Project Summary/Abstract Despite the fundamental importance of the human gut microbiome in health and disease, a cohesive understanding of the core metabolic pathways of many human gut bacterial species is lacking. The Actinobacterium Eggerthella lenta is a notable example: it is highly prevalent, associated with bacteremia and the development of autoimmune disease, and capable of diverse transformations of endogenous and xenobiotic compounds, yet little is known about its nutrient requirements, metabolic regulation, and ecological niche. This project will investigate metabolic and ecological properties of E. lenta across multiple scales. It will use a combination of experimental and computational approaches to evaluate these properties across strains and species in the family Eggerthellaceae, taking advantage of a new resource of strain isolates and genomes. Preliminary experiments established defined minimal media formulations that support the growth of Eggerthellaceae and identified key growth determinants, including an unexpected growth benefit from acetate. Pilot metabolomics analysis of E. lenta cultured in minimal media revealed context-specific metabolism and production of host-relevant metabolites. This project will first quantify growth, metabolite fluxes, and gene expression of Eggerthellaceae strains across minimal nutrient contexts. The resulting data resource will be used to construct and analyze computational genome-scale metabolic models of these taxa. Next, co-culture studies of E. lenta strains with other gut microbial taxa will elucidate their ecological interactions and possible metabolite exchanges. Lastly, newly available collections of Eggerthellaceae genomes assembled from public metagenomic datasets will be analyzed to evaluate associations of genomic and metabolic features with host disease, geography, age, and microbiome composition. Overall, this work will provide insights into the metabolic, ecological, and evolutionary properties of this clade and its role in human health and disease. Moreover, the integration of in vitro profiling, cross-strain comparative analyses, and computational modeling demonstrated here is a generalizable framework for expanding scientific understanding of the metabolism of poorly characterized gut microbes. The fellowship training program will include skill development in experimental biology, research mentoring, and professional skills; supported by a collaborative and successful microbiome research community at a top-ranked institution.