Microbial communities are critically important for many environmental processes such as the release of nutrients from the degradation of dead organic matter. Microbial communities are also important for health, as beneficial microbes help digest food, modulate immunity, and fend off intruding pathogens. Each species of microbe in the community uses certain compounds available in the environment and often the microbes release new compounds that other members of the community can use. These "metabolic interactions" impact the survival of individual species and the stability of the microbial community as a whole. The goal of this collaborative project is to better understand how these interactions develop and change depending on the environment and microbial species in the community, and how these interactions change the stability and composition of the communities. Ultimately, this project aims to reveal principles for the design of microbial communities for purposes such environmental remediation. Participants on this project will include high school teachers, underrepresented minority high school students, and underrepresented minority undergraduates.
Microbial communities are ubiquitous, and are critical players in mediating host health and disease and in the cycling of elements in ecosystems. Metabolic interactions between species impact community function and stability. However, the emergence and evolution of metabolic interactions is poorly understood. The laboratories involved in this project will take advantage of tractable synthetic yeast communities and mathematical modeling to experimentally and theoretically study the origin and evolution of metabolic interactions. They will undertake a fully integrated, collaborative approach that combines the expertise of both groups on metabolic modeling, synthetic biology, and microbial ecology and evolution. First, statistical thermodynamics and differential equations will be used to model metabolic overflows. Next, metabolic overflows as well as key cellular parameters will be experimentally characterized using targeted metabolomics, fluorescence microscopy, and single cell electrochemical measurements. These experimental measurements will be used to constrain, test, and refine the model. The tested model will be embedded within an in silico evolution framework to simulate evolution, and to predict how initial community conditions (e.g. nutrient environment, genotypes, and species interactions) might affect the evolution of new metabolic interactions. Finally, model predictions will be tested by evolving synthetic yeast communities from different starting conditions in chemostats and turbidostats, and emerging metabolic interactions will be characterized.
This collaborative US/UK project is supported by the US National Science Foundation and the UK Biotechnology and Biological Sciences Research Council.
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.
