Angie Mordant, J Alfredo Blakeley-Ruiz, Manuel Kleiner
{"title":"Metaproteomics-based stable isotope fingerprinting links intestinal bacteria to their carbon source and captures diet-induced substrate switching","authors":"Angie Mordant, J Alfredo Blakeley-Ruiz, Manuel Kleiner","doi":"10.1093/ismejo/wraf127","DOIUrl":null,"url":null,"abstract":"Diet has strong impacts on the composition and function of the gut microbiota with implications for host health. Therefore, it is critical to identify the dietary components that support growth of specific microorganisms in vivo. We used protein-based stable isotope fingerprinting (Protein-SIF) to link microbial species in gut microbiota to their carbon sources by measuring each microorganism’s natural 13C content (δ13C) and matching it to the 13C content of available substrates. We fed gnotobiotic mice, inoculated with a 13 member microbiota, diets in which the 13C content of all components was known. We varied the source of protein, fiber or fat to observe 13C signature changes in microbial consumers of these substrates. We observed significant changes in the δ13C values and abundances of specific microbiota species, as well as host proteins, in response to changes in 13C signature or type of protein, fiber, and fat sources. Using this approach we were able to show that upon switching dietary source of protein, fiber, or fat (1) some microbial species continued to obtain their carbon from the same dietary component (e.g., protein); (2) some species switched their main substrate type (e.g., from protein to carbohydrates); and (3) some species might derive their carbon through foraging on host compounds. Our results demonstrate that Protein-SIF can be used to identify the dietary-derived substrates assimilated into proteins by microorganisms in the intestinal tract; this approach holds promise for the analysis of microbiome substrate usage in humans without the need of substrate labeling.","PeriodicalId":516554,"journal":{"name":"The ISME Journal","volume":"18 1","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2025-06-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"The ISME Journal","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1093/ismejo/wraf127","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
Diet has strong impacts on the composition and function of the gut microbiota with implications for host health. Therefore, it is critical to identify the dietary components that support growth of specific microorganisms in vivo. We used protein-based stable isotope fingerprinting (Protein-SIF) to link microbial species in gut microbiota to their carbon sources by measuring each microorganism’s natural 13C content (δ13C) and matching it to the 13C content of available substrates. We fed gnotobiotic mice, inoculated with a 13 member microbiota, diets in which the 13C content of all components was known. We varied the source of protein, fiber or fat to observe 13C signature changes in microbial consumers of these substrates. We observed significant changes in the δ13C values and abundances of specific microbiota species, as well as host proteins, in response to changes in 13C signature or type of protein, fiber, and fat sources. Using this approach we were able to show that upon switching dietary source of protein, fiber, or fat (1) some microbial species continued to obtain their carbon from the same dietary component (e.g., protein); (2) some species switched their main substrate type (e.g., from protein to carbohydrates); and (3) some species might derive their carbon through foraging on host compounds. Our results demonstrate that Protein-SIF can be used to identify the dietary-derived substrates assimilated into proteins by microorganisms in the intestinal tract; this approach holds promise for the analysis of microbiome substrate usage in humans without the need of substrate labeling.