Microbiota-Ulcerative Colitis INterface: Phage-bacteria-immune interactions at the mucosal level.

Objetivo

Ulcerative colitis (UC) is a chronic inflammatory bowel disease marked by persistent mucosal inflammation and impaired gut barrier function. Its etiology remains partly unknown, and no definitive cure exists. While UC has been linked to gut microbiome (GM) alterations, its precise involvement remains unclear. Most research has focused on luminal bacteria, whereas emerging evidence suggests that the mucosal GM (mGM) may play a more critical role. In addition, phages, viruses that infect bacteria, may influence human health by reshaping bacterial communities and by directly stimulating the immune system through yet undefined mechanisms. The inflammatory potential of mucosal bacteria and phages in UC, however, remains unexplored.

This project will apply a multidisciplinary strategy to characterize the mGM–immune interface in UC at the mucosal level. Using datasets, infrastructure, and expertise from the host institution, secondment, and non-academic placement, GM DNA and human RNA will be sequenced from mucosal biopsies to profile the mGM and local immune activation. These datasets will be integrated to identify microbial features with inflammatory potential. Candidate phage immunogenicity will be validated in vitro and ex vivo. Alterations in microbial inflammatory signatures after faecal microbiota transplantation (FMT), a promising UC therapy, will be linked to clinical outcomes to assess FMT’s therapeutic potential. Finally, predictive modelling will identify stool-based biomarkers of mGM composition and inflammation.

By capitalizing on unique patient samples, state-of-the-art methods, and multidisciplinary expertise, this project will clarify the inflammatory potential of phages, provide new insights into UC etiology, and advance microbiome research by linking stool biomarkers to mucosal microbial–immune interactions, ultimately supporting the development of non-invasive tools for disease monitoring and detection.