全基因组测序预测淋病奈瑟菌的抗菌药物敏感性谱。

Whole-Genome Sequencing to Predict Antimicrobial Susceptibility Profiles in Neisseria gonorrhoeae.

机构信息

Department of Medicine, University of California San Diego, La Jolla, California, USA.

Department of Immunology and Infectious Diseases, Harvard T.H. Chan School of Public Health, Boston, Massachusetts, USA.

出版信息

J Infect Dis. 2023 Apr 12;227(7):917-925. doi: 10.1093/infdis/jiad027.

DOI:10.1093/infdis/jiad027

PMID:36735316

原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC10319951/

Abstract

BACKGROUND

Neisseria gonorrhoeae is a major public health problem due to increasing incidence and antimicrobial resistance. Genetic markers of reduced susceptibility have been identified; the extent to which those are representative of global antimicrobial resistance is unknown. We evaluated the performance of whole-genome sequencing (WGS) used to predict susceptibility to ciprofloxacin and other antimicrobials using a global collection of N. gonorrhoeae isolates.

METHODS

Susceptibility testing of common antimicrobials and the recently developed zolifodacin was performed using agar dilution to determine minimum inhibitory concentrations (MICs). We identified resistance alleles at loci known to contribute to antimicrobial resistance in N. gonorrhoeae from WGS data. We tested the ability of each locus to predict antimicrobial susceptibility.

RESULTS

A total of 481 N. gonorrhoeae isolates, collected between 2004 and 2019 and making up 457 unique genomes, were sourced from 5 countries. All isolates with demonstrated susceptibility to ciprofloxacin (MIC ≤0.06 μg/mL) had a wild-type gyrA codon 91. Multilocus approaches were needed to predict susceptibility to other antimicrobials. All isolates were susceptible to zoliflodacin, defined by an MIC ≤0.25 μg/mL.

CONCLUSIONS

Single marker prediction can be used to inform ciprofloxacin treatment of N. gonorrhoeae infection. A combination of molecular markers may be needed to determine susceptibility for other antimicrobials.

摘要

背景

淋病奈瑟菌由于发病率上升和抗微生物药物耐药性而成为一个主要的公共卫生问题。已经确定了对药物敏感性降低的遗传标记；这些标记在多大程度上代表全球抗微生物药物耐药性尚不清楚。我们评估了使用全基因组测序（WGS）预测对环丙沙星和其他抗菌药物敏感性的性能，使用了全球淋病奈瑟菌分离株的集合。

方法

使用琼脂稀释法测定最低抑菌浓度（MIC），对常见抗菌药物和最近开发的唑来膦酸的敏感性进行了测试。我们从 WGS 数据中确定了已知对抗微生物药物耐药性有贡献的基因座的耐药等位基因。我们测试了每个基因座预测抗菌药物敏感性的能力。

结果

共收集了 481 株淋病奈瑟菌分离株，采集于 2004 年至 2019 年之间，由 5 个国家的 457 个独特基因组组成。所有对环丙沙星（MIC≤0.06μg/ml）表现出敏感性的分离株都具有野生型 gyrA 密码子 91。需要多基因座方法来预测对其他抗菌药物的敏感性。所有分离株对唑来膦酸均敏感，定义为 MIC≤0.25μg/ml。