Stochastic models for circadian rhythms: effect of molecular noise on periodic and chaotic behaviour.
Circadian rhythms are endogenous oscillations that occur with a period close to 24 h in nearly all living organisms. These rhythms originate from the negative autoregulation of gene expression. Deterministic models based on such genetic regulatory processes account for the occurrence of circadian rhythms in constant environmental conditions (e.g., constant darkness), for entrainment of these rhythms by light-dark cycles, and for their phase-shifting by light pulses. When the numbers of protein and mRNA molecules involved in the oscillations are small, as may occur in cellular conditions, it becomes necessary to resort to stochastic simulations to assess the influence of molecular noise on circadian oscillations. We address the effect of molecular noise by considering the stochastic version of a deterministic model previously proposed for circadian oscillations of the PER and TIM proteins and their mRNAs in Drosophila. The model is based on repression of the per and tim genes by a complex between the PER and TIM proteins. Numerical simulations of the stochastic version of the model are performed by means of the Gillespie method. The predictions of the stochastic approach compare well with those of the deterministic model with respect both to sustained oscillations of the limit cycle type and to the influence of the proximity from a bifurcation point beyond which the system evolves to stable steady state. Stochastic simulations indicate that robust circadian oscillations can emerge at the cellular level even when the maximum numbers of mRNA and protein molecules involved in the oscillations are of the order of only a few tens or hundreds. The stochastic model also reproduces the evolution to a strange attractor in conditions where the deterministic PER-TIM model admits chaotic behaviour. The difference between periodic oscillations of the limit cycle type and aperiodic oscillations (i.e. chaos) persists in the presence of molecular noise, as shown by means of Poincaré sections. The progressive obliteration of periodicity observed as the number of molecules decreases can thus be distinguished from the aperiodicity originating from chaotic dynamics. As long as the numbers of molecules involved in the oscillations remain sufficiently large (of the order of a few tens or hundreds, or more), stochastic models therefore provide good agreement with the predictions of the deterministic model for circadian rhythms.
Gonze
Didier
D
Unité de chronobiologie théorique, faculté des sciences, université libre de Bruxelles, Campus Plaine, CP 231, B1050 Brussels, Belgium.
Halloy
José
J
Leloup
Jean-Christophe
JC
Goldbeter
Albert
A
D000818:Animals; D001683:Biological Clocks / Q000502:physiology*; D056926:CLOCK Proteins; D002940:Circadian Rhythm / Q000502:physiology* / Q000528:radiation effects; D003624:Darkness; D029721:Drosophila Proteins / Q000096:biosynthesis / Q000235:genetics / Q000502:physiology; D004331:Drosophila melanogaster / Q000235:genetics / Q000502:physiology; D008027:Light; D008954:Models, Biological; D017711:Nonlinear Dynamics; D009687:Nuclear Proteins / Q000096:biosynthesis / Q000235:genetics / Q000502:physiology; D056950:Period Circadian Proteins; D012333:RNA, Messenger / Q000096:biosynthesis; D013269:Stochastic Processes; D014157:Transcription Factors / Q000502:physiology
C120526:Clk protein, Drosophila; D029721:Drosophila Proteins; D009687:Nuclear Proteins; C539040:PER protein, Drosophila; D056950:Period Circadian Proteins; D012333:RNA, Messenger; D014157:Transcription Factors; D056926:CLOCK Proteins