Ruppitsch Werner, Pietzka Ariane, Prior Karola, Bletz Stefan, Fernandez Haizpea Lasa, Allerberger Franz, Harmsen Dag, Mellmann Alexander
German-Austrian Binational Consiliary Laboratory for Listeria, Austrian Agency for Health and Food Safety (AGES), Vienna, Austria
German-Austrian Binational Consiliary Laboratory for Listeria, Austrian Agency for Health and Food Safety (AGES), Vienna, Austria.
J Clin Microbiol. 2015 Sep;53(9):2869-76. doi: 10.1128/JCM.01193-15. Epub 2015 Jul 1.
Whole-genome sequencing (WGS) has emerged today as an ultimate typing tool to characterize Listeria monocytogenes outbreaks. However, data analysis and interlaboratory comparability of WGS data are still challenging for most public health laboratories. Therefore, we have developed and evaluated a new L. monocytogenes typing scheme based on genome-wide gene-by-gene comparisons (core genome multilocus the sequence typing [cgMLST]) to allow for a unique typing nomenclature. Initially, we determined the breadth of the L. monocytogenes population based on MLST data with a Bayesian approach. Based on the genome sequence data of representative isolates for the whole population, cgMLST target genes were defined and reappraised with 67 L. monocytogenes isolates from two outbreaks and serotype reference strains. The Bayesian population analysis generated five L. monocytogenes groups. Using all available NCBI RefSeq genomes (n = 36) and six additionally sequenced strains, all genetic groups were covered. Pairwise comparisons of these 42 genome sequences resulted in 1,701 cgMLST targets present in all 42 genomes with 100% overlap and ≥90% sequence similarity. Overall, ≥99.1% of the cgMLST targets were present in 67 outbreak and serotype reference strains, underlining the representativeness of the cgMLST scheme. Moreover, cgMLST enabled clustering of outbreak isolates with ≤10 alleles difference and unambiguous separation from unrelated outgroup isolates. In conclusion, the novel cgMLST scheme not only improves outbreak investigations but also enables, due to the availability of the automatically curated cgMLST nomenclature, interlaboratory exchange of data that are crucial, especially for rapid responses during transsectorial outbreaks.
全基因组测序(WGS)如今已成为鉴定单核细胞增生李斯特菌暴发的终极分型工具。然而,对于大多数公共卫生实验室而言,WGS数据的分析及实验室间的可比性仍具有挑战性。因此,我们开发并评估了一种基于全基因组逐基因比较的新型单核细胞增生李斯特菌分型方案(核心基因组多位点序列分型[cgMLST]),以实现独特的分型命名法。最初,我们采用贝叶斯方法基于多位点序列分型(MLST)数据确定了单核细胞增生李斯特菌群体的广度。基于全体代表性菌株的基因组序列数据,定义了cgMLST目标基因,并用来自两次暴发的67株单核细胞增生李斯特菌分离株及血清型参考菌株进行了重新评估。贝叶斯群体分析产生了5个单核细胞增生李斯特菌组。使用所有可用的NCBI RefSeq基因组(n = 36)和另外6株测序菌株,涵盖了所有遗传组。对这42个基因组序列进行成对比较,结果显示所有42个基因组中存在1701个cgMLST目标,重叠率为100%,序列相似性≥90%。总体而言,≥99.1%的cgMLST目标存在于67株暴发菌株和血清型参考菌株中,突出了cgMLST方案的代表性。此外,cgMLST能够将暴发分离株聚类,等位基因差异≤10个,并与无关的外群分离株明确区分。总之,新型cgMLST方案不仅改善了暴发调查,而且由于自动整理的cgMLST命名法的可用性,还实现了实验室间的数据交换,这对于跨部门暴发期间的快速响应尤为关键。