Mecp2 deficiency leads to delayed maturation and altered gene expression in hippocampal neurons

Statistical analyses

All statistical analyses were performed using unpaired, two-tailed, Student's t-test and in all figures, the data bars and error bars indicate mean ± standard error (s.e.m).

Isolation and in vitro analyses of adult NSCs

Isolation of adult NSCs was performed based on the published method (Zhao et al., 2003). Briefly, forebrains without olfactory bulb and cerebellum (4 mice/ genotype, age- and sex-matched) were dissociated mechanically followed by enzymatic digestion using PPD (2.5 U/ml papain, 1U/ml DNAseI, and 200 mg/100 ml Dispase II) in DMEM high glucose (Cellgro, Herndon, VA). After filtering through a 70-μm cell strainer (BD Falcon, San Jose, CA), a single cell suspension was loaded onto 50% percoll. The NSCs were separated from other cells by ultracentrifugation at 127 krpm for 30 min at 20°C using a SW41 rotor (Beckman, Fullerton, CA). The fraction containing NSCs (immediately above the red blood cell layer in the gradient) was collected, washed with PBS, and plated in N2 medium (DMEM/F12 1:1 containing N2 supplement (Invitrogen, Carlsbad, CA) supplemented with 20 ng/ml FGF-2 and 20 ng/ml EGF in a 5% CO₂ incubator. Cell proliferation analyses were performed as described (Lie et al., 2005). Briefly, BrdU was added to the culture medium at 5 μM for 16 hours, followed by fixation using 4% PFA. Cells were then stained with antibodies against BrdU (1:500, Accurate Chemicals, Westbury, NY) and Ki67 (1:1000, NovoCastra Laboratories, Newcastle upon Tyne, UK) and 10 μg/ml DAPI. The percentage of BrdU⁺ cells or Ki67⁺ over total DAPI⁺ cells indicates the percentage of cells that are proliferating. For in vitro differentiation analysis, cells were incubated in N2 media containing 1 μM forskolin, 1 μM all-trans retinoic acid and 0.5% FBS for 7 days. Cells were then fixed by 4% PFA, followed by immunocytochemical analysis as described previously (Zhao et al., 2003). Primary antibodies used were: rabbit anti-type III β-tubulin (1:4000, Covance, Berkeley, CA), RIP (1:50, Hybridoma Bank, Iowa City, Iowa), s-100β (1:1000; Sigma-Aldrich, St Louis, MO), and all secondary antibodies (Jackson ImmunoResearch, West Grove, PA) were used in 1:250 dilution. Cell phenotypes were analyzed using an Olympus BX51 Research microscope equipped with epifluorescence, an optronics microfire digital color camera, and StereoInvestigator software (MicroBrightField). Cell counting was performed using an optical fractionator sampling design and formula (Gundersen et al., 1988). Four independent experiments (each had triplicates), using similar passages of cells, were performed for in vitro proliferation and differentiation assays.

In vivo neurogenesis analyses

In vivo neurogenesis analyses were performed essentially as described previously (Zhao et al., 2003). Briefly, in 8-week-old mice (11 WT and 8 KO), BrdU (50mg/kg) was injected daily for 7 consecutive days to increase the amount of labeling. In 4-week-old mice (6 WT and 9 KO), BrdU was injected once daily for 4 consecutive days. Mice were then euthanized 1 day post-injection to assess proliferation (and early survival) of labeled cells. For cell survival analysis, mice injected at 4 weeks of age (6 WT and 9 KO, 1 injection/day for 4 days) were euthanized 4 weeks post-injection. For immunohistological analysis, 1-in-6 serial floating brain sections (240 μm apart) were performed based on the published method (Zhao et al., 2003). The primary antibodies used were: rat-anti-BrdU (1:500; Accurate Chemicals), mouse anti-NeuN (1:5000; Chemicon International, Temecula, CA), rabbit anti-S-100β (1:500; Sigma), and chicken anti-Mecp2 (1:5000, a generous gift from Dr. Janine LaSalle University of California, Davis). Fluorescent secondary antibodies were used at 1:250 dilutions (donkey, Jackson ImmunoResearch). After staining, sections were mounted, coverslipped, and maintained at 4°C in the dark until analysis. BrdU-positive cells in the granule layer were counted using unbiased stereology (StereoInvestigator, MicroBrightField) with a 5-μm guard zone as described elsewhere (Zhao et al., 2003). DG volume and cell density determinations were performed as described (Zhao et al., 2003). Phenotype analysis of BrdU⁺ cells was performed as described previously (Zhao et al., 2003). Briefly, 50 BrdU⁺ cells in the DG were randomly selected and their phenotypes (double labeling with either NeuN, S100β, or neither) were determined using a Zeiss LSM510 laser scanning confocal microscope. The data were analyzed using a Student's t-test (Graphpad software, www.graphpad.com).

Quantification of mature, immature, and “transitioning neurons” in the DG

This procedure was performed based on the published method (Brown et al., 2003). Briefly, 40-μm thick coronal tissue sections containing hippocampus were stained with antibodies against DCX (1:1000, goat, Santa Cruz), NeuN, and DAPI. The immunofluorescence signals were captured using a spinning disk confocal microscope (Nikon Eclipse TE2000-U, 40x oil,1.2 NA). Quantification was done by a person who was blind to the genotypes of the mice. The numbers of NeuN⁻/Dcx⁺, NeuN⁺/DCX⁺, NeuN⁺/DCX⁻, and cells were quantified by examining z-stacks taken at 1-um intervals using MetaMorph imaging software (Molecular Devices Inc., Sunnyvale, CA). A total of 5 WT and 6 KO mice for the 4-week time point and 8 WT and 5 KO mice for the 8-week time point were used. Three z-stacks were taken from each animal and 6 image planes per optical stack were used for quantification.

Immunohistological analyses and quantification of synaptophysin

Staining and analyses of synaptophysin immunoreactivity were performed according to published method (Li et al., 2002). Briefly, 40-μm thick brain sections were incubated in primary antibody against synaptophysin (rabbit, 1:100; Zymed, San Francisco, CA), followed by biotinylated secondary antibody (donkey anti rabbit IgG; 1:250; Jackson ImmunoResearch), then incubated in ABC reagent (VECTASTAIN ABC Kit, Vector Laboratories) and detected by diaminobenzidine (DAB Substrate Kit, Vector Laboratories, Burlingame, CA). The sections were then thoroughly washed, mounted, air dried, and coverslipped with Permount (Biomedia Corp., Foster City, CA). Sections incubated with normal rabbit IgG instead of a primary antibody (Sigma-Aldrich) were used as negative controls. Optical density analysis of synaptophysin staining was performed by placing 10 circles in each region using Image-J software, as described elsewhere (Li et al., 2002). To categorize the clustered staining pattern, 63X (Zeiss Axioscope, NA = 1.4) images of brain sections were used. Images were captured at 1300 pixels x 1030 pixels using Slidebook software (Intelligent Imaging Innovations, Denver, CO). Using Image-J (NIH) image analysis software, a threshold value was determined for positive staining and remained the same throughout the data analysis. Large clusters were determined to be clusters greater than 300 pixels² and were quantified using the “Analyze Particles” function of Image-J. Sections with 0-5 “large clusters” in the molecular layer of the hippocampus were placed into category 1, and sections with greater than 5 “large clusters” were placed into category 2. The experimenter was blind to the genotypes of the sections. The number of large clusters in each category was counted for each genotype and age group and the data were used to create Figure 3e.

Retroviral grafting

Production of CAG-eGFP retrovirus and in vivo grafting into the DG of mice were performed as described elsewhere (Zhao et al., 2006). Briefly, CAG-eGFP plasmid was co-transfected with packaging plasmids pCMV-gag-pol and pCMV-Vsvg into HEK293T cells and the medium containing virus was collected, filtered, and concentrated using ultracentrifugation. For in vivo grafting, 4-week-old mice were anesthetized with isofluorane and virus (1.5 μl with titer greater than 5×10⁵/μl) was injected stereotaxically into the DG using the following coordinates relative to bregma: anteroposterior, −(1/2) x d mm; lateral, −1.8 mm (if d > 1.6) or −1.7 mm; ventral, −1.9 mm (from dura). Four weeks after injection, mice were deeply anesthetized with pentobarbital and perfused with saline followed by 4% PFA.

Immunohistochemistry and dendritic spine density analyses

1-in-3 floating brain sections containing eGFP⁺ cells (120 μm apart, approximately 8 brain sections) were used for immunohistological staining using a protocol described elsewhere (Zhao et al., 2003). The primary antibody used was rabbit anti-GFP (Invitrogen, Eugene, OR). Briefly, for spine quantification, a minimum of 12-15 images of dendritic fragments were taken at 25-100 μm from the cell body of each eGFP⁺ neuron using a confocal microscope with an oil immersion objective (100x; NA = 1.3; Zeiss). Z-stacks at 1 μm intervals were taken and merged for a maximum intensity projection. For quantification of dendritic spines, protrusions were counted along 10 μm long dendrite segments measured using Image-J software (NIH Image). The “dendritic spine density” result was calculated as number of spines per 10 μm length of dendrite. A minimum of 40 dendritic fragments (10-μm each) from a minimum of 4 eGFP⁺ neurons were quantified from each animal. At least 3 animals from each genotype were analyzed and the final results were compared using a Student's t-test. The apposition of immunostained presynaptic boutons with eGFP-expressing postsynaptic spines was determined according to a published method (Belichenko et al., 2004). Briefly, the presynaptic terminal (synaptophysin⁺) and postsynaptic spine (eGFP⁺) were defined as apposed when there was an overlap between pre- and postsynaptic elements, or when these elements were separated by no more than one pixel (0.1 μm).

Laser Capture Microdissection (LCM) and gene expression analyses

LCM, amplification by in vitro transcription, and probe labeling were performed using a highly reproducible protocol that has been adapted and optimized to analyze gene expression profiles using as little as 5ng total RNA (Phillips and Eberwine, 1996) (Dr. FH Gage, unpublished). Briefly, 4 KO and 4 WT mice (8 weeks of age) were used. Brains were rapidly removed from the cranium and flash-frozen in OCT mounting medium (TissueTek, Sakura Finetek, Torrance, CA) in a dry ice-isopentane slurry and stored at −80°C. The day before LCM, 12 μm sections of brain were generated, stained with cresyl violate, and dehydrated. The granule cell layers of DG were captured using an Arcturus PixCelII LCM microscope (Arcturus Bioscience Inc., Mountain View, CA). An example is shown in Figure 5. LCM was performed at a power level between 25 and 45 mV, between 2 and 20 ms duration, and at a median spot size setting. A minimum of 30 brain sections (less than half of the sections generated from each brain) were used to capture sufficient DG neurons for this study. Captured tissue was dissolved in cell lysis buffer in the MicroRNA kit (Stratagene, San Diego, CA) for 2 to 5 minutes immediately after capturing. Total RNA was isolated from cell lysate using a MicroRNA kit (Stratagene), and approximately 20 ng total RNA was obtained. Half of the sample was used to quantify RNA using a Ribo Green kit (Invitrogen). Finally, 10 ng total RNA was amplified using 3 rounds of a MessageAmep kit (Ambion, Austin, TX). During the last round, RNA was labeled with biotin (Enzo kit, Affymetrix, Santa Clara, CA), purified, and quantified. Biotin-labeled cRNA (30 μg) was fragmented and hybridized to Affymetrix U430 arrays (Affymetrix). Analysis of microarray data was performed using three distinct software programs as described in our previous publication (Barkho et al., 2006). Briefly, the data were pre-processed using the Affymetrix Microarray Analysis Suite (MAS) 5.0 and subsequently analyzed using dChip (Li and Wong, 2001), Drop Method (Aimone and Gage, 2004), and the algorithms of RMA (Tusher et al., 2001; Irizarry et al., 2003). The combination of these methods has been shown to reduce both false positives and false negatives (Aimone et al., 2004; Barkho et al., 2006). Specifically, for dChip, we selected genes that passed with 90% confidence and had a fold change greater than 1.2. For the Drop method (the PM-only, and PM-MM are considered as one method), we selected genes that passed with a confidence of 70%. For RMA, a fold change had to meet the criteria of being greater than 1.2 and have a false discovery rate (FDR) less than 30%. The FDR value used for RMA was based on the Significance for Analysis of Microarrays software (SAM) (Tusher et al., 2001). Only genes identified by all three software programs were included as differentially expressed genes and are listed in Table 1.

Impaired maturation of Mecp2-deficient neurons

Despite the overall similar numbers of immature neurons in the DG of KO and WT mice, we noticed clear abnormalities in the neurite outgrowth from Mecp2-deficient immature neurons (Fig 1R and S). In the DG of WT mice, the cell bodies of the DCX⁺ neurons were typically located in the subgranular zone (SGZ) of the DG adjacent to the hilar region, with their processes perpendicularly extended through the granule cell layer (GCL) and exited into the opposite molecular layer (Fig 1N-P, arrowhead) (Brown et al., 2003; Rao and Shetty, 2004; Rao et al., 2005). In contrast, the processes of most DCX⁺ neurons in the DG of Mecp2 KO mice were found to traverse nearly parallel along the hilar boundary of the DG (Fig 1Q-S, arrowhead). This morphological difference might reflect impaired maturation because since horizontal and short processes are characteristic features for new neurons at early stage of differentiation (Esposito et al., 2005; Ge et al., 2006; Zhao et al., 2006). Because the majority of the DG granule neurons are generated during postnatal development, we exploited the possibility that this deficit was widespread in the developing DG. We therefore compared the ratio of NeuN⁺ mature and DCX⁺ immature neurons in the DG of Mecp2 KO and WT mice at two different ages: when the DG had just past the peak of primary cell genesis (4 weeks of age) and when DG had reached the adult level of maturity (8 weeks of age) (Fig 2A-G) (Mullen et al., 1992). Furthermore, we quantified the number of cells positive for both NeuN and DCX to distinguish the cells that were transitioning from an immature to a mature phenotype and to provide an additional index of this developmental maturation process (Fig 2E-G). Quantitative analysis of confocal images was used to determine the percentage of neurons in each maturation stage (Fig 2A-G, DCX+/NeuN-; DCX⁺/NeuN⁺; DCX^-/NeuN⁺) in both the KO and WT DG. The results summarized in Figure 2H show that whereas neither 4- nor 8-week-old Mecp2 KO mice displayed significant differences in the percentage of mature or immature neurons compared to WT mice, the DG of 8-week-old Mecp2 KO mice had a significantly higher percentage of “transitioning neurons” (p<0.001). In fact, comparison of the number of “transitioning neurons” (DCX⁺/NeuN⁺) among total neurons showed that maturation from juvenile (4 weeks) to young adult (8 weeks) was accompanied by a 75 % decrease in the percentage of “transitioning neurons” in normal WT brain but only a 44% reduction in the KO brains (Fig 2I, p<0.0001). In addition, comparison of the number of “transitioning neurons” (DCX⁺/NeuN⁺) and total immature neurons (both DCX⁺/NeuN⁻ and DCX⁺/NeuN⁺) showed that maturation from a juvenile (4 weeks) stage to a young adult (8 weeks) stage was accompanied, in the normal WT brain, by a 28.5% decrease in the percentage of “transitioning neurons” among the total population of DCX⁺ neurons (Fig 2J). However, the age-dependent reduction of this subpopulation of double positive “transitioning neurons” among total immature neurons did not occur in Mecp2-deficient mutants; but rather there was a 26.9% increase in the percentage of these neurons during this developmental time period (Fig 2J, p<0.0001). This finding may indicate that the deficiency in Mecp2 may have led to DCX⁺/NeuN⁺ double positive “transitioning neurons” being held up and failing to differentiate into more mature DCX⁻/NeuN⁺ neurons.

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Figure 2

Immature neurons in the DG of Mecp2 KO mice have delayed transitioning to mature stage

(A-D) Confocal images showing DG of the hippocampus labeled with antibodies against NeuN (A, green, mature neurons), DCX (B, red, immature neurons), and DAPI (C, blue, nuclear dye). Scale bars=100 μm. (D) Merged image of A-C. (E-G) Higher magnification images of granule neurons and examples of neurons that are NeuN⁺DCX⁻ (asterisk) and NeuN⁺DCX⁺ (arrowhead). Scale bars=10 μm. (H) Quantitative analyses indicate the percentage of mature neurons (NeuN⁺DCX⁻, white bar), immature neurons (DCX⁺NeuN⁻, light gray) and “transitioning neurons” (NeuN⁺DCX⁺, dark gray) in 4-week-old and 8-week-old mice. (I) Age-dependent changes in the proportion of “transitioning neurons” over total neurons are significantly different between KO and WT mice (p<0.0001), (J) The percentage of “transitioning neurons” among total DCX⁺ neurons are also significantly different between WT and KO mice at both 4 and 8-weeks-old. While WT mice exhibited an age-dependent decrease in the proportion of “transitioning neurons” over total DCX⁺ neurons, KO mice displayed an increase (p<0.0001), suggesting more neurons are stalled at the transitioning stage in the KO brains.

Impaired expression of developmentally regulated presynaptic proteins in Mecp2-deficient hippocampus

Because synaptogenesis is a crucial step for the maturation and integration of newborn neurons into the preexisting circuitry of the hippocampus, we investigated whether KO mice have deficits in synapse formation. For this purpose, we used an antibody against synaptophysin, a synaptic vesicle protein whose expression is known to reflect the distribution and density of presynaptic terminals (Li et al., 2002). We focused on the molecular layer of the hippocampus, where DG granule neuron dendrites receive input from perforant path axons from the entorhinal cortex (Henze et al., 2000). Overall, no consistent difference was found in optical density measurements of synaptophysin immunostaining between 4- and 8-week-old WT and KO mice suggesting that the level of expression, and thus the number of nerve terminals, was not affected by the lack of Mecp2. However, we did observe two patterns of synaptophysin immunoreactivity in both WT and KO mice: highly distributed small positive spots (<300 pixels², Fig 3C, arrowheads), and “large clusters” (>300 pixels², Fig 3C and 3D, arrows) that appeared to vary in density in different brain regions. To quantify the distribution of these large clusters and determine whether they might differentiate between the synaptic density of WT and KO hippocampus, we analyzed the number of “large clusters” (determined by Image-J quantitative software) found in the molecular layer, where dendrites of granule neurons form synapses. We found no significant difference in the number of large clusters in either 4-week-old or 8-week-old KO mice compared to their age-matched WT littermates (Fig 3E). However, when WT mice mature from 4 to 8 week of age, there was an 82.6% decrease in the number of large synaptic clusters in the molecular layer of the hippocampus (4-week, 18.29 ± 4.74, n = 14 mice; 8-week, 3.19 ± 1.10, n = 13 mice; P < 0.01), but such an age-dependent change was absent in KO mice (P = 0.48), suggesting a failure in dispersing these large clusters into a more uniform distribution of presynaptic terminals in the absence of functional Mecp2.

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Figure 3

Mecp2 KO mice have altered presynaptic protein expression pattern

(A-C) Digitized bright-field micrographs show synaptophysin immunoreactivity in the adult and young mice. Scale bar=100 μm. (A) The box indicates the region that is enlarged in C and D. (B) Sections were incubated with normal rabbit IgG, instead of synaptophysin antibody, as a negative control. (C) Example of a brain section with small synaptophysin positive spots (arrowheads) and two large clusters (arrows). scale bar=10 μm. (D) The output of particle analysis of (C) produced by Image-J showing the two large clusters (arrows). (E) Number of large clusters in 4- and 8-week-old WT mice (**P < 0.01) compared to 4- and 8-week-old KO mice. Note that WT animals showed a clear age-dependent reduction in the density of large synapse clusters, whereas KO failed to show this developmental change.

Altered dendritic spine distribution in Mecp2-deficient mutant neurons

As neurons mature the density of dendritic spines increases (Ge et al., 2006; Zhao et al., 2006). Consequently, reduced dendritic density is a common characteristic of the abnormal synaptic development seen in a variety of neurological disorders (Fiala et al., 2002). To clarify the current discrepancy in the literature and determine whether Mecp2 mutations affect dendritic spine development, we decided to analyze the morphology of individual Mecp2-deficient neurons in vivo. Because the persistent, albeit low level, of postnatal neurogenesis in the DG allowed us to trace the maturation of single new neurons, we performed detailed morphological analyses to investigate the maturation of these newly generated neurons in the Mecp2-deficient mice. Recombinant retroviruses, which are only capable of infecting dividing cells, have been previously used to label and follow the differentiation of NSCs in postnatal DG (van Praag et al., 2002; Ge et al., 2006; Zhao et al., 2006). We therefore injected recombinant retrovirus expressing enhanced green fluorescence protein (eGFP) under a chicken actin promoter (CAG-eGFP) (Zhao et al., 2006) into 4-week-old KO and WT mice and analyzed the morphology of new neurons after 4 weeks, a time when labeled new neurons would be expected to develop the dendritic morphology of fully mature neurons (van Praag et al., 2002; Ge et al., 2006; Zhao et al., 2006) (Fig 4A). As shown in Figure 4B-E, whereas most of the eGFP⁺ neurons expressed the mature neuronal marker NeuN, a few of them also expressed DCX, indicating NSCs that had not yet reached a fully matured state. To quantify the density of synapses, we counted the number of spines within each 10-μm segment of dendrites imaged by high-resolution confocal microscopy. Quantitative analyses indicated that the spine density of eGFP⁺ neurons in the DG of Mecp2 KO mice was significantly reduced compared to WT mice (Fig 4J, WT= 13.46 ± 0.31, KO= 11.41 ± 0.11; P < 0.005). Because the formation of functional synapses requires apposition of presynaptic terminals and postsynaptic spines, we asked whether the postsynaptic spines of eGFP⁺ neurons in the DG of KO mice were adjacent to synaptophysin-positive presynaptic terminals. As shown in Figure 4K and L, similar percentages of eGFP⁺ spines in WT and Mecp2 KO mice were apposed to synaptophysin–positive presynaptic terminals. These data indicate that, at the single neuron level, while newly matured neurons in Mecp2-deficient mice are able to form synaptic contacts, the number of these synapses is greatly diminished.

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Figure 4

Newly matured neurons in Mecp2 KO hippocampus have reduced dendritic spine density and abnormal distribution

(A) Schematic diagram demonstrating stereotaxic grafting of CAG-eGFP retrovirus into the DG of 4-week-old KO and WT mice to label dividing neuroprogenitors in the germinal zone of the DG. At 4 weeks post grafting, many eGFP⁺ cells had differentiated into NeuN⁺ (B, C, D, arrowheads) and/or DCX⁺ (E) new neurons. (F, G) High resolution image of dendrites of eGFP⁺ neurons were used to quantify the density of dendritic spines (number of spines/10 μm dendrites) to generate the data in (H-J). (G) High magnification view of the box in F. Scale bars in F and G=10 μm. (J) New neurons in KO brains had reduced dendritic spine density (P<0.005, n=3 t-test). (H, I) Frequency distribution data indicate higher variation in spine density in KO mice (I) than in WT mice (H), indicating an uneven distribution of spine density. (K) Z-stack confocal image showing apposition of presynaptic terminal marker synaptophysin (red, arrow) with eGFP⁺ spines of new neurons. (L) Quantitative analyses indicating that similar percentages of eGFP⁺ spines were apposed to presynaptic terminals in both WT and Mecp2 KO mice (p=0.33, n=3, t-test)

Images in this paper were generated in the University of New Mexico Cancer Center Fluorescence Microscopy Facility, supported as detailed on the webpage (http://hsc.unm.edu/crtc/microscopy/facility.html ). We thank R. Lee and G. Phillips for technical assistance. We thank Dr L.A. Cunningham for advice in stereotaxic grafting. We thank L.C. Tafoya, and Drs. M.C. Wilson, C.F. Valenzuela, P. Jin, X. Li, and H. van Praag for critical reading of the manuscript and helpful comments. We thank M.L. Gage and S.M. Wimberly for editorial assistance. This work was funded by research grants from RSRF, IRSA, Oxnard Foundation, Autism Speaks, NIH/NCRR/COBRE, and funds from UNM School of Medicine.