Elucidating the role of gut microbiota metabolites in diabetes by employing network pharmacology
Abstract Background Extensive research has underscored the criticality of preserving diversity and equilibrium within the gut microbiota for optimal human health. However, the precise mechanisms by which the metabolites and targets of the gut microbiota exert their effects remain largely unexplored....
Saved in:
| Main Authors: | , , , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
BMC
2024-12-01
|
| Series: | Molecular Medicine |
| Subjects: | |
| Online Access: | https://doi.org/10.1186/s10020-024-01033-0 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| _version_ | 1850102831403499520 |
|---|---|
| author | Weiguo Yao Jinlin Huo Jing Ji Kun liu Pengyu Tao |
| author_facet | Weiguo Yao Jinlin Huo Jing Ji Kun liu Pengyu Tao |
| author_sort | Weiguo Yao |
| collection | DOAJ |
| description | Abstract Background Extensive research has underscored the criticality of preserving diversity and equilibrium within the gut microbiota for optimal human health. However, the precise mechanisms by which the metabolites and targets of the gut microbiota exert their effects remain largely unexplored. This study utilizes a network pharmacology methodology to elucidate the intricate interplay between the microbiota, metabolites, and targets in the context of DM, thereby facilitating a more comprehensive comprehension of this multifaceted disease. Methods In this study, we initially extracted metabolite information of gut microbiota metabolites from the gutMGene database. Subsequently, we employed the SEA and STP databases to discern targets that are intricately associated with these metabolites. Furthermore, we leveraged prominent databases such as Genecard, DisGeNET, and OMIM to identify targets related to diabetes. A protein-protein interaction (PPI) network was established to screen core targets. Additionally, we conducted comprehensive GO and KEGG enrichment analyses utilizing the DAVID database. Moreover, a network illustrating the relationship among microbiota-substrate-metabolite-target was established. Results We identified a total of 48 overlapping targets between gut microbiota metabolites and diabetes. Subsequently, we selected IL6, AKT1 and PPARG as core targets for the treatment of diabetes. Through the construction of the MSMT comprehensive network, we discovered that the three core targets exert therapeutic effects on diabetes through interactions with 8 metabolites, 3 substrates, and 5 gut microbiota. Additionally, GO analysis revealed that gut microbiota metabolites primarily regulate oxidative stress, inflammation and cell proliferation. KEGG analysis results indicated that IL-17, PI3K/AKT, HIF-1, and VEGF are the main signaling pathways involved in DM. Conclusion Gut microbiota metabolites primarily exert their therapeutic effects on diabetes through the IL6, AKT1, and PPARG targets. The mechanisms of gut microbiota metabolites regulating DM might involve signaling pathways such as IL-17 pathways, HIF-1 pathways and VEGF pathways. |
| format | Article |
| id | doaj-art-64c7ca7816a244bcb1ea8e38a30ac856 |
| institution | DOAJ |
| issn | 1528-3658 |
| language | English |
| publishDate | 2024-12-01 |
| publisher | BMC |
| record_format | Article |
| series | Molecular Medicine |
| spelling | doaj-art-64c7ca7816a244bcb1ea8e38a30ac8562025-08-20T02:39:40ZengBMCMolecular Medicine1528-36582024-12-0130111210.1186/s10020-024-01033-0Elucidating the role of gut microbiota metabolites in diabetes by employing network pharmacologyWeiguo Yao0Jinlin Huo1Jing Ji2Kun liu3Pengyu Tao4Department of Nephrology, Jinshan District Central Hospital, Shanghai University of Medicine & Health SciencesInstitute of Precision Medicine, The First Affiliated Hospital of Shantou University Medical CollegeDepartment of Emergency, Shanghai Municipal Hospital of Traditional Chinese Medicine, Shanghai University of Traditional Chinese MedicineDepartment of Nephrology, Jinshan District Central Hospital, Shanghai University of Medicine & Health SciencesDepartment of Nephrology, Seventh People’s Hospital, Shanghai University of Traditional Chinese MedicineAbstract Background Extensive research has underscored the criticality of preserving diversity and equilibrium within the gut microbiota for optimal human health. However, the precise mechanisms by which the metabolites and targets of the gut microbiota exert their effects remain largely unexplored. This study utilizes a network pharmacology methodology to elucidate the intricate interplay between the microbiota, metabolites, and targets in the context of DM, thereby facilitating a more comprehensive comprehension of this multifaceted disease. Methods In this study, we initially extracted metabolite information of gut microbiota metabolites from the gutMGene database. Subsequently, we employed the SEA and STP databases to discern targets that are intricately associated with these metabolites. Furthermore, we leveraged prominent databases such as Genecard, DisGeNET, and OMIM to identify targets related to diabetes. A protein-protein interaction (PPI) network was established to screen core targets. Additionally, we conducted comprehensive GO and KEGG enrichment analyses utilizing the DAVID database. Moreover, a network illustrating the relationship among microbiota-substrate-metabolite-target was established. Results We identified a total of 48 overlapping targets between gut microbiota metabolites and diabetes. Subsequently, we selected IL6, AKT1 and PPARG as core targets for the treatment of diabetes. Through the construction of the MSMT comprehensive network, we discovered that the three core targets exert therapeutic effects on diabetes through interactions with 8 metabolites, 3 substrates, and 5 gut microbiota. Additionally, GO analysis revealed that gut microbiota metabolites primarily regulate oxidative stress, inflammation and cell proliferation. KEGG analysis results indicated that IL-17, PI3K/AKT, HIF-1, and VEGF are the main signaling pathways involved in DM. Conclusion Gut microbiota metabolites primarily exert their therapeutic effects on diabetes through the IL6, AKT1, and PPARG targets. The mechanisms of gut microbiota metabolites regulating DM might involve signaling pathways such as IL-17 pathways, HIF-1 pathways and VEGF pathways.https://doi.org/10.1186/s10020-024-01033-0DiabetesGut microbiotaMetabolitesNetwork pharmacologyKidney disease |
| spellingShingle | Weiguo Yao Jinlin Huo Jing Ji Kun liu Pengyu Tao Elucidating the role of gut microbiota metabolites in diabetes by employing network pharmacology Molecular Medicine Diabetes Gut microbiota Metabolites Network pharmacology Kidney disease |
| title | Elucidating the role of gut microbiota metabolites in diabetes by employing network pharmacology |
| title_full | Elucidating the role of gut microbiota metabolites in diabetes by employing network pharmacology |
| title_fullStr | Elucidating the role of gut microbiota metabolites in diabetes by employing network pharmacology |
| title_full_unstemmed | Elucidating the role of gut microbiota metabolites in diabetes by employing network pharmacology |
| title_short | Elucidating the role of gut microbiota metabolites in diabetes by employing network pharmacology |
| title_sort | elucidating the role of gut microbiota metabolites in diabetes by employing network pharmacology |
| topic | Diabetes Gut microbiota Metabolites Network pharmacology Kidney disease |
| url | https://doi.org/10.1186/s10020-024-01033-0 |
| work_keys_str_mv | AT weiguoyao elucidatingtheroleofgutmicrobiotametabolitesindiabetesbyemployingnetworkpharmacology AT jinlinhuo elucidatingtheroleofgutmicrobiotametabolitesindiabetesbyemployingnetworkpharmacology AT jingji elucidatingtheroleofgutmicrobiotametabolitesindiabetesbyemployingnetworkpharmacology AT kunliu elucidatingtheroleofgutmicrobiotametabolitesindiabetesbyemployingnetworkpharmacology AT pengyutao elucidatingtheroleofgutmicrobiotametabolitesindiabetesbyemployingnetworkpharmacology |