NEUROSYSTEMS

Gene expression analysis of the emergence of epileptiformactivity after focal injection of kainic acid into mousehippocampus

Dario Motti,1* Caroline Le Duigou,2,� Emmanuel Eugene,2 Nicole Chemaly,2,� Lucia Wittner,2,§ Dejan Lazarevic,3

Helena Krmac,1 Troels Marstrand,4 Eivind Valen,4 Remo Sanges,5 Elia Stupka,3,– Albin Sandelin,4 Enrico Cherubini,1

Stefano Gustincich1 and Richard Miles2

1S.I.S.S.A. ⁄ I.S.A.S. International School for Advanced Studies, Neurobiology sector, Trieste, Italy2INSERM U975, Cortex & Epilepsy, Paris, France3CBM S.c.r.l., Genomics, Trieste, Italy4Department of Biology & Biotech Research and Innovation Centre, Bioinformatics Centre, University of Copenhagen, Copenhagen,Denmark5CBM S.c.r.l., Bioinformatics, Trieste, Italy

Keywords: epilepsy, gene profile, hippocampus, kainate

Abstract

We report gene profiling data on genomic processes underlying the progression towards recurrent seizures after injection of kainicacid (KA) into the mouse hippocampus. Focal injection enabled us to separate the effects of proepileptic stimuli initiated by KAinjection. Both the injected and contralateral hippocampus participated in the status epilepticus. However, neuronal death induced byKA treatment was restricted to the injected hippocampus, although there was some contralateral axonal degeneration. We profiledgene expression changes in dorsal and ventral regions of both the injected and contralateral hippocampus. Changes were detectedin the expression of 1526 transcripts in samples from three time-points: (i) during the KA-induced status epilepticus, (ii) at 2 weeks,before recurrent seizures emerged, and (iii) at 6 months after seizures emerged. Grouping genes with similar spatio-temporalchanges revealed an early transcriptional response, strong immune, cell death and growth responses at 2 weeks and an activation ofimmune and extracellular matrix genes persisting at 6 months. Immunostaining for proteins coded by genes identified from arraystudies provided evidence for gliogenesis and suggested that the proteoglycan biglycan is synthesized by astrocytes and contributesto a glial scar. Gene changes at 6 months after KA injection were largely restricted to tissue from the injection site. This suggests thateither recurrent seizures might depend on maintained processes including immune responses and changes in extracellular matrixproteins near the injection site or alternatively might result from processes, such as growth, distant from the injection site andterminated while seizures are maintained.

Introduction

Gene profiling techniques have identified molecular dysfunctionsassociated with several diseases (Karp et al., 2000; Lock et al., 2002).Functional genomics approaches to the epilepsies have been facilitatedby the availability of living brain tissue after operations on patientswith pharmaco-resistant syndromes. Work on human temporal lobe

epilepsies has demonstrated changes in genes associated with theimmune system (Jamali et al., 2006) and glial function (Ozbas-Gerceker et al., 2006), but there are limits to studies on human tissue.First, it is difficult to obtain appropriate control tissue. Second, geneprofiles may differ between sclerotic regions and regions that generateepileptiform activity (Arion et al., 2006; Jamali et al., 2006). Finally,tissue is obtained from patients who have experienced seizures overseveral years so that altered genes include not only those involved inpathological or adaptive responses but also those altered by prolongedtreatment with anti-epileptic drugs (Tang et al., 2004; Aronica &Gorter, 2007).Animal models of the epilepsies involve fewer constraints and also

permit studies on gene expression changes during epileptogenesis.Temporal lobe epilepsies are mimicked by the kindling procedure(Goddard, 1967; Gorter et al., 2006) or by treatment with convulsantssuch kainic acid (KA) (Ben-Ari et al., 1979; Becker et al., 2003). Inboth cases control tissue is easily available, sclerotic regions can be

Correspondence: R. Miles, as above.E-mail: Richard.Miles@upmc.fr

*Present address: Miami Project to Cure Paralysis, Miller School of Medicine, Universityof Miami, Miami, FL, USA.�Present address: Department of Clinical and Experimental Epilepsy, Institute ofNeurology, UCL, Queen Square, London, UK.�Present address: Laboratoire d’EEG, Service de Pediatrie, Centre Hospito-Universitairede Reims, Reims, France.§Present address: Institute for Psychology, Hungarian Academy of Sciences, H-1068,Budapest, Szondi u. 83-85, Hungary.–Present address: Cancer Institute, UCL, Huntley Street, London, UK

Received 9 December 2009, revised 8 June 2010, accepted 14 July 2010

European Journal of Neuroscience, Vol. 32, pp. 1364–1379, 2010 doi:10.1111/j.1460-9568.2010.07403.x

ª 2010 The Authors. European Journal of Neuroscience ª 2010 Federation of European Neuroscience Societies and Blackwell Publishing Ltd

European Journal of Neuroscience

distinguished and spontaneous, recurrent seizures emerge after aperiod of several weeks.

Multiple processes are engaged between these initial stimuli and theemergence of seizures. Some neurons die (Sater & Nadler, 1988;Magloczky & Freund, 1993), receptor and channel expression changes(Shah et al., 2004; Epsztein et al., 2005), and novel synaptic circuitsare formed (Sutula et al., 1988; Patrylo & Dudek, 1998). Differentgroups of glial cells are activated and immune and inflammatoryresponses are triggered (Vezzani et al., 1999; Wetherington et al.,2008). The relations between the initial stimulus, these cellularchanges and epileptogenesis are only partially clear (Pitkanen &Lukasiuk, 2009).

We attempted to clarify these questions using gene profiletechniques to examine the progression to recurrent seizures in micetreated with KA. Focal intrahippocampal KA injection (Bouilleretet al., 1999) may permit the separation of several stimuli withdifferential effects on the injected and contralateral hippocampus. Bothhippocampi participate in a status epilepticus of several hours’duration. Neuronal death is restricted to the injected hippocampus,especially near the dorsal injection site, although axons maydegenerate contralaterally. We compared changes in gene expressionin dorsal and ventral regions of both the injected and contralateralhippocampus. The validity of micro-array results was verified withreal-time quantitative polymerase chain reaction (qPCR) measure-ments and the cell specificity of changes in corresponding proteinswas examined immunohistochemically. Finally we used data derivedfrom the cap analysis of the hippocampal gene expression [capanalysis of gene expression (CAGE)] technique (Carninci et al., 2006;Valen et al., 2009) to distinguish transcription factors associated withthe processes engaged in the emergence of epileptic activity.

Materials and methods

Intrahippocampal kainic acid injection

Experiments were performed on C57BL ⁄ 6J male mice aged2–3 months (Janvier, Le Genest Saint Isle, France) in accordancewith the European Committee Council Directive of November 24,1986 (86 ⁄ 89 ⁄ EEC) and with INSERM guidelines. KA (50 nLdissolved in 0.9% NaCl at 20 mm) was injected under anaesthesiawith 4% chloral hydrate (120 mL ⁄ kg; Sigma, France) and 4%urethane (1000 mL ⁄ kg; Sigma), as described previously (Le Duigouet al., 2008). Injections of KA or control injections of NaCl weremade at an apical dendritic site in the Cornus Ammonis 1 (CA1)region of the dorsal hippocampus at the following stereotaxiccoordinates: anterior–posterior, )1.8 mm; medial–lateral, )1.8 mm;and dorsal–ventral, )1.8 mm with respect to the bregma (Le Duigouet al., 2008). During recovery from anaesthesia, animals injected withKA displayed behavioural signs of status epilepticus, includingmaintained turning movements. After injection, animals were housedin groups of six to eight.

RNA extraction and target synthesis

We compared RNA expression levels in KA-treated (n = 6, two foreach time-point), NaCl-injected (n = 3, one for each time-point) anduntreated animals (n = 2). Tissue from injected animals was obtainedat three time-points: 6 h, 15 days and 3–6 months after injection. At6 h both hippocampi participated in a status epilepticus, at 15 daysinitial neuronal death was largely terminated and at 3–6 months theanimals generated recurrent seizures. In each case, animals wereanaesthetized with chloral hydrate and urethane, as for the injection

procedure, and decapitated. Both hippocampi were dissected underRNAse-free conditions and divided into ventral and dorsal portions ofapproximately equal volume. Analysed tissue included the dentategyrus, CA regions and subiculum. Samples were treated with TRIzol(Invitrogen, Paris, France) and stored at )80�C before RNA analysis.The time between the onset of anaesthesia and the immersion of tissuesamples in TRIzol was 5–15 min. Total RNA was isolated accordingto the TRIzol reagent protocol. Samples were treated with 2 units ofRNAse-free DNAse (2 units ⁄ lL, Ambion) for 15 min at 37�C toavoid genomic contamination. Total RNA was purified with theRNeasy mini kit (Qiagen, Chatsworth, CA, USA). The RNA integritynumber of our samples, assessed with an Agilent 2001 Bioanalyzer(Agilent, Palo Alto, CA, USA), varied between 8 and 10. ExtractedRNA was quantified with a spectrophotometer (Nanodrop Technolo-gies, Wilmington, DE, USA). A volume of 500 ng of total RNA fromeach sample was used as a template to generate biotinylated cRNAusing the Illumina probe synthesis protocol (Agilent).

Hybridization and scanning

The cRNA was hybridized to Affymetrix mouse 430A 2.0 gene chips(Affymetrix, Santa Clara, CA, USA), which detect RNA transcriptscorresponding to 14 000 well-characterized genes. Sample labellingand array hybridization were performed at the CBM (Trieste)according to the Affymetrix manual. RNA images were scanned andquantified with a GeneChip Scanner 3000 7G (Affymetrix) followingthe manufacturer’s instructions. Two samples of dorsal and ventralhippocampus from non-injected animals were hybridized. Twosamples from each area of KA-injected mice were hybridized foreach time-point, and one sample from NaCl-injected mice using a totalof 40 chips [= 3 · (4 · 3) + 4].

Analysis of genechip data

Expression levels and statistical analyses were made with theBioconductor packages (Gautier et al., 2004). Expression levels fordifferent RNA species were calculated with the Robust MicroarrayAnalysis (RMA) function (Irizarry et al., 2003) of the Affymetrixanalysis package using quantile normalization. Changes in geneexpression were assessed by comparing results from tissue derivedfrom KA-treated, NaCl-injected and untreated animals. Genes wereconsidered as ‘changed’ if their expression levels showed no overlap,that is both values were higher or both lower than all values from bothuntreated and NaCl-injected animals, for a given time-point and tissueorigin. These genes were then selected according to a threshold of logfold-change: KA-treated vs. untreated and vs. NaCl £ )1 or ‡ 1 inlog2 scale. When several copies of a given gene were present in the430A 2.0 gene chip, the highest fold-change was selected. Genesdefined as changed in KA-treated animals therefore passed a dualthreshold with respect to both NaCl-injected and untreated animals.Similar strategies based on values of fold-change have been used inarray studies with low numbers of samples for each condition (e.g.Taoufik et al., 2008). In additional analyses, fold-changes betweenKA-treated and untreated animals were considered.

Data clustering and Gene Ontology associations

Sets of genes with similar time and spatial profiles of alteredexpression were grouped using K-mean clustering. The data consistedof a set of 12 parameters corresponding to suprathreshold changes inexpression at each tissue site and time-point (zero was used for

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ª 2010 The Authors. European Journal of Neuroscience ª 2010 Federation of European Neuroscience Societies and Blackwell Publishing LtdEuropean Journal of Neuroscience, 32, 1364–1379

subthreshold changes). The optimal number of clusters was deter-mined using the Bayesian information criterion.Biological processes associated with different clusters were

examined using a reduced version of the Gene Ontology classifica-tion with the following categories: inflammatory and immuneresponses, cell death, cell growth, intracellular signalling, nuclearsignalling, metabolic processes, extracellular matrix, channels andtransporters, synaptic signalling and other. Genes were annotatedusing the GenMAPP version of Gene Ontology, DAVID Bioinfor-matic Resources (Huang et al., 2009), Medline, Entrez Gene andWikipedia. Matching with clusters was performed with a singleassociation for each species. If a gene was associated with multipleterms, one of them was chosen using Medline. Genes where nopublications were returned for ‘gene, brain’, ‘gene, neuron’ or ‘gene,glia’ were assigned to the category ‘other’. Genes associated withboth more and less specific terms such as ‘cell death’ and ‘nuclearsignalling’ were assigned to the more specific term, in that case ‘celldeath’. All associations for each gene are shown in SupportingInformation Data S2.

Real-time quantitative polymerase chain reaction analysis

Results obtained from array analysis were compared with data fromqPCR analyses of RNA obtained from injected mice at 6 h afterinjection. Tissue was analysed from three mice injected with KA andthree untreated mice. We analysed eight genes with a spread ofchanges in expression according to the array analysis. Forward andreverse primers were designed with a primer length of 18–25 bp, anabsence of cross-homology, a product length of 75–200 bp and amelting temperature of 58–62�C using the Beacon Designer6.0(PREMIER Biosoft International, Palo Alto, CA, USA). The genesselected together with their primers were: Ccl3 (forward primer: 5¢-CCCTTGCTGTTCTTCTCTGACC-3¢, reverse primer: 5¢-CGATG-AATTGGCGTGGAATCTTC-3¢), Gpr34 (forward primer: 5¢-GTGGACTGTGACCAGAATGGAAGC-3¢, reverse primer: 5¢-CCCGTTTGGAGCCAAGTAAGCC-3¢), Hes5 (forward primer: 5¢-GAGAT-GCTCAGTCCCAAG-3¢, reverse primer: 5¢-AAGGCTTTGCTGTG-TTTC-3¢), Hspa1b (forward primer: 5¢-TTCGTGGGAGGAGTTCAAG-3¢, reverse primer: 5¢-GTGATGGATGTGTAGAAGTC-3¢),Isl1 (forward primer: 5¢-ATTGTCCAACCACCATTTCACTG-3¢,reverse primer: 5¢-GATTACACTCCGCACATTTCAAAC-3¢), Inhba(forward primer: 5¢-GAGAACGGGTATGTGGAGATAG-3¢, reverseprimer: 5¢-GGTCACTGCCTTCCTTGG-3¢), Lcn2 (forward primer:5¢-ACGACAACATCATCTTCTC-3¢, reverse primer: 5¢-ATGCTCC-TTGGTATGGTG-3¢) and P2ry12 (forward primer: 5¢-ATTCACA-GAAGAACACTCAAGG-3¢, reverse primer: 5¢-TTGACACCAGGCACATCC-3¢). Transcription levels for the housekeeping genes Actband Gapdh were also tested: Actb (forward primer: 5¢-TGGGTAT-GGAATCCTGTGGCATC-3¢, reverse primer: 5¢-GTGTTGGCATA-GAGGTCTTTACGG-3¢) and Gapdh (forward primer: 5¢-AGAAGGTGGTGAAGCAGGCATC-3¢, reverse primer: 5¢-CGAAGGTGGAAGAGTGGGAGTTG-3¢). Experiments were performed onduplicate samples from three KA-treated and three untreated animals.A volume of 1 lg of RNA was used for reverse transcription,

after dilution at the lowest concentration, with 4 lL of 5 · iScriptSelect reaction mix and 1 lL of iScript reverse transcriptase (iScriptcDNA Synthesis Kit; Bio-Rad, Hercules, CA, USA). The mix waskept for 5 min at 25�C for primer annealing. Reverse transcriptionwas performed at 42�C for 50 min followed by 5 min at 80�C toinhibit the enzyme. For each sample 250 ng of cDNA was mixedwith 10 lL of 2 · iQ Supermix (Bio-Rad), and primers were

diluted to 250 nm in 20 lL with nuclease-free H2O. The reactionwas run on an iQ5 qPCR Detection System (Bio-Rad). Data wereobtained as threshold cycle values with the iQ5 Optical SystemSoftware v2.0 and relative gene expression was calculated bynormalizing with the endogenous housekeeping genes Actb andGadph.

Immunohistochemistry

Immunostaining was performed to examine the expression of proteinscorresponding to transcripts with changed expression from micro-array data. Protein expression was examined in KA-treated and NaCl-injected mice at 15 days and 3–6 months after injection. Mice wereanaesthetized and perfused through the heart with 0.1 m phosphatebuffer (PB) containing 4% paraformaldehyde. After fixation, tissuewas washed in PB, sectioned at 70 lm and immersed in acryoprotective solution containing 30% saccharose and 30% ethyleneglycol in PB saline before freezing at )20�C. Nissl staining wasperformed on one slice from each animal before immunostaining toverify the site and extent of neuronal death. Eight animals were used inimmunostaining work, four treated with kainate and four injected withNaCl.Before immunostaining, sections were washed overnight in 0.1 m

PB saline and then immersed for 4 h in a solution containing 2%bovine serum albumin, 5% skim milk powder and 0.1% Triton-X forsaturation and permeabilization. Primary antibodies were applied for24–48 h at 4�C. We used the following primary antibodies: rabbitanti-glial fibrillary acidic protein (GFAP) (1 : 1000; Promega,Madison, USA), chicken anti-vimentin (1 : 2000; Abcam, Cam-bridge, UK), neuronal nucleus stain (1 : 1000; Chemicon) andbiglycan (1 : 100; gift from Dr M. Goldberg). Immunostaining forbiglycan was preceded by a digestion for 20 min at 37�C with 0.25 Uof chondroitinase ABC (Sigma) at pH 7.5 (Tris buffer). Thesecondary antibodies, Cy-2-conjugated donkey anti-chicken IgY,Cy-3-conjugated F(ab’)2 donkey anti-mouse IgG (1 : 1000) andCy-5-conjugated F(ab’)2 donkey anti-rabbit (1 : 500) (Jackson Im-munoresearch, Baltimore, MD, USA), were then applied for 4 h atroom temperature: 23–25�C. Sections were washed in PB saline andmounted with the anti-fade agent Prolong Gold (Molecular Probes,Eugene, OR, USA).

Microscopy and image quantitation

Images were acquired, scanned and measured using the analysisprogramme Volocity (Improvision, Perkin-Elmer, Coventry, UK) andan acquisition system consisting of an inverted Olympus IX81microscope, an Optigrid II (Thales Optem, Qioptik, Rochester, NY,USA) and a QImaging Retiga EXI camera (Qimaging Surrey, BC,Canada). The Optigrid permitted the acquisition of structured imagesand subsequent three-dimensional reconstruction. Stacks of imagesof the CA1 region, hilus and dentate gyrus were acquired witheither a · 10 objective of NA 0.4 (30–45 images at 1 lm intervalwith voxel size 0.64 lm) or a · 40 objective of NA 1.3 (30–70images at 0.4 lm interval with voxel size 0.16 lm). We compareddorsal and ventral regions of the injected and contralateralhippocampus from three animals injected with either KA or NaCl.The numbers and locations of immunopositive cells, defined by theirhigher voxel intensity, were measured in regions of interest inreconstructed image stacks. Regions of interest were definedmanually in the hilus, stratum molecular of the dentate gyrus,stratum radiatum of the CA1 region and around the hippocampal

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fissure. Results are expressed as the number of cells in a volume of100 · 100 · 100 lm.

Transcription factor binding site analysis

Putative hippocampal promoter candidates were collected for clustersof genes with similar spatio-temporal expression profiles from themicro-array experiments. Promoter regions were selected fromhippocampal deepCAGE tags when available (Valen et al., 2009,promoters with > 10 tags per million only) or from RefSeq (NationalCenter for Biotechnology Information (NCBI) reference sequence)annotations for each gene, when tags were not available. Where a genehad multiple promoters, all regions were considered if they did notoverlap. Overlaps were resolved with the strongest promoters,measured in tags, or by random selection when only RefSeq promoterswere available. Regions were selected to include the annotatedtranscription start site, or the whole tag cluster for deepCAGE, andextended 1000 bp up-stream and 200 bp down-stream.

Models of transcription factor binding sites from the JASPARdatabase (Bryne et al., 2008) were then used to scan the regions. Thematrices were first converted into log-ratio models and searched usingthe Asap framework (Marstrand et al., 2008). The sequence environ-ments of different clusters were compared with each other and with abackground of 5000 randomly selected promoters from the transcrip-tion start-site database DBTSS (Suzuki et al., 2002). The expectednumber of sites per base pair was compared with the background orwith all sites detected across all clusters. The expected number of sitesper cluster was estimated, as the cluster size multiplied by the expectednumber of sites per base pair, and compared with the number of sitesdetected within that cluster. A Z-score was calculated with positivevalues for over-representation and negative values for under-repre-sentation.

Results

Intrahippocampal kainate injection in mice induces a recurringepilepsy syndrome similar to human temporal lobe epilepsies(Bouilleret et al., 1999; Heinrich et al., 2006, Ben-Ari et al., 1985).Epileptic activity emerges with a delay of several weeks (Williamset al., 2009). This genomic analysis was guided by preliminary workon the temporal and spatial properties of the initial status epilepticus,induced neuronal death and emergence of seizures (SupportingInformation Data S1).Genomic analyses were performed on hippocampal tissue at 6 h,

2 weeks and 6 months after kainate injection. Preliminary electroen-cephalogram records showed that at 5 h after KA injection, all regionsof the injected and contralateral hippocampus participated in a statusepilepticus (Supporting Information Data S1). At 5–8 days, neuronaldeath was detected, maximally near the injection site. Recurrentseizures were generated after a delay of several weeks and continuedfor more than 6 months.At each time-point, we analysed separately tissue from dorsal and

ventral regions of both the injected and contralateral hippocampus.Preliminary anatomy showed that neuronal death (SupportingInformation Data S1) was maximal near the injection site in thedorsal hippocampus, occurred in ventral regions of the injectedhippocampus, but was absent in the contralateral hippocampus.Degenerating fibres were evident in the non-injected hippocampus,especially in dorsal regions.All regions used for genomic analysis had thus participated in the

initial status epilepticus, but cell death was limited to the injectedhippocampus. Furthermore, interictal events occur spontaneously intissue slices prepared from both the injected and contralateralhippocampus (Supporting Information Data S1) (Le Duigou et al.,2008). Ictal-like events can be induced by tetanic stimulation at sites inboth the injected and contralateral hippocampus.

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Fig. 1. Numbers of transcripts changed in tissue samples from different time-points and sites. Different tissue sample sites are shown in columns (dorsal and ventralregions of the ipsilateral, injected and contralateral hippocampus) and different time-points (6 h, 15 days and 6 months) are displayed in rows. Each plot is anordered display of all up-regulated and all down-regulated transcripts with the fold-variation for altered transcripts on the y-axis and the number as the x-axis. Thenumber of up- and down-regulated genes for each site is shown as an inset. Note the reduced x-axis scale for the ID tissue at 15 days.

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ª 2010 The Authors. European Journal of Neuroscience ª 2010 Federation of European Neuroscience Societies and Blackwell Publishing LtdEuropean Journal of Neuroscience, 32, 1364–1379

Gene expression profile

Gene expression in hippocampal tissue obtained from KA-injectedanimals was compared with that in samples from NaCl-injected oruntreated animals. At 6 h, the expression of 496 genes was altered, at15 days 1187 genes were changed and at 6 months the expressionof 278 genes was altered. Supporting Information Data S2 lists all1526 genes whose expression was changed, together with the size ofchange at each site and time-point. Figure 1 shows their temporal andspatial distribution.At 6 h, the contralateral ventral (CV) hippocampus showed the

largest number of genes with altered expression (253 up-regulated and17 down-regulated). Genes with altered expression near the dorsalinjection site [ipsilateral dorsal (ID)] (155 genes up-regulated and 21down-regulated) were often different (66%) from those altered atcontralateral sites. Fewer genes were changed in the ipsilateral ventral(IV) (95 genes) and contralateral dorsal (CD) areas (85 genes) andtheir identity was similar to that of genes with altered expression nearthe injection site.As shown in Fig. 1, the largest number of genes were changed at

15 days and the ID region was the site with the largest number ofaltered genes (830 genes up-regulated and 289 down-regulated).Genes with altered expression in the IV hippocampus were oftensimilar (95%) to those affected near the injection site (385up-regulated and 30 down-regulated). In the CD hippocampus theexpression of 211 genes was changed and only eight of them differedfrom the genes altered in the ID hippocampus. The expression of 198genes was altered in the CV hippocampus, and 51 of them (26%)differed from those affected in the ID hippocampus.At 6 months, the expression of fewer genes was altered, nearly all

of them in the injected ID hippocampus (Fig. 1). This group includeda higher proportion of down-regulated transcripts (33%, 180 genesup-regulated, 88 down-regulated). At 6 months, 33% (88 ⁄ 268) weredown-regulated, whereas at 6 h after injection, 12% (21 ⁄ 176) of thegenes changed were down-regulated. Expression at 6 months waschanged for six or seven genes in the IV, CD and CV regions.

Correlation and verification of Affymetrix gene profile data withdata from quantitative polymerase chain reaction

We examined the accuracy of micro-array data by comparing changes ingene expression with those measured by qPCR (Fig. 2). Eighttranscripts were tested. Array analysis reported an altered expressionat 6 h after KA injection for each transcript at one or more sites. Theywere: Inhba (log fold-changes of 2.9 in ID tissue from KA-treated anduntreated animals, 3.4 in IV, 1.8 in CD and 2.7 in CV), Ccl3 (3.7 in ID,3.4 in IV and 2.0 in CD), Hspa1b (4.0 in ID, 2.6 in IV and 2.9 in CD),Lcn2 (4.6 in IV), Gpr34 ()2.1 in ID, )2.3 in IVand )1.9 in CD), Hes5()1.4 in ID and)1.0 in CV), P2ry12 ()2.5 in IV) and Isl1 ()2.9 in CD).Figure 2 compares values for changes in expression obtained with

qPCR and array analysis for the chosen transcripts. The plot includesall data points whether or not they met significance criteria from arrayanalysis. Values obtained from array analysis and from qPCR valueswere well fit with a linear relation: qPCR value = 1.19* (Affymetrixvalue) + 0.48. The r2 value was 0.77, demonstrating a good agreementbetween the two techniques.

Clustering of genes with similar temporal and spatial profilesof altered expression

The identity of transcripts with altered expression should provideinsights into the processes initiated by KA treatment. We sought to

order this information by grouping genes with similar profiles ofchanges in time and at distinct sites. K-mean clustering revealed 10distinct clusters, which are shown in Figs 3 and 4. Clusters 1–3included genes up-regulated at 6 h after KA treatment. Clusters 4–7included genes with distinct spatial patterns of up-regulation at either15 days (clusters 4 and 5) or at both 15 days and 6 months (clusters 6and 7). Transcripts of cluster 8 showed no striking pattern, whereasclusters 9 and 10 contained genes down-regulated at 15 days or atboth 15 days and 6 months.The biological processes associated with different clusters were

explored using a reduced number of terms derived from the GeneOntology classification (see Materials and methods). Each transcriptwas associated with one, or none, of the terms: immune andinflammatory responses, cell death, cell growth, intracellular signal-ling, nuclear signalling, metabolic processes, extracellular matrix,channels and transporters and synaptic signalling (SupportingInformation Data S2). We then defined over-represented processesin each cluster by comparing the proportion of associated transcriptswith the mean proportion for that process over all clusters (dotted linein lower panels of Figs 3 and 4, see Table 1).We tested whether the association of processes with clusters was

robust by making a higher-stringency list of altered genes compiledby increasing the log fold-threshold from 1.0 to 1.5. At higherstringency, the number of accepted genes was reduced from 1526 to847. Associations of processes with clusters were then re-examinedusing the same clusters; 13 of 15 processes over-represented in agiven cluster in low-stringency conditions were also over-repre-sented in the high-stringency case (Table 2). The associationsbetween processes and clusters satisfying both levels of stringencywere: cluster 1, cell death, nuclear signals and metabolic processes;cluster 2, nuclear signals; cluster 3, growth processes and intracel-lular signals; cluster 4, cell death; cluster 6, inflammation andimmune response; cluster 7, extracellular matrix and synapticprocesses; cluster 9, synaptic processes; and cluster 10, metabolicprocesses and channels and transporters. We next examined how

Fig. 2. Comparison of expression changes from array analysis and qPCR forselected genes. Estimates of expression changes for eight genes from qPCR areplotted against estimates from array analysis. Measurements were made ontissue from different hippocampal regions at 6 h after KA injection ofalterations in Inhba, Ccl3, Gpr34, Hspa1b, Hes5, Lcn2, P2ry12 and Isl1. Allvalues from both qPCR and array analysis were compared whether or not thearray data met our significance criteria. A linear fit gave the relation: qPCRvalue = 1.19* (Affymetrix value) + 0.48 (r2 = 0.77).

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individual genes associated with specific processes mapped onto theclusters.

Nuclear signalling

Transcripts associated with nuclear signalling were over-represented inclusters 1 (n = 43) and 2 (n = 199). Genes in both of these clusters(Fig. 3; Supporting Information Data S2 and S3) were up-regulated at6 h. Those of cluster 1 were maximally changed near the IV injectionsite, whereas cluster 2 showed a larger up-regulation in the CVhippocampus. Cluster 1 contained a high proportion of transcriptionfactors including Atf3, Fosb and Maff. Cluster 2 included transcriptionfactors (Zfx, Sp4 and Pbx1), as well as genes coding for molecules thatregulate chromatin structure either by DNA methylation (Atrx) or byhistone modification (Smarca5). These data suggest that distinctnuclear signalling processes were activated in the injected and non-injected hippocampus at 6 h.

Genes associated with nuclear signalling (Supporting InformationData S3) were under-represented in clusters 5–7 (Figs 3 and 4),

consisting of genes changed at multiple sites at later time-points.Clusters 4 and 9, comprising genes up- or down-regulated at theinjection site at 15 days, revealed a second wave of changes in genesassociated with nuclear signalling. Up-regulated transcripts includedgenes involved in cell cycle control (Cdc2a and Cdca3), whereastranscription factors from the LIM and distal homeobox families(Lhx8, Lhx9, Dlx1 and Dlx5) were down-regulated.

Cell death and cell growth

Transcripts associated with cell death processes were over-repre-sented in clusters 1 and 4 (n = 383). Cluster 4 consisted of genesup-regulated at the injection site at 6 h and 15 days (Fig. 3). Theyincluded (Supporting Information Data S2 and S3) members of thecaspase (Casp7 and Casp8) and cathepsin (Ctsb and Ctsl) families,and other regulators and effectors of cell death (Fas, Lamp2 andTnfrsf13b). Transcripts associated with cell death were also present inclusters 5 (Casp4 and Naip2) and 6 (Lyzs and Bcl2a1a) correspond-ing to increases in gene expression at the injection site at 15 days.

ID IV CD CV ID IV CD CV ID IV CD CV6 h 15 days 6 months

Cluster 2n = 198

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4 Cluster 5n = 197

ID IV CD CV ID IV CD CV ID IV CD CV6 h 15 days 6 months

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Fig. 3. Clusters of genes with similar patterns of regulation: part 1. Ten clusters emerged from a k-mean clustering of data for changes in expression of all alteredgenes produced. (A–F) Clusters 1–6. The number (n) of transcripts in each cluster is given. For each cluster, the upper panel shows values (fold-change, log2 scale)for each altered transcript in gray, together with mean and SDs of changes in black, for each time-point (6 h, 15 days and 6 months) and for each region. The lowerpanel summarizes the associations of transcripts of that cluster with a reduced number of Gene Ontology categories (inflam, inflammatory and immune processes;death, processes associated with cell death; growth, processes associated with cell growth; intsig, intracellular signalling molecules; nuc, nuclear signallingmolecules; met, metabolic processes; ecm, extracellular matrix molecules; chan, channel and transporter molecules; syn, molecules associated with synapticfunction). The mean for each category in all clusters, permitting definition of over- and under-represented categories for the cluster, is represented by a brokenhorizontal line.

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ª 2010 The Authors. European Journal of Neuroscience ª 2010 Federation of European Neuroscience Societies and Blackwell Publishing LtdEuropean Journal of Neuroscience, 32, 1364–1379

Changes in genes associated with cell death processes were restrictedto clusters involving the ID injection site and were under-representedin clusters associated with later time-points such as clusters 9 and 10(Fig. 4).In contrast, genes associated with growth processes were over-

represented in cluster 3 (n = 51) consisting of transcripts up-regulatedat both 6 h and 15 days in the contralateral hippocampus. Genes

associated with this cluster included Mbp and dclk1. The profile ofclusters 1–4 revealed an early activation of genes associated with celldeath near the injection site and a concurrent, contralateralup-regulation of genes associated with growth processes.Transcripts associated with cell growth (Supporting Information

Data 3) were also over-represented in clusters 7 and 9. Cluster 7included growth factors (Gdnf and Bdnf) and molecules of the Wnt

Table 1. Low stringency, threshold 1.0, 1526 genes

Inflam Death Growth Intsig Nuc Met Ecm Chan Syn Other Total

C1 18.9 10.8* 2.7 10.8 29.8* 18.9 0.0 5.4 2.7 6 43C2 2.5 5.0 10.6 14.2 40.4* 13.0 2.5 7.5 4.3 38 199C3 2.8 2.8 19.4* 27.8* 13.9 16.7 0.0 8.3 8.3 15 51C4 15.4 8.4* 7.7 14.1 18.5 15.8 9.4 6.7 4.0 85 383C5 31.2 6.6 7.3 13.9 10.6 15.9 8.6 4.6 1.3 46 197C6 60.5* 7.0 5.8 3.5 2.3 8.1 3.5 7.0 2.3 24 110C7 12.0 3.6 16.9* 9.6 9.6 15.7 16.9* 2.4 13.3* 11 94C8 17.7 2.5 8.4 11.8 23.5 15.1 10.9 5.9 4.2 29 148C9 3.3 1.1 19.7* 18.5 16.9 10.9 4.4 7.7 17.5* 54 237C10 15.0 0.0 2.5 7.5 17.5 22.5* 12.5 15.0* 7.5 24 64

1526Mean 17.9 4.8 10.1 13.2 18.3 15.3 6.9 7.1 6.5

SD 17.4 3.4 6.4 6.6 10.9 4.0 5.7 3.3 5.2

Comparison of the attribution of processes to clusters with low stringency threshold of log fold-change > 1.0 for gene inclusion (n = 1526 transcripts) (Table 1) andhigher stringency threshold of log fold-change > 1.5 (n = 847 transcripts) (Table 2). Clusters are numbered 1–10 and the proportion of transcripts associated with thefollowing terms is shown for each cluster: immune and inflammatory responses (Inflam), cell death (Death), growth processes (Growth), intracellular signalling(Intsig), nuclear signalling (Nuc), metabolic processes (Met), extracellular matrix (Ecm), channels and transporters (Chan), and synaptic signalling (Syn). Thenumber of genes assigned to the category ‘Other’ and the total number of genes assigned to that cluster are given. *Values indicating an up-regulation by more than 1SD from the mean for a category. Twelve of 14 attributions when the threshold was 1.0 were retained when the threshold was increased to 1.5 (Table 2).

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Fig. 4. Clusters of genes with similar patterns of regulation: part 2. (A–D) Clusters 7–10 are shown with the same conventions as in Fig. 3.

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(Wisp2) and semaphorin signalling families (Sema3a), which were up-regulated at both 15 days and 6 months. Genes of cluster 9, down-regulated at 15 days, included other growth factors (Nov) andmolecules associated with cellular adhesion (Pkp2).

Immune responses and inflammation

Figure 3 shows that genes associated with immune and inflammatoryresponses were over-represented in cluster 6 (n = 110) and stronglyrepresented in cluster 5 (n = 197). Cluster 6 consisted of transcripts up-regulated at ipsilateral and contralateral sites at both 15 days and6 months. They included cytokines (such as Cxcl13 and Ccl12) andtheir receptors (Ccr5 and Osmr), Fc receptors (Fcgr1 and Fcgr2b), CDfamily antigens (Cd44 and Cd52) and elements of the complementcascade (including C1 and C4b). Increased expression of genes incluster 5 was limited to tissue samples from 2 weeks. Cluster 6 includedcytokines (Cxcl9), their receptors (Cx3cr1 and Csf1r) and CD familyantigens (Cd22 andCd53). Elements of the complement cascade and Fcreceptors were poorly represented in this cluster but several componentsof the histocompatibility complex were up-regulated (including H2-Land H2-Q8), as were toll-like receptors (Tlr1, Tlr2 and Tlr7) andinterferon-induced proteins (Ifi204 and Ifitm3).

Multiple immune system genes (Supporting Information Data S2and S3), including some specific to immune cell types (such as Lcp2and Ctla2b), were activated at early or late time-points, transiently orpersistently, in the contralateral and ipsilateral hippocampus. Thecontralateral activation of immune system genes was typicallyweaker than changes in expression of the same genes near theipsilateral injection site. It included elements of the complementsystem (C1qa and C3ar1) as well as genes specific to immune cells(Xlr4b and Ctla2b). The expression of some cytokine ligands (suchas Ccl3 and Cxcl1), but not receptors, was enhanced at 6 h. Genesassociated with antigen presentation (including Fcgr1 and H2-Q8)and cell surface modulators of immune signalling (such as Cd52 andCd84) were activated at 15 days. Multiple transcripts associated withinflammatory responses were persistently activated at the IV site atboth 15 days and 6 months. They included genes coding formolecules of the complement cascade (including C1qc and C4b),for elements of interferon signalling pathways (Igtp and Ifit1) as wellas genes associated with immune cell types (such as Ctla2a andLcp1).

Intracellular signalling

Transcripts linked to intracellular signalling were most stronglyrepresented in cluster 3, which corresponded to changes in the CVhippocampus at early and mid time-points (Fig. 3). The most stronglyup-regulated genes in this cluster coded for kinases, including Jak1and Map2k4, and phosphatases, such as Ppm1b and Ptprt.

There were few changes in the expression of genes coding forintracellular signalling molecules near the injection site at 6 h (cluster1). They included transcripts coding for the kinase, Cam2kb, and theRAS-signalling molecule, Rhoj. Many genes in this category wereup-regulated at 15 days after injection. Some genes associated withlipid signalling, including Plek and Ptger4, were strongly and widelyup-regulated as were the tyrosine phosphatases Ptpn6 and Ptprc.Down-regulated genes near the injection site at 15 days included theRAS-signalling-related Rasd2 and the phosphodiesterases, Pde1a andPde2a. The RAS-related gene Arr3 and the kinase Prkcd were amongfew genes coding for intracellular signalling molecules that remainedaltered at 6 months.

Metabolic processes

Genes associated with metabolic processes were over-represented incluster 10 corresponding to transcripts down-regulated near theinjection site at 15 days and 6 months (Fig. 4). The most stronglydown-regulated genes were related to lipid (Pon1 and Pla2g5) andamino acid (Phgdh and Bhmt) metabolism.As listed in Supporting Information Data S3, heat-shock genes

associated with protein folding, Hspa1a and Hsp1b, were up-regulatedat early time-points (cluster 1) and transcripts associated withubiquination, including Usp18 and Ube2c, were enhanced at 15 daysafter KA injection (clusters 4–6). Genes involved in nucleotidemetabolism, including Oas1g and Oasl2, were strongly but transientlyup-regulated as were genes involved in prostaglandin synthesis,including Ptgds2 and Ptgs1(clusters 4–6). Some transcripts involvedin carbohydrate metabolism were persistently up-regulated at both15 days and 6 months after KA treatment (cluster7).

Extracellular matrix proteins

Genes associated with extracellular matrix molecules were over-represented in cluster 7 (n = 94). This cluster consisted of transcriptsup-regulated at multiple sites at 15 days and also persistently near theinjection site at 6 months (Fig. 4). They included proteoglycans,collagens and metallo-peptidases (Supporting Information Data S3).Up-regulation of genes coding for some proteoglycans, includingAcan, and Tnc was lower at 6 months than at 15 days, whereas theexpression of Fn1 and genes coding for the procollagens Col6a1 andCol11a1 was stronger at 6 months. These genes may be associatedwith the formation of a glial scar.Extracellular matrix proteins were little changed at 6 h after KA

injection (clusters 1 and 2; Supporting Information Data S2 and S3).Transcripts up-regulated at 15 days (clusters 4–6) included lectins(Lgals3bp and Lgals9), integrins (Itgb2 and Itgam) and metallo-proteinases (Timp1 and Timp2). Some genes coding for extracellularmatrix components, such as Col19a1, were down-regulated only at15 days and others, such as the coagulation factor F5, were also down-regulated at 6 months.

Synaptic signalling, membrane transporters and channels

Cluster 9 (n = 237) consisted of genes down-regulated at 15 daysand genes of cluster 10 (n = 64) were down-regulated at both15 days and 6 months (Fig. 4). These changes were largely limitedto the injection site. Genes associated with synaptic signalling tendedto be transiently down-regulated at 15 days (cluster 9), whereasthose coding for ion channels and transporters tended to bepersistently down-regulated (cluster 10). Transiently down-regulatedtranscripts associated with synaptic transmission included thosecoding for peptides (Nts and Sst), G-protein-operated receptors(Npy2r and Cckbr) as well as the vesicular GABA (Slc32a1) andvesicular glutamate (Slc17a6) transporters. Membrane channeltranscripts down-regulated at both 15 days and 6 months includedthe genes Kcnh2, Kcnq5 and Kcne2, which code for potassiumchannels.Few genes coding for channels, transporters and molecules

associated with synaptic function were altered at 6 h. Among theexceptions were Atp2b2, Slc12a2 and Gad2, which were allup-regulated in the contralateral hippocampus at 6 h after KAinjection. Clusters 5–7 consisted of transcripts up-regulated at multiplesites at 15 days including genes coding for the transporters, Slc43a3

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ª 2010 The Authors. European Journal of Neuroscience ª 2010 Federation of European Neuroscience Societies and Blackwell Publishing LtdEuropean Journal of Neuroscience, 32, 1364–1379

and Slc15a3, which transport amino acids and urea, respectively. Theyalso included transcripts coding for peptides and G-protein-coupledreceptors including Trh, Penk1 and Sucnr1, which were stronglyup-regulated at both 15 days and 6 months.

Changes in expression of selected proteins: glial cells

Although micro-array data identify RNA species with an alteredexpression, they do not provide insights into their cellular specificity.Astrocytes are activated in epilepsy models involving status epilep-ticus and neuronal cell death (Wetherington et al., 2008). Array datarevealed an up-regulation of genes expressed in astrocytes (Cahoyet al., 2008), including Aqp4 and Gfap. We examined the expressionof Gfap and vimentin, Vim, which are associated with intermediatefilaments and enriched in astrocytes. Array data indicated that Vim wasup-regulated at 6 h and both Vim and Gfap signals were increased at15 days and near the injection site at 6 months. Figure 5A showsimmunostaining for the neuronal marker neuronal nucleus stain todefine neuronal architecture and verify neuronal loss. Figure 5B and Cshows staining for Vim and Gfap. At 15 days, astrocytes expressingVim and Gfap in KA-injected animals were larger, with more complexprocesses than those expressing Gfap alone in NaCl-injected animals(Fig. 5C). At 15 days, the number of cells expressing both Vim andGfap increased. The increase was larger in the injected than in thecontralateral hippocampus (Fig. 5D) and was most evident in the hilusand the dentate region, although cells present in the CA1stratumradiatum also expressed both markers.

Changes in expression of selected proteins: extracellular matrix

Micro-array analysis also revealed a persistent up-regulation of genescoding for extracellular matrix proteins in ID tissue close to theinjection site (cluster 7, Fig. 4). Figure 6 shows immunohistochemicalevidence for changes in expression of the matrix proteoglycan,biglycan (Fleischmajer et al., 1991). In control animals at 2 weeksafter NaCl injection (Fig. 6B), biglycan was detected in the cytoplasmof isolated neuronal nucleus stain-immunopositive cells. InKA-injected animals, however, it was highly expressed in astrocytesidentified by GFAP immunostaining at 2 weeks after injection. Anindistinct, presumably extracellular, staining was evident especially inprincipal cell layers (Fig. 6A). At 6 months after KA injection,biglycan immunostaining was still somewhat elevated in regions ofneuronal loss, was largely absent from GFAP-positive cells and wasevident in distant neuronal nucleus stain-positive cells (Fig. 6C andD). Little contralateral staining was apparent. Our data suggest thatthis proteoglycan forms part of a persistent glial scar in regions ofneuronal loss (Galtrey & Fawcett, 2007; Gurtner et al., 2008) and maybe synthesized by activated astrocytes.

Transcription factor binding site analysis

Transcriptional mechanisms presumably orchestrate some of theprocesses induced after KA injection. One way to identify the factorsinvolved is to link changes in gene expression with potentialtranscription factor binding sites. We used a computational approach

A

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Fig. 5. Up-regulation of vimentin and GFAP in the ipsilateral hippocampus at 15 days. (A) Low-magnification micrograph showing the injected (left) andcontralateral hippocampus stained with neuronal nucleus stain (NeuN). The asterisk in the injected hippocampus indicates a reduced signal in the CA1 stratumpyramidale associated with KA injection. Red rectangles outline regions shown in subsequent panels. (B–D) Immunostaining for NeuN (neurons, orange), vimentin(Vim) (green), GFAP (red) and merged green and red images. The white asterisk indicates the CA1 pyramidal cell layer and the circle indicates the hilus. (B) Dorsalhippocampus of an NaCl-injected animal (NaCl ID). Dorsal injected hippocampus of a KA-treated animal (KA ID). Dorsal contralateral hippocampus of a KA-treated animal (KA CD). The expression of vimentin and GFAP was increased in CA1, the hilar region and the dentate of KA-injected animals. (C) Uppermicrographs: a cell from an NaCl-injected animal immunopositive for GFAP (red) but not Vim (green). Lower micrographs: a cell immunopositive for both Vim andGFAP from a KA-injected animal. Cells expressing both markers were larger with more complex processes. (D) Density of cells positive for both Vim and GFAP inthe hilar region (number of cells ⁄ 100 lm3). Vim- and GFAP-positive cell density was increased in dorsal and ventral regions of the injected hippocampus and in theventral contralateral hippocampus from KA-treated animals.

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to identify putative sites in promoter sequences corresponding togenes associated with the clusters. We took advantage of a dataset ofdeepCAGE tags from mouse hippocampus (Valen et al., 2009) toidentify transcription start sites and promoter regions in this brainregion and used RefSeqs when tags were unavailable. The JASPARdatabase of transcription factor binding sites (Bryne et al., 2008) wasthen used to compare the frequency of sequences for specifictranscription factors with an average frequency from a randomlychosen set of 5000 promoters. Over- and under-represented bindingsites linked to specific clusters are shown as a heatmap in Fig. 7A. Anuneven distribution within the clusters was detected for 60 of 89transcription factor binding profiles in the JASPAR database. Unsu-pervised hierarchical clustering revealed two major groups. The first,consisting of expression clusters 2, 4 and 9, was associated with thelargest over- and under-representations and binding sites forTranscription Factor AP-2 alpha (TFAP2A) and Ras-respondingelement binding protein 1 (RREB1), for instance, are strongly over-represented in these clusters. The other seven clusters showed weakerassociations.

We identified three transcription factors that showed both an unevendistribution across clusters and an altered expression in the array data(Fig. 7B–D). The temporo-spatial distribution of expression changeswas well matched with representations of their binding profiles. Thus,

Stat1(Fig. 7B), which may contribute to transcriptional processesassociated with the inflammatory response and gliogenesis (Bonniet al., 1997; He et al., 2005), was up-regulated in all areas at 15 daysand high expression persisted at the injection site at 6 months. Bindingsites for Stat1 were over-represented in clusters 4–7 (Figs 3 and 4)corresponding to genes up-regulated at the 15 day and 6 month time-points. The transcription factor Hlf (human in JASPAR) was down-regulated at the injection site at 15 days (Fig. 7C). Binding siteanalysis revealed an under-representation in clusters 4 and 9 consistingof transcripts of up- or down-regulated genes at 15 days. The thirdtranscription factor with altered expression and unevenly representedputative binding sites was Klf4 (Fig. 7D). RNA for Klf4 wasup-regulated at 6 h, whereas binding sites were detected later ingenes up-regulated at 15 days in clusters 4 and 5.

Discussion

This study has profiled changes in gene expression after theintrahippocampal injection of KA to produce a chronically epilepticanimal. Altogether, changes were detected in the expression of about1500 transcripts in samples from three time-points: (i) during theKA-induced status epilepticus, (ii) before recurrent seizures emerged,and (iii) in chronically epileptic animals. Clustering genes with similar

A B

C D

Fig. 6. Increased expression of biglycan at 15 days and 6 months. (A) Micrographs of the CA1 region, dentate gyrus and hilus, as in Fig. 5 , immunostained forbiglycan (Bgn) (red), neuronal nucleus stain (NeuN) (neurons, white), GFAP (astrocytes, green) and merged GFAP and biglycan signals. The white asterisks indicatethe CA1 pyramidal cell layer and the circles indicate the hilus. Upper row: NaCl-injected animal at 15 days. Middle row: KA-injected hippocampus at 15 days.Lower row: KA-injected hippocampus at 6 months. (B) Higher power micrographs showing different cell types. Upper row: Biglycan-immunopositive neuron(NeuN) of an NaCl-injected animal at 15 days. Middle row: Biglycan-immunopositive astrocyte (GFAP) from the KA-injected hippocampus at 15 days. Lower row:Biglycan-immunopositive neuron (NeuN) of a KA-injected hippocampus at 6 months. (C) The glial scar at 6 months showing the CA1 stratum pyramidale with fewneurons (NeuN, white), multiple astrocytes (GFAP, green) and a diffuse biglycan signal (red). (D) Comparison of the intensity of the biglycan signal at different sitesin tissue from NaCl- and KA-treated animals. Signal intensity was derived from a volume column including the CA1 stratum pyramidale and both blades of thedentate gyrus in animals at 15 days after injection. The NeuN and biglycan signals for one animal are shown above. Biglycan signal intensity was higher in KA-treated animals at all sites, with a specific increase in the dentate region after the hippocampal fissure. sr, stratum radiatum of CA1; FH, hippocampal fissure; sm,stratum moleculare of the dentate gyrus.

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ª 2010 The Authors. European Journal of Neuroscience ª 2010 Federation of European Neuroscience Societies and Blackwell Publishing LtdEuropean Journal of Neuroscience, 32, 1364–1379

patterns of altered expression revealed multiple processes withdifferent kinetics (Figs 3 and 4). They included an early activationof nuclear signalling, strong immune, cell death and growth responsesat 2 weeks, and a persistent activation of immune and extracellularmatrix genes. Immunostaining confirmed changes in proteins coded bysome genes identified from the array studies, provided evidencefavouring gliogenesis and suggested that the proteoglycan biglycan isone of the extracellular matrix proteins contributing to the glial scar inan epileptic brain.

A focal epilepsy model permits separation of differentepileptogenic stimuli

The focal KA injection model of epilepsy may permit discriminationbetween responses to distinct stimuli in the injected and contralateralhippocampus. Our data suggest that two proepileptic stimuli initiateddistinct genomic responses and another potential stimulus did notleave a major trace. The first stimulus was the status epilepticus. Itspread through all regions of both the ipsilateral and contralateralhippocampus. At 6 h, when samples were taken for transcript analysis,the largest electroencephalogram signals were generated in the

contralateral hippocampus (Supporting Information Data S1). Geneexpression changes centred on the ventral, contralateral hippocampusat 6 h and 15 days (clusters 2 and 3, but see also cluster 1) probablyderived from this stimulus. The second proepileptic stimulus wasneuronal death, which was maximal near the injection site and absentin the contralateral hippocampus (Supporting Information Data S1).Neuronal death and the ensuing events seem likely to have initiatedmany changes, strongest at ID sites near the injection site and apparentat both the 15 day and 6 month time-points (clusters 4–7, 9 and 10).Thirdly, deafferentation may be a proepileptic stimulus (SupportingInformation Data S1). Fibre degeneration was maximal near theinjection site, but deafferentation, due to the loss of commissuralprojections, was also evident in the dorsal contralateral hippocampus.We did not detect a group of genes whose pattern of altered expressionfit with the prediction for this stimulus.Figures 3 and 4 show over- and under-represented processes in

clusters of genes with similar spatio-temporal patterns of regulation.Continuation of this analysis, by separating clusters with ipsilateral(clusters 1, 4–7, 9 and 10) and ⁄ or contralateral (clusters 2, 3 and 6)contributions, provides a schematic time-course for different processesas shown in Fig. 8. During the status epilepticus, nuclear signalling

RoazNFYA

HNF4AETS1

ELK1MZF1_1.4

MZF1_5.13Myf

SP1Arnt.Ahr

ZNF354BRAC1

SPI1Klf4

RREB1TFAP2A

STAT1IRF1

NR2F1Pax4

Hand1.Tcfe2aRORA_1

ELF5NHLH1

MafbCREB1

MIZFBapx1

Ddit3.CebpaTAL1.TCF3

YY1Pax2

SOX9FOXI1

FosGATA3

Lhx3.1Pdx1

NoboxFOXL1

Foxd3Nkx2.5

Prrx2GATA2

Foxa2MEF2A

HLFNFIL3

Sox17Gata1

TBPCebpa

En1FOXC1

SRYSox5

NKX3.1Foxq1

Lhx3.2

SPIB

C4 C9 C2 C7 C10 C8 C3 C1 C5 C6

ID IV CD CV ID IV CD CV ID IV CD CV6 h 15 days 6 months

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Fig. 7. Transcription factor binding site analysis for differentially expressed genes. (A) Heatmap showing Z-scores for associations between transcription factors(columns at right) and clusters (as in Figs 3 and 4 , bottom line). Upper left: colour key and relative abundance histogram. Hierarchical clusters are indicated for bothgene clusters (above, clusters 1–10) and transcription factors (at right). An uneven distribution could be identified for the transcription factors STAT1, Klf4 and HLF(highlighted in red). (B–D) Plots for the three identified transcription factors of the changes in expression as solid lines superimposed on the distribution of changesin the clusters with which they showed a higher (B, Stat1; D, Klf4) or lower (C, Hlf) association.

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was engaged in both the ipsilateral and contralateral hippocampus.Genes associated with cell death were activated at 6 h in the ipsilateralhippocampus, whereas transcripts associated with growth processeswere up-regulated contralaterally. Both processes were maintained to15 days. At 15 days, genes contributing to an inflammatory responsewere strongly activated in both hippocampi. Distinct genes associatedwith cellular growth or coding for extracellular matrix proteins wereup-regulated in the injected hippocampus. Genes associated withsynaptic function or coding for membrane channels and transporterswere down-regulated in the injected hippocampus. At 6 months,changes in expression were largely restricted to the injection site.Genes involved in nuclear signalling, inflammatory processes, growthand extracellular matrix were persistently activated at that site. Genes

coding for channels and transporters, but not for synaptic function,remained down-regulated.

Technical points

Altered transcripts were identified with an array (mouse 430 A2.0;Affymetrix) that is more complete than previous versions and using arelatively low threshold to define change. Our detection of transcriptswith altered expression was based on a fold-change comparison (e.g.Taoufik et al., 2008) and a double threshold for change obtained bycomparing KA-treated with both NaCl-injected and untreatedanimals. Larger numbers of animals would have permitted alternativestatistical approaches. Caution is clearly needed, but the agreement

Hours

Nuclear signallingCell death

Dorsal Inflammation

Injected Channel

GrowthEc matrixSynapse

Ventral Cell deathInflammation

ContralateralNuclear signaling

Nuclear signaling

Dorsal Inflammation

Inflammation

GrowthIntracellular signaling

Ventral

Weeks Months

Fig. 8. Processes initiated in the ipsilateral and contralateral hippocampus. Schematic time-course of the processes initiated in the injected and contralateralhippocampus by KA injection, produced by identification of over-represented categories for clusters associated with ipsilateral sites (1, 4–7, 9 and 10) and thoseassociated with contralateral sites (2, 3 and 6) at 6 h (1–3), 15 days (1, 3–7, 9 and 10) and 6 months (6 and 10) Ec: Extracellular.

Table 2. Higher stringency, threshold 1.5, 847 genes

Inflam Death Growth Intsig Nuc Met Ecm Chan Syn Other Total

C1 19.4 11.1* 2.8 11.1 27.8* 19.4* 0.0 5.6 3.0 6 42C2 6.5 3.2 14.5 8.1 40.3* 11.3 1.6 8.1 6.5 13 75C3 8.3 0.0 41.7* 16.7* 8.3 8.3 0.0 8.3 8.3 3 15C4 22.3 9.7* 4.9 14.6 13.6 12.6 8.7 8.7 4.9 24 127C5 34.5 6.3 6.3 12.7 10.6 15.5 8.5 4.2 1.4 43 185C6 60.9* 5.7 5.7 3.4 2.3 8.0 3.4 6.9 2.3 23 110C7 15.4 3.8 15.4 7.7 10.3 16.7 15.4* 2.6 12.8* 11 89C8 23.3 0.0 10.0 13.3 16.7 16.7 16.7* 13.3 3.3 4 34C9 4.4 0.0 18.7 12.1 17.6 12.1 4.4 11.0 19.8* 24 115C10 20.6 0.0 2.9 8.8 14.7 20.6* 8.8 17.6* 5.9 21 55

847Mean 21.6 4.0 12.3 10.9 16.2 14.1 6.8 8.6 6.8

SD 16.5 4.2 11.7 3.9 10.8 4.4 6.0 4.4 5.7

*Values indicating an up-regulation by more than 1 SD from the mean for a category.

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between array data, qPCR data and also immunhistochemistry toexamine protein expression tends to support our approach. Theresulting list of modified genes (Supporting Information Data S2 andS3) is rather larger than those emerging from some previous profilingwork on animal models of epilepsy (Becker et al., 2003; Elliottet al., 2003; Lukasiuk et al., 2003). The larger number of identifiedtranscripts helped to construct a global view of processes initiated byKA injection (Fig. 8). Comparison with a higher stringency cut-offshowed that the identity of these processes is robust (Table 1). Ourtissue samples were relatively large, yielding large quantities of RNAbut dictating a coarse spatial resolution. A comparison of geneprofiles from smaller regions such as the sclerotic CA1 zone shouldprovide more precise information.We did not attempt to separate genetic material from different cell

types. Thus, our data include information on genes expressed by bothneurones and different types of glial cell (Wetherington et al., 2008;Cacheaux et al., 2009). Neuronal death and glial proliferation duringepileptogenesis (e.g. Lee et al., 2007) seem likely to alter theproportion of transcripts deriving from these different cell types andso introduce a bias. Such an effect should be maximal near theinjection site and absent contralaterally. To estimate its amplitude, wecompared changes in the expression of genes enriched in, or specificto, neurons with those in transcripts linked with astrocytes (Cahoyet al., 2008) (Supporting Information Data S4). The mean change inexpression of neuron-associated genes at the injection site at 15 daysafter kainate injection was )1.0 ± 1.6-fold (n = 60), significantlydifferent from that for transcripts associated with astrocytes, whichwas +1.4 ± 1.6-fold (n = 36; P < 0.01, unpaired t-test).

Changes in expression of specific genes

A reactive gliosis occurs in response to neuronal damage in brainregions from the spinal cord (Velardo et al., 2004) to the retina(Vazquez-Chona et al., 2004), including the hippocampus (Heinrichet al., 2006). Our array data detected, and immunohistochemistryconfirmed (Fig. 5), an up-regulation of the intermediate filamentproteins vimentin and GFAP, which are associated with reactiveastrocytes (Pekny & Pekna, 2004). Both proteins are also expressed bynewly generated astrocytes (Mi & Barres, 1999). Our data alsorevealed an up-regulation of genes (including Top2a, Pbk and Melk)enriched in immature astrocytes and preoligodendrocytes (Cahoyet al., 2008) (Supporting Information Data S4) near the injection site,which would support a gliogenesis. Neurogenesis seems to besuppressed at this time-point (Ledergerber et al., 2006; Hattiangady& Shetty, 2009), and we detected a down-regulation of dcx, which hasalso been observed in the neurogenic zone of the dentate (Heinrichet al., 2006). Transcripts associated with myelinization (Cahoy et al.,2008) were up-regulated in the contralateral hippocampus (clusters 3and 5), suggesting an enhanced oligodendrocyte activity. These datasuggest that multiple glial cell types are activated in response to thestatus epilepticus.Genes coding for extracellular matrix proteins were persistently

up-regulated at 6 months near the KA injection site. Proteins codedby these transcripts, including procollagens, glycoproteins andproteoglycans (Supporting Information Data S3), contribute to theformation and maintenance of a glial scar (Galtrey & Fawcett, 2007).Figure 6 shows an elevation of both intracellular and extracellularexpression of the proteoglycan biglycan (Schaefer & Iozzo, 2008) at15 days and 6 months. Astrocytes were strongly stained, suggestingthat they may synthesize biglycan when activated after neuronalinjury (Stichel et al., 1995). Extracellular matrix proteins are

suggested to inhibit axonal growth (Bareyre & Schwab, 2003;Galtrey & Fawcett, 2007) and biglycan could contribute to amaintained inflammatory state by interactions with proinflammatorymolecules (Babelova et al., 2009).

Binding sites and transcription factors

A computational approach provided some insights into the tran-scriptional basis of processes induced by KA injection (Fig. 7). Weused a database of transcription factor binding profiles (JASPAR)(Bryne et al., 2008) and data on promoter regions from deepCAGEanalysis of hippocampus tags to examine putative binding sitesassociated with all transcripts in each cluster. This approach, similarto that previously used to identify sets of coregulated genes fromarray data (Segal et al., 2003), revealed a start site distribution forstat1, Hlf and Klf4 that correlated well with their spatio-temporalchanges in expression.More generally, changes in transcription factor expression reported

by the array data tended to reflect processes engaged at that time-point (Fig. 8). Thus, transcription factors associated with stressresponses formed part of clusters 1 and 2. Several transcriptionfactors in mid time-point clusters 4–7, including stat1, are suggestedto orchestrate immune responses. The down-regulated clusters, 9 and10, included several transcription factors (Arx, Dlx1, 2 and 5, Lhx 6,8 and 9, and Otx2) associated with neuronal, especially interneuro-nal, specification. This effect may reflect a signal dilution due toGABAergic cell death, or possibly dedifferentiation processes inthose cells. Either process could underlie the transient down-regulation of the inhibitory cell markers, parvalbumin and somato-statin (cluster 9).

Comparison with previous gene array studies

Multiple gene profiling studies have now been made on animalepilepsy models. The differentially regulated genes detected in thesestudies vary (Wang et al., 2009), partly perhaps due to variability inarray techniques, or in the model or time-points studied. However, aconsensus may be emerging at least on genes that participate in similarbiological processes (Lukasiuk et al., 2003; Aronica & Gorter, 2007;Pitkanen & Lukasiuk, 2009).Early gene changes associated with epilepsy models, close to the

15 day time-point used here, include transcripts associated withinflammation, cell death and glia activation (Tang et al., 2002; Beckeret al., 2003; Elliott et al., 2003). Later time-points show an activation ofgenes coding for extracellular matrix proteins (Tang et al., 2002;Lukasiuk et al., 2003; Gorter et al., 2006). Genes associated withinflammatory responses are persistently activated (Becker et al., 2003;Gorter et al., 2006) including factors of the complement family(Aronica et al., 2007), as well as transcripts linked with microglialand astrocyte activation (Becker et al., 2003; Lukasiuk et al., 2003;Cacheaux et al., 2009). Molecules associated with the inflammatoryresponse are also persistently active in tissue from patients withepilepsies of the temporal lobe (Aronica et al., 2007; Ravizza et al.,2008).It is useful to compare changes in gene expression associated with

neuronal death in epilepsy models, such as those at the ID site in thisstudy, with responses to neuronal damage or death in other brain areas.Gene profile responses are available for damage in the spinal cord(Carmel et al., 2001; Bareyre & Schwab, 2003; Di Giovanni et al.,2003; Herrmann et al., 2008) and retina (Vazquez-Chona et al., 2004;

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Piri et al., 2006; Liedtke et al., 2007), where neuronal death is notassociated with an epileptic syndrome. However, some initiatedbiological processes and transcripts seem to be identical. Furthermorein the cortex, hypoglycaemia, haemorrhage and ischaemia seem toinitiate early genomic responses similar to those induced by kainatetreatment (Tang et al., 2002). Responses to neuronal damage includean activation of transcription factors, followed by genes coding forproteins associated with inflammatory responses and glial cellactivation. Maintained changes include a down-regulation of genesassociated with neuronal and synaptic function, and an up-regulationof immune system genes and those coding for extracellular matrixproteins. Such changes are associated with processes of wound healingin different tissues, and include an inflammatory response followed byscar tissue formation and attempted regeneration (Bareyre & Schwab,2003; Velardo et al., 2004; Gurtner et al., 2008). It may be useful tocompare changes in gene expression induced by neuronal death inbrain regions that do or do not support epileptogenesis.

Conclusion

How then does an epileptic brain emerge after KA injection? Precisedata on the initiation site of seizures in KA-injected animals wouldhelp to answer this question. In vitro interictal-like activity (Support-ing Information Data S1) (Le Duigou et al., 2008) occurred sponta-neously and ictal-like events could be triggered from both thecontralateral and injected hippocampus. In slices of human epileptictemporal lobe, interictal discharges are initiated in the subiculum, azone of moderate neuronal loss (Cohen et al., 2002), rather than thesclerotic CA1 region. However, in vivo studies on KA-treated animalssuggest that seizures are initiated in the injected hippocampus (Meieret al., 2007). Our array data suggest that, if seizures emerge from sitesof significant neuronal death, the role of proteins associated withinflammatory processes and the extracellular matrix should beexamined. Genetic changes at the injection site are maintained afterrecurring seizures emerge. Alternatively, seizures may emerge fromsites distant from sclerotic regions. If so, our data suggest that theymay result from processes initiated at earlier times. These mightinclude growth processes leading to novel and aberrant patterns ofsynaptic connectivity, but the genomic traces of these processes maybe absent even while recurrent seizures are maintained.

Supporting Information

Additional supporting information may be found in the online version.of this article:Data S1. Results and methods for EEG records from KA-injectedanimals, and for anatomical work and slice electrophysiology on tissueprepared from them.Data S2. Excel file showing changes in expression for all altered genesfrom four regions of the hippocampus at three time points.Data S3. Word file showing all changed genes in subcategories of thegroups: Immune and Inflammatory response, cell death-associated,growth processes, intracellular signalling, nuclear signalling, meta-bolic processes, extracellular matrix, channels and transporters,synapse and transmitter.Date S4. Comparison of data from this study with data on genesenriched in different cell types From Cahoy et al., J. Neuroscience(2008) 28, 246–278.Please note: As a service to our authors and readers, this journalprovides supporting information supplied by the authors. Such

materials are peer-reviewed and may be re-organized for onlinedelivery, but are not copy-edited or typeset by Wiley-Blackwell.Technical support issues arising from supporting information (otherthan missing files) should be addressed to the authors.

Acknowledgements

We thank Viviane Bouilleret for help and advice and Fiona Francis forcomments on the manuscript. None of the authors has competing interests. Wegratefully acknowledge financial support from the European Community (NFG,LSH-503221 to S.G., E.C. and R.M.), as well as from the Ministerodell’Istruzione, dell’Universita e della Ricerca (to E.C. and S.G.) and fromINSERM, the FRM and EPICURE (LSH-037315 to R.M.).

Abbreviations

CA, Cornus Ammonis; CAGE, cap analysis of gene expression; CD,contralateral dorsal; CV, contralateral ventral; GFAP, glial fibrillary acidicprotein; ID, ipsilateral dorsal; IV, ipsilateral ventral; KA, kainic acid; PB,phosphate buffer; qPCR, real-time quantitative polymerase chain reaction;RefSeq, NCBI reference sequence.

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