Restriction point control of the mammalian cell cycle

Taxon: Mammal
Process: Cell cycle
Submitter: Adrien Fauré

Supporting paper: Fauré, Adrien and Naldi, Aurélien and Chaouiya, Claudine and Thieffry, Denis (2006). Dynamical analysis of a generic Boolean model for the control of the mammalian cell cycle. Bioinformatics. 10.1093/bioinformatics/btl210

Model file(s) Description(s)
boolean_cell_cycle.zginml description of model file

Summary:
On the basis of a previous modelling study by Novak and Tyson 1, we have recently proposed a generic Boolean model of the core network controlling the restriction point of the mammalian cell cycle 2.

For proper logical parameter values, the simulation of this Boolean model leads to dynamical behaviours (sequences of activations and inactivations of key regulatory products) in qualitative agreement with current experimental data.

However, as kinetic details are still lacking, many different (in)activation pathways are compatible with existing data, including fully synchronous transition pathways. To further evaluate these different possibilities, we have analysed the asymptotical behaviour of this network under synchronous versus asynchronous updating assumptions. Furthermore, we consider intermediate updating strategies to improve the computation of asymptotical properties depending on available kinetic data. This approach has been implemented through user-defined priority classes in the logical modelling and simulation software GINsim.

The Figure 1 presents the regulatory graph corresponding to our Boolean model of the restriction point control for the mammalian cell cycle. In this graph, each node represents the activity of a key regulatory element, whereas the edges represent functional interactions between these elements. Blunt arrows stand for inhibitory effects, whereas normal arrows stand for activations.

TODO


Figure 1: Regulatory graph

Depending on CycD activity at the initial state, our model can lead to two different asymptotical behaviour:

To illustrate the impact of the updating assumption, we present here the cyclic attractors (terminal, maximal, strongly connected components) corresponding to three different updating assumptions:

Figure 2: attractors, depending on the updating policy (Node order in the state labelling: CycD Rb E2F CycE CycA p27Kip1 Cdc20 Cdh1 UbcH10 CycB)

  1. Béla Novák and John J. Tyson. A model for restriction point control of the mammalian cell cycle. Journal of Theoretical Biology, 230(4):563–579, October 2004. doi:10.1016/j.jtbi.2004.04.039. ↩

  2. Adrien Fauré, Aurélien Naldi, Claudine Chaouiya, and Denis Thieffry. Dynamical analysis of a generic boolean model for the control of the mammalian cell cycle. Bioinformatics, 22(14):e124–e131, July 2006. doi:10.1093/bioinformatics/btl210. ↩