Antibiotic combinations are considered a relevant strategy to tackle the global antibiotic resistance crisis since they are believed to increase treatment efficacy and reduce resistance evolution (World Health Organization and Global Tuberculosis Programme, 2016). However, studies of the evolution of bacterial resistance to combination therapy have focused on a limited number of drugs and have provided contradictory results (Hegreness et al., 2008; Lipsitch and Levin, 1997; Munck et al., 2014). To address this gap in our understanding, we performed a large-scale laboratory evolution experiment, adapting 8 replicate lineages of Escherichia coli to a diverse set of 22 different antibiotics and 33 antibiotic pairs. We found that combination therapy significantly limits the evolution of de novo resistance in E. coli, yet different drug combinations vary substantially in their propensity to select for resistance. In contrast to current theories, the phenotypic features of drug pairs are weak predictors of resistance evolution. Instead, the resistance evolution is driven by the relationship between the evolutionary trajectories that lead to resistance to a drug combination and those that lead to resistance to the component drugs. Drug combinations requiring a novel genetic response from target bacteria compared to the individual component drugs significantly reduce resistance evolution. These data support combination therapy as a treatment option to decelerate resistance evolution and provide a novel framework for selecting optimized drug combinations based on bacterial evolutionary responses.

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对组成抗生素的进化反应的相容性驱动对药物对的耐药性进化

抗生素组合被认为是解决全球抗生素耐药性危机的相关策略，因为据信它们可以提高治疗效果并减少耐药性演变（世界卫生组织和全球结核病规划，2016年）。然而，关于细菌对联合疗法耐药性演变的研究集中在有限的药物上，并提供了相互矛盾的结果（Hegreness等，2008； Lipsitch和Levin，1997； Munck等，2014）。为了解决我们理解中的这一空白，我们进行了一项大规模的实验室进化实验，将8个重复的大肠杆菌谱系适应22种不同的抗生素和33种抗生素对的多样化组合。我们发现联合疗法显着限制了从头发展大肠杆菌的耐药性，但不同的药物组合选择耐药性的倾向却有很大差异。与当前的理论相反，药物对的表型特征是耐药性进化的弱预测因子。相反，耐药性进化是由导致对药物组合产生耐药性的进化轨迹与导致对组分药物产生耐药性的进化轨迹之间的关系驱动的。与单个成分药物相比，要求靶细菌具有新的遗传反应的药物组合显着降低了耐药性的演变。这些数据支持联合疗法作为降低耐药性演变的一种治疗选择，并为基于细菌进化反应选择优化药物组合提供了新的框架。