Clostridioides difficile (C. difficile) colonizes up to 40% of community-dwelling adults without causing disease but can eventually lead to infection (C. difficile infection [CDI]). There has been a lack of focus on how to prevent colonization and facilitate the successful clearance of C. difficile prior to the emergence of CDI. We show that microbial community-scale metabolic models (MCMMs) accurately predict C. difficile colonization susceptibility in vitro and in vivo, offering mechanistic insights into microbiota-specific interactions involving metabolites like succinate, trehalose, and ornithine. MCMMs reveal distinct C. difficile metabolic niches—two growth-associated and one non-growth-associated—observed across 15,204 individuals from five cohorts. We further demonstrate that MCMMs can predict personalized C. difficile growth suppression by a probiotic cocktail designed to replace fecal microbiota transplants (FMTs) for the treatment of recurrent CDI, and we identify new probiotic targets for future validation. MCMMs represent a powerful framework for predicting pathogen colonization and assessing probiotic efficacy across diverse microbiota contexts.

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Virtually every surface of our planet is colonized by microbes and the human body is no exception. The 38 trillion microbes living in our gut metabolize a large fraction of the dietary metabolites, pharmaceutical drugs, and xenobiotics we consume and thus provide an important interface between the environment and our blood stream.

Whereas many of the species forming the human gut microbiome have been well-characterized by now, we still know very little about the factors that determine which microbial species can coexist in any given individual. This currently limits our understanding regarding engraftment of pathogens and probiotics and how those will interact with other microbes and host tissues in the human gut.