Neuroscience Letters 599 (2015) 140–145
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Neuroscience Letters journal homepage: www.elsevier.com/locate/neulet
Transcriptional regulation of the ␣-synuclein gene in human brain tissue Steffen Brenner a,∗ , Christophe Wersinger a,b , Thomas Gasser a,b a b
Hertie Institute for Clinical Brain Research, Department of Neurodegenerative diseases, University of Tübingen, Tübingen, Germany German Center for Neurodegenerative diseases (DZNE), Tübingen, Germany
h i g h l i g h t s • • • •
We identiﬁed a new binding site for GATA2 within the 5 -promoter of SNCA. zinc ﬁnger proteins ZSCAN21 occupy a speciﬁc region within human SNCA intron 1. zinc ﬁnger proteins GATA2 occupy a speciﬁc region within human SNCA intron 2. No SNPs or mutations were found within the binding sites of ZSCAN21 and GATA2.
a r t i c l e
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Article history: Received 5 February 2015 Received in revised form 14 May 2015 Accepted 15 May 2015 Available online 19 May 2015 Keywords: ␣-Synuclein Parkinson’s disease ZSCAN21 GATA2 Gene expression SNP
a b s t r a c t The transcriptional regulation of the gene encoding ␣-synuclein (SNCA) is thought to play a critical role in the pathogenesis of Parkinson’s disease (PD), as common genetic variability in this gene is associated with an elevated risk of developing PD. However, the relevant mechanisms are still poorly understood. So far, only few proteins have been identiﬁed as transcription factors (TFs) of SNCA in cellular models. Here we show that two of these TFs bind to the DNA in human brain tissue: the zinc ﬁnger protein ZSCAN21 occupies a region within SNCA intron 1, as described before, while GATA2 occupies a speciﬁc region within intron 2, where we have identiﬁed a new binding site within the complex structure of the 5 -promoter region of SNCA. Electrophoretic mobility shift assays conﬁrmed these binding sites. Genetic investigations revealed no polymorphisms or mutations within these sites. A better understanding of TF-DNA interactions within SNCA may allow to develop novel therapies designed to reduce ␣-synuclein levels. © 2015 Elsevier Ireland Ltd. All rights reserved.
1. Introduction Parkinson’s disease (PD) is the second most common neurodegenerative disorder after Alzheimer’s disease. About 5% of the cases show a Mendelian inheritance pattern. The SNCA gene and its product ␣-synuclein are linked both pathologically and genetically to PD. It is the main component of Lewy bodies which are pathological hallmarks of familial and sporadic forms of PD . The fact that not only point mutations in the SNCA gene [2–4] but also multiplications of the SNCA locus [5,6] can cause rare familial forms
Abbreviations: PD, Parkinson’s disease; TF, transcription factor; SNP, single nucleotide polymorphism; TFBS, transcription factor binding sites; siRNAs, small interfering RNAs; IP, immunoprecipitation; qRT-PCR, quantitative real-time PCR; ChIP, chromatin immunoprecipitation; bp, base pairs; EMSA, electrophoretic mobility shift assay; UTR, untranslated region. ∗ Corresponding author. Tel.: +49 17662502415. E-mail address: [email protected]
(S. Brenner). http://dx.doi.org/10.1016/j.neulet.2015.05.029 0304-3940/© 2015 Elsevier Ireland Ltd. All rights reserved.
of PD indicates that an increased expression level of wild-type ␣synuclein is sufﬁcient to cause PD. In addition, genome-wide association studies revealed that SNCA is not only linked to the rare familial forms of PD, but also to the more common sporadic cases . A number of polymorphisms in the 5 -promoter region and 3 -untranslated region (UTR) of SNCA were identiﬁed which are associated with both an increased risk to develop PD [8,9] and with signiﬁcantly higher SNCA expression levels in blood and brain . Thus, single nucleotide polymorphisms (SNPs) in the promoter region could affect the binding of transcription factors (TFs) or other regulatory elements. Despite the importance of SNCA expression, there is a paucity of knowledge about TFs of SNCA. Eight regulatory regions responsive to the basic leucine zipper domain TF C/EBP␤ have been described in the SNCA promoter which may mediate increased expression of SNCA after dopamine-induced cell stress in SH-SY5Y neuroblastoma cells . Other TFs identiﬁed to modulate SNCA expression in vitro are the TF zinc ﬁnger and SCAN domain containing ZSCAN21
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, as well as the TF zinc ﬁnger protein GATA2 . The latter ones have been shown to activate SNCA expression in cellular models. Small interfering RNAs (siRNAs) against ZSCAN21 or GATA2, respectively, reduce ␣-synuclein levels. Binding sites for both TFs within the 5 -promoter of SNCA have been identiﬁed [12,13]. In the present study, we have focused on C/EBP␤, ZSCAN21 and GATA2. We have investigated, whether these TFs bind speciﬁcally to the DNA at the SNCA locus in human brain cells, since all previous work has been done with model systems. We could conﬁrm some of the previous results and we present additional ﬁndings concerning TF-DNA interactions in human brain cells.
2.5. Primers Quantitative real-time PCR (qRT-PCR) primers were designed to amplify 75–275 bp fragments according to the binding sites identiﬁed with MatInspector. Ampliﬁcation products for high resolution melting and sequencing analyses ranged from 80 to 150 bp. All primers were designed using Primer-BLAST software (http:// www.ncbi.nlm.nih.gov/tools/primer-blast), synthesized and HPLCpuriﬁed by Metabion International. Sequences can be found in Supplementary material. 2.6. Chromatin immunoprecipitation (ChIP) assays and qRT-PCR
2. Materials and methods 2.1. Human post mortem tissues Brain tissue was provided by the German Brain Bank “BrainNet”. Only tissue from neurologically healthy donors was used. Donors were at the age of 67–78. Males and females were included equally. Four tissue samples from different areas of the brain (frontal cortex, cingulate gyrus and medulla oblongata) were used. The project was approved by the Ethics Committee of the Faculty of Medicine of the University of Tübingen.
2.2. DNA for genotyping DNA was obtained from the Biobank of the Hertie Institute for Clinical Brain Research. Only DNA from patients suffering from idiopathic PD was used. Patients were at the age of 25–87. Males and females were included equally. DNA was extracted from the patients’ blood after informed consent following our established protocol (Supplementary material).
2.3. Western blotting and immunoprecipitation (IP) assays Nuclear proteins were isolated from human brain tissue using the DUALXtract Nuclear and cytoplasmic protein extraction kit (Dualsystems Biotech). Lysates were mixed with Laemmli buffer, denaturated at 85 ◦ C for 20 min and subsequently run on 10% SDS polyacrylamide gels. Proteins were then transferred to PDVF membranes. Membranes were incubated with antibodies directed against GATA2, C/EBP␤ or ZSCAN21 (all 1:1000, Santa Cruz Biotechnology). Membranes were probed with HRP-conjugated secondary antibodies and developed with ImmobilonTM Western HRP Substrate Peroxide Solution (Millipore) followed by exposure to autoradiographic ﬁlms (HyperﬁlmTM ECL, Amersham). For the negative controls bovine serum albumin was used instead of nuclear proteins. For the IP assays, lysates were incubated with 2 g of antibodies directed against ZSCAN21 (Santa Cruz Biotechnology) followed by adding Protein A/G agarose beads and another incubation period. For the negative controls an irrelevant antibody of the same isotype was used. Immune complexes bound to agarose beads were then pelleted by centrifugation, subsequently washed three times in Tris buffer, denaturated in Laemmli buffer and resolved by Western blotting as described.
2.4. Bioinformatics Promoter analysis and prediction of potential transcription factor binding sites (TFBS) was performed using MatInspector software version 8.0.4 with MatInspector library version 8.3 from Genomatix.
ChIP assays were performed as previously described  using approximately 0.5 cm3 of human brain tissue and antibodies directed against GATA2, C/EBP␤ or ZSCAN21 (all from Santa Cruz Biotechnology). The DNA concentration was measured relatively by qRT-PCR. qRT-PCR was performed in duplicates for each sample and input DNA ( = genomic DNA) using LightCycler480 SYBR Green I Master (Roche) according to the manufacturer’s protocol in a Light cycler 2.0 RT-PCR system (Roche). For every binding site investigated, relative differences in DNA quantity were calculated by subtracting the Ct -value of the chromatin immunoprecipitated sample from the Ct -value of the input DNA. Expression levels of the target sequences were normalized to a housekeeping gene (amyloid precursor protein). PCR efﬁciency was measured for every approach and differences were considered in the calculations. Ct values were calculated by the Light cycler 3 software version 3.5 (Roche). 2.7. Electrophoretic mobility shift assays (EMSA) Double-stranded DNA probes were designed according to the TFBSs identiﬁed with ChIP assays for GATA2 (5 -GGCCCCGGTGTTATCTCATTCTTTT-3 ) and ZSCAN21 (5 Oligonucleotides were GACGAGGGGTAGGGGGTGGTCCC-3 ). synthesized and 3 -labeled with biotin by Metabion International. Assays were performed using the Gel Shift Chemiluminescent EMSA Assay Kit (Active Motif) according to the manufacturer’s instructions. For every approach 20 fmol labeled oligonucleotides were incubated in 1X binding buffer (Active Motif), 50 ng poly(dI/dC), 14.3% Glycerol, 200 mM KCl, 17.9 mM MgCl2 and 18 g of nuclear extract at room temperature for 20 min and subsequently run on a 4% non-denaturating polyacrylamide gel. Probes were then transferred on a nylon membrane (Sigma), cross-linked and developed using the reagents included in the kit, followed by exposure to HyperﬁlmTM ECL autoradiographic ﬁlms (Amersham). 2.8. Genotyping High resolution melting analyses were performed with High Resolution Melting Master (Roche) according to the manufacturer’s protocol in a Light cycler 2.0 RT-PCR system (Roche). Optimal primer concentration was found to be 0.25 M and MgCl2 concentration to be 1.25 mM. For every approach approximately 50 ng DNA was used and melting analyses were performed after 45 ampliﬁcation cycles. A sample set of 30 patients was analyzed with every run. Subsequently the melting curves of all samples were visualized in one graph using Light cycler 3 software version 3.5 (Roche). Melting curves which differed from the majority of curves were considered as “suspicious”. Samples with suspicious melting curves were genotyped by performing PCR ampliﬁcation, followed by Sanger sequencing of the puriﬁed PCR fragments using BigDye Terminator v3.1Cycle Sequencing kit (Applied Biosystems) in an ABI PRISM 3130xl
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Genetic Analyzer system (Applied Biosystems) according to the manufacturer’s instructions. Ampliﬁcation was performed in a 20 l reaction mix including 40 ng DNA, 0.2 M of each primer, 200 M dNTP mix and 0.5 U of Taq DNA polymerase together with GoTaq PCR buffer (both from Promega). Following 35 ampliﬁcation cycles, DNA was puriﬁed by ethanol/sodium acetate precipitation. Prior to sequencing, products were visualized on agarose gels by electrophoresis to verify speciﬁcity. Sequence results were analyzed using Gap4 software (Staden Package). 3. Results 3.1. GATA2, C/EBPˇ and ZSCAN21 TFs are expressed in several brain regions GATA2 has been shown to be abundantly expressed at both mRNA and protein levels in substantia nigra and frontal cortex . C/EBP␤ was previously described in frontal cortex . Since protein levels of ZCSAN21 in human brain tissue were never described, we performed Western blot analyses on nuclear lysates from human brain tissues. We were able to detect GATA2 and C/EBP␤ in frontal cortex, cingulate gyrus and medulla oblongata (Supplementary material Fig. 1A and B), but we failed to detect ZSCAN21. However, using IP assays to concentrate ZSCAN21, we observed a clear band for all brain regions investigated (Supplementary material Fig. 1C), suggesting low expression levels. 3.2. SNCA contains several putative promoter regions and TFBSs for GATA2, C/EBPˇ and ZSCAN21 SNCA consists of six exons (Fig. 1A) with the translational start site encoded by exon 2 . The promoter region of SNCA seems to be a complex structure including at least intron 1 [12,13]. We used MatInspector software for the prediction of potential promoter regions and could identify 6 sites (Supplementary material Table 1). These regions were located in the 5 -UTR and also within intron 1 and intron 2. Predicted promoter regions included a total of 11 putative TFBSs for GATA2, 4 sites for C/EBP␤ and 2 sites for ZSCAN21, respectively (Fig. 1B and Supplementary material Table 1). An additional putative TFBS for GATA2 was identiﬁed outside these regions (Fig. 1B and Supplementary material Table 1). Previously identiﬁed TFBSs for GATA2  and ZSCAN21  were among these sites. In addition to these ﬁndings, several other putative TFBSs for many different TFs were identiﬁed within these sites (data not shown). 3.3. ZSCAN21 occupies a region within SNCA intron 1, while GATA2 occupies a speciﬁc region within intron 2 To determine which of the TFBSs identiﬁed with MatInspector software have functional signiﬁcance, we performed ChIP analyses. Analysis of all 18 potential TFBSs for GATA2, C/EBP␤ and ZSCAN21 revealed that GATA2 occupies a speciﬁc region within intron 2, while ZSCAN21 occupies a single region within SNCA intron 1 (Fig. 1C). No signiﬁcant occupancy was detected at the other putative TFBSs for GATA2 and ZSCAN21. The same results were obtained for C/EBP␤ TFBSs. These ﬁndings were identical in all investigated brain areas. Thus, both GATA2 and ZSCAN21 TFs interact only with one selected site, respectively, among all potential TFBSs. 3.4. GATA2 and ZSCAN21 occupy the identiﬁed TFBSs with high speciﬁcity To further study the TF-DNA interactions identiﬁed with ChIP analyses, we performed EMSAs. As expected, we observed speciﬁc band shifts, when the GATA2 binding site was incubated with
nuclear extracts from human brain tissue (Fig. 2A, lane 2). The same observation was made for the ZSCAN21 binding site (Fig. 2B, lane 6). In the presence of a 200x-molar excess of speciﬁc competitor (unlabeled DNA with the same sequence as labeled DNA probes), there was no shift of the GATA2 band (Fig. 2A, lane 3) and a reduction of intensity of the shifted band for ZSCAN21 (Fig. 2B, lane 7). This loss or reduction of band shift was not observed when a 200x-molar excess of non-speciﬁc competitor (unlabeled DNA with a random sequence) was added (Fig. 2A, lane 4 and Fig. 2B, lane 8, respectively). Identical results were obtained using nuclear lysates from all investigated brain regions. The loss or attenuation of shifted bands in the presence of excess of unlabeled speciﬁc DNA, but not with an excess of unlabeled non-speciﬁc probe, veriﬁed that shifts result from speciﬁc DNA-protein interactions. 3.5. TFBSs of GATA2 and ZSCAN21 in patients suffering from PD are not altered by polymorphisms With the knowledge of the identiﬁed TFBSs we screened the DNA of 300 PD patients for potential rare polymorphisms within these sites that could lead to an alteration of TF binding. First, we performed high resolution melting analyses as a quick method to identify potential SNPs. Using this approach, 42 samples for the GATA2 TFBS and 97 samples for the ZSCAN21 TFBS could be identiﬁed whose melting curves were considered as suspicious. Suspicious melting curve results observed with this assay may be due to polymorphisms, but can also be caused by a poor quality of sample, inappropriate PCR reactions, pipetting errors, etc. In particular this seemed to apply to the ZSCAN21 TFBSs, since numerous melting curves were considered as suspicious. We then performed Sanger sequencing for all samples with suspicious melting curve results. Comparison of those sequences to the reference sequence revealed no polymorphisms within these sites. 4. Discussion 4.1. The complex structure of SNCA promoter regions Several previous studies indicated that SNCA contains a complex regulatory region which determines its level of transcription [12,13]. Additionally, the classical view of gene transcription, initiated by a speciﬁc TF-DNA interaction, has been replaced by the concept that transcriptional regulation requires the interaction of several regulatory elements, which can bind to upstream, downstream and intronic DNA sequences . Thus, it was not surprising that TFBSs predicted by MatInspector software spanned a long genomic distance and were located in the 5 -UTR, but also within intron 1 and intron 2. Within these locations, putative TFBSs for several different TFs were identiﬁed, suggesting that regulation of SNCA expression is governed by multiple DNA-binding elements. 4.2. Transcriptional regulation of SNCA by ZSCAN21 and GATA2 Previous studies have identiﬁed speciﬁc TFBSs for ZSCAN21 and GATA2, respectively, within intron 1. ␣-Synuclein protein levels signiﬁcantly decreased after knock-down of ZSCAN21 and GATA2 using siRNAs, conﬁrming their role as TFs for SNCA [12,13]. Here, we assessed whether these previous ﬁndings obtained from cellular models can be extrapolated to cells from human brain tissues. We could conﬁrm the previously reported interaction of ZSCAN21 with a speciﬁc TFBS in intron 1 . Thus, this interaction represents a key regulatory mechanism in SNCA gene transcription not only in model systems, but also in the human in vivo situation. Further, we could verify that GATA2 interacts with a SNCA promoter region. Surprisingly, this interaction was not observed in intron 1, as expected from the previous study , but in intron
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Fig. 1. ZSCAN21 occupies a region within SNCA intron 1, while GATA2 occupies a speciﬁc region within intron 2. (A) Human chromosome 4 with SNCA locus and neighboring genes. The organization of the SNCA locus with its 6 exons (black boxes, numbers equal exon numbers) is shown below. (B) Magniﬁcation of the upstream promoter regions of SNCA with the ﬁrst 3 exons. Arrows indicate putative binding sites for GATA2, C/EBP␤ and ZSCAN21 TFs. The most upstream GATA2 binding site was located outside the predicted promoter regions. (C) Analysis of the putative binding sites for GATA2, C/EBP␤ and ZSCAN21 TFs by ChIP showed one interaction for ZSCAN21 within intron 1 (indicated by *) and another one for GATA2 within intron 2 (indicated by **). No interaction was found for C/EBP␤. The white bar graphs depict relative occupancy for each TF at a possible binding site (mean ± standard error, at least three independent experiments). Occupancy was measured as n-fold accumulation of ChIP-DNA in real-time PCR in comparison to ChIP-input ( = genomic DNA). Negative controls ( = ChIP experiments without speciﬁc antibodies) are shown in black. For the exact locations of the TFBSs and the Ct values see Supplementary material Tables 1 and 2.
2. Here, a direct extrapolation from the model system to cells of human brain cannot be made. An explanation for this discrepancy may be that the GATA2 model system consisted of erythroid precursor cells derived from mice . Thus, this model system neither used cells from the same species nor from the same cell type as we used in our study. It is common practice to overcome differ-
ences based on species speciﬁcity by sequence alignments. Indeed, the previously described TFBS is an evolutionary conserved motif, which rendered it likely that this site also exists in human cells. However, some studies have indicated that multispecies sequence comparisons do not predict TF occupancy with high accuracy  and apart from this, it is also important to consider differences
Fig. 2. Electrophoretic mobility shift assays approved ZSCAN21 and GATA2 binding sites. GATA2 (A) and ZSCAN21 (B) oligonucleotide probes were incubated with nuclear extracts of human brain cells. In lanes 1 and 5, double-stranded probes for GATA2 and ZSCAN21, respectively, were run in absence of nuclear extract. When nuclear extract was added (lanes 2 and 6), a clear band shift for both probes was observed. In the presence of a 200x-molar excess of speciﬁc competitor (unlabeled control DNA), there was no shift of the GATA2 band (lane 3) and a reduction of intensity of the shifted band for ZSCAN21 (lane 7). When a 200x-molar excess of non-speciﬁc competitor (unlabeled random DNA) was added, a shift of both the GATA2 band and the ZSCAN21 band was observed again (lanes 4 and 8).
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which are due to cell and tissue speciﬁcity. In this case, different TF occupancy can occur from direct modiﬁcations of TFs  or from epigenetic alterations such as DNA methylation and histone modiﬁcations . As we observed TF-DNA interactions for both ZSCAN21 and GATA2 in all investigated brain regions, it is likely that these regulatory sites are widely used in the brain. This is of particular interest, as deposits of ␣-synuclein are found throughout the brain in PD and other synucleinopathies.
Acknowledgements We thank Oliver Rothfuss for assisting the ChIP assays, Claudia Schulte and Manu Sharma for helping with the SNP databases, AnnKathrin Hauser for supporting the sequencing experiments and Julia Sekler for helping with the qRT-PCR. This work was made possible through the support of a grant from the University of Tübingen (IZKF).
Appendix A. Supplementary data 4.3. The role of C/EBPˇ TFs In this study, we found no interaction for C/EBP␤ with SNCA promoter regions. Thus, it is unlikely that C/EBP␤ acts as a direct TF for SNCA in a physiological setting. When Gomez-Santos et al.  found that ␣-synuclein levels increased with a similar pattern as C/EBP␤ levels, they stressed cells with dopamine. This stress may activate additional pathways, including several kinases , which lead to phosphorylation of C/EBP␤ and thus may alter its binding characteristics. However, overexpression of C/EBP␤ in SH-SY5Y cells was also sufﬁcient to increase ␣-synuclein levels . This raises the possibility that there is indeed a relation between C/EBP␤ and ␣-synuclein, which is not associated with other pathways. With the link of GATA2 to SNCA expression, another explanation is conceivable, since some studies have reported C/EBP␤ as enhancer for GATA TFs [20,21]. These studies have demonstrated that both a protein-protein interaction between C/EBP␤ and GATA TFs and an interaction between them, after their binding to individual TFBSs, are possible. Since we found no interaction of C/EBP␤ with a TFBS, we hypothesize that C/EBP␤ increases the expression of SNCA via a protein-protein enhancer function for GATA2.
4.4. GATA2 and ZSCAN21 TF-DNA interactions are not inﬂuenced by SNPs in patients suffering from idiopathic PD Several SNPs which are associated with both an increased risk to develop idiopathic PD [8,9] and with elevated ␣-synuclein levels  have been identiﬁed. Thus, it can be assumed that at least some of these SNPs may alter the binding of TFs. This hypothesis was further strengthened with the recent ﬁnding that YY1 TFs exclusively bind to the protective allele of a SNP in the 3 -region of SNCA . Thus, we sequenced the identiﬁed TFBSs for ZSCAN21 and GATA2 in a European cohort of patients suffering from idiopathic PD. In this group, we could not identify any polymorphisms within these sites. The search of dbSNP on ncbi (http://www.ncbi.nlm.nih. gov/snp) revealed one annotated SNP, rs35347270, located within the TFBS of ZSCAN21. However, this SNP is poorly validated and did not pass the quality control of the International Parkinson Disease Genomics Consortium when they aimed to identify novel risk loci for PD . Thus, this SNP must be extremely rare, appear only in a particular population or is due to sequencing errors. There is no data available concerning frequency or association with PD. Given these results, it is more likely that SNPs associated with PD and elevated ␣-synuclein levels do not inﬂuence the binding of GATA2 and ZSCAN21. SNPs may have an impact on additional factors as described for YY1 , or the increased PD risk is due to other mechanisms, like alternative splicing of the mRNA, RNA stability, secondary structure or its intracellular transport.
Conﬂict of interests Authors have nothing to disclose.
Supplementary data associated with this article can be found, in the online version, at http://dx.doi.org/10.1016/j.neulet.2015.05. 029
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