Whole-Genome Sequencing for Routine Pathogen Surveillance in Public Health: a Population Snapshot of Invasive Staphylococcus aureus in Europe.
Whole-Genome Sequencing for Routine Pathogen Surveillance in Public Health: a Population Snapshot of Invasive Staphylococcus aureus in Europe.
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DOI：
10.1128/mbio.00444-16
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发表时间：
2016-05-05
期刊：
影响因子：
6.4
通讯作者：
European SRL Working Group
中科院分区：
文献类型：
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作者：
Aanensen DM;Feil EJ;Holden MT;Dordel J;Yeats CA;Fedosejev A;Goater R;Castillo-Ramírez S;Corander J;Colijn C;Chlebowicz MA;Schouls L;Heck M;Pluister G;Ruimy R;Kahlmeter G;Åhman J;Matuschek E;Friedrich AW;Parkhill J;Bentley SD;Spratt BG;Grundmann H;European SRL Working Group
常规全基因组测序（WGS）的实施有望改变我们监测细菌病原体出现和传播的能力。在这里，我们将来自308株侵袭性金黄色葡萄球菌分离株的WGS数据与流行病学和耐药性数据相结合，这些分离株对应于泛欧人群快照。通过一个为公共卫生目的设计的通用软件工具，使数据的地理空间可视化成为可能，该软件工具可在项目URL（http：//www.example.com）上获得www.microreact.org/project/EkUvg9uY? tt=rc）。我们的分析表明，高风险的克隆，可以确定的基础上，人口水平的属性，如克隆的相关性，丰度和空间结构，并推断毒力和抗性特性的基础上的基因内容。我们还表明，在计算机预测的抗生素耐药性概况至少是可靠的表型测试。我们认为，这项工作提供了一个全面的路线图，说明未来的分子流行病学监测的三个重要组成部分：（i）大规模结构化调查，（ii）WGS，（iii）面向社区的数据库基础设施和分析工具。抗药性细菌的传播是一个全球关注的突发公共卫生事件，威胁着各级医疗保健服务的医疗干预。最近的几项研究表明，细菌病原体的常规全基因组测序（WGS）有望用于流行病学监测、爆发检测和感染控制。然而，随着这一技术得到更广泛的采用，生成具有代表性的国家和国际数据集以及开发生物信息学工具来管理和解释数据的关键挑战变得越来越重要。这项研究为将WGS数据整合到常规病原体监测中提供了路线图。我们强调大规模常规调查的重要性，为更有针对性或本地化的调查提供人口背景，并开发开放获取的生物信息学工具，提供联合收割机组合和比较独立生成的数据的方法。公开可用的数据集。
The implementation of routine whole-genome sequencing (WGS) promises to transform our ability to monitor the emergence and spread of bacterial pathogens. Here we combined WGS data from 308 invasive Staphylococcus aureus isolates corresponding to a pan-European population snapshot, with epidemiological and resistance data. Geospatial visualization of the data is made possible by a generic software tool designed for public health purposes that is available at the project URL (http://www.microreact.org/project/EkUvg9uY?tt=rc). Our analysis demonstrates that high-risk clones can be identified on the basis of population level properties such as clonal relatedness, abundance, and spatial structuring and by inferring virulence and resistance properties on the basis of gene content. We also show that in silico predictions of antibiotic resistance profiles are at least as reliable as phenotypic testing. We argue that this work provides a comprehensive road map illustrating the three vital components for future molecular epidemiological surveillance: (i) large-scale structured surveys, (ii) WGS, and (iii) community-oriented database infrastructure and analysis tools. The spread of antibiotic-resistant bacteria is a public health emergency of global concern, threatening medical intervention at every level of health care delivery. Several recent studies have demonstrated the promise of routine whole-genome sequencing (WGS) of bacterial pathogens for epidemiological surveillance, outbreak detection, and infection control. However, as this technology becomes more widely adopted, the key challenges of generating representative national and international data sets and the development of bioinformatic tools to manage and interpret the data become increasingly pertinent. This study provides a road map for the integration of WGS data into routine pathogen surveillance. We emphasize the importance of large-scale routine surveys to provide the population context for more targeted or localized investigation and the development of open-access bioinformatic tools to provide the means to combine and compare independently generated data with publicly available data sets.