{"title":"人类肠道菌群对膳食纤维的时间反应模式","authors":"Xiaotong Lin, Chaoxun Wang, Biao Liu, Yin Zhu, Rui Zhai, Chenhong Zhang","doi":"10.1002/imt2.70046","DOIUrl":null,"url":null,"abstract":"<p>The gut microbiota is a highly dynamic and complex ecosystem. However, the processes by which its members respond to dietary fibers remain incompletely understood. Here, we performed daily sampling over a 14-day observational period under the habitual diet, followed by a 14-day dietary fiber intervention in overweight participants with and without type 2 diabetes mellitus. By combining daily sampling, guild-level approach, and time-series analysis, we revealed diverse temporal response patterns among various microbiota members that are often missed by conventional sampling. These patterns were closely linked to their genetic capacities for carbohydrate utilization and transport. Moreover, time-delayed analysis of longitudinal multi-omics data identified specific metabolites that potentially mediate the beneficial effects of gut microbiota on host metabolism. Overall, our findings demonstrate the necessity of high-frequency sampling for capturing dynamic microbial responses and offer reliable targets for mechanistic investigations.</p>","PeriodicalId":73342,"journal":{"name":"iMeta","volume":"4 4","pages":""},"PeriodicalIF":23.7000,"publicationDate":"2025-05-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/imt2.70046","citationCount":"0","resultStr":"{\"title\":\"Temporal response patterns of human gut microbiota to dietary fiber\",\"authors\":\"Xiaotong Lin, Chaoxun Wang, Biao Liu, Yin Zhu, Rui Zhai, Chenhong Zhang\",\"doi\":\"10.1002/imt2.70046\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p>The gut microbiota is a highly dynamic and complex ecosystem. However, the processes by which its members respond to dietary fibers remain incompletely understood. Here, we performed daily sampling over a 14-day observational period under the habitual diet, followed by a 14-day dietary fiber intervention in overweight participants with and without type 2 diabetes mellitus. By combining daily sampling, guild-level approach, and time-series analysis, we revealed diverse temporal response patterns among various microbiota members that are often missed by conventional sampling. These patterns were closely linked to their genetic capacities for carbohydrate utilization and transport. Moreover, time-delayed analysis of longitudinal multi-omics data identified specific metabolites that potentially mediate the beneficial effects of gut microbiota on host metabolism. Overall, our findings demonstrate the necessity of high-frequency sampling for capturing dynamic microbial responses and offer reliable targets for mechanistic investigations.</p>\",\"PeriodicalId\":73342,\"journal\":{\"name\":\"iMeta\",\"volume\":\"4 4\",\"pages\":\"\"},\"PeriodicalIF\":23.7000,\"publicationDate\":\"2025-05-10\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://onlinelibrary.wiley.com/doi/epdf/10.1002/imt2.70046\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"iMeta\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://onlinelibrary.wiley.com/doi/10.1002/imt2.70046\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"MICROBIOLOGY\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"iMeta","FirstCategoryId":"1085","ListUrlMain":"https://onlinelibrary.wiley.com/doi/10.1002/imt2.70046","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"MICROBIOLOGY","Score":null,"Total":0}
Temporal response patterns of human gut microbiota to dietary fiber
The gut microbiota is a highly dynamic and complex ecosystem. However, the processes by which its members respond to dietary fibers remain incompletely understood. Here, we performed daily sampling over a 14-day observational period under the habitual diet, followed by a 14-day dietary fiber intervention in overweight participants with and without type 2 diabetes mellitus. By combining daily sampling, guild-level approach, and time-series analysis, we revealed diverse temporal response patterns among various microbiota members that are often missed by conventional sampling. These patterns were closely linked to their genetic capacities for carbohydrate utilization and transport. Moreover, time-delayed analysis of longitudinal multi-omics data identified specific metabolites that potentially mediate the beneficial effects of gut microbiota on host metabolism. Overall, our findings demonstrate the necessity of high-frequency sampling for capturing dynamic microbial responses and offer reliable targets for mechanistic investigations.