Institute of Environmental Science and Researchgrid.419706.d Limited, Christchurch Science Centre, Ilam, Christchurch, New Zealand.
Institute of Environmental Science and Researchgrid.419706.d Limited, Kenepuru Science Centre, Porirua, Wellington, New Zealand.
J Clin Microbiol. 2021 Oct 19;59(11):e0084921. doi: 10.1128/JCM.00849-21. Epub 2021 Aug 18.
This study describes the epidemiology of listeriosis in New Zealand between 1999 and 2018 as well as the retrospective whole-genome sequencing (WGS) of 453 Listeria monocytogenes isolates corresponding to 95% of the human cases within this period. The average notified rate of listeriosis was 0.5 cases per 100,000 population, and non-pregnancy-associated cases were more prevalent than pregnancy-associated cases (averages of 19 and 5 cases per annum, respectively). WGS data was assessed using multilocus sequencing typing (MLST), including core-genome and whole-genome MLST (cgMLST and wgMLST, respectively) and single-nucleotide polymorphism (SNP) analysis. Thirty-nine sequence types (STs) were identified, with the most common being ST1 (21.9%), ST4 (13.2%), ST2 (11.3%), ST120 (6.1%), and ST155 (6.4%). A total of 291 different cgMLST types were identified, with the majority ( = 243) of types observed as a single isolate, consistent with the observation that listeriosis is predominately sporadic. Among the 49 cgMLST types containing two or more isolates, 18 cgMLST types were found with 2 to 4 isolates each (50 isolates in total, including three outbreak-associated isolates) that shared low genetic diversity (0 to 2 whole-genome alleles), some of which were dispersed in time or geographical regions. SNP analysis also produced results comparable to those from wgMLST. The low genetic diversity within these clusters suggests a potential common source, but incomplete epidemiological data impaired retrospective epidemiological investigations. Prospective use of WGS analysis together with thorough exposure information from cases could potentially identify future outbreaks more rapidly, including those that may have been undetected for some time over different geographical regions.
本研究描述了 1999 年至 2018 年间新西兰李斯特菌病的流行病学情况,以及同期 95%人类病例对应的 453 株单增李斯特菌的回顾性全基因组测序(WGS)结果。李斯特菌病的平均通报率为每 10 万人 0.5 例,非妊娠相关病例比妊娠相关病例更为普遍(平均每年分别为 19 例和 5 例)。WGS 数据通过多位点序列分型(MLST)进行评估,包括核心基因组和全基因组 MLST(cgMLST 和 wgMLST)和单核苷酸多态性(SNP)分析。共鉴定出 39 种序列型(ST),最常见的是 ST1(21.9%)、ST4(13.2%)、ST2(11.3%)、ST120(6.1%)和 ST155(6.4%)。共鉴定出 291 种不同的 cgMLST 型,其中大多数( = 243)为单一分离株,这与李斯特菌病主要呈散发性的观察结果一致。在包含两个或更多分离株的 49 种 cgMLST 型中,有 18 种 cgMLST 型各包含 2 至 4 个分离株(共 50 个分离株,包括 3 个与暴发相关的分离株),这些分离株的遗传多样性较低(0 至 2 个全基因组等位基因),其中一些在时间或地理区域上分散。SNP 分析也得到了与 wgMLST 相似的结果。这些聚类中较低的遗传多样性表明存在潜在的共同来源,但回顾性流行病学调查因不完全的流行病学数据而受到影响。前瞻性地使用 WGS 分析结合病例的详细暴露信息,有可能更快地识别未来的暴发,包括那些在不同地理区域可能已经存在一段时间而未被发现的暴发。