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Metabolic modelling in a dynamic evolutionary framework predicts adaptive diversification of bacteria in a long-term evolution experiment
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Großkopf, Tobias, Consuegra, Jessika, Gaffé, Joël, Willison, John C., Lenski, Richard E., Soyer, Orkun S. and Schneider, Dominique (2016) Metabolic modelling in a dynamic evolutionary framework predicts adaptive diversification of bacteria in a long-term evolution experiment. BMC Evolutionary Biology, 16 (1). doi:10.1186/s12862-016-0733-x
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Official URL: http://dx.doi.org/10.1186/s12862-016-0733-x
Abstract
Background:
Predicting adaptive trajectories is a major goal of evolutionary biology and useful for practical applications. Systems biology has enabled the development of genome-scale metabolic models. However, analysing these models via flux balance analysis (FBA) cannot predict many evolutionary outcomes including adaptive diversification, whereby an ancestral lineage diverges to fill multiple niches. Here we combine in silico evolution with FBA and apply this modelling framework, evoFBA, to a long-term evolution experiment with Escherichia coli.
Results:
Simulations predicted the adaptive diversification that occurred in one experimental population and generated hypotheses about the mechanisms that promoted coexistence of the diverged lineages. We experimentally tested and, on balance, verified these mechanisms, showing that diversification involved niche construction and character displacement through differential nutrient uptake and altered metabolic regulation.
Conclusion:
The evoFBA framework represents a promising new way to model biochemical evolution, one that can generate testable predictions about evolutionary and ecosystem-level outcomes.
| Item Type: | Journal Article | ||||||||
|---|---|---|---|---|---|---|---|---|---|
| Subjects: | Q Science > QR Microbiology | ||||||||
| Divisions: | Faculty of Science > Life Sciences (2010- ) | ||||||||
| Library of Congress Subject Headings (LCSH): | Escherichia coli -- Evolution, Evolution (Biology), Systems biology | ||||||||
| Journal or Publication Title: | BMC Evolutionary Biology | ||||||||
| Publisher: | BioMed Central Ltd. | ||||||||
| ISSN: | 1471-2148 | ||||||||
| Official Date: | 20 August 2016 | ||||||||
| Dates: |
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| Volume: | 16 | ||||||||
| Number: | 1 | ||||||||
| DOI: | 10.1186/s12862-016-0733-x | ||||||||
| Status: | Peer Reviewed | ||||||||
| Publication Status: | Published | ||||||||
| Access rights to Published version: | Open Access | ||||||||
| Funder: | France. Ministère de l'enseignement supérieur et de la recherche, Biotechnology and Biological Sciences Research Council (Great Britain) (BBSRC), France. Agence nationale de la recherche (ANR), Seventh Framework Programme (European Commission) (FP7), Université Grenoble, Centre national de la recherche scientifique (France) (CNRS), National Science Foundation (U.S.) (NSF), United States. Beacon Center for the Study of Evolution in Action | ||||||||
| Grant number: | BB/K003240 (BBSRC), ANR-08-BLAN-0283-01, FP7-ICT-2013-10 project EvoEvo (610427), DEB-1451740, DBI-0939454 (NSF) |
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