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基于基因序列的鲍曼不动杆菌核心基因组多位点序列分型——使用 Ridom SeqSphere+ 和 ARESdb 预测抗菌药物敏感性。

Acinetobacter baumannii Genomic Sequence-Based Core Genome Multilocus Sequence Typing Using Ridom SeqSphere+ and Antimicrobial Susceptibility Prediction in ARESdb.

机构信息

Division of Infectious Diseases, Department of Medicine, Mayo Clinicgrid.66875.3agrid.470142.4grid.66875.3a, Rochester, Minnesota, USA.

Division of Clinical Microbiology, Mayo Clinicgrid.66875.3agrid.470142.4grid.66875.3a, Rochester, Minnesota, USA.

出版信息

J Clin Microbiol. 2022 Aug 17;60(8):e0053322. doi: 10.1128/jcm.00533-22. Epub 2022 Jul 12.

Abstract

Whole-genome sequencing (WGS) is rapidly replacing traditional typing methods for the investigation of infectious disease outbreaks. Additionally, WGS data are being used to predict phenotypic antimicrobial susceptibility. Acinetobacter baumannii, which is often multidrug-resistant, is a significant culprit in outbreaks in health care settings. A well-characterized collection of A. baumannii was studied using core genome multilocus sequence typing (cgMLST). Seventy-two isolates previously typed by PCR-electrospray ionization mass spectrometry (PCR/ESI-MS) provided by the Antimicrobial Resistance Leadership Group (ARLG) were analyzed using a clinical microbiology laboratory developed workflow for cgMLST with genomic susceptibility prediction performed using the ARESdb platform. Previously performed PCR/ESI-MS correlated with cgMLST using relatedness thresholds of allelic differences of ≤9 and ≤200 allelic differences in 78 and 94% of isolates, respectively. Categorical agreement between genotypic and phenotypic antimicrobial susceptibility across a panel of 11 commonly used drugs was 89%, with minor, major, and very major error rates of 8%, 11%, and 1%, respectively.

摘要

全基因组测序(WGS)正在迅速取代传统的传染病爆发调查方法。此外,WGS 数据也被用于预测表型抗菌药物敏感性。鲍曼不动杆菌通常具有多重耐药性,是医疗机构爆发的主要罪魁祸首。本研究使用核心基因组多位点序列分型(cgMLST)对一组特征明确的鲍曼不动杆菌进行了研究。对来自抗菌药物耐药性领导组(ARLG)的经 PCR-电喷雾电离质谱(PCR/ESI-MS)分型的 72 株先前分离株进行了分析,该组分离株使用临床微生物实验室开发的 cgMLST 工作流程进行分析,并用 ARESdb 平台进行基因组药敏预测。先前进行的 PCR/ESI-MS 与 cgMLST 的相关性,分别在等位基因差异≤9 和≤200 时,相关度阈值为 78%和 94%。11 种常用药物药敏表型的基因型与表型药敏之间的类别一致性为 89%,分别有 8%、11%和 1%的微小错误、主要错误和非常大错误。

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