Center for Food Safety, Department of Food Science and Technology, University of Georgia, Griffin, Georgia, USA.
Nestlé Institute of Food Safety and Analytical Sciences, Nestlé Research, Vers-chez-les-Blanc, Lausanne, Switzerland.
Appl Environ Microbiol. 2019 Nov 27;85(24). doi: 10.1128/AEM.01985-19. Print 2019 Dec 15.
Single-nucleotide polymorphisms (SNPs) are widely used for whole-genome sequencing (WGS)-based subtyping of foodborne pathogens in outbreak and source tracking investigations. Mobile genetic elements (MGEs) are commonly present in bacterial genomes and may affect SNP subtyping results if their evolutionary history and dynamics differ from that of the bacterial chromosomes. Using as a model organism, we surveyed major categories of MGEs, including plasmids, phages, insertion sequences, integrons, and integrative and conjugative elements (ICEs), in 990 genomes representing 21 major serotypes of We evaluated whether plasmids and chromosomal MGEs affect SNP subtyping with 9 outbreak clusters of different serotypes found in the United States in 2018. The median total length of chromosomal MGEs accounted for 2.5% of a typical chromosome. Of the 990 analyzed isolates, 68.9% contained at least one assembled plasmid sequence. The median total length of assembled plasmids in these isolates was 93,671 bp. Plasmids that carry high densities of SNPs were found to substantially affect both SNP phylogenies and SNP distances among closely related isolates if they were present in the reference genome for SNP subtyping. In comparison, chromosomal MGEs were found to have limited impact on SNP subtyping. We recommend the identification of plasmid sequences in the reference genome and the exclusion of plasmid-borne SNPs from SNP subtyping analysis. Despite increasingly routine use of WGS and SNP subtyping in outbreak and source tracking investigations, whether and how MGEs affect SNP subtyping has not been thoroughly investigated. Besides chromosomal MGEs, plasmids are frequently entangled in draft genome assemblies and yet to be assessed for their impact on SNP subtyping. This study provides evidence-based guidance on the treatment of MGEs in SNP analysis for to infer phylogenetic relationship and SNP distance between isolates.
单核苷酸多态性 (SNP) 广泛用于基于全基因组测序 (WGS) 的食源性病原体的亚型分析，以进行暴发和溯源调查。移动遗传元件 (MGE) 通常存在于细菌基因组中，如果它们的进化历史和动态与细菌染色体不同，可能会影响 SNP 亚型分析结果。本研究以 作为模型生物，调查了包括质粒、噬菌体、插入序列、整合子和整合子-转座子元件 (ICE) 在内的主要 MGE 类别，共涵盖了 21 种血清型的 990 个基因组。我们评估了质粒和染色体 MGE 对 SNP 亚型分析的影响，使用了在美国 2018 年发现的不同血清型的 9 个暴发群集。染色体 MGE 的中位数总长度占典型 染色体的 2.5%。在分析的 990 个 分离株中，68.9%至少含有一个组装的质粒序列。这些分离株中组装质粒的中位数总长度为 93671bp。如果在 SNP 亚型分析的参考基因组中存在携带高 SNP 密度的质粒，那么它们会显著影响 SNP 系统发育和密切相关分离株之间的 SNP 距离。相比之下，染色体 MGE 对 SNP 亚型分析的影响有限。我们建议在参考基因组中识别质粒序列，并从 SNP 亚型分析中排除质粒携带的 SNPs。尽管 WGS 和 SNP 亚型分析在暴发和溯源调查中的应用越来越常规，但 MGE 如何以及是否影响 SNP 亚型分析尚未得到彻底研究。除了染色体 MGE 之外，质粒在基因组草图组装中经常纠缠不清，尚未评估其对 SNP 亚型分析的影响。本研究为 提供了基于证据的指导，用于 SNP 分析中处理 MGE，以推断分离株之间的系统发育关系和 SNP 距离。
