P1237 Development of an algorithm to identify the best donor-recipient match for FMT in IBD patients based on immune system/microbiota interactions

Abstract Background IBD are characterized by uncontrolled immune responses, in genetically predisposed individuals, to the dysbiotic microbiota. Its modulation has thus emerged as a potential therapeutic strategy . Fecal microbiota transplantation (FMT) showed encouraging results for the treatment of mild-to-moderate ulcerative colitis (UC) patients. However, currently the success rate of FMT in UC patients is around 30%, and there are no criteria to predict it. We hypothesized that the immune system-microbiota interaction can dictate which graft will be accepted or rejected. Thus, we generated an algorithm to identify the best donor-recipient match for FMT treatment in IBD patients based on the functional interaction of recipient's immune system with possible donors' microbiota . Methods Mucosal and circulating immune cells isolated from 16 active UC patients, potentially eligible for FMT, were exposed to the microbiota of a panel of 8 potential healthy FM donors collected in the FM biobank of the Policlinico Hospital, Milan. The functional profile of recipients' immune cells before and after the in vitro exposure to the possible donors’ microbiota was assessed by cytokine production, gene expression profiling and activatory or inhibitory surface molecules modulation on T cells. Sequencing of the microbiota of each individual FM donor was performed by 16S. These functional data were used to develop an algorithm to identify the best donor-recipient match based on the capability of individual donors’ microbial ecologies to simultaneously reduce the inflammatory functional profile and increase the tolerogenic functional profile of the recipient's immune cells Results We demonstrated that mucosal immune cells from UC recipients exhibited a variety of responses upon exposure to the microbiota from distinct healthy donors, which clusters in two different enterotypes. Each UC recipient exhibited specific preferences for one or more FM donor in the reduction of the inflammatory profile of immune cells and concomitantly enhancement of anti-inflammatory cytokines. On te basis of these data we generated an algorithm capable of predicting the most successful functional interaction between donors and recipients. Conclusion Our study suggest that specific functional characteristics of both the donor microbiota and the recipient's immune system should be considered when selecting an optimal donor-recipient match for FMT. This study contributes to the development of a screening tool for donor selection in FMT, enabling personalized and effective therapeutic interventions for UC patients