Abstract：
BACKGROUND: Salmonella spp. is a major foodborne pathogen with a wide variety of serovars associated with human cases and food sources. Nevertheless, in Europe a panel of ten serovars is responsible for up to 80% of confirmed human cases. Clustering studies by single nucleotide polymorphism (SNP) core-genome phylogenetic analysis of outbreaks due to these major serovars are simplified by the availability of many complete genomes in the free access databases. This is not the case for outbreaks due to less common serovars, such as Welikade, for which no reference genomes are available. In this study, we propose a method to solve this problem. We propose to perform a core genome MLST (cgMLST) analysis based on hierarchical clustering using the free-access EnteroBase to select the most suitable genome to use as a reference for SNP phylogenetic analysis. In this study, we applied this protocol to a retrospective analysis of a Salmonella enterica serovar Welikade (S. Welikade) foodborne outbreak that occurred in France in 2016. Finally, we compared the cgMLST and SNP analyses. SNP phylogenetic reconstruction was carried out considering the effect of recombination events identified by the ClonalFrameML tool. The accessory genome was also explored by phage content and virulome analyses.
RESULTS: Our findings revealed high clustering concordance using cgMLST and SNP analyses. Nevertheless, SNP analysis allowed for better assessment of the genetic distance among strains. The results revealed epidemic clones of S. Welikade circulating within the poultry and dairy sectors in France, responsible for sporadic and non-sporadic human cases between 2012 and 2019.
CONCLUSIONS: This study increases knowledge on this poorly described serovar and enriches public genome databases with 42 genomes from human and non-human S. Welikade strains, including the isolate collected in 1956 in Sri Lanka, which gave the name to this serovar. This is the first genomic analysis of an outbreak due to S. Welikade described to date.
RESULTS: Our findings revealed high clustering concordance using cgMLST and SNP analyses. Nevertheless, SNP analysis allowed for better assessment of the genetic distance among strains. The results revealed epidemic clones of S. Welikade circulating within the poultry and dairy sectors in France, responsible for sporadic and non-sporadic human cases between 2012 and 2019.
CONCLUSIONS: This study increases knowledge on this poorly described serovar and enriches public genome databases with 42 genomes from human and non-human S. Welikade strains, including the isolate collected in 1956 in Sri Lanka, which gave the name to this serovar. This is the first genomic analysis of an outbreak due to S. Welikade described to date.
摘要：
背景：沙门氏菌。是一种主要的食源性病原体，具有与人类病例和食物来源相关的多种血清变型。然而，在欧洲，由10个血清型组成的小组负责多达80％的确诊人类病例。通过在免费访问数据库中提供许多完整的基因组，简化了通过单核苷酸多态性（SNP）核心基因组系统发育分析对这些主要血清型爆发的聚类研究。由于不太常见的血清变型而爆发的情况并非如此，比如Welikade,没有参考基因组。在这项研究中,我们提出了解决这个问题的方法。我们建议使用自由访问EnteroBase进行基于层次聚类的核心基因组MLST（cgMLST）分析，以选择最合适的基因组作为SNP系统发育分析的参考。在这项研究中,我们将该方案应用于肠道沙门氏菌Welikade的回顾性分析(S.Welikade)2016年在法国发生的食源性疫情。最后,我们比较了cgMLST和SNP分析。考虑到通过ClonalFrameML工具鉴定的重组事件的影响,进行SNP系统发育重建。还通过噬菌体含量和病毒组分析探索了辅助基因组。
结果：我们的发现显示了使用cgMLST和SNP分析的高度聚类一致性。然而，SNP分析可以更好地评估菌株之间的遗传距离。结果显示，在法国的家禽和奶制品部门中流行的S.Welikade流行克隆，负责2012年至2019年期间的零星和非零星人类病例。
结论：这项研究增加了对这种描述不佳的血清型的认识，并丰富了来自人类和非人类S.Welikade菌株的42个基因组的公共基因组数据库，包括1956年在斯里兰卡收集的分离株，给这个血清型命名。这是迄今为止描述的S.Welikade爆发的首次基因组分析。
结果：我们的发现显示了使用cgMLST和SNP分析的高度聚类一致性。然而，SNP分析可以更好地评估菌株之间的遗传距离。结果显示，在法国的家禽和奶制品部门中流行的S.Welikade流行克隆，负责2012年至2019年期间的零星和非零星人类病例。
结论：这项研究增加了对这种描述不佳的血清型的认识，并丰富了来自人类和非人类S.Welikade菌株的42个基因组的公共基因组数据库，包括1956年在斯里兰卡收集的分离株，给这个血清型命名。这是迄今为止描述的S.Welikade爆发的首次基因组分析。
