%0 Journal Article %1 harcombe2014metabolic %A Harcombe, William R. %A Riehl, William J. %A Dukovski, Ilija %A Granger, Brian R. %A Betts, Alex %A Lang, Alex H. %A Bonilla, Gracia %A Kar, Amrita %A Leiby, Nicholas %A Mehta, Pankaj %A Marx, Christopher J. %A Segrè, Daniel %D 2014 %J Cell Reports %K discrete_populations metabolic_network methods modeling reaction-diffusion simulation software spatial_structure %N 4 %P 1104 - 1115 %R https://doi.org/10.1016/j.celrep.2014.03.070 %T Metabolic Resource Allocation in Individual Microbes Determines Ecosystem Interactions and Spatial Dynamics %U http://www.sciencedirect.com/science/article/pii/S2211124714002800 %V 7 %X Summary The interspecies exchange of metabolites plays a key role in the spatiotemporal dynamics of microbial communities. This raises the question of whether ecosystem-level behavior of structured communities can be predicted using genome-scale metabolic models for multiple organisms. We developed a modeling framework that integrates dynamic flux balance analysis with diffusion on a lattice and applied it to engineered communities. First, we predicted and experimentally confirmed the species ratio to which a two-species mutualistic consortium converges and the equilibrium composition of a newly engineered three-member community. We next identified a specific spatial arrangement of colonies, which gives rise to what we term the “eclipse dilemma”: does a competitor placed between a colony and its cross-feeding partner benefit or hurt growth of the original colony? Our experimentally validated finding that the net outcome is beneficial highlights the complex nature of metabolic interactions in microbial communities while at the same time demonstrating their predictability. Video Abstract

@article{harcombe2014metabolic, abstract = {Summary The interspecies exchange of metabolites plays a key role in the spatiotemporal dynamics of microbial communities. This raises the question of whether ecosystem-level behavior of structured communities can be predicted using genome-scale metabolic models for multiple organisms. We developed a modeling framework that integrates dynamic flux balance analysis with diffusion on a lattice and applied it to engineered communities. First, we predicted and experimentally confirmed the species ratio to which a two-species mutualistic consortium converges and the equilibrium composition of a newly engineered three-member community. We next identified a specific spatial arrangement of colonies, which gives rise to what we term the “eclipse dilemma”: does a competitor placed between a colony and its cross-feeding partner benefit or hurt growth of the original colony? Our experimentally validated finding that the net outcome is beneficial highlights the complex nature of metabolic interactions in microbial communities while at the same time demonstrating their predictability. Video Abstract }, added-at = {2017-05-23T16:30:05.000+0200}, author = {Harcombe, William R. and Riehl, William J. and Dukovski, Ilija and Granger, Brian R. and Betts, Alex and Lang, Alex H. and Bonilla, Gracia and Kar, Amrita and Leiby, Nicholas and Mehta, Pankaj and Marx, Christopher J. and Segrè, Daniel}, biburl = {https://www.bibsonomy.org/bibtex/21995664181161b0826696b56d076d6ad/peter.ralph}, doi = {https://doi.org/10.1016/j.celrep.2014.03.070}, interhash = {bb9d976886a30833aa9fcfc95f6742e0}, intrahash = {1995664181161b0826696b56d076d6ad}, issn = {2211-1247}, journal = {Cell Reports }, keywords = {discrete_populations metabolic_network methods modeling reaction-diffusion simulation software spatial_structure}, number = 4, pages = {1104 - 1115}, timestamp = {2017-05-23T16:30:05.000+0200}, title = {Metabolic Resource Allocation in Individual Microbes Determines Ecosystem Interactions and Spatial Dynamics }, url = {http://www.sciencedirect.com/science/article/pii/S2211124714002800}, volume = 7, year = 2014 }