Characterizing Staphylococcus aureus genomic epidemiology with multilevel genome typing.

IF 4.6 2区 生物学 Q1 MICROBIOLOGY
mSystems Pub Date : 2025-10-02 DOI:10.1128/msystems.00935-25
Michael Payne, Liam Cheney, Sandeep Kaur, Genevieve McKew, Ruiting Lan
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引用次数: 0

Abstract

Staphylococcus aureus is a major source of both hospital- and community-acquired infections worldwide. Advances in whole-genome sequencing (WGS) technologies have recently generated large volumes of S. aureus WGS data. The timely classification of S. aureus WGS data using genomic typing technologies has the potential to describe detailed genomic epidemiology at large and small scales. In this study, a multilevel genome typing (MGT) scheme, consisting of eight levels of multilocus sequence typing (MLST) schemes of increasing resolution, was developed for S. aureus and was used to analyze 50,481 publicly available genomes. The application of MGT to S. aureus epidemiology was shown in three case studies. First, the population structure of the globally disseminated MLST sequence type 8 (ST8) was described by MGT2 and compared with Spa typing. Second, MGT was used to characterize MLST ST8-USA300 isolates that colonized multiple body sites in the same patient. Finally, the MGT was used to describe the transmission of MLST ST239-SCCmec III throughout a single hospital. MGT STs were able to describe both isolates that had spread between wards and those that had colonized different reservoirs within a ward. S. aureus MGT describes S. aureus genomic epidemiology at multiple resolutions ranging from the global spread to local/individual scale using stable and standardized ST assignments. The S. aureus MGT database (https://mgtdb.unsw.edu.au/staphylococcus) is capable of tracking new and existing clones to facilitate the design of new strategies to reduce the global health burden of S. aureus infections.

Importance: Staphylococcus aureus causes both hospital- and community-acquired infections worldwide. Methicillin-resistant S. aureus is best known and has spread across the globe. Whole-genome sequencing (WGS) can type strains at the highest resolution. To enable best use of WGS data for surveillance of S. aureus, this study developed a multilevel genome typing (MGT) scheme that provides a publicly available, standardized, flexible, and easily communicated system to describe S. aureus strains. MGT has eight typing levels that provide progressively higher resolution. Each of these levels allows subtypes to be accurately identified and tracked. We show that MGT can be used to track well-known S. aureus strains at low resolution while simultaneously being able to track outbreaks in hospital settings at high resolution. The S. aureus MGT will facilitate the use of genomic data for surveillance without the need for bioinformatic expertise, improving efforts to control this important pathogen and prevent infections.

多水平基因组分型表征金黄色葡萄球菌基因组流行病学。
金黄色葡萄球菌是世界范围内医院和社区获得性感染的主要来源。全基因组测序(WGS)技术的进步最近产生了大量的金黄色葡萄球菌WGS数据。利用基因组分型技术对金黄色葡萄球菌WGS数据进行及时分类,有可能在大尺度和小尺度上描述详细的基因组流行病学。本研究为金黄色葡萄球菌开发了一个多级基因组分型(MGT)方案,该方案由8个不断提高分辨率的多级多位点序列分型(MLST)方案组成,并用于分析50,481个公开的基因组。MGT在金黄色葡萄球菌流行病学中的应用在三个案例研究中得到了证明。首先,利用MGT2描述了全球分布的MLST序列8型(ST8)的种群结构,并与Spa分型进行了比较。其次,MGT用于鉴定在同一患者体内多个部位定殖的MLST ST8-USA300分离株。最后,MGT被用来描述MLST ST239-SCCmec III在单个医院的传播。MGT STs能够描述在病房之间传播的分离株和在病房内定植不同储存库的分离株。金黄色葡萄球菌MGT使用稳定和标准化的ST分配,在从全球传播到局部/个体规模的多个分辨率上描述金黄色葡萄球菌基因组流行病学。金黄色葡萄球菌MGT数据库(https://mgtdb.unsw.edu.au/staphylococcus)能够跟踪新的和现有的克隆,以促进设计新的战略,以减少金黄色葡萄球菌感染的全球健康负担。重要性:金黄色葡萄球菌在世界范围内引起医院和社区获得性感染。耐甲氧西林金黄色葡萄球菌最为人所知,并已在全球蔓延。全基因组测序(WGS)能够以最高的分辨率对菌株进行分型。为了更好地利用WGS数据对金黄色葡萄球菌进行监测,本研究开发了一个多级基因组分型(MGT)方案,该方案提供了一个公开可用、标准化、灵活且易于沟通的系统来描述金黄色葡萄球菌菌株。MGT有八个类型级别,提供逐步提高的分辨率。这些级别中的每一个都允许精确地识别和跟踪子类型。我们表明,MGT可用于以低分辨率跟踪已知的金黄色葡萄球菌菌株,同时能够以高分辨率跟踪医院环境中的爆发。金黄色葡萄球菌MGT将促进使用基因组数据进行监测,而不需要生物信息学专业知识,从而改善控制这一重要病原体和预防感染的努力。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
mSystems
mSystems Biochemistry, Genetics and Molecular Biology-Biochemistry
CiteScore
10.50
自引率
3.10%
发文量
308
审稿时长
13 weeks
期刊介绍: mSystems™ will publish preeminent work that stems from applying technologies for high-throughput analyses to achieve insights into the metabolic and regulatory systems at the scale of both the single cell and microbial communities. The scope of mSystems™ encompasses all important biological and biochemical findings drawn from analyses of large data sets, as well as new computational approaches for deriving these insights. mSystems™ will welcome submissions from researchers who focus on the microbiome, genomics, metagenomics, transcriptomics, metabolomics, proteomics, glycomics, bioinformatics, and computational microbiology. mSystems™ will provide streamlined decisions, while carrying on ASM''s tradition of rigorous peer review.
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