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.

中文翻译：

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全基因组测序时代的微生物食品安全导航。

食源性暴发的流行病学调查（包括相关病例的识别，来源归因和干预策略的制定）在很大程度上取决于以足够高的分辨率对病原体进行亚型分析以区分相关病例与非相关病例的能力。从历史上看，几种不同的分子亚型化方法已用于此目的。但是，新兴技术，例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WGS相比，与缺乏完整信息的传统子类型化方法不同，WGS可以使用数据阐明系统发生关系，并且可以随时间跟踪和监视致病谱系。WGS数据提供的亚型分辨率和进化背景使研究人员可以将传统技术可能遗漏的相关疾病联系起来。WGS生成的数据的另一个优点是，这些数据也可以用于二级分析，例如毒力基因检测，抗生素抗性基因分析，同义性比较，移动遗传元件识别和地理归因。另外，现在有几种软件包可用于从全基因组序列中生成用于传统分子亚型化方法的计算机模拟结果，从而可以与历史数据库进行有效比较。使用下一代测序的元基因组学方法也已成功检测出不可培养的食源性病原体。这篇评论介绍了微生物WGS和分析中的最新技术，然后讨论了如何使用该技术来帮助支持食品安全调查。提出了使用WGS进行的回顾性暴发调查，以提供与传统分子亚分型技术相比，WGS带来的益处和挑战的特定于生物的示例。