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PLoS Computational Biology
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Syntrophy emerges spontaneously in complex metabolic systems

Authors: Eric Libby; Laurent Hébert-Dufresne; Sayed-Rzgar Hosseini; Sayed-Rzgar Hosseini; Andreas Wagner;

Syntrophy emerges spontaneously in complex metabolic systems

Abstract

Syntrophy allows a microbial community as a whole to survive in an environment, even though individual microbes cannot. The metabolic interdependence typical of syntrophy is thought to arise from the accumulation of degenerative mutations during the sustained co-evolution of initially self-sufficient organisms. An alternative and underexplored possibility is that syntrophy can emerge spontaneously in communities of organisms that did not co-evolve. Here, we study this de novo origin of syntrophy using experimentally validated computational techniques to predict an organism's viability from its metabolic reactions. We show that pairs of metabolisms that are randomly sampled from a large space of possible metabolism and viable on specific primary carbon sources often become viable on new carbon sources by exchanging metabolites. The same biochemical reactions that are required for viability on primary carbon sources also confer viability on novel carbon sources. Our observations highlight a new and important avenue for the emergence of metabolic adaptations and novel ecological interactions.

Countries
Sweden, Switzerland
Keywords

Evolution, QH301-705.5, 2804 Cellular and Molecular Neuroscience, Biochemistry, Models, Biological, 10127 Institute of Evolutionary Biology and Environmental Studies, Cellular and Molecular Neuroscience, 1311 Genetics, Behavior and Systematics, Modelling and Simulation, 1312 Molecular Biology, Genetics, Escherichia coli, Biology (General), Symbiosis, Biokemi, Molecular Biology, Molekylärbiologi, Ecology, Microbiota, Computational Biology, Adaptation, Physiological, Carbon, Markov Chains, 1105 Ecology, Evolution, Behavior and Systematics, Computational Theory and Mathematics, Mutation, 570 Life sciences; biology, 590 Animals (Zoology), 2303 Ecology, Monte Carlo Method, Algorithms, Metabolic Networks and Pathways, 2611 Modeling and Simulation, 1703 Computational Theory and Mathematics, Research Article

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    selected citations
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    This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
    33
    popularity
    This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
    Top 10%
    influence
    This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
    Average
    impulse
    This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
    Top 10%
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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
33
Top 10%
Average
Top 10%
Green
gold