• endocannabinoid system;
  • gut commensal microbiota;
  • intestinal dysbiosis;
  • secretory-IgA;
  • serotonergic system;
  • visceral pain


  1. Top of page
  2. Abstract
  3. Materials and Methods
  4. Results
  5. Discussion
  6. Acknowledgments
  7. Funding
  8. Disclosure
  9. Author Contribution
  10. References


Stress leads to altered gastrointestinal neuro-immune responses. We characterized the interaction between stress and gut commensal microbiota and their role modulating colonic responses to stress, the induction of inflammation, the expression of sensory-related markers, and visceral sensitivity.


C57BL/6N female mice were treated (7 days, PO) with non-absorbable-broad spectrum antibiotics (bacitracin/neomycin, 0.4 mg per mouse per day). Simultaneously, mice were subjected to a 1 h per day (7 days) session of psychological stress (water avoidance stress, WAS). Luminal and wall-adhered microbiota were characterized by fluorescent in situ hybridization. Cannabinoid receptors 1 and 2 (CB1/2), tryptophan hydroxylase 1 and 2 (TPH1/2), and inflammatory markers were quantified by reverse transcription–quantitative real-time PCR (RT-qPCR) and secretory-IgA (s-IgA) by ELISA. Visceral sensitivity was assessed after the intracolonic administration of capsaicin.

Key Results

Antibiotics did not affect the defecatory and endocrine responses to stress. However, antibiotics diminished by 2.5-folds total bacterial counts, induced a specific dysbiosis and favored bacterial wall adherence. Combining antibiotics and stress resulted in further reductions in bacterial counts and a dysbiosis, with enhanced bacterial wall adherence. Luminal s-IgA levels increased in dysbiotic mice. Nevertheless, no alterations consistent with the induction of colonic inflammation were observed. Dysbiosis upregulated CB2 expression and stress upregulated CB2 and TPH1 expression. Stress enhanced visceral pain-related responses, an effect prevented by antibiotic treatment.

Conclusions & Inferences

Manipulations of the commensal microbiota and the interaction host–microbiota are able to modulate the local expression of neuro–immune–endocrine systems within the colon, leading to a modulation of visceral sensitivity. These mechanisms might contribute to the pathogenic and protective roles of microbiota in gastrointestinal homeostasis.




cannabinoid receptor type 1


cannabinoid receptor type 2




enterochromaffin cells


fluorescent in situ hybridization


irritable bowel syndrome


interleukin 6


mouse mast cell protease I


secretory immunoglobulin A


reverse transcription–quantitative real-time PCR


tumor necrosis factor α


tryptophan hydroxylase isoform 1


tryptophan hydroxylase isoform 2


water avoidance stress

Functional gastrointestinal disorders, represented mainly by irritable bowel syndrome (IBS), are among the most prevalent gastrointestinal alterations in the western population. Alterations in bowel habits, abdominal pain, and discomfort, believed to reflect increased visceral sensitivity, are hallmarks of IBS.[1] Symptoms in IBS fluctuate over time in intensity and character, but the mechanisms underlying these cycles remain unclear. Several factors, including stress, intestinal infection, drugs, and diet have been reported to exacerbate symptomatology, and might be key components of the pathophysiology of the disease.[2, 3] A growing body of evidence suggests that IBS pathogenesis is likely dependent on the interaction between local immune reactions within the intestinal wall and environmental factors in genetically susceptible individuals. In particular, stress and perturbations of the gut commensal microbiota have been recognized as two potential factors contributing to the onset, maintenance, and exacerbation of both functional and inflammatory gastrointestinal disorders.[4, 5] Indeed, stressful life events or depression are risk factors for the onset or relapse of intestinal inflammation and for symptoms presentation in IBS patients. Similarly, growing evidences suggest that IBS patients have a dysbiotic intestinal microbiota.[4, 6] Despite these evidences, the exact role of gut microbiota and stress, individually or as interactive factors, in the pathophysiology of IBS remains largely unknown.

In this study, we characterized the interaction between stress and microbiota and their potential role modulating functional colonic responses to stress and the induction of inflammatory-like changes in mice. First, we assessed the effects of repetitive psychological stress (water avoidance stress, WAS) and antibiotic treatment, individually or in combination, on the composition of ceco-colonic commensal microbiota and the induction of inflammatory-like changes in the colon. In the same animals, endocrine and colonic motor responses to stress were assessed simultaneously. To characterize the ceco-colonic microbiota, we determined changes in both luminal and wall (epithelium)-adhered microbiota. The assessment of inflammatory responses was based on inflammatory markers, histological evaluation of the colon, and quantification of luminal secretory-IgA (s-IgA). s-IgA is considered the main anti-inflammatory immunoglobulin of the mucosal intestinal immune system regulating the number, composition, and functions of luminal bacteria.[7, 8] Moreover, we also determined changes in relevant systems that have been involved in sensory responses within the colon, with particular relevance to IBS, namely the endocannabinoid and the serotonergic systems. For this, colonic expression of cannabinoid receptors type 1 and 2 (CB1 and CB2) and activity of the serotonergic system [density of enterochromaffin cells (EC) and expression of the tryptophan hydroxylase isoform 1 and 2 (TPH1 and TPH2)] were characterized in the same animals. Finally, to determine if these alterations translate into functional changes in visceral sensitivity, we tested visceral pain-related responses in animals treated with antibiotics, with or without the addition of stress. For this, we assessed the presence of visceral pain-related behaviors associated with the intracolonic administration of capsaicin, as previously described.[9, 10]

Materials and Methods

  1. Top of page
  2. Abstract
  3. Materials and Methods
  4. Results
  5. Discussion
  6. Acknowledgments
  7. Funding
  8. Disclosure
  9. Author Contribution
  10. References


Female C57BL/6N mice, 6 weeks old (Charles River Laboratories, Lyon, France) were used. Upon arrival, animals were acclimatized for a 1-week period prior to any experimentation. All animals were maintained in standard conditions in an environmentally controlled room (20–22 °C, 12 h light : dark cycle), with food and water ad libitum. All procedures were approved by the Ethical Committee of the Universitat Autònoma de Barcelona (protocols 1099 and 1101) and the Generalitat de Catalunya (protocols 5645 and 5646).

Antibiotic treatment

Animals received a mixture of non-absorbable, broad spectrum antibiotics containing Bacitracin A (Vetranal™; Sigma-Aldrich, Barcelona, Spain), and Neomycin (Neomycin trisulfate salt hydrate; Sigma-Aldrich). Amphotericin B (Sigma-Aldrich) was added to prevent yeast overgrowth. Animals were dosed by oral gavage with 0.3 mL of the antibiotic/antifungal mixture, during seven consecutive days. In addition, the same antibiotic/antifungal mixture was added to the drinking water during the same period of time. This protocol ensured a minimum dose of 0.4 mg for bacitracin and neomycin and 0.1 mg for amphotericin B (per mouse and day). Vehicle-treated animals received vehicle (deionized water) by oral gavage (0.3 mL) and normal drinking water during the same period of time. Water consumption, assessed on a daily basis during the treatment period, was similar across groups (data not shown). Similar treatment protocols have been followed previously in comparable studies in mice and rats, demonstrating the induction of significant changes of the commensal microbiota.[11-13]

Repetitive psychological stress (WAS)

Water avoidance stress was performed following previous protocols described by us.[14, 15] Animals were placed on a platform (4 cm diameter, 6 cm height) located in the center of a standard plastic cage (530 × 280 × 155 mm) filled with tap water (18–20 °C) to about 1 cm below the edge of the platform. Stress sessions lasted for 1 h and were repeated on seven consecutive days. Control animals were maintained in their home cages. All procedures were performed in the morning (finishing no later than 12:00 h) to minimize any influence of circadian rhythms. Fecal pellet output during the 1-h session of WAS/non-stress was used as a marker of stress.

Behavioral responses to intracolonic capsaicin-evoked visceral pain

Spontaneous visceral pain-related behaviors induced by intracolonic capsaicin were assessed following previously described protocols, with minor modifications.[9, 10] Mice were anesthetized with isoflurane (Isoflo; Esteve, Barcelona, Spain) and capsaicin (0.05 mL per mice, 0.1% in ethanol : Tween 80 : saline; 1 : 1 : 8, v : v : v; Sigma-Aldrich) was administered intracolonically (about 4 cm from the anus) with a rounded tip plastic cannula (length 7.5 cm, diameter 0.61 mm). Petroleum jelly was applied on the perianal area to avoid stimulation of somatic areas through contact with capsaicin. Animals were placed in plastic cages (20 × 20 × 14 cm) and, after recovering consciousness, visceral pain-related behaviors were assessed during a 30-min period. Pain behaviors were visually assessed by two independent researchers. Behaviors assessed included: licking of the abdomen, stretching of abdomen, squashing the abdomen to the floor, and abdominal retractions. For each animal, the number of behaviors for the 30-min observation time was determined as the mean of the quantification performed by the two observers.

Experimental protocols

Mice (n = 24) were randomly divided into four experimental groups (n = 6 each): (i) vehicle-treated non-stressed mice; (ii) vehicle-treated stressed mice; (iii) antibiotic-treated non-stressed mice; and (iv) antibiotic-treated stressed mice. Animals were treated with antibiotics or vehicle for a period of 7 days, as described above. In addition, from day 2 to 8, animals were subjected to a 1 h per day session of psychological stress (WAS) or maintained in their home cages (control). On day 8, immediately after the last session of stress, animals were euthanized and blood, tissue (ceco-colonic region), and fecal samples were obtained.

In a second experiment, mice (n = 20) were divided into the same experimental groups and followed the same treatments (n = 5 per group). At the end of treatments, visceral pain-related responses to intracolonic capsaicin were assessed as described above. In this case, at the end of the procedure, animals were euthanized and weight of body organs was assessed (see samples collection).

Samples collection

Immediately after the last stress session, mice were deeply anesthetized with isoflurane (Isoflo; Esteve) and euthanatized by exsanguination through intracardiac puncture followed by cervical dislocation. Thereafter, a medial laparotomy was performed, the ceco-colonic region localized and the cecum and colon dissected. Afterward, ceco-colonic fecal contents and a tissue sample from the proximal colon were collected and frozen immediately in liquid nitrogen. Frozen samples were stored at −80 °C until analysis. At the same time, tissue samples of the proximal and middle colon (about 1.5 cm each) were collected and fixed overnight in Carnoy fixative (ethanol : chloroform : glacial acetic acid, 6 : 3 : 1, v : v : v) or in 4% paraformaldehyde. After an overnight fixing, tissues were paraffin embedded and 5-μm-thick sections were obtained. In addition, the adrenal glands, the thymus, and the spleen were dissected and weighed. Serum was obtained by centrifugation of blood samples (15 min, 2465 g, 4°°C) and maintained at −80°°C until analysis. In animals used to assess visceral sensitivity, at necropsy, only the weight of body organs was assessed (cecum, adrenal glands, thymus, and spleen).

Bacterial identification by fluorescence in situ hybridization

For fluorescence in situ hybridization (FISH), oligonucleotide probes consisted in a single-strain DNA covalently linked with a Cy3 (carbocyanine) reactive fluorescent dye at the 5′ end (Biomers, Ulm/Donau, Germany and Tib Molbiol, Mannheim, Germany). Probes used were as follows: EUB 338 (5′GCTGCCTCCCGTAGGAGT3′) to total Bacteria; NON 338 (5′ACATCCTACGGGAGGC3′) to non-bacteria (negative control); BAC 303 (5′CAATGTGGGGGACCTT3′) to Bacteroides spp.; EREC 482 (5′GCTTCTTAGTCAGGTACCG3′) to Clostridium Cluster XIVa; LAB 158 (5′GGTATTAGCACCTGTTTCCA3′) to Lactobacillus spp. and Enterococcus spp.; ENT-D (5′TGCTCTCGCGAGGTCGCTTCTCTT3′) to enterobacteria; and BIF 164 (5′CATCCGGCATTACCACCC3′) to Bifidobacterium spp.

Fecal samples of ceco-colonic content were used to characterize luminal commensal microbiota. In situ hybridization of bacteria in the luminal content was performed on glass slides, as previously described.[16, 17] Samples were hybridized in a dark moist chamber (for 3 h) by addition of 100 μL hybridization buffer (20 mmol L−1 Tris-HCl, 0.9 mol L−1 NaCl, 0.1% SDS at pH 7.2) with the corresponding Cy3-labeled oligonucleotide probe (concentration 5 ng μL−1). Treatments with formamide or lysozyme and hybridization temperatures were used as described to achieve the optimal stringency. After hybridization, the slides were rinsed in a pre-warmed washing buffer (20 mmol L−1 Tris-HCl, 0.9 mol L−1 NaCl at pH 7.2) for 30 min and then cleaned with miliQ water to remove unbound probes. Washed slides were air dried and mounted with Vectashield-DAPI (Vector Laboratoires, Orton Southgate, Peterborough, UK). The fluorescent stain 4′,6-diamidino-2-phenylindole (DAPI), that binds strongly to DNA, served as a control signal in all samples. Hybridized slides were viewed under oil immersion, using a Carl Zeiss Axioskop 40 FL epifluorescence microscope (Carl Zeiss, Jena, Germany) equipped with a digital camera (Zeiss AxioCam MRm) for obtaining digital images (Zeiss AxioVision Release 4.8.1). For quantification of bacteria, 20 randomly selected fields were photographed, the number of hybridized cells counted using the CellC software[18], and the mean value obtained. All procedures were performed on coded slides to avoid bias.

Hybridization of tissue samples was performed following, with minor modifications, methods described by Pelissier et al.[19] Sections from Carnoy-fixed tissues were deparaffinized, rehydrated, post-fixed in 4% paraformaldehyde and washed. Hybridization conditions used were, essentially, as described above for luminal bacteria, but tissue samples were incubated for 16 h with the hybridization buffer. In hybridized tissue samples, 20 randomly selected fields were photographed. Analysis of the images was performed manually by two independent researchers who observed the pictures and localized hybridized bacteria within the mucus layer or attached to the epithelial surface. A coincidence between the two observers in bacterial location in at least 15% of the pictures observed (at least three of 20) was required to decide that there was bacterial attachment to the epithelium. All procedures were performed on coded slides to avoid bias.

mRNA analysis

Total RNA was extracted from frozen tissue samples using TRI reagent with Ribopure Kit (Ambion/Applied biosystems, Foster City, CA, USA). Thereafter, a two-step quantitative real-time PCR (RT-qPCR) was performed. RNA samples were converted into cDNA using a High Capacity cDNA Reverse Transcription Kit (Applied Biosystems). Only a consistent 260/280 ratio (between 1.8 and 2) found with NanoDrop (ND-1000 spectrophotometer, NanoDrop Technologies, Wilmington, DE, USA) was accepted to perform a TaqMan quantitative RT-qPCR. TaqMan gene expressions assays (hydrolysis probes) for CB1 receptors (Mm01212171_s1), CB2 receptors (Mm00438286_m1), interleukin 6 (IL-6) (Mm00446190_m1), tumor necrosis factor α (TNFα; m00443258_m1), TPH1 (Mm00493794_m1), and TPH2 (Mm00557715_m1) were used (Applied Biosystems). β-2-microglobulin (Mm00437762_m1) was used as endogenous reference gene.

The PCR reaction mixture was incubated on the ABI 7900 HT Sequence Detection System (Applied Biosystems). All samples, as well as the negative controls, were assayed in triplicates. RQ Manager 1.2 software was used to obtain the cycle threshold for each sample; thereafter, all data were analyzed with the comparative Ct method (2−∆∆Ct) with the vehicle–non-stressed group serving as the calibrator.[20]

Quantification of secretory immunoglobulin A

Luminal s-IgA was measured in fresh homogenates of cecal contents (diluted in PBS 1×) using a commercial double-antibody sandwich ELISA, following manufacturers' instructions (MBS564073; MyBiosource, San Diego, CA, USA).


For histological examination, hematoxylin–eosin-stained sections from the colon were obtained following standard procedures. A histopathological score (ranging from 0, normal, to 12, maximal alterations) was assigned to each animal. Specifically, parameters scored included: epithelial structure (0: normal; 1: mild alterations of the villi; 2: local villi destruction and/or fusion; 3: generalized villi destruction and/or fusion), structure of the crypts (0: normal; 1: mild alterations of the crypts; 2: local destruction of the crypts; 3: generalized destruction of the crypts), presence of edema (0: normal; 1: mild local edema in submucosa and/or lamina propria; 2: moderate diffuse edema in submucosa and/or lamina propria; 3: severe generalized edema in submucosa and/or lamina propria), and presence of inflammatory infiltrate (0: normal; 1: mild localized infiltrate; 2: mild generalized infiltrate; 3: severe generalized infiltrate). Scoring was performed on coded slides by two independent researchers.

The mucous layer was assessed in Carnoy-fixed samples of colonic tissue. Thickness of the mucous layer was measured in 10 different fields, for triplicate, in representative regions covering, at least, 20% of the epithelial surface.[21] All measurements were performed on coded slides by two independent investigators using the Zeiss AxioVision Release 4.8.1 software. Moreover, tissue sections were also stained with Alcian Blue pH 2.5/Periodic Acid Schiff (AB 2.5/PAS kit; Bio-Optica, Milano, Italy) to specifically stain neutral (pink) and acidic (blue) mucins. Thereafter, colonic goblet cells were counted in 20 longitudinally oriented villus-crypt units. Length of the villus-crypt unit was also determined to obtain goblet cells density (number of cells mm−1).


Immunohistochemistry was used to detect serotonin (5-HT) and Mouse Mast Cell Protease I (MMCP-I) in colonic tissue. The primary antibodies included a rabbit polyclonal anti-5-HT (1:20000; RA20080; Neuromics, Edina, MN, USA) and a sheep polyclonal anti-MMCP-I (1:500; MS-RM8; Moredun Scientific, Penicuik, Midlothian, Scotland). The secondary antibodies used were a biotinylated polyclonal swine anti-rabbit IgG (1:200; E 0353; DakoCytomation, Glostrup, Denmark) or a polyclonal rabbit anti-sheep IgG-B (1:200; SC-2776, Santa Cruz Biotechnology, Santa Cruz, CA, USA), as appropriate. Antigen retrieval for serotonin was achieved by microwave processing of the slides in 10 mmol L−1 citrate buffer. Quenching of endogenous peroxidase was performed by 1-h incubation with 5% H2O2 in distilled water. Detection was performed with avidin/peroxidase kit (Vectastatin ABC kit; Vector Laboratories). Antigen–antibody complexes were reveled with 3-3′-diaminobenzidine (SK-4100 DAB; Vector Laboratories). Specificity of the staining was confirmed by omission of the primary antibody.

For quantification, immunopositive cells were counted at high power field (hpf; 400× magnification) in 10 microscope fields, randomly selected, in duplicate, for each tissue sample. When assessing serotonin immunoreactivity, immunopositive cells, likely corresponding to EC, were counted in the mucosa. When assessing MMCP-I immunoreactivity, immunopositive cells, corresponding to mucosal mast cells, were counted in the mucosa and submucosa. All cell counting was performed on coded slides to avoid bias.

Plasma corticosterone and haptoglobin

Plasma corticosterone levels were determined by double-antibody RIA. The characteristics of the antibody and the basic RIA procedure had been described previously.[22] In brief, 125I-corticosterone-carboximethyloxime-tyrosine-methyl ester (ICN-Biolink 2000, Barcelona, Spain), synthetic corticosterone (Sigma-Aldrich), as the standard, and an antibody raised in rabbits against corticosterone-carboximethyloxime-BSA were used. All samples were run in the same assay to avoid interassay variability. The intraassay coefficient of variation was less than 8% and the sensitivity was 0.1 μg dL−1.

Plasma concentrations of the acute-phase protein haptoglobin were determined using a commercial ELISA kit, following manufacturer's instructions (sensitivity; 0.005 mg−1; intraassay variability: 5.3–6.3%; interassay variability: 4.1–5.7%; “PHASE”TM Haptoglobin Assay; Tridelta Development Limited, Maynooth, County Kildare, Ireland).

Statistical analysis

Data are expressed as mean ± SEM. A robust analysis (one iteration) was used to obtain mean ± SEM for RT-qPCR data. Data were analyzed by one-way anova or a non-parametric anova (visceral pain data), followed, when necessary, by a Student–Neuwman–Keuls multiple comparisons test. Data were considered statistically significant when < 0.05. All statistical analyses were performed using GraphPad Prism 4 (GraphPad Software, La Jolla, CA, USA).


  1. Top of page
  2. Abstract
  3. Materials and Methods
  4. Results
  5. Discussion
  6. Acknowledgments
  7. Funding
  8. Disclosure
  9. Author Contribution
  10. References

Functional and endocrine responses to repetitive psychological stress (WAS)

In vehicle-treated mice maintained in non-stressful conditions, pellet output was low and not affected by the antibiotic treatment (mean value for the 7 days of stress; vehicle: 3.4 ± 0.6 fecal pellets h−1; antibiotic: 3.9 ± 0.7 fecal pellets h−1; P > 0.05; Fig. 1A). Repetitive WAS, independently of the experimental group considered, resulted in a significant increase in the fecal output rate during the period of stress, when compared with non-stressed groups (Fig. 1A). Defecatory response to stress was similar in vehicle- and antibiotic-treated animals and remained stable during the seven consecutive stress sessions (Fig. 1B).


Figure 1. Functional and endocrine responses to repetitive water avoidance stress (WAS, 1 h day−1 for 7 days) in mice. (A) Mean fecal pellet output during the time of stress, across the 7 days of treatment. *P < 0.05 vs non-stressed groups. (B) Mean fecal pellet output for the seven WAS sessions applied. (C) Plasma levels of corticosterone at the end of the last stress session. *P < 0.05 vs non-stressed groups. (D) Weight of the adrenal glands. *P < 0.05 vs vehicle–non-stressed group. In all cases data are mean ± SEM, n = 6 per group (except for the weight of the adrenal glands, n = 11 per group).

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Plasma corticosterone levels were increased in stressed animals, as assessed immediately after the last stress session. Stress-induced changes in plasma corticosterone were similar in vehicle- or antibiotic-treated mice (Fig. 1C).

Weight of body organs

At necropsy, weight of the adrenal glands was increased by 50% in the vehicle-WAS group when compared with non-stressed controls (Fig. 1D). Antibiotic treatment, per se, resulted in a slight increase in the adrenal glands weight, without reaching statistical significance. Addition of stress in antibiotic-treated mice leads to an increase in adrenal weight similar to that observed in vehicle-treated animals (Fig. 1D). The same differences were observed for the relative weight of the adrenal glands. No consistent changes across groups were observed in the absolute or relative weight of the spleen or the thymus (Fig. 2C).


Figure 2. Ceco-colonic histopathology and immune-related parameters at the time of necropsy in the different experimental groups. (A) (top row): Histopathological evaluation: weight of the cecum (left panel); relative weight of the colon (middle panel), and colonic histopathological scores (right panel). Data are mean ± SEM of 5–11 animals per group. Because of technical problems the weight of the cecum in the vehicle–WAS group was only assessed for five animals; and histopathological scores were not determined in one animal of the antibiotic-treated–WAS group. *P < 0.05 vs vehicle–non-stressed group. (B) (second row): Local and systemic inflammatory markers: colonic expression of IL-6 (left panel) and TNFα (middle panel) and plasma levels of haptoglobin (right panel). Each point represents an individual animal; the horizontal bar with errors represents de mean ± SEM; n = 6 per group. (C) (third row): Relative weight (% of total bodyweight) of the thymus (left panel) and the spleen (right panel). Data are mean ± SEM of 11 animals per group. (D) (bottom row): Luminal secretory-IgA (s-IgA) in the different experimental groups. Data are mean ± SEM of six animals per group. *P < 0.05 vs vehicle-treated groups.

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Macroscopic and microscopic evaluation of ceco-colonic tissues

In antibiotic-treated groups, irrespective of the addition of stress, the cecum appeared distended and its weight was significantly increased when compared to that of the vehicle–non-stressed group (Fig. 2A). These differences persisted when the relative weight of the cecum was calculated (data not shown), thus indicating that the increase in cecal weight was independent of a variation in bodyweight.

Upon macroscopical examination, both the cecum and colon showed a normal aspect, irrespective of the experimental group considered. Colonic relative weight was similar across groups (Fig. 2A). Overall, microscopic analysis of colonic tissue samples showed a normal histological structure, irrespective of the experimental group considered. Occasionally, a moderate multifocal-to-diffuse inflammatory infiltrate could be observed, but no treatment-related incidence could be established. Final histopathological scores were similar in all experimental groups (Fig. 2A). Nevertheless, total histopathological scores assigned to the antibiotic–WAS group were relatively high compared with other groups; however, no statistical significance was reached [F(3.19) = 2.090; P = 0.135]. Increased scores in this group were mainly associated with a worsening in the epithelial structure with increased desquamation and scant alterations in some of the crypts [F(3.19)  = 3.116; P = 0.048 antibiotic-treated–non-stressed vs antibiotic-treated–WAS]. No differences among groups were found in the length of the colonic crypts.

Very few MMCP-1-immunopositive cells (0–1 cells per field), identified as mucosal mast cells, were observed in colonic samples, irrespective of the experimental group considered (data not shown).

In Carnoy-fixed colonic samples, a layer of mucous was observed covering most of the epithelial surface. Stress decreased in a similar proportion the thickness of the mucous layer in either vehicle- or antibiotic-treated mice. Antibiotics, per se, had only a marginal, non-significant, effect reducing the thickness of the mucous layer (Table 1). Despite these changes, the density of goblet cells was similar across experimental groups. The relative abundance of mature goblet cells containing neutral mucins (pink color in a PAS/AB pH = 2.5 staining) was slightly increased by either antibiotic treatment or stress, although statistical significance was only achieved for the stress group (Table 1).

Table 1. Effect of stress and/or antibiotics on the colonic mucous layer and the density of goblet cells
 Thickness of the mucous layer (μm)Goblet cells density (cells mm−1)Density of Mature goblet cells (cells mm−1)
  1. Data are mean ± SEM, n = 6 animals per group; WAS, water avoidance stress.

  2. a

    P < 0.05 vs vehicle–non-stressed.

  3. b

    P < 0.05 vs antibiotics–non-stressed.

Vehicle–Non-stressed23.01 ± 1.8999.19 ± 7.4520.11 ± 1.90
Vehicle–WAS11.87 ± 0.32a114.06 ± 8.9929.88 ± 0.85a
Antibiotic–Non-stressed17.99 ± 0.72113.75 ± 2.3224.48 ± 1.32
Antibiotic–WAS7.34 ± 0.27a,b111.25 ± 9.4525.04 ± 4.6

Systemic and local markers of inflammation and luminal s-IgA

Plasma levels of the acute-phase protein haptoglobin were, in general, low and similar to those previously described by us.[15] No treatment-related changes in haptoglobin levels were found among groups (Fig. 2B). Similarly, no differences among groups were found for colonic cytokines mRNA expression (IL-6 and TNFα; Fig. 2B). In most cases, there was relatively large within-group variability in the expression levels. Overall, relative expression of TNFα was higher (by 12-fold) than that of IL-6.

S-IgA was detected in all fecal samples, regardless the experimental group considered. In vehicle–non-stressed animals, s-IgA levels were 7.19 ± 1.3 μg mL−1, the addition of stress increased s-IgA levels by 4.6-fold (Fig. 2D), although statistical significance was not reached. In the antibiotic–non-stressed group, s-IgA levels were increased by 36-fold (P < 0.05 vs vehicle–non-stress group). In these conditions, addition of stress did not further enhance the levels of s-IgA (Fig. 2D).

Characterization of luminal and wall-adhered microbiota

In vehicle-treated–non-stressed animals, total bacterial counts within the luminal content, determined by FISH as EUB338-positive cells, were between 3 × 1010 and 7 × 1010 cell mL−1, and within the margins previously described.[21, 23, 24] In these conditions, EUB338-positive bacteria represented a 90% of the total DAPI counts (Table 2). Within all bacterial groups characterized, Bacteroides spp. and Clostridium spp. were the most abundant strains; whereas Enterobacteria, Lactobacillus/Enterococcus spp. and Bifidobacterium spp. were below FISH detection levels (106 cell mL−1)[25] (Table 2; Fig. 3). Repetitive WAS had no effect, per se, on total bacterial counts, but induced a specific dysbiosis of the microbiota. In particular, Verrucobacteria counts were reduced to undetectable levels whereas counts of Clostridium spp. were increased by twofold and Lactobacillus/Enterococcus spp. appeared at a low level, borderline to the limit of detection (Table 2; Fig. 3).

Table 2. Composition of the luminal microbiota as assessed by FISH and DAPI stainingd
 DAPI (×108 cells mL−1)Total bacteria (×108 cells mL−1)Bacteroides spp. (×108 cells mL−1)Enterobacteria (×108 cells mL−1)Verrucobacteria (×108 cells mL−1)Clostridium coccoides cluster XIVa (×108 cells mL−1)Lactobacillus-Enterococcus spp. (×108 cells mL−1)Bifidobacterium spp (×108 cells mL−1)
  1. ND, Not detected (below 106 cells mL−1); FISH, fluorescent in situ hybridization; DAPI, 4′,6-diamidino-2-phenylindole; WAS, water avoidance stress.

  2. a

    P < 0.05 vs vehicle–non-stressed or vehicle–WAS groups.

  3. b

    P < 0.05 vs antibiotic–non-stressed group.

  4. c

    P < 0.05 vs vehicle–non-stressed group.

  5. d

    Data represent mean ± SEM from six animals per group.

Vehicle–Non-stressed462.5 ± 56.0433.5 ± 27.669.3 ± 3.7ND36.5 ± 2.368.7 ± 4.9NDND
Vehicle–WAS532.2 ± 55.7509.0 ± 26.864.3 ± 5.9NDND110.0 ± 8.4c0.1 ± 0.02ND
Antibiotic–Non-stressed286.9 ± 22.9173.5 ± 10.5a73.7 ± 8.47.0 ± 0.6a18.4 ± 1.2a31.4 ± 1.6a,b18.6 ± 1.7aND
Antibiotic–WAS341.3 ± 22.0196.8 ± 8.1a103.0 ± 9.511.0 ± 0.9a,b44.4 ± 1.7b18.8 ± 1.2a,b47.2 ± 3.8a,bND

Figure 3. Relative distribution of the ceco-colonic microbiota in the different experimental groups. Data represent the relative abundance (percent) of the main bacterial groups present in the gut commensal microbiota (Bacteroides spp., Clostridium spp., Enterobacteria, Lactobacillus spp., and Verrucobacteria), as quantified using fluorescent in situ hybridization (FISH) techniques. Relative percent composition of the microbiota was calculated taking as 100% the total counts of the different bacterial groups assessed. See Table 2 for exact cell counts.

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Treatment with antibiotics resulted in a 2.5-fold reduction in total bacterial counts and altered the overall composition of the luminal microbiota (Table 2). In antibiotic-treated mice, EUB338-positive counts only included a 60% of the total DAPI counts. Antibiotics reduced the counts of Verrucobacteria and Clostridium spp., while significantly increased the counts of Enterobacteria and Lactobacillus/Enterococcus spp. (Table 2; Fig. 3). Addition of stress to the antibiotic treatment further enhanced intestinal dysbiosis. In these conditions, total bacterial counts maintained their reduction when compared with the vehicle–WAS group. This was associated mainly with a sixfold reduction in Clostridium spp. counts, whereas the counts of Verrucobacteria, Enterobacteria and Lactobacillus/Enterococcus spp. were significantly increased (Table 2; Fig. 3). Bifidobacterium spp. was not detected in any experimental group.

As it relates to bacterial wall adherence, EUB338-positive cells were always observed attached to the wall, in most cases within the mucous layer located on the epithelial surface. In vehicle–non-stressed animals, the only bacterial group attached to the colonic wall was Verrucobacteria (Incidence: 83%). Addition of stress significantly reduced the incidence of Verrucobacteria attachment (Table 3, Fig. 4), without affecting the adherence of other bacterial groups.

Table 3. Incidence of bacterial wall adherencea
 Bacteroides spp.EnterobacteriaVerrucobacteriaClostridium coccoides cluster XIVaLactobacillus-Enterococcus spp
  1. a

    Data represent the number of animals showing bacterial wall adherence over the total of animals (percentage of incidence).

Vehicle–Non-stressed0/6 (0%)0/6 (0%)5/6 (83%)1/6 (17%)0/6 (0%)
Vehicle–WAS0/6 (0%)0/6 (0%)1/6 (17%)2/6 (33%)0/6 (0%)
Antibiotic–Non-stressed0/6 (0%)6/6 (100%)5/6 (83%)5/6 (83%)5/6 (83%)
Antibiotic–WAS3/6 (50%)2/6 (33%)5/6 (83%)6/6 (100%)5/6 (83%)

Figure 4. Representative colonic tissue images showing bacterial wall adherence for different bacterial groups. The left column corresponds to a vehicle-treated mice and the right column to an antibiotic-treated animal. Each line corresponds to a different bacterial group (from top to bottom: Clostridium spp, Lactobacillus spp, Enterobacteria, and Verrucobacteria). Note the higher abundance of bacteria attached to the epithelium and within the mucous layer covering the epithelial surface in the antibiotic-treated mice compared with the vehicle-treated mice.

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During antibiotic treatment, the incidence of bacterial wall adherence increased significantly for all bacterial groups detected in the luminal content (83–100% incidence), except for Bacteroides spp. (0% incidence). The addition of stress maintained a generalized adherence for all groups explored, but, particularly, facilitated Bacteroides spp. attachment while reduced the adherence of Enterobacteria (Table 3, Fig. 4).

Expression of Cannabinoid receptors and activity of the serotonergic system

mRNA for both cannabinoid receptors was detected in all samples. Expression levels in control conditions (vehicle–non-stressed animals) were low, with the levels of CB1 mRNA being about 10-fold higher than those of CB2. In vehicle-treated mice, WAS had a marginal effect increasing CB2 expression (by 6%, P > 0.05). In the antibiotic–non-stress group, CB2 expression was increased by 20% (P < 0.05 vs vehicle–non-stress group); addition of stress further increased CB2 expression, leading, approximately, to a 40% increase in expression (P < 0.05 vs vehicle-treated groups; Fig 5A). CB1 expression was not affected by either stress or antibiotics, alone or in combination (Fig 5A). Regardless of the experimental group considered, expression levels of CB2 receptors correlated positively with Lactobacillus spp. counts (P = 0.001; r2 = 0.38) and negatively with Clostridium spp. counts (P = 0.02; r2 = 0.21; Fig. 5B).


Figure 5. Effects of stress and/or antibiotics on the colonic expression of sensory-related systems (endocannabinoid and serotonergic) and visceral pain-related responses. (A) (upper row): Colonic expression of cannabinoid receptors, CB1 (left pane) and CB2 (right panel), in the different experimental groups. Each point represents an individual animal; the horizontal bar with errors represents de mean ± SEM of each group; n = 6 per group. *P < 0.05 vs vehicle–non-stressed and vehicle–WAS groups. #P < 0.05 vs antibiotic–non-stressed group. (B) (middle-upper row): Correlations between the relative expression of CB2 and the bacterial counts of Lactobacillus spp. (P = 0.0014; r2 = 0.38) (left panel) and Clostridium spp. (P = 0.02; r2 = 0.21) (right panel), as determined by fluorescent in situ hybridization. Each point represents an individual animal; broken lines represent the 95% confidence interval. (C) (middle-lower row): Activity of the serotonergic system within the colon. Left panel shows the relative expression of tryptophan hydroxylase 1 (TPH1). Each point represents an individual animal; the horizontal bar with errors represents the mean ± SEM of each group; n = 6 per group. *P < 0.05 vs respective non-stressed group. Right panel shows the density of enterochromaffin cells (5-HT-immunoreactive cells/field, ×400), as determined by immunohistochemistry, in the different experimental groups. Data are mean ± SEM of n = 6 animals per group. (D) (lower row): Intracolonic capsaicin-evoked visceral pain-related behaviors. Data represent the number of pain-related behaviors in a 30-min observation period after intracolonic capsaicin administration. Each point represents an individual animal; the horizontal bar with errors represents the mean ± SEM of each group; n = 5 per group. *P < 0.05 vs other experimental groups.

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The isoform 1 of the TPH was detected with high reproducibility and at relatively high levels in colonic tissues (Fig. 5C); however, the isoform 2 (TPH2) was found in a very low quantity (a mean of 36.6 Cq value). Overall, TPH1 expression levels were about 24-fold higher than those of TPH2. TPH1 expression levels were similar in vehicle-treated or antibiotic-treated non-stressed animals. Repetitive WAS increased TPH1 expression by similar proportion in either vehicle- or antibiotic-treated animals (40% increase; Fig. 5C).

Serotonin-immunopositive cells, likely corresponding to EC cells, were scattered throughout the colonic mucosa. Relative abundance was similar in all experimental groups (Fig. 5C).

Behavioral responses to intracolonic capsaicin

Intracolonic administration of capsaicin induced pain-related behaviors in all mice during the 30-min observation period. The behavior most expressed was the licking of the abdominal area, which was observed in all animals. In the vehicle–non-stress group, the number of pain-related behaviors reached a mean value of 40.9 ± 6.6 in the 30-min observation period (n = 5; Fig. 5D). In these conditions, treatment with antibiotics slightly reduced the number of pain behaviors, although statistical significance was not reached. In vehicle-treated animals, addition of stress increased the incidence of behaviors by 48% (P < 0.05 vs vehicle–non-stress group), an effect completely prevented by the treatment with antibiotics (Fig. 5D).


  1. Top of page
  2. Abstract
  3. Materials and Methods
  4. Results
  5. Discussion
  6. Acknowledgments
  7. Funding
  8. Disclosure
  9. Author Contribution
  10. References

In this study, we show that the colonic functional (motor) and endocrine responses to stress are essentially not affected by relatively large alterations of the ceco-colonic microbiota, either luminal or attached to the colonic wall, during an antibiotic treatment. Moreover, we show that microbiological changes, due to antibiotics and stress, are able to modulate the immune and sensory systems, namely the endocannabinoid and the serotonergic systems, within the colon, without the induction of a manifest state of intestinal inflammation. While antibiotics, per se, did not affect visceral pain-related responses, they prevented stress-induced hypersensitivity. This suggests that antibiotics-mediated effects on sensory systems might have functional consequences, leading to the modulation of visceral sensitivity.

Our results confirm the validity of chronic WAS as a valid, mild stressor in mice, as previously published.[14, 15, 26] Mice did not habituate to the stress protocol, as shown by the persistent colonic response along the 7-day period of WAS. Moreover, the efficacy of the stress paradigm is further demonstrated by the raise in plasma corticosterone and the increase in weight of the adrenal glands at the end of the last stress session.

Total bacterial counts were not affected by stress. However, repetitive WAS significantly increased the counts of Clostridium spp. and favored the appearance of Lactobacillus spp. These changes agree with those described in mice subjected to social stress, where the main change in the microbiota was an increase in the Clostridia group.[13] Interestingly, the Verrucobacteria group, present in a relatively high proportion in non-stressed mice, was undetectable in stressed animals. This group of microorganisms, which degrade mucus within the gastrointestinal tract,[17, 27] might have relevance in gastrointestinal diseases. For instance, an enhancement of the mucin-degrading microbiota in dysbiotic patients predispose to Crohn's disease.[28] During stress, the thickness of the mucus layer was reduced, in agreement with O'Malley et al.[28, 29] A reduction in mucus abundance might be a factor reducing also the relative abundance of Verrucobacteria. Alternatively, we cannot discard that these changes are secondary to the combined enhancing effects of stress on colonic motility and mucus secretion,[30-32] leading to an increased discharge of mucus and therefore to a net reduction in mucus content and associated bacteria. Moreover, although goblet cell density remained stable, stress increased the proportion of mature goblet cells, indicative of an increase in mucus production and secretion.[33] Despite these changes in mucus content, wall-adhered microbiota was not affected by stress.

As expected, treatment with wide-spectrum, non-absorbable antibiotics significantly reduced total bacterial counts. The reduction in bacterial counts was coupled to a specific dysbiosis which implied a proliferation of Lactobacillus spp. and Enterobacteria; whereas the Clostridium spp. and the Verrucobacteria groups were reduced. Interestingly, only antibiotic-induced changes in luminal microbiota were associated with an increase in bacterial wall adherence. This is important because adhered microbiota has been suggested to be the one directly interacting with the host's bacterial recognition systems, thus eliciting either beneficial or harmful responses within the gut.[34, 35] The relationship between luminal counts and epithelial attachment seems to be strain dependent. Overall, changes in bacterial wall adherence correlated positively with changes in luminal counts. However, the Clostridia group was reduced during antibiotic treatment, but presented an increased rate of adherence. This negative relationship might reflect the heterogeneity of Clostridium coccoides cluster XIVa. From the present data, we cannot rule out the possibility that antibiotics are affecting only a part of this cluster, leading to a relative selection of bacteria with high wall adherence capacities. In fact, it is well reported that most antibiotics can increase the risk of developing Clostridium difficile colitis[36, 37] and that the relapse of colitis in patients with recurrent C. difficile infections is associated with reduced intestinal microbial diversity.[38] Nevertheless, the role of gut commensal microbiota in intestinal inflammation remains controversial, and beneficial effects of wide spectrum antibiotics has been shown in DSS-induced colitis in rats.[39] The mucous layer represents also a protective barrier preventing bacterial wall adherence. Therefore, a loss of mucus should be regarded as a factor favoring bacterial–host interactions.[40, 41] Antibiotics had only a marginal effect reducing the mucous layer, thus suggesting that the mucus, per se, might play a minor role affecting bacterial wall adherence in the present conditions. Ceco-colonic dysbiosis was further enhanced when antibiotic-treated mice were subjected to stress. This was associated with a significant increase in the incidence of wall adherence, observed for all bacterial groups assessed, and a clear reduction in the thickness of the mucous layer.

Commensal microbiota is necessary for the development of spontaneous colitis, as suggested by observations in mice deficient in interleukin 10; however, gut commensal microbiota could also have a protective role, as seen in germfree mice with DSS-induced colitis.[42-44] These apparent discrepancies might be associated with the composition of the microbiota, the immaturity of the immune system, the environmental conditions of housing, and the type of treatment applied (duration and antibiotics used). In any case, the potential pathophysiological implications of these observations warrant further investigations. In humans, increased bacterial wall adherence has been suggested as a pathogenic factor leading to local immune responses that favor the appearance and maintenance of intestinal inflammation.[21, 45] Interestingly, antibiotic-induced dysbiosis had no impact on the gut-to-brain modulation of endocrine responses to psychological stress. This agrees with recent data suggesting that the gut-to-brain signaling is established during the early post-natal phase and that commensal microbiota is important during that imprinting period.[4, 46] Once the gut is colonized and the commensal microbiota established, changes in microbiota composition seem to have a minor impact in gut-to-brain signaling, at least as stress-related endocrine responses relates.[46] Despite this, intestinal microbiota has been related as a putative factor affecting gut sensory systems leading to altered behavioral[47, 48] and local visceral responses, such as visceral pain.[12, 49] For instance, gut commensal microbiota is fundamental for the development of inflammatory pain in mice.[12, 49, 50] Here, we assessed changes in the endocannabinoid and the serotonergic systems, two of the main sensory systems within the gut, with a demonstrated involvement in secretomotor- and visceral pain-related responses.[49, 51-54] In the present conditions, antibiotics selectively upregulated the expression of CB2; an effect further enhanced by the addition of stress. This agrees with data suggesting that gut microbiota is able to upregulate the endocannabinoid system within the gut.[55] Modification in the commensal microbiota by addition of specific bacterial strains (namely L. acidophilus) has been shown to upregulate CB2 expression in rats and mice, leading to the induction of visceral analgesia.[49] In agreement with this, changes in CB2 expression correlated positively with luminal counts of Lactobacillus spp., which increased with antibiotic treatment and were further enhanced in stressed antibiotic-treated mice. Overall, these observations further support the view that bacteria of the Lactobacillus spp. group should be regarded as a beneficial component of the microbiota, which might be implicated in the modulation of visceral pain responses through the modulation of the intestinal endocannabinoid system. On the other hand, counts of Clostridium spp. correlated in a negative manner with the CB2 expression reinforcing the potential role assigned to this bacterial group as a pathogenic component of the microbiota.

Expression of TPH1 and TPH2 and density of EC cells served to assess the activity of the serotonergic system. As expected, expression of TPH2, the isoform responsible for the synthesis of neuronal serotonin, was very low in whole colonic homogenates. On the other hand, expression TPH1, responsible for serotonin synthesis in EC cells, was detected at relatively high levels. Interestingly, TPH1 was upregulated in stressed animals, independently of the antibiotic treatment. These observations might suggest that, although not directly assessed, serotonin synthesis and availability is increased during stress, with commensal microbiota playing a minor role per se. Overall, this agrees with studies showing that serotonin availability might be increased within the colon during stress.[56] However, density of EC cells was not affected by stress, thus suggesting a cellular hyperactivity, rather than a hyperplasia. This contrasts with inflammatory models of gut dysfunction, such as the experimental infection with Trichinella spiralis, in which increased availability of serotonin has been associated with a hyperplasia of EC cells.[57, 58] The functional consequences of these changes in the cannabinoid and serotonergic systems warrant further studies, outside the original scope of the present work.

The changes observed in the expression of sensory-related systems are likely to have a functional significance. This is demonstrated by the changes in visceral pain-related responses observed in antibiotic-treated vs non-treated animals. In agreement with previous reports, we show that intracolonic capsaicin evokes behavioral responses consistent with the induction of visceral pain.[9, 10] Moreover, an increase in pain-related events was observed in stressed animals, thus confirming data indicating that repeated psychological stress induces visceral hypersensitivity in rodents.[26, 59] Interestingly, stress-induced hyperalgesic responses were completely prevented by the treatment with antibiotics. However, in non-stressed animals, antibiotics had no significant effects on visceral pain-related behaviors. This might suggest that the modulatory effects exerted by antibiotics are able to compensate states of altered (increased) sensitivity, without affecting basal responses. Therefore, it is feasible to assume that the changes observed in CB2 expression and serotonin availability might lead to functional effects modulating states of altered visceral sensitivity. Similarly, other sensory mediators not directly assessed here and involved in visceral pain responses, such as vanilloids,[60] might be involved in the responses observed. Overall, these observations further support an involvement of gut microbiota as a modulatory component of gut sensory functions.

As mentioned, none of the treatments applied resulted in evident intestinal inflammation. Although enlargement of the cecum was observed in antibiotic-treated animals, this was not associated with consistent histopathological alterations. It is interesting to point out that despite the increased host–bacterial interaction observed in dysbiotic mice, no signs of colonic inflammation (either macroscopical, microscopical or biochemical) were observed following the treatment with antibiotics. This contrasts with previous reports that observed signs of intestinal inflammation during both antibiotic treatment and stress.[12, 41, 61, 62] In particular, the appearance of stress-induced intestinal inflammation has been related with a mast cell infiltrate and the facilitation of bacterial wall adherence in rats.[12, 41, 61, 62] However, in our conditions, the density of mast cells was not increased by stress. Although inflammatory markers were unaltered, luminal s-IgA levels were increased during dysbiosis. Luminal s-IgA contributes to the suppression of immune reactions generated by commensal bacteria[63, 64] and, when binding to bacteria, prevent bacterial translocation.[65] Increased s-IgA levels might represent a mucosal response, likely triggered by the increased rate of bacterial attachment during dysbiosis, aiming the prevention of local and systemic inflammation and bacterial translocation. Multiple factors ranging from the species/strain used to the intensity of the stressors applied or the microbial environment might contribute to the final immune response to a dysbiotic state. Systematic studies addressing these aspects will be necessary to determine the relative contribution of these factors to the final responses observed within the gut.

In summary, the current study shows that gut commensal microbiota and stress are likely to act as interactive components in the maintenance of gut homeostasis and in the development of gut pathophysiology. Changes observed here suggest that microbiota and stress are able to selectively modulate gut sensory mechanisms, in the absence of obvious structural or biochemical alterations compatible with the presence of intestinal inflammation. Nevertheless, a mucosal immune response, characterized by increased s-IgA production, could be observed. Moreover, the treatment with antibiotics was associated with a reduction in stress-induced visceral hypersensitivity, thus suggesting that microbiota, influencing sensory-related systems within the gut, is able to modulate visceral pain arising from the intestine. Overall, these data support the potential involvement of stress and gut microbiota in the alterations observed in patients with functional gastrointestinal disorders, characterized by secretomotor and sensory alterations in the absence of structural changes. These observations warrant further studies dissecting the pathways altered by stress and gut microbes and the associated functional changes. Our observations support the view that the beneficial effect of certain bacterial strains, used as probiotics, might be associated with the modulation of the activity of endogenous sensory-related systems, such as the endocannabinoid system.


  1. Top of page
  2. Abstract
  3. Materials and Methods
  4. Results
  5. Discussion
  6. Acknowledgments
  7. Funding
  8. Disclosure
  9. Author Contribution
  10. References

E. Martínez and A. Acosta are thanked for their technical assistance.


  1. Top of page
  2. Abstract
  3. Materials and Methods
  4. Results
  5. Discussion
  6. Acknowledgments
  7. Funding
  8. Disclosure
  9. Author Contribution
  10. References

This study was supported by grants BFU2009-08229 and BES-2010-037699 (FPI program; M. A. personal support) from the Ministerio de Ciencia e Innovación (Spain) and 2009SGR708 from the Generalitat de Catalunya.

Author Contribution

  1. Top of page
  2. Abstract
  3. Materials and Methods
  4. Results
  5. Discussion
  6. Acknowledgments
  7. Funding
  8. Disclosure
  9. Author Contribution
  10. References

MA and VM designed and performed experiments, analyzed data, and wrote the manuscript; PV participated in the discussion of the data; All authors approved the final version of the manuscript.


  1. Top of page
  2. Abstract
  3. Materials and Methods
  4. Results
  5. Discussion
  6. Acknowledgments
  7. Funding
  8. Disclosure
  9. Author Contribution
  10. References
  • 1
    Longstreth GF, Thompson WG, Chey WD, Houghton LA, Mearin F, Spiller RC. Functional bowel disorders. Gastroenterology 2006; 130: 148091.
  • 2
    Elsenbruch S. Abdominal pain in Irritable Bowel Syndrome: a review of putative psychological, neural and neuro-immune mechanisms. Brain Behav Immun 2011; 25: 38694.
  • 3
    Barbara G, Cremon C, De Giorgio R et al. Mechanisms underlying visceral hypersensitivity in irritable bowel syndrome. Curr Gastroenterol Rep 2011; 13: 30815.
  • 4
    O'Mahony SM, Marchesi JR, Scully P et al. Early life stress alters behavior, immunity, and microbiota in rats: implications for irritable bowel syndrome and psychiatric illnesses. Biol Psychiatry 2009; 65: 2637.
  • 5
    Bercik P, Collins SM, Verdu EF. Microbes and the gut-brain axis. Neurogastroenterol Motil 2012; 24: 40513.
  • 6
    DuPont AW, DuPont HL. The intestinal microbiota and chronic disorders of the gut. Nat Rev Gastroenterol Hepatol 2011; 8: 52331.
  • 7
    Mantis NJ, Rol N, Corthesy B. Secretory IgA's complex roles in immunity and mucosal homeostasis in the gut. Mucosal Immunol 2011; 4: 60311.
  • 8
    Hansen J, Gulati A, Sartor RB. The role of mucosal immunity and host genetics in defining intestinal commensal bacteria. Curr Opin Gastroenterol 2010; 26: 56471.
  • 9
    Gonzalez-Cano R, Merlos M, Baeyens JM, Cendan CM. Sigma1 receptors are involved in the visceral pain induced by intracolonic administration of capsaicin in mice. Anesthesiology 2013; 118: 691700.
  • 10
    Laird JM, Martinez-Caro L, Garcia-Nicas E, Cervero F. A new model of visceral pain and referred hyperalgesia in the mouse. Pain 2001; 92: 33542.
  • 11
    van der Waaij D, Berghuis-de Vries JM, Korthals Altes C. Oral dose and faecal concentration of antibiotics during antibiotic decontamination in mice and in a patient. J Hyg 1974; 73: 197203.
  • 12
    Verdu EF, Bercik P, Verma-Gandhu M et al. Specific probiotic therapy attenuates antibiotic induced visceral hypersensitivity in mice. Gut 2006; 55: 18290.
  • 13
    Bailey MT, Dowd SE, Galley JD, Hufnagle AR, Allen RG, Lyte M. Exposure to a social stressor alters the structure of the intestinal microbiota: implications for stressor-induced immunomodulation. Brain Behav Immun 2011; 25: 397407.
  • 14
    Larsson MH, Miketa A, Martinez V. Lack of interaction between psychological stress and DSS-induced colitis affecting colonic sensitivity during colorectal distension in mice. Stress 2009; 12: 43444.
  • 15
    Melgar S, Engstrom K, Jagervall A, Martinez V. Psychological stress reactivates dextran sulfate sodium-induced chronic colitis in mice. Stress 2008; 11: 34862.
  • 16
    Teran-Ventura E, Roca M, Martin MT, Abarca ML, Martinez V, Vergara P. Characterization of housing-related spontaneous variations of gut microbiota and expression of toll-like receptors 2 and 4 in rats. Microb Ecol 2010; 60: 691702.
  • 17
    Salzman NH, de Jong H, Paterson Y, Harmsen HJ, Welling GW, Bos NA. Analysis of 16S libraries of mouse gastrointestinal microflora reveals a large new group of mouse intestinal bacteria. Microbiology 2002; 148: 365160.
  • 18
    Selinummi J, Seppala J, Yli-Harja O, Puhakka JA. Software for quantification of labeled bacteria from digital microscope images by automated image analysis. Biotechniques 2005; 39: 85963.
  • 19
    Pelissier MA, Vasquez N, Balamurugan R et al. Metronidazole effects on microbiota and mucus layer thickness in the rat gut. FEMS Microbiol Ecol 2010; 73: 60110.
  • 20
    Livak KJ, Schmittgen TD. Analysis of relative gene expression data using real-time quantitative PCR and the 2(-Delta Delta C(T)) Method. Methods 2001; 25: 4028.
  • 21
    Swidsinski A, Loening-Baucke V, Theissig F et al. Comparative study of the intestinal mucus barrier in normal and inflamed colon. Gut 2007; 56: 34350.
  • 22
    Amador-Arjona A, Delgado-Morales R, Belda X et al. Susceptibility to stress in transgenic mice overexpressing TrkC, a model of panic disorder. J Psychiatr Res 2010; 44: 15767.
  • 23
    Lupp C, Robertson ML, Wickham ME et al. Host-mediated inflammation disrupts the intestinal microbiota and promotes the overgrowth of Enterobacteriaceae. Cell Host Microbe 2007; 2: 204.
  • 24
    Swidsinski A, Sydora BC, Doerffel Y et al. Viscosity gradient within the mucus layer determines the mucosal barrier function and the spatial organization of the intestinal microbiota. Inflamm Bowel Dis 2007; 13: 96370.
  • 25
    Zoetendal EG, Mackie RI. Molecular methods in microbial ecology. In: Tannock GW, ed. Probiotics and Prebiotics: Scientific Aspects, 1st edn. Dunedin, New Zealand: Caister Academic Press, University of Otago, 2005: 124.
  • 26
    Larauche M, Gourcerol G, Million M, Adelson DW, Tache Y. Repeated psychological stress-induced alterations of visceral sensitivity and colonic motor functions in mice: influence of surgery and postoperative single housing on visceromotor responses. Stress 2010; 13: 34354.
  • 27
    Derrien M, Collado MC, Ben-Amor K, Salminen S, de Vos WM. The Mucin degrader Akkermansia muciniphila is an abundant resident of the human intestinal tract. Appl Environ Microbiol 2008; 74: 16468.
  • 28
    Joossens M, Huys G, Cnockaert M et al. Dysbiosis of the faecal microbiota in patients with Crohn's disease and their unaffected relatives. Gut 2011; 60: 6317.
  • 29
    O'Malley D, Julio-Pieper M, Gibney SM, Dinan TG, Cryan JF. Distinct alterations in colonic morphology and physiology in two rat models of enhanced stress-induced anxiety and depression-like behaviour. Stress 2010; 13: 11422.
  • 30
    Martinez V, Wang L, Rivier J, Grigoriadis D, Tache Y. Central CRF urocortins and stress increase colonic transit via CRF1 receptors while activation of CRF2 receptors delays gastric transit in mice. J Physiol 2004; 556: 22134.
  • 31
    Soderholm JD, Perdue MH. Stress and gastrointestinal tract. II. Stress and intestinal barrier function. Am J Physiol Gastrointest Liver Physiol 2001; 280: G713.
  • 32
    Caso JR, Leza JC, Menchen L. The effects of physical and psychological stress on the gastro-intestinal tract: lessons from animal models. Curr Mol Med 2008; 8: 299312.
  • 33
    Bergstrom KS, Guttman JA, Rumi M et al. Modulation of intestinal goblet cell function during infection by an attaching and effacing bacterial pathogen. Infect Immun 2008; 76: 796811.
  • 34
    Van den Abbeele P, Van de Wiele T, Verstraete W, Possemiers S. The host selects mucosal and luminal associations of coevolved gut microorganisms: a novel concept. FEMS Microbiol Rev 2011; 35: 681704.
  • 35
    Salzman NH. Microbiota-immune system interaction: an uneasy alliance. Curr Opin Microbiol 2011; 14: 99105.
  • 36
    Bishara J, Peled N, Pitlik S, Samra Z. Mortality of patients with antibiotic-associated diarrhoea: the impact of Clostridium difficile. J Hosp Infect 2008; 68: 30814.
  • 37
    Buffie CG, Jarchum I, Equinda M et al. Profound alterations of intestinal microbiota following a single dose of clindamycin results in sustained susceptibility to Clostridium difficile-induced colitis. Infect Immun 2012; 80: 6273.
  • 38
    Chang JY, Antonopoulos DA, Kalra A et al. Decreased diversity of the fecal Microbiome in recurrent Clostridium difficile-associated diarrhea. J Infect Dis 2008; 197: 4358.
  • 39
    Videla S, Vilaseca J, Guarner F et al. Role of intestinal microflora in chronic inflammation and ulceration of the rat colon. Gut 1994; 35: 10907.
  • 40
    Schultsz C, Van Den Berg FM, Ten Kate FW, Tytgat GN, Dankert J. The intestinal mucus layer from patients with inflammatory bowel disease harbors high numbers of bacteria compared with controls. Gastroenterology 1999; 117: 108997.
  • 41
    Soderholm JD, Yang PC, Ceponis P et al. Chronic stress induces mast cell-dependent bacterial adherence and initiates mucosal inflammation in rat intestine. Gastroenterology 2002; 123: 1099108.
  • 42
    Guarner F, Malagelada JR. Role of bacteria in experimental colitis. Best Pract Res Clin Gastroenterol 2003; 17: 793804.
  • 43
    Reeves AE, Theriot CM, Bergin IL, Huffnagle GB, Schloss PD, Young VB. The interplay between microbiome dynamics and pathogen dynamics in a murine model of Clostridium difficile Infection. Gut Microbes 2011; 2: 14558.
  • 44
    Tlaskalova-Hogenova H, Stepankova R, Kozakova H et al. The role of gut microbiota (commensal bacteria) and the mucosal barrier in the pathogenesis of inflammatory and autoimmune diseases and cancer: contribution of germ-free and gnotobiotic animal models of human diseases. Cell Mol Immunol 2011; 8: 11020.
  • 45
    Martinez-Medina M, Aldeguer X, Gonzalez-Huix F, Acero D, Garcia-Gil LJ. Abnormal microbiota composition in the ileocolonic mucosa of Crohn's disease patients as revealed by polymerase chain reaction-denaturing gradient gel electrophoresis. Inflamm Bowel Dis 2006; 12: 113645.
  • 46
    Sudo N, Chida Y, Aiba Y et al. Postnatal microbial colonization programs the hypothalamic-pituitary-adrenal system for stress response in mice. J Physiol 2004; 558: 26375.
  • 47
    Bravo JA, Forsythe P, Chew MV et al. Ingestion of Lactobacillus strain regulates emotional behavior and central GABA receptor expression in a mouse via the vagus nerve. Proc Natl Acad Sci USA 2011; 108: 160505.
  • 48
    Gareau MG, Wine E, Rodrigues DM et al. Bacterial infection causes stress-induced memory dysfunction in mice. Gut 2011; 60: 30717.
  • 49
    Rousseaux C, Thuru X, Gelot A et al. Lactobacillus acidophilus modulates intestinal pain and induces opioid and cannabinoid receptors. Nat Med 2007; 13: 357.
  • 50
    Amaral FA, Sachs D, Costa VV et al. Commensal microbiota is fundamental for the development of inflammatory pain. Proc Natl Acad Sci USA 2008; 105: 21937.
  • 51
    Brusberg M, Arvidsson S, Kang D, Larsson H, Lindstrom E, Martinez V. CB1 receptors mediate the analgesic effects of cannabinoids on colorectal distension-induced visceral pain in rodents. J Neurosci 2009; 29: 155464.
  • 52
    Cremon C, Carini G, Wang B et al. Intestinal serotonin release, sensory neuron activation, and abdominal pain in irritable bowel syndrome. Am J Gastroenterol 2011; 106: 12908.
  • 53
    Yuce B, Kemmer M, Qian G et al. Cannabinoid 1 receptors modulate intestinal sensory and motor function in rat. Neurogastroenterol Motil 2010; 22: 672e205.
  • 54
    Zoppi S, Madrigal JL, Perez-Nievas BG et al. Endogenous cannabinoid system regulates intestinal barrier function in vivo through cannabinoid type 1 receptor activation. Am J Physiol Gastrointest Liver Physiol 2011; 302: G56571.
  • 55
    Muccioli GG, Naslain D, Backhed F et al. The endocannabinoid system links gut microbiota to adipogenesis. Mol Syst Biol 2010; 6: 392.
  • 56
    Julio-Pieper M, O'Mahony CM, Clarke G, Bravo JA, Dinan TG, Cryan JF. Chronic stress-induced alterations in mouse colonic 5-HT and defecation responses are strain dependent. Stress 2012; 15: 21826.
  • 57
    Bertrand PP, Barajas-Espinosa A, Neshat S, Bertrand RL, Lomax AE. Analysis of real-time serotonin (5-HT) availability during experimental colitis in mouse. Am J Physiol Gastrointest Liver Physiol 2010; 298: G44655.
  • 58
    Wheatcroft J, Wakelin D, Smith A, Mahoney CR, Mawe G, Spiller R. Enterochromaffin cell hyperplasia and decreased serotonin transporter in a mouse model of postinfectious bowel dysfunction. Neurogastroenterol Motil 2005; 17: 86370.
  • 59
    Bradesi S, Martinez V, Lao L, Larsson H, Mayer EA. Involvement of vasopressin 3 receptors in chronic psychological stress-induced visceral hyperalgesia in rats. Am J Physiol Gastrointest Liver Physiol 2009; 296: G3029.
  • 60
    van den Wijngaard RM, Welting O, Bulmer DC et al. Possible role for TRPV1 in neomycin-induced inhibition of visceral hypersensitivity in rat. Neurogastroenterol Motil 2009; 21: 863e60.
  • 61
    Reber SO. Stress and animal models of inflammatory bowel disease–an update on the role of the hypothalamo-pituitary-adrenal axis. Psychoneuroendocrinology 2012; 37: 119.
  • 62
    Santos J, Yang PC, Soderholm JD, Benjamin M, Perdue MH. Role of mast cells in chronic stress induced colonic epithelial barrier dysfunction in the rat. Gut 2001; 48: 6306.
  • 63
    Tsuruta T, Inoue R, Iwanaga T, Hara H, Yajima T. Development of a method for the identification of S-IgA-coated bacterial composition in mouse and human feces. Biosci Biotechnol Biochem 2010; 74: 96873.
  • 64
    Mathias A, Corthesy B. N-Glycans on secretory component: mediators of the interaction between secretory IgA and gram-positive commensals sustaining intestinal homeostasis. Gut Microbes 2011; 2: 28793.
  • 65
    Duerkop BA, Vaishnava S, Hooper LV. Immune responses to the microbiota at the intestinal mucosal surface. Immunity 2009; 31: 36876.