Human Molecular Genetics, 2001, Vol. 10, No. 17 1729-1740
© 2001 Oxford University Press
Quantitative localization of heterogeneous methyl-CpG-binding protein 2 (MeCP2) expression phenotypes in normal and Rett syndrome brain by laser scanning cytometry
Medical Microbiology and Immunology, Rowe Program in Human Genetics, School of Medicine, 1 Shields Avenue, University of California, Davis, CA 95616, USA and 1Medical Pathology, University of California Davis Medical Center, Sacramento, CA 95817, USA
Received April 19 2001; Revised and Accepted June 19, 2001.
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ABSTRACT |
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 TOP ABSTRACT INTRODUCTIONRESULTSDISCUSSIONMATERIALS AND METHODSREFERENCES |
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Rett syndrome (RTT) is an X-linked, dominant neurodevelopmental disorder caused by mutations in MECP2, encoding the methyl-CpG-binding protein 2 (MeCP2). A major paradox in the pathogenesis of RTT is how mutations in ubiquitously transcribed MECP2 result in a phenotype specific to the central nervous system (CNS) during postnatal development. To address this question, we have used a novel approach for quantitating the level and distribution of wild-type and mutant MeCP2 in situ by immunofluorescence and laser scanning cytometry. Surprisingly, cellular heterogeneity in MeCP2 expression level was observed in normal brain with a subpopulation of cells exhibiting high expression (MeCP2hi) and the remainder exhibiting low expression (MeCP2lo). MeCP2 expression was significantly higher in CNS compared with non-CNS tissues of human and mouse by automated quantitation of MeCP2 on multiple tissue arrays. Quantitative localization of MeCP2 expression phenotypes in normal human brain showed a mosaic, but distinct, distribution pattern, with MeCP2hi neurons highest in layer IV of the cerebrum and MeCP2lo neurons highest in the granular layer of the cerebellum. In female RTT brains, MECP2 mutant-expressing cells were identified as cells negative for the MeCP2 C-terminal epitope. MECP2 mutant-expressing cells were randomly localized in Rett cerebrum and cerebellum and showed normal MeCP2 expression with N-terminal-specific anti-MeCP2. These results demonstrate a CNS-specific cellular phenotype of MeCP2 high expression and suggest that MECP2 mutations in RTT are only manifested in MeCP2hi cells. In addition, our results demonstrate the power of laser scanning cytometry in examining complex cellular phenotypes in disease pathogenesis.
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INTRODUCTION |
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TOPABSTRACTINTRODUCTIONRESULTSDISCUSSIONMATERIALS AND METHODSREFERENCES |
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Rett syndrome (RTT) is an X-linked dominant neurodevelopmental disorder initially manifesting around 6 to 18 months of age in females (1,2). Clinical features include deceleration of head growth, loss of purposeful hand movements, ataxia, loss of vocalization skills, autistic features, seizures and respiratory dysfunction. Approximately 80% of RTT patients have detectable mutations in MECP2 (3–6), encoding the methyl-CpG-binding protein 2 (MeCP2) (7,8). MeCP2 localizes to heterochromatin and is predicted to act as a transcriptional silencer for methylated genes (7,9–12). Paradoxically, MECP2 is ubiquitously expressed at the transcriptional level in normal human tissues (8,13,14), although RTT appears to only exhibit abnormalities in the central nervous system (CNS) (15). Similarly, a mouse model with MECP2 deletions targeted to the CNS has a RTT-like phenotype indistinguishable from deletions targeted to the whole organism (16,17). Quantitative assessments of MeCP2 protein expression between CNS and other tissues, however, have not been performed previously on normal or RTT tissues.
Here we describe a novel approach for quantitatively determining the level and distribution of wild-type and mutant MeCP2 in situ by immunofluorescence and laser scanning cytometry (LSC). LSC is a new technology with similarities to flow cytometry, but is microscope based rather than fluidics based (18,19). Samples of cells or paraffin-embedded tissue sections are fluorescently stained on a microscope slide and scanned by argon and helium/neon lasers to obtain digital images in up to four different fluorescent wavelengths. Contours are created based on nuclear staining to identify individual cells. Quantitative data regarding fluorescent intensity, size and position are recorded for each cell in different fluorescent channels. A large number of cells can be scanned rapidly, making the technology preferable to confocal microscopy, as cell population analyses and correlative relationships between different fluorescent stains can be performed. LSC has been previously useful in DNA ploidy and apoptosis analyses on clinical samples and cultured cell lines (18–23). The current study extends the application of LSC to investigating tissue microarrays and genetic mutations in situ.
In this report, we demonstrate the power of LSC in investigating the role of MeCP2 in the pathogenesis of RTT. Using a high-throughput quantitative analysis of immunofluorescence on multiple tissue microarrays, we demonstrate that MeCP2 shows significantly higher expression in cellular subpopulations within the CNS. We also demonstrate a distinct tissue distribution of cells according to their MeCP2 expression patterns in normal cerebrum and cerebellum and mutant-expressing cells in Rett brain. These results are expected to be significant in solving the current paradox of MECP2 mutation in the pathogenesis of RTT.
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RESULTS |
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TOPABSTRACTINTRODUCTIONRESULTSDISCUSSIONMATERIALS AND METHODSREFERENCES |
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Quantitative analysis of MeCP2 in brain by LSC
We devised a quantitative approach for the detection of immunofluorescence in brain by LSC. Sections of paraffin-embedded postmortem human brain samples were stained with a rabbit antiserum specific for the C-terminal end of MeCP2 and detected with a Cy5-labeled secondary antibody. Figure 1A–F shows examples of the raw data images from photomultiplier tubes preceded by the appropriate optical filter blocks for red, green and long red. Nuclei were counterstained with propidium iodide (PI) to identify all nuclei in the tissue (Fig. 1A). Contours were created based on red fluorescence and user-defined settings of minimum thresholds for size and intensity (Fig. 1B). The same contours were applied to images from the green and long red channels (Figs 1D and F). Contours containing overlapping cell multiples were removed by gating out contoured events on the basis of area and red fluorescence (Fig. 1G).
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As autofluorescence of unstained brain tissue is a potential impediment to accurate quantitation of immunofluorescence, we took several steps to avoid or remove non-specific fluorescent signals. First, since autofluorescence is less prevalent in the long red wavelengths (>600 nm), the dye Cy5 (650 nm emission) was used for detection of immunofluorescence. Secondly, since autofluorescent signals occur in both red and green channels, they can be identified and removed based on that property. Figure 1H shows the scattergram of green versus red max pixel (the peak fluorescent intensity inside each contour). Autofluorescent signals were observed as a distinct population forming a diagonal plot (top right quadrant). The events contained within the lower right quadrant were gated for inclusion in the analysis since they contain nuclei without detectable autofluorescence. The population of contoured events gated in Figure 1G and H shows a single uniform peak of red fluorescence, representing diploid nuclei (data not shown).
Surprisingly, the histogram of long red max pixel values in Figure 1I showed considerable population heterogeneity intensity of MeCP2 nuclear staining. When compared to the negative control rabbit IgG (filled histogram), anti-MeCP2 staining (open histogram) revealed a specific shift of the first narrow peak of low fluorescent intensity (MeCP2lo). A second broader and variable population of high fluorescent intensity (MeCP2hi) was also observed. Cellular heterogeneity was not observed with another nuclear protein with similar function and chromatin association, histone H1 (11) (Fig. 1J), demonstrating that the cellular heterogeneity in MeCP2 staining was not due to general nuclear heterogeneity in brain. Furthermore, neither autofluorescence nor spectral overlap with PI was responsible for the subpopulation of MeCP2hi cells since no coordinate increase was observed between the red and long red channels (Fig. 1K). Lastly, although the MeCP2hi subpopulation had generally larger nuclear size, there was no strict correlation between nuclear area and MeCP2 immunofluorescence (Fig. 1L). These results demonstrate a cellular phenotype of MeCP2 high expression in subpopulations of human brain.
Quantitation of MeCP2 immunofluorescence in multiple human and mouse tissue microarrays by LSC
We next asked if the MeCP2hi phenotype and cellular heterogeneity were observed in tissues other than brain and conserved in mouse by a high-throughput approach with multiple tissue microarrays. Tissue microarrays are a new technology that combine small (600 µm) cores from multiple fixed tissues into a single paraffin block (24). In addition to quantitating fluorescence, the LSC also records the slide positions of each cell contoured, so a distribution of cells according to the x and y positions on the slide can be plotted and array positions located. Figure 2A shows the plot of the x and y positions obtained for the human tissue microarray, containing 67 samples in duplicate (Fig. 2Aa–e and f–j) of 44 different human tissues from three different cadavers (male and female, when applicable). Quantitative analysis of MeCP2 phenotype was performed on approximately 20 000 nuclei from 35 different tissues by an automated LSC scan in about 3 h (Table 1). Figure 2B shows the filled histogram of MeCP2 immunofluorescence for the total array scan that contained 
20% CNS tissues, resulting in less population heterogeneity than observed in cerebrum (Fig. 1I). The region representing the highest expression level was defined as above the right intersect at half-maximum of the histogram and colored in red to represent the MeCP2hi phenotype. Each tissue type was individually gated to obtain the mean and coefficient of variation (CV) of MeCP2 immunofluorescence and the percentage of MeCP2hi cells (based on Region 2 in Figure 2B).
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Table 1 compiles the results of the analysis and gives array positions of each tissue in Figure 2A. As a group, the eight CNS tissues had the highest MeCP2 expression (population means > 3000 max pixel) and variance (CVs
30%) of all the tissues analyzed. In addition, with the exception of the cerebellar cortex, the CNS tissues (indicated by blue lines in Figure 2A) exhibited among the highest percentage of MeCP2hi cells (25%). The greatest heterogeneity in MeCP2 expression was observed in the cerebral cortex and cerebellar cortex (CVs, 70 and 67%, respectively). Some non-CNS tissues also showed a high percentage of MeCP2hi cells (>20%; purple lines in Figure 2A), including the lung, pituitary, thyroid, seminal vesicle, vena cava and cardiac muscle. In spite of these few tissue exceptions, however, the CNS tissues had significantly higher MeCP2 expression, population variance, and percentage of MeCP2hi cells than the non-CNS tissues (Table 1). To test whether the CNS-specific differences were general rather than unique to MeCP2, we performed the identical analysis on a subsequent section of the human tissue microarray, but with the substitution of anti-histone H1 as the primary antibody. The results, summarized in Table 1, show no significant difference between CNS and non-CNS tissue for histone H1 expression. A mouse tissue array in which approximately half of the samples were from the CNS was performed (Fig. 2C). The first scan of the mouse microarray was performed with the identical LSC settings as the human tissue array, resulting in efficient contouring of only half of the tissues (histogram in Figure 2D). Because mouse tissues have more densely spaced nuclei, the remaining samples were scanned using a higher threshold (tissues outlined with dashed lines in Figure 2C, histogram in 2E) that allowed sampling of most of the remaining tissues. The cerebellar cortex was scanned twice to include both the molecular layer and the higher density granular layer. The results of both scans are merged in Figure 2C. Of the 24 different tissues included on the mouse array, 19 were analyzed (five samples had <50 cells; gray bars in Figure 2C) and the statistical results are included in Table 2. The mean, variance and percentage of cells showing the MeCP2hi phenotype were significantly higher in the mouse CNS tissues compared with non-CNS tissues. Exceptions were the cerebellar granular layer, which was lower than other CNS tissues, and the lung, which showed a high percentage and mean of the population but low variance.
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Histologic distribution of MeCP2lo and MeCP2hi cell populations in CNS tissues
The ability of LSC technology to show localization of cells in addition to quantitating fluorescence was especially useful in determining the histologic localization of MeCP2lo and MeCP2hi cell populations within the brain. The gross tissue morphology can be observed in the distribution plot and is recognizable as the appropriate morphology for cerebrum, cerebellum and hippocampus. To determine the histologic distribution of MeCP2 subpopulations, cells in the different populations were differentially colored (Fig. 3A, E and I). Region 1 from the MeCP2 histogram represents the ‘negative’ cells (MeCP2neg) colored in blue, region 2 (green) includes the major peak representing the MeCP2lo cells, and region 3 (red) represents the MeCP2hi cells. In addition, the histological distribution of MeCP2 cell populations in cerebrum, cerebellum and hippocampus was confirmed and investigated at a higher resolution by wide-field fluorescence microscopy (Fig. 4). MeCP2 colocalized with the nuclear heterochromatin in all CNS tissues.
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The distribution of the MeCP2lo and MeCP2hi cells within each tissue exhibits distinct layering in each of the brain tissues examined (Fig. 3B, F and J, and Fig. 4). To quantitate regional differences in MeCP2 subpopulations, individual gates were created for four layers of the cerebrum and three layers of the cerebellum (Fig. 3C and G). For the cerebrum, the increased density of cells in layer IV of the cortex and the white matter allowed for a specific gating, while cortex layers I–III and V–VI were combined because of the lack of distinguishing features by LSC (Fig. 3B and C). In the cerebellum, the granular layer was the most distinguishing feature that allowed the gating of three distinct layers (Fig. 3F and G). The granular layer contains the highest density of cells in the brain (Fig. 4G), but most nuclei are overlapping, resulting in their removal from LSC analysis (Fig. 1G). Most cells within the inner and outer edges are contoured individually, so the granular layer is observed as a ribbon-like structure containing a high density of cells at the edges and a low density of cells in the middle. The molecular layer extends from the outer edge of the cerebellum to the edge of the granular layer, while the white matter is within the interior of the tissue. The Purkinje cells found between the molecular and granular layers are not well contoured by LSC analysis because their large euchromatic nuclei do not stain intensely with PI. Investigation of Purkinje cells by fluorescent microscopy showed MeCP2lo expression (Fig. 4F, arrows). In the hippocampus, an even greater population of MeCP2hi cells was observed (Figs 3I and 4I and J). Due to high autofluorescence and nuclear heterogeneity, not all hippocampus cells were sampled, making the distinction between specific layers problematic. MeCP2hi cells appeared to be in highest abundance in the outer pyramidal and polymorphic layers and lower abundance in the inner molecular layer (Figs 3J and 4I and J).
The percentage of cells in each subpopulation of MeCP2 phenotypes (MeCP2neg, MeCP2lo and MeCP2hi) were compared between the distinguishable layers of the cerebrum and cerebellum (Fig. 3D and H, respectively). Layer IV of the cerebral cortex and the molecular layer of the cerebellum exhibited a higher proportion of MeCP2hi to MeCP2lo cells. In contrast, the granular layer of the cerebellum had the highest percentage of MeCP2lo cells, while the remaining layers had roughly equivalent numbers of MeCP2 phenotypes. Glial cells in the cerebral and cerebellar white matter were mosaic for MeCP2, but MeCP2hi cells in the cerebral cortex appeared to be primarily neuronal. To directly test for MeCP2 levels in neurons versus glia, we combined a long red fluorescent Nissl dye (specific for neurons) with anti-MeCP2 immunofluorescence. The MeCP2 histogram from green fluorescent detection was comparable to long red detection (compare Figure 3A and K). The Nissl stain histogram (Fig. 3L) showed two distinct peaks of the total population (black) that were separately analyzed in Region 1 (Nissllo) and Region 2 (Nisslhi). While neurons in the cerebral cortex were mosaic for MeCP2lo (green) and MeCP2hi (red), glial cells were predominantly MeCP2lo.
Quantitative localization of MeCP2 cellular phenotypes in RTT brain
Because of X-inactivation, females with RTT are mosaic for expression of the mutant allele of MECP2 (4,25). Although X-inactivation assays have estimated the frequency of mutant expressing cells in blood and brain (4,25), there has been no technique available to directly determine the number and distribution of MECP2-mutant-expressing cells in brain. As anti-MeCP2 recognizes the C-terminus, truncating mutations of MeCP2 [70% of MECP2 mutations in RTT (15)] should not be recognized. RTT clonal cell lines exclusively expressing MECP2 truncating mutations [(26) and D.Balmer, R.S.Samaco, H.Y.Zoghbi and J.M.LaSalle, manuscript in preparation] and Mecp2-null mice (16,17) have confirmed the specificity of this antibody. Detection of immunofluorescence by LSC therefore allowed the quantitation and localization of MECP2 mutant-expressing cells in mosaic tissue as the MeCP2neg subpopulation.
The quantitative localization of MeCP2neg cells was observed on the plot of x, y position for all samples. A representative analysis of RTT brain B3393 (R168X MECP2 mutation) is shown in Figure 5A–H and was performed as described for Figure 3. The MeCP2neg cells were found to represent almost half of the cells in the cerebrum and cerebellum. The roughly equal ratio of mutant and wild-type expression was confirmed by RT–PCR analysis on RNA isolated from the same brain samples (Fig. 5I). The MeCP2neg cells were randomly distributed throughout the different layers of the cerebrum and cerebellum, with the exception of the molecular layer, where there was a slightly lower representation (Fig. 5H). As expected for wild-type-expressing cells in RTT brain, the distribution pattern of MeCP2lo and MeCP2hi subpopulations was similar to that observed in normal control samples.
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Table 3 lists the source of postmortem brain samples and shows the combined results from the quantitative analyses of MeCP2 in several normal and RTT brains. MECP2 mutations were detected in two of the available RTT brain samples (Fig. 5I, B3393 and B4312), while one (B4321) had no detectable mutations by MECP2 sequence analysis. A significantly higher percentage of MeCP2neg cells was observed in all three RTT brains, including the two samples with the most common R168X mutation. For the two known MeCP2 mutations, the percentage of MeCP2neg cells was comparable to the representation on the RT–PCR analysis in Figure 5I. In addition, the percentage of MeCP2neg cells was comparable between cerebrum and cerebellum samples of the same individual and within the range expected for random X-inactivation (4,26). The proportion of MeCP2 positively staining cells in MeCP2lo and MeCP2hi subpopulations varied greatly between brain samples from different individuals, but not in experimental replicates of the same sample (Table 3). The proportion of MeCP2lo and MeCP2hi cells in RTT samples, which represent the MECP2 wild-type-expressing cells, was not significantly different from control brain samples.
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To determine if MECP2 mutant-expressing cells expressed the truncated MeCP2 protein, a different anti-MeCP2 antibody reactive to the N-terminus was utilized. As expected for truncation mutations, virtually all cells stained positive for the N-terminal epitope and no significant difference was observed between the percentage of negative cells in control and RTT samples (Table 3). In contrast, a significant difference was observed between the percentage on MeCP2neg cells detected with the two different MeCP2 antibodies for the RTT samples, but not the controls.
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DISCUSSION |
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TOPABSTRACTINTRODUCTIONRESULTSDISCUSSIONMATERIALS AND METHODSREFERENCES |
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In this report, we have demonstrated the use of the new LSC technology for understanding complex cellular phenotypes associated with a human genetic disorder. Previously, LSC technology had been limited to cellular applications similar to flow cytometry (18–22) and had not been utilized as a method for obtaining quantitative fluorescent data of cellular phenotypes in situ. The technology presented here as an approach to understanding the pathogenesis of RTT is expected to have broader applications, including the quantitative analysis of phenotypes in mice with targeted gene mutations, gene therapy trials, and in understanding the pathogenesis of other human disorders with complex epigenetic phenotypes. The automated nature of LSC makes it amenable to the high-throughput applications such as tissue microarrays (24,27), and more broadly applicable to the quantitative detection of DNA and RNA fluorescence in situ hybridization (19,28). As exemplified by the experiments in this report, LSC provides an important tool to provide quantitative and statistical analyses of data from in situ investigations that were previously simply descriptive.
Using LSC to investigate MeCP2 expression in situ, we have made several important discoveries directly relevant to understanding the pathogenesis of RTT. First, we demonstrate MeCP2 high expression in cellular subpopulations of CNS tissues. These results demonstrate that although MECP2 is ubiquitously transcribed in all tissues (8,13,14), the level of protein expression is not equivalent in all cells or tissues (Fig. 2 and Tables 1 and 2). Western blot analyses have confirmed the abundance of MeCP2 in brain relative to non-CNS tissues (data not shown). Although the overabundance of MeCP2 in brain has been suggested by previous studies (9,13), ours is the first study to our knowledge to directly demonstrate this finding. The observation of significantly more MeCP2hi cells in human and mouse CNS tissues would explain the paradox of why the predominant phenotype of MECP2 mutation is CNS-specific in both species (15–17).
Interestingly, alternative polyadenylation of MECP2 results in at least two different sized transcripts of equivalent stability (13,14). By in situ hybridization analysis of postnatal mouse brain, the alternative long 3'-untranslated region (3'-UTR) shows tissues specificity with highest abundance in the hippocampus and olfactory bulb (13). Since the use of the long 3'-UTR is more predominant in brain compared with most other tissues, a novel avenue to pursue would be to test if the long 3'-UTR results in MeCP2 high expression.
The cellular heterogeneity of MeCP2 expression phenotype was another novel observation of this report that opens up additional interpretations relevant to RTT. The heterogeneity did not appear to be exclusively determined by cell type, as white matter glial cells and cerebral cortex neurons were mosaic for MeCP2lo and MeCP2hi phenotypes. These results demonstrate that MeCP2 heterogeneity is due to phenotypic differences within both neuronal and glial populations, but the abundance of the MeCP2hi phenotype depends on their anatomical location. Our new findings raise the possibility that the MeCP2hi phenotype may be acquired postnatally in cellular subpopulations of the CNS. The phenotype of MECP2 mutation is not apparent until 6–18 months in RTT (1) or 5–6 weeks in the mouse model (16,17), suggesting a postnatal requirement for MeCP2 in the CNS.
Finally, we have demonstrated the first localization of MECP2 mutant-expressing cells in RTT brain using a quantitative LSC approach. MECP2 mutant-expressing cells were identified as a significant population of MeCP2neg cells and found to be randomly distributed throughout the cerebrum and cerebellum. These results suggest that MECP2 mutation does not affect the normal migration patterns during development of the CNS and is consistent with our hypothesis of mutations being manifested postnatally in cells acquiring the MeCP2hi phenotype. The LSC analysis was confirmed by RT–PCR, demonstrating the ability to accurately detect MECP2 mutant-expressing cells by this approach. A previous study showing random X-inactivation patterns in RTT brain was also consistent with our results (25).
The use of a different anti-MeCP2 antibody reactive to the N-terminus allowed the detection of mutant as well as wild-type-expressing cells in the RTT samples and suggests that MECP2 truncation mutations do not affect protein expression. As the clinical features of RTT are only apparent in CNS tissues with greatest abundance of MeCP2hi cells, our results would therefore suggest that loss-of-function MECP2 mutations are only manifested when cells are phenotypically MeCP2hi. In conclusion, our results demonstrate a CNS-specific cellular phenotype of MeCP2 high expression relevant to the pathogenesis of RTT and introduce a powerful new tool for functional genetics.
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MATERIALS AND METHODS |
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TOPABSTRACTINTRODUCTIONRESULTSDISCUSSIONMATERIALS AND METHODSREFERENCES |
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Tissue samples
Human brain samples were either fresh frozen (HBTRC) or fixed in 10% formalin (UCDMC) within 24 h postmortem. Frozen tissues were thawed in 10% formalin and all tissues were embedded in paraffin and sectioned at 5 µm using standard procedures. Multiple human and mouse tissue VastArrays were obtained as a kind gift from Research Genetics (Huntsville, AL).
Immunofluorescence
Slides containing paraffin sections were baked overnight at 56°C, then deparaffinized with four washes in xylene followed by serial dehydration in ethanol. Tissue and epitope exposure was performed by boiling slides in a 1:10 dilution of antigen retrieval solution (DAKO, Carpintena, CA) for 1 h. Anti-MeCP2 C-terminus, rabbit IgG, anti-histone H1, mouse IgG (Upstate Biotechnology, Lake Placid, NY) or anti-MeCP2 N-terminus (Affinity Bioreagents, Golden, CO) were each diluted 1/100 in IF stain buffer (PBS/1% FCS/0.5% Tween-20) and incubated on slides for 1 h, followed by three washes in PBS/0.5% Tween. A Cy5-labeled secondary antibody (donkey anti-rabbit Ig, Jackson Immunochemicals, West Grove, PA) was diluted 1/100 in IF buffer and incubated on slides for 30 min, followed by three washes in PBS/0.5% Tween. For combined immunofluorescence and Nissl staining, slides were stained as above until the secondary antibody step where a 1/100 dilution of FITC-labeled donkey anti-rabbit Ig (Jackson Immunochemicals) and a 1/200 dilution of NeuroTrace 640/660 deep-red fluorescent Nissl stain (Molecular Probes) were added to slides for 30 min, followed by three washes in PBS/0.5% Tween. Slides were mounted in a 50% glycerol solution containing 1 µg/ml PI and 2M DABCO, coverslipped and sealed with nail polish.
Laser scanning cytometry
Slides stained for anti-MeCP2 and negative control were scanned with a 20x objective with both Argon and HeNe lasers on an LSC (CompuCyte, Cambridge, MA) equipped with filters for red (640 DRLP/600 DF60), green (555 DFLP/530 DF30), and long red fluorescence (650 EFLP). Settings for voltage, PMT, and threshold setting were identical between negative control and experimental samples. Data including red (PI) and long red (Cy5) maximum pixel values, x and y position, and area was recorded and analyzed for each scan. Contoured events containing autofluorescent signals were removed by gating out all events with equal max pixel values in both red and green channels. Large cell clusters were removed by gating single cells on the area versus red max pixel scattergram.
Wide-field fluorescence microscopy and image analysis
Slides were analyzed on an Axioplan 2 fluorescence microscope (Carl Zeiss, NY) equipped with a Sensys CCD camera (Photometrics, Tucson, AZ), appropriate fluorescent filter sets and automated xyz stage controls. The microscope and peripherals were controlled by a Macintosh Power Mac 9600/400 running IPLab Spectrum (Scanalytics, Vienna, VA) software with Multiprobe, Zeissmover and 3D extensions. Images were captured with red and long red filters at one edge of the specimen, then repeated at 0.4 µm sections through the depth of the tissue (3–5 µm). Each image stack was digitally deconvolved to remove out-of-focus light using HazeBuster software (Vaytek, Fairfield, IA).
MECP2 mutation analysis
Genomic DNA was isolated from all brain samples using the PureGene kit (Gentra Systems, Minneapolis, MN) and tested for MECP2 mutations by sequence analysis as described previously (29). Total RNA was isolated from fresh frozen RTT brain samples by Trizol reagent (Gibco, Grand Island, NY) and treated with 1 U RNase-free DNAse (Ambion, Austin, TX). Reverse transcription (RT) was performed using oligo-dT and the Superscript preamplification system (Gibco). cDNA was amplified with primers (forward, 5'-CTAAAGTGGAGTTGATTGCGTACT-3'; and reverse, 5'-GGCCTCAGCTTTTCGC-3') at 94°C for 30 s, followed by 35 cycles of 94°C for 30 s, 58°C for 30 s, 72°C for 30 s and final elongation at 72°C for 2 min. Genomic DNA was amplified using the same conditions except 30 cycles of amplification. PCR products were digested with HphI and analyzed by 10% PAGE.
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ACKNOWLEDGEMENTS |
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We thank P.Hagerman, R.Hagerman and M.Seldin for critical reading of the manuscript. This work was supported in part by the National Institutes of Health (1R21CA78851-01), the March of Dimes (Basil O’Connor Award, FY98-743) and the Rett Syndrome Research Foundation. Tissue was obtained from the Harvard Brain Tissue Resource Center, which is supported in part by PHS MH/NS 31862.
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FOOTNOTES |
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+ To whom correspondence should be addressed. Tel: +1 530 754 7598; Fax: +1 530 752 8692; Email: jmlasalle@ucdavis.edu
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REFERENCES |
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