Center for Food Safety and Applied Nutrition, US Food and Drug Administration, College Park, MD, USA.
Microb Genom. 2018 Jul;4(7). doi: 10.1099/mgen.0.000185. Epub 2018 Jun 15.
Pathogen monitoring is becoming more precise as sequencing technologies become more affordable and accessible worldwide. This transition is especially apparent in the field of food safety, which has demonstrated how whole-genome sequencing (WGS) can be used on a global scale to protect public health. GenomeTrakr coordinates the WGS performed by public-health agencies and other partners by providing a public database with real-time cluster analysis for foodborne pathogen surveillance. Because WGS is being used to support enforcement decisions, it is essential to have confidence in the quality of the data being used and the downstream data analyses that guide these decisions. Routine proficiency tests, such as the one described here, have an important role in ensuring the validity of both data and procedures. In 2015, the GenomeTrakr proficiency test distributed eight isolates of common foodborne pathogens to participating laboratories, who were required to follow a specific protocol for performing WGS. Resulting sequence data were evaluated for several metrics, including proper labelling, sequence quality and new single nucleotide polymorphisms (SNPs). Illumina MiSeq sequence data collected for the same set of strains across 21 different laboratories exhibited high reproducibility, while revealing a narrow range of technical and biological variance. The numbers of SNPs reported for sequencing runs of the same isolates across multiple laboratories support the robustness of our cluster analysis pipeline in that each individual isolate cultured and resequenced multiple times in multiple places are all easily identifiable as originating from the same source.
随着测序技术在全球范围内变得更加经济实惠和易于获取,病原体监测变得越来越精确。这种转变在食品安全领域尤为明显,全基因组测序 (WGS) 已被证明可以在全球范围内用于保护公众健康。GenomeTrakr 通过提供带有实时聚类分析的公共数据库,协调公共卫生机构和其他合作伙伴进行的 WGS,以进行食源性病原体监测。由于 WGS 被用于支持执法决策,因此必须对所使用数据的质量以及指导这些决策的下游数据分析有信心。常规的能力验证测试,如这里描述的测试,在确保数据和程序的有效性方面发挥着重要作用。2015 年,GenomeTrakr 能力验证测试向参与实验室分发了 8 株常见食源性病原体,要求他们按照特定的协议进行 WGS。对产生的序列数据进行了多个指标的评估,包括正确的标记、序列质量和新的单核苷酸多态性 (SNP)。在 21 个不同实验室中,为同一组菌株收集的 Illumina MiSeq 序列数据表现出高度的重现性,同时显示出狭窄的技术和生物变异性范围。在多个实验室对同一分离株的测序运行报告的 SNP 数量支持我们的聚类分析管道的稳健性,因为在多个地方培养和多次重新测序的每个单独分离株都很容易被识别为源自同一来源。