Zif268 - Wiley Online Library

Journal of Neurochemistry, 2005, 95, 796–810

doi:10.1111/j.1471-4159.2005.03400.x

Genomic profiling of the neuronal target genes of the plasticity-related transcription factor – Zif268 Allan B. James, Ann-Marie Conway and Brian J. Morris Division of Neuroscience and Biomedical Systems, Institute of Biomedical and Life Sciences, University of Glasgow, Glasgow, Scotland, UK

Abstract The later phases of neuronal plasticity are invariably dependent on gene transcription. Induction of the transcription factor Zif268 (Egr-1) in neurones is closely associated with many forms of functional plasticity, yet the neuronal target genes modulated by Zif268 have not been characterized. After transfection of a neuronal cell line with Zif268 we identified genes that show altered expression using high density microarrays. Although some of the genes identified have previously been associated with forms of neuronal plasticity, the majority have not been linked with neuronal plasticity or Zif268 action. Altered expression of a representative sample of the novel target genes was confirmed in

Zif268-transfected PC12 neurones, and in in vitro and in vivo models of Zif268-associated neuronal plasticity. In particular, altered expression of the protease inhibitor Cystatin C and the chemokine Cxcl10 was observed in striatal tissue after haloperidol administration. Surprisingly, the group of identified genes is enriched for components of the proteasome and the major histocompatibility complex. Our findings suggest that altered expression of these genes following Zif268 induction may be a key component of long lasting plasticity in the CNS. Keywords: Egr1, major histocompatibility complex, microarray, proteasome, synaptic plasticity. J. Neurochem. (2005) 95, 796–810.

Understanding the function of transcription factors (TFs) in the brain is one of the major challenges of contemporary neuroscience. The TF Zif268, also known as Egr-1, Krox24 or NGF-IA, is of particular interest as it is induced in nearly every model of long-lasting synaptic plasticity in the CNS. For example, goldfish retinal neurones express Zif268 during regeneration-associated neurite sprouting (Herdegen et al. 1993), songbird auditory telencephalic neurones show increased Zif268 expression during auditory-associated learning (Mello et al. 1992), ovine orbitofrontal cortical neurones show increased Zif268 expression during olfactoryassociated learning (DaCosta et al. 1997), and primate temporal cortical neurones show increased Zif268 expression during visual-associated learning (Okuno and Miyashita. 1996). Hippocampal long-term potentiation (LTP) is perhaps the best-characterized model of long-lasting synaptic plasticity, and neurones in both CA1 and dentate regions express increased Zif268 after the induction of LTP (Wisden et al. 1990; Roberts et al. 1996), while the duration of hippocampal LTP is correlated with the degree of Zif268 induction (Richardson et al. 1992). Zif268 is also induced in many other types of neurones in numerous plasticity models

(Herdegen et al. 1990; Worley et al. 1991; Fordyce et al. 1994; Miyashita et al. 1998; Ribeiro et al. 1999; Thomas et al. 2003). As suppression of Zif268 prevents neurite outgrowth in PC12 cells (Pignatellia et al. 1999; Levkovitz and Baraban 2002) and, strikingly, mice with a targeted disruption of the Zif268 gene show impaired hippocampal LTP and deficits in a range of memory tests (Jones et al. 2001), the evidence suggests that increased expression of Zif268 is essential for these responses.

796

Received March 23, 2005; revised manuscript received May 31, 2005; accepted July 4, 2005. Address correspondence and reprint requests to A. B. James, Division of Neuroscience and Biomedical Systems, Institute of Biomedical and Life Sciences, West Medical Building, University of Glasgow, Glasgow G12 8QQ, Scotland, UK. E-mail: [email protected] Abbreviations used: AMPA, amino-3-hydroxy-5-methyl-4-isoxazoleproprionic acid; ERE, Egr-response element; FDR, false discovery rate; GO, gene ontology; HPMC, hydroxypropylmethyl polyethylene glycol carbopol934; iGA, iterative group analysis; LTP, long-term potentiation; MHC, major histocompatibility complex; MIAME, minimum information about a microarray experiment; SAM, Significance Analysis of Microarrays; SGK, serum glucocorticoid-inducible kinase; TF, transcription factor; TH, tyrosine hydroxylase; TSS, transcriptional start site.

2005 International Society for Neurochemistry, J. Neurochem. (2005) 95, 796–810

Neuronal target genes of Zif268 797

Zif268 binds to specific target sequences in genomic DNA (Egr-response elements, or EREs) to alter the level of transcription of target genes (Milbrandt 1987). There has been intense interest in identifying the downstream targets of Zif268. Although there has been a traditional view that Zif268 target genes in the CNS will be up-regulated, based on the use of synthetic promoter–reporter constructs in cell lines, the more recent data from peripheral cells suggests that a large proportion of Zif268 target genes are in fact downregulated, and hence that the major role of Zif268 is in suppression of gene expression (Cao et al. 1993; Liu et al. 1996; Beckmann and Wilce 1997; Dinkel et al. 1997; Thottassery et al. 1999; Fukada and Tonks 2001; Bahouth et al. 2002; Davis et al. 2003; Zhang and Liu 2003; Wang et al. 2005). The potential Zif268-regulated genes identified in recent microarray studies using prostate carcinoma cells (Svaren et al. 2000; Virolle et al. 2003) showed no overlap with those identified using a similar approach in endothelial cells (Fu et al. 2003), reflecting a known tissue-specific dimension to the transactivation ability of Zif268. A very few genes have been suggested to be regulated by Zif268 in neurones; including synapsin I (Thiel et al. 1994), synapsin II (Petersohn et al. 1995), and the cdk5-regulator p35 (Harada et al. 2001). However, these are unlikely to be the sole Zif268 target genes in the CNS. Based on the close relationship between Zif268 induction and neuronal plasticity, identification of the neuronal target genes of Zif268 is clearly of major interest. In this study, we have exploited recent advances in microarray technology and analysis to monitor, in cultured neuronal cells, the effect of increased Zif268 expression on the levels of around 8000 distinct mRNAs. We identify a number of genes whose level of expression is modulated in neurones by Zif268. The results shed new light on the changes in the transcriptome that are likely to accompany synaptic plasticity, and suggest previously unrecognized components to the mechanisms of LTP.

Experimental procedures Expression constructs The murine Zif268 expression vector, pZif268, formerly termed pCMVzif, has been described (Groot et al. 2000). As a control expression construct, an N-terminal deletion mutant (D3-372) (Gosslar et al. 1999) of pZif268, termed ptrZif268, was constructed which retains the 5¢ and 3¢ non-coding DNA structure of the fulllength Zif268 insert. Rat Zif268-EGFP fusion constructs were prepared by TOPO cloning an RT–PCR product (amplified from rat cortex total RNA) into pCR-BluntII-TOPO (Invitrogen). Inserts (full length rat Zif268 cDNA and the equivalent N-terminal deletion of the mouse cDNA sequence in rat Zif268 cDNA (DN3-345)) were re-amplified from this construct and cloned in-frame into pEGFP-N2 (BD Biosciences) to give pZif268-EGFP and ptrZif268-EGFP, respectively.

Tissue culture, animals and treatments The PC12 cell culture conditions have previously been described (James et al. 2004). Primary dissociated rat hippocampal cell cultures were prepared as described (Simpson and Morris 2000) and at 7–10 days neurones were stimulated with 100 lM NMDA in the presence of 15 mM KCl, or vehicle, and RNA was extracted 6 h later. Striatal tissue was isolated from male Wistar rats (200–300 g) that had received 1 mg/kg haloperidol (Tocris, Ballwin, MO, USA) or vehicle [1 mL/kg 0.5% hydroxypropylmethyl polyethylene glycol carbopol934 (HPMC)] by i.p. injection; 6 h later the striatal tissue was dissected and RNA extracted as described below. Transient transfections Transient transfection of confluent PC12 cells (90%) seeded in six-well plates has been described previously (Conway et al. 2004; James et al. 2004). Briefly, cells were pre-incubated in penicillin/ streptomycin-free normal growth medium supplemented with 50 ng/mL NGF-7S prior to transfection. Endotoxin-free DNA (2 lg of pCMV5, pZif268, ptrZif268, or the Zif268-EGFP fusion constructs) was combined with Lipofectamine 2000 (LF2000) in OPTI-MEM I Medium incubated at room temperature for 20 min, and then added to the wells. Transfections were performed in the presence of 2 lM forskolin (adenylate cyclase activator). RNA was extracted 48 h post-transfection. Sample preparation and Affymetrix GeneChip hybridization All experiments were performed according to minimum information about a microarray experiment (MIAME) recommendations, using Affymetrix Rat Genome U34A oligonucleotide arrays (http:// www.affymetrix.com/products/arrays/specific/rgu34.affx). Briefly, RNA was extracted from pZif268 (n ¼ 3) and ptrZif268 (n ¼ 3) transiently transfected PC12 cells. Quality and amount of starting RNA was confirmed using a Bioanalyser2100 (Agilent, Palo Alto, CA, USA), whereupon 10 lg of total RNA was used to generate first-strand cDNA by using a T7-oligo(dT) primer. After secondstrand synthesis, in vitro transcription was performed with biotinylated UTP and CTP (Enzo Life Sciences, Inc., Farmingdale, NY, USA). The target cDNA generated from each sample was processed as per manufacturer’s recommendation using an Affymetrix GeneChip Instrument System (http://www.affymetrix.com/support/ technical/manual/expression_manual.affx). Spike controls were added to 20.5 lg unadjusted fragmented cRNA before overnight hybridization. Arrays were then washed and stained with streptavidin–phycoerythrin, before being scanned on an Affymetrix GeneChip scanner. 3¢/5¢ ratios for glyceraldehyde-3-phosphate dehydrogenase (GAPDH) were confirmed to be within acceptable limits (1.13–1.88), and BioB spike controls were found to be present on all chips, with BioC, BioD and CreX also present in increasing intensity. When scaled to a target intensity of 100 (using Affymetrix MAS 5.0 array analysis software), scaling factors for all arrays were within acceptable limits (< threefold differences), as were background, Q-values and mean intensities. RNA integrity, cDNA synthesis, biotin-labelled cRNA preparation and GeneChip hybridizations were carried out at the Sir Henry Wellcome Functional Genomics Facility (SHWFGF), University of Glasgow (http:// www.gla.ac.uk/departments/ibls/ASU/fgf/). The rat genome U34A GeneChip contains probe sets interrogating more than 7000 mRNA transcripts and EST clusters from the UniGene database.


798 A. B. James et al.

GeneChip data analysis Average difference and expression level of genes were calculated according to absolute and comparison analysis algorithms according to Affymetrix protocols. Normalization was performed using BioConductor (http://biohttp://www.dfci.harvard.edu/bioconduc tor/). Expression levels for the pZif268 transfection treatment relative to the control, ptrZif268, treatment were calculated using Significance Analysis of Microarrays (SAM) (Tusher et al. 2001) (http://www-stat.stanford.edu/tibs/SAM/). SAM assigns a score to each gene on the basis of change in gene expression relative to the standard deviation of repeated measurements. This software uses permutations of the repeated measurements to provide an accurate estimate of the percentage of genes identified by chance, the false discovery rate (FDR). Rank product analysis (Breitling et al. 2004b) – an equivalent non-parametric test also incorporating tight control of the false positive rate – was also used to assess the data.

In silico inspection of promoter regions of candidate target genes The program Gene2Promoter (http://www.genomatix.de) was used to extract the promoter regions from a list of accession numbers. Typically a region of 1101 bp [)1000 to +100, whereby +1 is the transcriptional start site (TSS)] was extracted. The program MatInspector (Quandt et al. 1995) (http://www.genomatix.de) was used to locate putative ERE sites in a DNA sequence. This program utilizes the TRANSFAC database (Wingender et al. 2000) [TRANSFAC is the database on eukaryotic TFs, their genomic binding sites, and DNA-binding profiles (http://www.gene-regulation.com)] to identify matches in DNA sequences. The output consists of a table indicating a list of putative binding sites. Core similarity was set at the default level of 0.75. For comparison, a selection of randomly chosen genes was obtained using the random gene selection tool at the ‘Regulatory Sequence Analysis Tools’ web site (http://rsat. ulb.ac.be/rsat). Gene ontology classification of flagged genes The group of differentially expressed genes from the RG-U34A GeneChip experiment were organized biologically in the context of their Gene Ontology (GO) using the program GoMiner (Zeeberg et al. 2003) (http://discover.nci.nih.gov/gominer/GoMiner.html) and Iterative Group Analysis (iGA) (Breitling et al. 2004a). Reverse transcription–polymerase chain reaction RNA was extracted from PC12 cells, cultured rat primary hippocampal cells and rat striatum using the RNeasy Mini Kit (Qiagen). The sequences for primer pairs are detailed in Supplementary Table S1. In the main at least one of the primer pairs were predicted to span an exon–intron boundary. For the NMDA-treated primary hippocampal neurone RT–PCR validation studies, a ‘window’ of typically six PCR cycles within the logarithmic phase of the PCR reaction was established empirically. The intercepts from linear regression analysis of the band intensities were used to normalize the data relative to Gapdh. The signal from NMDA-treated culture wells was expressed as a percentage of the signal from parallel vehicle-treated wells from the same culture, to allow comparison between cultures. Differences relative to control values were assessed using 95% confidence intervals of the mean and the Wilcoxon Signed Rank Test. For the PC12 cell and the

striatal neurone RT–PCR validation study a single PCR cycle within the logarithmic phase of the PCR reaction was selected (and used for each sample). Band intensity was normalized to the corresponding Gapdh signal and differences between the groups were assessed using the two sample t-test (striatal study) and the Mann–Whitney U-test (PC12 validation study).

Results

Over-expression of Zif268 in PC12 cells Microarray analyses were performed on PC12 cells transiently transfected with a control, truncated version of Zif268 or full-length Zif268 (Fig. 1a). The truncated protein retains most of the nuclear localization signal but lacks the N-terminal transcription activation domain (Gosslar et al. 1999). Localization of EGFP-tagged versions of both proteins confirmed that both were efficiently translocated into the nucleus (Fig. 1b). In many diverse forms of neuronal plasticity, from PC12 cells following depolarization, to hippocampal neurones in response to high-frequency stimulation, enhanced Zif268 expression is dependent on influx of Ca2+ ions, activation of mitogen-activated protein kinases (ERKs), and consequent phosphorylation of the constitutive TFs CREB and Elk-1, which bind to the Zif268 promoter. The conservation of this Ca2+ influx to Zif268 signalling pathway suggests that it is a core component of the neuronal plasticity response. The Ca2+ influx also activates cAMP synthesis and a parallel cAMPdependent signalling cascade (Morris 2004), and interestingly, the actions of Zif268 frequently require the concerted action of other permissive cAMP-regulated transcription factors (Cortes-Canteli et al. 2002; Zhang et al. 2003; James et al. 2004). We previously demonstrated that modulation of the Zif268 target gene, synapsin I, by exogenous transfected Zif268 required the presence of elevated cAMP (which would normally be present during periods of neuronal plasticity) provided by the adenyl cyclase activator, forskolin (James et al. 2004). All transfections were therefore performed with PC12 cells pre-treated with forskolin (see ‘Experimental Procedures’). Candidate Zif268 target genes The mRNA from PC12 cells transfected with pZif268 or ptrZif268 was processed for microarray analysis using Affymetrix GeneChip rat genome oligonucleotide arrays. After normalization of the data, it was apparent that the level of expression of the majority of the transcripts monitored on the chips was constant between the two experimental groups (Fig. 2a). An ‘M versus A’ plot, which is a scatter plot of log intensity ratios M versus average log intensities A, tends to be more revealing than log signal versus log signal plots in terms of detecting any intensity dependent patterns in the log



(a)

Fig. 1 Microarray analyses of Zif268 transfected versus control transfected PC12 cells. (a) The murine Zif268 cDNA (3.2 kbp) is expressed under the control of the cytomegalovirus IE gene promoter (pZif268). An N-terminally deleted (D3-372) truncated version of pZif268 was also used during this study as a control. ptrZif268 retains the 5¢- and 3¢-UTR structure of pZif268 but lacks sequence encoding amino acids 3–372, limiting DNA binding of the translated zinc finger domain, and thus dramatically reducing the trans-activation ability of Zif268. (b) Expression of Zif268EGFP fusion constructs in PC12 cells. EGFP was fused to the C-terminus of fulllength rat Zif268 cDNA (pZif268-EGFP) and truncated (D3-345) Zif268 (ptrZif268EGFP). Localization of Zif268 and truncated Zif268 was determined 48-h post-transfection.

(b)

ratios, reflecting suboptimal normalization. An ‘M versus A’ plot confirmed that the normalization had proved consistent between the two treatment groups across a wide-range of expression levels (Fig. 2b). We exploited recent advances in statistical analysis of microarray experiments to reveal genes showing altered expression. Early studies using large-scale microarrays used simple t-tests on thousands of transcripts, and hence suffered from large false-positive rates in the lists of putative differentially expressed transcripts obtained. We used the rigorous statistical analysis offered by ‘SAM’ software (Tusher et al. 2001), which allows direct control of the false-positive rate, and hence delivers an accurate estimate of the likelihood that genes in the list are genuine positives. With a false-positive rate of 0.05, SAM analysis revealed a list of 153 genes that showed altered expression after elevation of Zif268 levels (Table 1). Thus only around eight of the listed genes are likely to be false-positives. A virtually identical list of differentially expressed genes was obtained using another rigorous, but non-parametric, analysis with tight control of the false-positive rate – Rank Product analysis (Breitling et al. 2004b). The full dataset is available at http://www.gla.ac.uk/ ibls/NBS/nbsstaff/bmorris/genomic.html. The vast majority of the candidate transcripts were significantly down-regulated (Table 1). We validated the differential expression of 11 of the candidate Zif268 target genes after Zif268 transfection of PC12 cells using RT–PCR

(Figs 3a and b). The levels of all the mRNAs tested were altered by Zif268 transfection, the majority of them dramatically. We then compared the degree of change in mRNA levels as assessed by the signal from the microarrays with the degree of change in mRNA levels as assessed by RT–PCR (Fig. 4a). We found an excellent correspondence between the two sets of results. Eight of the candidate Zif268 target genes presented in Table 1 have previously suggested to be Zif268 targets; synapsin II, PDGF-A, c-jun, PAI1, mcp1, Mdm2, col1A1 and tyrosine hydroxylase (TH). Intriguingly, some of the candidate genes have been implicated in memory and learning processes, although the associated link with Zif268 has not been made. For example, integrin-associated protein-I (IAP/Cd47) and serum glucocorticoid-inducible kinase (SGK) are both known to be transcriptionally up-regulated after learning in rodents, and, in both cases, functional deletion of the gene compromises the ability of the animals to learn. Regulation of these genes by Zif268 is consistent with both down-regulation following direct elevation of Zif268 levels in PC12 cells and up-regulation following learning in hippocampal pyramidal neurones, since it is known that Zif268 can up- or down-regulate its target genes, depending on the neurochemical context onto which Zif268 induction is superimposed (Huang et al. 1997; Liu et al. 1998; Silverman and Collins 1999; Yu et al. 2004) (see ‘Discussion’).



analyses revealed, in the vast majority of cases, consensus Egr response elements (EREs) in the promoter regions consistent with these genes being direct targets of Zif268 (Table 1) and, indeed, in many cases, multiple potential EREs were detected. The median number of EREs, for all the candidate Zif268 target genes in Table 1, was significantly greater than the median number of EREs (0) in the promoter regions of 20 randomly selected genes (see methods) – Mann–Whitney U-test; p < 0.0001. Biological significance of identified genes The underlying biological organization of the group of differentially expressed genes was determined using two methods of Gene Ontology (GO) functional classification of genes; GoMiner (Zeeberg et al. 2003) and Iterative Group Analysis (iGA) (Breitling et al. 2004a), see Supplementary Tables S1 and S2. Both applications use statistical techniques to analyse a list of differentially expressed genes. However, in contrast to GoMiner, iGA does not depend on the use of a fixed list of differentially expressed genes, but rather detects concerted changes in functional classes of genes, allowing it to be a more sensitive gene detection method. Many of the genes identified corresponded to closely related functional classes. For example, a remarkable finding was that approximately 20% of identified genes were components of the class I major histocompatibility complex (MHC), or the proteasome, with which the MHC has a close functional relationship. Fig. 2 Scatter plots showing distribution of normalized gene expression values. (a) Gene expression signal values (on logarithmic axes) for pZif268 (y-axis) versus ptrZif268 (x-axis) transfected PC12 cells. The very similar levels of expression between the two groups for the majority of the genes is readily apparent. (b) ‘M versus A’ plot showing consistent relative expression between the two groups across a wide range of expression levels. M, log intensity ratios; A, average log intensities.

To assess whether the control, truncated Zif268 might itself be influencing the expression of the genes identified, we monitored the mRNA levels for selected candidate genes after transfection of PC12 cells with full-length Zif268 (pZif268), truncated Zif268 (ptrZif268), or empty vector (pCMV5). The results demonstrated that the truncated inactive Zif268 has no significant effect relative to empty vector overall, and that active Zif268 suppressed the expression of these genes relative to empty vector as well as relative to truncated inactive Zif268 (Fig. 4b). Promoter region Egr response elements To assess the likelihood that the identified genes are direct targets of Zif268 we analysed the genomic region upstream of the transcriptional start site (TSS) of candidate genes using the program MatInspector (Quandt et al. 1995). These

Zif268 candidate target genes and CNS plasticity Up until this point we had monitored the expression of candidate Zif268 target genes solely in PC12 cells. We next extended our analysis of the Zif268-mediated regulation of candidate genes by RT–PCR analysis using two wellcharacterized models of CNS plasticity; namely the response of rat hippocampal neurones in vitro to NMDA receptor stimulation and the response of rat striatal neurones to elevated corticostriatal activity following D2 receptor blockade in vivo. Both of these models involve Zif268 induction (Simpson and Morris 1994; Morris 1995, 2004). Relative expression levels of a selection of candidate genes in the two models were determined 6-h post treatment. One out of four candidate target genes were significantly differentially expressed in the hippocampal neurone model (Figs 5a and c), whereas two out of four candidate genes were differentially expressed in the striatal neurone model (Figs 5b and d). Intriguingly, the pattern of altered gene expression was clearly different in the two models, with genes being regulated in one paradigm but not the other. It was also noted that, of the significantly regulated genes across the two models, all were down-regulated (mirroring the observed relative expression levels for the candidate target genes in PC12 cells), possibly pointing to a more general transcriptional repressor role of Zif268 in CNS plasticity.



Table 1 List of differentially expressed genes and survey of the presence of Egr response elements (EREs) within the promoter region of identified genes Gene Neurotransmitters/modulators: PDGF Receptors: Cys-rich fibroblast growth factor receptor (CFR-1) Signalling: Kinases: dsRNA-dependent protein kinase Prkr cdc5 Serum/glucocorticoid regulated kinase – SGK GSK3b Aurora kinase (AIM-1 – Stk12) SNK-akin polo-like kinase, SAK (Stk18) p70S6 ribosomal kinase Rho-associated kinase ROCK II cyclin G-associated kinase GAK Neuronal cell death inducible kinase – NIPK/SKIP3/tribbles Cyclin B1 Cyclic nucleotide phosphodiesterase (cnp1) phosphatidic acid phosphatase type 2b (Dri42) Guanine nucleotide-binding protein – gnb1 Guanine nucleotide-binding protein – gnb2 Membrane-interacting protein of RGS16 – mir16 thioredoxin interacting protein – vdup1 Gadd45a cdc20 (p55cdc) pdcd8 calpastatin Raga ApoL-III Importin b ClnS1a Pre-synaptic: synapsin II syntaxin 4a synaptotagmin 3 (syt3) ykt6 SNARE protein Hbeta58 – vacuolar protein sorting 26 Synapse formation: PAI1 (Serpine 1) Agrin gephyrin Cystatin 3 (cst3) Galectin 3 – binding protein – Lgals3 BP Galectin 5 – Lgals5 Galectin 9 – Lgals9 Integrin-associated protein (IAP, CD47) CD48 Amyloid bA4-precursor binding protein – Apba3 Collagen Col1a2 neuropilin

Accession No.

% change

Significancea

AA944099

› 52%

p ¼ 0.05

2

AI176461

fl 27%

p ¼ 0.05

4

L29281 AF000578 L01624 X73653 D89731 AA894059 M58340 AA891595 D38560 H31287

fl fl fl fl fl fl fl fl fl fl

56% 28% 34% 26% 25% 35% 28% 35% 26% 38%

p p p p p p p p p p

¼ ¼ ¼ ¼ ¼ ¼ ¼ ¼ ¼ ¼

0.0025 0.05 0.05 0.05 0.0025 0.05 0.05 0.05 0.05 0.05

0 2 1 3 1 2 2 5 2 1

AA998164 L16532 AA924925 AF022083 AA817892 AA891916 AI237654/AI014169 L32591 AF052695 AA891591 AA875089 X85183 AA858505/AI070325 L38644 AI169005

fl fl fl fl fl fl fl fl fl fl fl fl fl fl fl

34% 51% 27% 33% 33% 32% 40% 23% 24% 24% 25% 28% 54% 37% 22%

p p p p p p p p p p p p p p p

¼ ¼ ¼ ¼ ¼ ¼ ¼ ¼ ¼ ¼ ¼ ¼ ¼ ¼ ¼

0.05 0.05 0.05 0.05 0.05 0.05 0.0025 0.05 0.05 0.05 0.05 0.05 0.0025 0.05 0.05

2 3 0 5 5 3 0 3 4 0 0 1 1 5 0

M27925/AI145494 L20821 D28512 AF033027 AA894037

fl fl › fl fl

27% 33% 40% 32% 41%

p p p p p

¼ ¼ ¼ ¼ ¼

0.0025 0.05 0.05 0.05 0.05

6 3 6 0 4

M24067 M64780 X66366 AI231292 AF065438 L21711 U72741 AF017437 X13016 AF029109 AA891828 AF016296

fl fl fl fl fl fl fl fl fl fl fl fl

65% 60% 26% 24% 77% 46% 28% 47% 31% 29% 29% 30%

p p p p p p p p p p p p

¼ 0.05 ¼ 0.0025 ¼ 0.05 ¼ 0.05 ¼ 0.05 ¼ 0.05 ¼ 0.05 < 0.0001 ¼ 0.05 ¼ 0.05 ¼ 0.05 ¼ 0.05

1 4 7 1 1 1 1 10 2 1 4 4


EREsb


Table 1 Continued Gene

Accession No.

% change

Significancea

Tight junction protein 2 (tjp2) Cys-rich fibroblast growth factor receptor (CFR-1) Alcam (CD166) Proteasome: proteasome subunit – psma5 proteasome subunit – psmb8 (lmp7) proteasome subunit – psmb9 (lmp2) proteasome subunit – psmc4 proteasome activator – PA28b (psme2) COP9 signalosome complex subunit 1 (csn1/gps1) COP9 signalosome complex subunit 7a (csn7a) E3 ubiquitin ligase: vhl cdc5 cdc20 Mdm2 Nedd8-ultimate buster NUB1 UBE2L6/UBCH8 (E2 ligase) ubiquitin D ubiq.-conj. enzyme UBC7 Ubiquilin 1 Suppressor of cytokine signalling (SOCS) Serum/glucocorticoid regulated kinase – SGK lysosomal acid lipase Small glutamine-rich tetratricopeptide – sgt protein Major Histocompatibility Complex: Tap1 transporter Tap2 transporter Tapasin RT1.S3

U75916 AI176461 AB008538

fl 24% fl 27% fl 30%

p ¼ 0.05 p ¼ 0.05 p ¼ 0.05

AA891383 D10729 D10757 D50695 D45250/AA851169 X87885 AA875470

fl fl fl fl fl fl fl

32% 44% 45% 22% 34% 33% 36%

p p p p p p p

¼ 0.05 ¼ 0.0025 < 0.0001 ¼ 0.05 < 0.0001 ¼ 0.05 ¼ 0.05

1 5 2 2 4 6 3

U14746 AF000578 AF052695 AI639488 AI232313 AI178800 AI030354 Af099093 AA875206 AA849015 L01624 S81497 AJ222724

fl fl fl fl fl fl fl fl fl fl fl fl fl

28% 28% 24% 35% 39% 48% 26% 30% 36% 33% 34% 41% 28%

p p p p p p p p p p p p p

¼ ¼ ¼ ¼ ¼ ¼ ¼ ¼ ¼ ¼ ¼ ¼ ¼

0.05 0.05 0.05 0.05 0.05 0.05 0.05 0.05 0.05 0.05 0.05 0.0025 0.05

4 2 4 4 8 2 2 3 8 4 1 0 6

X57523 X63854 AI179939 AF029240/ U16025 U16023 AF025308 M31038/L40362/ M31018/M11071 M64795 AF074609 AI818887 AA892014

fl fl fl fl

56% 45% 48% 51%

p p p p

¼ 0.0025 ¼ 0.05 ¼ 0.05 < 0.0001

2 3 1 1

fl 44% fl 42% fl 41%

p ¼ 0.0025 p ¼ 0.05 p < 0.0001

10

fl fl fl fl

41% 33% 40% 35%

p p p p

¼ ¼ ¼ ¼

Y07704 AI012235 U17035 X17053 X52711 AI030615 X52713 Z18877 AA849015 M80367 M34253 AA799861

fl fl fl fl fl fl fl fl fl fl fl fl

90% 50% 92% 28% 86% 80% 84% 82% 33% 52% 52% 78%


¼ 0.0025 ¼ 0.05 ¼ 0.05 ¼ 0.0025 ¼ 0.05 ¼ 0.05 ¼ 0.05 < 0.0001 ¼ 0.05 ¼ 0.05 < 0.0001 ¼ 0.0025

RT1.M3 RT1.C1 RT1.Aw2 RT1.A4 RT1.EC3 RT1.N1 Bat1a Immune response: Best5/cig5/viperin Cxcl11 (IP-9) Cxcl10 (Mob-1, IP-10) CCL2 (JE protein, mcp1) Mx1 Mx2 Mx3 oas1 Suppressor of cytokine signalling (SOCS) Gbp2 Irf1 Irf7

0.05 0.05 0.05 0.0025

EREsb 0 4 4

c

1 c c c

0 1 0 2 2 2 1 2 1 4 0 3 1




Accession No.

% change

Significancea

poliovirus receptor (CD155, tage4) Cx3cL1 (fractalkine/neurotactin) CCL5 (RANTES) Vesicle trafficking: SCFD1 (RA410) Arf6 Rab13 Arfrp1 Clathrin-associated protein – Ap2a2 Clathrin-associated protein – Ap2S1 Clathrin-associated complex3 protein -Ap3m1 rabaptin-5 Cytoskeletal: drebrin Atypical myosin heavy chain – myr2 Metabolic: GTP cyclohydrolase – Gch

L12025 AI227647 AI009658

fl 30% fl 19% fl 36%

p ¼ 0.05 p ¼ 0.05 p ¼ 0.05

D79221 AA944324 M83678 X78603 X53773 U75917 L07073 D85844

fl fl fl fl fl fl fl fl

p p p p p p p p

AI071800 AA944197

fl 23% fl 21%

p ¼ 0.05 p ¼ 0.05

3 2

M58364/E03424/ AI639457 AA874784 D50436 U96130 AI059508 L19927 J03621 U62897 AI111492 U90888 AB012759

fl 51%

p < 0.0001

0

fl fl fl fl fl fl fl fl fl fl

41% 24% 27% 44% 29% 22% 22% 88% 29% 23%

p p p p p p p p p p

¼ ¼ ¼ ¼ ¼ ¼ ¼ ¼ ¼ ¼

0.05 0.05 0.05 0.05 0.05 0.05 0.05 0.0025 0.05 0.0025

0 1 0 2 2 2 2 0 1 2

U75398 M19651 AI175959 M63282 AA892553/AA999171 H33459 AI237258 AI059254/AI009156 AI172476 M34253 AA799861 L01267

› fl fl fl fl fl fl fl fl fl fl fl

56% 27% 27% 36% 72% 26% 37% 48% 24% 52% 78% 40%


¼ 0.05 ¼ 0.05 ¼ 0.05 ¼ 0.05 < 0.0001 ¼ 0.05 ¼ 0.05 ¼ 0.0025 ¼ 0.05 < 0.0001 ¼ 0.05 ¼ 0.05

14 1 4 5 0 2 0 1 12 3 1 2

AI013194 M12156 (AA965147) U32577 D49708 AA892801 L14684 H31692

fl fl fl fl fl fl fl

45% 46% 39% 25% 48% 25% 33%

p p p p p p p

¼ ¼ ¼ ¼ ¼ ¼ ¼

M93257

fl 38%

Cholesterol esterase – Lipa ferredoxin glycogenin transketolase ATP synthase – ATP5c1 Succinate CoA ligase carboxypeptidase E Thymidylate kinase Adenosine deaminase 3 prolyl endopeptidase TFs: Egr1 Fos-like antigen – fra1 c-jun ATF3 Stat1 SMARCB1/SNF1 MYBBP1A ZNF313 KLF10, TGFb-inducible IEG (tieg) Irf1 Irf7 gtf2f2 Translation: eIF5 hnrpa1 hnrpm Srfs10 eef2 EF-G eIF2c1 Chromaffin cell function: COMT


26% 23% 24% 22% 32% 31% 23% 20%

¼ ¼ ¼ ¼ ¼ ¼ ¼ ¼

0.05 0.05 0.05 0.05 0.0025 0.05 0.05 0.05

EREsb 2 0 1 1 8 2 1 5 2 5 3

0.05 0.05 0.05 0.05 0.05 0.05 0.05

0 4 1 2 1 2 1

p ¼ 0.05

0



Accession No.

% change

Significancea

EREsb

Tyrosine hydroxylase Choline transporter CHOT1

AI104389 X66494

fl 30% fl 23%

p ¼ 0.05 p ¼ 0.05

3 12

a

Note that SAM (Significance Analysis of Microarrays) incorporates all transcripts in a single analysis, and hence is not subject to the problems of false-positives due to multiple comparisons, as seen for example with uncorrected t-tests. Some transcripts are present as multiple probe sets on the GeneChips: if a particular transcript appears as differentially expressed on multiple probe sets (each with a 5% false positive rate), then there is correspondingly smaller probability that the transcript appears in the list by chance. These transcripts are indicated by correspondingly smaller p-values above. b The presence of consensus Egr-response elements was assessed in a 1-kb region immediately upstream of the likely transcription start site (see ‘Experimental Procedures’). c The Major Histocompatibility Complex (MHC) region of rat chromosome 20 is poorly characterized, and unequivocal identification of the location of the genes encoding these transcripts, and hence of the likely promoter region, was not possible. Similarly, the high degree of homology between these MHC transcripts implies that the assignment of transcript identity should be viewed as tentative.

(a)

(b)

Fig. 3 Validation of a selection of Zif268-target candidate genes in PC12 cells. Semi-quantitative RT–PCR was used to determine the relative expression levels of a selection of genes that were differentially expressed. (a) Representative RT–PCR product band intensities for selected genes in pZif268 and ptrZif268 transfected PC12 cells. (b) Relative amounts of target cDNA were determined (see ‘Experimental Procedures’) 48-h post-transfection. Results from five independent experiments are shown (means ± SE). ***p £ 0.01; **0.01 < p < 0.025; *0.025 < p < 0.05, expression levels greater in ptrZif268 transfected PC12 cells compared to pZif268 transfected cells (with the exception of Syt3; pZif268 > ptrZif268), Mann–Whitney U-test.

We screened the literature for reports that any of the 153 genes detected are involved in various forms of neuronal plasticity known to involve Zif268 induction. Intriguingly, a number of the genes identified as Zif268 targets in this study have been previously implicated in one or more forms of longlasting neuronal plasticity. Further details, along with corresponding citations, are provided in Supplementary Table S4. Discussion

We report here the identification of a number of downstream neuronal target genes for Zif268. The list of genes obtained

as potential Zif268 targets can be viewed with considerable confidence for a number of reasons. Rigorous statistical analysis was performed to provide a tight control of the falsepositive rate, thus eliminating the problems associated with many early microarray studies. The identification of a number of known Zif268 target genes further validates the approach. Although eight of the genes identified here have been previously proposed as Zif268 target genes in other tissues, the vast majority of the genes have not previously been linked to Zif268 transactivation. Interestingly, there is no overlap at all with the Zif268 target genes identified using microarray analysis in prostate cells (Svaren et al. 2000; Virolle et al. 2003), and a single gene (ATF3) was shared with those identified in endothelial cells (Fu et al. 2003). This would appear to confirm suggestions that the target genes of Zif268 vary from tissue to tissue (Beckmann and Wilce 1997; Huang et al. 1997). However, although no direct link has been established, elevated Zif268 expression in various peripheral tissues correlates with increased expression of a number of the genes identified here (Cxcl10, ATF3, fra1, c-jun, mcp1, vhl, PAI1, ferredoxin, tjp2, vdup1, SGK, tage4 and tieg) (Yan et al. 2001; Chen et al. 2002; Peters et al. 2002; Ji et al. 2003), suggesting that the transcriptional response to Zif268 can show some commonalties in distinct tissues. We confirmed altered expression of 12 of the genes in Zif268 transfected cells by RT–PCR. The high proportion of the genes tested that showed differential expression after Zif268 transfection as assessed by RT–PCR is entirely consistent with the statistical predictions from the microarray analysis, where a low false-positive rate was imposed. As revealed by the microarray analysis, most of these genes were substantially down-regulated. When we compared the degree of change in expression from the microarray analysis and that from the confirmatory RT–PCR analysis, we found that there was an excellent correlation between the two (Etienne et al. 2004; Park et al. 2004; Irizarry et al. 2005).



Fig. 4 Effect of Zif268 expression vectors on candidate target genes in PC12 cells. (a) Correlation between the degree of change in mRNA levels as assessed by the signal from the microarrays with the degree of change in mRNA levels as assessed by RT–PCR (data from Fig. 3). Linear regression line is shown – r2 ¼ 0.775. (b) Semi-quantitative RT–PCR was employed to determine the relative expression levels of a selection of five differentially expressed genes in PC12 cells transfected with empty vector (pCMV), ptrZif268 (inactive Zif268) or pZif268 (active Zif268). Results are shown for cystatin 3 (Cst3), Cd47, Cxcl10, synaptotagmin 3 (Syt3) and tyrosine hydroxylase (TH). Mean ± SEM is depicted (n ¼ 3–5). Overall two-way ANOVA (factors: gene/treatment) revealed a significant effect of treatment – F2,46 ¼ 9.92, p < 0.001, with effect of pZif268 different from effect of pCMV and effect of ptrZif268 (p < 0.05), but effect of ptrZif268 not significantly different from effect of pCMV (post hoc Tukey’s test). ***p £ 0.01; **0.01 < p < 0.025; *0.025 < p < 0.05 versus ptrZif268; ###p £ 0.01; ##0.01 < p < 0.025; #0.025 < p < 0.05 versus pCMV: t-test.

This probably reflects the rigorous approach we have taken to the experimental aspects of the microarray study and to the data processing and analysis. Most of the early reports on the transcriptional effects of Zif268 had reported activation rather than suppression. However, these studies were almost entirely based on the use of minimal promoter–reporter constructs, which are known in many cases not to provide an accurate representation of the regulation of the complete endogenous gene. In fact there is little information available on the effects of elevated Zif268 expression on the expression of endogenous genes.

Although there has been a traditional view that Zif268 target genes in the CNS will be up-regulated, based on the use of synthetic promoter–reporter constructs in cell lines, the more recent data from peripheral cells suggests that the majority of Zif268 target genes are in fact down-regulated, and hence that the major role of Zif268 is in suppression of gene expression (Cao et al. 1993; Liu et al. 1996; Beckmann and Wilce 1997; Dinkel et al. 1997; Thottassery et al. 1999; Fukada and Tonks 2001; Bahouth et al. 2002; Davis et al. 2003; Zhang and Liu 2003; Wang et al. 2005). Hence the emerging picture of Zif268 is as a suppressive factor, and therefore we were not surprised to find that the majority of Zif268 target genes in neurones were down-regulated in this study, which represents the simplest situation of Zif268 induction. It was felt that control transfections should match the Zif268 expression vectors as closely as possible, and that nontransfected cells or cells transfected with empty vector were not sufficently similar when 1000 s of genes were being monitored. Therefore, a vector driving expression of a truncated Zif268 protein, retaining the nuclear localization signal of wild-type Zif268 but lacking the DNA transctivation domain, was constructed. This would behave identically to the wild-type Zif268 expression vector in terms of sequestration of protein synthesis machinery, exploitation of nuclear import machinery, etc., and would differ only in an inability to affect target promoter activity (Gosslar et al. 1999). We showed that the truncated Zif268 had no overall effect on the expression of a sample of genes, as compared to empty vector. There was a significant increase in Cxcl10 expression relative to empty-vector-transfected cells. However, even in this case, the effect of active Zif268 was qualitatively identical relative to both empty vector and truncated Zif268. For the genes in this set with known genomic organization, analysis via MatInspector (Quandt et al. 1995) revealed consensus Egr-1 binding sites within 1000 bases of the transcription start site (functional Egr-1 sites are generally located in proximal promoter regions). Although the presence of a consensus binding site in the promoter region does not of itself prove that the gene is a target of the transcription factor, this is nonetheless consistent with these genes being direct targets of Zif268. Equally, those genes listed in Table 1 that do not contain consensus EREs in this region may still be authentic Zif268 targets, but with Egr-1 binding sites either more than 1-kb upstream of the transcription start site, or in the proximal downstream region. The very high proportion of the genes identified that contain potential EREs is remarkable, considering that EREs are under-represented in promoters across the entire genome (Kel-Margoulis et al. 2003), and adds further to the evidence implicating these genes as Zif268 targets. From existing knowledge of the actions of Zif268 in peripheral cells, it is clear that a Zif268 target gene can be up- or down-regulated following induction of Zif268,



(a)

(b)

(c)

(d)

Fig. 5 Expression of Zif268-target candidate genes in two neuronal plasticity models. Semi-quantitative RT–PCR was employed to determine the relative expression levels of a selection of four differentially expressed genes in NMDA-treated primary hippocampal cells and in striatum tissue isolated from haloperidol-treated rats as compared to corresponding controls. (a) Representative RT–PCR product band intensities for candidate genes expressed in NMDA- and vehicletreated primary hippocampal cells. (b) Representative RT–PCR product band intensities for candidate genes expressed in striatum

tissue for haloperidol and vehicle-treated rats. (c) Relative amounts of target cDNA were determined (see ‘Experimental Procedures’) 6 h after treatment with vehicle or NMDA. Four experiments were performed and the mean ± SEM is depicted. *p £ 0.05 versus 100%, Wilcoxon Signed Rank Test. (d) Relative amounts of target cDNA were determined (see ‘Experimental Procedures’) 6 h after treatment with vehicle or haloperidol treatment. Three experiments were performed and the mean ± SEM is depicted. *p £ 0.05, two sample t-test.

depending on the neurochemical context onto which Zif268 induction is superimposed (Huang et al. 1997; Liu et al. 1998; Silverman and Collins 1999; James et al. 2004; Yu et al. 2004). For example, PDGF-A gene expression is reportedly suppressed by Zif268 in NIH3T3 cells, and enhanced by Zif268 in 293 cells. Strikingly, the levels of expression of the CBP and p300 genes in prostate cells are up-regulated via Zif268 after one stimulus, and downregulated via Zif268 after another stimulus. Thus it is very clear that the direction in which a target gene is modulated by Zif268 is not an absolute. Therefore, although most of the Zif268 target genes we detected were down-regulated by Zif268 expression in PC12 cells, they may be up-regulated by Zif268 in other neuronal types, according to other effects of the stimulus that occur in parallel with Zif268 induction. The observation that tyrosine hydroxylase expression was decreased by Zif268 (Table 1, Fig. 4b) is of some interest. There are a large number of reports describing increases in tyrosine hydroxylase gene expression after stimuli that are associated with Zif268 induction, such as membrane depolarization, PKC activation or Ca2+ influx. However, it is noteworthy that these increases in TH mRNA occur too rapidly to be mediated by Zif268 (Vyas et al. 1990; Kilbourne et al. 1992; Gizang-Ginsberg and Ziff 1994; Najimi et al. 2002). It is likely, as noted above, that Zif268 can act as either an activator or repressor of transcription, as indeed has been shown for the TH gene for AP1 transcription factors (Gizang-Ginsberg and Ziff 1994). In fact, it has

recently been reported that the Zif268 binding site in the TH promoter can mediate a suppression of gene expression (Maharjan et al. 2005), as well as activation (Papanikolaou and Sabban 2000). Hence it seems likely that Zif268 can mediate both activation and suppression of TH transcription depending on the circumstances. We tested whether a selection of the genes were modulated in two well-characterized models of neuronal plasticity. It is of interest that the results from related microarray studies on the gene expression changes induced by haloperidol treatment or NMDA receptor modulation show signficant overlap with our results (O’Donnell et al. 2003; Hong et al. 2004; Iwata et al. 2005). None of the genes we selected had previously been linked with NMDA receptor dependent plasticity in the hippocampus or with dopamine antagonistinduced plasticity in the striatum. Of the four genes tested, synaptotagmin 3 was not significantly affected in either model, although a recent microarray study on the effect of haloperidol treatment on striatal gene expression did detect synaptotagmin 3 as being signficantly modulated (MacDonald et al. 2005). Of the other three genes that were affected in these models, one was significantly modulated in hippocampal neurones by NMDA receptor stimulation in vitro, and two were significantly modulated in striatal neurones by haloperidol administration in vivo (Figs 5c and d). These two genes – cystatin C and Cxcl10 – have not previously been linked with dopamine antagonist-induced plasticity in the basal ganglia. However, it is interesting to note that acute



treatment with Cxcl10 has recently been demonstrated to alter synaptic plasticity in mouse hippocampal slices (Vlkolinsky et al. 2004), suggesting that Cxcl10 may play a direct role in the plasticity process. Although these changes cannot unequivocally be ascribed to transcriptional effects of Zif268, the genes examined have not previously been linked to the long-term effects of either NMDA in the hippocampus or D2 receptor antagonists in the striatum. Hence, since they were detected in our screen for Zif268 target genes, it is likely that Zif268 is involved in their modulation. The data not only identify novel genes modulated in these plasticity models, but also provide some physiological context for the list of genes in Table 1. Although this is only a small sample of the full list of genes identified in this piece of work, the results suggest that a high proportion are potentially involved in CNS plasticity. In addition, the results imply that, as predicted, the repertoire of the downstream effects of Zif268 induction will vary in different situations according to some other factor – for example the presence or absence of other TFs that are activated in parallel with Zif268. The genes identified fall into a number of clearly defined functional categories. Some striking features of the relevance of these genes to neuronal plasticity deserve particular mention. Synaptic function The number of genes involved in ‘immune synapse’ function that were significantly changed by neuronal Zif268 expression (including agrin, CD47, CD48, CFR-1 and neuropilin) is conspicuous, particularly in the light of the emerging concept of similarities between the immune synapse and CNS excitatory synapses. When antigen-presenting cells form contacts with T-cells, these adhesion molecules play major roles in forming and maintaining the immunological synapse, allowing MHC molecules to then transmit information across the synapse. These molecules may also be involved in activitydependent formation and maintenance of synapses in the CNS. Peptides produced by the 26S proteasome are transported to the class I MHC by the TAP complex (TAP1, TAP2, tapascin), and the MHC then presents the peptides at the synapse. A number of MHC genes, plus all the genes encoding TAP complex proteins, were detected in this study, suggesting they may have an important association with Zif268 action. Interestingly, genetic deletion of class I MHC and TAP1 has recently been shown to be alter the magnitude of hippocampal LTP (Huh et al. 2000). Induction of a number of class I MHC genes, including RT1aw2, is observed after epileptic activity and following induction of hippocampal LTP (Corriveau et al. 1998), and these genes are also regulated in an activity-dependent manner in the thalamus (Huh et al. 2000). It has therefore been proposed that the MHC may mediate signalling at CNS synapses in an analogous manner to its actions in the immune system, with

distinct proteins within the MHC providing signal specificity. Altered expression of a number of class I MHC genes, alongside the ‘immune synapse’ genes, by Zif268 should therefore modulate the trans-synaptic signalling properties of the post-synaptic cells. Protein degradation A relatively high percentage of the genes identified are associated with ubiquitination and protein degradation via the 26S proteasome. Our preliminary data confirm down-regulation of these genes by Zif268 (manuscript in preparation). The proteasome is reportedly present in dendritic spines, and a wealth of recent evidence has implicated proteasomal protein degradation as a key component of long-term neuronal plasticity. For example, inhibition of the proteasome suppresses alterations in dendritic morphology in cultured neurones (Obin et al. 1999), blocks long-term facilitation in Aplysia (Hegde et al. 1997), and suppresses hippocampusdependent long-term memory (Lopez-Salon et al. 2002). Recent data suggest that the composition of the postsynaptic density is regulated by the proteasome in an activity-dependent manner (Ehlers 2003). Proteasomal degradation of the regulatory subunit of PKA, also identified as a Zif268 target gene here, has been specifically implicated in synaptic plasticity, and synaptic AMPA receptor number (and PSD-95 levels) are known to be regulated by ubiquitination and clathrin-dependent endocytosis (Colledge et al. 2003), involving Arf6 (Burbea et al. 2002) and Mdm2 (Colledge et al. 2003). Synaptic plasticity also changes the expression of proteasome constituents: long-term facilitation in Aplysia and spinal cord sensitization in neuropathic pain are associated with increased expression of ubiquitin C-terminal hydrolase genes (Hegde et al. 1997; Moss et al. 2003), and hippocampal proteasome activity increases 4 h after memory formation in rats (Lopez-Salon et al. 2002). Induction or repression of the proteasome subunits Psmb8, Psmb9, PA28a and PA28b alters the protein specificity of the proteasome, and hence affects the composition of peptides presented across the synapse by the MHC (Groettrup et al. 1995). A number of proteasome genes, including Psmb2 and PA28, were detected recently in a screen for genes mediating ageing-related memory impairment (Blalock et al. 2003). Our data implicate Zif268 in these effects. There are discrepancies in the literature as to whether the proteasome suppresses or facilitates synaptic plasticity, and the overall picture of how the proteasome contributes to plasticity is not clear. However, it can be proposed that (possibly presynaptic) proteasome activity is necessary for early phase plasticity, and that post-synaptic proteasome activity suppresses plasticity (Zhao et al. 2003). Hence a suppression of proteasome activity via Zif268 induction in the post-synaptic neurone would be predicted to cause a long-lasting alteration in the activity of the proteasome, and hence the sensitivity of the post-synaptic density to subsequent synaptic stimulation.



A number of kinases were identified as potential Zif268 target genes. Remarkably, many of these kinases have been implicated in the regulation of proteasome activity, and in all cases are themselves substrates for proteasomal degradation. Thus Aurora, cdc5, tribbles/NIPK, GSK3, SGK and SAK phosphorylate proteasome components and promote target protein degradation. In addition, Aurora, NIPK, GSK3, cdc5, Prkar2a, SGK and SAK are all substrates for the 26S proteasome. Hence altered expression of this group of kinases by Zif268 would represent a powerful mechanism for long-term regulation of neuronal activity. Conclusion

By using a Zif268 expression vector to elevate the levels of Zif268 in a neuronal cell line, we have identified a number of potential Zif268 target genes in neurones. The genes identified in this study reveal some previously unsuspected aspects to the mechanisms sustaining long-term neuronal plasticity. Our original, intuitive expectation was that a relatively small number of genes would be identified as synaptic plasticity-related, Zif268 target genes. The emergence of 153 genes from the initial analysis was surprising, but became consistent with the original hypothesis when it became clear that the protein products of many of the genes acted together as members of protein complexes. Thus Zif268-dependent regulation of these functionally interrelated genes would provide co-ordinated regulation of the function of the protein complex. The Zif268 target genes described here thus provide a new insight into the mechanisms sustaining the late-phases of neuronal plasticity, and focus attention particularly on protein degradation and subsequent modification of synaptic transmission as underlying these enduring changes. Acknowledgements We thank Paul Burr (BioBest Laboratories) for advice in the early stages of the project, Gerald Thiel (University of Saarland) for the gift of the pZif268 expression vector, and the staff at the Sir Henry Wellcome Functional Genomics Facility (University of Glasgow) for assistance with the microarray processing and analysis. This research was supported by the BBSRC.

Supplementary Material The following material is available for this article online. Table S1. RT-PCR primer sequences used during this study. Table S2. Biological organisation of the differentially expressed genes from RG-U34A GeneChip array experiment in the context of their Gene Ontology (GO) as determined by the GoMiner program. Table S3.Biological interpretation of the functional classes (Gene Ontologies) of differentially expressed genes of the GeneChip RGU34A array experiment.

Table S4. Genes linked with activity-dependent plasticity in the CNS.

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