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We previously found that Mertk and its ligand Gas6, astrocytic genes involved in phagocytosis, are upregulated after acute sleep deprivation. These results suggested that astrocytes may engage in phagocytic activity during extended wake, but direct evidence was lacking. Studies in humans and rodents also found that sleep loss increases peripheral markers of inflammation, but whether these changes are associated with neuroinflammation and/or activation of microglia, the brain's resident innate immune cells, was unknown. Here we used serial block-face scanning electron microscopy to obtain 3D volume measurements of synapses and surrounding astrocytic processes in mouse frontal cortex after 6–8 h of sleep, spontaneous wake, or sleep deprivation (SD) and after chronic (∼5 d) sleep restriction (CSR). Astrocytic phagocytosis, mainly of presynaptic components of large synapses, increased after both acute and chronic sleep loss relative to sleep and wake. MERTK expression and lipid peroxidation in synaptoneurosomes also increased to a similar extent after short and long sleep loss, suggesting that astrocytic phagocytosis may represent the brain's response to the increase in synaptic activity associated with prolonged wake, clearing worn components of heavily used synapses. Using confocal microscopy, we then found that CSR but not SD mice show morphological signs of microglial activation and enhanced microglial phagocytosis of synaptic elements, without obvious signs of neuroinflammation in the CSF. Because low-level sustained microglia activation can lead to abnormal responses to a secondary insult, these results suggest that chronic sleep loss, through microglia priming, may predispose the brain to further damage.
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Cellular/Molecular
Sleep Loss Promotes Astrocytic Phagocytosis and Microglial
Activation in Mouse Cerebral Cortex
XMichele Bellesi,
1,2
Luisa de Vivo,
1
XMattia Chini,
1
Francesca Gilli,
3
Giulio Tononi,
1
and XChiara Cirelli
1
1
Department of Psychiatry, University of Wisconsin–Madison, Madison, Wisconsin 53719,
2
Department of Experimental and Clinical Medicine, Section of
Neuroscience and Cell Biology, Universita` Politecnica delle Marche, Ancona, 60026, Italy, and
3
Department of Neurology, Geisel School of Medicine at
Dartmouth, Lebanon, New Hampshire 03756
We previously found that Mertk and its ligand Gas6, astrocytic genes involved in phagocytosis, are upregulated after acute sleep depri-
vation. These results suggested that astrocytes may engage in phagocytic activity during extended wake, but direct evidence was lacking.
Studies in humans and rodents also found that sleep loss increases peripheral markers of inflammation, but whether these changes are
associated with neuroinflammation and/or activation of microglia, the brain’s resident innate immune cells, was unknown. Here we used
serial block-face scanning electron microscopy to obtain 3D volume measurements of synapses and surrounding astrocytic processes in
mouse frontal cortex after 6 –8 h of sleep, spontaneous wake, or sleep deprivation (SD) and after chronic (5 d) sleep restriction (CSR).
Astrocytic phagocytosis, mainly of presynaptic components of large synapses, increased after both acute and chronic sleep loss relative
to sleep and wake. MERTK expression and lipid peroxidation in synaptoneurosomes also increased to a similar extent after short and long
sleep loss, suggesting that astrocytic phagocytosis may represent the brain’s response to the increase in synaptic activity associated with
prolonged wake, clearing worn components of heavily used synapses. Using confocal microscopy, we then found that CSR but not SD mice
show morphological signs of microglial activation and enhanced microglial phagocytosis of synaptic elements, without obvious signs of
neuroinflammation in the CSF. Because low-level sustained microglia activation can lead to abnormal responses to a secondary insult,
these results suggest that chronic sleep loss, through microglia priming, may predispose the brain to further damage.
Key words: astrocyte; cortex; microglia; mouse; sleep; sleep deprivation
Introduction
Astrocytes are influenced by changes in behavioral state. Using
serial block-face scanning electron microscopy (SBEM), we re-
cently found that most excitatory synapses in mouse frontal cor-
tex are contacted by peripheral astrocytic processes (PAPs). PAPs
move closer to the synaptic cleft and expand after extended wake,
presumably because the need to clear glutamate and potassium
ions increases. Transcriptomic profiling also showed that the ex-
pression of 1.4% of astrocytic genes is state dependent and
mostly upregulated in wake relative to sleep (Bellesi et al., 2015).
Astrocytic “wake” genes in mice included Mertk (Bellesi et al.,
2015), and previous experiments in rats found that Gas6 was
upregulated in cortex after chronic sleep deprivation (Cirelli et
Received Dec. 31, 2016; revised March 23, 2017; accepted April 13, 2017.
Author contributions: M.B., G.T., and C.C. designed research; M.B., L.d.V., and M.C. performed research; M.B.,
L.d.V., M.C., and F.G. analyzed data; M.B., G.T., and C.C. wrote the paper.
This work was supported by NIH Grants DP 1OD579 (G.T.), 1R01MH091326 (G.T.), 1R01MH099231 (G.T., C.C.),
and 1P01NS083514 (G.T., C.C.). We thank Benjamin Jones, Hirotaka Nagai, Midori Nagai, Sakiko Honjoh, Alex
Rodriguez, Kayla Peelman, Douglas Haswell, and Giovanna Spano for helping with the chronic sleep restriction
experiments and Sophia Loschky, Andrea Schroeder, and Samuel Koebe for contributions to EM image analysis.
The authors declare no competing financial interests.
Correspondence should be addressed to Chiara Cirelli, Department of Psychiatry, University of Wisconsin–
Madison, 6001 Research Park Boulevard, Madison, WI 53719. E-mail: ccirelli@wisc.edu.
DOI:10.1523/JNEUROSCI.3981-16.2017
Copyright © 2017 the authors 0270-6474/17/375263-11$15.00/0
Significance Statement
We find that astrocytic phagocytosis of synaptic elements, mostly of presynaptic origin and in large synapses, is upregulated
already after a few hours of sleep deprivation and shows a further significant increase after prolonged and severe sleep loss,
suggesting that it may promote the housekeeping of heavily used and strong synapses in response to the increased neuronal
activity of extended wake. By contrast, chronic sleep restriction but not acute sleep loss activates microglia, promotes their
phagocytic activity, and does so in the absence of overt signs of neuroinflammation, suggesting that like many other stressors,
extended sleep disruption may lead to a state of sustained microglia activation, perhaps increasing the brain’s susceptibility to
other forms of damage.
The Journal of Neuroscience, May 24, 2017 37(21):5263–5273 • 5263
al., 2006). The receptor MERTK belongs to one of the two path-
ways that mediate astrocytic phagocytosis (AP; Chung et al.,
2015) and through the action of GAS6 (growth arrest-specific
protein 6) binds exposed phosphatidylserine in target debris
(Grommes et al., 2008). AP participates in developmental synap-
tic pruning (Berbel and Innocenti, 1988;Chung et al., 2013) and
adult astrocytes engulf axonal organelles and synaptic elements
even in healthy mice, suggesting that their constitutive phagocytic
activity contributes to the clearing of damaged cellular components
(Nguyen et al., 2011;Chung et al., 2013;Davis et al., 2014), likely in
response to wake-related neuronal activity (Chung et al., 2015).
Microglia are the resident phagocytes of the CNS. They con-
stantly monitor the surrounding microenvironment via their
processes, sense neuronal activity, clear neuronal debris after in-
jury and cell death (Wake et al., 2009;Tremblay et al., 2010;Tay et
al., 2017), and contribute to developmental synaptic pruning in
the healthy brain (Paolicelli et al., 2011;Schafer et al., 2012;Bialas
and Stevens, 2013;Sipe et al., 2016). Microglial phagocytosis is
mediated by C1q and C3, components of the complement cas-
cade that tag unwanted synapses; by the phagocytic complement
receptor expressed by microglia (Stevens et al., 2007); and by
MERTK, which is also expressed in microglia (Chung et al., 2013).
Any disturbance of brain homeostasis, including inflammation,
activates microglia. Acute and chronic sleep deprivation can lead
to a pro-inflammatory state in the absence of overt infection or
injury (Mullington et al., 2010;Hurtado-Alvarado et al., 2013).
Specifically, in humans and rodents, sleep loss can lead to ele-
vated white blood cell counts; increased circulating levels of
C-reactive protein, IL1
, IL6, and TNF
(Everson, 2005;Mull-
ington et al., 2010;Hurtado-Alvarado et al., 2013;He et al., 2014);
and enhanced permeability of the blood– brain barrier (Hurtado-
Alvarado et al., 2013;He et al., 2014). The source of the increase in
peripheral cytokines remains unclear but has been linked to the
increase in catecholamine levels associated with prolonged wake
(Mullington et al., 2010). Equally unclear is whether these pe-
ripheral changes are associated with signs of neuroinflammation
and/or with microglial activation.
Together, these findings suggest that sleep loss can trigger AP
and lead to microglia activation. Here we tested this hypothesis
using SBEM to study PAPs surrounding cortical mouse synapses
and measured AP occurrence after sleep, spontaneous wake, and
sleep loss. In cortical synaptoneurosomes, we also assessed changes
in MERTK protein levels and the extent of lipid peroxidation,
which can result from high oxidative stress and in turn can trig-
ger phagocytosis. In addition, we measured microglia state of
activation and phagocytic activity, as well as levels of inflam-
matory markers in the CSF of mice after sleep and sleep loss. We
find that AP, mainly of presynaptic elements in large synapses,
occurs after both acute and chronic sleep loss but not after spon-
taneous wake, suggesting that it may promote the housekeeping
and recycling of worn components of heavily used, strong syn-
apses. By contrast, only chronic sleep loss activates microglia cells
and promotes their phagocytic activity, apparently without overt
signs of neuroinflammation, suggesting that extended sleep dis-
ruption may prime microglia and perhaps predispose the brain to
other forms of insult.
Materials and Methods
Animals
Four-week-old homozygous B6.Cg-Tg(Thy1-YFP)16Jrs/J transgenic
mice of either sex were used in this study with the exception of microglia
experiments, in which 4-week-old male C57BL/6J mice were used. Mice
were housed in recording boxes for the duration of the experiment (12 h
light/dark cycle, light on at 8:00 A.M., 23 1°C; food and water available
ad libitum and replaced daily at 8:00 A.M.). All animal procedures fol-
lowed the National Institutes of Health Guide for the Care and Use of
Laboratory Animals, and facilities were reviewed and approved by the
Institutional Animal Care and Use Committee of the University of
Wisconsin–Madison and were inspected and accredited by the Associa-
tion for Assessment and Accreditation of Laboratory Animal Care.
Experimental conditions and protocols for sleep, spontaneous
wake, and acute and chronic sleep loss
Four experimental conditions were used (Fig. 1A): (1) sleeping (S) mice
were killed during the light phase, at the end of a long period of sleep
(45 min, interrupted by periods of wake of 4 min), and after spending
at least 75% of the previous 6 –7 h asleep; (2) spontaneously awake (W)
mice were killed during the dark phase, at the end of a long period of wake
(1 h, interrupted by periods of sleep of 5 min), and after spending at
least 70% of the previous 6 –7 h awake; (3) acutely sleep-deprived (SD)
mice were killed during the light phase after8hofsleep deprivation
enforced by introducing novel objects and by tapping on the cage when-
ever the animals appeared drowsy. As demonstrated in previous studies
with EEG recordings, this method can prevent sleep almost completely
for several hours [95% total time spent awake (Cirelli et al., 2004;
Bellesi et al., 2013,2015)]; and (4) chronically sleep-restricted (CSR)
mice were subjected in groups (six to eight mice per group) to 4.5 days of
chronic sleep restriction using a protocol optimized in our laboratory. A
previous validation study that used mice implanted with EEG electrodes
found that this CSR protocol results in a reduction of overall sleep dura-
tion by 70% (de Vivo et al., 2016). During chronic sleep restriction,
mice were housed in large cages where, during the day, sleep restriction
was enforced using ecologically relevant stimuli that included continuous
exposure to novel objects, changes of cage and bedding, social interaction,
and free access to multiple running wheels. Mild forced locomotion on a
slowly rotating platform was used to restrict sleep at night. The platform
was located above a tray filled with 2–3 cm of water, and the rotation
speed was low enough that mice (still in groups) could easily avoid falling
into the water if they moved continuously. Heat lamps were placed 2m
above the platform to keep mice at the proper temperature. Video cam-
eras and/or direct visual observation were used to continuously monitor
the mice. If a mouse fell in the water often enough such that it did not
have a chance to dry, it was removed to a cage filled with novel objects and
allowed to dry before being placed back onto the rotating platform. Be-
cause CSR mice were in groups, sleep and wake could not be quantified
with video recording as in S and W mice (see below).
Experimental procedure
S, W, and SD mice were individually housed starting at postnatal day 27
(P27) and killed at P30, and all of them were exposed to a few novel
objects and had access to running wheels during the dark phase. CSR
mice were subjected to sleep restriction in groups (six to eight mice per
group) from P25 to P30. S, SD, and CSR mice were killed at the same time
of day (4:00 P.M.), whereas W mice were killed at 4:00 A.M. (Fig.
1A). Independent groups of S, SD, and CSR mice were used for ultra-
structural, molecular, and histological studies (W mice were used only
for the ultrastructural studies).
Video recordings of behavioral states. To avoid possible tissue damage
and inflammation resulting from the implant of EEG electrodes, behav-
ioral states in S and W mice were determined by continuous video mon-
itoring with infrared cameras. As described previously (Maret et al., 2011;
Bellesi et al., 2015), this method consistently estimates total sleep time
with 90% accuracy even if it cannot distinguish nonrapid eye move-
ment sleep from rapid eye movement sleep. Motor activity was then
quantified by custom-made video-based motion detection algorithms
(Bellesi et al., 2012).
Ultrastructural studies. The image dataset used for the ultrastructural
analysis of astrocytic endocytosis is the same used in a previous study that
characterized the dynamics of peripheral astrocytic processes (PAPs) in
S, W, SD, and CSR mice (Bellesi et al., 2015), and a detailed description of
the methods (perfusion, staining, acquisition, and profiles segmenta-
tion) is reported there. Briefly, mice (three animals per group) were perfused
5264 J. Neurosci., May 24, 2017 37(21):5263–5273 Bellesi et al. Glial Phagocytosis in Sleep and Wake
under deep anesthesia (3% isoflurane). Tissue was stained with a solution of
1.5% potassium ferrocyanide/2% osmium tetroxide, followed by 1% thio-
carbonhydrazide, 2% osmium tetroxide, and 1% uranyl acetate at 4°C. The
following day, the tissue was stained with a solution of lead aspartate, dehy-
drated, and embedded with Durcupan resin and ACLAR film. Small squares
of tissue (1 mm
2
) from frontal cortex (anteroposterior, 1.85 mm; mediolat-
eral, 1.5 mm) were glued on the tip of a metal pin and coated with silver paint
to minimize specimen charging during imaging.
Image acquisition. Images were obtained using a IGMA VP field emis-
sion scanning electron microscope (Carl Zeiss) equipped with 3View tech-
nology (Gatan) and a backscattered electron detector (for SBEM). The
series of images were processed and analyzed using TrakEM2, a FIJI
plug-in (Schindelin et al., 2012). Segmentation of astrocytic profiles was
performed manually by two operators blind to the experimental condi-
tion. Small cuboid regions of interest (ROIs; 5– 6
m per side) of neuro-
pil (layers II–III, frontal cortex) were selected. PAPs were recognized
based on their distinctive shapes, interdigitating among neuronal profiles
and often contacting parts of the synapse, and on the presence of glyco-
gen granules. ROIs did not include large dendrites or somata of neurons,
glia, or endothelial cells. For each ROI, astrocytic volume and ROI vol-
ume were estimated. The occurrence of AP was established by the pres-
ence of a portion of axon, spine head, or dendrite being invaginated by
Figure 1. Sleep loss promotes AP. A, Experimental design. B, Volume of all ROIs analyzed in S (n295), W (n266), SD (n355), and CSR (n280) mice. Black bars depict mean and SD.
C, Example of AP as visualized in two-dimensional SBEM images (left) and its 3D reconstruction (right). Scale bar: 200 nm. D, Left, Number of synaptic elements phagocyted by astrocytes in S, W, SD,
andCSR mice. Values (meanSEM) areexpressed percubed millimeter ofastrocytic volume.*p0.05; **p0.01;***p0.001. Right,Breakdown frequencyanalysis of theneuropil structures
involved in AP for S, W, SD, and CSR. E, ASI size of all S, W, SD, and CSR APsynapses relative to mean ASI size (dashed line) in a random sample of synapses (S, n302; W, n256; SD, n345;
CSR, n296). F, Example of a presynaptic bouton (yellow) containing a mitochondrion (asterisk) and being phagocyted by a PAP (blue). Scale bar, 400 nm. G, Percentage of presynaptic boutons
containing a mitochondrion that are (blue bars) or are not (green bars) involved in AP in S, W, SD, and CSR mice. H, Examples of FE (asterisk, left) and EE (asterisk, right). Scale bar, 130 nm. I,3D
reconstruction of one EE (red). Note its tubular structure within the PAP (light blue). J, Number of EE and FE (mean SEM) per cubed millimeter of astrocytic volume in S, W, SD, and CSR mice.
Bellesi et al. Glial Phagocytosis in Sleep and Wake J. Neurosci., May 24, 2017 37(21):5263–5273 • 5265
the surrounding PAP, with a clear continuity between the part being
enclosed by the PAP (phagosome) and the neuronal structure. AP was
quantified using the following score: 1, phagocytosis of the spine head; 2,
phagocytosis of the presynaptic bouton; 3, phagocytosis of the axon (out-
side the axonal bouton); 4, phagocytosis of the dendritic shaft; 5, phago-
cytosis of an unknown structure. For those synapses whose axonal
bouton or spine head were involved in AP, the axon–spine interface
(ASI) was manually segmented and measured [as in the study by Bellesi et
al. (2015)]. Inside the PAPs, endosomes showing undigested, partially, or
fully digested material were scored as full endosomes (FE), whether or
not they were fused with lysosomes, whereas the endosomes with no
vesicles were scored as empty endosomes (EE).
Microarray: data analysis
We used the microarray data available at the NCBI Gene Expression
Omnibus (GEO) database (GSE60079) to perform gene expression anal-
ysis of cerebral cortex samples collected from sleeping (6 –7 h of sleep
during the light phase), awake (6 –7 h of spontaneous wake at night), and
forced enriched wake (4 h of sleep deprivation through exposure to novel
objects during the light phase) mice. Detailed methods were described by
Bellesi et al. (2015). Briefly, samples (six for each behavioral state) were
collected using the genetically targeted translating ribosome affinity pu-
rification methodology from bacterial artificial chromosome transgenic
mice expressing EGFP-tagged ribosomal protein L10a in astrocytes.
Samples were immunoprecipitated to isolate astrocytes. The precipitated
portion formed the bound (IP) sample containing astrocytes, and the
remaining part formed the unbound (UB) sample containing all the
remaining cell types (neurons and other glia cells). Then, both IP and UB
samples were processed, and RNA was extracted and run on Affymetrix
GeneChip Mouse Genome 430 2.0 arrays. In the present study, we used
array data obtained from the IP samples, and we compared S versus W
and S versus SD mice. Data were normalized within each behavioral state
group using Robust Multiarray Average. Comparisons were performed
using Welch’s ttest with Benjamini and Hochberg FDR multiple-test
correction. All probe sets with fold change 30% and p0.01 were
considered as differentially expressed.
Synaptoneurosome preparation and Western blotting. Under anesthesia,
mice (four S, four SD, four CSR) were decapitated, and the cerebral
cortex (including the striatum) was quickly collected. Samples were ho-
mogenized in ice-cold homogenization buffer [10 mMHEPES (Sigma),
1.0 mMEDTA (Promega), 2.0 mMEGTA (Thermo Fisher Scientific),
0.5 mMDTT (Invitrogen), 0.1 mMPMSF (Fluka), 10 mg/L leupeptin
(Sigma), 50 mg/L soybean trypsin inhibitor (Roche), and 100 nMmicro-
cystin (Alexis)] using a glass/glass tissue homogenizer (Kontes). A frac-
tion (10%) of the homogenate from each sample was boiled in 10%
SDS for 10 min and stored unprocessed at 80°C. The remaining frac-
tion of the homogenate was passed through two 105
m pore nylon mesh
filters (Small Parts), then through a 5
m pore filter (Millipore), and
centrifuged at 1000 gfor 10 min at 4°C. Pellets were resuspended in 1%
SDS, boiled for 10 min, and stored at 80°C. Protein concentration was
determined by the bicinchonic acid assay (Pierce). Since housekeeping
proteins (e.g.,
-actin and
-tubulin) can be affected by sleep and wake,
they were not used as an internal standard. Instead, for both homoge-
nates and synaptoneurosomes, equal amounts of protein were pooled
from each individual animal within each group. S, SD, and CSR pools
(four mice per group) were loaded onto the same gels in three to six
replicates (sample loading was randomized). The entire procedure, from
pool preparation to sample loading, was repeated four times. In each
experiment, equal amounts (5
g for GFAP, 10
g for MERTK, 20
g for
C3) of homogenate/synaptoneurosome from S, SD, and CSR pools were
separated by Tris-HCl gel electrophoresis (Bio-Rad). Nitrocellulose
membranes were probed with anti-GFAP (1:500, Sigma), anti-MERTK
(1:500, R&D Systems; AF591), or anti-C3 (1:500, Cappel Laboratories)
antibodies. After exposure to secondary antibodies, bands were visual-
ized using enhanced chemiluminescence (ECL-Prime, GE Healthcare)
and captured by the Typhoon 9410 Variable Mode Imager (GE Health-
care). Optical densities were calculated for each band of interest after
performing background correction (by subtracting the value of a band
immediately above the band of interest in the same lane) and normalized
within each experiment to the average density of S samples.
Lipid peroxidation. Lipid peroxidation was evaluated in cortical synap-
toneurosomes of S (n7), SD (n8), and CSR (n7) mice using the
Lipid Peroxidation (MDA) Assay kit (ab118970, Abcam). This assay pro-
vides an estimation of the end product [malondialdehyde (MDA)] of
lipid peroxidation. Aliquots of synaptoneurosomes (200
l) were incu-
bated with thiobarbituric acid (TBA) at 95°C for 60 min to generate a
MDA–TBA adduct, which was quantified colorimetrically (OD, 532 nm)
using a microplate reader.
CSF extraction and Luminex multiplex immune assay. Under anesthe-
sia, S (n11), SD (n10), and CSR (n8) mice were placed on a
stereotaxic apparatus, meninges overlying the cisterna magna were ex-
posed, and the surrounding area was gently washed to prevent blood
contamination. A small glass capillary tube was used to puncture the
arachnoid membrane covering the cisterna magna and collect CSF by
capillary action. Approximately 10
l of CSF were obtained from each
mouse and immediately stored at 80°C. Cytokine and chemokine con-
centrations were measured in a multiplex Luminex assay, i.e., the Bio-
Plex Pro Mouse Cytokine 23-plex Assay (Bio-Rad). Individual CSF
samples were diluted to 50
l of volume and incubated with a suspension
of analyte capture antibody-conjugated microspheres, per the manufac-
turer’s instructions. After further incubation with biotinylated detection
antibodies and phycoerythrin (PE)-conjugated streptavidin, fluorescent
signal was read on a Luminex MAGPIX Multiplex Reader (Bio-Rad). A
five-parameter logistic curve generated from standards of known con-
centration was used to convert fluorescent intensity to concentration
values, which were then adjusted for sample dilution. The analyzed mol-
ecules were IL1a, IL1b, IL2, IL3, IL4, IL5, IL6, IL9, IL10, IL12(p40),
IL12(p70), IL13, IL17a, Eotaxin, G-CSF, GM-CSF, IFN
, KC, MCP1,
MIP1a, MIP1b, RANTES, and TNF
.
Immunocytochemistry. S(n6), SD (n5), and CSR (n6) mice
were deeply anesthetized with isoflurane (1–1.5% volume) and perfused
transcardially with a flush (30 s) of saline, followed by 4% paraformal-
dehyde in phosphate buffer. Brains were removed, postfixed in the same
fixative overnight, and cut on a vibratome in 50
m coronal sections.
Sections were rinsed in a blocking solution [3% bovine serum albumin
(BSA) and 0.3% Triton X-100 for IBA-1 and V-GLUT1, 2% BSA and
0.2% Triton X-100 for MERTK] for 1 h and incubated overnight (4°C) in
the same blocking solution containing anti-IBA-1 (1:500, catalog #019-
19741, Wako), anti-VGLUT-1 (1:1000, ab5905, Millipore), or anti-
MERTK (1:100, AF591, R&D Systems). Sections were then probed with
secondary antibodies: Alexa Fluor 568 (1:500, Invitrogen)- and/or Alexa
Fluor 488 (1:500, Invitrogen)-conjugated secondary antibodies. For
MERTK staining, signal was amplified using anti-goat biotinylated
antibodies (1:100, Vector Laboratories) and the TSA kit #22, with HRP–
streptavidin and Alexa Fluor 488 Tyramide (T-20932); after the amplifi-
cation, sections were incubated with anti-GFAP antibodies (1:100,
Sigma; overnight at 4°C) and probed with Alexa Fluor 568 (1:500, Invit-
rogen). Sections were examined with a confocal microscope (Prairie
Technologies). For IBA-1, microscopic fields (n5 per section, 3 sec-
tions per mouse) were randomly acquired as 512 512 pixel images
(pixel size, 581 nm; Z-step, 750 nm) in mouse frontal cortex using a
UPlan FL N 40objective (numerical aperture, 1.3). To improve the
signal/noise ratio, two frames of each image were averaged. For IBA-1/
VGLUT-1, microscopic fields (n5 per section, 3 sections per mouse)
were randomly acquired as 1024 1024 pixel images (pixel size, 65 nm;
digital zoom, 3) in mouse frontal cortex using a UPlan FL N 60
objective (numerical aperture, 1.3).
Image analysis. For IBA-1 staining, all analyses were performed on
maximum-intensity projections (Z-project, Maximum Intensity func-
tion in ImageJ) of the 28 images constituting the Z-stack. Cell counting
was performed manually by two operators blind to the experimental
conditions using the cell-counting plugin of FIJI. Two methods were
implemented for the morphological analysis of microglia.
Method 1 was adapted from Morrison and Filosa (2013) and consisted
on the skeleton analysis of microglial processes. Briefly, background noise of
Z-projected images was diminished using the function “Despeckle” in FIJI.
5266 J. Neurosci., May 24, 2017 37(21):5263–5273 Bellesi et al. Glial Phagocytosis in Sleep and Wake
Then, images were binarized, skeletonized, and analyzed using the FIJI
plugin “Analyze Skeleton.” Branch length and the number of end points
(extremities) were then divided by the number of cell somas per frame to
obtain normalized values. Method 2 was adapted from Kozlowski and
Weimer (2012): images were first thresholded using the “Graythresh”
function within MATLAB, and objects with a size comprised between
200 and 1500 pixels, corresponding to putative microglial cells, were
identified. To analyze individual cells, the centroid (center of mass) for
each of these objects was computed and used to crop an ROI of 110 110
pixels around each cell. Each cell mask was visually examined to confirm
that a single microglial cell was accurately represented in the mask. Im-
ages in which the cell touched the boundary of the image, or images that
did not contain a single cell soma, were not considered for further
analysis. Overall, 5129 of 8653 microglial cells met the inclusion cri-
teria and were subsequently analyzed using the function “Regionprops”
in MATLAB to obtain an estimation of cell perimeter and area. Microglia
phagocytosis was quantified in the double-stained IBA-1/VGLUT-1 im-
ages. To optimize the detection of the VGLUT-1-positive puncta en-
gulfed within the microglia, green (IBA-1) and red (VGLUT-1) channels
were processed separately. The background noise of the green channel
was reduced by using the function Subtract Background (rolling ball
radius, 50 pixels) in FIJI. The image was subsequently filtered using a 3D
hysteresis filter1, followed by a 3D median filter2 in Matlab. The back-
ground noise of the red channel was diminished using the function Sub-
tract Background (rolling ball radius, 2 pixels) and Despeckle in FIJI. The
image was subsequently filtered through a 3D Maximum Filter (radius, 3
pixels in every dimension), automatically thresholded (“Auto Threshold”,
“Default” method), and segmented using the “Watershed” function. Green
and red channels were then remerged. Only VGLUT-1-positive puncta big-
ger than 100 pixels (0.03
m
3
)inxyz, and showing 100% overlap with the
processed IBA-1 signal, were quantified.
Results
Sleep loss enhances astrocyte phagocytosis
To study the occurrence of astrocytic phagocytosis in the cortical
neuropil, tridimensional ROIs were manually segmented and an-
alyzed in layers II/III of the mouse frontal cortex, in mice that
slept, were spontaneously awake, or were acutely or chronically
deprived of sleep (Fig. 1A; three mice per group; number of ROIs:
S, 295; W, 266; SD, 355; CSR, 280). The amount of analyzed
neuropil was similar across conditions [1mm
3
; Kruskal–Wallis
(KW) test, p0.45; Fig. 1B]. The four groups also did not differ
in analyzed astrocytic volume (KW test, p0.11, data not
shown), nor in mean synaptic density per ROI (number of syn-
apses/ROIs: S, 2.81; W, 3.03; SD, 2.93; CSR, 2.74). PAPs were
easily recognized because of their morphological features (see
Materials and Methods), and inside PAPs, AP was identified
structurally by the presence of a portion of spine head, axon, or
dendrite surrounded by the PAP, with a clear continuity between
the part being enclosed by the PAP (phagosome) and the neuro-
nal structure (see Fig. 1Cfor an example). Cumulative distribu-
tion analysis of all listed ROIs (S: n289; W: n266; SD: n
355; CSR: n280) showed that in all mice AP affected only a
small minority of synapses, but it changed across the experimen-
tal conditions (KW test, p0.0001). Specifically, AP occurred
more frequently in CSR and SD mice than in S mice (percentage
of all synapses within the ROI: CSR, 13.5%; W, 7.3%; SD, 8.4%; S,
5.7%; Dunn’s multiple comparison test, CSR vs S, p0.0001; SD
vs S, p0.0076; CSR vs SD, p0.026; Fig. 1D). In addition, we
found that AP occurrence in W mice was comparable to S mice
(Dunn’s multiple comparison test, p0.12) and significantly
different from CSR mice (Dunn’s multiple comparison test, p
0.005) but not from SD mice (Dunn’s multiple comparison test,
p0.9; Fig. 1D), suggesting that the increase in AP was related to
sleep loss and not just to the wake state. Note that the increase in
AP after sleep loss is unlikely to be explained by the exposure to
novel objects and running wheels during acute and chronic sleep
deprivation, because S and W mice were also exposed to the same
stimuli during the dark phase. Further analysis of the specific
structures of neuropil involved in AP revealed that axons and
axonal boutons accounted for 75% of all phagocyted elements,
and spine heads for 18 –20% of all phagocyted elements (Fig.
1D). Components that could not be identified were rare, and
parts of the dendritic shafts were almost never seen (Fig. 1D).
Despite the change in absolute number of synapses involved in
AP (APsynapses), the proportion of axons plus boutons rela-
tive to spine heads was primarily maintained across the four con-
ditions (S, W, SD, CSR), suggesting that sleep loss promotes AP as
a whole, with no specific effects on select components of the
neuropil.
During early development, AP mediates the elimination of
weak synapses in the lateral geniculate nucleus (Chung et al.,
2013). Given the correlation between synaptic strength and size
(Holtmaat and Svoboda, 2009), we measured the size of AP
synapses to test whether small synapses were more frequently
phagocyted by PAPs. We considered all synapses whose axon
bouton or spine head was being phagocyted and measured their
ASI, a reliable measure of synaptic strength that is also highly
correlated with spine head volume (Desmond and Levy, 1988).
AP involving other components outside the synapse (axons, den-
drites, and unknown) was not considered in this analysis. We
found that in all groups, the ASI of APsynapses was larger than
the average ASI size [Mann–Whitney U(MW) test, p0.01]
calculated from a pool of synapses randomly chosen in the S (n
302 synapses), W (n256), SD (n345), and CSR (n296)
datasets. Thus, independent of behavioral state, large synapses
were more likely to show AP than synapses of medium or small
size. We also quantified the prevalence of axonal boutons con-
taining one or more mitochondria in APand APsynapses of
comparable size (mitochondria are rare in spine heads; Sorra and
Harris, 2000). As before, APsynapses were selected from a pool
of synapses randomly chosen from the S (n216 synapses), W
(n206), SD (n301), and CSR (n203) datasets. In S and SD
mice, a strong trend toward an increase in the number of axonal
boutons with mitochondria was seen in APsynapses relative to
APsynapses (APvs AP: S, 57.2% vs 36.6%; SD, 50% vs
39.2%). However, Fisher’s exact test did not reach significance (S,
p0.098; SD, p0.22), and no changes were observed in the W
(APvs AP: W, 45.7% vs 43.7%; p0.86) and CSR (APvs
AP: 38.3% vs 40.9%; p0.87; Fig. 1G) groups.
In 30% of ROIs, PAPs contained endosomes, defined as
cytoplasmic membranous organelles of various size. To verify
whether their number was affected by experimental condition,
we annotated their presence while assessing AP. Since it was very
difficult to visually distinguish endosomes based on the different
types of inclusions, such as undigested engulfed synaptic material
or partially digested material, we considered all endosomes con-
taining some material as FE (Fig. 1H, left), whereas endosomes
with no material were scored as EE (Fig. 1H, right). Notably,
often EE appeared to form a complex tubular structure within
the PAP in the 3D reconstruction (Fig. 1I). Although the num-
ber of FE did not change significantly across experimental
conditions (KW test, p0.13), the number of EE showed a
large increase in S mice relative to SD (MW test, p0.0001)
and CSR (MW test, p0.0001) mice. The density of EE in W
mice was different from S mice (MW test, p0.045) but also
from SD (MW test, p0.006) and CSR (MW test, p0.0002)
mice (Fig. 1J).
Bellesi et al. Glial Phagocytosis in Sleep and Wake J. Neurosci., May 24, 2017 37(21):5263–5273 • 5267
Sleep loss increases the expression of MERTK
In a recent study in Aldh1L1-eGFP-L10a mice, we used translat-
ing ribosome affinity purification technology and microarrays to
identify astrocytic genes whose expression is affected by the sleep/
wake cycle and found Mertk among the “wake” genes, upregu-
lated in both spontaneous wake and acute sleep deprivation
relative to sleep (Bellesi et al., 2015). Here the same data sets
(NCBI GEO accession number GSE69079) were interrogated by
comparing S either with forced wake or with spontaneous wake,
to determine whether among the previously identified astrocytic
transcripts involved in phagocytosis (Cahoy et al., 2008) some
were specifically affected by acute sleep loss but not by spontane-
ous wake. We found little evidence for additional activation of
phagocytic genes in forced wake relative to spontaneous wake:
Mertk showed a similar increase in both comparisons (S vs W,
p0.005; S vs SD, p0.003; Fig. 2A), and Gas6, the MERTK
ligand, also showed a similar trend toward an increase (both p
0.06; Fig. 2A). The only difference was crk, whose protein inter-
acts with DOCK1, the downstream pathway of MERTK, which
trended to increase (p0.06) only after forced wake, and Itgb2,
which instead increased ( p0.014) only after spontaneous wake
(Fig. 2A). Overall, these results suggest that a few hours of wake
are sufficient to activate the MERTK pathway, even without sleep
loss. To verify whether Mertk was upregulated also at the protein
level, we first double stained coronal sections of frontal cortex
with antibodies against MERTK and GFAP, a well recognized
marker for astrocytes. We confirmed that several astrocytic pro-
cesses were MERTK positive (Fig. 2B), as described previously
(Chung et al., 2013). Then, to assess the MERTK expression level
in nearby synapses, we prepared cortical synaptoneurosomes
from S, SD, and CSR mice, and after checking that synaptoneu-
rosomes still contained perisynaptic glia using the astrocytic
marker GFAP (Fig. 2C, top), we measured MERTK protein ex-
pression (Fig. 2C, bottom). Quantitative immunoblot analysis
showed that both SD (Dunn’s multiple comparison test, p
0.05) and CSR (Dunn’s multiple comparison test, p0.05) were
associated with higher MERTK levels relative to S, and the in-
crease was similar in the two conditions (Fig. 2D), again suggest-
ing that the activation of MERTK is linked to being awake but
does not reflect the severity and/or duration of sleep loss.
Through the action of Gas6, the MERTK receptor can recog-
nize “eat-me” signals on the membrane of the cell that needs to be
phagocyted. These signals include the exposure of phosphatidyl-
serine on the outer leaflet of the plasma membrane (Ravichan-
dran, 2010), which can occur because of oxidative stress (Kagan
et al., 2002;Brown and Neher, 2014). To assess whether sleep loss
was associated with high levels of oxidative stress at the synaptic
level, we measured the extent of lipid peroxidation by quantifying
free MDA, a lipid peroxidation end product, in cortical synap-
toneurosomes of S, SD, and CSR mice. Colorimetric quantifica-
tion of MDA levels showed a similar trend toward an increase in
SD and CSR mice relative to S mice (KW test, p0.065), whereas
Figure 2. Sleep loss is associated with MERTK upregulation. A, Heat diagram showing the expression levels of astrocytic genes previously identified (Cahoy et al., 2008) as indicative of
phagocytosis in astrocytic-enriched samples of S, W, and SD adult heterozygous Aldh1L1-eGFP-L10a mice (Bellesi et al., 2015).
#
p0.05 in S versus W; *p0.1 and **p0.01 in S versus SD.
B, Example of an astrocyte stained with GFAP (red) and coexpressing MERTK (green) along its processes (arrowheads). Scale bar, 30
m. C, Top, GFAP expression in cortical homogenates (HN) and
synaptoneurosomes (SYN). Bottom, Representative bands from S, SD, and CSR pools (n4 per pool) showing MERTK expression in cortical synaptoneurosomes. D, Western blot quantification of
MERTK expression in SD ( p0.05) and CSR (p0.05) relative to S. E, Lipid peroxidation analysis showing MDA concentration for S, SD, and CSR mice (KW test, p0.065).
5268 J. Neurosci., May 24, 2017 37(21):5263–5273 Bellesi et al. Glial Phagocytosis in Sleep and Wake
no difference was observed between SD and CSR (MW test, p
0.4; Fig. 2E).
Chronic sleep restriction is associated with
microglia activation
MERTK protein is also expressed in microglia (Chung et al.,
2013), and microglia contributes to synaptic elimination during
normal development (Paolicelli et al., 2011;Schafer et al., 2012;
Bialas and Stevens, 2013) and in response to monocular depriva-
tion (Sipe et al., 2016). Thus, we sought to assess whether sleep
loss leads to microglia activation in mouse cerebral cortex. We
stained S, SD, and CSR brain sections with IBA-1, a recognized
marker for microglia and quantified microglia density in the
frontal cortex (Fig. 3A). Despite a small increase in CSR relative
to SD and S mice, we found no significant changes in cell number
(KW test, p0.09; Fig. 3B). Then, we analyzed the morphology
of microglial cells, since it correlates closely with their state of
activation (Kreutzberg, 1996;Nimmerjahn et al., 2005). To quan-
tify the complexity of microglia branching, we used two different
validated approaches. The first method (Morrison and Filosa,
2013) calculates the number of process end points per cell and the
length of microglia processes per cell by skeletonizing despeckled
IBA-1-stained fields (Fig. 3C). The number of end points per cell
did not significantly change across conditions (KW test, p0.15),
although a trend toward a decrease was present in CSR relative to
S animals (MW test, p0.06; Fig. 3D). Pairwise comparisons
between groups (S vs SD, SD vs CSR) were not significant. Quan-
titative analysis showed instead a significant reduction of process
length per cell in CSR relative to S mice (MW test, p0.004; Fig.
3E). In the second approach, using a custom-made Matlab algo-
rithm based on the study by Kozlowski and Weimer (2012),we
measured the area and perimeter of automatically, individually
identified IBA-1 microglial cells. For each experimental group,
cells were clustered in quartiles (from small area/perimeter to
large area/perimeter), and the relative number of cells within
each quartile was estimated (Fig. 3F). Repeated-measures two-
way ANOVA with experimental group as the between factor and
quartiles as the within factor showed a main effect of experimen-
Figure 3. Chronic sleep loss is associated with microglia activation. A, Raw images from S (n6), SD (n5), and CSR (n6) mice (frontal cortex) showing IBA-1 staining. Scale bar, 30
m.
B, Number of IBA-1-positive cells per cubed millimeter in S, SD, and CSR mice. C, Example of one IBA-1-positive microglial cell as it appears from the raw image and after processing (despeckling and
skeletonizing).D,E, Number of end pointsper cell (D) andsum of allprocess lengths permicroglial cell (E)in S, SD,and CSR mice.*p0.05. F, Left,Examples from Sand CSR fieldsshowing processed
and color-coded IBA-1 microglial cells (yellow, more ramified; blue, less ramified). Right, Examples of poorly ramified (above) and very ramified (below) IBA-1 microglial cells. G, Distribution in
quartiles of the number of IBA-1 microglial cells ranked by area size, an indirect measure of the complexity of process branching. *p0.05.
Bellesi et al. Glial Phagocytosis in Sleep and Wake J. Neurosci., May 24, 2017 37(21):5263–5273 • 5269
tal group (area: F
(2,14)
4.16, p0.038; perimeter: F
(2,14)
3.74,
p0.05) and a significant interaction (area: F
(6,42)
6.82, p
0.001; perimeter: F
(6,42)
6.35, p0.001). Post hoc analysis found
that in the first quartile, the number of cells was higher in CSR mice
relative to S (area: Bonferroni’s test, t4.78; p0.001; perimeter:
Bonferroni’s test, t4.95; p0.001) and SD (area: Bonferroni’s
test, t4.58; p0.001; perimeter: Bonferroni’s test, t4.68;
p0.001) mice, whereas the opposite was true in the fourth
quartile (CSR vs S, area: Bonferroni’s test, t3.44, p0.01;
perimeter: Bonferroni’s test, t3.44, p0.01; CSR vs SD, area:
Bonferroni’s test, t4.06, p0.001; perimeter: Bonferroni’s
test, t3.44, p0.01). These results suggest that there was a
higher number of less ramified cells and a lower number of well
ramified cells in CSR mice relative to SD and S mice (Fig. 3G,
values for perimeter are not shown).
Furthermore, we investigated whether sleep loss promoted
microglial phagocytosis by quantifying the number and volume
of presynaptic terminals, identified as VGLUT-1-positive puncta
with confocal microscopy, which were engulfed within IBA-1-
stained cells. Only VGLUT-1-positive puncta larger than 100 pix-
els (roughly corresponding to 0.03
m
3
) and showing an overlap
of 100% in xyz with microglial cells were considered as phago-
cyted (Fig. 4A–C). Quantitative analysis showed that the number
and volume of phagocyted VGLUT-1 puncta changed signifi-
cantly across conditions (KW test; number, p0.03; volume,
p0.03). Specifically, phagocyted VGLUT-1 puncta were more
numerous in CSR mice than S mice (density, 27.98 13.56%;
MW test, p0.009) and larger in CSR mice than S mice
(32.13 22.38%; MW test, p0.026) and SD mice (38.52
23.46%; MW test, p0.03; Fig. 4D,E). The percentage of
VGLUT-1 puncta engulfed within microglia relative to the total
number of VGLUT-1 puncta was higher in CSR mice (0.39
0.14%) than S (0.22 0.07%; MW test, p0.04) and SD (0.19
0.06%, MW test, p0.017; data not shown) mice.
To further characterize microglial-mediated phagocytosis, we
measured C3 expression levels in cortical homogenates of S, SD,
and CSR mice. C3, a central component of the complement cas-
cade, is deposited on cell debris and can directly activate C3 re-
ceptors on microglia, thus triggering phagocytosis. Western blot
analysis showed that C3 expression was higher in CSR mice than
S mice (Dunn’s multiple comparison test, p0.04). Despite
some variability, SD mice also showed higher C3 levels than S
animals (Dunn’s multiple comparison test, p0.04), suggesting
that even shorter periods of sleep loss can trigger C3 activation
(Fig. 4F). Overall, these results indicate that CSR is associated
with microglia activation and increased phagocytosis.
Finally, we ascertained whether microglia activation was asso-
ciated with increased levels of inflammatory mediators in the
CSF. CSF was extracted in additional groups of S, SD, and CSR
mice. Multiplex immune assay analysis showed that 14 of the 23
molecules analyzed (i.e., IL1a, IL2, IL3, IL4, IL5, IL6, IL10, IL12,
IL17a, G-CSF, IFN
, MIP1a, and RANTES) were undetectable in
almost all CSF samples. Nine of the remaining molecules (i.e.,
IL1b, IL9, IL12, IL13, Eotaxin, KC, MCP1, MIP1b, and TNF
)
were detected in 34 –100% of samples. Levels of IL1b, IL9, IL12,
IL13, Eotaxin, KC, MCP1, and MIP1b did not change signifi-
cantly across groups, whereas levels of TNF
were higher in S
mice relative to SD (MW test, p0.018) and CSR (MW test, p
0.047; Fig. 4G). Overall, these results indicate that CSR is associ-
ated with microglia activation and increased phagocytosis with-
out a notable increase of inflammatory mediators in the CSF.
Discussion
We show that acute sleep deprivation and chronic sleep loss in-
crease the number of phagocytic events mediated by astrocytes in
the mouse cortical neuropil, whereas only chronic sleep loss can
trigger microglial phagocytosis. In astrocytes, phagocytosis is as-
sociated with increased MERTK expression and lipid peroxida-
tion, whereas microglial phagocytosis is associated with increased
levels of the complement component C3 without clear signs of
inflammations in CSF.
Only a few synapses are affected by AP: peripheral astrocytic
processes target 80% of all excitatory synapses, the larger ones,
and 10% of them on average undergo AP. Our adolescent mice
had already experienced the critical period of most intense syn-
aptic pruning, but more subtle synaptic refinement was likely still
occurring (Hoel et al., 2016). Early developmental phagocytosis
mainly targets presynaptic elements of transient, likely weaker,
retinogeniculate synapses (Schafer et al., 2012;Chung et al.,
2013). By contrast, wake-enhanced phagocytosis preferentially tar-
gets larger, and thus stronger, synapses and often involves axonal
elements outside the presynaptic terminal. Thus, glial phagocy-
tosis may serve different functions: elimination of exuberant syn-
apses during early development and degradation of components
of strong, likely well established synapses in response to extended
wake during adolescence. Astrocytes could promote the housekeep-
ing of worn synaptic components, especially axonal elements, by
degrading portions of their membranes, perhaps damaged by ex-
cessive lipid peroxidation. Of note, we found that the presence of
mitochondria within the presynaptic boutons did not increase
the likelihood of a synapse to be phagocyted. At first, this result
seems to exclude a direct link between oxidative energy metabo-
lism and AP. However, mitochondria are present in only 40%
of presynaptic terminals (Chavan et al., 2015;de Vivo et al., 2017)
and are rarely seen in spine heads (Sorra and Harris, 2000), which are
characterized by intense metabolic activity (Harris et al., 2012), sug-
gesting that the presence of mitochondria may be a poor marker of
the overall metabolic activity of a synapse.
Our results suggest that extended wake enhances AP through
a mechanism that involves the MERTK receptor. In fact, a few
hours of spontaneous wake are sufficient to upregulate Merkt
expression relative to sleep (Bellesi et al., 2015), but not to in-
crease the incidence of AP (this study). Thus, the activation of the
MERTK pathway may start during spontaneous wake, but its
long-term, structural consequences become apparent only after
sustained sleep loss. MERTK recognizes “eat me signals” pre-
sented in target debris (Ravichandran, 2010). One of them is
phosphatidylserine, a phospholipid normally confined to the in-
ner leaflet of the plasma membrane, which triggers phagocytosis
when exposed on the cell surface. Increased calcium concentra-
tions, ATP depletion, and oxidative stress are all factors linked to
cell activity and metabolism that can induce membrane translo-
cation of phosphatidylserine (Brown and Neher, 2014). Since
synaptic activity accounts for most of the brain’s energy budget
(Harris et al., 2012), greater metabolic activity and/or increased
production of waste induced by extended wake (Cirelli et al.,
2006) could favor the externalization of phosphatidylserine on
the plasma membrane of heavily used synapses. Another possible
mechanism involves C1q, which localizes at the sites of synaptic
elimination in the developing reticulogeniculate system (Stevens
et al., 2007). The expression of all three subunits of the C1q
complex is upregulated when retinal ganglion cells are exposed to
astrocytes, and through C3 activation, C1q can initiate synapse
elimination by the classical complement cascade (Stevens et al.,
5270 J. Neurosci., May 24, 2017 37(21):5263–5273 Bellesi et al. Glial Phagocytosis in Sleep and Wake
2007). Of note, the C1q subunit
mRNA is upregulated in the
cortex of adult rats in wake relative to sleep (Cirelli et al., 2004),
and in the current study, C3 levels increased after acute and
chronic sleep loss relative to sleep. Using the same dataset of this
study, we recently also found that synaptic density in frontal
cortex does not change between S and SD, and most spines de-
crease in size during sleep in a manner proportional to their size
(de Vivo et al., 2017). Crucially, this downscaling is diffuse but
selective, sparing the large synapses (de Vivo et al., 2017) in which
we show here that AP is more common. Thus, stronger and more
“rigid” synapses, whose strength does not seem to change be-
tween sleep and wake, may use AP to recycle structural compo-
nents and guarantee a proper synaptic function, perhaps not only
in response to damage, but to prevent it.
In addition to AP, we also found endosomes enclosed within
the PAPs. In eukaryotic cells, endosomes are involved in mem-
brane recycling, receptor trafficking, exocytosis, and cellular
waste disposal (Maxfield and McGraw, 2004). In PAPs, we can-
not exclude that some of the endosomes, those containing undi-
gested material resembling presynaptic vesicles, represent further
Figure4. Chronic sleep loss is associatedwith microglial phagocytosis. A,Raw image showingan IBA-1-positive microglia(green) and VGLUT-1puncta staining (magenta)in a representativeCSR
mouse. Scale bar, 5
m. B, Enlarged frame of the cell shown in A, visualized also in the xz and yz projections and in gray separated channels, showing a VGLUT-1-positive element engulfed within
the microglial soma (arrowheads). C, 3D reconstruction of the same cell showing the engulfed VGLUT-1 element (arrowhead). D,E, Number (D) and volume (E) of phagocyted VGLUT-1 elements per
microglial cell for S (n6), SD (n5), and CSR (n6). *p0.05. F, Western blot analysis of the complement component C3 for SD and CSR pools relative to S pools. Representative bands are
depicted above from cortical homogenates of S, SD, and CSR pools (n4 per pool). G, Protein levels of cytokines and chemokines in CSF from S (n11), SD (n10), and CSR (n8) mice. Protein
levels were measured in individual CSF specimens using multiplex magnetic bead technology for the simultaneous measurement of the 23 cytokines/chemokines. Shown is the expression of the
detected molecules and the relative pvalues obtained from the KW test.
Bellesi et al. Glial Phagocytosis in Sleep and Wake J. Neurosci., May 24, 2017 37(21):5263–5273 • 5271
steps of the phagocytosis process. On the other hand, the reduc-
tion of empty endosomes after chronic sleep loss may indicate
that they are being used during the engulfment process and/or to
recycle heavily used portions of cytoplasmic membrane. Inde-
pendent of its functional significance, which is still unclear, this
finding is in line with the results of a recent study that character-
ized ultrastructural changes in the cell body of cortical pyramidal
neurons and found that empty endosomes were more frequently
observed in S relative to CSR mice (de Vivo et al., 2016).
Microglial cells, the resident innate immune cells in the brain,
are alert sentinels of the nervous system clearing debris, looking
for signs of infiltration by infectious agents, and mediating the
inflammatory and repair response to several brain injuries (Nim-
merjahn et al., 2005;Hanisch and Kettenmann, 2007;Tay et al.,
2017). Microglia regularly extend their protrusions to briefly touch
and sense the functional state of synapses in an activity-dependent
manner (Wake et al., 2009;Tremblay et al., 2010), and their role
in developmental synaptic pruning has recently been recognized
(Paolicelli et al., 2011;Schafer et al., 2012;Bialas and Stevens,
2013;Sipe et al., 2016). The two molecular mechanisms discussed
above as potential mediators of the wake-related activation of AP
could also apply to microglia, which express both MERTK and C3
receptors (Stevens et al., 2007;Chung et al., 2013) and could be
activated by some form of damage at synaptic membranes trig-
gered by sustained neuronal activity. However, direct morpholog-
ical evidence of microglial activation with transition to an active
ameboid state, and signs of microglial phagocytosis, were only found
after chronic sleep restriction, suggesting that severe and sustained
sleep loss is required to fully engage microglia. Microglial and
astrocytic activation were reported in the rat hippocampus after
5 d of total sleep deprivation (Hsu et al., 2003). Moreover, mice
treated with the antibiotic minocycline, an inhibitor of microglial
activation, showed a reduced rebound in slow-wave activity after
3 h of sleep deprivation, prompting the authors to suggest that
microglial activation may contribute to the buildup of sleep need
during extended wake (Wisor et al., 2011). In the same study,
however, short sleep deprivation did not increase the expression
of IL1
, IL6, and TNF
in brain homogenates and decreased the
expression of CD11b, which is enriched in microglia (Wisor et al.,
2011). We found that 6 8 h of sleep deprivation, which consis-
tently trigger a sleep rebound with increased slow-wave activity
(Bellesi et al., 2015), did not lead to microglial activation. Thus, in
our experimental conditions, microglia are unlikely to play a role
in sleep homeostasis.
Microglial activation after chronic sleep loss occurred without
signs of neuroinflammation. In both animals and humans, sleep
loss has been associated with a pro-inflammatory state (Mulling-
ton et al., 2010;Hurtado-Alvarado et al., 2013), and perhaps our
CSF assay was not sensitive enough to detect mild inflammation.
Alternatively, CSF inflammation may occur only in fully blown
pathological states but not in response to sleep loss per se. Since
microglia, like astrocytes, participate in the removal of synaptic
debris, their activation during prolonged wake may represent the
physiological response of these cells to worn synapses. An alter-
native explanation, however, is suggested by the finding that sleep
promotes the clearance of amyloid-
from the interstitial space
(Xie et al., 2013) whereas sleep deprivation promotes the deposi-
tion of amyloid plaques (Lim et al., 2014), which in turn can lead
to microglia activation (Xiang et al., 2006;Halle et al., 2008;Jung
et al., 2015). Persistent microglial activation, even at a low level
(microglia priming), can lead to exaggerated and detrimental
responses to a secondary insult, further promoting pathological
states (Perry and Holmes, 2014). Thus, we speculate that by
priming microglia, chronic sleep loss may increase the brain’s
susceptibility to other forms of damage, including neurodegen-
eration (Perry and Holmes, 2014;Calcia et al., 2016), although
this idea needs to be tested directly.
Our molecular screening identified Mertk and crk transcripts,
both belonging to the MERTK pathway, as the only astrocytic
genes linked to phagocytosis and overexpressed after sleep depri-
vation relative to sleep (Bellesi et al., 2015). Yet, the current study
is correlational, and we do not know whether MERTK and C3
receptors are necessary or sufficient for sleep loss-mediated
phagocytosis. Future experiments may be able to causally link the
astrocytic and microglial molecular changes to sleep loss, for in-
stance by using Mertk/(Chung et al., 2013) and CR3/
(Schafer et al., 2012) mice.
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Bellesi et al. Glial Phagocytosis in Sleep and Wake J. Neurosci., May 24, 2017 37(21):5263–5273 • 5273
... Therefore, as a ligand-gated ion channel dependent on ATP, microglial P2X7R plays an important role in sleep disorders. After an injury, reactive microglia increased in cortex regions, preceding the development of sleep disruptions (Bellesi et al., 2017). Given the probable causal relationship between pain relief and sleep disorder improvement induced by administration of P2X7R inhibitor, microglial P2X7R expression changes might be a response to pain relief and subsequently improved sleep. ...
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... The mechanisms underlying the associations between sleep and brain health are not well understood. However, recent studies found short sleep to be linked to increased oxidative stress 34 , microglial activation 35 , elevated circulating and brain pro-inflammatory cytokines 36 implicated in neuronal injury 37 , decreased dendritic spine and density 38 , demyelination 39 , microgliosis 40 , and white matter lesions 41 which contribute to brain atrophy 42,43 . Additionally, as noted above, the clearance of unwanted byproducts of cell metabolism, including amyloid β 5 and tau, which is facilitated by the opening of the brain glymphatic channels during sleep, is likely to be insufficient below certain sleep duration and may lead to the accumulation of toxic metabolites 44 . ...
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... The immune system and sleep are intimately linked (Krueger and Majde, 1990;Toth et al., 1993;Opp, 2005). There is growing evidence that microglia are involved in sleep regulation (Wisor et al., 2011;Ingiosi et al., 2013), as they are activated after sleep loss (Hsu et al., 2003;Bellesi et al., 2017;Wadhwa et al., 2018;Tuan and Lee, 2019;Xie et al., 2020), and improved sleep (based on the Pittsburgh sleep quality index (PSQI) self-report questionnaire) is associated with reductions in inflammation Livingston et al., 2015). Furthermore, short-term (72 h) REM deprivation produces activation of the immune system that can persist after recovery sleep (Yehuda et al., 2009) suggesting a possible role for REM in the neuroimmune responses induced by stress. ...
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... Previous studies have suggested that sleep is associated with increased elimination of dendritic spines in the developing mouse sensory cortices (Maret et al., 2011;Yang & Gan, 2012), and insufficient sleep can affect memory function (Fernandes et al., 2015). Consistent with previous studies (Ramesh et al., 2012;Wadhwa et al., 2017;Bellesi et al., 2017), our data demonstrated that defective working memory detected in sleep-restricted mice appeared in parallel with decreased synaptic density and dendritic spines. Dendritic spines are the major sites of synaptic transmission in the central nervous system, and alterations in the strength of synaptic connections directly affect neuronal communication, which is crucial for brain function as well as the processing and storage of information. ...
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... Finally, we acknowledge that our study presents some limitations. The EM analysis is limited to neuronal somas, and we ignore whether other brain cells, which promptly respond to sleep loss, such as microglia or astrocytes [53][54][55], display similar changes in the ER and mitochondrial dynamics. For example, there is evidence showing that astrocytes react to ischemic stress by increasing mitochondrial clustering and promoting MAMs at the perivascular end-feet [56]. ...
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