Research on the mechanism of Guanyu Zhixie Granule in intervening gastric ulcers in rats based on network pharmacology and multi-omics

Abstract

Objective: Guanyu Zhixie Granule (GYZXG) is a traditional Chinese medicine compound with definite efficacy in intervening in gastric ulcers (GUs). However, the effect mechanisms on GU are still unclear. This study aimed to explore its mechanism against GU based on amalgamated strategies.

Methods: The comprehensive chemical characterization of the active compounds of GYZXG was conducted using UHPLC-Q/TOF-MS. Based on these results, key targets and action mechanisms were predicted through network pharmacology. GU was then induced in rats using anhydrous ethanol (1 mL/200 g). The intervention effects of GYZXG on GU were evaluated by measuring the inhibition rate of GU, conducting HE staining, and assessing the levels of IL-6, TNF-α, IL-10, IL-4, Pepsin (PP), and epidermal growth factor (EGF). Real-time quantitative PCR (RT-qPCR) was used to verify the mRNA levels of key targets and pathways. Metabolomics, combined with 16S rRNA sequencing, was used to investigate and confirm the action mechanism of GYZXG on GU. The correlation analysis between differential gut microbiota and differential metabolites was conducted using the spearman method.

Results: For the first time, the results showed that nine active ingredients and sixteen targets were confirmed to intervene in GU when using GYZXG. Compared with the model group, GYZXG was found to increase the ulcer inhibition rate in the GYZXG-M group (p < 0.05), reduce the levels of IL-6, TNF-α, PP in gastric tissue, and increase the levels of IL-10, IL-4, and EGF. GYZXG could intervene in GU by regulating serum metabolites such as Glycocholic acid, Epinephrine, Ascorbic acid, and Linoleic acid, and by influencing bile secretion, the HIF-1 signaling pathway, and adipocyte catabolism. Additionally, GYZXG could intervene in GU by altering the gut microbiota diversity and modulating the relative abundance of Bacteroidetes, Bacteroides, Verrucomicrobia, Akkermansia, and Ruminococcus. The differential gut microbiota was strongly associated with serum differential metabolites. KEGG enrichment analysis indicated a significant role of the HIF-1 signaling pathway in GYZXG's intervention on GU. The changes in metabolites within metabolic pathways and the alterations in RELA, HIF1A, and EGF mRNA levels in RT-qPCR experiments provide further confirmation of this result.

Conclusion: GYZXG can intervene in GU induced by anhydrous ethanol in rats by regulating gut microbiota and metabolic disorders, providing a theoretical basis for its use in GU intervention.

Keywords: 16S rRNA; Guanyu Zhixie Granules; drug interaction; gastric ulcer; network pharmacology; untargeted metabolomics.

Figure 1

The workflow of this study.

Figure 2

(A,B) UHPLC-Q/TOF-MS total ion diagram of Guanyu Zhixie Granules. (C–K) Qualitative analysis of 9 active compounds.

Figure 3

(A) Volcano map of differential gene expression. Upregulated genes are indicated in red, downregulated genes are indicated in green, and black represents genes with no significant changes. (B) Gene heat map. Upregulated genes are indicated in red (logFC >0) in the genome, downregulated genes are indicated in green (logFC <0) in the genome, and black represents genes that do not have significant differences. The first 6 samples came from the control group, and the last 14 samples came from the disease group. (C) Venn diagram of the intersection gene of GU. (D) Venn diagram of GYZXG-related targets and GU-related targets. (E) Topological analysis of the PPI network. (E1) Interactive PPI network of GYZXG-related targets and GU-related targets. (E2) PPI network of significant proteins extracted from E1. (E3) PPI network of candidate GYZXG targets for GU treatment extracted from E2. (F) GO biological function enrichment of GYZXG in the treatment of GU. (G) KEGG signaling pathway enrichment of GYZXG in the treatment of GU.

Figure 4

(A) Compound-target network of GYZXG in intervening GU. Light blue, green, light red, dark blue and dark red circles represent the compounds from Gancao, Kudoucao, Laoguancao, Xiaohuixiang and Diyu; circle nodes of more than two colors are multiple drug compounds; and cyan squares represent targets. (B) The target signal pathway network is represented by red inverted triangle nodes representing the path and orange square nodes representing the target. (C) Molecular docking binding energy heatmap. (D) Docking patterns of key targets and specific active compounds.

Figure 5

(A) GYZXG intervention against anhydrous ethanol-induced GU model in rats. Appearance of the ethanol-induced gastric mucosa in rats: (B1) Normal control group; (B2) Model group; (B3) GYZXG medium-dose group. Effect of GYZXG on the microscopic appearance of the ethanol-induced gastric mucosa in rats (HE staining, ×200 and ×400): (C1,C2) Normal control group; (C3,C4) Model group; (C5,C6) GYZXG medium dose group. (D) Body weight changes in rats during the experimental period. (E) GU inhibition rate. (F1–F6) Changes in the levels of IL-10, IL-4, IL-6, TNF-α, EGF, and PP in the serum of rats.

Figure 6

mRNA levels of (A) Rela, (B) Hif1a in rat gastric tissue (n = 5). The values are the means ± SEMs. ^#p < 0.05, ^##p < 0.01 vs. the control group; ^*p < 0.05, ^**p < 0.01 vs. the model group.

Figure 7

Metabolites of GYZXG protection and treatment against GU rats analyzed by untargeted metabolic profiling. (A1,A2) Total ion diagram in positive and negative ion modes. (B1,B2) Principal compound analysis score chart. (C1,C2) OPLS-DA scoring chart. (D1,D2) Metabolite volcano map. (E) Venn plot of differential metabolites. (F1–F6) Changes in differential metabolites. ^*p < 0.05, ^**p < 0.01, ^***p < 0.001.

Figure 8

(A) Heat map of 47 differential metabolites. (B1,B2) Analysis of differential metabolite metabolism pathways in GU rats. (C) The main mechanism of action of GYZXG on GU rats.

Figure 9

Results of the diversity analysis of gut microbial communities in the three groups. (A) OTU-based Venn diagram for three groups. (B) Sparse curve. (C) Score plot of PCA analysis of gut microbiota. (D1–D4) Box plots of intergroup differences in Alpha diversity. (E1,E2) Gut microbial community abundance at phylum and genus level.

Figure 10

(A1–A4,B1,B2) Effect of GYZXG on the relative abundance of gut microbiota at genus and phylum level. (C) LEfSe analysis of gut microbiota. ^*p < 0.05, ^**p < 0.01, ^***p < 0.001.

Figure 11

(A1,A2,B1,B2) Phylum and genus level principal compound analysis score chart. (C1,C2,D1,D2) Correlation coefficients between phylum level and genus level and serum metabolic phenotypes.