Integration of network pharmacology and intestinal flora to investigate the mechanism of action of Chinese herbal Cichorium intybus formula in attenuating adenine and ethambutol hydrochloride-induced hyperuricemic nephropathy in rats

Abstract

Context: Cichorium intybus L. (Asteraceae) formula (CF) has been applied as a folk medicine to treat hyperuricemic nephropathy (HN). However, the exact mechanism remains unclear.

Objective: To explore the therapeutic effect and mechanism of CF on HN.

Materials and methods: Through network pharmacological methods, the targets of the active component of CF against HN were obtained. Subsequently, Male Wistar rats were divided into control, HN, allopurinol (50 mg/kg), CF high-dose (8.64 g/kg) and CF low-dose (2.16 g/kg) groups. The HN model was induced via intragastric administration of adenine (100 mg/kg) and ethambutol hydrochloride (250 mg/kg) for 3 weeks. After CF treatment, biochemical indicators including UA, UREA and CREA were measured. Then, HE staining, qRT-PCR and gut microbiota analysis were conducted to further explore the mechanism.

Results: The network pharmacology identified 83 key targets, 6 core genes and 200 signalling pathways involved in the treatment of HN. Compared to the HN group, CF (8.64 g/kg) significantly reduced the levels of UA, UREA and CREA (from 2.4 to 1.57 μMol/L, from 15.87 to 11.05 mMol/L and from 64.83 to 54.83 μMol/L, respectively), and mitigated renal damage. Furthermore, CF inhibited the expression of IL-6, TP53, TNF and JUN. It also altered the composition of gut microbiota, and ameliorated HN by increasing the relative abundance of some probiotics.

Conclusions: This work elucidated the therapeutic effect and underlying mechanism by which CF protects against HN from the view of the biodiversity of the intestinal flora, thus providing a scientific basis for the usage of CF.

Keywords: gut microorganisms; molecular docking; nephroprotective effect; traditional Chinese medicine formula.

Figure 1.

Effect of CF on serological changes and histopathological changes of renal tissue in HN rats. (A)Processing of the whole experiment. (B) Food intake of rats. (C) Body weight changes of rats. (D–F) Effects of CF on the level of UA, UREA and CREA. (G–P) HE staining result of kidney tissue in each group. Data are presented as mean ± SD (n = 6). G, I, K, M and O tissues were observed under an upright optical microscope (×10.0); H, J, L, N and P tissues were observed under an upright optical microscope (×40.0). *p < 0.05; **p < 0.01; ***p < 0.001, compared with the CG. ^#p < 0.05, compared with the HNG. The black arrows point to the renal tubules and their epithelial cell lesions.

Figure 2.

The major chemical components of CF. (A) UPLC/Q-TOF MS total ion chromatogram of CF in positive ion mode. (B) UPLC/Q-TOF MS total ion chromatogram of CF in negative ion mode. 1, Shanzhiside (Zhang et al. 2018); 2, Chlorogenic acid (Wang et al. 2015); 3, Cryptochlorogenic acid (Wang et al. 2015); 4, Isochlorogenic acid B (Tian et al. 2020); 5, Isochlorogenic acid A (Tian et al. 2020); 6, Isochlorogenic acid C (Tian et al. 2020); 7, Genipin 1-gentiobioside (Li et al. 2016); 8, Capparoside A (Luecha et al. 2009); 9, Puerarin 6″-O-xyloside (Yu et al. 2012); 10, Daidzin (Gaya et al. 2016).

Figure 3.

Network pharmacology-based analysis. (A) The Venn diagram of CF-HUA. (B) The protein–protein interaction (PPI) network of CF in the treatment of HUA. (C) Top 30 key targets of CF for HUA. (D) The drug-potential active ingredient-target network. (E) Gene Ontology (GO) function analysis of common targets. (F) Kyoto Encyclopaedia of Genes and Genomes (KEGG) pathway enrichment analysis of common targets.

Figure 4.

Molecular docking diagram and visualisation of the major active ingredients of CF and the core targets.

Figure 5.

Effect of CF on the mRNA expression of IL-6, TP53, TNF, VEGFA, CASP3 and JUN. (A) The relative mRNA expression of IL-6. (B) The relative mRNA expression of TP53. (C) The relative mRNA expression of TNF. (D) The relative mRNA expression of VEGFA. (E) The relative mRNA expression of CASP3. (F) The relative mRNA expression of JUN. Data were presented as mean ± SD (n = 6). *p < 0.05; **p < 0.01; ***p < 0.001, compared with the CG. ^#p < 0.05; ^##p < 0.05, compared with the HNG.

Figure 6.

(A) Phylogenetic tree of high abundance OUT. (B) Venn diagram analysis of differences in OTU distribution in each group.

Figure 7.

The Alpha diversity analysis. (A–D) The Chao1, PD, Simpson and Shannon index of each group. (E) The Rarefaction Curve of each sample. (F) OTU Rank abundance curves of each group. *p < 0.05; **p < 0.01; ***p < 0.001.

Figure 8.

β-Diversity analysis. (A) The OUT-based Principal Component Analysis (PCA). (B) Non-metric Multi-Dimensional Scaling (NMDS) based on Jaccard distance. (C) Principal Co-ordinates Analysis (PCoA) based on Bray-Curtis distance. (D) PCoA based on Bray-Curtis distance with ellipses. (E) Clustering Dendrogram based on Unweighted UniFrac distance. Confidence ellipses represented the 95% confidence interval of each group.

Figure 9.

Analysis of differences in the composition of intestinal flora. (A) Barplot of top 10 relative abundance at the phylum level. (B-C) The relative abundance of Firmicutes and Bacteroides in each group, the data were subjected by one-way ANOVA. Data are presented as mean ± SD (n = 6). (D) Barplot of top 10 relative abundance at the genus level. (E-F) The relative abundance of Ruminococcaceae UCG-014 and Bifidobacterium in each group, the data were subjected by one-way ANOVA. Data are presented as mean ± SD (n = 6). (G-I) Barplot of top 10 relative abundance at class, order and family level. *p < 0.05; **p < 0.01; ***p < 0.001. Others represent the sum of the relative abundance of all species other than 10 and species without annotation information.

Figure 10.

The result of LEfse analysis and functional enrichment of the ko metabolic pathway at 3 different levels. (A) LDA score of Lefse. (B) Cladogram of Lefse. (C) ko analysis of level 1. (D) ko analysis of level 2. (E) ko analysis of level 3.