目的:美罗培南通常用于铜绿假单胞菌。传统上,未结合的抗生素浓度超过MIC的时间(fT>MIC)用于选择碳青霉烯方案。我们旨在表征不同基线抗性机制对细菌杀灭和抗性出现的影响;评估fT>MIC是否可以预测这些影响;和,开发一种新的定量和系统药理学(QSP)模型来描述基线抗性机制对细菌反应时程的影响。
方法:在10天的中空纤维感染模型研究中使用了7种具有一系列耐药机制和MIC的等基因铜绿假单胞菌菌株。模拟了各种方案的美罗培南药代动力学曲线(t1/2,美罗培南=1.5h)。所有可行的都是无毒的,3×MIC,和所有菌株中含有5×MIC美罗培南的琼脂,五个方案,和对照(n=90个配置文件)同时进行QSP建模。在239小时完成了对总种群样品和紧急抗性菌落的全基因组测序。
结果:达到≥98%fT>1×MIC的方案抑制了mexR敲除菌株的抗性出现。即使100%fT>5×MIC也无法针对具有OprD损失的菌株以及ampD和mexR双敲除菌株实现这一目标。基线抗性机制影响细菌结果,即使是具有相同MIC的菌株。基因组分析显示,预先存在的抗性亚群推动了抗性的出现。在美罗培南暴露期间,在具有基线oprD突变的菌株中选择mexR中的突变,反之亦然,证实这些是抗性出现的主要机制。次级突变发生在lysS或argS,编码赖氨酰和精氨酰tRNA合成酶,分别。
结论:QSP模型同时很好地表征了七个菌株的所有细菌结果,fT>MIC不能。
OBJECTIVE: Meropenem is commonly used against Pseudomonas aeruginosa. Traditionally, the time unbound antibiotic concentration exceeds the MIC (fT>MIC) is used to select carbapenem regimens. We aimed to characterize the effects of different baseline resistance mechanisms on bacterial killing and resistance emergence; evaluate whether fT>MIC can predict these effects; and, develop a novel Quantitative and Systems Pharmacology (QSP) model to describe the effects of baseline resistance mechanisms on the time-course of bacterial response.
METHODS: Seven isogenic P. aeruginosa strains with a range of resistance mechanisms and MICs were used in 10-day hollow-fiber infection model studies. Meropenem pharmacokinetic profiles were simulated for various regimens (t1/2,meropenem = 1.5 h). All viable counts on drug-free, 3 × MIC, and 5 × MIC meropenem-containing agar across all strains, five regimens, and control (n = 90 profiles) were simultaneously subjected to QSP modeling. Whole genome sequencing was completed for total population samples and emergent resistant colonies at 239 h.
RESULTS: Regimens achieving ≥98%fT>1×MIC suppressed resistance emergence of the mexR knockout strain. Even 100%fT>5 × MIC failed to achieve this against the strain with OprD loss and the ampD and mexR double-knockout strain. Baseline resistance mechanisms affected bacterial outcomes, even for strains with the same MIC. Genomic analysis revealed that pre-existing resistant subpopulations drove resistance emergence. During meropenem exposure, mutations in mexR were selected in strains with baseline oprD mutations, and vice versa, confirming these as major mechanisms of resistance emergence. Secondary mutations occurred in lysS or argS, coding for lysyl and arginyl tRNA synthetases, respectively.
CONCLUSIONS: The QSP model well-characterized all bacterial outcomes of the seven strains simultaneously, which fT>MIC could not.