Colonizes Alternative Nutrient Niches during Infection across Distinct Murine Gut Microbiomes.

is the largest single cause of hospital-acquired infection in the United States. A major risk factor for infection (CDI) is prior exposure to antibiotics, as they disrupt the gut bacterial community which protects from colonization. Multiple antibiotic classes have been associated with CDI susceptibility, many leading to distinct community structures stemming from variation in bacterial targets of action. These community structures present separate metabolic challenges to . Therefore, we hypothesized that the pathogen adapts its physiology to the nutrients within different gut environments. Utilizing an CDI model, we demonstrated that highly colonized ceca of mice pretreated with any of three antibiotics from distinct classes. Levels of spore formation and toxin activity varied between animals based on the antibiotic pretreatment. These physiologic processes in are partially regulated by environmental nutrient concentrations. To investigate metabolic responses of the bacterium , we performed transcriptomic analysis of from ceca of infected mice across pretreatments. This revealed heterogeneous expression in numerous catabolic pathways for diverse growth substrates. To assess which resources exploited, we developed a genome-scale metabolic model with a transcriptome-enabled metabolite scoring algorithm integrating network architecture. This platform identified nutrients that used preferentially between pretreatments, which were validated through untargeted mass spectrometry of each microbiome. Our results supported the hypothesis that inhabits alternative nutrient niches across cecal microbiomes with increased preference for nitrogen-containing carbon sources, particularly Stickland fermentation substrates and host-derived glycans. Infection by the bacterium causes an inflammatory diarrheal disease which can become life threatening and has grown to be the most prevalent nosocomial infection. Susceptibility to infection is strongly associated with previous antibiotic treatment, which disrupts the gut microbiota and reduces its ability to prevent colonization. In this study, we demonstrated that altered pathogenesis between hosts pretreated with antibiotics from separate classes and exploited different nutrient sources across these environments. Our metabolite score calculation also provides a platform to study nutrient requirements of pathogens during an infection. Our results suggest that colonization resistance is mediated by multiple groups of bacteria competing for several subsets of nutrients and could explain why total reintroduction of competitors through fecal microbial transplant currently is the most effective treatment for recurrent CDI. This work could ultimately contribute to the identification of targeted, context-dependent measures that prevent or reduce colonization, including pre- and probiotic therapies.