Na+/H+ exchanger 1 (NHE1) is well known to function as a major regulator of intracellular pH (pHi). It is activated by low pHi and exchanges extracellular Na+ for intracellular H+ to maintain cellular homeostasis. Despite the fact that we now have evidence suggesting other roles for NHE1, there has been no comprehensive study investigating its role as a signaling molecule. Toward this aim, we used in this study NHE1 null mutant mice and cDNA microarrays to investigate the effects of NHE1 on global gene expression in various regions of the brain, e.g., cortex, hippocampus, brain stem-diencephalon, and cerebellum. We found that a total of 35 to 79 genes were up- or downregulated in each brain region, with the majority being downregulated. The effect of NHE1 null mutation on gene expression is region specific, and only 11 genes were changed in all brain regions studied. Further analysis of the cis-regulatory regions of downregulated genes revealed that transcription suppressors, BCL6 and E4BP4, were probable candidates that mediated the inhibitory effect of NHE1 null mutation. One of the genes, MCT-13, was not only downregulated in the NHE1 null mutant brain but also in tissue cultures treated with an NHE1 inhibitor. We conclude that 1) a relatively small number of genes were altered in the NHE1 null mouse brain; 2) the effects of NHE1 null mutation on gene expression are region specific; and 3) several genes implicated in neurodegeneration have altered expression, potentially offering a molecular explanation for the phenotype of the NHE1 null mouse.
- NHE1 null mutation
- gene expression profile
the Na+/H+ exchanger 1 (NHE1) is a ubiquitous mammalian plasma membrane protein and is considered an important “housekeeping” protein. NHE1 is activated by low intracellular pH (pHi) to catalyze the exchange of Na+ and H+ across the cell membrane (27, 30). In the past several years, however, NHE1 protein has also been shown to interact with scaffold proteins and affect cell migration and proliferation (11, 17, 25). Animals carrying deficient NHE1 either by spontaneous mutation or by gene targeting exhibit an ataxia and seizure phenotype (3, 9). In addition, it has been shown in fibroblast cultures that alteration of NHE1 function delayed cell cycle and altered the expression level of cell cycle proteins (26). Furthermore, we have shown that the expression level of several pH-regulatory transporters, such as NHE3, the electrogenic sodium-bicarbonate cotransporter 1 (NBCe1), and brain-specific anion exchanger 3 (AE3), were all altered in selected brain regions of the NHE1 null mutant mice (32). In the present study, high-throughput cDNA microarray technology and bioinformatic analysis were used to determine, on a large scale, the effect of NHE1 deficiency on gene expression in different brain regions in a spontaneous NHE1 mutant mouse strain.
MATERIALS AND METHODS
Animals and tissue preparation.
Heterozygote slow-wave epilepsy (B6SJL, +/swe) mice were obtained from Jackson Laboratories (Bar Harbor, ME) (9). Mice were mated in our institution, and homozygote (swe/swe) NHE1 mutant F1 progenies were used at postnatal ages between 20 and 21 days. All animal procedures were performed in accordance with the guidelines provided by the Animal Care Committee of Albert Einstein College of Medicine of Yeshiva University, which is accredited by the American Association of Laboratory Animal Care. The homozygote mutant mice were initially selected by phenotype and confirmed subsequently by PCR-based genotyping (33). Besides epilepsy, the phenotype is characterized by apparent locomotor ataxia and slow, wide-based gait with coarse truncal instability starting at ∼2–3 wk of age, as previously described (31). The animals were decapitated after halothane anesthesia, and brains were rapidly removed. Four brain regions (cortex, hippocampus, brain stem-diencephalon, and cerebellum) were quickly separated on ice, flash-frozen in liquid nitrogen, and stored at −80°C till use.
Total RNA purification, mRNA amplification, and probe labeling.
Total RNA was extracted from frozen tissue using the TRIzol reagent (Life Technologies, Grand Island, NY) followed by a cleanup with RNeasy kit (Qiagen, Valencia, CA). A linear amplification strategy based on cDNA synthesis and in vitro transcription was applied with minor modifications (2). Briefly, 3.0 μg total RNA was converted into double-stranded cDNA (ds-cDNA) with an oligo-dT primer containing a T7 RNA polymerase promoter (Qiagen). The ds-cDNA was extracted with Ultrapure phenol:chloroform:isoamyl alcohol (25:24:1) (Invitrogen, Carlsbad, CA). The supernatant was collected, 5.0 μg linear polyacrylamide (LPA; Sigma, St. Louis, MO) was added, and the ds-cDNA and LPA in the supernatant were precipitated with 95% ethanol at −20°C. Amplified RNA (aRNA) was synthesized by in vitro transcription using T7 polymerase and purified with RNeasy affinity column (Qiagen).
Microarray probes were labeled by direct incorporation of fluorescent nucleotide analogs during a reverse transcription reaction. aRNA (4.0 μg) was used in a random-primed reaction in the presence of 100 μM Cy3- or Cy5-dUTP (Amersham Biosciences, Piscataway, NJ), 200 μM dTTP, and 500 μM dATP, dCTP, and dGTP (Roche Molecular Biochemicals, Mannheim, Germany). The labeled cDNA probes were purified with QIAquick PCR purification kit (Qiagen, Valencia, CA).
Microarray slides containing the National Institute on Aging (NIA) mouse 15K cDNA clone set were purchased from the YCC/HHMI Biopolymer/Keck biotechnology resource laboratory at Yale University. The hybridization was carried out according to user instructions. Briefly, labeled cDNA probes were resuspended in hybridization solution, consisting of 62.8% formamide, 5× SSPE, 0.8% SDS, and 4× Denhardt solution, to which 1 μl poly(dA) at a concentration of 10 μg/μl and 1 μl mouse CotI DNA at a concentration of 20 μg/μl were added. The final volume of hybridization solution was 36 μl. The hybridization solution was denatured at 90°C for 2 min and snap-cooled on ice. Hybridization took place under a coverslip at 42°C overnight. Slides were washed at room temperature with 2× SSC/0.1% SDS for 10 min, 0.2× SSC/0.1% SDS for 10 min, and two times with 0.2× SSC for 10 min.
Image acquisition and data analyses.
Fluorescence intensities of Cy3 and Cy5 were measured separately at 532 nm and 635 nm with a laser scanner (GenePix 4000B; Axon Instruments, Union City, CA). The images were analyzed with GenePix Pro3.0 (Axon Instruments). Local background was subtracted from the fluorescent value of each spot to obtain a net value. The low-intensity spots were eliminated by filtering out the data either not having >75% of the pixels >2 standard deviations above the background signal or having a diameter of the spot less than 10 μm. The variability of sample values was determined by calculating the correlation coefficient for each gene on the array for all repeated samples. To identify genes whose expression differed in the mutant mouse, the log2 transformation of the ratio of mutant to wild-type median value for each brain region was used. The five slides representing three different RNA pools for each experiment were grouped together and treated as replicates. Variations among experiments were normalized by normalizing the ratios (mutant vs. wild type) from each replicate experiment to 1.0. A Student’s t-test was then performed to calculate whether the mean relative intensity for a gene was statistically different from 1.0 (21). The average values of standard deviation in each experimental group were used to determine the cutoff values for up- or downregulated genes. The value of three times standard deviations was set up as a criterion for gene selection. Genes were considered differentially expressed if they were present in at least two of three replicate experiments and were statistically significantly different (P < 0.05) from the wild-type controls.
Primary cortical neuronal and astrocytic cultures and treatments.
Primary cortical neuronal cultures were prepared from embryonic day 16–17 mice (Charles River CD-1 strain) as previously described (34). In brief, mice were decapitated, and cortical tissue was collected, minced, and dissociated with trypsin (0.25 mg/ml in Hanks’ balanced salt solution without Ca2+ and Mg2+) at 37°C for 10 min. Trypsin activity was stopped by trypsin inhibitor. Then the cell mixture was centrifuged at 1,400 rpm for 5 min at 4°C. The cell pellet was resuspended in serum-free neurobasal medium supplemented with B-27, 0.5 mM glutamine, 25 μM glutamate, 50 μg/ml penicillin, and 50 μg/ml streptomycin (GIBCO-BRL; Invitrogen) and passed through 80-nm mesh. Cells were plated at 1 × 106 cells/ml on poly-d-lysine-coated (0.1 mg/ml; Sigma) plates. Cultures were maintained in a humidified atmosphere of 95% air and 5% CO2 at 37°C. Half of the medium was replaced with fresh medium without glutamate every 3 days.
Primary cortical astrocytic cultures were prepared from postnatal day 1–2 mice (Charles River CD-1 strain) according to McCarthy and de Vellis (22). In brief, mice were decapitated, and cortical tissue was collected, minced, and dissociated with trypsin (0.25 mg/ml in Hanks’ balanced salt solution without Ca2+ and Mg2+) at 37°C for 10 min. Trypsin activity was stopped by trypsin inhibitor. Cell mixture was centrifuged at 1,400 rpm for 5 min at 4°C. The cell pellet was resuspended in Dulbecco’s modified Eagle’s medium (DMEM) with 10% FCS, 5 mM glucose, 50 μg/ml penicillin, and 50 μg/ml streptomycin (GIBCO-BRL) and passed through 80-nm mesh. Cells were plated at 2 × 105 cells/ml on poly-d-lysine-coated (0.1 mg/ml; Sigma) plates. Cultures were maintained in a humidified atmosphere of 95% air and 5% CO2 at 37°C. Half of the medium was replaced with fresh medium every 3 days.
Primary cultures were treated with hypoxia, acidosis, or NHE1 inhibitor individually on culture day 14 for neurons and day 21 for astrocytes. Hypoxia treatment was induced by incubating the cells at 37°C for 48 h in an incubator equipped with an air lock and continuously gassed with nitrogen and 5% CO2 to keep the oxygen level at 1%. Acidosis was induced by replacing the neutral culture medium with pH 6.8 medium for 48 h. For the NHE1 inhibitor treatment, HOE-694 (gift from Dr. Hans-J. Lang; Aventis Pharmaceuticals, Frankfurt, Germany) was added to the culture medium for a final concentration of 100 μM for 48 h. After treatment, cells were rinsed with PBS twice, then harvested in TRIzol reagent (Life Technologies). Total RNA was isolated according to manufacturer instructions for semiquantitative reverse transcription PCR (RT-PCR) analysis.
Real-time PCR and RT-PCR assay.
In real-time PCR experiments, the double-stranded DNA binding dye method was used to measure mRNA levels of selected transcripts. Primers were chosen using Primer3 program (http://www-genome.wi.mit.edu/cgi-bin/primer/primer3.cgi/). All primers were synthesized by Invitrogen (Carlsbad, CA). The nucleotide sequences of the primers are listed in Table 3. Reverse transcription was carried out in a final volume of 20 μl containing 1× RT-PCR buffer, 0.5 mM of each of the deoxynucleotide triphosphates, 5.0 mM MgCl2, 10 mM DTT, 10 U of RNase inhibitor, 50 U SuperScript II reverse transcriptase, 0.5 μg oligo-dT, and 2.0 μg of total RNA. Samples were incubated at 42°C for 50 min, followed by heat inactivation at 70°C for 15 min. Real-time PCR amplification was performed using ABI Prism 7900HT Sequence Detection System (Applied Biosystems, Foster City, CA). For each reaction, 4.0 μl of 2× SYBR green PCR master mix (Applied Biosystems) and 0.5 μM of both forward and reverse primers along with 2.0 μl of each appropriate cDNA samples were mixed. The thermal cycling conditions comprised an initial denaturation step at 95°C for 10 min, 40 cycles at 95°C for 10 s, 60°C for 20 s, and 72°C for 30 s. Melting curves were performed using software SDS 2.0 (Applied Biosystems) to ensure that only a single product was amplified, and the final products were isolated with 4% agarose gel to confirm the specificity. Data analyses were carried out using sequence detection software (SDS 2.0, Applied Biosystems). The threshold cycle (Ct) for each reaction, which is directly related to the amount of starting template in the reaction, was calculated. A difference in Ct values (ΔCt) was then calculated for each gene by taking triplicate Ct values from three reactions and subtracting the mean Ct of the triplicates for the control gene (β-actin) for each cDNA sample at the same concentration. An additional difference in ΔCt value (ΔΔCt) was calculated for each gene by taking the triplicate ΔCt values for each gene in the NHE1 mutant animals and subtracting the mean ΔCt value of the triplicates for the wild-type mice. The relative expression level was calculated using the 2−ΔΔCt method, as described previously (13, 20).
For the RT-PCR, primers for monocarboxylate transporter 13 (MCT-13) and β-actin were as follows: MCT-13, forward 5′-CCTCTTGCTAGTGTCTGCCC-3′, reverse 5′-AGTTCAGGAAGCACGGAGAA-3′ (483-bp product); β-actin forward 5′-TGTT-ACCAACTGGGACGACA-3′, reverse 5′-TCTCAGCTGTGGTGGTGAAG-3′ (392-bp product). The GeneAMP PCR system 2700 (Applied Biosystems) was used for the RT-PCR reaction. The reverse transcription was carried out using oligo-dT primer under the condition described previously (35). The PCR amplification of target transcripts was started with a 94°C denature step, then 30 cycles of 94°C for 30 s, 60°C for 30 s, and 72°C for 1 min, finally followed by 72°C for 10 min to ensure the complement elongation of products. The PCR product was isolated with 2% agarose gel electrophoresis.
Computational methods for functional and structural predictions.
To predict the function and structure of target transcripts by computational methods, the corresponding full-length peptide sequences of functionally unknown transcripts were retrieved from Swiss-Prot, followed by searching sequences homology by BLASTp in public databases (http://www.ncbi.nlm.nih.gov/blast) (1). Secondary structure prediction was made from the collated results of the MAXHOM multiple alignments. The methods used for secondary structure and conserved motif prediction were PHD (29), PROSITE (16), and ProDom (7). Parameters for each program provided by PredictProtein server can be found at the web site http://cubic.bioc.columbia.edu/predictprotein. The functional annotation and categorization of significantly altered genes were performed using the database for annotation, visualization, and integrated discovery (http://apps1.niaid.nih.gov/david/) (12).
Transcription factor binding element analysis.
The common transcription factor binding sites in the defined promoter regions of up- or downregulated genes were analyzed using GenomatixSuite (Genomatix Software, Munich, Germany). Since most genes were altered in the cerebellum, and since pathology was apparent in this region, we focused this analysis in this area. The significantly changed genes in the cerebellum were separated into up- or downregulated groups. Functional annotations and the GenBank IDs of their corresponding full-length cDNAs were extracted from the database for annotation, visualization and integrated discovery (http://apps1.niaid.nih.gov/david/) (12). The genes that have nonfunctional annotation and noncorresponding full-length cDNA were eliminated from further analysis. The GenBank full-length cDNA IDs of the up- or downregulated genes were used for promoter analysis by Gene2Promoter software. Only those genes whose transcription start sites (TSS) have been experimentally or computationally identified were included, and their genome DNA sequences from 2,000 bp upstream of their first TSS to 500 bp downstream of their last TSS were subjected to GEMS analysis for common model elements (Supplemental Table S2, available at the Physiological Genomics web site)1 (28).
Experimental strategy and overall analysis.
The main purpose of this study was to identify genes whose expression pattern was altered, directly or indirectly, by the absence of NHE1 protein. Twenty hybridizations were performed in this study, and three independent comparisons between NHE1 null mutant and wild-type brains were made. The average standard deviations (using log2 transformation) from cortex, hippocampus, brain stem-diencephalon, and cerebellum were 0.178, 0.160, 0.134, and 0.159, respectively. Based on this result, the expression ratio above 1.60 or below 0.60 was selected as a cutoff value for deciding on whether genes were significantly up- or downregulated (Supplemental Table S1). We identified a total of 48 genes in the cortex, 47 genes in the hippocampus, and 35 genes in the brain stem-diencephalon that were significantly altered in NHE1 null mutant mice. The highest number of altered genes (79 genes) occurred in the cerebellum. Among all of the identified genes, 11 genes were changed throughout all brain regions examined (Table 1).
Gene expression in response to NHE1 null mutation.
There are different targets of the NHE1 null mutation in different brain regions, and most of the altered transcripts were downregulated in each region. In the cortex, of 48 significantly altered genes, 37 genes were downregulated. Similarly, in the hippocampal region, 39 genes were downregulated out of 47 significantly altered transcripts. The least affected region was the brain stem-diencephalon region, where 28 of a total of 35 genes were downregulated. In the cerebellum, 49 of 79 significantly changed transcripts were downregulated (Supplemental Table S1).
The results from our analysis revealed distinct effects of NHE1 null mutation on gene expression. In the cortex, we categorized those affected genes with known function into two main groups. One group has DNA or RNA binding activity (e.g., Smarcc1, Zfp238, and Rbm3), and the other is related to various signaling pathways (e.g., 14-3-3 protein-γ, lysophosphatidic acid acyltransferase-α, and protein tyrosine phosphatase 4a3). In the hippocampus, the transcripts that were altered were related to multiple signaling pathways (e.g., 14-3-3 protein-ζ, PKC-δ, and jagged 1). In the cerebellum, the altered genes were involved in a variety of biological processes, especially metabolism and cell-cell communication (Table 2). Interestingly, most of the altered genes were not functionally characterized (55% in cortex, 65% in hippocampus, 73% in brain stem-diencephalon, and 64% in cerebellum). Some of the microarray-identified changes were selected for further confirmation using real-time PCR and RT-PCR, with primers specifically derived from full-length mRNA sequences. The results agreed with microarray results very well (Table 3 and Fig. 1).
Response of MCT-13 expression to NHE1 inhibition, hypoxia, and acidosis.
Among the commonly regulated genes (Table 1), the transcript that encodes MCT-13 was significantly downregulated throughout all brain areas studied. Its computational structure and the possible regulatory mechanisms are summarized in Fig. 1. Members of the MCT family are believed to be another transporter system that is involved in pHi regulation. To further explore the relationship between NHE1 and MCT-13 expression as well as the regulation of MCT-13 in different cell types, the expression of this transcript was measured by semiquantitative RT-PCR in primary cortical neuronal and astrocytic cultures under different treatments, including hypoxia (1% oxygen), acidosis (pH 6.8), or NHE1 inhibition (100 μM HOE-694). As shown in Fig. 2, the transcript encoding MCT-13 was detected in both neurons and astrocytes, with a higher expression level in neurons. Although no significant change in MCT-13 expression level was found in response to hypoxia or acidosis, MCT-13 was significantly downregulated by NHE1 inhibition. This is similar to the downregulation of MCT-13 in the NHE1 null mutant mice.
Analysis of BCL6 and E4BP4 binding motifs within cis-regulatory region of downregulated genes in the cerebellum.
To further understand transcriptional suppression caused by NHE1 null mutation, a screen for repressor binding elements was performed in the cis-regulatory region of the downregulated genes. Interestingly, most screened promoter regions contained binding elements for transcriptional repressor BCL6 (6, 15) (11 of 15, Table 4) and/or E4BP4 (8) (10 of 15, Table 5). We scanned the mouse genome, searching the 2,500-bp cis-regulatory region, to examine how common these motifs are in the genome. We further calculated the probability of finding these binding elements randomly at the observed frequency (i.e., 2/3) in the upstream regulatory regions. The promoter regions of 16,734 genes were examined; 133 genes (0.8%) had the BCL6 binding motif (consensus sequence: CNTTTCCTAGAAANNC), and 1,112 genes (6.6%) had the E4BP4 motif (consensus sequence: NRTTAYGTAAYN). Based on these frequencies, the probability (P) of finding a certain binding motif in M genes out of a cluster containing N genes (M ≤ N) in their 2,500-bp cis-regulatory sequence is obtained using a conditional, binomial probability equation (19). For BCL6 binding motif, P is very small and is about 1 × 10−20, and that of E4BP4 is also small and is about 3 × 10−9.
This study was performed on mice carrying a null mutation of NHE1 protein. Although NHE1 is ubiquitously expressed, we chose to study the brain in particular because the manifestations of the phenotypes are related to disturbed brain function, namely, ataxia and a seizure disorder. Previous studies from our laboratory on NHE1 null mutant CA1 neurons focused on measurements of steady-state pHi and response of these neurons to acid load. Despite the fact that NHE1 is a major acid extruder, these neurons did not show major changes in steady-state pHi or in response to lower pHi (33). Hence, we cannot readily explain the phenotype in these mice from these modest functional changes that result from NHE1 as an acid extruder.
Additional studies from our laboratory as well as from others have demonstrated that there are a number of consequential alterations to the NHE1 null mutation. For example, the expression levels of selected pHi regulatory transporters, such as NBCe1, NHE3, and AE3, are altered, and these alterations vary in different brain regions of the NHE1 null mutant mice (32). The AE3 gene was also downregulated in hippocampal samples; however, because of the coverage limitation of the NIA 15K clone set, we were not able to measure NBCe1 and NHE3 in the current microarray study (see data set GSE1013 at http://www.ncbi.nlm.nih.gov/geo). Interestingly, the absence of NHE1 function also delays the S phase and impairs G2/M transition in the fibroblasts. These changes in the mutant have been related to alterations in gene expression of cyclin B1 and Wee 1 kinase combined with a downregulation of cdc2 activity (26). Therefore, we believe that there may be complex interactions between NHE1 and other cellular proteins, and the interruptions of such protein-protein interactions may affect cellular function via, at least in part, regulation of target gene expressions. Indeed, there have been studies showing that NHE1 interacts with other signal transduction proteins and kinases (for review see Refs. 23, 27). Our current studies and results are the first to demonstrate, at a comprehensive level, that the absence of NHE1 protein has major consequences in terms of gene expression.
Our data have revealed three interesting findings. First, there is a relatively small number of genes that are affected by the NHE1 null mutation. Indeed, there are only 11 genes, out of thousands screened, that are affected throughout all brain regions studied (Table 1), suggesting that the effect of NHE1 absence is rather specific. Second, the effects of the mutation on the various brain regions are not uniform. For example, a number of genes are affected in one region but not in another, and vice versa. Change in protein kinase C (δ-isoform) is specific to the hippocampus, but changes in tyrosine hydroxylase and osteopontin are specific to the cerebellum. Third, it is very interesting that most of the altered genes are downregulated, and these vary from 83% of the genes in the hippocampus to 62% in the cerebellum. We raise the question here as to whether the NHE1 protein generally promotes activation rather than suppression of gene expression.
Our results have also demonstrated that there are three genes that are worth highlighting in trying to understand the phenotype of NHE1 null mutation. One of these genes is MCT-13, which was strikingly downregulated to about 20–30% of control levels in all brain regions studied. We believe that this effect on an MCT is important since the activity of MCTs has been shown to be important in terms of distribution of metabolic fuel (e.g., lactate, pyruvate, and ketone bodies) (10, 24). This MCT-13 is present in both neuronal and astrocytic primary cultures (Fig. 2) and responds by a significant downregulation when the cells were treated with an NHE1 inhibitor (HOE-694), a remarkable similarity to the response of MCT-13 in the brain of NHE1 null mice. To clarify whether the downregulation of this gene is a consequence of cellular acidification caused by HOE-694, hypoxia (a condition that can induce metabolic acidification) and direct extracellular acidosis were studied. Since no significant changes were found in the mRNA levels of MCT-13 under these conditions, the downregulation of MCT-13 expression with HOE-694 is likely to be a specific response to NHE1 inhibition but not necessarily related to a drop of pHi, further indicating that a specific functional linkage exists between these two transporters. Another group of genes that is downregulated in the cortex, hippocampus, and cerebellum is the one encoding 14-3-3 proteins (γ- and ζ-isoforms). As a protein family that is abundantly expressed in the brain and has more than 100 binding partners, 14-3-3 proteins are involved in multiple biological processes in the CNS (for review see Ref. 4). Furthermore, 14-3-3 protein directly interacts with NHE1 protein and regulates its activity (23). Last, the transcript encoding secreted phosphoprotein 1/osteopontin (SPP1/OPN) is upregulated, mostly in the cerebellar region, where altered function is reflected in ataxia and where cell death was been shown to occur in the NHE1 null mutant mice (3, 9). The upregulation of the SPP1/OPN transcript would seem to be important since SPP1/OPN is high in brain samples of patients (as well as animal models) with multiple sclerosis and Huntington disease (5, 18).
One question that can be raised about some of our results is whether the alterations in gene expression are related to the absence of NHE1 protein or secondary to the phenotype in the NHE1 mutant mouse (e.g., seizure disorder, ataxia). For example, is it possible that some of theses genetic changes are a consequence of the seizure disorder? We do not believe that these gene alterations result from the phenotype itself for four reasons. First, mice were studied and subjected to gene array analysis before mice showed any frank seizures. Mice were closely observed when they were growing and were checked a number of times each day. Second, in previous studies that we have performed (14, 31), we have shown that Na+ channels were upregulated in neurons, and these were also found before frank seizures were discovered. Indeed, we have previously suggested that it is this upregulation in Na+ channels that induced the neuronal overexcitability in NHE1 null mutant mice. Hence, a major question that can be asked is: What is inducing the increased expression of Na+ channels in these neurons? Unfortunately, because there are no representative probes for these channel subtypes on the microarray, we could not address this issue in this study. Third, previous studies in NHE1 mutant cell cultures have demonstrated that there are major changes in cytoskeletal proteins, proliferation, and differentiation phenotypes (11, 26). Finally, our current results showing a downregulation in MCT-13 expression following NHE1 inhibition in primary cultures argue against the notion that the altered gene expression in NHE1 null mutant mice is caused by the phenotype.
To further explore the mechanism(s) underlying the alterations in gene expression in the NHE1 null mutant mice, microarray data were subjected to further analysis. Two binding motifs of the transcription repressors, BCL6 and E4BP4, were found with high statistical significance in most of the downregulated genes in the cerebellum, suggesting a possible involvement of BCL6 and/or E4BP4 in mediating gene suppression.
In summary, this study provides the first evidence showing that NHE1 can induce distinct changes at the expression level of several genes in various brain regions. The number of affected genes throughout the brain regions studied is relatively small. Of those genes, we highlight three that we believe may be related closely to the phenotypes observed in NHE1 null mutant mice.
This work was supported by National Institutes of Health Grant P01-HD-32573. We also acknowledge the support from the cDNA microarray core facility and Bioinformatics Shared Resource of Albert Einstein College of Medicine of Yeshiva University.
↵1 The Supplementary Material for this article (Supplemental Tables S1 and S2) is available online at http://physiolgenomics.physiology.org/cgi/content/full/00076.2004/DC1.
Article published online before print. See web site for date of publication (http://physiolgenomics.physiology.org).
Address for reprint requests and other correspondence: G. G. Haddad, Dept. of Pediatrics, Albert Einstein College of Medicine of Yeshiva Univ., Rose F. Kennedy Center 845A, 1410 Pelham Parkway South, Bronx, NY 10461 (E-mail:).
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