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Quantitative measures of clock protein dynamics in the mouse suprachiasmatic nucleus extends the circadian time-keeping model

ABSTRACT: The suprachiasmatic nucleus (SCN) synchronises circadian rhythmicity (approximately 24 hours) across the body. The SCN cell-autonomous clock is modelled qualitatively as a transcriptional-translational feedback loop (TTFL), with heteromeric complexes of transcriptional activator and repressor proteins driving cyclical gene expression. How these proteins really behave within the SCN, individually and in relation to each other, is poorly understood. Imaging SCN slices from a novel array of knock-in reporter mice, we quantify the dynamic behaviours of combined repressors PERIOD2 (PER2) and CRYPTOCHROME1 (CRY1), and activator BMAL1. We reveal a spectrum of protein-specific intracellular and spatiotemporal behaviours that run counter to the qualitative TTFL model. We also show that PER and CRY1 exert independent actions on TTFL oscillations, and that their individual stabilities play a critical role in SCN circadian dynamics. These results reveal a rich and unanticipated complexity in the dynamic behaviours and functions of endogenous circadian proteins, prompting re-appraisal of current transcriptional-translational feedback loop models of the suprachiasmatic nucleus.

SUBMITTER: Nicola Smyllie

PROVIDER: S-SCDT-10_1038-S44318-025-00426-Z | biostudies-other |

REPOSITORIES: biostudies-other

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Project description:The biological master clock, suprachiasmatic nucleus (of rat and mouse), is composed of ~10,000 clock cells which are heterogeneous with respect to their circadian periods. Despite this inhomogeneity, an intact SCN maintains a very good degree of circadian phase (time) coherence which is vital for sustaining various circadian rhythmic activities, and it is supposedly achieved by not just one but a few different cell-to-cell coupling mechanisms, among which action potential (AP)-mediated connectivity is known to be essential. But, due to technical difficulties and limitations in experiments, so far very little information is available about the morphology of the connectivity at a cellular scale. Building upon this limited amount of information, here we exhaustively and systematically explore a large pool (~25,000) of various network morphologies to come up with some plausible network features of SCN networks. All candidates under consideration reflect an experimentally obtained 'indegree distribution' as well as a 'physical range distribution of afferent clock cells.' Then, importantly, with a set of multitude criteria based on the properties of SCN circadian phase waves in extrinsically perturbed as well as in their natural states, we select out appropriate model networks: Some important measures are, 1) level of phase dispersal and direction of wave propagation, 2) phase-resetting ability of the model networks subject to external circadian forcing, and 3) decay rate of perturbation induced "phase-singularities." The successful, realistic networks have several common features: 1) "indegree" and "outdegree" should have a positive correlation; 2) the cells in the SCN ventrolateral region (core) have a much larger total degree than that of the dorsal medial region (shell); 3) The number of intra-core edges is about 7.5 times that of intra-shell edges; and 4) the distance probability density function for the afferent connections fits well to a beta function. We believe that these newly identified network features would be a useful guide for future explorations on the very much unknown AP-mediated clock cell connectome within the SCN.

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Quantitative measures of clock protein dynamics in the mouse suprachiasmatic nucleus extends the circadian time-keeping model

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