Article

https://doi.org/10.1038/s41467-024-50168-5

Cortical parvalbumin neurons are
responsible for homeostatic sleep reboundthrough CaMKII activation
Received: 27 March 2023

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Accepted: 1 July 2024

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Kazuhiro Kon1,8, Koji L. Ode1,2, Tomoyuki Mano 1,2,3,9, Hiroshi Fujishima2,4,Riina R. Takahashi1, Daisuke Tone1,2, Chika Shimizu2, Shinnosuke Shiono1,
Saori Yada 1,10, Kyoko Matsuzawa2, Shota Y. Yoshida1,2,
Junko Yoshida Garçon2,11, Mari Kaneko5, Yuta Shinohara2,12,
Rikuhiro G. Yamada2,4, Shoi Shi1,2,10, Kazunari Miyamichi 6,
Kenta Sumiyama 7,13, Hiroshi Kiyonari 5, Etsuo A. Susaki 1,2,14 &Hiroki R. Ueda 1,2,3,4

The homeostatic regulation of sleep is characterized by rebound sleep after
prolonged wakefulness, but the molecular and cellular mechanisms underlying this regulation are still unknown. In this study, we show that Ca2+/calmodulin-dependent protein kinase II (CaMKII)-dependent activity control ofparvalbumin (PV)-expressing cortical neurons is involved in homeostatic regulation of sleep in male mice. Prolonged wakefulness enhances cortical PVneuron activity. Chemogenetic suppression or activation of cortical PV neurons inhibits or induces rebound sleep, implying that rebound sleep isdependent on increased activity of cortical PV neurons. Furthermore, we discovered that CaMKII kinase activity boosts the activity of cortical PV neurons,
and that kinase activity is important for homeostatic sleep rebound. Here, we
propose that CaMKII-dependent PV-neuron activity represents negative
feedback inhibition of cortical neural excitability, which serves as the distributive cortical circuits for sleep homeostatic regulation.

The sleep-wake cycle is homeostatically regulated1. The wakefulness
history is recorded as sleep need, which is dissipated during the subsequent sleep. In general, a mechanism with negative feedback loops
maintains homeostasis2, but the core feedback system underlying
sleep homeostasis is unknown.
Slow-wave activity (SWA), a sleep need indicator1, represents synchronous activity among cortical neurons in which the ﬁring patternalternates between depolarized/burst (up) and hyperpolarized/silent(down) states3. It has been reported that wake-promoting neurons in
the midbrain suppress SWA globally via bottom-up projections toward
the isocortex, whereas sleep-promoting neurons in the hypothalamus
can inhibit the wake-promoting neurons4,5. The mechanism for global
cortical activity regulation implies the presence of brain-wide control ofsleep homeostasis. Indeed, ablation of sleep-promoting neurons in the

A full list of afﬁliations appears at the end of the paper.

Nature Communications | (2024)15:6054

hypothalamic preoptic area (POA) impairs rebound sleep after sleep
deprivation (SD)6. However, the ﬂip-ﬂop switch between wake- andsleep-promoting neurons4, resulting in an overall positive feedback
system, is less suitable for homeostatic regulation.
Sleep homeostasis is locally regulated in addition to the brainwide regulation noted by the ﬂip-ﬂop model7. In humans and rodents,
the SWA is locally enhanced in cortical regions that have been more
activated during the preceding wakefulness8,9. Prolonged wakefulness
results in local sleep, in which cortical neurons locally become silent
like in sleep, despite the animal displaying an awake electroencephalogram (EEG) throughout the brain10. These ﬁndings suggested that a local and minimal unit of the cortical circuit records their
homeostatic sleep need and that the negative feedback system forsleep homeostasis can be found in general cortical circuits.

e-mail: uedah-tky@umin.ac.jp1Article
Parvalbumin (PV)-expressing neurons, the most abundant
GABAergic interneurons in the isocortex, contribute to feedforward
and feedback inhibition in cortical microcircuits11,12. Ca2+ activity in PV
neurons is increased during both rapid eye movement (REM) and nonREM (NREM) sleep in the somatosensory cortex13, whereas the activity
is constantly higher in REM sleep and incremental during NREM sleepin the motor cortex14. Chemogenetic activation of PV neurons in thesecondary motor (M2) cortex leads to an increase in NREM sleep
duration, but a decrease in the SWA15. These ﬁndings suggested thatthe cortical PV neurons play a role in physiological sleep-wakeregulation.
Moreover, cortical PV neurons mature throughout postnatal
development in terms of distribution, electrophysiological properties,
and gene expression16–18, coinciding with developmental changes insleep architecture and homeostatic sleep responses19–23. Developmental dysfunctions in cortical PV neurons are associated with autism
spectrum disorder (ASD)24,25, where abnormal sleep symptoms areobserved in both patients and animal models26–28, highlighting thepotential connection between the maturation of cortical PV neurons
and developmental changes of sleep. However, the role of cortical PV
neurons in the regulation of sleep architecture and homeostatic sleep
rebound remains poorly understood.
Here, we show that activity control of cortical PV neurons is
involved in the regulation of sleep homeostasis. We discovered apotential link between reduced sleep stability and a decline in thedensity of PV neurons during development using long-term sleep
recordings and whole-brain analyses of PV-neuron distribution indeveloping mice. The chemogenetic manipulation of cortical PVneuron activity revealed that the activity is important for sleep stability. Surprisingly, cortical PV-neuron activity is also required forhomeostatic sleep rebound. To induce rebound sleep, cortical PV
neurons require Ca2+/calmodulin-dependent protein kinase II (CaMKII), whose kinase activity is critical for sleep promotion29,30. Bidirectional stimulation of endogenous CaMKII kinase activity in cortical PV
neurons demonstrated that CaMKII activity induces homeostatic sleep
rebound by stimulating the activity of PV neurons. In summary, theseﬁndings support the hypothesis that CaMKII-dependent activity control of cortical PV neurons contributes to the regulation of sleep
homeostasis. This mechanism could be a key negative feedback system for sleep homeostasis in general and distributive cortical circuits,
explaining local sleep homeostasis regulation.

Results
Sleep architecture and sleep homeostasis change with
development
We conducted long-term sleep phenotyping in developing mice tobetter understand the developmental trajectory of the sleep phenotype. The 2-month sleep phenotyping was performed in individual
mice from weaning (P21) to adult (P84) stage using a respiration-based
sleep phenotyping system, Snappy Sleep Stager (SSS) (Fig. 1a). The SSS
system demonstrates high accuracy (95.3 ± 0.4%) when sleep/wakestaging based on EEG/electromyogram (EMG) recordings is used as areference31. We focused on PWS and PSW, the transition probabilities
from wakefulness to sleep and sleep to wakefulness, respectively, in
addition to daily sleep duration (Fig. 1b). There was no signiﬁcantchange in daily sleep duration during the post-weaning development(Fig. 1c). However, both PWS and PSW increased continuously as thedevelopmental stages progressed (Fig. 1d, e), indicating that sleep andwake states were gradually fragmented from weaning to adulthood.
The light phase saw a greater increase in PWS, while the dark phase saw
a greater increase in PSW (Supplementary Fig. 1a–e). Consistent with
this, the duration of sleep episodes in the dark phase became shorter
than that in the light phase during the later developmental stages(Supplementary Fig. 1f).

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Following that, we performed a 6-hour SD in individual mice aged
4, 8, and 12 weeks to validate sleep homeostasis in developing mice
(Fig. 1f). The homeostatic rebound in sleep duration was clearlyobserved at 8 and 12 weeks old, but less so at 4 weeks old (Fig. 1g–i),
indicating that the homeostatic regulatory system in sleep amount isimmature at 4 weeks old. PWS tended to increase during the reboundphase at 8 and 12 weeks old, whereas PSW tended to decrease, implyingthat wake fragmentation (i.e., increased PWS) and sleep consolidation(i.e., decreased PSW) were induced in rebound sleep (Fig. 1j, k). Following the SD experiments, we administered MK-801, an NMDA
receptor antagonist, which increases neural excitation and wake consolidation followed by rebound sleep29,32 (Fig. 1f). This approachallowed us to measure the actual sleep loss induced by MK-801 intraperitoneal (i.p.) administration (Fig. 1l). The homeostatic rebound in
sleep duration was clearer at 8 and 12 weeks old than at 4 weeks old
after MK-801 administration (Fig. 1l–n), as observed in the SD. Similar
to SD, increased PWS and decreased PSW were observed during therebound phase at 8 and 12 weeks old (Fig. 1o, p). The homeostatic
rebound in sleep duration was less pronounced at 4 weeks old, evenwhen rebound sleep was calculated from individual rebound onset
without limiting to the dark phase (Supplementary Fig. 2a–f). Together, long-term sleep phenotyping in developing mice revealed thatthe daily sleep-wake pattern and its homeostatic regulatory systemmature with post-weaning development in mice.

Whole-brain distribution of PV neurons changes with
development
We focused on PV neurons as a candidate neural basis for the changes
in order to better understand the mechanisms underlying the developmental changes in sleep. The mouse brains were collected at various
stages of development after weaning, followed by CUBIC-based tissue
clearing for a whole-brain analysis of PV-neuron distribution33,34(Fig. 2a). The averaged PV-positive (PV+) cell density in the whole brain
was increased from P21 to P28 and gradually decreased with subsequent developmental stages (Fig. 2b, top panel). Similar trends wereobserved in many cerebrum brain regions, including the isocortex,
olfactory bulb (OLF), hippocampus (HPF), cortical subplate (CTXsp),
striatum (STR), and pallidum (PAL) (Fig. 2b, middle panel), while thedensity of PV+ cells decreased monotonically in all brain-stem regions,
including the thalamus (TH), hypothalamus (HY), midbrain (MB), pons(P), and medulla (MY) (Fig. 2b, bottom panel). These changes could be
attributed to PV+ cell loss or a decrease in PV expression in individual
PV+ cells (Supplementary Fig. 3a, b).
A detailed comparison of PV-neuron distribution in the P28 andP84 brains revealed subregion-speciﬁc changes in PV+ cell density(Fig. 2c, d). Except for the visual (VIS) cortex, the PV+ cell density in P84
was lower than in P28 in almost all areas of isocortex (Fig. 2e). PV+ celldensity in the somatomotor (MO) and anterior cingulate (ACA) cortex
gradually decreased beginning at P28, whereas it increased or stabilized during the same period in the VIS cortex (Fig. 2f). The density of
PV+ cells in some cortical regions, such as the somatosensory (SS)cortex, changed little during development (Fig. 2f).
In addition to the isocortex, subcortical and brain-stem regions
showed region-speciﬁc changes in PV-neuron distribution. The PV+
cell density in the striatal caudoputamen (CP) increased from P21 toP28, decreased from P28 to P42, and then stabilized from P42 to P270
(Supplementary Fig. 3c). The PV+ cell density in the globus pallidus
external segment (GPe) or reticular nucleus of the thalamus (RT)decreased gradually from P21 to P42 and remained constant after P42(Supplementary Fig. 3c). PV+ cell density in the zona incerta (ZI) andinferior colliculus (IC) decreased steadily until P270 (Supplementary
Fig. 3c). In summary, the decline of PV+ cell density was observed
across the entire brain during development when the daily sleep-wakepattern and its homeostatic regulatory system matured.

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Articlehttps://doi.org/10.1038/s41467-024-50168-5
Fig. 1 | Sleep architecture and sleep homeostasis are altered along with
development. a SSS-based long-term sleep phenotyping during post-weaningdevelopment (from P21 to P84). b Diagram of transition probabilities between sleep
and wakefulness. When PWS or PSW is increased, the wake or sleep state becomes
unstable. c–e Daily sleep duration (c), PWS (d), and PSW (e) in developing mice(n = 10). The blue points represent the average sleep parameters at each age. Twosided Student’s paired t-test with Bonferroni correction was used on mice aged 4, 8,
and 12 weeks. f Schematic representation of sleep deprivation (SD) experiments
performed on developing mice (n = 12) at 4, 8, and 12 weeks of age. Mice were freely
behaving during the ﬁrst 3 days, and the averaged value of sleep parameters isshown as Basal. On the fourth day, SD was performed for 6 h from ZT0 to ZT6. On
the ﬁfth (Saline) and sixth (MK-801) days, respectively, saline and 2 mg/kg MK-801
were administered at ZT8. g Cumulative sleep loss (SD – Basal) in mice aged 4, 8,
and 12 weeks over 24 h. h, j, k Sleep duration (h), PWS (j), and PSW (k) on Basal and SD
during ZT12–24 (n = 12). At each age, two-sided Welch’s t-test was used. i Sleep
rebound ratio (SD / Basal during ZT12–24). Individual mouse dots are connected bygray lines. Between the ages, two-sided Welch’s t-test with Bonferroni correction
was used. l Cumulative sleep loss (MK-801 – Saline) in mice aged 4, 8, and 12 weeks
over 24 h. m, o, p Sleep duration (m), PWS (o), and PSW (p) on Saline and MK-801
during ZT12–24 (n = 12). At each age, two-sided Welch’s t-test was used. n Sleep
rebound ratio (MK-801 / Saline during ZT12–24). Individual mouse dots are connected by gray lines. Between the ages, two-sided Welch’s t-test with Bonferroni
correction was used. Line plots show mean ± SEM. In box plot, boxes show themedian, 25th and 75th percentiles, and whiskers show minima to maxima excluding
outliers. Source data are provided as a Source Data ﬁle.

reports35 (Fig. 3b and Supplementary Fig. 4c). We also discovered that
the SD increased the density of PV+ cell in the isocortex to some extent(Fig. 3c and Supplementary Fig. 4d). Furthermore, there was an increase in c-Fos+ cell density among the PV+ cell population (i.e., c-Fos+PV+ cells), particularly in the isocortex (Fig. 3d and Supplementary Fig. 4e).
Because the SD had the greatest effect on c-Fos+PV+ cell density
in the isocortex (Fig. 3d), we looked into changes in c-Fos+PV+ cells in
cortical subregions. The number of c-Fos+PV+ cells was higher in SD
brains than in S brains in many subregions (Fig. 3e). The SD led to anincrease in the population of PV+ cells expressing c-Fos (i.e., c-Fos+PV+
cells in c-Fos+ cells) or c-Fos+ cells expressing PV (i.e., c-Fos+PV+ cells
in PV+ cells) (Fig. 3f and Supplementary Fig. 4f, g), indicating that theSD signiﬁcantly increased the activity of PV+ cells. The same effect wasseen with MK-801 administration; cortical c-Fos+PV+ cells were foundto be increased in MK-801-treated brains (Fig. 3g, h). These ﬁndings
indicate that prolonged wakefulness increases cortical PV-neuron
activity, implying that these neurons are involved in the homeostatic
regulation of sleep.

Activation of cortical PV neurons induces a rebound-sleeplike state

Cortical PV neurons are activated upon the prolonged
wakefulness
Although the PV+ cell density may not directly reﬂect their inhibitory
function, previous studies indicated that a lower number of PV neurons is associated with PV-neuron hypoactivity and reduced inhibition
onto excitatory neurons in ASD models24,25, whose sleep homeostasis is
impaired28. Thus, we next investigated the potential link between PVneuron activity and homeostatic regulation of sleep. After a 6-hour SD(ZT6), whole-mouse brains were collected for CUBIC-based clearing
and immunostaining of PV and c-Fos proteins33,34 (Fig. 3a and Supplementary Fig. 4a, b). A comparison of control (ad libitum sleep: S) andsleep-deprived (SD) brains revealed that SD increased c-Fos-positive(c-Fos+) cell density in many brain regions, consistent with previous

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The adeno-associated virus (AAV)-mediated targeting approach wasused to test the inﬂuence of PV-neuron activity on sleep architectureand sleep homeostasis (Fig. 3i). PV neurons were targeted using E11, aPV-neuron selective enhancer derived from the Pvalb gene region36.
The E11 enhancer and transgene(s) were packaged in the AAV-PHP.eB
vector (Fig. 3i), which can be systemically injected to deliver the vector
to the entire brain37. As previously reported36, nuclear-localized
mCherry signals under the E11 enhancer (E11-H2B-mCherry) deliveredby the AAV-PHP.eB vector were primarily detected in cerebral regions
including the isocortex (Fig. 3j, k). Colocalization analysis of E11-H2BmCherry and anti-PV immunostaining signals revealed that more than
80% of E11-labeled cells in the isocortex were PV+ cells, whereas E11labeled cells in other regions were less selective for PV+ cells (Fig. 3l
and Supplementary Figs. 5a–c). These results demonstrated that theE11 enhancer can, to some extent, selectively target cortical PV neurons. The neural population targeted by this system was termed as E11
neurons after that.
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Fig. 2 | PV-neuron distribution is altered along with development. a Whole-brain
analysis of PV+ cell distribution during post-weaning development. P21, P28, P35,
P42, P84, and P270 mouse brains were collected (n = 6 for each age). Each set ofwhole-brain images was uploaded to the CUBIC-Cloud and registered to the CUBICAtlas brain. Image of CUBIC-Atlas brain was from the CUBIC-Cloud. b The mean of
PV+ cell density in the whole brain (top), cerebral regions (middle), and brain-stem
regions (bottom) across post-weaning development (n = 6 for each age). Each point
represents the mean value of each age normalized by P21. c Representative wholebrain views of PV+ cell distribution from the dorsal and lateral sides at P28 and P84
ages. d A virtual cortical slice depicts a voxel-wise P-value heat map of PV+ celldensity in comparison to P28 and P84 brains. P28 and P84 brains were tested using

two-sided Welch’s t-test. Red and blue colors represent a signiﬁcant increase anddecrease in P84 brains compared to P28 brains, respectively. Gray was assigned toregions with no signiﬁcance (P > 0.05). e A region-wise heat map of relative cellnumber depicting changes in PV+ cell number in the isocortex. Red and blue colors
represent a signiﬁcant increase and decrease in P84 brains compared to P28 brains,respectively. f Mean PV+ cell density across post-weaning development in selectedcortical regions (n = 6 for each age). Each point represents the mean value of eachage normalized by that of P21. Images of coronal brain slice were from the Allen
Brain Atlas. Line plots show mean ± SEM. The Allen Brain Atlas ontology is used todeﬁne brain region acronyms. Source data are provided as a Source Data ﬁle.

To see if E11-neuron activity inﬂuenced sleep/wake stability,
we expressed a tetanus-toxin light-chain (TeLC) protein under theE11 enhancer to block SNARE-mediated synaptic transmission.
TeLC expression under the E11 enhancer resulted in a negligible

change in sleep duration but a signiﬁcant increase in PWS and PSW(Supplementary Fig. 5d–g), demonstrating that chronic silencingof E11 neurons resulted in sleep-wake state fragmentation. In linewith this, mice expressing TeLC (E11-TeLC mice) had shorter sleep

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Article

episodes in both the light and dark phases (Supplementary Fig. 5h).
We conducted chemogenetic manipulations of E11-neuron activity
to investigate the effects of acute changes in E11-neuron activity on
sleep-wake states (Fig. 3m). Mice expressing hM3Dq (E11-hM3Dq mice)
had an increase in sleep duration after clozapine-N-oxide (CNO)
administration (Fig. 3n and Supplementary Fig. 5i, j). In the E11-hM3Dqinduced sleep state, increased PWS and decreased PSW were observed(Fig. 3o, p and Supplementary Figs. 5k–n). This pattern is similar to therebound phase after SD (Fig. 1g–p), indicating that E11 neuron excitation

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caused the rebound-sleep-like state. Chemogenetic suppression, on theother hand, resulted in an acute reduction in sleep duration in miceexpressing hM4Di (E11-hM4Di mice) (Fig. 3n and Supplementary
Fig. 5i, j). The decreased sleep duration can be attributed to both wakeconsolidation (i.e., lower PWS) and sleep fragmentation (i.e., higher PSW)
(Fig. 3o, p and Supplementary Fig. 5k–n), demonstrating that chemogenetic suppression of E11 neurons reduced sleep stability. Similareffect was observed in chemogenetic manipulation using another PVneuron selective enhancer E22, which predominantly conﬁned gene
expression to cortical PV neurons36 (Supplementary Fig. 6a–f).
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Fig. 3 | Activation of PV-enhancer-targeted (E11) neurons induces a reboundsleep-like state. a Whole-brain analysis of c-Fos+PV+ cell distribution in sleepdeprived (SD) condition. Control (S) and SD brains were collected at ZT6.
b–d Normalized cell density (SD / S) of c-Fos+ (b), PV+ (c), and c-Fos+PV+ (d) cells inmajor brain regions (n = 6 for each group). Individual SD brains were normalized by
the mean of S brains (black-dashed lines), and the colored bars represent the meanof SD brains in each brain region. Two-sided Welch’s t-test was applied to thenormalized value of S brains. e, g A region-wise heat map of relative c-Fos+PV+ cellnumber in the isocortex. SD brains were compared to S brains (e), and MK-801injected brains were compared to saline-injected brains (g). f, h Rate of c-Fos+PV+
cells in c-Fos+ (left) or PV+ cells (right) in the isocortex under SD (n = 6 for eachgroup) (f) or MK-801 administration (n = 4 for each group) (h). The groups werecompared using two-sided Welch’s t-test. i AAV-based gene expression under E11

enhancer. j Representative whole-brain views of dorsal and lateral E11-H2B-mCherry
and anti-PV signals. k Whole-brain distribution of E11-H2B-mCherry signals (n = 4).
The plot depicts the demographics of mCherry+ cells in major brain regions. l The
positive predictive value (PPV) was calculated by dividing the number of mCherry+PV+ cells by the total number of mCherry+ cells (n = 4). m Each mouse received i.p.
injection in turn: 0, 1, 3, or 5 mg/kg CNO injection at ZT12, with at least 2 days
between injections. n–p Sleep duration (n), PWS (o), and PSW (p) on the days with
CNO injection during ZT12–15 (n = 8 for each group). Colored dots represent themean values in each condition. Individual’s mouse dots are connected by graydashed lines. Within the groups, two-sided Welch’s t-test with Bonferroni correction were run against the 0 mg/kg CNO condition. Bar and interval plots show
mean ± SEM. Brain region acronyms follow the ontology deﬁned by the Allen Brain
Atlas. Source data are provided as a Source Data ﬁle.

Fig. 4 | Suppression of E11 neurons inhibits rebound sleep. a Schematic diagramof CNO injection after sleep deprivation (SD). Every mouse received i.p. injection
after a 6-hour SD during ZT0–6. At ZT12, 0 (SD + Sal) or 0.25 (SD + CNO) mg/kg CNO
injection was given. One day before the scheduled day with SD and i.p. injections
are labeled before SD. b Sleep duration over 24 h in E11-mCherry (n = 12) and E11hM4Di (n = 11) mice on SD + Sal, SD + CNO, and before SD days. c, e, g Sleep
duration (c), PWS (e), and PSW (g) on the days shown in the panel during ZT12–15 (b).
Each gray dot represents an individual mouse of E11-mCherry (n = 12) and E11hM4Di (n = 11) groups, while the colored dots represent the mean in each condition.

Individual mouse dots are connected by gray-dashed lines. Two-sided Welch’s t-test
was used to compare the day with SD to the day before SD. d, f, h The differences(Δ) in sleep duration (d), PWS (f), and PSW (h) between SD day during and the before
SD day during ZT12–15. Two-sided Welch’s t-test was used to compare the groups in
the SD + Sal or SD + CNO conditions. Line and interval plots show mean ± SEM. In
box plot, boxes show the median, 25th and 75th percentiles, and whiskers show
minima to maxima excluding outliers. Source data are provided as a Source
Data ﬁle.

Suppression of cortical PV neurons inhibits rebound sleep

a lower CNO dosage that had little effect on the normal sleep-wakecycle (Supplementary Fig. 7a–g). Even in this condition, E11-hM4Di
mice had impaired homeostatic rebound in sleep duration after CNO
administration (E11-hM4Di mice: SD + CNO), whereas normal reboundsleep was observed in the absence of CNO administration (E11-hM4Di
mice: SD + Sal) (Fig. 4b, c). Mice only expressing mCherry (E11-mCherrymice) exhibited normal rebound sleep with or without CNO

We hypothesized that cortical PV-neuron activity is required forrebound sleep because acute enhancement of the activity induced arebound-sleep-like state (Fig. 3m–p and Supplementary Fig. 6a–f). To
test this, we used chemogenetic inhibition of E11 neurons from theonset of dark period in rebound phase because an increase of sleep
duration after SD is mainly shown during dark period (Fig. 4a). We used

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Articleadministration (E11-mCherry mice: SD + Sal or SD + CNO) (Fig. 4b, c).
The comparison of E11-mCherry and E11-hM4Di mice conﬁrmed the
impaired rebound sleep in the E11-hM4Di mice with CNO administration (Fig. 4d). Rebound responses in PWS and PSW were also reduced inE11-hM4Di mice after CNO administration (E11-hM4Di mice: SD + CNO)
(Fig. 4e–h). These ﬁndings suggested that rebound sleep responses(i.e., increased sleep duration, increased PWS, and decreased PWS)
require increased E11-neuron activity.

CaMKII inhibition in cortical PV neurons impairs sleep
homeostasis
We then sought to identify key molecules in cortical PV neurons thatare involved in the regulation of sleep architecture and homeostasis.
To that end, we concentrated on CaMKII within PV neurons because
the phosphorylation states of CaMKII and its potential substrates inforebrain synapses change with sleep-wake states32,38,39, and animals
with CaMKIIα/β genetic modiﬁcation had abnormal sleep
architecture29,30.
Using open single-cell RNA sequencing (scRNA-seq) data40, we
ﬁrst examined the mRNA expression of CaMKII isoforms within cortical PV neurons. For this dataset, we considered cells assigned to thePvalb subclass in the scRNA-seq data to be PV neurons. All CaMKII
isoforms (Camk2a, Camk2b, Camk2g, and Camk2d) were detected at
the mRNA level in cortical PV neurons (Supplementary Fig. 8a–d).
Furthermore, we used other scRNA-seq data to investigate the developmental changes in the CaMKII expression pattern41. Camk2a
expression level and positive-cell rate in PV neurons were higher in theyoung adults (P60) compared to juveniles (P21) (Supplementary
Fig. 8e–h). CaMKII isoforms are expressed within cortical PV neurons,
and the expression pattern of Camk2a is developmentally modulated.
To see if CaMKII within PV neurons regulates sleep architecture
based on its kinase activity, we inhibited the kinase activity of endogenous CaMKII in E11 neurons with CN19o, an optimized CaMKII
inhibitory peptide42 (Fig. 5a). Mice expressing mCherry-fused CN19o
under the E11 enhancer (E11-CN19o mice) showed no signiﬁcant difference in sleep duration when compared to mice expressing mCherryfused CN19scr (E11-CN19scr mice), the CN19o scrambled sequence(Supplementary Fig. 9a). However, the E11-CN19o mice had higher PWS
and PSW than the E11-CN19scr mice (Supplementary Fig. 9b, c). Theseﬁndings show that CaMKII inhibition caused sleep-wake state fragmentation in a case similar to E11-neuron chronic silencing (Supplementary Fig. 5c–e).
Following that, we performed a 6-h SD on E11-CN19o and E11CN19scr mice to investigate the effects of CaMKII kinase activity in E11
neurons on the homeostatic regulation of sleep amount (Fig. 5a).
Surprisingly, the E11-CN19o mice barely showed the homeostatic
rebound in sleep duration, whereas the E11-CN19scr mice clearly
showed rebound responses following SD (Fig. 5b–d and Supplementary Fig. 9d). Increased PWS (i.e., fragmented wakefulness) anddecreased PSW (i.e., consolidated sleep), both of which are hallmarks ofrebound sleep, were barely observed in E11-CN19o mice (Fig. 5e, f).
After MK-801 administration, the E11-CN19o mice showed lower
rebound responses than the E11-CN19scr mice, which is consistent withthe case of SD (Fig. 5g–k and Supplementary Fig. 9e). These ﬁndings
suggest that CaMKII kinase activity in E11 neurons is important for bothbasal sleep architecture and homeostatic rebound of sleep duration.
In order to conduct a detailed analysis of sleep architecture, we
performed EEG/EMG recording in E11-CN19o mice. There was no signiﬁcant difference in NREM sleep or REM sleep duration between the
E11-CN19o and E11-CN19scr mice (Fig. 5l, m). The E11-CN19o mice, on
the other hand, had higher transition probabilities between wake and
NREM sleep states (i.e., increased W → N and N → W) and lower statestabilities (i.e., decreased W → W and N → N) (Fig. 5n). The level of delta(0.5–4.0 Hz) or slow oscillation (SO, 0.5–1.0 Hz) power (i.e., the SWA)
during NREM sleep is correlated with the level of sleep depth43. The

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delta power of the E11-CN19o mice decreased signiﬁcantly during
NREM sleep (Fig. 5o, p and Supplementary Fig. 9f–h). These ﬁndings
show that decreased CaMKII activity in the E11 neurons reduces NREM
sleep quality (i.e., its stability and delta power).
We next investigated whether CaMKII in cortical PV neurons is
involved in the homeostatic regulation of the SWA as well as sleep
duration. We performed a 6-hour SD on E11-CN19o and E11-CN19scr
mice under EEG/EMG recording (Fig. 6a). The delta power during
NREM sleep was signiﬁcantly increased after SD and returned tobaseline over 6 h in the E11-CN19scr mice (Fig. 6b, c). In contrast, theE11-CN19o mice presented no remarkable increase in delta power afterSD, suggesting that the homeostatic rebound in delta power after SD
was attenuated in the E11-CN19o mice (Fig. 6b, c). Accordingly, thedelta power rebound was signiﬁcantly lower in the E11-CN19o micecompared to the E11-CN19scr mice (Fig. 6d). These results indicate that
CaMKII kinase activity in E11 neurons is crucial not only for homeostatic rebound of sleep amount but also for homeostatic rebound of
the SWA.
To express CN19o in cortical PV neurons more speciﬁcally, we
employed a conﬁnement strategy using the E11 enhancer and Pvalb−2A-Cre mice (Fig. 6e). Cre-dependent expression of E11-CN19o resulted in a reduction in REM sleep duration, while it had no signiﬁcant
impact on total sleep or NREM sleep duration (Supplementary
Fig. 9i–k). In contrast, a signiﬁcant reduction in delta power during
NREM sleep was observed (Supplementary Fig. 9l–n). The Credependent E11-CN19o expression markedly attenuated the homeostatic rebound in delta power following SD (Fig. 6f–h), while its effecton the homeostatic rebound in sleep duration was less pronounced
and exhibited high individual variation (Supplementary Fig. 9o–p).

CaMKII activation in cortical PV neurons induces rebound sleep
We then investigated the links between CaMKII activation in E11 neurons and sleep architectures and sleep homeostasis. Because changes
in the expression level of Camk2a during development are more visible
than those of the other CaMKII isoforms (Supplementary Fig. 8g, h), weconcentrated on the CaMKIIα isoform in E11 neurons. CaMKIIα isactivated by Ca2+/calmodulin (CaM) binding and autophosphorylates
threonine (T) 286 to maintain kinase activity even when Ca2+/CaM is
not present44 (Fig. 7a). As a result, the T286 phosphomimetic mutant(T286D), in which the threonine (T) is replaced with aspartic acid (D),becomes constitutively kinase-active form and phosphorylates physiological substrates including the T286 residue in endogenous
CaMKIIα44. To see if CaMKIIα activation in E11 neurons affects sleep
architecture, we expressed either wild-type (WT) or active-formed(T286D) CaMKIIα under the E11 enhancer. Mice expressing WT CaMKIIα (E11-CaMKIIα (WT) mice) showed no differences in all sleep
parameters (sleep duration, PWS, and PSW) when compared to control(E11-EGFP) mice (Fig. 7b–d). In contrast, E11-CaMKIIα (T286D) mice hada signiﬁcantly longer sleep duration than E11-EGFP and E11-CaMKIIα(WT) mice (Fig. 7b). The E11-CaMKIIα (T286D) mice also had higher PWS
and lower PSW (Fig. 7c, d). These ﬁndings suggest that CaMKIIα activation in E11 neurons induces a sleep-predominant state similar to therebound sleep (i.e., increased sleep duration, increased PWS, anddecreased PWS). T286 non-phosphomimetic alanine (A) mutation (i.e.,
T286A) or kinase-dead mutation (K42R) adding to T286D (i.e.,
K42R:T286D) did not exhibit the changes of sleep parameters as
observed in E11-CaMKIIα (T286D) mice (Supplementary Fig. 10a–c),
conﬁrming that the sleep-promoting effects require the constitutive
kinase activity of expressed CaMKIIα. The expression of constitutively
active CaMKIIβ (T287D) under the E11 enhancer also resulted in arebound-sleep-like state as well as CaMKIIα activation (Supplementary
Fig. 10d–f).
The next step was to see if the sleep-promoting effects of CaMKIIαactivation in E11 neurons were dependent on the circadian core clock
genes. CaMKIIα (WT or T286D) was expressed under the E11 enhancer
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Fig. 5 | Inhibition of CaMKII activity in E11 neurons inhibits rebound in sleep
amount. a Diagram of CaMKII inhibition by CN19o peptide (left) and experimental
schedule (right). b Cumulative sleep loss (SD – Basal) in E11-CN19scr and E11-CN19o
mice over 24 h (n = 8 for each group). The averaged parameters from the three days
prior to SD are shown as Basal. c, e, f Sleep duration (c), PWS (e), and PSW (f) during
ZT12–24 on Basal and SD (n = 8 for each group). Two-sided Student’s paired t-test
was performed within the groups. d Sleep rebound ratio (SD/Basal during ZT12-24;
n = 8 for each group). Two-sided Welch’s t-test was used. g Cumulative sleep loss
(MK-801 – Saline) in E11-CN19scr and E11-CN19o mice over 24 h (n = 10 for eachgroup). Each mouse received saline or 2 mg/kg MK-801 injection at ZT8, allowing atleast 2 days between injections. h, j, k Sleep duration (h), PWS (j), and PSW (k) during
ZT12–24 on days with saline or MK-801 injection (n = 10 for each group). Two-sided
Student’s paired t-test was used within the groups. i Sleep rebound ratio (MK-801 /Saline during ZT12–24, n = 10 for each group). Two-sided Welch’s t-test was used.
l, m Daily NREM sleep duration (l) and REM sleep duration (m) in E11-CN19scr (n = 4)
and E11-CN19o (n = 6) mice. Two-sided Welch’s t-test was used. n The differences intransition probabilities between wake, NREM, and REM sleep states. The solid-red
and dotted-gray lines represent a signiﬁcant increase and decrease, respectively.
o Power spectral density (PSD) of the EEG during NREM sleep. The extracted diagram in the 0–10 Hz range is also shown (top-right). p Normalized delta power(0.5–4 Hz) during NREM sleep in E11-CN19scr (n = 4) and E11-CN19o (n = 6) mice.
Two-sided Welch’s t-test was used. Line and interval plots show mean ± SEM. In box
plot, boxes show the median, 25th and 75th percentiles, and whiskers show minima
to maxima excluding outliers. *P < 0.05, **P < 0.01. Source data are provided as a
Source Data ﬁle.

in Per1-/-:Per2-/- (Per dKO) or Cry1-/-:Cry2-/- (Cry dKO) mice (Fig. 7e). Under
constant dark (DD) conditions, these dKO lines exhibit arrhythmic
circadian behavior45,46. Regardless of circadian time (CT), E11-CaMKIIα(T286D) mice in both Per dKO and Cry dKO backgrounds kept under
DD condition showed a signiﬁcant increase in sleep duration compared to E11-CaMKIIα (WT) mice (Fig. 7f and Supplementary Fig. 10g, j).
The increased sleep amount in E11-CaMKIIα (T286D) mice is explainedby higher PWS and lower PSW (Fig. 7g, h and Supplementary Fig. 10h–i,k–l). These ﬁndings imply that CaMKII-mediated sleep facilitation is
independent of behavioral circadian rhythmicity.

Given the rebound-sleep-like phenotype observed in E11-CaMKIIα(T286D) mice (Fig. 7b–d), it is reasonable to conclude that these mice
have already acquired the saturated sleep need and that further SD
does not effectively induce rebound sleep. To put this theory to thetest, we performed a 6-hour SD on E11-CaMKIIα (T286D) mice. The E11CaMKIIα (T286D) mice had rebound sleep characteristics even in basal
sleep and only had marginal rebound sleep after the SD (Supplementary Fig. 10m–q). Similarly, after MK-801 administration, E11-CaMKIIα(T286D) mice showed lower rebound responses (Supplementary
Fig. 10r–v). These ﬁndings support the notion that constitutive

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Fig. 6 | Inhibition of CaMKII activity in E11 neurons inhibits rebound in slowwave activity. a Diagram of CN19o expression in E11 neurons for CaMKII inhibition.
b Hourly normalized delta power (0.5–4 Hz) during NREM sleep in E11-CN19scr(n = 22) and E11-CN19o mice (n = 15) in SD experiments. Mice were allowed tobehave freely for 1 day prior to SD, and the value is shown as Basal. SD was effectively performed during ZT0–6 with a high success rate (93.4 ± 5.3%). c Normalized
delta power during NREM sleep on Basal and SD during ZT6–12 in E11-CN19scr(n = 22) and E11-CN19o mice (n = 15). Two-sided Welch’s t-test was performed
between Basal and SD within the groups. d The percentage of delta power change
upon SD during ZT6–12 in E11-CN19scr (n = 22) and E11-CN19o mice (n = 15). The
groups were compared using two-sided Welch’s t-test. e Diagram of CN19o
expression in cortical PV neurons with enhanced speciﬁcity using E11 enhancer andPvalb−2A-Cre mice. f Hourly normalized delta power (0.5–4 Hz) during NREM sleepin Pvalb−2A-Cre:E11-DIO-CN19scr (n = 16) and Pvalb−2A-Cre:E11-DIO-CN19o mice(n = 13) in SD experiments. Mice were allowed to behave freely for 1 day prior to SD,
and the value is shown as Basal. SD was effectively performed during ZT0–6 with ahigh success rate (95.0 ± 6.2%). g Normalized delta power during NREM sleep on
Basal and SD during ZT6–12 in Pvalb−2A-Cre:E11-DIO-CN19scr (n = 16) and Pvalb−2A-Cre:E11-DIO-CN19o mice (n = 13). Two-sided Welch’s t-test was performed
between Basal and SD within the groups. h The percentage of delta power change
upon SD during ZT6–12 in Pvalb−2A-Cre:E11-DIO-CN19scr (n = 16) and Pvalb−2ACre:E11-DIO-CN19o mice (n = 13). The groups were compared using two-sided
Welch’s t-test. Line plots show mean ± SEM. In box plot, boxes show the median,
25th and 75th percentiles, and whiskers show minima to maxima excluding outliers.
Source data are provided as a Source Data ﬁle.

CaMKIIα activation in E11 neurons induces a rebound-sleep-like state,
and that the mice already had a saturated level of sleep need.
Furthermore, we recorded EEG and EMG in E11-CaMKIIα (WT) andE11-CaMKIIα (T286D) mice. The increased sleep duration in the E11CaMKIIα (T286D) mice is due to an increase in NREM sleep (Fig. 7i),
whereas REM sleep did not differ between groups (Fig. 7j). Consistent
with this, E11-CaMKIIα (T286D) mice had higher NREM sleep stability(i.e., increased N → N) (Fig. 7k). The SO power was increased in E11CaMKIIα (T286D) mice (Fig. 7l, m and Supplementary Fig. 11a, b), but
the delta power changes were not signiﬁcant (Fig. 7l and Supplementary Fig. 11c). These ﬁndings show that constitutive CaMKIIα activationin E11 neurons improves both the quantity and quality of NREM sleep.
To conﬁrm the involvement of cortical PV neurons, weemployed the conﬁnement strategy using the E11 enhancer and Pvalb−2A-Cre mice for speciﬁc CaMKIIα expression in cortical PV neurons(Fig. 7n). Similar to the direct CaMKIIα expression under the E11
enhancer, the rebound-sleep-like state was induced by Cre-dependent
CaMKIIα (T286D) expression under the E11 enhancer (Fig. 7o–q).
Sleep-promoting effects were also observed with Cre-dependent
CaMKIIα (T286D) expression under pan-neural hSyn promoter (Supplementary Fig. 11d–g). These ﬁndings further support the hypothesisthat CaMKII activation in cortical PV neurons induces rebound sleep.

expressing CaMKIIα (T286D) in E11 neurons to look at the activity ofcortical PV neurons. The isocortex contained more than three-quartersof the detected c-Fos+PV+ cells (Fig. 8a, b). When E11-CaMKIIα (T286D)
brains were compared to E11-CaMKIIα (WT) brains, c-Fos+PV+ cells
were increased in entire cortical regions (Fig. 8c). CaMKIIα (T286D)
expression in E11 neurons selectively enhanced c-Fos expression incortical PV neurons (Fig. 8d, e) but had little effect on the overall
number of c-Fos+ or PV+ cells (Supplementary Fig. 12a, b). Theseﬁndings imply that intracellular CaMKII activation increases PV-neuron
activity. Given that prolonged wakefulness also increases PV-neuron
activity (Fig. 3d–h), higher sleep needs appear to increase the activity,
regardless of whether the preceding state was sleep or wakefulness.
We next evaluated whether enhancement of c-Fos expression
upon CaMKII activation is characteristic of PV neurons. We expressed
CaMKIIα and H2B-mCherry in excitatory neurons using Vglut2-ires-Cre
mice to induce intracellular CaMKII activation in Vglut2 neurons, not in
PV neurons (Supplementary Fig. 13a, b). The sleep-promoting effects
were observed with CaMKIIα (T286D) expression in Vglut2 neurons(Supplementary Fig. 13c–e), consistent with sleep induction by CaMKIIβ activation in this population30. However, CaMKIIα (T286D)
expression in Vglut2 neurons did not alter c-Fos expression proﬁle ofcortical Vglut2 neurons (Supplementary Fig. 13f, g), suggesting that
intracellular CaMKII activation speciﬁcally enhances PV-neuron activity, rather than excitatory neuron activity, despite their similar sleeppromoting effects.
The next step was to see if the level of CaMKII T286 autophosphorylation in cortical PV neurons increases in response to theaccumulation of sleep need. We developed a system for measuring
CaMKIIα T286 autophosphorylation using liquid chromatography with

CaMKII activity in cortical PV neurons reﬂects sleep need
CaMKII kinase activity in E11 neurons has similar effects on sleep
homeostasis as E11-neuron activity manipulation. These ﬁndings support the hypothesis that CaMKII activation increases cortical PVneuron activity, causing rebound sleep. To test this hypothesis, weused double immunostaining of PV and c-Fos proteins in brains

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Fig. 7 | Elevation of CaMKIIα activity in E11 neurons induces rebound-sleeplike state. a Illustration of CaMKIIα protein sequences (left) and endogenous
CaMKIIα activation mechanism (right). The phosphorylation of T286 residue in theregulatory segment is critical for CaMKIIα activity regulation. b–d Daily sleep
duration (b), PWS (c), and PSW (d) in E11-EGFP (n = 11), E11-CaMKIIα (WT) (n = 11), andE11-CaMKIIα (T286D) (n = 12) mice. The groups were compared using two-sided
Welch’s t-test with Bonferroni correction. e Diagram of CaMKII expression andexperimental schedule in Per or Cry dKO mice under constant dark conditions.
f–h Daily sleep duration (f), PWS (g), and PSW (h) in the Per (left) or Cry (right) dKO
mice expressing E11-CaMKIIα (WT) (n = 7 or 6) or E11-CaMKIIα (T286D) (n = 6 or 5).
The groups were compared using two-sided Welch’s t-test. i, j Daily NREM sleep
duration (i) and REM sleep duration (j) in E11-CaMKIIα (WT) and E11-CaMKIIα(T286D) mice (n = 8 for each group). The groups were compared using two-sided
Welch’s t-test. k The difference in transition probabilities between wake, NREM, andREM sleep states in E11-CaMKIIα (T286D) mice versus E11-CaMKIIα (WT) mice. The
solid red and dotted gray lines represent a signiﬁcant increase and decrease,respectively. l Power spectral density (PSD) of the EEG during NREM sleep. The
extracted diagram in the 0–10 Hz range is also shown in the top-right corner of thepanel. m Normalized slow-oscillation power (SO, 0.5–1 Hz) during NREM sleep in
E11-CaMKIIα (WT) and E11-CaMKIIα (T286D) mice (n = 8 for each group). The
groups were compared using two-sided Welch’s t-test. n Diagram of CaMKIIαexpression in cortical PV neurons with enhanced speciﬁcity using E11 enhancer andPvalb−2A-Cre mice. o–q Daily sleep duration (o), PWS (p), and PSW (q) in Pvalb−2ACre:E11-DIO- CaMKIIα (WT), and Pvalb−2A-Cre:E11-DIO-CaMKIIα (T286D) mice(n = 12 for each group). The groups were compared using two-sided Welch’s t-test.
Line and interval plots show mean ± SEM. *P < 0.05, **P < 0.01. Source data areprovided as a Source Data ﬁle.

tandem mass spectrometry (LC-MS/MS) in conjunction with AAVmediated expression of watermark mutant CaMKIIα in E11 neurons(Fig. 8f). We created a watermark mutation near CaMKIIα T286
autophosphorylation residue by replacing glutamic acid (E) withaspartic acid (D) (i.e., E285D). The watermark mutant CaMKIIα (E285D)
is distinguishable from all endogenous CaMKII isoforms(Supplementary Fig. 14a), allowing us to selectively quantify the T286
autophosphorylation level of CaMKIIα (E285D) expressed in the brain(Fig. 8f). We conﬁrmed that CaMKIIα (E285D) expression and kinase
activity were nearly identical to WT CaMKIIα (Supplementary
Fig. 14b, c). We also conﬁrmed that no difference in any sleep parameters was observed between E11-CaMKIIα (WT) and E11-CaMKIIαNature Communications | (2024)15:6054

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Article(E285D) mice under basal and sleep-deprived conditions (Supplementary Fig. 14d–n). These ﬁndings show that the E285D mutation has
no effect on CaMKIIα physiological function in vitro or in vivo. We gave
the E11-CaMKIIα (E285D) mice a 6-h SD and collected their corticalregions of brain immediately afterward (Fig. 8f). T286 phosphorylation(pT286) level derived from E11-CaMKIIα (E285D) increased in SD groupcompared to ad libitum sleep (S) group (Fig. 8g). Although pT286 levelserves as a surrogate for CaMKIIα kinase activity, this result suggests

Nature Communications | (2024)15:6054

https://doi.org/10.1038/s41467-024-50168-5

that CaMKII kinase activity in cortical PV neurons increases upon theaccumulation of sleep need.

Discussion
We identiﬁed cortical PV neurons as a neural population responsible
for homeostatic sleep rebound. We also discovered that CaMKII kinase
activity in cortical PV neurons is essential for rebound sleep. As a result,
we propose a model in which CaMKII kinase activity increases cortical11

Articlehttps://doi.org/10.1038/s41467-024-50168-5

Fig. 8 | CaMKII activity in E11 neurons reﬂects sleep need. a Representative
whole-brain views of dorsal and lateral double-positive (c-Fos+PV+) cell distribution. The brains of E11-CaMKIIα (WT) (left) and E11-CaMKIIα (T286D) (right) mice
were collected. b Stacked percentage bar plots of c-Fos+PV+ cells in the E11CaMKIIα (WT) and E11-CaMKIIα (T286D) brains (n = 4 for each group). The plot
depicts the demographics of c-Fos+PV+ cells in major brain regions. c A region-wiseheat map of relative cell number showing changes in c-Fos+PV+ cell number in theisocortex. The E11-CaMKIIα (T286D) brains were compared to the E11-CaMKIIα(WT) brains, with red indicating an increase and blue indicating a decrease. d The
rate of double-positive (c-Fos+PV + ) cells in c-Fos+ cells in each cortical region (left)or entire isocortex (right). The groups were compared using two-sided Welch’s ttest. e The cortical distribution of c-Fos signal intensity per c-Fos+PV+ cell in eachgroup. f Experimental design for quantitative analysis of CaMKIIα T286

phosphorylation in E11 neurons. The cortical region of E11-CaMKIIα (T285D) mousebrain was dissected, and homogenates were used for LC-MS/MS analysis. g Signal
intensities of peptides derived from CaMKIIα (T285D) with phosphorylated T286
residues (n = 21 for each group). The intensities were normalized to the total
CaMKIIα level, which was calculated using all quantiﬁable non-phosphorylated
peptides derived from WT CaMKIIα. Two-sided two-samples Wilcoxon test wasused to compare the groups. h CaMKII-dependent activity regulation of cortical PV
neurons for homeostasis regulation. i Cortical feedback circuit model for sleep
homeostasis regulation. Bar plots show mean ± SEM. In box plot, boxes show themedian, 25th and 75th percentiles, and whiskers show minima to maxima excluding
outliers. Brain region acronyms follow the ontology deﬁned by the Allen Brain
Atlas. Source data are provided as a Source Data ﬁle.

PV-neuron activity, resulting in homeostatic sleep rebound (Fig. 8h).
This model is supported by the following: (1) the inhibition/activationof cortical PV neurons suppresses/induces rebound sleep; (2) Prolonged wakefulness activates cortical PV neurons and CaMKII within
the neurons; (3) CaMKII activation in cortical PV neurons evokes PVneuron activity and a rebound-sleep-like state, while inhibition suppresses rebound sleep. These ﬁndings imply that cortical negative
feedback circuits formed by PV neurons regulate sleep homeostasis.
Although previous research has shown that subcortical and/or
brain-stem regions regulate sleep homeostasis across the brain, brainwide regulatory systems are unable to fully account for several aspectsof sleep homeostasis as demonstrated by local sleep, in which corticalactivity becomes a sleep pattern locally. Recent research has revealed
that silencing cortical excitatory (pyramidal) neurons in layer 5 resultsin impaired sleep rebound47, demonstrating cortical regulation of
sleep homeostasis. In this study, we discovered that increased activityof cortical PV neurons is required for rebound sleep. Our ﬁndings
emphasize the importance of both cortical excitatory and inhibitory
neurons in the regulation of sleep homeostasis. PV neurons establish
negative feedback loops with pyramidal neurons, enabling the detection and synchronization of local circuit activity48,49. Given that synchronized cortical activity correlates with an expected level of sleep
need50, cortical PV neurons may regulate the synchronicity of local
cortical microcircuits and generate cortical slow waves in collaboration with other inhibitory neurons51,52. The microcircuits, characterized
by reciprocal connections between pyramidal and PV neurons, arewidespread across cortical areas and species49,53,54. It would be interesting to see if the microcircuits of pyramidal-PV neurons are
responsible for the local sleep observed in the mammalian cortex.
While kinase activity, including CaMKII and salt-inducible kinase 3(SIK3), in excitatory neurons has been shown to inﬂuence baseline
sleep amounts and depth30,55, the speciﬁc kinases involved in homeostatic regulation of sleep within inhibitory neurons remain unidentiﬁed. Our ﬁndings suggest that CaMKII kinase activity in corticalPV neurons is one of the molecular factors reﬂecting sleepiness.
CaMKII inhibition in excitatory neurons resulted in changes in the total
amount of daily sleep30. In contrast, CaMKII inhibition in cortical PV
neurons had minimal impact on daily sleep amount but impaired
homeostatic rebound of sleep. Moreover, the intracellular CaMKII
activation speciﬁcally enhances the activity of cortical PV neurons(Fig. 8c–e), not excitatory neurons (Supplementary Fig. 13f, g), eventhough both have similar sleep-promoting effects. These ﬁndings
suggest that distinctive CaMKII signaling pathways exist in cortical PV
neurons for the homeostatic regulation of sleep (Fig. 8i). The precise
molecular mechanisms underlying this modulation remain unclear,but synaptic strength and/or intrinsic excitability in PV neurons may bealtered. Indeed, sleep-wake states inﬂuence neural activity of corticalPV neurons and a balance between synaptic excitation and inhibition(E-I balance) in cortical microcircuits13,14,56. Although the downstream
targets (i.e., substrates) of CaMKII remain unknown, the core circadianclock factors are not involved (Fig. 7e–h and Supplementary

Fig. 10g–l). The voltage-dependent K+ channels Kv3.1 and Kv3.3 may be
important candidates because double knockout of these channels
changes the electrophysiological properties of PV neurons and impairs
rebound sleep57. It will be important to investigate what physiologicalproperties of PV neurons are modulated by CaMKII and what molecular mechanisms are responsible for this modulation through physiological recordings.
While studies in rats and mice contributed to understanding of
the developmental aspects of sleep homeostasis, the results acrossthese studies are not fully consistent. Some studies suggest that
homeostatic rebound in sleep amount emerges even before weaning
in rats22,58, whereas others indicate that it matures during the postweaning period in rats or mice21,23. Our longitudinal sleep recordings indeveloping mice found that rebound sleep appears late in developmental stage (Fig. 1g–p). Long-term EEG/EMG recording to assess the
SWA remains a future challenge, as it could not be validated in thislongitudinal sleep recording. However, it is noteworthy that the SWA is
negatively correlated with the number of micro-arousals43, suggestingthat the decreased PSW could serve as a surrogate for the increased
SWA. Consistent with the previous report that a signiﬁcant increase in
SWA after SD is observed only in mice older than 6 weeks old21, asigniﬁcant decrease in PSW after SD was observed at 8 and 12 weeks old,but not at 4 weeks old (Fig. 1k,p). Our ﬁndings align with previous
reports suggesting that the homeostatic regulatory system of sleep isimmature in juveniles and matures during the post-weaning period
in mice.
The scRNA-seq analysis revealed that Camk2a expression in cortical PV neurons increases from juveniles to adulthood (Supplementary Fig. 8e–h). Given that CaMKIIα in cortical PV neurons is required
for rebound sleep, the lack of rebound response in the juvenile phase
may be due to premature CaMKII activation for rebound sleep induction. While it was conventionally believed that cortical PV neurons lack
CaMKIIα expression at the protein level, a recent study identiﬁed
CaMKIIα protein signals in a subpopulation of cortical PV neurons59.
Another study demonstrated that CaMKIIγ in cortical and hippocampal PV neurons plays a crucial role in synaptic regulation andmemory60. Investigating the developmental changes in protein
expression of CaMKII isoforms within PV neurons and their speciﬁcfunctions in sleep homeostatic regulation remains crucial tasks for
future research.
Various cortical and subcortical cell populations, including neurons and glial cells, contribute to homeostatic regulation of
sleep6,47,61,62. Sleep substances such as adenosine and cytokines are also
involved in this regulation63. Investigating the interplay of these factors
and cortical PV neurons to regulate sleep homeostasis would be
intriguing for future research. As a recent study revealed that distinct
populations of excitatory neurons respectively regulate sleep durationand SWA through SIK3 signaling55, it also may be crucial to identify
subpopulation(s) of PV neurons involved in homeostatic rebound in
sleep duration and SWA. Previous ﬁnding showed that activating cortical PV neurons in the M2 cortex increased NREM sleep duration but

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Articledecreased the SWA15, whereas our results indicated that elevating E11neuron activity through CaMKII activation increases both NREM sleep
duration and SWA. These differences might be attributed to the heterogeneous nature of cortical PV neurons and the E11 enhancer’s
potential to selectively target speciﬁc subpopulation(s) within theseneurons36,40. Furthermore, CaMKII inhibition in E11 neurons signiﬁcantly suppressed homeostatic rebound in sleep duration and SWA,
whereas combining the E11 enhancer and Pvalb−2A-Cre mice predominantly suppressed SWA rebound. Although this difference may
result from lower efﬁciency of CaMKII inhibition in the Cre-dependent
expression, there is a possibility that speciﬁc subpopulations within E11
neurons regulate the two aspects of homeostatic rebound of sleep
with different efﬁciencies.
In conclusion, we propose that CaMKII is a key molecular factor in
cortical PV neurons for encoding sleep need and inducing reboundsleep. The proposed mechanism may be responsible for local sleep
homeostasis via the canonical negative feedback circuit in corticalinhibitory-excitatory neuron network (Fig. 8i). Such a regulatory motif
for sleep homeostasis may be conserved across the animal kingdom: adistinct negative feedback circuit in ﬂies is critical for sleep homeostasis regulation, with physiological properties modulated by sleep
need64,65. The design principle of the sleep homeostatic machinery may
be shared across species.

Methods
Mice
The Animal Care and Use Committee of the Graduate School of Medicine in the University of Tokyo or the Institutional Animal Care and
Use Committee of RIKEN BDR approved all animal care and experimental procedures. Mice were housed in humidity- and temperaturecontrolled conditions on a 12-hour light/dark (LD) cycle, with standard
chow and water available ad libitum in groups, unless otherwise speciﬁed. This study used C57BL/6NJcl (B6N WT) mice (CLEA Japan), Pvalb−2A-Cre mice (heterozygous B6.Cg-Pvalbtm1.1(cre)Aibs/J mise; #012358, The
Jackson Laboratory), Vglut2-ires-Cre mice (heterozygous Slc17a6tm2(cre)Lowl/J mouse; #016963, The Jackson Laboratory), Per1-/-:Per2-/- (Per dKO)
mice45, and Cry1-/-:Cry2-/- (Cry dKO) mice46. Pvalb−2A-Cre, Vglut2-iresCre, Per dKO, and Cry dKO mice were derived from ES cells using 3i
methods and used in experiments without crossing66. All mice used inthis study were 3–12 weeks old male to avoid the inﬂuence of the estrus
cycle in females.

Plasmids
Except for CN19o expressing vectors without DIO sequences, pAAV
plasmids were built using pAAV-hSyn-DIO-hM3Dq-mCherry (Addgene#44361, kindly provided by Dr. Bryan Roth). CN19o expressing vectors
without DIO sequences were constructed from another pAAV backbone kindly provided by Dr. Hirokazu Hirai30. The promoter/enhancer,
reporter/effector, WPRE, and polyA sequences were all present in all
pAAV plasmids between ITRs (Fig. 3i). The enhancers were placed
upstream of a minimal human β-globin promoter (Addgene #83900,
kindly provided by Dr. Gordon Fishell). TeLC, hM3Dq or hM4Di
sequence was cloned from pAAV-hSyn-FLEX-TeLC-P2A-EYFP (Addgene
plasmid #135391, a gift from Dr. Fan Wang), pAAV-hSyn-DIO-hM3DqmCherry, or pAAV-hSyn-DIO-hM4Di-mCherry (Addgene plasmid#44362, a gift from Dr. Bryan Roth). CN19scr (VKEARIDGKPDALRGQKQI) or CN19o (KRAPKLGQIGRQKAVDIED) sequence
was fused to the C-terminus of mCherry via a (GGGGS)x3 linker.
Camk2b sequence was cloned from pAAV-hSyn-FLAG-CaMKIIβ used in
our previous report30. Camk2a sequence (NM_177407) was ampliﬁed
and cloned from C57BL/6 N mouse cDNA. The Infusion HD Cloning Kit(Takara Bio) was used to clone these sequences. Detailed vector
information can be found in Supplementary Table 1.
The plasmids were then introduced into competent cells DH5α
(TOYOBO) or NEB stable (New England Biolabs). The plasmids were

Nature Communications | (2024)15:6054

https://doi.org/10.1038/s41467-024-50168-5

puriﬁed using the Pure Yield Plasmid Midiprep System (Promega) anddigested with XmaI (New England Biolabs) to ensure ITR integrity.

Adeno-associated virus
In this study, we used an engineered AAV serotype, AAV-PHP.eB37, andgenerated AAVs based on the previous reports67. AAVpro 293 T cells(632273, Takara Bio) were transfected using Polyethylenimine (PEI,
MW 25,000, Polysciences) with three plasmids: pAAV (containing thegene(s) of interest), pUCmini-iCAP-PHP.eB (Addgene #103005, kindly
provided by Dr. Viviana Gradinaru), and pHelper (Takara Bio). The
medium from cultured AAVpro 293 T cells was collected three days
after transfection, and the cells and medium were harvested at leastﬁve days later. Centrifugation (2000×g, 15 min, and 25 °C) was used toseparate the harvested cells and medium. Freeze-thawing lysed thepellets, which were then treated with Benzonase Nuclease (Merck) or
TurboNuclease (Accelagen) to digest non-packaged DNA. The lysates
were mixed with 8% (wt/vol) polyethylene glycol (PEG MW 8,000, MP
Biomedical). AAVs were isolated from the salting-out supernatant
using ultracentrifugation (350,000 × g, 2 h 25 min, 18 °C; Optima XE90, Beckman Coulter; Type 70Ti Fixed-Angle Titanium Rotor, Beckman Coulter) with iodixanol (OptiPrep, Sigma). Before use, an AAV
solution in Dulbecco’s phosphate-buffered saline (DPBS) was concentrated using a centrifuge (AmiconUltra-15, Merck) andstored at 4 °C.
The titration method was adapted from previous reports67. Using
quantitative PCR (qPCR), AAV titers were calculated as the number ofeffective vector genomes (vg) in AAV solution. To avoid contaminationof non-packaged DNA, a portion of the AAV solution was treated with
nuclease (50 U/ml, 1 h, 37 °C; Benzonase Nuclease or TurboNuclease).
Proteinase K (30 μg/ml, 1 h, 37 °C; N-lauroylsarcosine in 3 mM NaCl,
Fujiﬁlm) was then added to the AAV solution to digest the viral capsid
and release the viral genome. A general phenol/chloroform extractionand ethanol precipitation method was used to purify the viral genome.
AAV titers (vg) were determined using qPCR with SYBR Green MasterMix (Thermo Fisher Scientiﬁc). The following primer sequences wereused to amplify the target site (WPRE sequence):
WPRE_qPCR_fwd: 5′-CTGTTGGGCACTGACAATTC-3′
WPRE_qPCR_rev: 5′-GAAGGGACGTAGCAGAAGGA-3′
AAV vectors were administered to 6-week-old male mice via retroorbital injection (Fig. 3i). DPBS was used to adjust the injected AAV
solution to the determined titer (0.5–15.0 × 1011 vg/mouse, detailed
titer information can be found in Supplementary Table 1), and
100–150 μl/mouse was injected. Mice were anesthetized in ambient air
with 1%–5% isoﬂurane prior to the injection. Mice were housed in theirhome cage for at least >2 weeks prior to behavioral experiments orbrain sampling, unless otherwise noted, to allow time for gene
expression.

Respiration-based sleep measurements by SSS
SSS was used to perform sleep phenotyping based on respiration31. The
recordings were made in either WT male mice (3–12 weeks old) for thedevelopmental analysis (details in below) or AAV-injected mice
(8–10 weeks old) for other experiments. To measure respiratory ﬂow,
each experimental mouse was placed in the SSS chamber from its
home cage. Unless otherwise speciﬁed, the recording condition was a
12-hour LD cycle with ad libitum food and water. Within two weeks, one
set of recordings was completed. To avoid the ﬁrst-night effect, datafrom the ﬁrst day of the recording session were excluded from theanalysis. The recordings of circadian KO mice were made under the DD
condition for two weeks, and the data from the last six days was analyzed (Fig. 7e).
SSS data were divided into 8-second segments (epochs), withsleep/wake annotation performed after each epoch. The annotation
rules and sleep parameters, such as sleep duration, PWS, and PSW, havepreviously been deﬁned31. PWS and PSW are the probabilities in an
13

Articlehttps://doi.org/10.1038/s41467-024-50168-5

observed period from wake to sleep state (the tendency for sleep) andfrom sleep to wake state (the tendency for wakefulness) (Fig. 1b).
Because NXY denotes the number of transitions from X to Y (X, Y ∈{sleep (S), wake (W)}), the transition probabilities are independent of
one another, and are calculated as follows:
P WS = N WS = N WS + N WW
P SW = N SW = N SW + N SS





ð1Þ
ð2Þ

PWS or PSW was treated as 1, when (NWS + NWW) or (NSW + NSS) was 0(i.e., consecutive sleep or wake state in an observed period). The
duration of a sleep or wake episode is calculated by taking the averageof consecutive sleep or wake bouts, which is inversely related to PSW or
PWS, respectively.
Long-term recording with development lasted approximately
2 months in male mice, from P21 (just after weaning) to P84. During therecording, the SSS chambers were replaced with new ones every week,
and sleep/wake annotation was performed on a weekly basis.

Sleep measurements by EEG/EMG recording
EEG and EMG surgery was performed 4–5 days after AAV injection(6–7 weeks old). A combination anesthetic containing 0.9 mg/kg
medetomidine hydrochloride (Domitol, ZENOAQ), 4.8 mg/kg midazolam (Sandos, Novartis), and 6.0 mg/kg butorphanol (Vetorphale,
Meiji Seika Pharma) was used to anesthetize mice. Two EEG electrodes
were placed in the skull over the cortex (1.5-mm right from midline, 1.5mm anterior to the bregma; 1.5-mm right from the midline, 1.5-mm
anterior to the lambda), and two EMG electrodes were placed in theneck muscle. Insulated wires connected the electrodes and were soldered to a pin header that was secured to the skull with dental cement.
Mice were given 0.9 mg/kg atipamezole hydrochloride (Antisedan,
ZENOAQ) after surgery and warmed to 37 °C using a warming plate topromote anesthesia recovery. The mice were given at least ten days torecover from surgery.
Ampliﬁed EEG/EMG signals from 8-week-old male mice wererecorded in the EEG/EMG chamber with food and water using Vital
Recorder software (KISSEI COMTEC). For both EEG and EMG, thesampling frequency was 128 Hz. One recording session lasted less thana week. Data analysis began the day after data was collected. For further analysis, the EEG/EMG data recorded in KCD format was converted to EDF format.
For sleep recording, an in-house improved version of the FASTER
method was used to automatically annotate the stages (wakefulness,
REM, and NREM sleep) from EEG/EMG data30. EEG/EMG data weredivided into 8-second segments (epochs), and annotation was performed after each epoch. Following FASTER’s auto-staging, eachepoch was manually corrected using the following criteria. The lowamplitude EEG and high amplitude EMG were used to determine
wakefulness. NREM sleep was distinguished by high amplitude EEG
with a low frequency wave (0.5–4 Hz) and a low EMG signal. The lowamplitude EEG with predominantly theta wave (6–10 Hz) and EMG
atonia was used to stage REM sleep.
As previously reported30, transition probabilities between wakefulness, NREM sleep, and REM sleep were calculated in the same way as
PWS and PSW (see ”Methods” section for “Respiration-based sleep
measurements by SSS”). The transition from wakefulness to REM sleep(PWR) was not depicted because it occurred so brieﬂy.
For each epoch, the power spectral density (PSD) was calculatedusing fast Fourier transformation and Welch’s averaging method. The
spectral analysis excluded epochs that contained movement artifacts.
Each PSD bin was calculated by averaging within each behavioral state
and was expressed as a percentage of the total power over all frequencies. Delta or SO power was calculated during NREM sleep as

Nature Communications | (2024)15:6054

percentages of delta (0.5–4 Hz) or SO (0.5–1 Hz) power over total EEG
power per hour or day.

Sleep measurements with SD
SD was performed during ZT0–6 (the ﬁrst half of light phase) in SSS
recordings using an automated orbital shaker (TAITEC). Every mouse
was moved from an SSS chamber to new cage on the shaker at ZT0 on
the fourth day of recording. The shaker was programmed to turn on
for 30 s every 80 s (30 s on, 50 s off) at around maximum speed ofaround 120 rpm. Following the SD session (at ZT6), each mouse wasreturned to the same SSS chamber as before, and the recording was
resumed. The basal recording was made three days before the SD
session.
In the EEG/EMG recordings, mice underwent SD for 6 h from
ZT0 to ZT6. SD was achieved by gently touching their bodies with abrush when they became immobile and assumed a sleeping posture.
The day preceding the SD session corresponded to the basal
recording.

Sleep measurements with pharmacological administration
Natural saline was used to dissolve all chemicals used in pharmacological administration experiments (Otsuka pharma). Adjusting forindividual mouse body weight, the single volume of injection was in
the range of 150–250 μl. For MK-801 administration experiments, mice
were given 0 or 2 mg/kg MK-801 maleate (Merck) i.p. injection at ZT8,
with at least 1 day between injections.
For chemogenetic experiments, clozapine-N-oxide (CNO, Tocris)
was used as the ligand of Gq-coupled DREADD hM3Dq and Gi-coupled
DREADD hM4Di. For chemogenetic manipulation experiments underad libitum sleep, mice expressing EGFP, hM3Dq, or hM4Di under theE11 enhancer were given i.p. injection of 0, 1, 3, or 5 mg/kg CNO at ZT12,
with at least 2 days between injections. Mice expressing mCherry or
hM4Di under the E11 enhancer were given i.p. injection of 0 or 0.25 mg/
kg CNO at ZT12 for chemogenetic suppression experiments after SD
using the above-mentioned method (see “Sleep measurements withSD” in “Methods” section).

Whole-brain clearing, immunostaining, imaging, and analysis
An improved version of the CUBIC-HV methods was used to clear andstain mouse brains34. Mice were sedated with 100 mg/kg pentobarbital
before being perfused transcardially with PBS and 4% paraformaldehyde (PFA). The brains were post-ﬁxed in 4% PFA overnight at 4 °C andstored in PBS until the clearing processes began. CUBIC-L (10% [wt/wt]
N-butyldiethanolamine, 10% [wt/wt] Triton X-100 in water) was used todilapidate the brains. Nuclear staining and immunostaining were performed after delipidation using nuclear staining dye (SYTOX Green,
Thermo Fisher Scientiﬁc) and ﬂuorescence-dye-conjugated antibodies. CUBIC-R+ (45% [wt/wt] antipyrine, 30% [wt/wt] Nicotinamide,
0.5% [vol/vol] N-butyldiethanolamine in water) was used to process
brains for refractive index matching, followed by embedding in 1.5%
agarose gel in CUBIC-R + .
All whole-brain imaging was performed at International ResearchCenter for Neurointelligence in the University of Tokyo. A custommade light-sheet microscope was equipped with diode or DPSS lasers
with wavelengths of 488, 532, 594, and 642 nm (Coherent). To ensure
homogeneous resolution in XYZ axes, the microscope employed anaxially-swept light sheet mechanism68. The microscope was ﬁtted with
a 0.63X macro-zoom objective lens (Olympus) and variable 0.63-6.3X
intermediate zoom optics (Olympus). The ﬂuorescence signal was
efﬁciently captured using an sCMOS camera (PCO), paired withappropriate ﬂuorescence ﬁlters. In all conducted experiments, thevoxel size was (X, Y, Z) = (6.45, 6.45, 7.0) μm with 1.6X intermediate
zoom optics, providing total 1.0X magniﬁcation. An effective resolution should consider the moderate tissue expansion (1.5X) induced by
the CUBIC-R+ treatment.
14

Articlehttps://doi.org/10.1038/s41467-024-50168-5

Image analysis procedures on CUBIC-Cloud included cell detection, brain registration, and data quantiﬁcation/visualization33. The
ilastik software was used to detect cells in 3D brain image data. Manual
annotations were prepared from at least two brains with identicallabeling conditions in some parts of the 3D images using ITK-SNAP
software, and the classiﬁer was trained using the manual annotation
data. The XYZ position, mean ﬂuorescence intensity, and volume ofsingle cells at the whole brain level were obtained in CSV format by
applying the trained classiﬁer to the whole brain 3D image. The symmetric image normalization (SyN) algorithm was used to register the
3D brain image. Individual brains in CUBIC-Cloud were registered to
CUBIC-Atlas brains using nuclear staining images and single cells displayed regional information69. The CUBIC-Cloud platform (https://
cubic-cloud.com/) was used to perform some data quantiﬁcation andvisualization.

independently for each channel, and the center of mass of the detected cells was determined. For each c-Fos+ cells, if a PV+ cell was foundwithin a distance of 16 μm69, it was considered a c-Fos+PV+ cell. Notethat due to tissue expansion by a factor of ~1.5, this distance equated toapproximately 10.5 μm in untreated tissue. This procedure was applied
for the identiﬁcation of PV+mCherry+ or c-Fos+mCherry+ cells.
To evaluate the colocalization analysis using the light-sheet
microscope, selected cortical regions of the cleared brain were also
imaged using a confocal microscope (BX61WI, Olympus) equippedwith a 25X objective lens (NA: 1.00, WD: 8 mm, Olympus) and 559- and635-nm lasers (NTT Electronics). The voxel size was (X, Y, Z) = (0.497,
0.497, 0.497) μm under the condition of no tissue expansion. Colocalization of c-Fos and PV signals was conﬁrmed in images obtained
from both types of microscopes in a three-dimensional manner (Supplementary Fig. 4b).

Whole-brain analysis of PV proﬁle with development

In vitro assay for CaMKIIα expression and kinase activity

B6N WT male brains (P21, P28, P35, P42, P84, and P270; n = 6 for eachage) were cleared, stained, imaged, and analyzed (see “Whole-brain
clearing, immunostaining, imaging, and analysis” in “Methods” section). PV antibody (1:50, PV235, Swant; with anti-mouse IgG1 secondary
Fab fragment conjugated with A594 [1:150, 115-587-185, Jackson]) andSYTOX Green were used to stain the mouse brains.

HEK293T cells (CRL-3216, ATCC) were transfected with pMU2-CMVFLAG-CaMKIIα plasmids using PEI. After 24 h, the medium of cultured
HEK293T cells was replaced with fresh culture medium. After 60 h, thecells were lysed with 1 ml of cell lysis buffer (50 mM HEPES-NaOH pH
7.6, 150 mM NaCl, 0.5 mM CaCl2, 1 mM MgCl2, and 0.25% [v/v] NP-40)
supplemented with 1% phosphatase inhibitor cocktail (Nacalai) andhomogenized using the homogenizer (Hielscher). Cell lysates werecollected and kept at −80 °C.
Dot blot was used to estimate the relative expression levels of
CaMKIIα in each cell lysate. Each cell lysate was diluted four times (1/4),
then spotted on PVDF membrane (Merck). The membranes werereacted to anti-CaMKIIα antibody (1:3,000, SMC-124D, StressMarq)
after blocking with Blocking One (Nacalai), followed by the reaction to
the secondary antibody: anti-mouse IgG peroxidase (HRP)-conjugatedantibody (1:3,000, W402B, Promega). HRP chemiluminescent reaction(Clarity Western ECL Substrate; ChemiDoc XRS+ system, Bio-Rad) wasused to detect immunoreactivity of the blotted proteins. To ensurethat the dot blot signals were within the linear range of detection, a celllysate expressing the WT CaMKIIα was serially diluted (1, 1/2, 1/4, 1/8, 1/
16, 1/32, 1/64, or 1/128) was spotted on the same membrane (datanot shown).
The mobility shift assay was used to determine the CaMKII kinase
activity in each cell lysate (LabChip EZ Reader II, PerkinElmer). Eachdiluted CaMKIIα cell lysate (1, 1/2, 1/4, 1/8, 1/16, 1/32, 1/64, or 1/128) was
mixed with 0.25 mM ATP and 3.7 µM Fluorescently labeled peptide
substrate 11 (PerkinElmer) in the presence or absence of 0.50 µM CaM(Merck). The mixture was incubated at 37 °C for 10 min, then at 98 °C
for 10 min to stop the reaction. CaMKII kinase activity is calculated by
dividing the phosphorylated peptide signal by the total substrate
peptide signal.

Whole-brain analysis of c-Fos proﬁle with sleep-wakeperturbation
B6N WT male mice (8 weeks old; n = 6 for S and SD groups) wereindividually housed in an SSS camber for 3 days prior to SD session forexperiments. On the fourth day, mice in the SD group were sleepdeprived as described above (see “Sleep measurements with sleep
deprivation” in “Methods” section), whereas mice in the S group wereallowed to sleep ad libitum as much as they wanted. At ZT6 (just after
the SD session), all mouse brains were sampled.
B6N WT male mice (8 weeks old; n = 4 for saline and MK-801
groups) were individually housed under the DD condition in an SSS
camber for 3 days prior to i.p. administration of MK-801. On the fourthday, mice received i.p. injection of 0 or 2 mg/kg MK-801 maleate at
CT2. Mouse brains were harvested two hours after i.p. injection (CT4).
To prepare brains for CaMKII activation in cortical PV neurons, theAAV.PHP.eB vector transducing E11-CaMKIIα (WT) or E11-CaMKIIα(T286D) was injected via retro-orbital sinus into B6N WT male mice
(6 weeks old; n = 4 for each group). The mice were individually housedin an SSS camber for 1 week when they were 8 weeks old, to monitor
their sleep phenotype. Following sleep phenotype, the brains of mice
were collected at ZT6. This procedure was employed to prepare thebrains for CaMKII activation in Vglut2 neurons. Two types of AAV.PHP.eB vectors, which carried H2B-mCherry and either CaMKIIα (WT or
T286D) in a Cre-dependent manner, were injected into Vglut2-ires-Cre
male mice (6 weeks old; n = 3 for each group). After 2 weeks, their sleep
phenotype was recorded for one week using SSS. Subsequently, theirbrains were sampled at ZT6.
In all c-Fos analysis, collected mouse brains were cleared, stained,
imaged, and analyzed as described above (see “Whole-brain clearing,
immunostaining, imaging, and analysis” in “Methods” section). c-Fos
antibody (1:26, 2250S, CST; with anti-rabbit IgG secondary Fab fragment conjugated with Alexa 647 [1:80, 111-607-008, Jackson]), PV
antibody (1:20, PV235, Swant; with anti-mouse IgG1 secondary Fabfragment conjugated with A594 [1:80, 115-587-185, Jackson]), andSYTOX Green were used to stain the mouse brains. The c-Fos+PV+ cells
were identiﬁed by a search for cells characterized by the presence ofboth c-Fos and PV signals (Supplementary Fig. 4a). We previously
conﬁrmed that the accuracy of the cell detection is more than 80%
precision for both PV+ and c-Fos+ cells in most of brain regions33. The
accuracy is relatively lower in the cerebellar regions so that we excluded the regions from the analysis. Cell counting was performed

Nature Communications | (2024)15:6054

Liquid chromatography with tandem mass spectrometry
B6N WT male mice (6 weeks old) were injected with the AAV.PHP.eB
vector transducing E11-CaMKIIα (T285D) via retro-orbital sinus. The
E11-CaMKIIα (T285D) mice were individually housed in an SSS camber
for 1 week after they were 8 weeks old to monitor their sleep phenotype. The mice in the SD group were then sleep-deprived using themethod described above (see “Sleep measurements with SD” in“Methods” section), whereas mice in the S group were allowed to sleep
ad libitum as much as they wanted. The mice were killed by cervicaldislocation at ZT6 (immediately following the SD session), and theircortical regions were quickly dissected and frozen in liquid nitrogen(n = 21 for each group). The brain tissues were stored at −80 °C topreserve phosphorylation state.
The brain tissues were lysed and digested for LC-MS/MS analysis
as previously described30. The frozen sample crusher (Tokken) wasused to powder the brain tissues, and 5–10 mg of brain powder was
homogenized in 0.5 ml of Solution B buffer (12 mM Sodium
15Articledeoxycholate, 12 mM N-lauroylsarcosine sodium salt, 50 mM Ammonium hydrogen carbonate) supplemented with 1% phosphatase inhibitor cocktail (Nacalai), preheated at 98 °C. Following a 15-minuteincubation at 98 °C, the samples were reduced with 9 mM dithiothreitol (Fujiﬁlm) at room temperature for 30 min before being alkylated with 45 mM iodoacetamide (Merck) at room temperature for
30 min. The samples were then digested overnight at 37 °C with 1 μg/
ml of lysyl endopeptidase (Lys-C) (Fujiﬁlm) and for 3–6 h with 0.8 μg/
ml of trypsin (Roche). Following digestion, the sample was acidiﬁedwith 0.5% TFA and an equal volume of ethyl acetate was added. The
sample was thoroughly mixed before being centrifuged (1500×g,
30 min, 25 °C) to separate the peptide solution. Using a SpeedVac(Thermo Fisher Scientiﬁc), the peptide solution (an aqueous layer) wascollected and dried.
The dried peptides were dissolved in a solution of 2% acetonitrile and 0.1% TFA. Each peptide solution was divided into twogroups: one for individual samples, and the other for a mixture ofeach peptide solution as an internal control. Using a Sep-Pak C18
cartridge (Waters), the individual samples and internal control weretrapped and desalted. The peptides on the cartridge were thendimethyl-labeled as previously described70, with formaldehyde(CH2O; Nacalai) added to the internal control (light label) or
isotope-labeled formaldehyde (CD2O; Cambridge Isotope Laboratories) added to the individual samples (medium label) together
with NaBH3CN (Merck). The dimethyl-labeled peptides were eluted
with a solution of 80% acetonitrile and 0.1% TFA. After that, an equalamount of light-labeled internal control was added to each mediumlabeled individual sample, allowing us to compare the relative
amount of peptides in the individual samples using internal control
as a standard.
A portion of the mixture (10%) was subjected to LC-MS/MS analysis to determine the amount of CaMKIIα and total proteins. The
remaining mixture (90%) was used to enrich the phosphorylated
peptides using the High-Select Fe-NTA Phosphopeptide Enrichment
Kit (Thermo Fisher Scientiﬁc) according to the manufacturer’s protocol. All samples were SpeedVac dried before being dissolved in 2%acetonitrile and 0.1% TFA.
The samples were analyzed using an LC-MS system with Orbitrap Exploris 480 (Thermo Fisher Scientiﬁc) equipped with a nano
HPLC system (Advance UHPLC; Bruker Daltonics) and an HTC-PAL
autosampler (CTC Analytics) with a trap column (0.3 × 5 mm, Lcolumn, ODS, Chemicals Evaluation and Research Institute). A gradient was used to separate samples using mobile phases A (0.1%
formic acid/H2O) and B (0.1% formic acid and 100% acetonitrile) at a
ﬂow rate of 300 nl/ minute (4%–32% B for 190 min, 32%–95% B for
1 min, 95% B for 2 min, 95%–4% B for 1 min, and 4% B for 6 min) with ahome-made capillary column (length of 200 mm and inner diameterof 100 μm) packed with 2-μm C18 resin (L-column2, Chemicals
Evaluation and Research Institute). Several samples were separatedusing a different gradient (4%–36% B for 55 min, 36%–95% B for
1 min, 95% B for 5 min, 95%–4% B for 1 min, and 4% B for 8 min)without the phosphorylated peptide enrichment process. The
eluted peptides were electrosprayed (2.1 kV) and subjected topositive ion mode analysis. Full MS spectra were obtained with ascan range of 350–1800 m/z and resolution of 60,000 FWHM at
200 m/z. MS2 spectra with 7,500 FWHM resolution at 200 m/z and adeﬁned ﬁrst mass at 120 m/z were obtained. Without the phosphorylated peptide enrichment process, samples were analyzed bydata-dependent MS/MS acquisition, in which precursor ions(excluding isotopes of a cluster) above 5.0e3 intensity thresholdwith charge state ranging from 2+ to 7+ were selected for the MS/MS
acquisition at 2.0 m/z isolation window during the 3 s interval
between every full MS spectra acquisition. A dynamic exclusion of
20 s was used. Samples from the phosphorylated peptide enrichment process were analyzed by targeted MS/MS acquisition, where

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https://doi.org/10.1038/s41467-024-50168-5

precursor ions matched with the dimethyl-labeled peptide, which
included the phosphorylated T286 residue derived from the CaMKIIα (WT) and CaMKIIα (E285D) (i.e., light-WT 564.754 m/z,
medium-WT 568.779 m/z, light-E285D 557.748, medium-E285D
561.773; z = 2 + ).
The raw data obtained were subjected to database searches(UniProt, reviewed mouse database as of October 5th, 2022) using
the Sequest HT/Percolator algorithm running on Proteome Discoverer 2.5 (Thermo Fisher Scientiﬁc). Peptide cleavage was set totrypsin; missed cleavage sites were allowed to be up to two residues;
peptide lengths were set to 6–144 amino acids; and mass toleranceswere set to 40 ppm for precursor ions and 0.08 Da for fragment ions.
Fixed modiﬁcation included carbamidomethylation at cysteine anddimethylation [H (4) C (2), or 2H (4) C (2)] at lysine and the peptide
N-terminus. Methionine oxidation was designated as a variable
modiﬁcation. A signiﬁcance level of q < 0.01 was used. Precursor ion
abundances for the phosphorylated T286 residue were manuallychecked and quantiﬁed using Qual browser function of the Xcalibur
4.4 software (Thermo Fisher Scientiﬁc). Proteome Discoverer 2.5 wasused to calculate the abundances of the other precursor ions
(Thermo Fisher Scientiﬁc).

Statistical analysis
Microsoft Excel for Mac version 16.49, R version 3.6.1., and Python
version 3.8.2 were used for statistical analyses. For all tests, the signiﬁcance level was set at <0.05 (*P < 0.05, **P < 0.01, ***P < 0.001, n.s. =non-signiﬁcance). The Fig. legends describe the statistical method andresults for each comparison. The statistical analysis procedures wereas follows.
To assess normality and homoscedasticity in two samples, theShapiro test and F-test with a signiﬁcance level of 0.05 were used.
When two groups had normal distributions with equal variance, theStudent’s t-test was used for independent samples; and the Student’s
paired t-test was used for paired samples. When two groups had normal distributions with unequal variance, Welch’s t-test was used;otherwise, two-samples Wilcoxon test was used.
To evaluate normality and homoscedasticity in more than threesamples, the Kolmogorov–Smirnov test (KS-test) and Bartlett’s test at
the signiﬁcance level of 0.05 were used. When all groups were normally distributed with equal variance, the Student’s t-test with Bonferroni correction was used; when two groups had normal
distributions but not equal variance, the Welch’s t-test with Bonferroni
correction was used; otherwise, the Steel test was used.

Reporting summary
Further information on research design is available in the Nature
Portfolio Reporting Summary linked to this article.

Data availability
Protein mass spectrometry raw data have been deposited in MassIVE
repository (MSV000095087). Due to the large size of raw data, otherdata used in this study is available from the corresponding author
upon request. Source data are provided with this paper.

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Acknowledgements
We would like to express our gratitude to S. Tomita, A. Shimokawa, and
H. Ono for their assistance with the SSS and EEG/EMG recordings; A.
Shimokawa, K. Yamashita, R. Narumi, K. Yamamoto, M.N.B. Roig, and F.
Kinoshita for their help in SD experiments; T. Miyawaki, S. Sato, and K.
Shimizu for assisting with AAV production; Y. Saito for assisting withbrain sample preparation; M. Kuroda for LSFM imaging technical

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https://doi.org/10.1038/s41467-024-50168-5
assistance; D.R. Weaver and W. Nakamura for providing Per dKO mice;
G.T.J. van der Horst and J.H.J. Hoeijmakers for providing Cry dKO mice;and T. Jin for supporting with NMR analysis. We would like to thankEnago (www.enago.jp) for the English language review. This work was
supported by a Grant-in-Aid for JSPS Fellows (JSPS KAKENHI, 19J22074
and 23KJ0234, to K.K.); a Grant-in-Aid for Scientiﬁc Research (C) (JSPS
KAKENHI, 20K06576 and 23K05738, to K.L.O.); a Grant-in-Aid for EarlyCareer Scientists (JSPS KAKENHI, 20K15766, to Y.S.); a Grant-in-Aid for
Scientiﬁc Research (B) (JSPS KAKENHI, 22H02824, to E.A.S.); AMEDPRIME (JP20gm6210027, to E.A.S.); a Grants-in-Aid from the Takeda
Science Foundation, Nakatani foundation for advancement of measuring technologies in biomedical engineering, and Uehara Memorial
Foundation (to E.A.S.); a Grant-in-Aid for Scientiﬁc Research (S) (JSPS
KAKENHI, 18H05270, to H.R.U.); Human Frontier Science Program(HFSP) Research Grant Program (RGP0019/2018, to H.R.U.); Exploratory
Research for Advanced Technology (ERATO) (JST, JPMJER2001, to
H.R.U.); Quantum Leap Flagship Program (Q-LEAP MEXT,JPMXS0120330644, to H.R.U.); Brain Mapping by Integrated Neurotechnologies for Disease Studies (Brain/MINDS) (AMED,
JP21wm0425003, to E.A.S.; JP21dm0207049, to H.R.U.); Innovative Drug
Discovery and Development (AMED, JP19am0401011, to H.R.U.); and an
intra-mural Grant-in-aid (RIKEN BDR, to H.R.U.).

Author contributions
K.K., K.L.O., and H.R.U. designed the study; S.Shi, and E.A.S. helpedwith the study design; K.K., H.F., D.T., and R.G.Y. performed the SSS
recording; K.K., H.F., R.R.T., S.Shiono, K.Matsuzawa, and R.G.Y. performed the EEG/EMG recording; K.K., K.L.O., and R.G.Y. analyzed thesleep data; K.K., K.L.O., D.T., and S.Y. designed and constructed theplasmids; K.K., R.R.T., and C.S. produced AAVs; K.K., T.M., R.R.T., C.S.,
and S.Shiono performed the brain sample preparation, LSFM imaging, and data analysis; S.Y.Y., R.R.T., and S.Shiono performed theconfocal imaging; K.K., K.L.O., and R.R.T. performed biochemical
experiments and analyzed the data; Y.S. synthesized CNO for preliminary chemogenetic experiments; R.G.Y. established the improved
FASTER methods for EEG/EMG sleep staging; E.A.S. developed theimproved version of the CUBIC-HV methods for whole-brain immunostaining; D.T., J.Y.G., M.K., K.Miyamichi., K.S., and H.K. establishedthe ES-cell-derived mice; K.K. prepared the ﬁgures and draft manuscript; K.K., K.L.O., and H.R.U. wrote the manuscript with input fromall co-authors.

Competing interests
R.G.Y. and E.A.S. are employees of CUBICStars, Inc. H.R.U. is a founderand CTO of CUBICStars, Inc., which provides and maintains CUBIC-Cloudweb service. The remaining authors declare no competing interests.

Additional information
Supplementary information The online version contains
supplementary material available athttps://doi.org/10.1038/s41467-024-50168-5.
Correspondence and requests for materials should be addressed to
Hiroki R. Ueda.
Peer review information Nature Communications thanks Qinghua Liu
and the anonymous reviewers for their contribution to the peer review ofthis work. A peer review ﬁle is available.
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© The Author(s) 2024

1

Department of Systems Pharmacology, Graduate School of Medicine, The University of Tokyo, Bunkyo-ku, Tokyo, Japan. 2Laboratory for Synthetic Biology,
RIKEN Center for Biosystems Dynamics Research (BDR), Suita, Osaka, Japan. 3Department of Information Physics and Computing, Graduate School ofInformation Science and Technology, The University of Tokyo, Bunkyo-ku, Tokyo, Japan. 4Department of Systems Biology, Institute of Life Science, Kurume
University, Kurume, Fukuoka, Japan. 5Laboratory for Animal Resources and Genetic Engineering, RIKEN Center for Biosystems Dynamics Research (BDR),
Chuou-ku, Kobe, Hyogo, Japan. 6Laboratory for Comparative Connectomics, RIKEN Center for Biosystems Dynamics Research (BDR), Chuou-ku, Kobe,
Hyogo, Japan. 7Laboratory for Mouse Genetic Engineering, RIKEN Center for Biosystems Dynamics Research (BDR), Suita, Osaka, Japan. 8Present address:
Kennedy Krieger Institute, Solomon H. Snyder Department of Neuroscience, Johns Hopkins University School of Medicine, Baltimore, MD, USA. 9Present
address: Computational Neuroethology Unit, Okinawa Institute of Science and Technology, Onna, Okinawa, Japan. 10Present address: International Institutefor Integrative Sleep Medicine (IIIS), University of Tsukuba, Tsukuba, Ibaraki, Japan. 11Present address: Department of Molecular Embryology, ResearchInstitute, Osaka Women’s and Children’s Hospital, Izumi, Osaka, Japan. 12Present address: Division of Molecular Psychoimmunology, Institute for Genetic
Medicine, Graduate School of Medicine, Hokkaido University, Sapporo, Japan. 13Present address: Laboratory of Animal Genetics and Breeding, Graduate
School of Bioagricultural Sciences, Nagoya University, Chikusa-ku, Nagoya, Japan. 14Present address: Department of Biochemistry and Systems Biomedicine,
Juntendo University Graduate School of Medicine, Bunkyo-ku, Tokyo, Japan.
e-mail: uedah-tky@umin.ac.jp

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