Project 1: Mechanisms, Dynamics, and Prediction of Heteroresistance

摘要 了解抗生素耐药性机制对于设计新的方法和治疗方法至关重要， 对抗抗药性细菌。异源耐药性（HR）是一种细菌表型，其中分离物含有一种或多种抗生素。 与主要群体相比，显示抗生素抗性显著增加的细胞亚群。 许多种类的细菌和几乎所有种类的抗生素都表现出这种形式的表型抗性， 是来自体外实验、数学建模、动物感染模型和临床研究的证据， 耐药亚群可在抗生素暴露期间富集并导致治疗失败。最近的研究 表明HR中的耐药表型在大多数情况下是不稳定的，并且在没有抗生素的情况下 压力会迅速恢复敏感性。不稳定的一个主要原因是遗传学的发生， 不稳定的串联基因扩增的不同类型的基因，可以导致电阻时，存在于一个 增加的拷贝数（例如，真正的抗性基因通常以低水平表达，外排 泵）。由于其不稳定性、低频特性和瞬态特性，对其进行检测和研究具有挑战性 在临床微生物学环境中，这通常导致难以明确分类 细菌敏感或耐药，这可能导致潜在的治疗失败。为了促进改善 治疗和检测HR感染，我们需要详细了解其潜在机制， 抗性亚种群形成的动力学，维持并退回到其基线 频率在没有抗生素的情况下。具体来说，我们会问：什么是关键的遗传，生理和 控制抗性亚群产生的环境过程和信号， 我们是否以及如何修改和干预它们。为了解决这些问题，我们将使用临床分离的 肠杆菌科（E. coli、克雷伯氏菌（K. pneumoniae和Enterobacter spp）和A.鲍曼不动杆菌。 在一个基本的水平上，这项工作将大大拓宽我们的理解（i）如何表现出的特质，由一个 细胞亚群的产生，并可以影响行为和细菌种群的进化，（ii）如何 HR由CNV产生，（iii）CNV的机制和动力学以及（iv）如何从CNV预测HR 全基因组测序数据。从长远来看，这将为我们提供更好的工具来识别人力资源， 其在临床环境中的作用，从而改善抗生素治疗结果。

ABSTRACT Understanding antibiotic resistance mechanisms is critical to designing novel approaches and therapeutics to combat resistant bacteria. Heteroresistance (HR) is a bacterial phenotype in which an isolate contains a subpopulation of cells that show a substantial increase in antibiotic resistance compared to the main population. Many species of bacteria and nearly all classes of antibiotics exhibit this form of phenotypic resistance and there is evidence from in vitro experiments, mathematical modeling, animal infection models and clinical studies that the resistant subpopulations can enrich during antibiotic exposure and lead to treatment failure. Recent studies show that the resistance phenotype in HR is in the majority of cases unstable and in the absence of antibiotic pressure it rapidly reverts to susceptibility. One major reason for the instability is the occurrence of genetically unstable tandem gene amplifications of different types of genes that can cause resistance when present at an increased copy number (e.g., bona fide resistance genes that are normally expressed at low levels, efflux pumps). Due to the instability, low frequency and transient character, it is challenging to detect and study these subpopulations and in a clinical microbiology setting this often leads to difficulties in unambiguously classifying bacteria as susceptible or resistant, which can lead to potential treatment failures. To facilitate the improved treatment and detection of HR infections, we need to understand in detail the underlying mechanisms and dynamics by which the resistant sub-populations form, are maintained and recede back to their baseline frequency in the absence of antibiotic. Specifically, we will ask: what are the key genetic, physiological and environmental processes and signals that govern the generation of resistant sub-populations and subsequently, if and how we may modify and interfere with them. To address these questions, we will use clinical isolates of Enterobacteriaceae (E. coli, K. pneumoniae and Enterobacter spp) and A. baumannii. At a basic level, this work will significantly broaden our understanding of (i) how traits exhibited by a subpopulation of cells is generated and can influence behavior and evolution of bacterial populations, (ii) how HR is generated by CNV, (iii) the mechanisms and dynamics of CNV and (iv) how HR may be predicted from whole genome sequencing data. This will, in the long-term, provide us with better tools to identify HR and mitigate its effects in clinical settings and, thereby, improve antibiotic treatment outcome.