bachmann2

The SBML for this model was obtained from the BioModels database (BioModels ID: BIOMD0000000347) Biomodels notes: Figure S9 of the supplementary material has been reproduced here. The model was integrated and simulated using Copasi v4.7 (Build 34). Plots were made using Gnuplot. JWS Online curation: This model was curated by reproducing the figures as described in the BioModels Notes. No additional changes were made.

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Division of labor by dual feedback regulators controls JAK2/STAT5 signaling over broad ligand range.

  • Julie Bachmann
  • Andreas Raue
  • Marcel Schilling
  • Martin E Böhm
  • Clemens Kreutz
  • Daniel Kaschek
  • Hauke Busch
  • Norbert Gretz
  • Wolf D Lehmann
  • Jens Timmer
  • Ursula Klingmüller
Mol. Syst. Biol. 2011; 7 : 516
Abstract
Cellular signal transduction is governed by multiple feedback mechanisms to elicit robust cellular decisions. The specific contributions of individual feedback regulators, however, remain unclear. Based on extensive time-resolved data sets in primary erythroid progenitor cells, we established a dynamic pathway model to dissect the roles of the two transcriptional negative feedback regulators of the suppressor of cytokine signaling (SOCS) family, CIS and SOCS3, in JAK2/STAT5 signaling. Facilitated by the model, we calculated the STAT5 response for experimentally unobservable Epo concentrations and provide a quantitative link between cell survival and the integrated response of STAT5 in the nucleus. Model predictions show that the two feedbacks CIS and SOCS3 are most effective at different ligand concentration ranges due to their distinct inhibitory mechanisms. This divided function of dual feedback regulation enables control of STAT5 responses for Epo concentrations that can vary 1000-fold in vivo. Our modeling approach reveals dose-dependent feedback control as key property to regulate STAT5-mediated survival decisions over a broad range of ligand concentrations.

Unit definitions have no effect on the numerical analysis of the model. It remains the responsibility of the modeler to ensure the internal numerical consistency of the model. If units are provided, however, the consistency of the model units will be checked.

Name Definition
Id Name Spatial dimensions Size
cyt cyt 3.0 0.4
nuc nuc 3.0 0.275
Id Name Initial quantity Compartment Fixed
CIS CIS 0.0 cyt (cyt)
CISRNA CISRNA 0.0 cyt (cyt)
CISnRNA1 CISnRNA1 0.0 nuc (nuc)
CISnRNA2 CISnRNA2 0.0 nuc (nuc)
CISnRNA3 CISnRNA3 0.0 nuc (nuc)
CISnRNA4 CISnRNA4 0.0 nuc (nuc)
CISnRNA5 CISnRNA5 0.0 nuc (nuc)
Epo Epo 0.000000124997 cyt (cyt)
EpoRJAK2 EpoRJAK2 3.97622 cyt (cyt)
EpoRJAK2_CIS EpoRJAK2_CIS 0.0 cyt (cyt)
EpoRpJAK2 EpoRpJAK2 0.0 cyt (cyt)
SHP1 SHP1 26.7251 cyt (cyt)
SHP1Act SHP1Act 0.0 cyt (cyt)
SOCS3 SOCS3 0.0 cyt (cyt)
SOCS3RNA SOCS3RNA 0.0 cyt (cyt)
SOCS3nRNA1 SOCS3nRNA1 0.0 nuc (nuc)
SOCS3nRNA2 SOCS3nRNA2 0.0 nuc (nuc)
SOCS3nRNA3 SOCS3nRNA3 0.0 nuc (nuc)
SOCS3nRNA4 SOCS3nRNA4 0.0 nuc (nuc)
SOCS3nRNA5 SOCS3nRNA5 0.0 nuc (nuc)
STAT5 STAT5 79.7535 cyt (cyt)
npSTAT5 npSTAT5 0.0 nuc (nuc)
p12EpoRpJAK2 p12EpoRpJAK2 0.0 cyt (cyt)
p1EpoRpJAK2 p1EpoRpJAK2 0.0 cyt (cyt)
p2EpoRpJAK2 p2EpoRpJAK2 0.0 cyt (cyt)
pSTAT5 pSTAT5 0.0 cyt (cyt)

Initial assignments are expressions that are evaluated at time=0. It is not recommended to create initial assignments for all model entities. Restrict the use of initial assignments to cases where a value is expressed in terms of values or sizes of other model entities. Note that it is not permitted to have both an initial assignment and an assignment rule for a single model entity.

Definition
Id Name Objective coefficient Reaction Equation and Kinetic Law Flux bounds
reaction_1 EpoRJAK2 > EpoRpJAK2

JAK2ActEpo * Epo * EpoRJAK2 / (SOCS3Inh * SOCS3 / SOCS3Eqc + 1) * cyt
reaction_10 EpoRJAK2_CIS > ∅

EpoRCISRemove * EpoRJAK2_CIS * (p12EpoRpJAK2 + p1EpoRpJAK2) / init_EpoRJAK2 * cyt
reaction_11 SHP1 > SHP1Act

SHP1ActEpoR * SHP1 * (EpoRpJAK2 + p12EpoRpJAK2 + p1EpoRpJAK2 + p2EpoRpJAK2) / init_EpoRJAK2 * cyt
reaction_12 SHP1Act > SHP1

SHP1Dea * SHP1Act * cyt
reaction_13 STAT5 > pSTAT5

STAT5ActJAK2 * STAT5 * (EpoRpJAK2 + p12EpoRpJAK2 + p1EpoRpJAK2 + p2EpoRpJAK2) / (init_EpoRJAK2 * (SOCS3Inh * SOCS3 / SOCS3Eqc + 1)) * cyt
reaction_14 STAT5 > pSTAT5

STAT5ActEpoR * STAT5 * pow(p12EpoRpJAK2 + p1EpoRpJAK2, 2) / (pow(init_EpoRJAK2, 2) * (CISInh * CIS / CISEqc + 1) * (SOCS3Inh * SOCS3 / SOCS3Eqc + 1)) * cyt
reaction_15 pSTAT5 > npSTAT5

STAT5Imp * pSTAT5 * cyt
reaction_16 npSTAT5 > STAT5

STAT5Exp * npSTAT5 * nuc
reaction_17 ∅ = CISnRNA1

-(CISRNAEqc * CISRNATurn * npSTAT5 * (ActD - 1) / init_STAT5 * nuc)
reaction_18 CISnRNA1 > CISnRNA2

CISRNADelay * CISnRNA1 * nuc
reaction_19 CISnRNA2 > CISnRNA3

CISRNADelay * CISnRNA2 * nuc
reaction_2 EpoRpJAK2 > EpoRJAK2

JAK2EpoRDeaSHP1 * SHP1Act * EpoRpJAK2 / init_SHP1 * cyt
reaction_20 CISnRNA3 > CISnRNA4

CISRNADelay * CISnRNA3 * nuc
reaction_21 CISnRNA4 > CISnRNA5

CISRNADelay * CISnRNA4 * nuc
reaction_22 CISnRNA5 > CISRNA

CISRNADelay * CISnRNA5 * nuc
reaction_23 CISRNA > ∅

CISRNATurn * CISRNA * cyt
reaction_24 ∅ > CIS

CISEqc * CISTurn * CISRNA / CISRNAEqc * cyt
reaction_25 CIS > ∅

CISTurn * CIS * cyt
reaction_26 ∅ > CIS

CISoe * CISEqc * CISTurn * CISEqcOE
reaction_27 ∅ = SOCS3nRNA1

-(SOCS3RNAEqc * SOCS3RNATurn * npSTAT5 * (ActD - 1) / init_STAT5 * nuc)
reaction_28 SOCS3nRNA1 > SOCS3nRNA2

SOCS3RNADelay * SOCS3nRNA1 * nuc
reaction_29 SOCS3nRNA2 > SOCS3nRNA3

SOCS3RNADelay * SOCS3nRNA2 * nuc
reaction_3 EpoRpJAK2 > p1EpoRpJAK2

EpoRActJAK2 * EpoRpJAK2 / (SOCS3Inh * SOCS3 / SOCS3Eqc + 1) * cyt
reaction_30 SOCS3nRNA3 > SOCS3nRNA4

SOCS3RNADelay * SOCS3nRNA3 * nuc
reaction_31 SOCS3nRNA4 > SOCS3nRNA5

SOCS3RNADelay * SOCS3nRNA4 * nuc
reaction_32 SOCS3nRNA5 > SOCS3RNA

SOCS3RNADelay * SOCS3nRNA5 * nuc
reaction_33 SOCS3RNA > ∅

SOCS3RNATurn * SOCS3RNA * cyt
reaction_34 ∅ > SOCS3

SOCS3Eqc * SOCS3Turn * SOCS3RNA / SOCS3RNAEqc * cyt
reaction_35 SOCS3 > ∅

SOCS3Turn * SOCS3 * cyt
reaction_36 ∅ > SOCS3

SOCS3oe * SOCS3Eqc * SOCS3Turn * SOCS3EqcOE
reaction_4 EpoRpJAK2 > p2EpoRpJAK2

3 * EpoRActJAK2 * EpoRpJAK2 / ((SOCS3Inh * SOCS3 / SOCS3Eqc + 1) * (EpoRCISInh * EpoRJAK2_CIS + 1)) * cyt
reaction_5 p1EpoRpJAK2 > p12EpoRpJAK2

3 * EpoRActJAK2 * p1EpoRpJAK2 / ((SOCS3Inh * SOCS3 / SOCS3Eqc + 1) * (EpoRCISInh * EpoRJAK2_CIS + 1)) * cyt
reaction_6 p2EpoRpJAK2 > p12EpoRpJAK2

EpoRActJAK2 * p2EpoRpJAK2 / (SOCS3Inh * SOCS3 / SOCS3Eqc + 1) * cyt
reaction_7 p1EpoRpJAK2 > EpoRJAK2

JAK2EpoRDeaSHP1 * SHP1Act * p1EpoRpJAK2 / init_SHP1 * cyt
reaction_8 p2EpoRpJAK2 > EpoRJAK2

JAK2EpoRDeaSHP1 * SHP1Act * p2EpoRpJAK2 / init_SHP1 * cyt
reaction_9 p12EpoRpJAK2 > EpoRJAK2

JAK2EpoRDeaSHP1 * SHP1Act * p12EpoRpJAK2 / init_SHP1 * cyt

Global parameters

Id Value
ActD 0.0
CISEqc 432.871
CISEqcOE 0.530261
CISInh 784653000.0
CISRNADelay 0.144775
CISRNAEqc 1.0
CISRNATurn 1000.0
CISTurn 0.00839842
CISoe 0.0
EpoRActJAK2 0.267308
EpoRCISInh 1000000.0
EpoRCISRemove 5.42932
JAK2ActEpo 633253.0
JAK2EpoRDeaSHP1 142.722
SHP1ActEpoR 0.001
SHP1Dea 0.00816391
SOCS3Eqc 173.653
SOCS3EqcOE 0.679157
SOCS3Inh 10.408
SOCS3RNADelay 1.06465
SOCS3RNAEqc 1.0
SOCS3RNATurn 0.00830844
SOCS3Turn 10000.0
SOCS3oe 0.0
STAT5ActEpoR 38.9757
STAT5ActJAK2 0.0780965
STAT5Exp 0.0745155
STAT5Imp 0.0268889
epo_level 0.000000124997
init_EpoRJAK2 3.97622
init_SHP1 26.7251
init_STAT5 79.7535

Local parameters

Id Value Reaction

Assignment rules

Definition

Rate rules

Definition

Algebraic rules

Definition
Trigger Assignments