Yan Liu, Shurong Liu, Chunyan Zhang, Lihua Pei, Jingyi Wu
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引用次数: 0
Abstract
Endometriosis is an estrogen-dependent disorder characterized by chronic inflammation, immune dysregulation, and altered hormone metabolism. Although gut microbiota-derived metabolites have been implicated in shaping immune microenvironments and lesion development, the underlying regulatory mechanisms remain incompletely understood. Here, we integrated multi-omics, protein-protein interaction (PPI), SHapley Additive exPlanations (SHAP), and single-cell transcriptomics to identify core targets and delineate their interactions with microbiota-derived metabolites, followed by molecular simulations to evaluate metabolite-target binding stability. In this study, we identified 61 differentially expressed genes (DEGs) associated with microbial metabolites. Among these, MET and SELL emerged as key hub genes, with MET showing a potentially protective association and SELL exhibiting a modest positive association with endometriosis risk. Specific gut microbes, including Bacteroides, Parabacteroides, and Bifidobacterium, along with metabolites such as palmitoylethanolamide and dihydroresveratrol, were implicated in modulating immune and inflammatory pathways relevant to lesion formation. Additionally, cell-cell communication analysis indicated that the 61 DEGs were enriched in the Macrophage migration inhibitory factor (MIF) and C-X-C motif chemokine ligand family (CXCL) signaling pathways, suggesting their potential importance in the endometriotic microenvironment. Computational simulations further indicated potential binding interactions between multiple metabolites and MET and SELL. These findings delineate a multi-layered regulatory framework linking gut microbiota, metabolites, molecular targets, and immune interactions, thereby providing a foundation for mechanistic studies and targeted therapeutic strategies.
期刊介绍:
Open Life Sciences (previously Central European Journal of Biology) is a fast growing peer-reviewed journal, devoted to scholarly research in all areas of life sciences, such as molecular biology, plant science, biotechnology, cell biology, biochemistry, biophysics, microbiology and virology, ecology, differentiation and development, genetics and many others. Open Life Sciences assures top quality of published data through critical peer review and editorial involvement throughout the whole publication process. Thanks to the Open Access model of publishing, it also offers unrestricted access to published articles for all users.