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单一和多重耐药机制对细菌对美罗胺的反应的影响

Dominika T Fuhs¹, Sara Cortés-Lara², Jessica R Tait¹

¹Drug Delivery, Disposition and Dynamics, Monash Institute of Pharmaceutical Sciences, Monash University, Parkville, VIC, Australia.

Clinical microbiology and infection : the official publication of the European Society of Clinical Microbiology and Infectious Diseases

|August 6, 2024

概括

在Pseudomonas aeruginosa中,美罗胺耐药性是复杂的. 一种新的定量和系统药理 (QSP) 模型比传统方法更好地预测细菌杀死和耐药性,并考虑了基线耐药性机制.

科学领域:

药理学药理学是指药理学的学科.
微生物学微生物学
基因组学就是基因组学.

背景情况:

梅罗是治疗Pseudomonas aeruginosa感染的关键抗生素.
传统的剂量策略依赖于最小抑制度 (fT>MIC) 以上的时间.
基线耐药机制可以影响美罗的疗效和耐药性的出现.

研究的目的:

描述不同基线耐药机制如何影响细菌杀死和耐药性.
评估FT>MIC对这些结果的预测能力.
开发一个量化和系统药理学 (QSP) 模型,用于P. aeruginosa.中的美罗胺反应.

主要方法:

在空洞纤维感染模型中利用了七种具有不同抵抗机制的同源P. aeruginosa菌株.
模拟的美罗胺药理动力学特征,用于不同的剂量方案.
在细菌活力数据和耐药群体的全基因组测序上采用QSP建模.

主要成果:

fT>MIC值未能预测具有特定基线抗性机制 (例如,OprD损失,ampD/mexR双击) 的菌株的抗性抑制.
基线耐药机制显著影响了细菌结果,独立于MIC.
基因组分析确定了先前存在的耐药亚群和特定突变 (mexR, oprD, lysS, argS),推动了耐药性的出现.

结论:

开发的QSP模型有效地描述了多个菌株和耐药性机制的细菌结果.
与fT>MIC相比,QSP建模在P. aeruginosa治疗中提供了优越的预测能力,具有多样化的耐药性.

关键词:

抗生素耐药性抗生素耐药性人口基因组学是人口的基因组学.伪omonas aeruginosa 这种类型的病毒.量化系统药理学药理学整个基因组的测序.

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