Exploring Persister Antibiotic Responses as a Source of Biomarkers and Elimination Strategies

 描述(由申请人提供)：细菌持续者耐受抗生素治疗，并导致生物膜感染复发的倾向。对持续生理学的了解将导致开发更有效的治疗方法来对抗利用生物被膜的病原体，如大肠埃希菌、铜绿假单胞菌和金黄色葡萄球菌。在我们对持久者的理解中，一个关键的知识鸿沟是他们对抗生素的机械性反应。我们还不知道持久者是如何管理抗生素压力的，也不知道这些过程的哪些方面需要他们的耐受性。这种知识的缺乏很大程度上源于与测量外周生理学相关的困难。因此，荧光激活细胞分选技术(FACS)已成为量化持久生理学的最佳技术。我们假设，持续型抗生素反应的知识以及它们与死亡细胞的反应如何比较，可以用于了解持续型生存和识别持续型生物标志物。持续者和濒临死亡的细胞的抗生素反应之间的异同将提供关于持续者如何避免杀戮的知识，此外，这些差异将构成潜在的生物标志物。为了验证我们的假设，我们将比较持久者和死亡细胞的转录反应，并识别有助于持久耐受性和/或可以作为持久生物标记物的特征。为此，我们将测量死于抗生素的大肠杆菌的时程mRNA，并利用网络成分分析确定介导基因表达变化的调控因子。这些“死亡反应”将被用来选择启动子在持续者中进行分析，因为FACS对持久生理学的量化是时间和劳动力密集型的。选定的启动子将被荧光标记，并通过分类、持久性分析和统计方法进行研究，以量化和比较濒临死亡的细胞的持久反应。将确定相似和不同之处，并通过在启动子和调控水平上的反应的基因重连来测试它们对持久耐受性的影响。这项建议的结果将填补关于持续者核心特征的基本知识空白，确定改善的持续者浓缩的生物标记物，通过扰乱持久抗生素应激管理，阐明治疗干预的新途径，并影响抗生素耐受性、微生物学和传染病领域。

 DESCRIPTION (provided by applicant): Bacterial persisters tolerate antibiotic treatment, and underlie the propensity of biofilm infections to relapse. An improved understanding of persister physiology will lead to the development of more effective therapies against biofilm-utilizing pathogens such as Escherichia coli, Pseudomonas aeruginosa, and Staphylococcus aureus. A critical knowledge gap in our understanding of persisters is their mechanistic response toward antibiotics. We do not yet know how persisters manage antibiotic stress or what aspects of these processes are required for their tolerances. This lack of knowledge largely originates from difficulties associated with measuring persister physiology. Persisters have yet to be isolated, and therefore, fluorescence activated cell sorting (FACS) has become the best technique to quantify persister physiology. We hypothesize that knowledge of persister antibiotic responses and how they compare to those of cells that die can be used to understand persister survival and identify persister biomarkers. Similarities and differences between the antibiotic responses of persisters and dying cells will provide knowledge of how persisters avoid killing, and in addition, the differences will constitute potential biomarkers. To test our hypothesis, we will compare the transcriptional responses of persisters to those of cells that die, and identify features that contribute to persister tolerances and/or can serve as persister biomarkers. To do this, we will measure time-course mRNA from Escherichia coli dying from antibiotics and identify the regulators mediating gene expression changes with Network Component Analysis. These "death responses" will be used to select promoters for analysis in persisters, because FACS quantification of persister physiology is time- and labor-intensive. Selected promoters will be fluorescently-labelled and studied with sorting, persistence assays, and statistical methods to quantify and compare persister responses to those of dying cells. Similarities and differences will be identified, and both tested for their impacts on persister tolerances through genetic rewiring of the responses at both the promoter and regulatory levels. Results from this proposal will fill fundamental knowledge gaps about the core characteristic of persisters, identify improved biomarkers for persister enrichment, illuminate new avenues for therapeutic intervention through disruption of persister antibiotic stress management, and impact the fields of antibiotic tolerance, microbiology, and infectious disease.