Genomic analysis of ischemic preconditioning in adult rat hippocampal slice cultures

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a v a i l a b l e a t w w w. s c i e n c e d i r e c t . c o m

w w w. e l s e v i e r. c o m / l o c a t e / b r a i n r e s

Research Report

Genomic analysis of ischemic preconditioning in adult rat hippocampal slice cultures Ethan A. Benardete a,⁎, Peter J. Bergold a,b a

Department of Neurosurgery, SUNY Downstate Medical Center, 450 Clarkson Ave., Brooklyn, NY 11203, USA Department of Pharmacology and Physiology, SUNY Downstate Medical Center, 450 Clarkson Ave., Brooklyn, NY 11203, USA

b

A R T I C LE I N FO

AB S T R A C T

Article history:

Understanding endogenous mechanisms of neuroprotection may have important clinical

Accepted 8 July 2009

applications. It is well established that brain tissue becomes more resistant to ischemic

Available online 22 July 2009

injury following a sublethal ischemic insult. This process, called ischemic preconditioning

Keywords:

deprivation (OGD) [Hassen, G.W., Tian, D., Ding, D., Bergold, P.J., 2004. A new model of

Ischemic preconditioning

ischemic preconditioning using young adult hippocampal slice cultures. Brain Res. Brain

Hippocampus

Res. Protoc. 13, 135–143]. We have analyzed the changes in gene expression brought about by

Slice culture

IPC in this model in order to understand the mechanisms involved. Total RNA was isolated

Microarray

at different time points following a brief OGD (3, 6 and 12 h) and used to probe genome-wide

Receptor signaling pathway

expression microarrays. Genes were identified that were significantly up- or down-

Apoptosis

regulated relative to controls. We placed genes that were differentially expressed into

(IPC), can be induced in adult rat hippocampal slice cultures by a brief oxygen–glucose

statistically significant groups based on Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways and gene ontology (GO) terms. Genes involved in signal transduction, transcription, and oxidative phosphorylation are differentially expressed at each time point. The analysis demonstrates that alterations in signaling pathways (TGF-β, Wnt, MAPK, ErbB, Toll-like receptor, JAK-STAT, VEGF) consistently accompany IPC. RT-PCR was used to confirm that members of these signaling pathways are regulated as predicted by the microarray analysis. We verified that protein translation following OGD is necessary for IPC. We also found that blocking the NMDA receptor during OGD does not significantly inhibit IPC in this model or produce large changes in gene expression. Our data thus suggests that changes in signaling pathways and their down-stream targets play an important role in triggering endogenous neuroprotection. © 2009 Elsevier B.V. All rights reserved.

1.

Introduction

Brief exposure to sublethal ischemia can induce tolerance to a subsequent, otherwise lethal ischemic insult in many tissues including brain (Dirnagl et al., 2003; Gidday, 2006; Steiger and Hanggi, 2007). Understanding mechanisms of endogenous protection from cerebral ischemia may lead to novel treat-

ments for brain injury, especially stroke. Ischemic tolerance or ischemic preconditioning (IPC) can be induced in adult rat hippocampal slice cultures by a brief period of oxygen and glucose deprivation (OGD) (Hassen et al., 2004; PellegriniGiampietro et al., 1999). The exact mechanisms of IPC are unknown, but multiple modifications have been hypothesized including alterations in signal transduction, hypoxia-induci-

⁎ Corresponding author. E-mail address: [email protected] (E.A. Benardete). 0006-8993/$ – see front matter © 2009 Elsevier B.V. All rights reserved. doi:10.1016/j.brainres.2009.07.027

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ble factors, and inflammatory mediators (Gidday, 2006). In order to explore these possibilities, we have analyzed changes in gene expression after IPC in adult rat hippocampal slice cultures and characterized these transcripts using genomewide DNA microarrays. Adult rat hippocampal slice cultures are an attractive model because they are a stable, well-defined population of neurons and glial cells that maintain much of the normal connectivity and architecture of the brain. This is the first study to fully characterize IPC-related changes in gene expression in adult rat hippocampal slice cultures with a genome-wide DNA microarray. DNA microarray analysis allowed us to identify differentially expressed genes following IPC. Using bioinformatics techniques, we were then able to categorize these genes into functional groups and known pathways. The purpose of this analysis is to gain insight into the underlying mechanisms of neuroprotection associated with IPC.

2.

Results

2.1.

Microarray gene expression analysis

Previous work has demonstrated that 5 min of OGD is sufficient to induce IPC in adult rat hippocampal slice cultures (Hassen et al., 2004). IPC results in increased neuronal survival following an ischemic injury given 24 h later. Therefore, we isolated total RNA from adult hippocampal slice cultures at 3, 6 and 12 h following 5 min of OGD and mock-OGD (control). We also isolated total RNA from cultures undergoing 5 min of OGD in the presence of 100 μM (RS)-3-(2-Carboxypiperazin-4-yl)propyl-1-phosphonic acid (CPP). CPP is a high-affinity, competitive antagonist of NMDA receptors. Table 1 shows the number of genes that were significantly regulated either up or down at each time point. When all time points were considered together, 298 genes were identified that had a relative change in expression level >1.5 (either up- or down-regulated) after OGD or OGD in the presence of CPP (p-value < 0.05). We performed hierarchical clustering analysis and generated a heat map with this subset of genes and their changes in expression level (relative to control) to look for overall patterns in the expression data. The

Table 1 – Number of genes showing significant expression changes (p-value <0.05) at 3, 6, and 12 h post-OGD. Number of differentially expressed genes following IPC 3h 6h 12 h post-OGD post-OGD post-OGD # Total up-regulated genes # Genes >1.3-fold increase # Total down-regulated genes # Genes >1.3-fold decrease

784 22 642

765 166 732

738 11 591

54

39

80

In addition, the number of genes undergoing large changes (>1.3-fold) are indicated. As seen in the table, at 6 h, a large subset of genes is upregulated >1.3-fold, while a large subset is markedly down-regulated at 12 h.

heat map (Fig. 1) shows several large clusters of genes with similar expression patterns. At 3 h post-IPC, a cluster of genes, which includes many transcription and translation factors, is up-regulated (Fig. 2). The majority of up-regulated genes that peak in the 6-hour and 12-hour time period are signaling pathway intermediates (Fig. 3). At 12 h post-IPC, a large cluster of genes is down-regulated including a number of genes involved in inflammation (e.g. tumor necrosis factor) (Fig. 4). The heat maps also show that most genes did not change expression with OGD in the presence of 100 μM CPP compared to OGD alone. Bioinformatics analysis was used to identify significant associations between the up-regulated and down-regulated genes and known pathways archived in the Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway database (www.genome.jp/kegg). The KEGG pathway database contains over 200 pathways involved in a myriad of cellular and organism-level functions such as cellular metabolism, cellular function, and human disease. Differentially expressed genes were identified at each time point using the Student's t-test (p-value < 0.05). This list of genes was then compared to KEGG pathways. Z-scores, which quantify the statistical likelihood of the association between the genes in the list and the KEGG pathway, were assigned. Z-scores > 2.0 are considered significant. Table 2 lists KEGG pathways with z-scores >2.0 and four or more members in the list of differentially expressed genes, both at each time point and when all time points were considered together. The majority of the KEGG pathways recognized in our analysis of IPC are signaling pathways. At each time point (3, 6, and 12 h post-OGD), multiple differentially expressed genes are found to be members of these pathways (Table 2). For example, at 3 h post-OGD, several genes that are members of the mitogen-activated protein kinase (MAPK) signaling pathway, which is involved in cytokine signaling and response to stress, and the Wnt signaling pathway, which is involved in determining cell survival, are up- and down-regulated. Other signaling pathways recognized in our analysis include the TGF-β, ErbB, JAK-STAT, VEGF, and the Toll-like receptor signaling pathway. Supplementary tables list the differentially expressed members of the KEGG pathways, which were identified when the data from all time points were considered together (Supplementary Tables 1 and 2). The KEGG analysis also identified pathways that are not directly involved in signaling. For example, the neuronspecific pathways of long-term depression (3 h post-OGD) and long-term potentiation (6 h post-OGD) each have several significantly regulated members. Neuron-specific nitric oxide synthase 1, which is thought to be neuroprotective (Vieira et al., 2008), is a member of the long-term depression pathway and is up-regulated at 3 h. The apoptosis pathway was identified as significantly regulated at both 6 and 12 h. This pathway includes nuclear factor of kappa light polypeptide gene enhancer in B-cells 1, p105 (NFkB1, up-regulated at 6 h post-OGD) and nuclear factor of kappa light polypeptide gene enhancer in B-cells inhibitor, alpha (IkBα, down-regulated at 12 h post-OGD). Up-regulation of the enhancer and downregulation of the inhibitor may limit apoptosis. Members of the complement cascade are down-regulated at 12 h post-

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Fig. 1 – Cluster and heat map analysis of IPC-regulated genes. Genes that were differentially expressed (>1.5 fold compared with control) following OGD for 5 min or following OGD for 5 min in the presence of CPP were subjected to hierarchical clustering. The heat map shows the level of expression expressed as log2 (ratio post-OGD to control) at different times for the selected genes (blue is a decrease and yellow an increase relative to control). There are three large clusters: a group that is either up or down-regulated at 3 h, a second group that is up-regulated at 6 h, and a group that is down-regulated at 12 h. The color scale is shown at the bottom left.

OGD. For example, both complement component 2 and complement component 3 are down-regulated at 12 h postOGD, which may limit complement-mediated cell damage.

The NF-E2-related factor 2 (Nrf2) pathway (Satoh et al., 2006) and the hypoxia-inducible factor 1 (HIF-1) pathway (Semenza, 2007) are commonly associated with ischemia

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Fig. 2 – Expanded view of the cluster of genes that are up-regulated at 3 h post-OGD. Many of these genes are involved in transcriptional and translational regulation. The inset (upper left) shows where the cluster is in the heat map of Fig. 1.

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Fig. 3 – Expanded view of the cluster of genes that are up-regulated at 6 h. Many of these genes are involved in signaling pathways. The inset (upper left) shows where the cluster is in the heat map of Fig. 1.

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Fig. 4 – Expanded view of the cluster of genes that are down-regulated at 12 h post-OGD. A smaller cluster at the bottom shows genes that are down-regulated by CPP. The arrows indicate prostaglandin-endoperoxide synthase 2 (COX-2) and activity-regulated cytoskeletal protein; both of which showed inhibition of expression by CPP following a brief OGD. The inset (upper left) shows where the cluster is in the heat map of Fig. 1.

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Table 2 – Significantly regulated KEGG pathways determined by z-score analysis.

KEGG pathways with greater than 4 members and a z-score >2.0 are listed. The gray-shaded boxes indicate at which time points these pathways were found to be significant. The last column indicates whether a KEGG pathway was found to be significant when all genes at the three time points that had significant changes in gene expression >1.2-fold were considered together.

and oxidative stress. At 3, 6, and 12 h post-OGD, genes that are members of the Nrf2 oxidative-stress response pathway are up-regulated such as Fos-like antigen 1 (Fosl-1), JunD, and thioredoxin reductase 1. This relationship however fell slightly below statistical significance and was not part of our KEGG analysis. Analysis of the microarray data also indicated that the hypoxia-inducible factor 1 (HIF-1) alpha subunit was up-regulated at 3 and 6 h post-OGD. HIF-1 is a transcriptional regulator that activates many genes following ischemia including erythropoietin, a pro-survival factor, up-regulated at 12 h post-OGD in our data (Zhang et al., 2006). HIF-1 is also a down-stream target of the MAPK pathway (Hua et al., 2003). As a complement to the KEGG analysis, gene ontology (GO) analysis was used to classify the differentially expressed genes. The gene ontology project (www.geneontology.org) provides a hierarchical structure for classifying genes into functional groups. GO categories are divided into three large clusters: biological process, cellular component, and molecular function. Lists of genes in each category were compared to the list of genes with significant expression changes brought about by IPC. A p-value was calculated based on the likelihood that the group of genes would occur by chance in the data. We considered GO groups statistically significant if they had 4 or more members in the list of differentially expressed genes and the calculated p-value was <0.05. These results are shown in Tables 3–5. Within biological processes, highly significant associations occurred with the GO categories of positive regulation of transcription, signal transduction, cytokines, and oxidative phosphorylation (Table 3). Apoptosis, cell death, and protein unfolding were also significant categories. The cellular component analysis identified gene products that localize to the nucleus or mitochondrion

(Table 4). The molecular function categories show significant groups of transcription regulators, receptor binding activity, and tRNA binding (Table 5). These data suggest that transcription, translation, and receptor activation are major mediators of IPC.

2.2.

RT-PCR confirmation of microarray analysis

RT-PCR was used to confirm the results of the DNA microarray analysis by quantifying the changes in gene expression expected from the microarray data. Seventeen primer-probe sets were selected based on the results of the microarray analysis. Genes were chosen based on involvement in the MAPK signaling, Toll-like receptor signaling or apoptosis pathways. Two “housekeeping” genes were chosen for relative quantification (β-actin and glyceraldehyde 3phosphate dehydrogenase). We directly verified that the relative expression of β-actin and glyceraldehyde 3-phosphate dehydrogenase did not change at 3, 6, and 12 h postOGD relative to controls in keeping with their “housekeeping” function (data not shown). Sixteen out of 17 genes were confirmed to have marked regulation by IPC as predicted (Fig. 5 and Supplementary Table 3). Fig. 6 charts the close correlation of the microarray data with the RT-PCR data. The signaling pathway genes (except for Clcf1) peak early at 3 h post-IPC and show a gradual decline (Fig. 5, top). Some genes involved in signaling and inflammation such as IL6 and Tnf actually fall below baseline levels at 12 h. Most transcription factors show a sharp peak at 3 h (Fig. 5, middle). Genes that have functional roles outside of signaling show a more prolonged change in expression (Fig. 5, bottom). For example, reactive oxygen species are known to cause cellular damage and induce apoptosis. Our microarray data, confirmed with RT-PCR shows that sulfiredoxin 1 homolog, a potent enzyme

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Table 3 – Significant biological process GO categories. Category

p-value

Transcription GO:45941: positive regulation of transcription GO:45944: positive regulation of transcription from RNA polymerase II promoter GO:45893: positive regulation of transcription, DNA-dependent Regulation of cellular process GO:43119: positive regulation of physiological process GO:6469: negative regulation of protein kinase activity GO:51242: positive regulation of cellular physiological process GO:31325: positive regulation of cellular metabolism GO:45935: positive regulation of nucleic acid metabolism GO:9893: positive regulation of metabolism Cell death GO:16265: death GO:8219: cell death Response to stress GO:30968: unfolded protein response GO:6986: response to unfolded protein Signal transduction GO:6984: ER-nuclear signaling pathway GO:7182: common-partner SMAD protein phosphorylation GO:7183: SMAD protein heteromerization Intracellular transport GO:6607: NLS-bearing substrate import into nucleus Cellular metabolism GO:6752: group transfer coenzyme metabolism GO:6520: amino acid metabolism GO:6754: ATP biosynthesis GO:42089: cytokine biosynthesis GO:42107: cytokine metabolism GO:9142: nucleoside triphosphate biosynthesis GO:42446: hormone biosynthesis GO:9058: biosynthesis Oxidative phosphorylation GO:15986: ATP synthesis coupled proton transport GO:15985: energy coupled proton transport, down electrochemical gradient GO:6119: oxidative phosphorylation Regulation of biological process GO:7026: negative regulation of microtubule depolymerization GO:31114: regulation of microtubule depolymerization Cellular development GO:30098: lymphocyte differentiation

†† †† † † † † †† †† † † † † † † † † † † † † † † † † † † † † † † †

† represents p-value <0.01. †† represents p-value <0.001. Categories not shown (0.01
that reduces perioxiredoxins, is up-regulated by IPC. On the other hand, thioredoxin-interacting protein is down-regulated by IPC, which would increase the activity of thioredoxin, a powerful reducing enzyme.

2.3.

Inhibition of protein translation

In order to test the hypothesis that acquisition of IPC would require translation of the new transcripts made following a brief OGD, we blocked protein translation following the brief OGD using either cycloheximide or anisomycin. Previous work in other models has also tested this hypothesis (Barone et al., 1998; Currie et al., 2000; Nishio et al., 2000). The protein translation inhibitor was placed in the media during the period 4 to 8 h following the brief OGD, which is a peak period

of changes in gene expression suggested by the microarray analysis. Slice cultures were then subjected to an ischemic challenge 24 h following OGD. Inhibition of protein translation blocked IPC, and slice cultures demonstrated an equivalent amount of neuronal death (measured by PI staining) as mockOGD controls (Figs. 7 and 8).

2.4.

Effects of NMDA-receptor blockade

To test the hypothesis that new gene expression following OGD is driven solely by an NMDA-dependent excitatory mechanism, we used CPP (100 μM) to block the NMDA receptor during IPC. When slice cultures were stained with PI following IPC and an ischemic challenge, slice cultures that had been exposed to CPP during OGD, showed minimal

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Table 4 – Significant cellular component GO categories. Category GO:5634: nucleus GO:5622: intracellular GO:16469: proton-transporting two-sector ATPase complex GO:5740: mitochondrial membrane GO:5956: protein kinase CK2 complex GO:5730: nucleolus GO:19867: outer membrane GO:5741: mitochondrial outer membrane GO:30532: small nuclear ribonucleoprotein complex GO:5654: nucleoplasm GO:5743: mitochondrial inner membrane GO:119: mediator complex GO:16471: hydrogen-translocating V-type ATPase complex GO:5635: nuclear membrane GO:5774: vacuolar membrane

p-value †† †† †† † † † † † † † † † † † †

† represents p-value <0.05. †† represents p-value <0.01.

neuronal death (Figs. 7 and 8). This data suggests that NMDA-receptor activation is not necessary for IPC. DNA microarray analysis was also performed to test the hypothesis that NMDA-receptor blockade would alter gene expression following OGD. Total RNA was isolated from hippocampal slices that had undergone treatment with CPP during IPC. Analysis of the DNA microarray data revealed that less than 10% of the genes that were differentially expressed following IPC were significantly altered by CPP treatment. However, both prostaglandin-endoperoxide

Table 5 – Significant molecular function GO categories (p-value <0.01). Category GO:30528: transcription regulator activity GO:3700: transcription factor activity GO:8243: plasminogen activator activity GO:3676: nucleic acid binding GO:46933: hydrogen-transporting ATP synthase activity, rotational mechanism GO:51082: unfolded protein binding GO:4034: aldose 1-epimerase activity GO:50220: prostaglandin-E synthase activity GO:4903: growth hormone receptor activity GO:51008: Hsp27 protein binding GO:8321: Ral guanyl-nucleotide exchange factor activity GO:166: nucleotide binding GO:46961: hydrogen-transporting ATPase activity, rotational mechanism GO:19829: cation-transporting ATPase activity GO:5154: epidermal growth factor receptor binding GO:49: tRNA binding GO:5519: cytoskeletal regulatory protein binding

p-value † † † † † † † † † † † † † † † † †

† represents p-value <0.01. †† represents p-value < 0.001. Categories not shown (0.01 < p-value < 0.05) include protein kinase activity, RNA binding activity, and DNA binding activity.

Fig. 5 – Relative expression changes for genes measured with RT-PCR. The results for 16 primer-probe sets are shown. The change in expression was calculated by the 2− ΔΔCT method and plotted here as the log2. Thus a two-fold increase is plotted as 1 and a two-fold decrease as −1. Genes were grouped into transcription factors (regulators), signaling pathway genes, and effector genes.

synthase 2 (COX-2) and activity-regulated cytoskeletal protein (Arc) showed increased expression following IPC, which was blocked by CPP treatment (see Fig. 4). Both COX2 and Arc are well known to be up-regulated by a NMDAreceptor-dependent mechanism (Andreasson et al., 2001; Larsen et al., 2005). This data suggests that CPP did produce the intended effect of blocking NMDA receptors on the neuronal population in the adult hippocampal slice cultures, but that many of the genes involved in IPC in this model are not regulated by NMDA-receptor-dependent mechanisms. Our data show that NMDA-receptor activation is not necessary for IPC in this model, but that NMDAreceptor activation is part of the response to IPC under normal conditions.

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A number of different methods exist to induce IPC in hippocampal slice preparations including exposure to hyperbaric oxygen, nitric oxide, chemical reagents, and hyperthermia (Aketa et al., 2000; Nakagawa et al., 2003). We chose a brief oxygen–glucose deprivation because it seems to best mimic physiological conditions of ischemia. The time course of IPC can also be divided into rapid IPC and prolonged IPC. Rapid IPC occurs within minutes of the preconditioning stimulus and does not involve transcriptional activation to a significant degree (Perez-Pinzon and Born, 1999). Our model focuses on the changes that occur with long-term IPC and depend on transcriptional and translational activation. Fig. 6 – Correlation of microarray data with RT-PCR. To document that the microarray data was confirmed by RT-PCR, the relative expression values of the 16 genes measured with RT-PCR were calculated from the microarray data and plotted versus the RT-PCR measurements. The data show a good linear fit with a Pearson correlation of 0.55. The slope is 0.90.

3.

Discussion

3.1.

Ischemic preconditioning

Numerous studies have shown that the brain can become resistant to an otherwise lethal ischemic injury by prior exposure to a sublethal ischemic insult. This phenomenon, known as ischemic preconditioning (IPC) or ischemic tolerance, is a tool for understanding endogenous mechanisms of neuroprotection that may have clinical relevance (Dirnagl et al., 2003; Gidday et al., 1994; Steiger and Hanggi, 2007). While IPC can be demonstrated in in vivo mammalian preparations (e.g. the middle cerebral artery occlusion model; Bates et al., 2001), the rat hippocampal slice culture has emerged as a useful experimental paradigm to investigate mechanisms of IPC (Hassen et al., 2004; Perez-Pinzon, 1999). IPC can be induced in acute slices (Perez-Pinzon et al., 1996), organotypic culture (Hassen et al., 2004) and even in dissociated mixed neuronal/glial culture (Khaspekov et al., 1998). Unlike dissociated cell cultures, adult slice cultures maintain much of the in vivo connectivity and have less intrinsic ischemic tolerance. One possible criticism of the chronic adult hippocampal slice model is the necessity to culture the slices at 32 °C prior to experimental manipulation, which is common practice (Federoff and Richardson, 2001). Prolonged “hypothermia” might alter the baseline molecular profile of the cultures, making them less susceptible to ischemia. There is data, however, to suggest that hypothermia simply slows metabolism rather than changing gene expression (Bossenmeyer-Pourie et al., 2000). Our data also shows that adult hippocampal slice cultures, which are shifted to 37 °C 24 h prior to experimental manipulation, undergo neuronal death following ischemia as expected (Hassen et al., 2004) (see Fig. 7). Furthermore, since control and preconditioned slices are cultured identically, the changes in gene expression that we have identified should be related to IPC alone.

3.2.

Gene expression in ischemic preconditioning

Several previous studies have characterized gene expression following IPC with microarrays (Bernaudin et al., 2002; Dhodda et al., 2004; Kawahara et al., 2004; Stenzel-Poore et al., 2003; Tang et al., 2006; Wang et al., 2006). These studies used smaller microarrays than in the present study giving far less coverage of the genome. Nevertheless, in each study, results similar to ours can be found. For example, Kawahara et al. (2004) found that differential gene expression peaks between 3 and 12 h following preconditioning and that signal transduction genes, heat shock proteins, receptors, and apoptosis-pathway genes are regulated by IPC. Feng et al. (2007) recently published a study similar to ours. They used hippocampal tissue harvested from an in vivo rat model of MCAO to perform a genome-wide expression analysis. The authors then used GO and KEGG pathway analysis to further classify the genes differentially expressed following IPC. Similar to our findings, they found that the TGFβ, MAPK, Wnt, and VEGF signaling pathways are all regulated following IPC. Although our study was performed in vitro, it is remarkable that similar results were found as in vivo. This fact demonstrates the cellular (not organismal) nature of the IPC response. It is noteworthy that Feng et al. used an NDMDA-receptor antagonist, MK-801, to block IPC in their model. However, our results do not confirm the NMDA-receptor dependence of IPC in slice cultures. Similar to our study, Chen et al. (2008) and Werner et al. (2007) found that NMDA blockade by MK-801 does not inhibit IPC. The effect of MK-801 on blocking IPC may depend on its delivery in vivo, and it may not work in slice culture (Duszczyk et al., 2005).

3.3.

The role of signaling pathways in IPC

A consistent feature of our data on IPC-related gene expression is the change in expression of numerous signaling pathway molecules. The mechanism by which these changes in expression result in neuroprotection is unclear. It is reasonable to assert that modification of these pathways may work through two overlapping mechanisms. On the one hand, “sensitizing” these pathways may enhance the expression of neuroprotective effector molecules (e.g. heat shock proteins and brain-derived neurotrophic factor (BDNF)) when the next ischemic challenge occurs. On the other hand, IPC may change the balance of these pathways such that further ischemia is less likely to activate apoptotic

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Fig. 7 – Effect of IPC on slice cultures. Representative slice cultures stained with PI 1 and 4 days following ischemic challenge (10 min of OGD). Twenty-four hours prior to ischemia, the slices received either mock-OGD for 5 min (labeled “Mock”), OGD for 5 min (labeled “IPC”), or OGD in the presence of CPP for 5 min (labeled “IPC + CPP”). Slices labeled “IPC + CHX” received cycloheximide from 4–8 h after 5 min of OGD. The data shows that robust neuronal death occurs following ischemia with mock-OGD (top row). IPC limits neuronal death in the dentate and CA1 region of the hippocampal slice culture (second row). The addition of the NDMA-receptor antagonist, CPP, during 5 min of OGD fails to block IPC (third row). However, cycloheximide following 5 min of OGD completely inhibits IPC.

pathways i.e. by down-regulating pro-apoptotic molecules like TNF. Several recent reviews have focused on the role of the Tolllike receptor signaling pathway in IPC (Kariko et al., 2004; Marsh et al., 2009; Stevens and Stenzel-Poore, 2006). Our data supports the notion that multiple genes in this pathway are regulated during IPC. The Toll-like receptors (Tlrs) are a family of receptors involved in inflammation. Our microarray data shows that Tlr2, which is found on glia (Park et al., 2008), is upregulated following IPC. This fact suggests that IPC is a property of neurons and glia working together.

New data also suggests that the same signaling pathways (e.g. MAPK), which are regulated by IPC, are also involved in the response to prolonged ischemia (Kariko et al., 2004; Marsh et al., 2009; Stevens and Stenzel-Poore, 2006). However, it is important to note that we have not compared the changes in expression after prolonged ischemia before and after preconditioning. Stenzel-Poore et al. (2004) have found that the gene expression changes that occur with ischemia are different from the gene expression changes that occur with preconditioning although most of the gene expression changes fall within the same categories (signaling pathways,

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confirmed that some genes such as COX-2 and Arc are strongly modulated by NDMA-receptor activation because IPC-driven up-regulation was blocked by CPP. In addition, some groups have shown that COX-2 is neuroprotective (Choi et al., 2006). Our data thus suggests that IPC induces NMDA-dependent mechanisms of neuroprotection, but these mechanisms are not solely responsible for IPC.

3.6.

Fig. 8 – Quantitative analysis of the experiment shown in Fig. 7. Cell death was quantified with PI florescence (relative units). Increased florescence correlates with greater death. The intensity of florescence in the CA1 region was calculated with Image/J software, and the background was subtracted. Each data point represents the mean for 12 slice cultures under each condition. The data show that IPC protects neurons from ischemia and that the NMDA-receptor antagonist, CPP, fails to inhibit this effect. Cycloheximide (CHX), however, does block IPC when given 4–8 h following OGD. Error bars show the standard error of the mean.

inflammation, oxidative phosphorylation, etc.). Future work will focus on how the expression changes that occur with IPC lead to the altered response to ischemia that occurs with the preconditioned phenotype.

3.4.

Our work suggests that changes in signaling pathways are central to the acquisition of IPC. In addition, changes in oxidative phosphorylation, transcription, translation, and inflammatory pathways are implicated. Future work will focus on confirming the protein changes in these pathways, identifying the cellular localization of these gene products (neurons vs. glia), and understanding their functional roles and interactions. Furthermore, organotypic hippocampal slice cultures provide an attractive model for dissecting the molecular events involved in IPC. We have identified changes in gene expression in a number of pathways seen in previous experiments with whole animals suggesting that it is valid model for IPC. The model allows for a large number of samples to be obtained in way that is prohibitive with in vivo experiments. Using recombinant vectors and other agents, experimental manipulations to block various pathways are possible in slice cultures without giving these agents to the whole animal.

Protein translation is necessary for IPC

We hypothesized that new protein translation is required for IPC in our model. We confirmed that either cycloheximide or anisomycin given during the peak of gene expression changes following a brief OGD blocks IPC. This data agrees with other investigators (Barone et al., 1998; Burda et al., 2003; Burda et al., 2006; Currie et al., 2000; Emerson et al., 1999; Gage and Stanton, 1996; Ma et al., 2006; Nishio et al., 2000). For example, using cycloheximide, Barone et al. (1998) demonstrated this effect in an in vivo middle cerebral artery occlusion model. These data suggest that translation of new transcripts brings about the IPC phenotype. However, more complex scenarios involving translation of pre-existing pools of mRNA could account for IPC phenomena. Future work will focus on confirming the predicted changes in protein levels based on our preliminary genomic analysis.

3.5.

Conclusion

NMDA-receptor-dependent mechanisms of IPC

Some investigations have implicated NMDA-receptor activation as responsible for IPC (Bond et al., 1999). We did not find NMDA-receptor blockade to significantly inhibit IPC in our model. Our findings corroborate those of Duszczyk et al. (2005) and Tremblay et al. (2000). The work of Gage and Stanton in acute hippocampal slices also agrees with our work in that the NMDA-receptor inhibitor, D-AP5, did not block preconditioning (Gage and Stanton, 1996). Similar to our work in organotypic hippocampal slice cultures, Werner et al. (2007) found that MK-801 did not block IPC although the group I mGlu receptor antagonists and AMPA/kainite antagonists did. We

4.

Experimental procedures

4.1.

Slice preparation

The SUNY Downstate Medical Center Institutional Animal Use and Care Committee approved the experimental procedures involving animals. Hippocampal slices were prepared according to the method of Hassen et al. (2004). Briefly, P20–P30 Sprague–Dawley rats were anesthetized with halothane and ketamine (100 μg/g). Under sterile conditions, hippocampi were isolated and cut into 400 μM sections while bathed in icecold dissecting solution (modified Gey's balanced salt solution). Hippocampal slices (3 per well) were then plated on microfilters (0.4 μm Millicell-CM, Millipore, Inc.; Bedford, MA), resting on nutrient media. The media was exchanged every 3 days, and the concentration of serum in the media was gradually decreased. Slices were cultured for 14 days at 32 °C in a 5% CO2 environment. The slices were then stained in situ with propidium iodide (PI) solution (4 μg/ml) for 30 min to gauge cell death (Noraberg et al., 1999) and observed with fluorescence microscopy (see below). Inserts with slices showing staining of the dentate or pyramidal cell layers were discarded.

4.2.

Ischemic preconditioning

After 14 days in culture, slice cultures were shifted to 37 °C, 5% CO2 for 24 h. The cultures were then subjected to 5 min of OGD by placing them on their insert in an incubator bubbled

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with 95% N2, 5% CO2 in modified Earle's Balanced Salt solution (mEBSS) lacking glucose. “Mock-OGD” controls were given the same treatment in mEBSS containing 5.6 mM glucose and bubbled with 95% O2, 5% CO2. Following OGD or mock-OGD treatment, inserts were returned to the 37 °C incubator. Slice cultures were then removed from the incubator at 3, 6, and 12 h following OGD or mock-OGD treatment. Six to nine slice cultures at each time point were then placed in 500 μl of RNAlater (Ambion, Inc.; Austin, TX) and after 24 h at 4 °C, were transferred to −20 °C for storage. At each time point, 3 or 4 sets of slice cultures (6–9 slices each) were obtained. NMDA-receptor blockade was carried out with (RS)-3-(2Carboxypiperazin-4-yl)-propyl-1-phosphonic acid (CPP). CPP is a selective, high-affinity, competitive NMDA-receptor antagonist with a Ki of 220 nM (Davies et al., 1986; Murphy et al., 1988). For cultures undergoing OGD in the presence of CPP, CPP (100 μM final concentration) was added to the culture medium 30 min prior to OGD to allow for complete receptor occupation (Lehmann et al., 1987). During 5 min of OGD, 100 μM CPP was also present in the mEBSS solution. The cultures were then returned to fresh media at 37 °C.

4.3.

RNA isolation and DNA microarray analysis

DNase I-treated total RNA was isolated from slice cultures using RNAeasy Micro (Qiagen, Inc.; Valencia, CA). For each condition (mock-OGD, OGD, and OGD in presence of CPP) approximately 2 μg of total RNA was obtained in triplicate or quadruplicate. Between 6 and 9 slice cultures were needed to obtain 2 μg of total RNA (approx. 300 ng per slice culture). Approximately 9–12 slices can be obtained from each hemisphere during slicing. Thus, for each time point, approximately 6 rats (both male and female) were sacrificed. Slices (on their inserts) from different animals were randomized to experimental treatments (mock-OGD, OGD, and OGD in the presence of CPP) in order to avoid bias. For each sample, Abs 260/280 was >1.9, measured using a microspectrophotometer (NanoDrop 1000, Thermo Scientific, Inc.; Waltham, MA), and integrity was checked on an Agilent Bioanalyzer 2100 (Agilent Technologies, Inc.; Santa Clara, CA). Reverse transcription, biotin-labeled cRNA generation, and hybridization to DNA microarrays were performed by Asuragen, Inc. (Austin, TX). Briefly, biotin-labeled cRNA was generated using MessageAmp-based protocols (Ambion, Inc.; Austin, TX). The labeled cRNA was fragmented and hybridized to microarrays at 45 °C for 16 h in an Affymetrix hybridization oven (Model 640) (Affymetrix, Inc.; Santa Clara, CA). Arrays were washed and stained in an Affymetrix FS450 Fluidics Station and scanned on an Affymetrix GeneChip Scanner 3000 7G. Affymetrix rat 230 2.0 DNA microarrays representing the entire transcribed rat genome were used (>30,000 ESTs). Over two-thirds of these ESTs have been annotated (Lahousse et al., 2006). Gene expression levels were calculated from the probe level intensity data (.cel files) with log-scale robust multi-array analysis (RMA) (Irizarry et al., 2003). Statistical analysis, data visualization, and gene ontology testing were performed with GeneSifter Analysis Edition (Geospiza, Inc.; Seattle, WA) and Genespring Gx software ver. 7.3.1 (Agilent Technologies, Inc.; Santa Clara, CA). The

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Student's t-test was used to test for significant differences between gene expression levels under two different conditions. When gene expression levels were compared for three or more conditions, ANOVA was used. Since the number of samples at each time point was relatively small (3 or 4), a correction for the false discovery rate (FDR) was not used when a pair-wise comparison was done. When all the data sets were analyzed together, ANOVA was performed to determine differentially expressed genes. A correction to the p-value (Bonferroni) was applied to adjust for the FDR. Other correction methods designed to control for the FDR (such as Benjamini-Hochberg) gave similar results. Significant KEGG pathways were identified with the GeneSifter software, which assigns a z-score to each pathway with at least one member gene in the list of differentially expressed genes. Z-scores greater than 2.0 were considered significant. The z-score, z, is calculated as:
 r n NR Z = qffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffi


 n NR 1 NR 1 Nn 11 where r = the number of differentially expressed genes in the specified KEGG pathway, n = total number of genes in the specified KEGG pathway, R = the total number of differentially expressed genes, and N = total number of genes measured. Genespring GX software (ver. 7.3.1) was used for GO category analysis. A simplified hierarchy of GO categories (GO SLIMS) was used to place genes into functional groups. The software assigned p-values to each GO category based on the likelihood that genes would be placed in that category by chance. p-values less than 0.05 were considered significant. Hierarchical clustering and heat map analysis were performed with Cluster 3.0 and Java TreeView 1.1.3. Both programs are freely available (www.sourceforge.net). Hierarchical clustering was done using a Pearson correlation on the relative expression data and the centroid linkage method.

4.4.

Real-time PCR quantification of gene regulation

DNase I-treated total RNA was isolated from mock-OGD-treated (control) and OGD-treated (3, 6, and 12 h post-treatment) adult hippocampal slice cultures as above. OD 260/280 was greater than 2.0 for each sample, and integrity was checked using an Agilent Bioanalyzer 2100 (Agilent Technologies, Inc.; Santa Clara, CA). The samples were then reverse-transcribed from 2 μg of total RNA to cDNA using the ABI High-Capacity cDNA Reverse Transcription Kit (Applied Biosystem, Inc.; Foster City, CA). PCR reactions without reverse-transcription were used to verify that there was no significant genomic DNA contamination. Nineteen primer-probe sets (obtained from ABI) were performed in a linear fashion with 5 ng to 30 ng of cDNA per reaction. Each reaction was then run in triplicate with 20 ng of cDNA, the ABI primer-probe, and TaqMan Universal PCR Master Mix (Applied Biosystems, Inc.; Foster City, CA). The reactions were run on an Applied Biosystems Prism 7000 with the following parameters: 50 °C for 2 min, 95 °C for 10 min, and then 60 °C for 1 min for 40 cycles. Relative expression values were calculated using the change in threshold florescence values according to the 2− ΔΔCT method (Livak and Schmittgen, 2001), where CT represents the number of PCR cycles at which

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florescence reaches the threshold value. Both β-actin and glyceraldehyde 3-phosphate dehydrogenase were used as housekeeping gene controls and showed no significant change in expression under these conditions. CT was calculated for each primer-probe set and the two housekeeping genes under each condition in triplicate. The difference, ΔCT, under mock-OGD conditions represents the baseline expression of the target gene relative to the housekeeping gene. ΔCT was then calculated at 3, 6, and 12 h post-OGD. The expression, 2- ΔΔCT, is the relative change in the target transcript following IPC. The TaqMan gene expression assays (ABI) used were: β-actin (Actb) Rn00667869_m1; glyceraldehyde 3-phosphate dehydrogenase (Gapdh) Rn99999916_s1; mediator complex subunit 13 (Med13) Rn01299744_m1; Rho family GTPase 3 (Rnd3) Rn01449467_m1; fos-like antigen 1 (Fosl1) Rn00564119_m1; prostaglandin-endoperoxide synthase 2 (Ptgs2) Rn01483828_m1; sulfiredoxin 1 homolog S. cerevisiae (Srxn1) Rn01536084_g1; cardiotrophin-like cytokine factor 1 (Clcf1) Rn01233709_s1; tumor necrosis factor (Tnf) Rn01525859_g1; interleukin 1 alpha (Il1a) Rn00566700_m1; toll-like receptor 2 (Tlr2) Rn02133647_s1; interleukin 6 (Il6) Rn01410330_m1; Jun D protooncogene (Jund) Rn00824678_s1; dual specificity phosphatase 6 (Dusp6) Rn00518185_m1; interleukin 1beta (Il1b) Rn00676333_g1; nuclear receptor subfamily 4, group A, member 1 (Nr4a1) Rn00666995_m1; heat shock 70 kDa protein 8 (Hspa8) Rn00821195_g1; and thioredoxin-interacting protein (Txnip) Rn01533885_g1. One primer-probe set (eukaryotic translation initiation factor2, subunit 3, structural gene xlinked, Rn01419594_m1) did not perform as predicted and was not included in the analysis. The RT-PCR experiments were carried out at SeqWright, Inc. (Houston, TX).

4.5. Ischemic challenge and quantification of neuronal death Following 5 min of OGD or mock-OGD, adult hippocampal slice cultures were returned to 37 °C, 5% CO2 for 24 h. Slice cultures then were subjected to a 10 min period of OGD and returned to 37 °C, 5% CO2. Slice cultures were stained with PI as above and observed with fluorescence microscopy through rhodamine optics (Leica Axiovert 100, Leica, Inc.; Wetzlar, Germany) at 1 and 4 days following ischemia. Images were captured with a PTI I-100 CCD camera (Photon Technology International, Inc.; Birmingham, NJ). The staining of the CA1 region was quantified using Image/J software (www.nih.org) and was used to gauge neuronal death (Noraberg et al., 1999). PI enters cells with damaged cell membranes, binds to nucleic acids in the nucleus, and is a reliable indicator of cell death (Noraberg et al., 1999). The staining intensity of the CA1 region was calculated and background florescence was subtracted as previously described (Hassen et al., 2004). Statistical analysis was performed with Excel (Microsoft, Inc.; Redmond, WA) and Prism ver. 5.0a (Graphpad Software, Inc.; La Jolla, CA). Either cycloheximide (35 μM) (Ma et al., 2006) or anisomycin (10 μM) (Shen et al., 1995) were used to reversibly block protein synthesis by adding it to the culture media from 4 to 8 h following OGD and then removed by exchanging with fresh media. Cycloheximide and anisomycin caused a minimal amount of baseline toxicity under these conditions (data not shown). (RS)-CPP, cycloheximide, and anisomycin were obtained from Tocris Bioscience, Inc. (Ellsville, MO).

Acknowledgments The authors would like to thank Shirley Murray for her excellent technical assistance, and Frank Barone and Victor Neel for useful suggestions. E.A.B. was supported by a grant from the SUNY Downstate Academic Reinvestment Fund.

Appendix A. Supplementary Data

Supplementary data associated with this article can be found, in the online version, at doi:10.1016/j.brainres.2009.07.027.

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