Individual differences in the forced swimming test and neurochemical kinetics in the rat brain

Individual differences in the forced swimming test and neurochemical kinetics in the rat brain

Physiology & Behavior 128 (2014) 60–69 Contents lists available at ScienceDirect Physiology & Behavior journal homepage: www.elsevier.com/locate/phb...

544KB Sizes 0 Downloads 63 Views

Physiology & Behavior 128 (2014) 60–69

Contents lists available at ScienceDirect

Physiology & Behavior journal homepage: www.elsevier.com/locate/phb

Individual differences in the forced swimming test and neurochemical kinetics in the rat brain Andrey Sequeira-Cordero a,b,⁎, Andrea Mora-Gallegos b, Patricia Cuenca-Berger a,b,c, Jaime Fornaguera-Trías b,c a b c

Instituto de Investigaciones en Salud, Universidad de Costa Rica, ZIP code 11501-2060 San Pedro, San José, Costa Rica Centro de Investigación en Neurociencias, Universidad de Costa Rica, ZIP code 11501-2060 San Pedro, San José, Costa Rica Depto. De Bioquímica, Escuela de Medicina, Universidad de Costa Rica, ZIP code 11501-2060 San Pedro, San José, Costa Rica

H I G H L I G H T S • Time course of depression-related factors was studied in rats with low/high despair. • BDNF variations across time were different in animals with low and high immobility. • Monoamine changes after FST outlasted from hours to at least a day.

a r t i c l e

i n f o

Article history: Received 7 August 2013 Received in revised form 28 November 2013 Accepted 23 January 2014 Available online 8 February 2014 Keywords: Individual differences Time course BDNF expression Neurotransmitters Brain

a b s t r a c t Individual differences in the forced swimming test (FST) could be associated with differential temporal dynamics of gene expression and neurotransmitter activity. We tested juvenile male rats in the FST and classified the animals into those with low and high immobility according to the amount of immobility time recorded in FST. These groups and a control group which did not undergo the FST were sacrificed either 1, 6 or 24 h after the test. We analyzed the expression of the CRF, CRFR1, BDNF and TrkB in the prefrontal cortex, hippocampus and nucleus accumbens as well as norepinephrine, dopamine, serotonin, glutamate, GABA and glutamine in the hippocampus and nucleus accumbens. Animals with low immobility showed significant reductions of BDNF expression across time points in both the prefrontal cortex and the nucleus accumbens when compared with non-swim control. Moreover, rats with high immobility only showed a significant decrease of BDNF expression in the prefrontal cortex 6 h after the FST. Regarding neurotransmitters, only accumbal dopamine turnover and hippocampal glutamate content showed an effect of individual differences (i.e. animals with low and high immobility), whereas nearly all parameters showed significant differences across time points. Correlational analyses suggest that immobility in the FST, probably reflecting despair, is related to prefrontal cortical BDNF and to the kinetics observed in several other neurochemical parameters. Taken together, our results suggest that individual differences observed in depression-like behavior can be associated not only with changes in the concentrations of key neurochemical factors but also with differential time courses of such factors. © 2014 Elsevier Inc. All rights reserved.

1. Introduction Behavioral research based on individual differences (i.e. classification of individuals according to systematic variations of specific behaviors) has shown to be a very informative approach to understand brain function and mood disorders [1–4]. The individual phenotype of an organism is influenced, to a greater or lesser extent, by a number of interacting factors such as endocrine status, genetic variation and environmental effects among others (reviewed in [5]). Thus, the study of individual

⁎ Corresponding author at: Instituto de Investigaciones en Salud (INISA), Universidad de Costa Rica, ZIP code 11501-2060, San Pedro, Costa Rica. Tel.: + 506 2511 3482; fax: + 506 2511 5130. E-mail address: [email protected] (A. Sequeira-Cordero). 0031-9384/$ – see front matter © 2014 Elsevier Inc. All rights reserved. http://dx.doi.org/10.1016/j.physbeh.2014.01.037

differences in behavioral traits allows the identification of relevant information concerning such influencing factors [6]. The individual differences approach has been used, for example, to study critical elements underlying the development of anxiety- and depressionlike disorders [7–11]. The development of depression is associated with previous stress exposures and involves altered function of many brain regions and physiological and molecular pathways (reviewed in [12]). Several limbic structures play a central role in the development of the disease, with the hippocampus (HPC) and the nucleus accumbens (NAc) being widely studied so far [13–15]. Likewise, the prefrontal cortex (PFC) has also been shown to play an important role [16,17]. In addition, depression is associated with alterations in a growing number of molecular regulators such as the corticotropin-releasing factor (CRF) and the corticotropin-releasing factor receptor 1 (CRFR1)

A. Sequeira-Cordero et al. / Physiology & Behavior 128 (2014) 60–69

[18,19]. Furthermore, the brain-derived neurotrophic factor (BDNF) and its receptor tyrosine-related kinase B (TrkB) were shown to have a relevant modulatory action. Changes in their expression profiles have been considered as vulnerability factors for disease development and/or antidepressant activity [20,21]. On the other hand, alterations in monoamine neurotransmission have been repeatedly associated with depression (for a meta-analysis see [22]). We have previously found that individual differences in the duration of immobility in the forced swimming test (FST), a validated model of behavioral despair [23], are associated with differential expression of CRFR1 and monoaminergic neurotransmission one week after the exposure to the FST [24]. Nevertheless, such findings offered no insights regarding the dynamics shortly after the aversive experience. Therefore, we studied the temporal dynamics of gene expression and monoamine and amino acid neurotransmission in order to determine if individual differences in FST behavior are associated with the dynamics of these factors across a period of 24 h. We found that, in comparison with a non-swim control group, prefrontal and accumbal BDNF levels differentially decreased across the first 24 h, suggesting that high or low despair responses are related to further downstream neurobiological events that could be associated with the development of depression. Thus, it should be noticed that not only differences in levels but also in the time course dynamics of BDNF could play an important role in the stress response.

2. Materials and methods 2.1. Animals Three groups of thirty-four (experimental groups) and one group of ten (control group) outbred male Sprague–Dawley rats (Rattus norvegicus) four weeks old were used in this study (provided by LEBi Laboratories, University of Costa Rica). The use of juvenile prepubertal animals was based on our previous findings showing that juvenile rats are more vulnerable to the swim stress [24], which would increase the possibility of finding factors with differential time course dynamics between animals with low and high immobility. Each group of animals was studied separately. Rats were individually marked and housed in groups (5 animals per cage) in standard polycarbonate home cages (37.5 × 22 × 18 cm; with woodchip bedding) with ad libitum access to food and water, under 12:12 h light–dark schedule (lights on at 06:00 until 18:00 h) at a room temperature of 25.5 °C ± 1.20 °C and 78–87% relative humidity. A one-week acclimatization period was used prior to the behavioral tests. Afterwards, each group (except the non-tested control one) was subjected to two behavioral tests: the open field test (OFT) and the FST (see below). Experimental procedures were done in accordance to the guidelines of the Costa Rican Ministry of Science and Technology for the Care and Use of Laboratory Animals and were approved by the Institutional Committee for Animal Care and Use of the University of Costa Rica. Rats were sacrificed 1 h (experimental group 1), 6 h (experimental group 2) and 24 h (experimental group 3) after FST exposure (see below). Rats from the control group (non-subjected to the behavioral tests) were sacrificed simultaneously with the experimental group 1. All experimental and control groups were managed identically during the study in order to avoid management-derived variation. For each experimental group, animals were classified post-hoc as animals with low (lower third) or high (upper third) immobility depending on the duration in the FST test session. Animals showing medium scores for this parameter were not included in the study. Then, high, low and control animals were compared regarding neurochemistry and gene expression profiles in different brain areas in order to determine if differences in the duration of immobility are associated with neurochemical profiles at different time points after the FST exposure.

61

2.2. Behavioral tests The OFT was carried out on post natal day (PND) 29. Animals were subjected to this test in order to replicate previously published experiments [24]. Behavioral testing was conducted between 8:00 and 11:00 in the morning. One hour before each test animals were placed in a red light room adjacent to the testing room for context habituation. The testing room was illuminated with one 25 W red bulb located 130 cm above the floor. The open field arena consisted of a black, square, wooden chamber (55 cm × 55 cm × 40 cm). Single animals were placed in the center of the arena during a 10 minute session. A trained observer manually scored behavioral parameters using the Etholog 2.25 software [25]. In addition, the software Any-maze™ 4.3 (Stoelting Co., USA) was used to measure the total distance traveled (m). The following variables were studied: locomotion represented by the number of squares crossed with the four paws in the center and the periphery (i.e., crossings), total distance traveled, average speed, time (in seconds) spent in the center, rearing time (posture sustained with hind paws on the floor) and total grooming time (including washing or mouthing of forelimbs, hind paws, face, body and genitals). In the FST rats were individually placed into plastic cylinders (45 cm height, 31 cm diameter) containing water (25 °C ± 0.5 °C) to a depth of 30 cm (the animals' hind paws and tail did not touch the cylinder's bottom). After each session, rats were removed from water, dried with a towel, and placed in a warmed enclosure, and the cylinders were cleaned and refilled. The FST consisted of two sessions on two consecutive days: a 15 minute pre-test and a 5 minute test (at PNDs 31 and 32 respectively). Behavior was videotaped and scored by a trained observer by means of the Etholog 2.25 software. The analyzed parameters were: duration of immobility, swimming and climbing. It is worth noting that only the first 5 min was scored in the pre-test in order to properly compare them with the 5 min of the test session. 2.3. Gene expression Animals were sacrificed by decapitation without anesthetics 1, 6 and 24 h after the second FST. Brains were quickly dissected on ice and three different areas were dissected out: HPC, PFC and NAc (40.13 ± 0.06 mg, 13.70 ± 0.06 mg and 8.50 ± 0.03 mg, respectively). In the case of PFC the two hemispheres were pooled, whereas the HPC and the NAc sample collection followed a right-and-left alternating method. The remaining hemispheres were used for neurochemical analysis (see below). Tissue samples were collected in a tube with 300 μL TRIzol (Invitrogen, USA), homogenized by 20 s of sonication using an ultrasonic dismembrator (Fisher, USA), immediately frozen and stored at − 70 °C. The extraction of total RNA was carried out according to the manufacturer's instructions. Briefly, samples were thawed, incubated for 5 min at 25 °C and mixed with 100 μL of chloroform. A centrifugation step of 15 min at 12,000 g and 4 °C separated the mixture into three phases. The aqueous phase (containing the RNA) was transferred to a fresh tube and the RNA was precipitated with 250 μL of isopropyl alcohol and centrifugation at 12,000 g. The RNA pellet was washed with 75% ethanol and centrifuged at 7500 g for 5 min at 4 °C. Finally, the pellet was dissolved in RNase-free water. RNA samples were immediately quantified by means of a NanoDrop spectrophotometer (Thermo Scientific, USA) and stored at −70 °C. The integrity of total RNA was assessed by electrophoresis on 1.5% (w/v) agarose gels. Samples were treated with DNase I (Fermentas, USA) in order to avoid genomic DNA contamination. cDNA synthesis was carried out by RevertAid First Strand cDNA Synthesis Kit (Fermentas, USA) according to the manufacturer's specifications, but adapted to a final volume of 10 μL. In brief, for each sample, 500 μg of total RNA was mixed with 2 μL of 5× reaction buffer, 0.25 μg of oligo (dT)18 primer, 1 mM dNTPs, 10 U of RNase inhibitor and 100 U of RevertAid M-MuLV Reverse Transcriptase. Reactions were incubated for 60 min at 42 °C, followed by 5 min at 70 °C. Samples were diluted 1:10 and stored at − 20 °C.

62

A. Sequeira-Cordero et al. / Physiology & Behavior 128 (2014) 60–69

Four genes were analyzed: CRF, CRFR1, BDNF and TrkB (full-length isoform). Oligonucleotides for real-time reverse transcription quantitative polymerase chain reaction (RT-qPCR) used in this study were designed elsewhere [26–28]. Primer sequences were the following: CRF-F 5′-AAAATGTGGATCCAAGGAGGA-3′ and CRF-R 5′-TAGCCACCCC TCAAGAATGAA-3′, CRFR1-F 5′-TTGGCAAACGTCCTGGGGTAT-3′ and CRFR1-R 5′-GCGGACAATGTTGAAGAGAAAG-3′, BDNF1-F 5′-CAAGGCAA CTTGGCCTACCC-3′ and BDNF1-R 5′-GAGCATCACCCGGGAAGTGT-3′, TrkB-F 5′-GATCTTCACCTACGGCAAGC-3′ and TrkB-R 5′-TCGCCAAG TTCTGAAGGAGT-3′, HPRT1-F 5′-CCTTGACTATAATGAGCACTTC-3′ and HPRT1-R 5′-GCCACATCAACAGGACTC-3′, and PPIA-F 5-TTTGGG AAGGTGAAAGAAGGC-3′ and PPIA-R 5′-ACAGAAGGAATGGTTTGATG GG-3′. Three pairs of primers (for TrkB, CRFR1 and HPRT1) span exon–intron junctions in order to allow amplification only from cDNA templates. Relative gene expression was determined by the comparative method with peptidylprolyl isomerase A (PPIA) as a reference gene for the HPC and the PFC, and hypoxanthine phosphoribosyltransferase 1 (HPRT1) for the NAc, according to a previous validation assay (unpublished data). Expression levels were reported as a fold of the control group expression. The real time PCR was performed using a Rotor-Gene Q (QIAgen, Germany). The reactions contained 2 μL of 1:10 diluted cDNA, 5 μL 2 × Sybr green (Fermentas, USA), and a final primer concentration of 75 ηM for HPRT1 and PPIA, 300 ηM for BDNF, TrkB and CRFR1, and 200 ηM for CRF, in a final volume of 10 μL. After an initial denaturation step at 95 °C for 10 min amplification was performed with 40 cycles of denaturation at 95 °C for 30 s, annealing at 57 °C for 45 s and extension at 72 °C for 30 s. A melting curve analysis (95 °C for 15 s, 60 °C for 60 s and 95 °C for 15 s) was performed to confirm the specificity of the amplifications and the absence of primer dimmer formation. All the samples were run in duplicate and the mean value was used for further calculations. Each run included all the samples for three groups (low, high and control animals) for individual genes according to the sample maximization method [29]. Non-template controls and minus RT controls were included in each run. The absence of amplification in the non-template and in the minus RT controls excluded the possibility of genomic DNA contamination. Fluorescence data were collected and the threshold cycle (Ct) was calculated using the Rotor-Gene Q Series Software (QIAgen, Germany). 2.4. Neurochemistry The remaining hemisphere was used for the dissection and neurochemical analyses of HPCs and NAcs. Following decapitation these brain regions were immersed in a 0.05 M perchloric acid solution with DHBA as the internal standard and stored at − 70 °C until analysis. High-performance liquid chromatography coupled with electrochemical detection (HPLC–EC) was used. Samples were homogenized by sonication, filtered in 0.22 μm nylon membranes and injected in the apparatus as previously reported by our group [30]. The flow rate was fixed at 1.5 mL/min with a final injection volume of 50 μL. All samples were analyzed for their contents of noreprinephrine (NE), dopamine (DA) and its metabolite 3,4-dihydroxyphenylacetic acid (DOPAC), serotonin (5-HT) and its metabolite 5-hydroxyindoleacetic acid (5-HIAA), using the internal standard method. Furthermore, the DA (DOPAC/DA) and 5-HT (5-HIAA/5-HT) turnover ratios were also calculated. For amino acid analysis, 10 μL of brain filtrates was diluted in 990 μL of deionized water. Glutamate (Glu), glutamine (Gln) and gamma-aminobutiric acid (GABA) were analyzed by reverse phase HPLC with fluorescence detection (Agilent Technologies, USA). Amino acids were separated by means of an Eclipse Plus C-18 column (250 × 4.6 mm, 5 μm; Agilent Technologies, USA) and a security guard column (4.6 × 12.5 mm, 5 μm; Agilent Technologies, USA). The flow rate was fixed at 0.5 mL/min with a final injection volume of 20 μL. Chromatographic data were processed using the ChemStation for LC 3D System (Agilent Technologies, USA). The amino acid concentration was determined using the peak area and the external standard

method. Data for both monoamine and amino acid concentration were expressed as nanograms per milligram of wet tissue weight. 2.5. Statistical analysis Statistical analyses were performed using the SPSS software (v17, SPSS Inc.). A p value b 0.05 was considered statistically significant, whereas a nearly significant trend was noted for p = 0.05–0.07. Data are presented as mean ± standard error of the mean (SEM). Rats in the lower and upper third of the distribution of the immobility time scores for the FST test session were classified as animals with low or high immobility, respectively. Given that behavioral testing was carried out at the same ages for the three groups, behavior was only compared between animals with low and high immobility by using Student's t test. For neurochemical data, statistical analyses were carried out by means of factorial ANOVA with subgroups (i.e. animals with low and high immobility) and time point (i. e. sacrifices 1, 6 and 24 h after the FST and non-swim control) as fixed factors. Gene expression data were directly compared by one-way ANOVA, given the impossibility of comparing samples analyzed in different runs. In both cases, ANOVAS were followed by Tukey's test or Student's t test as post hoc analysis (where appropriate). Finally, Pearson's correlation analysis was used to evaluate relationships between parameters. 3. Results 3.1. Behavior Three groups of rats were subjected to the FST and classified in animals with low (rats showing immobility times of 272.03, 259.02 and 257.88 s, respectively), medium (animals ranging from 273.94 to 284.99, 259.65 to 281.99, 258.42 to 276.55 s, respectively) and high immobility (rats showing immobility times above 285.47, 281.15 and 277.24 s, respectively). Animals with low immobility showed significantly higher levels of swimming and climbing time in the test session compared with rats with high immobility (t(62) = 7.24, p b 0.001 and t(62) = 6.48, p b 0.001, respectively). In the pre-test session identical results were found: rats with low immobility showed significantly lower levels of immobility and higher levels of swimming and climbing time compared with animals with high immobility (t(62) = 46.08, p b 0.001; t(62) = 2.61, p = 0.01 and t(62) = 3.85, p b 0.001, respectively). There were no significant differences in any of the open field measurements (data not shown). 3.2. Gene expression Gene expression profiles showed a number of differences across the time points studied. When the three time groups were compared for BDNF expression in the PFC, significant differences were observed at 1 h [F(2,28) = 3.58, p = 0.04, n = 8–11 animals/group] and 6 h [F(2,28) = 7.79, p = 0.002, n = 9–10 animals/group], whereas no differences were found at 24 h [F(2,29) = 0.50, p = 0.61, n = 9–10 animals/group] (Fig. 1A). Post hoc comparisons corroborated that 1 h after FST significant differences were only observed between the control group and animals with low immobility (p = 0.03; Fig. 1A). Additionally, in animals sacrificed 6 h after the FST significant differences were observed between control and the two subgroups: low immobility (p = 0.005) and high immobility (p = 0.003; Fig. 1). Although accumbal expression of BDNF significantly differed between groups 6 h after the swim stress [F (2,27) = 3.84, p = 0.035, n = 9–10 animals/group], no differences were found either 1 h [F(2,30) = 0.10, p = 0.90, n = 10–11 animals/group] or 24 h [F(2,29) = 1.93, p = 0.16, n = 10 animals/group] after the FST (Fig. 1B). Post hoc analysis showed that only rats with low immobility showed significantly decreased accumbal BDNF mRNA levels 6 h after the swim stress (p = 0.03). When hippocampal data were analyzed, no differences

A) Prefrontal cortex 6 hours

24 hours

1.40

1.40

1.40

1.20

1.20

1.20

1.00

1.00

1.00

*

0.80

0.80

0.80

*

*

0.60

0.60

0.60

0.40

0.40

0.40

0.20

0.20

0.20

0.00

0.00 Control

Low immobility

High immobility

0.00 Control

Low immobility

High immobility

Control

Low immobility

High immobility

B) Nucleus accumbens

BDNF mRNA levels (relative expression)

1 hour

6 hours

24 hours

1.40

1.40

1.40

1.20

1.20

1.20

1.00

1.00

1.00

0.80

0.80

0.80

0.60

0.60

0.40

0.40

0.40

0.20

0.20

0.20

0.00

*

0.60

0.00 Control

Low immobility

High immobility

A. Sequeira-Cordero et al. / Physiology & Behavior 128 (2014) 60–69

BDNF mRNA levels (relative expression)

1 hour

0.00 Control

Low immobility

High immobility

Control

Low immobility

High immobility

Fig. 1. BDNF expression in the prefrontal cortex (1A) and the nucleus accumbens (1B) of rats with low and high immobility in the FST. Animals (n = 9–11 per group) were sacrificed 1, 6 and 24 h after the FST. * p b 0.05 when compared with control group (n = 9–10, sacrifice matched with animals decapitated 1 h after the FST).

63

64

A) Prefrontal cortex 6 hours

24 hours

1.40

1.40

1.20

1.20

1.20

1.00

1.00

1.00

0.80

0.80

*

*

0.80

0.60

0.60

0.60

0.40

0.40

0.40

0.20

0.20

0.20

Control

Low immobility

High immobility

*

0.00

0.00

0.00

*

Control

Low immobility

High immobility

Control

Low immobility

High immobility

B) Nucleus accumbens

CRF mRNA levels (relative expression)

1 hour

6 hours

24 hours

1.40

1.40

1.40

1.20

1.20

1.20

1.00

1.00

1.00

0.80

0.80

0.80

*

*

0.60

0.60

0.40

0.40

0.40

0.20

0.20

0.20

0.00

0.00 Control

Low immobility

High immobility

0.60

0.00 Control

Low immobility

High immobility

Control

Low immobility

High immobility

Fig. 2. CRF expression in the prefrontal cortex (2A) and the nucleus accumbens (2B) of rats with low and high immobility in the FST. Animals (n = 10–11 per group) were sacrificed 1, 6 and 24 h after the FST. * p b 0.05 when compared with control group (n = 10, sacrifice matched with animals decapitated 1 h after the FST).

A. Sequeira-Cordero et al. / Physiology & Behavior 128 (2014) 60–69

CRF mRNA levels (relative expression)

1 hour 1.40

A. Sequeira-Cordero et al. / Physiology & Behavior 128 (2014) 60–69

in BDNF expression were found between groups either 1 h [F(2,31) = 0.28, p = 0.76, n = 10–11 animals/group], 6 h [F (2,29) = 0.41, p = 0.67, n = 10 animals/group] or 24 h [F(2,31) = 0.81, p = 0.45, n = 10–11 animals/group] after the FST. CRF expression also yielded time-dependent group differences. In the PFC, although CRF expression showed no significant differences between groups 1 h after the FST [F(2,29) = 0.53, p = 0.60, n = 8–11 animals/group], mRNA levels significantly differed 6 h [F(2,28) = 7.79, p = 0.002, n = 10–11 animals/group] and 24 h [F(2,30) = 6.44, p = 0.005, n = 10–11 animals/group] after the stressful event (Fig. 2A). Post hoc analysis showed that 6 and 24 h after the FST animals with low (p = 0.005 and p = 0.007, respectively) and high immobility (p = 0.007 and p = 0.02, respectively) expressed decreased CRF levels compared with the control group in the PFC (Fig. 2A). On the other hand, accumbal mRNA levels of CRF showed no significant differences between groups 1 h [F (2,29) = 1.84, p = 0.18, n = 10 animals/group] and 24 h [F(2,31) = 2.17, p = 0.13, n = 10–11 animals/group] after the FST, although significant differences were observed 6 h after the test [F(2,28) = 4.46, p = 0.02, n = 9–10

65

animals/group] (Fig. 2B). Post hoc analysis determined that only rats with high immobility showed significantly lower CRF expression levels in the NAc when compared with non-swim controls (p = 0.02; Fig. 2B). With regard to hippocampal profiles, CRF expression showed the same pattern described above for BDNF in this brain area, that is, no differences between groups were found when animals were sacrificed either 1 h [F(2,30) = 0.33, p = 0.72, n = 9–11 animals/ group], 6 h [F(2,29) = 2.35, p = 0.11, n = 10 animals/group] or 24 h [F(2,31) = 0.75, p = 0.48, n = 10–11 animals/group] after the exposure to swim stress. Finally, there were no significant effects of group or time for CRFR1 and TrkB expression levels in the three brain regions included in this study (data not shown). 3.3. Neurotransmitters Animals with low and high immobility showed significant group differences fin hippocampal Glu and accumbal DA turnover (see Tables 1 and 2). However, when compared within each time point, neither

Table 1 Factorial ANOVA results for neurochemical content. Two factors were used: individual differences (low and high immobility) and time point (1 h, 6 h and 24 h). Brain region

Neurotransmitter

Factor/interaction

F statistic

Df

p value

η2

HPC

NE

Individual differences Time point Individual differences × time point Individual differences Time point Individual differences × time point Individual differences Time point Individual differences × time point Individual differences Time point Individual differences × time point Individual differences Time point Individual differences × time point Individual differences Time point Individual differences × time point Individual differences Time point Individual differences × time point Individual differences Time point Individual differences × time point Individual differences Time point Individual differences × time point Individual differences Time point Individual differences × time point Individual differences Time point Individual Differences × time point Individual differences Time point Individual differences × time point Individual differences Time point Individual differences × time point Individual differences Time point Individual differences × time point Individual differences Time point Individual differences × time point Individual differences Time point Individual differences × time point

0.33 125.60 0.43 0.02 7.08 0.40 0.17 6.99 1.77 0.27 4.61 0.24 0.75 84.87 1.81 4.17 6.64 0.45 0.02 12.86 0.24 0.66 19.10 0.58 0.009 4.66 1.61 0.60 52.14 1.96 1.60 44.11 8.15 3.96 3.25 1.12 0.04 5.21 0.46 0.007 20.84 0.85 0.10 16.85 0.56 0.00 0.63 0.44

1, 67 2, 67 2, 67 1, 67 2, 67 2, 67 1, 66 2, 66 2, 66 1, 66 2, 66 2, 66 1, 65 2, 65 2, 65 1, 67 2, 67 2, 67 1, 67 2, 67 2, 67 1, 67 2, 67 2, 67 1, 67 2, 67 2, 67 1, 67 2, 67 2, 67 1, 67 2, 67 2, 67 1, 66 2, 66 2, 66 1, 66 2, 66 2, 66 1, 67 2, 67 2, 67 1, 67 2, 67 2, 67 1, 67 2, 67 2, 67

0.57 b0.001 0.65 0.89 0.002 0.67 0.90 0.02 0.17 0.60 0.01 0.80 0.40 b0.001 0.20 0.04 0.002 0.45 0.90 b0.001 0.78 0.42 b0.001 0.56 0.93 0.013 0.21 0.44 b0.001 0.15 0.21 b0.001 0.001 0.05 0.04 0.33 0.83 0.008 0.64 0.93 b0.001 0.43 0.75 b0.001 0.58 0.98 0.54 0.64

0.005 0.80 0.01 b0.001 0.17 0.012 b0.001 0.17 0.05 0.004 0.12 0.007 0.01 0.72 0.05 0.06 0.16 0.01 b0.001 0.27 0.01 0.01 0.36 0.02 b0.001 0.12 0.05 0.009 0.61 0.05 0.02 0.57 0.20 0.06 0.09 0.03 0.001 0.14 0.01 b0.001 0.38 0.02 0.002 0.33 0.02 b0.001 0.02 0.01

DA

5-HT

DA turnover

5-HT turnover

Glu

Gln

GABA

NAc

NE

DA

5-HT

DA turnover

5-HT turnover

Glu

Gln

GABA

Significant statistics are marked with bold.

66

A. Sequeira-Cordero et al. / Physiology & Behavior 128 (2014) 60–69

Table 2 Neurochemical content expressed in nanograms per milligram (ηg/mg) of wet tissue weight (means ± SEM) in animals sacrificed 1, 6 and 24 h after being tested in the FST. Brain region

Neurotransmitter

Time point

Content (mean ± SEM)

p value

HPC

NE

1h 6h 24 h 1h 6h 24 h 1h 6h 24 h 1h 6h 24 h 1h 6h 24 h 1h 6h 24 h 1h 6h 24 h 1h 6h 24 h 1h 6h 24 h 1h 6h 24 h 1h 6h 24 h 1h 6h 24 h 1h 6h 24 h 1h 6h 24 h 1h 6h 24 h 1h 6h 24 h

0.58 ± 1.43 ± 1.60 ± 0.04 ± 0.10 ± 0.10 ± 1.13 ± 1.55 ± 1.26 ± 0.72 ± 1.32 ± 0.75 ± 2.01 ± 0.78 ± 2.44 ± 0.79 ± 0.90 ± 0.87 ± 0.47 ± 0.56 ± 0.56 ± 0.13 ± 0.10 ± 0.11 ± 1.06 ± 1.46 ± 1.30 ± 6.53 ± 16.76 ± 22.83 ± 1.82 ± 5.18 ± 2.47 ± 0.28 ± 0.28 ± 0.36 ± 1.11 ± 1.01 ± 1.48 ± 0.80 ± 0.99 ± 1.51 ± 0.68 ± 0.84 ± 1.00 ± 0.31 ± 0.28 ± 0.28 ±

0.98 b0.001 b0.001 0.99 0.03 0.05 0.88 0.17 0.99 0.80 0.60 0.87 0.82 b0.001 0.002 0.80 0.28 0.60 0.06 0.90 0.72 0.99 b0.001 0.02 0.70 0.005 0.05 0.99 b0.001 b0.001 0.94 b0.001 0.91 0.98 0.98 0.14 0.89 0.99 0.04 1.00 0.08 b0.001 1.00 0.14 b0.001 0.53 0.93 0.95

DA

5-HT

DA turnover

5-HT turnover

Glu

Gln

GABA

NAc

NE

DA

5-HT

DA turnover

5-HT turnover

Glu

Gln

GABA

0.02 0.08 0.05 0.005 0.01 0.01 0.08 0.10 0.08 0.06 0.24 0.12 0.12 0.06 0.08 0.02 0.02 0.02 0.01 0.01 0.02 0.003 0.003 0.004 0.11 0.12 0.04 0.40 1.60 1.60 0.22 0.50 0.06 0.01 0.03 0.03 0.11 0.16 0.06 0.04 0.05 0.05 0.03 0.04 0.05 0.02 0.02 0.01

Significant statistics are marked with bold (in comparison with the control group).

hippocampal Glu content or accumbal DA turnover showed significant differences between rats with low and high immobility after 1 h (t(20) = 1.86, p = 0.08, and t(19) = − 0.05, p = 0.69, respectively), 6 h (t(18) = 0.77, p = 0.45 and t(18) = 1.24, p = 0.23, respectively) or 24 h (t(21) = 0.65, p = 0.52 and t(20) = 1.70, p = 0.10, respectively). Neurotransmitter content differed across time following specific patterns depending on the brain region and time elapsed since the FST was performed (for statistics and data see Tables 1 and 2). Concerning hippocampal measurements (Tables 1 and 2), NE levels were significantly increased 6 h and 24 h after the swim stress. Similar to NE, DA content was significantly higher at 6 and 24 h when compared with DA levels observed for control animals, whereas DA turnover did not differ across time points. 5-HT content remained unaltered across time points, although 5-HT turnover showed a significant decrease at 6 h, followed by a significant increase at 24 h. On the other hand, Glu showed no differences across time points, whereas Gln showed a significant decrease at 1 h and, finally, GABA levels significantly decreased at 6 and 24 h, although after 24 h such decrease was less significant compared with non-swim rats. In the NAc, compared with non-swim control, NE content showed a significant increase 6 h after

the FST and, although such content decreased at 24 h, it still was significantly higher than NE in the control group. Furthermore, accumbal DA showed significantly higher levels at 6 and 24 h, whereas 5-HT significantly increased 6 h after the swim stress and, thereafter, it reached basal levels. Conversely, DA turnover showed no significant differences across time points, whereas 5-HT turnover was significantly higher than control at 24 h. Finally, Glu and Gln showed a significant increase 24 h after the FST, whereas GABA remained unaltered. 3.4. Correlational analysis Concerning gene expression analyses, immobility time in the FST test session showed a significant negative correlation with accumbal BDNF levels (r = − 0.27, p = 0.04) but not with other parameters (data not shown). With regard to neurochemical data, immobility time only showed a significant negative correlation with DA turnover in the NAc (r = − 0.37, p = 0.003). Interestingly, prefrontal cortical BDNF levels positively correlated with CRF levels in the PFC (r = 0.31, p = 0.02) and with BDNF and CRF levels in the NAc (r = 0.43, p = 0.001 and r = 0.51, p b 0.001, respectively). Moreover, CRF levels in the PFC showed a significant positive correlation with CRF levels in the NAc (r = 0.39, p = 0.002). On the other hand, Glu content showed significant positive correlations with prefrontal cortical BDNF and accumbal CRF (r = 0.27, p = 0.04 and r = 0.26, p = 0.04, respectively). 4. Discussion Experimental data suggest that individuality is associated with differential gene expression and neurotransmission [24,31,32]. Additionally, behavioral individual differences could also be associated with differences in the temporal dynamics of gene expression and neurotransmitter concentrations in different brain regions [32]. Thus, we explored such an assumption by studying mRNA levels and neurochemical contents in three brain regions at three time points (i.e., 1 h, 6 h and 24 h after the FST) in animals showing high and low immobility in the FST test session. First, animals with low and high immobility were compared according to the behavioral response observed in the FST and in the OFT. Animals with low immobility also showed higher levels of swimming and climbing time in the FST test session in comparison with animals with high immobility. Such results were similar in the pre-test session suggesting that differences in all three behaviors are stable traits that seem to be maintained across two testing sessions. Conversely, animals with low and high immobility showed no differences in any of the parameters analyzed in the OFT. Such lack of differences suggests that individual differences in the FST are not echoed by behavioral responses displayed in the OFT when such test is carried out two days before the exposure to the swim stress. These behavioral observations regarding the OFT and the FST replicate previous results reported elsewhere by our group; a detailed discussion of such findings can be found in [24]. BDNF showed decreased expression levels in the PFC at 1 and 6 h after the FST (Fig. 1A). Although no differences between animals with low and high immobility were observed, a differential time course was found when compared with non-swim control. One hour after the FST, BDNF mRNA levels were significantly different between control and low immobility rats, but not between control and high immobility animals. At 6 h, both groups showed a significant reduction compared with the control group (Fig. 1A). Several studies in rodents and humans showed that stress is capable of decreasing BDNF levels in the PFC, and that anti-depressant treatments increase and restore them, supporting a role of prefrontal cortical BDNF expression in stress response and depression [33–36]. Our results also showed such a reduction and, surprisingly, also pointed at a putative association between behavioral despair, i.e., immobility, and the dynamics of BDNF decrease, even though the lack of correlation between immobility and expression levels seems not to support such relationship. According to our data,

A. Sequeira-Cordero et al. / Physiology & Behavior 128 (2014) 60–69

it is possible that differences in the BDNF temporal dynamics in the PFC after the exposure to the FST test session could be linked with downstream events associated with despair and/or the strategy of coping (i.e., active vs. passive). Nonetheless, given that a BDNF decrease has been associated with depression [33], we would have expected animals with high immobility to show a faster decrease than rats with low immobility. Our data showed however an opposite trend. Therefore, more research is needed in order to explain this observation, which at first glance is counter-intuitive. Interestingly, although animals with low and high immobility did not differ for BDNF accumbal expression across time points, only rats with low immobility showed a significant decrease of mRNA levels 6 h after the FST compared with the control group (Fig. 1B). Again, such a finding suggests differential temporal dynamics for a peptide between animals with low and high levels of FST immobility. In addition, the correlational analysis showed a significant negative relationship between immobility time and accumbal BDNF expression. Experimental evidence suggests that, unlike in the PFC, depression is associated with an increase in BDNF expression in the NAc [20,37,38]. Although animals with higher scores of immobility (i.e., increased despair) showed no significant increases in the accumbal BDNF expression, our results are still consistent with those of previous reports inasmuch as decreased levels are associated with lower despair. Moreover, the NAc is an integration center receiving information of contextual stimuli processed in the HPC and executive functions processed in the PFC in order to control goal-directed behavior [39,40]. In fact, BDNF expression in the PFC is directly related to BDNF action in the NAc given that it has been observed that an important amount of the BDNF protein in the striatum, including the NAc, is derived from prefrontal connections [41]. Taken together, such cortico-accumbal innervations and our results suggest that changes in the BDNF expression in the PFC are echoed, at some level, in the NAc, offering some consistency to our data. Such interpretation was supported by the positive correlation between BDNF levels in both brain regions. These results also suggest that significant reductions of accumbal BDNF could be associated with lower levels of despair as observed in the FST. Interestingly, even though we did not found differences in BDNF mRNA levels between animals with low and high immobility our results clearly pointed to differential time courses in the expression of such neurotrophin in both the PFC and the NAc. The reduction of BDNF in the PFC compared to the control group occurred faster in animals with low immobility in comparison with rats with high immobility (Fig. 1A). Furthermore, also in comparison with the control group BDNF was significantly reduced in the NAc 6 h after the FST in animals with low immobility, whereas no differences were observed at this time point in animals with high immobility (Fig. 1B). Such results strongly suggest that neural responses to the FST display different temporal dynamics echoing behavioral responses during the test. Although such differences were observed after the behavioral display, it is clear that they are associated with the individual differences observed in the FST. Accordingly, the time course of responding of neurochemical factors (in this case, BDNF) emerges as a relevant variable to take into account when characterizing vulnerability or resilience to develop a depression-related behavior (i.e., immobility). CRF expression also differed across time points, even though no differences between animals with low and high immobility were found and no correlations with immobility time were observed. In the PFC, both groups showed a significant decrease at 6 and 24 h after the FST compared with the control group (Fig. 2A). Studies addressing the effect of acute stress on CRF prefrontal expression have reported contradictory results. For example, one study showed that a single restraint increased CRF mRNA levels in the PFC [42], whereas another one found no effect on gene expression [43]. Interestingly, Sutherland and colleagues (2010) also showed that repeated restraint induced no change on CRF expression in the PFC and that the effects on the brain

67

depended on the strain. Our results suggest that repeated swim stress probably leading to despair induces downstream reductions in the production of prefrontal cortical CRF observable at 6 h and lasting 24 h, at least. We argue that discrepancies described above could be explained by a number of variables such as strain and type of stress. As with BDNF expression, accumbal CRF data were partially paralleled by observations in the PFC. CRF levels were significantly decreased in animals sacrificed 6 h after the FST (Fig. 2B). Our correlational results suggest a significant relationship between CRF mRNA concentrations in both brain areas. Increased CRF expression in the NAc has been associated with behavioral arousal [44] and positive motivation for cued rewards [45]. Taking into account that behavioral despair appears during the second exposure to the swim stress, a decreased CRF expression in this brain area would be expected as a downstream event related to the re-exposure to stress and/or the display of despair. Moreover, such parallelism between CRF expression in the PFC and in the NAc could point at cortico-accumbal interactions involved in the response to repeated swim stress. Although the PFC and the NAc are not considered CRF cell body rich brain regions, as opposed to the amygdala or the paraventricular nucleus of the hypothalamus, CRF-producing neurons have been identified in both the PFC and the NAc [46,47]. Thus, taking into account that the NAc receives afferent connections from the PFC and projects to several brain regions such as the ventral pallidum, the lateral hypothalamus and ventral tegmental area and the substantia nigra [48], we propose that the exposure to the FST may decrease the production of CRF by neurons in the PFC, which in turn would reduce the secretion of this peptide in the NAc. Moreover, the decrease of the action of CRF in the NAc seems to be associated with the reduction in the synthesis of accumbal CRF mRNA which would lead to the reduction of this peptide in several brain areas. These related variations in the CRF expression could be involved in the downstream mechanisms of the stress response activated by the exposure to the FST. In this regard, both prefrontal cortical or accumbal CRF showed no correlations with immobility time, suggesting that reductions reported here may not be directly related to despair. Although the behavioral and physiological responses displayed in the FST test session are interpreted as a consequence of despair, it also encompasses the general mechanisms involved in the stress response [49], which suggests that CRF reductions could represent downstream changes related to the stress response itself instead of physiological despair-related changes. Regarding neurochemical measures, individual differences in the FST showed an effect for hippocampal Glu content and accumbal DA turnover (Tables 1–2). One hour after the FST animals with low immobility had higher levels of Glu. In addition, accumbal DA turnover showed a trend to differentiation given that DA neurotransmission in rats with low immobility tended to be increased in comparison with rats with high immobility. Although no significant differences between animals with low and high immobility within time points were observed, the latter result is relevant in light of our previous finding that one week after the FST animals with low immobility showed significantly higher DA turnover [24]. DA turnover tended to increase in animals with low immobility sacrificed 24 h after the FST (Table 2). Thus, if such trend remains beyond that time point it would corroborate our previous result supporting that differences in DA neurotransmission downstream to the exposure to stress could be associated with despair. On the other hand, several differences were observed when time points were compared (Table 2). It has been previously suggested that monoaminergic release and actions are fast (i.e. minutes), seldom outlasting the duration of stressor exposure [50]. Astonishingly, our results showed that such an assumption must be reassessed given that several changes in monoaminergic content and/or turnover outlasted from hours to at least a day, suggesting that monoamine and amino acid neurotransmission could play a role in long-term events related to an acute stress response and development of depression-like behaviors. Interestingly, neurochemical differences observed between animals with low and high immobility (i.e., BDNF expression in the PFC and

68

A. Sequeira-Cordero et al. / Physiology & Behavior 128 (2014) 60–69

the NAc, hipoccampal Glu content and accumbal DA turnover) were transient, which suggests that the changes are reflective of state but not trait characteristics, this is, differences are evident for a brief period of time instead of being constitutive features of animals with low and high immobility. It has been suggested that such initial transient changes related to an acute stress such as the FST induce several subsequent neural responses which in turn would be in charge of achieving the long-term effects of acute stress [50]. Accordingly, our results do not help to understand the underlying mechanisms related to the display of low and high immobility. In spite of this, our data point to transient neurochemical differences subsequent to the behavioral display suggesting that rats showing active or passive coping strategies in the FST also show different downstream neural responses. Such observation becomes relevant for the characterization of processes occurring after the display of depression-related behaviors given that it could help to identify key factors involved in the development of resilience or vulnerability to depression. It is worth noting that we have focused our work on juvenile rats. This choice was made because the brains of both humans and rats undergo several critical changes during adolescence (reviewed in [51]) which in turn are related to increased vulnerability to the development of stress-related disorders such as depression [52,53]. Thus, we carried out our experiments using juvenile rats based on the premise that such increased vulnerability would induce a higher differentiation between animals with low and high immobility, optimizing the chance to find factors differently changing across time points. However, it is expectable that rats in other developmental stages might show different results than those observed here. In fact, all the aforementioned works using the individual differences approach have been realized in adult rats [8,11,32], and only one carried out a similar time course study with no differentiation of BDNF expression between animals with low and high immobility [32]. To our knowledge, there are no published studies focusing on individual differences and neurochemical kinetics in the rat brain that involve juvenile rats and therefore, it is not possible to properly compare our data with previous results. More research should be realized in order to determine if temporal dynamics of depression-related factors is different between rats showing low and high immobility time in the FST at different ages. Finally, it is important to point to a variable that was not taken into account in our experiments but could play a role in the results: the circadian rhythm. It has been shown that BDNF, TrkB and CRF oscillate during the light–dark in a tissue-dependent manner [54–57]. Accordingly, such oscillations could have exerted an effect at least in the six hour time point (the one hour and twenty-four hour measurements were carried out exactly at the same moment of the day). In this regard, it is interesting to note that the BDNF and TrkB mRNA levels in the PFC remain relatively constant during the light in comparison with the dark cycle [56], suggesting that, at least in this region, the effect of circadian rhythm on BDNF and TrkB expression in the six hour time point (i.e., between 14:00 and 16:00 h) should be irrelevant. Nonetheless, the necessity of dissecting the effects of both variables (i.e., the FST and circadian fluctuations) remains relevant and should be considered in future experiments. 5. Conclusion In conclusion, the FST induced tissue-specific changes in the expression profiles of BDNF and CRF and neurotransmitter contents that varied across a twenty-four hour period. Accumbal and prefrontal cortical BDNF expression did not differ between animals with low and high immobility time, but both subgroups differed across time points in comparison with the non-swim control group, suggesting an association between despair and BDNF time course dynamics. Furthermore, DA neurotransmission also differed between subgroups. Our results suggest that individual differences in the development of despair involve not only changes in the concentration of key neurochemical factors,

but also in their time course. These findings offer relevant insights to understand the complex picture related to stress responses and mood disorders. Conflict of interest The authors have no conflict of interest. Acknowledgments We acknowledge the valuable collaboration and effort of Adriana Saborío from the Neurosciences Program, and Dayana Vargas from the Institute for Health Research, both entities from the University of Costa Rica, whose hard work and support at different stages made this research possible. In addition, we acknowledge Karen Lüdtke for her comments and language corrections. We also want to thank the UCR and the MICIT/CONICIT for providing the resources to conduct this study (project numbers VI-742-A9-120 and FI-293-2009 respectively). References [1] Ho YJ, Eichendorff J, Schwarting RK. Individual response profiles of male Wistar rats in animal models for anxiety and depression. Behav Brain Res 2002;136(1):1–12. [2] Kazlauckas V, Schuh J, Dall'Igna OP, Pereira GS, Bonanc CD, Lara DR. Behavioral and cognitive profile of mice with high and low exploratory phenotypes. Behav Brain Res 2005;162:272–8. [3] Görisch J, Schwarting RKW. Wistar rats with high versus low rearing activity differ in radial maze performance. Neurobiol Learn Mem 2006;86(2):175–87. [4] Mällo T, Alttoa A, Kõiv K, Tõnissaar M, Eller M, Harro J. Rats with persistently low or high exploratory activity: behaviour in tests of anxiety and depression, and extracellular levels of dopamine. Behav Brain Res 2007;177(2):269–81. [5] Lathe R. The individuality of mice. Genes Brain Behav 2004;3(6):317–27. [6] Pawlak CR, Ho YJ, Schwarting RK. Animal models of human psychopathology based on individual differences in novelty-seeking and anxiety. Neurosci Biobehav Rev 2008;32(8):1544–68. [7] Borta A, Schwarting RK. Inhibitory avoidance, pain reactivity, and plus-maze behavior in Wistar rats with high versus low rearing activity. Physiol Behav 2005;84(3):387–96. [8] Naudon L, Jay TM. Opposite behaviours in the forced swimming test are linked to differences in spatial working memory performances in the rat. Neuroscience 2005;130(2):285–93. [9] Herrero AI, Sandi C, Venero C. Individual differences in anxiety trait are related to spatial learning abilities and hippocampal expression of mineralocorticoid receptors. Neurobiol Learn Mem 2006;86:150–9. [10] Antoniou K, Papathanasiou G, Papalexi E, Hyphantis T, Nomikos GG, Spyraki C, et al. Individual responses to novelty are associated with differences in behavioral and neurochemical profiles. Behav Brain Res 2008;187:462–72. [11] Enríquez-Castillo A, Alamilla J, Barral J, Gourbière S, Flores-Serrano AG, Góngora-Alfaro JL, et al. Differential effects of caffeine on the antidepressant-like effect of amitriptyline in female rat subpopulations with low and high immobility in the forced swimming test. Physiol Behav 2008;94:501–9. [12] Krishnan V, Nestler EJ. The molecular neurobiology of depression. Nature 2008;455(7215):894–902. [13] Videbech P, Ravnkilde B. Hippocampal volume and depression: a meta-analysis of MRI studies. Am J Psychiatry 2004;161:1957–66. [14] Nestler EJ, Carlezon Jr WA. The mesolimbic dopamine reward circuit in depression. Biol Psychiatry 2006;59(12):1151–9. [15] Rao M, Chen LA, Bidesi AS, Shad MU, Thomas MA, Hammen CL. Hippocampal changes associated with early-life adversity and vulnerability to depression. Biol Psychiatry 2010;67:357. [16] Drevets WC, Bogers W, Raichle ME. Functional anatomical correlates of antidepressant drug treatment assessed using PET measures of regional glucose metabolism. Eur Neuropsychopharmacol 2002;12(6):527–44. [17] Lee BT, Seong WC, Hyung SK, Lee BC, Choi IG, Lyoo IK, et al. The neural substrates of affective processing toward positive and negative affective pictures in patients with major depressive disorder. Prog Neuropsychopharmacol Biol Psychiatry 2007;31(7):1487–92. [18] Tan H, Zhong P, Yan Z. Corticotropin-releasing factor and acute stress prolongs serotonergic regulation of GABA transmission in prefrontal cortical pyramidal neurons. J Neurosci 2004;24(21):5000–8. [19] Chen Y, Andres AL, Frotscher M, Baram TZ. Tuning synaptic transmission in the hippocampus by stress: the CRH system. Front Cell Neurosci 2012;6:13. [20] Eisch AJ, Bolaños CA, de Wit J, Simonak RD, Pudiak CM, Barrot M, et al. Brain-derived neurotrophic factor in the ventral midbrain-nucleus accumbens pathway: a role in depression. Biol Psychiatry 2003;54(10):994–1005. [21] Koponen E, Rantamäki T, Voikar V, Saarelainen T, MacDonald E, Castrén E. Enhanced BDNF signaling is associated with an antidepressant-like behavioral response and changes in brain monoamines. Cell Mol Neurobiol 2005;25(6):973–80.

A. Sequeira-Cordero et al. / Physiology & Behavior 128 (2014) 60–69 [22] Ruhe HG, Mason NS, Schene AH. Mood is indirectly related to serotonin, norepinephrine and dopamine levels in humans: a meta-analysis of monoamine depletion studies. Mol Psychiatry 2007;12:331–59. [23] Porsolt R, Le Pichon M, Jalfre M. Depression: new animal model sensitive to antidepressant treatments. Nature 1977;266:730–2. [24] Sequeira-Cordero A, Mora-Gallegos A, Cuenca-Berger P, Fornaguera-Trías J. Individual differences in the immobility behavior in juvenile and adult rats are associated with monoaminergic neurotransmission and with the expression of corticotropin-releasing factor receptor 1 in the nucleus accumbens. Behav Brain Res 2013;252:77–87. [25] Ottoni E. EthoLog 2.2: a tool for the transcription and timing of behavior observation sessions. Behav Res Methods Instrum Comput 2000;32(3):446–9. [26] Marini F, Pozzato C, Andreetta V, Jansson B, Arban R, Domenici E, et al. Single exposure to social defeat increases corticotropin-releasing factor and glucocorticoid receptor mRNA expression in rat hippocampus. Brain Res 2006;1067:25–35. [27] Rage F, Silhol M, Binamé F, Arancibia S, Tapia-Arancibia L. Effect of aging on the expression of BDNF and TrkB isoforms in rat pituitary. Neurobiol Aging 2007;28:1088–98. [28] Santos AR, Duarte CB. Validation of internal control genes for expression studies: effects of the neurotrophin BDNF on hippocampal neurons. J Neurosci Res 2008;86(16):3684–92. [29] Hellemans J, Mortier G, De Paepe A, Speleman F, Vandesompele J. qBase relative quantification framework and software for management and automated analysis of real-time quantitative PCR data. Genome Biol 2007;8(2):R19. [30] Brenes JC, Rodríguez O, Fornaguera J. Differential effect of environment enrichment and social isolation on depressive-like behavior, spontaneous activity and serotonin and norepinephrine concentration in prefrontal cortex and ventral striatum. Pharmacol Biochem Behav 2008;89(1):85–93. [31] Kabbaj M. Neurobiological bases of individual differences in emotional and stress responsiveness: high responders-low responders model. Arch Neurol 2004;61(7):1009–12. [32] Shishkina GT, Kalinina TS, Berezova IV, Bulygina VV, Dygalo NN. Resistance to the development of stress-induced behavioral despair in the forced swim test associated with elevated hippocampal Bcl-xl expression. Behav Brain Res 2010;213(2):218–24. [33] Castrén E. Neurotrophins as mediators of drug effects on mood, addiction, and neuroprotection. Mol Neurobiol 2004;29(3):289–302. [34] Gourley SL, Kedves AT, Olausson P, Taylor JR. A history of corticosterone exposure regulates fear extinction and cortical NR2B, GluR2/3, and BDNF. Neuropsychopharmacology 2009;34(3):707–16. [35] Ceretta LB, Réus GZ, Stringari RB, Ribeiro KF, Zappellini G, Aguiar BW, et al. Imipramine treatment reverses depressive-like behavior in alloxan-diabetic rats. Diabetes Metab Res Rev 2012;28(2):139–44. [36] Li LF, Lu J, Li XM, Xu CL, Deng JM, Qu R, et al. Antidepressant-like effect of magnolol on BDNF up-regulation and serotonergic system activity in unpredictable chronic mild stress treated rats. Phytother Res 2012;26(8):1189–94. [37] Berton O, McClung CA, Dileone RJ, Krishnan V, Renthal W, Russo SJ, et al. Essential role of BDNF in the mesolimbic dopamine pathway in social defeat stress. Science 2006;311(5762):864–8. [38] Yu H, Chen ZY. The role of BDNF in depression on the basis of its location in the neural circuitry. Acta Pharmacol Sin 2011;32(1):3–11.

69

[39] Mogenson GJ, Yang CR, Yim CY. Influence of dopamine on limbic inputs to the nucleus accumbens. Ann N Y Acad Sci 1988;537:86–100. [40] Grace AA. Gating of information flow within the limbic system and the pathophysiology of schizophrenia. Brain Res Brain Res Rev 2000;31:330–41. [41] Altar CA, Cai N, Bliven T, Juhasz M, Conner JM, Acheson AL, et al. Anterograde transport of brain-derived neurotrophic factor and its role in the brain. Nature 1997;389(6653):856–60. [42] Meng QY, Chen XN, Tong DL, Zhou JN. Stress and glucocorticoids regulated corticotropin releasing factor in rat prefrontal cortex. Mol Cell Endocrinol 2011;342(1–2):54–63. [43] Sutherland JE, Burian LC, Covault J, Conti LH. The effect of restraint stress on prepulse inhibition and on corticotropin-releasing factor (CRF) and CRF receptor gene expression in Wistar-Kyoto and Brown Norway rats. Pharmacol Biochem Behav 2010;97(2):227–38. [44] Holahan MR, Kalin NH, Kelley AE. Microinfusion of corticotropin-releasing factor into the nucleus accumbens shell results in increased behavioral arousal and oral motor activity. Psychopharmacology (Berl) 1997;130(2):189–96. [45] Peciña S, Schulkin J, Berridge KC. Nucleus accumbens corticotropin-releasing factor increases cue-triggered motivation for sucrose reward: paradoxical positive incentive effects in stress? BMC Biol 2006;4:8. [46] Merchenthaler I, Vigh S, Petrusz P, Schally AV. Immunocytochemical localization of corticotropin-releasing factor (CRF) in the rat brain. Am J Anat 1982;165(4):385–96. [47] Swanson LW, Sawchenko PE, Rivier J, Vale WW. Organization of ovine corticotropinreleasing factor immunoreactive cells and fibers in the rat brain: an immunohistochemical study. Neuroendocrinology 1983;36(3):165–86. [48] Groenewegen HJ, Wright CI, Beijer AV, Voorn P. Convergence and segregation of ventral striatal inputs and outputs. Ann N Y Acad Sci 1999;877:49–63. [49] Slattery DA, Cryan JF. Using the rat forced swim test to assess antidepressant-like activity in rodents. Nat Protoc 2012;7(6):1009–14. [50] Joëls M, Baram TZ. The neuro-symphony of stress. Nat Rev Neurosci 2009;10(6):459–66. [51] Casey BJ, Jones RM, Hare TA. The adolescent brain. Ann N Y Acad Sci 2008;1124:111–26. [52] Dahl RE. Adolescent brain development: a period of vulnerabilities and opportunities. Keynote address. Ann N Y Acad Sci 2004;1021:1–22. [53] Jankord R, Solomon MB, Albertz J, Flak JN, Zhang R, Herman JP. Stress vulnerability during adolescent development in rats. Endocrinology 2011;152(2):629–38. [54] Ixart G, Szafarczyk A, Belugou JL, Assenmacher I. Temporal relationships between the diurnal rhythm of hypothalamic corticotrophin releasing factor, pituitary corticotrophin and plasma corticosterone in the rat. J Endocrinol 1977;72(2):113–20. [55] Garrick NA, Hill JL, Szele FG, Tomai TP, Gold PW, Murphy DL. Corticotropin-releasing factor: a marked circadian rhythm in primate cerebrospinal fluid peaks in the evening and is inversely related to the cortisol circadian rhythm. Endocrinology 1987;121(4):1329–34. [56] Bova R, Micheli MR, Qualadrucci P, Zucconi GG. BDNF and trkB mRNAs oscillate in rat brain during the light–dark cycle. Brain Res Mol Brain Res 1998;57(2):321–4. [57] Schaaf MJ, Duurland R, de Kloet ER, Vreugdenhil E. Circadian variation in BDNF mRNA expression in the rat hippocampus. Brain Res Mol Brain Res 2000;75(2):342–4.