Examining gut microbiota and metabolites to clarify mechanisms of Dimocarpus longan Lour leaf components against type 2 diabetes

Abstract

Background: Dimocarpus longan Lour leaf components (DLC) contain key active compounds such as quercetin, kaempferol, and quercitrin. They are effective for managing type 2 diabetes mellitus (T2DM), though the exact mechanism by which DLC acts remains unclear.

Aim: To investigate the material basis and mechanism underlying the therapeutic effect of DLC in T2DM.

Methods: T2DM was triggered in rats using a high-sugar, high-fat diet alongside 35 mg/kg streptozotocin. The effect of DLC on the intestinal microbiota in T2DM rats was analyzed via 16S rDNA sequencing. Targeted metabolomics was conducted to evaluate the impact of DLC on the levels of nine short-chain fatty acids (SCFAs). Untargeted metabolomics examined DLC-induced alterations in fecal metabolites and associated metabolic pathways. Additionally, Spearman's correlation analysis assessed gut microbiota and fecal metabolite relationships.

Results: DLC significantly attenuated pathological weight loss, reduced fasting blood glucose levels, restored blood sugar homeostasis, and ameliorated dyslipidemia in T2DM rats. The 16S rDNA sequencing revealed that DLC enhanced microbial diversity and reversed intestinal dysbiosis. Targeted metabolomics indicated decreased acetic acid and propionic acid levels and increased butyric acid, isobutyric acid, and 2-methylbutyric acid levels after DLC treatment. Untargeted metabolomics revealed 57 metabolites with altered expression associated with amino acid, carbohydrate, purine, and biotin pathways. The Spearman analysis demonstrated significant links between specific gut microbiota taxa and fecal metabolites.

Conclusion: DLC may exert hypoglycemic effects by modulating intestinal flora genera, SCFA levels, and fecal metabolites.

Keywords: 16S rDNA sequencing; Dimocarpus longan Lour leaf components; Metabolomics; Short-chain fatty acids; Type 2 diabetes.

Figure 1

Influence of Dimocarpus longan Lour leaf components on type 2 diabetes mellitus rats. A: Experimental protocol for the treatment of type 2 diabetes mellitus (T2DM) rats by Dimocarpus longan Lour leaf components (DLC); B: DLC treatment mitigated weight loss in T2DM rats; C: DLC therapy reduced fasting blood glucose levels in T2DM rats; D and E: The area under the curve of oral glucose tolerance test was lowered in T2DM rats following DLC treatment; F-I: Alterations in blood lipids post-DLC therapy. Results were expressed as mean ± SD (n = 6). ^aP < 0.05 vs the control (Con) group; ^bP < 0.01 vs the Con group; ^dP < 0.01 vs the model group. HDL-C: High-density lipoprotein cholesterol; Con: Control group; Mod: The model group; Met: The metformin group; HDLC: The high-dose group; MDLC: The medium-dose group; LDLC: The low-dose group; AUC: Area under the curve; OGTT: Oral glucose tolerance test. Figure 1A created with BioRender.com (Supplementary material).

Figure 2

Impact of Dimocarpus longan Lour leaf components on gut microbial diversity in type 2 diabetes mellitus rats. A: Venn diagram; B: Observed-amplicon sequence variant index; C: Chao1 index; D: Shannon index; E: Simpson index; F: Bray Curtis-based principal component analysis; G: Bray Curtis-based nonparametric multidimensional scaling. Results were expressed as mean ± SD (n = 6). All variations were assessed via one-way ANOVA with Tukey-Kramer post hoc analysis; multiple comparisons were adjusted using the Benjamini–Hochberg false discovery rate method. Con: Control group; Mod: The model group; Met: The metformin group; HDLC: The high-dose group; ASV: Amplicon sequence variant.

Figure 3

Alterations in the microbial composition at the phylum and genus levels. A: The proportion of intestinal microbiota at the phylum level; B: The proportion of Firmicutes; C: The proportion of Bacteroidetes; D: The proportion of Actinobacteria; E: The proportion of gut microbiota at the genus levels; F: Community heatmap analysis on genus level. Results were expressed as mean ± SD (n = 6). ^bP < 0.01 vs the control group; ^cP < 0.05 vs the model group. Con: Control group; Mod: The model group; Met: The metformin group; HDLC: The high-dose group.

Figure 4

Functional predictive analytics.

Figure 5

Effects of Dimocarpus longan Lour leaf components on short-chain fatty acids in type 2 diabetes mellitus rats. A: Acetic acid; B: Propionic acid; C: Butyric acid; D: Isobutyric acid; E: 2-Methylbutyrate acid; F: Valeric acid; G: Isovaleric acid; H: Hexanoic acid; I: 4-Methylvaleric acid. Results were expressed as mean ± SD (n = 6). ^aP < 0.05 vs the control (Con) group; ^bP < 0.01 vs the Con group; ^cP < 0.05 vs the model (Mod) group; ^dP < 0.01 vs the Mod group. Con: Control group; Mod: The model group; Met: The metformin group; HDLC: The high-dose group.

Figure 6

Multivariate statistical analysis (n = 6). A: Principal component analysis (PCA) score plot (positive ion mode); B: PCA score plot (negative ion mode); C and D: Orthogonal partial least squares - discriminant analysis (OPLS-DA) score plot (positive ion mode); E and F: OPLS-DA score plot (negative ion mode); G and H: OPLS-DA model validation in positive ion mode via permutation test (n = 200); I and J: OPLS-DA model validation in negative ion mode via permutation test (n = 200). R²Y (model interpretability) and Q²Y (predictive power) are critical metrics for OPLS-DA. A robust model is confirmed when R²Y > Q²Y. Con: Control group; Mod: The model group; Met: The metformin group; HDLC: The high-dose group.

Figure 7

Potential marker analysis. A volcano diagram illustrating the distinct metabolite compositions for control group vs model group and model group vs the high-dose group (The X-axis represents the diversity of metabolite variations across groups, while the Y-axis denotes the statistical significance of these variations). Con: Control group; Mod: The model group; Met: The metformin group; HDLC: The high-dose group.

Figure 8

Metabolic pathway analysis of type 2 diabetes mellitus-linked biomarker candidates. a: Arginine biosynthesis; b: Arginine and proline metabolism; c: Histidine metabolism; d: Alanine, aspartic acid, and glutamate metabolism; e: Lysine degradation; f: Purine metabolism; g: Phenylalanine metabolism; h: Biotin metabolism; i: Tricarboxylic acid cycle (citrate cycle).

Figure 9

Correlation analysis of the intestinal flora with untargeted metabolomics. The vertical axis illustrates the varying abundance of gut microbiota. The color coding within the grids reflects the outcomes of the Spearman correlation analysis. Red grids signify positive correlations, where the correlation value exceeds 0.1, whereas blue grids represent negative correlations with values falling below -0.1. The color gradient in the heatmap represents these correlation values, with more intense shades of red or blue indicating stronger correlations.