Using strain history to improve prediction of the evolution of antimicrobial resistance in Acinetobacter baumannii

项目总结 这一建议的目的是为了更全面地了解进化的影响 历史对进化的可预测性的影响。理解进化的可预测性和可重复性一直是 这是进化生物学家的目标。将这些问题应用到抗菌素耐药性(AMR)领域提供了 在研究基础问题的同时获得临床相关结果的好处 进化生物学。AMR是一个迅速恶化的全球健康问题，随着细菌数量的增加 感染变得不可能用大多数药物治疗。令人严重关注的是鲍曼不动杆菌，一种 医院内和高度耐多药(MDR)病原菌。尽管抵抗通常是通过 常见的途径，如药物外排增加和药物靶点的修饰，目前仍不清楚 进化历史影响AMR的进化，耐药进化到什么程度或水平是可以预测的。 病史(如遗传相关和以前接触抗生素)是一个被低估的方面， 影响进化，并可能对基因组产生持久的影响，从而改变或限制可用于 对抗生素压力的适应。 为了解决这些知识上的差距，我们建议使用先前存在的鲍曼不动杆菌临床集合。 分离株。这项建议的第一个目标是了解基因和表型的差异 这些菌株，特别关注毒力和抗药性。通过比较基因组学，我们将识别 序列相似性以及泛基因组组成。我们将使用已知的抗药性原因，从 之前库珀实验室和其他实验室的研究，创建了一个基于基因组的多基因座耐药性预测因子 表型。我们将把比较基因组学分析与生物膜表型分析结果结合起来。 形成、在不同条件下的生长和持久性，以评估任何系统发育表型模式。我们 将通过分子工程验证选定的基因-表型关联，帮助分离基因- 鲍曼不动杆菌表型图谱。第二个拟议目标将进一步加深我们对 抗性进化的可预测性。我们将在核糖体的存在下进化出20个临床分离株- 靶向药物替吉环素，并监测相应的耐药性倍数增加，并预测 初始阻力水平将决定最终的进化阻力水平。通过整个种群、整个基因组 通过测序，我们将能够评估耐药进化发生在基因上的可预测性水平。 该项目的完成不仅将为广泛的进化问题提供答案，而且还将 对抗抗菌素耐药性危机的关键一步。我们将得出结论，说明在什么程度上 AMR在机制上是可预测的。更好地理解可预测性将具有直接的临床意义。 并为治疗和预防MDR感染提供个性化的治疗策略。

PROJECT SUMMARY The objective of this proposal is to gain a more complete understanding of the influence of evolutionary history on the predictability of evolution. Understanding predictability and repeatability of evolution has long been a goal of evolutionary biologists. Applying these questions to the field of antimicrobial resistance (AMR) provides the benefit of obtaining clinically relevant results while also studying questions that are fundamental to evolutionary biology. AMR is a rapidly worsening global health issue, with an increasing number of bacterial infections becoming impossible to treat with most drugs. Of serious concern is Acinetobacter baumannii, a nosocomial and highly multidrug resistant (MDR) pathogen. Although resistance is often attained through common pathways, such as increased drug efflux and modifications to the drug target, it remains unclear how evolutionary history affects the evolution of AMR, and to what degree or level resistance evolution is predictable. History (such as genetic relatedness and previous antibiotic exposure) is an underappreciated aspect that influences evolution and can have lasting effects on the genome that alter or constrain paths available for adaptation to antibiotic stress. To address these gaps in knowledge, we propose to use a preexisting collection of A. baumannii clinical isolates. The first aim of this proposal focuses on understanding the genetic and phenotypic differences within these isolates, with special focus on virulence and resistance. Through comparative genomics we will identify sequence similarity as well as pan-genome composition. We will use known causes of resistance, compiled from previous studies in the Cooper Lab and others, to create a genome based multi-locus predictor of resistance phenotypes. We will combine the comparative genomics analysis with results of phenotypic assays for biofilm formation, growth in different conditions, and persistence, to assess any phylogenetic phenotypic patterns. We will verify select gene-phenotype associations through molecular engineering, helping to detangle the genotype- phenotype map of A. baumannii. The second proposed aim will further enhance our knowledge regarding the predictability of resistance evolvability. We will evolve 20 clinical isolates in the presence of the ribosome- targeting drug, tigecycline, and monitor the corresponding fold increase of resistance, with the prediction that initial resistance level will dictate final evolved resistance level. Through whole population, whole genome sequencing, we will be able to assess the level of predictability to which resistance evolution occurs genetically. Completion of this project will not only provide answers to broad evolutionary questions but will also be a crucial step in the fight against the antimicrobial resistance crisis. We will make conclusions as to what level AMR is predictable mechanistically. A greater understanding of predictability will have direct clinical importance and allow for personalized therapeutic strategies for the treatment and prevention of MDR infections.