Journal of Biological Rhythms最新文献

Wearable devices have become commonplace tools for tracking behavioral and physiological parameters in real-world settings. Nonetheless, the practical utility of these data for clinical and research applications, such as sleep analysis, is hindered by their noisy, large-scale, and multidimensional characteristics. Here, we develop a neural network algorithm that predicts sleep stages by tracking topological features (TFs) of wearable data and model-driven clock proxies (CPs) reflecting the circadian propensity for sleep. To evaluate its accuracy, we apply it to motion and heart rate data from the Apple Watch worn by young subjects undergoing polysomnography (PSG) and compare the predicted sleep stages with the corresponding ground truth PSG records. The neural network that includes TFs and CPs along with raw wearable data as inputs shows improved performance in classifying Wake/REM/NREM sleep. For example, it shows significant improvements in identifying REM and NREM sleep (AUROC/AUPRC improvements >13% and REM/NREM accuracy improvement of 12%) compared with the neural network using only raw data inputs. We find that this improvement is mainly attributed to the heart rate TFs. To further validate our algorithm on a different population, we test it on elderly subjects from the Multi-ethnic Study of Atherosclerosis cohort. This confirms that TFs and CPs contribute to the improvements in Wake/REM/NREM classification. We next compare the performance of our algorithm with previous state-of-the-art wearable-based sleep scoring algorithms and find that our algorithm outperforms them within and across different populations. This study demonstrates the benefits of combining topological data analysis and mathematical modeling to extract hidden inputs of neural networks from puzzling wearable data.

Circadian rhythms synchronize the internal physiology of animals allowing them to anticipate daily changes in their environment. Arctic habitats may diminish the selective advantages of circadian rhythmicity by relaxing daily rhythmic environmental constraints, presenting a valuable opportunity to study the evolution of circadian rhythms. In reindeer, circadian control of locomotor activity and melatonin release is weak or absent, and the molecular clockwork is reportedly non-functional. Here we present new evidence that the circadian clock in cultured reindeer fibroblasts is rhythmic and temperature-compensated. Compared with mouse fibroblasts, however, reindeer fibroblasts have a short free-running period, and temperature cycles have an atypical impact on clock gene regulation. In reindeer cells, Per2 and Bmal1 reporters show rapid responses to temperature cycles, with a disintegration of their normal antiphasic relationship. The antiphasic Per2-Bmal1 relationship re-emerges immediately after release from temperature cycles, but without complete temperature entrainment and with a marked decline in circadian amplitude. Experiments using Bmal1 promoter reporters with mutated RORE sites showed that a reindeer-like response to temperature cycles can be mimicked in mouse or human cell lines by decoupling Bmal1 reporter activity from ROR/REV-ERB-dependent transcriptional regulation. We suggest that weak coupling between core and secondary circadian feedback loops accounts for the observed behavior of reindeer fibroblasts in vitro. Our findings highlight diversity in how the thermal environment affects the temporal organization of mammals living under different thermoenergetic constraints.

Mating success depends on many factors, but first of all, a male and a female need to meet at the same place and time. The circadian clock is an endogenous system regulating activity and sex-related behaviors in animals. We studied bumble bees (Bombus terrestris) in which the influence of circadian rhythms on sexual behavior has been little explored. We characterized circadian rhythms in adult emergence and locomotor activity under different illumination regimes for males and gynes (unmated queens). We developed a method to monitor adult emergence from the pupal cocoon and found no circadian rhythms in this behavior for either males or gynes. These results are not consistent with the hypothesis that the circadian clock regulates emergence from the pupa in this species. Consistent with this premise, we found that both gynes and males do not show circadian rhythms in locomotor activity during the first 3 days after pupal emergence, but shortly after developed robust circadian rhythms that are readily shifted by a phase delay in illumination regime. We conclude that the bumble bees do not need strong rhythms in adult emergence and during early adult life in their protected and regulated nest environment, but do need strong activity rhythms for timing flights and mating-related behaviors. Next, we tested the hypothesis that the locomotor activity of males and gynes have a similar phase, which may improve mating success. We found that both males and gynes have strong endogenous circadian rhythms that are entrained by the illumination regime, but males show rhythms at an earlier age, their rhythms are stronger, and their phase is slightly advanced relative to that of gynes. An earlier phase may be advantageous to males competing to mate a receptive gyne. Our results are consistent with the hypothesis that sex-related variations in circadian rhythms is shaped by sexual selection.

The present study aimed to develop a TaqMan genotyping card for molecular chronotype assessment based on a predictive panel of 35 previously identified genetic variants. A reliable TaqMan assay was successfully developed for 33 out of the 35 chronotype-predictive variants. The resulting TaqMan genotyping card was utilized to genetically characterize 196 new individuals (in addition to the previously studied 96) and the Morningness-Eveningness Questionnaire was utilized for their phenotypical chronotype assessment. The predictive panel performance was validated on (a) a group of morning and evening individuals (logistic regression model), (b) a representative sample of the original study population also including intermediate chronotypes (linear regression model) and, (c) 25,986 individuals from the Estonian Biobank, for whom Munich Chronotype Questionnaire scores were available. The validation of the morningness-eveningness logistic regression model on 25 morning and 21 evening types resulted in a predictive value of 72%, confirming the reliability of the predictive panel and the success of its conversion into a TaqMan genotyping card. By contrast, the inclusion of intermediate individuals in the model led to a significant decrease in predictive performance (45% on 100 individuals [25 morning, 54 intermediate, and 21 evening]), with intermediate types being the most affected. No significant associations were observed between the genotype panel and chronotype in the Estonian Biobank sample. In conclusion, our genotyping card might represent a promising molecular chronotyping tool for the Italian population. Its performance in other populations is worthy of further study.

My journey into chronobiology began in 1977 with lectures and internships with Wolfgang Engelmann and Hans Erkert at the University of Tübingen in Germany. At that time, the only known animal clock gene was Period, and the location and organization of the master circadian clock in the brain was completely unknown for the model insect Drosophila melanogaster. I was thus privileged to witness and participate in the research that led us from discovering the first clock gene to identifying the clock network in the fly brain and the putative pathways linking it to behavior and physiology. This article highlights my role in these developments and also shows how the successful use of D. melanogaster for studies of circadian rhythms has contributed to the understanding of clock networks in other animals. I also report on my experiences in the German scientific system and hope that my story will be of interest to some of you.

Many organisms inhabiting the interface between land and sea have evolved biological clocks corresponding to the period of the semilunar (14.77 days) or the lunar (29.53 days) cycle. Since tidal amplitude is modulated across the lunar cycle, these circasemilunar or circalunar clocks not only allow organisms to adapt to the lunar cycle, but also to specific tidal situations. Biological clocks are synchronized to external cycles via environmental cues called zeitgebers. Here, we explore how light at night sets the circalunar and circasemilunar clocks of Clunio marinus, a marine insect that relies on these clocks to control timing of emergence. We first characterized how moonlight intensity is modulated by the tides by measuring light intensity in the natural habitat of C. marinus. In laboratory experiments, we then explored how different moonlight treatments set the phase of the clocks of two C. marinus strains, one with a lunar rhythm and one with a semilunar rhythm. Light intensity alone does not affect the phase of the lunar rhythm. Presenting moonlight during different 2-h or 4-h windows during the night shows that (1) the required duration of moonlight is strain-specific, (2) there are strain-specific moonlight sensitivity windows and (3) timing of moonlight can shift the phase of the lunar rhythm to stay synchronized with the lowest low tides. Experiments simulating natural moonlight patterns confirm that the phase is set by the timing of moonlight. Simulating natural moonlight at field-observed intensities leads to the best synchronization. Taken together, we show that there is a complex and strain-specific integration of intensity, duration and timing of light at night to precisely entrain the lunar and semilunar rhythms. The observed fine-tuning of the rhythms under natural moonlight regimes lays the foundation for a better chronobiological and genetic dissection of the circa(semi)lunar clock in C. marinus.

Animal circadian clocks play a crucial role in regulating behavioral adaptations to daily environmental changes. The fruit fly Drosophila melanogaster exhibits 2 prominent peaks of activity in the morning and evening, known as morning (M) and evening (E) peaks. These peaks are controlled by 2 distinct circadian oscillators located in separate groups of clock neurons in the brain. To investigate the clock neurons responsible for the M and E peaks, a cell-specific gene expression system, the GAL4-UAS system, has been commonly employed. In this study, we re-examined the two-oscillator model for the M and E peaks of Drosophila by utilizing more than 50 Gal4 lines in conjunction with the UAS-period¹⁶ line, which enables the restoration of the clock function in specific cells in the period (per) null mutant background. Previous studies have indicated that the group of small ventrolateral neurons (s-LN_v) is responsible for controlling the M peak, while the other group, consisting of the 5^th ventrolateral neuron (5^th LN_v) and the three cryptochrome (CRY)-positive dorsolateral neurons (LN_d), is responsible for the E peak. Furthermore, the group of posterior dorsal neurons 1 (DN_1p) is thought to also contain M and E oscillators. In this study, we found that Gal4 lines directed at the same clock neuron groups can lead to different results, underscoring the fact that activity patterns are influenced by many factors. Nevertheless, we were able to confirm previous findings that the entire network of circadian clock neurons controls M and E peaks, with the lateral neurons playing a dominant role. In addition, we demonstrate that 4 to 6 CRY-positive DN_1p cells are sufficient to generate M and E peaks in light-dark cycles and complex free-running rhythms in constant darkness. Ultimately, our detailed screening could serve as a catalog to choose the best Gal4 lines that can be used to rescue per in specific clock neurons.

The estrous cycle regulates rhythms of locomotor activity, body temperature, and circadian gene expression. In female mice, activity increases on the night of proestrus, when elevated estrogens cause ovulation. Exogenous estradiol regulates eating behavior rhythms in female mice fed a high-fat diet, but it is unknown whether endogenous estrogens regulate eating rhythms. In this study, we investigated whether diurnal and circadian eating behavior rhythms change systematically across the estrous cycle. We first studied diurnal eating behavior rhythms in female C57BL/6J mice in 12L:12D. Estrous cycle stages were determined by vaginal cytology while eating behavior and wheel revolutions were continuously measured. The mice had regular 4- to 5-day estrous cycles. Consistent with prior studies, the greatest number of wheel revolutions occurred on the night of proestrus into estrus when systemic levels of estrogens peak. The amplitude, or robustness, of the eating behavior rhythm also fluctuated with 4- to 5-day cycles and peaked primarily during proestrus or estrus. The phases of eating behavior rhythms fluctuated, but not at 4- or 5-day intervals, and phases did not correlate with estrous cycle stages. After ovariectomy, the eating behavior rhythm amplitude fluctuated at irregular intervals. In constant darkness, the amplitude of the circadian eating behavior rhythm peaked every 4 or 5 days and coincided with the circadian day that had the greatest number of wheel revolutions, a marker of proestrus. These data suggest that fluctuations of ovarian hormones across the estrous cycle temporally organize the robustness of circadian eating behavior rhythms so that it peaks during ovulation and sexual receptivity.