Krajewska Joanna, Tyski Stefan, Laudy Agnieszka E
Department of Environmental Health and Safety, National Institute of Public Health NIH-National Research Institute, 00-791 Warsaw, Poland.
Department of Pharmaceutical Microbiology and Laboratory Diagnostic, National Medicines Institute, 00-725 Warsaw, Poland.
Pharmaceuticals (Basel). 2024 Aug 15;17(8):1068. doi: 10.3390/ph17081068.
Despite the urgent need for new antibiotics, very few innovative antibiotics have recently entered clinics or clinical trials. To provide a constant supply of new drug candidates optimized in terms of their potential to select for resistance in natural settings, in vitro resistance-predicting studies need to be improved and scaled up. In this review, the following in vitro parameters are presented: frequency of spontaneous mutant selection (FSMS), mutant prevention concentration (MPC), dominant mutant prevention concentration (MPC-D), inferior-mutant prevention concentration (MPC-F), and minimal selective concentration (MSC). The utility of various adaptive laboratory evolution (ALE) approaches (serial transfer, continuous culture, and evolution in spatiotemporal microenvironments) for comparing hits in terms of the level and time required for multistep resistance to emerge is discussed. We also consider how the hit-to-lead stage can benefit from high-throughput ALE setups based on robotic workstations, do-it-yourself (DIY) continuous cultivation systems, microbial evolution and growth arena (MEGA) plates, soft agar gradient evolution (SAGE) plates, microfluidic chips, or microdroplet technology. Finally, approaches for evaluating the fitness of in vitro-generated resistant mutants are presented. This review aims to draw attention to newly emerged ideas on how to improve the in vitro forecasting of the potential of compounds to select for resistance in natural settings.
尽管迫切需要新型抗生素，但最近进入临床或临床试验的创新抗生素却非常少。为了持续提供在自然环境中选择耐药性潜力方面经过优化的新候选药物，体外耐药性预测研究需要改进并扩大规模。在这篇综述中，介绍了以下体外参数：自发突变体选择频率（FSMS）、突变预防浓度（MPC）、优势突变预防浓度（MPC-D）、劣势突变预防浓度（MPC-F）和最小选择浓度（MSC）。讨论了各种适应性实验室进化（ALE）方法（连续传代、连续培养以及在时空微环境中的进化）在比较命中物在多步耐药性出现的水平和时间方面的效用。我们还考虑了从基于机器人工作站、自行搭建（DIY）连续培养系统、微生物进化与生长平台（MEGA）平板、软琼脂梯度进化（SAGE）平板、微流控芯片或微滴技术的高通量ALE设置中，命中物到先导物阶段如何能从中受益。最后，介绍了评估体外产生的耐药突变体适应性的方法。这篇综述旨在引起人们对关于如何改进体外预测化合物在自然环境中选择耐药性潜力的新出现想法的关注。
