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Human Molecular Genetics Advance Access originally published online on August 18, 2004
Human Molecular Genetics 2004 13(20):2535-2543; doi:10.1093/hmg/ddh268
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Human Molecular Genetics, Vol. 13, No. 20 © Oxford University Press 2004; all rights reserved

Gene profiling links SCA1 pathophysiology to glutamate signaling in Purkinje cells of transgenic mice

Heliane G. Serra1,2, Courtney E. Byam1,2, Jeffrey D. Lande2, Susan K. Tousey1,2, Huda Y. Zoghbi3 and Harry T. Orr1,2,*

1Department of Laboratory Medicine and Pathology and 2Institute of Human Genetics, University of Minnesota, Mayo Mail Code 206, Minneapolis, Minnesota 55455, USA and 3Department of Molecular and Human Genetics and Howard Hughes Medical Institute, Baylor College of Medicine, One Baylor Plaza, Houston, TX 77030, USA

Received May 12, 2004; Accepted July 27, 2004


   ABSTRACT
TOP
 ABSTRACT
INTRODUCTION
 RESULTS
 DISCUSSION
 MATERIALS AND METHODS
 REFERENCES
 
Spinocerebellar ataxia type 1 (SCA1) is a neurodegenerative disease caused by the expansion of a polyglutamine repeat within the disease protein, ataxin 1. To elucidate cellular pathways involved in SCA1, we used DNA microarrays to determine the pattern of gene expression in SCA1 transgenic mice at two specific times in the disease process; 5 weeks, a timepoint prior to onset of pathology, and 12 weeks, at the midpoint of the disease progression. Taking advantage of the availability of three SCA1 transgenic mouse lines, each expressing a different form of ataxin-1, we utilized a strategy that resulted in the identification of a limited number of genes with an altered pattern of expression specific to the development of disease. By comparing the pattern of gene expression in the SCA1 ataxic B05-ataxin-1[82Q] transgenic mouse line with those seen in two non-ataxic lines, A02-ataxin-1[30Q] and K772T-[82Q], nine genes were identified whose expression was consistently altered in the cerebellum of B05[82Q] mice at 5 and 12 weeks of age. Interestingly, five of the genes in this group form a biological cohort centered on glutamate signaling pathways in Purkinje cells.


   INTRODUCTION
TOP
 ABSTRACT
 INTRODUCTION
RESULTS
 DISCUSSION
 MATERIALS AND METHODS
 REFERENCES
 
Spinocerebellar ataxia type 1 (SCA1) is a neurodegenerative disease caused by the expansion of a glutamine repeat inside the disease protein, ataxin-1 (1). This autosomal-dominant disorder typically has its clinical onset in adulthood, presenting with progressive loss of coordination of voluntary movements with minimal cognitive deficits. Death usually occurs within 10–15 years after the onset of symptoms due to bulbar dysfunction. SCA1 is a member of a group of neurological disorders designated the polyglutamine diseases, which include Huntington disease, dentatorubropallidoluysian atrophy, spinobulbar muscular atrophy, and the spinocerebellar ataxias SCA1, SCA2, SCA3, SCA6, SCA7 and SCA17 (2). Although ataxin-1 is ubiquitously expressed (3), the disease affects specific subsets of neurons such as the Purkinje cells in the cerebellar cortex and neurons within the brainstem. Similar to what is observed in SCA1 patients, progressive ataxia and Purkinje cell degeneration occur in transgenic mice overexpressing a mutant SCA1 allele with 82 CAG repeats (4–6). Interestingly, mice expressing high levels of mutant protein only in the cytoplasm and not in the nucleus of Purkinje cells do not develop Purkinje cell pathology or neurological dysfunction (7).

Previous studies on gene expression in the SCA1 mice demonstrated altered expression of genes in the early phase of the disease, before any detectable pathological or neurological alteration could be observed (8). Fernandez-Funez et al. (9) performed a genetic screen in a fly model of SCA1 and identified genetic loci capable of modifying SCA1 neurodegeneration. These studies focused on a limited set of gene products and did not evaluate the simultaneous expression of a large number of genes that may be involved in this complex disease. DNA microarray technology provides the capability to simultaneously monitor thousands of genes. This capability allows a systems level genetic approach to examine brain function/dysfunction (10).

To better understand the molecular processes involved in SCA1, we used genome-wide oligonucleotide microarrays to characterize gene expression patterns in the cerebellum of three different SCA1 transgenic mouse lines at 5 and 12 weeks of age, that is, before and after the onset of the neurological disease phenotype. By this approach, we were able to identify a small biological cohort of genes with altered patterns of expression that were specific to disease in the SCA1 mice.


   RESULTS
TOP
 ABSTRACT
 INTRODUCTION
 RESULTS
DISCUSSION
 MATERIALS AND METHODS
 REFERENCES
 
Our study utilized three lines of mice in order to thoroughly examine differences of gene expression involved in SCA1. Each line expressed a different allele of full-length ataxin-1. One line, B05, expresses a mutant allele of SCA1 encoding ataxin-1 with 82 glutamines, designated B05[82Q] (4). Expression of this SCA1 allele in B05[82Q] Purkinje cells results in a well-characterized form of ataxia and Purkinje cell pathology in a fashion similar to SCA1 patients. The other two SCA1 transgenic mouse lines do not develop ataxia. In the A02 line, a wild-type allele of ataxin-1 with 30 glutamines, designated A02[30Q], is expressed (4). The second unaffected SCA1 transgenic line used expresses a form of ataxin-1[82Q] that does not cause disease due to a single amino acid substitution in the nuclear localization signal of ataxin-1 that prevents it from entering the nucleus of Purkinje cells (7). Although this line, K772T[82Q], demonstrated that the nucleus is the site of ataxin-1-induced pathogenesis, in the present study, K772T[82Q] mice served as a control for alterations in gene expression that might ensue with the overexpression of ataxin-1[82Q] that are unrelated to disease. Cerebellar RNA was isolated from the three different SCA1 transgenic lines at 5 and 12 weeks of age. These ages were selected as they correspond to times prior to the onset of pathology as well as a midpoint of disease progression, respectively (4–6).

Figure 1 outlines the strategy that we utilized to identify genes with a high probability of being relevant to SCA1. Genes were identified that were altered upon comparing the affected SCA1 line, B05[82Q], with the two unaffected SCA1 lines, A02[30Q] and K772T[82Q]. This yielded two sets of genes. These gene sets were compared and those genes with a similar altered pattern of expression in each set were identified, i.e. genes whose expression pattern changed in only one of the B05[82Q]/non-disease line comparisons were subtracted. A second gene subtraction was performed from this subset that included those genes that had an altered pattern of expression in the comparison of the two unaffected SCA1 transgenic lines, A02[30Q] and K772T[82Q] mice. After this second subtraction, the resulting set of genes was designated the SCA1-selected gene set.



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  		Figure 1. A scheme depicting the subtraction strategy used to generate the SCA1-selected gene sets.

 
mRNA changes identified between the SCA1 mice
To identify mRNA changes associated with an early stage of disease, we profiled cerebellar RNA samples prepared from six different animals from each of the three SCA1 transgenic lines at 5 weeks of age. Each mRNA sample was independently hybridized to a different Affymetrix array. In the B05[82Q]/A02[30Q] comparison, 76 genes were found to change by ≥1.8-fold (Fig. 2A). Of these, 45 were increased in B05[82Q] when compared with A02[30Q], and 31 had a decreased level of expression in B05[82Q] when compared with A02[30Q] cerebella. Substantially fewer genes were identified by the B05[82Q]/K772T[82Q] comparison. Of 16 genes identified (Fig. 2B), 10 had a decreased level of expression in B05[82Q] and six had an increased level of expression in B05[82Q] relative to K772T[82Q]. Upon comparing the two unaffected SCA1 lines, A02[30Q] and K772T[82Q], 14 genes were identified with an altered pattern of expression (Fig. 2C). Eleven of these were increased in K772T[82Q] relative to A02[30Q] cerebella and three were decreased (Fig. 2C).



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  		Figure 2. Altered RNAs detected upon comparing the cerebellar RNA samples from the 5-week-old SCA1 mice. Each column depicts the results obtained in comparing one mouse of one genotype with one animal of the other genotype. Each row depicts the pattern of changes for a given RNA seen in all comparisons. (A) Comparison of RNA samples from the SCA1 affected line B05(82Q) with samples from the SCA1 unaffected line A02[30Q]. RNAs whose expression increased in B05[82Q] relative to A02[30Q] are depicted in red and those that decreased are shown in green. (B) Comparison of RNA samples from the SCA1 affected line B05[82Q] with samples from the SCA1 unaffected line K772T(82Q). RNAs whose expression increased in B05[82Q] relative to K772T[82Q] are depicted in red and those that decreased are shown in green. (C) Comparison of RNA samples from the two unaffected SCA1 lines A02[30Q] and K772T[82Q]. Those RNAs that increased in expression in K772T[82Q] relative to A02[30Q] are shown in red and those that decreased are depicted in green.

 
At a later age, 12 weeks, the B05[82Q] mice show signs of ataxia by cage behavior and have a considerable amount of atrophy of the Purkinje cell dendritic tree (5). For the microarray analysis of the 12-week-old animals we used cerebella RNA samples from three animals per SCA1 transgenic line. Each one of the samples was hybridized to a different Affymetrix array. When the comparison was carried out between B05[82Q] and A02[30Q] lines, 40 genes displayed ≥1.8-fold change in expression (Fig. 3A). Of these, 10 genes had an increased level of expression in B05[82Q] when compared with A02[30Q] and 30 genes had a decreased level of expression in B05[82Q] mice relative to A02[30Q]. A larger number (62) of genes were identified when comparing B05[82Q] and K772T[82Q] animals (Fig. 3B). Twenty-five genes were decreased and 37 genes were increased in B05[82Q] relative to K772T[82Q]. A comparison between the two non-affected lines, K772T[82Q] and A02[30Q], identified 52 differentially expressed genes (Fig. 3C). Twenty-seven genes were increased and 25 genes displayed a decreased expression in K772T[82Q] mice when compared with A02[30Q] line.



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  		Figure 3. Altered RNAs detected upon comparing the cerebellar RNA samples from the 12-week-old SCA1 mice. Each column depicts the results obtained when comparing one mouse of one genotype with one animal of the other genotype. Each row depicts the pattern of changes for a given RNA seen in all comparisons. (A) Comparison of RNA samples from the SCA1 affected line B05[82Q] with samples from the SCA1 unaffected line A02[30Q]. RNAs whose expression increased in B05[82Q] relative to A02[30Q] are depicted in red and those that decreased are shown in green. (B) Comparison of RNA samples from the SCA1 affected line B05[82Q] with samples from the SCA1 unaffected line K772T[82Q]. RNAs whose expression increased in B05[82Q] relative to K772T[82Q] are depicted in red and those that decreased are shown in green. (C) Comparison of RNA samples from the two unaffected SCA1 lines A02[30Q] and K772T[82Q]. Those RNAs that increased in expression in K772T[82Q] relative to A02[30Q] are shown in red and those that decreased are depicted in green.

 
The SCA1-selected set of genes
We reasoned that the alterations in gene expression with the highest likelihood of being specifically associated with the Purkinje cell disease in the B05[82Q] mice would be those genes with a similar altered pattern of expression in B05[82Q] when compared with both unaffected transgenic lines, A02[30Q] and K772T[82Q]. In addition, this biologically most relevant set of genes should not include genes with an altered pattern of expression when comparing the two unaffected lines with each other.

When comparing the microarray data generated from the 5-week-old SCA1 mouse cerebellar samples, 14 genes were found to have the same pattern of expression in the B05[82Q] data when compared with the data from each of the two unaffected SCA1 lines (Fig. 4A). Of these 14 genes, two genes had an altered pattern of expression upon comparing the microarray data from the two unaffected SCA1 lines with each other. Subtraction of these two genes left 12 genes in the 5-week-old SCA1-selected gene set. The same analytical procedure applied to the microarray data from the 12-week-old samples of cerebellar RNA yields a SCA1-selected gene set that contained 13 genes (Fig. 4B).



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  		Figure 4. Summary of the cerebellar RNA changes in the SCA1 mice. (A) A Venn diagram showing the RNA changes detected in the genotype comparisons designated in the 5-week-old animals. The shaded area designates the number genes placed into the 5-week-old SCA1-selected set. (B) Venn diagram showing the RNA changes detected in the genotype comparisons designated in the 12-week-old animals. The shaded area designates the number of genes placed into the 12-week-old SCA1-selected set.

 
Table 1 lists the 12 genes that remained in the SCA1-selected gene set from the microarray data generated from the 5-week-old mice after the two rounds of gene subtractions were performed. This set included two ESTs (AI852661 and AI842002) and 10 genes of known function. The 10 known genes are: the sarcoplasmic/endoplasmic reticulum calcium ATPase 3 SERCA3, the transcription factor Nkx6/Gtx, the carbonic anhydrase-related gene CARP, the phosphatase inhibitor G-substrate, Homer-3, inositol 1,4,5-triphosphate receptor IP3R1, Purkinje cell protein 1, the glutamate transporter EAAT4, Tachykinin 1 and Neurogranin.


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  		Table 1. Five-week-old SCA1-selected gene set
 
The SCA1-selected gene set obtained using cerebellar RNA from the 12-week-old animals is presented in Table 2. This set includes 12 known genes and one EST (AI842002). Of the 13 genes within the 12-week-old SCA1-selected gene set, nine were also in the 5-week-old set. The nine genes that overlapped between the two SCA1-selected gene sets were Homer-3, G-substrate, the glutamate transporter EAAT4, IP3R1, AI842002, the homeotic protein Gtx, Purkinje cell protein 1, CARP and SERCA3. As discussed later, five of the nine genes that were found in both SCA1-selected gene sets form a biological cohort centered on glutamate signaling in Purkinje cells.


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  		Table 2. Twelve-week-old SCA1-selected gene set
 
Verification of the selected gene set by real-time PCR
The SCA1-specific decreased expression of four genes in the putative biological cohort indicated by the microarray analyses was confirmed using two additional approaches. Quantitative RT–PCR revealed a decrease in the expression level of G-substrate mRNA in cerebellar RNA from B05[82Q] mice when compared with cerebellar from A02[32Q] mice and K772T[82Q] mice (Fig. 5A and B). We also confirmed the downregulation of Homer-3 mRNA in the SCA1 B05 mice by quantitative RT–PCR (Fig. 5C and D). Decreased expression of IP3R1 and EAAT4, in cerebella of SCA1 B05 relative to the two unaffected lines, A02[30Q] and K772T[82Q] mice, has been shown previously (8). Using northern blot analysis we verified the downregulation of G-substrate expression in B05 cerebellum (Fig. 6A). We also performed western blots that could link the decrease in EAAT4 RNA level with significant low level of EAAT4 protein (Fig. 6B).



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  		Figure 5. Quantitative RT–PCR analysis of G-substrate expression (A and B) and Homer-3 expression (C and D) in the cerebellum of the 5-week-old SCA1 transgenic mice from lines A02[30Q], B05[82Q] and K772T[82Q]. (A and C) Semi-log plots showing changes in fluorescence versus PCR cycle. The mean values of fluorescence were calculated from results obtained from six independent RNA samples for each mouse line. Diamond indicates results from SCA1 line A02[30Q], square indicates results from SCA1 line K772T[82Q] and circle indicates results from SCA1 line B05[82Q]. (B and D) Bar graphs showing the mean value of RNA concentration (ng/µl) obtained from the quantitative RT–PCR analyses. The reduction in expression of Homer-3 is significant when comparing B05[82Q] with A02[30Q] (P=0.006), B05[82Q] with K772T[82Q] (P=0.03), and B05[82Q] with A02[30Q] (P=0.0001) and K772T[82Q] (P=0.01).

 


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  		Figure 6. (A) G-substrate expression in the SCA1 mice. Northern blot using G-substrate cDNA as a probe and total RNA (20 µg) from cerebellum of 5-week-old wild-type (FVB), B05, A02 and K772T. GAPDH levels are shown as a loading control. (B) EAAT4 protein level in the mouse lines studied. Western blot using EAAT4 antibody and 12-week-old cerebella protein lysate showing the decreased level of the protein in B05 when compared with wild-type (WT), A02 and K772T.

 

   DISCUSSION
TOP
 ABSTRACT
 INTRODUCTION
 RESULTS
 DISCUSSION
MATERIALS AND METHODS
 REFERENCES
 
In this study we established a comprehensive gene expression profile associated with a polyglutamine-induced disease in the SCA1 transgenic mice. In order to gain insight into the pathophysiology of SCA1, a key component of our strategy was the availability of two different unaffected SCA1 transgenic mouse lines whose cerebellar gene profiles could be compared with a profile obtained from affected B05[82Q] animals. When comparing these mice using two age groups, that is 5- and 12-week-old animals, we reasoned that genes found to differ in both ages would reveal pathways to the disease process.

Twelve thousand genes and ESTs were interrogated. To identify those genes most likely to be of biological relevance to disease, we performed a two-step series of gene subtractions, initially using the data generated from the cerebella of the 5-week-old animals. The first step was to remove those genes whose expression pattern changed in only one of the B05[82Q]/unaffected line comparisons. Of the 16 genes whose expression was altered in B05[82Q] compared with K772T[82Q] cerebellum, 14 (87%) had the same altered pattern of expression in the B05[82Q]/A02[30Q] comparison. The second subtraction performed was to remove those genes with a similar change in expression upon comparing the two unaffected lines, A02[30Q] and K772T[82Q], reducing the number of genes from 14 to 12. This final set of genes was designated the ‘SCA1-selected gene set’ and consists of 10 previously characterized genes and two uncharacterized ESTs (Table 1).

When this same subtraction strategy was applied to the gene profile data obtained using the cerebellar RNA samples from the 12-week-old animals, a timepoint that in the SCA1 B05[82Q] mice corresponds to the midpoint of disease progression (4–6), a limited number of genes was also revealed (Table 2). Intriguingly, of the 13 genes placed into the 12-week-old SCA1-selected gene set, nine were also in the 5-week-old selected set. The considerable proportion of the genes that overlapped between the two SCA1-selected gene sets suggests that alteration in the expression of these genes is central for the disease process.

Several points support the postulated biological relevance to SCA1 for five of the nine overlapping genes (Homer-3, G-substrate, EAAT4, IP3R1 and CARP). Each of these genes is richly expressed in Purkinje cells (11), and their products localize to the dendritic tree of Purkinje cells (12–15), an important subcellular site of pathology in the SCA1 mice (4–6). In addition, two of the five genes, IP3R1 and EAAT4, were reported previously to be downregulated prior to disease onset in SCA1 B05-ataxin-1[82Q] mice using a subtractive cDNA cloning approach (8). The downregulation of the two other genes, Homer-3 and G-substrate, was also confirmed by quantitative PCR and northern blot analysis in our laboratory. Intriguingly, the products of these five genes can be positioned as regulators of the glutamate signaling pathway in Purkinje cells (Fig. 7). This observation is notable since each Purkinje cell is innervated by several hundred thousand parallel fiber synapses that use the excitatory transmitter glutamate (16). From about 2 weeks of age, Purkinje cells rely almost exclusively on two types of glutamate receptors; AMPA receptors for fast excitation and a metabotropic glutamate receptor, mGluR1, for a slower phase of excitation. mGluR1 and AMPA receptor activation are functionally intertwined. For example, cerebellar long-term depression (LTD) is a use-dependent reduction in postsynaptic strength that requires activation of both mGluR1 and AMPA receptors at the parallel fiber/Purkinje cell synapse (17).



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  		Figure 7. Glutamate signaling pathways in the Purkinje cell dendrite at the parallel fiber/Purkinje cell synapse. The double line depicts the postsynaptic Purkinje cell membrane. AMPAR, AMPA glutamate receptor (memb, at the membrane and inter, intracellular localization); EAAT4, glutamate excitatory amino acid transporter type 4; IP3, inositol 1,4,5-triphosphate; IP3R1, inositol 1,4,5-triphosphae receptor; mGluR, metabotropic glutamate receptor; PLC, phospholipase C; PKC, protein kinase C; PP2A, protein phosphatase 2A. Shaded ovals indicate components placed within the SCA1-selected gene set.

 
How might the five genes found in both ‘selected sets’ be involved in regulation of glutamate signaling? Homer-3 is a member of a family of proteins that function as adapters to couple membrane receptors with intracellular pools of releasable Ca2+ (18,19). In Purkinje cells, Homer-3 would bind to the proline-rich motif of the mGluR1 receptor and link it to the type 1 inositol 1,4,5-triphosphate receptor (12), IP3R1 (Fig. 7). Studies have shown that among the homer proteins, Homer-3 preferentially co-localizes with the mGluR1a receptor subtype (20). In line with this finding, it was also demonstrated that Homer-3 inhibits the constitutive activity of mGluR1a/5, and this inhibition is released after induction of Homer 1a (21). Homer proteins may also effect the intracellular trafficking of mGluR1 receptors (22). Quantitative PCR indicated a decrease in the expression of mGluR1 in B05[82Q] when compared with A02[30Q] and K772T[82Q] lines (H.G. Serra, unpublished data).

The EAAT4 glutamate transporter was another gene that was downregulated in the SCA1-selected set. In Purkinje cell dendrites, the subcellular distribution of EAAT4 overlaps with that of mGluR1 (13,23). This co-localization may provide a role for EAAT4 in the regulation of extracellular glutamate levels and, consequently, the activity of mGluRs. Consistent with this idea are the recent observations that inhibition of postsynaptic glutamate transporters enhances mGluR1 activity and facilitates development of mGluR1-dependent LTD at the parallel fiber/Purkinje cell synapse (24). Further experiments demonstrated that EAAT4 inhibition alone enhances mGluR1 activity (25).

IP3R1, another gene placed in the SCA1-selected gene sets, is expressed highly in Purkinje cells (12), and is a downstream effector of type I mGluRs (26). IP3R1 is a Ca2+-release channel that increases cytoplasmic Ca2+ concentration upon binding IP3, generated in response to extracellular signals through G protein-coupled receptors such as the mGluR receptors (27). The functional importance of IP3R1 is indicated by the demonstration that it is required for LTD in Purkinje cells (28), and that a 50% reduction of IP3R1 results in decreased motor coordination (29).

CARP, the carbonic anhydrase-related protein, that lacks carbonic anhydrase activity is highly expressed in the cytoplasm, dendrites and axons of Purkinje cells (14). Recently, it was demonstrated that CARP binds to IP3R1 and reduces the receptor affinity for IP3 (30). The inhibitory effect of CARP on IP3 binding to IP3R1 could be involved in the low IP3-induced Ca2+ release seen in Purkinje cells (31).

G-substrate can also be linked to glutamate receptor function in Purkinje cells (Fig. 7). G-substrate is almost exclusively expressed in the dendrites of Purkinje cells and is a specific substrate of the cGMP-dependent protein kinase (15). When phosphorylated, G-substrate is a potent inhibitor of protein phosphatase 2A, PP2A (31–34). Receptor phosphorylation is a key step in the expression of LTD through the internalization of phosphorylated AMPA receptors (17,35). The phosphorylation status of AMPA receptors is regulated by both kinase and phosphatase pathways. It has been suggested that induction of LTD, an attenuation of postsynaptic AMPA receptor function, proceeds via inhibition of PP2A, the only known cerebellar phosphatase involved in LTD (16,36). This could place G-substrate, an inhibitor of PP2A, in a position for the regulation of AMPA receptor activity in Purkinje cells. It is possible that the decreased expression of the four genes mentioned above could cause alteration in cerebellar LTD in the SCA-1 mice.

A previous study used a PCR-based cDNA subtractive hybridization strategy to identify several genes with an altered pattern of expression at an early stage of SCA1 (8). Of the genes identified by this subtractive cDNA study, three genes were present on the Affymetrix chips used in our study (IP3R1, EAAT4, SERCA2). Two of which were confirmed to be downregulated in our study (IP3R1 and EAAT4). The other genes found to be downregulated by Lin et al. (prenylcysteine carboxymethyltransferase, transient receptor potential type 3, type 1 inositol polyphosphate 5-phosphatase, {alpha}-1 antichymotrypsin) were not on the chip used in our study.

A prediction from the alterations in gene expression found in this study along with the previously reported decrease in the Ca2+-binding proteins (37) and other genes associated with Ca2+ homeostasis (8) is that intracellular Ca2+ dynamics of Purkinje cells would be affected in the SCA1 mice. However, Inoue et al. (38) using Ca2+ imaging found that the basic Ca2+ handling properties of Purkinje cells in SCA1 and wild-type mice were essentially identical. Perhaps one explanation for this apparent discrepancy is that functionally important Ca2+ signaling domains can be localized to precise subcellular compartments within a neuron (39). An example of a Ca2+ signaling microdomain is the dendritic spine where the signal can spread over just a few microns (40,41). Our observation that many of the genes within the SCA1-selected set encode proteins that localize to the postsynaptic spines of Purkinje cells is consistent with the possibility that alterations in signaling might be localized to a discrete microdomain that is difficult to image and for which changes in Ca2+ handling properties have not yet been tested.

In summary, we utilized a high density DNA microarray approach to identify a SCA1-selected set of genes whose alteration in expression was specifically associated with SCA1 in transgenic mice. Although it is impossible at this time to determine which of these genes are affected directly by the actions of mutant ataxin-1 protein versus those that change due to compensatory mechanisms, the genes positioned within the SCA1-selected gene set indicate that SCA1 Purkinje cell pathophysiology involves an alteration in glutamate signaling. That alterations in glutamate signaling can lead to Purkinje cell degeneration was recently demonstrated in the lurcher mouse (42). Purkinje cell degeneration in the lurcher mouse is due to a mutation in the GluR{delta}2 gene that results in a constitutively active glutamate receptor ion channel. Lurcher mice Purkinje cells appear to die via autophagy involving the formation of cytoplasmic autophagic vacuoles. These results are intriguing in light of the recent report of an increase in cytoplasmic vacuoles in Purkinje cells of affected SCA1 transgenic mice (6).


   MATERIALS AND METHODS
TOP
 ABSTRACT
 INTRODUCTION
 RESULTS
 DISCUSSION
 MATERIALS AND METHODS
REFERENCES
 
DNA microarray analyses
Cerebellar gene expression in the SCA1 mice was assessed using MG-U74A oligonucleotide arrays (Affymetrix, Santa Clara, CA, USA) containing 12 000 mouse genes and ESTs. Total cerebellar RNA was isolated from six mice of each SCA1 genotype at 5 weeks and from three mice at 12 weeks of age using Trizol Reagent (Invitrogen) according to manufacturer's specifications. Following, RNAs were purified over RNeasy columns (Qiagen) and cRNA was prepared and hybridized as directed by the manufacturer (Affymetrix).

Microarray data analysis was performed using Affymetrix Microarray Suite Version 5 and Microsoft Access 2000. All arrays were scaled to a target intensity of 200. Criteria used to detect differences in gene expression were ≥1.8-fold change in expression; a change value of increase, marginal increase, decrease or marginal decrease; a signal change greater than 50 and a detection call of present in at least 16/36 of the comparisons at 5 weeks of age and 4/9 of the comparisons at 12 weeks. Cluster analyses were performed using TREEVIEW.

Quantitative RT–PCR Analysis
For each SCA1 transgenic line analyzed, six independent cerebellar total RNA was prepared using Trizol Reagent (Invitrogen). Each RNA sample was treated with RNase-free DNase I (10 µg/µl, Boehringer Mannheim). One-step RT–PCR was performed with LightCycler-RNA amplification Kit SYBR Green I (Roche Molecular Biochemicals) using a LightCycler instrument and SYBR Green I as the detection format. LightCycler RT–PCR reactions were set up with 5 µl of total RNA (20 ng/µl) and 5 µl master mix containing 1 µl of downstream and upstream primers (10 µM each), 0.8 µl MgCl2 (25 mM), 2 µl of 5X SYBR Green I react buffer and 0.2 µl of Taq Polymerase. Control PCR reactions with RNA samples without added reverse transcriptase were carried out using the same primers and cycling conditions to confirm the absence of DNA contamination.

The primer set used for G-substrate amplification was: forward primer 5'-GACTCTAAGATCTAGACGCCTC-3' and reverse primer 5'-CCCCTCCCCATCTTTTATCC-3'. Length of the amplified G-substrate was 223 bases, from nucleotide 707 to 910. LightCycler settings for the G-substrate amplification were: a denaturing temperature of 95°C, an annealing temperature of 49°C for 20 s, an extension temperature of 72°C for 15 s and an acquisition temperature of 78°C for 5 s. The primer set for Homer-3 was: forward primer 5'-CTTACTATTTCG CACTCCCTTC-3' and reverse primer: 5'-ACTCAGTGTTTCCTGTCCC-3'. Length of the amplified Homer-3 product was 116 bases, between nucleotides 2018 and 2134. LightCycler settings for the Homer-3 amplification were: a denaturing temperature of 95°C, an annealing temperature of 60°C for 20 s, an extension temperature of 72°C for 15 s, and an acquisition temperature of 85°C for 5 s.

For the G-substrate and the Homer-3 quantitative RT–RCR analyses, a dilution series of control RNA (100, 50, 10, 1 ng) was assayed in each run to compare expression levels of the target gene in the mouse lines relative to controls. The LightCycler quantification software package V 3.2 was used to determine gene expression in experimental samples during the PCR log-linear phase by extrapolating the samples concentration from the standard curve constructed from the dilution series of control RNA. All statistical analyses were performed using the Student's t-test.

Northern blot analysis
Total RNA was isolated from cerebellum with TRIZOL reagent following manufacturer's instruction (Gibco-BRL, Maryland). RNA (20 µg) was fractionated and transferred to nylon membrane according to standard protocols and probed with radiolabeled mouse G-substrate cDNA clone. The relative amount of RNA on the blot was evaluated by hybridization with a GAPDH cDNA.

Western blot analysis
For western blot analysis, whole cerebella were homogenized in 500 µl lysis buffer [50 mM Tris–HCl (pH 7.5), 2.5 mM MgCl2, 100 mM NaCl, 0.5% Triton X-100, 1X protease inhibitors (Roche Biochemicals), phosphatase inhibitor cocktails I and II (Sigma)]. A portion of the crude lysate was heated with loading buffer and run on 3–8% Tris–acetate polyacrilamide gel (Invitrogen). Following electrophoresis and transfer to nitrocellulose membrane (Protran, Schleicher and Schuell), the membrane was probed with rabbit cEAAT4 (1 : 200) (a gift from J.D. Rothstein, Johns Hopkins University) and subjected to autoradiography.


   ACKNOWLEDGEMENTS
 
We thank Dr L. Boland for critical comments on the manuscript. This work was supported by NIH grant NINDS 220920 (H.T.O.).


   FOOTNOTES
 
* To whom correspondence should be addressed. Tel: +1 6126253647; Fax: +1 6126267031; Email: harry{at}lenti.med.umn.edu


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