Public health implications of Yersinia enterocolitica investigation: an ecological modeling and molecular epidemiology study
Abstract Background Yersinia 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 Ningx...
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| Format: | Article |
| Language: | English |
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BMC
2023-04-01
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| Series: | Infectious Diseases of Poverty |
| Subjects: | |
| Online Access: | https://doi.org/10.1186/s40249-023-01063-6 |
| _version_ | 1797827296942358528 |
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| author | Yuan Yue Jinxin Zheng Mei Sheng Xiang Liu Qiong Hao Shunxian Zhang Shuai Xu Zhiguo Liu Xuexin Hou Huaiqi Jing Yang Liu Xuezhang Zhou Zhenjun Li |
| author_facet | Yuan Yue Jinxin Zheng Mei Sheng Xiang Liu Qiong Hao Shunxian Zhang Shuai Xu Zhiguo Liu Xuexin Hou Huaiqi Jing Yang Liu Xuezhang Zhou Zhenjun Li |
| author_sort | Yuan Yue |
| collection | DOAJ |
| description | Abstract Background Yersinia 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. Methods A 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. Results A 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 (χ 2 = 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. Conclusions The 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. |
| first_indexed | 2024-04-09T12:46:19Z |
| format | Article |
| id | doaj.art-82e1082216c7480ea65ec208a2a38550 |
| institution | Directory Open Access Journal |
| issn | 2049-9957 |
| language | English |
| last_indexed | 2024-04-09T12:46:19Z |
| publishDate | 2023-04-01 |
| publisher | BMC |
| record_format | Article |
| series | Infectious Diseases of Poverty |
| spelling | doaj.art-82e1082216c7480ea65ec208a2a385502023-05-14T11:31:26ZengBMCInfectious Diseases of Poverty2049-99572023-04-0112111510.1186/s40249-023-01063-6Public health implications of Yersinia enterocolitica investigation: an ecological modeling and molecular epidemiology studyYuan Yue0Jinxin Zheng1Mei Sheng2Xiang Liu3Qiong Hao4Shunxian Zhang5Shuai Xu6Zhiguo Liu7Xuexin Hou8Huaiqi Jing9Yang Liu10Xuezhang Zhou11Zhenjun Li12Key Laboratory of the Ministry of Education for the Conservation and Utilization of Special Biological Resources of Western China, Ningxia UniversityDepartment of Nephrology, Ruijin Hospital, Institute of Nephrology, Shanghai Jiao Tong University School of MedicineNingxia Hui Autonomous Region Centre for Disease Control and PreventionNingxia Hui Autonomous Region Centre for Disease Control and PreventionNingxia Hui Autonomous Region Centre for Disease Control and PreventionSchool of Global Health, Chinese Center for Tropical Diseases Research-Shanghai Jiao Tong University School of MedicineState Key Laboratory for Infectious Disease Prevention and Control, National Institute for Communicable Disease Control and Prevention, Chinese Center for Disease Control and PreventionState Key Laboratory for Infectious Disease Prevention and Control, National Institute for Communicable Disease Control and Prevention, Chinese Center for Disease Control and PreventionState Key Laboratory for Infectious Disease Prevention and Control, National Institute for Communicable Disease Control and Prevention, Chinese Center for Disease Control and PreventionState Key Laboratory for Infectious Disease Prevention and Control, National Institute for Communicable Disease Control and Prevention, Chinese Center for Disease Control and PreventionDepartment of Computer Science, Hong Kong Baptist UniversityKey Laboratory of the Ministry of Education for the Conservation and Utilization of Special Biological Resources of Western China, Ningxia UniversityState Key Laboratory for Infectious Disease Prevention and Control, National Institute for Communicable Disease Control and Prevention, Chinese Center for Disease Control and PreventionAbstract Background Yersinia 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. Methods A 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. Results A 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 (χ 2 = 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. Conclusions The 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.https://doi.org/10.1186/s40249-023-01063-6Yersinia enterocoliticaEcologicalMachine learningMolecular epidemiologyCore genome multilocus sequence typingNingxia, China |
| spellingShingle | Yuan Yue Jinxin Zheng Mei Sheng Xiang Liu Qiong Hao Shunxian Zhang Shuai Xu Zhiguo Liu Xuexin Hou Huaiqi Jing Yang Liu Xuezhang Zhou Zhenjun Li Public health implications of Yersinia enterocolitica investigation: an ecological modeling and molecular epidemiology study Infectious Diseases of Poverty Yersinia enterocolitica Ecological Machine learning Molecular epidemiology Core genome multilocus sequence typing Ningxia, China |
| title | Public health implications of Yersinia enterocolitica investigation: an ecological modeling and molecular epidemiology study |
| title_full | Public health implications of Yersinia enterocolitica investigation: an ecological modeling and molecular epidemiology study |
| title_fullStr | Public health implications of Yersinia enterocolitica investigation: an ecological modeling and molecular epidemiology study |
| title_full_unstemmed | Public health implications of Yersinia enterocolitica investigation: an ecological modeling and molecular epidemiology study |
| title_short | Public health implications of Yersinia enterocolitica investigation: an ecological modeling and molecular epidemiology study |
| title_sort | public health implications of yersinia enterocolitica investigation an ecological modeling and molecular epidemiology study |
| topic | Yersinia enterocolitica Ecological Machine learning Molecular epidemiology Core genome multilocus sequence typing Ningxia, China |
| url | https://doi.org/10.1186/s40249-023-01063-6 |
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