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Martins2004_Yeast_Glycolysis_GlycerolSynthesis

ABSTRACT: A systems biology study of two distinct growth phases of Saccharomyces cerevisiae cultures AM Martins, D Camacho, J Shuman, W Sha, P Mendes, V Shulaev, Current Genomics 2004 5:649-663 This is a model of yeast glycolysis and glycerol synthesis for high medium glucose concentration. It was constructed by joining the glycolysis model of Teusink et al. (2000) Eur J Biochem 267, 5313, modified by Pritchard and Kell (2002) Eur. J. Biochem. 269, 3894, with the glycerol synthesis model of Crownright et al. (2002) Appl. Env. Microbiol. 68, 4448. Glycerol transport was added as a first order reaction with parameters that comply with empirical data on internal/external glycerol ratios. Curation notes The model provided by the authors is available from http://www.mcisb.org/resources/models/martins04_original.xml . It contains one error: the kinetic law of glycerol 3-phosphate dehydrogenase has denominator of the form (1+NADH/Kdhap+NAD/Kg3p)*(1+DHAP/Knadh+G3P/Knad) rather than (1+DHAP/Kdhap+G3P/Kg3p)*(1+NADH/Knadh+NAD/Knad). This has now been corrected; steady states of the original model may be resolved by exchanging the order of substrates and products in COPASI . Some other cosmetic changes (e.g minutes to seconds) have also been carried out. 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: MODEL1009220000 | BioModels | 2005-01-01

REPOSITORIES: BioModels

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Project description:Previous findings have demonstrated that the NADH/NAD+ ratio has a strong impact on the glycolytic flux in C. glutamicum under anaerobic conditions in the absence of external electron acceptors. During an attempt to rewire anaerobic metabolism to achieve high yield formation of ethanol, we inactivated the malate dehydrogenase and lactate dehydrogenase in a C. glutamicum strain expressing pyruvate decarboxylase and alcohol dehydrogenase, to eliminate formation of the by-products succinate and lactate, respectively. This modification increased the yield of ethanol but had a negative effect on glycolysis, which we found to correlate with an elevated NADH/NAD+ ratio. The pyruvate dehydrogenase (PDH) of C. glutamicum is active under anaerobic conditions, and can potentially exacerbate the negative effect on glycolysis, due to NADH formation. To reduce PDH activity under anaerobic conditions, we decided to replace the gene encoding the E3 subunit of PDH with its Escherichia coli counterpart, as E. coli PDH has been reported to be functional under aerobic conditions only. The resultant strain JS133 produced far less acetate with a further increased ethanol production, however, the glycolytic flux was still low. After observing differences in glycolytic flux for JS133 on glucose and fructose, we speculated that the pentose phosphate pathway (PPP) might be involved in the reduced flux on glucose. To prove this, we deleted the zwf gene, encoding glucose-6-phosphate dehydrogenase, which is the entry point into PPP, and immediately observed a stimulating effect on glycolysis. Subsequent characterization revealed a direct correlation between the intracellular NADH/NAD+ and NADPH/NADP+ ratios under anoxic conditions. Based on these findings we managed to re-channel the metabolism of C. glutamicum successfully towards either to ethanol or D-lactate with 92% and 98% of the theoretical yield respectively, which is the highest yields for D-lactate production thus far reported in the literature.

Project description:Can yeast glycolysis be understood in terms of in vitro kinetics of the constituent enzymes? Testing biochemistry. Teusink,B et al.: Eur J Biochem 2000 Sep;267(17):5313-29. The model reproduces the steady-state fluxes and metabolite concentrations of the branched model as given in Table 4 of the paper. It is derived from the model on JWS online, but has the ATP consumption in the succinate branch with the same stoichiometrie as in the publication. The model was successfully tested on copasi v.4.4(build 26). For Vmax values, please note that there is a conversion factor of approx. 270 to convert from U/mg-protein as shown in Table 1 of the paper to mmol/(min*L_cytosol). The equilibrium constant for the ADH reaction in the paper is given for the reverse reaction (Keq = 1.45*10 4 ). The value used in this model is for the forward reaction: 1/Keq = 6.9*10 -5 . Vmax parameters values used (in [mM/min] except VmGLT): VmGLT 97.264 mmol/min VmGLK 226.45 VmPGI 339.667 VmPFK 182.903 VmALD 322.258 VmGAPDH_f 1184.52 VmGAPDH_r 6549.68 VmPGK 1306.45 VmPGM 2525.81 VmENO 365.806 VmPYK 1088.71 VmPDC 174.194 VmG3PDH 70.15 The result of the G6P steady state concentration (marked in red) differs slightly from the one given in table 4. of the publication Results for steady state: orig. article this model Fluxes[mM/min] Glucose 88 88 Ethanol 129 129 Glycogen 6 6 Trehalose 4.8 4.8 (G6P flux through trehalose branch) Glycerol 18.2 18.2 Succinate 3.6 3.6 Conc.[mM] G6P 1.07 1.03 F6P 0.11 0.11 F1,6P 0.6 0.6 DHAP 0.74 0.74 3PGA 0.36 0.36 2PGA 0.04 0.04 PEP 0.07 0.07 PYR 8.52 8.52 AcAld 0.17 0.17 ATP 2.51 2.51 ADP 1.29 1.29 AMP 0.3 0.3 NAD 1.55 1.55 NADH 0.04 0.04 Authors of the publication also mentioned a few misprints in the original article: in the kinetic law for ADH : the species a should denote NAD and b Ethanol the last term in the equation should read bpq /( K ib K iq K p ) in the kinetic law for PFK : R = 1 + λ 1 + λ 2 + g r λ 1 λ 2 equation L should read: L = L0*(..) 2 *(..) 2 *(..) 2 not L = L0*(..) 2 *(..) 2 *(..) To make the model easier to curate, the species ATP , ADP and AMP were added. These are calculated via assignment rules from the active phosphate species, P , and the sum of all AXP , SUM_P . 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.

Project description:Background: Anaerobic Saccharomyces cerevisiae cultures require glycerol formation to re-oxidize NADH formed in biosynthetic processes. Introduction of the Calvin-cycle enzymes phosphoribulokinase (PRK) and ribulose-1,5-biphosphate carboxylase/oxygenase (RuBisCO) has been shown to couple re-oxidation of biosynthetic NADH to ethanol production and improve ethanol yield on sugar in fast-growing batch cultures. Since growth rates in industrial ethanol-production processes are not constant, performance of engineered strains was studied in slow-growing cultures. Results: In slow-growing anaerobic chemostat cultures (D = 0.05 h-1), an engineered PRK-RuBisCO strain produced 80-fold more acetaldehyde and 30-fold more acetate than a reference strain. This observation suggested an imbalance between in vivo activities of PRK-RuBisCO and formation of NADH in biosynthesis. Lowering the copy number of the RuBisCO-encoding cbbm expression cassette from 15 to 2 reduced acetaldehyde and acetate yields by 67% and 29%, respectively. Additional C-terminal fusion of a 19 amino-acid tag to PRK reduced its protein level by 13-fold while acetaldehyde and acetate production decreased by 94% and 61%, respectively, relative to the 15x cbbm strain. These modifications did not affect glycerol production at 0.05 h-1 but caused a 4.6 fold higher glycerol production per amount of biomass in fast-growing (0.29 h-1) anaerobic batch cultures than observed for the 15x cbbm strain. In another strategy, the promoter of ANB1, whose transcript level positively correlated with growth rate, was used to control PRK synthesis in a 2x cbbm strain. At 0.05 h-1, this strategy reduced acetaldehyde and acetate production by 79% and 40%, respectively, relative to the 15x cbbm strain, without affecting glycerol yield. The maximum growth rate of the resulting strain equalled that of the reference strain, while its glycerol yield was 72% lower. Conclusions: Acetaldehyde and acetate formation by slow-growing cultures of engineered S. cerevisiae strains carrying a PRK-RuBisCO bypass of yeast glycolysis was attributed to an in vivo overcapacity of PRK and RuBisCO. Reducing the capacity of PRK and/or RuBisCO was shown to mitigate this undesirable byproduct formation. Use of a growth-rate-dependent promoter for PRK expression highlighted the potential of modulating gene expression in engineered strains to respond to growth-rate dynamics in industrial batch processes.

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Martins2004_Yeast_Glycolysis_GlycerolSynthesis

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