Attacking failure of antibiotic treatment by targeting antimicrobial resistance enabler cell-states

总结 耐药性的快速演变迅速规避了新抗菌剂的部署， 迫切需要制定新的战略，以便在与细菌病原体的军备竞赛中保持领先地位。开发一 详细了解抗生素使用的情况以及遗传和机制基础 抵抗的发展为先发制人地破坏这一进程提供了机会。而感染由 携带抗微生物剂抗性（AMR）基因的生物体是抗生素治疗失败（ATF）的主要原因， 当病原体不是传统药敏试验确定的AMR时，常发生ATF。它正在成为 越来越多的人认识到，细胞的瞬时状态，如耐受性、持久性和异质抗性是至关重要的 导致治疗失败的驱动因素。然而，关于遗传和基因的数据很少， 这些细胞状态的机制基础以及缺乏诊断检测方法。ATF细胞状态 最初作为少数变异体存在于群体中，并显示出瞬时表型， 压力减弱，使得它们难以检测，从而在当前的诊断测定中被遗漏。 这些使能细胞状态在机制上仍然知之甚少，似乎优先出现在 波动的治疗方案，例如由药物的PK/PD特征引起的，由此ATF细胞状态 可以在抗生素压力减弱后促使（易感）细菌感染重新出现。重要的是， 这就创造了机会，多步高水平耐药突变被给予了延长的机会， 出现。因此，由于抗生素耐药变异体往往紧跟着抗生素耐药的发生， ATF细胞状态，这些细胞状态可以被视为抗生素治疗失败和AMR的促成因素。这 一项提案的重点是解开ATF细胞状态在抗生素出现中的重要性 耐药性和治疗失败，并设计新的方法和战略，以确定，跟踪和目标 他们主要团队由4名主要研究人员组成，他们有着非常成功的合作历史。 他们将共同致力于分布在3个项目中的5个挑战，并由一个行政和一个 基因组学和生物信息学核心。在挑战：1）可能的遗传途径的完整概况，可以诱导 确定ATF细胞状态; 2）确定驱动ATF细胞状态出现的治疗方案; 3)确定ATF细胞状态如何使AMR出现; 4）筛选药物和化合物 5）提出了一种计算反褶积方法 预测复杂细菌群体中ATF细胞状态的存在和频率。总的来说这 提案包含一系列概念和技术创新方面，旨在 了解耐药性产生的根源是遗传机制和进化力量， 最终目标是设计新的诊断和抗菌策略，可以减缓甚至阻止 目前无休止的军备竞赛“需要我们尽一切努力，保持在同一个地方”。

SUMMARY Deployment of new antimicrobials is promptly circumvented by the rapid evolution of resistance, underscoring the critical need for new strategies to stay ahead in the arms-race against bacterial pathogens. Developing a detailed understanding of the circumstances as well as genetic and mechanistic basis for which antibiotic resistance develops provides opportunities for pre-emptively subverting this process. While infections caused by organisms harboring antimicrobial resistance (AMR) genes are a major cause of antibiotic treatment failure (ATF), ATF frequently occurs when the etiological agents are not AMR by traditional susceptibility testing. It is becoming increasingly recognized that transient cell-states such as tolerance, persistence and hetero-resistance are critical drivers underlying treatment failure. However, there is a paucity of data with regards to the genetic and mechanistic basis for these cell-states as well as a lack of diagnostic-detection approaches. ATF cell-states initially exist as minority variants within a population and display a transient phenotype that tends to dissipate as the stress subsides, making them challenging to detect and consequently missed in current diagnostic assays. These enabler cell-states remain mechanistically poorly understood and seem to preferentially arise during fluctuating treatment regimens, for instance caused by a drug’s PK/PD characteristics, whereby ATF cell-states can drive the re-emergence of the (susceptible) bacterial infection after antibiotic pressure wanes. Importantly, this creates opportunities where multi-step high-level resistance mutations are given an extended opportunity to emerge. Therefore, because antibiotic resistant variants often follow closely on the heels of the occurrence of ATF cell-states, these cell-states can be viewed as enablers of antibiotic treatment failure and AMR. This proposal focuses on untangling the importance of ATF cell-states in the emergence of antibiotic resistance and treatment failure, and designs new approaches and strategies to identify, track and target them. The main team consists of 4 principal investigators that have a very successful collaboration history. Together they will work on 5 challenges distributed across 3 projects and supported by an administrative and a genomics and bioinformatics core. In Challenge: 1) the full profile of possible genetic pathways that can induce ATF cell-states is determined; 2) treatment regimens that drive the emergence of ATF-cell states are determined; 3) it is determined how ATF cell-states enable the emergence of AMR; 4) drugs and compounds are screened for, that target ATF cell-state collateral sensitivities; 5) a computational deconvolution approach is developed that predicts the presence and frequency of ATF cell-states in a complex bacterial population. Overall this proposal contains a collection of conceptually and technically innovative aspects that are geared towards understating the genetic mechanisms and evolutionary forces that sit at the root of the emergence of resistance, with the ultimate goal to design new diagnostics and antimicrobial strategies that can slow or even stop the current endless arms-race “that takes all the running we can do, to keep in the same place”.