Ronholm J, Nasheri Neda, Petronella Nicholas, Pagotto Franco
Bureau of Microbial Hazards, Food Directorate, Health Canada, Ottawa, ON, Canada
Bureau of Microbial Hazards, Food Directorate, Health Canada, Ottawa, ON, Canada.
Clin Microbiol Rev. 2016 Oct;29(4):837-57. doi: 10.1128/CMR.00056-16.
The epidemiological investigation of a foodborne outbreak, including identification of related cases, source attribution, and development of intervention strategies, relies heavily on the ability to subtype the etiological agent at a high enough resolution to differentiate related from nonrelated cases. Historically, several different molecular subtyping methods have been used for this purpose; however, emerging techniques, such as single nucleotide polymorphism (SNP)-based techniques, that use whole-genome sequencing (WGS) offer a resolution that was previously not possible. With WGS, unlike traditional subtyping methods that lack complete information, data can be used to elucidate phylogenetic relationships and disease-causing lineages can be tracked and monitored over time. The subtyping resolution and evolutionary context provided by WGS data allow investigators to connect related illnesses that would be missed by traditional techniques. The added advantage of data generated by WGS is that these data can also be used for secondary analyses, such as virulence gene detection, antibiotic resistance gene profiling, synteny comparisons, mobile genetic element identification, and geographic attribution. In addition, several software packages are now available to generate in silico results for traditional molecular subtyping methods from the whole-genome sequence, allowing for efficient comparison with historical databases. Metagenomic approaches using next-generation sequencing have also been successful in the detection of nonculturable foodborne pathogens. This review addresses state-of-the-art techniques in microbial WGS and analysis and then discusses how this technology can be used to help support food safety investigations. Retrospective outbreak investigations using WGS are presented to provide organism-specific examples of the benefits, and challenges, associated with WGS in comparison to traditional molecular subtyping techniques.
食源性疾病暴发的流行病学调查，包括识别相关病例、溯源以及制定干预策略，在很大程度上依赖于以足够高的分辨率对病原体进行亚型分型的能力，以便区分相关病例和非相关病例。从历史上看，已经使用了几种不同的分子亚型分型方法来实现这一目的；然而，新兴技术，如基于单核苷酸多态性（SNP）的技术，使用全基因组测序（WGS）提供了以前无法实现的分辨率。与缺乏完整信息的传统亚型分型方法不同，利用WGS，数据可用于阐明系统发育关系，并且致病谱系可随时间进行追踪和监测。WGS数据提供的亚型分型分辨率和进化背景使调查人员能够发现传统技术会遗漏的相关疾病。WGS生成的数据的另一个优势是，这些数据还可用于二次分析，如毒力基因检测、抗生素抗性基因谱分析、共线性比较、可移动遗传元件鉴定和地理溯源。此外，现在有几个软件包可根据全基因组序列生成传统分子亚型分型方法的计算机模拟结果，从而能够与历史数据库进行有效比较。使用下一代测序的宏基因组学方法在检测不可培养的食源性病原体方面也取得了成功。本综述介绍了微生物WGS及分析方面的最新技术，然后讨论了如何利用这项技术来支持食品安全调查。还介绍了使用WGS进行的回顾性暴发调查，以提供与传统分子亚型分型技术相比，WGS相关的益处和挑战的特定生物体实例。
