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Abstract

Microbes play a significant role in supporting life on our planet, and their metabolic capabilities mediate their interactions with each other and with their environments. In host-associated communities such as the human gut microbiome, microbes have been implicated in a variety of host physiological processes. Indeed, dysbiosis of the human gut microbiome is associated with several diseases and disorders. In the marine environment, microbes contribute to important biogeochemical cycles such as nitrogen fixation. The ability to predict metabolic capacity is thus critical to understanding microbial ecology in these systems. This thesis presents a novel software framework for estimating metabolic potential from ‘omics data and showcases its application to studies of the human gut microbiome and the marine microbiome. In the human gut, high metabolic independence emerges as a determinant of microbial fitness in the face of gut stress, as demonstrated by a longitudinal time-series analysis of colonization after fecal microbiota transplant (FMT) and a high-throughput meta-analysis of community metabolism in individuals with inflammatory bowel disease (IBD). In studies of the global surface oceans, this framework identifies an understudied yet abundant group of heterotrophic bacterial diazotrophs. Overall, this new tool facilitates diverse and flexible analyses of microbial metabolism from ‘omics datasets, leading to interesting insights into microbial ecology that are relevant to both human health and the health of the planet.

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