Significance of whole genome sequencing for surveillance, source attribution and microbial risk assessment of foodborne pathogens
Significance of whole genome sequencing for surveillance, source attribution and microbial risk assessment of foodborne pathogens
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DOI：
10.1016/j.cofs.2016.04.004
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发表时间：
2016-04-01
影响因子：
9.9
通讯作者：
Dallman, Tim
中科院分区：
文献类型：
--
作者：
Franz, Eelco;Gras, Lapo Mughini;Dallman, Tim
随着全基因组测序（WGS）革命的迅速发展，了解这项技术的意义及其在食品安全方面的未来应用是至关重要的。本文综述了WGS在疫情检测和监测、微生物来源归属和微生物风险评估等方面的最新进展。虽然WGS主要用于监测和疫情调查目的，但仍然迫切需要统一方法（样品制备、序列质量和病例定义、分析），并就适当的命名法（SNP与等位基因水平）和病例定义达成共识。WGS在污染源归属和微生物风险评估中的应用尚未得到充分的探索。WGS在来源归属中的使用需要开发新的建模方法，这些方法可以处理大量数据和与WGS相关的高分辨能力。对于微生物风险评估，与表型特征的联系至关重要，但全基因组关联研究的可重复性和与流行病学的联系方面的缺点需要创新的统计方法。总的来说，在没有健全的公共卫生或生物学背景的情况下，仅凭WGS数据的用途有限。事先确定假设和研究问题对于正确分析和解释WGS数据至关重要。
As the whole genome sequencing (WGS) revolution is rapidly gaining momentum, it is essential to understand the significance of this technology and its future applications in food safety. This review discusses the recent advances concerning the use of WGS for outbreak detection and surveillance, microbial source attribution and microbial risk assessment. Although the WGS is mainly being applied for surveillance and outbreak investigation purposes, there is still, a strong need for harmonization of methods (sample preparation, sequence quality and case-definition, analysis) and consensus on suitable nomenclature (SNP versus allele level) and case definition. The application of WGS in source attribution and microbial risk assessment is largely unexplored. The use of WGS in source attribution requires the development of new modelling approaches that can handle the large amount of data and the high discriminatory power associated with WGS. For microbial risk assessment, the link with phenotypic features is crucial, but the short-comings regarding the reproducibility of genome-wide-association studies and the link to epidemiology need innovative statistical approaches. Overall, WGS data alone are of limited use without a sound public health or biological context. Defining hypotheses and research questions beforehand are crucial for the correct analysis and interpretation of WGS data.