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Omics studies of the murine intestinal ecosystem exposed to subchronic and mild social defeat stress Ayako Aoki-Yoshida, Reiji Aoki, Naoko Moriya, Tatsuhiko Goto, Yoshifumi Kubota, Atsushi Toyoda, Yoshiharu Takayama, and Chise Suzuki J. Proteome Res., Just Accepted Manuscript • DOI: 10.1021/acs.jproteome.6b00262 • Publication Date (Web): 02 Aug 2016 Downloaded from http://pubs.acs.org on August 3, 2016

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Journal of Proteome Research

Omics studies of the murine intestinal ecosystem exposed to subchronic and mild social defeat stress Running title: Omics studies of the gut of depression model mice Ayako Aoki-Yoshida1, §, Reiji Aoki1, Naoko Moriya1, Tatsuhiko Goto2, 3, ¶, Yoshifumi Kubota2,†, Atsushi Toyoda2, 3, 4, Yoshiharu Takayama1 and Chise Suzuki1* 1

Institute of Livestock and Grassland Science, National Agriculture and Food Research

Organization (NARO), Tsukuba, Ibaraki 305-0901, Japan. 2 College 3

of Agriculture, Ibaraki University, Ami, Ibaraki 300-0393, Japan.

Ibaraki University Cooperation between Agriculture and Medical Science (IUCAM),

Ami, Ibaraki 300-0393, Japan. 4 United

Graduate School of Agricultural Science, Tokyo University of Agriculture and

Technology, Fuchu-city, Tokyo 183-8509, Japan. §

Current address: Graduate School of Agricultural and Life Sciences, The University of

Tokyo, Yayoi, Bunkyo-ku, Tokyo 113-8657, Japan. † Current address: Central Research Institute for Feed and Livestock, National Federation

of Agricultural Cooperative Associations, Tsukuba, Ibaraki 300-4204, Japan. ¶

Current address: Genetics, Ecology and Evolution, School of Life Sciences, The

University of Nottingham, University Park, Nottingham, NG7 2RD, UK * Corresponding author. To whom corresponding to be addressed Chise Suzuki, Ph.D. Animal Products Research Division Institute of Livestock and Grassland Science, NARO 2 Ikenodai, Tsukuba, Ibaraki 305-0901, Japan telephone: +81-29-838-8687 fax number: +81-29-838-8606 e-mail address: [email protected]

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Abstract The microbiota-gut-brain axis plays an important role in the development of stress-induced mental disorders. We previously established the subchronic and mild social defeat stress (sCSDS) model, a murine experimental model of depression, and investigated the metabolomic profiles of plasma and liver. Here, we used omics approaches to identify stress-induced changes in the gastrointestinal tract. Mice exposed to sCSDS for 10 days showed the following changes: 1) elevation of cholic acid and reduction of 5-aminovaleric acid among cecal metabolites; 2) downregulation of genes involved in the immune response in the terminal ileum; 3) a shift in the diversity of the microbiota in cecal contents and feces; and 4) fluctuations in the concentrations of cecal metabolites produced by gut microbiota reflected in plasma and hepatic metabolites. Operational taxonomic units (OTUs) within the family Lachnospiraceae showed an inverse correlation with certain metabolites. The social interaction score correlated with cecal metabolites, IgA, and cecal and fecal microbiota, suggesting that sCSDS suppressed the ileal immune response, altering the balance of microbiota, which together with host cells and host enzymes resulted in a pattern of accumulated metabolites in the intestinal ecosystem distinct from that of control mice. Keywords: Social defeat stress, ileum, cecum, microbiota-gut-brain axis, cholic acid, depression


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Introduction Excessive stress has adverse effects on human and animal health. Stress has been implicated as a cause or contributing factor in various diseases, and it is the most common risk factor for the development of mood disorders such as depression.1 Chronic social defeat stress (CSDS)

2

is widely used to develop animal models of

depression. Despite different durations and frequencies of exposure to CSDS used by different investigators, the model is based on the resident intruder paradigm or inter-male aggression.2,

3

In previous work from our group, we developed a mouse

model using the subchronic and mild social defeat stress (sCSDS) paradigm. In that study, mice exposed to standard CSDS showed reduced body weight in response to a 10 day session of CSDS; however, mice exposed to sCSDS (sCSDS mice) retained more water than control mice, which accounted for an increase in body weight, in addition to exhibiting social deficit-associated behaviors and hyperphagia.4 Furthermore, we showed that exposure to sCSDS increases the levels of several hepatic metabolites, such as taurocyanine and phosphorylcholine,5 and reduces hepatic coenzyme A molecular species 6 in parallel with the appearance of early stage depression-like symptoms. The mutual interactions between the central nervous system (CNS), the enteric nervous system, and the gut microbiota (the microbiota-gut-brain axis) have been characterized.7 The microbiota-gut-brain axis has the potential to modulate emotion, behavior, and the mucosal immune system.7, 8 Psychological stress affects the function of the gastrointestinal tract.9,

10

For example, exposing adult mice to prolonged

restraint stress significantly alters microbial profiles in the cecal content.11 However, the gut microbiota is important for normal healthy brain function.12,

13

Gut microbiota

depletion by antibiotics affects mental behavior and the expression of neuromodulators in juvenile mice.14 Exposure to psychological stressors disrupts the intestinal bacterial community.15-17 Studies show that exposure to 2 hours of social defeat stress repeated over 6 consecutive nights or even a single application affects the population profile of the intestinal microbiota.15,

18

The gut is a complex ecosystem composed of host

intestinal cells, microbiota, and digested materials, including metabolites produced by the host and microbiota; however, few studies have focused on understanding the gut as an ecosystem. In the present study, the intestinal ecosystem of sCSDS mice showing some phenotypes including social deficit-associated behavior, polydipsia, and 3 ACS Paragon Plus Environment


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hyperphagia was compared with that of control mice. We used a multifaceted approach consisting of microarray analysis of ileal gene expression, metabolome analysis of cecal metabolites, and metagenome analysis of cecal and fecal microbiota to understand the effects of psychological stress on the gut. The mutual interactions of these factors and their systemic effects are discussed. Experimental Procedures Animals This study was approved by the Animal Care and Use Committee of Ibaraki University and the Animal Care Committee of the National Institute of Livestock and Grassland Science, and conformed to the guidelines of the Ministry of Education, Culture, Sports, Science, and Technology (MEXT) of Japan (Notification No. 71) and the Guide for the Care and Use of Experimental Animals (National Agriculture and Food Research Organization; NARO). Male C57BL/6JJmsSlc (B6) mice (7 weeks of age) and male Slc:ICR (ICR) mice (older than 5 months of age) were purchased from SLC Japan (Shizuoka, Japan) and reared in the animal facility of the College of Agriculture, Ibaraki University. B6 mice had received ad libitum reverse-osmosis–purified drinking water and a semi-purified diet (AIN-93G, Oriental Yeast, Tokyo, Japan). The dietary ingredients and food composition were described in the Supporting Information of our previous study.5 Experimental Design of sCSDS The sCSDS was performed as described previously.4, 5, 19 The sCSDS model used in the present study is based on the resident intruder paradigm between an older resident ICR mouse and a younger intruder B6 mouse. The experimental model consisted of physical and sensory contact between resident and intruder for 10 days. The introduction of a B6 mouse into the cage of an ICR mouse resulted in the resident attacking the intruder. The duration of physical contact was limited to 5 min after the first attack bites on Day 1, after which the duration was reduced stepwise by 0.5 min per day. After the initial physical contact, the ICR mouse and the intruder B6 mouse were kept in the same cage for 24 hours with a divider, which enabled sensory contact while preventing physical contact. Control B6 mice were housed in the cage on either side of a divider for 10 days without any physical contact. To evaluate the social behaviors of B6 mice after exposure 4 ACS Paragon Plus Environment

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to sCSDS (sCSDS mice) for 10 days (Day 1–10) and control mice, a social interaction test was performed on Day 11 as described previously.4, 5 Social interaction scores (% of target absent) were estimated as 100 × (interaction time with target present / interaction time with target absent), as described by Krishnan et al.20 Body weight gain, food and water intake, and social interaction scores of the mice in this study were described in our previous study.5 Sampling Samples were obtained from the same mice as used in our previous study.5 Feces were collected from B6 mice on Days 0 and 11, and those of ICR mice were collected on Day 11.

After a 3 hour fast in the morning on Day 13, B6 mice were sacrificed by decapitation. The terminal ileum (1 cm) was removed and immediately placed in RNAlater (QIAGEN, Valencia, CA, USA). The cecal contents were isolated and suspended in nine volumes (weight/volume) of cold phosphate buffered saline (PBS). After centrifugation at 12,000 × g for 5 min, the supernatants and precipitates were quickly frozen in liquid N2 and kept at -80°C until analysis. Metabolomic Analysis of Cecal Contents The supernatants of cecal contents were subjected to capillary electrophoresis time-of-flight mass spectrometry (CE-TOFMS) analysis at Human Metabolome Technology Inc. (Tsuruoka, Japan). The relative area of each compound was calculated using m/z (mass-to-charge ratio), migration time, the peak area of samples, and the internal standard. The concentrations of the major 110 metabolites selected by Human Metabolome Technology Inc. were determined from the peak areas by comparison with the internal standard. Welch t-tests were used to compare the mean differences between the control (n = 5) and stressed (n = 5) groups. The q value, a measure of significance in terms of the false discovery rate (FDR), was calculated by the method of Storey and Tibshirani.21 The significant threshold was set to q < 0.1. Principal component analysis (PCA) was performed using SampleStat software (Human Metabolome Technologies Inc.). The metabolites identified from the metabolome library were assigned to the Kyoto Encyclopedia of Genes and Genomes (KEGG) to facilitate the search for the metabolic pathways involved.22



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Enzyme-linked Immunosorbent assay (ELISA) Total IgA levels in the supernatants of cecal contents were determined by ELISA using a mouse IgA ELISA Quantitation set (Bethyl Lab. Inc., Montgomery, TX, USA). The statistical significance of differences in total IgA levels between control mice and sCSDS mice was analyzed using an unpaired t-test. The statistical analysis of the correlation between cecal IgA production and the number of operational taxonomic units (OTU) reads was performed using Pearson’s test. P values < 0.05 were considered to indicate statistical significance. Microarray Analysis of the Ileum RNA was prepared from terminal ileum extracts preserved in RNAlater using an RNeasy kit (QIAGEN). The integrity of the RNA sample was evaluated using the Experion automated electrophoresis system (Bio-Rad. Laboratories, Inc.). Total RNA (100 ng) was amplified and labeled using the GeneChip 3’ IVT Express Kit (Affymetrix, Santa Clara, CA, USA) according to the manufacturer’s instructions. Biotin-labeled aRNA was analyzed using a GeneChip mouse 430 2.0 array (Affymetrix). Fluorescence data were scanned using the GeneChip Scanner with GeneChip Operating Software (Affymetrix). The microarray data were analyzed using the statistical language R (http://www.r-project.org/) and Bioconductor (http://www.bioconductor.org/). The CEL files were quantified by robust multi-array analysis.23 The rank product (RP) method 24 was used to detect differentially expressed genes between control and sCSDS mice [num.perm (number of permutations used in the calculation of the null density) = 1000]. Gene set enrichment analyses were performed to identify functional classes of differentially expressed genes according to the Biological Process in Gene Ontology (GO) consortium guidelines and the Kyoto Encyclopedia of Genes and Genomes (KEGG) Pathway database.25 All microarray data were submitted to the National Center for

Biotechnology

Information

(NCBI)

Gene

Expression

Omnibus

(http://www.ncbi.nlm.nih.gov/geo/, Series GSE64004). DNA Isolation and Metagenomic Analysis After PBS extraction of cecal contents, DNA was prepared from precipitates using the QIAamp DNA Stool Mini Kit (QIAGEN). Pyrosequence of 16S ribosomal RNA (rRNA) genes was performed at Macrogen Inc. (Seoul, South Korea). The genomic 6 ACS Paragon Plus Environment

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DNA was subjected to PCR to amplify 16S rRNA genes using barcoded fusion primers for the V1–V3 regions (27F/518R primer). PCR products were cleaned using Agencourt AMPure beads (Beckman Coulter Inc., Brea, CA, USA). All samples were then pooled to a final concentration of ca. 107 molecules/µl from each sample. The pooled amplicons were used in emulsion PCR and samples were subjected to GS-FLX 454 pyrosequencing with Titanium chemistry (Roche, Basel, Switzerland). The sorted reads corresponding to cecal samples from ten mice were 54,222 with an average read length of 358.0, and those corresponding to fecal samples from 25 mice were 151,193 with an average read length of 463.0. All sequences were clustered into OTUs using a 97% identity threshold using CD-HIT-OTU software,26 and OTUs were classified from phylum to genus using the MOTHUR v. 1.33.0 program 27 and the SILVA rRNA database. The Shannon index and Simpson’s index were used to estimate species diversity.28 To visualize potential differences between mice in terms of fecal bacterial communities, the distances between those communities were computed using the Yue & Clayton measure of dissimilarity (Thetayc).29 Sequences that OTU clustering classified to a specific genus were compared between cecum and feces using MEGA5. A PCA plot based only on the relative OTU abundance in each sample was generated using the R function ‘prcomp’. The RP method 24

was used to detect differences in the abundance of genera or OTU between control and

sCSDS mice (num.perm = 1000). To compare cecal and fecal OTUs, OTUs that appeared in both cecal and fecal samples consisting of more than 20 reads in total (n = 10) and OTUs that significantly differed between control and sCSDS mice were selected, and the number of OTU reads was used to calculate the RP. Pearson’s correlations between these OTUs and metabolites that significantly differed between control and sCSDS mice were determined. OTUs showing correlations denoted by an |r| ≥ 0.6 were used to generate a heat map using R. Nucleotide sequence data reported are available in the DDBJ Sequenced

Read

Archive

under

the

BioProject

PRJDB4063,

BioSamples

SAMD00035437–SAMD00035446 for cecal samples, and the BioProject DRA004574, BioSamples SAMD00035497–SAMD00035521 for fecal samples. Results Metabolomic Analysis of Cecal Contents In this study, we used three omics approaches to analyze the effect of sCSDS on the intestinal ecosystem. In our previous study, we investigated the effect of sCSDS on 7 ACS Paragon Plus Environment


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metabolites in the plasma, liver, and urine.5 Using the same mice, we analyzed metabolites in the cecal contents of both control and sCSDS mice using CE-TOFMS. In the cecal contents of both control and sCSDS mice, 79 metabolites (49 cations and 30 anions) were identified by CE-TOFMS (Table S1). Sixteen metabolites (nine cations and seven anions) were significantly different between stressed and control mice by the Welch t-test (p < 0.05), and ten metabolites (eight cations and two anions) by the method of Storey and Tibshirani (q < 0.1; Table 1). Correlation analysis showed significant correlations between the social interaction score and these metabolites (Table 1). No control mice-specific or sCSDS mice-specific metabolites were identified. Cholic acid, a principal bile acid produced by the liver, was the most abundant component in the cecum of sCSDS mice. The host metabolites carnitine and creatine were also significantly accumulated in the cecum of sCSDS mice. Glutamate and its derivatives were higher in the cecum of sCSDS mice than in that of control mice. Several microbial metabolites including γ-butyrobetaine (γ-BB) and valeric acid (VA) were increased in sCSDS mice. A bacterial metabolite, 5-aminovaleric acid (5-AV), was the most abundant component in the control ceca and was significantly lower in stressed ceca. Quantitative analysis using 110 metabolite standards was used to determine the concentration of 33 metabolites (25 cations and 8 anions; Table S2). The concentration of glutamate in the cecum of sCSDS mice (2.5 mM) was significantly higher than in that of control mice (1.5 mM). PCA of the cecum metabolites identified nine principal components. The sCSDS and control mice were divided by PC2 (Figure 1). The metabolites 5-AV and VA had the highest and lowest eigenvectors of PC2, respectively, indicating that these metabolites characterized the two groups. Microarray Analysis of the Terminal Ileum The ileum is the final part of the small intestine, where digested materials including bile salts and vitamins are absorbed. It is also a part of the gut-associated lymphoid tissue that protects the host from pathogenic microorganisms. To elucidate the effects of sCSDS on gene expression in the terminal ileum, microarray analysis was performed, followed by RP calculation 24 to identify differentially expressed genes. After 10 days of sCSDS, 206 upregulated spots (representing 134 genes; Table S3) and 218 downregulated spots (representing 151 genes; Table S4) with an overall FDR of 0.5) with most metabolites highly abundant in sCSDS mice. Our result indicates that sCSDS differentially affected the abundance of each OTU, which would thereby lead to the contribution of specific metabolites. Correlation among Cecal IgA Production, the Social Interaction Score, Microbiota, and Metabolites Microarray analysis showed that the expression of B-cell- and plasma cell-related genes was significantly lower in sCSDS mice (rank products < 143, FDR < 0.01) than in control mice (Table S4). The following genes were significantly downregulated in sCSDS mice: Ig heavy chain genes (Ighg1, Ighg, and Ighm), κ light chain genes (Igkv6-14, Igkv14-111, Igkv8-30, Igk-V1, and Igk-V28), Ig joining chain gene (Igj), and the gene encoding the CD38 antigen (Cd38). These results suggested that sCSDS reduced the number of plasma cells and antibody production in the terminal ileum. Consistent with the tendency for decreased expression of Ig heavy chain constant region 11 ACS Paragon Plus Environment


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α (rank products = 394, FDR = 0.18) in sCSDS mice, cecal IgA levels tended to be decreased in sCSDS mice compared with those in control mice (p = 0.06; Figure 4A) and showed a significant correlation with the social interaction score (Figure 4B). Correlative analysis between cecal IgA levels and the abundance of OTUs comprising the cecal microbiota showed that cecal IgA levels were significantly correlated (p < 0.05) with OTU1 (Allobaculum), OTU8 (Lachnospiraceae), OTU54 (Lachnospiraceae), and OTU58 (Ruminococcaceae). OTU1 and OTU8 showed a positive correlation (Pearson's correlation coefficient of 0.72 and 0.83, respectively), whereas OTU54 and OTU58 showed a negative correlation (Pearson's correlation coefficient of -0.68 and -0.80, respectively). Other OTUs were not significantly correlated with IgA levels. These results suggested that the suppression of mucosal IgA by sCSDS correlated with the abundance of specific bacteria. Analysis of cecal metabolites showed that only proline (r = 0.89, p < 0.001) and carnitine (r = -0.70, p < 0.05) were correlated with IgA levels. Discussion The present study showed that sCSDS had a significant impact on the intestinal ecosystem, affecting the cecal and fecal microbiota (Tables 3 and 4, Figure 2), cecal metabolites (Table 1), and intestinal gene expression (Table 2), in addition to social deficit-associated behavior, polydipsia, and hyperphagia.4,

5

Although the

intestinal ecosystem heavily influenced by diet and drink, it is difficult to classify the effects of sCSDS on the intestinal microbiota or metabolites independent of polydipsia and hyperphagia. Galley et al.

16

showed that a single 2 hours of social defeat,

independent of the effect of food intake, is sufficient to significantly change the composition of the intestinal microbiota. However, prolonged chronic stressor exposure and alterations in feeding and drinking behaviors as stress responses may be integral components affecting the intestinal ecosystem. Whereas the effects of stress on the profiles of microbiota have been reported,13, 16-18 little is known about the functional relationship between gut microbiota, the metabolites produced, and the systemic effect of those metabolites. Our findings in a previous study

5

and the present study suggest

that several plasma and hepatic metabolites affected by sCSDS are derived from the cecum. The fluctuations in the concentration of several cecal metabolites such as 5-AV, 12 ACS Paragon Plus Environment

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γ-BB, UMP, and spermidine, were similar to those observed in the plasma and liver. sCSDS mice were characterized by a significant decrease in 5-AV, which was the most abundant cecal metabolite in control mice (Table 1). In our previous study,5 5-AV was detected in the plasma and liver of control mice, whereas it was undetectable in the plasma or detected at lower levels in the liver of sCSDS mice. These results indicate that changes in the cecal concentration of 5-AV reflected the concentration of 5-AV in the plasma and liver via the bloodstream. 5-AV is a common product of the anaerobic degradation of protein hydrolysates by Clostridium species in the gut;34, 35 this was confirmed by the absence of 5-AV in an aqueous extract of the colon from germ-free mice.36 5-AV is involved in the modulation of the glutamine-glutamate-γ-aminobutyric acid (GABA) metabolic pathway, and prevents the development of severe seizures in the methionine sulfoximine model of mesial temporal lobe epilepsy.37 It is also implicated as a GABAb receptor antagonist.38 GABAb receptors are expressed on neurons and enteroendocrine cells in the gastrointestinal tract39 and are involved in the regulation of acetylcholine release from cholinergeic neurons to regulate the peristaltic acticity of the colon through interaction with GABA.40 Suppressed intestinal production of 5-AV by sCSDS may have a negative effect on tissue homeostasis regulated by GABAergic cells with GABA receptors. γ-BB is a major gut microbial metabolite formed from dietary L-carnitine

in mice.41 L-carnitine and γ-BB both serve as sources of trimethylamine

(TMA), which is produced by gut microbiota and converted into trimethylamine-N-oxide (TMAO) by host hepatic flavin mono-oxygenases.41 Specific bacterial taxa in human feces are associated with both plasma TMAO and dietary status.42 Both γ-BB and carnitine were significantly increased in the cecum of sCSDS mice, and hepatic γ-BB was significantly accumulated in sCSDS mice,5 whereas hepatic TMAO accumulation was lower in sCSDS mice than in control mice. sCSDS affected the cecal microbiota, which would increase the production of γ-BB. Our results showed that sCSDS led to the systemic accumulation of the sources of TMA and TMAO, which enhance atherosclerosis. Depression has been identified as a robust risk factor for the development of coronary heart disease;43 however, depression-specific metabolites in the gut have received little attention. Accumulation of those pathogenic metabolites in the gut and their circulation via the blood stream could be involved in the comorbidity of depression and coronary heart disease. The most abundant metabolite in the cecum of sCSDS mice was cholic acid, 13 ACS Paragon Plus Environment


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which was significantly accumulated compared with the levels in the cecum of control mice. Consistent with the increase of cholic acid in the cecum, Fgf15 was upregulated in the terminal ileum of sCSDS mice (Table S3). Fgf15 is expressed in the ileum in response to bile acid absorption, and the gene product fibroblast growth factor 15 represses hepatic bile acid synthesis by CYP7a1 in a feedback inhibition loop, suggesting that sCSDS affects the enterohepatic circulation. In the present study, cholic acid and taurocholic acid were the only bile acid target molecules in the CE-TOFMS analysis (Table S1). Because sCSDS affected the gut microbiota, it would also affect the production of secondary bile acids. The effect of sCSDS on other individual bile acids is under investigation. Examining the influence of specific bile acids or bile acid metabolites on stress-induced behavior will provide further insight into the role of the intestinal ecosystem. Our results revealed that the second most abundant metabolite in the cecum of sCSDS mice was glutamate. The increase in the abundance of glutamate is likely to occur due to the suppression of glutamate metabolism and/or increase of glutamate production. Glutamate is a major oxidative fuel for intestinal epithelial cells,44 suggesting that the stressed intestinal cells did not use it and the metabolism of glutamate was suppressed. The glutamate transporter genes Slc1a1, Slc1a2, and Slc1a3 were expressed at lower levels in the ileum of sCSDS mice than in that of control mice, although the difference was not significant. On the other hand, intestinal glutaminase (Gls), which catalyzes the hydrolysis of glutamine to glutamate and ammonia, was upregulated (FDR = 0.1). The activity of Gls in intestine is increased by various regulators including glucocorticoids.45, humans

and

corticosterone

46

Secretion of glucocorticoids, cortisol in

in

rodents,

is

regulated

by

the

hypothalamus-pituitary-adrenal (HPA) axis.47 In various social defeat stress models, defeated animals showed significant increases in serum corticosterone levels as compared to non-defeated animals.48-50 Serum corticosterone levels during the period of sCSDS remain to be investigated. Among genes involved in hormone regulation, upregulation of Hsd11b2 and downregulation of Adm were observed in microarray analysis of distal ileum of sCSDS mice on Day 13. Hsd11b2 (RP 298, FDR = 0.14, control < sCSDS) encodes hydroxysteroid 11-β dehydrogenase 2 and is expressed at high levels in sodium-transporting epithelia co-localized with mineralocorticoid receptor (MR). The 14 ACS Paragon Plus Environment

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enzyme regulates local access of glucocorticoids to the MR by converting active 11-hydroxy steroids to the inactive 11-keto-steroids.51 A decrease in HSD11b2 activity by inhibition or mutation causes excess stimulation of MR by glucocorticoids and induces the state of mineralocorticoid excess with polydipsia.51 Our previous study revealed an excessive water intake during the period of sCSDS (Day 1 - Day 10) in mice which returned to normal after Day 11.4 Increased expression of Hsd11b2 on Day 13 might be involved in restoration of the polydipsia-like symptoms. Adm (RP 163, FDR = 0.06, control > sCSDS) encodes 2 biologically active peptides, adrenomedullin (ADM) and proadrenomedullin N-terminal 20 peptide (PAMP) with several functions, including vasodilation,52 regulation of the active transport of sugars, water and ions, and antimicrobial activity.53 ADM and PAMP inhibit ACTH secretion in the pituitary gland and aldosterone release from adrenal gland.54 These genes could be candidates of intestinal markers for elucidation of microbiota-gut-brain axis. Microarray analysis of the terminal ileum showed that sCSDS significantly downregulated

the

expression

IMMUNE_RESPONSE,

of

genes

involved

in

INFLAMMATORY_RESPONSE,

immunity, and

such

as

RESPONSE_

TO_BACTERIUM (Table 2). Furthermore, the cecum of sCSDS mice contained a lower concentration of IgA than that of control mice. Commensal bacteria are recognized in the small intestine and a considerable proportion (24–74%) of them are coated by secretory IgA (SIgA) when they enter the cecum.55, 56 The fate of SIgA-coated bacteria depends on the multi-functional interaction of the SIgA complex.55 Studies have investigated whether production of SIgA is influenced by the duration and intensity of stress. For example, the number of IgA-producing cells in Peyer’s patches was decreased in restraint-stressed mice 57 and IgA secretion was reduced in a rat-based stress model.58 In the present study, only four cecal OTUs were significantly correlated with the concentration of cecal SIgA. PCA of cecal OTUs indicated that the control mice and sCSDS mice were divided by PC2 (p < 0.05). However, PC2 was not correlated with cecal IgA, suggesting that the alteration of cecal OTUs by sCSDS was not solely due to SIgA. In addition to the downregulation of genes involved in immunity, the expression of Fut2 in the ileum was significantly decreased in sCSDS mice compared with that in control mice. Fut2 plays important roles in the formation of the highly fucosylated adult gut phenotype and in recovery from inflammation in the gut.59, 60

Fucosylated glycans in the gut are protective in several models of systemic and 15 ACS Paragon Plus Environment


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intestinal inflammation and infection, such as necrotizing enterocolitis and Crohn’s disease.59,

61, 62

Therefore, decreased expression of Fut2 would make the intestine

vulnerable to inflammation and infection, which may be involved in the comorbidity of depression and intestinal diseases.63 The gut is the largest organ of the immune system and provides the largest area of contact with the outside environment; therefore, a significant downregulation of genes involved in immune responses increases the vulnerability of the intestine to bacterial infection. In other words, the intestinal bacterial community, normally counterbalanced by the host’s immune system, would be disturbed by stress-induced downregulation of immunity-related genes. Whereas innate immunity protects against bacterial translocation, the suppression of innate immunity in sCSDS mice would lead to a failure of protection. This may be one of the pathological changes that occur under stress conditions. We showed in Figures 2 and 3 that the abundance of distinct OTUs in the same family Lachnospiraceae increased or decreased, and that these OTUs correlated with distinct metabolites, indicating that distinct species or strains in the same family show differential responses to sCSDS. Distinct metabolites produced by altered populations in the microbiota would affect not only the intestinal ecosystem, but the whole body via the blood stream. From the point of view of the modulation of the intestinal ecosystem, probiotics or food components such as prebiotics could affect populations within the microbiota and their metabolites. Alternatively, specific food components could alter host metabolites, such as bile acids, which would in turn affect the microbiota community. sCSDS mice fed a semi-purified diet (AIN-93G) show the greatest social avoidance behavior compared with that of mice fed a non-purified diet (MF),64 suggesting that diet quality and purity affect susceptibility and resilience to stress in the sCSDS mouse model. Elucidation of the mutual effects of diet quality and sCSDS on gut microbiota and the metabolites produced, and the effect of dietary components that affect vulnerability to social defeat stress would provide an important clue to modulate the intestinal ecosystem by foods. Further studies of stress-specific metabolites such as bile acids and 5-AV, and stress-specific changes in the composition of the microbiota are needed to determine their value as novel markers or chemo-preventive targets. Conclusions 16 ACS Paragon Plus Environment

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In this study, we used omics approaches to elucidate the effect of sCSDS on the intestinal ecosystem to expand previous findings on sCSDS mice exhibiting social deficit-associated behavior and hyperphagia. sCSDS suppressed the ileal expression of genes involved in the immune response, which may disturb the balance of the gut microbiota, leading to changes in its composition. The altered intestinal ecosystem with altered microbiota accumulated metabolites that were distinct from those of control mice. Several metabolites circulated via the blood stream, some of which may become pathogenic or affect behavior. Supporting Information Figure S1: Heat map showing the top 50 downregulated genes in the ileum after sCSDS for 10 days. Figure S2: PCA of cecal OTUs from control and sCSDS mice. Figure S3: Phylogenetic tree of microbiota in B6 (control and sCSDS) mice and ICR mice. Table S1: Metabolome analysis of cecum contents using capillary electrophoresis-mass spectrometry. Table S2: Quantitative analysis of cecum contents by CE-MS. Table S3: Upregulated genes (FDR < 0.01) in the ileum of sCSDS mice ranked by the rank products method. Table S4: Downregulated genes (FDR < 0.01) in the ileum of sCSDS mice ranked by the rank products method. Table S5: Correlation between cecal and fecal OTUs and the social interaction score. Conflict of Interest The authors declare no competing financial interest. Acknowledgments The authors thank Dr. Koji Kadota (University of Tokyo) and Dr. Masuko Kobori (National Food Research Institute) for the microarray analysis. This research was supported in part by the Research Project on Development of Agricultural Products and Foods with Health-Promoting Benefits (NARO, The MAFF, Japan)(ID:B-3) and by the Council for Science, Technology and Innovation (CSTI), Cross-Ministerial Strategic Innovation Promotion Program (SIP) (ID:14532924), “Technologies for creating next-generation agriculture, forestry and fisheries” (NARO). This research was also supported in part by the Ibaraki University Cooperation between Agriculture and Medical Science (IUCAM) (The MEXT, Japan). 17 ACS Paragon Plus Environment


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Neurosci.

2015,


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Figure Legends

Figure 1. PCA of metabolome analysis of cecal contents from control and sCSDS mice. PCA, principal component analysis; sCSDS, subchronic and mild social defeat stress. n = 5 for each group (control 1–5; sCSDS 1–5).

Figure 2. Cecal and fecal microbiota of control and sCSDS mice. Abundance of operational taxonomic units (OTUs) in control and sCSDS mice in cecum or feces was compared using the rank product (RP) method. Highly ranked OTUs (FDR < 0.3) consisting of more than 20 reads in total (n = 10) were analyzed. ***, FDR < 0.001; **, FDR < 0.01; *, FDR < 0.05; +, FDR < 0.1.

Figure 3. Heat map showing Pearson’s correlations between cecal metabolites and cecal OTUs. Metabolites that significantly differed between control and sCSDS mice, and OTUs that appeared in both cecal and fecal samples consisting of more than 20 reads in total (n = 10) were used to calculate the Pearson correlation coefficient. OTUs showing correlations denoted by an |r| ≥ 0.6 were used to generate a heat map using R.

Figure 4. Correlation of cecal IgA concentration with the microbiota. (A) Secretory IgA concentration in cecal contents of control and sCSDS mice. Data are shown as the mean ± SD. (B) Correlation of cecal IgA production and the social interaction score. Open circles represent control mice (n = 5) and closed circles represent sCSDS mice (n = 5).


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Figure 1.



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Figure 2.


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Figure 3.



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Figure 4.


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for TOC only. Illustration by Chise Suzuki. Copyright 2016.


Omics Studies of the Murine Intestinal Ecosystem ... - ACS Publications

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