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Increased microglial catalase activity in multiple sclerosis grey matter

Brain Research


Chronic demyelination, on-going inflammation, axonal loss and grey matter neuronal injury are likely pathological processes that contribute to disease progression in multiple sclerosis (MS). Although the precise contribution of each process and their aetiological substrates is not fully known, recent evidence has implicated oxidative damage as a major cause of tissue injury in MS. The degree of tissue injury caused by oxidative molecules, such as reactive oxygen species (ROS), is balanced by endogenous anti-oxidant enzymes which detoxify ROS. Understanding endogenous mechanisms which protect the brain against oxidative injury in MS is important, since enhancing anti-oxidant responses is a major therapeutic strategy for preventing irreversible tissue injury in the disease. Our aims were to determine expression and activity levels of the hydrogen peroxide-reducing enzyme catalase in MS grey matter (GM). In MS GM, a catalase enzyme activity was elevated compared to control GM. We measured catalase protein expression by immune dot-blotting and catalase mRNA by a real-time polymerase chain reaction (RT-PCR). Protein analysis studies showed a strong positive correlation between catalase and microglial marker IBA-1 in MS GM. In addition, calibration of catalase mRNA level with reference to the microglial-specific transcript AIF-1 revealed an increase in this transcript in MS. This was reflected by the extent of HLA-DR immunolabeling in MS GM which was significantly elevated compared to control GM. Collectively, these observations provide evidence that microglial catalase activity is elevated in MS grey matter and may be an important endogenous anti-oxidant defence mechanism in MS.



  • Levels of catalase activity are increased in MS grey matter.
  • Catalase protein levels correlate with microglial markers.
  • Catalase gene transcription is increased relative to microglial gene transcription.
  • Microglial numbers are increased in MS grey matter.

Keywords: Multiple sclerosis, Anti-oxidant, Microglia, Catalase.

1. Introduction

Multiple sclerosis (MS) is an inflammatory disease of the central nervous system characterised by significant levels of oxidative stress. Although classically described as a white matter (WM) disease, in recent years the importance of grey matter (GM) injury in MS has been emphasised as a likely substrate for some of the more ‘cortical’ features of MS, such as cognitive dysfunction ( Calabrese et al., 2009 ). Cortical atrophy on MRI scans is a well-recognised feature of established progressive disease. Pathological studies of MS GM have revealed evidence for demyelination, inflammation and neuronal loss (Kutzelnigg et al, 2005 and Lucchinetti et al, 2011). The precise relationship between inflammation and GM neuronal loss is not clear, although studies have revealed higher levels of neuronal injury in areas of GM with greater lesion activity characterised by inflammatory cell infiltrates ( Mahad et al., 2008 ).

A major mechanism by which inflammatory cells produce tissue injury is through oxidative stress pathways. Oxidative molecules such as nitric oxide, superoxide, hydrogen peroxide and peroxynitrite are released from inflammatory cells as part of their physiological function to protect against invading pathogens. However, reactive oxygen species (ROS) may also cause damage to endogenous DNA, RNA and cellular proteins and, if present in high enough concentrations, can cause cell death ( Haider et al., 2011 ). Experimentally, ROS cause cellular injury to neurons (and their axons) and oligodendrocytes (Li et al, 2005 and Wilkins and Compston, 2005). In MS, there is now almost overwhelming evidence implicating activation and generation of ROS as a major cause of tissue injury (Cross et al, 1998, Smith et al, 1999, and van Horssen et al, 2011). Oxidative stress is kept in check by a number of endogenous anti-oxidant enzymes and it is likely that the balance of oxidative stress and anti-oxidant response mechanisms may be crucial in determining the degree of tissue injury. Of particular interest is catalase, which catalyses the detoxification of hydrogen peroxide (itself formed as a by-product of superoxide dismutase activity on superoxide ions).

Endogenous anti-oxidant molecules are expressed widely and there is a complex interplay between oxidative injury and endogenous anti-oxidant defence mechanisms which determines the degree of cellular injury induced by ROS. In MS, oxidative damage coincides with enhanced anti-oxidant enzyme expression, but the precise pattern and cellular origin of anti-oxidant enzyme expression are not completely clear ( van Horssen et al., 2008 ). In this study we focused on determining activity and expression pattern of the major hydrogen peroxide reducing enzyme catalase within MS grey matter. Understanding endogenous anti-oxidant molecule expression may lead to enhanced therapeutic strategies for the disease.

2. Results

2.1. Catalase activity is significantly increased in MS grey matter

As an assessment of anti-oxidant capacity, we measured activity of the peroxisomal enzyme catalase. Catalase activity was measured in homogenates prepared from MS (n=25) and control (n=14) grey matter. Post-mortem delay was significantly greater in the control (mean=21.05 h, SE=1.957, median=22) than the MS group (mean=16.59 h, SE=0.5816, median=16;P<0.05). However, within two groups (MS and control GM) there was no significant relationship between catalase activity and post-mortem delay (P=0.25). Regression analysis of the contributions to catalase activity of the presence/absence of MS indicated a strong positive association between MS and levels of catalase (P<0.0001; Fig. 1 ). Analysis of samples based on the presence or absence of demyelination within tissue blocks (determined by MBP labelling) revealed no difference in catalase activity dependent on the presence of demyelination (demyelinated block: mean catalase activity 12.92 nmol/min/mg total protein ±0.75 SEM; non-demyelinated block: mean catalase activity 12.63 nmol/min/mg total protein ±0.91 SEM;P=0.34)


Fig. 1 Catalase activity in multiple sclerosis (MS) grey matter and control grey matter. The mean values±SE are shown for samples from 25 cases of multiple sclerosis grey matter and 14 controls. Catalase activity is significantly increased in multiple sclerosis grey matter (P<0.0001).

2.2. Catalase protein levels positively correlate with IBA-1 protein levels in MS grey matter

Levels of catalase protein were evaluated in grey matter via immune-dot blotting. Protein levels of glyceraldehyde 3-phosphate dehydrogenase (GAPDH, as a pan-cellular protein), neuron specific enolase (NSE, as a neuronally expressed protein) and an ionised calcium-binding adapter molecule-1 (IBA1, which is expressed in activated microglia) were also measured. Levels of catalase, NSE and IBA-1 were expressed relative to GAPDH expression levels from the tissue sample to account for any cell loss. We analysed the data to determine if there was a correlation between the neuron-specific marker (NSE) and the catalase expression or between the microglia-specific marker (IBA-1) and the catalase expression. No correlation existed between NSE (controlled to GAPDH expression) protein levels and catalase (controlled to GAPDH expression) protein levels ( Fig. 2 A). However, there was a strong positive correlation between IBA-1 (controlled to GAPDH expression) protein levels and catalase (controlled to GAPDH expression) protein levels in homogenates examined ( Fig. 2 B).


Fig. 2 Catalase protein expression levels in multiple sclerosis (MS) grey matter and control grey matter. Catalase protein expression was measured by dot-blotting on samples from 25 cases of MS grey matter and 13 controls. In addition protein expression of GAPDH, NSE and IBA-1 protein was measured by dot-blotting. Catalase, NSE and IBA-1 protein levels within the tissue were expressed relative to GAPDH expression levels. There was no significant correlation between catalase/GAPDH vs. NSE/GAPDH (A), whereas there was a significant positive correlation between catalase/GAPDH vs. IBA-1/GAPDH (E,p=0.001).

2.3. Catalase gene expression is increased in MS grey matter relative to AIF-1 expression

We analysed catalase gene expression relative to the expression of a number of genes. In order to determine whether there were cell-type specific gene transcription changes we expressed catalase RT-PCR values relative to cell-specific markers. Measurement of catalase gene expression in relation to ABCD3 (which encodes the peroxisomal protein PMP-70) revealed no change between MS and control GM ( Fig. 3 A). We measured the gene expression of catalase relative to the microglial specific transcript AIF-1 (which codes for IBA-1), NSE (as a neuron-specific gene), GFAP (as an astrocyte-specific gene) and GalC (as an oligodendrocyte-specific gene). Catalase gene expression was significantly elevated in MS relative to AIF-1 ( Fig. 3 E;P<0.05) with levels being greater than 2-fold of those present in control grey matter. Catalase gene expression in relation to GFAP, GalC and NSE was not significantly different between MS and control ( Fig. 3 B–D).


Fig. 3 Catalase gene expression in multiple sclerosis (MS) grey matter and control grey matter. Catalase gene expression was measured by RT-PCR. The fold difference relative to the average in control grey matter was calculated for MS grey matter by the 2−ΔΔCtmethod, with ABCD3 (A); NSE (B); GFAP (C); GalC (D); and AIF-1 (E) as the calibrator. Catalase gene expression was significantly elevated in MS relative to AIF-1 expression (E;P<0.05). There were no significant differences in catalase gene expression calibrated against NSE, GFAP, GalC or ABCD3 expression (A, B, C and D). The geometric mean and 95% confidence intervals are shown on a logarithmic scale (to base 2) for samples from 25 cases of MS grey matter and 14 controls.

2.4. Microglial numbers are increased in MS cerebral cortex

The above data suggested that increased catalase activity found in MS grey matter may occur predominantly via an increased microglial expression. Elevated microglial activation has been previously shown to be present in MS grey matter ( Gray et al., 2008 ). We therefore labelled sections of MS grey matter and control for the microglial marker HLA-DR and counted for the presence of labelled cells in random areas of grey matter. We found that HLA-DR immunolabelling was significantly higher in MS grey matter compared to control grey matter (P<0.0001, Fig. 4 A and B-i and -ii, Mann–Whitney test). In addition, double immunofluorescent labelling of tissue sections for catalase and HLA-DR, and for catalase and IBA-1, showed co-localisation of staining throughout the grey matter ( Fig. 4 B and C).


Fig. 4 HLA-DR positive cell numbers in multiple sclerosis (MS) grey matter and control grey matter. (A) The mean values±SE are shown for 22 samples of MS grey matter and 13 controls. HLA-DR immunolabelling is significantly higher in MS than control grey matter (P<0.0001). (B) Control (i) and MS (ii) grey matter labelled for HLA-DR using immunoperoxidase/DAB staining. Scale bar 100 μm; microglial cell labelled for (iii) the nuclear stain 4׳6׳-diamidino-2-phenylindole (blue); (iv) catalase (red); (v) HLA-DR (green); and (vi) merged image within MS grey matter. Scale bar 10 μm. (C) Control (i–iv) and MS (v–viii) grey matter labelled for (i and v) the nuclear stain 4׳6׳-diamidino-2-phenylindole (blue); (ii and vi) catalase (red); (iii and vii) IBA-1 (green); and (iv and viii) merged image. Scale bar 50 μm.

3. Discussion

In this study, we have demonstrated for the first time that the activity of the anti-oxidant enzyme catalase is significantly higher in MS grey matter (GM) compared to control GM. We found no link between catalase expression and demyelination, but have shown increased numbers of microglial cells in MS GM, and have also shown that levels of the microglial specific protein IBA-1 correlate strongly with catalase protein expression in samples, suggesting that catalase expression in MS GM may predominantly occur in microglial cells.

GM pathology in MS has been the subject of a number of recent studies. Despite MS being thought of predominantly as a white matter (WM) disease, features of GM demyelination, inflammation and neuronal injury are commonly found ( Vercellino et al., 2005 ). The degree of GM demyelination in MS appears rather variable, although the extent is generally much higher in those with progressive disease (vs. those with relapsing and remitting disease) (Bo et al, 2003, Kutzelnigg et al, 2005, and Kutzelnigg et al, 2007). Inflammatory infiltrates in GM are usually found to be of lower intensity that in WM and inflammatory cells typically have the appearance of activated microglia (Peterson et al, 2001 and Bo et al, 2003). However, inflammatory cell-mediated injury in the GM is of importance since markers of neuronal injury-transected dendrites and axons- correlate with the degree of inflammation ( Peterson et al., 2001 ). Indeed GM lesions and atrophy have been associated with disability in MS, particularly cognitive impairment ( Calabrese et al., 2009 ).

Oxidative stress is thought to play a major role in the generation of tissue injury in MS. Release of reactive oxygen species (ROS), such as superoxide and hydrogen peroxide, from inflammatory cells is linked to cellular and myelin injury in the disease ( van Horssen et al., 2011 ). ROS may induce cellular injury via a number of mechanisms. For instance, oxidative damage to cell membrane lipids generates toxic molecules, such as 4-hydroxy-2-nonenal (4-HNE), which induces oligodendrocyte and neuronal injury in MS (van Horssen et al, 2008 and Haider et al, 2011). Generation of ROS in MS occurs predominantly via two mechanisms: activation of ROS-producing enzymes as part of the inflammatory response and via mitochondrial dysfunction ( Mahad et al., 2008 ). NADPH oxidase, the enzyme that generates superoxide ions, is highly expressed in activated microglia in active MS lesions ( Fischer et al., 2012 ). In addition, nitric oxide synthase, which is the enzyme responsible for the generation of nitric oxide (NO) which reacts with superoxide to form the highly toxic ROS peroxynitirite, is highly expressed in MS ( Liu et al., 2001 ).

Anti-oxidant enzymes are widely expressed and limit tissue injury caused by ROS and associated molecules. The balance of anti-oxidant enzyme expression and oxidative injury in MS is crucial, since this determines the degree of tissue injury. Some studies have shown elevation in levels of certain endogenous anti-oxidant enzymes in MS tissue, including superoxide dismutase-1 (SOD1), glutathione peroxidase (GPx) and catalase (Tajouri et al, 2003 and van Horssen et al, 2008). A more recent study using whole genome arrays has suggested that GPx isoenzyme transcripts may be differentially expressed in MS lesions ( Fischer et al., 2012 ). A further anti-oxidant enzyme, periredoxin-1, is up-regulated in MS tissue particularly in blood vessels adjacent to blood-brain barrier disruption ( Schreibelt et al., 2008 ). However, studies are limited and functional activity levels of these enzymes within tissue have not been previously reported.

In this study, catalase enzymatic activity was shown to be significantly elevated in MS GM compared to control and catalase protein expression correlated with expression of the microglial protein IBA-1. A previous report has shown co-localisation of catalase protein and CD-68 positive microglia in MS white matter ( van Horssen et al., 2008 ). Catalase activity is known to be regulated by a number of factors, e.g. NADPH binding, and the overall catalytic properties of the enzyme may be cell specific and dependent on multiple external factors ( Kirkman and Gaetani, 2007 ). To date, the precise factors that regulate the activity of catalase are still under debate. Cao et al. provided evidence to suggest c-Abl and Arg phosphorylate catalase at Tyr231 and Tyr286 in response to hydrogen peroxide ( Cao et al., 2003 ). The data presented here suggest that catalase activity is up-regulated in MS in response to microglial activity in an auto-regulatory fashion.

Anti-oxidant molecules have been considered as potential therapies for MS for some time ( Gilgun-Sherki et al., 2004 ). The finding of enhanced catalase activity in the brains of patients with long standing MS suggests that anti-oxidant defences continue to operate in the GM throughout the disease. Certain drugs, notably PPARγagonists such as pioglitazone, have been shown to increase catalase activityin vitro( Gray et al., 2012 ). Catalase gene expression is regulated by PPARγ-response elements suggesting that modulation of catalase expression via these drugs may be a viable therapy to reduce oxidative injury in MS GM ( Okuno et al., 2010 ).

In conclusion, we provide evidence of increased catalase activity in MS GM and a correlation between microglia and catalase expression. Catalase is an important anti-oxidant enzyme which abrogates oxidative stress. We propose that microglial expression of catalase acts as an auto-regulatory process to reduce excessive oxidative injury. Therapeutic strategies that aim to enhance endogenous catalase activity within MS may be relevant in the attenuation of tissue injury in MS.

4. Experimental procedures

4.1. Brain tissue

Tissue for this study was obtained from the UK Multiple Sclerosis Tissue Bank, Imperial College, London. Frozen tissue from multiple regions of grey matter (GM) and white matter was available from 25 cases of neuropathologically confirmed MS and 14 controls (see Table 1 for clinical details). The tissue had been snap-frozen by immersion in isopentane and stored at −80 °C. Paraffin blocks of formalin-fixed tissue from multiple regions of GM were available from 22 cases of neuropathologically confirmed multiple sclerosis and 13 controls ( Table 1 ).

Table 1 The clinical details of multiple sclerosis and control patients used in this study.

MS case number Age (years) Sex Cause of death Duration of MS (years) Course of MS Tissue
MS1 49 F Chronic renal failure/heart disease 18 Secondary Progressive F/P
MS2 50 F Multiple sclerosis Not known Secondary Progressive F/P
MS3 51 F Bronchio pneumonia/MS Not known Secondary Progressive F/P
MS4 53 F Multiple sclerosis 28 Secondary Progressive F/P
MS5 38 M Aspiration pneumonia/pulmonary oedema 16 Relapsing Progressive F/P
MS6 47 F Pneumonia, multiple sclerosis 25 Secondary Progressive F/P
MS7 54 M Bronchopneumonia 16 Primary Progressive F
MS8 39 F Bronchopneumonia 21 Not known F/P
MS9 44 F Aspiration pneumonia, multiple sclerosis 16 Secondary Progressive F/P
MS10 54 F Bronchopneumonia Not known Not known F/P
MS11 48 F Pneumonia, multiple sclerosis Not known Secondary Progressive F
MS12 45 F Septicaemia, multiple sclerosis Not known Relapsing/ remitting F
MS13 44 F Sepsis, multiple sclerosis 19 Secondary Progressive F/P
MS14 53 M Bronchial pneumonia, multiple sclerosis 16 Secondary Progressive F/P
MS15 46 M Pneumonia 8 Secondary Progressive F/P
MS16 42 F Multiple sclerosis Not known Secondary Progressive F/P
MS17 39 F Pulmonary embolism, pneumonia 15 Relapsing Progressive F/P
MS18 59 F Chest infection, heart failure 42 Relapsing/ remitting P
MS19 45 M Bronchopneumonia, advanced multiple sclerosis 25 Secondary Progressive P
MS20 53 F Aspiration pneumonia, multiple sclerosis 24 Secondary Progressive P
MS21 51 M Bronchopneumonia 2 Primary Progressive P
MS22 35 F Multiple sclerosis 5 Secondary Progressive P
MS23 46 F Multiple sclerosis 26 Secondary Progressive P
MS24 43 M Bronchopneumonia, multiple sclerosis 18 Secondary Progressive P
MS25 56 F Bronchopneumonia, multiple sclerosis 34 Secondary Progressive P
MS26 51 F Multiple sclerosis 21 Secondary Progressive F
MS27 53 M Advanced multiple sclerosis, urinary tract infection 11 Secondary Progressive F
MS28 49 F Multiple sclerosis 14 Secondary Progressive F
MS29 44 M Bronchopneumonia Not known Secondary Progressive F
MS30 88 F Bronchopneumonia 32 Primary Progressive F
MS31 70 F Cerebral bleed, aspiration 12 Secondary Progressive F
MS32 57 F Sepsis 19 Secondary Progressive F
MS33 64 M Bronchopneumonia, multiple sclerosis 26 Secondary Progressive F
MS34 45 M Multiple sclerosis 16 Secondary Progressive F
MS35 45 M Advanced multiple sclerosis 18 Secondary Progressive F
Control case number Age (years) Sex Cause of death     Tissue
C1 64 M Cardiac failure     F
C2 92 M Cardiac failure     F
C3 82 M Myelodysplastic syndrome     F/P
C4 84 M Bladder cancer, pneumonia     F/P
C5 54 M Lung cancer     F
C6 68 M Cardiac failure     F/P
C7 84 F Cardiac failure     F/P
C8 60 F Ovarian cancer     F/P
C9 88 M Prostate cancer     F/P
C10 35 M Tongue cancer     F
C11 78 F Leukaemia     F/P
C12 69 F Lung cancer     F/P
C13 77 F Non-hodgkin׳s Lymphoma     P
C14 91 F Pneumonia     P
C15 75 M Metastatic renal carcinoma     P
C16 85 M Ischaemic heart disease     P
C17 71 M Abdominal and retroprofusion haemorrhage, ruptured spleen     P
C18 93 F Bronchopneumonia, cerebrovascular accident     F
C19 82 M Not known     F

4.2. Assessment of demyelination in blocks of frozen tissue

Sections 15 µm in thickness were cut from the blocks of frozen tissue (each measuring approximately 2×2 cm2in cross-section and 1 cm in thickness) and immunostained for myelin basic protein (MBP). The sections were fixed in acetone, pre-treated in ice-cold methanol, rinsed, immersed in 3% hydrogen peroxide in methanol for 30 min to block endogenous activity and rinsed in PBS. Non-specific binding was blocked by incubation for 20 min in Vectastain blocking serum (Vector Laboratories). Sections were incubated for 1 h at room temperature with MBP antibody (1:3200; Serotec, Oxford, UK). The sections were then rinsed in PBS before incubation for 20 min with secondary antibody (Vectastain Biotinylated Universal antibody) and 20 min with Vectalite ABC complex (Vector Laboratories, Peterborough, UK) followed by a 10-min incubation with 3,3׳-diaminobenzidine (DAB) and 0.01% H2O2. Sections were washed in water, immersed in copper sulphate DAB enhancer (4 min), counterstained with hematoxylin, dehydrated, cleared and mounted.

4.3. Immunoperoxidase labelling of paraffin sections

7 µm sections were cut from blocks of the frontal and temporal lobes. Sections were stained with antibodies to MBP (as above) or HLA-DR (1:800; Dako, Ely, UK). Sections were dewaxed, hydrated, and immersed in 3% hydrogen peroxide in methanol for 30 min to block endogenous peroxidase activity, rinsed and microwaved in sodium citrate buffer (0.01 M, pH 6.0, 5 min) or EDTA buffer (1 mM, pH 8, 10 min) as appropriate and rinsed in phosphate-buffered saline (PBS). Non-specific binding was blocked with Vectastain blocking serum (20 min). After addition of the primary antibody, sections were incubated overnight at 4 °C. The sections were then rinsed in PBS before incubation for 20 min with secondary antibody (Vectastain Biotinylated Universal antibody) and 20 min with Vectalite ABC complex (Vector Laboratories, Peterborough, UK) followed by a 10-minute incubation with 3,3׳-diaminobenzidine (DAB) and 0.01% H2O2. Sections were washed in water, immersed in copper sulphate DAB enhancer (4 min), counterstained with hematoxylin, dehydrated, cleared and mounted. Controls in each run included sections incubated overnight in PBS instead of primary antibody.

4.4. Immunfluorescent labelling of paraffin sections

Sections were dewaxed, hydrated and rinsed as above. To reduce auto-fluorescence, sections were incubated in 5 mM copper sulphate and 50 mM ammonium acetate for 1 h at room temperature prior to microwaving of the sections in sodium citrate buffer (0.01 M, pH 6.0, 5 min). Microglial expression of catalase was assessed by double immunofluorescence using rabbit anti-catalase antibody (1:500; Abcam, Cambridge, UK) in combination with a mouse monoclonal antibody to HLA-DR (1:800; Dako, Ely, UK). Non-specific binding was blocked with 10% normal goat serum diluted in PBS containing 0.1% triton. Sections were incubated at 4 °C overnight with primary antibodies. Sections were then washed in PBS and incubated for 30 min in the dark with the appropriate secondary antibodies (1:500): goat anti-mouse Alexa Fluor 555, goat anti-rabbit Alexa Fluor 488 (Invitrogen, Paisley, UK), before being washed in PBS and mounted in Vectashield medium containing the nuclear dye 4׳6׳-diamidino-2-phenylindole (DAPI). For IBA-1/catalase staining, primaries used were catalase (as above) and a goat polyclonal antibody to IBA-1 (1:200; Abcam, Cambridge, UK) blocked in 5% BSA in PBS containing 0.1% triton. Secondary antibodies (1:500) were donkey anti-goatAlexa Fluor 555, donkey anti-rabbit Alexa Fluor 488 (Invitrogen, Paisley, UK) For all the immunofluorescence, images were acquired using an inverted Leica CTR 6000 fluorescence microscope and merged with Leica Application Suite Advanced Fluorescence software.

4.5. Measurement of catalase activity in grey matter

Frozen blocks were thawed on ice and GM carefully dissected away from underlying white matter. GM was homogenised on ice using the PARIS kit (Ambion). Supernatants were removed and stored at −80 °C until required. Catalase activity was subsequently assayed in the supernatants (Cayman Chemical, Ann Arbor, USA). The assay utilises the peroxidatic function of catalase for the determination of enzyme activity. The method is based on the reaction of the enzyme with methanol in the presence of an optimal concentration of H2O2. The formaldehyde produced is measured spectrophotometrically with 4-amino-3-hydrazino-5-mercapto-1,2,4-triazole (Purpald) as the chromogen. 20 µl aliquots of homogenate containing 3 mg/ml of protein were added in duplicate. Each plate included a 0–75 µM range of formaldehyde standards that was used to construct a standard curve and blank wells that contained sample buffer alone. The reaction was initiated by adding 20 µl of hydrogen peroxide and the plates incubated on a shaker at room temperature for 20 min. The reaction was stopped by the addition of 30 µl of potassium hydroxide followed by 30 µl of purpald (chromogen) and 10 µl of potassium periodate in each well. The absorbance was read at 540 nm and the activity of catalase (nmol/min/mg total protein) determined by interpolation from the standard curve.

4.6. Measurement of catalase protein levels by dot blotting

GM homogenates were diluted 1 in 200 in TBS prior to use. The Bio-Dot™ apparatus (Bio-Rad, Hercules, CA, USA) containing a nitrocellulose membrane was assembled according to manufacturer׳s instructions and the vacuum applied for tightening of the manifold. With the vacuum switched off and the apparatus exposed to air, 100 µl of sample was added to wells and left to incubate for 90 min. Blanks and any un-used wells were filled with 100 µl TBS. Following this incubation, the apparatus was disassembled and the membrane was washed briefly in TBS-T prior to being incubated in 5% BSA TBS-T blocking solution for 1 h at room temperature. The membrane was then incubated overnight on a rocking platform at 4 °C with anti-Iba 1 (goat polyclonal, Abcam) (1:500) or anti-catalase (1:3000) primary antibody in 5% BSA TBS-T. The membrane was then washed in three changes of TBS-T and incubated with either a horse-anti goat (Vector Laboratories) ( 1:5000) or goat anti-rabbit (1:3000) horseradish peroxidase conjugated antibody (Abcam) in 5% BSA TBS-T on a rocking platform. Immunolabelled dots were visualised by chemiluminescence using a Geneflow Limited Western Blotting Detection System (Geneflow Limited, Staffordshire, UK). The integrated area density for each dot was measured using Image-J software. Relative catalase expression values for each sample on the dot blot were calculated using integrated area density values obtained from an Iba 1 dot blot performed on the same samples.

4.7. Quantitative assessment of activated microglia in paraffin sections

Image Pro-Plus software (Bethesda, USA), driving an Olympus IX70 microscope (Olympus, UK) with a motorised stage, was used to quantify HLA-DR immunolabelling. Areas of GM were outlined interactively and the software was programmed to make an automated unbiased selection of 30 random ×20 objective fields (0.2 mm2) within the outlined area. The mean number of HLA-DR immunopositive microglia was determined for each area of GM.

4.8. cDNA generation and real-time polymerase chain reaction (PCR) on brain tissue

RNA was isolated from the homogenates of brain tissue using the PARIS kit (Ambion) according to manufacturer׳s instructions and stored at −80 °C. RNA concentration was determined using the Quant-iT RNA kit (Invitrogen). RNA extracts were then treated with DNase-I (Roche Diagnostics Ltd, West Sussex, UK) to remove any DNA and cDNA was produced using the High-Capacity c-DNA archive kit from Applied Biosystems (Foster City, CA, USA). Real-time PCR was performed using the Step One Plus system (Applied Biosystems), with assay-on-demand gene expression products for ATP-Binding Cassette Sub-Family D Member3 (ABCD3; Hs01082795_m1), catalase (Hs00156308_m1), glial fibrillary acidic protein (HS00909233_m1; GFAP), galactosylceramidase (Hs01012300_m1; GalC) and allograft inflammatory factor 1 (AIF1) (Hs00610419_g1) (Taqman MGB probes, FAM dye-labelled, Applied Biosystems), gene expression master mix and 10 ng of cDNA. All samples were analysed in triplicate. Relative gene expression (expressed as fold difference relative to control tissue) was calculated using the 2−ΔΔCtmethod and the geometric mean taken for each group ( Livak and Schmittgen, 2001 ). For example, catalase expression in relation to the calibrator gene GAPDH was calculated (ΔCt) and used to determine the fold change in ABCD3 expression (2−ΔΔCt) in each sample relative to the mean expression in controls. Since catalase is predominantly found within peroxisomes, we calculated gene expression for catalase relative to the pan cellular peroxisomal gene ABCD3, as well as cell specific gene transcripts: the astrocyte gene GFAP, the neuronal gene NSE, the oligodendrocyte gene GalC and the microglial gene AIF-1, in order to determine the influence of cell-specific gene transcription on catalase expression.

4.9. Statistics

Mann–Whitney test was used to compare HLA-DR immunolabeling and relative catalase integrated density in the MS brains with those in control brains. These statistical tests were performed using GraphPad v5 for Windows (GraphPad Software Inc., LaJolla, CA, USA). Because the mRNA and catalase activity measurements were on different samples from the same brains, we could not treat all the values independently and for statistical analysis therefore fitted a maximum restricted likelihood mixed-effect regression model that assumed both random effects between and within subjects and a fixed effect between subjects, based on presence/absence of MS. The model was chosen to take account of variable repeated measurements coming from different specimens of the same brain. The analysis was performed with the help of STATA v12.0 (Timberlake Consultants, London, UK). For all tests, values ofp<0.05 were considered statistically significant.

5. Conclusions

Catalase enzymatic activity is increased in MS grey matter compared to control GM. In addition, microglial numbers are increased in MS grey matter and catalase protein expression levels positively correlate with microglial protein markers, suggesting that in MS grey matter microglial catalase activity may be an important anti-oxidant source to limit oxidative stress.

Conflict of interest and ethics statement

The authors declare no conflicts of interest relating to this paper. All human studies have been approved by the appropriate ethics committee and have been performed in accordance with the ethical standards laid down in the 1964 Declaration of Helsinki and its later amendments.


This work was supported by a Junior Research Fellowship grant from the Multiple Sclerosis Society of Great Britain and Northern Ireland. The authors thank the UK Multiple Sclerosis Tissue Bank at Imperial College, London, UK, for providing all the tissues used in this study.


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MS Labs, Burden Centre, University of Bristol, Institute of Clinical Neurosciences, Frenchay Hospital, BS16 1JB Bristol, UK

lowast Corresponding author. Fax: +44 117 3406655.