Cell cycle dynamics in a response/signalling feedback system with a gap

Xue Gong, Richard Buckalew, Todd Young, Erik Boczko

Research output: Contribution to journalArticlepeer-review

7 Scopus citations


We consider a dynamical model of cell cycles of n cells in a culture in which cells in one specific phase (S for signalling) of the cell cycle produce chemical agents that influence the growth/cell cycle progression of cells in another phase (R for responsive). In the case that the feedback is negative, it is known that subpopulations of cells tend to become clustered in the cell cycle; while for a positive feedback, all the cells tend to become synchronized. In this paper, we suppose that there is a gap between the two phases. The gap can be thought of as modelling the physical reality of a time delay in the production and action of the signalling agents. We completely analyse the dynamics of this system when the cells are arranged into two cell cycle clusters. We also consider the stability of certain important periodic solutions in which clusters of cells have a cyclic arrangement and there are just enough clusters to allow interactions between them. We find that the inclusion of a small gap does not greatly alter the global dynamics of the system; there are still large open sets of parameters for which clustered solutions are stable. Thus, we add to the evidence that clustering can be a robust phenomenon in biological systems. However, the gap does effect the system by enhancing the stability of the stable clustered solutions. We explain this phenomenon in terms of contraction rates (Floquet exponents) in various invariant subspaces of the system. We conclude that in systems for which these models are reasonable, a delay in signalling is advantageous to the emergence of clustering.

Original languageEnglish (US)
Pages (from-to)79-98
Number of pages20
JournalJournal of Biological Dynamics
Issue number1
StatePublished - Jan 25 2014

Bibliographical note

Publisher Copyright:
© 2014 The Author(s). Published by Taylor & Francis.


  • nonlinear feedback
  • yeast metabolic oscillations


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