Differential DNA Methylation Patterns Define Status Epilepticus and Epileptic Tolerance

Abstract

Prolonged seizures (status epilepticus) produce pathophysiological changes in the hippocampus that are associated with large-scale, wide-ranging changes in gene expression. Epileptic tolerance is an endogenous program of cell protection that can be activated in the brain by previous exposure to a non-harmful seizure episode before status epilepticus. A major transcriptional feature of tolerance is gene downregulation. Here, through methylation analysis of 34,143 discrete loci representing all annotated CpG islands and promoter regions in the mouse genome, we report the genome-wide DNA methylation changes in the hippocampus after status epilepticus and epileptic tolerance in adult mice. A total of 321 genes showed altered DNA methylation after status epilepticus alone or status epilepticus that followed seizure preconditioning, with >90% of the promoters of these genes undergoing hypomethylation. These profiles included genes not previously associated with epilepsy, such as the polycomb gene Phc2. Differential methylation events generally occurred throughout the genome without bias for a particular chromosomal region, with the exception of a small region of chromosome 4, which was significantly overrepresented with genes hypomethylated after status epilepticus. Surprisingly, only few genes displayed differential hypermethylation in epileptic tolerance. Nevertheless, gene ontology analysis emphasized the majority of differential methylation events between the groups occurred in genes associated with nuclear functions, such as DNA binding and transcriptional regulation. The present study reports select, genome-wide DNA methylation changes after status epilepticus and in epileptic tolerance, which may contribute to regulating the gene expression environment of the seizure-damaged hippocampus.

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Royal College of Surgeons in Ireland
e-publications@RCSI
Molecular and Cellular erapeutics Articles Department of Molecular and Cellular erapeutics
2-1-2012
Dierential DNA methylation paerns dene
status epilepticus and epileptic tolerance.
Suzanne F C Miller-Delaney
Royal College of Surgeons in Ireland
Sudipto Das
Royal College of Surgeons in Ireland
Takanori Sano
Royal College of Surgeons in Ireland
Eva M. Jimenez-Mateos
Royal College of Surgeons in Ireland
Kenneth Bryan
Royal College of Surgeons in Ireland
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Citation
Miller-Delaney SF, Das S, Sano T, Jimenez-Mateos EM, Bryan K , Buckley PG, Stallings RL, Henshall DC. Dierential DNA
methylation paerns dene status epilepticus and epileptic tolerance. J Neurosci. 2012;32(5):1577-88.

Authors
Suzanne F C Miller-Delaney, Sudipto Das, Takanori Sano, Eva M. Jimenez-Mateos, Kenneth Bryan, Patrick G.
Buckley, Raymond L. Stallings, and David C. Henshall
is article is available at e-publications@RCSI: hp://epubs.rcsi.ie/mctart/47

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Neurobiology of Disease
Differential DNA Methylation Patterns Define Status
Epilepticus and Epileptic Tolerance
Suzanne F. C. Miller-Delaney,
1
Sudipto Das,
2,4
Takanori Sano,
1
Eva M. Jimenez-Mateos,
1
Kenneth Bryan,
2,4
Patrick G. Buckley,
2,3,4
Raymond L. Stallings,
2,4
and David C. Henshall
1
Departments of
1
Physiology and Medical Physics and
2
Cancer Genetics and
3
Molecular and Cellular Therapeutics, Royal College of Surgeons in Ireland,
Dublin 2, Ireland, and
4
National Children’s Research Centre, Our Lady’s Children’s Hospital, Dublin 12, Ireland
Prolonged seizures (status epilepticus) produce pathophysiological changes in the hippocampus that are associated with large-scale,
wide-ranging changes in gene expression. Epileptic tolerance is an endogenous program of cell protection that can be activated in the
brain by previous exposure to a non-harmful seizure episode before status epilepticus. A major transcriptional feature of tolerance is gene
downregulation. Here, through methylation analysis of 34,143 discrete loci representing all annotated CpG islands and promoter regions
in the mouse genome, we report the genome-wide DNA methylation changes in the hippocampus after status epilepticus and epileptic
tolerance in adult mice. A total of 321 genes showed altered DNA methylation after status epilepticus alone or status epilepticus that
followed seizure preconditioning, with ⬎90% of the promoters of these genes undergoing hypomethylation. These profiles included
genes not previously associated with epilepsy, such as the polycomb gene Phc2. Differential methylation events generally occurred
throughout the genome without bias for a particular chromosomal region, with the exception of a small region of chromosome 4, which
was significantly overrepresented with genes hypomethylated after status epilepticus. Surprisingly, only few genes displayed differential
hypermethylation in epileptic tolerance. Nevertheless, gene ontology analysis emphasized the majority of differential methylation events
between the groups occurred in genes associated with nuclear functions, such as DNA binding and transcriptional regulation. The present
study reports select, genome-wide DNA methylation changes after status epilepticus and in epileptic tolerance, which may contribute to
regulating the gene expression environment of the seizure-damaged hippocampus.
Introduction
The brain possesses endogenous neuroprotective mechanisms
that require forewarning to bring protection optimally to bear.
When subjected to an insult that is subthreshold for damage,
such as brief ischemia or brief seizures, a coordinated response of
gene changes and signaling pathways are activated that render the
tissue powerfully refractory against a subsequent and otherwise
damaging insult (Gidday, 2006; Dirnagl et al., 2009; Jimenez-
Mateos and Henshall, 2009). Termed tolerance, this is an evolu-
tionarily conserved program of cell protection. In epilepsy
models, brief seizures triggered by chemoconvulsants or electri-
cal stimulation are the preconditioning stimuli, reducing neuro-
nal death caused by a subsequent episode of status epilepticus
(SE). For example, non-convulsive seizures elicited by low-dose
systemic kainic acid (KA) prevent hippocampal injury by intra-
amygdala KA-induced SE in C57BL/6 and SJL mice (Hatazaki et
al., 2007; Tanaka et al., 2010). In recent years, our understanding
of the molecular processes underlying tolerance has been assisted
by microarray profiling, which has revealed large-scale, genomic
reprogramming of the response to injury (Stenzel-Poore et al.,
2007; Johnson and Simon, 2009). In epileptic tolerance, 73% of
the 565 differentially expressed genes in the hippocampus were
downregulated (Jimenez-Mateos et al., 2008). This included
genes that encode ion channels, excitatory neurotransmitter re-
ceptors, and calcium signaling components, indicating that sup-
pression of excitability- and excitotoxicity- related pathways is
the main transcriptional phenotype of epileptic tolerance
(Jimenez-Mateos et al., 2008).
Epigenetic processes might play an important role in the reg-
ulation of gene expression in tolerance. DNA methylation, which
is the covalent attachment of methyl groups (CH
3
) to the cytosine
base present in CG dinucleotide-containing regulatory se-
quences, a process catalyzed by a group of enzymes known as
DNA methyl transferases (Dnmts), is of particular interest (Rob-
ertson, 2005; Feng and Fan, 2009). Differential DNA methylation
of gene promoter regions is responsible, in part, for the modula-
tion of gene expression profiles that promote cell identity and
function throughout life (Jaenisch and Bird, 2003). The molecu-
lar machinery for DNA methylation and demethylation is ex-
pressed and functional in adult brain (Endres et al., 2000; Feng et
al., 2010; Guo et al., 2011a). Although originally thought to be a
static process after cellular differentiation, DNA methylation can
be highly dynamic in the hippocampus in response to neural
Received Oct. 14, 2011; revised Nov. 21, 2011; accepted Nov. 30, 2011.
Author contributions: S.F.C.M.-D., R.L.S., and D.C.H. designed research; S.F.C.M.-D., S.D., T.S., E.J.-M., K.B., and
P.G.B. performed research; S.F.C.M.-D., S.D., E.J.-M., K.B., P.G.B., R.L.S., and D.C.H. analyzed data; S.F.C.M.-D. and
D.C.H. wrote the paper.
This work was supported by Science Foundation Ireland Grants 08/IN.1/B1875 (D.C.H.) and 07/IN.1/B1776
(R.L.S.), Brainwave, and Children’s Medical and Research Foundation. We thank James Reynolds for technical
support.
Correspondence should be addressed to Dr. David C. Henshall, Department of Physiology and Medical Physics,
Royal College of Surgeons in Ireland, Dublin 2, Ireland. E-mail: dhenshall@rcsi.ie.
DOI:10.1523/JNEUROSCI.5180-11.2012
Copyright © 2012 the authors 0270-6474/12/321577-12$15.00/0
The Journal of Neuroscience, February 1, 2012 •32(5):1577–1588 • 1577

activity (Levenson et al., 2006; Miller and
Sweatt, 2007; Guo et al., 2011b). Such epi-
genetic mechanisms are important for
certain plasticity and injury responses in
brain, and aberrant methylation profiles
are associated with neurodevelopmental,
neuropsychiatric, and neurodegenerative
disorders (Urdinguio et al., 2009; Iraola-
Guzman et al., 2011).
Presently, we performed the first
genome-wide DNA methylation analysis
of SE, contrasting the profile to that in
epileptic tolerance. Our analysis reveals
that changes in DNA methylation state
occurred for 288 genes after SE. Although
we hypothesized there would be increased
DNA methylation in tolerance, only 15
genes were differentially hypermethy-
lated in this group, although many of
these were novel and not previously im-
plicated in tolerance. The results indi-
cate a more limited role than expected
for hypermethylation in the mechanism
of epileptic tolerance.
Materials and Methods
Animal model. Animal experiments were per-
formed as described previously (Hatazaki et al.,
2007; Jimenez-Mateos et al., 2008) in accor-
dance with the European Communities Coun-
cil Directive (86/609/EEC) and were reviewed
and approved by the Research Ethics Commit-
tee of the Royal College of Surgeons in Ireland,
under license from the Department of Health,
Dublin, Ireland. Adult male mice (C57BL/6,
20 –25 g) were obtained from Harlan. Animals
were group housed in a climate-controlled vi-
varium on a 12 h light/dark cycle with food and
water provided ad libitum.
Figure 1Aillustrates the experimental para-
digms. Seizure preconditioning was induced
by a single intraperitoneal injection of KA (15
mg/kg in 0.2 ml volume) (Ascent Scientific).
Sham-preconditioned animals received the
same volume of saline (intraperitoneally).
To model epileptic tolerance, SE was induced
24 h after preconditioning by intra-amygdala mi-
croinjection of KA (1
␮
gin0.2
␮
l of PBS). A
group of sham-preconditioned mice also under-
went SE induced by intra-amygdala KA and
served as injury controls. Another group of sham-preconditioned mice re-
ceived intra-amygdala injection of vehicle and served as non-seizure controls
(Fig. 1 A). Lorazepam (6 mg/kg, i.p.) was administered to all animals 40 min
after intra-amygdala injections to minimize morbidity and mortality from SE.
For comparisons between control and preconditioning, animals were
killed at 4, 8, or 24 h. All animals given intra-amygdala injections (con-
trol, injury, and tolerance) were killed at 24 h.
Microdissection of CA3. The CA3 subfield of the ipsilateral and con-
tralateral hippocampus was microdissected on dry ice and flash frozen in
liquid nitrogen for temporary storage at ⫺80°C, as described previously
(Hatazaki et al., 2007).
Gene expression analysis. CA3 subfields were microdissected from hip-
pocampus and total RNA extracted using the miRNeasy kit (Qiagen) as
per protocol. Double-stranded cDNA was synthesized from DNase-
treated total RNA using SuperScript II reverse transcriptase (catalog
#18064-014; Invitrogen). PCR analysis was performed using cDNA
in triplicate on the 7900 HT Fast Realtime System (Applied Biosys-
tems) for the following genes: Atp2ci (ATPase, Ca
2⫹
-sequestering)
(Mm00723486_m1), Cpne6 (copine VI) (Mm00464849_m1), Dnmt1
(Mm00599763_m1),Dnmt3a(Mm00432881_m1),Dnmt3b(Mm01240113_
m1), Gtf2i (general transcription factor II I) (Mm00494826_m1), Hmga2
(high mobility group AT-hook 2) (Mm04183367_g1), Hspa1b (heat
shock protein 1B) (Mm03038954_s1), Map3k7ip2 (Map3k7 binding
protein 2) (Mm00663112_m1), Phc2 (Mm00502093_m1), Slc1a6 (solute
carrier family 1, member 6) (Mm00436593_m1), and Usp16 (ubiquitin-
specific peptidase 16) (Mm00470393_m1). Gapdh (glyceraldehyde-3-
phosphate dehydrogenase) (Mm99999915_g1) was used for normalization.
Minus reverse transcription and non-template controls were routinely used
to rule out genomic DNA and cross-well contamination, respectively. A
relative fold change in expression was performed using the comparative cycle
threshold method (2
⫺⌬⌬CT
).
Western blot analysis. Western blot analysis was performed as de-
scribed previously (Hatazaki et al., 2007). Hippocampal CA3 subfields
Figure 1. Organization of study groups and expression of DNA methylating and demethylating enzymes after seizure precon-
ditioning. A, Experimental groups. Top, For comparison of the effects of preconditioning, animals received intraperitoneal (i.p.)
saline (Con) or intraperitoneal KA [preconditioning (PC)]. Bottom, For methylation studies, non-seizure controls received intra-
peritonealvehicle on day 1 andintra-amygdala (i.a.)vehicle on day2. Injuryanimals (Inj)receive shampreconditioning on thefirst
day and undergo SE by intra-amygdala KA on day 2. Tolerance animals (Tol) receive preconditioning on day 1 and undergo SE on
day 2 by intra-amygdala KA. Samples from these groups are collected 24 h after intra-amygdala injections. B, Graphs show
real-time qPCR measurement of the Dnmts in the CA3 subfield 4, 8, and 24 h after PC. Dnmt1 levels were significantly increased
after seizure preconditioning (*p⬍0.05 compared with control; n⫽3 per group). C,D, CA3 subfields from control and precon-
ditioning at 24 h (n⫽3 per group) were analyzed by Western blot. Immunoblots show protein levels of Dnmt 1 (⬃180 kDa),
Dnmt3a (⬃95 kDa), Dnmt3b (⬃85 kDa), Tet1 (⬃100 kDa), and Gadd45
␤
(⬃20 kDa) (n⫽1 per lane).
␤
-Actin and
␣
-tubulin
(Tub) are included as a guide to protein loading. Protein levels were unchanged after preconditioning. Box to left of main panel in
Dshows the signal for Gadd45
␤
in a cerebellum sample.
1578 •J. Neurosci., February 1, 2012 •32(5):1577–1588 Miller-Delaney et al. •DNA Methylation Changes after Seizures

were homogenized in a lysis buffer, boiled in gel-loading buffer, sepa-
rated by SDS-PAGE, and transferred onto nitrocellulose membranes.
The following primary antibodies were used: Dnmt1 and
␤
-actin
(Sigma-Aldrich), Dnmt3a/b, Tet1 (also known as CXXC finger 6),
Gadd45
␤
(growth arrest and DNA damage-inducible protein 45
␤
), and
␣
-tubulin (Santa Cruz Biotechnology). Membranes were then incubated
with horseradish peroxidase-conjugated secondary antibodies (Jackson
ImmunoResearch), and bands were visualized using Supersignal West
Pico chemiluminescence (Pierce). Images were captured using a FujiFilm
LAS-300 (Fuji), and densitometry was performed using AlphaEaseFC4.0
gel-scanning integrated optical density software (Alpha Innotech).
Methylated DNA immunoprecipitation. DNA was isolated from hip-
pocampal CA3 subfields using the DNeasy Blood and Tissue kit (Qiagen)
as per the protocol. The CA3 subfields from three mice were pooled for
use on a single array. The protocol used for methylation analysis was as
described previously (Murphy et al., 2009; Das et al., 2010; Buckley et al.,
2011). Briefly, 4
␮
g of sonicated DNA was incubated overnight with 10
␮
g of anti-5⬘-methylcytidine antibody (BIMECY-1000; Eurogentec) and
immunoprecipitated using Dynabeads (112-02D; Bio Sciences) and a
magnetic particle concentrator (DynaMagTM, catalog #123.21D; Bio
Sciences). Methylated DNA immunoprecipitation (MeDIP) and refer-
ence control DNA were differentially labeled and hybridized (accord-
ing to NimbleGen DNA methylation analysis protocol version 6.0) to
CpG Island promoter plus arrays from Roche NimbleGen (catalog
#5543649001; Mouse Meth 385K Prom Plus CpG) covering 34,143 loci
representing all annotated CpG islands and promoter regions in the
mouse genome. Replicate arrays were performed per condition. Scan-
ning of arrays was performed on an Axon 4000B scanner, and data were
processed using GenePix Pro 6.0. Image analysis and peak detection were
performed using the methylation application in Nimblescan version 2.4.
Methylated peaks were identified using the following parameters: sliding
window of 750 bp, pvalue minimum cutoff (⫺log10) of 2.0, and a min-
imum of two probes per peak. Resulting data files were visualized using
SignalMap 1.9. Methylation data will be deposited at www.ebi.ac.uk/
arrayexpress (accession number: E-MEXP-3503). Only hypermethylated
peaks that were detected in replicate experiments were used for addi-
tional analysis.
Real-time qPCR validation of MeDIP results. The MeDIP experiments
were validated using a relative quantification approach using SYBR
Green master mix (Applied Biosystems, part #309155). Previously pub-
lished primers for the Utf1 (Undifferentiated embryonic cell transcrip-
tion factor 1) unmethylated region (Hiura et al., 2010) were obtained
from Sigma-Genosys alongside purpose-designed primers for the H19
(H19 fetal liver mRNA) imprinted control region (forward primer, 5⬘-
CGTTCCCTTGTTGCACATAACA-3⬘; reverse primer, 5⬘-CCCCAAAA
CCAGCCAGTGT-3⬘). The relative level of enrichment (RQ) was
calculated for each of the model conditions using the comparative Ct
method. A negative control of immunoprecipitated DNA using normal
mouse IgG (catalog #sc-2025; Santa Cruz Biotechnology) was also in-
cluded. All real-time qPCR analysis was performed, in duplicate, on the
7900HT Applied Biosystems real-time PCR.
Bioinformatics. Compilation, preprocessing, and analysis of genomic
methylation data were performed using in-house developed Java (ver-
sion 1.6) software. MeDIP probe significances in terms of pvalues were
generated using the Kolmogorov–Smirnov test as implemented by Nim-
bleScan SignalMap software version 1.9. These values were then trans-
formed (⫺log10) to give peak scores. A peak was called when two or
more consecutive probes achieved a score of at least 2. Methylation pro-
files were then generated from the peak score profiles by assessing the
presence or absence of a peak over all promoter regions [⫺2000 and
⫹500 bp around the transcriptional start site (TSS)] and CpG islands.
Cluster analysis was then performed using Pearson’s correlation as a
similarity metric and using complete linkage as cluster distance method.
Heat-map visualization was performed using the heatmap.2 package.
Analysis was implemented in the R statistical computing language.
Gene ontology (GO) and functional analyses were assigned by manual
interrogation of Entrez Gene (http://www.ncbi.nlm.nih.gov/sites/entrez?
db⫽gene). Ideogram generation was performed using Idiographica
Web-based software (Kin and Ono, 2007). Positional gene enrichment
analysis was performed using Web-based software (De Preter et al.,
2008).
Bisulfite sequencing. DNA was isolated from CA3 subfields of injury
and tolerance mice using the DNeasy Blood and Tissue kit (Qiagen) as
per the instructions of the manufacturer. A total of 500 ng of DNA from
individual CA3 subfields was bisulfite converted using the EZ DNA-
methylation Gold kit (catalog #D5005 and #D5006; Zymo), and PCR was
performed on 10 ng of the bisulfite-treated DNA as outlined previously
(Das et al., 2010). PCR primers were designed using methyl primer ex-
press (www.appliedbiosystems.com/methylprimerexpress) and were as
follows: Atp2c1, forward primer, 5⬘-GTATTTGTAAGAGAAATTAGGA
GAAG-3⬘and reverse primer, 5⬘-TATCTACTCCTACCCCTATTTCC-
3⬘;Cpne6, forward primer, 5⬘-AAGTATTGTGAGAGTGTGTTTTTT-3⬘
and reverse primer, 5⬘-TCACAAACTCACACATATCTTAAC-3⬘;Gtf2i,
forward primer, 5⬘-GTTAATTAGGAGCGAAGGAGTAGG-3⬘and re-
verse primer, 5⬘-CCCCAAAATCCACTCTACTTAAA-3⬘;Hmga2, for-
ward primer, 5⬘-TTTTTTAGTGTGTAGTGGGGTT-3⬘and reverse
primer, 5⬘-TCAAATCCTCTAACTTTCACAAA-3⬘; and Phc2, forward
primer, 5⬘-GAGGGGTGTAAGGTGATTTTTA-3⬘and reverse primer,
5⬘-CAACTTTCCAAACAAACTACCA-3⬘. PCR products were purified
using the QIAquick PCR purification kit (catalog #28104; Qiagen) as per
the instructions of the manufacturer and sequenced in the forward di-
rection at Eurofins MWG Operon.
Data analysis. Data are presented as mean ⫾SEM. Gene expression
analysis comparisons were made using ANOVA, followed by Newman–
Keuls post hoc testing with significance accepted at p⬍0.05.
Results
DNA methyltransferase expression in the CA3 subfield of
the hippocampus
We first sought to establish the presence of DNA methyltrans-
ferases in the CA3 subfield, which is the site of major neuronal
death after intra-amygdala KA-induced SE and which is pro-
tected in animals given seizure preconditioning (Hatazaki et al.,
2007; Jimenez-Mateos et al., 2008). We were also interested in
whether seizure preconditioning caused changes to levels of these
genes that might influence how and whether methylation differ-
ences occurred when SE is applied. Dnmt1 is thought to contrib-
ute to maintenance of DNA methylation, whereas Dnmt3a and
Dnmt3b are responsible for de novo DNA methylation (Jaenisch
and Bird, 2003).
As expected, expression of Dnmt1,Dnmt3a, and Dnmt3b was
detected in control animals (Fig. 1B). Seizure preconditioning
increased Dnmt1 transcript levels in the CA3 subfield at 24 h (Fig.
1B). No changes were noted for Dnmt3a and Dnmt3b expression
after seizure preconditioning (Fig. 1B). To extend this analysis,
we examined protein levels of each Dnmt after seizure precondi-
tioning (Fig. 1C). Dnmt1 and Dnmt3b protein was present in
control mouse CA3, but Dnmt3a was minimally expressed (Fig.
1C). There were no changes in protein levels for any of the Dnmts
in CA3 subfields 24 h after seizure preconditioning (Fig. 1Cand
data not shown).
Because DNA demethylation could also contribute to the
transcriptional phenotype in epileptic tolerance, we also analyzed
samples 24 h after preconditioning for protein levels of Tet1 and
Gadd45
␤
, enzymes implicated in DNA demethylation in brain
(Ma et al., 2009; Guo et al., 2011a,b). Tet1 was readily detected in
the CA3 subfield of control mice (Fig. 1D), whereas Gadd45
␤
was essentially undetectable in control CA3 samples but was pres-
ent in cerebellum (Fig. 1D). Protein levels of Tet1 and Gadd45
␤
were not different in samples 24 h after seizure preconditioning
(Fig. 1Dand data not shown). Thus, the DNA methylation/de-
methylation apparatus is present in the CA3 subfield of mice but
is not noticeably changed by seizure preconditioning.
Miller-Delaney et al. •DNA Methylation Changes after Seizures J. Neurosci., February 1, 2012 •32(5):1577–1588 • 1579

DNA methylation analysis
We moved next to establish the methylation profiles of the CA3
subfield from non-seizure controls, animals subjected to SE alone
(injury), and mice given seizure preconditioning before SE (epi-
leptic tolerance) using MeDIP. Enrichment of immunoprecipi-
tated DNA was confirmed by a qPCR-based assay for the
imprinted H19 locus compared with the unmethylated Utf1 lo-
cus. The fold enrichment for H19 compared with Utf1 using the
comparative Ct method ranged from 6- to 27-fold for each of the
samples tested (data not shown).
A pairwise comparison of MeDIP replicates for control, in-
jury, and tolerance resulted in Pearson’s correlation coefficients
of 0.92, 0.72, and 0.87, respectively, indicating high reproducibil-
ity (Fig. 2A). Methylation peaks that were not detected in both
independent arrays were removed from the dataset. The number
of hypermethylation peaks conserved between replicates of each
condition is shown in Figure 2B. The average number of hyper-
methylated loci (including gene promoters and CpG islands) de-
tected was 2538, which corresponds to 7.4% of the fraction of the
genome interrogated (considering 34,143 regions were analyzed
on the microarray). Common methylation peaks identified using
the NimbleScan 2.4 software in each experiment were mapped to
genes using a window of ⫺2kbto⫹500 bp relative to the tran-
scriptional start site. This resulted in the identification of 2822,
1590, and 1701 hypermethylated genes in control, injury, and
tolerance, respectively (Fig. 2 B). Genes whose methylation status
remained unchanged between control and injury or tolerance
samples were removed. The remaining dataset contained genes
whose promoters were differentially methylated in injury and/or
tolerance compared with control (Fig. 2C).
Visualization of the raw data is presented in Figure 3. Hierar-
chical clustering analysis revealed methylation profiles from each
group that validated the paired biological replicates (Fig. 3).
Methylation patterns in injury and tolerance animals were more
similar to each other than to controls, but each independent sam-
ple within a treatment group showed most similarity to its own
replicate. Most shared regions of hypomethylation were between
injury and tolerance. We also observed a smaller subset of
genomic locations that were differentially methylated in injury
and tolerance (Fig. 3). Thus, analysis of differential methylation
Figure 2. Validation and analysis of methylation profiles. A, Pairwise comparison of MeDIP replicates for control, injury, and tolerance resulted in Pearson’s correlation coefficients of 0.92, 0.72,
and 0.87, respectively. B, Numbers of common hypermethylation peaks detected in each condition and equivalent gene numbers. C, Venn diagrams illustrating the number of genes whose
promoters are shared or differentially methylated in injury (inj) and/or tolerance (tol) when compared with controls. Eighteen genes are differentially hypomethylated in tolerance alone, whereas
47 genes are differentially hypomethylated in injury alone. Fifteen genes are differentially hypermethylated in tolerance alone, whereas seven genes are differentially hypermethylated in injury
alone.
1580 •J. Neurosci., February 1, 2012 •32(5):1577–1588 Miller-Delaney et al. •DNA Methylation Changes after Seizures

in injury and tolerance compared with
control highlights unique methylation
profiles in each condition.
Promoter methylation profiles after SE
and epileptic tolerance
The more prominent methylation response
in injury and tolerance compared with con-
trol was differential hypomethylation. Of
293 differentially hypomethylated genes, the
majority of hypomethylation events were
found to be common occurrences in both
injury and tolerance when compared with
control (228 genes; 77.8%) (Fig. 2Cand data
not shown). Among these were several
members of the adam (a disintegrin and
metallopeptidase domain), slc (solute car-
rier), olfr (olfactory receptor), and USP fam-
ilies of genes. A relatively small subgroup of
18 genes (6.1%) was found to be differen-
tially hypomethylated in tolerance, whereas
47 (16%) were differentially hypomethy-
lated in injury (Fig. 2C).
Although modest in terms of gene
number, the majority of differential hy-
permethylation events were found to oc-
cur in tolerance (15 genes of a total of 28;
53.6%). The promoters of seven genes
(25%) were differentially hypermethy-
lated in injury alone (Fig. 2C), whereas
those of six genes [21.4%; Abtb1 (Ankyrin
repeat & BTB (POZ) domain containing
1), Acp5 (Acid phosphatase 5, tartrate re-
sistant), Bzrap1 (Benzodiazepine receptor
associated protein 1), Hspa12a (Heat
Shock Protein 12a), Prima1 (Proline rich
membrane anchor 1), and Zfa (Zinc fin-
ger protein, autosomal)] were found to be
commonly hypermethylated in both in-
jury and tolerance when compared with
control. Genes whose promoters were
found to be differentially methylated in
tolerance alone are listed in Table 1. Genes
whose promoters were found to be differ-
entially methylated in injury alone are
listed in Table 2. Notably, few genes pres-
ent in either dataset have previously been
linked with epilepsy.
An interrogation of the previously re-
ported genes differentially downregulated
in epileptic tolerance (Jimenez-Mateos
et al., 2008) found two of the differen-
tially hypermethylated genes in tolerance:
Figure 3. Hierarchical clustering of methylation profiles. Dendrogram showing the hierarchical clustering of raw data methyl-
ationprofiles between control (Con), injury(Inj), and tolerance(Tol) groups.This provides technicalvalidation inthe form ofpaired
biological replicates. Hypomethylation locations are signified by dark red areas, most of which are shared by injury and tolerance
4
groups. Also apparent is a smaller subset of genomic locations
that are differentially methylated in injury and tolerance
groups and some regions in which there is a clear difference in
tolerance from both injury and control. Count signifies the
number of CpGs. Value represents the average of the probes
for a given region (from ⫺2kbto⫹500 bp around the TSS).
This value was calculated for each gene that is represented on
the histogram.
Miller-Delaney et al. •DNA Methylation Changes after Seizures J. Neurosci., February 1, 2012 •32(5):1577–1588 • 1581

Cpne6 and Slc1a6. None of the differentially hypomethylated
genes were present among the differentially upregulated genes re-
ported previously in epileptic tolerance (Jimenez-Mateos et al.,
2008).
Ontology analysis of genes differentially methylated in injury
and tolerance
Bioinformatic analysis of cellular location and molecular func-
tion was performed for genes whose promoters were found to be
differentially methylated in injury and tolerance. Several striking
differences are evident when comparing injury with tolerance
(Fig. 4). First, the majority of nucleus-associated differentially
methylated genes in injury were hypomethylated, whereas in tol-
erance the majority of differentially methylated nuclear genes
were hypermethylated (Fig. 4). This result corresponds with a
difference in the functional profiles of genes differentially methyl-
ated in injury and tolerance. The majority of differentially methyl-
ated genes that encode DNA binding proteins in injury are found
to be hypomethylated (hypomethylated, 7; hypermethylated, 2),
whereas in tolerance, all five differentially methylated genes encod-
ing DNA binding proteins are hypermethylated (Fig. 4). Of the dif-
ferentially methylated genes encoding DNA binding proteins,
several are predicted transcriptional regulators. This is of particular
relevance when considering the establishment of gene suppression as
the major phenotype of epileptic tolerance (Jimenez-Mateos et al.,
Table 1. Genes differentially methylated in epileptic tolerance
Gene ID
Accession
number Gene title
Hypermethylated
Cpne6 NM_009947 Copine VI
Gtf2i NM_010365 General transcription factor II I
Hint1 NM_008248 Histidine triad nucleotide binding protein 1
Hmga2 NM_178057 High mobility group AT-hook 2
Mif NM_010798 Macrophage migration inhibitory factor
Pold1 NM_011131 Polymerase, delta 1, catalytic subunit
Rab40c NM_139154 Rab40c, member RAS oncogene family
Rtl1 NM_184109 Retrotransposon-like 1
Sae1 NM_019748 SUMO1 activating enzyme subunit 1
Scrt1 NM_130893 Scratch homolog 1, zinc finger protein
Sfmbt2 NM_177386 Scm-like with four mbt domains 2
Slc1a6 NM_009200 Solute carrier family 1, member 6
Zap70 NM_009539 zeta-Chain (TCR) associated protein kinase
4632419K20Rik NM_199009 Family with sequence similarity 160, member A2
5031439G07Rik NM_001033273 RIKEN cDNA 5031439G07 gene
Hypomethylated
Akp5 NM_007433 Alkaline phosphatase, placental-like 2
Casp4 NM_007609 Caspase 4, apoptosis-related cysteine peptidase
Cmtm5 NM_026066 CKLF-like MARVEL transmembrane domain
containing 5
C4bp NM_007576 Complement component 4 binding protein
Fabp6 NM_008375 Fatty acid binding protein 6, ileal (gastrotropin)
Kncn NM_001039124 Kinocilin
Map3k7ip2 NM_138667 MAP3K7 binding protein 2
Mrpl53 NM_026744 Mitochondrial ribosomal protein L53
Muc19 NM_207243 Mucin 19
Myom1 NM_010867 Myomesin 1
Olfr1509 NM_020514 Olfactory receptor 1509
Olfr653 NM_147074 Olfactory receptor 653
Prg3 NM_016914 Proteoglycan 3
Slfn4 NM_011410 Schlafen 4
Smgc NM_198927 Submandibular gland protein C
Usp16 NM_024258 Ubiquitin-specific peptidase 16
1700006J14Rik NM_177313 RIKEN cDNA 1700006J14 gene
1810048P08Rik NM_133717 RAB43, member RAS oncogene family
Table 2. Genes differentially methylated in injury
Gene ID
Accession
number Gene title
Hypermethylated
Apoa2 NM_013474 Apolipoprotein A-II
Atp2c1 NM_175025 ATPase, Ca
2⫹
-sequestering
Clgn NM_009904 Calmegin
Mta1 NM_054081 Metastasis associated 1
Qrfp NM_183424 Pyroglutamylated RFamide peptide
Tcf7l2 NM_009333 Transcription factor 7-like 2
E130203B14Rik NM_178791 RIKEN cDNA E130203B14 gene
Hypomethylated
Adam4 NM_009620 A disintegrin and metallopeptidase domain 4
Aipl1 NM_053245 Aryl hydrocarbon receptor-interacting protein-like 1
Bnc1 NM_007562 Basonuclin 1
Cbfa2t3h NM_009824 Core-binding factor, runt domain, alpha subunit 2,
translocated to, 3 (human)
Cpxm2 NM_018867 Carboxypeptidase X 2 (M14 family)
Cyp2c44 NM_001001446 Cytochrome P450, family 2, subfamily c, polypeptide
44
Dzip1 NM_025943 DAZ interacting protein 1
Fgf1 NM_010197 Fibroblast growth factor 1
Fgl1 NM_145594 Fibrinogen-like protein 1
Gcnt7 NM_001039560 Glucosaminyl (N-acetyl) transferase family member 7
Hspa1a NM_010479 Heat shock protein 1a
Hspa1b NM_010478 Heat shock protein 1b
Ifitm6 NM_001033632 Interferon-induced transmembrane protein 6
Irf4 NM_013674 Interferon regulatory factor 4
Krtap13 NM_010671 Keratin-associated protein 13
Krtap6-2 NM_010673 Keratin-associated protein 6-2
Lamc1 NM_010683 Laminin, gamma 1
Lgals3bp NM_011150 Lectin, galactoside-binding, soluble, 3 binding protein
Lrfn1 NM_030562 Leucine rich repeat and fibronectin type III domain
containing 1
Mab21l1 NM_010750 Mab-21-like 1
Map3k7ip1 NM_025609 MAP3K7 binding protein 1
Mib2 NM_145124 Mindbomb homolog 2
Ndufb8 NM_026061 NADH dehydrogenase (ubiquinone) 1 beta
subcomplex 8
Olfr462 NM_146411 Olfactory receptor 462
Pdzd3 NM_133226 PDZ domain containing 3
Pfpl NM_019540 Pore forming protein-like
Phc2 NM_018774 Polyhomeotic-like 2
Pik3ca NM_008839 Phosphatidylinositol 3-kinase, catalytic, alpha
polypeptide
Rai2 NM_198409 Retinoic acid induced 2
Rhbdd1 NM_029777 Rhomboid domain containing 1
Rnf43 NM_172448 Ring finger protein 43
Sec16A NM_153125 SEC16 homolog A
Serhl NM_023475 Serine hydrolase-like
Slc38a10 NM_024249 Solute carrier family 38, member 10
Sox5 NM_011444 SRY-box containing gene 5
Suz12 NM_199196 Suppressor of zeste 12 homolog
Tcfap2e NM_198960 Transcription factor AP-2, epsilon
Tlr12 NM_205823 Toll-like receptor 12
Usp18 NM_011909 Ubiquitin-specific peptidase 18
Zfp14 NM_011748 Zinc finger protein 14
Gm1604 NM_001033442 Predicted gene 1604
Gm4894 NM_177701 Predicted gene 4894
AU021092 NM_001033220 Expressed sequence AU021092
1700001P01Rik NM_028156 RIKEN cDNA 1700001P01 gene
4632404H12Rik NM_028726 RIKEN cDNA 4632404H12 gene
4921510H08Rik NM_025724 RIKEN cDNA 4921510H08 gene
4932430I15Rik NM_001033815 RIKEN cDNA 4932430I15 gene
1582 •J. Neurosci., February 1, 2012 •32(5):1577–1588 Miller-Delaney et al. •DNA Methylation Changes after Seizures

2008). Nuclear genes whose promoters were differentially methyl-
ated in injury include the transcription regulators Mta1 (metastasis
associated 1; differentially hypermethylated) and Bnc1 (basonuclin
1), Cbfa2t3h (core-binding factor runt domain
␣
subunit 2 translo-
cated to 3) (human), Irf4 (interferon regulatory factor 4), Sox5 (SRY-
box containing gene 5), Tcfap2e (transcription factor AP-2, epsilon),
and Zfp14 (zinc finger protein 14) (all differentially hypomethy-
lated). In epileptic tolerance, the differentially hypermethylated nu-
clear genes include four transcription regulators: Gtf2i,Hmga2,Scrt1
(Scratch homolog 1), and Sfmbt2 (Scm-like with four mbt domains
2), as well as the polymerase subunit Pold1 (polymerase delta 1).
Differential methylation of promoters after SE in injury and
tolerance occurs throughout the genome
Clustering of hypermethylation sites within the genome has been
demonstrated in several cancers (Frigola et al., 2006; Novak et al.,
2008; Dallosso et al., 2009; Wu et al., 2010; Buckley et al., 2011).
Furthermore, recent reports have shown that nuclear positioning
of many genomic regions changes during physiological processes
and in disease (Meaburn and Misteli, 2007, 2008) and, during
differential activity, in some cases before the start of expression
(Ragoczy et al., 2003, 2006).
To visualize the chromosomal location of gene promoters that
were differentially methylated in injury or epileptic tolerance and
to investigate whether any chromosomes/chromosomal regions
were enriched for methylation events, we mapped differentially
methylated gene locations (Kin and Ono, 2007) (Fig. 5). Posi-
tional gene enrichment analysis (De Pre-
ter et al., 2008) was performed on each of
the six differentially methylated gene sets
(as defined in Fig. 2C). A single region
on chromosome 4 (chr 4: 128292690 –
128430125) was found to be overrepre-
sented when positional gene enrichment
analysis was performed on the 47 genes
differentially hypomethylated in injury
alone (minPi; p⬍0.002). Only two genes
are located in this region, Tlr12 (Toll-like
receptor 12) and the polycomb group
member Phc2, and both were found to be
differentially hypomethylated in injury.
No other chromosomal regions were
found to be overrepresented in the re-
maining gene sets. In general, genes whose
promoter regions were differentially
methylated in epileptic tolerance and in-
jury were spread throughout the genome,
and any apparent clustering of differen-
tially methylated genes occurred in gene-
dense chromosomal regions that were not
overrepresented (Fig. 5).
Focal-onset SE results in bilateral
hippocampal methylation changes
Differential methylation of gene promot-
ers in injury and tolerance was confirmed
by bisulfite sequencing. Seizure precondi-
tioning would be expected to affect both
hippocampi, and, because intra-amygdala
KA-induced SE also has bilateral effects
on the hippocampus (Araki et al., 2002),
ipsilateral and contralateral CA3 subfields
of injury and tolerant mice were separately
analyzed using bisulfite sequencing analysis. Genes analyzed in-
cluded Gtf2i,Cpne6, and Hmga2 (hypermethylated in tolerance),
Atp2c1 (hypermethylated in injury), and Phc2 (hypomethylated in
injury).
Differential methylation of individual CpG sites was found to
be robust and reproducible (Fig. 6, Table 3). The methylation
state of individual CpG sites was found to be strongly conserved
across biological replicates in a manner consistent with array
profiling. In many cases, long stretches of CpG sites were
analyzed by bisulfite sequencing and hypermethylation was
confirmed. For example, for Gtf2i,⬃30 CpG sites were hyper-
methylated across all biological replicates in tolerance compared
with conserved hypomethylation of all these sites in injury (Fig.
6A). Similarly for Atp2ci, 18 CpG sites were hypermethylated
across all biological replicates in injury compared with conserved
hypomethylation of these sites in tolerance (Fig. 6 B). Methylation of
Cpne6 and Phc2 were also validated as showing the expected meth-
ylation differences between injury and tolerance (Fig. 6D,E, Table
3). For Hmga2, scattered CpG sites were found to be methylated in
injury as well as tolerance (Fig. 6C). Notably, contralateral CA3 sub-
fields were found to exhibit similar patterns of methylation as the
ipsilateral CA3 for all investigated genes (Fig. 6).
Hippocampal expression of genes exhibiting differential
methylation in injury and tolerance
To explore whether promoter methylation had the expected ef-
fect on transcription, gene expression analysis was performed on
Figure 4. Molecular function and cellular location of differentially methylated genes in injury and tolerance. Bar graphs show-
ing GO analysis for cellular location (top) and molecular function (bottom) of the differentially methylated genes in injury and
tolerance. Note the hypermethylation and hypomethylation differences for genes associated with the nucleus between injury and
tolerance.
Miller-Delaney et al. •DNA Methylation Changes after Seizures J. Neurosci., February 1, 2012 •32(5):1577–1588 • 1583

a sample of nine genes that were found to
exhibit differential promoter methyl-
ation in injury or tolerance. These in-
cluded Atp2c1 (hypermethylated in
injury), Hspa1b and Phc2 (both hypom-
ethylated in injury), Cpne6,Gtf2i,Hmga2,
and Slc1a6 (all hypermethylated in toler-
ance), and Map3k7ip2 and Usp16 (both hy-
pomethylated in tolerance).
Analysis of the expression of various
genes for which differential methylation
had been demonstrated indicated com-
plex relationships between methylation
profiles and expression trends. For Gtf2i,a
hypermethylated gene in tolerance, and
Atp2c1, a hypermethylated gene in injury,
expression was not different between in-
jury and tolerance groups (Fig. 7 A,B). For
Hmga2, another hypermethylated gene in
tolerance, the expression level was actually
significantly increased in tolerance com-
pared with injury. Bisulfite sequencing had
shown hypermethylation of Cpne6 in toler-
ance (Fig. 6 D), and real-time qPCR analysis
confirmed on average a 2.4-fold decrease in
Cpne6 transcript levels in tolerance com-
pared with controls (Fig. 6D). However,
Cpne6 levels were not lower in tolerance
than injury (Fig. 7D).
Expression trends for the polycomb
group member Phc2 followed the pattern
predicted by differential hypomethylation
in injury (Fig. 6E). Expression of the Phc2
transcript was significantly increased in
injury compared with tolerance and con-
trol (Fig. 7E). No significant difference in
Phc2 expression levels was evident be-
tween tolerance and control samples. In a
second example, methylation array data
identified Hspa1b (also known as Hsp70)
as differentially hypomethylated in injury.
Real-time qPCR analysis of Hspa1b ex-
pression confirmed an 11.27-fold increase
in expression in injury compared with
control (Fig. 7F). Expression was also in-
creased, however, in tolerance, and no sig-
nificant difference in Hspa1b expression
levels was found between tolerance and injury (Fig. 7F). For the
remaining interrogated genes, expression trends did not correlate
with methylation status being the sole determinant of transcrip-
tional activity. Thus, for Map3k7ip2,Slc1a6, and Usp16, gene
expression did not differ significantly between control, injury, or
tolerance samples (data not shown).
Discussion
Here we used genome-wide DNA methylation analysis to profile
changes brought about by SE and to test the hypothesis that
changes to DNA methylation may contribute to transcriptional
downregulation, which is a feature of epileptic tolerance. We
found distinct methylation changes in the CA3 subfield of the
hippocampus after SE and show multiple DNA methylation dif-
ferences in epileptic tolerance. Changes in methylation profiles
were found to be robust, bilateral, and highly conserved between
biological replicates. Only few genes, however, showed differen-
tial hypermethylation in tolerance. This study contributes to our
understanding of mechanisms regulating gene expression after
SE and the alterations produced when the brain has been exposed
previously to seizure activity.
DNA methylation is an important epigenetic mechanism con-
trolling gene expression, and the present study is the first
genome-wide DNA methylation analysis of SE. Only a few hun-
dred genes showed differential methylation after SE alone. This
supports current ideas on the static nature of the majority of
DNA methylation, including in neurological disease (Mill et al.,
2008; Morahan et al., 2009; Wu and Zhang, 2010; Guo et al.,
2011b). Altogether, 321 genes were differentially methylated in
the CA3 subfield of injury and tolerance mice, in contrast to
⬎2200 genes for which expression at the mRNA level is altered by
twofold or greater in these models (Jimenez-Mateos et al., 2008).
Figure 5. Chromosomal localization of genes differentially methylated in tolerance and injury. Visualization of the location on
mouse chromosomes in which sites of differential methylation in injury and tolerance occurred. Hypomethylated genes are
identifiedby a blue circle and hypermethylatedgenes by ared triangle.Positional gene enrichmentanalysis ofthe dataset ofgenes
hypomethylatedininjury showed that a region of chromosome 4 was overrepresented. Thisregion included the neighboring genes
Tlr12 and Phc2, the location of which are identified by a blue circle with a yellow center. Heat map shows gene density for
chromosomes.
1584 •J. Neurosci., February 1, 2012 •32(5):1577–1588 Miller-Delaney et al. •DNA Methylation Changes after Seizures

The prominent methylation change caused by SE in both injury
and tolerance mice was hypomethylation/demethylation of gene
promoters. Demethylation of CpGs is also evident after electro-
convulsive seizures (Guo et al., 2011b). Our data therefore em-
phasizes a dominance of expression-activating methylation
changes after SE over gene silencing (Roopra et al., 2001; Urdin-
guio et al., 2009). Active demethylation of genes has emerged as
an important epigenetic mechanism involved in the regulation of
embryonic and CNS development, although the mechanisms of
demethylation are not fully resolved (Weaver et al., 2004; Feng
and Fan, 2009; Wu and Zhang, 2010). We did not see changes to
protein levels of known demethylating enzymes (nor the DNA
methylating enzymes Dnmt1, Dnmt3a, and Dnmt3b) after pre-
conditioning. Nevertheless, the majority of differential hyper-
methylation events were found to occur in tolerance, not injury,
although the number of genes in this dataset was relatively low
considering the extent of gene suppression in epileptic tolerance
(Jimenez-Mateos et al., 2008). Two of the differentially hyperm-
ethylated genes in tolerance (Cpne6 and Slc1a6) were previously
Figure 6. Verification of differentially methylated genes in injury and tolerance. A–E, Bisulfite sequencing of ipsilateral (Ipsil) and contralateral (Contra) CA3 subfields confirming differentially
hypermethylated and hypomethylated genes in injury (Inj) and tolerance (Tol) for Gtf2i (A), Atp2c1 (B), Hmga2 (C), Cpne6 (D), and Phc2 (E). Filled circles represent methylated CpG sites, and open
circles represent unmethylated CpG sites. Missing circles represent CpG sites for which methylation status could not be determined. Distance to the TSS from the first CpG site analyzed is indicated.
Table 3. Bisulfite validation of methylation status of genes in injury and tolerance
Gene ID Size of PCR product
a
Number of CpG sites Definitive methylation status assigned
Atp2c1 240 18 15 of 18
Cpne6 115 4 4 of 4
Gtf2i 307 34 28 of 34
Hmga2 381 21 20 of 21
Phc2 354 5 5 of 5
a
Product size in basepairs.
Miller-Delaney et al. •DNA Methylation Changes after Seizures J. Neurosci., February 1, 2012 •32(5):1577–1588 • 1585

identified as differentially downregulated at the mRNA level in tol-
erance (Jimenez-Mateos et al., 2008). None of the differentially hy-
pomethylated genes in tolerance had been found previously among
differentially upregulated genes in tolerance (Jimenez-Mateos et al.,
2008). The limited association between altered methylation state and
gene expression in tolerance supports, therefore, mechanisms in ad-
dition to changed methylation as determinants of differential gene
expression. Nevertheless, potential significance of the methylation
profile in epileptic tolerance was emphasized by GO analysis, which
highlighted differences in the cellular locations and molecular func-
tion of differentially methylated genes in injury and tolerance. For
example, the majority of nucleus-associated genes in tolerance were
hypermethylated, in contrast to the demethylation trends evident in
injury, implying a role for these changes in transcription or other
nuclear activities. Indeed, analysis of molecular function illustrated
that the tolerance dataset included genes involved in DNA binding
and transcriptional regulation, including Gtf2i,Hmga2, and Pold1,
which may play an active role in the gene suppression evident in
epileptic tolerance.
Studies in cancer have found clustering of hypermethylation
sites within the genome and, in the case of neuroblastic tumors,
toward the telomeric ends of chromosomes (Buckley et al., 2011).
Our study shows that differential methylation events in injury
and tolerance generally occur throughout the genome, with no
enrichment for a particular chromosomal region, with a notable
exception. Positional gene enrichment analyses indicated that a
small region of chromosome 4, which encompassed Phc2 and
Tlr12, was significantly overrepresented in genes demethylated in
injury. Toll-like receptors have been implicated previously in the
neuroprotection evident in ischemic tolerance (Stevens et al.,
2008; Marsh et al., 2009; Vartanian and Stenzel-Poore, 2010).
Furthermore, Tlr4 expression is increased in human and mouse
epileptic tissue, and TLR4-defective mice are resistant to KA-
induced seizures (Maroso et al., 2010). Differential demethyl-
ation and expression of Phc2 in injury may also be important.
Several members of the polycomb family have been shown re-
cently to be differentially upregulated and essential for the estab-
lishment of ischemic tolerance (Stapels et al., 2010). These
included the polycomb repressive complex 1 (PRC1) member
BMI1, which protects against chemical stress-induced cell death
(Lee et al., 2008) and with which Phc2 has been shown to interact
(Satijn et al., 1997). Initially, polycomb proteins were thought to
regulate the transcription of only a few genes, including the Hox
(homeotic) genes. However, the list of polycomb targeted genes has
expanded in recent years to include genes encoding proteins in-
volved in electron and glucose transport, as well as endopeptidases,
oxidoreductases, and G-protein-coupled receptors (Bracken et al.,
2006; Tolhuis et al., 2006). In the present study, a second polycomb
gene, Suz12 (suppressor of zeste 12 homolog) was also identified as
differentially hypomethylated in injury. Because differential hypom-
ethylation of Phc2 and Suz12 occurred only in injury and not in
epileptic tolerance, the results suggest that this family of transcrip-
tional regulators may contribute to the ordinary control of gene
expression in the wake of SE.
Most of the genes present in the unique differential methyl-
ation profiles of injury or tolerance have not been captured pre-
viously by microarray-based screening for seizure-regulated or
epileptogenesis genes (Becker et al., 2003; Lukasiuk and Pitka¨nen,
2004; Gorter et al., 2006; Laure´ n et al., 2010; Wang et al., 2010).
The present study therefore identifies potentially new genes reg-
ulated by seizures and the mechanism by which they may be
regulated, in addition to identifying novel players in epileptic
tolerance that may be interesting targets for neuroprotection and
anti-epileptogenesis (Jimenez-Mateos and Henshall, 2009). The
expression of several of these genes was investigated, and, in in-
dividual cases, promoter methylation was consistent with a role
in the regulation of gene expression in epileptic tolerance and
injury. However, gene expression did not always correlate with
differential methylation state. Previously, gene-centric studies in
epilepsy have highlighted direct links between promoter methyl-
ation and pathohistological findings. Increased promoter meth-
ylation is responsible for the downregulation of Reelin, which is
associated with granule cell dispersion in human temporal lobe
epilepsy (Kobow et al., 2009), and DNA methylation may regu-
late levels of brain-derived neurotrophic factor in animal models
of epilepsy (Aid et al., 2007). In the context of the individual cases
highlighted in our study, this emphasizes the impact even single
gene methylation changes can exert on seizure pathophysiology.
Hippocampal damage is often bilateral in patients with uni-
lateral temporal lobe epilepsy by clinical and neurophysiological
criteria (Babb, 1991; Jokeit et al., 1999; Arau´ jo et al., 2006). Fur-
thermore, SE can lead to bilateral CA3 damage in humans (Fu-
jikawa et al., 2000) and in animal models, transforming the
contralateral hippocampus into an independent epileptogenic
focus, capable of generating spontaneous and evoked seizures
(Araki et al., 2002; Khalilov et al., 2003). A final observation in
our study was the occurrence of bilateral hippocampal methyl-
ation changes. Bilateral changes are what would be expected if the
preconditioning stimulus is contributing to differential methyl-
ation in tolerance because systemic KA would drive changes af-
Figure 7. Tissue expression of genes hypermethylated and hypomethylated in injury (Inj)
and tolerance (Tol). Graphs show mRNA expression levels (relative fold level) at 24 h measured
by real-time qPCR for Gtf2i (A, hypermethylated in tolerance), Atp2c1 (B, hypermethylated in
injury), Hmga2 (C, hypermethylated in tolerance), Cpne6 (D, hypermethylated in tolerance),
Phc2 (E, hypomethylated in injury) and Hspa1b (F, hypomethylated in injury) (*p⬍0.05, n⫽
3– 6 per group). Con, Control.
1586 •J. Neurosci., February 1, 2012 •32(5):1577–1588 Miller-Delaney et al. •DNA Methylation Changes after Seizures

fecting both hippocampi. Bilateral methylation changes also
support changes in DNA methylation being attributable to sei-
zure activity alone, consistent with reports of activity-dependent
DNA methylation changes during memory encoding (Miller and
Sweatt, 2007). Bilateral DNA methylation changes also suggest
that the genes affected may regulate processes other than cell
death and survival decisions, leaving open contributions by other
transcriptional control mechanisms to the neuroprotection in
epileptic tolerance.
A direct assessment of the contribution of DNA hypermeth-
ylation to the transcriptional environment of tolerance requires
the individual or combined manipulation of Dnmts. Dnmt1 lev-
els can be depleted using 5-aza-2⬘-deoxycytidine (Christman,
2002). However, when used acutely, this DNA methyltransferase
inhibitor is neuroprotective against excitotoxic injuries (Endres
et al., 2000), which would complicate interpretation of its effects
against tolerance. Surprisingly, genetic deletion of Dnmt1 or
Dnmt3a alone produces virtually no neuronal phenotype (Fan et
al., 2001; Feng et al., 2010). Conditional mutants lacking both
Dnmt1 and Dnmt3a display defects in synaptic plasticity, but
their loss resulted in upregulation of only 0.26% of profiled genes
in vivo (Feng et al., 2010). An evaluation of the impact of blocking
components of DNA methylation or demethylation on otherwise
hypermethylated or hypomethylated genes in tolerance may ex-
tend the present insights.
In summary, through genome-wide methylation analysis, we
have identified unique profiles of differential methylation after
SE and in epileptic tolerance. These profiles include many novel
genes that have not been associated previously with epilepsy. Al-
though differential hypermethylation was not substantial and is
not likely to act as the sole molecular mechanism underlying gene
suppression in epileptic tolerance, large contributions by a small
number of genes remain possible. Together, our study identifies
differential methylation of genes as a novel mechanism for en-
dogenous programs of neuroprotection and the molecular envi-
ronment impacted by SE.
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