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Abstract Most organisms possess three biological oscillators, circadian clock, cell cycle, and redox rhythm, which are autonomous but interact each other. However, whether their interactions and autonomy are beneficial for organisms remains unclear. Here, we modeled a coupled oscillator system where each oscillator affected the phase of the other oscillators. We found that multiple types of coupling prevent a high H2O2 level in cells at M phase. Consequently, we hypothesized a high H2O2 sensitivity at the M phase and found that moderate coupling reduced cell damage due to oxidative stress by generating appropriate phase relationships between three rhythms, whereas strong coupling resulted in an elevated cell damage by increasing the average H2O2 level and disrupted the cell cycle. Furthermore, the multicellularity model revealed that phase variations among cells confer flexibility in synchronization with environments at the expense of adaptability to the optimal environment. Thus, both autonomy and synchrony among the oscillators are important for coordinating their phase relationships to minimize oxidative stress, and couplings balance them depending on environments.

The phase response curve (PRC) is crucial in elucidating the synchronization characteristics of nonlinear oscillators under the influence of external forces. Oscillatory phenomena in nature often consist of an ensemble of multiple oscillators, which complicates the measurement of individual oscillator PRCs. A prior study introduced a technique for estimating individual PRCs from the singularity response (SR)—the reaction of an ensemble of desynchronized oscillators without couplings. However, the utility of this method is somewhat limited, as it considers only the first harmonic of the PRC. The current study demonstrates that the detailed contour of the PRC can be ascertained by employing the higher harmonics of the SR.

Abstract Entrainment is characterized by phase response curves (PRCs), which provide a summary of responses to perturbations at each circadian phase. The synchronization of mammalian circadian clocks is accomplished through the receipt of a variety of inputs from both internal and external time cues. A comprehensive comparison of PRCs for various stimuli in each tissue is required. Herein, we demonstrate that PRCs in mammalian cells can be characterized using a recently developed estimation method based on singularity response (SR), which represents the response of desynchronized cellular clocks. We confirmed that PRCs can be reconstructed using single SR measurements and quantified response properties for various stimuli in several cell lines. SR analysis reveals that the phase and amplitude after resetting are distinguishable among stimuli. SRs in tissue slice cultures reveal tissue-specific entrainment properties. These results demonstrate that SRs can be employed to unveil entrainment mechanisms with diverse stimuli in multiscale mammalian clocks.

Many patients with psychiatric conditions, such as bipolar disorder and major depressive disorder, frequently experience disruptions in their sleep–wake cycles. Several case studies and clinical trials have shown that the administration of aripiprazole, a commonly prescribed antipsychotic drug, alleviates the symptoms of circadian sleep disorders in these patients. This improvement may be attributed to the effects of aripiprazole on the circadian central clock, specifically the hypothalamic suprachiasmatic nucleus (SCN), which regulates various circadian physiological rhythms, including the sleep–wake cycle, in mammals. To examine whether aripiprazole facilitates adaptation to changes in the light–dark cycle, we orally administered aripiprazole to mice and subjected them to jet-lag experiments. Mice receiving aripiprazole were more rapidly entrained to 6 h advanced light–dark cycles. Moreover, we examined the effect of aripiprazole on the cellular rhythms of SCN slice cultures and found that aripiprazole disrupted cellular synchronization in the SCN, thereby accelerating the damping of the SCN rhythm at the population level. Adenosine 3′5’ monophosphate (cAMP) assay using a bioluminescence indicator revealed that intracellular cAMP level in the SCN increased following aripiprazole treatment. However, this increase was blocked by pre-treatment with the serotonin 1A receptor (5-HT1AR) antagonist. Based on these findings, we propose that aripiprazole modulates intracellular signaling, including 5-HT1AR-mediated cAMP signaling, and desynchronizes SCN neurons, ultimately leading to enhanced entrainment to phase advanced light–dark cycles in mice. These findings indicate that the improvement in sleep symptoms reported in patients with psychiatric disorders receiving aripiprazole may be due to modulation of the circadian clock. Our study provides novel insights into the potential clinical applications of aripiprazole in patients with various circadian sleep disorders.

Aging disrupts circadian clocks, as evidenced by a reduction in the amplitude of circadian rhythms. Because the circadian clock strongly influences sleep–wake behavior in mammals, age-related alterations in sleep–wake patterns may be attributable, at least partly, to functional changes in the circadian clock. However, the effect of aging on the circadian characteristics of sleep architecture has not been well assessed, as circadian behaviors are usually evaluated through long-term behavioral recording with wheel-running or infrared sensors. In this study, we examined age-related changes in circadian sleep–wake behavior using circadian components extracted from electroencephalography (EEG) and electromyography (EMG) data. EEG and EMG were recorded from 12 to 17-week-old and 78 to 83-week-old mice for 3 days under light/dark and constant dark conditions. We analyzed time-dependent changes in the duration of sleep. Rapid eye movement (REM) and non-REM (NREM) sleep significantly increased during the night phase in old mice, whereas no significant change was observed during the light phase. The circadian components were then extracted from the EEG data for each sleep–wake stage, revealing that the circadian rhythm in the power of delta waves during NREM sleep was attenuated and delayed in old mice. Furthermore, we used machine learning to evaluate the phase of the circadian rhythm, with EEG data serving as the input and the phase of the sleep–wake rhythm (environmental time) as the output. The results indicated that the output time for the old mice data tended to be delayed, specifically at night. These results indicate that the aging process significantly impacts the circadian rhythm in the EEG power spectrum despite the circadian rhythm in the amounts of sleep and wake attenuated but still remaining in old mice. Moreover, EEG/EMG analysis is useful not only for evaluating sleep–wake stages but also for circadian rhythms in the brain.

The circadian clock plays an important role in agriculture, especially in highly controlled environments, such as plant factories. However, multiple environmental factors have an extremely high degree of freedom, and it is difficult to experimentally search for the optimal design conditions. A recent study demonstrated that the effect of time lags between light and temperature cycles on plant growth could be predicted by the entrainment properties of the circadian clock in Arabidopsis thaliana. Based on this prediction, it was possible to control plant growth by adjusting the time lag. However, for application in plant factories, it is necessary to verify the effectiveness of this method using commercial vegetables, such as leaf lettuce. In this study, we investigated the entrainment properties of the circadian clock and the effect of the time lag between light and temperature cycles on circadian rhythms and plant growth in Lactuca sativa L. seedlings. For evaluation of circadian rhythms, we used transgenic L. sativa L. with a luciferase reporter in the experiment and a phase oscillator model in the simulation. We found that the entrainment properties for the light and temperature stimuli and the effects of time lags on circadian rhythm and growth were similar to those of A. thaliana. Moreover, we demonstrated that changes in growth under different time lags could be predicted by simulation based on the entrainment properties of the circadian clock. These results showed the importance of designing a cultivation environment that considers the circadian clock and demonstrated a series of methods to achieve this.

Phase response curves reveal how biological clocks respond to stimuli applied during different circadian phases but can be costly to produce. Here Masuda et al. show that phase response curves for plants can be reconstructed by monitoring how a desynchronized population responds to a single stimulus.

Plant growth responses to cues such as light, temperature, and humidity enable the entrainment of the circadian rhythms with diurnal cycles. For example, the temperature variations between day and night affect plant growth and accompany the time lag to light cycle. Despite its importance, there has been no systematic investigation into time lags, and the mechanisms behind the entrainment of the circadian rhythms with multiple cycles remain unknown. Here, we investigated systemically the effects of the time lag on the circadian rhythm and growth in Arabidopsis thaliana. To investigate the entrainment status of the circadian clock, the rhythm of the clock gene CIRCADIAN CLOCK ASSOCIATION 1 (CCA1) was measured with a luciferase reporter assay. As a result, the rhythm was significantly modulated by the time lag with +10°C heating for 4 h every day but not −10°C cooling. A model based on coupled cellular oscillators successfully described these rhythm modulations. In addition, seedling growth depended on the time lag of the heating cycle but not that of the cooling cycle. Based on the relationship between the CCA1 rhythms and growth, we established an estimation method for the effects of the time lag. Our results found that plant growth relates to the CCA1 rhythm and provides a method by which to estimate the appropriate combination of light–dark and temperature cycles.