PROJECT SUMMARY/ABSTRACT Clostridium difficile (C. difficile) is a major antibiotic resistant intestinal pathogen that is a leading cause of antibiotic associated diarrhea and colitis which, in severe cases, can lead to death. Treatment with antibiotics frequently leads to recurrence of the infection, which is then treated with fecal microbiota transplantation (FMT). In this case, a fecal sample from a healthy donor is transplanted into a patient with C. difficile infection, which has been shown to prevent recurrence of infections. Notably, FMT can lead to negative health outcomes including death due to the potential transmission of pathogens and uncharacterized factors in the samples. The observed efficacy of FMT suggests that commensal gut bacteria play a critical role in suppressing infection caused by C. difficile. Previous studies have elucidated specific molecular mechanisms that can influence C. difficile colonization including exploitation of key nutrients available in the inflamed gut and secondary bile acids. We postulate that there are diverse classes of ecological and molecular mechanisms mediating protection from C. difficile depending on the ecological and environmental context. Indeed, treatments of C. difficile infection based on defined microbiota have not proven successful. To elucidate the diverse classes of mechanisms, we propose to develop a droplet microfluidic workflow to construct millions of synthetic human gut communities, screen these consortia based on the abundance of C. difficile and determine species composition of the sorted “hits.” Combining this method with exo-metabolomics and machine learning techniques, we will infer microbial interactions and metabolite effectors impacting C. difficile growth. A detailed understanding of the diverse community types and metabolic properties that suppress C. difficile growth will be a major advance towards designing safe and effective treatments for this major intestinal pathogen.