Aminoglycoside-Enabled Elucidation of Persister Metabolism

描述（由申请人提供）：细菌持久性耐抗生素治疗，并且是生物膜感染复发倾向的基础。对持久性生理学的进一步了解将导致开发出更有效的治疗方法来对抗利用生物膜的病原体，如大肠杆菌、铜绿假单胞菌和金黄色葡萄球菌。持续性代谢尤其重要，因为它影响抗生素耐受状态的进入、维持和退出。不幸的是，持久者是一个小的，短暂的亚群，其生理很容易被更丰富的表型（例如，有活力但不可培养的细胞（vbnc））所掩盖。最近的证据表明，目前的持久体分离技术提供的样本中vbnc比持久体多得多。如果没有改进的分离技术，vbnc和持久体之间的区别特征，即在标准培养基上的恢复生长，就必须用来描述持久体的生理特征。在这里，我们建议开发一种方法来阐明持久性的代谢能力从生存数据，从而绕过目前的分离困难。最近的研究表明，持久性生物可以分解碳源，保持非复制性，但对氨基糖苷敏感。在这里，我们建议利用这一现象来绘制持久性代谢能力的图表。为了实现这一目标，我们将开发一种快速的AG增强试验，开发一种计算方法来分析由此产生的存活数据并指导进一步的实验，最后，通过绘制三个持久性种群的代谢能力来证明我们方法的实用性。为了开发一种快速的AG增强实验，我们将使用表型阵列（每个孔包含不同的营养物质）同时测量AG增强和数百种不同营养物质的必要对照。为了分析由此产生的生存数据，我们将使用混合整数线性优化来生成能够解释数据的非冗余最小代谢途径的集合。这些途径将聚集在一起，在竞争集群之间最明显的区别反应将被实验干扰，以确定持久性的代谢能力。为了证明我们的方法的实用性，我们将使用我们的技术来研究代谢能力

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. Persister metabolism is of particular importance, as it influences entry into, maintenance of, and exit from this antibiotic-tolerant state. Unfortunately, persisters are a minor, transient subpopulation whose physiology is easily obscured by more abundant phenotypes (e.g., viable but non-culturable cells (VBNCs)). Recent evidence suggests that current persister isolation techniques provide samples with many more VBNCs than persisters. Without improved isolation techniques, the distinguishing feature between VBNCs and persisters, growth- resumption on standard media, must be used to characterize persister physiology. Here we propose to develop a method to elucidate the metabolic abilities of persisters from survival data, and thus circumvent the present isolation difficulties. Recent work has demonstrated that persisters can catabolize carbon sources, remain non-replicative, and yet become susceptible to aminoglycosides. Here we propose to harness this phenomenon to chart the metabolic capabilities of persisters. To accomplish this goal, we will develop a rapid AG potentiation assay, develop a computational approach to analyze the resulting survival data and direct further experimentation, and finally, demonstrate the utility of our approach by charting the metabolic abilities of three persister populations. To develop a rapid AG potentiation assay, we will use phenotype arrays (each well contains a different nutrient) to simultaneously measure AG potentiation and the necessary controls from hundreds of separate nutrients. To analyze the resulting survival data, we will use mixed integer linear optimization to generate an ensemble of non-redundant minimal metabolic pathways capable of explaining the data. These pathways will be clustered, and the reactions that most significantly discriminate between competing clusters will be experimentally perturbed to determine the metabolic capabilities of persisters. To demonstrate the utility of our approach, we will use our technique to study the metabolic abilities of three persister populations: exponential phase persisters tolerant to ofloxacin, exponential phase persisters tolerant to ampicillin, and stationary persisters tolerant to ofloxacin. Results from this proposal will fill fundamental knowledge gaps in persister metabolism, identify new avenues for therapeutic intervention through disruption of persister maintenance or enhancement of persister awakening, and impact the fields of network biology, microbiology, and infectious disease.