Department of Medical Microbiology, University Medical Center, Utrecht, The Netherlands.
Department of Medical Microbiology and Immunology, Creighton University School of Medicine, Omaha, NE, USA.
Clin Microbiol Infect. 2018 Apr;24(4):350-354. doi: 10.1016/j.cmi.2017.12.016. Epub 2018 Jan 5.
Whole genome sequence (WGS)-based strain typing finds increasing use in the epidemiologic analysis of bacterial pathogens in both public health as well as more localized infection control settings.
This minireview describes methodologic approaches that have been explored for WGS-based epidemiologic analysis and considers the challenges and pitfalls of data interpretation.
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When applying WGS to study the molecular epidemiology of bacterial pathogens, genomic variability between strains is translated into measures of distance by determining single nucleotide polymorphisms in core genome alignments or by indexing allelic variation in hundreds to thousands of core genes, assigning types to unique allelic profiles. Interpreting isolate relatedness from these distances is highly organism specific, and attempts to establish species-specific cutoffs are unlikely to be generally applicable. In cases where single nucleotide polymorphism or core gene typing do not provide the resolution necessary for accurate assessment of the epidemiology of bacterial pathogens, inclusion of accessory gene or plasmid sequences may provide the additional required discrimination.
As with all epidemiologic analysis, realizing the full potential of the revolutionary advances in WGS-based approaches requires understanding and dealing with issues related to the fundamental steps of data generation and interpretation.
全基因组序列(WGS)为基础的菌株分型在公共卫生和更本地化的感染控制环境中,对细菌病原体的流行病学分析越来越有帮助。
本综述描述了用于 WGS 流行病学分析的方法学方法,并考虑了数据解释的挑战和陷阱。
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当应用 WGS 来研究细菌病原体的分子流行病学时,通过确定核心基因组比对中的单核苷酸多态性,或通过索引数百到数千个核心基因中的等位基因变异,将菌株之间的基因组变异转化为距离的度量,将类型分配给独特的等位基因谱。从这些距离推断分离株的亲缘关系具有高度的物种特异性,试图建立物种特异性的截止值不太可能普遍适用。在单核苷酸多态性或核心基因分型不能为准确评估细菌病原体的流行病学提供必要分辨率的情况下,包含辅助基因或质粒序列可能会提供所需的额外区分。
与所有流行病学分析一样,要充分发挥基于 WGS 方法的革命性进展的潜力,需要理解和处理与数据生成和解释的基本步骤相关的问题。