Scaltriti Erika, Bolzoni Luca, Vocale Caterina, Morganti Marina, Menozzi Ilaria, Re Maria Carla, Pongolini Stefano
Risk Analysis and Genomic Epidemiology Unit, Istituto Zooprofilattico Sperimentale della Lombardia e dell'Emilia-Romagna, Parma, Italy.
Operating Unit of Clinical Microbiology, Regional Reference Center for Microbiological Emergencies, St. Orsola-Malpighi Polyclinic, Bologna, Italy.
Front Public Health. 2020 Sep 18;8:519293. doi: 10.3389/fpubh.2020.519293. eCollection 2020.
The population structure of human isolates of in Emilia-Romagna, Italy, from 2012 to 2018 was investigated with the aim of evaluating the presence of genomic clusters indicative of possible outbreaks, the proportion of cluster-associated vs. sporadic isolates and different methods and metrics of genomic analysis for use in routine surveillance. In the 2012-2018 period the notification rate of confirmed invasive cases in Emilia-Romagna was 0.91 per 100,000 population per year, more than twice the average rate of EU countries. Out of the total 283 cases, 268 (about 95%) isolates were typed through whole genome sequencing (WGS) for cluster detection with methods based on core-genome multi-locus sequence typing and single nucleotide polymorphisms. Between 66 and 72% of listeriosis cases belonged to genomic clusters which included up to 27 cases and lasted up to 5 years. This proportion of cluster-associated cases is higher than previously estimated in other European studies. Rarefaction analysis, performed by reducing both the number of consecutive years of surveillance considered and the proportion of isolates included in the analysis, suggested that the observed high proportion of cluster-associated cases can be ascribed to the long surveillance duration (7 years) and the high notification and typing rates of this study. Our findings show that a long temporal perspective and high surveillance intensity, intended as both exhaustiveness of the system to report cases and high WGS-typing rate, are critical for sensitive detection of possible outbreaks within a WGS-based surveillance of listeriosis. Furthermore, the power and complexity of WGS interpretation emerged from the integration of genomic and epidemiological information in the investigation of few past outbreaks within the study, indicating that the use of multiple approaches, including the analysis of the accessory genome, is needed to accurately elucidate the population dynamics of .
对2012年至2018年意大利艾米利亚 - 罗马涅地区人类分离株的种群结构进行了调查，目的是评估表明可能爆发疫情的基因组簇的存在情况、与簇相关的分离株与散发病例分离株的比例，以及用于常规监测的基因组分析的不同方法和指标。在2012 - 2018年期间，艾米利亚 - 罗马涅地区确诊侵袭性病例的报告率为每年每10万人口0.91例，是欧盟国家平均水平的两倍多。在总共283例病例中，268株（约95%）分离株通过全基因组测序（WGS）进行分型，以便使用基于核心基因组多位点序列分型和单核苷酸多态性的方法检测簇。66%至72%的李斯特菌病病例属于基因组簇，其中包含多达27例病例，持续时间长达5年。这一与簇相关病例的比例高于其他欧洲研究先前的估计。通过减少所考虑的连续监测年份数量和分析中包含的分离株比例进行的稀疏分析表明，观察到的与簇相关病例的高比例可归因于本研究的长时间监测（7年）以及高报告率和分型率。我们的研究结果表明，从长时间角度和高监测强度来看，即系统报告病例的详尽程度和高WGS分型率，对于在基于WGS的李斯特菌病监测中灵敏检测可能的疫情爆发至关重要。此外，在研究中对过去少数疫情爆发的调查中，通过整合基因组和流行病学信息，凸显了WGS解释的能力和复杂性，这表明需要使用多种方法，包括对辅助基因组的分析，来准确阐明……的种群动态。
