Abstract Background Ulcerative colitis (UC) is a chronic inflammatory disease of the colon with multifactorial aetiology involving genetic, immune, environmental, and microbial factors. Alterations in the gut microbiome are a consistent feature of UC, yet their causal contribution to disease onset and progression remains unresolved. Current animal models rely largely on chemical or genetic induction and fail to capture the complexity of host-microbiome interactions characteristic of human disease. To address this limitation and enhance the translational relevance of preclinical research, this study employed patient-derived microbiota to model UC-associated dysbiosis and investigated its effects alone and in combination with chemical induction. Results We compared three mouse models using different UC-induction triggers: dextran sulphate sodium (DSS), faecal microbiota transplantation (FMT) from a UC patient, and their combination (COMB). DSS and COMB treatments induced marked clinical symptoms, whereas FMT alone caused only mild changes, likely due to the short exposure period. Immunophenotyping revealed distinct immune profiles across all models, with leukocyte and neutrophil infiltration in the colonic mucosa of all groups, demonstrating that the microbiota alone can elicit localized immune activation. Transcriptomic analysis showed that FMT significantly modulated tight junction and mucin gene expression and induced microbiome shifts resembling those observed in human UC. In contrast, DSS triggered a strong pro-inflammatory transcriptional response and reduced microbial diversity, but with compositional changes mostly opposing those seen in UC patients. The COMB model combined features of both approaches – producing clinical symptoms and inflammatory activation similar to DSS and tight junction dysregulation resembling FMT. Conclusions This study investigated novel experimental models of ulcerative colitis by incorporating patient-derived microbiota as an inducing factor. DSS induced strong clinical and inflammatory responses, FMT primarily altered barrier gene expression and microbiome composition, and their combination merged both inflammatory and epithelial characteristics. These microbiota-based models show promise for more accurately reproducing UC pathophysiology and thereby improving translational relevance. Further optimization is needed, including adjustment of exposure duration and sequence of induction, as well as validation for reproducibility.
Rynikova et al. (Mon,) studied this question.