Quantitative analysis of phase wave of gene expression in the mammalian central circadian clock network

Abstract

Background: 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. Methodology/Principal Findings: 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. Conclusions/Significance: 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. © 2011 Fukuda et al.