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dc.contributor.authorHarcombe, William R.en_US
dc.contributor.authorDelaney, Nigel F.en_US
dc.contributor.authorLeiby, Nicholasen_US
dc.contributor.authorKlitgord, Nielsen_US
dc.contributor.authorMarx, Christopher J.en_US
dc.date.accessioned2014-02-18T18:10:28Z
dc.date.issued2013en_US
dc.identifier.citationHarcombe, William R., Nigel F. Delaney, Nicholas Leiby, Niels Klitgord, and Christopher J. Marx. 2013. “The Ability of Flux Balance Analysis to Predict Evolution of Central Metabolism Scales with the Initial Distance to the Optimum.” PLoS Computational Biology 9 (6): e1003091. doi:10.1371/journal.pcbi.1003091. http://dx.doi.org/10.1371/journal.pcbi.1003091.en
dc.identifier.issn1553-734Xen
dc.identifier.urihttp://nrs.harvard.edu/urn-3:HUL.InstRepos:11717494
dc.description.abstractThe most powerful genome-scale framework to model metabolism, flux balance analysis (FBA), is an evolutionary optimality model. It hypothesizes selection upon a proposed optimality criterion in order to predict the set of internal fluxes that would maximize fitness. Here we present a direct test of the optimality assumption underlying FBA by comparing the central metabolic fluxes predicted by multiple criteria to changes measurable by a 13C-labeling method for experimentally-evolved strains. We considered datasets for three Escherichia coli evolution experiments that varied in their length, consistency of environment, and initial optimality. For ten populations that were evolved for 50,000 generations in glucose minimal medium, we observed modest changes in relative fluxes that led to small, but significant decreases in optimality and increased the distance to the predicted optimal flux distribution. In contrast, seven populations evolved on the poor substrate lactate for 900 generations collectively became more optimal and had flux distributions that moved toward predictions. For three pairs of central metabolic knockouts evolved on glucose for 600–800 generations, there was a balance between cases where optimality and flux patterns moved toward or away from FBA predictions. Despite this variation in predictability of changes in central metabolism, two generalities emerged. First, improved growth largely derived from evolved increases in the rate of substrate use. Second, FBA predictions bore out well for the two experiments initiated with ancestors with relatively sub-optimal yield, whereas those begun already quite optimal tended to move somewhat away from predictions. These findings suggest that the tradeoff between rate and yield is surprisingly modest. The observed positive correlation between rate and yield when adaptation initiated further from the optimum resulted in the ability of FBA to use stoichiometric constraints to predict the evolution of metabolism despite selection for rate.en
dc.language.isoen_USen
dc.publisherPublic Library of Scienceen
dc.relation.isversionofdoi:10.1371/journal.pcbi.1003091en
dc.relation.hasversionhttp://www.ncbi.nlm.nih.gov/pmc/articles/PMC3688462/pdf/en
dash.licenseLAAen_US
dc.subjectBiologyen
dc.subjectBiochemistryen
dc.subjectMetabolismen
dc.subjectMetabolic Pathwaysen
dc.subjectComputational Biologyen
dc.subjectMetabolic Networksen
dc.subjectSystems Biologyen
dc.subjectEvolutionary Biologyen
dc.subjectPopulation Geneticsen
dc.subjectNatural Selectionen
dc.subjectEvolutionary Geneticsen
dc.subjectMicrobiologyen
dc.subjectMicrobial Evolutionen
dc.subjectMicrobial Metabolismen
dc.subjectModel Organismsen
dc.subjectProkaryotic Modelsen
dc.subjectEscherichia Colien
dc.subjectPopulation Biologyen
dc.subjectEngineeringen
dc.subjectBioengineeringen
dc.subjectBiological Systems Engineeringen
dc.titleThe Ability of Flux Balance Analysis to Predict Evolution of Central Metabolism Scales with the Initial Distance to the Optimumen
dc.typeJournal Articleen_US
dc.description.versionVersion of Recorden
dc.relation.journalPLoS Computational Biologyen
dash.depositing.authorHarcombe, William R.en_US
dc.date.available2014-02-18T18:10:28Z
dc.identifier.doi10.1371/journal.pcbi.1003091*
dash.contributor.affiliatedHarcombe, William R
dash.contributor.affiliatedDelaney, Nigel Francis
dash.contributor.affiliatedLeiby, Nicholas
dash.contributor.affiliatedMarx, Christopher J


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