Gonze Didier, Halloy José, Leloup Jean-Christophe, Goldbeter Albert
Unité de chronobiologie théorique, faculté des sciences, université libre de Bruxelles, Campus Plaine, CP 231, B1050 Brussels, Belgium.
C R Biol. 2003 Feb;326(2):189-203. doi: 10.1016/s1631-0691(03)00016-7.
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.
昼夜节律是几乎所有生物体中以接近24小时的周期发生的内源性振荡。这些节律源于基因表达的负自调节。基于这种基因调控过程的确定性模型解释了在恒定环境条件下(如持续黑暗)昼夜节律的出现、这些节律被明暗周期所调节以及被光脉冲所引起的相移。当参与振荡的蛋白质和mRNA分子数量较少时,这种情况可能发生在细胞环境中,就有必要采用随机模拟来评估分子噪声对昼夜振荡的影响。我们通过考虑先前提出的用于果蝇中PER和TIM蛋白及其mRNA昼夜振荡的确定性模型的随机版本,来探讨分子噪声的影响。该模型基于PER和TIM蛋白之间的复合物对per和tim基因的抑制作用。通过 Gillespie 方法对该模型的随机版本进行数值模拟。随机方法的预测结果与确定性模型的预测结果在极限环型持续振荡以及接近分岔点(超过该点系统演变为稳定稳态)的影响方面都比较吻合。随机模拟表明,即使参与振荡的mRNA和蛋白质分子的最大数量仅为几十或几百个左右,强大的昼夜振荡也能在细胞水平上出现。随机模型还再现了在确定性PER-TIM模型呈现混沌行为的条件下向奇怪吸引子的演化。如通过庞加莱截面所示,在存在分子噪声的情况下,极限环型的周期性振荡与非周期性振荡(即混沌)之间的差异依然存在。因此,随着分子数量减少而观察到的周期性逐渐消失可以与源于混沌动力学的非周期性区分开来。只要参与振荡的分子数量保持足够大(几十或几百个左右,或更多),随机模型就因此与昼夜节律的确定性模型的预测结果具有良好的一致性。