The gastrointestinal microbiota in the gut interacts metabolically and immnunologically with the host tissue in the contact zone of the mucus layer. For understanding the detail's of these interactions and especially their dynamics it is crucial to identify the metabolically active subset of the microbiome. This became possible by the development of stable isotope probing techniques, which have only sparsely been applied to microbiome research. We applied the in vivo stable isotope approach using N-15-labeled diet with subsequent identification of metabolically active bacterial species. Four-week old male Sprague Dawley rats were randomly assigned to chow diet (CD, n=15) and high-fat diet (HFD, n=15). After 11 weeks, three animals from each group were sacrificed for baseline characterization of anthropometric and metabolic obesity. The remaining animals were exposed to either a N-15-labeled (n=9) or a N-14-unlabeled experimental diet (n=3). Three rats from each cohort (HFD and CD) were sacrificed at 12, 24, and 72 h. The remaining three animals from each cohort, which received the N-14-unlabeled diet, were sacrificed after 72 h. The colon was harvested and divided into three equal sections (proximal; medial, and distal), and the mucus layer of each specimen Was sampled by scraping. We identified the active subset in an HFD model of obesity in comparison with lean controls rats using metaproteomics. In addition, all samples were investigated by 16S rRNA amplicon gene sequencing. The active microbiome of the HFD group showed an increase in bacterial taxa for Verrucomicrobia and Desulfovibrionaceae. In contrast with no significant changes in alpha diversity, time- and localization-dependent effects in beta-diversity were clearly observed. In terms of enzymatic functions the HFD group showed strong affected metabolic pathways such as energy production and carbohydrate metabolism. In vivo isotope labeling combined with metaproteomics provides a valuable method to distinguish the active from the non-active bacterial phylogenetic groups that are relevant for microbiota host interaction. For morbid obesity such analysis may provide potentially new strategies for targeted pre- or probiotic treatments.