Integrated spatially resolved metabolomics and network toxicology to investigate the hepatotoxicity mechanisms of component D of Polygonum multiflorum Thunb. (15th November 2022)

• Record Type: Journal Article
• Authors: Jiang, Hai-Yan; Gao, Hui-Yu; Li, Jie; Zhou, Tian-Yu; Wang, Shu-Ting; Yang, Jian-Bo; Hao, Rui-Rui; Pang, Fei; Wei, Feng; Liu, Zhi-Gang; Kuang, Lian; Ma, Shuang-Cheng; He, Jiu-Ming; Jin, Hong-Tao
• Is Part Of: Journal of ethnopharmacology. Volume 298(2022)
• Publication Date: 2022-11-15
• Subjects: Polygonum multiflorum Thunb -- Spatially resolved metabolomics -- Hepatotoxicity -- Network toxicology -- Mass spectrometry imaging; Ethnopharmacology -- Periodicals; Pharmacognosy -- Periodicals; Herbs -- Periodicals; Herbs -- Periodicals; Pharmacognosy -- Periodicals; Pharmacognosie -- Périodiques; Herbes -- Périodiques; 615.1
• DOI: 10.1016/j.jep.2022.115630
• Languages: English
• ISSNs: 0378-8741

Abstract

Abstract: Ethnopharmacological relevance: The liver toxicity of Reynoutria multiflora (Thunb.) Moldenke. (Polygonaceae) ( Polygonum multiflorum Thunb, PM) has always attracted much attention, but the related toxicity materials and mechanisms have not been elucidated due to multi-component and multi-target characteristics. In previous hepatotoxicity screening, different components of PM were first evaluated and the hepatotoxicity of component D [95% ethanol (EtOH) elution] in a 70% EtOH extract of PM (PM-D) showed the highest hepatotoxicity. Furthermore, the main components of PM-D were identified and their hepatotoxicity was evaluated based on a zebrafish embryo model. However, the hepatotoxicity mechanism of PM-D is unknown. Aim of the study: This work is to explore the hepatotoxicity mechanisms of PM-D by integrating network toxicology and spatially resolved metabolomics strategy. Materials and methods: A hepatotoxicity interaction network of PM-D was constructed based on toxicity target prediction for eight key toxic ingredients and a hepatotoxicity target collection. Then the key signaling pathways were enriched, and molecular docking verification was implemented to evaluate the ability of toxic ingredients to bind to the core targets. The pathological changes of liver tissues and serum biochemical assays of mice were used to evaluate the liver injury effect of mice with oral administration of PM-D. Furthermore, spatially resolved metabolomics was used to visualize significant differences in metabolic profiles in mice after drug administration, to screen hepatotoxicity-related biomarkers and analyze metabolic pathways. Results: The contents of four key toxic compounds in PM-D were detected. Network toxicology identified 30 potential targets of liver toxicity of PM-D. GO and KEGG enrichment analyses indicated that the hepatotoxicity of PM-D involved multiple biological activities, including cellular response to endogenous stimulus, organonitrogen compound metabolic process, regulation of the apoptotic process, regulation of kinase, regulation of reactive oxygen species metabolic process and signaling pathways including PI3K-Akt, AMPK, MAPK, mTOR, Ras and HIF-1. The molecular docking confirmed the high binding activity of 8 key toxic ingredients with 10 core targets, including mTOR, PIK3CA, AKT1, and EGFR. The high distribution of metabolites of PM-D in the liver of administrated mice was recognized by mass spectrometry imaging. Spatially resolved metabolomics results revealed significant changes in metabolic profiles after PM-D administration, and metabolites such as taurine, taurocholic acid, adenosine, and acyl-carnitines were associated with PM-D-induced liver injury. Enrichment analyses of metabolic pathways revealed tht linolenic acid and linoleic acid metabolism, carnitine synthesis, oxidation of branched-chain fatty acids, and six other metabolic pathways were significantly changed. Comprehensive analysis revealed that the hepatotoxicity caused by PM-D was closely related to cholestasis, mitochondrial damage, oxidative stress and energy metabolism, and lipid metabolism disorders. Conclusions: In this study, the hepatotoxicity mechanisms of PM-D were comprehensively identified through an integrated spatially resolved metabolomics and network toxicology strategy, providing a theoretical foundation for the toxicity mechanisms of PM and its safe clinical application. Graphical abstract: Image 1 Highlights: The contents of key ingredients in PM-D were quantified. Network toxicology was an effective tool for toxic mechanism of TCMs. The toxic metabolic mechanism of PM-D was visualized by MSI technology. An integrated strategy was proposed for investigating the toxicity mechanism of TCMs.