Abel John H, Meeker Kirsten, Granados-Fuentes Daniel, St John Peter C, Wang Thomas J, Bales Benjamin B, Doyle Francis J, Herzog Erik D, Petzold Linda R
Department of Chemical Engineering, University of California, Santa Barbara, CA 93106; Systems Biology Program, Harvard University, Cambridge, MA 02138;
Department of Computer Science, University of California, Santa Barbara, CA 93106;
Proc Natl Acad Sci U S A. 2016 Apr 19;113(16):4512-7. doi: 10.1073/pnas.1521178113. Epub 2016 Apr 4.
In the mammalian suprachiasmatic nucleus (SCN), noisy cellular oscillators communicate within a neuronal network to generate precise system-wide circadian rhythms. Although the intracellular genetic oscillator and intercellular biochemical coupling mechanisms have been examined previously, the network topology driving synchronization of the SCN has not been elucidated. This network has been particularly challenging to probe, due to its oscillatory components and slow coupling timescale. In this work, we investigated the SCN network at a single-cell resolution through a chemically induced desynchronization. We then inferred functional connections in the SCN by applying the maximal information coefficient statistic to bioluminescence reporter data from individual neurons while they resynchronized their circadian cycling. Our results demonstrate that the functional network of circadian cells associated with resynchronization has small-world characteristics, with a node degree distribution that is exponential. We show that hubs of this small-world network are preferentially located in the central SCN, with sparsely connected shells surrounding these cores. Finally, we used two computational models of circadian neurons to validate our predictions of network structure.
在哺乳动物的视交叉上核(SCN)中,有噪声的细胞振荡器在神经网络内进行通信,以产生精确的全系统昼夜节律。尽管先前已经研究了细胞内遗传振荡器和细胞间生化耦合机制,但驱动SCN同步的网络拓扑结构尚未阐明。由于其振荡成分和缓慢的耦合时间尺度,这个网络特别难以探测。在这项工作中,我们通过化学诱导的去同步化,以单细胞分辨率研究了SCN网络。然后,我们将最大信息系数统计应用于单个神经元重新同步其昼夜节律循环时的生物发光报告数据,从而推断出SCN中的功能连接。我们的结果表明,与重新同步相关的昼夜节律细胞功能网络具有小世界特征,节点度分布呈指数分布。我们表明,这个小世界网络的枢纽优先位于SCN的中央,周围有稀疏连接的壳层围绕着这些核心。最后,我们使用了两个昼夜节律神经元的计算模型来验证我们对网络结构的预测。