Elucidating the role of gut microbiota metabolites in diabetes by employing network pharmacology.

IF 6 2区 医学 Q1 BIOCHEMISTRY & MOLECULAR BIOLOGY Molecular Medicine Pub Date : 2024-12-20 DOI:10.1186/s10020-024-01033-0
Weiguo Yao, Jinlin Huo, Jing Ji, Kun Liu, Pengyu Tao
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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.

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利用网络药理学阐明肠道微生物代谢物在糖尿病中的作用。
背景:广泛的研究强调了保持肠道微生物群多样性和平衡对人类最佳健康的重要性。然而,肠道微生物群的代谢物和目标发挥作用的确切机制在很大程度上仍未被探索。本研究利用网络药理学方法来阐明糖尿病背景下微生物群、代谢物和靶点之间复杂的相互作用,从而促进对这种多方面疾病的更全面的理解。方法:在本研究中,我们首先从gutMGene数据库中提取肠道微生物代谢物的代谢物信息。随后,我们使用SEA和STP数据库来识别与这些代谢物复杂相关的靶标。此外,我们利用著名的数据库,如Genecard、DisGeNET和OMIM来确定与糖尿病相关的靶标。建立蛋白相互作用(PPI)网络,筛选核心靶点。此外,我们利用DAVID数据库进行了全面的GO和KEGG富集分析。此外,还建立了微生物群-底物-代谢物-靶点之间的关系网络。结果:我们在肠道菌群代谢物和糖尿病之间共确定了48个重叠靶点。随后,我们选择了IL6、AKT1和PPARG作为治疗糖尿病的核心靶点。通过MSMT综合网络的构建,我们发现三个核心靶点通过与8种代谢物、3种底物和5种肠道菌群的相互作用来发挥对糖尿病的治疗作用。此外,氧化石墨烯分析显示,肠道微生物代谢物主要调节氧化应激、炎症和细胞增殖。KEGG分析结果显示,IL-17、PI3K/AKT、HIF-1和VEGF是dm的主要信号通路。结论:肠道微生物代谢产物主要通过IL6、AKT1和PPARG靶点发挥其对糖尿病的治疗作用。肠道菌群代谢物调节糖尿病的机制可能涉及IL-17、HIF-1、VEGF等信号通路。
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来源期刊
Molecular Medicine
Molecular Medicine 医学-生化与分子生物学
CiteScore
8.60
自引率
0.00%
发文量
137
审稿时长
1 months
期刊介绍: Molecular Medicine is an open access journal that focuses on publishing recent findings related to disease pathogenesis at the molecular or physiological level. These insights can potentially contribute to the development of specific tools for disease diagnosis, treatment, or prevention. The journal considers manuscripts that present material pertinent to the genetic, molecular, or cellular underpinnings of critical physiological or disease processes. Submissions to Molecular Medicine are expected to elucidate the broader implications of the research findings for human disease and medicine in a manner that is accessible to a wide audience.
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