Hemez Colin, Clarelli Fabrizio, Palmer Adam C, Bleis Christina, Abel Sören, Chindelevitch Leonid, Cohen Theodore, Abel Zur Wiesch Pia
Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA.
Graduate Program in Biophysics, Harvard University, Boston, MA 02115, USA.
Comput Struct Biotechnol J. 2022 Aug 24;20:4688-4703. doi: 10.1016/j.csbj.2022.08.030. eCollection 2022.
Antibiotic-resistant pathogens are a major public health threat. A deeper understanding of how an antibiotic's mechanism of action influences the emergence of resistance would aid in the design of new drugs and help to preserve the effectiveness of existing ones. To this end, we developed a model that links bacterial population dynamics with antibiotic-target binding kinetics. Our approach allows us to derive mechanistic insights on drug activity from population-scale experimental data and to quantify the interplay between drug mechanism and resistance selection. We find that both bacteriostatic and bactericidal agents can be equally effective at suppressing the selection of resistant mutants, but that key determinants of resistance selection are the relationships between the number of drug-inactivated targets within a cell and the rates of cellular growth and death. We also show that heterogeneous drug-target binding within a population enables resistant bacteria to evolve fitness-improving secondary mutations even when drug doses remain above the resistant strain's minimum inhibitory concentration. Our work suggests that antibiotic doses beyond this "secondary mutation selection window" could safeguard against the emergence of high-fitness resistant strains during treatment.
抗生素耐药性病原体是对公众健康的重大威胁。更深入地了解抗生素的作用机制如何影响耐药性的出现，将有助于新药的设计，并有助于维持现有药物的有效性。为此，我们开发了一个将细菌群体动态与抗生素-靶点结合动力学联系起来的模型。我们的方法使我们能够从群体规模的实验数据中获得关于药物活性的机制性见解，并量化药物机制与耐药性选择之间的相互作用。我们发现，抑菌剂和杀菌剂在抑制耐药突变体的选择方面同样有效，但耐药性选择的关键决定因素是细胞内药物失活靶点的数量与细胞生长和死亡速率之间的关系。我们还表明，群体内药物-靶点结合的异质性使耐药细菌即使在药物剂量保持高于耐药菌株的最低抑菌浓度时，也能进化出提高适应性的二次突变。我们的研究表明，超出这个“二次突变选择窗口”的抗生素剂量可以防止在治疗过程中出现高适应性耐药菌株。
