title: Predictive modeling of biomass component tradeoffs in Brassica napus developing oilseeds based on in silico manipulation of storage metabolism.
abstract: Seed oil content is a key agronomical trait, while the control of carbon allocation into different seed storage compounds is still poorly understood and hard to manipulate. Using bna572, a large-scale model of cellular metabolism in developing embryos of rapeseed (Brassica napus) oilseeds, we present an in silico approach for the analysis of carbon allocation into seed storage products. Optimal metabolic flux states were obtained by flux variability analysis based on minimization of the uptakes of substrates in the natural environment of the embryo. For a typical embryo biomass composition, flux sensitivities to changes in different storage components were derived. Upper and lower flux bounds of each reaction were categorized as oil or protein responsive. Among the most oil-responsive reactions were glycolytic reactions, while reactions related to mitochondrial ATP production were most protein responsive. To assess different biomass compositions, a tradeoff between the fractions of oil and protein was simulated. Based on flux-bound discontinuities and shadow prices along the tradeoff, three main metabolic phases with distinct pathway usage were identified. Transitions between the phases can be related to changing modes of the tricarboxylic acid cycle, reorganizing the usage of organic carbon and nitrogen sources for protein synthesis and acetyl-coenzyme A for cytosol-localized fatty acid elongation. The phase close to equal oil and protein fractions included an unexpected pathway bypassing α-ketoglutarate-oxidizing steps in the tricarboxylic acid cycle. The in vivo relevance of the findings is discussed based on literature on seed storage metabolism.
authors.affiliation: Biology Department, Brookhaven National Laboratory, Upton, New York 11973, USA. schwend@bnl.gov
authors.forename: Jörg
authors.initials: J
authors.lastname: Schwender
authors.forename: Jordan O
authors.initials: JO
authors.lastname: Hay
mesh_terms: D018533:Biomass; D029688:Brassica napus / Q000235:genetics / Q000378:metabolism*; D002244:Carbon / Q000378:metabolism; D002952:Citric Acid Cycle; D019295:Computational Biology / Q000379:methods*; D003198:Computer Simulation; D005998:Glycine / Q000378:metabolism; D053858:Metabolic Networks and Pathways; D008954:Models, Biological; D010938:Plant Oils / Q000378:metabolism*; D010940:Plant Proteins / Q000378:metabolism; D012639:Seeds / Q000378:metabolism*; D012694:Serine / Q000378:metabolism; D014280:Triglycerides / Q000378:metabolism
chemical_list: D010938:Plant Oils; D010940:Plant Proteins; D014280:Triglycerides; D012694:Serine; D002244:Carbon; D005998:Glycine