Christopher Chang - Kinetic Modeling and Exploratory Numerical Simulation of Chloroplastic Starch Degradation

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      Publication Details (including relevant citation   information):

      A Nag, M Lunacek, PA Graf & CH Chang (2011) BMC Sys.   Biol. 5: 94



      Higher plants and algae are able to fix atmospheric carbon   dioxide through photosynthesis and store this fixed carbon in   large quantities as starch, which can be hydrolyzed into sugars   serving as feedstock for fermentation to biofuels and precursors.   Rational engineering of carbon flow in plant cells requires a   greater understanding of how starch breakdown fluxes respond to   variations in enzyme concentrations, kinetic parameters, and   metabolite concentrations. We have therefore developed and   simulated a detailed kinetic ordinary differential equation model   of the degradation pathways for starch synthesized in plants and   green algae, which to our knowledge is the most complete such   model reported to date.


      Simulation with 9 internal metabolites and 8 external   metabolites, the concentrations of the latter fixed at reasonable   biochemical values, leads to a single reference solution showing   β-amylase activity to be the   rate-limiting step in carbon flow from starch degradation.   Additionally, the response coefficients for stromal glucose to   the glucose transporter kcat and KM are   substantial, whereas those for cytosolic glucose are not,   consistent with a kinetic bottleneck due to transport. Response   coefficient norms show stromal maltopentaose and cytosolic   glucosylated arabinogalactan to be the most and least globally   sensitive metabolites, respectively, and β-amylase kcat and KM for   starch to be the kinetic parameters with the largest aggregate   effect on metabolite concentrations as a whole. The latter   kinetic parameters, together with those for glucose transport,   have the greatest effect on stromal glucose, which is a precursor   for biofuel synthetic pathways. Exploration of the steady-state   solution space with respect to concentrations of 6 external   metabolites and 8 dynamic metabolite concentrations show that   stromal metabolism is strongly coupled to starch levels, and that   transport between compartments serves to lower coupling between   metabolic subsystems in different compartments.


      We find that in the reference steady state, starch cleavage is   the most significant determinant of carbon flux, with turnover of   oligosaccharides playing a secondary role. Independence of   stationary point with respect to initial dynamic variable values   confirms a unique stationary point in the phase space of   dynamically varying concentrations of the model network. Stromal   maltooligosaccharide metabolism was highly coupled to the   available starch concentration. From the most highly converged   trajectories, distances between unique fixed points of phase   spaces show that cytosolic maltose levels depend on the total   concentrations of arabinogalactan and glucose present in the   cytosol. In addition, cellular compartmentalization serves to   dampen much, but not all, of the effects of one subnetwork on   another, such that kinetic modeling of single compartments would   likely capture most dynamics that are fast on the timescale of   the transport reactions.

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