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BIOMD0000000237 - Schaber2006_Pheromone_Starvation_Crosstalk

 

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Reference Publication
Publication ID: 16884493
Schaber J, Kofahl B, Kowald A, Klipp E.
A modelling approach to quantify dynamic crosstalk between the pheromone and the starvation pathway in baker's yeast.
FEBS J. 2006 Aug; 273(15): 3520-3533
Max Planck Institute for Molecular Genetics, Berlin, Germany.  [more]
Model
Original Model: JWS logo
Submitter: Lukas Endler
Submission ID: MODEL5952001443
Submission Date: 25 Jun 2009 18:46:44 UTC
Last Modification Date: 08 Sep 2011 11:27:23 UTC
Creation Date: 20 Aug 2009 17:18:13 UTC
Encoders:  Lukas Endler
   Vijayalakshmi Chelliah
   Jorg Schaber
set #1
bqbiol:hasVersion Gene Ontology pheromone metabolic process
Gene Ontology regulation of filamentous growth
set #2
bqbiol:isVersionOf Gene Ontology cellular response to starvation
set #3
bqbiol:hasProperty Mathematical Modelling Ontology MAMO_0000046
set #4
bqbiol:hasTaxon Taxonomy Saccharomyces cerevisiae
Notes

This a model from the article:
A modelling approach to quantify dynamic crosstalk between the pheromone and the starvation pathway in baker's yeast.
Schaber J, Kofahl B, Kowald A, Klipp E FEBS J.2006 Aug; 273(15):3520-33 16884493,
Abstract:
Cells must be able to process multiple information in parallel and, moreover, they must also be able to combine this information in order to trigger the appropriate response. This is achieved by wiring signalling pathways such that they can interact with each other, a phenomenon often called crosstalk. In this study, we employ mathematical modelling techniques to analyse dynamic mechanisms and measures of crosstalk. We present a dynamic mathematical model that compiles current knowledge about the wiring of the pheromone pathway and the filamentous growth pathway in yeast. We consider the main dynamic features and the interconnections between the two pathways in order to study dynamic crosstalk between these two pathways in haploid cells. We introduce two new measures of dynamic crosstalk, the intrinsic specificity and the extrinsic specificity. These two measures incorporate the combined signal of several stimuli being present simultaneously and seem to be more stable than previous measures. When both pathways are responsive and stimulated, the model predicts that (a) the filamentous growth pathway amplifies the response of the pheromone pathway, and (b) the pheromone pathway inhibits the response of filamentous growth pathway in terms of mitogen activated protein kinase activity and transcriptional activity, respectively. Among several mechanisms we identified leakage of activated Ste11 as the most influential source of crosstalk. Moreover, we propose new experiments and predict their outcomes in order to test hypotheses about the mechanisms of crosstalk between the two pathways. Studying signals that are transmitted in parallel gives us new insights about how pathways and signals interact in a dynamical way, e.g., whether they amplify, inhibit, delay or accelerate each other.

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.

Model
Publication ID: 16884493 Submission Date: 25 Jun 2009 18:46:44 UTC Last Modification Date: 08 Sep 2011 11:27:23 UTC Creation Date: 20 Aug 2009 17:18:13 UTC
Mathematical expressions
Reactions
v1 v2 v3 v4
v5 v6 v7 v8
v9 v10 v11 v12
v13 v14 v15 v16
v17 v18 v19 v20
v21 v22 v23 v24
v25 v26 v27 v28
v29 v30 v31  
Rules
Assignment Rule (variable: alpha) Assignment Rule (variable: beta)    
Physical entities
Compartments Species
compartment Ste5 Ste11 Ste5Ste11
Gbg Ste5Ste11Gbg Fus3
Ste5Ste11GbgFus3 Ste5Ste11GbgFus3P Fus3PP
Ste5Ste11GbgP Ste11Ubi p
Kss1 Ste5Ste11GbgKss1 Ste5Ste11GbgKss1P
Kss1PP Ste11P Ste12Kss1
Ste12 Ste12P s
PREP Ste12TeSte5Kss1 Ste12TeSte5
Ste12TeSte5P FREP  
Global parameters
alpha beta alphaA betaA
alphat betat alphas betas
alphae betae k3 k4
k5 k6 k9 k10
k11 k12 k13 k17
k19 k20 k21 k22
k23 k25 k27 k31
k32 k33 k34 k8
k14 k15 k16 k26
k30 k7 k18 k1
k2 k24 k28 k29
alphastim betastim    
Reactions (31)
 
 v1 [Ste5] + [Ste11] ↔ [Ste5Ste11];  
 
 v2 [Ste5Ste11] + [Gbg] ↔ [Ste5Ste11Gbg];  
 
 v3 [Ste5Ste11Gbg] + [Fus3] ↔ [Ste5Ste11GbgFus3];  
 
 v4 [Ste5Ste11GbgFus3] ↔ [Ste5Ste11GbgFus3P];  
 
 v5 [Ste5Ste11GbgFus3P] ↔ [Fus3PP] + [Ste5Ste11GbgP];  
 
 v6 [Fus3] + [Ste5Ste11GbgP] ↔ [Ste5Ste11GbgFus3P];  
 
 v7 [Ste5] + [Ste5Ste11GbgP] ↔ [Gbg] + [Ste11Ubi];  
 
 v8 [Ste11Ubi] ↔ [p];  
 
 v9 [Ste5Ste11Gbg] + [Kss1] ↔ [Ste5Ste11GbgKss1];  
 
 v10 [Ste5Ste11GbgKss1] ↔ [Ste5Ste11GbgKss1P];  
 
 v11 [Ste5Ste11GbgKss1P] ↔ [Ste5Ste11GbgP] + [Kss1PP];  
 
 v12 [Ste5Ste11GbgP] + [Kss1] ↔ [Ste5Ste11GbgKss1P];  
 
 v13 [Ste11] ↔ [Ste11P];  
 
 v14 [Ste11P] ↔ [Ste11];  
 
 v15 [Kss1] ↔ [Kss1PP];   {Ste11P} , {Ste11Ubi}
 
 v16 [Kss1PP] ↔ [Kss1];   {Fus3PP}
 
 v17 [Ste12Kss1] ↔ 2.0 × [Kss1] + [Ste12];  
 
 v18 2.0 × [Kss1] + [Ste12] ↔ [Ste12Kss1];  
 
 v19 [Ste12] ↔ [Ste12P];   {Fus3PP} , {Kss1PP}
 
 v20 [s] ↔ [PREP];   {Ste12P}
 
 v21 [Ste12TeSte5Kss1] ↔ [Kss1] + [Ste12TeSte5];  
 
 v22 [Kss1] + [Ste12TeSte5] ↔ [Ste12TeSte5Kss1];  
 
 v23 [Ste12TeSte5] ↔ [Ste12TeSte5P];   {Kss1PP}
 
 v24 [Ste12TeSte5] ↔ [p];   {Fus3PP}
 
 v25 [s] ↔ [FREP];   {Ste12TeSte5P}
 
 v26 [Fus3PP] ↔ [Fus3];  
 
 v27 [Ste5Ste11] ↔ [Ste5] + [Ste11];  
 
 v28 [Ste12P] ↔ [Ste12];  
 
 v29 [PREP] ↔ [p];  
 
 v30 [Ste12TeSte5P] ↔ [Ste12TeSte5];  
 
 v31 [FREP] ↔ [p];  
 
Rules (2)
 
 Assignment Rule (name: alpha) alpha = alphastim*piecewise(alphaA*(1-exp((-(time-alphat))/alphas)), (time >= alphat) and (time <= alphae), piecewise(alphaA*exp((-(time-alphat))/alphas), time >= alphae, 0))
 
 Assignment Rule (name: beta) beta = betastim*betaA*piecewise(1-exp((-(time-betat))/betas), (time >= betat) and (time <= betae), piecewise(exp((-(time-betae))/betas), time > betae, 0))
 
 compartment Spatial dimensions: 3.0  Compartment size: 1.0
 
 Ste5
Compartment: compartment
Initial concentration: 42.3
 
 Ste11
Compartment: compartment
Initial concentration: 13.3
 
 Ste5Ste11
Compartment: compartment
Initial concentration: 5.6
 
 Gbg
Compartment: compartment
Initial concentration: 53.0
 
 Ste5Ste11Gbg
Compartment: compartment
Initial concentration: 0.0
 
 Fus3
Compartment: compartment
Initial concentration: 217.0
 
 Ste5Ste11GbgFus3
Compartment: compartment
Initial concentration: 0.0
 
 Ste5Ste11GbgFus3P
Compartment: compartment
Initial concentration: 0.0
 
 Fus3PP
Compartment: compartment
Initial concentration: 0.0
 
 Ste5Ste11GbgP
Compartment: compartment
Initial concentration: 0.0
 
 Ste11Ubi
Compartment: compartment
Initial concentration: 0.0
 
 p
Compartment: compartment
Initial concentration: 0.0
Constant
 
 Kss1
Compartment: compartment
Initial concentration: 54.4
 
 Ste5Ste11GbgKss1
Compartment: compartment
Initial concentration: 0.0
 
 Ste5Ste11GbgKss1P
Compartment: compartment
Initial concentration: 0.0
 
 Kss1PP
Compartment: compartment
Initial concentration: 0.0
 
 Ste11P
Compartment: compartment
Initial concentration: 0.0
 
 Ste12Kss1
Compartment: compartment
Initial concentration: 35.9
 
 Ste12
Compartment: compartment
Initial concentration: 0.07
 
 Ste12P
Compartment: compartment
Initial concentration: 0.0
 
 s
Compartment: compartment
Initial concentration: 0.0
Constant
 
 PREP
Compartment: compartment
Initial concentration: 0.0
 
 Ste12TeSte5Kss1
Compartment: compartment
Initial concentration: 13.7
 
 Ste12TeSte5
Compartment: compartment
Initial concentration: 0.25
 
 Ste12TeSte5P
Compartment: compartment
Initial concentration: 0.0
 
 FREP
Compartment: compartment
Initial concentration: 0.0
 
Global Parameters (46)
 
   alpha
Value: NaN
 
   beta
Value: NaN
 
   alphaA
Value: 1.0
Constant
 
   betaA
Value: 1.0
Constant
 
   alphat
Constant
 
   betat
Constant
 
   alphas
Value: 2.0
Constant
 
   betas
Value: 20.0
Constant
 
   alphae
Value: 10.0
Constant
 
   betae
Value: 360.0
Constant
 
   k3
Value: 1.0
Constant
 
   k4
Value: 1.0
Constant
 
   k5
Value: 1.0
Constant
 
   k6
Value: 1.0
Constant
 
   k9
Value: 1.0
Constant
 
   k10
Value: 1.0
Constant
 
   k11
Value: 1.0
Constant
 
   k12
Value: 1.0
Constant
 
   k13
Value: 1.0
Constant
 
   k17
Value: 1.0
Constant
 
   k19
Value: 1.0
Constant
 
   k20
Value: 1.0
Constant
 
   k21
Value: 1.0
Constant
 
   k22
Value: 1.0
Constant
 
   k23
Value: 1.0
Constant
 
   k25
Value: 1.0
Constant
 
   k27
Value: 1.0
Constant
 
   k31
Value: 1.0
Constant
 
   k32
Value: 1.0
Constant
 
   k33
Value: 1.0
Constant
 
   k34
Value: 1.0
Constant
 
   k8
Value: 0.1
Constant
 
   k14
Value: 0.1
Constant
 
   k15
Value: 0.1
Constant
 
   k16
Value: 0.1
Constant
 
   k26
Value: 0.1
Constant
 
   k30
Value: 0.1
Constant
 
   k7
Value: 10.0
Constant
 
   k18
Value: 10.0
Constant
 
   k1
Value: 0.01
Constant
 
   k2
Value: 0.01
Constant
 
   k24
Value: 0.01
Constant
 
   k28
Value: 0.01
Constant
 
   k29
Value: 0.01
Constant
 
   alphastim
Value: 1.0
Constant
 
   betastim
Value: 1.0
Constant
 
Representative curation result(s)
Representative curation result(s) of BIOMD0000000237

Curator's comment: (updated: 24 Nov 2009 16:01:27 GMT)

The model reproduces figure 4 of the reference publication. The four plots for "Fus3PP", "Kss1PP", "PREP" and "FREP" displays for the case 1) that only pheromone (alpha; green in the plot) is present, 2) that only a starvation signal (beta; blue in the plot) is present and 3) that both are active (alpha and beta; red in the plot). For the case that have only
1) pheromone is present, the parameter is set as, alphastim=1 and betastim=0. 2) starvation signal is present, the parameter is set as, alphastim=0 and betastim=1. 3)for both active, alphastim=betastim=1.
The model was simulated and integrated using Copasi v4.5 (Build 30).

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