OOS 11-5
Using system biology to investigate eco-evolutionary feedbacks in microbial communities
Eco-evolutionary dynamics are strongly influenced by the extent to which genetic changes generate ecological changes. There has been a great deal of work on both the robustness of genomes and the stability of communities, but little work connecting the two. It is commonly held that competitive interactions should stabilize total community biomass through “compensatory dynamics.” In contrast, community composition is thought to be more stable in obligate mutualisms. However, stability of these emergent properties will be influenced by the degree to which species’ interactions are robust to genetic perturbations. We use genome-scale metabolic modeling to computationally analyze the impact of genetic changes when two species of bacteria are competiting versus when they involved in an obligate mutualism. We analyzed the stability of interactions between Escherichia coli and Salmonella enterica. The type of interaction between species was determined by the initial metabolites present in the environment. We systematically knocked out in silico each reaction in the metabolic network of E. coli to construct all 2,583 mutant stoichiometric models. Then, using a recently developed multi-scale computational framework, we simulated the growth of each mutant E. coli in the presence of S. enterica
Results/Conclusions
We found that the community was most robust to genetic perturbations when the organisms were cooperating. Species ratios were more stable in the cooperative community, and community biomass had equal variance in the two contexts. Additionally, the number of mutations that have a substantial effect is lower when the species cooperate than when they are competing. In contrast, when mutations were added to the S. enterica network the system was more robust when the bacteria were competing. These results highlight the utility of connecting metabolic mechanisms and studies of ecological stability. Cooperation and conflict alter the connection between genetic changes and properties that emerge at higher levels of biological organization.