论文标题
预测抗生素耐药性演化的轨迹和机制
Predicting trajectories and mechanisms of antibiotic resistance evolution
论文作者
论文摘要
细菌通过多种机制进化对抗生素的抗性。一个中心但未解决的问题是抗性演化如何影响不同药物水平的细胞生长。在这里，我们开发了一个适应性模型，该模型可以通过其对细胞代谢的影响来预测公共抗性突变体的生长速率。我们绘制在无药物环境和药物挑战下抗性突变的代谢作用；由此产生的健身折衷定义了抗药性演变的帕累托表面。我们预测剂量依赖性生长速率和耐药水平的进化轨迹，以及根据药物和营养水平的普遍抗性机制。这些预测通过经验生长曲线和大肠杆菌种群的基因组数据证实。我们的结果表明，通过耦合主要代谢途径的抗性演化与微生物种群的系统生物学和生态学密切相关。
Bacteria evolve resistance to antibiotics by a multitude of mechanisms. A central, yet unsolved question is how resistance evolution affects cell growth at different drug levels. Here we develop a fitness model that predicts growth rates of common resistance mutants from their effects on cell metabolism. We map metabolic effects of resistance mutations in drug-free environments and under drug challenge; the resulting fitness trade-off defines a Pareto surface of resistance evolution. We predict evolutionary trajectories of dosage-dependent growth rates and resistance levels, as well as the prevalent resistance mechanism depending on drug and nutrient levels. These predictions are confirmed by empirical growth curves and genomic data of E. coli populations. Our results show that resistance evolution, by coupling major metabolic pathways, is strongly intertwined with systems biology and ecology of microbial populations.
