D Segre Boston University
Thursday 30th October 2014 - 15:55 to 16:30
INI Seminar Room 1
Metabolism, in addition to being the “engine” of every living cell, plays a major role in the cell-cell and cell-environment relations that shape the dynamics and evolution of microbial communities, e.g. by mediating competition and cross-feeding interactions between different species. Despite the increasing availability of metagenomic sequencing data for numerous microbial ecosystems, fundamental aspects of these communities, such as the unculturability of most isolates, and the conditions necessary for taxonomic or functional stability, are still poorly understood. In the past few years we have been developing new computational methods for studying these ecosystems based on genome scale stoichiometric models of metabolism (such as flux balance analysis), showing for example how one can computationally identify minimal growth media that could induce metabolic cross-feeding between two microbial species – an approach that has applications in the nascent fiel d of synthetic ecology. A more comprehensive understanding of the role of metabolic networks in the dynamics of microbial communities will require a broader theoretical framework capable of dealing with the multi-scale spatio-temporal complexity of these ecosystems. Our new, experimentally validated, open source platform for the Computation of Microbial Ecosystems in Time and Space (COMETS), addresses this challenge by combining flux balance analysis with diffusion equations to simulate the 3D spatio-temporal dynamics of metabolism in microbial communities. While some COMETS predictions are non-intuitive and surprisingly accurate, abundant work is still needed in order to bridge the gap between the dynamics of small engineered communities, and the huge diversity and complexity of natural ecosystems.