Integrating network pharmacology and multi-omics in a systems approach: a mechanism study of Jinhong tablets against chronic superficial gastritis

Abstract

Background: Chronic gastritis (CG) significantly impacts patients' quality of life and can progress to more severe gastric conditions. In China, Traditional Chinese Medicine (TCM) has been widely applied for its holistic efficacy in treating chronic superficial gastritis (CSG), including formulas like Jinhong Tablets (JHT), known for their anti-inflammatory effects. However, the mechanism of action of JHT in treating CSG still requires further clarification.

Purpose: This study aimed to elucidate the mechanism by which JHT alleviates CSG, integrating network pharmacology, untargeted metabolomics, and gut microbiota analyses.

Methods: The CSG rat model was established, and treatment effects were assessed via Hematoxylin and eosin (H&E) staining. The target profiles of JHT's components and the holistic targets of JHT were obtained. Enrichment analyses were performed on holistic targets and a multi-layer biomolecular network of JHT was established. The study also analyzed rat plasma for differential metabolites through untargeted metabolomics and evaluated the diversity and composition of gut microbiota in fecal and cecal contents samples using 16S rRNA sequencing.

Results: JHT effectively reduced gastric inflammation in CSG rats. Network pharmacology indicated that diverse metabolic processes including lipid metabolism and nitric oxide metabolism play pivotal roles in the therapeutic effects of JHT on CSG. Metabolomics analysis identified differential metabolites, including betaine, which help enrich the gut microbiota. Phospholipids and citrulline indicate the severity of CSG. The pathway enrichment of differential metabolites confirmed the network pharmacology results and indicated the association with the gut microbiota. Through gut microbiota analyses, it was discovered that JHT could augment the gut microbiota by enhancing the abundance of betaine. Additionally, JHT was shown to boost the production of short-chain fatty acids (SCFAs) by increasing the abundances of Faecalibaculum and Bifidobacterium, consequently alleviating gastric inflammation in CSG.

Conclusion: Our study revealed that JHT alleviated CSG through diverse metabolic processes including lipid and energy metabolism. Metabolites such as betaine, along with gut microbiota including Faecalibaculum and Bifidobacterium, play crucial roles in the therapeutic interventions. Our findings support the therapeutic potential of JHT and contribute to a deeper understanding of the role of TCM in the treatment of CSG.

Keywords: Chronic superficial gastritis; Gut microbiota; Jinhong tablets; Network pharmacology; Untargeted metabolomics.

Fig. 1

Target prediction, validation and comparison among different compounds set in JHT. A Target prediction accuracy of major compounds in JHT. B Proportion of seven chemical components types in JHT. C Hierarchical clustering of JHT compounds. D Upset plot for holistic targets sets of four herbs in JHT

Fig. 2

JHT improves the inflammation in gastric tissues of CSG rats. A Experimental design and schedule in treatment of CSG using JHT. B Representative photomicrographs among four groups (Magnification 100×, Scale bar = 250 μm). C Statistical tests for inflammation scores of gastric tissues in different groups, with mean and standard deviation above the bars. *p < 0.05, **p < 0.01 and ***p < 0.001 as compared between two groups

Fig. 3

Network pharmacology analysis of JHT in modules of CSG. A Multi-layer biomolecular network representing the mechanism of action of JHT in the treatment of CSG. SGJY Shugan Jieyu, LQHX Liqi Huoxie, HWZT Hewei Zhitong. B Enrichment plot of GO biological processes in metabolism of JHT in the treatment of CSG

Fig. 4

Comprehensive metabolomics and pathway enrichment analysis of JHT’s therapeutic effects in CSG. A PCA Plot showing the distribution of samples from each group on the two main components. B Heatmap demonstrating the standardized abundance of differential metabolites between groups. C Volcano plots revealing the standardized abundance of 5 key differentially expressed metabolites varied between different groups. Not significant (NS), *p < 0.05, **p < 0.01 and ***p < 0.001 as compared between two groups. D Boxplots displaying the upregulation and downregulation of metabolites between two groups. E Pathway enrichment analysis representing 25 significantly enriched metabolic pathways after JHT treatment for CSG, sorted by enrichment ratio

Fig. 5

Diversity analysis of gut microbiota in rat fecal samples across experimental groups. A PLS-DA plot showing the distribution of samples at the OTU level along the two main components. B Venn diagram depicting the number of shared and unique OTUs among the experimental groups. C Community barplot showing the relative abundance of microbial communities at the phylum level across different groups. D Genus-level heatmap illustrating the relative abundance of microbial genera across groups. E Kruskal–Wallis H Test Bar Plot showing significant differences in microbial taxa among groups, with distinct taxa enriched in specific groups. *p < 0.05, **p < 0.01. F Cladogram representing the phylogenetic relationships of microbial taxa, with nodes and branches color-coded to indicate group-specific enrichment

Fig. 6

Diversity analysis of gut microbiota in rat cecal content samples across experimental groups. A PLS-DA plot depicting the distribution of samples at the OTU level along the two main components. B Venn diagram showing the number of OTU intersection and difference across different groups. C Community barplot displaying the relative abundance of microbial communities at the phylum level among the experimental groups. D Genus-level heatmap illustrating the relative abundance of microbial genera among groups. E Kruskal–Wallis H test barplot demonstrating significant differences in microbial abundance across different groups. *p < 0.05, **p < 0.01, ***p < 0.01. F Cladogram showing the significant enrichment of microbial communities between different groups, with different colors representing bacterial communities in different groups

Fig. 7

Mechanistic insights into JHT’s therapeutic effects on CSG rats via gut microbiota and metabolite regulation