MIM: Systematic Dissection of Complex Synthetic Gut Bacterial Communities

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The species composition of microbial communities is key to understanding their ecological functions. While the forces that determine composition are known to involve a complex network of interactions, general rules remain mysterious in part due to the lack of model systems with sufficient complexity that can be precisely tuned and experimentally dissected in a systematic fashion. This project will use a collection of the 100 most common gut microbes, to develop and analyze models of gut microbial communities of realistic complexity, yet defined composition at multiple scales, quantify the robustness of these communities to nutrient perturbations, and discover the interaction mechanisms most important for shaping these communities. This work is important because microbial communities are critical components of practically every ecosystem on the planet, including the healthy functioning of the guts of animals. This project also has educational goals, including: (1) to establish outreach programs at local high schools focused on a novel strategy for microbial isolation; (2) to provide quantitative training in theory, computational biology, and bioinformatics through the design of a project-based course; (3) to broaden participation of underrepresented minorities in microbiology through a novel partnership with UC Merced, a minority-serving institution, and via improving practices in graduate student admission and hiring practices through a series of workshops and materials; (4) to implement software for modeling microbial communities that is disseminated to local high schools. This project will combine high-throughput experimentation and mathematical modeling to produce a mechanistic understanding of the assembly and resilience of microbial communities. The research will perturb stable in vitro communities derived from fecal samples to ascertain whether the synthetic communities respond similarly to perturbations as in vivo. Critically, these defined communities enable the equivalent of genotype-phenotype mapping in a community context, to understand the roles of interspecies and strain-nutrient interactions on community structure and function in a quantitative manner that enables mechanistic modeling. Researchers will parameterize coarse-grained and molecular consumer-resource models to distinguish between modes of interaction and predict community dynamics, during growth in simple sugars, gut-relevant metabolites such as corrinoids, and complex media. The results will provide a mechanistic framework for understanding how nutritional and strain-strain interactions dictate the composition and stability of microbial communities. These scientific goals will be supplemented with broader impact achieved through course development, outreach, and other synergistic activities.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.