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全基因组测序数据在铜绿假单胞菌分离株O-特异性抗原分析及电子血清分型中的应用

Application of Whole-Genome Sequencing Data for O-Specific Antigen Analysis and In Silico Serotyping of Pseudomonas aeruginosa Isolates.

作者信息

Thrane Sandra Wingaard, Taylor Véronique L, Lund Ole, Lam Joseph S, Jelsbak Lars

机构信息

Technical University of Denmark, Department of Systems Biology, Kgs. Lyngby, Denmark.

University of Guelph, Department of Molecular and Cellular Biology, Guelph, Canada.

出版信息

J Clin Microbiol. 2016 Jul;54(7):1782-1788. doi: 10.1128/JCM.00349-16. Epub 2016 Apr 20.

Abstract

Accurate typing methods are required for efficient infection control. The emergence of whole-genome sequencing (WGS) technologies has enabled the development of genome-based methods applicable for routine typing and surveillance of bacterial pathogens. In this study, we developed the Pseudomonas aeruginosa serotyper (PAst) program, which enabled in silico serotyping of P. aeruginosa isolates using WGS data. PAst has been made publically available as a web service and aptly facilitates high-throughput serotyping analysis. The program overcomes critical issues such as the loss of in vitro typeability often associated with P. aeruginosa isolates from chronic infections and quickly determines the serogroup of an isolate based on the sequence of the O-specific antigen (OSA) gene cluster. Here, PAst analysis of 1,649 genomes resulted in successful serogroup assignments in 99.27% of the cases. This frequency is rarely achievable by conventional serotyping methods. The limited number of nontypeable isolates found using PAst was the result of either a complete absence of OSA genes in the genomes or the artifact of genomic misassembly. With PAst, P. aeruginosa serotype data can be obtained from WGS information alone. PAst is a highly efficient alternative to conventional serotyping methods in relation to outbreak surveillance of serotype O12 and other high-risk clones, while maintaining backward compatibility to historical serotype data.

摘要

高效的感染控制需要准确的分型方法。全基因组测序(WGS)技术的出现推动了适用于细菌病原体常规分型和监测的基于基因组方法的发展。在本研究中,我们开发了铜绿假单胞菌血清型分型程序(PAst),该程序能够利用WGS数据对铜绿假单胞菌分离株进行电子血清型分型。PAst已作为一项网络服务公开提供,极大地促进了高通量血清型分型分析。该程序克服了一些关键问题,比如慢性感染的铜绿假单胞菌分离株常出现的体外分型能力丧失问题,并能根据O特异性抗原(OSA)基因簇的序列快速确定分离株的血清群。在此,对1649个基因组进行的PAst分析在99.27%的案例中成功完成了血清群分型。这一频率是传统血清型分型方法很少能达到的。使用PAst发现的不可分型分离株数量有限,原因要么是基因组中完全没有OSA基因,要么是基因组组装错误造成的假象。借助PAst,仅从WGS信息就能获得铜绿假单胞菌血清型数据。在血清型O12及其他高风险克隆的暴发监测方面,PAst是传统血清型分型方法的一种高效替代方法,同时还能与历史血清型数据保持向后兼容性。

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