Dataset Information

Bruck2008_Glycolysis

ABSTRACT: Exploring the effect of variable enzyme concentrations in a kinetic model of yeast glycolysis Jozsef Bruck, Wolfram Liebermeister, Edda Klipp, Genome Inform 2008 20:1-14 Abstract: Metabolism is one of the best studied fields of biochemistry, but its regulation involves processes on many different levels, some of which are still not understood well enough to allow for quantitative modeling and prediction. Glycolysis in yeast is a good example: although high-quality quantitative data are available, well-established mathematical models typically only cover direct regulation of the involved enzymes by metabolite binding. The effect of various metabolites on the enzyme kinetics is summarized in carefully developed mathematical formulae. However, this approach implicitly assumes that the enzyme concentrations themselves are constant, thus neglecting other regulatory levels - e.g. transcriptional and translational regulation--involved in the regulation of enzyme activities. It is believed, however, that different experimental conditions result in different enzyme activities regulated by the above mechanisms. Detailed modeling of all regulatory levels is still out of reach since some of the necessary data - e.g. quantitative large scale enzyme concentration data sets - are lacking or rare. Nevertheless, a viable approach is to include the regulation of enzyme concentrations into an established model and to investigate whether this improves the predictive capabilities. Proteome data are usually hard to obtain, but levels of mRNA transcripts may be used instead as clues for changes in enzyme concentrations. Here we investigate whether including mRNA data into an established model of yeast glycolysis allows to predict the steady state metabolic concentrations for different experimental conditions. To this end, we modified an established ODE model for the glycolytic pathway of yeast to include changes of enzyme concentrations. Presumable changes were inferred from mRNA transcript level measurement data. We investigate how this approach can be used to predict metabolite concentrations for steady-state yeast cultures at five different oxygen levels ranging from anaerobic to fully aerobic conditions. We were partly able to reproduce the experimental data and present a number of changes that were necessary to improve the modeling result. Further modifications to this model and improved data fit will be presented soon. This model originates from BioModels Database: A Database of Annotated Published Models (http://www.ebi.ac.uk/biomodels/). It is copyright (c) 2005-2011 The BioModels.net Team. To the extent possible under law, all copyright and related or neighbouring rights to this encoded model have been dedicated to the public domain worldwide. Please refer to CC0 Public Domain Dedication for more information. In summary, you are entitled to use this encoded model in absolutely any manner you deem suitable, verbatim, or with modification, alone or embedded it in a larger context, redistribute it, commercially or not, in a restricted way or not. . To cite BioModels Database, please use: Li C, Donizelli M, Rodriguez N, Dharuri H, Endler L, Chelliah V, Li L, He E, Henry A, Stefan MI, Snoep JL, Hucka M, Le Novère N, Laibe C (2010) BioModels Database: An enhanced, curated and annotated resource for published quantitative kinetic models. BMC Syst Biol., 4:92.

SUBMITTER: Kieran Smallbone

PROVIDER: MODEL1011010000 | BioModels | 2005-01-01

REPOSITORIES: BioModels

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Publications

Exploring the effect of variable enzyme concentrations in a kinetic model of yeast glycolysis.

Bruck József J Liebermeister Wolfram W Klipp Edda E

Genome informatics. International Conference on Genome Informatics 20080101

Metabolism is one of the best studied fields of biochemistry, but its regulation involves processes on many different levels, some of which are still not understood well enough to allow for quantitative modeling and prediction. Glycolysis in yeast is a good example: although high-quality quantitative data are available, well-established mathematical models typically only cover direct regulation of the involved enzymes by metabolite binding. The effect of various metabolites on the enzyme kinetic ...[more]

PMID: 19425118

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Project description:Water soluble carbohydrates (WSC, composed of mainly fructans, sucrose, glucose and fructose) deposited in wheat stems are important carbon sources for grain filling. Variation in stem WSC concentrations among wheat genotypes is one of the genetic factors influencing grain weight and yield under water-limited environments. Here, we describe the molecular dissection of carbohydrate metabolism in stems, at the WSC accumulation phase, of recombinant inbred SB (Seri/Babax) lines of Triticum aestivum differing in stem WSC concentrations. Affymetrix GeneChip analysis of carbohydrate metabolic enzymes revealed that the mRNA levels of two fructan synthetic enzyme families (sucrose:sucrose 1-fructosyltransferase and sucrose:fructan 6-fructosyltransferase) in the stem were positively correlated with stem WSC and fructan concentrations, while the mRNA levels of enzyme families involved in sucrose hydrolysis (sucrose synthase and soluble acid invertase) were inversely correlated with WSC concentrations. Differential regulation of the mRNA levels of these sucrose hydrolytic enzymes in SB lines resulted in genotypic differences in these enzyme activities. Down-regulation of sucrose synthase and soluble acid invertase in high WSC lines was accompanied by significant decreases in the mRNA levels of enzyme families related to sugar catabolic pathways (fructokinase and mitochondrion pyruvate dehydrogenase complex) and enzyme families involved in diverting UDP-glucose to cell wall synthesis (UDP-glucose 6-dehydrogenase, UDP-glucuronate decarboxylase and cellulose synthase), resulting in a reduction in cell wall polysaccharide contents (mainly hemicellulose) in the stem of high WSC lines. These data suggest that differential carbon partitioning in the wheat stem is one mechanism that contributes to genotypic variation in WSC accumulation. We used Affymetrix GeneChip to dissect genotypic variation in carbohydrate metabolism related to water soluble carbohydrate accumulation in stems of wheat. Experiment Overall Design: 8 genotypes of recombinant inbred lines Seri M82 x Babax with 2 biological replicates per genotype. Grown in the field under rain-fed conditions

Project description:Water soluble carbohydrates (WSC, composed of mainly fructans, sucrose, glucose and fructose) deposited in wheat stems are important carbon sources for grain filling. Variation in stem WSC concentrations among wheat genotypes is one of the genetic factors influencing grain weight and yield under water-limited environments. Here, we describe the molecular dissection of carbohydrate metabolism in stems, at the WSC accumulation phase, of recombinant inbred SB (Seri/Babax) lines of Triticum aestivum differing in stem WSC concentrations. Affymetrix GeneChip analysis of carbohydrate metabolic enzymes revealed that the mRNA levels of two fructan synthetic enzyme families (sucrose:sucrose 1-fructosyltransferase and sucrose:fructan 6-fructosyltransferase) in the stem were positively correlated with stem WSC and fructan concentrations, while the mRNA levels of enzyme families involved in sucrose hydrolysis (sucrose synthase and soluble acid invertase) were inversely correlated with WSC concentrations. Differential regulation of the mRNA levels of these sucrose hydrolytic enzymes in SB lines resulted in genotypic differences in these enzyme activities. Down-regulation of sucrose synthase and soluble acid invertase in high WSC lines was accompanied by significant decreases in the mRNA levels of enzyme families related to sugar catabolic pathways (fructokinase and mitochondrion pyruvate dehydrogenase complex) and enzyme families involved in diverting UDP-glucose to cell wall synthesis (UDP-glucose 6-dehydrogenase, UDP-glucuronate decarboxylase and cellulose synthase), resulting in a reduction in cell wall polysaccharide contents (mainly hemicellulose) in the stem of high WSC lines. These data suggest that differential carbon partitioning in the wheat stem is one mechanism that contributes to genotypic variation in WSC accumulation. We used Affymetrix GeneChip to dissect genotypic variation in carbohydrate metabolism related to water soluble carbohydrate accumulation in stems of wheat. Keywords: Genotypic differences in water soluble carbohydrate metabolism in stem

Project description:This model is from the article: A model of flux regulation in the cholesterol biosynthesis pathway: Immune mediated graduated flux reduction versus statin-like led stepped flux reduction. Watterson S, Guerriero ML, Blanc M, Mazein A, Loewe L, Robertson KA, Gibbs H, Shui G, Wenk MR, Hillston J, Ghazal P. Biochimie. 2012 Jun 1. 22664637 , Abstract: The cholesterol biosynthesis pathway has recently been shown to play an important role in the innate immune response to viral infection with host protection occurring through a coordinate down regulation of the enzymes catalysing each metabolic step. In contrast, statin based drugs, which form the principle pharmaceutical agents for decreasing the activity of this pathway, target a single enzyme. Here, we build an ordinary differential equation model of the cholesterol biosynthesis pathway in order to investigate how the two regulatory strategies impact upon the behaviour of the pathway. We employ a modest set of assumptions: that the pathway operates away from saturation, that each metabolite is involved in multiple cellular interactions and that mRNA levels reflect enzyme concentrations. Using data taken from primary bone marrow derived macrophage cells infected with murine cytomegalovirus or treated with IFNγ, we show that, under these assumptions, coordinate down-regulation of enzyme activity imparts a graduated reduction in flux along the pathway. In contrast, modelling a statin-like treatment that achieves the same degree of down-regulation in cholesterol production, we show that this delivers a step change in flux along the pathway. The graduated reduction mediated by physiological coordinate regulation of multiple enzymes supports a mechanism that allows a greater level of specificity, altering cholesterol levels with less impact upon interactions branching from the pathway, than pharmacological step reductions. We argue that coordinate regulation is likely to show a long-term evolutionary advantage over single enzyme regulation. Finally, the results from our models have implications for future pharmaceutical therapies intended to target cholesterol production with greater specificity and fewer off target effects, suggesting that this can be achieved by mimicking the coordinated down-regulation observed in immunological responses.

Dataset Information

Bruck2008_Glycolysis

Publications

Exploring the effect of variable enzyme concentrations in a kinetic model of yeast glycolysis.

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