From structure to dynamics: frequency tuning in the p53-Mdm2 network. II Differential and stochastic approaches.

J Theor Biol

Université Libre de Bruxelles (U.L.B.), Faculté des Sciences, Unit of Theoretical and Computational Biology, Campus Plaine C.P. 231, B-1050 Brussels, Belgium.

Published: June 2010

In Part I of this work, we carried out a logical analysis of a simple model describing the interplay between protein p53, its main negative regulator Mdm2 and DNA damage, and briefly discussed the corresponding differential model (Abou-Jaoudé et al., 2009). This analysis allowed us to reproduce several qualitative features of the kinetics of the p53 response to damage and provided an interpretation of the short and long characteristic periods of oscillation reported by Geva-Zatorsky et al. (2006) depending on the irradiation dose. Starting from this analysis, we focus here on more quantitative aspects of the dynamics of our network and combine the differential description of our system with stochastic simulations which take molecular fluctuations into account. We find that the amplitude of the p53 and Mdm2 oscillations is highly variable (to a degree that depends, however, on the bifurcation properties of the system). In contrast, peak width and timing remain more regular, consistent with the experimental data. Our simulations also show that noise can induce repeated pulses of p53 and Mdm2 that, at low damage, resemble the slow irregular fluctuations observed experimentally. Adding the stochastic dimension in our modeling further allowed us to account for an increase of the fraction of cells oscillating with a high frequency when the irradiation dose increases, as observed by Geva-Zatorsky et al. (2006).

Download full-text PDF

Source
http://dx.doi.org/10.1016/j.jtbi.2010.03.031DOI Listing

Publication Analysis

Top Keywords

geva-zatorsky 2006
8
irradiation dose
8
p53 mdm2
8
structure dynamics
4
dynamics frequency
4
frequency tuning
4
tuning p53-mdm2
4
p53-mdm2 network
4
network differential
4
differential stochastic
4

Similar Publications

Dynamics of posttranslational modifications of p53.

Comput Math Methods Med

January 2015

Institute of Systems Biology, Shanghai University, 99 Shangda Road, Shanghai 200444, China.

The latest experimental evidence indicates that acetylation of p53 at K164 (lysine 164) and K120 may induce directly cell apoptosis under severe DNA damage. However, previous cell apoptosis models only studied the effects of active and/or inactive p53, that is, phosphorylation/dephosphorylation of p53. In the present paper, based partly on Geva-Zatorsky et al.

View Article and Find Full Text PDF

From structure to dynamics: frequency tuning in the p53-Mdm2 network. II Differential and stochastic approaches.

J Theor Biol

June 2010

Université Libre de Bruxelles (U.L.B.), Faculté des Sciences, Unit of Theoretical and Computational Biology, Campus Plaine C.P. 231, B-1050 Brussels, Belgium.

In Part I of this work, we carried out a logical analysis of a simple model describing the interplay between protein p53, its main negative regulator Mdm2 and DNA damage, and briefly discussed the corresponding differential model (Abou-Jaoudé et al., 2009). This analysis allowed us to reproduce several qualitative features of the kinetics of the p53 response to damage and provided an interpretation of the short and long characteristic periods of oscillation reported by Geva-Zatorsky et al.

View Article and Find Full Text PDF

From structure to dynamics: frequency tuning in the p53-Mdm2 network I. Logical approach.

J Theor Biol

June 2009

Université Libre de Bruxelles (U.L.B.), Faculté des Sciences, Unit of Theoretical and Computational Biology, Campus Plaine C.P. 231, B-1050 Brussels, Belgium.

We investigate the dynamical properties of a simple four-variable model describing the interactions between the tumour suppressor protein p53, its main negative regulator Mdm2 and DNA damage, a model inspired by the work of Ciliberto et al. [2005. Steady states and oscillations in the p53/Mdm2 network.

View Article and Find Full Text PDF

Analysis of a minimal model for p53 oscillations.

J Theor Biol

November 2007

Laboratoire Matières et Systèmes Complexes, Université Paris 7, CNRS UMR 7057, c.c. 7056, 75205 Paris Cedex 13, France.

Oscillatory behaviours in genetic networks are important examples for studying the principles underlying the dynamics of cellular regulation. Recently the team of Alon has reported a surprisingly rich oscillatory response of the p53 tumor suppressor to irradiation stress et al. [Lahav, G.

View Article and Find Full Text PDF

Protein expression is a stochastic process that leads to phenotypic variation among cells. The cell-cell distribution of protein levels in microorganisms has been well characterized but little is known about such variability in human cells. Here, we studied the variability of protein levels in human cells, as well as the temporal dynamics of this variability, and addressed whether cells with higher than average protein levels eventually have lower than average levels, and if so, over what timescale does this mixing occur.

View Article and Find Full Text PDF

Want AI Summaries of new PubMed Abstracts delivered to your In-box?

Enter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!