Metabolic resource allocation in individual microbes determines ecosystem interactions and spatial dynamics

William R. Harcombe, William J. Riehl, Ilija Dukovski, Brian R. Granger, Alex Betts, Alex H. Lang, Gracia Bonilla, Amrita Kar, Nicholas Leiby, Pankaj Mehta, Christopher J. Marx, Daniel Segrè

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354 Scopus citations


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.

Original languageEnglish (US)
Pages (from-to)1104-1115
Number of pages12
JournalCell reports
Issue number4
StatePublished - May 22 2014

Bibliographical note

Funding Information:
This work was supported by the Office of Science (BER), U.S. Department of Energy (grant DE-SC0004962 to D.S.). D.S., W.J.R., I.D., B.R.G., and A.K. were supported also by the NASA Astrobiology Institute (NNA08CN84A) and NIH (5R01GM089978 and 5R01GM103502-06). G.B. was supported by IGERT NSF DGE-0654108. W.R.H. was supported also by NIH NRSA 1F32GM090760 and DOE award to C.J.M. (DE-SC0006731). N.L. was supported by NSF GRFP DGE-1247312. P.M. was partially supported by NIH K25 GM086909. A.H.L. was supported by NSF DGE-0741448. The authors are grateful for useful conversations with Niels Klitgord, Melanie Muller, and with members of the Segrè and Marx labs.


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