Genetic diversity, virulence factors and farm-to-table spread pattern of Vibrio parahaemolyticus food-associated isolates.

Chao Yang, Xianglilan Zhang,Hang Fan, Yinghui Li,Qinghua Hu, Ruifu Yang,Yujun Cui

Food microbiology(2019)

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摘要
Vibrio parahaemolyticus is the leading bacterial cause of seafood-associated gastroenteritis worldwide. Moreover, infections and outbreaks caused by V. parahaemolyticus has kept increasing over the last two decades. In this study, we investigated the genetic diversity, virulence factors and farm-to-table spread pattern of V. parahaemolyticus by analyzing 383 genomes of food-associated isolates. These strains were isolated from diverse sample types from six provinces of China in 2014, being classified into three tiers of the farm-to-table spread process: food production, circulation and consumption. The genetic diversity of V. parahaemolyticus in different classifications, including geographical location, sample type, source and spread tier, was similar, as the median number of pairwise SNPs within each classification was between 33,013 and 33,659. Specifically, there was no clear boundaries in genetic diversity of the isolates from inland vs. coastal provinces, as well as of those from freshwater vs. seawater products. Moreover, the virulence genes and genomic islands were only found in a small number of isolates, indicating a low disease risk of the food-associated isolates in this study. By further exploring 28 recently emerged clonal groups, we identified seven farm-to-table spread events, showing a common pattern of single-source radial spread accompanied with occasional gene gain/loss events. Generally speaking, our work highlighted the colonization of V. parahaemolyticus in inland provinces and freshwater environment, and provided a snapshot of the farm-to-table spread pattern of V. parahaemolyticus food-associated isolates. Our results showed the feasibility of tracking the farm-to-table spread of foodborne pathogen, which would help construct the whole genome sequencing-based molecular tracking network in the future.
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