1
Introduction
Microglia are the resident immunocompetent and phagocytic cells in the CNS that play
a critical role in normal functioning of the CNS. They respond to injury, damage and
pathogens by rapidly changing their phenotype and secretion of a plethora of soluble
factors. The microglia also play a key role in the communication of systemic infection
and inflammation to the brain resulting in behavioural changes, but this signalling
is not detrimental to the adult healthy brain and rather contributes to recovery and
maintenance of homeostasis (Dantzer and Kelley, 2007; Teeling and Perry, 2009). Microglia
can become activated or ‘primed’ in chronic neurodegenerative or inflammatory diseases,
and these primed cells, in contrast to the normal resident microglia, have a lower
threshold for activation and can become harmful upon further stimulation (Cunningham
et al., 2009; Perry et al., 2010). The normal ageing process can also induce microglia
priming (Chen et al., 2008; Frank et al., 2010; Godbout et al., 2005) but the mechanism
underlying these age-related changes in microglial cells are not understood. This
study aimed to investigate if the age-related changes in microglia phenotype show
regional differences and whether these are associated with functional changes or previously
described age-related changes in neuronal integrity.
Microglial cells are long lived, myeloid-derived cells that populate the CNS during
early development (Alliot et al., 1999; Ginhoux et al., 2010; Lawson et al., 1992).
It is estimated that the adult mouse brain contains approximately 3.5 million microglia
(Lawson et al., 1990; Long et al., 1998). Their morphology and density, however, is
region specific and can range from 5% up to 12% of total cells per region, with higher
densities found in the grey matter (Lawson et al., 1990). The distribution and phenotype
of microglia also differs between regions in the human brain but, in contrast to rodents,
the white matter contains significantly more microglia, about 13% of total glial cell
density, with grey matter showing a low microglial density (Mittelbronn et al., 2001).
To gain more insight into the cellular functions of microglia in the adult mouse brain,
De Haas et al. (2008) compared the cellular expression level of a number of functional
surface molecules in different brain regions and found distinct regional differences.
For example, the expression levels of CD11b and CD40 in the cerebral cortex were significantly
lower than the levels in the spinal cord. The different regional expression of some
immune molecules on microglia may reflect different aspects of microglial activation,
which is of interest in the context of the rostro-caudal gradient of reactivity to
injury and inflammatory stimuli in the CNS. Lesions to spinal cord promote more extensive
leucocyte recruitment and blood–brain barrier breakdown than comparable lesions to
cortex (Schnell et al., 1999a). The rostro-caudal gradient is also observed following
focal cytokine injections with more overt leucocyte recruitment in the caudal than
forebrain regions (Phillips and Lampson, 1999; Phillips et al., 1999; Schnell et al.,
1999b).
With age the distribution and number of microglia changes little, if at all (Deng
et al., 2006; Long et al., 1998; Ogura et al., 1994). In contrast, age-related changes
in phenotype and functional properties of microglial cells have been widely reported.
In the healthy adult brain, microglia display a down-regulated phenotype characterized
by low expression of functionally relevant molecules such as CD45, CD68 and MHC class
II (Aloisi, 2001; Perry et al., 2007) and a low phagocytic activity, but the expression
levels of these molecules increase after acute CNS injury or ageing (Conde and Streit,
2006; DiPatre and Gelman, 1997; Ogura et al., 1994; Perry et al., 1993; Rogers et
al., 1988; Streit, 1996). In the aged rat brain there is an increase in CD68 + cells
throughout the parenchyma in both grey and white matter and appearance of MHCII positive
aggregates of cells in and adjacent to white matter (Perry et al., 1993). Similar
changes have been observed in aged mice. These changes have been associated with an
increased sensitivity to systemic inflammatory challenge with increased cytokine production
and altered behavioural responses (Barrientos et al., 2006; Chen et al., 2008; Henry
et al., 2009; Wynne et al., 2010).
Many studies on age-related changes in microglia phenotype and function during ageing
have focused on single regions and have not addressed possible regional differences
within the CNS. Microglia activation is evident in the white matter of the cerebral
hemispheres of old rats (Ogura et al., 1994), old monkeys (Sheffield and Berman, 1998;
Sloane et al., 1999), and elderly humans (Simpson et al., 2007), and it has been reported
that the extent of microglial cell activation in white matter, as measured by increased
expression of MHCII and iNOS, is related to the degree of cognitive impairment (Sloane
et al., 1999). The aim of this study was to compare the phenotype and morphology of
microglia in various regions of young (4 months) and aged (21 months) mouse brain
using a range of functional surface markers and to assess their phenotype following
a systemic inflammatory challenge. We selected eight distinct regions of grey or white
matter distributed along a rostral-caudal neuraxis. The regions included in our study
were: striatum, corpus callosum, fimbria, dentate gyrus, substantia nigra, cerebellar
nuclei, molecular layer of the cerebellar cortex and the inferior cerebellar peduncle.
The striatum is a mixed white/grey matter region – we studied the most caudal segment
of the putamen, an area that is mostly grey matter. The corpus callosum and fimbria
are rostral white matter areas, while the dentate gyrus is a grey matter region from
the hippocampus. The substantia nigra is a grey matter area caudal to the hippocampus
with a particularly high microglial density (Lawson et al., 1990). Within the cerebellum
we analysed the white matter tracts of the inferior cerebellar peduncle, the deep
cerebellar nuclei, which represent a mixture of white and grey matter, and the molecular
layer, which is grey matter neuropil of the cerebellar cortex.
The functional markers used in this study were selected for their sensitivity to changes
in the activation state of microglia and their relevance to microglial function. CD11b
and CD11c are adhesion molecules that play a role in cell migration and phagocytosis,
CD68 is involved in phagocytosis and MHCII is important for antigen presentation (Kettenmann
et al., 2011). FcγRs bind IgG, and play a role in antigen presentation and uptake
of opsonised cell debris (Nimmerjahn and Ravetch, 2008). F4/80 contributes to peripheral
tolerance induction in T regulatory cells by myeloid cells (Lin et al., 2005), Dectin-1
is a non-TLR pattern recognition receptor expressed during alternative activation
of macrophages (Shah et al., 2008) and DEC-205 is a dendritic cell marker involved
in antigen presentation (Jiang et al., 1995). These markers are myeloid cellspecific
within the CNS and up-regulated upon cell activation (Buttini et al., 1996; Lunnon
et al., 2011; Ponomarev et al., 2005; Qin et al., 2004; Shah et al., 2008). In this
study we show that microglial age-related phenotypes vary regionally, with evidence
of a differential expression of myeloid antigens along the rostro-caudal neuraxis.
These phenotype differences correlate with age-related behavioural deficits dependent
on hippocampus and cerebellum integrity.
2
Materials and methods
2.1
Animals and procedures
Female C57BL/6 mice (Harlan, UK, bred in house) were used in all experiments. Mice
were housed in groups of 5–10 in plastic cages with sawdust bedding and standard chow
diet and water available ad libitum. The holding room temperature was kept between
19 and 23 °C with a 12:12 h light–dark cycle (light on at 0700 h). Young mice were
4 months old and aged mice were 20–21 months old (n = 10–15 per treatment group).
Changes in behaviour and microglial phenotype were assessed in the same cohort of
mice. All procedures were performed under the authority of a UK Home Office License
in accordance with the UK animals (Scientific Procedures) Act 1986, and after obtaining
local ethical approval by the University of Southampton.
2.2
LPS administration
Mice were injected intraperitoneally with saline or LPS at a dose of 100 μg/kg (L5886,
Salmonella abortus equi, Sigma, Poole, UK).
2.3
Burrowing
Burrowing behaviour was assessed as described previously (Teeling et al., 2007). Briefly,
plastic cylinders 20 cm long and 6.8 cm in diameter and fixed at a slight incline
were filled with 190 g of normal food diet pellets and placed in individual cages.
Burrowing activity was measured between 3 and 5 h after saline or LPS injection by
weighing the amount of displaced food pellets, after which the tube was refilled to
measure overnight burrowing activity. Baseline burrowing activity over 2 h or overnight
was determined for each mouse 24 h prior to the experiment to allow the expression
of data as percentage of baseline activity.
2.4
Multiple static rod test
Static rod test performance was assessed as previously described (Contet et al., 2001)
with minor adaptations. Three wooden rods of varying diameter (35, 22 and 9 mm) each
60 cm long were fixed on one end to a supporting platform and suspended 60 cm above
a bed of foam. A mouse was placed at the end of the rod facing towards the open end.
The time taken to orientate 180 degrees (“orientation”) and the time to travel to
the wooden platform (“transit time”) were then noted. If the mouse failed to reach
the wooden platform, it was assigned a score of “fail”. The multiple static rod test
was performed between 1 and 2 h after saline or LPS injection. A baseline measurement
was taken 24 h prior to the experiment. Prior to baseline mice were habituated to
all three rods. All mice successfully traversed the two larger rods, therefore only
data from the smallest rod is presented.
2.5
Rod climbing assay
An L-shaped metal rod of 2 mm diameter and 28 cm length was suspended from a wire
mesh screen 0.5 m above a bed of foam. The mouse was placed at the bottom of the rod
and allowed to climb for 60 s to reach the wire mesh screen. Mice were scored as follows:
fell within 10 s (=1), 25 s (=2) or 59 s (=3), remained on the rod for > 60 s (=4),
or reached the inverted screen within 60 s (=5), 25 s (=6), or 10 s (=7).
2.6
Tissue processing and immunohistochemistry
24 h after LPS or saline injection mice received a terminal dose of pentobarbital
and, following transcardiac perfusion with heparinised saline, brain and spleen tissue
were immediately removed, embedded and frozen in optimal cutting temperature (OCT)
medium (Sakura Finetek, Thatcham, UK). 10 μm sections were cut on a cryostat in the
coronal plane at −0.9, −3.0 or −6.0 mm ± 0.3 mm from bregma, air dried and frozen
at −20 °C until required.
For immunohistochemical analysis, sections were dried at 37 °C and fixed for 10 min
in 100% ethanol at 4 °C. Sections were then quenched with 3% hydrogen peroxide (Sigma,
Poole, UK) in phosphate buffered saline (PBS) and blocked with appropriate 10% animal
serum (Vector Laboratories, Peterborough, UK) and 1% bovine serum albumin (Fisher
Scientific, Loughborough, UK). Primary antibodies were incubated overnight at 4 °C,
for details see Table 1. Biotinylated secondary antibodies, either rabbit-anti-rat
IgG or goat-anti-hamster IgG (Vector Laboratories, Peterborough, UK), were added for
45 min, followed by exposure to avidin biotin complexes (Vector Laboratories, Peterborough,
UK) and DAB (3,3′-Diaminobenzidine) (Sigma, Poole, UK). Sections were counterstained
with Harris haematoxylin (Sigma, Poole, UK). If prepared for immunofluorescence sections
were incubated with a donkey-anti-rat or goat-anti-rabbit IgG secondary antibody conjugated
with a 488 or 568 nm fluorophore (Invitrogen, Paisley, UK) or with biotinylated secondary
antibodies followed by 488 or 568 nm fluorophore conjugated streptavidin (Invitrogen,
Paisley, UK). Specificity of primary antibodies was confirmed using spleen as a positive
control and omission of the primary antibody as a negative control. The specificity
of FcγRI staining was confirmed using brain tissue from ME7 infected Fc gamma chain
deficient mice.
2.7
Quantification of immunohistochemistry
Images were analysed and quantified using ImageJ. The DAB and haematoxylin channels
were isolated using a plugin and a threshold was determined for quantification. Thresholds
were determined for each experiment to control for variation in DAB staining intensity
between experiments. Background or excessively dark haematoxylin staining was removed
using the “despeckle” setting and, when required, by superimposing a mask of the haematoxylin
channel onto the image. The region of interest was traced by “freehand” from the image
and the average pixel density within the selected area was calculated. For each animal
(n = 4–5 per treatment group), two images per region of interest were captured at
×20 magnification for quantification, using a brain atlas to identify matching regions
of interest in each hemisphere. The average pixel density above threshold of the two
images was calculated and data expressed as fold increase over 4 month old, saline
treated expression levels in the same region. FcγRI expression in the striatum was
excluded from analysis due to non-specific nuclear binding in this particular region.
2.8
Quantitative PCR
Brain tissue was rapidly removed following perfusion and dissected to separate the
cerebellum from a coronal section of hippocampus, thalamus and cortex (bregma -1.5 mm
to -3.5 mm). The coronal section was divided into two hemispheres, snap frozen in
liquid nitrogen and stored at -80 °C. Total RNA was extracted from brain tissue using
RNeasy mini kits (Qiagen, Crawley, UK) and treated with DNAse I to remove any contaminating
gDNA (Qiagen). cDNA was synthesised using reverse transcription reagents from Applied
Biosystems (Warrington, UK). SYBR green super mix (BioRad, Hemel Hempstead, UK) was
used to detect amplification of primer products. IL-1β primers were purchased from
Invitrogen and iNOS, GAPDH and IL-6 primers were purchased from Sigma, Poole, UK.
Primer sequences are as previously described (Palin et al., 2008; Sato et al., 2003).
Samples were quantified against a standard curve using mouse hippocampus tissue infected
with ME7, injected intraperitoneally with LPS and collected 6 h after injection as
a positive control. The amount of mRNA was then estimated as the ratio of GAPDH. n = 3–4
per treatment group.
2.9
Statistical analysis
Data sets were tested for a normal distribution using the D’agostino-Pearson omnibus
test. All tests were performed in either Sigmaplot 11.0 or GraphPad Prism 5.0. Overnight
burrowing data was normally distributed and was analysed using two way ANOVAs with
Holm-Sidak post tests. Two hour burrowing data was not normally distributed and was
therefore analysed using Mann–Whitney tests on saline and LPS groups. Pass/fail data
from the multiple static rod tests was analysed using a Chi squared test. Transit
time data was analysed using a Mann–Whitney test. Quantification of the immunohistochemical
analysis was performed by expressing data as fold increase from the mean of the 4 month
old saline values from the same brain region, logarithmically transformed and analysed
using a three way ANOVA with Holm-Sidak post tests. Quantitative PCR data was logarithmically
transformed and analysed by two way ANOVA and Holm-Sidak post tests.
3
Results
3.1
Microglial morphology changes with age
Many, but not all, microglia exhibited a change in morphology in the aged brain (Figs.
1 and 2), including a thickening and de-ramification of processes and hypertrophy
of the cell body (Fig. 1C and G). Morphological changes were observed in all regions
studied, and microglia broadly retained the pattern that has previously been reported
in grey versus white matter (Lawson et al., 1990), with longitudinal processes that
run parallel to the axonal tracts in the white matter and radially branched microglia
in the grey matter. Aged mice exhibited cell aggregates of approximately 20–30 μm
in diameter, containing multiple nuclei and fewer, shorter, highly thickened processes
(Fig. 1G, H, P). Some aggregates contained as many as 6 or 7 nuclei. These aggregates
were predominantly found in the white matter, particularly in the cerebellum (Fig.
1G, H, P). Our results further show that systemic LPS challenge did not appear to
change the morphology of the microglia or the number of multinucleate aggregates observed
in aged mice (Fig. 1).
3.2
Microglial phenotype changes with age
In addition to morphological changes we noted distinct phenotypic changes in the aged
brain, including increased expression of CD11b (Fig. 1A–H), CD68 (Fig. 1I–P), CD11c
(Fig. 2D and G), FcγRI (Fig. 2E and H) and F4/80 (Fig. 2F and I). The phenotype changes
were more pronounced in the cerebellum compared to the hippocampus. Increased levels
of CD68 were found on microglia in the white matter regions of the cerebellum of aged
brain, while in the young brain immunoreactivity for this marker was predominantly
associated with perivascular macrophages (Fig. 1M and O). Double immunofluorescence
showed that cell aggregates in the aged brain are microglia as CD11b positive aggregates
were not associated with blood vessels and mainly found in the parenchyma, and are
therefore not components of the perivascular macrophage population (Fig. 2A and B).
Some aggregates extended processes that made contact with vasculature, but most did
not. We also show that these aggregates were not groups of proliferating cells by
double staining for CD11c and Ki67 (Fig. 2C). Expression of CD11c, FcγRI and F4/80
was very weak or not detectable in the 4 month old brain (Fig. 2G–I), but all three
markers were robustly expressed in aged cerebellar white matter (Fig. 2D–F). In summary,
age dependent changes in morphology and phenotype appear to arise in a region dependent
manner, with a specific white matter phenotype present in the aged brain, in particular
in the cerebellum.
3.3
Quantification of microglial phenotype changes with age: CD11b, CD68 and F4/80
We quantified the expression levels of functional markers in the different regions
studied. In the ageing brain an increased expression of CD11b, CD68 and F4/80 (Fig.
3, n = 5 per group): for all three markers there was a strong effect of age on expression
level (CD11b: F
(1,111) = 38.35, p < 0.001; CD68: F
(1,108) = 271.36, p < 0.001; F4/80: F
(1,109) = 75.86, p < 0.001). None of these markers were significantly affected by
systemic LPS 24 h after injection. Region had a strong effect on expression of all
three markers, (CD11b: F
(7,111) = 2.45, p = 0.022; CD68: F
(7,108) = 7.90, p < 0.001; F4/80: F
(7,109) = 4.64, p < 0.001). We detected an interaction between age and region for
expression of all three markers (CD11b: F
(7,111) = 2.12, p = 0.047; CD68: F
(7,108) = 7.789, p < 0.001; F4/80: F
(7,109) = 4.64, p < 0.001), suggesting that microglial activation is differentially
affected by age in different brain regions. The increases in expression of CD11b,
CD68 and F4/80 were greatest in the cerebellum and in particular in the cerebellar
inferior peduncles. Microglial expression of all three markers in the fimbria and
for CD11b and CD68 the corpus callosum was also strongly increased in aged animals
(Fig. 3A and B). Changes in the expression of these molecules in the white matter
were greater than those in the grey matter. The dentate gyrus did not exhibit any
changes in expression with ageing for any of these three markers.
3.4
Quantification of microglial phenotype changes with age: CD11c and FcγRI
The expression levels of CD11c (Fig. 4A) and FcγRI (Fig. 4B) were also quantified
and expression of both was significantly increased by age (CD11c: F
(1,128) = 63.08, p < 0.001; FcγRI: F
(1,92) = 61.37, p < 0.001), region (CD11c: F(7,128) = 15.76, p < 0.001; FcγRI: F
(6,92) = 4.84, p < 0.001) and, for FcγRI, LPS injection (F
(1,92) = 5.97, p < 0.05). An interaction between age and region was detected for CD11c
expression (F
(7,128) = 11.72, p < 0.001), but not FcγRI. Strikingly, CD11c expression was up-regulated
exclusively in white matter regions during ageing. All four white matter regions examined
demonstrated a significant increase in CD11c expression with age (Fig. 4A) and the
most caudal area of white matter studied, the inferior cerebellar peduncle, exhibited
the greatest increase in expression, but CD11c expression was not further influenced
by systemic LPS. Although expression of FcγRI was increased in all regions of the
ageing brain, changes in FcγRI expression were more pronounced in white matter areas
and the cerebellum than in the hippocampus of 21 month old mice (Fig. 4B). FcγRI expression
after LPS injection was also highest in the three cerebellar regions investigated.
Changes in other molecules expressed by microglia during ageing and after systemic
LPS injection were investigated in a qualitative manner using immunohistochemistry
(data not shown). A small number of Dectin-1 positive cells were detected in the white
matter tracts of aged animals (3–4 cells per ×20 field of cerebellum), but not in
aged grey matter or young white matter. The expression levels of Dectin-1 were not
influenced by systemic LPS. DEC-205 positive cells were not observed in either the
young or aged brain. We also investigated FcγRII/III and MHCII expression levels and
the majority of positive cells were associated with blood vessels. We could not detect
any noticeable changes in the expression of these two molecules on microglia dependent
on age or LPS. In summary, age related changes in expression of microglia associated
molecules varied greatly between different brain regions, with the cerebellum and
the white matter showing the most pronounced changes, while the effect of systemic
LPS on microglia associated molecule expression was limited to FcγRI.
3.5
Aged animals show an exaggerated decline in burrowing in response to systemic LPS
To investigate whether the age related, region specific changes in microglial phenotype
were associated with compromised CNS function, we performed behavioural assays dependent
on two of the regions analysed for phenotype changes – the hippocampus and the cerebellum.
We used burrowing as a measure of hippocampus dependent sickness behaviours (Deacon
et al., 2002). A small decline in burrowing activity was seen at baseline with age,
which may be attributable to changes in baseline locomotor activity (Supplementary
Fig. 1). Between 3 and 5 h after a systemic LPS injection all mice showed a decline
in burrowing, with a greater decline in activity in aged mice compared to young mice
(Fig. 5A) (LPS group: p < 0.001, n = 14–15). Most 21 month old mice failed to show
any burrowing activity (median = 0%), whereas the majority of 4 month old mice retained
a degree of burrowing activity (median = 12.1%). There was no age-related effect of
saline injection on burrowing (p = 0.233, n = 10–15). At 24 h after injection the
LPS-challenged mice had partially recovered their burrowing activity (Fig. 5B), but
this recovery was significantly less in the 21 month old mice compared to the 4 month
old mice (4 vs 21 month group p < 0.001. n = 14–15). Age and LPS both had a significant
effect on overnight burrowing (Age: F1,
50 = 13.34, p < 0.001. LPS: F1,
50 = 28.21, p < 0.0001). In addition, an interaction between the two factors was detectable
(F1,
50 = 5.053, p = 0.029). To conclude, a systemic challenge of LPS led to an exacerbated
and decrease in burrowing activity in 21 month old mice when compared to 4 month old
mice.
3.6
Static rod performance declines with age, but is not modulated by systemic LPS
Next, we investigated a cerebellum dependent behaviour, the multiple static rod test,
which assesses the co-ordination and balance of mice on different diameter static
rods (Carter et al., 1999; Contet et al., 2001). Mice were placed on a suspended 9 mm
diameter static rod and the transit time to reach a platform after orientation was
assessed in saline and LPS-treated mice (Fig. 5C and D). Chi squared analysis of baseline
static rod performance showed a significant difference between young (7%, n = 30)
and aged (68%, n = 25) mice in pass/fail ratios on the 9 mm static rod (х2 = 22.69,
d.f. = 1, p < 0.0001) (Fig. 5C). Analysis of baseline transit times also showed a
significant difference between young and aged mice (Mann Whitney test, p < 0.0001,
n = 25–30 per group) (Fig. 5D). Injection of LPS or saline did not have a significant
effect on pass/fail rates at any age and there were not sufficient successful completions
of the test in the 21 month old mice to test for differences in transit times after
injection. We also tested muscle strength using the climbing rod test to investigate
whether changes in muscle strength correlated with poorer static rod performance.
There was a decline in climbing rod performance with age (p < 0.0001, Mann Whitney
test; supplementary data Fig. 2A), but we found no difference in climbing rod performance
between 21 month old mice that passed or failed the static rod test (supplementary
data Fig. 2B). There was also no correlation between climbing rod test performance
and static rod transit time in 4 month old mice (Supplementary data Fig. 2C).
Finally we investigated the effect of LPS injection on the expression of inflammatory
mediators in the different CNS regions of aged and young mice using quantitative real
time PCR. However, we could not detect any significant increase of IL-6, IL-1β or
iNOS mRNA expression 24 h after LPS injection in young or aged cerebellum or hippocampus
(data not shown).
4
Discussion
In this study we have investigated the phenotype and morphological changes of microglia
in eight distinct regions of the young and aged mouse brain. We show that age-related
phenotype changes of microglial cells are more pronounced in the white matter, with
the cerebellum, the most caudal structure studied, showing the greatest differences.
Variations in microglial density have been well described in adult mouse brain with
the hippocampus and substantia nigra exhibiting the highest and the cerebellar cortex
the lowest density of microglia (Lawson et al., 1990). A number of studies in several
areas of the CNS indicate that there is little, if any, change in the distribution
or numbers of microglia with age (Deng et al., 2006; Long et al., 1998; Ogura et al.,
1994; Peters et al., 2010), but less is known about phenotype changes in different
regions of the aged mouse brain. Our results are in accord with a recent study describing
regional variation in expression levels of immunoregulatory molecules in the healthy
adult mouse brain. De Haas et al. showed that regional differences between microglial
phenotypes in the adult mouse brain are subtle: expression levels of surface markers
such as CD11b, CD40 and the fractalkine receptor CX3CR1 appeared higher in the microglia
of the spinal cord and cerebellum than the hippocampus (De Haas et al., 2008). In
our study all functional markers tested displayed the greatest increase in expression
with age in white matter regions, particularly in the cerebellum, identifying a clear
trend in phenotype changes along the rostro-caudal axis in the aged mouse brain.
4.1
Microglial phenotype changes in response to injury along the rostro-caudal axis
Phenotype changes in microglia are well described in response to acute and chronic
injury or disease, but only a few studies have looked at differential responsiveness
to the grey matter versus the white matter along the rostro-caudal neuraxis. Trauma-induced
lesions lead to a greater microglial response in the spinal cord than the cortex or
corpus callosum and the spinal white matter exhibited a greater microgliosis than
spinal grey matter (Batchelor et al., 2008; Schnell et al., 1999a). Regional differences
in responsiveness to inflammatory stimuli are partly responsible for these observations,
as stereotaxic injections of recombinant cytokines into the striatum fail to evoke
a robust response, while similar injections into the spinal cord or brainstem are
associated with BBB breakdown, microgliosis and secondary tissue damage (Campbell
et al., 2002; Phillips and Lampson, 1999; Phillips et al., 1999; Schnell et al., 1999b).
This regional difference in responsiveness to inflammatory stimuli is also evident
in EAE, which targets the spinal cord rather than more rostral regions of the brain,
such as the forebrain (Sun et al., 2004). Collectively, these studies suggest that
the caudal and white matter regions of the CNS are more responsive and therefore more
vulnerable to inflammatory stimuli. Our study suggests that the differential sensitivity
of these microglial populations also applies to the ageing process. We show that in
the aged brain there is a greater up-regulation of CD11b, CD11c, CD68, F4/80 and FcγRI
in white matter than in grey matter and more in caudal areas than rostral areas. These
data are in agreement with previous studies in the aged rat brain suggesting a rostral
caudal gradient of microglial activation (Kullberg et al., 2001).
4.2
Pronounced white matter related changes
It has been previously reported that the microglia of the white matter express greater
levels of microglia associated molecules with age than those of the grey matter (Kullberg
et al., 2001; Perry et al., 1993), and that the microglia may appear in “clumps” of
immunoreactive membranes in white matter (Perry et al., 1993; Stichel and Luebbert,
2007). Our study shows that these aggregates are not directly associated with blood
vessels and are not clusters of proliferating cells. Macrophages and microglia are
known to form multinucleate giant cells through fusion under a variety of inflammatory
conditions (Fendrick et al., 2007; Gasser and Most, 1999; Suzumura et al., 1999).
Whether these cells are aggregates of individual microglia or a single syncytium is
not clear from our study, but the appearance of multinucleate giant cells during ageing
would represent a significant alteration in microglial phenotype and function.
4.3
Pronounced changes in CD11c expression
We observed a significant increase in CD11c expression levels, predominantly in the
white matter of the cerebellum. CD11c is a protein found at high levels on dendritic
cells, but is also found on macrophages and microglia under neuroinflammatory conditions
(Reichmann et al., 2002; Remington et al., 2007). Increases in CD11c immunoreactivity
with age have been reported previously with robust CD11c expression in the aged white
matter and occasional CD11c expression throughout the grey matter (Kaunzner et al.,
2010; Stichel and Luebbert, 2007). These studies describe CD11c positive cells as
dendritic cells, as they express DEC-205, MIDC8, MHCII and the co-stimulatory molecules
CD80 and CD86. Using immunohistochemistry we did not detect DEC-205 or MHCII expression
in the aged brain. This discrepancy may be explained by the superior sensitivity of
alternative methods of detection, such as flow cytometry, or by the strain of mice
used (Henry et al., 2009). The functional consequence and mechanism underlying increased
expression of CD11c in the aged brain is unknown, but increased turnover of myelin
with age may be a contributing factor (Ando et al., 2003). It has been shown that
engagement of low density lipoprotein receptor 1 (LRP-1) on macrophages results in
increased expression of CD11c (Cho et al., 2007; Gower et al., 2011). Ligands for
LRP-1 include low density lipoprotein (Kuchenhoff et al., 1997) and the myelin component
MBP-1 (Gaultier et al., 2009). Whether the CD11c + cells in our study are microglia
that have taken up myelin components/breakdown products, or infiltrating dendritic
cells or macrophages remains to be determined.
4.4
Neurodegeneration in the ageing brain
It is well recognised that the microglia are exquisitely sensitive to neurodegeneration.
However, in rodents and primates the extent to which neurodegeneration occurs in the
ageing CNS varies considerably from region to region. The substantia nigra (Ma et
al., 1999; Mouton et al., 2010) and cerebellum (Sturrock, 1989; Woodruff-Pak et al.,
2010) exhibit significantly greater age-related neuronal loss than the hippocampus
(Calhoun et al., 1998; Rapp and Gallagher, 1996) or striatum (Pesce and Reale, 1987),
and substantial loss of myelinated axons has been reported in white matter regions
(Bowley et al., 2010; Cavallotti et al., 2001; Sandell and Peters, 2002, 2003). The
areas with greatest neuronal loss are also the regions that exhibit greater changes
in microglial phenotype.
Whether neuronal loss drives microglial phenotype changes in ageing, or if changes
to the microglia precede and contribute towards neuronal loss, is not known. There
are however several mechanisms by which neurons and oligodendrocytes keep microglia
in a quiescent state, such as interactions between CD200, fractalkine or CD47 and
their cognate receptors on microglia (Gitik et al., 2011; Hoek et al., 2000; Kong
et al., 2007; Koning et al., 2009; Lyons et al., 2009). Two studies in the healthy
adult mouse brain have revealed significant regional variations in the distribution
of these molecules. Koning et al. (2009) observed that CD200 expression is greater
in grey than white matter, which may contribute to the regional differences in microglial
phenotype we report in this study. Fractalkine transcript expression has been reported
to be significantly lower in the cerebellum and other caudal areas such as the brainstem
than the hippocampus or striatum, which may help to explain the rostral caudal gradient
of microglial phenotype changes (Tarozzo et al., 2003). Decreased expression of CD200
in the hippocampus and substantia nigra (Frank et al., 2006; Wang et al., 2011), and
of fractalkine in the hippocampus and forebrain have been demonstrated in aged mice
(Lyons et al., 2009; Wynne et al., 2010). Increased numbers of multinuclear giant
cells have also been observed in CD200-/- mice (Hoek et al., 2000), providing a possible
explanation for their presence in the aged brains of our study. A wider assessment
of the expression of these immunoregulatory molecules in different regions of the
aged brain and how they may correlate with changes in microglial phenotype would be
of interest.
4.5
Impact of systemic inflammation on aged-related microglia phenotype
We anticipated an increase in expression levels of microglia associated molecules
after systemic LPS injection, which has previously been shown to up-regulate FcγRI
(Lunnon et al., 2011) and CD11b (Buttini et al., 1996). However, the only molecule
we found to be sensitive to systemic LPS injection was FcγRI. CD11b expression was
not significantly altered 24 h after systemic LPS challenge. Furthermore, the effect
of systemic LPS on FcγRI expression was subtle, region dependent and primarily observed
in the white matter regions and the cerebellum of both young and aged mice. A later
time point post injection, such as three days, may yield a more robust effect on expression
of these molecules (Buttini et al., 1996).
4.6
Age-related functional deficits
Since we had shown that the molecular expression patterns of the microglia in distinct
CNS regions were altered with age we used behavioural assays to assess the functional
integrity of two regions, the hippocampus and the cerebellum. We demonstrate a significant
age-related deficit in static rod test performance and verified that this was not
dependent on loss of muscle strength. There is a progressive loss of Purkinje neurons
with age (Woodruff-Pak et al., 2010) and Purkinje neuron specific degeneration has
previously been shown to compromise the performance of mice in tasks assessing co-ordination
and balance (Chen et al., 1996; Kyuhou et al., 2006). A correlation of conditioned
eye blink response with Purkinje neuron numbers has also been previously shown, suggesting
that Purkinje cell loss may be the critical component of age-related cerebellar dysfunction
(Woodruff-Pak, 2006). LPS injection did not exacerbate deficits in performance in
this task at any age, suggesting the cerebellar circuitry controlling static rod performance
is not sensitive to systemic LPS.
Burrowing is a hippocampus dependent (Deacon et al., 2002), species typical behaviour
that is sensitive to systemic inflammatory challenge (Teeling et al., 2007). We demonstrated
that aged mice exhibit an exaggerated response and a delayed recovery from systemic
LPS challenge. Exaggerated sickness behaviour in aged animals in response to systemic
inflammatory challenge has been previously reported (Barrientos et al., 2006; Godbout
et al., 2005, 2008; McLinden et al., 2011), but this is the first study to use burrowing
in response to systemic LPS treatment in an ageing context. Elevated levels of cytokines
within the aged hippocampus have been demonstrated following systemic inflammatory
challenge (Barrientos et al., 2009; Chen et al., 2008; Godbout et al., 2005), which
are likely produced by primed microglia in the aging brain (Frank et al., 2010; Wynne
et al., 2010). We were not able to demonstrate the presence of inflammatory cytokines
or iNOS 24 h after systemic LPS injection in any brain region studied. We had anticipated
that elevation of these molecules would be prolonged in aged animals in line with
other studies (Godbout et al., 2005; Wynne et al., 2010). This discrepancy may be
due to our use of a lower dose of LPS (100 μg/kg vs 330 μg/kg) and a different sex
and strain of mouse (male BALB/c vs female C57/BL6). Our data does not however exclude
the possibility of an exaggerated local inflammatory at an earlier time-point following
systemic LPS injection.
5
Summary
In this study we have demonstrated significant differences in microglial phenotypes
between distinct regions of the aged brain. The microglia of the white matter show
more robust changes than those of grey matter and there is evidence of a rostro-caudal
gradient in the magnitude of these changes. The age-related changes in microglia phenotype
reported here may be of particular interest when comparing studies in rodent and human
material. In humans white matter makes up ∼40% of the adult human brain (Gur et al.,
1999) compared to 10% in the mouse (Zhang and Sejnowski, 2000), and human white matter
contains a greater density of microglia than grey matter (Mittelbronn et al., 2001),
conversely to the mouse (Lawson et al., 1990). The functional significance of these
grey/white matter differences in microglial phenotype during ageing remain to be elucidated.
Conflict of interest statement
All authors declare that there are no conflicts of interest.