Bailey M Magers, Kyle D Brumfield, Sunil Kumar, Rita R Colwell, Antarpreet S Jutla
{"title":"机器学习在理解沿海水域弧菌病的环境变异性中的应用。","authors":"Bailey M Magers, Kyle D Brumfield, Sunil Kumar, Rita R Colwell, Antarpreet S Jutla","doi":"10.1128/aem.00716-25","DOIUrl":null,"url":null,"abstract":"<p><p><i>Vibrio spp.</i> comprise ecologically significant bacteria that thrive in warm, moderately saline water, and their incidence and proliferation are strongly influenced by environmental factors. In recent years, <i>Vibrio spp</i>. infections have been reported more frequently and over a greater geographical area along the US eastern seaboard. This study provides an analysis of <i>Vibrio spp</i>. infections, notably caused by <i>Vibrio alginolyticus</i>, <i>Vibrio cholerae</i> non-O1/non-O139, <i>Vibrio fluvialis</i>, <i>Vibrio mimicus</i>, <i>V. parahaemolyticus</i>, and <i>V. vulnificus</i>, extracted from the Centers for Disease Control and Prevention's Cholera and Other <i>Vibrio</i> Illness Surveillance system, located within 200 km of the eastern US coast, to analyze latitudinal distribution trends between 1990 and 2019. For each <i>Vibrio spp</i>., case incidence (presence/absence) was modeled, including environmental data and employing extreme gradient boosting machine learning algorithms (XGBoost). Environmental parameters associated with the incidence of vibriosis were clustered using k-means clustering. The northern limit of total cases of vibriosis was found to have increased <i>ca</i>. 40 km/year, with <i>V. alginolyticus</i> (<i>ca</i>. 70 km/year), <i>V. fluvialis</i> (<i>ca</i>. 60 km/year), and <i>Vibrio parahaemolyticus</i> (<i>ca</i>. 60 km/year) showing the greatest latitudinal shifts. These changes were found to be linked to environmental parameters that enhance the proliferation of <i>Vibrio spp</i>. The average accuracy of the XGBoost models was 60.9%-71.0%, with temperature and salinity being the most significant predictors. Relationships among other environmental parameters were complex and nonlinear, but phytoplankton and precipitation served to differentiate the models. Clustering using k-means yielded results that supported temperature, salinity, and phytoplankton as important environmental parameters. Research in progress will aid in developing global predictive risk models for <i>Vibrio spp</i>. infections.IMPORTANCE<i>Vibrio spp</i>. are ecologically significant bacteria, and their incidence and proliferation are strongly influenced by environmental factors. In recent years, <i>Vibrio spp</i>. infections have been reported more frequently and over a greater geographical area along the US eastern seaboard. This study provides an analysis of latitudinal distribution trends of <i>Vibrio spp</i>. infections, notably caused by <i>Vibrio alginolyticus</i>, <i>Vibrio cholerae</i> non-O1/non-O139, <i>Vibrio fluvialis</i>, <i>Vibrio mimicus</i>, <i>Vibrio parahaemolyticus</i>, and <i>V. vulnificus</i>, within 200 km of the eastern US coast. The northern limit of total cases of vibriosis was found to have increased <i>ca</i>. 40 km/year. These changes were found to be linked to environmental parameters that enhance the proliferation of <i>Vibrio spp</i>. Temperature and salinity were the most significant predictors of vibriosis case presence and absence. Phytoplankton and precipitation changes served to differentiate <i>Vibrio sp</i>. presence. Research in progress will aid in developing global predictive risk models for <i>Vibrio spp</i>. infections.</p>","PeriodicalId":8002,"journal":{"name":"Applied and Environmental Microbiology","volume":" ","pages":"e0071625"},"PeriodicalIF":3.7000,"publicationDate":"2025-09-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12442386/pdf/","citationCount":"0","resultStr":"{\"title\":\"Machine learning in understanding environmental variability of vibriosis in coastal waters.\",\"authors\":\"Bailey M Magers, Kyle D Brumfield, Sunil Kumar, Rita R Colwell, Antarpreet S Jutla\",\"doi\":\"10.1128/aem.00716-25\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><p><i>Vibrio spp.</i> comprise ecologically significant bacteria that thrive in warm, moderately saline water, and their incidence and proliferation are strongly influenced by environmental factors. In recent years, <i>Vibrio spp</i>. infections have been reported more frequently and over a greater geographical area along the US eastern seaboard. This study provides an analysis of <i>Vibrio spp</i>. infections, notably caused by <i>Vibrio alginolyticus</i>, <i>Vibrio cholerae</i> non-O1/non-O139, <i>Vibrio fluvialis</i>, <i>Vibrio mimicus</i>, <i>V. parahaemolyticus</i>, and <i>V. vulnificus</i>, extracted from the Centers for Disease Control and Prevention's Cholera and Other <i>Vibrio</i> Illness Surveillance system, located within 200 km of the eastern US coast, to analyze latitudinal distribution trends between 1990 and 2019. For each <i>Vibrio spp</i>., case incidence (presence/absence) was modeled, including environmental data and employing extreme gradient boosting machine learning algorithms (XGBoost). Environmental parameters associated with the incidence of vibriosis were clustered using k-means clustering. The northern limit of total cases of vibriosis was found to have increased <i>ca</i>. 40 km/year, with <i>V. alginolyticus</i> (<i>ca</i>. 70 km/year), <i>V. fluvialis</i> (<i>ca</i>. 60 km/year), and <i>Vibrio parahaemolyticus</i> (<i>ca</i>. 60 km/year) showing the greatest latitudinal shifts. These changes were found to be linked to environmental parameters that enhance the proliferation of <i>Vibrio spp</i>. The average accuracy of the XGBoost models was 60.9%-71.0%, with temperature and salinity being the most significant predictors. Relationships among other environmental parameters were complex and nonlinear, but phytoplankton and precipitation served to differentiate the models. Clustering using k-means yielded results that supported temperature, salinity, and phytoplankton as important environmental parameters. Research in progress will aid in developing global predictive risk models for <i>Vibrio spp</i>. infections.IMPORTANCE<i>Vibrio spp</i>. are ecologically significant bacteria, and their incidence and proliferation are strongly influenced by environmental factors. In recent years, <i>Vibrio spp</i>. infections have been reported more frequently and over a greater geographical area along the US eastern seaboard. This study provides an analysis of latitudinal distribution trends of <i>Vibrio spp</i>. infections, notably caused by <i>Vibrio alginolyticus</i>, <i>Vibrio cholerae</i> non-O1/non-O139, <i>Vibrio fluvialis</i>, <i>Vibrio mimicus</i>, <i>Vibrio parahaemolyticus</i>, and <i>V. vulnificus</i>, within 200 km of the eastern US coast. The northern limit of total cases of vibriosis was found to have increased <i>ca</i>. 40 km/year. These changes were found to be linked to environmental parameters that enhance the proliferation of <i>Vibrio spp</i>. Temperature and salinity were the most significant predictors of vibriosis case presence and absence. Phytoplankton and precipitation changes served to differentiate <i>Vibrio sp</i>. presence. Research in progress will aid in developing global predictive risk models for <i>Vibrio spp</i>. infections.</p>\",\"PeriodicalId\":8002,\"journal\":{\"name\":\"Applied and Environmental Microbiology\",\"volume\":\" \",\"pages\":\"e0071625\"},\"PeriodicalIF\":3.7000,\"publicationDate\":\"2025-09-17\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12442386/pdf/\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Applied and Environmental Microbiology\",\"FirstCategoryId\":\"99\",\"ListUrlMain\":\"https://doi.org/10.1128/aem.00716-25\",\"RegionNum\":2,\"RegionCategory\":\"生物学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"2025/8/14 0:00:00\",\"PubModel\":\"Epub\",\"JCR\":\"Q2\",\"JCRName\":\"BIOTECHNOLOGY & APPLIED MICROBIOLOGY\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Applied and Environmental Microbiology","FirstCategoryId":"99","ListUrlMain":"https://doi.org/10.1128/aem.00716-25","RegionNum":2,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"2025/8/14 0:00:00","PubModel":"Epub","JCR":"Q2","JCRName":"BIOTECHNOLOGY & APPLIED MICROBIOLOGY","Score":null,"Total":0}
Machine learning in understanding environmental variability of vibriosis in coastal waters.
Vibrio spp. comprise ecologically significant bacteria that thrive in warm, moderately saline water, and their incidence and proliferation are strongly influenced by environmental factors. In recent years, Vibrio spp. infections have been reported more frequently and over a greater geographical area along the US eastern seaboard. This study provides an analysis of Vibrio spp. infections, notably caused by Vibrio alginolyticus, Vibrio cholerae non-O1/non-O139, Vibrio fluvialis, Vibrio mimicus, V. parahaemolyticus, and V. vulnificus, extracted from the Centers for Disease Control and Prevention's Cholera and Other Vibrio Illness Surveillance system, located within 200 km of the eastern US coast, to analyze latitudinal distribution trends between 1990 and 2019. For each Vibrio spp., case incidence (presence/absence) was modeled, including environmental data and employing extreme gradient boosting machine learning algorithms (XGBoost). Environmental parameters associated with the incidence of vibriosis were clustered using k-means clustering. The northern limit of total cases of vibriosis was found to have increased ca. 40 km/year, with V. alginolyticus (ca. 70 km/year), V. fluvialis (ca. 60 km/year), and Vibrio parahaemolyticus (ca. 60 km/year) showing the greatest latitudinal shifts. These changes were found to be linked to environmental parameters that enhance the proliferation of Vibrio spp. The average accuracy of the XGBoost models was 60.9%-71.0%, with temperature and salinity being the most significant predictors. Relationships among other environmental parameters were complex and nonlinear, but phytoplankton and precipitation served to differentiate the models. Clustering using k-means yielded results that supported temperature, salinity, and phytoplankton as important environmental parameters. Research in progress will aid in developing global predictive risk models for Vibrio spp. infections.IMPORTANCEVibrio spp. are ecologically significant bacteria, and their incidence and proliferation are strongly influenced by environmental factors. In recent years, Vibrio spp. infections have been reported more frequently and over a greater geographical area along the US eastern seaboard. This study provides an analysis of latitudinal distribution trends of Vibrio spp. infections, notably caused by Vibrio alginolyticus, Vibrio cholerae non-O1/non-O139, Vibrio fluvialis, Vibrio mimicus, Vibrio parahaemolyticus, and V. vulnificus, within 200 km of the eastern US coast. The northern limit of total cases of vibriosis was found to have increased ca. 40 km/year. These changes were found to be linked to environmental parameters that enhance the proliferation of Vibrio spp. Temperature and salinity were the most significant predictors of vibriosis case presence and absence. Phytoplankton and precipitation changes served to differentiate Vibrio sp. presence. Research in progress will aid in developing global predictive risk models for Vibrio spp. infections.
期刊介绍:
Applied and Environmental Microbiology (AEM) publishes papers that make significant contributions to (a) applied microbiology, including biotechnology, protein engineering, bioremediation, and food microbiology, (b) microbial ecology, including environmental, organismic, and genomic microbiology, and (c) interdisciplinary microbiology, including invertebrate microbiology, plant microbiology, aquatic microbiology, and geomicrobiology.