Genome-scale metabolic models (GSMs) enable the prediction of metabolic landscapes from limited experimental data. They are therefore beneficial for analyzing the metabolic capabilities of whole plants, in which experimental measurement of intracellular fluxes can be challenging. There are relatively few GSMs for plants and to our knowledge, no published GSMs for woody plants (trees). The development of a tree GSM is compelling because tree metabolism is the source of commodities ranging from cellulosic biomass to atmospheric isoprene, and because trees undergo seasonal metabolic changes whose underlying biology is not fully investigated. Here, we present the reconstruction and flux balance analysis (FBA) of a fully compartmentalized GSM of <i>Populus trichocarpa</i> (poplar) to investigate tree-specific metabolic events.<br/>We reconstructed the GSM from the PoplarCyc database and compartmentalized it on the basis of experimental data and organelle-prediction algorithms. After extensively curating the model, we ensured that it can produce all necessary biomass constituents individually and in experimentally reported proportions. Our GSM is comprehensive (not tissue-specific) and can readily be rendered tissue-specific by adding suitable transport reactions and blocking appropriate pathways.<br/>To investigate seasonal internal nitrogen recycling that is specific to woody deciduous trees and central to nitrogen conservation in them, we developed a multi-tissue version of the GSM comprising leaf and bark tissues. FBA of this model using several biologically relevant, nontrivial objectives enabled the prediction of particular amino acids as preferred vehicles of seasonal nitrogen transport, consistent with experimental field observations. Furthermore, the FBA results indicate that the choice of particular amino acids is dominated by the metabolic demand of one tissue over the other, thus providing insights on metabolic costs and benefits associated with seasonal nitrogen cycling. Thus, this GSM is able to provide meaningful answers to complex questions on woody plant metabolism, thus making it a potentially predictive tool.

Genome-scale stoichiometric model of poplar for investigation of woody plant metabolism

251st National Meeting (2016)

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