Recent developments in genome sequencing open new opportunities for explaining the intraspecific variability of phenotypes (e.g. virulence, growth behavior). Successful association between WGS-data and specific phenotypes is thought to contribute to better predicting microbial behaviors. Implementing this information in hazard identification, exposure assessment, and hazard characterization processes will refine quantitative microbial risk assessments (QMRA) models. The aim of this study was to explore the refinements in QMRA studies when considering phenogenotype associations for the hazard properties, particularly related to the growth ability at low temperature (minimal growth temperature, T_min) and the virulence. The used QMRA-model was previously developed for the assessment of the number of listeriosis cases associated to cold-smoked salmon in France. The global prevalence in the existing model was replaced by the specific prevalence for each genotypic subgroup (clonal complex - CC) in Europe. In order to describe the variability of Listeria monocytogenes’ growth characteristics more accurately, two different distributions of T_min were implemented. For risk characterization, three different groups of virulence were considered according to the CCs. Each group was associated with a specific dose-response model. The new QMRA model showed that CCs contributing the most in consumer exposure were not those that contributed the most to listeriosis cases. The most prevailing CCs led to few listeriosis cases, whereas uncommon high virulent strains were responsible for the majority of predicted cases. Similarly, the less prevailing group of strains with high T_min was approximately two times less implicated when considering human listeriosis in comparison to food contamination. Considering genotypic data in QMRA opens the way for the establishment of risk based measures specific to distinct sub-groups of L. monocytogenes.

基因组测序的最新进展为解释表型的种内变异性（例如毒力，生长行为）提供了新的机会。WGS数据和特定表型之间的成功关联被认为有助于更好地预测微生物行为。在危害识别，暴露评估和危害表征过程中实施此信息将完善定量微生物风险评估（QMRA）模型。这项研究的目的是在考虑表型与危险特性的关联时，探索QMRA研究的改进，特别是与低温下的生长能力有关（最低生长温度，T _min）和毒力。以前使用过的QMRA模型是用于评估法国与冷熏鲑鱼有关的李斯特菌病病例数的。现有模型中的全球患病率已被欧洲每个基因型亚组（克隆复合体-CC）的特定患病率所取代。为了更准确地描述单核细胞增生李斯特菌的生长特征的变异性，T _min的两种不同分布被实施。为了进行风险表征，根据CC，考虑了三种不同的毒力组。每组均与特定的剂量反应模型相关。新的QMRA模型显示，在消费者接触中贡献最大的CC不是那些在李斯特菌病病例中贡献最大的CC。最流行的CC导致李斯特菌病病例很少，而罕见的高毒力菌株是大多数预测病例的原因。同样，与食品污染相比，考虑到人类李斯特菌病时，具有较高T _min的较不流行的菌株所涉及的几率要低大约两倍。考虑QMRA中的基因型数据，为建立针对单核细胞增生李斯特氏菌不同亚组的基于风险的措施开辟了道路。