摘要

尽管我们对理解抗生素耐药性的持续改进，抗性突变的自然选择与环境之间的相互作用仍不清楚。为了研究细菌代谢在抑制抗生素耐药性进化中的作用，我们将在糖酵解或糖异生碳源上生长的大肠杆菌进化为三种不同抗生素的选择压力。对190个进化群体中超过500种细胞内和细胞外推定代谢物进行分析表明，碳和能量代谢强烈地限制了进化轨迹，无论是在速度和阻力获取模式方面。为了解释和探索代谢组变化的空间，我们使用影子价格的概念开发了一种新颖的基于约束的建模方法。该分析与抗性群体的基因组重测序一起，鉴定了抗生素抗性的条件依赖性代偿机制，例如在外排泵的过表达时从呼吸代谢转变为葡萄糖的发酵代谢。此外，基于代谢组学的预测揭示了耐药菌株出现的弱点，例如氨苄西林耐药菌株对磷霉素过敏。总体而言，在抗生素驱动的进化轨迹中解决代谢适应问题为抗击新兴抗生素抵抗打开了新的视角。

Despite our continuous improvement in understanding antibiotic resistance, the interplay between natural selection of resistance mutations and the environment remains unclear. To investigate the role of bacterial metabolism in constraining the evolution of antibiotic resistance, we evolved Escherichia coli growing on glycolytic or gluconeogenic carbon sources to the selective pressure of three different antibiotics. Profiling more than 500 intracellular and extracellular putative metabolites in 190 evolved populations revealed that carbon and energy metabolism strongly constrained the evolutionary trajectories, both in terms of speed and mode of resistance acquisition. To interpret and explore the space of metabolome changes, we developed a novel constraint‐based modeling approach using the concept of shadow prices. This analysis, together with genome resequencing of resistant populations, identified condition‐dependent compensatory mechanisms of antibiotic resistance, such as the shift from respiratory to fermentative metabolism of glucose upon overexpression of efflux pumps. Moreover, metabolome‐based predictions revealed emerging weaknesses in resistant strains, such as the hypersensitivity to fosfomycin of ampicillin‐resistant strains. Overall, resolving metabolic adaptation throughout antibiotic‐driven evolutionary trajectories opens new perspectives in the fight against emerging antibiotic resistance.

http://msb.embopress.org/content/13/3/917