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From structure to dynamics: frequency tuning in the p53-Mdm2 network I. Logical approach
Wassim Abou-Jaoudé1, Djomangan A Ouattara, Marcelle Kaufman
1Université Libre de Bruxelles (U.L.B.), Faculté des Sciences, Unit of Theoretical and Computational Biology, Campus Plaine C.P. 231, B-1050 Brussels, Belgium.
Journal of Theoretical Biology
|February 24, 2009
Summary
This study models the p53-Mdm2 network dynamics, revealing how DNA damage, repair, and p53 activity influence tumor suppressor protein p53 (p53) responses and oscillations.
Area of Science:
- Systems Biology
- Molecular Biology
- Biophysics
Background:
- The p53-Mdm2 network is crucial for cellular responses to DNA damage.
- Understanding the dynamical properties of this network is key to comprehending cell fate decisions.
- Previous models have explored steady states and oscillations, but integrated approaches are needed.
Purpose of the Study:
- To investigate the dynamical properties of a four-variable model of the p53-Mdm2 network.
- To analyze the network's behavior using logical analysis and differential equations.
- To introduce and utilize "logical bifurcation diagrams" to summarize complex dynamics.
Main Methods:
- Developed a four-variable mathematical model of the p53-Mdm2 network.
- Employed logical analysis to understand network structure and dynamics.
- Utilized differential equations to model continuous system behavior.
- Introduced and applied "logical bifurcation diagrams" to identify key dynamical scenarios.
Main Results:
- The model exhibits diverse behaviors influenced by DNA damage levels, repair efficiency, and p53's DNA-binding and transcriptional activity.
- Logical bifurcation diagrams effectively summarize the network's qualitative dynamics.
- Results qualitatively explain experimental observations like p53 pulsing, oscillation frequency shifts, and population-level dampening.
- Differential analysis explains observed high and low-frequency oscillations based on irradiation dose.
Conclusions:
- The p53-Mdm2 network's dynamics are highly sensitive to parameters reflecting cellular stress and p53 properties.
- Variability in p53 post-translational modifications and transactivation can lead to cell-to-cell differences in response.
- The model provides a framework for understanding oscillations and variability in the p53 system.
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