Evolutionary Tradeoffs in Antibiotic Resistance

当细菌中的突变导致先前抑制浓度的 变得可生存的化合物。通过突变的累积导致不同程度的增加 耐药性已经使许多容易治疗的感染变得几乎无法治愈，并正在部分蔓延。 从人类学的角度来看。抗性进化的经典模型，即抗性突变体在 抗生素使用的存在，因此在人群中传播到接近固定的状态，捕捉到抗生素的兴起 耐药性，但仔细观察并不能解释耐药性的几个关键特征。第一，抗生素 在临床人群中，耐药性很少达到固定；更重要的是，敏感性高于 种群遗传模型可以预测。其次，在中国，抗生素耐药性是存在的，而且可能很常见。 甚至在人类开始使用抗生素之前就已经发生了临床感染。第三，尽管广泛流行的是 在环境中产生抗生素的细菌，这些细菌仍然被敏感的 邻里。出于这些原因，我们假设现有的耐药性进化模型是不完整的，并且 尤其是在环境中存在着具有潜在抵抗力的进化因素 对耐药性演变的影响与人类使用抗生素的程度相似或更大。在这里，我们将 将模型系统中的进化实验与计算建模和数据库挖掘相结合 研究序列数据对抗性演化的制约作用，重点放在两个关键方面：空间作用 结构在抗性进化中的作用，以及包括噬菌体和寄生虫在内的自私遗传元件的作用 质粒。抗性为研究微生物进化提供了一个几乎理想的模型系统；适合度可以是 定义良好的、施加的选择性压力可以很容易地调整，并且可以自发地或通过 水平基因转移。我们希望揭开出现、传播和传播背后的进化机制 限制抗生素耐药性。

Antibiotic resistance emerges when a mutation in a bacterium causes a previously inhibitory concentration of a compound to become survivable. Through the accumulation of mutations conferring varying increases in resistance, already many easy-to-treat infections have become nearly incurable, and are spreading in part anthropogenically. The classical model of resistance evolution, that a resistant mutant has a fitness advantage in the presence of antibiotic use, and so spreads in the population to near-fixation, captures the rise of antibiotic resistance, but on closer inspection fails to explain several critical features of resistance. First, antibiotic resistance rarely reaches fixation in clinical populations; more importantly, sensitivity is higher than the population-genetic models would predict. Second, antibiotic resistance was present, and likely common, in clinical infections before the human use of antibiotics even began. Third, despite the widespread prevalence of antibiotic-producing bacteria in the environment, these same bacteria remain surrounded by sensitive neighbors. For these reasons, we hypothesize that the existing model of resistance evolution is incomplete, and in particular that there exist evolutionary factors in the environment which have a potentially countervailing effect on resistance evolution of similar or greater magnitude to the human use of antibiotics. Here, we will combine evolution experiments in model systems with computational modeling and database mining of sequence data to study the constraints on the evolution of resistance, focusing on two key areas: the role of spatial structure in the evolution of resistance, and the role of selfish genetic elements including phages and parasitic plasmids. Resistance provides an almost ideal model system for the study of microbial evolution; fitness can be well defined, imposed selective pressures can be readily tuned, and can emerge either spontaneously or by horizontal gene transfer. We expect to uncover the evolutionary mechanisms behind the emergence, spread, and limitation of antibiotic resistance.