C Carlock1, J Wu1, J Shim1, I Moreno-Gonzalez2, M R Pitcher3, J Hicks4, A Suzuki1, J Iwata1, J Quevado3,5, Y Lou1. 1. Department of Diagnostic Sciences, School of Dentistry, McGovern School of Medicine, University of Texas Health Science Center at Houston, Houston, TX, USA. 2. Department of Neurology, McGovern School of Medicine, University of Texas Health Science Center at Houston, Houston, TX, USA. 3. Department of Psychiatry and Behavioral Sciences, McGovern School of Medicine, University of Texas Health Science Center at Houston, Houston, TX, USA. 4. Department of Pathology, Baylor College of Medicine, Houston, TX, USA. 5. Laboratory of Neurosciences, Graduate Program in Health Sciences, Health Sciences Unit, University of Southern Santa Catarina, Criciúma, Brazil.
Abstract
Late-onset Alzheimer's disease (AD) remains a medical mystery. Recent studies have linked it to impaired repair of aged neurons. Potential involvement of interleukin33 (IL33) in AD has been reported. Here we show that IL33, which was expressed by up to 75% astrocytes in the aged brains, was critical for repair of aged neurons. Mice lacking Il33 gene (Il33-/-) developed AD-like disease after 60-80 weeks, which was characterized by tau abnormality and a heavy loss of neurons/neurites in the cerebral cortex and hippocampus accompanied with cognition/memory impairment. We detected an abrupt aging surge in the cortical and hippocampal neurons at middle age (40 weeks). To counter the aging surge, wild-type mice rapidly upregulated repair of DNA double-strand breaks (DSBs) and autophagic clearance of cellular wastes in these neurons. Il33-/- mice failed to do so, but instead went on to develop rapid accumulation of abnormal tau, massive DSBs and abnormal autophagic vacuoles in these neurons. Thus, uncontrolled neuronal aging surge at middle age due to lack of IL33 resulted in neurodegeneration and late-onset AD-like symptome in Il33-/- mice. Our study also suggests that the aging surge is a time to search for biomarkers for early diagnosis of AD before massive neuron loss.
Late-onset Alzheimer's disease (AD) remains a medical mystery. Recent studies have linked it to impaired repair of aged neurons. Potential involvement of interleukin33 (IL33) in AD has been reported. Here we show that IL33, which was expressed by up to 75% astrocytes in the aged brains, was critical for repair of aged neurons. Mice lacking Il33 gene (Il33-/-) developed AD-like disease after 60-80 weeks, which was characterized by tau abnormality and a heavy loss of neurons/neurites in the cerebral cortex and hippocampus accompanied with cognition/memory impairment. We detected an abrupt aging surge in the cortical and hippocampal neurons at middle age (40 weeks). To counter the aging surge, wild-type mice rapidly upregulated repair of DNA double-strand breaks (DSBs) and autophagic clearance of cellular wastes in these neurons. Il33-/- mice failed to do so, but instead went on to develop rapid accumulation of abnormal tau, massive DSBs and abnormal autophagic vacuoles in these neurons. Thus, uncontrolled neuronal aging surge at middle age due to lack of IL33 resulted in neurodegeneration and late-onset AD-like symptome in Il33-/- mice. Our study also suggests that the aging surge is a time to search for biomarkers for early diagnosis of AD before massive neuron loss.
Late-onset Alzheimer’s disease (AD), which is an increasing socioeconomic
burden worldwide, remains a medical mystery.[1] However, recent studies have linked this disease to the
impairment in rejuvenation or repair of aged neurons.[2, 3, 4,
5, 6] These
mechanisms include DNA damage repairing and autophagic elimination of metabolic
wastes.[7, 8,
9] Neuron’s aberrant reentry into cell
cycle in AD may de-regulate these mechanisms, resulting in neuron death.[10] Deficiencies in cytokines or other immune
molecules have also reportedly implicated in these rejuvenation mechanisms and
neurodegenerative diseases including AD.[11,
12, 13]
Expression of various cytokines such as IL-1β and TNFα in ADpatients
suggests their roles in AD pathogenesis.[13,
14] However, it remains to be determined if
these cytokines may act as protective or inflammatory roles.Interleukin33 (IL33), which is often detected as a nuclear protein, is a member of
the interleukin1 cytokine family. It acts as mature cytokine after cleavage with ST2
as its receptor. Beyond its multifunction in immune defense, IL33 also plays a role
in the injury healing in central nervous system and other diseases.[15, 16, 17, 18, 19] IL33 has been genetically linked to humanAD.[20] Injection of recombinant IL33
shows a beneficial effect in mouseAD models.[21] Constitutive expression of IL33 in a wide range of tissues
including the brain suggests its potential roles beyond immune defense.[22, 23, 24, 25, 26, 27] Our previous
study has demonstrated one such role for IL33 in tissue homeostasis in degenerative
ovarian tissue.[28, 29] In the present study, we investigated role of IL33 in
tissue homeostasis in the brain. We found that IL33 was critical for repair of aged
neurons. Its deficiency caused tau abnormality and late-onset of neurodegeneration in
the cerebral cortex and hippocampus, accompanied with AD-like cognition and memory
impairment.
Materials and methods
Mice and their treatment
C57BL/6 (B6) mice were purchased from Harlan (Indianapolis, IN, USA).
Il33tm1(KOMP)Vlcg
(Il33) mouse strain was
created (WWW.KOMP.org) and
characterized.[29, 30] The Il33
strain shows generally normal without any developmental defects.[29, 31] All animal
procedures in this study were approved by institutional animal welfare committee.
Mice were randomly selected for all experiments, and were tested with the group
allocation blind to investigators; data were assembled after testing for each
group for statistical analysis. Mice were perfused with room temperature PBS
followed 2% paraformaldehyde before brains were harvested. In some cases,
fresh brains were used.
Histology and electron microscopy
Brain tissues, fixed through perfusion, were embedded in paraffin and used for
routine histology, including hematoxylin–eosin (H–E) staining,
Bielschowsky silver staining and crystal violet staining. Three samples per group
were processed for transmission electron microscopy following an established
method.[29]
Behavioral tests
Four behavioral tests were performed for assessment of cognition/memory
impairment associated with AD in mice.[32,
33, 34]
Locomotor activities (horizontal and vertical) test was performed in a
computer-controlled activity cage (Ugo Basile, Monvalle, Italy) for an untrained
mouse in the open testing chamber (54 × 50 × 37 cm) for
recording its horizontal and vertical motions for 30 min. For habituation
test, a mouse was placed in an open-field (60 × 40 cm) surrounded by
50 cm high plexi-glass wall, and allowed to explore freely for 5 min
at day 1 and day 2 with numbers of its movements, that is crossing and rearing,
recorded. Fear-based passive avoidance test was performed in
Shocker-with-Scrambler behavioral chamber (PanLab, Barcelona, Spain). Mice
received an electric shock (0.8 mA × 2 s) as training. The
trained mice returned to the white chamber at day 1 and day 7 with their latency
time for entering dark chamber (limited to 3 min) recorded. Rotarod
performance test was carried out on an automatic instrument (Rotamex 4, Columbus
Instrument, Columbus, OH, USA).
Bromodeoxyuridine incorporation test
Bromodeoxyuridine (BrdU; BD Biosciences, Franklin Lakes, NJ, USA) was dissolved in
sterile DPBS at 10 mg ml−1. Each mouse received
intra-peritoneal injection of BrdU solution at a dose of 1.5 mg per
25 g bodyweight in 150 μl of solution. The mice were killed
24 h late and perfused, and their brains or other tissues removed for
detection of incorporated BrdU by immunofluorescence using an anti-BrdU
antibody.
Cerebral cortical homogenate, and fractionation of nuclei and organelles by
gradient centrifugation
Fresh cortexes were homogenized on ice in an extraction buffer containing a
protease inhibitor cocktail (Sigma-Aldrich, St Louis, MO, USA). After
centrifugation at 5000 g for 15 min at 4 °C, the
supernatant was removed, and protein concentration measured. For nuclear
fractionation, a published method with modifications was followed.[35] Whole cortex was cut into 2 ×
2 mm3 in cold PBS, and gently homogenized in a glass
homogenizer by B pestle (Wheaton Dounce tissue grinder, Millville, NJ, USA). Crude
nuclear fraction was recovered by centrifugation, laid on the top of five-layer
sucrose gradient (2.0, 2.2, 2.4, 2.6 and 2.8 M), and centrifugation in a
swing basket rotor at 53 500 g for 45 min. Each
nuclear fraction was recovered from the interfaces: astrocyte nuclei on interface
of 2.4 and 2.6 M, and neuronal nuclei 2.6 and 2.8 M. A small portion
was used for microscopy to confirm expected nuclear morphology for each fraction.
A published method was followed for fractionation of autophagosomes, autolysosomes
and lysosomes of cortical tissues.[36, 37] Cortical homogenate was centrifuged at
6500 g for 5 min, and the supernatant was further
centrifuged at 17 000 g for 10 min to pellet the
subcellular compartments, followed by Nycodenz (Sigma-Aldrich) discontinuous
gradient (10, 20, 24, 26, 50%) at 25 000 r.p.m. for
4 h. Fractions recovered from interfaces of 10–20% and
20–24%, contained autophagosomes and autolysosomes, respectively. All
procedures were carried out at 4 °C.
Antibodies
Following antibodies were used in this study: biotingoat anti-mouseIL33, rat
anti-mouseIL33, biotinrabbit anti-LC3, Alex Fluor555 rabbit anti-LC3, rabbit
anti-GFAP, mouse anti-tubulin β3, rabbit anti-BrdU, rabbit anti-PγH2AX,
rabbit anti-ubiquitin, rabbit anti-amyloid β antibody, mouse
anti-phosphor-tau AT8, PHF1 and MC1, FITC-labeled anti-α-actin. Secondary
reagents included Alexa-555, Alexa-594 and Alexa-647-labeled (Life Technologies,
Carlsbad, CA, USA) and PE-labeled streptavidin. Biotin/avidin and anti-mouseCD16/32 were used for blocking non-specific IgG binding. Immunoglobulin
isotypes were used as negative controls (BD Biosciences).
Western blot
Proteins were quantitated (Epoch Gen5, BioTek, Winooski, VT, USA), and mixed at
1:1 with SDS sample buffer. Ten micrograms of protein were loaded on a
SDS-polyacrylamide gel electrophoresis of various concentrations depending on size
of target protein, and ran at a constant current. After transfer, the membrane
(Immobilon-P PVDF, Millipore, Billerica, MA, USA) was used for immunostaining.
Anti-α-actin mouse monoclonal antibody (AC-15, Sigma) was simultaneously
added with the antibody to the target protein. The membrane was further incubated
with IRDye 800CW-labeled secondary antibody for target protein and IRDye 680LT
anti-mouse IgG antibody (LI-COR, Lincoln, NE, USA). The membrane was
simultaneously scanned at both wave lengths on an infrared fluorescence scanner
(Odyssey, LI-COR), with target protein as green and control α-actin as
red.
Immunofluorescence, terminal-deoxynucleotidyl-transferase dUTP nick-end
labeling, immunohistochemistry and quantitation of cells on sections
Frozen sections were cut from brain tissues, and were blocked in 3% BSA
with CD16/32 antibodies. If biotin-labeled antibodies were to be used, a
biotin and avidin blocking step was added (Vector BioLab, Philadelphia, PA, USA).
Up to four colors, that is, green (FITC or Alex488), red (TRITC, PE,
Alex594/555), false purple (APC or Alex647) and blue (DAPI) were applied for
each sections. In some cases, 20 μm sections were used for 3D scan
through Z-stack in confocal microscopy. For terminal-deoxynucleotidyl-transferase
dUTP nick-end labeling (TUNEL) staining, a kit (In Situ Cell Death
Detection Kit, Fluorescein, Roche, Nutley, NJ, USA) was used. The tissue sections
observed by a confocal microscope (Nikon, Tokyo, Japan, C2+
Eclipse Ti). In some cases, whole-brain sections were automatically
scanned and merged (Nikon Eclipes Ni). Digital images were analyzed with
NIS Elements 3.2 (Nikon) for fluorescent intensity as integrated optical density,
cellular area or cell numbers. For immunohistochemistry, secondary reagents
(avidin-peroxidase or peroxidase-conjugated secondary antibody) were used to
generate a brown deposition using DAB as a substrate in the presence of
H2O2.
Statistics
Paired (habituation tests) or unpaired T-tests (others) were used for
comparison between two groups. For three groups, one-way analysis of variance was
performed. Before pooling data from multiple individuals, data from each were
statistically compared to rule out any differences among them. Linear regression
test was used for analysis of correlations between ages and TUNEL densities,
between age and locomotor activities, in wild-type (WT) and
Il33mice, respectively;
r and P-value for deviation from zero
was calculated for each progression. Finally, slopes of the two linear
progressions were compared for statistical significance. In addition, time courses
for TUNEL densities in Il33 or WT
mice were constructed by non-linear four-parameter progression. Statistical
significances were indicated by *(P<0.05),
**(P<0.01) or ***(P<0.001).
Results
IL33 expression in astrocytes increases with age
Expression of IL33 in brains has been well studied.[23, 24, 25, 26] We especially
examined spatial and temporal expression pattern of IL33 in mouse brains from 3 to
75 weeks. Nuclear IL33 expression increased with age well past both immune and
sexual maturity (Figure 1a). The highest density of
nuclear IL33+ cells (>1000 cells per mm2 or up to
75% of cells) was in the regions rich in nervous fibers of aged mice
(Figure 1b). Immunofluorescence revealed that IL33
was often detected in nuclei of astrocytes, which were identified by GFAP (Figure 1c). Western blots of the fractionated brain cell
nuclei confirmed that astrocyte nuclei were the most abundant in IL33 (Figure 1d). Thus, IL33 was primarily expressed by
astrocytes, which is in agreement with several previous studies.[15, 26] A cleaved
IL33 (19 kDa) was also detectable (Figure 1d),
suggesting a release of cytokine IL33 in normal brains. Increasing extensive
expression of IL33 with age and release of cytokine IL33 in normal brains are
un-proportional to central nervous system immune privilege, suggesting
IL33’s role in central nervous system tissue homeostasis during aging.
Figure 1
Interleukin33 (IL33) expression in astrocytes in brains increases with age.
(a) Distribution pattern of nuclear IL33+ cells in the
brains at different ages. Densities were calculated from two to three mice for
each age. Scale for density of IL33+ cells per mm2 is
shown. (b) Immunofluorescence of nuclear IL33+ cells (red)
in the boxed area in a. (c) Immunofluorescence reveals nuclear IL33
(red) in astrocytes identified by GFAP (green). Left panels show each fluorescent
channel of the boxed cell at right panel. (d) Western blot detects (lower
panel) abundant IL33 protein in astrocyte nuclei. Both nuclear IL33 and cleaved
cytokine IL33 were detected. Phase-contrast images for fractionated nuclei are
shown on the top.
Il33−/− mice develop tau abnormality and
late-onset neurodegeneration in cerebral cortex and hippocampus
A mouse strain with Il33 gene deleted
(Il33) has been generated
and characterized.[29] We compared their
brains to WT littermates. Il33
brain were normal before 40 weeks, but showed significant neurodegeneration in the
cerebral cortex and hippocampus after 60 weeks (Figure
2a). Heavy deposition of abnormal tau, that is, hyper-phosphorylated,
paired helical fragment (PHF), and insoluble tau was detected in cortical and
hippocampal neurons in six out of seven mice of 65–80 weeks (Figures 2b and c). Both silver staining on 30-μm
sections and immunofluorescence on tubulin β3 revealed a heavy loss of
neurites/neurons. The loss is well exemplified by disappearance of both normal
cortical layers and hippocampal apical dendrite tufts constituted by tubulin
β3 in Il33mice (Figures 2d and e, Supplementary
Figures 1a and b). Quantitation showed that tubulin β3 density
in Il33mice reduced to 55%
and 37% of the WT mice in the cortex and hippocampus, respectively (Figure 1f). Vacuoles were often observed in neuronal soma
and neurites as early as 40 weeks (Figure 2g). Often
open oval-shaped empty space was left after the loss of neurons (Figure 2g). These changes prompted us to test for any
behavioral changes in Il33mice.
Increased locomotor activities are associated with murineAD.[38, 39]
Il33mice showed an age-related
increase in locomotor activities especially after 60 weeks (Figure 3a, Supplementary Figure 1c).
In habituation tests, old Il33mice (60–80 weeks) did not display a decline in exploration activities post
training as age-matched WT mice (Figure 3b).
Fear-based passive avoidance test is often used to assess behavioral changes
associated with AD or neurodegenerative diseases.[40] This test revealed a significantly higher re-entry rate
into the dark chamber post electric shock training in old
Il33mice, suggesting loss
of short memory (Figure 3c). However,
Il33mice under 40 weeks did
not show any behavioral changes as compared with WT mice (Figures 3a–c). Thus,
Il33mice began to develop
cognition/memory impairments after 60–80 weeks. Interestingly, old
Il33mice showed no differences
from age-matched WT mice in either motor function assessment or Purkinje cell
density, suggesting that their cerebella were relatively unaffected (Figures 3d and e, Supplementary Figure
1d).
Figure 2
Il33 mice develop late-onset
neurodegeneration and abnormal tau accumulation in the cerebral cortex and
hippocampus. (a) Cortex and hippocampus from a representative 60-week
Il33 mouse display
neurodegeneration as compared to a wild-type (WT) mouse; enlarged boxed areas are
shown below. Total seven mice for each group were examined with similar results.
(b) Immunohistochemistry reveals heavy accumulation of paired helical
fragment (PHF1) tau in cortical and hippocampal neurons in a representative
70-week Il33 mouse
(n=7). (c) Immunohistochemistry reveals cellular abnormal
tau (AT8, PHF and insoluble tau MC1) in neurons. Arrows indicate neuron with MC1.
(d) Silver stain of 30-μm section shows greatly reduced neurite
networks in the cortex of a representative 70 weeks of
Il33 mouse
(n=5) as compared to a WT littermate of the same age
(n=6). (e) Three-dimensional immunofluorescence on protein
tubulin β3 reveals loss of neurite tufts of hippocampus in a 65-week
Il33mouse (n=5)
as compared to an age-matched WT mouse (n=5). (f)
Statistical summary of tubulin β3 area in WT and
Il33 brains. (g)
Crystal violet staining shows vacuoles in soma and axon of pyramid neurons (upper
right), or empty spaces (arrow heads, lower right) in dentate gyrus of an
Il33mouse
(n=3). Note many neurons (arrows in lower left panel) are present
in the same locations in a WT mouse. Bar unit=μm.
Figure 3
Il33 mice develop
cognition/memory impairments after 60–80 weeks. (a) Locomotor
activity (vertical and horizontal) tests reveal elevated activities in old
Il33 mice (60–80 weeks).
(b) Habituation test reveals no decline in exploring activities (both
rearing and crossing) at day 2 (d2) in aged
Il33 mice (60–80
weeks) after training at day 1 (d1). Wild-type (WT) or young
Il33 mice displayed
significantly lower exploration activities at day 2. Activities were shown for
each individual. (c) Electric shock-based passive avoidance test shows more
frequent re-entry into dark chamber among aged
Il33 mice (60–80
weeks). Data are shown for each individual. (d) Rotamex test show no
differences between either young or old WT and
Il33 mice. Data are shown
for each individual. (e) Old
Il33 mice show a similar
density of Purkinje cells in cerebella as compared to age-matched WT mice;
n=5. Comparisons were made by two-tailed t-test
(a,d,e), paired t-test (b) and
Welch’s t-test (c).
Il33
mice fail to repair stressed neurons after an abrupt aging surge at middle
age
We next explored what had led to neurodegeneration in the cortex and hippocampus
in old Il33mice. We first
detected an overwhelmingly large number of TUNEL+ nuclei in the
cortex and hippocampus in aged
Il33mice (Figure 4a). Notably, ~90% of the cells in the dentate gyrus
and CA region of hippocampus were TUNEL+. Co-staining with tubulin
β3 revealed that the TUNEL+ cells were neurons (Figure 4b). Brain TUNEL+ neurons have been
detected in humanAD autopsy and animal models for neurodegenerative
diseases.[41, 42] However, the nature of these TUNEL+
neurons remains ambiguous. We compared these TUNEL+ neurons with
apoptotic ovarian cells during atresia of the same individuals.[29] TUNEL intensity in neurons was only 1/20
to 1/40 of that of those apoptotic cells without any detectable caspases or
DNA condensation (Supplementary Figures 2a and b).
TUNEL can also detect genomic DNA double-strand breaks (DSBs). Thus,
TUNEL+ in neuronal nuclei of
Il33mice indicated
accumulation of a large number of DSBs. Whole-brain sections were scanned for
calculating TUNEL density to quantitate DSBs. A rapid increase in DSBs was
observed in a 35–40-week window in
Il33 brains (Figure 4c). The DSBs continued to increase with age
thereafter, but at a slower rate. In contrast, only a few TUNEL+
cells were sporadically present in WT mice even after 60 weeks.
Figure 4
Il33 mice fail to initiate the
repair of rapidly increasing DNA double-strand breaks (DSBs) in the cortical and
hippocampal neurons after 40 weeks. (a)
Terminal-deoxynucleotidyl-transferase dUTP nick-end labeling (TUNEL) reveals the
accumulation of DSBs (green) in neurons in the cortex and hippocampus (CA) of a
40-week Il33 mouse, in comparison
to a 40-week wild-type (WT) mouse. (b) Co-staining of TUNEL (green) with
tubulin β3 (red) for numbered boxes in a shows that neurons are
TUNEL+, but glial cells (arrowheads) are TUNEL negative.
(c) Time course of TUNEL density in brains reveals a rapid increase in
TUNEL+ neurons in
Il33 mice between 35 and 40
weeks. TUNEL+ density in each brain is quantitated as total
fluorescent intensity/brain section area. Liner progression was used for
comparison between WT and Il33
group, and four-parameter progression for construction of curves. (d)
Immunofluorescence demonstrates incorporated BrdU (red) in the nuclei of WT (left)
but not in Il33 (right) neurons in
cortex and hippocampus at 40 weeks (n=4). (e) Enlarged
numbered boxed areas in d showed nuclear BrdU (red) only in WT neuronal
nuclei. (f) Quantitation of BrdU incorporation in hippocampal dentate gyrus
(n=4 per age). Each dot represents BrdU incorporation in one
neuron (fluorescent intensity/nuclear area). (g) Immunofluorescence
reveals PγH2AX (red) in the cortex and hippocampus (CA) of WT mice, but not
in Il33 mice, at 40 weeks
(n=4). Note heavy loss of neurons/neurites in
Il33 mice as revealed by
co-staining for tubulin β3 (green). (h) Enlarged-numbered-boxed areas
in g show PγH2AX (red) only in WT neuronal nuclei (green). (i)
Summary of PγH2AX+ neuron density (%) in dentate
gyrus at various ages (n=3 per group). (j) Western blot on
cortical proteins shows reduced PγH2AX in
Il33 mice at 40 weeks.
(k) Distribution of PγH2AX+ cells in the mouse
brains at 40 weeks (n=3). Cell densities (%) are indicated
by color scale.
Oxidative stress may induce chronic neuronal death in AD.[10, 43, 44] It causes apurinic/apyrimidinic (AP) site DNA
lesion, leading to DSBs. However, AP lesion sites in
Il33 cortex at 40 weeks was
comparable to WT mice (Supplementary Figure 2c).
We next asked whether increased DSBs were due to a failure in DNA repair in
Il33mice. BrdU incorporation
is a measurement for DSB repairing. After injected with BrdU, young WT mice (up to
20 weeks) showed no BrdU incorporation in their brain. However, animals over 40
weeks showed numerous neurons with nuclear BrdU in the cortex and hippocampus
(Figures 4d–f), where TUNEL positive cells
were extensive in Il33mice. In
contrast, BrdU incorporation was not observed at any ages in
Il33mice, suggesting a
failure in DSB repairing in
Il33neurons (Figures 4d–f). When a DSB occurs, histone γH2AX will be
phosphorylated for recruiting repair machinery. Thus, phosphorylated γH2AX
(PγH2AX) is a marker for both DSBs and the initiation of
repair.[45] Similar to BrdU
incorporation distribution pattern, immunofluorescence detected PγHA2X in
the nuclei of 80% of neurons in the cortex and 60% in the
hippocampus of WT mice over 40 weeks (Figures
4g–i, Supplementary Figure 2d).
PγH2AX was limited to neuronal nuclei (Figure
4h). In contrast, Il33mice of any ages showed nearly no PγH2AX+ neurons (Figure 4g–i, Supplementary
Figure 2d). Western blot of cortical proteins also showed a
significantly lower level of PγH2AX in
Il33mice (Figure 4j). The distribution pattern of
PγH2AX+neurons in the brain was very similar to that for
BrdU in WT mice. The cortex and hippocampus of
Il33mice showed a
substantial reduction in PγH2AX+ neuron density. Nearly
90% of neurons in the WT dentate gyrus were PγH2AX+,
but close to zero in Il33mice
(Figure 4k). Co-incidental appearance of DSBs as
TUNEL+ in Il33mice with a rapid increase in DSB repairing in WT mice in the same cortex and
hippocampus region at or after 40 weeks reveals a surge of aging process in these
neurons, which accelerated DSB generation. A failure in repairing these DSBs after
the aging surge at 40 weeks had led to DBS accumulation in neurons as
TUNEL+ in Il33mice. Unrepaired DSBs are cytotoxic and have been implicated in neuronal death in
humanAD.[7, 8,
46, 47,
48]Abnormal autophagy has been implicated in vacuolar neurodegenerations in central
nervous system including AD.[2, 3, 49] Autophagy
deficiency has been linked to tau deposition and amyloid plaque.[50, 51] We studied
nature of neuronal vacuoles (Figure 2e). Electron
microscopy first showed accumulation of numerous vesicles or vacuoles in both
neural soma and neurites of Il33mice at 60 weeks with many of them double-membraned (Figure
5a, Supplementary Figure 2e). This
indicates an abnormal accumulation of autophagosomes. LC3 and ubiquitinated
proteins are often used as a measure for autophagy activities.[52] LC3, a critical protein for the formation of
autophagosomes, was reduced at 40 weeks prior to the onset of neuron loss in
Il33mice (Figures 5b and c). Decrease in autophagy was also evidenced by an
increase in ubiquitinated proteins in
Il33mice (Figures 5d and e). However, reduced autophagic activities
in Il33mice could not explain the
accumulation of autophagosomes in
Il33 neurons. Cortical cells
were fractionated into various organelles. A significantly lower quantity of
autolysosomal LC3 was found in
Il33mice (Figures 5f and g). This suggests a failure in fusion between
autophagosomes and lysosomes in
Il33 neurons, leading to
accumulation/aggregation of autophagosomes. Aggregated autophagosomes were
detectable by immunofluorescence on LC3 in the neurons of
Il33mice after 40 weeks
(Figure 5h). Thus,
Il33 neurons also failed to
complete autophagic digestion.
Figure 5
Il33 mice fail to complete
autophagic digestion in the neurons. (a) Electron microscopy reveals
autophagic vesicles or vacuoles (arrows) in
Il33 cortical neurons. Inset
shows a double-membraned autophagic vesicle. Vacuoles are also present in neurites
(arrowheads in right most panel). Three mice per group were observed with similar
results. (b) Western blots detect reduced LC3 in cortical proteins. Each
lane is for one individual. (c) Quantified IOD of LC3 I, LC3 II and
α-actin bands in cortical proteins at 40 weeks. Ratios between total LC3 vs
α-actin (left) and LC3 II vs LC3 I (right) are shown; n=5.
(d) Western blots reveal increased ubiquitinated proteins in the cortex
of Il33 mice. Each lane is for one
individual. (e) Quantified total IOD for ubiquitinated proteins and
α-actin. Ratios between IODs of ubiquitinated proteins and α-actin of
cortical proteins are shown for wild-type (WT) and
Il33 mice at 40 weeks
(n=5) or 60–70 weeks (n=5). (f)
Western blot reveals a lower level of LC3 in autolysosomal fraction (arrowheads)
in Il33 mice as compared to WT
mice. Note that LC3 levels in other fractions were comparable to WT mice. Two
representative sets of samples are shown for each group. Autolysosomes and
autophagosomes were isolated from the cortex. (g) Ratio of IODs between
autolysosomal and autophagosomal LC3 in WT and
Il33 mice at 40 weeks.
(h) Immunofluorescence shows LC3 aggregates (arrows in purple channel)
in Il33 neurons, which are
distinguishable from WT neurons by TUNEL+ (green) nuclei and
diminished tubulin β3 (red); n=3. IOD, integrated optical
density.
Discussion
Current models for AD are largely transgenic animals, which overexpress mutant humanamyloid precursor protein (APP), tau, or presenilin 1.[53, 54] Those models have shed
light on the role of aggregation of tau or amyloid β2 in interference with
essential cellular mechanisms. However, amyloid plaques and tau deposition in
late-onset AD are not associated with mutations. Thus, cause of late-onset AD remains
unclear. Mounting evidence suggests a critical role of abnormal neuronal aging in
late-onset AD.[2, 3,
4, 5]
Il33mice developed AD-like disease
at old age due to impaired repair of aged neurons. Furthermore, the disease in our
model resembles many pathological features of human late-onset AD. These shared
features include late-onset neurodegeneration, heavy neuron loss in the cerebral
cortex and hippocampus, tau abnormality and impaired cognition/memory at old age.
Tau deposition is one of the most important hallmarks for human late-onset AD. To our
knowledge, our model probably is the first one to show tau abnormality, which is
un-related to mutant tau genes. Although amyloid plaques were not present in
Il33mice, it is expected because
murine APP lacks cleavage sties and hydrophobic residues for generating amyloid
plaque.[54]Neuronal aging process is also a result of accumulation of damaged molecules e.g.
DSBs, reactive oxygen species and old organelles.[47] Failed repair of DNA damage in aged neurons has been
implicated in humanAD.[7, 8, 9] Our study revealed an
abrupt aging surge in cortical and hippocampal neurons at middle-age (40-week) in
mice. Failure in up-regulation of neuronal repair mechanisms to counter this aging
surge in Il33mice may have led to
chronic neuron death at old age. Therefore, neurodegeneration is initiated in
Il33 neurons probably just after
the aging surge. There are two significances for our discovery of the aging surge.
First, neurodegeneration in Il33mice
is due to uncontrolled aging surge. It can be considered an accelerated aging process
in neurons. This accelerated aging process causes slow and chronic neuron death,
which is well reflected by a long period of time between the aging surge at 40 weeks
and heavy neuron loss/behavioral changes after 60–80 weeks. In fact,
chronic neurodegeneration with a long asymptomatic period followed by a stage with
mild clinical symptoms is an important hallmark for humanAD.[1] Second, human late-onset AD is often diagnosed when massive
neuronal death has already occurred, and effective therapeutic intervention is
impossible.[1] Therefore, identification
of biomarker for early diagnosis is a medical priority. If a neuronal aging surge at
middle age (45–50 years) exists in humans, it will be then a promising time
point to search for biomarkers for early diagnosis of AD long before massive loss of
neurons. Our model will be a useful tool in exploring these biomarkers.From this study, we are able to propose a hypothesis for cause of late-onset AD. The
aging surge at middle age causes damages to neurons. Stressed neurons may signal
surrounding astrocytes, which, in turn, cleave nuclear IL33 to release cytokine IL33.
With ST2 as receptor, IL33 upregulates DSB repairing and autophagic digestion to
ensure ‘rejuvenation’ of the aged neurons. Thus, deficiency in IL33 or
its associated signal pathway impairs neuronal rejuvenation, leading to accumulation
of DSBs and incomplete autophagy, which are known to accelerate aging process in
neurons. Some studies also showed that defective autophagy is responsible for
accumulation of abnormal tau and amyloid.[50,
51] As neurons are non-proliferative,
rejuvenation of aged neurons is a prerequisite for a functional brain in
elderly.[41, 42, 43] Many studies have shown
that repair of DNA damages and autophagic disposal of cellular wastes, for example,
abnormal tau, are essential for neuronal rejuvenation.[6, 7, 8,
9, 10, 47] Failed repair of stressed neurons leads to
neurodegeneration in the cortex and hippocampus after middle-age and subsequent
AD-like dementia at old age. To test our hypothesis in future, we need to address
several questions. First, how does IL33 regulate repair mechanisms in aged neurons?
Although it still remains unclear, our study suggests that cytokine IL33 and its
receptor ST2 may be involved, because of presence of cytokine IL33 in normal brains
(Figure 1d) and expression of ST2 mRNA in the cortex
and hippocampus but not in other regions at middle age (unpublished data). Recent
studies also revealed roles of other cytokines in AD.[14] It will be interesting to examine cross-talk among these
cytokines. Second, whether the aging surge and IL33 also play roles in AD development
in transgenic mice with WT human genes? It is worthwhile to mention that transgenicmice with WT human APP or tau do not develop AD-like disease or amyloid
plaque/tau deposition.[53, 54, 55] It will be
very interesting to test whether IL33 deficiency in those transgenic mice will cause
AD-like disease as well as amyloid plaques/tau deposition. In conclusion, our
study revealed a critical role of IL33 in repair of stressed neurons especially in
the cortex and hippocampus after an abrupt aging surge. IL33 deficiency leads to
uncontrolled neuronal aging, which in turn causes tau abnormality, neurodegeneration
and AD-like disease at old age.
Authors: Randall J Bateman; Ling Y Munsell; John C Morris; Robert Swarm; Kevin E Yarasheski; David M Holtzman Journal: Nat Med Date: 2006-06-25 Impact factor: 53.440
Authors: L Mucke; E Masliah; G Q Yu; M Mallory; E M Rockenstein; G Tatsuno; K Hu; D Kholodenko; K Johnson-Wood; L McConlogue Journal: J Neurosci Date: 2000-06-01 Impact factor: 6.167
Authors: Donna M Wilcock; Matthew R Lewis; William E Van Nostrand; Judianne Davis; Mary Lou Previti; Nastaran Gharkholonarehe; Michael P Vitek; Carol A Colton Journal: J Neurosci Date: 2008-02-13 Impact factor: 6.167
Authors: Jessica C Garbern; Jason Williams; Amy C Kristl; Alyyah Malick; Inbal Rachmin; Benjamin Gaeta; Nafis Ahmed; Ana Vujic; Peter Libby; Richard T Lee Journal: J Mol Cell Cardiol Date: 2019-02-11 Impact factor: 5.000
Authors: Hashan S M Jayarathne; Lucas K Debarba; Jacob J Jaboro; Brett C Ginsburg; Richard A Miller; Marianna Sadagurski Journal: Aging Cell Date: 2022-06-15 Impact factor: 11.005
Authors: Katherine M Still; Samantha J Batista; Carleigh A O'Brien; Oyebola O Oyesola; Simon P Früh; Lauren M Webb; Igor Smirnov; Michael A Kovacs; Maureen N Cowan; Nikolas W Hayes; Jeremy A Thompson; Elia D Tait Wojno; Tajie H Harris Journal: PLoS Pathog Date: 2020-10-27 Impact factor: 6.823