Introduction

The circadian clock orchestrates a range of behaviors, physiological processes, and cellular and biochemical activities in organisms with approximately 24-hour rhythms, facilitating adaptation to environmental changes (Bell-Pedersen et al., 2005). In mammals, the master clock localized in the suprachiasmatic nucleus (SCN) of the anterior hypothalamus synchronizes peripheral tissue clocks throughout the body to the light/dark cycle (Mohawk et al., 2012). The circadian clock’s molecular mechanism is driven by a transcriptional translational feedback loop (TTFL). CLOCK and BMAL1 form a heterodimer that triggers expression of the repressor genes, Period (Per) and Cryptochrome (Cry), along with other clock-controlled output genes. PER and CRY proteins then translocate to the nucleus, where they interact with CLOCK/BMAL1, halting further transcriptional activation. A secondary feedback loop involving the interplay between transcriptional activation by ROR and repression by REV-ERB finely regulates the rhythmic transcription of Bmal1 (Takahashi, 2017). Recent studies have revealed that the circadian clock controls the rhythmic transcription of numerous genes, displaying notable tissue specificity. This characteristic underscores the time-of-day-specific functional specialization of diverse tissues (Mure et al., 2018; Zhang et al., 2014). Consequently, circadian clock-controlled genes significantly influence various physiological processes including development, metabolism, aging, and neurodegeneration (Lananna & Musiek, 2020; Reinke & Asher, 2019; Schultz & Kay, 2003).

Astrocytes, the most abundant glial cells in the CNS, play vital roles in maintaining homeostasis of extracellular fluids, ions, and neurotransmitters; proving energy substrates to neurons; regulating local blood flow; modulating neuronal activity through gliotransmission; and assisting in interstitial fluid drainage (Sofroniew & Vinters, 2010). Though not electrically excitable, astrocytes exhibit complex intracellular Ca²⁺ signaling, both spatially and temporally, within individual astrocytes and across astrocytic networks. Astrocytes express various types of Gq-coupled receptors activated by neurotransmitters such as ATP, epinephrine, glutamate, and dopamine etc. (Verkhratsky & Nedergaard, 2018). Activation of these Gq-coupled receptors initiates the inositol 1,4,5-trisphosphate receptor (IP₃R) signaling cascade, causing a release of Ca²⁺ from the ER that substantially increases intracellular Ca²⁺ levels (Guerra-Gomes et al., 2017; Verkhratsky & Nedergaard, 2018). Increases in intracellular Ca²⁺ in astrocytes are involved in regulating numerous afore-mentioned processes (Giaume et al., 2021; Verkhratsky & Nedergaard, 2018). Recent studies have shown that astrocyte Ca²⁺ signaling can regulate circadian rhythms and sleep patterns (Bojarskaite et al., 2020; Brancaccio et al., 2019).

Accumulating evidence underscores the importance of the circadian clock in astrocytes function. Cultured murine cortical astrocytes expressing a PER-luciferase reporter (PER::LUC) exhibit circadian oscillations and can be entrained by temperature cycle (Prolo et al., 2005) and vasoactive intestinal polypeptide (VIP), which synchronizes SCN (Marpegan et al., 2009). These findings provide strong evidence that a molecular clock operates in astrocytes. In addition, disruption of clock genes specific to astrocytes has been linked to a range of deleterious effects, including excessive astrocyte activation, disruptions in daily activity patterns, impaired learning, metabolic imbalances, and a shortened lifespan (Barca-Mayo et al., 2020; Barca-Mayo et al., 2017; Griffin et al., 2019; Lananna et al., 2018). Remarkably, these phenotypic changes closely resemble those observed in astrocytes during the progression of neurodegenerative diseases (Brandebura et al., 2023; Phatnani & Maniatis, 2015). Moreover, the rhythmic metabolic activity of astrocytes, including intracellular Ca²⁺ fluctuations and neurotransmitter release, is critical for circadian timing in the SCN (Brancaccio et al., 2017). Despite the emerging significance of circadian rhythms in astrocyte function in health and disease, our understanding of the link between the circadian clock and specific astrocytic functions is still limited.

In this study, we conducted a transcriptome analysis to investigate how the circadian clock regulates astrocyte function. Our research uncovered that Herp (homocysteine-inducible ER protein with ubiquitin like domain 1; Herp) exhibited a BMAL1-dependent rhythmic expression, peaking at subjective midday phase and reaching its nadir at subjective midnight phase. HERP was crucial for ER Ca²⁺ regulation by modulating the degradation of ITPRs. Importantly, the ATP-stimulated ER Ca²⁺ response varied according to time post synchronization, a dependence that was absent in cultured astrocytes from Bmal1^-/-mice. Furthermore, the pronounced release of Ca²⁺ during the subjective night phase led to robust phosphorylation of the Ser368 residue of CX43, diminishing cell-to-cell communication between astrocytes. Overall, our study demonstrates that the circadian clock orchestrates a variety of astrocytic processes including Ca²⁺ homeostasis by controlling the rhythmic transcription of genes, highlighting its pivotal role in CNS function.

Results

Defining circadian rhythmic transcripts in cultured mouse cortical astrocytes

To understand how the circadian clock regulates astrocyte physiology, we conducted a circadian transcriptome analysis of cultured mouse cortical astrocytes. Cultured astrocytes were synchronized using serum shock (SS) and harvested every 4hrs for 2 days starting at 12hrs post-SS. The time series astrocyte transcriptome was determined by RNA-seq (Figure 1A). Using a Gaussian mixture model, we defined expressed transcripts, choosing 0.577 transcripts per million (TPM) as the cut-off, corresponding to the 1% threshold in the distribution curve of highly expressed genes (Figure 1-figure supplement 1A). A total of 17,671 transcripts with the highest TPM values of the 12 time points exceeding 0.577, were considered expressed. To validate astrocyte enrichment, we compared the expression of marker genes for nervous cells. Our transcriptome data were replete with astrocyte markers but lacked markers for microglia, oligodendrocytes, neurons, and endothelial cells (Figure 1-figure supplement 1B).

Figure 1.

Various methods have been used to identify periodicity in time-series data, such as Lomb-Scargle (Glynn et al., 2006), JTK_CYCLE (Hughes et al., 2010) and ARSER (Yang & Su, 2010), each with distinct advantages and limitations. MetaCycle, integrates these three methods, facilitating the evaluation of periodicity in time-series data without requiring the selection of an optimal algorithm (Wu et al., 2016). Additionally, BioCycle has been developed using a deep neural network trained with extensive synthetic and biological time series datasets (Agostinelli et al., 2016). Because MetaCycle and Biocycle identify periodic signal based on different algorithms, we applied both packages to identify periodicity in our time-series transcriptome data. BioCycle and MetaCycle analyses detected 321 and 311 periodic transcripts, respectively (FDR corrected, q-value < 0.05) (Figure 1B). Among these, 220 (53.4%) were detected by both methods, but many transcripts did not overlap. MetaCycle is known for its inability to detect asymmetric waveforms (Mei et al., 2020). In our analysis, genes with increasing waveforms like Adora1 and Mybph were identified as rhythmic only by BioCycle, while Plat and Il34 were identified as rhythmic only by MetaCycle (Figure 1-figure supplement 1C). Despite these discrepancies, the clear circadian rhythmic expression profiles of these genes led us to conclude that using the union of the two lists compensates for the limitations of each algorithm. Consequently, we identified a total of 412 circadian rhythmic transcripts (2.3% of all transcripts) (Supplementary file 1). The circadian oscillations of these transcripts are illustrated in the heatmap in Figure 1-figure supplement 1D.

Next, we compared rhythmic transcripts of astrocytes with those of 12 mouse tissues from CircaDB (Zhang et al., 2014), a database of circadian rhythmic genes (Figure 1C). A majority of the rhythmic transcripts in astrocytes (265 of 412, 65.3%) were not rhythmic or were rhythmic in one tissue. 14 transcripts were rhythmic in more than 10 tissues; most of these were core clock genes except Tspan4, Tsc22d3, and Wee1. This result is consistent with previous reports of tissue-specific circadian rhythmic expression (Mure et al., 2018; Panda et al., 2002). A phase comparison of these 14 common oscillating transcripts between CircaDB and our analysis showed a consistent time difference, with 8hrs after SS corresponding to ZT0 (Figure 1D). An additional phase comparison of 82 transcripts that overlapped in only one tissue indicated a very robust phase correlation between astrocytes and the corresponding tissue (r = 0.69, p < 0.001) (Figure 1E). Collectively, our analysis indicates that the identified oscillating transcripts were not false positive but were clearly associated with the circadian clock. Hierarchical clustering analysis of oscillating transcripts revealed two clusters: cluster 1 with 185 transcripts and cluster 2 with 227 transcripts (Figure 1-figure supplement 2). A circular map of peak phases across all rhythmic genes revealed two major peaks, one in the early night (ZT12 to ZT16) and one in the late night or dawn (ZT21 to ZT1) (Figure 1F). Here for more intuitive interpretation, we set 8hrs post synchronization (sync) to ZT0 based on a previous phase comparison. Circadian transcriptome studies conducted in multiple animal tissues have indicated that the phases of each tissue are not randomly distributed but are predominantly clustered in one or two narrow temporal windows (Panda et al., 2002). Consistent with these previous reports, mouse cultured astrocytes exhibited a high degree of temporal organization. Intriguingly, there was a relatively quiescent zone during subjective daytime, a finding different from that observed for diurnal animals, which showed a quiescent zone during subjective nighttime (Mure et al., 2018).

To understand the biological processes and pathways controlled by the circadian clock, we performed a Gene Ontology (GO) analysis on each cluster using Metascape (https://metascape.org) (Figure 1G). Given that the goal of our research was to investigate processes specifically controlled by the circadian clock, we excluded 17 core clock transcripts (Arntl, Clock, Nfil3, Npas2, Bhlhe40, Bhlhe41, Cry1, Cry2, Dbp, Elf, Nr1d1, Nr1d2, Per1, Per2, Per3, Rorc, and Tef) from our GO enrichment analysis. Among the rhythmic processes, we focused on “calcium ion homeostasis (GO:0055074)” due to the importance of intracellular Ca²⁺ signaling in numerous astrocyte functions (Agulhon et al., 2008; Bojarskaite et al., 2020; Brancaccio et al., 2019; Giaume et al., 2021; Guerra-Gomes et al., 2017; Verkhratsky & Nedergaard, 2018). In this category, Ca²⁺ homeostasis-related genes included Herp, Slc4a11, Sord and Kcnh1 etc. with Herp showing the most robust oscillation with large amplitude (Table S1).

Circadian rhythmic expression of Herp in cultured mouse cortical astrocytes

We first assessed the expression patterns of core clock genes and Herp in our cultured astrocytes. Bmal1, was rhythmically expressed with a peak at 30hr post sync while Per2 and Rev-Erbα showed rhythmic expression with peaks at 20hr and 16hr, respectively (Figure 2A). Herp displayed a robust rhythmic expression pattern, peaking at 20hr, similar to Per2 (Figure 2A). To verify the circadian expression of Herp, we performed quantitative real-time RT-PCR, which confirmed that Bmal1, Rev-Erbα and Herp exhibited circadian rhythms consistent with the RNAseq results (Figure 2B).

Figure 2.

Next, we examined whether HERP protein levels also showed rhythmic changes, as many genes exhibit rhythmic transcription without corresponding protein level changes (Reddy et al., 2006). We validated the specificity of HERP antiserum using Western blot analysis of astrocytes treated with Herp siRNA (Herp-KD), which significantly reduced Herp mRNA levels (Figure 2C) and the intensities of specific bands in Western blots (Figure 2D and 2E). SS-synchronized cultured astrocytes were sampled every 6hrs for 2 days and processed for Western blot analysis of BMAL1 and HERP. BMAL1 phosphorylation showed circadian variation, with hyper-phosphorylation peaking at midday and hypo-phosphorylation peaking early in the day or late at night (Yoshitane et al., 2009). In our SS-synchronized cultured astrocytes, BMAL1 was hyperphosphorylated at 18hr, 24hr, 42hr, and 48hr (corresponding to midday) and hypo-phosphorylated at 12hr, 36hr (corresponding to early in the day), and 30hr, 54hr (corresponding to late at night) throughout two daily cycles (Figure 2F) indicating strong circadian rhythms in cultured astrocytes. Importantly, HERP protein levels oscillated peaking at 18hr and 42hr and reaching a minimum at 12hr, 30hr, and 54hr, mirroring its mRNA pattern (Figure 2F and 2G).

Herp also exhibited rhythmic expression in astrocyte cultures synchronized by either dexamethasone (Balsalobre et al., 2000) or forskolin (Yagita & Okamura, 2000) treatments which are other commonly used for circadian clock resetting (Figure 2-figure supplement 1). Finally, to investigate whether the rhythmic expression of Herp is regulated by a circadian clock, we examined Herp mRNA and protein expression patterns in primary astrocyte cultured from Bmal1^-/- mice. The rhythmic expression patterns of Per2, Rev- Erbα, and Herp were abolished in Bmal1^-/- astrocyte cultures with their expression maintained at trough levels (Figure 2A). HERP protein levels remained constant throughout the daily cycles (Figure 2H and 2I). Collectively, these observations indicate that the expression of Herp exhibits a robust circadian rhythm that is controlled by BMAL1 in cultured mouse astrocytes. These results suggest that HERP-regulated cellular processes vary in a time-of-day specific manner.

Herp knockdown alters ATP-induced ER Ca²⁺ release

Herp was first identified as a gene with altered expression in response to homocysteine treatment in human umbilical vein endothelial cells (HUVECs) (Kokame et al., 1996). It is strongly induced not only by homocysteine but also by ER stress-causing agents such as tunicamycin or thapsigargin. HERP, characterized by an N-terminal ubiquitin-like domain and present in the ER membrane facing cytoplasmic side, is involved in the unfolded protein response (UPR) (Kokame et al., 2000) and is part of the ER- associated degradation (ERAD) complex, participating in the ubiquitination and relocation of ERAD substrates (Leitman et al., 2014). Notably, HERP modulates the ER Ca²⁺ response through IP₃R degradation (Paredes et al., 2016; Torrealba et al., 2017).

Thus, we sought to investigate whether HERP-controlled processes are subject to circadian regulation by examining the HERP-regulated ER Ca²⁺ response in the astrocytes. We employed the organelle-specific fluorescent Ca²⁺ indicators: G-CEPIA1er for the ER (Suzuki et al., 2014), R-GECO1 for the cytosol (Wu et al., 2013), and mito-R-GECO1 for mitochondria (Zhao et al., 2011). We first confirmed that these Ca²⁺ indicators colocalized with organelle-specific markers (Figure 3-figure supplement 1). ATP serves not only as a fundamental energy source but also as an active intercellular messenger. In astrocytes, ATP application induces an increase in intracellular Ca²⁺ (Neary et al., 1988) by binding to the G_q/G₁₁ coupled P2Y receptor, activating PLC-β and inducing the hydrolysis of PIP₂ to diacylglycerol (DAG) and IP₃, which mobilizes Ca²⁺ through IP₃Rs on the ER membrane (Baryshnikov et al., 2003; James & Butt, 2001).

We treated control and Herp-KD astrocytes with 100μM ATP and monitored subcellular Ca²⁺ changes. ATP treatment rapidly decreased ER Ca²⁺ in control astrocytes and this response was more pronounced in Herp-KD astrocytes (Figure 3A-3C). As the main Ca²⁺ store in the cell, ER releases Ca²⁺ which is then rapidly transmitted to other organelles such as mitochondria and cytosol (Carreras-Sureda et al., 2018; Giorgi et al., 2018). Although ATP treatment did not significantly alter cytosolic Ca²⁺ signal in control astrocytes, it greatly increased cytosolic Ca²⁺ signals in Herp-KD astrocytes (Figure 3D-3F). Consistently, mitochondrial Ca²⁺ significantly increased in Herp-KD astrocytes compared with control (Figure 3G-3I).

Figure 3.

Next, we examined the mechanism by which HERP controls ER Ca²⁺.There are three subtypes of IP₃Rs encoded by the genes Itpr1, Itpr2, and Itpr3. Transcriptome analysis of our cultured astrocytes indicated Itpr1 as the most prevalent, followed by Itpr2, while Itpr3 expression was minimal (Figure 3-figure supplement 2). Notably, expression of these Itpr subtypes was not rhythmic. We then assessed the ITPR1 and ITPR2 protein levels in control and Herp-KD astrocytes and found that the levels of both ITPR1 and ITPR2 were slightly but statistically significantly increased in Herp-KD astrocytes compared to controls (Figure 3J-3M). These results, consistent with previous reports (Paredes et al., 2016; Torrealba et al., 2017) indicated that HERP negatively regulates ITPRs in astrocyte.

To confirm that the HERP-ITPR axis underlies ER Ca²⁺ response, we analyzed the ER Ca²⁺ response following treatment with Xestospongin C (XesC), an IP3R inhibitor. XesC treatment reduced the ATP- induced ER Ca²⁺ release and abolished the enhanced effect observed in Herp-KD compared to control (Figure 3N-3P). Collectively, these results clearly indicate that HERP controls ER Ca²⁺ release by negatively regulating IP3Rs.

ATP-induced ER Ca²⁺ release varies according to time post synchronization

Given that HERP levels exhibited circadian variation and HERP regulated ER Ca²⁺ release, we investigated whether ATP-induced ER Ca²⁺ responses differ depending on circadian phase. After SS, we measured ER Ca²⁺ following ATP treatment at peak (42hr post sync) and trough (30hr post sync) phases of HERP (Figure 4A). With lower HERP levels potentially resulting in higher IP₃R levels at 30hr, we anticipated greater ER Ca²⁺ release at 30hr than at 42hr. Consistent with this, ER Ca²⁺ decreased more at 30hr than at 42hr upon ATP treatment (Figure 4B-4D). Also, in keeping with previous result (Figure 3A-3I), cytosolic Ca²⁺ increased more at 30hr than at 42hr following ATP treatment (Figure 4E-4G). Although mitochondrial Ca²⁺ responses exhibited a similar trend, the differences were not statistically significant (Figure 4H-4J).

Figure 4.

To confirm that HERP underlies this circadian phase-dependent ER Ca²⁺ release, we compared ER Ca²⁺ release in control and Herp-KD astrocytes at 30hr and 42hr post sync. Control astrocytes exhibited time-dependent variation in ER Ca²⁺ release, which was abolished in Herp-KD astrocytes (Figure 4K-4L), indicating the involvement of HERP in this regulation.

We then assessed whether ITPR1 and ITPR2 levels varied with time. BMAL1 phosphorylation served as a proxy for circadian phase (Figure 4N). ITPR2 levels showed time-dependent changes opposite to those of HERP, whereas ITPR1 levels remained constant (Figure 4N and 4O). Since Itpr2 mRNA levels did not exhibit a rhythmic pattern (Figure 3-figure supplement 1), the circadian phase-dependent differences in ITPR2 levels are likely driven by HERP-mediated ITPR2 degradation. Consequently, circadian rhythmic ER Ca²⁺ release is primarily driven by oscillations in ITPR2.

To verify if ER Ca²⁺ release is regulated by the circadian clock, we analyzed the ER Ca²⁺ response in Bmal1^-/-mouse astrocyte cultures. In WT astrocyte cultures, there was a clear circadian phase-dependent difference in ER Ca²⁺ release. However, this difference was abolished in Bmal1^-/- astrocyte cultures (Figure 5A-C). The absence of rhythmic ER Ca²⁺ release in Bmal1^-/- astrocytes correlated with constant levels of HERP (Figure 5D-E). Additionally, ER Ca²⁺ release was significantly faster in Bmal1^-/- astrocytes compared to WT astrocytes (Figure 5A-C) attributed to lower levels of HERP in Bmal1^-/- astrocytes (Figure 5D-E). Collectively, these results indicate that ER Ca²⁺ release is regulated by HERP, which is under circadian clock control.

Figure 5.

ATP-induced S368-phosphorylation of CX43 and gap junctional communication shows circadian variation

Syncytial coupling through gap junctions is a prominent feature of astrocytes, critical for their homeostatic functions, including the diffusion and equilibration of ions, metabolites, and signaling molecules (Langer et al., 2012; Verkhratsky & Nedergaard, 2018). This coupling allows the astrocytic syncytium to propagate Ca²⁺ waves, affecting nearby and remote cells through release of “gliotransmitters” and modulating synaptic functions in a far-reaching network (Pacholko et al., 2020). Connexin (Cx) family proteins constitute gap junction channels (GJCs) (Giaume et al., 2021), with Cx43 (also known as Gja1) and Cx30 (also known as Gjb6) being the main connexins in astrocytes (Kunzelmann et al., 1999; Nagy et al., 1999). In our cultured astrocytes, Cx43 was the most abundantly expressed connexin (Figure 6-figure supplement 1). Phosphorylation of CX43 at Ser368 by protein kinase C (PKC), activated in response to intracellular Ca²⁺, is known to decrease gap junction conductance (Enkvist & McCarthy, 1992; Nimlamool et al., 2015; Solan & Lampe, 2014). Accordingly, we hypothesized that the circadian variations in ATP-driven ER Ca²⁺ responses might differentially impact CX43 phosphorylation according to times of day.

First, we confirmed that ATP treatment induces rapid phosphorylation of CX43 at Ser368 (pCX43 (S368)) in cultured astrocytes (Figure 6A and 6B). We then examined whether pCX43 (S368) varies with circadian phase. Notably, ATP-induced ER Ca²⁺ release was more pronounced at 30hr than at 42hr post sync (Figure 3), and pCX43 (S368) in response to ATP was also significantly higher at 30hr compared to 42hr post sync (Figure 6C and 6D).

Figure 6.

We also examined circadian variations of pCX43 (S368) in vivo. Mice were entrained to a 12:12 hour light/dark (LD) cycle for two weeks and then kept in constant darkness (DD). This ensured that variations in CX43 phosphorylation were due to the internal circadian clock and not external light stimuli. Prefrontal cortex tissues were dissected at circadian time (CT) 58 and CT70 on the third day of DD. pCX43 (S368) levels were higher at CT70 (subjective night) than at CT58 (subjective day), consistent with our in vitro results (Figure 6E and 6F).

To confirm that HERP underlies the rhythmic phosphorylation of CX43 at Ser368, we compared pCX43 (S368) in control and Herp-KD astrocytes at 30hr and 42hr post sync. In control astrocytes pCX43 (S368) was higher at 30hr compared to 42hr, consistent with previous results. However, in Herp-KD astrocytes, the circadian phase-dependent differences in pCX43 (S368) were abolished despite the normal circadian rhythm indicated by BMAL1 phosphorylation, (Figure 6G and 6H). This suggests that rhythms of HERP levels are required for the rhythmic phosphorylation of CX43 (S368).

Finally, we assessed if rhythmic phosphorylation of CX43 contributes to circadian phase-dependent variation in gap junctional communication in cultured astrocytes by using fluorescence recovery after photobleaching (FRAP) method. The absence of FRAP signal in carbenoxolone (CBX)-treated astrocytes confirmed the involvement of gap junctions in intercellular communication of cultured astrocytes (Figure 7A-7C). We observed a faster and more pronounced recovery of fluorescence in photobleached astrocytes at 42hr compared to 30hr post sync (Figure 7D-7F). Importantly, this variation was absent in astrocytes cultured from Bmal1^-/- mice, indicating that circadian clock regulates gap junctional communication (Figure 7G.-7I).

Figure 7.

In summary, we propose a model illustrating how the circadian clock influences astrocyte function through the regulation of ER Ca²⁺ response. Based on phase comparisons of clock genes between our data and CircaDB (Figure 1D), we defined subjective day and night, with 8hr post sync corresponding to the beginning of the day. In astrocytes, BMAL1/CLOCK-controlled oscillation of HERP regulates day and night variations in ITPR2 levels. These oscillations contribute to changes in ER Ca²⁺ responses, which in turn result in the distinct day and night differences in pCx43 (S368) and the gap junction conductance (Figure 7J).

Discussion

It is widely acknowledged that the circadian clock orchestrates cellular functions in a highly cell type-specific manner by governing transcription (Mure et al., 2018; Zhang et al., 2014). Although the importance of the circadian clock in astrocytes has been well-documented (Barca-Mayo et al., 2020; Barca-Mayo et al., 2017; Griffin et al., 2019; Lananna et al., 2018; Prolo et al., 2005; Tso et al., 2017), studies specifically exploring astrocyte-specific circadian transcriptomes have been limited. Our study conducted such an analysis on primary cultured cortical astrocytes, discovering that rhythmic expression of Herp underlies day/night variation in ER Ca²⁺ response by regulating IP₃R levels. We also found that Ca²⁺-activated CX43 phosphorylation varied according to the daily rhythmic ER Ca²⁺ response. Given that astrocytes function in a network in which Ca²⁺ propagates through GJCs, we propose that the time-dependent control of ER Ca²⁺ responses could influence the role of astrocytes in modulating synaptic activity throughout the day (see below).

Circadian oscillations of Herp expression have been previously documented in various mouse tissues including the lung, heart, liver, kidney, aorta, skeletal muscle, adrenal gland, pancreatic islet and SCN (Panda et al., 2002; Rakshit et al., 2016; Zhang et al., 2014). In this study, we identified that Herp is also rhythmically expressed in cultured astrocytes. Herp exhibited rhythmic expression in phase with Per2 and showed flattened expression at its nadir level in Bmal1^-/- astrocyte cultures, suggesting direct regulation CLOCK/BMAL1 heterodimers (Figure 2A). ChIP-Atlas analysis (https://chip-atlas.org) (Oki et al., 2018; Zou et al., 2022) has shown CLOCK binding to the genomic region of Herp (Annayev et al., 2014; Hong et al., 2018). Although no canonical E-Box is present in the upstream 6kb region of the Herp gene, several non-canonical E-Boxes, important for circadian expression (Yoo et al., 2005; Zhang et al., 2011), were identified (Table S2). Among these, the non-canonical E-Box sequence “CACGTT,” located near transcription start site (chr8:94386194-94386543), is highly conserved across diverse mammalian species. Therefore, we propose that these non-canonical E boxes might drive the CLOCK/BMAL1 dependent expression of Herp. A recent study employing a circadian single-cell RNA seq analysis of SCN reported that Herp displays a circadian rhythm exclusively in astrocytes and oligodendrocytes (Wen et al., 2020). Given that astrocytic Ca²⁺ levels in the SCN show a circadian rhythm, peaking during the subjective night and are crucial for circadian timing (Brancaccio et al., 2019; Patton et al., 2022), HERP’s circadian rhythmic expression in SCN astrocytes (Wen et al., 2020) may be integral to the mechanisms of circadian timing.

We demonstrated that HERP regulated ER Ca²⁺ responses by degrading IP₃Rs in astrocytes (Figure 3J-3M). (Paredes et al., 2016; Torrealba et al., 2017). When Herp was downregulated, both ITPR1 and ITPR2 levels increased, suggesting HERP’s role in degrading both ITPR1 and ITPR2. However, only the levels of ITPR2 exhibited circadian phase-dependent variation (Figure 3J-3M, Figure 4K-4L). The min/max ratio of HERP expression throughout the day was 0.38 under normal conditions but 0.072 in Herp-KD conditions. Based on this, we reasoned that the amplitude of HERP oscillations impacted the levels of ITPR2 under normal circumstances, while having a much lesser effect on the levels of ITPR1. Thus, the circadian control of ER Ca²⁺ release in response to stimulation in cultured astrocytes is primarily attributable to ITPR2.

ER and cytosolic Ca²⁺ responses following ATP treatment exhibited distinct circadian variation, but mitochondrial Ca²⁺ responses did not show significant variations (Figure 4). We think of several possibilities to account for the absence of significant circadian variations in mitochondrial Ca²⁺ relative to cytoplasmic Ca²⁺ change. Upon ATP stimulation, direct Ca²⁺ transfer occurs through IP₃R in the cytosol. For mitochondrial uptake, Ca²⁺ first transits to the intermembrane space via IP₃Rs and the voltage-dependent anion channel (VDAC) complex before entering the matrix through mitochondrial calcium uniporter (MCU) (Giorgi et al., 2018). The Mito-R-GECO1 reporter is confined within the mitochondrial matrix and thus limiting assessment of Ca²⁺ levels in the intermembrane space (Wu et al., 2013). Substantial changes in Ca²⁺ levels might occur in the intermembrane space, but the influx into the matrix via MCUs could remain constant across different time, resulting in apparent lack of significant change. Secondly, the amount of VDAC or the VDAC:IP₃R complex on the mitochondrial membrane might vary inversely with HERP levels, potentially maintaining a consistent flow of Ca²⁺ into the mitochondria irrespective of the time. Additionally, the presence of several Ca²⁺ extrusion mechanisms in mitochondria (Giorgi et al., 2018) points to a more complex regulation of Ca²⁺ compared with that in the cytosol. Although the precise mechanism remains to be elucidated, our data indicate that the circadian variation in Ca²⁺ release from the ER, particularly in response to stimuli, predominantly impacts cytoplasmic signaling rather than mitochondrial signaling.

During the subjective night phase (active period for mice), ATP- stimulated ER Ca²⁺ release was pronounced than during the subjective day phase (rest period for mice) (Figure 4). This finding aligns with studies showing heightened stimulus-evoked Ca²⁺ activity in astrocytes during wakefulness, which diminishes during sleep (Bojarskaite et al., 2020; Ingiosi et al., 2020). In flies, Ca²⁺ activity in astrocytes is correlated with the duration of wakefulness, suggesting that astrocytic Ca²⁺ is a key factor in the homeostatic regulation of sleep (Blum et al., 2021). Our findings provide a mechanistic explanation for differential Ca²⁺ levels observed between wake and sleep states, with circadian regulation of ITPR2 by HERP being a key factor in this process.

ATP-stimulated Cx43 (S368) phosphorylation is higher at 30hr (subjective night phase) than at 42hr post sync (subjective day phase) (Figure 6C and 6D.), a finding further supported by in vivo experiments (Figure 6E and 6F). What are the implications of this day/night variation in CX43 (S368) phosphorylation? We reasoned that the circadian variation in CX43 phosphorylation could significantly impact astrocyte functionality within the syncytium. Indeed, our cultured astrocytes exhibited circadian phase-dependent variation in gap junctional communication (Figure7D-7F). Astrocytes influence synaptic activity through the release of gliotransmitters such as glutamate, GABA, D-serine, and ATP, triggered by increases in intracellular Ca²⁺ in response to the activity of adjacent neurons and astrocytes (Verkhratsky & Nedergaard, 2018). Importantly, this increase in Ca²⁺ spreads to adjacent astrocytes through GJCs (Fujii et al., 2017), influencing a large area of the neuronal network. Considering that Cx43 Ser368 phosphorylation occurs to uncouple specific pathways in the astrocytic syncytium to focus local responses (Enkvist & McCarthy, 1992), our findings suggest that astrocytes better equipped for localized responses when presented with a stimulus during the active phase in mice. Conversely, during the rest period, characterized by more synchronous neuronal activity across broad brain areas (Vyazovskiy et al., 2009) higher GJC conductance might allow astrocytes to exert control over a larger area. In support of this idea, recent study showed that synchronized astrocytic Ca²⁺ activity advances the slow wave activity (SWA) of the brain, a key feature of non-REM sleep (Szabó et al., 2017). Blocking GJC was found to reduce SWA, further supporting this interpretation. However, conflicting findings have also been reported. For instance, Ingiosi et al. (Ingiosi et al., 2020) found that astrocytic synchrony was higher during wakefulness than sleep in the mouse frontal cortex. Whether these differing results in astrocyte synchrony during resting and active periods are attributable to differences in experimental context (e.g., brain regions, sleep-inducing condition) remains unclear. Indeed, astrocyte Ca²⁺ dynamics during wakefulness/sleep vary according to brain regions (Tsunematsu et al., 2021). While the extent of astrocyte synchrony might differ depending on brain region and/or stimulus, our results suggest that the baseline state of astrocyte synchrony, which is affected by GJC conductance, varies with the day/night cycle.

In conclusion, our findings enhance the understanding of the circadian regulation of astrocytic functions, particularly through the rhythmic expression of HERP and its impact on ER Ca²⁺ signaling and CX43 phosphorylation. This study underscores the intricate interplay between the circadian clock and astrocyte physiology, highlighting the pivotal role of HERP in modulating key astrocytic processes such as sleep, gap junction communication and synaptic modulation. The day/night variations in ER Ca²⁺ response and CX43 phosphorylation, and their implications for astrocytic network dynamics and neuronal interactions, open new avenues for exploring the broader implications of astrocytic circadian rhythms in brain function and health.

Materials and Methods

Animals

All procedures for the care and use of laboratory animals were approved by the Institutional Animal Care and Use Committee (IACUC) of Ajou University School of medicine. Bmal1^-/+ mice (B6.129-Bmal1^tm1Bra/J; Jackson Laboratory, #009100)(Bunger et al., 2000) were purchased from Jackson Laboratory(USA) and housed in a specific pathogen-free environment at the Animal Research Center of Ajou University Medical Center, with a standard 12-hour light/dark cycle and free access to food. Primary cultured astrocytes involving only WT mice used 1day-old C57BL/6 mice (Koatch Inc., Korea). In experiments employing primary cultured astrocytes from Bmal1^-/- mice, wild type (WT) littermates were used as controls. For animal studies, 7-8 week-old adult C57BL/6 male mice were first entrained in a standard 12-hour light/dark cycle for 2 weeks and then maintained in a constant darkness (DD). On the third day of DD, mice were sacrificed at indicated time and its prefrontal cortex (PFC) was dissected.

Primary astrocyte culture

Primary astrocyte culture was prepared according to a previous report (Choi et al., 2018) with minor modifications. In brief, 1 day old pups were anesthetized by hypothermia and their cerebral cortices were dissected out and triturated in Modified Eagle’s medium (MEM; Welgene, Korea, LM 007-11) containing 10% fetal bovine serum (FBS; Hyclone, USA, SV30207.02), penicillin/streptomycin (Gibco, USA, 15140-122), 10 µM HEPES (Gibco, USA, 15630080) and GlutaMAX (Gibco, USA, 35050-061) yielding a single-cell suspension. Cells were plated into 75 cm² T-flasks (1pup/flask) and incubated at 37°C in a humidified 5% CO₂ incubator for 2 weeks. Primary astrocytes were then incubated in a serum-free MEM for 7 days, after which astrocytes were detached from the T-flask with 0.25% trypsin and plated on culture dishes (1.0X10⁶cells/60 mm dish) for experiments.

Circadian transcriptome analysis

The experimental scheme for synchronizing circadian clocks of cultured astrocyte is illustrated in Figure 1A. In brief, astrocytes were grown in dishes (1.0 X 10⁶cells/60 mm dish) until reaching complete confluence and then incubated in serum-free MEM for 72hrs. Cells were then subjected to serum shock (SS), a well-established procedure for synchronizing the circadian clock of cultured cells (Balsalobre et al., 1998), by exchanging the medium for MEM containing 50% horse serum. 12hrs post SS, astrocytes were harvested at 4-h intervals for 2 days for RNA sequencing (RNA-seq). Total RNA was extracted and purified from harvested astrocytes using a RNeasy Plus Micro Kit (Qiagen, Germany, 74034). RNA quality and quantity assessments, RNA-Seq library construction, and next-generation sequencing analysis were performed by Macrogen Inc. (Korea). Total RNA integrity and library size were analyzed using an Agilent Technologies 2100 Bioanalyzer. Paired-end raw reads, generated using an Illumina HiSeq 2000 system, were aligned to the mm10 mouse genome using STAR aligner (v.2.5.2b)(Dobin et al., 2013). Gene expression was subsequently quantified by calculating transcripts per million (TPM) using Ensemble gene (release 82) annotations. The threshold for defining expressed transcripts was set using a Gaussian mixture model in the R package ‘mixtools’. To detect circadian oscillating transcripts, we employed two circadian oscillation detection methods BioCycle (Agostinelli et al., 2016) and MetaCycle (Wu et al., 2016).

Quantitative reverse transcription polymerase chain reaction (qRT-PCR)

Total RNA was extracted from cells and purified using the RNeasy Plus Micro Kit (Qiagen, 74034). 1μg of total RNA was reverse transcribed using an oligo-dT primer and PrimeScript RTase (TaKaRa, Japan, 2680A). Quantitative real-time PCR was performed using a Rotor Gene Q (Qiagen) with TB Green Premix Ex Taq (Takara, RR420A) The specific primers used were provided in the Table S3. Noncycling mRNA encoding HPRT was used to normalize gene expression. The data were analyzed using Rotor Gene 6000 software, and the relative mRNA levels were quantified using the 2^-ΔΔCt method in which ΔΔCt=[(Ct _target - Ct _HPRT) of experimental group]-[(Ct _target - Ct _HPRT) of control group].

siRNA transfection and Immunoblotting

The following On-Target plus SMARTpool siRNAs were purchased from Dharmacon (USA): Non-targeting CTRL siRNA (D-001810-01-50), Herp siRNA (L-049714-01-0005), Itpr1 siRNA (L-040933-00-0005), and Itpr2 siRNA (L-041018-00-0005). Upon reaching >90% confluence, the medium was replaced with serum-free MEM, and cells were incubated for 72hrs. Cells were then transfected with siRNA using Lipofectamine RNAiMAX (ThermoFisher, USA, 13778150) per the manufacturer’s instructions. Experiments were conducted 48hrs post-transfection.

For immunoblotting, astrocytes were lysed using modified-RIPA buffer (50 mM Tris-HCl pH 7.4, 1% NP-40, 0.5% sodium deoxycholate, 150 mM NaCl). Mouse prefrontal cortex was lysed using T-Per (ThermoFisher, 78510) with protease inhibitor cocktail (Sigma-Aldrich, P8340) and phosphatase inhibitor cocktails 2 and 3 (Sigma-Aldrich, P5726 and P0044). Proteins were separated by SDS-PAGE and transferred to polyvinylidene fluoride membranes. Membranes were blocked with 5% skim milk and incubated overnight at 4°C with primary antibodies: anti-BMAL1 (Abcam (UK), ab93806), 1:2000; anti-HERP (Abcam, ab150424), 1:1000; anti-ITPR1 (Abcam, ab264284), 1:1000; anti-ITPR2 (Alomone Labs, Israel, ACC-116), 1:1000; anti-CX43 (Sigma, C6219), 1:5000; anti-pCX43 (Ser368) (CST, USA, 3511), 1:1000; anti-GAPDH (Novus, USA, NB100-56875), 1:5000; anti-vinculin (Sigma-Aldrich, V4505), 1:5000; and anti-total ERK (CST, 9102), 1:5000. Membranes were washed with TBST, incubated with secondary antibodies, and visualized using enhanced chemiluminescence. Protein levels were quantified by densitometric analysis of band intensities using ImageJ software.

Ca²⁺ reporter plasmid transfection and imaging analysis

After cells reached >90% confluence, the medium was replaced with serum-free MEM. For Ca²⁺ measurements, cells were transfected with Ca²⁺ indicator plasmids pCMV-G-CEPIA1er (a gift from Masamitsu Iino, Addgene plasmid #58215) (Suzuki et al., 2014), CMV-mito-R-GECO1, or CMV-R-GECO1 (gifts from Robert Campbell, Addgene plasmid #46021, #32444) (Wu et al., 2013) 72hrs post-serum deprivation using Lipofectamine 2000, with or without siRNA treatment. For Xestospongin C (XesC) experiments, 10 μM XesC was applied 30 minutes before imaging. 48hrs post-transfection, the medium was replaced with Ca²⁺- and Mg²⁺-free HBSS (Gibco, 14175095). Fluorescence images were captured every 3 seconds using a Nikon A1R Confocal Microscope with a x60 1.4 NA Plan-Apochromat objective at 37°C and 5% CO2. These experiments were conducted at the Three-Dimensional Immune System Imaging Core Facility of Ajou University (Korea). Images were analyzed using NIS Elements C software. Fluorescence intensity at each time point (F_t) and ΔF values (F_t-F₀) were calculated. F₀ values were averaged from the fluorescence intensity of 10 frames prior to stimulation.

Ca²⁺ reporter plasmid co-localization analysis

After cells reached >90% confluence, the medium was replaced with serum-free MEM. 72hrs later, cells were transfected with either the ER Ca²⁺ reporter plasmid pCMV-G-CEPIA1er or the mitochondrial Ca²⁺ reporter CMV-mito-R-GECO1. For ER co-localization analysis, pCMV-G-CEPIA1er was co-transfected with DsRed2-ER-5 (a gift from Michael Davidson, Addgene plasmid #55836) (Day & Davidson, 2009). For mitochondrial co-localization, 200 nM Mitotracker was applied 30 minutes before imaging. Live imaging was performed using a Nikon A1R Confocal Microscope with a x60 1.4 NA Plan-Apochromat objective at 37°C and 5% CO2. These experiments were conducted at the Three-Dimensional Immune System Imaging Core Facility of Ajou University (Korea). Images were analyzed using NIS Elements C software.

Gap-FRAP (fluorescence recovery after photobleaching) analysis

Astrocyte communication was evaluated using a modified gap-FRAP assay (Santiquet et al., 2012). 30 minutes before imaging, cells were incubated with 0.5 μM Calcein-AM (Invitrogen, C1430) and 0.05% Pluronic-127 (Invitrogen, P6866) at 37°C. After incubation, cells were rinsed twice with serum-free MEM to remove excess dye. For carbenoxolone (CBX) experiments, 20 μM CBX was added for 30 minutes after calcein incubation. Immediately before imaging, the medium was replaced with Ca²⁺- and Mg²⁺-free HBSS (Gibco, 14175095). Live imaging was performed using a Nikon A1R Confocal Microscope with a 488 nm argon laser and a x60 1.4 NA Plan-Apochromat objective. Photobleaching was performed on a region of interest (ROI) cell, and fluorescence was measured at 37°C and 5% CO2. Fluorescence intensity was recorded pre-bleach (5 images), during a 15-second laser pulse (100% power, 5.3 lines/sec), and post-bleach (every 3 seconds for 3 minutes). Images were analyzed using NIS Elements C software. Fluorescence intensity at each time point (F_t) was normalized to the pre-bleach intensity (F₀), calculated as the average of 5 pre-bleach frames. The percentage of fluorescence recovery was calculated using: (F_FR-F_A)/(F₀-F_A)x100, where F_FR is the full recovery fluorescence intensity and F_A is the intensity immediately after photobleaching.

Quantification and statistical analysis

To conduct the statistical analyses, all samples were first tested for normality. For cases where normality testing was not possible, such as with the Area Under/Above Curve, t-tests were used for comparing two groups, and one-way ANOVA was used for comparing three or more groups, considering the sufficient sample size. When comparing two groups, a t-test was performed if the data followed a normal distribution; otherwise, the Mann-Whitney U test was used. For comparisons among three or more groups, one-way ANOVA was used if the data were normally distributed, and the Brown-Forsythe and Welch ANOVA tests were used if they were not. When comparing three or more groups across multiple time points, a two-way ANOVA was performed. A p < 0.05 was considered statistically significant for all tests.

Data and code availability

• Circadian RNA sequencing data have been deposited at GEO under accession number GEO: GSE254678.

• Any additional information required to reanalyze the data reported in this paper is available from the E.Y.K upon request.

Acknowledgements

We are very grateful to Eunhye Joe and all members of Eun Young Kim’s laboratory for critical comments on the manuscript. This research was supported by National Research Foundation of Korea (NRF) grants funded by the Korean government (Ministry of Science and ICT; grant numbers, 2019M3C7A1031905, 2019R1A5A2026045).

Additional information

Author Contributions

J.E.R., H.W.R., J.L., and E.Y.K designed research. J.E.R., K. S., H.W.R., and J.L. performed research. All authors analyzed data. J.E.R. and E.Y.K. wrote the first draft of the manuscript and all authors contributed to revising the manuscript.

Declaration of interests

The authors declare no competing interests.

Supplemental information

Table S1.

Table S2.

Table S3:

Figure 1-figure supplement 1.

Figure 1-figure supplement 2.

Figure 2-figure supplement 1.

Figure 3-figure supplement 1.

Figure 3-figure supplement 2.

Figure 6-figure supplement 1.