Quantitative analysis of phase wave of gene expression in the mammalian central circadian clock network.
Quantitative analysis of phase wave of gene expression in the mammalian central circadian clock network.
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DOI：
10.1371/journal.pone.0023568
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发表时间：
2011
期刊：
影响因子：
3.7
通讯作者：
Hayasaka N
中科院分区：
文献类型：
--
作者：
Fukuda H;Tokuda I;Hashimoto S;Hayasaka N
视交叉上核（SCN），主生物钟，是一个异构的振荡器网络，但显示出强大的同步动力学。最近的单细胞生物发光成像揭示了SCN离体生物钟基因表达的时间梯度。然而，由于技术上的困难，在生物学方法来阐明整个网络结构的SCN，梯度的特点，我们称之为相位波，仍然是未知的。我们采用了新的方法，即，定量分析和模型模拟来表征大鼠SCN切片的Per 2：：荧光素酶时钟报告基因表达中的相位波。我们的定量研究不仅证明了神经元之间的高度同步和相位波传播的定期发生，而且还包含在波中的相位波动的显着量。此外，我们基于局部耦合模型的模拟表明，由模型模拟估计的细胞间耦合强度显着高于产生相波的临界值。模型模拟还表明，SCN神经元的异质性是造成相位波波动的主要因素之一。此外，SCN网络对动态噪声和这些神经元固有的自然频率的变化的鲁棒性进行了定量评估。据我们所知，这是相位波的第一次定量评估和生成波的SCN神经元网络特征的进一步表征，即，细胞间同步性、相位波动性、强局部耦合性、异质周期性和鲁棒性。我们目前的研究提供了一种方法，这将导致一个全面的了解机制和/或生物学意义的相位波在中央昼夜振荡系统。
The suprachiasmatic nucleus (SCN), the master circadian clock, is a heterogeneous oscillator network, yet displays a robust synchronization dynamics. Recent single-cell bioluminescent imaging revealed temporal gradients in circadian clock gene expression in the SCN ex vivo. However, due to technical difficulty in biological approaches to elucidate the entire network structure of the SCN, characteristics of the gradient, which we refer to as phase wave, remain unknown. We implemented new approaches, i.e., quantitative analysis and model simulation to characterize the phase waves in Per2::Luciferase clock reporter gene expression of the rat SCN slice. Our quantitative study demonstrated not only a high degree of synchronization between the neurons and regular occurrence of the phase wave propagation, but also a significant amount of phase fluctuations contained in the wave. In addition, our simulations based on local coupling model suggest that the intercellular coupling strength estimated by the model simulations is significantly higher than the critical value for generating the phase waves. Model simulations also suggest that heterogeneity of the SCN neurons is one of the main factors causing the phase wave fluctuations. Furthermore, robustness of the SCN network against dynamical noise and variation of the natural frequencies inherent in these neurons was quantitatively assessed. To our knowledge, this is the first quantitative evaluation of the phase wave and further characterization of the SCN neuronal network features generating the wave i.e., intercellular synchrony, phase fluctuation, strong local coupling, heterogeneous periodicity and robustness. Our present study provides an approach, which will lead to a comprehensive understanding of mechanistic and/or biological significance of the phase wave in the central circadian oscillatory system.
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