| 研究実績の概要 |
We investigate how extra-terrestrial solar days (non-24-h days) reorganize component circadian clocks in the suprachiasmatic nucleus (SCN), the master circadian clock of the brain (Azzi et al, Neuron, 2017). The solar day reorganization is mediated by the neural network connection in the SCN, as blockade of GABA signaling abolishes the phenotypes. We apply the asymmetric coupling model for the photoperiodic encoding (Myung et al, PNAS, 2015) and find it equally applicable to solar day adaptation. While the dynamical properties in the SCN culture can be described by temporal phase relations, the system as a whole can be seen as a generator of spatial patterns. Therefore, we introduce a new quantitative measure for spatiotemporal patterns, called Moran’s I (Schmal et al, Bioinformatics, accepted).
The intra-SCN dynamics is a bridge to understand the brain-wide dynamics. The circadian oscillators in the brain similarly reorganize their relative phases under summer days, which we have found to be equivalent to the long solar days. To understand how this reorganization influences the overall in vivo dynamics, we generated CP-specific Bmal1 KO mice (FOXJ1-Cre;Bmal1flx/flx). These mice lack circadian clocks in their CPs and show lengthened circadian period under constant darkness. This in vivo phenotype can be reproduced in vitro, through co-culture of the SCN and the CP. This is compelling evidence that internal disorganization of circadian clocks has direct consequences in vivo and provides a first clue to understand the brain endophenotype under chronic non-24-h solar days.
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| 現在までの達成度 (区分) |
現在までの達成度 (区分)
2: おおむね順調に進展している
理由
One paper on solar day entrainment of the SCN has been successfully published in Neuron as a collaboration project [1]. And a second paper focusing on methods is accepted in May 2017 [2].
[1] Azzi A, Evans JA, Leise T, Myung J, Takumi T, Davidson AJ, Brown SA (2017). Network dynamics mediate circadian clock plasticity. Neuron. 93:441-450.
[2] Schmal C, Myung J, Herzel H, Bordyugov G (2017). Moran’s I quantifies spatio-temporal pattern formation in neural imaging data. Bioinformatics. (accepted)
In addition, two more papers are close to submission.
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