Network-based prioritization of sepsis-associated metabolites and in vivo validation of diosmetin in sepsis-associated acute kidney injury

BACKGROUND: Gut microbiota dysbiosis and microbiota-associated metabolites contribute to the development of sepsis and sepsis-related organ dysfunction, however, the key metabolites and host targets remain poorly understood. Diosmetin is a bioactive flavonoid that can be generated from dietary flavonoid glycosides through gut microbiota-mediated biotransformation. This study aimed to identify sepsis-associated microbiota-related candidate metabolites and to perform preliminary in vivo validation of diosmetin in sepsis-associated acute kidney injury (AKI). METHODS AND RESULTS: A network pharmacology framework was used to construct a sepsis-related microbiota-metabolite-target-pathway network. Pharmacodynamic analysis, absorption, distribution, metabolism, excretion, and toxicity (ADMET) evaluation, and molecular docking were performed to prioritize candidate metabolites and assess the potential interaction between diosmetin and AKT1. Diosmetin was evaluated in a cecal ligation and puncture (CLP)-induced mouse model of sepsis-associated AKI. Network analysis predicted 19 core metabolites and 45 sepsis-associated targets, with IL-6, TNF-α, AKT1, TP53, IL-1β, and PPAR-γ as central nodes. The network was enriched in inflammation- and immune-related pathways, particularly the Toll-like receptor, PI3K/AKT, and mitogen-activated protein kinase signaling pathways. ADMET assessments identified 12 metabolites with favorable predicted pharmacokinetic and safety profiles. Molecular docking predicted potential binding between diosmetin and AKT1. In CLP-induced septic mice, diosmetin alleviated renal histopathological injury, reduced serum IL-6, TNF-α and creatinine levels, and was associated with increased PI3K and AKT phosphorylation in kidney tissue compared with untreated CLP mice. CONCLUSIONS: This study identified sepsis-associated microbiota-related candidate metabolites through network-based analysis. In vivo evidence suggested that diosmetin attenuated inflammatory responses in a sepsis-associated AKI model.

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Journal
Molecular Biology Reports
Published
2026-08-21
DOI
https://doi.org/10.1007/s11033-026-12642-9
Primary Topic
Computational Drug Discovery Methods
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article
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article

Network-based prioritization of sepsis-associated metabolites and in vivo validation of diosmetin in sepsis-associated acute kidney injury

Mingliang Ye, Lei Huang, Yinghui Hong, Xi Li
Molecular Biology Reports
Computational Drug Discovery Methods
article

Network-based prioritization of sepsis-associated metabolites and in vivo validation of diosmetin in sepsis-associated acute kidney injury

Mingliang Ye, Lei Huang, Yinghui Hong, Xi Li
article en

Abstract

BACKGROUND: Gut microbiota dysbiosis and microbiota-associated metabolites contribute to the development of sepsis and sepsis-related organ dysfunction, however, the key metabolites and host targets remain poorly understood. Diosmetin is a bioactive flavonoid that can be generated from dietary flavonoid glycosides through gut microbiota-mediated biotransformation. This study aimed to identify sepsis-associated microbiota-related candidate metabolites and to perform preliminary in vivo validation of diosmetin in sepsis-associated acute kidney injury (AKI). METHODS AND RESULTS: A network pharmacology framework was used to construct a sepsis-related microbiota-metabolite-target-pathway network. Pharmacodynamic analysis, absorption, distribution, metabolism, excretion, and toxicity (ADMET) evaluation, and molecular docking were performed to prioritize candidate metabolites and assess the potential interaction between diosmetin and AKT1. Diosmetin was evaluated in a cecal ligation and puncture (CLP)-induced mouse model of sepsis-associated AKI. Network analysis predicted 19 core metabolites and 45 sepsis-associated targets, with IL-6, TNF-α, AKT1, TP53, IL-1β, and PPAR-γ as central nodes. The network was enriched in inflammation- and immune-related pathways, particularly the Toll-like receptor, PI3K/AKT, and mitogen-activated protein kinase signaling pathways. ADMET assessments identified 12 metabolites with favorable predicted pharmacokinetic and safety profiles. Molecular docking predicted potential binding between diosmetin and AKT1. In CLP-induced septic mice, diosmetin alleviated renal histopathological injury, reduced serum IL-6, TNF-α and creatinine levels, and was associated with increased PI3K and AKT phosphorylation in kidney tissue compared with untreated CLP mice. CONCLUSIONS: This study identified sepsis-associated microbiota-related candidate metabolites through network-based analysis. In vivo evidence suggested that diosmetin attenuated inflammatory responses in a sepsis-associated AKI model.

Molecular Biology ReportsVol. 53(1)
Sun Yat-sen University (CN), Peking University Shenzhen Hospital (CN), Sun Yat-sen University Cancer Center (CN), Eighth Affiliated Hospital of Sun Yat-sen University
Good health and well-being
Openalex Percentile: Top 8%
Computational Drug Discovery Methods
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