LC-HRMS-based untargeted metabolomics coupled with quantitative spectrum-effect relationship analysis for screening bioactive components of astragalus membranaceus ameliorating diabetes in mouse oral trial

LC-HRMS-based untargeted metabolomics coupled with quantitative spectrum-effect relationship analysis for screening bioactive components of astragalus membranaceus ameliorating diabetes in mouse oral trial | Authorea try { document.documentElement.classList.add('js'); } catch (e) { } var _gaq = _gaq || []; _gaq.push(['_setAccount', 'G-8VDV14Y67G']); _gaq.push(['_trackPageview']); (function() { var ga = document.createElement('script'); ga.type = 'text/javascript'; ga.async = true; ga.src = ('https:' == document.location.protocol ? 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Data may be preliminary. 29 March 2025 V1 Latest version Share on LC-HRMS-based untargeted metabolomics coupled with quantitative spectrum-effect relationship analysis for screening bioactive components of astragalus membranaceus ameliorating diabetes in mouse oral trial Authors : Tang Chao , Xie Shuangnan , Jia Hongtao , Shen Qi , Wei-Zhong He , Deng Shiyi , Tang Jing , Liu Zhi , and Cheng Wang [email protected] Authors Info & Affiliations https://doi.org/10.22541/au.174327851.17001789/v1 200 views 92 downloads Contents Abstract Supplementary Material Information & Authors Metrics & Citations View Options References Figures Tables Media Share Abstract Rationale: Diabetes mellitus poses a substantial global health burden, necessitating novel therapeutic strategies. Astragalus membranaceus (AM), a traditional Chinese medicinal herb, has demonstrated potential in alleviating diabetic symptoms. This study aimed to investigate the mechanism of AM (root) extract in ameliorating diabetes and identify its bioactive components through advanced metabolomic and data-mining approaches. Methods: Untargeted metabolomics utilizing liquid chromatography-high resolution mass spectrometry (LC-HRMS), combined with quantitative spectrum-effect relationship analysis (QSERA), was applied to analyze AM (root) extract administered in oral experiments using the Leprdb/db mouse model. The AntDAS (Automatic Data Analysis Strategy) platform enabled screening of bioactive compounds from LC-HRMS fingerprints under heavily interfered background conditions. Molecular efficacy predictions for diabetes alleviation were derived via QSERA modeling. Results: 56 bioactive compounds associated with diabetic remediation were identified. Specific adjusting efficacies of bioactive compound on mouse diabetes were predicted by QSERA, proving that astragalus polysaccharide (APS) is the main medicinal component alleviating mouse diabetes and it may be as a potential insulin sensitizer for treating type II diabetes of human. Conclusion: Integrating LC-HRMS-based metabolomics and QSERA provides a systematic strategy to elucidate the pharmacodynamic basis of AM (root) extract, advancing the clinical translation of traditional Chinese medicine resources for diabetes management. Supplementary Material File (manuscript.docx) Download 79.31 KB File (table 1.docx) Download 23.73 KB File (table 2.docx) Download 32.81 KB Information & Authors Information Version history V1 Version 1 29 March 2025 Copyright This work is licensed under a Non Exclusive No Reuse License. Keywords antdas astragalus membranaceus diabetes qsera screening of bioactive components untargeted metabolomics Authors Affiliations Tang Chao Xinjiang Agricultural University View all articles by this author Xie Shuangnan Xinjiang Agricultural University View all articles by this author Jia Hongtao Xinjiang Agricultural University View all articles by this author Shen Qi Xinjiang Academy of Agricultural Sciences View all articles by this author Wei-Zhong He Xinjiang Academy of Agricultural Sciences View all articles by this author Deng Shiyi Hunan University of Humanities Science and Technology View all articles by this author Tang Jing Hunan University of Humanities Science and Technology View all articles by this author Liu Zhi Hunan University of Humanities Science and Technology View all articles by this author Cheng Wang [email protected] Xinjiang Academy of Agricultural Sciences View all articles by this author Metrics & Citations Metrics Article Usage 200 views 92 downloads .FvxKWukQNSOunydq8rnd { width: 100px; } Citations Download citation Tang Chao, Xie Shuangnan, Jia Hongtao, et al. LC-HRMS-based untargeted metabolomics coupled with quantitative spectrum-effect relationship analysis for screening bioactive components of astragalus membranaceus ameliorating diabetes in mouse oral trial. Authorea . 29 March 2025. DOI: https://doi.org/10.22541/au.174327851.17001789/v1 If you have the appropriate software installed, you can download article citation data to the citation manager of your choice. Simply select your manager software from the list below and click Download. For more information or tips please see 'Downloading to a citation manager' in the Help menu . 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