Microbiota characteristic in the pathogenesis and progression of NAFLD

PCR-DGGE fingerprinting results showed that the diversity of gut flora in model C group were notably less than that of control group and model group A (Fig. 1A). Cluster analysis revealed that similarity coefficient in the same group was higher than that between groups. The similarity coefficient within control group was the highest (69.16% ± 4.64%). The similarity coefficient within model group A, model group B and model group C were 69.48% ± 2.36%, 50.84% ± 3.61% and 56.21% ± 11.06%, respectively. For similarity between groups, the similarity coefficient was 66.61% ± 5.58% between control group and model group A. The similarity coefficient between control group and model group B was 51.22% ± 7.47%. Of note, model group C showed the lowest similarity with control group and the similarity coefficient was just 49.46% ± 4.69% (Fig. 1B).

Figure 1: The variability of intestinal bacterial communities as determined by DGGE analysis of samples from the feces. (A) Representative DGGE profiles of the fecal samples from control group and model group (A, B and C). C1 to C5 were representative of the control group, M1 to M5 were representative of the model group A, M6 to M10 were representative of the model group B, M11 to M15 were representative of the model group C. (B) Dendrogram generated from the bacterial community fingerprints of the feces, the similarities between mucosal specimens were shown in the dendrogram. Dice’s band-matching coefficient and unweighted pair group method with arithmetic averages (UPGMA) were employed to analyze the results. Full size image

To furtherly assess alterations in gut microbial composition, we detected Escherichia coli, Enterococcus, Lactobacillus, Bifidobacteria and Bacteroides in the fecal samples of rats from control group and model group A, B and C using traditional culture method and QT-PCR analysis. As shown in both Fig. 2A and B, amounts of Escherichia coli and Enterococcus increased with prolonged feeding period. Escherichia coli and Enterococcus in model group B and C were significantly elevated compared with control group. Significant differences were observed between model group A and control group for Enterococcus but not for Escherichia coli. Moreover, the amounts of Escherichia coli and Enterococcus in both model group B and model group C were significantly increased as compared to model group A, and it was also significantly different between model group B and model group C. For anaerobic bacteria, the levels of Lactobacillus, Bifidobacteria and Bacteroides in all three model groups were all decreased as compared to control group. Model group B and C had a significant decrease in these anaerobic bacteria relative to model group A, and there were also significant difference between model group B and model group C. Analysis of B/E, employed as an indicator of gut flora colonization resistance, revealed a significant reduction in all three model groups compared with control group. It was observed that B/E value in both model group B and model group C was significantly higher than that in model group A. B/E value was also significantly different between model group B and model group C for RT-PCR analysis but not for traditional culture method.

Figure 2: Comparison of five representative bacteria in feces of control group and model group A, B and C. (A) Quantification of representative bacteria in feces by quantitative PCR analysis (B) Quantification of representative bacteria in feces by traditional culture method. The ratio of Bifidobacteria to Escherichia coli was used to indicate B/E value representing gut mircobiological colonization resistance. Data represent the mean ± SD of each group. *P < 0.05 compared to the control group; **P < 0.01 compared to the control group; #P < 0.05 compared to the model group A; &P < 0.05 compared to the model group B. Full size image

Variations of the serum LPS and liver TLR4 expression in NAFLD models

As shown in Fig. 3A, the concentration of serum LPS showed a rising trend in model group A, B and C as compared to control group. Serum LPS was increased in model group B and C as compared to model group A, and the increased proportion was higher in model group C than that in model group B.

Figure 3: Comparison of serum LPS level, liver TLR4 expression and serum inflammatory cytokines in the control group and model group A, B and C. (A) Serum LPS concentration by ELISA (B) Liver TLR4 expression by quantitative PCR analysis. Data represent the mean ± SD of each group. *P < 0.05 compared to the control group; **P < 0.01 compared to the control group; ***P < 0.001 compared to the control group; #P < 0.05 compared to the model group A; ##P < 0.01 compared to the model group A; ###P < 0.001 compared to the model group A. &P < 0.05 compared to the model group B; &&P < 0.01 compared to the model group B. &&&P < 0.001 compared to the model group B. Full size image

For liver TLR4-mRNA expression, we observed a notably higher levels in model group B and C than that in control group (P < 0.001), but there was no difference between model group A and control group (P > 0.05). Model group B and C had a significant increase in levels of serum LPS relative to model group A (P < 0.05), and there was also significant difference between model group B and model group C (Fig. 3B).

Moreover, there was a positive correlation between serum LPS and the amounts of aerobic bacteria such as Escherichia coli and Enterococcus while a negative correlation was observed between serum LPS and amounts of anaerobic bacteria such as Lactobacillus, Bifidobacteria and Bacteroides. For the correlation between liver TLR4 and gut bacteria, there was a similar trend. Notably, we found a negative correlation between serum LPS and intestinal flora B/E value (r culture = −0.709 and r PCR = −0.797). The expression of liver TLR4-mRNA was also negatively associated with B/E value (r culture = −0.723 and r PCR = −0.822) (Table 1).

Table 1 Correlation analysis between serum LPS or liver TLR4-mRNA expression and gut representative bacteria, and between serum LPS or liver TLR4-mRNA expression and B/E value. Full size table

Variations of the serum inflammatory cytokines in NAFLD models

As shown in Fig. 3C and D, TNF-α and IL-18 were also increased in model group B and C compared to that in control group (P < 0.05), while no significant difference was found between model group A and control group. Both model group B and model group C exhibited a rising trend in serum levels of TNF-α and IL-18 compared with model group A. The increased proportion of IL-18 and TNF-α was significantly higher in model group C than that in model group B (P < 0.01). For IL-18, no significant increase was found in model group C as compared to model group B.

Probiotics reduce body weight in NAFLD models

As shown in Fig. 4, after feeding for 2 w, rats in both model group and intervention group gained significantly more weight than that in the control group. Notably, rats in model group gained significantly more weight than that in the intervention group after feeding for 4 w, and the increased proportion was higher with the prolonged feeding period.

Figure 4: Effects of probiotics on body weight in NAFLD models. Data represent the mean ± SD of each group. *P < 0.05 model group versus control group; **P < 0.01 model group versus control group; ***P < 0.001 model group versus control group; #P < 0.05 intervention group versus control group; ##P < 0.01 intervention group versus control group; ###P < 0.001 intervention group versus control group; &P < 0.05 intervention group versus model group; &&P < 0.01 intervention group versus model group; &&&P < 0.001 intervention group versus model group. Full size image

Probiotics ameliorate gut microbiota dysbiosis in NAFLD models

As shown in Fig. 5, amounts of both Escherichia coli and Enterococcus were significantly increased in the model group compared with control group (P < 0.01). Oppositely, amounts of anaerobic bacteria including Lactobacillus, Bifidobacteria and Bacteroides were significantly decreased in the model group compared with control group (P < 0.01). Notably, the intervention group showed a rising trend in these anaerobic bacteria but a declining trend in Escherichia coli and Enterococcus compared to the model group (P < 0.05). Consistent with anaerobic bacteria, B/E in the intervention group was obviously higher than that in model group. Although B/E presented a decreasing trend in the intervention group relative to the control group, no significant differences were observed.

Figure 5: Effects of probiotics on gut microbiota dysbiosis in NAFLD models. Quantitative PCR analysis of fecal five representative bacteria. Data represent the mean ± SD of each group. *P < 0.05 compared to the control group; **P < 0.01 compared to the control group; ***P < 0.001 compared to the control group; #P < 0.05 compared to the model group; ##P < 0.01 compared to the model group; ###P < 0.001 compared to the model group. Full size image

Probiotics ameliorate loss of intestinal barrier integrity in NAFLD models

We examined the tight junctions in the jejunum under a transmission electronmicroscope (TEM) to evaluate the jejunum microstructure. As shown in Fig. 6A, the jejunum in the control group had intact tight junctions and much more regularly aligned and extensive microvilli. However, widened tight junctions and irregularly arranged microvilli were observed in the model group. Of note, tight junctions were more complete and microvilli were more extensive in the invention group than those in the model group. Western-blotting revealed that the level of occludin protein expression was the highest in the intestinal mucosa of control group while the model group had the lowest occludin expression. Moreover, the intervention group displayed a higher expression of occludin than the model group (Fig. 6B).

Figure 6: Effects of probiotics on intestinal barrier integrity in NAFLD models. (A) Representative images of tight junctions in the jejunal mucosa (transmission electron microscopy, x5000) (B) The expression of occludin protein in the intestinal mucosa was detected with β-actin as a loading control by western blotting. Data represent the mean ± SD of each group. *P < 0.05 compared to the control group; **P < 0.01 compared to the control group; ***P < 0.001 compared to the control group; #P < 0.05 compared to the model group; ##P < 0.01 compared to the model group; ###P < 0.001 compared to the model group. Full size image

Probiotics ameliorate high expression of serum LPS and liver TLR4-mRNA in NAFLD models

From Fig. 7A and B, it was found that the levels of serum LPS and liver TLR4-mRNA were significantly increased in the model group and intervention group as compared to the control group (P < 0.05). Moreover, the intervention group had a lower levels of serum LPS and liver TLR4-mRNA than the model group (P < 0.05).

Figure 7: Effects of probiotics on the levels of serum LPS, liver TLR4-mRNA and serum inflammatory cytokines in NAFLD models. (A) Serum LPS concentration (B) Liver TLR4-mRNA expression (C) Serum IL-18 level (D) Serum TNF-α level. Data represent the mean ± SD of each group. **P < 0.01 compared to the control group; ***P < 0.001 compared to the control group; #P < 0.05 compared to the model group; ##P < 0.01 compared to the model group; ###P < 0.001 compared to the model group. Full size image

Probiotics ameliorate serum levels of inflammatory cytokines

As show in Fig. 7C and D, the serum levels of TNF-α and IL-18 were significantly higher in the model group compared with control group and there were significant differences between the two groups (P < 0.01). Notably, the serum levels of TNF-α and IL-18 showed an decreasing trend in the intervention group relative to the model group, and significant differences were observed (P < 0.05).

Probiotics ameliorate liver pathology in NAFLD models

Liver histology exhibited that the rats in control group have normal liver histology. In the model group, hepatocyte swelling, disorderly arrangement and inflammatory cells infiltration with large fat droplets emerging were observed. Comparatively, there was just mild steatosis and few infiltrations of inflammatory cells in the intervention group (Fig. 8A). Statistical analysis showed that the degree of liver inflammatory activity was significantly higher in model group and intervention group compared with control group (P < 0.01), and it was also significantly different between model group and intervention group (P < 0.01) (Fig. 8B).

Figure 8: Effects of probiotics on liver pathology in NAFLD models. (A) Typical images of representative liver pathology for HE staining (B) Statistic analysis of liver inflammation scoring. Data represent the mean ± SD of each group. *P < 0.05 compared to the control group; ***P < 0.001 compared to the control group; ##P < 0.01 compared to the model group. Full size image

Probiotics ameliorate serum levels of liver enzymes and metabolic indices

As shown in Fig. 9A, the activity of serum liver enzymes including alanine aminotransferase (ALT), aspartate aminotransferase (AST), gamma-glutamyltransferase (GGT) and alkaline phosphatase (ALP) were significantly higher in the model group compared with control group (P < 0.01). The activity of these serum enzymes presented an increasing trend in the intervention group relative to the control group, however, no significant differences were observed. Notably, the activity of these enzymes in the intervention group was decreased compared to that in model group, and significant differences were observed (P < 0.05).

Figure 9: Effects of probiotics on serum levels of liver enzymes and metabolic indices in NAFLD models. (A) Serum levels of alanine aminotransferase (ALT), aspartate aminotransferase (AST), gamma-glutamyltransferase (GGT) and alkaline phosphatase (ALP) (B) Serum levels of triglyceride (TG), total cholesterol (TC), low-density lipoprotein (LDL), high density lipoprotein (HDL) and free fatty acid (FFA) (C) fasting plasma glucose (FPG), fasting insulin (FINS) and homoeostasis model assessment of insulin resistance (HOMA-IR). Data represent the mean ± SD of each group. *P < 0.05 compared to the control group; **P < 0.01 compared to the control group; ***P < 0.001 compared to the control group; #P < 0.05 compared to the model group; ##P < 0.01 compared to the model group; ###P < 0.001 compared to the model group. Full size image

For serum lipid, we observed that the model group had higher serum levels of free fatty acid (FFA), triglyceride (TG), total cholesterol (TC) and low-density lipoprotein (LDL) whereas a lower level of high density lipoprotein (HDL) relative to the control group (P < 0.05). Importantly, serum levels of TC, TG, LDL and FFA were significantly decreased while that of HDL was remarkably increased in the intervention group as compared to model group (Fig. 9B).

For glycometabolism indices, it was observed that fasting plasma glucose (FPG), fasting insulin (FINS) and homoeostasis model assessment of insulin resistance (HOMA-IR) were significantly higher in the model group compared with control group (P < 0.01). Of note, the intervention group had reduced FPG, FINS and HOMA-IR compared with model group, and significant differences were observed (P < 0.05) (Fig. 9C).