Tissue sampling

Mice were anaesthetised (ketamine/xylazine, intraperineally, 100 and 10 mg/kg, respectively) after a 5 h period of fasting, and blood samples and tissues were harvested for further analysis. Mice were killed by cervical dislocation. Liver, caecum (full and empty), muscles (vastus lateralis), and adipose tissues (epididymal, subcutaneous and visceral) were precisely dissected and weighed. The intestinal segments (jejunum, colon) were immersed in liquid nitrogen, and stored at −80°C, for further analysis.

Microbial analysis of the caecal content of selected mice

Metagenomic DNA was extracted from the caecal content of randomly selected mice (5/group), using the QIAamp DNA stool mini kit (Qiagen, Venlo, Netherlands) according to the manufacturer’s instructions. Denaturing gradient gel electrophoresis (DGGE) on total bacteria, bifidobacteria and lactobacilli were performed to study the qualitative effect of the treatment on the structure and composition of the intestinal microbial community.⁴⁰ DGGE with a 45–60% denaturant gradient were used to separate the polymerase chain reaction (PCR) products obtained with a nested approach for the 16S rRNA genes of bifidobacteria (primers BIF164f-BIF662r) and lactobacilli (SGLAB0158f-SGLAB0667). The first PCR round was followed by a second amplification with primers 338F-GC and 518R. The latter primers were also used to amplify the 16S rDNA of all bacteria on total extracted DNA. The DGGE patterns obtained were subsequently analysed using the Bionumerics software version 2.0 (Applied Maths, Sint-Martens-Latem, Belgium).⁴¹ In brief, the calculation of the similarities was based on the Pearson (product–moment) correlation coefficient. Clustering analysis was performed using the unweighted pair group method with arithmetic mean clustering algorithm (UPGMA) to calculate the dendrograms of each DGGE gel and a combination of all gels. The latter was performed on a created composite dataset. Multidimensional scaling (MDS) analysis was used to reduce the different data of the complex DGGE patterns of one sample to one point in a three-dimensional space. MDS was based on the combined information from the distance matrices of each DGGE, obtained using similarity coefficients (Pearson correlation).

Quantitative PCR (qPCR) for total bacteria (using primers PRBA338f and P518r) and specific for bifidobacteria, lactobacilli or the Eubacterium rectale/Clostridium coccoides grp. was performed to study the quantitative effect of the treatment on the composition of the intestinal microbial community as reported by Possemiers et al.⁴²

Real-time qPCR

Total RNA from tissues was prepared using the TriPure reagent (Roche, Basel, Switzerland) as described.³³ cDNA was synthesised using a reverse transcription kit (Promega, Madison, Wisconsin, USA) from 1 μg of total RNA. qPCR was performed with a STEP one PLUS instrument and software (Applied Biosystems, Foster City, California, USA), as described.⁶ Primer sequences for the targeted mouse genes are presented in supplemental table 1.

Immunofluorescence analysis of occludin and ZO-1

Jejunum segments were immediately removed, washed with PBS, mounted in embedding medium (Tissue-Tek, Sakura, Netherlands), and stored at −80°C until use. Cryosections (5 μm) were fixed in acetone at −20°C for 5 min for occludin and fixed in ethanol for 30 min at room temperature and in acetone at −20°C for 5 min for ZO-1. Non-specific background was blocked by incubation with 10% bovine serum albumin (BSA) in Tris-buffered saline (TBS) and 0.3% Triton X-100 (30 min at room temperature). Sections were incubated with rabbit anti-occludin or rabbit anti-ZO-1 (1:400 for ZO-1 and 1:100 for occludin staining; Zymed Laboratories, San Francisco, California, USA) for 2 h. Sections were washed three times for 10 min in TBS and probed with goat anti-rabbit fluorescein isothiocyante (FITC)-conjugated antibodies (1:50, Zymax; Zymed Laboratories). Slides were washed three times for 10 min in TBS and mounted in mounting medium (Vectashield; Vector Laboratories, Burlingame, California, USA). Sections were visualised on a fluorescence microscope using a ×40 objective, and images were stored digitally with Leica software. As a control, slides were incubated with serial dilutions of the primary antibody to signal extinction. Two negative controls were used: slides incubated with irrelevant antibody or without primary antibody. All the stainings were performed in duplicate in non-serial distant sections, and analysed in a double-blind manner by two different investigators.

Intestinal permeability in vivo

This measure is based on the intestinal permeability towards 4000 Da fluorescent dextran–FITC (DX-4000–FITC) (FD4000; Sigma-Aldrich, St. Louis, Missouri, USA) as described.^{6 43} Briefly, mice that had fasted for 6 h were given DX-4000–FITC by gavage (500 mg/kg body weight, 125 mg/ml). After 1 h and 4 h, 120 μl of blood was collected from the tip of the tail vein. The blood was centrifuged at 4°C, 12000g for 3 min. Plasma was diluted in an equal volume of PBS (pH 7.4) and analysed for DX-4000–FITC concentration with a fluorescence spectrophotometer (HTS-7000 Plus-plate-reader; Perkin Elmer, Wellesley, Massachusetts, USA) at an excitation wavelength of 485 nm and emission wavelength of 535 nm. Standard curves were obtained by diluting FITC–dextran in non-treated plasma diluted with PBS (1:3 v/v).

Biochemical analyses

Plasma LPS concentration was determined by using a kit based upon a Limulus amoebocyte extract (LAL kit endpoint-QCL1000; Cambrex BioScience, Walkersville, Maryland, USA), samples were diluted 1/40 to 1/100 and heated for 20 cycles of 10 min at 68°C and 10 min at 4°C. An internal control for LPS recovery was included in the calculation. Plasma cytokines (interleukin (IL) 1α, IL1b, tumour necrosis factor (TNF) α, IL6, monocyte chemoattractant protein (MCP)-1, macrophage inflammatory protein (MIP)-1α, IL10, interferon (INF) γ, IL15, IL18) and gut hormones (GLP-1 (active), GIP (total), amylin (active), pancreatic polypeptide) were respectively determined in duplicate by using a Bio-Plex Multiplex kit (Bio-Rad, Nazareth, Belgium), or a mouse gut hormones panel (LincoPlex; Millipore, Brussels, Belgium), and measured by using Luminex technology (Bio-Rad Bioplex; Bio-Rad) following the manufacturer’s instructions, an EIA kit (GLP-2 EIA kit) (Yanaihara Institute, Shizuoka, Japan) was used to quantify GLP-2.

Changes in the gut microbiota upon prebiotic administration reduce intestinal permeability

Ob-Pre fed mice exhibited a 3-fold lower plasma DX-4000–FITC area under the curve (fig 2A) as compared to Ob-CT and Ob-Cell mice. In accordance with the in vivo assessment of intestinal permeability, LPS levels were significantly lower in Ob-Pre mice plasma samples, as compared to the other groups (fig 2B). Moreover, plasma DX-4000–FITC and portal plasma LPS levels were positively and significantly correlated (fig 2B, inset), further confirming the relation between intestinal permeability and the development of metabolic endotoxaemia. Gut permeability is controlled by several specific tight-junction proteins. Among these, ZO-1 and occludin have been proposed as key markers of tight-junction integrity.²⁶ The prebiotic treatment increased ZO-1 and occludin mRNA in the jejunum segment (fig 2C,F). As previously suggested, a representative immunofluorescence assay performed on intestinal sections of wild-type C57BL/6J mice demonstrated an intact network of ZO-1 and occludin proteins which were predominantly localised along the apical cellular border.²⁶ In strong contrast, ZO-1 and occludin staining appears to be decreased and discontinuous in Ob-CT tissues (fig 3A,B). Furthermore, immunohistochemical score analysis confirmed the strong alteration of ZO-1 and occludin distribution and expression as compared to wild-type mice (fig 2E,H). In accordance with the mRNA analysis, prebiotic feeding improved the tight junctions, since the immunohistochemical staining of both proteins localised along the apical cellular border was higher in Ob-Pre as compared to Ob-CT and Ob-Cell mice (fig 3A,B).

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Figure 2

Prebiotic treatment reduces intestinal permeability. (A) Intestinal permeability assay: Plasma DX-4000–FITC (μg/ml) oral challenge measured in ob/ob mice fed a normal diet (Ob-CT), non-prebiotic control diet (Ob-Cell), prebiotic diet (Ob-Pre) for 5 weeks. The inset corresponds to the area under curve (AUC) in the same groups. (B) Plasma endotoxin (LPS) concentrations (EU/ml); the inset corresponds to correlation between plasma LPS levels and plasma DX-4000–FITC (Pearson’s r correlation and corresponding p value). (C,F) Jejunum epithelial tight-junction protein markers (ZO-1 and occludin mRNA concentrations) relative expression to Ob-CT. Data are mean with the SEM. Data with different superscript letters are significantly different (p<0.05), according to the post hoc ANOVA statistical analysis. (D,G) Correlations between intestinal permeability markers: plasma DX-4000–FITC and ZO-1 and occludin mRNA concentrations (p<0.05); the inset corresponds to Pearson’s r correlation and corresponding p value. (E,H) Immunohistochemistry score of the jejunum epithelial tight-junction proteins (ZO-1 and occludin) in wild-type (CT), Ob-CT, Ob-Cell or Ob-Pre mice. DX-4000, dextran of molecular weight 4000 Da; EU, endotoxin unit; FITC, fluroescein isothiocyanate; LPS, lipopolysaccharide.

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Figure 3

Prebiotic treatment changes tight-junction proteins distribution. Representative immunofluorescence staining for (A) ZO-1 and (B) occludin in ob/ob mice fed a normal diet (Ob-CT), non-prebiotic control diet (Ob-Cell), prebiotic diet (Ob-Pre) for 5 weeks. WT, wild-type.

To identify whether the changes in the gut microbiota and tight-junction protein expression are associated with in vivo gut permeability, multiple correlation analysis between these parameters was performed. Indeed, a negative correlation between tight-junction proteins mRNA and plasma DX-4000–FITC was found in the jejunum segment (fig 2D,G), and in the colon (supplementary data 1). In addition, the caecal content of Bifidobacterium spp. and portal plasma levels of LPS showed a negative correlation (supplemental data 1), suggesting that the specific increase of bifidobacteria positively impacted the development of metabolic endotoxaemia.

Changes in the gut microbiota upon prebiotic administration are associated with improved systemic and hepatic inflammation

To study the effects of changes in the gut microbiota and improved barrier function on the one hand, and metabolic disorders on the other hand, we first assessed systemic inflammation. All plasma cytokine and chemokine concentrations were decreased in Ob-Pre mice when compared to Ob-CT and Ob-Cell mice (fig 4). Metabolic endotoxaemia is frequently associated with hepatic inflammation, and with increased oxidative stress driving metabolic disorders. Here we found that changing the gut microbiota significantly reduced plasminogen activator inhibitor 1 (PAI-1), CD68, NADPH oxidase (NADPHox) and inducible nitric oxide synthase (iNOS) mRNA concentrations (fig 5A,B,E,F), and tended to decrease toll-like receptor 4 (TLR4) and TNFα mRNA concentrations (fig 5I,J). The oxidative stress marker NADPHox positively correlated with macrophage infiltration markers (CD68, TLR4) (fig 5 C,D). Moreover, both macrophage infiltration markers were correlated (fig 5G). Plasma chemokine MCP-1 positively correlated with tissue macrophages infiltration and oxidative stress markers (fig 5 H,K,L). Accordingly, plasma LPS levels were positively correlated with NADPHox and macrophage infiltration markers (liver CD68 mRNA and plasma MCP-1 levels) (supplemental data 1). Furthermore, we found that these markers were negatively correlated with the content of Bifidobacterium spp. (supplemental data 1). The lower inflammatory and oxidative stress was associated with a lower total hepatic lipid content (Ob-CT: 839^a (SEM 111); Ob-Cell: 781^a (SEM 42); Ob-Pre: 531^b (SEM 58) mg of lipids/liver, Ob-Pre p<0.05 vs Ob-CT and Ob-Cell) and confirmed by histological analysis (not shown). (Different superscript letters denote a statistical difference between the groups.) Altogether, these multiple correlations support a strong relationship between gut microbiota, gut permeability, systemic and hepatic inflammation, oxidative stress and macrophage infiltration in ob/ob mice.

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Figure 4

Prebiotic treatment reduces the occurrence of systemic inflammation. (A) IL1α, (B) IL1b, (C) TNFα, (D) MCP-1, (E) MIP-1a, (F) INFγ, (G) IL6, (H) IL10, (I) IL18 and (J) IL15 plasma levels (pg/ml) in ob/ob mice fed a normal diet (Ob-CT), non-prebiotic control diet (Ob-Cell) or prebiotic diet (Ob-Pre) for 5 weeks. Data are mean with the SEM. Data with different superscript letters are significantly different (p<0.05), according to the post hoc ANOVA statistical analysis. IFN, interferon; IL, interleukin; MCP-1, monocyte chemoattratant protein-1; MIP-1a, macrophage inflammatory protein-1a; TNF, tumour necrosis factor.

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Figure 5

Changes in the gut microbiota control hepatic inflammation, oxidative stress and macrophage infiltration markers. (A,I) Inflammation: PAI-1, TNFα mRNA concentrations; (B,J) Macrophage infiltration markers: CD68, TLR4 mRNA concentrations; (E,F) Oxidative stress markers: NADPHox, iNOS mRNA concentrations in ob/ob mice fed a normal diet (Ob-CT), non-prebiotic control diet (Ob-Cell) or prebiotic diet (Ob-Pre) for 5 weeks. Data are mean with the SEM. Data with different superscript letters are significantly different (p<0.05), according to the post hoc ANOVA statistical analysis. Correlations between liver NADPHox mRNA and (C) liver CD68 mRNA, (D) TLR4 mRNA or (K) plasma MCP-1 levels. Correlations between plasma MCP-1 and (H) liver CD68 mRNA or (L) TLR4 mRNA. (G) Correlation between liver CD68 mRNA and TLR4 mRNA concentrations (p<0.05) the inset corresponds to Pearson’s r correlation and corresponding p value. iNOS, inducible nitric oxide synthase; MCP-1, monocyte chemoattractant protein-1; NADPHox, NADPH oxidase; PAI-1, plasminogen activator inhibitor; TLR, toll-like receptor; TNF, tumour necrosis factor.

Prebiotic feeding modulates plasma gut peptides and adiposity

Prebiotic administration decreased food intake (Ob-CT: 24.9^a (SEM 0.7); Ob-Cell: 20.0^b (SEM 0.5); Ob-Pre: 16.3^c (SEM 1.1) kcal/day.mouse; p<0.05). We have previously demonstrated that prebiotic-induced changes in the gut microbiota modulate gastrointestinal peptides (GLP-1, peptide YY (PYY), ghrelin) involved in glucose homeostasis, appetite and/or body weight regulation.^{8 33 44–48} Here, we found that the prebiotic treatment also modulated portal plasma gut peptides in ob/ob mice, leading to a significant increase in GLP-1 (table 2). In addition, the glucose-dependent insulinotropic polypeptides (GIPs), another peptide associated with the development of obesity, diabetes and adiposity, was significantly decreased (table 2).^49–51 In accordance with this, Ob-Pre mice had lower visceral, epididymal and subcutaneous adipose depots and a higher muscle mass as compared to the other groups (supplemental data 2).

This study is the first in which it is shown that, besides an effect on gut peptides, feeding prebiotics also modulated two pancreatic peptides, since it significantly increased amylin (table 2) and decreased pancreatic polypeptide (PP) as compared to Ob-CT and Ob-Cell mice (table 2). The link between the above-mentioned peptides modulated by prebiotics and gut permeability has not been described so far. Moreover, the decrease in food intake and/or a decrease in adiposity are not involved in changes in gut permeability. Thus, we have hypothesised that GLP-2, a peptide clearly related to GLP-1 production, could link changes in gut microbiota and intestinal barrier function.

Prebiotic administration increases intestinal proglucagon mRNA and portal plasma proglucagon-derived peptide GLP-2

We and other have previously shown that changing gut microbiota by using fermentable non-digestible carbohydrate significantly increases gut weight and promotes proliferation of epithelial cells.^52–54 We have also shown – and confirmed in the present study (table 2) – that feeding mice with prebiotic doubled GPL-1 portal plasma levels.^{8 33 44 45 47 48 55 56} In previous studies, the increase in GLP-1 plasma level was associated with a higher GPL-1 peptide and proglucagon mRNA expression in the (proximal) colon tissue. Interestingly, our study is the first to show that a higher proglucagon mRNA content occurs in the proximal colon – as expected – and also in the jejunum (fig 6A,B). Among the proglucagon-derived peptides, GLP-2 is co-secreted with GLP-1 and exerts an intestinotrophic effect.^{39 57 58} GLP-2 enhances intestinal epithelial proliferation and reduces gut permeability,^59–62 hence, we found that Ob-Pre fed mice exhibited a significant increase of plasma GLP-2 levels (table 2). Importantly, portal plasma GLP-2 and both plasma markers of gut permeability (DX-4000–FITC and LPS) were negatively correlated (fig 6C,D). Along the same line, intestinal proglucagon and tight-junction mRNA (ZO-1, occludin) were positively correlated (fig 6E,F). Altogether, these data suggest that the prebiotic-induced intestinal proglucagon mRNA enhanced expression and the consequent GLP-2 production indicate that this peptide may positively impacts on gut barrier integrity.

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Figure 6

Prebiotic administration increases intestinal proglucagon mRNA and correlates with intestinal permeability markers. (A) Jejunum proglucagon mRNA concentrations; (B) proximal colon proglucagon mRNA concentrations in ob/ob mice fed a normal diet (Ob-CT), non-prebiotic control diet (Ob-Cell), prebiotic diet (Ob-Pre) for 5 weeks. Data are mean with the SEM. Data with different superscript letters are significantly different (p<0.05), according to the post hoc ANOVA statistical analysis. Correlations between plasma GLP-2 levels and (C) plasma LPS plasma; or (D) DX-4000–FITC plasma levels. Correlations between proglucagon mRNA and (E) jejunum ZO-1 or (F) occludin mRNA concentrations; the inset corresponds to Pearson’s r correlation and corresponding p value. DX 4000, dextran of molecular weight 4000 Da; FITC, fluorescein isothiocyanate; GLP-2, glucogon-like protein-2; LPS, lipopolysaccharide.

Chronic GLP-2 antagonist treatment blunts prebiotic-induced reduction in endotoxaemia and hepatic inflammatory tone

To causally link changes in endogenous GLP-2 production upon prebiotic treatment with the improvement of metabolic endotoxaemia, and inflammatory markers, we chronically blocked GLP-2 receptor in prebiotic fed ob/ob mice by using GLP-2 antagonist.

In this second set of experiments, we confirm the data observed in the first study showing that prebiotic-induced changes in gut microbiota are linked to a significant decrease in plasma LPS levels, hepatic inflammation and oxidative stress markers such as PAI-1, CD68, NADPHox and TLR4 mRNA concentrations (fig 7B–D,F), and to a tendency to decrease for iNOS and TNFα mRNA concentrations (fig 7E,G). In addition, we also confirm that the prebiotic treatment increases ZO-1 and occludin mRNA (fig 7H) and the GLP-2 precursor transcript (proglucagon mRNA) content in the jejunum (fig 7I).

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Figure 7

Chronic GLP-2 antagonist treatment blunts prebiotic-induced reduction in endotoxaemia and hepatic inflammatory tone. (A) Plasma LPS concentrations (EU/ml); (B,D) Macrophage infiltration markers: TLR4, CD68mRNA concentrations; (C,E) oxidative stress markers: NADPHox, iNOS mRNA concentrations; (F,G) hepatic inflammation: PAI-1, TNFα mRNA concentrations; (H) jejunum epithelial tight-junction protein markers (ZO-1 and occludin mRNA) concentrations; (I) jejunum proglucagon mRNA concentrations in ob/ob mice fed a normal diet and injected twice daily with a saline (Ob-CT), prebiotic diet and injected twice daily with a saline (Ob-Pre), prebiotic diet and injected twice daily with GLP-2 antagonist (ObPre-Ant), normal diet and injected twice daily with GLP-2 antagonist (Ob-Ant) for 4 weeks. Data are mean with the SEM. *Significantly different (p<0.05) from Ob-CT and Ob-Pre-Ant according to the Kruskal–Wallis test analysis. Data with different superscript letters are significantly different (p<0.05), according to the post hoc ANOVA statistical analysis. EU, endotoxin unit; GLP-2, glucagon-like protein-2; iNOS, inducible nitric oxide synthase; NADPHox, NADPH oxidase; PAI-1, plasminogen activator inhibitor-1; PG, proglucagon; TJ, tight junction; TLR, toll-like receptor; TNF, tumour necrosis factor.

Importantly, the GLP-2 antagonist completely blunts the prebiotic-induced reduction endotoxaemia (fig 7A). Hence, most of the prebiotic-induced changes of hepatic inflammation and oxidative stress markers are also controlled by a GLP-2-dependent mechanism. We observed that mice treated concomitantly with the prebiotic and the GLP-2 antagonist or GLP-2 antagonist alone exhibit CD68, NADPHox and TLR4 mRNA levels (fig 7B–D) similar to the control mice, except for the PAI-1 mRNA levels (fig 7F) which remains equivalent to the prebiotic treated mice with or without GLP-2 antagonist treatment. Moreover, GLP-2 antagonist treatment completely blocked the enhanced proglucagon, ZO1 and occludin mRNA levels found in prebiotic fed mice that reach values similar to the control (fig 7H,I).

We thank RM Goebbels for assistance with the histology.