Study on Gardeniae Fructus for treating depression with combination of network pharmacology, metabolomics and gut microbiota

Background Depression is a prevalent and disabling mental disorder with limited therapeutic efficacy and delayed response to conventional antidepressants, highlighting the urgent need for safe and effective alternatives. Gardeniae Fructus (GF), a traditional Chinese medicine with documented neuroprotective properties, has shown rapid antidepressant-like effects, yet its mechanisms remain incompletely understood. Methods Depression-like behaviors were induced by reserpine in adult Sprague–Dawley rats. Thirty-five rats were randomly and evenly divided into five groups: control (CON), Model, low-dose GF (GFL, 1.2 g/kg·d), high-dose GF (GFH, 2.4 g/kg·d), and fluoxetine (FLU, 10 mg/kg·d). Depressive behaviors were assessed by sucrose preference test, forced swimming test, open field test, body temperature, and eyelid ptosis tests. Differential metabolites were identified through serum untargeted metabolomics, and metabolic pathways were analyzed using MetaboAnalyst. The anti-depression targets of GF were determined by network pharmacology. A network pharmacology–metabolomics network was constructed in Cytoscape, and interactions between key components and key targets were verified by molecular docking. Gut microbiota of rats in different groups was analyzed by 16S rDNA sequencing, and multi-omics integration analysis was performed. Results 11 active components of GF and 140 potential targets associated with depression were identified, with quercetin emerging as a key compound. Protein–protein interaction analysis highlighted AKT1, TNF, IL6, VEGFA, and TP53 as core targets. In reserpine-induced depressive rats, GF treatment significantly ameliorated depressive-like behaviors, involving shortened immobility time and enhanced sucrose preference, improved body temperature, and alleviated eyelid ptosis. 16S rRNA sequencing revealed that GF modulated gut microbiota composition, and altering functional pathways including thiamine, butanoate, and fatty acid metabolism. Untargeted metabolomics identified 28 differentially expressed metabolites between GF-treated and model groups, predominantly involving lipids and amino acids. Integrated network and metabolomic analyses pinpointed glycosphingolipid metabolism as a critical pathway, with PTEN as a key target and sphinganine and phytosphingosine as principal metabolites. Molecular docking confirmed stable binding between quercetin and PTEN (binding energy: −7.2 kcal/mol). Correlation analyses demonstrated that Bifidobacterium and Turicibacter exhibited pronounced associations with multiple metabolic alterations. Conclusion This integrative approach reveals that GF alleviates depression through multi-target, multi-pathway mechanisms involving regulation of gut microbiota, modulation of glycosphingolipid metabolism, and targeting of PTEN, providing a comprehensive basis for its neuroprotective effects and offering novel insights into Traditional Chinese Medicine-based antidepressant strategies.