Chassagnole2001_Threonine Synthesis
Ontology highlight
ABSTRACT:
SUBMITTER: 
Nicolas Le Novère
PROVIDER: BIOMD0000000066 | BioModels | 2006-08-29
REPOSITORIES: BioModels
Publications
Control of the threonine-synthesis pathway in Escherichia coli: a theoretical and experimental approach.
Chassagnole C C Fell D A DA Raïs B B Kudla B B Mazat J P JP
The Biochemical journal 20010601 Pt 2
A computer simulation of the threonine-synthesis pathway in Escherichia coli Tir-8 has been developed based on our previous measurements of the kinetics of the pathway enzymes under near-physiological conditions. The model successfully simulates the main features of the time courses of threonine synthesis previously observed in a cell-free extract without alteration of the experimentally determined parameters, although improved quantitative fits can be obtained with small parameter adjustments. ...[more]
Similar Datasets
Project description:.
.
.
SBML
level 2 code generated for the JWS Online project by Jacky Snoep using PySCeS
Run this model online at http://jjj.biochem.sun.ac.za
To cite JWS Online please refer to: Olivier, B.G. and Snoep, J.L. (2004) Web-based
modelling using JWS Online
, Bioinformatics, 20:2143-2144
.
.
.
.
.
.
Biomodels Curation
The model reproduces the flux value of "Gpp p" (rate of Glycerol synthesis) as depicted in Fig 3 of the paper. The model reproduces the flux for early exponential phase , however it can be used to reproduce the values for other phases by plugging in appropriate values for maximal rates as given in Table 1 and metabolite concentrations as given in Table 2 of the paper. The model was succesfully reproduced using Jarnac.
2006-11-06 | BIOMD0000000076 | BioModels
Project description:.
.
.
SBML level 2 code generated for the JWS Online project by Jacky Snoep using PySCeS
Run this model online at http://jjj.biochem.sun.ac.za
To cite JWS Online please refer to: Olivier, B.G. and Snoep, J.L. (2004) Web-based
modelling using JWS Online, Bioinformatics, 20:2143-2144
.
.
.
.
.
.
Biomodels Curation
The model simulates the flux values as given for "kinetic model" in Table 1 of the paper. The model was successfully tested on Jarnac.
2006-09-07 | BIOMD0000000070 | BioModels
Project description:.
.
.
SBML
level 2 code generated for the JWS Online project by Jacky Snoep using PySCeS
Run this model online at http://jjj.biochem.sun.ac.za
To cite JWS Online please refer to: Olivier, B.G. and Snoep, J.L. (2004) Web-based
modelling using JWS Online
, Bioinformatics, 20:2143-2144
.
.
Biomodels Curation:
The paper refers to the model equations present in Bakker et al's " Glycolysis in bloodstream from Trypanosoma brucei can be understood in terms of the kinetics of glycolytic enzymes" (Pubmed ID: 9013556), also, the authors claim that some of the modifications in these equations were made based on the experimental results from the paper "Contribution of glucose transport in the control of glycolytic flux in Trypanosoma brucei" (Pubmed ID: 10468568). The model reproduces the various flux values in Fig 3 for 100% TPI activity. It also matches with the values provided in Table 2 of the paper. The model was successfully tested with Copasi and SBML ODE Solver.
The volumes are set to the values containing 1 mg of total protein per microlitre total cell volume. To change the protein concentration use Vt
, the total cell volume in micro litre per mg protein.
To change the TPI activity use the global parameter TPIact
.
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.
2008-10-09 | BIOMD0000000071 | BioModels
Project description:The model reproduces Figures 4,5 and 6 of the publication. The analytical functions for cometabolites Catp, Camp, Cnadph, and Cnadp slightly differ from the equations given in the paper. These changes were made in consultation with Dr. Christophe Chassagnole and are essential for reproducing the figures. The dependency of the rate of change of extracellular glucose concentration on the ratio of biomass concentration to specific weight of biomass (Cx*rPTS/Rhox) is taken into account by appropriately adjusting the stoichiometries of the species involved in the phosphotransferase system (rPTS). The rmax values for the various reactions are obtained from experiments and are not provided in the paper. However, these were personally communicated to the JWS repository. The model has been successfully tested on MathSBML.
SBML
level 2 code generated for the JWS Online project by Jacky Snoep using PySCeS
Run this model online at http://jjj.biochem.sun.ac.za
To cite JWS Online please refer to: Olivier, B.G. and Snoep, J.L. (2004) Web-based
modelling using JWS Online
, Bioinformatics, 20:2143-2144
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.
2006-01-18 | BIOMD0000000051 | BioModels
Project description:This a model from the article:
A kinetic model of the branch-point between the methionine and threonine biosynthesis pathways in Arabidopsis thaliana.
Curien G, Ravanel S, Dumas R Eur. J. Biochem.
2003 Dec; Volume: 270 (Issue: 23 )]:4615-27 14622248
,
Abstract:
This work proposes a model of the metabolic branch-point between the methionine and threonine biosynthesis pathways in Arabidopsis thaliana which involves kinetic competition for phosphohomoserine between the allosteric enzyme threonine synthase and the two-substrate enzyme cystathionine gamma-synthase. Threonine synthase is activated by S-adenosylmethionine and inhibited by AMP. Cystathionine gamma-synthase condenses phosphohomoserine to cysteine via a ping-pong mechanism. Reactions are irreversible and inhibited by inorganic phosphate. The modelling procedure included an examination of the kinetic links, the determination of the operating conditions in chloroplasts and the establishment of a computer model using the enzyme rate equations. To test the model, the branch-point was reconstituted with purified enzymes. The computer model showed a partial agreement with the in vitro results. The model was subsequently improved and was then found consistent with flux partition in vitro and in vivo. Under near physiological conditions, S-adenosylmethionine, but not AMP, modulates the partition of a steady-state flux of phosphohomoserine. The computer model indicates a high sensitivity of cystathionine flux to enzyme and S-adenosylmethionine concentrations. Cystathionine flux is sensitive to modulation of threonine flux whereas the reverse is not true. The cystathionine gamma-synthase kinetic mechanism favours a low sensitivity of the fluxes to cysteine. Though sensitivity to inorganic phosphate is low, its concentration conditions the dynamics of the system. Threonine synthase and cystathionine gamma-synthase display similar kinetic efficiencies in the metabolic context considered and are first-order for the phosphohomoserine substrate. Under these conditions outflows are coordinated.
SBML
level 2 code generated for the JWS Online project by Jacky Snoep using PySCeS
Run this model online at http://jjj.biochem.sun.ac.za
To cite JWS Online please refer to: Olivier, B.G. and Snoep, J.L. (2004) Web-based
modelling using JWS Online
, Bioinformatics, 20:2143-2144
Biomodels Curation
The model simulates the flux for TS and CGS under conditions given in Table 2 and reproduces the dotted lines given in Table 3 of the paper. There is a typo in the equation for the apparent specificity constant for Phser, Kts (equation13). This was changed after communication with the authors to be: Kts = 5.9E-4+6.2E-2*pow(AdoMet,2.9)/(pow(32,2.9)+pow(AdoMet,2.9)). The model was successfully tested on Jarnac and Copasi. Due to a suggestion from Pedro Mendez the parameter AdoMet, TS and CGS where made constant species.
This model originates from BioModels Database: A Database of Annotated Published Models (http://www.ebi.ac.uk/biomodels/). It is copyright (c) 2005-2010 The BioModels.net Team.
For more information see the terms of use
.
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.
2006-08-30 | BIOMD0000000068 | BioModels
Project description:The model reproduces Fig 6 of the paper. The stoichiometry and rate of reactions involving uptake of metabolites from extracellular medium have been changed corresponding to Yvol (ratio of extracellular volume to cytosolic volume) mentioned in the publication. The extracellular and cytosolic compartments have been set to 1. Concentration of extracellular glucose, GlcX, is set to 6.7 according to the equation for cellular glucose uptake rate in Table 7 of the paper. The model was successfully tested on MathSBML and Jarnac
.
.
.
SBML
level 2 code generated for the JWS Online project by Jacky Snoep using PySCeS
Run this model online at http://jjj.biochem.sun.ac.za
To cite JWS Online please refer to: Olivier, B.G. and Snoep, J.L. (2004) Web-based
modelling using JWS Online
, Bioinformatics, 20:2143-2144
.
.
.
.
.
.
This model originates from BioModels Database: A Database of Annotated Published Models. It is copyright (c) 2005-2009 The BioModels Team.
For more information see the terms of use
.
To cite BioModels Database, please use Le Novère N., Bornstein B., Broicher A., Courtot M., Donizelli M., Dharuri H., Li L., Sauro H., Schilstra M., Shapiro B., Snoep J.L., Hucka M. (2006) BioModels Database: A Free, Centralized Database of Curated, Published, Quantitative Kinetic Models of Biochemical and Cellular Systems Nucleic Acids Res., 34: D689-D691.
2006-07-12 | BIOMD0000000061 | BioModels
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.
2008-09-16 | BIOMD0000000064 | BioModels
Project description:The process for making monocyte derived DCs (moDCs) has been previously described (46). All analysis was performed on “day 5” immature DCs. Etanercept 10mg/mL was added to experimental wells on days 0, 2, and 4. We chose this concentration of etanercept as it approximates the plasma concentration of drug when given 50mg BIW. Keywords: Inhibition assay
2007-10-06 | GSE9239 | GEO
Project description:Online buffer exchange (OBE)-MS data for "Stepwise design of pseudosymmetric protein hetero-oligomers"(https://doi.org/10.1101/2023.04.07.535760). Raw file names correspond to file names given in the reports in Table S7. Data was collected using Xcalibur and data were deconvolved using UniDec (https://github.com/michaelmarty/UniDec)
2023-08-22 | MSV000092722 | MassIVE
Project description:This a model from the article:
Modelling the dynamics of the yeast pheromone pathway.
Kofahl B, Klipp E
Yeast[2004 Jul; Volume: 21 (Issue: 10 )] Page info: 831-50
15300679,
Abstract:
We present a mathematical model of the dynamics of the pheromone pathways in haploid yeast cells of mating type MATa after stimulation with pheromone alpha-factor. The model consists of a set of differential equations and describes the dynamics of signal transduction from the receptor via several steps, including a G protein and a scaffold MAP kinase cascade, up to changes in the gene expression after pheromone stimulation in terms of biochemical changes (complex formations, phosphorylations, etc.). The parameters entering the models have been taken from the literature or adapted to observed time courses or behaviour. Using this model we can follow the time course of the various complex formation processes and of the phosphorylation states of the proteins involved. Furthermore, we can explain the phenotype of more than a dozen well-characterized mutants and also the graded response of yeast cells to varying concentrations of the stimulating pheromone.
The model was updated on 21st October 2010, by Vijayalakshmi Chelliah.
The following changes were made: 1) The model has been converted to SBML l2v4.
2) The model has been recurated and the curation figure was updated (units are in nanoMolar; but the publication has units in microMolar). Simulations were done using Copasi v4.6 (Build 32).
3) Notes have been added.
4) Annotation for one of the species has been corrected (Complex M).
SBML level 2 code generated for the JWS Online project by Jacky Snoep using
PySCeS
Run this model online at
http://jjj.biochem.sun.ac.za
To cite JWS Online please refer to: Olivier, B.G. and Snoep, J.L. (2004)
Web-based
modelling using JWS Online, Bioinformatics, 20:2143-2144
The following are the four major differences between the original publication by Kofahl et al and the model that actually is able to replicate the results as depicted in the publication (those corrections have been made in agreement with the authors):
1. Bar1 is the inactive protease present inside the cell but the publication wrongly mentions that Bar1 is also the protease that is present on the extracellular surface.
The model correctly names the protease in it's different forms by calling inactive Bar1 within the cell as Bar1, active Bar1 within the cell as Bar1a and extracellular Bar1 as Bar1aex
2. The initial amount of Alpha-factor is given as 1000nM but the model uses a value of 100nM.
3. The value of the paramenter k8 is given as 0.33 but the model uses a value of 0.033.
4. The value of the paramenter k41 is given as 0.002 but the model uses a value of 0.02.
This model originates from BioModels Database: A Database of Annotated Published Models (http://www.ebi.ac.uk/biomodels/).(http://www.ebi.ac.uk/biomodels/). It is copyright (c) 2005-2010 The BioModels.net Team.
For more information see the terms of use.
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.
2005-06-08 | BIOMD0000000032 | BioModels