Period-2 (Per2) expression in tissues peripheral to the suprachiasmatic nuclei (SCN) increases during sleep deprivation and at times of the day when animals are predominantly awake spontaneously, suggesting that the circadian sleep-wake distribution directly contributes to the daily rhythms in Per2. We found support for this hypothesis by recording sleep-wake state alongside PER2 bioluminescence in freely behaving mice, demonstrating that PER2 bioluminescence increases during spontaneous waking and decreases during sleep. The temporary reinstatement of PER2-bioluminescence rhythmicity in behaviorally arrhythmic SCN-lesioned mice submitted to daily recurring sleep deprivations substantiates our hypothesis. Mathematical modeling revealed that PER2 dynamics can be described by a damped harmonic oscillator driven by two forces: a sleep-wake-dependent force and an SCN-independent circadian force. Our work underscores the notion that in peripheral tissues the clock gene circuitry integrates sleep-wake information and could thereby contribute to behavioral adaptability to respond to homeostatic requirements.In the mouse,  Circadian rhythms are daily cycles in behavior and physiology which repeat approximately every 24 hours. The master regulator of these rhythms is located in a small part of the brain called the supra-chiasmatic nucleus. This brain structure regulates the timing of sleep and wakefulness and is also thought to control the daily rhythms of cells throughout the body on a molecular level. It does this by synchronizing the activity of a set of genes called clock genes.Under normal conditions, the levels of proteins coded for by clock genes change throughout the day following a rhythm that matches sleep-wake patterns. However, keeping animals and humans awake at their preferred sleeping times affects the protein levels of clock genes in many tissues of the body. This suggests that, in addition to the supra-chiasmatic nucleus, sleep-wake cycles may also influence clock-gene rhythms throughout the body.Period-2, while tracking sleep-wake states in mice. They did this by imaging a bioluminescent version of the PERIOD-2 protein in the brain and the kidneys, at the same time as they recorded the brain activity, movement and muscle response of animals. Results showed that PERIOD-2 increased on waking and decreased when mice fell asleep. Additionally, in mice lacking a circadian rhythm in sleep-wake behavior – whose changes in PERIOD-2 levels with respect to time were greatly reduced – imposing a regular sleep-wake cycle restored normal PERIOD-2 rhythmicity.To test this theory, Hoekstra, Jan et al. measured the levels of PERIOD-2, a protein coded for by the clock gene . developed a mathematical model to understand how sleep-wake cycles together with circadian rhythms affect clock-gene activity in the brain and kidneys. Computer simulations suggested that sleep-wake cycles and circadian factors act as forces of comparable strength driving clock-gene dynamics. Both need to act in concert to keep clock-genes rhythmic. The model also predicted the large and immediate effects of sleep deprivation on PERIOD-2 levels, giving further credence to the idea that waking accelerated clock-gene rhythms while sleeping slowed them down. Modelling also suggested that having regular clock-gene rhythms protects against sleep disturbances.Next, Hoekstra, Jan et alIn summary, this work shows how sleep patterns contribute to the daily rhythms in clock genes in the brain and body. The findings support the idea that well-timed sleep-wake schedules could help people to adjust to new time zones. It might also be useful to inform other strategies to reduce the health impacts of shift work. Period  and Cryptochrome  genes. Subsequently, PER and CRY proteins assemble into repressor complexes that inhibit CLOCK/NPAS2:ARNTL-mediated transcription, including their own. The resulting reduction of the repressor complex allows a new cycle to start. This feedback loop, present in almost each cell of the mammalian body, interacts with other molecular pathways, together ensuring a period of ~24 hr , electromyogram (EMG), locomotor activity (LMA), and PER2-dependent bioluminescence signals from cortex and kidney in freely behaving mice, we established that the circadian sleep-wake distribution importantly contributes to the daily rhythmic changes in central and peripheral PER2 levels. To further test this hypothesis, we predicted that (i) in behaviorally arrhythmic SCN-lesioned (SCNx) mice, daily recurring SDs mimicking a circadian sleep-wake distribution will temporarily reinstate high-amplitude PER2 bioluminescence rhythms, and (ii) in intact rhythmic animals, reducing the amplitude of the circadian sleep-wake distribution will result in a reduced amplitude of PER2 rhythms. While daily SDs indeed enhanced the amplitude of peripheral PER2 rhythms in SCNx mice, the protocol used to reduce the amplitude of the sleep-wake distribution did not reduce PER2 amplitude in all mice. To reconcile the sleep-wake-driven and circadian aspects of PER2 dynamics, we implemented a mathematical model in which waking represents a force that sets in motion a harmonic oscillator describing PER2 dynamics and found that the sleep-wake distribution, also under undisturbed conditions, is an important contributor to the daily changes in PER2 bioluminescence. Moreover, we discovered a second, SCN and sleep-wake independent force with a circadian period that underlay the residual circadian PER2 rhythms in SCNx mice, and that the phase relationship between these two forces is important for predicting the amplitude response in PER2 rhythms to sleep-wake perturbations.LucPer2 KI mice have been used to follow clock gene expression in vivo (LucPer construct was back-crossed onto a C57BL/6J (B6) background . For the experiments that quantified bioluminescence in the periphery, we used hairless SKH1 mice carrying the LucPer2 KI construct because lack of fur allows for the unobstructed measurement of emitted photons  construct encoding a fused PER2::LUCIFERASE (PER2::LUC) protein and in which changes in emitted bioluminescence can be used as proxy for changes in PER2 protein levels . Per2Luc in vivo . However in vivo , we assesee also .In three pilot experiments, we optimized our experimental set-up. We established that the most important source contributing to the peripheral bioluminescence signals in the SKH1 mice are the kidneys . We havePer2 mRNA and protein levels in various tissues and mammalian species  with wireless EEG/EMG recorders  and monitored simultaneously sleep-wake state, PER2 bioluminescence, and LMA under constant darkness . As expected from a housekeeping gene, bioluminescence in Pkg1-Luc mice was relatively constant and did not increase at sleep-wake transitions  enforced wakefulness has both acute and long-term effects on PER2 bioluminescence; (2) the changes in PER2 bioluminescence at sleep-wake transitions demonstrate that also spontaneous waking is associated with an increase, and sleep with a decrease, in PER2 bioluminescence; and (3) that PER2 bioluminescence is high when mice are spontaneously awake more.LucPer2 SKH1 mice. Because waking correlates highly with LMA  lack a circadian organization of sleep-wake behavior under constant conditions . Under tLesioning the SCN rendered LMA arrhythmic under DD conditions . In arrhIn the next experiment, we aimed at reducing the amplitude of the circadian sleep-wake distribution in intact mice using the 2-day 2hOnOff protocol. We measured sleep-wake state and PER2 bioluminescence during baseline conditions, the 2hOnOff procedure, and the two recovery days in two cohorts of mice. In the first cohort, PER2 bioluminescence was monitored, and mice were taken out of the RT-Biolumicorder for the 2 hr SDs. Bioluminescence was therefore quantified only during the SOWs, thus biasing the read-out of PER2 bioluminescence during the 2hOnOff protocol towards levels reached during sleep. A second cohort was implanted with tethered EEG/EMG electrodes to determine the efficacy of the 2hOnOff protocol in reducing the sleep-wake distribution amplitude.As expected, mice exhibited a circadian PER2-bioluminescence rhythm under baseline conditions . Contrart-test, BSL vs. 2hOnOff-day 1: t(7) = 8.86, p<0.001; BSL vs. 2hOnOff-day 2: t(7) = 4.18, p=0.004; 2hOnOff-day 1 vs. -day 2, t(7) = 1.97, p=0.09), combined with the difficulty for the experimenters to visually detect and prevent sleep in pinkish hairless mice under dim-red light conditions. During recovery from the 2hOnOff protocol, baseline amplitudes were re-established  both forces are required to predict PER2-bioluminescence dynamics, (2) lesioning the SCN affects the forces exerted on PER2 bioluminescence under undisturbed, DD conditions, and (3) differences in the circadian phase could predict the opposing response in PER2-bioluminescence amplitude among mice in the 2hOnOff experiment.To evaluate if captured , Table 2ll model . Also, td F→PERI , Table 2To answer the second question, we compared the forces driving PER2 bioluminescence in the baseline recordings of the 2hOnOff (intact mice) and the SCNx experiments. The model estimated that the average absolute force  spontaneous sustained bouts of waking and sleep were associated with increased and decreased PER2 bioluminescence, respectively; (2) a single SD acutely increased PER2 bioluminescence and during subsequent recovery dampened its circadian amplitude; (3) repeated SDs temporarily reinstated robust rhythmicity in PER2 bioluminescence in behaviorally arrhythmic mice; and (4) mathematical modeling suggests that PER2 dynamics is best understood as a harmonic oscillator driven by two forces: a sleep-waking-dependent force . Because of this, Per2 can appear rhythmic even in the absence of a functional TTFL, provided these signaling pathways fluctuate cyclically  and are the SCN . One stuted rats , underscnslation , suggestnslation .Casein kinase 1 (Csnk1)-mediated phosphorylation (β-transducin repeat-containing proteins (Btrc)  (Transformed mouse 3T3 cell double minute 2 (Mdm2)  . Other k3 (Sik3) , and pho2 (Mdm2) , p. 2, aPer2 in the forebrain partly depended on glucocorticoids  contributes to the wake-driven changes in PER2 protein. We already established that the SD-incurred increase in rticoids . Along trticoids . To deteormation .The model accurately captured the main features of peripheral PER2 dynamics observed in all three experiments, thereby giving further credence to the notion that sleep-wake state importantly contributes to the changes in PER2 observed in the periphery. Moreover, it demonstrated that the large amplitude of the circadian PER2 rhythm in intact mice is likely the result of the momentum gained in the harmonic oscillator through the daily recurring sleep-wake distribution. This is conceptually different from a currently accepted scenario, in which direct and indirect outputs from the SCN assure phase coherence of locally generated self-sustained circadian rhythms . AccordiThe harmonic oscillator model further showed that, although important, the sleep-wake force alone was not sufficient to predict PER2 dynamics. In addition to account for the residual PER2 rhythms observed in undisturbed SCNx mice, the SCN-independent and sleep-wake-independent circadian force greatly improved the performance of the model. The synergistic effect of both forces  mice. Mice were kept under a 12 hr light/12 hr dark cycle with light- and dark onset referred to as Zeitgeber time (ZT)-0 and -12, respectively. Age at time of recording varied between 12 and 24 weeks. Food and water was available ad libitum, and after surgery mice were singly housed. All experiments were approved by the Ethical Committee of the State of Vaud Veterinary Office Switzerland under license VD2743, 3201, and 3402.To measure peripheral PER2-bioluminescence levels, we made use of the onstruct . The KI LucPer2 KI mice express ubiquitously luciferase and the RT-Biolumicorder cannot discriminate between different sources of bioluminescence, we assessed which peripheral organ(s) was/were the major source of bioluminescence. Two male heterozygous LucPer2 SKH1 mice were implanted with an osmotic mini-pump  and 5 days later lightly anesthetized with 2.5% isoflurane and imaged for 60 s (Xenogen IVIS Lumina II) around ZT6. The main source of dorsal bioluminescence overlapped with the expected location of the kidney, whereas ventrally almost no bioluminescence was detected  containing 70 mg/mL of luciferin and could recover for 2 days before bioluminescence and activity was monitored for the second experiment in the RT-Biolumicorder.In a second pilot experiment, we investigated the optimal route of luciferin administration. Although luciferin administration via drinking water has been used before to measure bioluminescence , we wereExperimental design of the three main experiments is depicted in Mice were implanted with EEG and EMG electrodes under deep ketamine/xylazine anesthesia. Three gold-plated screws  were screwed into the skull over the right cerebral hemisphere, where the cerebellar screw served as a reference for the other two electrodes. Two additional screws were used as anchor screws. For the EMG, a gold wire was inserted into the neck musculature along the back of the skull. For brain delivery of D-luciferin, a cannula  was introduced stereotaxically into the right lateral ventricle  under deep anesthesia , and connected to the mini-pump. A depression (diameter 2 mm) was made in (but not through) the skull in a region of the left frontal cortex , in which a glass cylinder  was positioned and fixed with dental cement. The EMG and three EEG electrodes were subsequently soldered to a connector and cemented to the skull. The cerebellar screw served as a reference for the parietal and frontal screw and the EMG. After the first recovery day, mice were habituated to the weight of the wireless EEG recording system by attaching a dummy of same size and weight to their connector. Two days before habituation to the RT-Biolumicorder, mice were implanted with the osmotic mini-pump  under light anesthesia. 8–10 days post-surgery, mice were placed in the RT-Biolumicorder at the end of the light phase (~ZT10-ZT12) for 2 days in LD to habituate to the novel environment. At the end of the second habituation day, the dummy was replaced with a wireless EEG . After two-and-a-half days of baseline recording in constant darkness, mice were sleep deprived for 6 hr at a time they were expected to rest (ZT0 under LD conditions) by gentle handling as described . In shorFour SKH1 mice were recorded over the course of the experiment and served as their own control. Briefly, their PER2-bioluminescence rhythm was monitored before SCNx (once), under undisturbed conditions post-SCNx (twice), and after the second measure under SCNx conditions, the mice were subjected to the repeated 4 hr SDs.Bilateral lesion of the two SCNs was performed stereotaxically  under ketamine/xylazine anesthesia . Two electrodes (0.3 mm in diameter) were introduced bilaterally at the following coordinates . Electrolytic lesions  were made using a direct current (DC) lesion device . After lesion, mice were housed in constant dark (DD) conditions for at least 10 days to verify absence of circadian organization of overt behavior. Activity was quantified using passive infrared sensors . ClockLab software  was used for data acquisition and analyses.SKH1 mice (n = 8) were implanted with EEG and EMG electrodes as described previously  to deterDuring the baseline recording and SD days, red light at very low intensity was present to allow the experimenters to observe the mice. Mice were sleep deprived for 2 hr according to the ‘gentle handling’ method.SKH1 mice (n = 6) were implanted with an osmotic mini-pump  2 days before the habituation. At the end of the light phase (~ZT10-ZT12), mice were moved from their cage to the RT-Biolumicorder for 2–3 days of habituation in LD. They were housed for 2.5 days in DD, after which the 2hOnOff protocol was initiated at light onset (ZT0) under the preceding LD conditions. At the start of each SD, mice were moved from the RT-Biolumicorder and placed into a novel cage that was in the same room as the EEG-implanted mice. Fifteen minutes before the end of each SD, mice were brought back to their RT-Biolumicorder cage.Pgk1 promoter . See The adenoviral vector used in the experiment was constructed by cloning the cassette flanked by PacI sites from vector prLV1  into vecpost hoc align the EEG/EMG signals with the bioluminescence signal. In addition, time stamps provided by the SyncBox  were used to verify the start and end time of the EEG/EMG recording. The cerebellar electrode was used as a reference for both EMG and EEG. Data were sampled at 256 Hz. The frontal signal was subtracted from the parietal signal (EDF Browser) to support sleep-wake state determination by enhancing the identification of slow waves and theta waves within the same trace. The data were subsequently loaded in Somnologica  to determine offline the mouse’s behavior as wakefulness, REM sleep, or NREM sleep per 4 s epochs based on the EEG and EMG signals. Wakefulness was characterized by EEG activity of mixed frequency and low amplitude, and present but variable muscle tone. NREM sleep (NREM) was defined by synchronous activity in the delta frequency (1–4 Hz) and low and stable muscle tone. REM sleep (REM) was characterized by regular theta oscillations (6–9 Hz) and EMG muscle atonia.Batteries  were inserted into the NeuroLogger. This insertion was timed with the clock of the computer that controlled the RT-Biolumicorder to EEG and EMG signals were recorded continuously for 96 hr. The recording started at the beginning of the subjective rest phase, ZT0 of the preceding LD cycle. The analog EEG and EMG signals were amplified (2000×) and digitized at 2 kHz and subsequently down-sampled to 200 Hz and stored. Like the EEG and EMG traces obtained with the NeuroLogger, the data were imported in Somnologica and sleep-wake state was determined per 4 s epochs. LMA was monitored with passive infrared activity (Actimetrics) and recorded with ClockLab (Actimetrics).Circadian time was determined to inspect the circadian changes in bioluminescence relative to LMA. To this end, the period length per mouse was determined based on activity measurements (1 min resolution) by chi-square analysis in ClockLab. Subsequently, the activity and bioluminescence data were folded according to the period. The activity data were binned per 10 min, and activity onset was visually determined for each mouse and set at CT12. The aligned activity and bioluminescence data were subsequently averaged per circadian hour across mice.detrend in MATLAB and R (pracma package). Subsequently, the bioluminescence signal was expressed relative to the overall mean per mouse to account for inter-individual differences. Changes in PER2 would be expected to occur at a slower rate than 4 s. Therefore, sleep-wake and bioluminescence data are averaged per blocks of 3 min.Bioluminescence and activity were sampled at a resolution of 4 s, which is the same resolution of the epochs for sleep-wake state determination. Data processing was subsequently performed in MATLAB 2017b  and R (version 4.0.0). Linear trends were removed from the signal by the build-in function For the sleep-wake transition analysis, 3 min intervals in which the mouse was awake for more than 50%  were deemed awake, otherwise as asleep. Based on this new 3 min sleep-wake sequence, clear sleep-to-wake and wake-to-sleep transitions were selected according to the following criteria: at least 9 min  of the initial state had to be followed by at least 15 min  of the other state. Transitions were followed both forward and backward in time as long as state did not change. Bioluminescence for all 3 min intervals of a transition was expressed as a percentage of the level reached at the transition; that is, the average between the level reached in the last 3 min prior to the transition and the first 3 min after the transition. Transitions were aligned according to time of the state transition (time 0) and then averaged first within and then across mice. Average time courses were reported for the longest time spent in state after the transition to which all mice contributed.Bioluminescence data obtained 5 min before and 10 min after the SDs were excluded from analysis. Subsequent data normalization of the bioluminescence data was as above. To determine the influence of the 2hOnOff protocol on the strength of the ongoing circadian oscillation of the circadian distribution of sleep and wake, as well as on PER2 bioluminescence, an estimation of amplitude by sinewave fitting was done  of the driven harmonic oscillator, we transformed it into the following system of two first-order ODEs describing the change of position and speed of our oscillator:We then used the fourth-order Runge–Kutta (RK4) numerical method to approximate the solution using a fixed time step of 0.1 hr. In the SCNx experiment, initial values of speed  between our model and a flat model (linear model with intercept only) as follows:http://sia.webpopix.org/nonlinearRegression.html.To compute confidence interval of our model parameters, we used 500 Monte Carlo simulations and calculated a confidence interval for our parameters based on 95% empirical quantiles (95% CI). The method was adapted from the code of Marc Lavielle  for nonlinear models, available here: α = 0.05. Performed statistical tests are mentioned in the text and figure legends.Statistics were performed in R (version 4.0.0), SAS (version 9.4), and Prism (version 7.0), with the threshold of significance set at  This work contributes interesting data to both the circadian and sleep fields as it presents evidence that clock gene expression in peripheral tissues can be regulated in sleep-wake-state- and peripheral-circadian-dependent manners. To support this idea, the authors monitor sleep-wake state, as well as PER2 expression (utilizing a PER2-luciferase system), in both intact or SCN-lesioned freely behaving mice. Analysis of central and peripheral PER2LUC levels, under diverse sleep protocols, and aided by mathematical models allows them to support the idea that in peripheral tissues the clock gene circuitry integrates sleep-wake information, potentially contributing to behavioral adaptability to homeostatically respond to different challenges. In the interests of transparency, eLife publishes the most substantive revision requests and the accompanying author responses.Decision letter after peer review:[Editors’ note: the authors submitted for reconsideration following the decision after peer review. What follows is the decision letter after the first round of review.]eLife. Your article has been reviewed by 3 peer reviewers, and the evaluation has been overseen by a Reviewing Editor and a Senior Editor. The following individual involved in review of your submission has agreed to reveal their identity: Hiroki Ueda (Reviewer #1).Thank you for submitting your work entitled "The sleep-wake distribution contributes to the peripheral rhythms in PERIOD-2" for consideration by eLife.Our decision has been reached after consultation between the reviewers. Based on these discussions and the individual reviews below, we regret to inform you that your work will not be considered further for publication in eLife would be needed to address these concerns.As you can see from the feedback provided by the reviewers they found the data interesting and thought-provoking, yet they also raised substantial concerns about different aspects of the work. Importantly, the reviewers noted that some of the main conclusions (based on the presented data) are not fully supported. A considerable amount of work that is beyond the scope of a revision at Reviewer #1:In this paper entitled "The sleep-wake distribution contributes to the peripheral rhythms in PERIOD-2", the authors observed PER2 expression in peripheral tissues of freely behaving animals and found that the sleep-wake distribution contributes to the peripheral PER2 dynamics. In addition, implementing the mathematical model, they showed that the peripheral PER2 rhythms can be generated by two factors: a sleep-wake state dependent one and a peripheral (not master) circadian dependent one. Despite the difficulty to dissect the effect of these two factors in vivo, the authors, dealing with this problem by the unique experimental designs, provided direct evidence that sleep-wake state itself affects peripheral daily rhythms. However, this paper has a couple of points to be improved, which are summarized in the comments below.1. As for Figure 1B, 1C and 1D, the authors showed PER2 bioluminescence changes according to circadian rhythm and state transitions in only one individual mouse (ID: 2MP82), which might be insufficient for concluding that the PER2 bioluminescence changes depending on the circadian and sleep-wake cycle. Plus, there might be a mistake in the time label of Figure 1B (is this plot started from time = 6 or time = 0?). Thus, the reviewer suggests that the authors should add data about other mice and perform the statistical analyses to clarify the validity of the circadian- and sleep-wake-dependent change of PER2 bioluminescence. With Figure 4, the reviewer suggests the same, i.e., the authors should analyze not only one representative mouse but a group of mice.2. In lines 202 to 205, the authors concluded that the behavioral rhythm reduction by 2hOnOff protocol appeared to be insufficient to consistently reduce the amplitude of the PER2-bioluminescence oscillation. However, it is difficult to follow its logic toward the conclusion. Thus, the reviewer recommends that the authors should describe their logic in more detail.3. As for Figure 4 and Table 2, the authors compared two mathematical models and concluded that the two forces model has better prediction accuracy. However, it is unclear whether the circadian force itself or the combination of the two forces is important to predict PER2-bioluminescence dynamics. The reviewer suggests that the authors should add a comparison with a model that using a single circadian force (F = FPERI).4. In lines 277 to 280, the authors described the increase in PER2 amplitude during the 2hOnOff experiment by advancing the phase of FPERI by 6h. The reviewer suggests that the authors should clearly explain why they apply their mathematical model to the 6h advancing, although they observed 1-2h phase advance in their experiments.Reviewer #2:By measuring EEG/EMG and PER2::LUC bioluminescence  from freely behaving mice simultaneously or from separate cohort mice with similar conditions, the authors observed that sleep state acutely changed PER2::LUC bioluminescence, repeated daily sleep deprivation reinstated circadian PER2::LUC rhythm in SCN ablated behaviorally arrhythmic mice. The authors also did a mathematical simulation modeling peripheral PER2::LUC bioluminescence influenced by a sleep dependent force and a SCN independent force.eLife.I believe the data presented in the current manuscript, however, I don't think the main conclusions are supported by the data. The acute changes (within 30 min) of luminescence they observed is most likely caused by in vivo factors . It is very problematic to assess the amplitude change from averaged luminescence record from multiple behaviorally arrhythmic mice . Although the above mentioned two major conclusions must be removed from the manuscript, the study validates previously published results done by ex vivo tissue and in vivo anesthetized animal with luminescence measure from freely behaving mice. So I encourage the authors to publish the data to another journal , but I don't think discovery reported in the work is novel for the publication in 1. It is unlikely that the acute change of PER2::LUC luminescence reflects PER2 protein translation and degradation. As the authors refer to correctly, luminescence from PER2::LUC knockin mice reflects PER2::LUC fusion protein (not Per2 transcription). The authors didn't correctly refer to the studies measuring light induction of Per2 mRNA and protein in the SCN. The light induction of Per2 mRNA in the SCN can only be seen 60 min after onset of the light pulse . Increased PER2 protein in the SCN can only be seen at 4 h after the light pulse . Therefore, the acute luminescence change observed at sleep wake transitions  is unlikely reflecting changes in the PER2::LUC fusion protein. Temperature, pH, and Ca/Mg and ATP levels all strongly affect luminescence produced by firefly luciferase and luciferin. It was shown that the ultradian rhythm of the core body temperature closely matched the ultradian behavior rhythm (Blessing 2018 PMID: 30454601). The authors referred to their own published study that luminescence rhythm change was vilified by qPCR. However, the time scale of their published work showed that changes occurred after 6 h of sleep deprivation, not in the 30 min range.2. The advantage of continuous luminescence measurement from the same mouse is that the presence and absence of the rhythm can be determined from a mouse that has no phase marker (e.g. SCN lesioned mice). Arrhythmicity (or lowered amplitude of the rhythm) observed by conventional population sampling (from multiple mice) cannot be determined if individual mice lose rhythmicity, or if individual mice retained intact rhythm but they are out of sync. From the data presented in Figure 2, the authors claimed repeated sleep deprivations reinstated the rhythm, but they didn't analyze amplitude change before, during, and after sleep deprivation in individual mice . It is well known that the SCN-lesioned mice do not show a daily rhythm under LD cycle (Light cannot reinstate behavior rhythm). The authors stated that they performed daily sleep deprivation to the mice 5 weeks after SCN-lesioned. From average luminescence rhythms of 4 SCN-X mice, the authors cannot conclude their main claim that sleep deprivation reinstated the peripheral circadian rhythm. It is possible there is no change in the amplitude of individual peripheral circadian oscillators, but repeated sleep deprivation entrained those rhythms .3. In the complementary experiment presented in Figure 3, the authors analyzed the amplitude changes from individual mice, but didn't analyze from the averaged data. The authors observed a reduced amplitude by 2hOnOff procedure in 4 out of 6 mice, and an increased amplitude in 2 out of 6 mice. But the authors concluded that the 2hOnOff procedure did not "consistently" affect the rhythm .4. Because of the issues pointed out above, the parameters used for the mathematical simulation are not valid. Use of locomotor activity as a wake parameter is also not appropriate. Mice can be wake without moving.5. In the method section, the authors described each procedure. However, it was impossible for me to know how exactly each individual mouse went through the procedures. It seems some sleep deprivation was done under dim red light and other was done under light. I suggest the authors provide a timeline (e.g. flowchart figure) of procedures in each experiment.6. Since in vivo bioluminescence recording became popular technology, I strongly suggest the authors move the data presented in supplementary Figure 2 to the main text as an actual figure. Were CAG mice also crossed with hairless strain? Does tissue explanted from this mouse in vitro not show a circadian rhythm? It even looks like luminescence from the mice with luciferin supplemented by osmic pump shows a weak rhythm. I wonder if CAG promoter may have circadian rhythm as CMV promoter does . Amplitude of activity rhythm is lowered in mice with pump. Is this due to surgery (pump implantation)? If so, lowered amplitude of luminescence rhythm might also be affected by surgery. Having a control  is necessary.Reviewer #3:This is an interesting study. As far as I know, there are no previous studies performing simultaneous measurement of sleep-wake state and bioluminescence (clock gene expression) in freely moving mice. In addition, their measurement method was well validated through several pilot studies, and measurements obtained using this method are therefore reliable. In fact, the presented data are clear and convincing. However, although I have no doubt that the results are useful and valuable for a wide range of circadian scientists, I feel the present version of their work may not be a strong candidate for publication in this journal because of insufficient novelty and impact.1) The results clearly revealed the temporal relationship between sleep-wake state and PER2 bioluminescence through simultaneous monitoring in freely moving mice, with high time resolution. However, because previous studies have already found that sleep deprivation results in a change in PER2 levels, I feel that the present study does not make obvious progress toward further understanding the mechanism. The simultaneous monitoring experiments are interesting but each of the techniques was originally established by other groups. For example, some findings related to the identification of systemic or molecular pathways controlling PER2 expression during sleep deprivation may be required.2) Although a detailed description of the method for sleep deprivation is important, I was not able to find it in the main text. The authors should clarify whether sleep deprivation itself or other factors such as stress signals triggered by sleep deprivation affect PER2 expression. At this time, I feel not sleep deprivation per se but some stress signals affect PER2 expression. Many previous studies have shown that glucocorticoids, well-known stress hormones, strongly affect peripheral clocks. Sleep deprivation, one of the stimuli activating stress signals, may therefore affect PER2 expression in peripheral clocks via glucocorticoid signaling pathways. The contribution of glucocorticoids to PER2 expression during sleep deprivation can be examined simply through surgical removal of the adrenal glands.3) Their conclusions may be specific to the kidney. All bioluminescence data were obtained through monitoring only the kidney. The authors should justify why they can conclude that sleep deprivation affects "peripheral clocks" only judging from kidney data. To generalize kidney data to other peripheral clocks, they should repeat similar experiments using at least another organ or tissue. Real-time monitoring of bioluminescence from the liver is technically simple because injected adenoviruses (carrying a reporter gene driven by a clock gene promoter) specifically infect the liver.eLife. Your revised article has been evaluated by Kate Wassum (Senior Editor) and a Reviewing Editor.Thank you for resubmitting your work entitled "The sleep-wake distribution contributes to the peripheral rhythms in PERIOD-2" for further consideration by The manuscript has been improved but there are some remaining issues that need to be addressed, as outlined below:As you will be able to see in the accompanying comments, while reviewers valued the changes included in this new version of the MS, they still raised important questions. Some may be addressed by reanalyzinging the data already present in the paper . It is claimed that PER2LUC luminescence spikes in Figure 1B are caused by changes in sleep-wake status . Currently, for the CAG-LUC animals, there is only group average data . A valid suggestion, hinted by reviewers, is to show individual records: if spikes are not seen in these animals it helps excluding the possibility that the in vivo luminescence spikes are an artifact (e.g. caused by core body temperature changes). Although it doesn't seem to be recorded EEG/EMG from the non-circadian reporter mice, a similar analysis (based on defining sleep as sustained immobility) could be conducted.Yet, what would really provide strong support to the claims, eliminating doubts about potential artifacts, is to validate the data with conventional methods (immunoblot). As it is mentioned in the MS, during previous work  the authors have partially validated by Western blot analyses peripheral Per2luc bioluminescence data . Yet, the temporal resolution, and experimental condition of such analyses may not be fully comparable to what is present here,It is also important to consider that most of the conclusions drawn from the data are based on the temporal correlation between kidney-derived bioluminescence and sleep-wake states. Therefore, it is difficult to generalize the temporal correlation between single organ-derived bioluminescence and sleep-wake states to other peripheral and central clocks. Such limitation of the work  should be clearly acknowledged.Reviewer #1:In this paper entitled "The sleep-wake distribution contributes to the peripheral rhythms in PERIOD-2", the authors attempted to find the factor(s) directly contributing to clock gene expression in peripheral tissues. To achieve that, they observed PERIOD-2 (PER2) expression in peripheral tissues of freely moving mice and developed new mathematical models to analyze them. They found that the sleep-wake distribution correlates to the peripheral PER2 dynamics, and that the peripheral PER2 rhythms can be predicted by sleep-wake-state- and peripheral-circadian-dependent factors. Despite the difficulty to dissect the effects of circadian and the sleep-wake cycle on gene expression in vivo, they provided direct evidence that the sleep-wake cycle itself affects peripheral daily rhythms by the unique experimental designs. However, there are still a few points to be addressed before publication including a detailed validation of the PER2 bioluminescence system, which would further support their conclusion.All things considered, their findings will have an impact on the chronobiology field, as giving direct evidence on sleep-wake-state-dependent regulation of peripheral clock gene expression. In addition, those methods can be useful to investigate the gene expression not only in the kidney or cerebral cortex but also in other various tissues of freely moving mice.In the revised paper, the authors addressed almost all our concerns with proper correction and additional analyses, but it has some points to be improved before publication, which are summarized in the comments below.1. The authors assumed that PER2 bioluminescence directly reflected expression of PER2 protein, but it has not been fully confirmed yet especially in the fast (within an hour) dynamics. For further progress of the method, the combination with other techniques to quantify fast and small (< 10%) protein changes would be required, as the authors mentioned in the paper.2. This reviewer suggests that the authors should discuss about the controversial results regarding PER2-bioluminescene amplitude and sleep-wake distribution in Figure 3 and Suppl. Figure 7. When the amplitude of the sleep-wake distribution was reduced, PER2-bioluminescence amplitude was reduced in 4/6 mice as the model expected, while it was increased in 2/6 mice.3. Regarding Figure 3E, the authors showed that the 2hOnOff protocol decreased the amplitude of sleep-wake distribution. However, the sleep-wake distribution during the recovery phase was not assessed. Thus, the reviewer recommends that the authors should add data of recovery day to Figure 3E and compare it to the PER2 bioluminescence trends .4. In lines 290 to 294, the authors concluded that the prediction from the model, the behavioral rhythm reduction reduces PER2 bioluminescence amplitude, which is consistent with their observation in the Figure 3. However, this conclusion could be difficult to understand because the 2hOnOff protocol increases the PER2 bioluminescence amplitude in one-third of mice . The authors provided an additional model  to explain the individual difference, and thus the reviewer suggests the authors to describe that conclusion after the modeling part to make the logic clearer.5. Regarding Suppl. Figure 7A-C, the authors described the increase in PER2 amplitude during the 2hOnOff experiment by advancing the phase of FPERI more than 2.5h. The reviewer suggests that the authors could mention these results in Results or Discussion section.Reviewer #2:Hoekstra et al. investigated the relationship between sleep state and PER2::LUC luminescence in freely behaving mice and showed that luminescence acutely changed at sleep/wake transitions. The authors also showed that daily sleep deprivation enhanced the PER2::LUC luminescence rhythm amplitude in SCN ablated mice.A strength of this study is the simultaneous recording of EEG/EMG/activity and PER2::LUC luminescence in freely moving mice.Weakness: One obvious concern is that acute PER2::LUC luminescence changes occurring at sleep/wake transitions are artifacts (e.g. due to acute change in core body temperature), but not caused by synthesis/degradation of PER2 protein. Because those luminescence changes are relatively large and fast (30-40% change within 30 min), a conventional method may be used for validation. The authors recorded activity and bioluminescence from non-circadian luminescence reporter mice (CAG -luc). Alternatively, the authors can analyze that data and exclude artifact possibility if luminescence change doesn't occur at active/inactive transitions.Another weakness is the PER2::LUC luminescence measurement from the brain. The authors must show IVIS imaging and show the signal coming from the brain and not from other tissues.Abstract: Line 18, 19: instead of saying PER2 increases or PER2 rhythmicity, I suggest using PER2::LUC luminescence increases, PER2::LUC luminescence rhythmicity.Line 89, Suppl. Figure 1: should be Suppl. Figure 3.Figure 1B: The hypnogram only includes sleeping and waking, please include REM and NREM. I understand that the authors only wanted to indicate sleep/wake transition used for the luminescence analysis indicated in C, but I think the authors should plot standard hypnogram.Figure 1C: To avoid confusion, it is better to use the same colors as in A and B .Figure 2: The authors should show individual records in the supplemental information. I know the authors discussed two possibilities that can explain changes in amplitude in group average data. The amplitude of an individual mouse was shown in Figure 2C. But I think, like me, the readers will still want to see the individual record. The amplitude of 3 cycles in REC should be analyzed separately . Technically REC day 1 is the same as SD, but it is good to show how the amplitude in the group average and the individual mouse declines.Line 573-584: This is an important discussion addressing the possible temperature artifact. However, all statements are based on analysis, "data not shown", unfortunately. The authors must show the data.Line 763: I think the activity data was binned, not averaged.Supplementary Figure 1: I know luminescence recording was done in DD, but please indicate this, as the lighting condition in the other treatments was stated.Supplementary Figure 3B: Please indicate individual records as well, so the relationship between luminescence and activity can be evaluated.Reviewer #3:Response to the comment #1It is my understanding that almost all of the conclusions made by the authors are based on the temporal correlation between kidney-derived bioluminescence and sleep-wake states. Therefore, I do not feel convinced about these conclusions without additional experimental evidence suggesting the causal link between spontaneous wakefulness and PER2 expression.A few previous studies, although not cited in the present version, clearly demonstrated that arousal levels affect the circadian clock via the SCN . I think that the present data may not make obvious progress from these previous achievements.Response to the comment #3The authors claim that spontaneous wakefulness-driven PER2 increase is one of the major findings. Therefore, under not sleep deprivation but spontaneous wakefulness conditions, they need to confirm PER2 expression in other organs and apply expression data to their mathematical model.Many previous studies have indicated that circadian phase in clock gene expression varies among peripheral organs and tissues, and it is therefore difficult to generalize the temporal correlation between single organ-derived bioluminescence and sleep-wake states to other peripheral and central clocks. In particular, circadian phase of the SCN is largely phase-advanced in comparison with that of peripheral clocks, raising a question on the author's thought that spontaneous wakefulness is a similar trigger of PER2 in both peripheral and central clocks.eLife. Your revised article has been evaluated by Kate Wassum (Senior Editor) and a Reviewing Editor.Thank you for resubmitting your work entitled "The sleep-wake distribution contributes to the peripheral rhythms in PERIOD-2" for further consideration by The manuscript has been improved but there are some remaining issues that need to be addressed, as outlined below:There are only two final pending issues that we anticipate should be easy to incorporate as part of the results/discussion and be included in the final rebuttal letter, without the need for any additional experiments.Essential revisions:1) Although the new data has clearly enriched the paper, this still raises the concern of one of the reviewers regarding the presence of low amplitude baseline rhythm in luminescence .2) Without showing an absolute luminescence value emitted from the brain, liver, and kidney in the same mouse, it cannot be utterly said that the luminescence signal from the entire mouse is just coming from the cortex. Part of this concern is based on the fact that the Curie et al., 2015 work not only shows signals (in B6 mice) coming from the cortex, but also clear signals coming from the kidney/liver .Reviewer #2:Hoekstra et al. investigated the relationship between sleep state and PER2::LUC luminescence in freely behaving mice and showed that luminescence acutely changed at sleep/wake transitions. The authors also showed that repeated daily sleep deprivation reinitiated the PER2::LUC luminescence rhythm in SCN ablated behaviorally arrhythmic mice. This re-initiated rhythm sustained a few cycles in constant conditions, indicating that sleep can synchronize (or coordinate) peripheral circadian oscillators.A strength of this study is the simultaneous recording of EEG/EMG/activity and PER2::LUC luminescence in freely moving mice.One obvious concern is that acute PER2::LUC luminescence changes occurring at sleep/wake transitions are artifacts , but not caused by the synthesis/degradation of PER2 protein. After two major revisions, the authors now provided the data showing that no luminescence change occurs at sleep/wake transitions in Pkg1-luc activity (housekeeping gene promoter activity measured by luminescence reporter). Although it is still difficult for this reviewer to believe 30-40% changes in PER2 protein can occur within 30 min in the brain and peripheral organs, the new Pkg1-luc data rejects the above-mentioned concern. The authors also provided an interesting new analysis that acute luminescence changes at sleep/wake transitions in CAG-luc mice are much faster compared to changes in PER2::LUC mice. The authors reasoned this by saying the CAG synthetic promoter is activated by transcription factors . This is an interesting result but raises a new concern. The authors used this CAG-luc mouse to optimize the luciferin administration method, as this is a non-circadian reporter. However, if being awake activates CAG promoter, this reviewer expects to see a basal circadian change of luminescence in CAG-luc mice.Another relatively minor concern is that the authors used PER2::LUC in pigmented C57BL/6 mice with a cranial window for "the central quantification of bioluminescence". This reviewer suggested the authors to perform IVIS imaging and show the signal coming from the brain and not from other tissues. Instead, the authors referred to their previous publication  that the luminescence signal is from the cortex. However, in this paper, the authors actually detected a signal from the liver and kidney as well. Because the authors only showed the hold changes in those tissues , it is not known how strong the signal from cranial windows compare to that from the liver and kidney. Without showing an absolute luminescence value emitted from the brain, liver, and kidney in the same mouse, the authors cannot say that the luminescence signal from the entire mouse is from the cortex.This reviewer appreciates the efforts of the authors to address the concerns raised by the reviewer.This reviewer can now recommend this work to be published in this journal. However, those two concerns need to be addressed.One additional suggestion is that it may not be clear to the reader that mice with a cranial window is used for measuring signal from the cortex. This is only mentioned in the methods section. It may be better to state this in the main text and figure caption. [Editors’ note: the authors resubmitted a revised version of the paper for consideration. What follows is the authors’ response to the first round of review.]Reviewer #1:In this paper entitled "The sleep-wake distribution contributes to the peripheral rhythms in PERIOD-2", the authors observed PER2 expression in peripheral tissues of freely behaving animals and found that the sleep-wake distribution contributes to the peripheral PER2 dynamics. In addition, implementing the mathematical model, they showed that the peripheral PER2 rhythms can be generated by two factors: a sleep-wake state dependent one and a peripheral (not master) circadian dependent one. Despite the difficulty to dissect the effect of these two factors in vivo, the authors, dealing with this problem by the unique experimental designs, provided direct evidence that sleep-wake state itself affects peripheral daily rhythms. However, this paper has a couple of points to be improved, which are summarized in the comments below.We thank the reviewer for his positive evaluation and particularly for stating that the results “provided direct evidence that sleep-wake state itself affects peripheral daily rhythms”, which is the central claim of our work. We also thank the reviewer for the suggestions to help improve our manuscript.1. As for Figure 1B, 1C and 1D, the authors showed PER2 bioluminescence changes according to circadian rhythm and state transitions in only one individual mouse (ID: 2MP82), which might be insufficient for concluding that the PER2 bioluminescence changes depending on the circadian and sleep-wake cycle. Thus, the reviewer suggests that the authors should add data about other mice and perform the statistical analyses to clarify the validity of the circadian- and sleep-wake-dependent change of PER2 bioluminescence. With Figure 4, the reviewer suggests the same, i.e., the authors should analyze not only one representative mouse but a group of mice.Indeed, Figure 1B and -C  represented an example of one mouse. Group means based on 5 mice were, however, depicted in Figure 1A and -D , as was mentioned in the figure legend, illustrated by the individual recordings of the 4 remaining mice in Suppl. Figure 3 , stated in the ‘transparent reporting’ form in our submission, and can be deduced from the raw data we provided for this and all other figures. The same holds true for Figure 4 where the model was based on recordings in 4 and 6 mice, respectively. In response to a suggestion from Reviewer 2, we have included a supplementary figure  with an overview of all experiments explicitly stating the number of animals used in each.Plus, there might be a mistake in the time label of Figure 1B (is this plot started from time = 6 or time = 0?).The plot starts at 12h, at a time of day that under the previous LD cycles is referred to as ZT12; i.e., the beginning of the dark phase. The tick and label indeed disappeared. This has been corrected in the revised version.2. In lines 202 to 205, the authors concluded that the behavioral rhythm reduction by 2hOnOff protocol appeared to be insufficient to consistently reduce the amplitude of the PER2-bioluminescence oscillation. However, it is difficult to follow its logic toward the conclusion. Thus, the reviewer recommends that the authors should describe their logic in more detail.We thank the reviewer for this suggestion. With the use of the word ‘appeared’ we hoped it was clear that this was an interpretation. Our logic was as follows: If the sleep-wake distribution contributes to the diurnal changes in PER2 bioluminescence then we can expect that after experimentally reducing the amplitude of the sleep-wake distribution, the amplitude of the PER2 oscillation will be reduced as a result. With the 2hOnOff protocol we reduced, but did not eliminate, the amplitude of the sleep-wake distribution. This reduction was however accompanied by a reduction of PER2 amplitude in only 4 of the 6 mice and we therefore concluded that the reduction in sleep-wake amplitude appeared to be insufficient to elicit the anticipated PER2 effects in all mice. We now have eliminated this interpretative sentence from the Result section.3. As for Figure 4 and Table 2, the authors compared two mathematical models and concluded that the two forces model has better prediction accuracy. However, it is unclear whether the circadian force itself or the combination of the two forces is important to predict PER2-bioluminescence dynamics. The reviewer suggests that the authors should add a comparison with a model that using a single circadian force (F = FPERI).Again, we thank the reviewer for this valuable suggestion. We have now performed the suggested additional analysis in the revised manuscript, illustrating better that both forces are needed and their combination represents an important statistical gain in predicting PER2. The results have been added to Figure 4B and C and are presented in the text (l. 326-332). We now extended the modeling to predict results of the 6h SD experiments using the parameters obtained in the other two experiments .4. In lines 277 to 280, the authors described the increase in PER2 amplitude during the 2hOnOff experiment by advancing the phase of FPERI by 6h. The reviewer suggests that the authors should clearly explain why they apply their mathematical model to the 6h advancing, although they observed 1-2h phase advance in their experiments.in silico experiments and, on the other hand, that the initial conditions could give rise to diametrically opposing results. We made this clearer in the manuscript. We have now regrouped this analysis together with the analysis mentioned under the preceding point 3, as one of three questions addressed by the model as in silico experiments (l. 356-379). In a re-analysis for the revised manuscript, we found that the same effect  could already be observed with a 2.5h phase advance. We have added this finding to the revised manuscript (l. 360-365) and illustrated this analysis in Suppl. Figure 7C.This analysis was meant as thought-experiment to illustrate on the one hand the power of our dynamic model to perform Reviewer #2:By measuring EEG/EMG and PER2::LUC bioluminescence  from freely behaving mice simultaneously or from separate cohort mice with similar conditions, the authors observed that sleep state acutely changed PER2::LUC bioluminescence, repeated daily sleep deprivation reinstated circadian PER2::LUC rhythm in SCN ablated behaviorally arrhythmic mice. The authors also did a mathematical simulation modeling peripheral PER2::LUC bioluminescence influenced by a sleep dependent force and a SCN independent force.I believe the data presented in the current manuscript, however, I don't think the main conclusions are supported by the data. The acute changes (within 30 min) of luminescence they observed is most likely caused by in vivo factors . It is very problematic to assess the amplitude change from averaged luminescence record from multiple behaviorally arrhythmic mice . Although the above mentioned two major conclusions must be removed from the manuscript, the study validates previously published results done by ex vivo tissue and in vivo anesthetized animal with luminescence measure from freely behaving mice. So I encourage the authors to publish the data to another journal , but I don't think discovery reported in the work is novel for the publication in eLife.We have addressed each of the issues mentioned in detail below. What the reviewer refers to as “very problematic” and “analysis flaw” could be easily addressed. Moreover, the reasons given to deem our bioluminescence signal as artifact are flawed.1. It is unlikely that the acute change of PER2::LUC luminescence reflects PER2 protein translation and degradation. As the authors refer to correctly, luminescence from PER2::LUC knockin mice reflects PER2::LUC fusion protein (not Per2 transcription). The authors didn't correctly refer to the studies measuring light induction of Per2 mRNA and protein in the SCN. The light induction of Per2 mRNA in the SCN can only be seen 60 min after onset of the light pulse . Increased PER2 protein in the SCN can only be seen at 4 h after the light pulse . Therefore, the acute luminescence change observed at sleep wake transitions  is unlikely reflecting changes in the PER2::LUC fusion protein. Temperature, pH, and Ca/Mg and ATP levels all strongly affect luminescence produced by firefly luciferase and luciferin. It was shown that the ultradian rhythm of the core body temperature closely matched the ultradian behavior rhythm (Blessing 2018 PMID: 30454601). The authors referred to their own published study that luminescence rhythm change was vilified by qPCR. However, the time scale of their published work showed that changes occurred after 6 h of sleep deprivation, not in the 30 min range.First, we have to correct two of the reviewer’s statements: (1) We did not claim that the literature showed that 30min light-pulses induce PER2 in the SCN and (2) we previously used western blot, and not qPCR, to validate the sleep-deprivation induced increases in PER2 bioluminescence in brain and liver.et al. (Nat Neurosci 2015), demonstrating that PER2 protein can indeed be rapidly induced through other means than light; i.e., within 30 min after a serum shock (see Discussion paragraph l. 400-414). The wake-related rapid induction of PER2 is an important novel aspect of our study. Whether the signal obtained with the PER2::Luciferase construct indeed reflects PER2 protein was already discussed in detail in the Discussion (“Do changes in bioluminescence reflect changes in PER2 levels?”).We are aware that no study has reported on such quick induction of PER2 after a light pulse. We did, however, not study light effects in the SCN, and the effects of wakefulness on PER2 in peripheral tissues are vastly under-explored and might differ from those of light in the SCN as a variety of molecular pathways activated by waking are known to affect PER2 (reviewed in the Discussion). The fact that in the literature there is no precedent of wakefulness rapidly inducing small but significant changes in PER2 using more conventional techniques, cannot be used as argument that we reported on a mere artefact. We already cited the study by Cao et al. reference mentioned by the reviewer and our own work: Hoekstra et al. eLife 2019), PER2-bioluminescence follows a much slower time course and initially continues to decrease before subsequently increasing . For this rebuttal we followed both central  and peripheral PER2-bioluminescence for as long as waking prevailed as opposed to the 1st 30min after wake onset only. The new analysis shows that peripheral PER2 increases and then again decreases with increasing wake duration, while central levels monotonically keep increasing consistent with the western-blot verified tissue-specific effects of experimentally prolonging wakefulness . These results further underscore that changes in PER2 bioluminescence do not follow wake related changes in temperature. We have replaced the transition analyses in Figure 1C with this new analysis.Although the variables listed by the reviewer do affect the bioluminescence reaction, they seem not to play a large role (see Discussion section: ‘Do changes in bioluminescence reflect changes in PER2 levels?’). The reviewer’s example of a potential temperature effect can illustrate this. Body temperature changes in a circadian fashion, yet the bioluminescence time courses reporting on clock genes known to be regulated in anti-phase, remain anti-phasic and do not simply follow the temperature dynamics. Also the lack of a noticeable rhythm in the CAGbioluminescence signal  confirms that the circadian rhythm in activity and associated temperature changes have little or no effect . We have added this observation to the Discussion (l. 577-579). While temperature increases quickly (within minutes) after awakening and stays high while awake (see the Blessing 2. The advantage of continuous luminescence measurement from the same mouse is that the presence and absence of the rhythm can be determined from a mouse that has no phase marker (e.g. SCN lesioned mice). Arrhythmicity (or lowered amplitude of the rhythm) observed by conventional population sampling (from multiple mice) cannot be determined if individual mice lose rhythmicity, or if individual mice retained intact rhythm but they are out of sync. From the data presented in Figure 2, the authors claimed repeated sleep deprivations reinstated the rhythm, but they didn't analyze amplitude change before, during, and after sleep deprivation in individual mice .The authors stated that they performed daily sleep deprivation to the mice 5 weeks after SCN-lesioned. From average luminescence rhythms of 4 SCN-X mice, the authors cannot conclude their main claim that sleep deprivation reinstated the peripheral circadian rhythm. It is possible there is no change in the amplitude of individual peripheral circadian oscillators, but repeated sleep deprivation entrained those rhythms .We thank the reviewer for raising this issue. We had provided the individual amplitude information for the baseline bioluminescence rhythms of the SCNx mice in the first version of our manuscript , but indeed did not include this information during and after the sleep deprivations. As mentioned in our reply to minor issue 1 from Reviewer 1, we have added these data to main Figure 2C. The results clarified that increased amplitude during the sleep deprivations does not simply result from a phase alignment as it is significantly larger than in the baseline recordings. This analysis and conclusion has now been added in the Results (l. 206-210).It is well known that the SCN-lesioned mice do not show a daily rhythm under LD cycle (Light cannot reinstate behavior rhythm).et al. PNAS 2021 in press; bioRxiv).We did not make this claim in the manuscript and therefore fail to see the relevance of this comment. Moreover, the literature indicates that this claim is less well-known as the reviewer makes us believe . Light is an important driver of rhythmic sleep-wake behavior .We did analyze the amplitude changes at the group level by comparing PER2 amplitude under baseline with the 2hOnOff regime, and mentioned the results in the figure legend  along with the statistics. In the Results section, the lack of an overall effect was reiterated twice. We now have added the mean values and the SEMs to the figure legend for additional clarity.4. Because of the issues pointed out above, the parameters used for the mathematical simulation are not valid.The reviewer claims the parameters for the simulation are not valid, but does not explain how he or she arrives at this conclusion. Many issues were raised in the preceding three points, none of which make reference to the model. We will not try and guess what the reviewer might have meant especially since we have now addressed the issues pointed out above.Use of locomotor activity as a wake parameter is also not appropriate. Mice can be wake without moving.2=0.79) which we presented in Suppl. Figure 5A , confirming that the two variables strongly covary. Moreover, from a modeling perspective the important point is not whether locomotor activity one-to-one relates to waking but that the time courses of the two variables match. We have added another panel to this supplementary figure illustrating the time course of LMA and waking to underscore their similarity . Finally, we now have modelled PER2 dynamics in the 6h SD experiments based on either wakefulness or LMA. Both resulted in similar tight fits. These findings were added to the results and Suppl. Figure 6C. To conclude, in the context of the model, locomotor activity is a highly appropriate proxy for the sleep-wake distribution.Indeed, locomotor activity can importantly deviate from time-spent-awake in certain situations. This was however not the case in the current experiments as could be deduced from the very strong positive correlation between waking and LMA  of procedures in each experiment.We thank the reviewer for this useful suggestion and we have included the suggested figure as Suppl. Figure 1.6. Since in vivo bioluminescence recording became popular technology, I strongly suggest the authors move the data presented in supplementary Figure 2 to the main text as an actual figure. Were CAG mice also crossed with hairless strain? Does tissue explanted from this mouse in vitro not show a circadian rhythm? It even looks like luminescence from the mice with luciferin supplemented by osmic pump shows a weak rhythm. I wonder if CAG promoter may have circadian rhythm as CMV promoter does . Amplitude of activity rhythm is lowered in mice with pump. Is this due to surgery (pump implantation)? If so, lowered amplitude of luminescence rhythm might also be affected by surgery. Having a control  is necessary.Although the many suggested follow-up experiments related to the results obtained in the CAGmice have their merit, addressing them experimentally is clearly far removed from the aims of our manuscript and would be more appropriate for a separate, technical paper. With a straightforward and unique approach, we show that administering the luciferase substrate in the drinking water gives rise to high-amplitude bioluminescence rhythms that all but disappear when using mini-pumps. The by far most plausible explanation is that the large-amplitude rhythms are an artefact associated with the circadian timing of water intake (and thus luciferin availability) and that therefore mini-pumps are to be preferred to administer the substrate.Indeed, a small yet significant bioluminescence rhythm is present in CAG mice implanted with mini-pumps which does, however, not challenge our choice of route of administration. Moreover, this residual bioluminescence rhythm peaks 6.3 circadian hours prior to when the activity rhythm peaks and bioluminescence thus decreases when animals are awake most, again demonstrating that changes in bioluminescence do not simply follow changes in e.g. body temperature associated with the circadian sleep-wake distribution.The reviewer claims that the amplitude of the activity rhythm in mice implanted with minipumps is lower. Statistics fail to support the reviewer’s claim .Reviewer #3:This is an interesting study. As far as I know, there are no previous studies performing simultaneous measurement of sleep-wake state and bioluminescence (clock gene expression) in freely moving mice. In addition, their measurement method was well validated through several pilot studies, and measurements obtained using this method are therefore reliable. In fact, the presented data are clear and convincing. However, although I have no doubt that the results are useful and valuable for a wide range of circadian scientists, I feel the present version of their work may not be a strong candidate for publication in this journal because of insufficient novelty and impact.We thank the reviewer for judging our work well validated and our data reliable, clear, and convincing. Our study is indeed the first to simultaneously record EEG/EMG and bioluminescence, as well as locomotor activity allowing to show that undisturbed sleep-wake behavior contributed to PER2 dynamics.1) The results clearly revealed the temporal relationship between sleep-wake state and PER2 bioluminescence through simultaneous monitoring in freely moving mice, with high time resolution. However, because previous studies have already found that sleep deprivation results in a change in PER2 levels, I feel that the present study does not make obvious progress toward further understanding the mechanism. The simultaneous monitoring experiments are interesting but each of the techniques was originally established by other groups. For example, some findings related to the identification of systemic or molecular pathways controlling PER2 expression during sleep deprivation may be required.eLife by referring to previous sleep-deprivation studies. In doing so, the reviewer overlooked an important novel aspect of our current study: we are the first to have quantified the relationship between spontaneous sleep-wake behavior and PER2-bioluminescence, whereas our previous work only assessed the effects of sleep deprivation. We discovered that like sleep deprivation, also spontaneous wakefulness, raises PER2 levels. The finding that PER2’s increase is associated with wakefulness per se and does not result from confounding physiological changes accompanying the sleep deprivation , is a core assumption of the mathematical model which, with high accuracy, could predict PER2’s behavior under three challenging experimental protocols. Thus, the circadian distribution of sleep-wake behavior under undisturbed conditions, considered by most a mere output of the clock, modulates the circadian time-keeping circuitry and is required to maintain high-amplitude PER2 oscillations. We believe this to be a major advance in understanding circadian-rhythm generation in tissues peripheral to the SCN as it challenges current dogma of the clockgene circuitry being responsible for all rhythmic gene expression, including clock genes themselves. In the Discussion we had already reviewed the molecular pathways by which sleep-wake state could affect the clock-gene circuitry. We recently published on one of these pathways  through which the sleep-wake distribution could modulate clock-gene expression outside the SCN. We now have put more emphasis on the importance of spontaneous sleep-wake behavior on PER2 bioluminescence rhythms and added an analysis documenting this further (l. 344-353).The reviewer states our work lacks the novelty that would justify publication in 2) Although a detailed description of the method for sleep deprivation is important, I was not able to find it in the main text.We indeed did not describe the sleep-deprivation method in detail but referred to our sleep- phenotyping methods paper instead [“…mice were sleep deprived for six hours at a time they were expected to rest (….) by gentle handling as described ”]. We have expanded on this method in the revised manuscript (l. 683-689).The authors should clarify whether sleep deprivation itself or other factors such as stress signals triggered by sleep deprivation affect PER2 expression. At this time, I feel not sleep deprivation per se but some stress signals affect PER2 expression. Many previous studies have shown that glucocorticoids, well-known stress hormones, strongly affect peripheral clocks. Sleep deprivation, one of the stimuli activating stress signals, may therefore affect PER2 expression in peripheral clocks via glucocorticoid signaling pathways. The contribution of glucocorticoids to PER2 expression during sleep deprivation can be examined simply through surgical removal of the adrenal glands.et al. Sleep 2010). This study shows that the increase in Per2 expression during sleep deprivation is not solely due to the sleep-deprivation associated corticosterone increase as in adrenalectomized mice sleep deprivation still significantly increases Per2 levels. These results, together with the results obtained after spontaneous periods of waking (which are not accompanied by an increase in corticosterone) presented in the current study, strongly argue against the simple scenario proposed by the reviewer. These issues are addressed in the Discussion (l. 499-511).Short-term sleep deprivation by gentle handling is indeed considered a mild stressor and corticosterone does increase as we had already clarified in the Discussion (“How does wakefulness increase PER2?”). We published the experiment the reviewer suggested a while ago (Mongrain 3) Their conclusions may be specific to the kidney. All bioluminescence data were obtained through monitoring only the kidney. The authors should justify why they can conclude that sleep deprivation affects "peripheral clocks" only judging from kidney data. To generalize kidney data to other peripheral clocks, they should repeat similar experiments using at least another organ or tissue. Real-time monitoring of bioluminescence from the liver is technically simple because injected adenoviruses (carrying a reporter gene driven by a clock gene promoter) specifically infect the liver.et al. Sleep 2015), using an in vivo imaging approach, we already demonstrated that sleep deprivation increases PER2 in cortex, liver, and kidney, which, for cortex and liver, were confirmed by western blot. The baseline and recovery bioluminescence dynamics obtained in central and peripheral tissue with the RT-Biolumicorder depicted in Figure 1A match remarkably well those reported for cortex and liver and kidney, respectively, with the in vivo imaging method. We are therefore confident that the effects we report can be generalized to other organs peripheral to the SCN.In an earlier publication  PER2bioluminescence together with EEG/EMG in 6 C57BL/6J PER2::LUC mice. Because detected bioluminescence levels were somewhat noisier (l. 167-169), for the original manuscript we decided to focus on the better accessible (hairless SKH1 mice) and more robust peripheral (kidney) signals. Nevertheless, also the cortical bioluminescence signals demonstrate that the results we reported are not specific to kidney, albeit with tissue-specific dynamics during spontaneous wake episodes. We have included these central data in Figure 1 and addressed the tissue-specificity in the Discussion (l. 531-551).[Editors’ note: what follows is the authors’ response to the second round of review.]Reviewer #1:In this paper entitled "The sleep-wake distribution contributes to the peripheral rhythms in PERIOD-2", the authors attempted to find the factor(s) directly contributing to clock gene expression in peripheral tissues. To achieve that, they observed PERIOD-2 (PER2) expression in peripheral tissues of freely moving mice and developed new mathematical models to analyze them. They found that the sleep-wake distribution correlates to the peripheral PER2 dynamics, and that the peripheral PER2 rhythms can be predicted by sleep-wake-state- and peripheral-circadian-dependent factors. Despite the difficulty to dissect the effects of circadian and the sleep-wake cycle on gene expression in vivo, they provided direct evidence that the sleep-wake cycle itself affects peripheral daily rhythms by the unique experimental designs. However, there are still a few points to be addressed before publication including a detailed validation of the PER2 bioluminescence system, which would further support their conclusion.All things considered, their findings will have an impact on the chronobiology field, as giving direct evidence on sleep-wake-state-dependent regulation of peripheral clock gene expression. In addition, those methods can be useful to investigate the gene expression not only in the kidney or cerebral cortex but also in other various tissues of freely moving mice.In the revised paper, the authors addressed almost all our concerns with proper correction and additional analyses, but it has some points to be improved before publication, which are summarized in the comments below.1. The authors assumed that PER2 bioluminescence directly reflected expression of PER2 protein, but it has not been fully confirmed yet especially in the fast (within an hour) dynamics. For further progress of the method, the combination with other techniques to quantify fast and small (< 10%) protein changes would be required, as the authors mentioned in the paper.technology. This latter point is important when assessing the effects of spontaneous wakefulness on PER2 as this would require each animal to be closely monitored  for periods of either sleep or wake of similar duration to appear at approximately the same circadian phase, before rapidly killing the mouse for tissue extraction such that waking up (if asleep) and stressing the animal does not affect the measurement. Moreover, because of the semi-quantitative nature of Western blots, small effect size, and group instead of within-subject comparisons, we would need to kill a large number of mice for quantifying PER2 for each time point and a time course analyses, as presented here, would be practically impossible. For these reasons, we decided to analyze bioluminescence dynamics in mice with other luciferase reporter constructs to rule out nonspecific sleep-wake related effects on the bioluminescence reaction. See our response to the first comment by Reviewer 2 below.We fully agree with the reviewer and if techniques were available that could reliable quantify the small but significant changes in protein levels that we reported on, we would have readily used them. However, for several reasons this is less straightforward as it might seem: (i) Western blots are not sensitive enough to pick up such small differences as this method is semi-quantitative at best and (ii) the design can no longer be longitudinally  in contrast to our current in vivo 2. This reviewer suggests that the authors should discuss about the controversial results regarding PER2-bioluminescene amplitude and sleep-wake distribution in Figure 3 and Suppl. Figure 7. When the amplitude of the sleep-wake distribution was reduced, PER2-bioluminescence amplitude was reduced in 4/6 mice as the model expected, while it was increased in 2/6 mice.in silico analysis and, as we pointed out in that section, it is clear that this hypothesis must be tested by follow-up experiments before making any firmer claims.We believe that, given the data, we went as far as we could in trying to explain these counterintuitive results. Our model gave us a tool to investigate this issue and the simulation results suggest that the phase of the circadian force relative to the phase of the wake force could be a contributing factor. This scenario was presented and discussed in detail in the Results section (Lines 386-410). However, this explanation follows from an 3. Regarding Figure 3E, the authors showed that the 2hOnOff protocol decreased the amplitude of sleep-wake distribution. However, the sleep-wake distribution during the recovery phase was not assessed. Thus, the reviewer recommends that the authors should add data of recovery day to Figure 3E and compare it to the PER2 bioluminescence trends .We recorded recovery after the 2hOnOff protocol, but did not further analyze the sleep-wake distribution during this period. Following the reviewer’s recommendation, we now have analyzed sleep-wake states for 48h of recovery and added the estimated amplitude of the sleep-wake distribution during these two recovery days to Figure 3E. After the reduction of the daily sleep-wake amplitude during the 48h 2hOnOff experiment, during recovery amplitude was restored to baseline levels.4. In lines 290 to 294, the authors concluded that the prediction from the model, the behavioral rhythm reduction reduces PER2 bioluminescence amplitude, which is consistent with their observation in the Figure 3. However, this conclusion could be difficult to understand because the 2hOnOff protocol increases the PER2 bioluminescence amplitude in one-third of mice . The authors provided an additional model  to explain the individual difference, and thus the reviewer suggests the authors to describe that conclusion after the modeling part to make the logic clearer.5. Regarding Suppl. Figure 7A-C, the authors described the increase in PER2 amplitude during the 2hOnOff experiment by advancing the phase of FPERI more than 2.5h. The reviewer suggests that the authors could mention these results in Results or Discussion section.in silico experiment in the Results section after the modeling part (Lines 386-410). To enhance clarity, we have now commented after line 256 (now Lines 260-263) on the results of the modelling section, stating that variation in circadian phase could underlie the differential individual response.At the group level the reduction in PER2 amplitude during the 2hOnOff protocol did not reach significance, as was clearly stated in the Results section and figure legend. Yet, when inspecting the individual responses, we found an interesting pattern suggesting that the 2hOnOff protocol did affect PER2 amplitude albeit in opposite direction for individual mice (Lines 251-261). With the analysis presented in Suppl. Figure 7A-C , we did not introduce an additional model to explain this phenomenon. Instead, we used the same model as proposed earlier, but instead of letting the model determine a single  phase of the circadian force, we systematically varied it to predict the resulting effects on PER2 amplitude. We described the rational and results of this Reviewer #2:Hoekstra et al. investigated the relationship between sleep state and PER2::LUC luminescence in freely behaving mice and showed that luminescence acutely changed at sleep/wake transitions. The authors also showed that daily sleep deprivation enhanced the PER2::LUC luminescence rhythm amplitude in SCN ablated mice.A strength of this study is the simultaneous recording of EEG/EMG/activity and PER2::LUC luminescence in freely moving mice.Weakness: One obvious concern is that acute PER2::LUC luminescence changes occurring at sleep/wake transitions are artifacts (e.g. due to acute change in core body temperature), but not caused by synthesis/degradation of PER2 protein. Because those luminescence changes are relatively large and fast (30-40% change within 30 min), a conventional method may be used for validation. The authors recorded activity and bioluminescence from non-circadian luminescence reporter mice (CAG -luc). Alternatively, the authors can analyze that data and exclude artifact possibility if luminescence change doesn't occur at active/inactive transitions.Thank you for this great suggestion. With the reviewer we would have preferred to use a conventional method for confirmation but as explained in our answer to the first comment of Reviewer 1 this is unfortunately less straightforward as it might seem.LucPER2 mice. This result is consistent with the CMV major-immediate early enhancer/promotor, which is part of the CAG synthetic promotor driving luciferase, being rapidly activated by large number of transcription factors such as NF-κB, CREB/ATF, and AP-1 , a response comparable to that of an immediate early response such as c-FOS 00178-9 and Collaco and Geusz BMC Physiol. 2003; doi: 10.1186/1472-6793-3-8).Following your suggestion, we analyzed bioluminescence dynamics at the onset of activity bouts in the CAG-Luc mice. As you can see in and the new Figure 1 —figure supplement 5, activity bouts in CAG-Luc mice are accompanied by robust increases in bioluminescence, even larger in amplitude than those observed in Pgk1 (Pkg1-Luc mice). As expected of a housekeeping gene, overall bioluminescence levels do not consistently vary during the recording and no activity-bout related changes were observed . These recordings demonstrate that the increases in PER2 bioluminescence we observed at sleep-wake transitions are not an artifact of the sleep-wake transition as similar activity-related increases should have been observed for all 3 constructs. We have added the Pgk1-Luc results together with the CAG-Luc results to the Results section (Lines 177-182) and added a new supplementary figure . For details on the Pgk1-Luc mice see Methods.We used the CAG-Luc mice to verify the effect of the route of luciferin administration on circadian bioluminescence dynamics because we expected this synthetic promotor not to be regulated in a circadian fashion (which we confirmed). We did, however, not chose this mouse line to rule out that PER2bioluminescence changes at sleep-wake transitions are artefacts, an issue that was raised during the review process. After discussing this issue with Prof. David Gatfield, a colleague at my institute studying circadian aspects of translation, he shared some of his recordings with other luciferase-reporter constructs using the same set-up . We recorded bioluminescence in mice expressing luciferase under the control of the promotor of the housekeeping gene Another weakness is the PER2::LUC luminescence measurement from the brain. The authors must show IVIS imaging and show the signal coming from the brain and not from other tissues.et al. Sleep; 2015 doi: 10.5665/sleep.4974). As described in the Results section these experiments were performed in C57BL6/J mice with pigmented pelage absorbing emitted photos. In addition, the substrate luciferin was administrated only centrally and the by far largest  source of photons in this setup is the glass cone directly mounted on top of the skull over the left cortical hemisphere. Moreover, in the same publication in situ immune-histofluorescence indicated the cerebral cortex as the main source of the almost 2-fold increase in brain bioluminescence after a 6h sleep deprivation. This work was cited when we first stated that brain signal represents cortical activity but now have stated this more explicit (Lines 126-130).We performed the experiment the reviewer suggested in a previous publication using IVIS imaging  here but now have added the reference to the other figure as suggested.Figure 1B: The hypnogram only includes sleeping and waking, please include REM and NREM. I understand that the authors only wanted to indicate sleep/wake transition used for the luminescence analysis indicated in C, but I think the authors should plot standard hypnogram.As the reviewer noted, this is not a classical hypnogram but our way of indicating which sleep-wake and wake-sleep transitions met our criteria and contributed to the analyses. In the manuscript we made no statements on the two substates of sleep (REM sleep and NREM sleep), and their respective possible effects on PER2 bioluminescence. Moreover, adding separate tracks for REM sleep and NREM sleep will clutter the figure and might confuse the reader. We therefore prefer to keep the figure as is but we now give values of REM sleep and NREM sleep obtained in the recordings on which Figure 1B is based in the text (Lines 122-125) to assure the reader that NREM and REM sleep were expressed at expected quantities under the different recording conditions.Figure 1C: To avoid confusion, it is better to use the same colors as in A and B .In this figure panel we now have used the same red and purple hues for peripheral and central transition data, respectively.Figure 2: The authors should show individual records in the supplemental information. I know the authors discussed two possibilities that can explain changes in amplitude in group average data. The amplitude of an individual mouse was shown in Figure 2C. But I think, like me, the readers will still want to see the individual record. The amplitude of 3 cycles in REC should be analyzed separately . Technically REC day 1 is the same as SD, but it is good to show how the amplitude in the group average and the individual mouse declines.We have added these data to Figure 2 —figure supplement 2.Line 573-584: This is an important discussion addressing the possible temperature artifact. However, all statements are based on analysis, "data not shown", unfortunately. The authors must show the data.We have added these data to the new Figure 1 —figure supplement 6.Line 763: I think the activity data was binned, not averaged.We indeed binned the data into (circadian) hourly intervals. However, values in corresponding circadian hours were then averaged across individuals. We have now specified this (see Lines 818-820).Supplementary Figure 1: I know luminescence recording was done in DD, but please indicate this, as the lighting condition in the other treatments was stated.We have added this information to the figure.Supplementary Figure 3B: Please indicate individual records as well, so the relationship between luminescence and activity can be evaluated.We have now provided an example of individual recordings of the CAG-Luc bioluminescence in Figure 1 —figure supplement 5, as well as an assessment of the association between changes in activity and bioluminescence in the CAG-Luc mice.Reviewer #3:Response to the comment #1It is my understanding that almost all of the conclusions made by the authors are based on the temporal correlation between kidney-derived bioluminescence and sleep-wake states. Therefore, I do not feel convinced about these conclusions without additional experimental evidence suggesting the causal link between spontaneous wakefulness and PER2 expression.Response to the comment #3The authors claim that spontaneous wakefulness-driven PER2 increase is one of the major findings. Therefore, under not sleep deprivation but spontaneous wakefulness conditions, they need to confirm PER2 expression in other organs and apply expression data to their mathematical model.We had already included brain (cortex) derived PER2-bioluminescence dynamics at sleep-wake transitions in our revised manuscript submitted in May 2021 . As similar dynamics were observed at sleep-wake transitions in both cortex and kidney, we demonstrate that our observations go beyond the kidney and also beyond a mere correlation as PER2 bioluminescence consistently follows spontaneous as well as experimentally induced wakefulness in both tissues. Moreover, we were able to predict the brain dynamics of PER2 with the model parameters set for kidney (Lines 329-331), confirming that at least mathematically sleep-wake driven PER2 dynamics in kidney and cortex underlie similar  rules. See next our reply concerning the phase of the SCN.A few previous studies, although not cited in the present version, clearly demonstrated that arousal levels affect the circadian clock via the SCN . I think that the present data may not make obvious progress from these previous achievements.et al., Gen Dev 2000; doi: 10.1101/gad.183500), does not affect clock-gene rhythms in the SCN in the mouse (see Discussion Lines 520-521). Therefore, at least under entrained conditions, the phase of clock-gene rhythms in the SCN remains locked to the light-dark cycle, while phase in tissues peripheral to the SCN (including the cortex) can be dissociated from that in SCN by e.g. an altered sleep-wake distribution.The reference mentioned does not take position on clock-gene rhythms because their expression was not quantified. Our work highlights the importance of the sleep-wake distribution when evaluating clock-gene rhythms in tissues peripheral to the SCN (including the cortex) in the mouse. Moreover, altered ‘arousal levels’ such as associated with a sleep deprivation  or with food-restriction conditions, which redistributes activity patterns  Although the new data has clearly enriched the paper, this still raises the concern of one of the reviewers regarding the presence of low amplitude baseline rhythm in luminescence .versus osmotic mini-pumps) was best.This might indeed be expected provided that the CMV activation upon waking up (i) does not vary with circadian time and (ii) does not again decreases as wakefulness progresses. From the example in Figure 1 —figure supplement 5 it seems that the wake-related activation is strongest after consolidated bouts of sleep (i.e. rest phase), and weakest during the active phase, when the fewer and shorter periods of sleep do not appreciatively decrease the CAG-luc signal. Therefore, although CAG-luc bioluminescence increases after sleep-wake transitions, a circadian modulation in this response might explain the lack of a robust modulation of the average hourly bioluminescence levels. If examining the precise dynamics linking the bioluminescence signal of this synthetic promotor to the sleep-wake distribution is considered of interest by the scientific community, this should be addressed experimentally – however this clearly falls outside the scope of our PER2 work. We only invested in recording CAG-luc mice to assess which route of luciferin administration (drinking water 2) Without showing an absolute luminescence value emitted from the brain, liver, and kidney in the same mouse, it cannot be utterly said that the luminescence signal from the entire mouse is just coming from the cortex. Part of this concern is based on the fact that the Curie et al., 2015 work not only shows signals (in B6 mice) coming from the cortex, but also clear signals coming from the kidney/liver .et al. 2015 publication we indeed recorded bioluminescence in the brain, liver, and kidney of B6 mice. However, recording of peripheral and central signals has to be done in separate animals for two reasons. First, where luciferin is delivered  is key to where bioluminescence is detected, as luciferin does not readily cross the blood-brain barrier . To further facilitate central detection of bioluminescence, a glass cone was directly mounted on a thinned skull allowing passage of photons generated by the underlying cortex. Second, the body of the B6 mice, the strain we used specifically to detect central PER2 bioluminescence, was not shaved, thereby preventing the release of photons. In B6 mice thus prepared , the PER2-bioluminescence signal by and large represents photons emitted by the brain . The tissue-specific PER2-bioluminescence dynamics observed after sleep deprivation, which were confirmed by western blot analyses and brain immune-histofluorescence, confirm that the bioluminescence originated from different sources. We now have further emphasized in the Results section the specific preparation of the animals used to record central PER2 bioluminescence (Lines 102-106), detailed the IVIS imaging experiment in the Methods (Lines: 681-686), and added to Figure 1 —figure supplement 2 the image of central bioluminescence detected with the IVIS setup, clearly showing that besides the head no other above-background signal could be detected from the animal.In the Curie