Hat2016 - Reponse of p53 System to irradiation in cell fate decision making

  public model
Model Identifier
BIOMD0000000943
Short description 
The p53 transcription factor is a regulator of key cellular processes including DNA repair, cell cycle arrest, and apoptosis. In this theoretical study, we investigate how the complex circuitry of the p53 network allows for stochastic yet unambiguous cell fate decision-making. The proposed Markov chain model consists of the regulatory core and two subordinated bistable modules responsible for cell cycle arrest and apoptosis. The regulatory core is controlled by two negative feedback loops (regulated by Mdm2 and Wip1) responsible for oscillations, and two antagonistic positive feedback loops (regulated by phosphatases Wip1 and PTEN) responsible for bistability. By means of bifurcation analysis of the deterministic approximation we capture the recurrent solutions (i.e., steady states and limit cycles) that delineate temporal responses of the stochastic system. Direct switching from the limit-cycle oscillations to the "apoptotic" steady state is enabled by the existence of a subcritical Neimark-Sacker bifurcation in which the limit cycle loses its stability by merging with an unstable invariant torus. Our analysis provides an explanation why cancer cell lines known to have vastly diverse expression levels of Wip1 and PTEN exhibit a broad spectrum of responses to DNA damage: from a fast transition to a high level of p53 killer (a p53 phosphoform which promotes commitment to apoptosis) in cells characterized by high PTEN and low Wip1 levels to long-lasting p53 level oscillations in cells having PTEN promoter methylated (as in, e.g., MCF-7 cell line).
Format
SBML (L2V4)
Related Publication
  • Feedbacks, Bifurcations, and Cell Fate Decision-Making in the p53 System.
  • Hat B, Kochańczyk M, Bogdał MN, Lipniacki T
  • PLoS computational biology , 2/ 2016 , Volume 12 , Issue 2 , pages: e1004787 , PubMed ID: 26928575
  • Institute of Fundamental Technological Research, Polish Academy of Sciences, Warsaw, Poland.
  • The p53 transcription factor is a regulator of key cellular processes including DNA repair, cell cycle arrest, and apoptosis. In this theoretical study, we investigate how the complex circuitry of the p53 network allows for stochastic yet unambiguous cell fate decision-making. The proposed Markov chain model consists of the regulatory core and two subordinated bistable modules responsible for cell cycle arrest and apoptosis. The regulatory core is controlled by two negative feedback loops (regulated by Mdm2 and Wip1) responsible for oscillations, and two antagonistic positive feedback loops (regulated by phosphatases Wip1 and PTEN) responsible for bistability. By means of bifurcation analysis of the deterministic approximation we capture the recurrent solutions (i.e., steady states and limit cycles) that delineate temporal responses of the stochastic system. Direct switching from the limit-cycle oscillations to the "apoptotic" steady state is enabled by the existence of a subcritical Neimark-Sacker bifurcation in which the limit cycle loses its stability by merging with an unstable invariant torus. Our analysis provides an explanation why cancer cell lines known to have vastly diverse expression levels of Wip1 and PTEN exhibit a broad spectrum of responses to DNA damage: from a fast transition to a high level of p53 killer (a p53 phosphoform which promotes commitment to apoptosis) in cells characterized by high PTEN and low Wip1 levels to long-lasting p53 level oscillations in cells having PTEN promoter methylated (as in, e.g., MCF-7 cell line).
Contributors
Submitter of the first revision: Matthieu MAIRE
Submitter of this revision: Ahmad Zyoud
Modellers: Matthieu MAIRE, Ahmad Zyoud

Metadata information

is (2 statements)
BioModels Database MODEL1809060002
BioModels Database BIOMD0000000943

hasTaxon (1 statement)
Taxonomy Homo sapiens

hasPart (1 statement)
Gene Ontology cell cycle

hasProperty (1 statement)
Mathematical Modelling Ontology Ordinary differential equation model

isDescribedBy (1 statement)
Curation status
Curated
Modelling approach(es)
ordinary differential equation model
Tags

Connected external resources

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Model files
Hat2016.xml SBML L2V4 representation of Reponse of p53 System to irradiation in cell fate decision making 350.00 KB Preview | Download

Additional files
Hat2016.cps COPASI version 4.27 (Build 217) file for reproducing figure 7 in the reference publication 441.89 KB Preview | Download
Hat2016.sedml sed-ml L1V2 file for reproducing figure 7 in the reference publication. 5.63 KB Preview | Download

  • Model originally submitted by : Matthieu MAIRE
  • Submitted: Sep 6, 2018 12:17:17 PM
  • Last Modified: May 4, 2020 6:06:11 PM
Revisions
  • Version: 4 public model Download this version
    • Submitted on: May 4, 2020 6:06:11 PM
    • Submitted by: Ahmad Zyoud
    • With comment: Automatically added model identifier BIOMD0000000943
  • Version: 2 public model Download this version
    • Submitted on: Sep 6, 2018 12:17:17 PM
    • Submitted by: Matthieu MAIRE
    • With comment: Edited model metadata online.

(*) You might be seeing discontinuous revisions as only public revisions are displayed here. Any private revisions unpublished model revision of this model will only be shown to the submitter and their collaborators.

Legends
: Variable used inside SBML models


Species
Species Initial Concentration/Amount
HIPK2

Homeodomain-interacting protein kinase 2 		0.0 mmol
p53 0phosphorylated

Cellular tumor antigen p53 ; phosphorylated 		0.0 mmol
Mdm2 nuc S166S186p S395p

E3 ubiquitin-protein ligase Mdm2 ; phosphorylated 		0.0 mmol
PTEN mRNA

Phosphatidylinositol 3,4,5-trisphosphate 3-phosphatase and dual-specificity protein phosphatase PTEN ; ribonucleic acid 		0.0 mmol
p21 free

p21 RAS Protein 		0.0 mmol
Bad phosphorylated free

Bcl2-associated agonist of cell death ; phosphorylated 		0.0 mmol
proCaspase

Precursor 		0.0 mmol
Reactions
Reactions Rate Parameters
=> HIPK2 nuclear*s8 s8 = 30.0
p53_0phosphorylated => ; Mdm2_nuc_S166S186phosphorylated nuclear*(g101+g11*Mdm2_nuc_S166S186phosphorylated^h)*p53_0phosphorylated g101 = 1.0E-5; h = 2.0; g11 = 1.0E-11
Mdm2_nuc_S166S186p_S395p => nuclear*g16*Mdm2_nuc_S166S186p_S395p g16 = 1.0E-4
=> PTEN_mRNA; p53_killer nuclear*s2*(q0_pten+q1_pten*p53_killer^h)/(q2+q0_pten+q1_pten*p53_killer^h) q1_pten = 3.0E-13; s2 = 0.03; h = 2.0; q0_pten = 1.0E-5; q2 = 0.003
p21__free + Cyclin_E__free => Cyclin_E_p21_complex nuclear*b5*p21__free*Cyclin_E__free b5 = 1.0E-5
Bad_0__free => Bad_phosphorylated__free; AKT_phosphorylated cytoplasm*p7*AKT_phosphorylated*Bad_0__free p7 = 3.0E-9
=> Bad_phosphorylated__free; AKT_phosphorylated, BclXL_Bad_complex cytoplasm*p7*AKT_phosphorylated*BclXL_Bad_complex p7 = 3.0E-9
Bad_phosphorylated__free => ; Fourteen33_free b3*Fourteen33_free*Bad_phosphorylated__free b3 = 0.003
proCaspase => nuclear*g17*proCaspase g17 = 3.0E-4
p53_0phosphorylated => p53_S46phosphorylated; HIPK2 nuclear*p11*HIPK2*p53_0phosphorylated p11 = 1.0E-10
Curator's comment:
(added: 06 Sep 2018, 12:18:43, updated: 04 May 2020, 18:05:59)
Figure 7 of the reference publication has been reproduced using Copasi 4.27 Build 217. Use attached SEDML file to reproduce the figure 7.