Figure 7. Integrating COBRA methods to study community interactions.
COBRA methods are providing insight into the metabolic interactions in various types of microbial communities. (a) To study the mutualistic behavior of co-dependent mutant E. coli, researchers used MOMA50 to simulate synergistic growth of pairs of auxotrophic E. coli. (b) Shadow prices from FBA simulations of these pairs were used to compute cooperation efficiencies between strains, which were subsequently compared with measured fitness improvements. (c) Competition in communities was modeled using DMMM122 to understand how communities of Geobacter and Rhodoferax compete for resources, and how the demographics vary under different nutrient ratios, thereby affecting the efficiency of bioremediation efforts. Host-pathogen interactions between M. tuberculosis and a human macrophage were studied using COBRA. (d) While transcriptomic data were employed to build host-pathogen models at different stages of infection, the cellular objective of internalized M. tuberculosis is not known, so refinements to the objective function were predicted from transcriptomic data to account for changes in required amounts of compounds like lipids and amino acids (AAs). (e) This information was used to compute flux states of internalized M. tuberculosis with MCMC sampling32. This demonstrated a suppression of central metabolism and activation of the glyoxylate shunt, represented here by enolase and isocitrate lyase, respectively. The role of communities in evolution has been studied using Reductive evolutionary simulation117. In particular, this method predicted the minimal set of genes needed to for Buchnera to grow in the rich innards of the aphid. The predicted minimial gene sets (f) and temporal order of gene loss (g) were consistent with the gene content and phylogenetic structure of several Buchnera species.