Constraint-based Modeling of Marine Microbial Community Metabolism and Physiology
Massachusetts Institute of Techology
Marine microbial communities mediate the transformation of Earth’s major bioelements through an intricate web of inorganic and organic ‘conduits,’ connecting microbes to microbes, and connecting microbes to global biogeochemical cycles. Within the CBIOMES project, my objective is to identify and quantify the fluxes through each conduit within and between the numerically dominant microbial taxa of the oligotrophic ocean gyres: Prochlorococcus, Synechococcus, Crocosphaera, SAR11 and Roseobacter.
We will be reconstructing genome-scale metabolic networks — detailed and stoichiometrically balanced networks of the many biochemical transformations within a cell — from the ‘pangenomes’ of each taxonomic group. From each pangenome, hundreds of randomized in silico and sequenced strains will be reconstructed in an effort to capture the phylogenetic, physiological and metabolic microdiversity within each group. By leveraging laboratory and field data, including environmental ‘omics datasets, we plan to build realistic simulations designed to predict the winners and losers within the broad environmental niches they occupy.
Using a convex optimization approach (dynamic flux balance analysis and its family of variants) to predict fluxes and growth rates within and between each network, the costs and benefits associated with metabolic interactions of in silico representatives of microbial consortia will be quantified. Ultimately, reduced-complexity metabolic models will be designed to complement ecosystem-scale modeling approaches developed by other CBIOMES project investigators.