Gene expression profiles highlight adaptive brain mechanisms in corticotropin releasing factor overexpressing mice

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Molecular Brain Research

Research report

Gene expression profiles highlight adaptive brain mechanisms in

corticotropin releasing factor overexpressing mice

Pieter J. Peetersa, Frederik L.P. Fierensa,*, Ilse van den Wyngaerta, Hinrich W. Goehlmanna,

Sigrid M. Swagemakersa, Stefan U. Kassa, Xavier Langloisa, Shirley Pullana,

Mary P. Stenzel-Pooreb, Thomas Stecklera

aJohnson and Johnson Pharmaceutical Research and Development, Turnhoutseweg 30, B-2340 Beerse, BelgiumbDepartment of Molecular Microbiology and Immunology, Oregon Health Sciences University, Portland, OR, USA

Accepted 12 June 2004

Available online 27 August 2004

Abstract

Corticotropin-releasing factor (CRF) plays an important role in mediating central and peripheral responses to stress. Alterations in CRF

system activity have been linked to a number of psychiatric disorders, including anxiety and depression. Aim of this study was to elucidate

homeostatic mechanisms induced by lifelong elevated CRF levels in the brain. We therefore profiled gene expression in several brain areas of

transgenic mice overexpressing CRF (CRF-OE), a model for chronic stress.

Several genes showed altered expression levels in CRF-OE mice when compared to their wild type littermates and were confirmed by

quantitative PCR. Differences in gene expression profiles revealed the presence of previously unrecognized homeostatic mechanisms in

CRF-OE animals. These included changes in glucocorticoid signaling, as exemplified by changes in 11h-hydroxysteroid dehydrogenase type1, FK506 binding protein 5 and serum/glucocorticoid kinase. Alterations in expression of genes involved in myelination (myelin, myelin-

associated glycoprotein), cell proliferation and extracellular matrix formation (Edg2, Fgfr2, decorin, brevican) suggest changes in the

dynamics of neurogenesis in CRF-OE. Pronounced changes in neurotensin (NT) receptors 1 and 2 mRNA were identified. Overall

downregulation of NT receptors in CRF-OE animal was substantiated by receptor binding studies. Pronounced neurotensin receptor

downregulation was observed for NT type 1 receptors in limbic brain areas, suggesting that NT could be implicated in some of the effects

attributed to CRF overexpression.

These data show that lifelong exposure to excessive CRF leads to adaptive changes in the brain which could play a role in some of the

behavioral and physiological alterations seen in these animals.

D 2004 Elsevier B.V. All rights reserved.

Theme: Neurotransmitters, modulators, transporters, and receptors

Topic: Signal transduction: gene expression

Keywords: CRF; Transgenic; Glucocorticoid; Neurotensin; Spectral map analysis; Microarray; Receptor autoradiography; Quantitative PCR; R121919

0169-328X/$ - s

doi:10.1016/j.m

Abbreviation

factor; CRF-OE

protein-coupled

like 1; Hsd11B1

Ntsr2, neurotens

of microarray da

* Correspon

E-mail addr

129 (2004) 135–150

ee front matter D 2004 Elsevier B.V. All rights reserved.

olbrainres.2004.06.038

s: ACTH, adrenocorticotropin hormone; Bdnf, brain-derived neurotrophic factor; CNS, central nervous system; CRF, corticotropin releasing

, CRF overexpressing mice; CRF1, CRF receptor subtype 1; CRF2, CRF receptor 2; Edg2, endothelial differentiation lysophosphatidic acid G-

receptor 2; Fgfr2, fibroblast growth factor receptor 2; Gab1, growth factor receptor bound protein 2-associated protein 1; Hpcal1, hippocalcin

, 11h-hydroxysteroid dehydrogenase 1; Id2, Inhibitor of DNA binding 2; Klk, kallikrein; NT, Neurotensin; Ntsr1, neurotensin receptor 1;

in receptor 2; Ntsr3, neurotensin receptor 3; PVN, periventricular hypothalamic nuclei; R, treated with compound; SAM, significance analysis

ta; Sgk, serum/glucocorticoid regulated kinase; SPM, spectral map analysis; U, untreated; Ve, treated with vehicle only; WT, Wild-type

ding author. Tel.: +32 14 60 78 60; fax: +32 14 60 37 53.

ess: [email protected] (F.L.P. Fierens).

P.J. Peeters et al. / Molecular Brain Research 129 (2004) 135–150136

1. Introduction

Corticotropin-releasing factor (CRF) plays an impor-

tant role in the mediation of the central and peripheral

responses to stress. Alterations in CRF system activity

have been linked to a number of psychiatric disorders,

including anxiety and depression [21]. In line with a role

of brain CRF in the mediation of endocrine, autonomic

and behavioral responses to stress, transgenic mice

overexpressing CRF (CRF-OE) have been reported to

show increased anxiety-related behaviour, cognitive

impairments and an increased HPA axis activity in

response to stress, at least part of which can be

attenuated by central administration of a CRF antagonist

[43,44,48,49].

Sustained exposure of an individual to stress or high

levels of CRF decrease CRF binding sites [3,11,14],

desensitize CRF-stimulated cyclic AMP accumulation,

and decrease ACTH release by corticotrophs [1,15].

Treatment of anterior pituitary cells or AtT20 cells with

CRF causes large reductions in CRF-stimulated ACTH

release resulting from downregulation of CRF receptors 1

(CRFR1) and desensitization of CRFR1 stimulated cAMP

stimulation [20,35]. Likewise, central administration of

CRF can induce a number of adaptive changes in the

brain, including changes in CRF receptor expression in

various brain areas [3].

One possibility to investigate the long-term effects of

alterations of CRF system activity on compensatory brain

mechanisms is the assessment of gene expression profiles

using microarray technology. Comparing the mRNA

expression patterns from the whole brains of mice lacking

a functional CRFR1 to that of mice that had received 40

mg/kg of the CRFR1 antagonist R121919 administered

orally for 0, 1 or 7 days, alterations in gene expression

seen in the knockout mice were reported to mimic sub-

chronic (7-day) treatment with the CRFR1 antagonist

[23].

More recently, we studied the effects of acute CRF

exposure and of blockade of the CRFR1 with R121919

in mouse pituitary AtT-20 cell cultures. Microarray

analysis of 7256 genes revealed altered gene expression

in about 90 genes that was attenuated by the antagonist.

Known targets of CRFR1 receptor signaling that were

altered included immediate early genes such as Jun/B,

Nurr1, and Nurr77. Moreover, several previously

unknown targets involved in this signaling cascade were

identified and subsequently confirmed by quantitative

PCR [57].

To investigate the long-term effects of CRF over-

activity and the adaptive mechanisms that may exist to

compensate for the life-long exposure to elevated levels

of CRF in vivo, the present study investigated the

gene expression profiles in different brain regions in

CRF overexpressing transgenic mice using microarray

technology.

2. Material and methods

2.1. Animal housing and treatment

Male transgenic CRF overexpressing C57BL/6J mice

(CRF-OE) and their wild-type littermates (WT) were

maintained in a specific pathogen-free facility that meets

all national and European requirements for animal care.

Transgenic animals were generated as previously described

by Stenzel-Poore et al. [43]. Experiments were approved by

the ethical committee on the use of transgenic animals.

Animals were housed individually 4 weeks before the start

of the experiment in a climate-controlled animal colony with

a 12-h light–dark cycle (lights on 7:00 EST) with food and

water ad libitum. Prior to treatment, 3-month-old mice were

randomized over three groups, each comprising 7 wild-type

and 7 transgenic animals. One group received no treatment

(U), a second group received subcutaneous vehicle injec-

tions over 5 days, 2 times per day (10% cyclodextrine) (Ve)

and a third group received 10 mg/kg of the specific CRFR1

receptor antagonist 3-[6-(dimethylamino)-4-methyl-pyrid-3-

yl]-2,5-dimethyl-N,N-dipropyl-pyrazol o[2,3-a]pyrimidin-7-

amine (R121919) (R) [17]. Sixteen hours after the last

treatment, animals were sacrificed by decapitation. Brains

from 4 animals of each group were dissected for RNA

isolation. The brains of the three remaining animals of each

group were further used for ex vivo radioligand binding

studies.

2.2. Hormonal assays

Trunk blood was collected in ice-cooled microtainer cups

containing K2EDTA (BD, Erembodegem-Aalst, Belgium).

Plasma was separated by centrifugation (3000 rpm for 10

min). Aliquots were stored at �80 8C (adrenocorticotropin

hormone (ACTH) in the presence of aprotinin) and at �20

8C (corticosterone) until assayed. Plasma ACTH and

corticosterone levels were measured in duplicate using

double antibody radioimmunoassays (ICN Biomedicals,

Asse, Belgium) following the manufacturers instructions.

2.3. RNA preparation

Brain tissue was homogenized in Trizol (Invitrogen Life

Technologies, Merelbeke, Belgium) using an Ultra-turrax

T25 grinder (IKA-Labortechnik, Staufen, Germany). Total

RNA was extracted according to the instructions of the

manufacturer. Total RNA was further purified using the

RNeasy kit (Qiagen/Westburg, Leusden, The Netherlands)

with DNAse I treatment on the column.

2.4. Microarray hybridization

cRNAwas prepared as follows: Reverse transcription was

performed on 10Ag of total RNA for 1 h at 42 8C using a T7-

oligo(dT)24-primer and SuperscriptII RT (Invitrogen Life

P.J. Peeters et al. / Molecular Brain Research 129 (2004) 135–150 137

Technologies). Second strand cDNA synthesis was done for

2 h at 16 8C using Escherichia coli DNA Polymerase I, DNA

ligase and RNAseH (Invitrogen Life Technologies). After

phenol–chloroform extraction using phase-lock gel (Eppen-

dorf, Hamburg, Germany), in vitro transcription was

performed for 6 h at 37 8C using the Bioarray high-yield

RNA transcript labeling kit with Biotin labeled ribonucleo-

tides (Enzo Diagnostics, Farmingdale, NY). cRNA samples

were purified on Qiagen RNeasy columns followed by

fragmentation for 35 min at 95 8C. cRNA yields were

between 50 and 100 Ag. Samples were processed on

GeneChips (Affymetrix, Santa Clara, CA). In order to check

the quality of each sample, 5 Ag of labeled cRNAwas run on

Test2-arrays. Actual experiments were performed on Murine

Genome U74Av2 arrays, containing probe sets interrogating

approximately 12,000 full-length mouse genes and

expressed sequence tag clusters from the UniGene database

(Build 74). Hybridization was performed using 15 Ag cRNAfor 16 h at 45 8C under continuous rotation. cRNA from

individual animals were processed on separate arrays. No

material was pooled. Arrays were stained in Affymetrix

Fluidics stations using Streptavidin/Phycoerythrin (SAPE)

followed by staining with anti-streptavidin antibody and a

second Streptavidin/Phycoerythrin staining. Subsequently,

fluorescent signal bound to the microarray was measured

with an HP-Laserscanner and data were analyzed with the

Microarray Suite Software (Affymetrix). No scaling or

normalization was performed at this stage.

2.5. Data analysis and selection of genes

2.5.1. Normalization

Genes which were called absent (non-reliable detection)

in all samples according to Affymetrix’ MAS 5.0 software

( p-value of N0.06) were removed from further analysis.

Raw fluorescence intensities from each array were log-

transformed and data were quantile normalized using the

method described by Amaratunga and Cabrera [2]. Follow-

ing the group-wise quantile normalization per treatment and

genotype, a second quantile normalization was carried out

across the data of all samples of a given brain area.

Basically, this alignment sets the average intensity range of

one array to the average measured across all arrays,

compensating for array-to-array variations in hybridization,

washing and staining, ultimately allowing a reasonable

comparison between arrays.

2.5.2. Spectral map analysis

Visual inspection of overall changes in gene expression

profile between different treatment groups was done using

spectral map analysis. Spectral map analysis [25] (or SPM)

is a special case of multivariate projection methods that

help to reduce the complexity (dimensions) of highly

dimensional data (n genes vs. p samples). This so-called

unsupervised method allows the reduction of the complex-

ity of large microarray datasets and provides means to

visually inspect and thereby identify clusters of genes and/

or subjects in the data. Typically, projected data are

displayed in a biplot combining genes and samples in the

same plot. Multivariate projection methods are based on a

derived space with k orthogonal axes. These k axes are

linear combinations of the p original measurements

(intensities) on the n genes. The axes are constructed in

such a way that the first axis lies in the direction (in the

multivariate data space) with the largest variability and the

last axis in the direction with the smallest variability. In

conventional principal component analysis the first axis

(principle component) that maximizes the variability is

often related to the size of the intensities. Clusters that can

be identified based on the first axis will simply differ in

absolute size of the intensities. In spectral map analysis of

log-transformed data, the distances between objects are

proportional to ratios of genes or samples.

In microarray data, we are mainly interested in contrasts

and not in simple high or low intensities. For that reason

SPM has the appropriate properties (double centering) that

remove the size component from the data. SPM will look for

contrasts in intensities between genes without the nuisance

effect of the absolute values of the intensities. Microarray

data tend to be more reliable with increasing intensity.

Therefore, re-introduction of the size component via

variable weighting proportional to the mean intensities of

genes and samples is required. A biplot [6] created by the

first two axis displays the maximal separation of both the

genes and the samples. Coinciding clusters of samples and

genes on the biplot indicate the genes (signatures) that are

responsible for the separation of the samples. Genes that are

located in the general direction of a sample on the biplot

should be looked at as potential signatures for the separation

of that sample vs. the others. Since, in micro-array data there

is a large difference in row- and column-dimension, an

asymmetric factor scaling is recommended in constructing

the biplot. This operation pulls the genes away from the

center of the biplot, while leaving the samples at their

original places [54]. The method was carried out in R

(version 1.6.1) using the functions described by Wouters et

al. [54] (http://users.pandora.be/luc.wouters/spm.htm). R is

an open source implementation of the statistical program-

ming language S (http://www.r-project.org).

2.5.3. Significance analysis

Individual genes with a different expression level

between groups were identified using significance analysis

of microarray (SAM) data [47]. SAM assigns a score to each

gene on the basis of change in gene expression relative to the

standard deviation of repeated measurements. For genes with

scores greater than an adjustable threshold, SAM uses

permutations of the repeated measurements to estimate the

percentage of genes identified by chance; i.e., the false

discovery rate (FDR). Thus, the FDR is the expected

proportion of false positives amongst the tests found to be

significant. An extension of this FDR is the so-called q-value

http://users.pandora.be/luc.wouters/spm.htm

http://www.r-project.org

http://users.pandora.be/luc.wouters/spm.htm

http://www.r-project.org

Table 2

Quality parameters for the microarray experiment

Area Present calls 3V/5Vh-Actin 3V/5VGAPDH

Temporal area 46.15F1.98% 1.96F0.53 1.46F0.38

Hippocampus 46.27F1.89% 1.58F0.39 1.22F0.29

Cerebellum 47.14F2.13 1.67F0.37 0.97F0.08

Frontal cortex 44.68F2.23 1.85F0.39 1.29F0.26

Nucleus accumbens 44.27F2.11 2.69F0.85 2.52F1.20

Pituitary 45.33F1.67 1.53F0.28 1.25F0.21

Table 1

Sequence of oligonucleotides used for quantitative PCR

h-Actin forward 5V-CATCTTGGCCTCACTGTCCAC-3Vh-Actin probe 5V-TGCTTGCTGATCCACATCTGCTGGA-3Vh-Actin reverse 5V-GGGCCGGACTCATCGTACT-3VCRF2 forward 5V-GGGAGAACAGAAGCGCCTG-3VCRF2 probe 5V-AGAAGGGTGAGGATCCCCCAAATCAGAGT-3VCRF2 reverse 5V-CCCTTGTTTCAATCACTCCCA-3VCRF1 forward 5V-TTTCTGAACAGTGAGGTCCGC-3VCRF1 probe 5V-CCGGAAGAGGTGGCGGCGA-3VCRF1 reverse 5V-GGGCTCTGATGGAGTGCTTG-3VNtsr1 forward 5V-CGCCGCCGAAAGAAGAG-3VNtsr1 probe 5V-CCAACGTTCTCCAGGAAGCCAAACAG-3VNtsr1 reverse 5V-ACGCATGGTTGCTGGACAT-3VNtsr2 forward 5V-TGGTGACCAACACGCTCTTCT-3VNtsr2 probe 5V-TCAGCTCGGCAGTGACCCCA-3VNtsr2 reverse 5V-AGGAAGACACGGCGTTGTAGA-3VNtsr3 forward 5V-GGAAGCCGGAGAACAGCAA-3VNtsr3 probe 5V-TGCGACGCTACCGCAAAGAACA-3VNtsr3 reverse 5VGGATATGAAGGCTGCACTCGTT-3VSgk forward 5V-TGGACCAATGCCCCAGTT-3VSgk probe 5V-TCAGTCAAAGCCGTTGGTGTTTTCATTG-3VSgk reverse 5V-GCCCGTTTTATAGGTGACATTTTAA-3VHsd11b1 forward 5V-GGGATAATTAACGCCCAAGCTT-3VHsd11b1 probe 5V-CCCAAGGAGGAGTGCGCCCT-3VHsd11b1 reverse 5V-AGAGCTGTGCCTTTGATGATCTC-3V


introduced by Storey and Tibshirani [45]. This q-value is

similar to the well-known p-value. It gives each hypothesis

test a measure of significance in terms of a certain error rate.

The p-value of a test measures the minimum false positive

rate that is incurred when calling that test significant.

Likewise, the q-value of a test measures the minimum false

discovery rate that is incurred when calling that test

significant. Whereas the p-value is commonly used for

performing a single significance test, the q-value is useful for

assigning a measure of significance to each of many tests

performed simultaneously, as in microarray experiments. A

10% threshold is accepted practice for array data analysis (as

applied for pituitary data). However, deviation of this rule of

thumb can be made when number of significantly changed

Fig. 1. HPA-axis parameters in animals used for microarray analysis. Plasma cortic

( pb0.001). No significant differences were observed in ACTH levels. Data presen

U, untreated; Ve, vehicle-treated; R, R121919-treated; WT, wild type.

genes is limited. Therefore, a q-value below 20% was used in

all other datasets (see http://faculty.washington.edu/~jstorey/

qvalue/manual.pdf).

2.6. Quantitative RT-PCR

Microarray data were confirmed using real time PCR

analysis. First strand cDNA synthesis was performed on

0.5 Ag total RNA using random hexamer primers and

SuperscriptII RT (Invitrogen Life Technologies). Quantita-

tive PCR was performed on an ABIPrism 7700 cycler

(Applied Biosystems, Foster City, CA) using a Taqman

PCR kit. Serial dilutions of cDNA were used to generate

standard curves of threshold cycles vs. the logarithms of

concentration for h-actin, CRFR1 receptor, CRFR2 recep-

tor, neurotensin receptor 1 (Ntsr1), neurotensin receptor 2

(Ntsr2), neurotensin receptor 3 (Ntsr3), 11h-hydroxyste-roid dehydrogenase 1 (Hsd11b1) and serum/glucocorticoid

regulated kinase (Sgk). The sequence of the oligonucleo-

tides used for these reactions are given in Table 1. A linear

regression line calculated from the standard curves allowed

the determination of transcript levels in RNA samples from

the different treatment groups at each brain area. Quanti-

tative PCR data were analyzed after natural logarithm

transformation using two-way ANOVA for identification of

genotype and treatment effects. Post-hoc analysis was

performed on non-transformed data using a non-parametric

Wilcoxon/Kruskal–Wallis test.

osterone levels were 6–8 times higher in CRF-OE compared to WT animals

ted are the averageFS.E.M. of 5–7 animals. CRF-OE, CRF overexpressing;

http://www.faculty.washington.edu/~jstorey/qvalue/manual.pdf

http://www.faculty.washington.edu/~jstorey/qvalue/manual.pdf

Fig. 2. Spectral map analysis of microarray data obtained in the pituitary showing the projection of both genes and samples in two dimensions. The axes are

constructed in such a way that the first axis (X-axis, PC1) lies in the direction with the largest over all variability in the data set and the second axis ( Y-axis,

PC2) lies in the direction with the second largest variability. These two axes display the maximal separation of both the genes and the samples. Squares depict

different samples, whereas circles depict genes. The diameter of the highlighted circles corresponds to the average intensity of that gene. A positive association

of a gene with a given sample (i.e., an upregulation of that gene in that particular sample) results in the positioning of both gene and sample on a common side

of the centroid (depicted by a cross). Proximity of squares represent a measure for similarity of samples. Positioning of the samples derived from CRF-OE on

the opposite side of the centroid compared to the WT samples along the X-axis (PC1) indicates that 28% of the variation in gene expression levels is explained

by the genotype of the animals. Genes that contribute largely to the difference between WT and CRF-OE (indicated by their positioning at the extremities of the

graph) are highlighted and depicted by their gene symbol. ucv, unit column-variance scaling; RW, row weight; CW, column weight.


2.7. Autoradiography

[125I]Neurotensin (NT) binding and film radiographs on

brains of adult male transgenic C57BL/6J mice and their

wild-type littermates were performed as described previ-

ously [29]. Twenty-micron-thick sections were incubated

with 0.1 nM monoiodo [125I]Tyr3 neurotensin (2200 Ci/

mmol, Perkin Elmer) in 50 mM Tris–HCl, pH 7.4

containing 0.1% bovine serum albumin, 1 mM EDTA,

Table 3A

Genes altered in hippocampus

Probe set ID Title

Down 93137_at neurotensin receptor 2

94079_at septin 4

103835_f_at hippocalcin-like 1

97867_at hydroxysteroid 11-beta dehydrogenase 1

97061_g_at tyrosine 3-monooxygenase/tryptophan

5-monooxygenase activation protein, theta

103456_at Mus musculus, clone IMAGE:4196918, mRNA

101923_at phospholipase A2, group VII

platelet-activating factor acetylhydrolase, plasma)

102405_at myelin-associated glycoprotein

93496_at homolog of yeast long chain polyunsaturated

fatty acid elongation enzyme

160089_at lysosomal membrane glycoprotein 1

Genes indicated in bold were confirmed with quantitative PCR.a Median arbitrary fluorescence intensity.

5�10�5 M bacitracin, 2 Ag/ml chymostatin and 4 Ag/ml

leupeptin. Incubating additional sections in the presence of

1 AM native neurotensin assessed the non-specific staining.

[125I]NT binding with blockade of the Ntsr2 was achieved

on hippocampal sections in the presence of 1 AMlevocabastine, a Ntsr2 specific ligand. Densiometric

analysis of the film radiographs was performed using an

MCID M4 digital analyzer (Imaging Research, St Cathar-

ines, ON, Canada). On each section, structures were

Fold change Mediana WT Median CRF-OE q-Value (%)

0.46 419 202 13.97

0.51 440 216 13.97

0.52 270 141 13.97

0.57 124 68 13.97

0.57 1071 614 13.97

0.68 81 54 13.97

0.74 147 107 13.97

0.49 159 86 19.56

0.69 261 184 19.56

0.85 1277 1090 19.56

Table 3B

Genes altered in frontal cortex

Probe set ID Title Fold change Median WT Median CRF-OE q-Value (%)

Down 93137_at neurotensin receptor 2 0.41 387 151 14.16

98967_at fatty acid binding protein 7, brain 0.43 82 36 14.16

103835_f_at hippocalcin-like 1 0.48 236 105 14.16

102704_at aquaporin 4 0.49 243 114 14.16



0.56 1026 574 14.16

96672_at homeodomain only protein 0.66 189 123 14.16

95356_at apolipoprotein E 0.68 4317 2993 14.16

160217_at RIKEN cDNA 2310001A20 gene 0.54 55 30 16.53

99041_at TATA box binding protein (Tbp)-associated

factor, RNA polymerase I, B

0.62 70 44 16.53

100566_at insulin-like growth factor binding protein 5 0.62 328 193 16.53

104432_at ras homolog N (RhoN) 0.63 97 61 16.53

95135_at RIKEN cDNA 3110038L01 gene 0.65 279 178 16.53

93496_at homolog of yeast long chain polyunsaturated

fatty acid elongation enzyme

0.66 255 178 16.53

100927_at phospholipid transfer protein 0.66 198 122 16.53

93013_at inhibitor of DNA binding 2 0.71 471 319 16.53

93290_at purine-nucleoside phosphorylase 0.73 85 62 16.53

102296_at proprotein convertase subtilisin/kexin type 2 0.78 527 410 16.53

99052_at zinc finger homeobox 1a 0.81 151 124 16.53

103438_at deiodinase, iodothyronine, type II 0.53 346 174 19.83

92642_at carbonic anhydrase 2 0.53 488 264 19.83

96019_at synaptophysin-like protein 0.63 138 92 19.83

96653_at RIKEN cDNA 0610007O07 gene 0.67 124 84 19.83

98627_at insulin-like growth factor binding protein 2 0.75 150 112 19.83

161294_f_at clusterin 0.85 345 290 19.83

92549_at protein kinase inhibitor, gamma 0.86 336 290 19.83

Genes indicated in bold were confirmed with quantitative PCR.


delineated interactively and pixel gray levels were meas-

ured in the outlined areas. The pixel gray levels were

converted to radioactivity per mg of tissue using the co-

exposed 125I standards and averaged over the measured

area.

The represented values on [125I]NT binding for the

different structures are an average of three animals per

group, with each structure measured at three bregma

sections in triplicate for left and right hemisphere. Data

were statistically analyzed by a two-way ANOVA and

Table 3C

Genes altered in temporal area

Probe set ID Title

Up 93669_f_at SRY-box containing gene 11

97890_at serum/glucocorticoid regulated kinase

92202_g_at ESTs, Highly similar to 2118318A promyelocyte

leukemia Zn finger protein

94297_at FK506 binding protein 5

93346_at phosphoglycerate kinase 1

93077_s_at lymphocyte antigen 6 complex, locus C

Down 93137_at neurotensin receptor 2

97226_at EST

92642_at carbonic anhydrase 2

160714_at growth factor receptor bound protein 2-associated prot

93090_at fibroblast growth factor receptor 2

96948_at quininoid dihydropteridine reductase

162387_f_at mitofusin 1

Genes indicated in bold were confirmed with quantitative PCR.

concomitant Bonferroni’s post-hoc test using SPSS 11.0

software.

3. Results

3.1. Animal treatment and stress hormone levels

CRF-OE animals had plasma corticoserone levels that

were 6–8 times higher than in WT animals (Fig. 1). There

Fold change Median WT Median CRF-OE q-Value (%)

2.60 35 90 9.80

2.32 132 310 9.80

2.24 125 270 9.80

2.17 207 449 9.80

1.32 1153 1527 9.80

1.10 1136 1241 9.80

0.49 874 440 9.80

0.61 240 147 9.80

0.64 1100 723 9.80

ein 1 0.53 134 72 13.57

0.61 437 265 13.57

0.64 1219 843 13.57

0.67 64 44 13.57

Table 3D

Genes altered in nucleus accumbens


Up 93669_ f_at serum/glucocorticoid regulated kinase 2.21 131 296 5.46

97890_at SRY-box containing gene 11 2.39 27 67 14.84

94297_at FK506 binding protein 5 2.02 93 192 14.84

93673_at neurturin 1.64 49 78 14.84

93728_at transforming growth factor beta 1 induced transcript 4 1.64 274 432 14.84

94435_at DNA segment, Chr 10, ERATO Doi 438, expressed 1.44 83 121 14.84

93158_at RIKEN cDNA 9130206N08 gene 1.32 100 134 14.84

104744_at RIKEN cDNA 2610319K07 gene 1.29 120 154 14.84

97472_at ralA binding protein 1 1.10 230 254 14.84

95746_at solute carrier family 25, member 17 1.29 90 114 15.21

93255_at ATPase, H+ transporting, V1 subunit A, isoform 1 1.14 879 1012 15.21

Down 93534_at decorin 0.30 59 16 5.46

100435_at lysophosphatidic acid G-protein-coupled receptor, 2 0.38 89 34 5.46

99071_at macrophage expressed gene 1 0.48 93 45 5.46

97226_at EST 0.50 112 54 5.46

102704_at aquaporin 4 0.51 253 128 5.46

98549_at vitronectin 0.52 53 28 5.46

94079_at septin 4 0.54 399 212 5.46

103571_at leukocyte specific transcript 1 0.54 122 70 5.46



0.61 1228 735 5.46

92770_at S100 calcium binding

protein A6 (calcyclin)

0.63 128 81 5.46

96948_at quininoid dihydropteridine reductase 0.65 630 403 5.46

97985_ f_at Mus musculus, clone IMAGE:3375769,

mRNA, partial cds

0.69 232 157 5.46

101991_at flavin containing monooxygenase 1 0.71 47 33 5.46

102248_f_at calcium/calmodulin-dependent serine protein kinase 0.74 126 95 5.46

98114_at Niemann Pick type C1 0.77 321 241 5.46

99598_g_at guanine nucleotide binding protein, alpha inhibiting 2 0.77 801 612 5.46

103835_f_at hippocalcin-like 1 0.48 316 144 7.42

92642_at carbonic anhydrase 2 0.62 424 270 7.42

160714_at growth factor receptor bound protein

2-associated protein 1

0.63 55 34 7.42

104414_at RIKEN cDNA 0610010K14 gene 0.69 158 114 7.42

98451_at DnaJ (Hsp40) homolog, subfamily B, member 10 0.72 155 114 7.42

102942_at RIKEN cDNA 2810012G08 gene 0.79 76 61 7.42

93379_at dihydropyrimidinase-like 4 0.82 84 68 7.42

95406_at RIKEN cDNA 1810037I17 gene 0.85 962 810 7.42

102120_f_at RIKEN cDNA 1700030C10 gene 0.42 51 21 11.24

97317_at ectonucleotide pyrophosphatase/phosphodiesterase 2 0.54 392 219 11.24

93137_at neurotensin receptor 2 0.62 308 196 11.24

93090_at fibroblast growth factor receptor 2 0.63 202 129 11.24

160464_s_at N-myc downstream regulated 1 0.73 144 107 11.24

103559_at protein kinase, cAMP dependent, catalytic, alpha 0.77 191 143 11.24

95531_at RIKEN cDNA E230009N18 gene 0.81 57 46 11.24

101939_at RIKEN cDNA 2610110L04 gene 0.81 387 318 11.24

100990_g_at integrin beta 1 binding protein 1 0.51 50 25 14.84

93013_at inhibitor of DNA binding 2 0.60 286 169 14.84

161433_f_at phosphatidylinositol glycan, class A 0.69 24 16 14.84

104209_at cysteine and histidine rich 1 0.70 111 81 14.84

96596_at N-myc downstream regulated-like 0.72 229 163 14.84

101834_at mitogen activated protein kinase 3 0.73 101 74 14.84

99668_at bridging integrator 1 0.77 696 535 14.84

103997_at erythropoietin receptor 0.84 51 43 14.84

97240_g_at hypothetical protein MGC6696 0.86 232 198 14.84

160458_at melanoma cell adhesion molecule 0.50 45 20 15.21

92558_at vascular cell adhesion molecule 1 0.56 58 29 15.21

95453_f_at S100 calcium binding protein A1 0.72 299 225 15.21

103542_at hypothetical protein LOC228140 0.75 58 43 15.21

(continued on next page)


Table 3D (continued)


102960_at recombination activating gene 1 gene activation 0.75 126 94 15.21

100005_at Tnf receptor associated factor 4 0.76 51 40 15.21

95502_at sirtuin 2 (silent mating type information

regulation 2, homolog) 2 (S. cerevisiae)

0.77 205 158 15.21

160568_at enolase 1, alpha non-neuron 0.84 1086 897 15.21

97273_at arsenate resistance protein 2 0.87 191 170 15.21


was a tendency for ACTH levels being lower in CRF-OE

animals but this did not reach significance ( p=0.08). A 5-

days treatment with R121919 (last treatment 16 h before

sacrifice) did not result in a significant effect on glucocorti-

coid and ACTH plasma levels.

3.2. Array hybridizations

RNA was isolated from the different brain regions under

investigation. These included pituitary, nucleus accumbens,

frontal cortex, temporal area, hippocampus and cerebellum.

Expression of CRFR1 and CRFR2 was measured in these

brain areas using quantitative PCR (data not shown).

Although CRFR1 was readily detectable, no reliable

measurements could be obtained for CRFR2 in these brain

areas. RNA isolated from different animals was processed

separately per individual animal and per brain region on

Affymetrix murine U74 arrays containing 12,000 murine

expressed sequence tags. Average percentages of present

calls and 3V/5Vratios for h-actin and GAPDH obtained in the

different areas are given in Table 2. Samples with low yields

of RNA or low percentages present calls (number of reliably

detectable probe sets/genes) or deviating 3V/5V ratios were

omitted from subsequent analysis, leaving 3–4 animals per

genotype and treatment.

3.3. Expression profile analysis

After normalization of the data, first pass examination

was performed using spectral map analysis (SPM). This

method allows an overall graphical interpretation of gene

expression responses in relation to the treatment group and

genotype. SPM indicated no gross changes in expression

between treatment groups for all areas except pituitary. In the

SPM biplot shown in Fig. 2, the two axes represent the first

two principle components explaining together 38% of the

variance observed in the pituitary dataset. At the level of the

pituitary a clear difference in overall gene expression pattern

was observed between CRF-OE and WT animals. This is

illustrated by the clustering at opposite sites in the spectral

map of the CRF-OE and WTsamples (depicted by squares in

Fig. 2). Genes (depicted as circles) that do not contribute to

difference between the samples end up around the centroid

(depicted as +) of the biplot. Genes at the periphery of the

biplot on the contrary, contribute significantly to the differ-

ences in expression profiles between samples. This is

exemplified by genes such as kallikreins (Klk9, Klk13,

Klk16 and Klk26) and preproenkphalin A, that clustered

together at the same side of the plot as the CRF-OE samples.

This is an indication for the expression levels of these genes

to be different (i.e., upregulated) in CRF-OE compared to

WT animals. Treatment with the CRFR1 antagonist

R121919 nor vehicle treatment did induce gross changes in

expression profile and did not normalize expression patterns

in CRF-OE relative to those observed in WT animals, as

illustrated by the pituitary SPM (Fig. 2).

In order to identify genes that were significantly

changed, the Significance analysis of microarray (SAM)

data algorithm was applied. In agreement with the SPM,

only a limited number of genes were significantly altered in

most brain areas with only 10 genes being downregulated in

the hippocampus. In the nucleus accumbens, 50 genes were

downregulated, whereas 11 genes were upregulated. Sig-

nificant changes per brain area are summarized in Tables

3A–3E. Recurring changes in expression patterns in several

brain areas can be clustered into a few pathways. These

pathways include glucocorticoid signaling (downregulation

of 11h-hydroxysteroid dehydrogenases type 1 and upregu-

lation of the immunophilin Fkbp5), intracellular calcium

signaling/sensing (alterations in hippocalcin like 1 and

calcyclin), myelination (myelin, myelin-associated glyco-

protein), cell proliferation and extracellular matrix formation

(lysophosphatidic acid receptor (Edg2), growth factor

receptor bound protein 2-associated protein 1 (Gab1),

Inhibitor of DNA binding 2 (Id2), fibroblast growth factor

receptor 2 (Fgfr2), decorin and brevican). Examples of

individual gene expression profiles in different brain areas

and their confirmation by quantitative PCR are shown in

Figs. 3 and 4, respectively.

At the level of the pituitary, 114 genes differed

significantly in their expression between untreated WT

and CRF-OE animals and were more than 2 times up- or

downregulated (see Table 3E). When comparing WT to

CRF-OE animals, 102 genes had a q-value below 10% and

were more than 1.5-fold downregulated in CRF-OE.

Similarly, 180 genes had a q-value below 10% and were

more than 1.5-fold upregulated in CRF-OE. In agreement

with SPM, SAM identified kallikrein genes Klk9, Klk13,

Klk16 and Klk26, but in addition also identified Klk5 and

Klk8 to be significantly upregulated in CRF-OE. The

highest change in expression was observed in the endoge-

nous opioid peptide gene preproenkephalin A (10 times

higher in CRF-OE vs. WT). To a lesser extent also

prodynorphin was affected (2 times higher in CRF-OE vs.

Table 3E

Genes altered in pituitary

Probe set ID Title Fold

change

Median

WT

Median

CRF-OE

q-Value (%)

Up 94516_f_at preproenkephalin 1 11.67 142 1659 0.32

97783_at chemokine (C-C motif) ligand 17 9.52 8 81 0.32

100334_f_at kallikrein 26 7.76 49 374 0.32

101420_at vesicular inhibitory amino acid transporter 7.14 7 69 0.32

100719_f_at kallikrein 16 6.60 67 404 0.32

103362_at prostaglandin E receptor 4 (subtype EP4) 6.35 4 23 0.32

92550_at keratin complex 1, acidic, gene 19 6.00 4 35 0.32

161825_f_at CEA-related cell adhesion molecule 10 5.68 20 113 0.32

94716_f_at kallikrein 9 5.64 50 298 0.32

92917_at matrix metalloproteinase 7 4.93 8 44 0.32

101289_f_at unknown EST 4.80 48 232 0.32

99964_at vitamin D receptor 4.61 8 38 0.32

102693_f_at kallikrein 26 4.52 75 329 0.32

103087_at sulfotransferase family 1A, phenol-preferring,

member 1

4.15 10 44 0.32

103289_at low density lipoprotein receptor-related protein 4 4.11 8 33 0.32

95775_f_at unknown EST 4.04 64 247 0.32

100681_f_at unknown EST 3.98 26 96 0.32

93122_at cysteine-rich secretory protein 1 3.90 17 60 0.32

100061_f_at kallikrein 6 3.89 43 149 0.32

99927_at complement component factor i 3.87 12 46 0.32

100596_at selenium binding protein 1 3.78 21 69 0.32

96134_at deleted in polyposis 1-like 1 3.75 18 68 0.32

96720_f_at parvalbumin 3.64 5 20 0.32

95465_s_at protein distantly related to the gamma subunit family 3.58 50 184 0.32

104497_f_at kallikrein 9 3.50 14 47 0.32

102968_at gamma-glutamyltransferase-like activity 1 3.49 9 34 0.32

93134_at neuronal pentraxin 1 2.97 20 72 1.14

94517_r_at preproenkephalin 1 2.97 36 135 0.32

96828_at glycine N-methyltransferase 2.95 59 171 0.32

95603_at glycine decarboxylase 2.88 26 75 0.32

104697_at ras homologgene family, member J 2.84 14 41 0.32

101637_at CEA-related cell adhesion molecule 10 2.79 24 70 0.32

161637_f_at unknown EST 2.77 23 61 0.32

161361_s_at troponin T1, skeletal, slow 2.75 57 151 0.32

104495_f_at kallikrein 5 2.72 20 54 0.32

96643_at RIKEN cDNA 1600023A02 gene 2.71 125 325 0.32

92546_r_at prostaglandin D2 synthase (brain) 2.70 115 321 1.14

99840_at prodynorphin 2.57 27 61 0.32

102020_at potassium channel, subfamily K, member 3 2.55 10 23 0.32

92426_at transmembrane 4 superfamily member 9 2.54 21 54 0.32

100026_at branched chain aminotransferase 1, cytosolic 2.53 59 143 0.32

95334_at neurotrophic tyrosine kinase, receptor, type 3 2.52 14 33 0.32

93669_f_at SRY-box containing gene 11 2.51 19 47 0.32

97420_at RIKEN cDNA 1300008B03 gene 2.49 17 44 0.32

92199_at signal transducer and activator of transcription 5B 2.47 12 37 3.84

100060_i_at kallikrein 6 2.46 3 11 2.51

96047_at retinol binding protein 4, plasma 2.43 99 232 0.32

95025_at DNA segment, Chr 16, human D22S680E, expressed 2.41 115 292 0.32

96025_g_at S-adenosylhomocysteine hydrolase 2.38 287 682 0.32

96592_at phosphatidylinositol 3-kinase, regulatory subunit, (p85 alpha) 2.38 43 99 0.32

97735_at thyrotropin releasing hormone receptor 2.37 14 33 0.32

103974_at transmembrane protease, serine 2 2.37 15 36 0.32

162174_at unknown EST 2.35 9 21 0.32

94881_at cyclin-dependent kinase inhibitor 1A (P21) 2.35 36 89 0.32

92422_at chromogranin A 2.34 656 1499 0.32

97731_at indoleamine-pyrrole 2,3 dioxygenase 2.33 8 16 0.32

161100_at unknown EST 2.33 12 31 0.32

101191_at double C2, beta 2.32 16 40 0.32

98473_at arginase type II 2.32 11 24 0.32

(continued on next page)


Table 3E (continued)

Probe set ID Title Fold

change

Median

WT

Median

CRF-OE

q-Value (%

Up 92590_at 3-hydroxy-3-methylglutaryl-Coenzyme A synthase 2 2.31 11 24 1.14

93088_at beta-2 microglobulin 2.28 727 1732 0.32

104407_at activated leukocyte cell adhesion molecule 2.27 132 304 0.32


103562_f_at unknown EST 2.26 32 69 2.51

104192_at expressed sequence C77892 2.26 3 9 2.23

101387_at aminoacylase 1 2.26 65 147 0.32

93143_at RIKEN cDNA 1190005I06 gene 2.25 63 126 0.32

104268_at interleukin 6 receptor, alpha 2.24 65 151 0.32

97198_at ATP-binding cassette, sub-family A (ABC1), member 1 2.23 15 32 1.93

102727_at brain derived neurotrophic factor 2.22 58 137 0.32

97834_g_at phosphofructokinase, platelet 2.22 58 121 0.32

102707_f_at serine (or cysteine) proteinase inhibitor, clade A, member 3C 2.21 32 62 0.32

96198_at protein kinase C, zeta 2.20 85 191 0.32

160813_r_at cytochrome c oxidase subunit VIb, testes-specific 2.18 12 26 0.58

160894_at CCAAT/enhancer binding protein (C/EBP), delta 2.17 248 556 0.32

94297_at FK506 binding protein 5 2.16 333 720 0.32

102849_at potassium inwardly-rectifying channel, subfamily J, member 8 2.14 17 38 0.78

102292_at growth arrest and DNA-damage-inducible 45 alpha 2.13 140 283 0.32

93974_at RIKEN cDNA 1300002F13 gene 2.13 42 85 0.32

95290_at corticotropin releasing hormone receptor 1 2.13 39 73 0.32

103721_at nephronectin 2.11 10 24 1.44

104579_r_at striamin 2.10 21 44 0.32

99994_at cell death-inducing DNA fragmentation factor, alpha

subunit-like effector A

2.09 149 322 0.32

102243_at ets homologous factor 2.08 6 12 1.44

99032_at RAS, dexamethasone-induced 1 2.08 122 244 0.78

102335_at potassium channel, subfamily K, member 1 2.07 97 180 0.32

96024_at S-adenosylhomocysteine hydrolase 2.06 211 429 0.32

103503_at phospholipase C, gamma 2 2.03 18 34 0.32

160085_at thiosulfate sulfurtransferase, mitochondrial 2.03 39 80 0.32

104214_at solute carrier family 7, member 8 2.03 43 88 0.32

93975_at RIKEN cDNA 1300002F13 gene 2.02 68 131 0.32


103391_at Mus musculus transcribed sequence 2.01 11 22 0.78

92904_at PR domain containing 1, with ZNF domain 2.01 11 25 0.78

97833_at phosphofructokinase, platelet 2.01 33 65 0.32

Down 97235_f_at apolipoprotein B editing complex 2 0.40 8 3 1.77

93568_i_at Mus musculus transcribed sequences 0.40 75 32 0.32

160522_at DNA segment, human D4S114 0.41 164 67 0.32

93374_at junctophilin 3 0.41 92 38 0.32

95905_at expressed sequence AI118078 0.41 80 30 0.58

103066_at thymidylate kinase family LPS-inducible member 0.42 29 12 1.31

92866_at histocompatibility 2, class II antigen A, alpha 0.42 208 68 0.78

98350_at somatostatin receptor 2 0.43 37 15 0.78

93387_at keratocan 0.44 10 4 1.31

99637_at procollagen, type XV 0.45 38 17 0.32

93569_f_at Mus musculus transcribed sequences 0.46 36 16 1.31

99524_at solute carrier family 8 (sodium/calcium exchanger), member 1 0.46 39 19 1.44

100998_at histocompatibility 2, class II antigen A, beta 1 0.47 71 30 0.78

162204_r_at unknown EST 0.48 36 15 1.44

101054_at Ia-associated invariant chain 0.49 537 202 1.44

99548_at aldehyde dehydrogenase family 3, subfamily A1 0.49 104 53 0.32

93414_at ATP-binding cassette, sub-family B (MDR/TAP), member 1B 0.49 8 4 2.75

96506_at anaplastic lymphoma kinase 0.50 174 92 0.32

103048_at neuroblastoma myc-related oncogene 1 0.50 46 24 1.31


WT). Other interesting observations include upregulation of

brain-derived neurotrophic factor (Bdnf, 2.2 times) and

vesicular inhibitory amino acid transporter (Viaat, 7.1

times).

)

3.4. Alterations in the neurotensin system

Microarray analysis revealed downregulation of neuro-

tensin receptor 2 (Ntsr2) mRNA levels in several brain

Fig. 3. (A) Microarray data for genes implicated in glucocorticoid signaling. Array data showed a downregulation of 11h-HSD1 and Ntsr2 in the hippocampus

(HC) and showing a significant upregulation in the hippocampus of Fkbp5, a modulator of glucocorticoid receptor activation. Sgk was also upregulated in the

temporal area (TC) and frontal cortex (FC). (B) Microarray data for Ntsr2 in cerebellum (CB), temporal area (TA), nucleus accumbens (NA) and frontal cortex

(FC). For other abbreviations, see legend of Fig. 1.

Fig. 4. The downregulation of hippocampal (HC) 11h-HSD1 and Ntsr2 as well as the upregulation of frontal cortical (FC) Sgk in CRF-OE mice observed with

microarray was confirmed by quantitative RT-PCR. In addition, qRT-PCR, established a similar Ntsr2-like downregulation of Ntsr1 in CRF-OE. Two-way

ANOVA on qRT-PCR data revealed a significant effect of vehicle treatment that was abolished by treatment with R121919. For abbreviations, see legend of

Fig. 1.


Fig. 5. [125I]NT binding (0.1 nM, 30 min, RT) to all Ntsr sites as determined by quantitative autoradiography. Data are represented as the average IODFS.E.M.

of three animals determined on at least three different sections each. *: Difference between the genetic groups with pb0.05. AMG, amygdala including central

and medial amygdala nuclei, basolateral and basomedial anterior amygdala; CG2, anterior cingulate cortex; HC-SR, hippocampus-stratum radiatum; RSG,

retrosplenial granular cortex; TC, temporal/parietal cortex; other abbreviations, see legend of Fig. 1.


regions including the hippocampus (�54%) (Fig. 3A), the

nucleus accumbens (�38%) and the frontal cortex

(�59%), but not in the pituitary (Fig. 3B). Although

levels of Ntsr1 mRNA were below the detection limit in

microarray analysis, the observation of Ntsr2 mRNA

downregulation prompted us to investigate the expression

levels of all members of the NT receptor family by

quantitative PCR. Ntsr3 mRNA did not show any change

in expression in any area tested. In contrast, Ntsr1

mRNA was significantly downregulated in CRF-OE, with

the most pronounced effect in the hippocampus (WT vs.

CRF-OE p=0.0019; WT U vs. CRF-OE-U p=0.0433)

(Fig. 4). Quantitative PCR also demonstrated a 67%

downregulation of Ntsr2 mRNA in hippocampus, con-

firming the microarray data (WT vs. CRF-OE p=0.0002;

WT U vs. CRF-OE-U p=0.0209). However, this decrease

was less pronounced than for Ntsr1 mRNA (�82%)

Fig. 6. [125I]NT binding (0.1 nM, 30 min, RT) to Ntsr1 and 3 sites at the level

quantitative autoradiography. Data are represented as the average IODFS.E.M.

Difference between the genetic groups with pb0.001 SNC, substantia nigra pars

when untreated WT animals were put side by side to

their CRF-OE equivalent. Strikingly, Ntsr1 mRNA was

upregulated in vehicle-treated animals (both in CRF-OE

and WT), when compared to untreated animals. R121919

still abolished this increase in expression levels even 16 h

after its last administration.

3.5. Neurotensin binding studies

In order to evaluate the changes in Ntsr1 and Ntsr2

mRNA at the protein level, we assessed the presence of

receptor (Ntsr1–3) by autoradiography of [125I]NT binding

on brain sections. In agreement with array and quantitative

PCR results, autoradiography data demonstrated an overall

(Ntsr1–3), genetically determined downregulation of the

[125I]NT binding capacity in the stratum radiatum bordering

the CA1–CA2 region of the hippocampus (�21.8F3.0%,

of the hippocampus (Ntsr2 sites blocked by levocabastine) determined via

of three animals determined on at least three different sections each. ***:

compacta; other abbreviations, see legends of Figs. 1 and 5.


pb0.05) and the anterior cingulate cortex (�22.2F2.7%,

pb0.05%) in CRF-OE vs. WT animals (Fig. 5). No changes

were seen in the olfactory bulb, nucleus accumbens and

septum.

Blocking of the Ntsr2 receptors by a saturating concen-

tration of levocabastine, unmasked prominent differences in

expression of Ntsr1. Based on the overall [125I]NT binding

data, focus was set on the hippocampal brain sections. A

pronounced downregulation of the [125I]NT binding in the

CRF-OE animals was observed in the stratum radiatum

(�63.8F6.5%, pb0.001%), the retroslenial granular cortex

(�49.4F7.5%, pb0.001%) and the temporal cortex

(�34.8F3.5%, pb0.001%; Figs. 6 and 7).

Although Ntsr1 mRNA levels in the hippocampus of

both WT and CRF-OE vehicle-treated mice were upregu-

lated compared to untreated animals (Fig. 4), no such

alterations were observed in the vehicle-treated animals at

the level of [125I]NT binding (Figs. 5 and 6). Moreover, no

effect was seen after a subchronic administration of

R121919, except for an upward trend in the stratum

radiatum with a p-value of 0.057, almost reaching

significance levels, when both WT and CRF-OE animals

were compared to vehicle-treated animals for their overall

[125I]NT binding capacity (Fig. 5).

Fig. 7. Representative examples of [125I]NT autoradiography on hippo-

campal C57BL/6J mice brain sections with blockade of Ntsr2 with

levocabastine. For abbreviations, see legends of Figs. 1, 5 and 6.

4. Discussion

CRF overexpressing mice represent a model of chronic

pituitary–adrenal activation [43,44]. Although CRF-OEmice

have been studied in great detail from a behavioral and

physiological point of view, insight in cellular pathways

affected by lifelong exposure to CRF is limited. The

expression profiles in the brain areas examined in this study

reveal the presence of previously unrecognized homeostatic

mechanisms in the CRF-OE animals. The presence of CRF

receptors in these brain areas was assessed by quantitative

PCR. The observed expression levels of CRF receptors

correspond with previous reports of high levels of Crfr1

mRNA in cerebellum and frontal cortex and lower levels of

expression of Crfr2 mRNA which is expressed in more

restricted brain area’s and peripherally [5,50].

R121919 did not exert any obvious effects on cortico-

sterone and ACTH secretion both in WT and CRF-OE

animals. This is in agreement with previous human and

animal studies, where basal levels of ACTH remain

unaffected upon treatment with this antagonist [17,22,56].

It has been shown that the HPA axis is not completely shut

down after CRFR1 blockade and reactivity to stress

remains even under conditions of CRFR1 antagonism

[17,34]. This suggests that escape routes to maintain ACTH

release exist, e.g., mediated by vasopressin, and that some

of the basic functions of the HPA axis would not be

hindered by this treatment approach. Similar dosing of

R121919 (10 mg/kg) in CRF-OE animals does however

alter behavior as demonstrated by ameliorated locomotor

activity and enhanced mounting frequency in male CRF-

OE animals [16]. At the level of gene expression however,

no overall effects of 5-day treatment with R121919 were

observed 16 h after the last administration. This suggests

that changes in gene expression induced by prolonged CRF

exposure are not overcome by this treatment regime,

although changes in behavior can be observed. It is

tempting to speculate that whereas the changes in behavior

are the immediate consequence of CRFR1 antagonism, the

changes in gene expression are the consequence of

prolonged HPA axis activation that are not easily overcome

by 5-day treatment.

4.1. Pituitary

Prolonged elevated levels of CRF as present in CRF-OE

are expected to induce major changes in the expression

profiles in the pituitary. Spectral map analysis clearly

demonstrated pronounced differences in expression level

between CRF-OE and their wild-type littermates. The

elevated levels of endogenous opioids (preproenkephalin

A and prodynorphin) in the pituitary of CRF-OE are in line

with the notion that these opioids represent a major

modulatory system in the adaptation of an organism to

chronic stress. A multitude of data supports the attenuating

role of endogenous opiods in response to stress as a


protective action of the organism [10]. Other interesting

findings in the pituitary include the elevation of Bdnf

mRNA levels; one of the most prevalent neurotrophic

factors in the brain [24]. This observation agrees with

previous reports wherein acute and repeated immobilization

stress show increased Bdnf mRNA levels in the pituitary

[12,41].

4.2. Intracellular calcium

Besides these changes in the pituitary, recurring changes

in expression patterns in other brain areas were categorized

into the following pathways: glucocorticoid signaling,

intracellular calcium signaling/sensing, myelination, cell

proliferation and extracellular matrix formation.

Changes in intracellular calcium signaling/sensing were

exemplified by modulation of hippocalcin like 1 (Hpcal1)

expression. Hpcal1 belongs to the neuronal calcium sensor

family of Ca2+-binding proteins that play a role in diverse

processes, including modulation of neurotransmitter

release, control of cyclic nucleotide metabolism, biosyn-

thesis of phosphoinositides and indirect regulation of ion

channels [4].

4.3. Neurogenesis

The changes of expression observed in genes encoding

proteins involved in myelination, cell proliferation and

extracellular matrix formation suggest changes in the

dynamics of neurogenesis in CRF-OE. In support of this

are the changes in expression observed mainly in nucleus

accumbens, involving Edg2, Id2, Gab1 and Fgfr2.

4.4. Glucocorticoid signaling

Tissue glucocorticoid concentrations are determined by

plasma corticosterone levels and by two intracellular 11h-hydroxysteroid dehydrogenases (type 1 and 2) that locally

interconvert active glucocorticoids and inert 11-keto forms.

11h-HSD1, the predominant isoform in the brain, appears to

function predominantly as a 11h-reductase, regenerating

active glucocorticoids from 11-keto forms [53]. Studies with

11h-HSD1 deficient mice demonstrate that the intracellular

regeneration of glucocorticoids by 11h-HSD1 plays an

important role in HPA-axis control [13]. 11h-HSD1 deficientmice show alterations in response to stress and are less

sensitive to exogenous cortisol suppression of HPA activa-

tion, suggesting a diminished glucocorticoid feedback in

these animals [13]. Downregulation of 11h-HSD1 in the

hippocampus of CRF-OE hints towards an altered glucocor-

ticoid feedback in these animals. This idea is further

strengthened by the changes observed in the expression of

the immunophilin Fkbp5 gene. The exchange of Fkbp5 for

Fkbp4 is an important first step in the activation of the

glucocorticoid receptors [7]. In squirrel monkey and New

World primate genera in general, Fkbp5 constitutes a potent

inhibitor of glucocorticoid receptor binding [8,38]. The

observed Fkbp5 induction suggests attenuation of glucocor-

ticoid receptors by Fkbp5 in response to persistent high levels

of circulating glucocorticoids in CRF-OE. A further indica-

tion for an altered glucocorticoid signaling is the upregulation

of serum/glucocorticoid kinase (Sgk) mRNA in the cerebel-

lum, nucleus accumbens and temporal area, as the tran-

scription of the serine/threonine protein kinase Sgk is induced

by glucocorticoids [30,52].

4.5. Neurotensin

Neurotensin (NT), a tridecapeptide, found in numerous

areas of the CNS, exerts a variety of CNS effects including

hypolocomotion, hypothermia, analgesia and reduced food

consumption [26,51]. Three receptors for NT have been

identified (Ntsr1, 2 and 3) [27,28,31]. Glucocorticoids have

been shown to increase NT mRNA expression (+92%) and

NT release (+100%) in primary hypothalamic neuron

cultures and periventricular hypothalamic nuclei (PVN)

[32,39,42]. High NT levels in turn, downregulate Ntsr1 and

Ntsr2 [18]. In addition, hypercortisolism or dexamethasone

administration have been reported to result in Ntsr1 mRNA

downregulation (40–70%) in the PVN [32] and dexame-

thasone decreases [125I]NT binding in primary hypothala-

mic neuronal cultures [40]. In line with this, the Ntsr2

mRNA level was downregulated in several brain regions

including the hippocampus and the nucleus accumbens,

except for the pituitary. Like Ntsr2, Ntsr1 was significantly

downregulated in CRF-OE. This effect was most pro-

nounced in the hippocampus. Reduced [125I]NT binding in

the stratum radiatum of the hippocampus and the anterior

cingulate cortex in CRF-OE confirmed the downregulation

of NT receptors (Fig. 5). When Ntsr2 receptor binding sites

were blocked with the Ntsr2 receptor specific ligand

levocabastine, a dramatic up to 64% downregulation of

[125I]NT binding to the Ntsr1 receptors in the stratum

radiatum of the hippocampus, the retrosplenial granular

cortex and the temporal cortex was observed in CRF-OE

animals. This effect was more pronounced than for the

overall Ntsr1–3 binding, suggesting that Ntsr2 expression

was less affected by CRF overexpression. Although Ntsr3

receptors are also expressed in the characterized regions

[37], the affinity of NT for Ntsr3 is much lower than that for

Ntsr1. In addition, no alterations in Ntsr3 mRNAwere seen

in the quantitative PCR in any of the investigated regions.

Overall these data strongly support the assumption that

[125I]NT binding in these regions is mainly Ntsr1 receptor

related.

Taken together, our observations support the idea that the

downregulated Ntsr1 and Ntsr2 receptor levels in CRF-OE

are a consequence of the chronically increased cortico-

sterone levels. This could reflect the presence of an

adaptative mechanism present in CRF-OE animals that

compensates the NT-induced CRF release as NT is known to

induce CRF release in the PVN [33,36].


Strikingly, Ntsr1 mRNA expression was upregulated

(N5 times) in vehicle-treated CRF-OE and WT animals.

This mRNA increase might be induced by repeated

injection stress and was counteracted by subchronic

administration of the CRFR1 antagonist R121919. Yet,

this was not translated at the receptor level as [125I]NT

displayed equal binding to Ntsr1 receptors in the hippo-

campus of untreated and vehicle-treated WT and CRF-OE

mice (Figs. 5 and 6). However, it has been suggested that,

once internalized, Ntsr1 receptors are degraded instead of

being recycled to the cell surface [9,19,46,55]. In line with

this it is tempting to speculate that a transient increase in

NT release following injection stress in vehicle-treated

animals induces Ntsr1 receptor degradation, counteracting

increased Ntsr1 expression at the protein level due to

higher mRNA levels.

5. Conclusion

In conclusion, gene expression profiling of several brain

areas of CRF-OE mice identified consistent changes in

expression patterns related to glucocorticoid signaling,

intracellular calcium signaling/sensing, myelination, cell

proliferation and extracellular matrix formation. Adaptation

to chronically increased corticosterone levels was further

reflected in downregulation of Ntsr1 and Ntsr2 receptors.

These molecular data suggest that lifelong exposure to

excessive CRF leads to adaptive changes in the brain which

could play a role in some of the behavioral and

physiological alterations seen in this animal model for

chronic stress.

Acknowledgments

The authors like to thank Luc Bijnens and Jos Prickaerts

for their suggestions on the statistical data analysis and

anatomical interpretation. We also thank Ilse Lenaerts, Ilse

Goris, Gie Daneels, Jean-Marc Taymans and Paula te Riele

for their aid during the experiments.

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Gene expression profiles highlight adaptive brain mechanisms in corticotropin releasing factor overexpressing mice

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