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DNA Research Advance Access originally published online on January 8, 2007
DNA Research 2006 13(6):275-286; doi:10.1093/dnares/dsl016
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© The Author 2006. Kazusa DNA Research Institute
The online version of this article has been published under an open access model. Users are entitled to use, reproduce, disseminate, or display the open access version of this article for non-commercial purposes provided that: the original authorship is properly and fully attributed; the Journal and Oxford University Press are attributed as the original place of publication with the correct citation details given; if an article is subsequently reproduced or disseminated not in its entirety but only in part or as a derivative work this must be clearly indicated. For commercial re-use, please contact journals.permissions@oxfordjournals.org

Identification of Genes Related to Parkinson's Disease Using Expressed Sequence Tags

Jeong-Min Kim1, Kyu-Hwa Lee1, Yeo-Jin Jeon1, Jung-Hwa Oh1, So-Young Jeong1, In-Sung Song1, Jin-Man Kim2, Dong-Seok Lee3 and Nam-Soon Kim1,*

1 Laboratory of Human Genomics, Genome Research Center, Korea Research Institute of Bioscience and Biotechnology (KRIBB) Daejeon, Korea
2 Department of Pathology, College of Medicine, Chungnam National University Daejeon, Korea
3 College of animal resource sciences, Kangwon National University Chunchon, Korea

Received 26 April 2006; revised 20 November 2006


   Abstract
Top
 Abstract
1. Introduction
 2. Materials and methods
 3. Results
 4. Discussion
 Acknowledgements
 REFERENCES
 
In a search for novel target genes related to Parkinson's disease (PD), two full-length cDNA libraries were constructed from a human normal substantia nigra (SN) and a PD patient's SN. An analysis of the gene expression profiles between them was done using the expressed sequence tags (ESTs) frequency. Data for the differently expressed genes were verified by quantitative real-time RT–PCR, immunohistochemical analysis and a cell death assay. Among the 76 genes identified with a significant difference (P > 0.9), 21 upregulated genes and 13 downregulated genes were confirmed to be differentially expressed in human PD tissues and/or in an MPTP-treated mice model by quantitative real-time RT–PCR. Among those genes, an immunohistochemical analysis using an MPTP mice model for alpha-tubulin including TUBA3 and TUBA6 showed that the protein levels are downregulated, as well as the RNA levels. In addition, MBP, PBP and GNAS were confirmed to accelerate cell death activity, whereas SPP1 and TUBA3 to retard this process. Using an analysis of ESTs frequency, it was possible to identify a large number of genes related to human PD. These new genes, MBP, PBP, GNAS, SPP1 and TUBA3 in particular, represent potential biomarkers for PD and could serve as useful targets for elucidating the molecular mechanisms associated with PD.

Key words: parkinson's disease; expressed sequence tags; gene expression profiling; immunohistochemistry; cell death


   1. Introduction
Top
 Abstract
 1. Introduction
2. Materials and methods
 3. Results
 4. Discussion
 Acknowledgements
 REFERENCES
 
Parkinson's disease (PD) is one of the most common neurodegenerative movement disorders.1Go Approximately 1% of the population older than 65 years suffers from this slowly progressive neurodegenerative disorder.2Go The disease is clinically characterized by impaired motor function, manifested by resting tremors, rigidity, bradykinesia and postural instability.3Go The primary pathological changes associated with PD include the degeneration of pigmented neurons in the substantia nigra (SN) pars compacta of the brain which results in a decrease in dopamine availability.4Go In addition, the important feature of PD is the presence of Lewy bodies in the affected brain areas.1Go

The etiology of PD is diverse and complex. Several mutations that lead to familial PD have been described. Ten distinct loci, including {alpha}-synuclein (PARK1), Parkin (PARK2), DJ-1 (PARK7) and PTEN-induced kinase 1 (PINK, alternatively PARK6), have been reported to be responsible for rare Mendelian forms of PD,2Go,5Go whereas the etiology of sporadic PD, occurring in 95% of the cases of PD, is not fully understood. Several studies, including genetic analyses, finding of environmental factors and new experimental models of PD have provided new information on the pathogenesis of PD.2Go,6Go–9Go In addition, several pathologic and genetic animal models have been employed in an attempt to develop an understanding of both the pathophysiology and potential neuroprotective therapeutics for PD. Neurotoxins such as 6-hydroxydopamine (6-OHDA), 1-methyl-4-phenyl-1,2,3,6-tetrahydropiridine (MPTP), N,N'-dimethyl-4-4'-bipiridinium (paraquate) and rotenone, which induce dopaminergic neurodegeneration, have been used in the generation of PD animal models. The MPTP model induces pathologies that are similar to those seen in humans and is thus the most widely studied.3Go,6Go

The application of global approaches such as collecting expressed sequence tags (ESTs), the serial analysis of gene expression (SAGE) and microarray techniques have been shown to be very useful in the analysis of complex biological phenomena, including certain human diseases.10Go–14Go Ryu et al.15Go reported that the expression profiles of genes are changed as the result of 6-OHDA treatment of PC12 cells using SAGE. In addition, the gene expression profiles for human parkinsonian SN using oligonucleotide arrays16Go,17Go and the expression profiles of genes induced by oxidative stress in a nigral DA cell line using a cDNA microarray18Go have been reported. Furthermore, a wide spectrum of molecular events prior to dopaminergic neurodegeneration in MPTP mice model have also been reported.19Go,20Go However, global gene expression studies of PD using ESTs analysis have not been reported. The ESTs generated by the single-pass sequencing of cDNA clones that were randomly selected from cDNA libraries have been used to in the identification of novel genes,10Go and the differential and quantitative analysis of expression patterns21Go as well as the evaluation of gene expression profiles in a specific tissue.10Go,21Go,22Go

To identify genes related to PD by examining their expression profiles, we collected a large number of genes expressed in human normal SN and human PD's SN. In particular, we applied a strategy for obtaining full-length cDNAs, since these clones are a valuable resource for the functional study of genes. As a first step, we constructed two full-length and two normalized cDNA libraries23Go from human normal SN and PD's SN. Using the EST frequency mainly obtained from the full-length libraries, the expression profile of the genes expressed in human normal SN and PD's SN was analyzed and genes that are differentially expressed between them were selected. The expression levels of these selected genes were also confirmed in human SN tissues as well as MPTP mice model and the cell death activity of these genes was also examined. These newly identified genes represent potentially useful targets for elucidating the molecular mechanisms associated with PD.


   2. Materials and methods
Top
 Abstract
 1. Introduction
 2. Materials and methods
3. Results
 4. Discussion
 Acknowledgements
 REFERENCES
 
2.1. RNA preparations
Total RNAs were obtained from commercial sources or from tissues from the Human Brain and Spinal Fluid Resource Center (HBSFRC). Total RNAs from human SN tissues were extracted using a commercially available RNA isolation kit (Qiagen, Hilden, Germany) following the procedures recommended by the manufacturer. Information relative to the three normal human SN total RNAs is as follows; Cat#6866 (Ambion, USA), male caucasian 81 years of age, died of congestive heart failure and negative for HIV 1, HIV 2, HBV and HCV; HSB#3482 (HBSFRC), female 79 years of age, diagnosed with coronary artery disease, and the hippocampus shows no evidence of degenerative disease or global hypoxia; HSB#3484 (HBSFRC), male 72 years of age, diagnosed with chronic obstructive pulmonary disease and pulmonary emphysema, and negative for neurodegenerative disease or other neuropathology. Information on the three human PD SN total RNAs is as follows; Cat#6288 (Ambion, USA), male caucasian 60 years of age, diagnosed with PD, died from a gun shot wound, and negative for HIV 1/2, HBV and HCV; Cat#B6288 (Ambion, USA), male caucasian 81 years of age, diagnosed with PD, negative for HIV 1/2, HBV and HCV, and the cause of death was unknown; HSB#3642 (HBSFRC), female 83 years of age, diagnosed with PD and Dementia (MID). No evidence of other causes of dementia (e.g. Alzheimer). Total RNAs of mouse SN were extracted from the SN of the constructed MPTP mice model (see ‘Construction of MPTP mice model’ in Materials and methods) using same method.

2.2. Construction of cDNA library and DNA sequencing
The full-length cDNA library was constructed using an improved capping method with the pCNS-D2 vector.23Go Plasmid DNAs were extracted from clones that were randomly selected in the constructed cDNA libraries by using a MWG plasmidprep 96 (MWG Biotech., Ebersberg, Germany). Sequencing of the DNAs was performed using previously described procedures.11Go A normalized cDNA library was also constructed to obtain genes that are rarely expressed by the previous method.24Go

2.3. Bioinformatic analysis of ESTs
Analysis of the collected ESTs with a bioinformatic tool was performed according to previously described procedures.11Go The annotation of ‘high quality’ SN ESTs were carried out using the human mRNA subset extracted from the GenBank database and the UniGene database (Hs.seq.all, build #164) for similarity comparisons using BLASTN. For protein similarity assessment, a comparison was performed against the non-redundant protein database using BLASTX.

2.4. Gene expression analysis
The frequency of each gene was analyzed by dividing the number of ESTs of a gene by the number of total clones merged into the UniGene database build #164 in each full-length cDNA library. Genes that were abundantly expressed in each library are selected and are listed among the ESTs. Significant differences in gene expression between the datasets were calculated using a previously described method.25Go Analysis of expressional differences between the normal full-length SN library and the PD full-length SN library was performed at a cut-off probability of 0.9. The gene list was sorted according to the gene frequency in the library of the overexpressing gene. In addition, an analysis for the chromosomal location of the selected genes was performed.

2.5. Construction of MPTP mice model
All procedures using the mouse model were carried out in accordance with the NIH Guidance for the Care and Use of Laboratory Animals and were approved by the guidelines of the Institutional Animal Care and Use Committee, KRIBB. C57Bl/6 male mice (10 weeks; 25 g) were purchased from Charles River Laboratories (Canada), and maintained on a 12 h day–night cycle. Food and water were given ad libitum under standard animal care conditions. On Day 10, sample groups (n = 3 per sample) were injected (intraperitoneal) with 200 µl of PBS containing three different dosages of MPTP (5 mg, 10 mg and 25 mg MPTP/kg, Sigma, MO, USA) for 5 days at 1 day intervals, whereas the control group (n = 3) was injected with 200 µl of PBS. On Day 15, the mice were decapitated and the brains removed quickly and frozen in isopentane (–40°C). The SN region of the brain was used for the preparation of the total RNA.

2.6. Quantitative real-time RT–PCR
Reverse transcription (RT) was performed with 5 µg of the total RNA using the same procedures as previously described.11Go To validate the expression level of the selected genes, PCR was performed using the 1st cDNAs as templates and a specific primer set for each gene (Table 1). The amplification was carried out using Exicycler version 2 (Bioneer Co., Korea) in a 10 µl reaction mixture containing 4 µl of diluted DNA template, 2 pmol of each primer and 5 µl of 2x SYBR® Premix Ex TaqTM (TaKaRa Biotechnology Co., Ltd) including a dNTP mixture and Mg2+, under the following conditions: 95°C for 5 min, followed by 45 cycles at 95°C for 30 s, at 55°C for 30 s, at 72°C for 30 s. The tyrosine hydrolase (TH) gene was used as a positive control for PD and the reaction of each sample was performed in triplicate. A melting curve and the melting temperature for each sample were calculated using the procedures recommended by the manufacturer. The relative quantification of gene expression was analyzed by the 2-ddCt method. The transcriptional activity of each gene was calculated as relative amounts, such as PD versus normal groups in human tissues and MPTP groups versus the control group in MPTP mice tissues, and then presented as the relative fold expression change (log base 2), after normalization against B2M expression (for human samples) or actin expression (for mice samples). The standard deviations and standard errors were also calculated.


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  		Table 1. Primer sequences for quantitative real time RT–PCR

 
2.7. Immunohistochemistry
For immunohistochemistry, the fixed tissues were embedded in paraffin. Coronal sections (3 µm thick) of mouse brains were collected along the rostrocaudal extent of the brain from the bregma 2.92 to –3.80 µl.26Go After deparaffinization and antigen retrieval by a pressure cooker in 10 mM sodium citrate buffer (pH 6.0) at full power for 4 min, tissue sections were treated with 3% hydrogen peroxide for 10 min. Immunostaining for monoclonal mouse of TH (1:50 dilution, Novocastra, UK) was performed using the mouse EnVision kit (Dako, Carpinteria, CA, USA). The primary antibody was incubated for 30 min followed by incubation with the mouse EnVision reagent for 30 min. The slides were then sequentially incubated with DAB chromogen for 5 min, counterstained with Meyer's hematoxylin and mounted. Immunofluorescence staining for monoclonal mouse alpha-tubulin which detects TUBA3 and TUBA6 was performed using Cy2-conjugated rabbit anti-mouse immunoglobulin. The primary antibody (1:400 dilution, Santa Cruz, CA, USA) was incubated overnight at 4°C and then labeled with Cy2-conjugated immunoglobulin (1:200 dilution, Jackson ImmunoResearch, PA, USA) for 30 min. Cy2-labeled sections were analyzed by confocal microscopy using a Fluoview FV500 instrument (Olympus, Japan).

2.8. Cell death activity assay
Human neuroblastoma cell line, SH-SY5Y (ATCC, CRL-2266) were grown in DMEM supplemented with 10% fetal bovine serum (Invitrogen). For transfection, the cells were subcultured at a density of 2 x 104 cells in 24-well plates for 1 day. Transient transfection was performed with the Lipofectamine 2000 reagent (Invitrogen) following the manufacturer's instructions. In each well, 200 ng of each plasmid DNA and 50 ng of pDsRed2-Mito plasmid DNA, a mitochondria marker gene (BD Biosciences Clontech, USA), were cotransfected into the cells. The human Bcl-2 and Bcl-xl plasmid DNAs were used as a positive control for retarding cell death, and pcDNA-HA plasmid DNA acted as a negative control. After 24 h of transfection, cell death was induced by the administration of 1 mM MPTP in each well for 24 h as previously described procedure.27Go Cell death was then evaluated by observation under an inverted microscope (Nikon, Eclipse TS-100, Japan) equipped with a fluorescence observation device (Nikon, C-SHG, Japan) based on the morphology and RFP pattern of pDsRed2-Mito-positive cells using a previously described method with minor modifications.28Go All experiments were performed in triplicate.


   3. Results
Top
 Abstract
 1. Introduction
 2. Materials and methods
 3. Results
4. Discussion
 Acknowledgements
 REFERENCES
 
3.1. Large-scale ESTs collection from human SN tissues
Two full-length and two normalized cDNA libraries were constructed from normal and PD human SN tissues. A total of 6528 clones were randomly selected from these 4 libraries and used for 5' end single-pass sequencing. The sequences obtained were subjected to quality control procedures, namely trimming of the vector region and the removal of low-quality or short (<100 bp) sequences. Finally, 6067 high-quality ESTs with an average read length of 500 bp were collected (Table 2). After screening out 220 ESTs derived from mitochondrial DNAs, ribosomal DNAs and human repetitive sequences, the remaining 5847 sequences were submitted to the NCBI dbEST database. When all of our ESTs were annotated by coalescing into human UniGene clusters (Build #164), they were assembled into 2878 clusters. Most were ESTs coding a known gene having an identity of at least 95% with human Refseq or mRNA. These annotated results were used in an analysis of the subsequent expression profiles.


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  		Table 2. Summary of cDNA libraries

 
3.2. Identification of PD-related genes
To identify candidate genes related to PD, we selected genes that showed a significant difference (P > 0.9) between the two full-length cDNA libraries. As shown in Fig. 1, we found 38 upregulated genes and 38 downregulated genes specifically in the PD's SN library.


Figure 1
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  		Figure 1. Genes showing significant difference (P a > 0.9) in expression between normal and PD' SN.

 
Among the upregulated genes in PD, significant differences were observed in gene groups associated with central nervous system development (MBP and Golli-MBP), protein modification and catabolism (UBB, PSMC1, RNF10 and RNF5), signal transduction (STMN1, GNAS, BCR and HMP19), iron ion transport (FTL and FTH1), glycolysis pathway (LDHB, MDH1, PGK1 and LDHA), protein synthesis (RPL3, EIF4A2, RPS3A, RPL17, RPS4X and FRSB), lipid metabolism (APOD and ELOVL1) and metabolite detoxification (HMOX2). Although the MBP gene was relatively abundant in the normal library, the frequency of this gene in the PD library was significantly higher than in normal library.

In the case of downregulated genes in PD, significant differences were observed in gene groups related to microtube-based movement (K-ALPHA-1, TUBA6, MGC8685 and TUBA3), protein synthesis (EEF1A1, RPL15, RPL13, EIF3S2 and RPL31), immune response (SPP1, CD74, ACT, HLA-DRB3 and ARHGDIB), transport (ATP6V1E1, TMP21, AP1S2, AQP4, CSE1L, JWA and COPE), protein folding (TEBP, DNAJB6 and PFDN1), proteolysis and peptidolysis (SMT3H1 and CAPN3) and nerve–nerve synaptic transmission (KIF1B).

3.3. Verification of PD-related genes in SN tissues from human PD and MPTP mice model using quantitative real-time RT–PCR
To validate the upregulated and downregulated genes in PD selected from ESTs frequency data, we randomly selected 15 upregulated genes and 11 downregulated genes from the PD's SN library and real-time RT–PCR was performed on human SN tissues of three normal and three PD. As shown in Fig. 2A (I), all of the upregulated genes in human PD's SN tissues were highly expressed in human PD's SN tissues compared to normal SN tissues. On the other hand, many of the downregulated genes as well as the TH gene, which is a dopaminergic neuron specific marker, were expressed at low levels in PD, and showed high expression levels in normal SN tissues. Among the tested genes, 20 genes (77%) were upregulated or downregulated at a statistically significant level in more than one sample. These results show that the transcriptional levels of the selected genes, as evidenced by real-time RT–PCR, are almost consistent with the ESTs frequency data for all genes. In addition, to obtain more PD-related genes, genes showing slight frequency differences between the two normalized libraries from the SN of the human PD and normal tissues, six upregulated genes of EIF3S5, SNRPN, KIAA1276, PTK6, ST13 and DJ462O23.2, and two downregulated genes of HNRPC and EIF3S2 were selected and their expression levels were confirmed using real-time RT–PCR. As shown in Fig. 2A (II), the real-time RT–PCR data were almost consistent with the EST frequency data. This indicates that genes showing a slight difference between the normalized libraries actually might be present at highly different levels in between original libraries or cells.


Figure 2
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  		Figure 2. Quantitative real-time RT–PCR of upregulated or downregulated genes randomly selected from the libraries of human normal SN and PD's SN. (A) Total RNAs were extracted from human SN tissues of three normal and three PD, and then used as templates. PD1, Cat#6288; PD2, Cat#B6288; PD3, HSB#3642. (B) Total RNAs were extracted from SN tissues of three types of MPTP mice model which were injected with MPTP at levels of 5, 10, 25 mg/kg and then used as templates. The transcript levels of the target genes were calculated, as described in Materials and Methods. (a) Upregulated genes in PD; (b) downregulated genes in PD; (I) genes showing significant frequency differences between the full-length cDNA libraries; (II) genes showing slight frequency differences between the normalized libraries (for details, see Materials and Methods). Asterisks denote a significant difference in target genes between the sample and control by the t test (*P < 0.05; **P < 0.01; ***P < 0.001).

 
The MPTP model has provided a useful model of Parkinsonism because it induces pathologies that are similar to those seen in humans. To validate the genes confirmed in human SN tissues, the expression level of these genes was also confirmed in SN tissues from three types of mice models which were injected with various concentrations of MPTP (5, 10 and 25 mg/kg weight). The upregulated or downregulated genes in these mice model were assigned to genes which were upregulated or downregulated in over two to three samples. As shown in Fig. 2B (b), when the confirmation for the constructed MPTP mice model was performed using the TH gene, the real-time RT–PCR data showed that the expression of the TH gene was decreased in MPTP mice model. In addition, Fig. 2B shows that of 21 genes are upregulated in human SN, 9 genes (43%), Golli-MBP, FTL, PBP, GNAS, RPS3A, EIF3S5, PTK9, ST13 and DJ462O23.2, are highly expressed in SN tissues of MPTP mice which is in agreement with the data from human tissues. On the other hand, 8 of 13 downexpressed genes (62%), SPP1, CD74, ACT, RPL13A, TUBA6, AQP4, TUBA3 and HNRPC were expressed at lower levels in SN tissues of MPTP mice. These results indicate that gene expression in human PD is about 50% in agreement with that for the MPTP mice model.

3.4. Verification of protein levels for selected genes using immunohistochemistry
To verify the protein levels of the genes that were confirmed by quantitative real-time RT–PCR, an immunohistochemical analysis was performed in the MPTP mice model. PBP, SPP1 and alpha-tubulin (TUBA) including TUBA6 and TUBA3 were selected as target genes for PD, because their antibodies were available.

The immunohistochemical data for the TH protein, a dopaminergic neuron marker, clearly showed that the TH protein in the coronal sections of mouse brains were detected at very low levels compared to their controls (Fig. 3A). With the quantitative real-time RT–PCR data for TH gene, the results indicated that dopaminergic neurons in the SN of the PD model by MPTP treatment had degenerated. As shown in Fig. 3B, TUBA protein including TUBA6 and TUBA3, which is downregulated in human PD tissues and tissues of PD mice model using quantitative real-time RT–PCR, was decreased in the SN region of MPTP-treated mouse brains compared to the SN region of control mouse. On the other hand, PBP and SPP1 proteins were not detected in the SN region of either control mice or MPTP mice in our study. This is thought to be due to the low reactivity of antibodies against PBP and SPP1. These results indicate that a decrease in mRNA levels for target genes such as TUBA6 and TUBA3 in PD are coupled to the corresponding protein levels, although TUBA antibody can not specifically detect TUBA6 and TUBA3, respectively. In addition, these results suggest that the selected target genes represent possible candidates for markers for the identification of PD.


Figure 3
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  		Figure 3. Immunohistochemical staining for TH and alpha-tubulin in the SN of an MPTP mice model. Immunoreactivity for TH and alpha-tubulin was markedly decreased in MPTP mice model (b) compared to control mice (a). The mice were treated with MPTP (25 mg/kg) for 5 days, and after 2 days, the SN region was dissected and used in immunohistochemical staining experiments (for details, see Materials and Methods). (A) TH; (B) alpha-tubulin; (a) control mice; (b) MPTP-treated mice. Scale bar: (A) 500 µm; (B) 50 µm.

 
3.5. Identification of the genes having cell death activity from selected genes
The neurodegeneration associated with PD is known to be related many apoptotic events including ROS generation, caspase activation and DNA fragmentation. Alterations in certain apoptotic cell death-related molecules during MPTP-induced dopaminergic degeneration have also been reported. To identify genes having cell death activity from the target genes obtained, the cell death activity of 34 genes which were confirmed by quantitative real-time RT–PCR analysis was examined.

Fig. 4A shows that, of the upregulated genes, four genes such as MBP, PBP, GNAS and PAQR6 were associated with the acceleration in cell death compared to the control gene, pcDNA-HA. On the other hand, four downregulated genes, SPP1, ARHGDIB, TUBA3 and TUBA6, were found to retard cell death. Among them, SPP1, ARHGDIB and TUBA3 had a cell death activity with a statistically significant level compared to the control gene (P < 0.05). In particular, SPP1 and TUBA3 had a high anti-apoptotic activity, similar to those of Bcl-2 and Bcl-xl which are known as anti-apoptotic genes (Fig. 4B). The remaining genes had no activity related to cell death (data not shown). These results indicate that genes related to cell death exist in genes which are differentially expressed between human normal SN and PD's SN. In particular, genes which accelerate cell death were highly present in the upregulated genes, whereas genes which retard cell death were present in downregulated genes.


Figure 4
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  		Figure 4. Cell death activity of differentially expressed genes in PD. (A) Upregulated genes in PD. (B) Downregulated genes in PD. SH-SY5Y cells were transfected with DNA of both the target gene and the pDsRed2-Mito vector. After 24 h, cell death was induced by the administration of 1 mM MPTP and cell death activity was measured (for details, see Materials and Methods). The human Bcl-2 and Bcl-xl genes were used as a positive control for anti-apoptotic activity and the pcDNA-HA plasmid as a negative control. Asterisk denotes a significant difference between the tested gene and the pcDNA-HA vector by the t test (P < 0.05).

 

   4. Discussion
Top
 Abstract
 1. Introduction
 2. Materials and methods
 3. Results
 4. Discussion
Acknowledgements
 REFERENCES
 
A global gene expression analysis profile extracted from an ESTs database has been reported to provide important clues for our understanding of the development of human disease and has led to improvements in our ability to predict its clinical behavior.29Go However, a comprehensive analysis of ESTs in human PD has not been reported. In order to investigate genes that are associated with human PD, we undertook the large-scale sequencing of cDNA libraries of human SN tissues from normal and PD, and examined the difference in gene expression profiles between them by an EST frequency analysis. The expression levels of selected genes were confirmed in the MPTP mice model as well as in human PD tissues using quantitative real-time RT–PCR in order to overcome the shortage of human PD tissues. Among them, a number of obtained genes were shown to be novel genes which are not reported to be related to PD or not involved in pathways related to PD. Of these genes, some represented the pro- or anti-apoptotic activity related to neuronal cell death in PD.

The profile of our gene expression between human SN tissues of three normal and three PD showed that genes involved in the central nerve system development, Golli-MBP and MBP, were increased in PD's SN. Among them, which are known as structural constituents of the myelin sheath, MBP was recently reported to be upregulated in PD's SN.30Go The expression of the Golli protein was also reported to be increased by activated microglia during neuroinflammation.31Go,32Go From these reports, it is likely that the upregulation of Golli-MBP and MBP in PD's SN is due to the activation of microglia by dopaminergic cell death. In addition, defects in ubiquitination and proteasomal protein handling are reported to be common features of PD and other chronic neurodegenerative disease such as Alzheimer's disease (AD), Huntington's disease and in ageing.5Go,16Go,30Go,33Go These defects have been known to lead to the impairment of several cellular processes that are linked to ubiquitination such as the cell cycle, signaling pathways and the degradation of normal and damaged intracellular proteins.16Go,33Go These reports were consistent with our results that genes, which are involved in protein modification and catabolism such as UBB, RNF5 and ST13 and in signaling transduction such as GNAS, were upregulated in PD. UBB is reported to be immunopositive in the Lewy body of PD1Go and alteration in this gene led to the failure of ubiquitination, finally resulting in cell death and neurological disease.16Go,34Go In addition, some genes that are involved in iron ion transport, FTL and FTH1, were also increased in PD, which is in agreement with other reports of an increase in the case of a 6-OHDA treated cellular PD model15Go and in normal individuals within the age at onset of PD.35Go This result supports the previous report that an abnormal accumulation of iron in SN is a prominent pathological feature of PD.36Go Many genes that are involved in glycolysis such as MDH1 and LDHA were also highly expressed in PD's SN. Ryu et al.15Go reported that genes such as G6PD, HK2, PFK-C, PKM2, LDHA and COX8A were upregulated in a 6-OHDA treated cellular PD model. As suggested by Ryu et al., the upregulation of glycolysis genes is thought to compensate for a decrease in ATP production as the result of mitochondria dysfunction in PD.17Go Furthermore, the upregulation of some genes involved in protein synthesis, EIF4A2, RPS3A, RPL17 and EIF3S5, were also in agreement with a previous report that genes involved in protein synthesis such as EIF4G1, EIF4EBP2 and RPL36 were highly up-expressed in PD SN.16Go Among them, RPL17 is known to be upregulated in multiple sclerosis (MS).37Go Genes such as TPT1, PBP, VIM, THY1, HMOX2 and PAQR6 were also upregulated in PD, but their relation to PD has not yet been reported, although HMOX1, an isozyme of HMOX2, is known to have the capacity to promote neurodegeneration through the pathological deposition of free iron.

On the other hand, many genes for proteins that participate in protein folding, protein transport, and proteolysis and peptidolysis were downregulated in PD's SN. These data support a previous report that genes related to protein degradation were downregulated in PD.17Go,18Go This is also in agreement with previous findings that protein misfolding can lead to the accumulation of protein aggregates and confer toxic properties on cells in PD and AD.38Go,39Go In addition, our data revealed that genes which are involved in the immune response such as SPP1, CD74, ACT and ARHGDIB are particularly downregulated in PD. SPP1 was reported to be upregulated in several types of cancer and MS,37Go but its involvement in PD has not yet been reported. ACT was reported to be useful as a screening marker for Alzheimer-type dementia40Go and a polymorphism in this gene was found in PD patients.41Go In addition, tubulin genes such as TUBA6, K-ALPHA-1, MGC8685 and TUBA3, which were involved in microtube-based movement, were downregulated in our data. The decrease of tubulin genes were also reported in dopaminergic cell by oxidative stress18Go and in human PD's SN.16Go,30Go In our data, genes that are related to protein synthesis such as RPL15 and RPL13 were also downregulated in PD's SN. However, protein synthesis related genes such as EIF4A2, RPS3A and RPL17 were shown to upregulated in PD's SN. These data indicate that they might have a different function in PD, although they belong to the same protein synthesis category. In addition, BBOX1, HNRPC and AQP4 were downregulated in PD. AQP4 was found to be upregulated in brain injuries and tumors42Go but, downregulated in human muscles with neurogenic atrophy.43Go

The administration of MPTP to mice is one of the most common animal models used in PD studies. When the expression level of PD candidate genes selected from human PD were checked in MPTP mice model, it coincided with about 50% between human SN and the MPTP mice model. These difference due to the MPTP mouse model compared to human PD showed subchronic progress, no formation of the Lewy body which is a pathological hallmark of human PD,6Go and did not directly address the involvement of systemic mitochondrial impairment in PD.9Go Among the selected genes, the downexpression of TUBA6 and TUBA3 genes in PD was also detected by its protein level using immunohistochemistry, although a decrease in each protein was specifically not detected. These results indicate that the downregulation of TUBA6 and TUBA3 genes couples transcription to translation. In addition, genes related to cell death were identified from some of the selected target genes. In particular, MBP, PBP, GNAS and PAQR6, which are upregulated in PD, were shown to have activity with accelerating cell death. Among them, it was reported that PBP, also known as RKIP, may represent a novel effector of signal transduction pathways leading to apoptosis.44Go On the other hand, SPP1 and TUBA3, both of which are downregulated in PD, have activity with retarding cell death. SPP1 was reported to be an anti-apoptosis molecule by ISS (inferred by sequence similarity) in Gene Ontology. These data indicate that our target genes might be a candidate related to apoptotic events that induce neuronal cell death in SN region.

The gene expression profile from our study partially supports a previous hypothesis for PD that iron transport proteins which are upregulated in PD, FTL and FTH1, affect the iron redox status and then contribute to protein misfolding and aggregation in ageing, leading to disease affected brains. Such protein misfolding and aggregation were linked to an increase in protein modification proteins, UBB and ST13, and a decrease in proteins that are involved in protein folding, proteolysis and peptidolysis. In addition, the observed elevation of HMOX2 also accelerated neurodegeneration through the deposition of free iron. In addition to this hypothesis, since a number of genes involved in central nervous system development, glycolysis, protein synthesis and immune response as well as genes related to apoptotic events were shown to be related to PD, a more complex mechanism including neuroprotective response as well as neuronal death appears to be involved in PD.

To examine the tissue specificity of the PD-related genes, the expression levels of our selected genes were analyzed using a public database (UniGene database build #181) and our internal ESTs databases including mainly brain, stomach, and liver ESTs. The results revealed that most of the upregulated genes have a high expression frequency in PD compared to other tissue sources including brain tumors, and most of the downregulated genes have a high frequency in normal individual (data not shown). In particular, upregulated genes such as MBP, Golli-MBP, UBB, TPT1, PBP, EIF4A2, THY1, MDH1, PAQR6, EIF3S5, KIAA1276, PTK9 and DJ462O23.2 were shown to be highly present in PD's SN tissues, while downregulated genes such as SPP1, BBOX1, RPL15, TMP21, RPL13A, AQP4 and EIF3S2 were present in normal brain SN. These results indicate that our selected PD candidate genes are specifically expressed in PD's SN compared to other tissues.

The PD candidate genes newly identified in our study showed a high relation to PD in the data for transcript and protein levels in the MPTP-mice model, for cell death activity in a human neuroblastoma cell line, and for the expression analysis on a public database. These PD candidate genes should provide valuable resources for developing an understanding of the molecular mechanism associated with PD in the SN of the brain and for discovering potential diagnostic/therapeutic markers for PD, although the transcript level in the SN of PD patients as well as MPTP mouse model reflect alterations in gene expression in not only neurons but also astroglia and microglia, because the loss of dopaminergic neurons in the SN of PD accompany robust astrogliosis and microglial reactions.


   Acknowledgements
Top
 Abstract
 1. Introduction
 2. Materials and methods
 3. Results
 4. Discussion
 Acknowledgements
REFERENCES
 
We wish to express our appreciation for the gift of human SN tissue (HSB#3482, HSB#3484 and HSB#36 42) specimens from the Human Brain and Spinal Fluid Resource Center, VA West Los Angeles Healthcare Center, LA, CA 90073, which is sponsored by NINDS/NIMH, the National Multiple Sclerosis Society, and the Department of Veterans Affairs. We also thank the supply of the mice from Institute of Animal Resources, Kangwon National University, Korea. We also thank Yong-Keun Jung, School of Biological Sciences, Seoul National University, Korea, for technical support regarding the cell death activity assay and Jae-Hee Pyo, KRIBB, for technical assistance in the construction of the MPTP mice models. This work was supported by a grant M103KV01000303 K2201 of the MOST 21C Frontier R & D program in neuroscience from the Ministry of Science & Technology of Korea, a grant R01-2004-000-10095-0 from the Basic Research Program of the Korea Science and Engineering Foundation and by KRIBB Research Initiative Program.


   Footnotes
 
*To whom correspondence should be addressed. Tel. +82-42-879-8112, Fax. +82-42-879-8119. E-mail: nskim37{at}kribb.re.kr

Communicated by Shoji Tsuji Sequence data from this article have been deposited with the GenBank Data Libraries under Accession Nos DT214917 [GenBank] –DT221046 [GenBank] .


   REFERENCES
Top
 Abstract
 1. Introduction
 2. Materials and methods
 3. Results
 4. Discussion
 Acknowledgements
 REFERENCES
 

  1. Smeyne, R. J. and Jackson-Lewis, V. 2005, The MPTP model of Parkinson's disease, Brain Res. Mol. Brain Res., 134, 57–66.[Medline]
  2. Bossy-Wetzel, E., Schwarzenbacher, R., Lipton, S. A. 2004, Molecular pathways to neurodegeneration, Nat. Med., 10, Suppl, S2–S9.
  3. Dauer, W. and Przedborski, S. 2003, Parkinson's disease: mechanisms and models, Neuron, 39, 889–909.[CrossRef][ISI][Medline]
  4. Jenner, P. and Olanow, C. W. 1998, Understanding cell death in Parkinson's disease, Ann. Neurol., 44, S72–S84.[CrossRef][ISI][Medline]
  5. Dawson, T. M. and Dawson, V. L. 2003, Molecular pathways of neurodegeneration in Parkinson's disease, Science, 302, 819–822.[Abstract/Free Full Text]
  6. Beal, M. F. 2001, Experimental models of Parkinson's disease, Nat. Rev. Neurosci., 2, 325–334.[ISI][Medline]
  7. Siderowf, A. and Stern, M. 2003, Update on Parkinson disease, Ann. Intern. Med., 138, 651–658.[Abstract/Free Full Text]
  8. Warner, T. T. and Schapira, A. H. 2003, Genetic and environmental factors in the cause of Parkinson's disease, Ann. Neurol., 53, Suppl 3, S16–S23 discussion S23–S15.
  9. Betarbet, R., Sherer, T. B., Greenamyre, J. T. 2002, Animal models of Parkinson's disease, Bioessays, 24, 308–318.[CrossRef][ISI][Medline]
  10. Adams, M. D., Kelley, J. M., Gocayne, J. D., et al. 1991, Complementary DNA sequencing: expressed sequence tags and human genome project, Science, 252, 1651–1656.[Abstract/Free Full Text]
  11. Kim, N. S., Hahn, Y., Oh, J. H., et al. 2004, Gene cataloging and expression profiling in human gastric cancer cells by expressed sequence tags, Genomics, 83, 1024–1045.[CrossRef][ISI][Medline]
  12. DeRisi, J., Penland, L., Brown, P. O., et al. 1996, Use of a cDNA microarray to analyse gene expression patterns in human cancer, Nat. Genet., 14, 457–460.[CrossRef][ISI][Medline]
  13. Kim, J. M., Sohn, H. Y., Yoon, S. Y., et al. 2005, Identification of gastric cancer-related genes using a cDNA microarray containing novel expressed sequence tags expressed in gastric cancer cells, Clin. Cancer Res., 11, 473–482.[Abstract/Free Full Text]
  14. Velculescu, V. E., Zhang, L., Vogelstein, B., Kinzler, K. W. 1995, Serial analysis of gene expression, Science, 270, 484–487.[Abstract/Free Full Text]
  15. Ryu, E. J., Angelastro, J. M., Greene, L. A. 2005, Analysis of gene expression changes in a cellular model of Parkinson disease, Neurobiol. Dis., 18, 54–74.[CrossRef][ISI][Medline]
  16. Grunblatt, E., Mandel, S., Jacob-Hirsch, J., et al. 2004, Gene expression profiling of parkinsonian substantia nigra pars compacta; alterations in ubiquitin-proteasome, heat shock protein, iron and oxidative stress regulated proteins, cell adhesion/cellular matrix and vesicle trafficking genes, J. Neural. Transm., 111, 1543–1573.[CrossRef][ISI][Medline]
  17. Hauser, M. A., Li, Y., Xu, H., et al. 2005, Expression profiling of substantia nigra in Parkinson disease, progressive supranuclear palsy, and frontotemporal dementia with parkinsonism, Arch. Neurol., 62, 917–921.[Abstract/Free Full Text]
  18. Yoo, M. S., Chun, H. S., Son, J. J., et al. 2003, Oxidative stress regulated genes in nigral dopaminergic neuronal cells: correlation with the known pathology in Parkinson's disease, Brain Res. Mol. Brain Res., 110, 76–84.[Medline]
  19. Grunblatt, E., Mandel, S., Maor, G., Youdim, M. B. 2001, Gene expression analysis in N-methyl-4-phenyl-1,2,3,6-tetrahydropyridine mice model of Parkinson's disease using cDNA microarray: effect of R-apomorphine, J. Neurochem., 78, 1–12.[CrossRef][ISI][Medline]
  20. Mandel, S., Grunblatt, E., Maor, G., Youdim, M. B. 2002, Early and late gene changes in MPTP mice model of Parkinson's disease employing cDNA microarray, Neurochem. Res., 27, 1231–1243.[CrossRef][ISI][Medline]
  21. Okubo, K., Hori, N., Matoba, R., et al. 1992, Large scale cDNA sequencing for analysis of quantitative and qualitative aspects of gene expression, Nat. Genet., 2, 173–179.[CrossRef][ISI][Medline]
  22. Mao, M., Fu, G., Wu, J. S., et al. 1998, Identification of genes expressed in human CD34(+) hematopoietic stem/progenitor cells by expressed sequence tags and efficient full-length cDNA cloning, Proc. Natl Acad. Sci. USA, 95, 8175–8180.[Abstract/Free Full Text]
  23. Oh, J. H., Kim, Y. S., Kim, N. S. 2003, An improved method for constructing a full-length enriched cDNA library using small amounts of total RNA as a starting material, Exp. Mol. Med., 35, 586–590.[ISI][Medline]
  24. Soares, M. B., Bonaldo, M. F., Jelene, P., Su, L., Lawton, L., Efstratiadis, A. 1994, Construction and characterization of a normalized cDNA library, Proc. Natl Acad. Sci. USA, 91, 9228–9232.[Abstract/Free Full Text]
  25. Audic, S. and Claverie, J. M. 1997, The significance of digital gene expression profiles, Genome Res., 7, 986–995.[Abstract/Free Full Text]
  26. Paxions, G. and Franklin, K. J. The mouse brain in stereotaxic coordinates2001, San Diego Academic Press.
  27. Song, X., Perkins, S., Jortner, B. S., Ehrich, M. 1997, Cytotoxic effects of MPTP on SH-SY5Y human neuroblastoma cells, Neurotoxicology, 18, 341–353.[ISI][Medline]
  28. Kugawa, F., Matsumoto, K., Aoki, M. 2004, Apoptosis-like cell death of human breast cancer cell line MCF-7 induced by buprenorphine hydrochloride, Life Sci., 75, 287–299.[CrossRef][ISI][Medline]
  29. Krizman, D. B., Wagner, L., Lash, A., Strausberg, R. L., Emmert-Buck, M. R. 1999, The Cancer Genome Anatomy Project: EST sequencing and the genetics of cancer progression, Neoplasia, 1, 101–106.[CrossRef][Medline]
  30. Noureddine, M. A., Li, Y., van der Walt, J. M., et al. 2005, Genomic convergence to identify candidate genes for Parkinson disease: SAGE analysis of the substantia nigra, Mov. Disord., 20, 1299–1309.[CrossRef][ISI][Medline]
  31. Filipovic, R. and Zecevic, N. 2005, Interaction between microglia and oligodendrocyte cell progenitors involves Golli proteins, Ann. NY Acad. Sci., 1048, 166–174.[Abstract/Free Full Text]
  32. Filipovic, R. and Zecevic, N. 2005, Lipopolysaccharide affects Golli expression and promotes proliferation of oligodendrocyte progenitors, Glia, 49, 457–466.[CrossRef][ISI][Medline]
  33. Ciechanover, A. and Brundin, P. 2003, The ubiquitin proteasome system in neurodegenerative diseases: sometimes the chicken, sometimes the egg, Neuron, 40, 427–446.[CrossRef][ISI][Medline]
  34. Ding, Q. and Keller, J. N. 2001, Proteasomes and proteasome inhibition in the central nervous system, Free Radic. Biol. Med., 31, 574–584.[CrossRef][ISI][Medline]
  35. Hauser, M. A., Li, Y. J., Takeuchi, S., et al. 2003, Genomic convergence: identifying candidate genes for Parkinson's disease by combining serial analysis of gene expression and genetic linkage, Hum. Mol. Genet., 12, 671–677.[Abstract/Free Full Text]
  36. Mandel, S., Maor, G., Youdim, M. B. 2004, Iron and alpha-synuclein in the substantia nigra of MPTP-treated mice: effect of neuroprotective drugs R-apomorphine and green tea polyphenol (-)-epigallocatechin-3-gallate, J. Mol. Neurosci., 24, 401–416.[CrossRef][ISI][Medline]
  37. Steinman, L. and Zamvil, S. 2003, Transcriptional analysis of targets in multiple sclerosis, Nat. Rev. Immunol., 3, 483–492.[CrossRef][ISI][Medline]
  38. Selkoe, D. J. 2004, Cell biology of protein misfolding: the examples of Alzheimer's and Parkinson's diseases, Nat. Cell Biol., 6, 1054–1061.[CrossRef][ISI][Medline]
  39. Henn, I. H., Gostner, J. M., Lackner, P., Tatzelt, J., Winklhofer, K. F. 2005, Pathogenic mutations inactivate parkin by distinct mechanisms, J. Neurochem., 92, 114–122.[CrossRef][ISI][Medline]
  40. Matsubara, E., Hirai, S., Amari, M., et al. 1990, Alpha 1-antichymotrypsin as a possible biochemical marker for Alzheimer-type dementia, Ann. Neurol., 28, 561–567.[CrossRef][ISI][Medline]
  41. Yamamoto, M., Kondo, I., Ogawa, N., Asanuma, M., Yamashita, Y., Mizuno, Y. 1997, Genetic association between susceptibility to Parkinson's disease and alpha1-antichymotrypsin polymorphism, Brain Res., 759, 153–155.[CrossRef][ISI][Medline]
  42. Vizuete, M. L., Venero, J. L., Vargas, C., et al. 1999, Differential upregulation of aquaporin-4 mRNA expression in reactive astrocytes after brain injury: potential role in brain edema, Neurobiol. Dis., 6, 245–258.[CrossRef][ISI][Medline]
  43. Jimi, T., Wakayama, Y., Matsuzaki, Y., Hara, H., Inoue, M., Shibuya, S. 2004, Reduced expression of aquaporin 4 in human muscles with amyotrophic lateral sclerosis and other neurogenic atrophies, Pathol. Res. Pract., 200, 203–209.[CrossRef][ISI][Medline]
  44. Chatterjee, D., Bai, Y., Wang, Z., et al. 2004, RKIP sensitizes prostate and breast cancer cells to drug-induced apoptosis, J. Biol. Chem., 279, 17515–17523.[Abstract/Free Full Text]

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