Post-antibiotic effect and design of optimal antibiotic dosing protocols

抗生素后效应和最佳抗生素给药方案的设计

• 批准号: 9239349
• 负责人: LINGCHONG YOU
• 金额: $ 29.3万
• 依托单位: DUKE UNIVERSITY
• 依托单位国家: 美国
• 财政年份: 2011
• 资助国家: 美国
• 起止时间: 2011-09-15 至 2021-01-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/9239349
• 关键词: Accounting; Address; Age; Antibiotic Resistance; Antibiotic Therapy; Antibiotics; Bacteria; Bacterial Infections; Binding; Cells; Clinical; Computer Simulation; Darkness; Data; Development; Dose; Escherichia coli; Evaluation; Foundations; Future; Generations; Genetic; Growth; Individual; Kinetics; Literature; Measurement; Measures; Mediating; Medical; Methods; Microbe; Microbiology; Microfluidics; Modeling; Molecular; Pharmaceutical Preparations; Pharmacotherapy; Population; Population Dynamics; Prevalence; Process; Protocols documentation; Public Health; Recovery; Reporting; Research; Resistance; Testing; Time; Treatment Efficacy; Treatment Protocols; Work; bacterial resistance; base; combat; design; effective therapy; efficacy testing; efflux pump; high throughput screening; insight; microbiota; misuse of prescription only drugs; novel therapeutics; pathogen; pressure; response; therapy design; treatment strategy; uptake

Abstract Antibiotics have been considered the single most significant medical discovery of the 20th century. Due to decades of over-prescription and misuse, however, antibiotics are losing their efficacy due to the emergence and rapid rise of antibiotic-resistant bacteria. To combat this imminent threat, in addition to developing new drugs, it is equally critical to develop strategies that enable more effective use of existing antibiotics. Doing so requires a mechanistic understanding of both short-term and long-term bacterial population dynamics in response to antibiotic treatment. An intriguing phenomenon that arises from antibiotic treatment is the post-antibiotic effect (PAE) – after transient treatment, the growth of a bacterial population is often temporarily suppressed even after the antibiotic is removed. This phenomenon was first described in the 1940s and has since been reported in the majority of, but not all, antibiotics. Despite the prevalence of PAE, however, the underlying mechanisms are poorly understood. The objective of our proposed research is to elucidate the molecular mechanism underlying generation of PAE and, based on this understanding, to design effective antibiotic treatment protocols. In our preliminary work, we measured PAE arising from treatment of E. coli with several well-characterized antibiotics. Based on these measurements and the literature data, we hypothesized that PAE can be explained by the uptake and export kinetics of antibiotics by cells. Our proposed research will examine this hypothesis and its alternatives in depth and breadth. Moreover, we will use computation modeling to design and experimentally test antibiotic protocols to exploit PAE. In particular, we aim to design treatment protocols that achieve similar treatment efficacy while using minimal amounts of drugs. Such protocols will reduce perturbation to the native microbiota and exert less selection pressure that can drive emergence and spread of antibiotic resistance.

摘要 抗生素被认为是人类历史上最重要的医学发现。 世纪。然而，由于几十年来的过度处方和滥用，抗生素 由于抗药性细菌的出现和迅速增加而失去其功效。 要对抗这一迫在眉睫的威胁，除了研发新药，同样至关重要的是 制定策略，使现有的抗生素得到更有效的利用。这样做 需要对短期和长期细菌感染的机制性理解， 对抗生素治疗反应的种群动态。一个有趣的现象， 抗生素治疗引起的是抗生素后效应（PAE）-在短暂的 治疗后，细菌种群的生长通常会暂时受到抑制，即使在治疗后， 去除抗生素。这一现象在20世纪40年代首次被描述， 在大多数但不是所有的抗生素中都有报道。尽管流行的 然而，PAE的潜在机制知之甚少。我们的目标 拟议的研究是阐明潜在的分子机制， 并在此基础上设计有效的抗生素 治疗方案。在我们的初步工作中，我们测量了治疗引起的PAE， 大肠大肠杆菌与几种特征良好的抗生素。根据这些测量结果， 根据文献数据，我们假设PAE可以通过摄取和 抗生素通过细胞的输出动力学。我们的研究计划将研究这一点 假设和它的替代品的深度和广度。此外，我们将使用计算 建模，以设计和实验测试抗生素协议，以利用PAE。在 特别是，我们的目标是设计治疗方案，实现类似的治疗效果 同时使用最少量的药物。这样的协议将减少干扰， 原生微生物群，并施加较少的选择压力，可以推动出现， 抗生素耐药性的传播。