Everything in our world is covered in complex communities of microorganisms called microbiomes. These microbiomes are important for human health, clean environments, and productive crops. Since they are much smaller than their hosts, microorganisms can evolve much faster. Within the microbiomes, some theoretical models predict that faster evolution will result in microorganisms that cause more severe disease, whereas other models predict that faster evolution will cause beneficial microorganisms to become even more beneficial. Understanding when each of these outcomes occurs will be important for coming up with strategies to manage microbiomes. This project will use coevolutionary theoretical models to understand how communities of microorganisms that colonize the roots of clover plants interact and evolve. Clover is a relative of many crop plants such as beans, alfalfa, and chickpeas, and this information can be used to improve agricultural yield and soil health. Students will be trained in methods to study these microorganisms and will isolate strains, analyze genomes and physiology, and measure ecological interactions. The project will recruit underserved Native American students in the Pacific Northwest. This project will also produce a coevolutionary video game that will combine outreach and education with research. A symposium bringing together student researchers, empiricists, and theoreticians will catalyze transformative research in this rapidly moving field.
Host-associated microbial communities are key mediators of host traits and ecosystem processes, and a scientific frontier is understanding how these communities interact and coevolve in nature. Clover nodule-associated microorganismal communities are an ideal model system to study these processes. This project has three key elements: (1) an accessible field system at Bodega Bay, amenable to the collection of long-term data on both hosts and associated microorganisms, (2) the ability to bring key players into the lab to measure the molecular basis of host-microorganism and microorganism-microorganism interactions, assess patterns of fitness covariance, and conduct experimental coevolution, and (3) mathematical models that can be parameterized with empirical data to predict community assembly and coevolutionary dynamics. The project will address (1) how asymmetries in evolutionary rates influence coevolution in complex communities, (2) scenarios in which 'Red Queen' dynamics–arms races between antagonists–outpace 'Red King' dynamics, where rapidly-evolving mutualists evolve costly traits that enhance host fitness, and (3) how multi-partite interactions influence host benefit and specialization. By linking empirical measurements over varying evolutionary timescales to mathematical models, this project will potentially generate insight into general properties of complex coevolving host-associated communities.
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.
