Crude Polysaccharide Extracted From Moringa oleifera Leaves Prevents Obesity in Association With Modulating Gut Microbiota in High-Fat Diet-Fed Mice

Abstract

Moringa oleifera is a commonly used plant with high nutritional and medicinal values. M. oleifera leaves are considered a new food resource in China. However, the biological activities of M. oleifera polysaccharides (MOP) in regulating gut microbiota and alleviating obesity remain obscure. In the present study, we prepared the MOP and evaluated its effects on obesity and gut microbiota in high-fat diet (HFD)-induced C57BL/6J mice. The experimental mice were supplemented with a normal chow diet (NCD group), a high-fat diet (HFD group), and HFD along with MOP at a different dose of 100, 200, and 400 mg/kg/d, respectively. Physiological, histological, biochemical parameters, genes related to lipid metabolism, and gut microbiota composition were compared among five experimental groups. The results showed that MOP supplementation effectively prevented weight gain and lipid accumulation induced by HFD, ameliorated blood lipid levels and insulin resistance, alleviated the secretion of pro-inflammatory cytokines, and regulated the expression of genes related to lipid metabolism and bile acid metabolism. In addition, MOP positively reshaped the gut microbiota composition, significantly increasing the abundance of Bacteroides, norank_f_Ruminococcaceae, and Oscillibacter, while decreasing the relative abundance of Blautia, Alistipes, and Tyzzerella, which are closely associated with obesity. These results demonstrated that MOP supplementation has a protective effect against HFD-induced obesity in mice, which was associated with reshaping the gut microbiota. To the best of our knowledge, this is the first report on the potential of MOP to prevent obesity and modulating gut microbiota, which suggests that MOP can be used as a potential prebiotic.

Keywords: Moringa oleifera leaves; gut microbiota; high-fat diet; obesity; polysaccharide.

Figure 1

MOP reduces body weight in HFD-fed mice. (A) The change in body weight of the mice during the experiment (n = 8 mice/group); (B) body weight gain (n = 8); (C) daily food intake (n = 3 cages/group); (D) caloric intake (n = 3); (E) food efficiency ratio (EFR), food efficiency ratio (%) = total body weight gain/total food intake × 100 (n = 8); (F) Lee's index, Lee's index = body weight (g)∧(1/3) × 1,000/body length (cm) (n = 8). Data are shown as means ± SEM. Bars marked with different superscript letters (a–c) indicate significant differences at p < 0.05 based on one-way ANOVA with Duncan's post-hoc test.

Figure 2

Preventive effects of MOP on fat accumulation in HFD-fed mice (n = 8 mice/group). (A) Perirenal fat weight, (B) Mesenteric fat weight, (C) Histological examination of perirenal fat by H & E staining, scale bar = 100 μm, (D) Adipocyte size was monitored in mesenteric fat tissue, (E) Liver index, (F) Representative liver histology by H & E staining, scale bar = 50 μm. Data are shown as means ± SEM. Bars marked with different superscript letters (a–c) indicate significant differences at p < 0.05 based on one-way ANOVA with Duncan's post-hoc test.

Figure 3

MOP ameliorates blood lipid levels and insulin resistance in HFD-fed mice (n = 8 mice/group). Serum levels of (A) total cholesterol (T-CHO), (B) triglycerides (TG), (C) high-density lipoprotein cholesterol (HDL-C), (D) low-density lipoprotein cholesterol (LDL-C), (E) Fasting blood glucose, (F) fasting serum insulin, (G) homeostasis model assessment of insulin resistance (HOMA-IR) index. Data are shown as means ± SEM. Bars marked with different superscript letters (a-c) indicate significant differences at p < 0.05 based on one-way ANOVA with Duncan's post-hoc test.

Figure 4

MOP alleviates the production of pro-inflammatory cytokines in HFD-fed mice. (A) Serum protein levels of TNF-α and IL-1β were determined by ELISA (n = 8 mice/group); (B) Relative mRNA expression levels of TNF-α, IL-1β, IL-6, and monocyte chemotactic protein-1 (MCP-1) in the liver as determined by qRT-PCR (n = 6). Bars marked with different superscript letters (a-d) indicate significant differences at p < 0.05 based on one-way ANOVA with Duncan's post-hoc test.

Figure 5

MOP regulates the mRNA expression levels of genes involved in lipid metabolism and bile acid synthesis in the liver. (A) Relative mRNA expression levels of genes involved in lipid synthesis; (B) Relative mRNA expression levels of genes involved in bile acids metabolism. The data are expressed as means ± SEM (n = 6). Bars marked with different superscript letters (a-c) indicate significant differences at p < 0.05 based on one-way ANOVA with Duncan's post-hoc test.

Figure 6

MOP alters the diversity and composition of the gut microbiota in HFD-fed mice (n = 8 mice/group). (A–D) Sobs index, Chao index, ACE index, and Shannon index, respectively; (E) Venn diagrams that illustrated the observed overlap of OTUs; (F) Heatmap of top 50 OTUs; (G) Hierarchical clustering dendrograms of all samples based on unweighted UniFrac distance; (H) PCoA plot of unweighted UniFrac distance; (I) Analysis of similarity (ANOSIM) using bray-curtis distance at OTU level. The data are expressed as mean ± SD. Bars marked with different superscript letters (a-c) indicate significant differences at p < 0.05 based on one-way ANOVA with Duncan's post-hoc test.

Figure 7

MOP affects the relative abundance of gut microbiota at the phylum and family level in HFD-fed mice (n = 8 mice/group). Bacterial taxonomic profiling at the phylum (A) and family (B) levels from different experimental groups. The relative abundance of Firmicutes (C) and Bacteroidetes (D); (E) The Firmicutes to Bacteroidetes (F/B) ratio in different groups; (F) Comparisons of relative abundance of the bacterial genera. The LEfSe analysis of the gut microbiota differed between NCD and HFD groups (G), and between HFD and HFD+MOP 400 groups (H). The histogram showed the lineages with LDA values of 3.0 or higher as determined by LEfSe.

Figure 8

Two-factor correlation network analysis showing correlations between specific gut microbiota and obesity-related biomarkers (n = 8 mice/group). (A) Correlations between gut bacteria and weight parameters, including body weight, mesenteric fat, perirenal fat, and liver weight. (B) Correlation between gut bacteria and blood lipid profile of TG, T-CHO, LDL-C, and HDL-C in serum. (C) Correlations between gut bacteria and glucose hemostasis, including fasting blood glucose, insulin, and the HOMA-IR index. (D) Correlations between gut bacteria and pro-inflammatory cytokines including TNF-α and IL-1β in serum. Spearman's r coefficient, |r| of ≥ 0.5, p < 0.05. Red lines represent r ≥ 0.5, and green lines represent r ≤ −0.5.