Exploring the Prevention of Lipid Deposition Caused by High-Fat Diet and Its Mechanism of Action of Rosa roxburghii Fermented Juice Based on Liver Metabolomics and Gut Microbiota

Abstract

Hyperlipidemia has become a prevalent disease in the global epidemic, posing a threat to human health. This study aims to investigate the mechanism by which Rosa roxburghii fermented juice (RRFJ) can prevent lipid deposition induced by a high-fat diet in mice. The results showed that mice in the RRFJ intervention group had significantly reduced body weight as well as lower levels of serum and liver lipid indicators compared to the high-fat diet group. Metagenomic analysis revealed that the RRFJ intervention reversed the decrease in intestinal flora Alistipes and Colidextribacter genes in mice fed a high-fat diet. Liver metabolomics showed that the RRFJ prevented liver dyslipidemia by modulating the biosynthesis of phenylalanine, tyrosine, tryptophan, and phenylalanine metabolism. RRFJ is effective in preventing dyslipidemia through the 'gut-liver axis', which regulates the imbalance of intestinal flora and improves hepatic metabolic profiles. This provides a new intervention strategy for the prevention and treatment of hyperlipidemia.

Keywords: Rosa roxburghii fermented juice; gut microbiota; lipid deposition; liver metabolism.

FIGURE 1

Experimental design diagram.

FIGURE 2

Changes in weekly body weight of mice during the feeding period (a). Mouse organ index (b). Serum TG (c) levels. Serum TC (d) levels. Serum LDL‐C (e) levels. *p < 0.05, **p < 0.01, ***p < 0.001 versus the HFD group. #p < 0.05, ##p < 0.01, ###p < 0.001 versus the Normal group.

FIGURE 3

Liver lipid metabolism level: TG (a), TC (b), LDL‐C (c). Liver oxidative stress levels: GSH (d), MDA (e). Liver inflammatory factor levels: TNF‐α (f), IL‐6 (g). Note: N = 6, mean ± SEM. *p < 0.05, **p < 0.01, ***p < 0.001 versus the HFD group. ##p < 0.01, ### p < 0.001 versus the normal group.

FIGURE 4

(A) Liver section H&E staining (100×). (B) Liver slices stained with oil red O (400×).

FIGURE 5

Composition of gut microbiota. (a) The alpha diversity of simplicity index. (b) The alpha diversity of Shannon index. (c) The alpha diversity of observed otus index. (d) The relative abundance of 3D PCA. (e) The relative abundance at the phylum level. (f) Relative abundance at the genus level of microorganisms. (g) The abundance of Alistipes genus. (h) The abundance of Colidextribacter genus. (i) LDA value distribution bar chart based on genus level. (j–m) Statistical chart of significant differences in species Metastats between groups based on genus level: Alistipes genus (j), Bifidobacterium genus (k), Colidextribacter genus (l), Faecalibacterium genus (m). (n) Using Spearman correlation analysis, the correlation between 12 gut microbiota and 10 physiological parameters in HFD versus YLM, with red representing upregulation and purple representing downregulation. *p < 0.05, **p < 0.01, ***p < 0.001. #p < 0.05, ##p < 0.01, ###p < 0.001.

FIGURE 6

Liver metabolome. PCA diagram of normal versus HFD versus YLM (a). Heat map of differentially expressed metabolites in liver metabolites (b). Pathway enrichment of differentially expressed metabolites in liver and liver metabolites (c). Heat map (d) the correlation analysis between differentially expressed metabolites in liver metabolites and physiological indicators such as blood lipids, with red representing upregulation and purple representing downregulation *p < 0.05, **p < 0.01, ***p < 0.001.

FIGURE 7

Using Spearman correlation analysis, 37 liver differential metabolites and 12 gut microbiotas were correlated in HFD versus YLM, with red representing upregulation and purple representing downregulation. *p < 0.05, **p < 0.01, ***p < 0.001.

FIGURE 8

Schematic representation of the mechanism of RRFJ in preventing HFD‐induced dyslipidemia in mice. (By Figdraw).