Big data meets reductionist experimentation: A synthetic fecal transplant clarifies resistance to C. difficile infection
C. difficile, a major cause of antibiotic-associated diarrhea, is suppressed by the gut microbiome, but the precise mechanisms are not fully described. Through meta-analysis of 12 human studies, we designed a synthetic fecal microbiota transplant (sFMT1) by reconstructing microbial networks negatively associated with C. difficile colonization. This lab-built 37-strain consortium formed a functional community suppressing C. difficile in vitro and in animal models. Using sFMT1 as a tractable model system, we find that bile acid 7⍺-dehydroxylation is not a determinant of sFMT1 efficacy while a single strain performing Stickland fermentation, a pathway of competitive nutrient utilization, is both necessary and sufficient for suppression of C. difficile replicating the efficacy of a human fecal transplant in a gnotobiotic mouse model. These studies demonstrate a generalizable pipeline merging big data approaches with reductionist experimental models for the mechanistic interrogation of complex microbial communities.