Network pharmacology-based insights into the role of gut microbiota metabolites in insulin resistance
BackgroundExtensive research has demonstrated that the gut microbiota plays a critical role in maintaining homeostasis and promoting overall human health. However, the pharmacological mechanisms and functional roles of gut microbiota metabolites remain insufficiently understood. This study employs a...
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Frontiers Media S.A.
2025-06-01
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| Series: | Frontiers in Microbiology |
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| Online Access: | https://www.frontiersin.org/articles/10.3389/fmicb.2025.1617496/full |
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| author | Bing Xiao Xin Chen Ruiyu Zong Yiming Guan Zhu Zhu Siling Bi |
| author_facet | Bing Xiao Xin Chen Ruiyu Zong Yiming Guan Zhu Zhu Siling Bi |
| author_sort | Bing Xiao |
| collection | DOAJ |
| description | BackgroundExtensive research has demonstrated that the gut microbiota plays a critical role in maintaining homeostasis and promoting overall human health. However, the pharmacological mechanisms and functional roles of gut microbiota metabolites remain insufficiently understood. This study employs a network pharmacology approach to elucidate the metabolic transformation processes of gut microbiota metabolites and their molecular mechanisms in the pathogenesis of insulin resistance (IR), aiming to uncover the complex interactions among gut microbiota, metabolites, and therapeutic targets.MethodsGut microbiota metabolites and their corresponding target genes were retrieved from the gutMGene database. Potential targets of the metabolites were predicted using the SEA and STP databases. Disease-related targets for insulin resistance were collected from the GeneCards, DisGeNET, and OMIM databases. Core targets were identified via a protein–protein interaction (PPI) network, followed by comprehensive GO and KEGG enrichment analyses. Finally, a network illustrating the relationship among microbiota-substrate-metabolite-target was established.ResultsThirteen overlapping targets between the gut microbiota and insulin resistance were identified, among which IL6, JUN, and PPARG were recognized as hub genes. The MSMT (microbiota-substrate-metabolite-target) network revealed that these three hub genes exert therapeutic effects through 10 gut microbiota metabolites, 10 substrates, and 21 microbial species. KEGG pathway analysis indicated that the IL-17, Toll-like receptor, HIF-1, NOD-like receptor, TNF, and VEGF signaling pathways are the primary pathways involved in the pathogenesis of IR.ConclusionGut microbiota metabolites may exert therapeutic effects on insulin resistance primarily through the targets IL6, JUN, and PPARG. The regulatory mechanisms are likely associated with several key signaling pathways, including the IL-17, Toll-like receptor and HIF-1, pathways. These three pathways collectively form an interconnected inflammation-metabolism-hypoxia network. Targeting key nodes within this network—such as the IL-17 receptor, TLR4, or HIF-1α—may offer a multidimensional therapeutic strategy for insulin resistance (IR) and its associated complications. |
| format | Article |
| id | doaj-art-17e329af48fb4e638e8475625058e640 |
| institution | DOAJ |
| issn | 1664-302X |
| language | English |
| publishDate | 2025-06-01 |
| publisher | Frontiers Media S.A. |
| record_format | Article |
| series | Frontiers in Microbiology |
| spelling | doaj-art-17e329af48fb4e638e8475625058e6402025-08-20T03:16:18ZengFrontiers Media S.A.Frontiers in Microbiology1664-302X2025-06-011610.3389/fmicb.2025.16174961617496Network pharmacology-based insights into the role of gut microbiota metabolites in insulin resistanceBing Xiao0Xin Chen1Ruiyu Zong2Yiming Guan3Zhu Zhu4Siling Bi5College of Acupuncture and Massage, Shandong University of Traditional Chinese Medicine, Jinan, ChinaCollege of Acupuncture and Massage, Shandong University of Traditional Chinese Medicine, Jinan, ChinaCollege of Acupuncture and Massage, Shandong University of Traditional Chinese Medicine, Jinan, ChinaCollege of Health Sciences, Shandong University of Traditional Chinese Medicine, Jinan, ChinaCollege of Acupuncture and Massage, Shandong University of Traditional Chinese Medicine, Jinan, ChinaMedical College, Shandong University of Traditional Chinese Medicine, Jinan, ChinaBackgroundExtensive research has demonstrated that the gut microbiota plays a critical role in maintaining homeostasis and promoting overall human health. However, the pharmacological mechanisms and functional roles of gut microbiota metabolites remain insufficiently understood. This study employs a network pharmacology approach to elucidate the metabolic transformation processes of gut microbiota metabolites and their molecular mechanisms in the pathogenesis of insulin resistance (IR), aiming to uncover the complex interactions among gut microbiota, metabolites, and therapeutic targets.MethodsGut microbiota metabolites and their corresponding target genes were retrieved from the gutMGene database. Potential targets of the metabolites were predicted using the SEA and STP databases. Disease-related targets for insulin resistance were collected from the GeneCards, DisGeNET, and OMIM databases. Core targets were identified via a protein–protein interaction (PPI) network, followed by comprehensive GO and KEGG enrichment analyses. Finally, a network illustrating the relationship among microbiota-substrate-metabolite-target was established.ResultsThirteen overlapping targets between the gut microbiota and insulin resistance were identified, among which IL6, JUN, and PPARG were recognized as hub genes. The MSMT (microbiota-substrate-metabolite-target) network revealed that these three hub genes exert therapeutic effects through 10 gut microbiota metabolites, 10 substrates, and 21 microbial species. KEGG pathway analysis indicated that the IL-17, Toll-like receptor, HIF-1, NOD-like receptor, TNF, and VEGF signaling pathways are the primary pathways involved in the pathogenesis of IR.ConclusionGut microbiota metabolites may exert therapeutic effects on insulin resistance primarily through the targets IL6, JUN, and PPARG. The regulatory mechanisms are likely associated with several key signaling pathways, including the IL-17, Toll-like receptor and HIF-1, pathways. These three pathways collectively form an interconnected inflammation-metabolism-hypoxia network. Targeting key nodes within this network—such as the IL-17 receptor, TLR4, or HIF-1α—may offer a multidimensional therapeutic strategy for insulin resistance (IR) and its associated complications.https://www.frontiersin.org/articles/10.3389/fmicb.2025.1617496/fullnetwork pharmacologygut microbiotagut microbiota metabolitesinsulin resistancemolecular mechanism |
| spellingShingle | Bing Xiao Xin Chen Ruiyu Zong Yiming Guan Zhu Zhu Siling Bi Network pharmacology-based insights into the role of gut microbiota metabolites in insulin resistance Frontiers in Microbiology network pharmacology gut microbiota gut microbiota metabolites insulin resistance molecular mechanism |
| title | Network pharmacology-based insights into the role of gut microbiota metabolites in insulin resistance |
| title_full | Network pharmacology-based insights into the role of gut microbiota metabolites in insulin resistance |
| title_fullStr | Network pharmacology-based insights into the role of gut microbiota metabolites in insulin resistance |
| title_full_unstemmed | Network pharmacology-based insights into the role of gut microbiota metabolites in insulin resistance |
| title_short | Network pharmacology-based insights into the role of gut microbiota metabolites in insulin resistance |
| title_sort | network pharmacology based insights into the role of gut microbiota metabolites in insulin resistance |
| topic | network pharmacology gut microbiota gut microbiota metabolites insulin resistance molecular mechanism |
| url | https://www.frontiersin.org/articles/10.3389/fmicb.2025.1617496/full |
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