BIOMARKERS OF HIPPOCAMPAL GENE EXPRESSION IN A MOUSE

RESTRAINT CHRONIC STRESS MODEL

Massimo Ubaldi1, Eugenia Ricciardelli2,3, Lorenza Pasqualini2,3$,

Giuseppina Sannino2,3#, Laura Soverchia1, Barbara Ruggeri4, Silvia Falcinelli2,3, Alessandra

Renzi2,3, Colleen Ludka2, Roberto Ciccocioppo1 and Gary Hardiman3 ,6, 7*

1 School of Pharmacy, Pharmacology Unit, University of Camerino, Via Madonna delle Carceri 9,

Italy.

2 Dept of Medicine, School of Medicine, University of California, La Jolla, CA, USA

3 Facoltà di Scienze, Università Politecnica delle Marche, 60131 Ancona Italy

4 Medical Research Council – Social, Genetic and Developmental Psychiatry Centre, Institute of

Psychiatry, King’s College London, De Crespigny Park, London, United Kingdom, SE5 8AF,

6 Computational Science Research Center and Biomedical Informatics Research Center

San Diego State University

7 Department of Medicine, Medical University of South Carolina, Charleston, SC

*To whom correspondence may be addressed

Gary Hardiman, Ph.D., Department of Medicine & Center for Genomic Medicine,

Medical University of South Carolina, 135 Cannon Street, Suite 303 MSC 835,

Charleston, SC 29425

(P): 843-792-0771; hardiman@musc.edu

1

Current address: #GS, Natural and Medical Sciences Institute, University of Tuebingen,

Reutlingen, Germany. $LP, Innsbruck Medical University, Department of Urology,

Innsbruck, Austria.

2

Abstract

Objective: Acute stress provides many beneficial effects whereas chronic stress

contributes to a variety of human health issues including anxiety, depression,

gastrointestinal problems, cardiac disease, sleep disorders and obesity. The goal of this

work was to identify, using a rodent model, hippocampal gene signatures associated

with prolonged chronic stress representing candidate biomarkers and therapeutic

targets for early diagnosis and pharmacological intervention for stress induced disease.

Methods: Mice underwent “restraint stress” over 7 consecutive days and hippocampal

gene expression changes were analyzed at 3, 12 and 24 hours following the final

restraint treatment.

Results: Data indicated that mice exposed to chronic restraint stress exhibit a

differential gene expression profile compared to non-stressed controls. The greatest

differences were observed 12 and 24 hrs following the final stress test.

Conclusions: Our study indicated that Gpr88, Ttr, Gh and Tac1 mRNAs were modulated in

mice exposed to chronic restraint stress. These transcripts represent a panel of

biomarkers and druggable targets for further analysis in the context of chronic stress

associated disease in humans.

Keywords: chronic, acute, stress, restraint, hippocampus, cortex, amygdala

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Introduction

Stress occurs when an individual is unable to cope effectively with physical or

psychological requests. While acute stress may be beneficial to recruit adaptive responses to

cope with the stressful situation, prolonged stress may results in maladaptation that can be a

risk factor of numerous affective mental illness [1-3]. Moreover stress impacts the

cardiovascular system, metabolism, digestion, growth, the immune system and memory [4-6].

In the context of the cardiovascular system, chronic stress is related to hypertension, heart

disease, and atherosclerosis of the coronary arteries. In addition, chronic stress affects blood

sugar levels promoting the development of diabetes [4].

There are many brain regions affected by stress and that mediate stress-associated

responses. Among these the hippocampus is the brain region in which the effects of stress have

been extensively studied. The hippocampus is a major component of the brains of humans and

other vertebrates. It mediates cognitive functions such as learning and memory and is highly

sensitive to both endogenous and exogenous insults, including stress [5, 7-9]. It regulates

human stress responses serving as a major feedback site for increased levels of glucocorticoid

hormones, which if unchecked are neurotoxic [10, 11]. In addition, the hippocampus is one of

the key brain regions involved in the pathophysiology and management of mood affective

disorders. Animal studies have revealed that a reduction in hippocampal neurons upon

exposure to stress [12-14]. Similarly in humans psychiatric conditions related to stressful events,

including posttraumatic stress disorder, emotional intensity disorder, and clinical depression

diminish hippocampal neurons [15-17].

Chronic stress is a risk factor for clinical depression in individuals with genetic

vulnerability [18, 19]. Moreover, repetitive stress is often used as a rodent representation of

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depression because it induces the symptoms, one of which is anhedonia [20]. Others include

alterations in REM sleep [21, 22]; reduced sexual activity [23, 24]; increased corticosterone

levels [19]; and disturbed circadian rhythms [25]. Clinical studies have shown that individuals

with long term stress exhibit reduced hippocampal volume, in addition to degeneration of other

limbic brain regions. Reduced hippocampal volume has been reported in individuals with

recurrent depressive disorder and post-traumatic stress disorder (PTSD) [25-27]. High-

resolution magnetic resonance imaging revealed correlation between PTSD and a smaller mean

CA3/dentate gyrus subfield volume, a finding in line with animal models. This indicates that

chronic stress inhibits neurogenesis and dendritic branching in these structures [27]. Protraction

of stressful stimuli leads to dysregulation of specific neurochemical mechanisms, long-term

changes in synaptic plasticity, and alterations in the hippocampal structure and function [28,

29].

To better elucidate how prolonged stress affects the molecular function of the

hippocampus we carried out genome wide microarray analysis using a well established mouse

chronic stress restraint model, shown previously to cause atrophy of the CA3 pyramidal neurons

[28, 30]. Previous array based studies have focused on the Wistar rat model and the

hippocampal dentate gyrus [31] and anxiety- and depression-like behaviors and their effects on

gene expression in the mouse cortex [32]. The aim of this study was to uncover in this mouse

model, molecular signatures associated with prolonged stress in the hippocampus which could

represent promising markers for early diagnosis of stress associated disease and potential

therapeutic targets in humans.

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Materials and Methods

Animal handling and restraint stress

Male CD 1 mice 8 weeks old (weight 32-38g) purchased by Harlan were used in this

study. Animals were housed in groups of 3–4 per cage under controlled conditions of

temperature (20–22 °C) and 12:12 h light/dark cycle (lights on at 5:00 am). Food and water were

freely available. A total of 36 mice (CD-1 Harlan) were subjected to a 2-week acclimation period

before the onset of experimentation. These mice were divided in four discrete experimental

groups: control (basal levels), 3 hours (h) chronic stress, 12 h chronic stress and 24 h chronic

stress (prolonged stressful levels). Each group contained 9 animals. The mice were subjected to

a stress defined as “restraint stress”, where mice were immobilized in restraint bags for 60

minutes (min). Restraint stress was performed during the light phase of the light/dark cycle. The

chronic stress was simulated in the mice for 7 consecutive days. The mice were exposed to one

final stressor treatment and were sacrificed at 3, 12 and 24 hours following the terminal

restraint treatment. The control group included mice not exposed to the restraint procedures.

These animals were sacrificed with the stressed animals at each of the time points.

For each experimental group (9 animals in total) the hippocampal tissues were pooled

randomly; such that each pool was composed of 3 hippocampal tissues from 3 different animals.

This yielded a total of 12 samples for microarray analysis. Tissues were harvested under RNAse

free conditions to avoid RNA degradation as previously described [33]. All studies involving use

of mice were reviewed and approved by the Institutional Review Board, University of Camerino,

Italy.

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RNA extraction, fluorescent target labeling and microarray hybridizations

Isolation of total RNA from each pool of three hippocampus samples was carried out

using TRIzol reagent (Invitrogen) and the extracted RNA were further enriched using the RNeasy

Mini kit (Qiagen, Valencia, CA). All RNA was subjected to on-column digestion of DNA during

RNA purification from cells, to ensure highly pure RNA free from DNA contamination. The

concentrations were measured via by absorbance readings (OD) at 260nm using an ND-1000

(Nanodrop, Wilmington, DE). RNA was examined for integrity using a 6000 Nano LabChip assay

from Agilent, (Santa Clara, CA). Only RNA samples with a RIN score of >7.0 were used for

microarray analyses.

For microarray analysis, the Illumina Mouse 6 Sentrix Expression BeadChip (Illumina, San

Diego, CA) and UniSet Mouse I Expression Bioarray (Applied Microarrays, Tempe, AZ) platforms

were used. Biotinylated cRNA was generated using the Illumina RNA Amplification Kit, Catalog

#1L1791 (Ambion, Inc., Austin, TX) from 250 ng total RNA. Ambion cDNA and cRNA filters

facilitated reverse transcription (RT) and (in vitro transcription) IVT product cleanups [34].

BeadChip processing was carried out according to the Illumina BeadStation 500x manual.

Image analysis and data extraction was performed as described previously [35, 36]. For the

UniSet Mouse I Expression Bioarray experiment, total RNA was processed as originally described

by Ramakrishnan [37].

Statistical and bioinformatics analysis of microarray data

Array data has been archived in the EBI Array Express Database (E-MTAB-2402).

Statistical analysis of our microarray experiment involved three steps described in detail

elsewhere: 1) normalization of microarray data and false discovery rate analysis, 2) ranking of

genes, and 3) statistical analysis of pathways and gene ontology terms represented by the

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ranked genes [38, 39]. Heat maps were created using custom software program employing

Ward clustering. The colors qualitatively reflect fold changes with respect to a reference which is

set as the mid-point between compared groups.

Quantitative real-time PCR analysis.

Relative mRNA transcript levels were obtained by real-time quantitative RT-PCR in a

Light Cycler 480 (Roche, Indianapolis, IN). Hippocampal total RNA (from the same pool of three

mice per time point for the array experiments) was reverse-transcribed using the Roche

Transcriptor kit. The Light Cycler 480 SYBR Green Master kit was used to quantify 50 ng cDNA.

Gene-specific primers were generated with Primer3 [40]. The sequences of all primers used in

this study are provided in Table S1. The Glyceraldehyde-3-phosphate dehydrogenase (Gapdh)

mRNA served as a housekeeping reference for normalization. In order to ensure specificity for

the respective mRNA targets melt curve analysis was performed. For all the PCR assays carried

out each sample was run in triplicate along with a no-template control (NTC) and mean values

were reported. A one-way ANOVA and a Tukey test were carried out using GraphPad Prism

version 5.0 (GraphPad Prism Software, Inc., USA) to determine significance. The LightCycler

Relative Quantification software (Roche Applied Science) was utilized to obtain normalized gene

expression values. Relative gene copy numbers were derived using the comparative

quantification method that employs the formula 2CT where CT is the difference in PCR cycles

needed to detect amplification product from similar input RNA amounts.

Results

Genome wide analysis of hippocampal gene expression in acute and chronic restraint

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We assessed genome wide alterations in hippocampal gene expression in mice exposed

to chronic stress using a restraint stress model and the Illumina Mouse 6 Sentrix Expression

Bead Chip platform. Three experimental groups and one control group were examined, with

each group containing nine animals. Mice were subjected to restraint stress for a 60 minute

period which was repeated over 7 consecutive days. Gene expression changes were then

investigated following the final restraint stress relative to control animals at 3h, 12h and 24h

post exposure to the final stressor.

We performed Gene Ontology (GO) analyses and the data is summarized in Figure 1.

Owing to the overlap of gene membership among GO terms we clustered significant gene sets

using variation of information (VI) as the distance metric [41, 42], and display data as a heat map

(Figure 1). We included gene sets with adjusted p-values ≤ 0.01. Significant GO biological

process terms enriched in mice exposed to chronic stress were ‘transmission of nerve impulse’,

‘multicellular organismal signaling’ and ‘negative regulation of molecular function’. ‘Dendrite’,

‘neuron projection’, ‘cell projection’, ‘synapse’ and ‘cell junction’ were significantly enriched

cellular component terms.

Subsequently we examined the highly ranked differentially regulated probes. For this

analysis, the fold changes were obtained from log2 ratios between the probe signal for each

individual mouse and a corresponding control mouse. The log2 ratio value was determined as

the median of the three biological replicate log2 intensity ratios. Array probes were ranked by

their importance in descending order of the sum-squared statistic (i.e., sum of squares of log2

ratios across all samples) as described previously [43]. The reason for this strategy was that the

sum-squared statistic determined the amount of variance across the entire time course. The top

ranked probes were arbitrarily selected and a heat map was made representing differentially

expressed transcripts in the chronic group relative to control mice reference at the various time

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points (Figure 2). We examined this list for genes that represented potential therapeutic

targets. Based on this criterion the following nine mRNAs were selected for further

consideration; G-protein coupled receptor 88 (Gpr88), tachykinin 1 (Tac1), growth hormone

(Gh), activity regulated cytoskeletal-associated protein (Arc), transthyretin (Ttr), junctophilin 4

(Jph4), guanine nucleotide binding protein, alpha q polypeptide (Gnaq), CDC−like kinase 1 (Clk1)

and serum/glucocorticoid regulated kinase (Sgk). Ttr, Arc, Gpr88, Clk1, Jph4 and Sgk were up

regulated. Gnaq and Gh were both down regulated. Tac1 was up-regulated at the 3 h time point

and down regulated in the later time points.

Validation of targets of interest using Applied Microarrays/Codelink Bioarrays.

The UniSet Mouse I Expression Bioarray (Applied Microarrays/Codelink) was used to see

if we could validate our findings from the Illumina experiments (Figure 3A). This three

dimensional hydrophilic gel based substrate contains a different surface to the Illumina platform

and represents an independent technical microarray assessment of gene expression with

different probe sets. This smaller content array platform (10K probes) did not contain probes

for Jph4 or Sgk but the other targets of interest were present. This revealed that Ttr, Arc, Gpr88

and Clk1 mRNAs were up-regulated as was observed in the Illumina experiment. Similarly the

Applied Microarrays/Codelink data revealed that Gnaq and Gh were both down regulated

mirroring the observations from the Illumina data set. Tac1 again exhibited variable expression

and was most notably up-regulated at the 3 h time point.

Gene expression profiling in rat hippocampus, amygdala and cortex tissue in response to

prolonged restraint stress using the Affymetrix Rat Genome U34A chip.

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A search of gene expression data sets in public repositories revealed an Affymetrix data

set for the Norway rat model exposed to prolonged restraint stress in the GEO database

(Accession: GSE2870). This data derived from rats which received either 30s of exposure

(Control group; n=15) or 3h of immobilization stress (Stress group; n=15) daily for 14

consecutive days. This stress model is analogous to the experiment we conducted with mice and

has formerly been shown to generate opposing effects on dendritic morphology and brain

region-specific behaviors for the hippocampus compared to amygdala. Hippocampal, amygdala

and cortex mRNA profiles from rats under basal and stressful conditions were examined and

gene expression changes were determined for Gpr88, Tac1, Gh, Arc, Ttr, Clk1 and Gnaq. The

mRNA level fold changes for the selected targets observed between prolonged stress treatment

and reference rats after the 14 day chronic stressor exposure are presented in Figure 4.

Examination of the expression patterns in hippocampus revealed that Gpr88, Tac1, Ttr,

Clk1 and Gnaq were all up regulated and Gh and Arc were down-regulated in the prolonged

restraint group. In contrast to the hippocampus and cortex where it was down-regulated, Gh

was up-regulated in the amygdala. Gpr88, Tac1 and Ttr were also up-regulated in the amygdala

under stressful conditions. A comparison of the hippocampal expression signatures between rat

and mouse revealed similar profiles for Ttr, Tac1, Gpr88 and Clk1 (up-regulated) and Gh (down-

regulated). However Gnaq was mildly up-regulated in the rat hippocampus post stress, which

differed from mouse where we observed down-regulation. Arc also exhibited a cross species

difference in its modulation in response to stress, being modestly down-regulated in the rat and

strongly up-regulated in the mouse.

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Validation of targets of interest using Quantitative PCR.

We examined using the qPCR panel the expression patterns of Ttr, Arc, Gpr88, Jph4,

Gnaq, Clk1, Tac1, Sgk and Gh in mice exposed to the chronic stressor (Figure 5). This revealed

that Gpr88 and Ttr were strongly and consistently increased at all time points in the mice

exposed to the restraint stress over the control group, confirming the findings with the Illumina

and Applied Microarrays/Codelink array experiments and agreeing with the up-regulation seen

in rat (Figure 4). Tac1 was up regulated at the 3 h time point and was then down regulated at

the later time points, again confirming the findings with the array data sets. The qPCR data

revealed that Gh was strongly down regulated in the stressed mice, which concurred with the

array data. Additionally qPCR revealed a modest down-regulation in Gnaq at the 12 time point

correlating with the Illumina data but differing from the findings with rat hippocampus, where

stress up regulated Gnaq. Arc was strongly and consistently up regulated at all time points in the

mice exposed to the restraint stress over the control group, confirming the findings with the

Illumina and Applied Microarrays/Codelink array experiments but not correlating with the up-

regulation seen in rat (Figure 4). Sgk and Jph4 were also up regulated in the qPCR experiment

consistent with the Illumina data set. The qPCR data revealed no significant change in Clk1.

Based on these multiple genomics platform results and cross species observations, the best

biomarkers for chronic stress were identified as Gpr88, Ttr, Gh and Tac1.

Drug-gene interactions for GPR88, TTR, GH and TAC1

A query of the Drug-Gene Interaction database (DGIdb) revealed that of the four targets GPR88,

TTR, GH and TAC1, only Ttr yielded a drug-gene interaction [44]. Two compounds ALN-TTR01/

DCL001138 (Alnylam Pharmaceuticals) and ISIS-TTR/ DCL001204 (Isis Pharmaceuticals) were

both reported to interact with TTR.

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Discussion

Although the results of chronic stress on the hippocampus have been well documented

gene expression changes induced by stress remain to be fully elucidated due to the limited

number of studies that have been performed to date. Datson and colleagues utilized a rat model

focused on the dentate gyrus (DG) of the hippocampus which plays an essential role in learning

and memory [31]. Using DNA microarrays, they uncovered molecular signatures in the DG

sensitive to chronic stress. The identified pathways provided critical insight into the stress-

induced adaptive plasticity of the hippocampal DG [31]. In a separate study, Andrus and

colleagues examined an endogenously depressed rat developed via bidirectional selective

breeding from the Wistar-Kyoto (WKY) rat, an accepted model of clinical depression [30].

Expression analyses uncovered differentially regulated mRNAs in hippocampi and amygdalae for

models of endogenous depression and the chronic stress. No significant differences were found

in the expression of monoaminergic transmission-related targets in either group. Although

chronic stress may lead to depressive behavior, the gene expression signatures of chronic stress

and endogenous depression in the rats studied by Andrus et al. differed significantly. This

suggests that different treatment regimens are needed for managing endogenous depression

and chronic stress in humans. Unexplored mRNAs and novel pathways could potentially be

selected for the development of new therapeutics.

The focus of this study was to utilize a mouse model of chronic stress, where the

animals were subjected daily to restraint stress over a 7 day period. Control animals under

normal conditions (no exposure to stressor) provided a measure of basal gene expression levels.

Genome wide gene expression patterns were examined 3h, 12h and 24h after the animals were

subjected to the final stress treatment. The rationale behind the time points selected for study

is as follows. The 3h time point was chosen for two reasons: firstly, to avoid the acute stress

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effects from the last restraint treatment; secondly, because a survey of literature demonstrated

that the peak of the transcriptional response in the mouse brain occurred between 3 and 4

hours following administration of chemical stimuli [45]. Additionally in the rat hippocampus the

greatest changes in the expression of brain-derived neurotrophic factor (BDNF) and anti-

apoptotic B cell lymphoma like X (Bcl-xl) mRNAs occurred 2 hours after forced swim stress tests

(FST) [46]. Moreover previous studies showed that changes in BDNF and corticotropin-releasing

factor (CRF) expression in the rat nucleus accumbens and prefrontal cortex brain took place

between 1 and 6 hours after FST [47]. We selected the 24h time point because the literature

demonstrates that the behavioral consequences of restraint stress are still present at this time

point [48, 49]. Furthermore 24h following stress exposure the mRNA levels of many different

proteins were found to be modulated in different brain regions [46, 47, 49-51]. The 12h is an

intermediate between the 3h and 24h time points.

Data obtained from genome wide expression profiling of the hippocampus indicated

that mice exposed to chronic restraint stress exhibit a differential gene expression profile and

differing biological processes compared to the non-stressed controls (Figures 1 and 2). We noted

that amylase 1 (Amy 1) mRNA expression was down regulated with chronic stress. This is in

agreement with chronic restraint stress performed in rats where amylase activity decreased in

response to chronic stress [52].

We sought to uncover biomarkers that could potentially be used as targets for

therapeutic intervention for stress. We compared gene expression data in the prolonged

restraint stress groups (exposed) relative to a control mice (basal levels) and ranked the

microarray probes on the basis of fold changes using a method described previously [43]. A

candidate target approach was performed to query these top ranked probes and a series of

mRNA were selected for further analyses. The criteria for selection required differential

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expression in the chronic stress model that the mRNA in question was promising as a drug

target. We utilized an alternative microarray platform and designed qPCR assays to further

examine the expression patterns of these selected mRNA targets. In addition we examined these

mRNAs in a rat model of chronic stress. This approach revealed that the following mRNAs, Ttr,

Tac1, Gh and Gpr88, represented the optimal biomarkers for chronic stress exposure.

The transthyretin mRNA encodes the primary transporter of vitamin A and thyroid

hormones in plasma and cerebrospinal fluid [53]. The link between TTR and stress has been

observed previously. However the experimental data generated to date does not clarify the

exact role of this protein in stress responses. It has been observed that both acute and chronic

psychosocial stress increased Ttr expression in liver, choroid plexus and CSF [54]. The same

increase was observed with glucocorticoids [54]. On the contrary Ttr levels were decreased in

the mouse cortex after chronic restraint stress [32]. In the hippocampus, chronic mild stress

exposure down regulated Ttr [55]. A similar trend was noted in the hippocampus following

chronic restraint stress [30]. In contrast we observed an upregulation of Ttr in the hippocampus

following restraint stress. Even if the stress protocols were different in the two previous studies

it should be noted that the application of the stressful conditions were both more protracted

than in our study, 2 hours for 15 days in the case of restraint stress study and 15 days for the

chronic mild stress.

One possibility is that the upregulation that was observed in the present study could

represent an anti-depressant adaptive response to counteract the effect of stress at this time

point. In fact a restraint stress regimen of 2 h/day for 10 days [56] or 6 h/day for 7 days [57]

does not induce depression-like behavior as measured by forced swimming test. Conversely the

effect of prolonged stress on the depressive-like behavior is evident after 14 days of restraint

[57]. Many others lines of evidence point to a link between TTR and depression but, similar to

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stress, the role and the direction of change of TTR expression in depressive-like status is yet not

clear. Transthyretin levels are lower in depressed patients [58-60]. However mice lacking the Ttr

gene, showed reduction in depressive like behavior [61]. Interestingly upregulation of Ttr has

been observed in rodents following administration of the histone deacetylase inhibitor sodium

butyrate that possesses antidepressant-like effects [62]. Additionally Ttr is up regulated by

tricyclic antidepressant treatments [63]. A different picture is generated however from the

observation that the mood stabilizer lithium, used in bipolar disorder, decreases the expression

of the Ttr gene [64]. These results have demonstrated the involvement of TTR in depressive-like

states. However TTR levels are greatly dependent on the conditions of the study. Moreover it

still remains to be clarified if TTR levels are causal for, or the result of depressive like states.

Taken together these data suggest that the Ttr gene represents a molecular response to chronic

stress and may function in the development of depression.

A search of the Drug-Gene Interaction database yielded a drug-gene interaction for Ttr

[44]. Two compounds ALN-TTR01/ DCL001138 (Alnylam Pharmaceuticals) and ISIS-TTR/

DCL001204 (Isis Pharmaceuticals) interact with TTR, both of which were developed to treat

Transthyretin Amyloidosis, a genetic condition in which the patient has a defective TTR protein

which leads to tissue damage and familial amyloid cardiomyopathy and polyneuropathy. These

compounds may have utility as potential therapeutics for the treatment of chronic stress.

Tac 1 mRNA expression was up-regulated 3h following chronic restraint treatment and

was down-regulated at subsequent time points. It encodes substance P, neurokinin A,

neuropeptide K and neuropeptide gamma which represent four tachykinin peptide family

members. Substance P (SP) and its receptor (neurokinin 1 receptor, NK1R) have been implicated

in the mediation of stress-related, affective and/or anxious behavior [65]. Firstly, brain regions

that play functional roles in stress, fear and affective responses (including hippocampus,

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hypothalamus, amygdala and cingulate cortex) express SP and NK1R mRNAs. Secondly, stressful

conditions alter the SP content in these regions producing fear related behaviors [66, 67].

Additionally the SP/NK1R system functions as neurotransmitters (like serotonin and

noradrenaline (norepinephrine) which mediate stress, mood and anxiety responses. Previous

studies have revealed that mice lacking the Tac1 gene have diminished depression and anxiety

following the application of specific challenges [68]. Therefore, it has been hypothesized that

blockage of NK1R might exhibit anxiolytic in addition to antidepressant effects [65].

Amongst the targets we selected Tac1 is the only one that was up regulated at the 3h

time point and subsequently down regulated following chronic restraint treatment. This

behavior may be in part explained by the biophysical properties of substance P/neurokinin 1

receptor (SP/NK1R) system which regulated the HPA axis. Previous studies have demonstrated

that SP increases corticosterone release and the expression of corticotropin-releasing factor-1

receptor 1 (CRF1R) [69, 70]. NK1R KO mice exhibited decreased anxiety behaviors and increased

corticosterone release following stress exposure [71]. However blockage of NK1R increased

adrenocorticotropic hormone (ACTH) and CRF release [72], while its activation decreased ACTH

release [73]. Interestingly, in this study, the effects of NK1R antagonist can be observed in non

stressed animals indicating a tonic suppression of HPA axis by SP/NK1R. Collectively this

suggests a biphasic regulation of HPA axis by SP/NK1R that depends on the state of the system

inhibiting HPA activity in non stressed animals while enhancing it when a stressful condition

occurs. Thus the down regulation of Tac1 observed in our study 12 and 24 hours after the last

restraint can be interpreted as a potential mechanism to counteract the effects of stress, since

the down regulation of SP/NK1R could increase HPA axis activity. On the other hand our data

suggest also that 3h after the last stressor the SP/NK1R system undergoes the effects of stress

with an up regulation that can at least initially, decrease the HPA axis response.

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GH is synthesized primarily in the pituitary but also in the hippocampus and other brain

regions [74, 75]. In the hippocampus GH is primarily involved in synaptic plasticity [76-78]. Work

to date has shown that hippocampal GH is regulated by exposure to stressful conditions [79]

and that the glucocorticoid stress hormones modulate GH mRNA expression [80]. Recent data

demonstrated that chronic stress down regulated GH in the hippocampus together with

impairment of several hippocampus-dependent functions. Interestingly restoration of

hippocapampal GH levels led to the recovery of stress-induced functional impairment [81]. Our

data fits well with this picture since we also observed GH downregulation induced by chronic

restraint stress. This suggests that pharmacological intervention aimed to restore GH levels after

stress could help to prevent some of the damage caused by the repeated application of stressful

stimuli.

It is compelling, from a pharmacotherapeutics perspective, that one of the proteins

regulated by chronic stress is GPR88, an orphan GPCR. GPR88 shows a high degree of homology

to receptors of biogenic amines, namely 5HT1D and the beta 3 adrenergic receptor. Initially

GPR88 was believed to expressed solely in the striatum [82], however recent evidence shows

that is also expressed in the locus coeruleus, nucleus acccumbens, cerebral cortex, thalamus,

hypothalamus and hippocampus [83, 84]. GPR88 has been linked with psychiatric illness

including depression and bipolar disorder. Lithium, as already noted, is used in the management

of bipolar disorder and increases Gpr88 levels in rat cortical slices while inositol, which is

involved in the therapeutic action of lithium, decreases gpr88 transcript levels [85]. Moreover a

study found that methamphetamine, an inducer of bipolar disorder symptomatology, and

valproate a mood stabilizer used in the treatment of bipolar disorder, both up regulated Gpr88

[86]. Finally electro-convulsive therapy and sleep deprivation (both of which are well established

behavioral antidepressant treatments) and pharmacological treatment with fluoxetine affected

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the expression of Gpr88 in the hypothalamus. The behavioral treatments both caused down

regulation of Gpr88 whereas fluoxetine increased Gpr88 transcript expression. Interestingly

Gpr88 was amongst the limited number of mRNAs impacted by all the treatments [83] .

Taken together all this data suggest that Gpr88 expression is associated with several

psychiatric conditions and primarily bipolar disorder. Our data showed that Gpr88 was up

regulated following exposure to chronic stress. This suggests that chronic stress could affect the

neurobiological substrates that are associated with psychiatric illnesses such as depressive-like

states and that targeting such substrates could represent a possible therapeutic intervention in

the path that leads from repeated stressful conditions to more serious and invalidating diseases.

A limitation of this study was that the biomarkers were uncovered solely via genomic

and bioinformatics analyses. Another limitation is the fact that this work was carried out using

an inbred mouse strain which may not be entirely reflective of the genetic variation observed

with human populations. The small size of the hippocampus tissues and cost considerations

required pooling of three individual samples for microarray analyses. However three biological

replicates were examined for each of the stress time points tested which controlled for

experimental variables and potential technical variations in the pooling procedure. Future

studies will examine expression profiles in hippocampal subregions, the three cornu ammonis

regions (CA1, 2 and 3) and the dentate gyrus (DG) and explore the effects of chronic stress

regimens that are longer than seven days.

Conclusion & Future Perspective

In summary the genome wide expression data and systems level analysis reported here

revealed key hippocampal biomarkers associated with exposure to chronic stress in two

independent rodent models. We uncovered several biomarkers that suggest parallel avenues

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through which negative outcomes could be mediated. These biomarkers for chronic stress

exposure and adverse outcomes can be further investigated in animal and human models. This

will be the subject of future work.

Financial and competing interests

The authors have no affiliations or financial involvement with any organization or entity

with a financial interest in or financial conflict with the subject matter or materials discussed in

the manuscript. No writing assistance was utilized in the production of this manuscript.

Ethical conduct of research

The authors state that they have obtained appropriate institutional review board

approval or have followed the principles outlined in the Declaration of Helsinki for all human or

animal experimental investigations.

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Acknowledgements

We thank J Lapira, J Sprague and M Harabaglia at the UCSD Biomedical Genomics

Facility for assistance with microarray experiments and N Lekmine and Dr. R Šášik for help with

microarray data analysis. ER, LP, GS, SF and AR were recipients of training grants from The

Campus World Program. MU and RC acknowledge support by the European Community: "To

Spread Bioinformatic Knowledge applied to Functional Genomic” Program MTKD-CT-2004-

509242, by FIRB/LITBIO Laboratory for Interdisciplinary Technologies in Bioinformatics and FIRB

2003: “Sviluppo ed applicazione di tecnologie altamente innovative ed efficienti per la sintesi di

nuove molecole con dimostrazione della loro attivita' biologica su proteine di membrana

implicate nel danno cerebrale” (RBNE03YA3L). GH gratefully acknowledges support from NIH

grants DK063491, CA023100 and DK080506. No writing assistance was utilized in the production

of this manuscript.

21

Table S1

The oligonucleotide probe sequences for qPCR and the corresponding amplicon sizes are given.

Figures

Figure 1

Information clustering of significant biological process and cellular component terms

in the hippocampus from the comparison of control and mice exposed to acute or

chronic stress at 3h, 12h and 24h. Numbers in parentheses are the number of

expressed genes in the process and adjusted p-value (Bonferroni adjusted p-value <

0.01). The shade of the red color is proportional to (log) p-value; a darker color indicates

greater significance.

Figure 2

Hippocampal gene expression profiling of mRNAs in mice exposed to chronic stress at

3h, 12h and 24h. Hippocampal tissues were collected 3h, 12h and 24h following the

final stress exposure. The control samples were hippocampal tissues from mice not

subjected to the restraint stress. Fold changes were calculated from log2 ratios

between the array probe signal in the control or exposed mice. The log2 ratio was

calculated for each probe from three biological replicates using the median value.

Following this the probes were ranked in descending order of the sum-squared statistic

(i.e., sum of squares of log2 ratios across the chronic time course). The top 100 altered

22

probes were chosen for inclusion in the heat map. The difference in colors is between -

4.1-fold and +4.1-fold and maintains qualitative relationships amongst the individual

values. All fold changes outside of this range have been truncated to ± 4.1. Genes

mentioned in the text are noted in blue text.

Figure 3

Gene expression profiling of selected targets in mouse hippocampus in response to

prolonged restraint stress using Applied Microarrays/Codelink Bioarrays. Gene

expression changes were investigated in mice exposed to chronic restraint stress for the

following targets (Gpr88, Tac1, Gh, Arc, Ttr, Clk1 and Gnaq). The mRNA level fold

changes for the selected targets observed between chronic stress and reference mice

are depicted as a heat map. The log2 ratio for each gene is defined as the mean value of

all representations of that gene across independent data points from three microarrays.

Figure 4

Gene expression profiling of selected targets in rat hippocampus, amygdala and cortex

in response to prolonged restraint stress using the Affymetrix Rat Genome U34A chip.

Gene expression changes were investigated in rats exposed to chronic restraint stress

for the following targets (Gpr88, Tac1, Gh, Arc, Ttr, Clk1 and Gnaq). Hippocampal,

amygdal and cortex tissues were examined from rats under basal and stressful

conditions. The mRNA level fold changes for the selected targets observed between

prolonged stress and reference rats are shown as a heat map. The log2 ratio for each

23

gene is defined as the mean value of all representations of that gene across three

independent Affymetrix chip data points. The color differential is between -4-fold and

+4-fold and maintains qualitative relationships amongst individual values. Fold changes

that are outside of this range have been truncated to ± 4.

Figure 5

Real Time qPCR Gene expression analysis of selected targets in mouse hippocampus in

response to chronic stress. Gene expression changes were examined in mice exposed to

both acute and chronic restraint stress for the following targets (Gpr88, Tac1, Gh, Arc,

Ttr, Clk1, Gnaq, Jph4, Sgk1). The mRNA level fold changes for the selected targets

observed between stress and reference mice for the chronic and acute studies are

depicted as heat maps. The fold change was obtained from the mean log2 ratio

between three mice exposed to stress and three control mice (and is based on triplicate

technical measurements). The color differential is between -4-fold and +4-fold and

maintains qualitative relationships amongst individual values. Fold changes that lie

outside of this range have been reduced to ± 4.

24

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