Proctor2008 - p53/Mdm2 circuit - p53 stabilisation by ATM

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Model Identifier
BIOMD0000000188
Short description
Proctor2008 - p53/Mdm2 circuit - p53 stabilisation by ATM

This model is described in the article:

Proctor CJ, Gray DA.
BMC Syst Biol 2008; 2: 75

Abstract:

BACKGROUND: In individual living cells p53 has been found to be expressed in a series of discrete pulses after DNA damage. Its negative regulator Mdm2 also demonstrates oscillatory behaviour. Attempts have been made recently to explain this behaviour by mathematical models but these have not addressed explicit molecular mechanisms. We describe two stochastic mechanistic models of the p53/Mdm2 circuit and show that sustained oscillations result directly from the key biological features, without assuming complicated mathematical functions or requiring more than one feedback loop. Each model examines a different mechanism for providing a negative feedback loop which results in p53 activation after DNA damage. The first model (ARF model) looks at the mechanism of p14ARF which sequesters Mdm2 and leads to stabilisation of p53. The second model (ATM model) examines the mechanism of ATM activation which leads to phosphorylation of both p53 and Mdm2 and increased degradation of Mdm2, which again results in p53 stabilisation. The models can readily be modified as further information becomes available, and linked to other models of cellular ageing. RESULTS: The ARF model is robust to changes in its parameters and predicts undamped oscillations after DNA damage so long as the signal persists. It also predicts that if there is a gradual accumulation of DNA damage, such as may occur in ageing, oscillations break out once a threshold level of damage is acquired. The ATM model requires an additional step for p53 synthesis for sustained oscillations to develop. The ATM model shows much more variability in the oscillatory behaviour and this variability is observed over a wide range of parameter values. This may account for the large variability seen in the experimental data which so far has examined ARF negative cells. CONCLUSION: The models predict more regular oscillations if ARF is present and suggest the need for further experiments in ARF positive cells to test these predictions. Our work illustrates the importance of systems biology approaches to understanding the complex role of p53 in both ageing and cancer.

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Format
SBML (L2V4)
Related Publication
  • Explaining oscillations and variability in the p53-Mdm2 system.
  • Proctor CJ, Gray DA
  • BMC systems biology , 8/ 2008 , Volume 2 , pages: 75 , PubMed ID: 18706112
  • Centre for Integrated Systems Biology of Ageing and Nutrition, Institute for Ageing and Health, Newcastle University, Newcastle upon Tyne, UK. c.j.proctor@ncl.ac.uk
  • In individual living cells p53 has been found to be expressed in a series of discrete pulses after DNA damage. Its negative regulator Mdm2 also demonstrates oscillatory behaviour. Attempts have been made recently to explain this behaviour by mathematical models but these have not addressed explicit molecular mechanisms. We describe two stochastic mechanistic models of the p53/Mdm2 circuit and show that sustained oscillations result directly from the key biological features, without assuming complicated mathematical functions or requiring more than one feedback loop. Each model examines a different mechanism for providing a negative feedback loop which results in p53 activation after DNA damage. The first model (ARF model) looks at the mechanism of p14ARF which sequesters Mdm2 and leads to stabilisation of p53. The second model (ATM model) examines the mechanism of ATM activation which leads to phosphorylation of both p53 and Mdm2 and increased degradation of Mdm2, which again results in p53 stabilisation. The models can readily be modified as further information becomes available, and linked to other models of cellular ageing.The ARF model is robust to changes in its parameters and predicts undamped oscillations after DNA damage so long as the signal persists. It also predicts that if there is a gradual accumulation of DNA damage, such as may occur in ageing, oscillations break out once a threshold level of damage is acquired. The ATM model requires an additional step for p53 synthesis for sustained oscillations to develop. The ATM model shows much more variability in the oscillatory behaviour and this variability is observed over a wide range of parameter values. This may account for the large variability seen in the experimental data which so far has examined ARF negative cells.The models predict more regular oscillations if ARF is present and suggest the need for further experiments in ARF positive cells to test these predictions. Our work illustrates the importance of systems biology approaches to understanding the complex role of p53 in both ageing and cancer.
Contributors
Carole Proctor

Metadata information

is
BioModels Database MODEL5836973167
BioModels Database BIOMD0000000188
isDescribedBy
PubMed 18706112
hasTaxon
Taxonomy Homo sapiens

Curation status
Curated

Tags
Name Description Size Actions

Model files

BIOMD0000000188_url.xml SBML L2V4 representation of Proctor2008 - p53/Mdm2 circuit - p53 stabilisation by ATM 43.83 KB Preview | Download

Additional files

BIOMD0000000188-biopax2.owl Auto-generated BioPAX (Level 2) 39.82 KB Preview | Download
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BIOMD0000000188_urn.xml Auto-generated SBML file with URNs 42.77 KB Preview | Download
BIOMD0000000188.svg Auto-generated Reaction graph (SVG) 50.89 KB Preview | Download
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BIOMD0000000188.m Auto-generated Octave file 9.48 KB Preview | Download
BIOMD0000000188.png Auto-generated Reaction graph (PNG) 181.07 KB Preview | Download
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  • Model originally submitted by : Carole Proctor
  • Submitted: 05-Sep-2008 15:13:40
  • Last Modified: 08-Apr-2016 16:43:18
Revisions
  • Version: 2 public model Download this version
    • Submitted on: 08-Apr-2016 16:43:18
    • Submitted by: Carole Proctor
    • With comment: Current version of Proctor2008 - p53/Mdm2 circuit - p53 stabilisation by ATM
  • Version: 1 public model Download this version
    • Submitted on: 05-Sep-2008 15:13:40
    • Submitted by: Carole Proctor
    • With comment: Original import of BIOMD0000000188.xml.origin

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Legends
: Variable used inside SBML models


Species
Reactions
Reactions Rate Parameters
p53 + ATMA => p53_P + ATMA kphosp53*p53*ATMA kphosp53 = 5.0E-4 pmolpsec
ATMA => ATMI kinactATM*ATMA kinactATM = 5.0E-4 psec
Mdm2 + ATMA => Mdm2_P + ATMA kphosMdm2*Mdm2*ATMA kphosMdm2 = 2.0 pmolpsec
=> damDNA kdam*IR IR = 0.0 dGy; kdam = 0.08 molepsecpdGy
damDNA => Sink krepair*damDNA krepair = 2.0E-5 psec
Mdm2_p53 => Mdm2 + p53deg kdegp53*Mdm2_p53*kproteff kproteff = 1.0 dimensionless; kdegp53 = 8.25E-4 psec
Mdm2 => Sink + mdm2deg kdegMdm2*Mdm2*kproteff kproteff = 1.0 dimensionless; kdegMdm2 = 4.33E-4 psec
Mdm2_mRNA => Mdm2_mRNA + Mdm2 + mdm2syn ksynMdm2*Mdm2_mRNA ksynMdm2 = 4.95E-4 psec
p53 => p53 + Mdm2_mRNA + Mdm2mRNAsyn ksynMdm2mRNA*p53 ksynMdm2mRNA = 1.0E-4 psec
p53_P => p53_P + Mdm2_mRNA + Mdm2mRNAsyn ksynMdm2mRNA*p53_P ksynMdm2mRNA = 1.0E-4 psec
p53 + Mdm2 => Mdm2_p53 kbinMdm2p53*p53*Mdm2 kbinMdm2p53 = 0.001155 pmolpsec
Mdm2_p53 => p53 + Mdm2 krelMdm2p53*Mdm2_p53 krelMdm2p53 = 1.155E-5 psec
Curator's comment:
(added: 05 Sep 2008, 15:08:16, updated: 05 Sep 2008, 15:08:16)
Comment: The model is simulated and integrated using SBML OdeSolver with options (-n --printstep 1e4 --error 1e-14 -z). Figure 13 (for ATM model) of the original paper (Procter CJ, 2008) is reproduced in here.