Constraint‐based modeling of metabolomic systems

Beard, Daniel A.; Qian, Hong

doi:10.1002/047001153x.g308203

Cited by 2 publications

(1 citation statement)

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“…Constraint‐based modelling is a metabolic modelling approach that uses a set of physical, biochemical, and thermodynamic constraints to define a solution space that describes all feasible flux distributions supported by a system of metabolic reactions of defined stoichiometry. This modelling approach does not require enzyme/metabolite concentrations or kinetic parameters (Beard and Qian, 2005). The most commonly implemented formulation, flux balance analysis (FBA), has been extensively used to study leaf metabolism in C 3 plants (Arnold and Nikoloski, 2014; Chatterjee et al., 2017; Cheung et al., 2014, 2015; de Oliveira Dal'Molin et al., 2010; Herrmann et al., 2019; Lakshmanan et al., 2015; Mintz‐Oron et al., 2012; Poolman et al., 2013; Shameer et al., 2019; Yuan et al., 2016).…”

Section: Introductionmentioning

confidence: 99%

A hybrid kinetic and constraint‐based model of leaf metabolism allows predictions of metabolic fluxes in different environments

et al. 2021

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SUMMARY While flux balance analysis (FBA) provides a framework for predicting steady‐state leaf metabolic network fluxes, it does not readily capture the response to environmental variables without being coupled to other modelling formulations. To address this, we coupled an FBA model of 903 reactions of soybean (Glycine max) leaf metabolism with e‐photosynthesis, a dynamic model that captures the kinetics of 126 reactions of photosynthesis and associated chloroplast carbon metabolism. Successful coupling was achieved in an iterative formulation in which fluxes from e‐photosynthesis were used to constrain the FBA model and then, in turn, fluxes computed from the FBA model used to update parameters in e‐photosynthesis. This process was repeated until common fluxes in the two models converged. Coupling did not hamper the ability of the kinetic module to accurately predict the carbon assimilation rate, photosystem II electron flux, and starch accumulation of field‐grown soybean at two CO2 concentrations. The coupled model also allowed accurate predictions of additional parameters such as nocturnal respiration, as well as analysis of the effect of light intensity and elevated CO2 on leaf metabolism. Predictions included an unexpected decrease in the rate of export of sucrose from the leaf at high light, due to altered starch–sucrose partitioning, and altered daytime flux modes in the tricarboxylic acid cycle at elevated CO2. Mitochondrial fluxes were notably different between growing and mature leaves, with greater anaplerotic, tricarboxylic acid cycle and mitochondrial ATP synthase fluxes predicted in the former, primarily to provide carbon skeletons and energy for protein synthesis.

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