Laboratory of Molecular Cell Biology, Department of Biology, KU Leuven, Leuven, Belgium.
Evolutionary Modelling Group, Department of Biology, KU Leuven, Leuven, Belgium.
Nat Microbiol. 2024 Nov;9(11):2954-2969. doi: 10.1038/s41564-024-01811-w. Epub 2024 Oct 29.
Antifungal drug resistance represents a serious global health threat, necessitating new treatment strategies. Here we investigated collateral sensitivity (CS), in which resistance to one drug increases sensitivity to another, and cross-resistance (XR), in which one drug resistance mechanism reduces susceptibility to multiple drugs, since CS and XR dynamics can guide treatment design to impede resistance development, but have not been systematically explored in pathogenic fungi. We used experimental evolution and mathematical modelling of Candida auris population dynamics during cyclic and combined drug exposures and found that especially CS-based drug cycling can effectively prevent the emergence of drug resistance. In addition, we found that a CS-based treatment switch can actively select against or eradicate resistant sub-populations, highlighting the potential to consider CS in therapeutic decision-making upon resistance detection. Furthermore, we show that some CS trends are robust among different strains and resistance mechanisms. Overall, these findings provide a promising direction for improved antifungal treatment approaches.
抗真菌药物耐药性是一个严重的全球健康威胁，需要新的治疗策略。在这里，我们研究了药物交叉敏感性（CS），即一种药物的耐药性会增加对另一种药物的敏感性，以及药物交叉耐药性（XR），即一种耐药机制会降低对多种药物的敏感性，因为 CS 和 XR 的动态变化可以指导治疗设计以阻止耐药性的发展，但在致病性真菌中尚未系统地进行研究。我们使用实验进化和数学建模方法研究了在周期性和联合药物暴露下的耳念珠菌种群动态，发现特别是基于 CS 的药物循环可以有效地防止耐药性的出现。此外，我们发现基于 CS 的治疗转换可以主动选择或根除耐药亚群，这突出了在检测到耐药性时考虑 CS 进行治疗决策的潜力。此外，我们还表明，在不同的菌株和耐药机制中，一些 CS 趋势是稳健的。总的来说，这些发现为改进抗真菌治疗方法提供了一个有前途的方向。
