Department of Medical Biochemistry and Microbiology, Uppsala University, 751 23 Uppsala, Sweden; email:
Annu Rev Microbiol. 2017 Sep 8;71:579-596. doi: 10.1146/annurev-micro-090816-093813. Epub 2017 Jul 11.
The ability to predict the evolutionary trajectories of antibiotic resistance would be of great value in tailoring dosing regimens of antibiotics so as to maximize the duration of their usefulness. Useful prediction of resistance evolution requires information about (a) the mutation supply rate, (b) the level of resistance conferred by the resistance mechanism, (c) the fitness of the antibiotic-resistant mutant bacteria as a function of drug concentration, and (d) the strength of selective pressures. In addition, processes including epistatic interactions and compensatory evolution, coselection of drug resistances, and population bottlenecks and clonal interference can strongly influence resistance evolution and thereby complicate attempts at prediction. Currently, the very limited quantitative data on most of these parameters severely limit attempts to accurately predict trajectories of resistance evolution.
预测抗生素耐药性的进化轨迹将极大地有助于调整抗生素的剂量方案，从而最大限度地延长其使用期限。耐药性进化的有用预测需要有关以下方面的信息：（a）突变供应率；（b）耐药机制赋予的耐药水平；（c）抗生素耐药突变细菌在药物浓度下的适应性；以及（d）选择压力的强度。此外，包括上位性相互作用和补偿性进化、药物耐药性的共选择、种群瓶颈和克隆干扰在内的过程可以强烈影响耐药性的进化，从而使预测变得复杂。目前，这些参数中的大多数都非常有限的定量数据严重限制了准确预测耐药性进化轨迹的尝试。
