Predictability of Phenotype in Relation to Common β-Lactam Resistance Mechanisms in Escherichia coli and Klebsiella pneumoniae

大肠杆菌和肺炎克雷伯菌中常见β-内酰胺类抗生素耐药机制与表型的可预测性

阅读:1

Abstract

The minimal concentration of antibiotic required to inhibit the growth of different isolates of a given species with no acquired resistance mechanisms has a normal distribution. We have previously shown that the presence or absence of transmissible antibiotic resistance genes has excellent predictive power for phenotype. In this study, we analyzed the distribution of six β-lactam antibiotic susceptibility phenotypes associated with commonly acquired resistance genes in Enterobacteriaceae in Sydney, Australia. Escherichia coli (n = 200) and Klebsiella pneumoniae (n = 178) clinical isolates, with relevant transmissible resistance genes (blaTEM, n = 33; plasmid AmpC, n = 69; extended-spectrum β-lactamase [ESBL], n = 116; and carbapenemase, n = 100), were characterized. A group of 60 isolates with no phenotypic resistance to any antibiotics tested and carrying none of the important β-lactamase genes served as comparators. The MICs for all drug-bacterium combinations had a normal distribution, varying only in the presence of additional genes relevant to the phenotype or, for ertapenem resistance in K. pneumoniae, with a loss or change in the outer membrane porin protein OmpK36. We demonstrated mutations in ompK36 or absence of OmpK36 in all isolates in which reduced susceptibility to ertapenem (MIC, >1 mg/liter) was evident. Ertapenem nonsusceptibility in K. pneumoniae was most common in the context of an OmpK36 variant with an ESBL or AmpC gene. Surveillance strategies to define appropriate antimicrobial therapies should include genotype-phenotype relationships for all major transmissible resistance genes and the characterization of mutations in relevant porins in organisms, like K. pneumoniae.

特别声明

1、本页面内容包含部分的内容是基于公开信息的合理引用;引用内容仅为补充信息,不代表本站立场。

2、若认为本页面引用内容涉及侵权,请及时与本站联系,我们将第一时间处理。

3、其他媒体/个人如需使用本页面原创内容,需注明“来源:[生知库]”并获得授权;使用引用内容的,需自行联系原作者获得许可。

4、投稿及合作请联系:info@biocloudy.com。