Presenter: Steve Zhang, From the Song Lab

Title: Modeling of Metabolic Coupling between Cyanobacteria and Heterotrophs

Summary: Photoautotroph-heterotroph communities are a key driver of material and energy cycles in natural ecosystems. Member species in these communities dynamically interact with each other through diverse metabolic activities. For example, photoautotrophs, such as cyanobacteria, convert inorganic nutrients into organic substrates, which are shared among heterotrophs. They also cooperatively degrade polymeric substrates through the division of labor. Despite ongoing studies in the literature, we still do not have a detailed understanding of what makes the two bacterial groups (i.e., phototrophs and heterotrophs) metabolically dependent and how they interact at a reaction and gene level. Towards addressing these knowledge gaps, we comparatively analyzed two cyanobacterial consortia derived from Hot Lake, WA, as a model system. Each of these two consortia contains only one cyanobacterium that is distinct but shares the heterotrophic membership - thus called unicyanobacterial consortia (UCC). Using genome-scale metabolic networks reconstructed by the U.S. DOE’s Systems Biology Knowledgebase (KBase) pipeline, we predicted key metabolites exchanged between cyanobacteria and heterotrophs and performed flux coupling analysis to reveal what part of the reaction pathways in cyanobacteria needs to be essentially expressed to support the growth of heterotrophs. Interestingly, metabolic coupling patterns were predicted to be quite distinct between the two UCCs, indicating that cyanobacteria are a major determinant of interspecies interactions and community dynamics.