Understanding the evolution of interspecies metabolic interactions using dynamic genome-scale metabolic modeling

Microbial communities are ubiquitous in nature and play a significant role in various biogeochemical cycles on earth. They are dynamic in nature and exhibit different metabolic interactions under different conditions. Recently, genome-scale metabolic modeling (GEM) emerged as an effective tool to study microbial communities. However, the representative dynamic GEM approaches cannot predict the interspecies metabolic interactions within a community, while the steady-state GEM approaches cannot capture the dynamic evolvement of the metabolic interactions. In this work, using a methanotroph-cyanobacteria (Methylomicrobium buryatense 5GB1- Arthrospira platensis) coculture as the model system, we present a dynamic GEM approach, termed DynamiCom that can predict the evolution of interspecies metabolic interactions within the coculture over time. DynamiCom integrates a semi-structured kinetic model we developed recently with a steady-state GEM (SteadyCom) to predict the dynamic changes of interspecies interactions. Besides consistently predicting the same set of top metabolic exchanges within the coculture under different in silico setups, DynamiCom predicted the establishment of the mutualistic relationship between the methanotroph and cyanobacteria.