Evolutionary dynamics of combinational antimicrobial treatments

联合抗菌药物治疗的进化动力学 摘要 由于过度处方和滥用，抗生素因出现而失去效力。 以及抗药性细菌的迅速崛起。不同类型的抗生素，β-内酰胺类 自发现青霉素以来，已被开出用于治疗大多数感染的处方。 从那时起，细菌对β-内酰胺类抗生素的耐药性，由其产生的延长 产超广谱β-内酰胺酶(β-lacamase，ESBL)已成为一种普遍存在的酶。使用β-内酰胺酶 (血乳酸)抑制剂可以恢复β-内酰胺类药物对耐药细菌的疗效，这是一种策略 这对于在面临投资下降的情况下保护现有的抗生素是必要的 新的抗生素。然而，联合处理对β-内酰胺类药物选择的影响 抵抗并没有得到很好的理解。由于BLA生产既有利于抗性细胞又有利于 生长有利的敏感细胞，这些好处可能受到不同的影响 BLA抑制剂的引入，导致了非直观的进化动力学。我们的 初步工作表明，联合治疗的进化影响取决于 关于三个菌株特有的因素：产生细胞对 在单个细胞水平上的抗生素，抑制剂可以抑制这种作用的程度 抵抗，以及BLA生产的负担。特别是，对于提供 更大程度的私人利益(对于生产细胞)，组合处理可以 基本上选择具有抗性的部分。然而，对于主要用作 作为一种公共利益，联合治疗将非常有效地选择 耐药细胞。我们提议的研究将深入研究这些进化动态。 采用数学建模和定量实验相结合的方法。特别是， 我们将使用工程菌作为良好控制的模型系统来测试预测 进化动力学。然后，我们将使用以下方法来检验预测的进化动力学 由耐药病原体和敏感细菌组成的微生物群落。 从拟议的工作中学到的见解对指导有效的 联合治疗耐β-内酰胺类细菌病原体。

Evolutionary dynamics of combinational antimicrobial treatments Abstract Due to over-prescription and misuse, antibiotics are losing their efficacy due to emergence and rapid rise of antibiotic-resistant bacteria. Of different types of antibiotics, β-lactams have been prescribed to treat the majority of infections since the discovery of penicillin. Since then, bacterial resistance to β-lactams, mediated by the production of extended spectrum β-lactamase (ESBL) enzymes, has become widespread. Using β-lactamase (Bla) inhibitors can restore the efficacy of β-lactams against resistant bacteria, a strategy which is necessary to preserve existing antibiotics in the face of declining investment in new antibiotics. However, the effect of combination treatment on selection for β-lactam resistance is not well understood. Since Bla production benefits both resistant cells and growth-advantaged sensitive cells, and these benefits may be differentially impacted by the introduction of Bla inhibitor, leading to non-intuitive evolutionary dynamics. Our preliminary work suggests that the evolutionary impact of combination treatment depends on three strain-specific factors: the extent to which producing cells are resistant to the antibiotic at the individual cell level, the extent to which the inhibitor can suppress this resistance, and the burden of Bla production. In particular, for Bla variants that offer a greater degree of private benefit (for the producing cells), the combination treatment can substantially select for the resistant fraction. However, for variants that primarily serve as a public good, the combination treatment will be highly effective in selecting against the resistant cells. Our proposed research will examine these evolutionary dynamics in depth using a combination of mathematical modeling and quantitative experiments. In particular, we will use engineered bacteria as well-controlled model systems to test the predicted evolutionary dynamics. Then, we will test the predicted evolutionary dynamics by using microbial communities consisting of both resistant pathogens and sensitive bacteria. Insights learned from the proposed work have implications for guiding effective design of combination treatments against β-lactam-resistant bacterial pathogens.