Modeling the seasonal adaptation of circadian clocks by changes in the network structure of the suprachiasmatic nucleus.
Modeling the seasonal adaptation of circadian clocks by changes in the network structure of the suprachiasmatic nucleus.
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DOI：
10.1371/journal.pcbi.1002697
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发表时间：
2012
影响因子：
4.3
通讯作者：
Perc M
中科院分区：
文献类型：
--
作者：
Bodenstein C;Gosak M;Schuster S;Marhl M;Perc M
昼夜节律的动态需要适应夏季和冬季之间的日长变化。然而，实验已经观察到，视交叉上核（SCN）的单个神经元的动力学不随季节的变化而变化。相反，昼夜节律钟的季节性适应被假设为细胞间动力学变化的结果，这导致SCN神经元的电活动的相位分布在冬季较窄，在夏季较宽。然而，为了理解这种复杂的细胞间动力学，需要更深入地了解SCN神经元形成的网络结构的影响。为此，我们提出了一个数学模型的SCN神经元结构的动态网络的结构中起着举足轻重的作用。使用我们的模型，我们表明，在日常节奏的长距离细胞到细胞的连接和季节性变化的分数可能是密切相关的。特别是，所提出的数学模型的模拟表明，细胞之间的长距离连接的分数调整的相位分布，因此行为活动的长度如下：密集的长距离连接在冬季导致一个狭窄的活动阶段，而罕见的长距离连接在夏季导致一个广泛的活动阶段。我们的模型也能够解释实验观察结果，表明在冬季光诱导的生物钟相移较大，我们表明这是神经元之间更高同步的结果。因此，我们的模型提供的证据表明，昼夜节律钟的季节性动态变化也可以部分地被理解和调节的SCN网络结构的可塑性。生物钟驱动内部生物过程的时间协调，这反过来又决定了最多样化生物体的生理和行为的每日节律。在哺乳动物中，24小时计时时钟位于下丘脑的视交叉上核（SCN）。SCN是一个相互连接的神经元网络，作为一个强大的自我维持的昼夜节律起搏器。这些神经元的电活动及其与24小时周期的同步是通过环境昼夜周期建立的。除了每天的亮度变化外，哺乳动物也会受到季节性日长变化的影响。值得注意的是，它已被实验表明，不同的光周期的季节性适应相关的SCN的神经元活动的修改，由于网络的可塑性。在我们的论文中，通过建立SCN结构的数学模型，我们深入探讨了这个重要的神经元网络结构的作用。我们发现，在冬季和夏季的神经元活动的重新分配可以部分地解释网络的结构变化。有趣的是，电活动模式的改变可以与我们提出的SCN网络的小世界特性有关。
The dynamics of circadian rhythms needs to be adapted to day length changes between summer and winter. It has been observed experimentally, however, that the dynamics of individual neurons of the suprachiasmatic nucleus (SCN) does not change as the seasons change. Rather, the seasonal adaptation of the circadian clock is hypothesized to be a consequence of changes in the intercellular dynamics, which leads to a phase distribution of electrical activity of SCN neurons that is narrower in winter and broader during summer. Yet to understand this complex intercellular dynamics, a more thorough understanding of the impact of the network structure formed by the SCN neurons is needed. To that effect, we propose a mathematical model for the dynamics of the SCN neuronal architecture in which the structure of the network plays a pivotal role. Using our model we show that the fraction of long-range cell-to-cell connections and the seasonal changes in the daily rhythms may be tightly related. In particular, simulations of the proposed mathematical model indicate that the fraction of long-range connections between the cells adjusts the phase distribution and consequently the length of the behavioral activity as follows: dense long-range connections during winter lead to a narrow activity phase, while rare long-range connections during summer lead to a broad activity phase. Our model is also able to account for the experimental observations indicating a larger light-induced phase-shift of the circadian clock during winter, which we show to be a consequence of higher synchronization between neurons. Our model thus provides evidence that the variations in the seasonal dynamics of circadian clocks can in part also be understood and regulated by the plasticity of the SCN network structure. Circadian clocks drive the temporal coordination of internal biological processes, which in turn determine daily rhythms in physiology and behavior in the most diverse organisms. In mammals, the 24-hour timing clock resides in the suprachiasmatic nucleus (SCN) of the hypothalamus. The SCN is a network of interconnected neurons that serves as a robust self-sustained circadian pacemaker. The electrical activity of these neurons and their synchronization with the 24-hour cycle is established via the environmental day and night cycles. Apart from daily luminance changes, mammals are exposed to seasonal day length changes as well. Remarkably, it has been shown experimentally that the seasonal adaptations to different photoperiods are related to the modifications of the neuronal activity of the SCN due to the plasticity of the network. In our paper, by developing a mathematical model of the SCN architecture, we explore in depth the role of the structure of this important neuronal network. We show that the redistribution of the neuronal activity during winter and summer can in part be explained by structural changes of the network. Interestingly, the alterations of the electrical activity patterns can be related with small-world properties of our proposed SCN network.
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