Metabonomics Approach to Understanding Acute and Chronic

On day 1, rats of the CE group were exposed to −10 °C for 2 h, while rats of the ... A twenty-four hour urine sample from each animal was collected...
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Metabonomics Approach to Understanding Acute and Chronic Stress in Rat Models† Xiaoyan Wang,‡,§ Tie Zhao,‡,§ Yunping Qiu,‡ Mingming Su,‡ Tao Jiang,| Mingmei Zhou,| Aihua Zhao,‡ and Wei Jia*,⊥ Shanghai Center for Systems Biomedicine, and School of Pharmacy, Shanghai Jiao Tong University, Shanghai, 200240, People’s Republic of China, Shanghai University of Traditional Chinese Medicine, Shanghai, 201203, People’s Republic of China, and Department of Nutrition, University of North Carolina at Greensboro, North Carolina Research Campus, Kannapolis, North Carolina 28081 Received December 18, 2008

The effects of acute and chronic stress on the production of systemic metabolites were investigated in male Sprague-Dawley (SD) rats. Metabolites excreted in urine were analyzed using GC/MS in conjunction with multivariate and univariate statistical techniques. SD rats were subjected to two kinds of acute stress and chronic unpredictable mild stress, respectively. Metabolic analysis demonstrated that urinary expression of a number of metabolites including glutamate, glutamine, homovanillate, proline, succinate, citrate, and tyrosine altered in the acute stress model in the same way as in the chronic model, while pimelate and hippurate changed in the opposite trend. The results suggested that the stress induced metabolic perturbations were reversible and nonspecific. Metabolic response to chronic combined stress revealed biochemical clues to depression-like symptoms validated by behavior and physiologic results. This study provides a noninvasive and dynamic analytical strategy for the characterization of endogenous metabolic perturbations induced by external stress. Keywords: metabonomics • acute stress • chronic stress • urine • gas chromatography/mass spectrometry • multivariate analysis

Introduction Stress is experienced in all human subjects (and other biological systems) during their lifetimes, affects multiple biochemical regulatory systems, and triggers many conditions and disorders, including hypertension, gastric ulcer, depression, etc.1 Consequently, stress physiology has become an essential means to explore the pathogenesis of physical and mental diseases.2,3 A growing awareness that fast-paced lifestyles can cause physiologic and psychological stress has led to a increasing number of experimental studies on various stress-induced diseases.4 It has been reported that certain stressful events, especially chronic and low intensity daily pressures affecting the central nervous system, are the main cause of depression.5 Accordingly, experimental animal models of “chronic stress” were established to further pathomechanistic research. In these animal models, chronic mild stress due to daily physical and mental irritations were found to closely mimic the stress of human society, and so have become the most commonly used animal model for experimental depression studies. * To whom correspondence should be addressed. E-mail: [email protected]. † Originally submitted and accepted as part of the “Tissue Proteomics and Metabolomics” special section, published in the April 2009 issue of J. Proteome Res. (Vol. 8, No. 4). ‡ Shanghai Jiao Tong University. § These authors contributed equally to this work. | Shanghai University of Traditional Chinese Medicine. ⊥ University of North Carolina at Greensboro, North Carolina Research Campus. 10.1021/pr801086k CCC: $40.75

 2009 American Chemical Society

Currently, stress and depression research focuses primarily on molecular biological studies that use invasive procedures to obtain samples such as plasma, tissue, and cerebrospinal fluid. These invasive sample collections may cause agitation and serve as additional sources of stress, thus complicating the interpretation of data. The one-point and single-targeting data collection window of this method does not reflect the dynamic and systemic effects of stress. Another issue is that the behavior evaluation is subjective, often leading to ambiguous conclusions for many pathological and pharmacological studies.6 The urinary metabonomics study can be a noninvasive approach that is able to collect continuous data from numerous targets simultaneously, avoiding many limitations of current research methods. Understanding the systemic metabolic effects of various stressors will enhance our current knowledge of both acute and chronic stress on the initiation and development of depressive disorders. The emerging metabolite profiling method, using NMR and GC/MS in conjunction with modern multivariate statistical techniques, has successfully captured considerable biochemical changes in psychologically stressed rats.1,4,7 Our previous research has developed a series of study methods based on GC/MS to identify the metabolic influence of acute cold stress as well as the antistress effects of ginsenosides.4 The current study was designed as a follow-up investigation to compare the metabolic influence of two different acute stressorssexposure to -10 ( 2 °C for 2 h and swimming at room temperature for 20 minsand chronic unpredictable mild Journal of Proteome Research 2009, 8, 2511–2518 2511 Published on Web 03/18/2009

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Table 1. Schedule of CUMS items Stressors

Forced swimming 5 min Room temperature 40 °C for 5 min Water deprivation 24 h Food deprivation 24 h Squeeze tail for 1 min Electric shock for 10s Day and night reversal Room temperature -10 °C for 30 min Behavior restriction 2 h

Days of CUMS Experiments

1 2 3 4 5 6 7 8 9

16 15 12 10 11 14 13 17 18

25 21 24 23 22 20 19 26 27

stress on adult male Sprague-Dawley (SD) rats. In this study, we performed a comprehensive analysis of urinary metabolites from SD rats exposed to acute and chronic stimuli to investigate the stress induced biochemical responses and metabolic consequences. Behavioral tests, body weight, sucrose consumption, and stress hormone levels were recorded to crossvalidate the metabonomics data of stressed animals.

Experimental Methods Animal Handling and Sampling. The animal study was conducted in accordance with the Chinese national legislation and local guidelines, and was performed at the Centre of Laboratory Animals, Shanghai University of Traditional Chinese Medicine, Shanghai, P. R. China. Eight-week-old male SD rats (for stable metabolic status) (200 ( 20 g) were purchased from the Shanghai Laboratory Animal Co. Ltd. (SLAC, Shanghai, China), housed individually in stainless steel wire mesh cages, and provided with a certified standard rat chow and tap water ad libitum. Room temperature and humidity were regulated at 24 ( 1 °C and 45 ( 15%, respectively. A light cycle of 12 h on and 12 h off was set, with lights on at 8 a.m. After 2 weeks of acclimatization in metabolic cages, rats were grouped for the two experiments. Experiment 1. Rats were randomly divided into the following three groups: cold exposure group (CE), forced swim group (FS), and control group (C). A twenty-four-hour baseline urine sample was collected from each animal on day 0. On day 1, rats of the CE group were exposed to -10 °C for 2 h, while rats of the FS group were forced to swim in 80 cm deep water at room temperature for 20 min, then taken out, dried, and returned to metabolic cages at room temperature. For the remainder of the day, all animals were housed in normal conditions without disturbances. Urine samples were collected for a 24-h period from each animal on day 1, 2 and 6; all urine samples were centrifuged at 6000 g for 10 min at room temperature to remove particle contaminants. The resultant supernatants were stored at -80 °C pending metabonomic analysis. Experiment 2. Rats were randomly divided into two groups s the chronic unpredictable mild stress (CUMS) group (n ) 6) was exposed to chronic mild stress from day 1 through day 27 and the control group (n ) 6) was not exposed to stress. CUMS consisted of alternating stressors: forced swimming for 5 min, at 40 °C for 5 min, water deprivation for 24 h, food deprivation for 24 h, tail squeezing for 1 min, electric shock for 10 s, reversal of day and night, exposure to -10 °C for 30 min, and 2-h behavior restriction.8,9 The CUMS group was exposed to one type of stress daily between 9:30 and 11:30 a.m. according to the randomly designed schedule in Table 1. Body weight, food consumption, sucrose intake, and results of an 2512

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open-field test were recorded for each rat on day 0, 9, and 27. Plasma and serum were collected at the end of the entire experiment on day 27. A twenty-four hour urine sample from each animal was collected at day 0, 9, and 27, and centrifuged at 6000 g for 10 min at room temperature to remove particle contaminants. The resultant supernatants were stored at -80 °C pending metabonomic analysis. GC/MS Sample Preparation, Derivatization, and Spectral Acquisition. Urine samples were prepared for GC/MS and relevant spectral acquisition was obtained according to published methods with minor modifications.7 Briefly, a 600-µL aliquot of urine sample diluted with an equal volume of water was derivatized with ethyl chloroformate, using L-2-chlorophenylalanine as an internal standard to monitor batch reproducibility. A 1-µL aliquot of analyte was injected into a DB-5MS capillary column coated with 5% diphenyl cross-linked 95% dimethylpolysiloxane (30 m × 250 µm i.d., 0.25-µm film thickness (Agilent J&W Scientific, Folsom, U.S.A.) and GC/MS was conducted on a hyphenated Perkin-Elmer gas chromatograph and TurboMass coupled to an Autosystem XL mass spectrometer (PerkinElmer Inc., U.S.A.) as described. Data Reduction and Pattern Recognition. Unprocessed GC/ MS files were converted into NetCDF format via DataBridge (Perkin-Elmer Inc., U.S.A.) and directly processed by our custom scripts in MATLAB (The MathWorks, Inc., U.S.A.), to carry out baseline correction, peak discrimination and alignment, internal standard exclusion, and normalization to the total sum of the chromatogram. The resulting three-dimensional matrix, including arbitrary compound index (paired retention time-m/z), sample names (observations), and normalized peak areas (variables) were introduced into the SIMCA-P 11.0 Software package (Umetrics, Umeå, Sweden) for multivariate statistical analysis. The peak areas of the metabolites with relatively high concentrations among samples were carefully examined, no drastic alterations were found. The data normalization was performed prior to the multivariate analysis, according to previously published data pretreatment method.10,11 The pareto/unit variance scaled, normalized data were then analyzed by principal component analysis (PCA) to visualize general clustering, trends, or outliers among the observations. Partial least-squares-discriminant analysis (PLS-DA) validated the PCA model and identified the metabolites differentially produced by CUMS exposure. To avoid overfitting of the models, the PLSDA model was carefully validated by an iterative 7-round cross-validation10 with 1/7 of the samples being excluded from the model in each round and 1000 random permutations testing.12 A correlation coeffcient (Corr(t,X)) of ( 0.7, with a significance level of 0.05, was adopted as a cutoff value to select the most important variables for PLSDA models of the integrated MS data.10 Differentially expressed metabolites were identified by chromatogram-MS data and labeled using thresholds of the fold change and p-values of the Kruskal-Wallis test. In addition to the nonparametric test, classical one-way analysis of variance (ANOVA) was also used to judge statistical significance of the results. The critical p value of both tests was set to 0.05 for this study. Behavioral Investigation of CUMS Group. In experiment 2, an open-field test was conducted in a quiet room between 1 and 3 p.m. Each animal was placed in the central square of rectangular arena (80 × 80 cm2 with 40-cm-high side walls, the floor marked with a grid dividing it into 25 equal-size squares) and observed for 5 min. A record was kept of the amount of

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Figure 1. Effects of two acute stresses on urinary metabolic variation. PCA scores plot (PC1 versus PC2). (A) Before and after cold exposure (CE) and forced swimming (FS). (B) Control group on day 0 and 1. (C) Most significant metabolites accounting for metabolic differences caused by the two acute stresses derived from a PLS-DA model (the scores plot, loading plot, cumulative Q2Y, and permutation testing result of the PLSDA model are provided in Supplemental Table 1 and Supplemental Figure 1).

time spent grooming and rearing (defined as standing upright on hind legs) and the number of grid lines crossed with at least three paws. Every incidence of grooming or rearing counted as one point, every grid crossed counted as one point, and the behavioral score was the total number of points. The apparatus was cleaned between animal tests. Sucrose Preference Test. The rats were trained to the sweet taste as described previously.13,14 Briefly, single housed rats were introduced to 1% sucrose solution supplied in two drinking bottles 48 h prior to the test. Then 24 h later, the sucrose preference test was carried out by providing rats with two bottles for 1 hsone bottle filled with 1% sucrose and the other with water. Food and water were withheld from rats for 14 h before the sucrose preference test. Food Consumption and Body Weight. Rat chow was added into the feed bucket of each rat at 5 p.m. After 24 h, the uneaten food was removed, weighed, and the weight recorded. At the same time, the body weight of each rat was recorded. Stress Hormone Determination. After sacrificing the rats, a trunk blood sample from each rat was collected and divided into two tubs: one with heparin coating the inner wall, the other without heparin. Blood in the heparin tub was centrifuged at

800 × g for 10 min, and the supernatant removed and stored at -80 °C until analysis was performed. Blood in the other tub was allowed to clot at room temperature before centrifuging and freezing. The plasma adrenocorticotropic hormone (ACTH) concentrations were measured using the Adrenocorticotropic Hormone Radioimmunoassay Kit D14 PGA (Beijing, North Institute of Biological Technology Co). The blood serum corticosterone (CORT) concentrations were measured using the Rat Corticosterone RIA Kit DSL-80100 (Diagnostic Systems Laboratories, Inc. U.S.A.). Statistical Analysis. Data from the behavioral investigation and the stress hormone determination were expressed as mean ( SD. Differences between the means of the treatment and control groups were analyzed using one-way analysis of variance (ANOVA). The critical p value was set at 0.05.

Results Metabolic Variation Induced by Acute Stress. The scores plot derived from the GC/MS data (PC (principal component) 1 vs PC2) is depicted in Figure 1A. The scores plot, loading plot, cumulative Q2Y, and permutation testing result of the PLSDA model corresponding to PCA model as shown in Figure 1A are Journal of Proteome Research • Vol. 8, No. 5, 2009 2513

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Figure 2. Time-dependent PCA trajectory of PCA showing timedependent trajectory for the control group (C), cold exposure group (CE), and forced swim group (FS) on days 1, 2, and 6.

demonstrated in Supplemental Table 1 and Supplemental Figure 1 (see Supporting Information). It shows two distinct clusters without overlap between the samples of the CE and FS groups on day 0 and day 1, (i.e., comparison of the rat metabolic status before and after acute stress). Meanwhile, samples taken during the same time periods from the control group were not clearly separated (Figure 1B). We have combined the two stressors into one influential factor for PCA plots to visualize the general characteristics of stress. To investigate the temporal metabolic variation in rats exposed to stress, MS spectra of all the urine samples collected in the experiment were integrated and coanalyzed using PCA. Metabolic trajectories were obtained from the mean scores value of PC1 and PC2 shown in Figure 2. This trajectory plot depicts a time-dependent stress reaction consisting of prestress, poststress, and recovery status. Compared to the physiologic variations in the control group, both CE and FS rats deviate considerably from prestress status on day 1, shift toward normal status on day 2, and return to normal status on day 6. Differentially expressed metabolites identified and designated according to the corresponding GC/MS analysis were summarized in Figure 1C. Among the metabolites differentially produced immediately after stress, several compounds (e.g., glycine, glutamine, citrate, glutamate, homovanillate, and hippurate) were consistent with those produced during cold stress.4 In the following time point, these metabolites still differed from those of prestress, but with reduced fold changes and significance, reflecting the same tendency as the trajectory plot (Figure 2). Finally on day 6, the metabolite profiles produced by normal and acute stress groups are not significantly different. Metabolic Variation Induced by CUMS. After GC/MS determination and data analysis, a two-dimensional PCA scores plot was used to depict the general variation between groups. Little separation between the two groups was observed in the PCA scores plot on day 0 (Figure 3A). Following 9 days of exposure to CUMS, a clear separation between the chronic stress and control groups was observed in the PCA scores plot, suggesting that exposure to chronic unpredictable mild stress may lead to systemic metabolic variation (Figure 3B). The scores plot, loading plot, cumulative Q2Y and permutation testing results of the PLSDA model corresponding to the PCA model of GC/MS data on day 9 (as shown in Figure 3) are provided in Supplemental Table 1 and Supplemental Figure 2. 2514

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Wang et al. However, after 27 days of exposure to CUMS, metabolic difference between these two groups was not distinct, suggesting that the systemic metabolic network was able to adapt to such environmental stimuli through self-regulation (Figure 3C). Since the PLSDA model was not able to differentiate the two metabolic profiles of the chronic stress and control groups on the 27th days, the identification of urinary metabolite biomarkers responsible for the 27 d exposure to CUMS was carried out by univariate statistical analysissANOVA and Kruskal-Wallis test with the threshold of p value set at 0.05. A number of important urinary metabolites contributing to the differences in metabolic profiles between the chronic stress model and control groups were identified and are summarized in Figure 3D. Clear separations between metabolic states after 0, 9, and 27 days of CUMS rats were observed (Figure 4A), suggesting that exposure to unpredictable chronic stress may lead to a gradual metabolic variation in SD rats. Metabolic variations in the control rats due to physiological changes with time were also observed (Figure 4B). Behavioral Investigation Results. The open-field test scores were decreased by CUMS, particularly on day 27, as shown in Figure 5A. The reduced activity and curiosity of model animals fits the clinical psychomotor symptoms of depression. Chronic stress also resulted in induced food consumption and body weight, similar to the loss of appetite experienced by patients with depression.15 In this animal experiment, the food consumption of rats decreased initially, but recovered as the CUMS continued, with the body weight increasing moderately (Supplemental Table 2). Sucrose consumption reflects the rats’ preference for sweet tastes, learned before the test. When faced with the choice between bottles of pure water and sucrose solution, rats normally prefer to drink the sucrose solution. Anhedonia is the loss of interest in stimuli normally found to be rewarding, a core symptom of clinical depression. Sucrose consumption is well accepted as a criterion for evaluating a depressive rat model.16,17 In this study, sucrose consumption began to decrease by day 9 in the CUMS model group, further decreasing by day 27, indicating CUMS-induced anhedonia of rats (Figure 5B). Stress Hormone Variation. The hypothalamic-pituitaryadrenocortical (HPA) axis plays a critical role in regulating adrenal cortex functionsthe production and secretion of glucocorticoids, hormones required in managing stressful stimuli. Chronic stress undoubtedly affects the HPA axis, but it is unclear whether it causes an increase or decrease in glucocorticoids (e.g., ACTH, CORT), due to the transient variation at different sampling times. Generally, a single incidence of acute stress induces the secretion of stress hormones, but long-term stress reduces stress hormones levels, probably because of hypoadrenocorticism.18 In the CUMS model group, both ACTH and CORT are decreased on day 27 (Supplemental Table 3), which may indicate chronic stressinduced hypoadrenocorticism.

Discussion Metabonomic technologies have been successfully used to investigate the systemic metabolic response to adverse stimuli including physiologic and psychological stress. Collecting blood samples to assess metabolic changes may lead to agitation; and thus the process of assessing stress may cause additional stress. In contrast, urine sampling, commonly used for in vivo

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Figure 3. PCA scores plot of comparing control group and chronic unpredictable mild stress group on day 0 (A), 9 (B), and 27 (C) and (D). The most significant metabolites accounting for metabolic differences caused by chronic unpredictable mild stress derived from a PLS-DA model (the scores plot, loading plot, cumulative Q2Y and permutation testing result of the PLSDA model were provided in Supplemental Table 1 and Supplemental Figure 2).

metabolic profiling, is noninvasive and therefore does not create additional stress. In this study, we utilized this method to capture the dynamic systemic metabolic variation in both acute (CE and FS) and chronic unpredictable mild stress (CUMS). Metabolic Response to Acute Stress. Cold exposure and the forced swimming caused different physiologic reactions. Exposure to a low ambient temperature for 2 h is a purely physical stimulus, causing vascular contraction and shifting blood flow from the extremities (hands, feet, arms, and legs) and outer skin to the core (chest and abdomen), as well as activating the central nervous system (i.e., stimulating alertness). The 20-min forced swim test was both physically exhausting and psychologically stressful. Although there are many differences between these two stressors, the metabolic impact is similar according to PLS-DA analysis, which elucidated the nonspecificity of stress. In general, the trajectory plot provides time-dependent analysis and a visible means of monitoring the dynamic variation of the majority of samples in the cluster. Different time points of sampling were chosen to reflect the status of prestress, poststress and recovery, according to the prior study.4 The result reveals that the two stressors induced similar metabolic variations with a similar trajectory, resulting in recovery at the end point, so our method may potentially be a suitable approach to noninvasive dynamic stress research.

Our results demonstrated the impact of a single acute stress on body systems as indicated by the up- or downregulated levels of these low-molecular-weight metabolites in both stress groups compared with the control group. Several pathways involving the tricarboxylic acid (TCA) cycle (citrate, succinate), glutamate and glutamine biosynthesis (glutamate, glutamine),19 tyrosine metabolism (tyrosine, homovanillate, 4-hydroxyphenylacetate),20,21 and gut microbiota metabolic activity (4-hydroxyphenylacetate, hippurate)22,23 were affected immediately, and then gradually returned to the normal state concomitant with withdrawal of the stressor. Metabolic Changes in Response to CUMS. In contrast with acute stress, chronic mild stress is more common in daily human life, although it has not yet been associated with disturbances of systemic metabolites that may help elucidate the mechanisms of depression.24 In this study, CUMS led to reduced food consumption, body weight, and sucrose consumption, and to the secretion of two stress hormones, which are similar to the classic symptoms of clinical depression in humans.25 After exposure to CUMS, a number of important metabolites altered contributing to a significantly different metabolic profile of the CUMS group compared to the control. Significant variations of glutamine, glutamate, citrate and homovanillate concentrations were detected at day 9. These variations were Journal of Proteome Research • Vol. 8, No. 5, 2009 2515

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Figure 4. PCA scores plot of variation in urinary metabolites of rats during 27 days of chronic stress. (A) CUMS group. (B) Control group.

Figure 5. Scores of chronically stressed rats on days 0, 9, and 27 for (A) open-field test and (B) sucrose solution consumption (%). * p < 0.05, ** p < 0.01 compared with the control group.

similar to the metabolic response to cold stress, except for different trends in hippurate concentration, presumably associated with disturbance in gut microbial populations.26 Our previous cold stress treatment was acute, while the cold stress treatment for this study consisted of cumulative combined mild cold stresses for 9 days. Different types of stressors resulted in the significant alteration of the same group of metabolites, supporting the concept of “non-specificity” of the physiologic response to stress. Chronic stress treatment also led to down-regulation of threonine, succinate, pimelate, proline, and hexadecanoate and up-regulation of hexanedioate, methionine, phenylalanine, and tyramine. Threonine, an essential amino acid, helps the body maintain protein equilibrium, protects against stress and strengthens immune response.27 It is involved in liver functioning and lipotropic functions when combined with aspartic acid and methionine. It is also involved in assisting the immune system by helping the production of antibodies and promoting thymus growth and activity. Chronic stress could induce thymus involution,28 which may be associated with a down-regulation of threonine. Phenylalanine, another essential amino acid, is converted first to tyrosine by phenylalanine hydroxylase, and then to catecholamines (hormones released by the adrenal glands in response to stress).4 It has been well documented that exercise

increases the concentration of aromatic amino acids, like phenylalanine, in human muscle.29 The elevated phenylalanine levels detected in this study may be caused by fatigue due to resisting the physical stressors in this study (forced swim, behavior restriction, electric shock, and caloric restriction). Tyramine is produced by tyrosine via decarboxylation and is considered to be a downstream metabolite of catecholamines. Another amino acid, methionine, is a methyl acceptor for methionine synthase, the only reaction that allows for the recycling of this form of folate, and also a methyl acceptor for the catabolism of adrenalin. The methionine cycle had been discussed in one of our previous article.30 It has been reported that exposure to stress affects homocysteine metabolism in rats.31 Therefore we conceive that the elevation of methionine level might be indicative of a methionine cycle abnormality. On day 27, the metabolic variation between the control and the model group was reduced in the PCA scores plot compared to day 9 (Figure 3). Seven compounds were similarly produced at the two different time points: pimelate, proline, citrate, glutamate, hippurate, tyramine, and hexadecanoate. In contrast, levels of glutamine and homovanillate changed considerably from day 9 to day 27. Additionally, tyrosine, hexanoate, valine, suberate, 5-hydroxyindoleacetate, tryptophan, and 4-aminohippurate were altered on day 27. Depression-like symptoms were observed in the physiologic and behavior results of the chronic stress model group after

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Understanding Acute and Chronic Stress in Rat Models 27 days CUMS. In support of these findings, the chemometric analysis of samples collected on day 27 showed many differentially produced metabolites associated with depression symptoms. For example, tyrosine, including its metabolites, 4-hydroxyphenylactate and homovanillate, precursor and metabolite of catecholamines respectively, were significantly decreased. Tyramine, another catecholamine product, was increased in the urine samples of animals exposed to CUMS. A decrease in 5-hydroxyindoleacetate, an important metabolite of 5-hydroxytryptamine (5-HT)sthe depression-related neurotransmitter in both central and peripheral bloodswas observed to be decreased following 27 days CUMS. Simultaneously, the relative concentration of tryptophan, a precursor of 5-HT, was also decreased. Along with reports that depression reduces the blood concentrations of both 5-HT and 5-hydroxyindoleacetate,32 and that tryptophan deficiency may induce depressive disorders,33 our results provide evidence for the association between the 5-HT pathway and the onset of depression in the later stages of chronic stress. Glutamine is a significantly fluctuating metabolite which initially decreased at day 9, then increased at day 27, while homovanillate level significantly increased and then decreased. The fluctuation of these two metabolites indicates the altered activities of glutamine synthetase and catecholamine turnover under prolonged stress condition. The increased production of 4-aminohippurate (a metabolite related to gut microbiota like hippurate) observed on day 9 was further elevated at day 27, suggesting increased disturbance of the gut microbiota as CUMS progressed. This is supported by a significant alteration of organic acid production by gut microflora in association with CUMS, including hexanoate, pimelate, and suberate, at day 27. Metabolic Changes Response to both acute and chronic stress. In Figures 1C and 3D, it is interesting to note that there are 6 differential metabolites, glutamate, glutamine, homovanillate, proline, succinate, citrate, and tyrosine, in the same trend (marked by *). Meanwhile, 2 metabolites, pimelate and hippurate, are in the opposite trend (marked by #), when compared to acute stress on day 9 of CUMS. These coincidences actually prove the similar impacts of the two different types of stress on systemic metabolic pathways.

Conclusion In summary, a urinary metabolite profiling using high resolution analytical means such as GC/MS in conjunction with modern multivariate statistical techniques permits noninvasive, simultaneous monitoring of numerous metabolic pathways. Two kinds of stress, acute stress and combined chronic stress produced a similar metabolic variation that was time-dependently reversible in rat urine using this metabonomic method. Some biochemical pathways were transiently impacted, then gradually recovered in the days following the withdrawal of stressors; while several biological pathways (such as tyrosine, tryptophan, and glutamine pathways) became progressively affected, leading to depression-like symptoms if the stressor persisted for a longer period of time. Abbreviations: GC/MS, gas chromatography/mass spectrometry; CUMS, chronic unpredictable mild stress; PCA, principal component analysis; PLS-DA, partial least-squaresdiscriminant analysis; SD, Sprague-Dawley; CE, cold exposure group; FS, forced swim group; C, control group.

Acknowledgment. This work was financially supported by the National Basic Research Program of China

(2007CB914700), the International Collaborative Project of Chinese Ministry of Science and Technology (2006DFA02700), and the project of Chinese Ministry of Science and Technology (2006BAI08B04-01).

Supporting Information Available: The parameters of PLSDA model. Food consumption and body weight of rats during the period of chronic stress. Plasma ACTH and serum CORT value in rat blood at the end point of CUMS. The score plots, loading plots and permutation testing results. This material is available free of charge via the Internet at http:// pubs.acs.org. References (1) Teague, C. R.; Dhabhar, F. S.; Barton, R. H.; Beckwith-Hall, B.; Powell, J.; Cobain, M.; Singer, B.; McEwen, B. S.; Lindon, J. C.; Nicholson, J. K.; Holmes, E. Metabonomic studies on the physiological effects of acute and chronic psychological stress in Sprague-Dawley rats. J. Proteome Res. 2007, 6 (6), 2080–93. (2) Kanayama, N.; Khatun, S.; Belayet, H.; She, L.; Terao, T. Chronic local cold stress to the soles induces hypertension in rats. Am. J. Hypertens. 1999, 12 (11 Pt 1), 1124–9. (3) Chrousos, G. P. The role of stress and the hypothalamic-pituitaryadrenal axis in the pathogenesis of the metabolic syndrome: neuro-endocrine and target tissue-related causes. Int. J. Obes. Relat. Metab. Disord. 2000, 24 (2), S50-5. (4) Wang, X.; Su, M.; Qiu, Y.; Ni, Y.; Zhao, T.; Zhou, M.; Zhao, A.; Yang, S.; Zhao, L.; Jia, W. Metabolic regulatory network alterations in response to acute cold stress and ginsenoside intervention. J. Proteome Res. 2007, 6 (9), 3449–55. (5) Joca, S. R.; Padovan, C. M.; Guimaraes, F. S. Stress, depression and the hippocampus. Rev. Bras. Psiquiatr. 2003, 25 (2), 46–51. (6) Paizanis, E.; Hamon, M.; Lanfumey, L. Hippocampal neurogenesis, depressive disorders, and antidepressant therapy. Neural Plast. 2007, 2007, 73754. (7) Qiu, Y.; Su, M.; Liu, Y.; Chen, M.; Gu, J.; Zhang, J.; Jia, W. Application of ethyl chloroformate derivatization for gas chromatography-mass spectrometry based metabonomic profiling. Anal. Chim. Acta 2007, 583, 277–283. (8) Murua, V. S.; Gomez, R. A.; Andrea, M. E.; Molina, V. A. Shuttlebox deficits induced by chronic variable stress: reversal by imipramine administration. Pharmacol., Biochem. Behav. 1991, 38 (1), 125–30. (9) Papolos, D. F.; Yu, Y. M.; Rosenbaum, E.; Lachman, H. M. Modulation of learned helplessness by 5-hydroxytryptamine2A receptor antisense oligodeoxynucleotides. Psychiatry Res 1996, 63 (2-3), 197–203. (10) Ni, Y.; Su, M.; Lin, J.; Wang, X.; Qiu, Y.; Zhao, A.; Chen, T.; Jia, W. Metabolic profiling reveals disorder of amino acid metabolism in four brain regions from a rat model of chronic unpredictable mild stress. FEBS Lett. 2008, 582 (17), 2627–36. (11) Dumas, M. E.; Barton, R. H.; Toye, A.; Cloarec, O.; Blancher, C.; Rothwell, A.; Fearnside, J.; Tatoud, R.; Blanc, V.; Lindon, J. C.; Mitchell, S. C.; Holmes, E.; McCarthy, M. I.; Scott, J.; Gauguier, D.; Nicholson, J. K. Metabolic profiling reveals a contribution of gut microbiota to fatty liver phenotype in insulin-resistant mice. Proc. Natl. Acad. Sci. U.S.A. 2006, 103 (33), 12511–6. (12) Westerhuis, J. A.; Hoefsloot, H. C. J.; Smit, S.; Vis, D. J.; Smilde, A. K.; van Velzen, E. J. J.; van Duijnhoven, J. P. M.; van Dorsten, F. A. Assessment of PLSDA cross validation. Metabolomics 2008, 4 (1), 81–89. (13) Harro, J.; Tonissaar, M.; Eller, M.; Kask, A.; Oreland, L. Chronic variable stress and partial 5-HT denervation by parachloroamphetamine treatment in the rat: effects on behavior and monoamine neurochemistry. Brain Res. 2001, 899 (1-2), 227–39. (14) Dalla, C.; Antoniou, K.; Drossopoulou, G.; Xagoraris, M.; Kokras, N.; Sfikakis, A.; Papadopoulou-Daifoti, Z. Chronic mild stress impact: are females more vulnerable. Neuroscience 2005, 135 (3), 703–14. (15) Sohlberg, S. Personality, life stress and the course of eating disorders. Acta Psychiatr. Scand. Suppl. 1990, 361, 29–33. (16) Baker, S. L.; Kentner, A. C.; Konkle, A. T.; Santa-Maria Barbagallo, L.; Bielajew, C. Behavioral and physiological effects of chronic mild stress in female rats. Physiol. Behav. 2006, 87 (2), 314–22. (17) Yadid, G.; Nakash, R.; Deri, I.; Tamar, G.; Kinor, N.; Gispan, I.; Zangen, A. Elucidation of the neurobiology of depression: insights from a novel genetic animal model. Prog. Neurobiol. 2000, 62 (4), 353–78.

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