BioModels Database logo

BioModels Database

spacer

BIOMD0000000104 - Klipp2002_MetabolicOptimization_linearPathway(n=2)

 

 |   |   |  Send feedback
Reference Publication
Publication ID: 12423338
Klipp E, Heinrich R, Holzhütter HG.
Prediction of temporal gene expression. Metabolic opimization by re-distribution of enzyme activities.
Eur. J. Biochem. 2002 Nov; 269(22): 5406-5413
Max-Planck-Institute of Molecular Genetics, Berlin, Germany.  [more]
Model
Original Model: BIOMD0000000104.xml.origin
Submitter: Enuo He
Submission ID: MODEL4931762955
Submission Date: 26 Mar 2007 18:08:46 UTC
Last Modification Date: 04 Apr 2014 15:25:43 UTC
Creation Date: 26 Mar 2007 09:35:54 UTC
Encoders:  Nicolas Le Novère
   Enuo He
   Nick Juty
set #1
bqbiol:isVersionOf Gene Ontology regulation of gene expression
Gene Ontology catalytic activity
bqbiol:hasTaxon Taxonomy cellular organisms
bqmodel:is BioModels Database MODEL4931762955
set #2
bqmodel:is BioModels Database Klipp2002_MetabolicOptimization_linearPathway(n=2)
set #3
bqbiol:hasProperty Mathematical Modelling Ontology MAMO_0000046
Notes
Klipp2002_MetabolicOptimization_linearPathway(n=2)

The model describes time dependent gene expression as a means to enable cells to adapt metabolic activity optimally based on environmental conditions. It uses a simple unbranched pathway and a constraint of fixed total enzyme. It calculates enzyme profiles at different times which optimise a performance function, and compares them to experimental data. The initial model is cell-type agnostic, while the experimeental data is from yeast.

This model is described in the article:

Klipp E, Heinrich R, Holzhütter HG.
Eur. J. Biochem. 2002 Nov; 269(22): 5406-5413

Abstract:

A computational approach is used to analyse temporal gene expression in the context of metabolic regulation. It is based on the assumption that cells developed optimal adaptation strategies to changing environmental conditions. Time- dependent enzyme profiles are calculated which optimize the function of a metabolic pathway under the constraint of limited total enzyme amount. For linear model pathways it is shown that wave-like enzyme profiles are optimal for a rapid substrate turnover. For the central metabolism of yeast cells enzyme profiles are calculated which ensure long-term homeostasis of key metabolites under conditions of a diauxic shift. These enzyme profiles are in close correlation with observed gene expression data. Our results demonstrate that optimality principles help to rationalize observed gene expression profiles.

This model is from the paper Prediction of temporal gene expression metabolic optimization by re-distribution of enzyme activities. The model describes optimal enzyme profiles and metabolite time courses for a simple linear metabolic pathway (n=2). Figure 1 was reproduced using roadRunner. The values of k1 and k2 were not explicitly stated in the publication, but calculations were performed for equal catalytic efficiencies of the enzymes (ki=k), hence the curator assigned k1=k2=1. Also enzyme concentrations are given in units of Etot; times are given in units of 1/(k*Etot) in the papaer, for simplicity , we use defalut units of the SBML to present the concentration and time.

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.

Model
Publication ID: 12423338 Submission Date: 26 Mar 2007 18:08:46 UTC Last Modification Date: 04 Apr 2014 15:25:43 UTC Creation Date: 26 Mar 2007 09:35:54 UTC
Mathematical expressions
Reactions
S->X1 X1->P    
Rules
Assignment Rule (variable: E2)      
Events
single switch      
Physical entities
Compartments Species
cell S X1 E1
E2 P Etot
Reactions (2)
 
 S->X1 [S] → [X1];   {E1}
 
 X1->P [X1] → [P];   {E2}
 
Rules (1)
 
 Assignment Rule (name: species_3) E2 = species_5-species_2
 
Events (1)
 
 single switch
E1 = 0.4
 
 cell Spatial dimensions: 3.0  Compartment size: 1.0
 
 S
Compartment: cell
Initial concentration: 1.0
 
 X1
Compartment: cell
Initial concentration: 0.0
 
 E1
Compartment: cell
Initial concentration: 1.0
 
  E2
Compartment: cell
Initial concentration: 0.0
 
 P
Compartment: cell
Initial concentration: 0.0
 
 Etot
Compartment: cell
Initial concentration: 1.0
Constant
 
S->X1 (1)
 
   k1
Value: 1.0
Constant
 
X1->P (1)
 
   k2
Value: 1.0
Constant
 
Representative curation result(s)
Representative curation result(s) of BIOMD0000000104

Curator's comment: (updated: 26 Mar 2007 18:58:39 BST)

Figure 1 has been obtained by RoadRunner. Species_0 is S, Species_1 is X1, Species_4 is P.

spacer
spacer