Beneficial effects of exercise on gut microbiota functionality and barrier integrity, and gut-liver crosstalk in an in vivo model of early obesity and non-alcoholic fatty liver disease

Abstract

Childhood obesity has reached epidemic levels, representing one of the most serious public health concerns associated with metabolic syndrome and non-alcoholic fatty liver disease (NAFLD). There is limited clinical experience concerning pediatric NAFLD patients, and thus the therapeutic options are scarce. The aim of this study was to evaluate the benefits of exercise on gut microbiota composition and functionality balance, and consequent effects on early obesity and NAFLD onset in an in vivo model. Juvenile (21-day-old) male Wistar rats fed a control diet or a high-fat diet (HFD) were subjected to a combined aerobic and resistance training protocol. Fecal microbiota was sequenced by an Illumina MiSeq system, and parameters related to metabolic syndrome, fecal metabolome, intestinal barrier integrity, bile acid metabolism and transport, and alteration of the gut-liver axis were measured. Exercise decreased HFD-induced body weight gain, metabolic syndrome and hepatic steatosis, as a result of its lipid metabolism modulatory capacity. Gut microbiota composition and functionality were substantially modified as a consequence of diet, age and exercise intervention. In addition, the training protocol increased Parabacteroides, Bacteroides and Flavobacterium genera, correlating with a beneficial metabolomic profile, whereas Blautia, Dysgonomonas and Porphyromonas showed an opposite pattern. Exercise effectively counteracted HFD-induced microbial imbalance, leading to intestinal barrier preservation, which, in turn, prevented deregulation of the gut-liver axis and improved bile acid homeostasis, determining the clinical outcomes of NAFLD. In conclusion, we provide scientific evidence highlighting the benefits of gut microbiota composition and functionality modulation by physical exercise protocols in the management of early obesity and NAFLD development.

Keywords: Childhood obesity; Fecal metabolome; Gut-liver axis; Intestinal microbiota; Metabolic syndrome.

Fig. 1.

Effects of diet and exercise intervention on obesity, NAFLD-associated hepatic histological findings and lipid-metabolism regulation in juvenile rats fed a control diet or HFD over 11 weeks. (A) Body weight. (B) Food intake. (C) Top: liver specimens. Bottom: representative H&E-stained liver sections. Scale bar: 200 μm. (D) NAFLD activity score (NAS) (calculated from individual scores for steatosis, lobular inflammation and ballooning). (E) Intrahepatic triglyceride content. (F) mRNA levels of hepatic lipid-metabolism-related genes, determined by quantitative real-time PCR (RT-qPCR) at the end of the study (week 11). Data are means±s.e.m. (n=12 rats per group). *P<0.05, **P<0.01, ***P<0.001 versus control; ^#P<0.05, ^##P<0.01 versus HFD. C, control diet; C+E, control diet and exercise training; HFD, high-fat diet; HFD+E, high-fat diet and exercise training.

Fig. 2.

Effects of diet, exercise and age on gut microbiota composition. (A) Total bacterial concentration analyzed by quantitative PCR, Shannon diversity index and Firmicutes/Bacteroidetes ratio. Data are means±s.e.m. *P<0.05 versus control, ****P<0.0001 versus control; ^#P<0.05 versus HFD. (B) Relative abundances of the indicated total populations at phylum level. (C) Box plots showing differences in the numbers of reads of Firmicutes, Bacteroidetes, Proteobacteria and Verrucomicrobia phyla. The boxes represent the interquartile range (IQR) between the first and third quartiles (25th and 75th percentiles, respectively) and the horizontal line inside the box defines the median. Whiskers represent the lowest and highest values within 1.5 times the IQR from the first and third quartiles, respectively. Samples exceeding those values are represented as points beside the boxes. Statistical analysis was performed using Kruskal–Wallis followed by Mann–Whitney U-test; ^aaaaP<0.0001 versus control (week 6); *P<0.05 versus control; ^#P<0.05 versus HFD. (D) Relative abundances of the indicated populations at class level.

Fig. 3.

Principal coordinates analysis (PCoA) plot derived from the Morisita-Horn dissimilarity index at the phylum level of the six experimental groups at 6 and 11 weeks. The percentage of the total variance explained is indicated in parentheses in each axis. Shaded areas denote sample clusters according to diet (light gray, control; dark gray, HFD). The dashed line demarcates a subset associated with age.

Fig. 4.

Effects of diet, exercise and age on gut microbiota balance at genus level. Box plots representing the differences between control and HFD-fed rats with and without exercise training at 6 and 11 weeks. The boxes represent the interquartile range (IQR) between the first and third quartiles (25th and 75th percentiles, respectively) and the horizontal line inside the box defines the median. Whiskers represent the lowest and highest values within 1.5 times the IQR from the first and third quartiles, respectively. Samples exceeding those values are represented as points beside the boxes. Statistical analysis was performed using the Mann–Whitney U-test; ^aP<0.05, ^aaP<0.01, ^aaaaP<0.0001 versus control (6 weeks); *P<0.05, ***P<0.001 versus control; ^#P<0.05 versus HFD; ⁺⁺⁺⁺P<0.0001 versus 6 weeks, independently of diet. P-values are corrected for multiple comparisons based on false discovery rate (FDR).

Fig. 5.

Relationship between gut microbiota and fecal metabolome. (A) Orthogonal projections to latent structures discriminant analysis (OPLS-DA) of metabolites from control and HFD-fed rats at 6 weeks. (B) OPLS-DA showing the effect of age on metabolomic profile. (C) Partial least squares discriminant analysis (PLS-DA) of metabolites from control and HFD-fed rats with and without exercise training at 11 weeks. Colored ellipses represent the 95% confidence range for the indicated experimental group. (D) Spearman's correlation analysis was used to investigate the relationship between fecal bacterial populations and metabolite levels, considering results obtained longitudinally in all groups. Red and blue cells indicate positive and negative correlations, respectively. ⁺P<0.05, ⁺⁺P<0.01, ⁺⁺⁺P<0.001. P-values are corrected for multiple comparisons based on FDR.

Fig. 6.

Effects of diet and exercise intervention on intestinal barrier integrity, activation of the gut-liver axis and bile acid (BA)-metabolism-related gene expression in control and HFD-fed rats at 11 weeks. (A) Representative H&E-stained small intestine sections (left). Scale bar: 200 μm. Bar graph showing villus height, crypt depth and mucosa thickness linear measurements (right). (B) mRNA levels of intestinal claudin-1 and occluding, determined by RT-qPCR. (C) Plasma LPS levels were measured using an LAL Chromogenic Endotoxin Quantitation Kit. (D,F) mRNA levels of Cyp2e1, Tlr-4, Tnf-a and Il-6 (F, liver samples; D, gut samples). (E,G) NF-κB (p65) transcriptional activity (G, liver samples; E, gut samples). (H,I) mRNA levels of BA-metabolism-related genes (H, liver samples; I, gut samples). Data are means±s.e.m. (n=12 rats per group). *P<0.05, **P<0.01, ***P<0.001, ****P<0.0001 versus control; ^#P<0.05, ^###P<0.001, ^####P<0.0001 versus HFD.

Fig. 7.

Correlation between gut microbiota composition and early-obesity-associated NAFLD spectrum. Spearman's coefficient (r), ranging from positive (red) to negative (blue) values, was used to cross-correlate bacterial genera and phenotypic parameters associated with early obesity and NAFLD at 11 weeks. ⁺P<0.05. Box plots represent the differences between control and HFD-fed rats with and without exercise training at week 11 of the study. The boxes represent the interquartile range (IQR) between the first and third quartiles (25th and 75th percentiles, respectively) and the horizontal line inside the box defines the median. Whiskers represent the lowest and highest values within 1.5 times the IQR from the first and third quartiles, respectively. Samples exceeding those values are represented as points beside the boxes. Fasting insulin and leptin levels, epididymal fat (as % of body weight), liver triglycerides, body weight gain and ALT levels at week 11 are represented as bar graphs. *P<0.05, **P<0.01, ***P<0.001 versus control, ^#P<0.05 versus HFD.