为有效的抗生素治疗的延迟。 增加长期发病率和增加死亡率，导致总体较差的患者预后。而当 抗生素耐药性是ATF的主要机制之一，在瞬时细胞状态中起着重要作用 抗生素的耐受性、持久性和异质性耐药，在这里被称为“促进剂”越来越多。 被认为是细菌逃避抗生素治疗的主要机制。这些促进剂细菌 人口具有相当大的科学和医学重要性，通常先于随后的 进化或获得高水平的抗性机制，使这些种群成为“煤炭中的金丝雀” 了解耐药性和治疗失败是如何出现的。由此确定的启动子突变体 远中央细胞通路表明了发展启动状态的共性，提示这些 这些发现将以跨物种的方式广泛适用。我们的基本假设是 可以识别和合理地针对使能型的伴随表型，以优化 治疗结果，并防止随后获得高水平的耐药性。我们计划使用一个 多方面的方法，以了解使能突变的遗传和机制基础。我们会 在两种情况下使用连续可变的抗生素暴露实验选择启动子突变 敏感菌株和有明确启动子突变的菌株。这些抗生素对抗生素敏感但耐受 种群将被用来模拟不同的启动子基因对概率和遗传的影响 高水平抗生素耐药性后续进化的途径，这些基因类型在 耐药性的水平转移，以及使能突变如何影响体内抗生素治疗失败。这些 使能菌株将被用来模拟各自的基因类型在抗生素暴露时如何影响关键 细菌严格反应、转录信号和翻译保真度等途径，以及如何 这进而导致启动子表型的产生。这些调查路线将提供洞察力 不同的启动子基因是否有共同的机制基础。我们还计划 检查合理的靶向促进剂是否可以提供治疗益处，以阻止 当存在使能突变时，可产生抗药性或提高抗生素效力。启动子突变通常是 与对化学物质代谢具有敏感性或抵抗力的附带后果有关 压力。我们将确定利用这些交叉敏感性的可能性，通过有针对性的和 无偏见的化学筛选方法。然后，将调查这些协同效应是否具有以下能力 防止诱因突变体的出现及其更有效地治疗感染的能力 由对抗生素治疗顽固不化的菌株所致。这些目标的成功实现将提供一个 遗传基础和机制洞察的瞬时细胞状态赋予启动表型。我们期待着 考虑到保守的可能性，这些发现将适用于多种细菌物种 促进因素的潜在机制，并可能提供预防抗生素治疗的额外策略 在细菌感染期间失败。

Project 2: Collateral Consequences of Enabler Genotypes in Antibiotic Treatment Failure Antibiotic treatment failure (ATF) is of critical medical importance as delays in effective antibiotic therapy promotes prolonged morbidity and increase mortality leading to overall poorer patient outcomes. While antibiotic resistance is one primary mechanism for ATF, the roles for transient cell-states conferring antibiotic tolerance, persistence, and hetero-resistance, herein referred to as “enablers” are increasingly recognized as a major mechanism for bacterial evasion of antibiotic therapy. These enabler bacterial populations are of considerable scientific and medical importance as typically precede the subsequent evolution or acquisition of high-level resistance mechanisms, making these populations a “canary in the coal mine” for understanding how resistance and treatment failures can emerge. Enabler mutants identified thus far in central cellular pathways indicate commonalities for developing an enabler state suggest these findings will be broadly applicable in a cross-species manner. Our underlying hypothesis is that the collateral phenotypes of enabler genotypes can be identified and rationally targeted to optimize the treatment outcomes and prevent subsequent acquisition of high-level resistance. We plan on using a multifaceted approach to understand the genetic and mechanistic basis of enabler mutations. We will experimentally select for enabler mutations using continuously variable antibiotic exposures in both sensitive strains and those with defined enabler mutations. These antibiotic sensitive but tolerant populations will be used to model the impact of different enabler genotypes on the probability and genetic pathways to subsequent evolution of high-level antibiotic resistance, the role of these genotypes on horizontal transfer of resistance, and how enabler mutants impact antibiotic treatment failure in vivo. These enabler strains will be used to model how the respective genotypes, upon antibiotic exposure, affect key pathways such as bacterial stringent response, transcriptional signaling, and translational fidelity, and how this in turn leads to the production of enabler phenotypes. These lines of investigation will provide insight into whether different enabler genotypes have common mechanistic underpinnings. We also plan to examine if rational targeting of enablers could provide therapeutic benefit to either stop the spread of resistance or improve antibiotic efficacy when enabler mutants are present. Enabler mutations are often associated with collateral consequences that confer sensitivity or resistance to metabolic of chemical stresses. We will determine the possibility of exploiting these cross-sensitivities by both targeted and unbiased chemical screening approaches. These synergies will then be investigated for their capacity to prevent emergence of enabler mutants as well as their capacity to more effectively treat infections caused by enabler strains recalcitrant to antibiotic therapy. The successful completion of these aims will provide a genetic basis and mechanistic insight into transient cell-states conferring enabler phenotypes. We anticipate these findings will be applicable across multiple bacterial species given the likelihood of conserved mechanisms underlying enablers and may provide additional strategies to prevent antibiotic treatment failure during bacterial infection.