Metabolomics combined with metagenomics analysis reveals the potential mechanism of Zhejiang psyllium polysaccharides against hyperuricemia in rats

Abstract

This study aimed to assess the anti-hyperuricemia efficacy of Zhejiang psyllium polysaccharides (ZPP) in rats and to explore its underlying mechanism. Hyperuricemia was induced by intragastric administration of potassium oxonate, hypoxanthine, and adenine. The serum levels of uric acid (UA), creatinine (Cr), and blood urea nitrogen (BUN) were measured, and kidney pathology was examined. Serum metabolomics was employed to monitor metabolic alterations following ZPP intervention. Metagenomic analysis was conducted to investigate the impact of ZPP on the intestinal flora of hyperuricemia rats. The results showed that ZPP could significantly reduce the serum UA level in hyperuricemia rats and exhibited a certain renal protective effect. The metabolomics results indicated that ZPP regulates uric acid levels in rats with hyperuricemia and ameliorates renal pathological changes by modulating biomarkers associated with purine metabolism, amino acid metabolism, and lipid metabolism. Metagenomic research also found that ZPP could increase the relative abundance of uric acid metabolism-related probiotics, such as Limosilactobacillus reuteri and Lactobacillus murinus, thereby improving intestinal flora imbalance in rats with hyperuricemia.

Keywords: Hyperuricemia; Metabolomics; Metagenomics; Polysaccharide; Zhejiang psyllium.

Fig. 1

Effect of ZPP on Serum (A) UA level, (B) Cr level, (C) BUN level. All values are mean ± standard deviation(n = 8). ^#p < 0.05 and ^##p < 0.01 compared with the Control group. *p < 0.05 and **p < 0.01 compared with the hyperuricemia group.

Fig. 2

Representative H&E stained sections of rat kidney. Scale bar = 100 μm, original magnification 200 ×.

Fig. 3

Metabolomics analyses of serum samples. (A, B) PLS-DA score plots of the three groups from the CON, the HUA, and the ZPP group in positive mode and negative mode. (C, D) Permutation test from the model and the drug-treated group in positive mode and negative mode. (E, F) VIP plots for PLS-DA models in positive mode and negative mode. The red dot means VIP > 1.0.

Fig. 4

Hierarchical clustering heat map of the 23 differential metabolites, with the degree of change marked in red (up-regulation) and blue (down-regulation).

Fig. 5

Pathway analysis (A) and enrichment analysis (B) of potential biomarkers affected by ZPP.

Fig. 6

Metagenomics reveals differences in microbial (A) phylum-level and (B) species-level composition in hyperuricemia rats after ZPP intervention. (C) PcoA analysis of each group.

Fig. 7

(A) Cladogram of the CON, HUA, and ZPP groups. (B) LDA value distribution histogram (LDA > 3.5). (C) Circos of species and functional contribution analysis.

Fig. 7

(A) Cladogram of the CON, HUA, and ZPP groups. (B) LDA value distribution histogram (LDA > 3.5). (C) Circos of species and functional contribution analysis.