Public health implications of Yersinia enterocolitica investigation: an ecological modeling and molecular epidemiology study

Infectious Diseases of Poverty

Research Article

Yang Liu¹  Jinxin Zheng²  Xuezhang Zhou³  Yuan Yue⁴  Mei Sheng⁵  Qiong Hao⁵  Xiang Liu⁵  Shunxian Zhang⁶  Zhiguo Liu⁷  Huaiqi Jing⁷  Shuai Xu⁷  Zhenjun Li⁷  Xuexin Hou⁷ 

[1] Department of Computer Science, Hong Kong Baptist University, Hong Kong, Special Administrative Region, People’s Republic of China;Department of Nephrology, Ruijin Hospital, Institute of Nephrology, Shanghai Jiao Tong University School of Medicine, Shanghai, People’s Republic of China;School of Global Health, Chinese Center for Tropical Diseases Research-Shanghai Jiao Tong University School of Medicine, Shanghai, People’s Republic of China;Key Laboratory of the Ministry of Education for the Conservation and Utilization of Special Biological Resources of Western China, Ningxia University, Yinchuan, People’s Republic of China;Key Laboratory of the Ministry of Education for the Conservation and Utilization of Special Biological Resources of Western China, Ningxia University, Yinchuan, People’s Republic of China;State Key Laboratory for Infectious Disease Prevention and Control, National Institute for Communicable Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing, People’s Republic of China;Ningxia Hui Autonomous Region Food Testing and Research Institute, Yinchuan, People’s Republic of China;Ningxia Hui Autonomous Region Centre for Disease Control and Prevention, Yinchuan, People’s Republic of China;School of Global Health, Chinese Center for Tropical Diseases Research-Shanghai Jiao Tong University School of Medicine, Shanghai, People’s Republic of China;Longhua Hospital, Shanghai University of Traditional Chinese Medicine, Shanghai, People’s Republic of China;State Key Laboratory for Infectious Disease Prevention and Control, National Institute for Communicable Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing, People’s Republic of China;

关键词: Yersinia enterocolitica;    Ecological;    Machine learning;    Molecular epidemiology;    Core genome multilocus sequence typing;    Ningxia, China;   

DOI  :  10.1186/s40249-023-01063-6

 received in 2022-08-07, accepted in 2023-02-05,  发布年份 2023

来源: Springer

【 摘 要 】

BackgroundYersinia enterocolitica has been sporadically recovered from animals, foods, and human clinical samples in various regions of Ningxia, China. However, the ecological and molecular characteristics of Y. enterocolitica, as well as public health concerns about infection in the Ningxia Hui Autonomous Region, remain unclear. This study aims to analyze the ecological and molecular epidemiological characteristics of Y. enterocolitis in order to inform the public health intervention strategies for the contains of related diseases.MethodsA total of 270 samples were collected for isolation [animals (n = 208), food (n = 49), and patients (n = 13)], then suspect colonies were isolated and identified by the API20E biochemical identification system, serological tests, biotyping tests, and 16S rRNA-PCR. Then, we used an ecological epidemiological approach combined with machine learning algorithms (general linear model, random forest model, and eXtreme Gradient Boosting) to explore the associations between ecological factors and the pathogenicity of Y. enterocolitis. Furthermore, average nucleotide identity (ANI) estimation, single nucleotide polymorphism (SNP), and core gene multilocus sequence typing (cgMLST) were applied to characterize the molecular profile of isolates based on whole genome sequencing. The statistical test used single-factor analysis, Chi-square tests, t-tests/ANOVA-tests, Wilcoxon rank-sum tests, and Kruskal–Wallis tests.ResultsA total of 270 isolates of Yersinia were identified from poultry and livestock (n = 191), food (n = 49), diarrhoea patients (n = 13), rats (n = 15), and hamsters (n = 2). The detection rates of samples from different hosts were statistically different (χ2 = 22.636, P < 0.001). According to the relatedness clustering results, 270 isolates were divided into 12 species, and Y. enterocolitica (n = 187) is a predominated species. Pathogenic isolates made up 52.4% (98/187), while non-pathogenic isolates made up 47.6% (89/187). Temperature and precipitation were strongly associated with the pathogenicity of the isolates (P < 0.001). The random forest (RF) prediction model showed the best performance. The prediction result shows a high risk of pathogenicity Y. enterocolitica was located in the northern, northwestern, and southern of the Ningxia Hui Autonomous Region. The Y. enterocolitica isolates were classified into 54 sequence types (STs) and 125 cgMLST types (CTs), with 4/O:3 being the dominant bioserotype in Ningxia. The dominant STs and dominant CTs of pathogenic isolates in Ningxia were ST429 and HC100_2571, respectively.ConclusionsThe data indicated geographical variations in the distribution of STs and CTs of Y. enterocolitica isolates in Ningxia. Our work offered the first evidence that the pathogenicity of isolates was directly related to fluctuations in temperature and precipitation of the environment. CgMLST typing strategies showed that the isolates were transmitted to the population via pigs and food. Therefore, strengthening health surveillance on pig farms in high-risk areas and focusing on testing food of pig origin are optional strategies to prevent disease outbreaks.

【 授权许可】

CC BY   
© The Author(s) 2023

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