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Metabolic Resource Allocation in Individual Microbes Determines Ecosystem Interactions and Spatial Dynamics

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

Cell reports (Cambridge), 2014-05, Vol.7 (4), p.1104-1115 [Periódico revisado por pares]

United States: Elsevier Inc

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  • Título:
    Metabolic Resource Allocation in Individual Microbes Determines Ecosystem Interactions and Spatial Dynamics
  • Autor: Harcombe, William R. ; Riehl, William J. ; Dukovski, Ilija ; Granger, Brian R. ; Betts, Alex ; Lang, Alex H. ; Bonilla, Gracia ; Kar, Amrita ; Leiby, Nicholas ; Mehta, Pankaj ; Marx, Christopher J. ; Segrè, Daniel
  • Assuntos: Ecosystem ; Microbiota - physiology ; Models, Biological ; Spatial Behavior - physiology ; Spatio-Temporal Analysis
  • É parte de: Cell reports (Cambridge), 2014-05, Vol.7 (4), p.1104-1115
  • Notas: ObjectType-Article-1
    SourceType-Scholarly Journals-1
    ObjectType-Feature-2
    content type line 23
    Current address: Department of Ecology, Evolution, and Behavior, University of Minnesota, St. Paul, MN 55108, USA
    Current address: Department of Zoology, University of Oxford, Oxford, OX1 3PS, United Kingdom
    Current address: Department of Biological Sciences, University of Idaho, Moscow, ID 83844, USA
    These authors contributed equally to this work
    Current address: Lawrence Berkeley National Laboratory, Berkeley, CA 94720, USA
  • Descrição: 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. [Display omitted] [Display omitted] •Microbial community dynamics can be inferred from intracellular metabolism•Metabolic interactions drive engineered microbial consortia to predictable equilibria•Spatial organization shapes the dynamics of mutualism in a metabolic eclipse scenario•Computation of Microbial Ecosystems in Time and Space (COMETS): a flexible tool Microbes can interact with the environment and with each other through the uptake and secretion of metabolites. Here, Harcombe et al. ask whether mathematical modeling of the metabolic network of individual species can help forecast the spatiotemporal behavior of two- and three-species engineered microbial ecosystems. In addition to accurately predicting colony growth rates and equilibrium community compositions, their approach sheds new light on the complex nature of cooperation and competition in spatially structured environments.
  • Editor: United States: Elsevier Inc
  • Idioma: Inglês
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