{"title":"单一和多重耐药机制对细菌对美罗培南反应的影响。","authors":"","doi":"10.1016/j.cmi.2024.06.026","DOIUrl":null,"url":null,"abstract":"<div><h3>Objectives</h3><p>Meropenem is commonly used against <em>Pseudomonas aeruginosa</em>. Traditionally, the time unbound antibiotic concentration exceeds the MIC (<em>f</em>T<sub>></sub><sub>MIC</sub>) 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 <em>f</em>T<sub>></sub><sub>MIC</sub> 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.</p></div><div><h3>Methods</h3><p>Seven isogenic <em>P. aeruginosa</em> 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 (t<sub>1/2,meropenem</sub> = 1.5 h). All viable counts on drug-free, 3 × MIC, and 5 × MIC meropenem-containing agar across all strains, five regimens, and control (<em>n</em> = 90 profiles) were simultaneously subjected to QSP modeling. Whole genome sequencing was completed for total population samples and emergent resistant colonies at 239 h.</p></div><div><h3>Results</h3><p>Regimens achieving ≥98%<em>f</em>T<sub>>1</sub> <sub>×</sub> <sub>MIC</sub> suppressed resistance emergence of the <em>mexR</em> knockout strain. Even 100%<em>f</em>T<sub>>5 × MIC</sub> failed to achieve this against the strain with OprD loss and the <em>ampD</em> and <em>mexR</em> 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 <em>mexR</em> were selected in strains with baseline <em>oprD</em> mutations, and <em>vice versa</em>, confirming these as major mechanisms of resistance emergence. Secondary mutations occurred in <em>lysS</em> or <em>argS</em>, coding for lysyl and arginyl tRNA synthetases, respectively.</p></div><div><h3>Discussion</h3><p>The QSP model well-characterized all bacterial outcomes of the seven strains simultaneously, which <em>f</em>T<sub>></sub><sub>MIC</sub> could not.</p></div>","PeriodicalId":10444,"journal":{"name":"Clinical Microbiology and Infection","volume":null,"pages":null},"PeriodicalIF":10.9000,"publicationDate":"2024-08-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S1198743X24003069/pdfft?md5=b92165f1079fbc388f18f571380eb78e&pid=1-s2.0-S1198743X24003069-main.pdf","citationCount":"0","resultStr":"{\"title\":\"The effects of single and multiple resistance mechanisms on bacterial response to meropenem\",\"authors\":\"\",\"doi\":\"10.1016/j.cmi.2024.06.026\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><h3>Objectives</h3><p>Meropenem is commonly used against <em>Pseudomonas aeruginosa</em>. Traditionally, the time unbound antibiotic concentration exceeds the MIC (<em>f</em>T<sub>></sub><sub>MIC</sub>) 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 <em>f</em>T<sub>></sub><sub>MIC</sub> 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.</p></div><div><h3>Methods</h3><p>Seven isogenic <em>P. aeruginosa</em> 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 (t<sub>1/2,meropenem</sub> = 1.5 h). All viable counts on drug-free, 3 × MIC, and 5 × MIC meropenem-containing agar across all strains, five regimens, and control (<em>n</em> = 90 profiles) were simultaneously subjected to QSP modeling. Whole genome sequencing was completed for total population samples and emergent resistant colonies at 239 h.</p></div><div><h3>Results</h3><p>Regimens achieving ≥98%<em>f</em>T<sub>>1</sub> <sub>×</sub> <sub>MIC</sub> suppressed resistance emergence of the <em>mexR</em> knockout strain. Even 100%<em>f</em>T<sub>>5 × MIC</sub> failed to achieve this against the strain with OprD loss and the <em>ampD</em> and <em>mexR</em> 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 <em>mexR</em> were selected in strains with baseline <em>oprD</em> mutations, and <em>vice versa</em>, confirming these as major mechanisms of resistance emergence. Secondary mutations occurred in <em>lysS</em> or <em>argS</em>, coding for lysyl and arginyl tRNA synthetases, respectively.</p></div><div><h3>Discussion</h3><p>The QSP model well-characterized all bacterial outcomes of the seven strains simultaneously, which <em>f</em>T<sub>></sub><sub>MIC</sub> could not.</p></div>\",\"PeriodicalId\":10444,\"journal\":{\"name\":\"Clinical Microbiology and Infection\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":10.9000,\"publicationDate\":\"2024-08-05\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://www.sciencedirect.com/science/article/pii/S1198743X24003069/pdfft?md5=b92165f1079fbc388f18f571380eb78e&pid=1-s2.0-S1198743X24003069-main.pdf\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Clinical Microbiology and Infection\",\"FirstCategoryId\":\"3\",\"ListUrlMain\":\"https://www.sciencedirect.com/science/article/pii/S1198743X24003069\",\"RegionNum\":1,\"RegionCategory\":\"医学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"INFECTIOUS DISEASES\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Clinical Microbiology and Infection","FirstCategoryId":"3","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S1198743X24003069","RegionNum":1,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"INFECTIOUS DISEASES","Score":null,"Total":0}
引用次数: 0
摘要
目的:美罗培南常用于抗击铜绿假单胞菌。传统上,非结合抗生素浓度超过 MIC 的时间(fT>MIC)用于选择碳青霉烯类方案。我们的目的是描述不同基线耐药机制对细菌杀灭和耐药性产生的影响;评估 fT>MIC 是否能预测这些影响;以及开发一种新型定量和系统药理学(QSP)模型来描述基线耐药机制对细菌反应时间过程的影响:方法:在为期 10 天的中空纤维感染模型研究中使用了 7 株具有不同耐药机制和 MIC 的同源铜绿假单胞菌。模拟了各种治疗方案(t1/2,美罗培南=1.5小时)的美罗培南药动学曲线。同时对所有菌株、五种方案和对照组(n = 90 个剖面)在无药、3 × MIC 和 5 × MIC 含美罗培南琼脂上的所有存活计数进行 QSP 建模。在 239 小时内完成了全部菌群样本和新出现耐药菌落的全基因组测序:结果:≥98%fT>1×MIC的治疗方案抑制了mexR基因敲除菌株耐药性的产生。对 OprD 缺失菌株和 ampD 与 mexR 双基因敲除菌株,即使 100%fT>5×MIC 也无法抑制耐药性的产生。即使对 MIC 相同的菌株,基线抗性机制也会影响细菌的结果。基因组分析表明,先前存在的耐药亚群推动了耐药性的出现。在接触美罗培南的过程中,omexR的突变被选入具有基线oprD突变的菌株中,反之亦然,这证实了这些突变是耐药性产生的主要机制。次要突变发生在分别编码赖氨酰和精氨酰 tRNA 合成酶的 lysS 或 argS 中:讨论:QSP 模型同时描述了七株菌株的所有细菌结果,而 fT>MIC 却无法做到这一点。
The effects of single and multiple resistance mechanisms on bacterial response to meropenem
Objectives
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.
Discussion
The QSP model well-characterized all bacterial outcomes of the seven strains simultaneously, which fT>MIC could not.
期刊介绍:
Clinical Microbiology and Infection (CMI) is a monthly journal published by the European Society of Clinical Microbiology and Infectious Diseases. It focuses on peer-reviewed papers covering basic and applied research in microbiology, infectious diseases, virology, parasitology, immunology, and epidemiology as they relate to therapy and diagnostics.