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An automatic LC-MS/MS data analysis workflow for herbal compound annotation with AutoAnnotatoR: A case study of ten botanical origins of Fritillaria species

文献类型：期刊论文

作者An, Ya-ling2,3; Li, Jia-yuan3; Wei, Wen-long3; Li, Yun3; Zhang, Jian-qing3; Yao, Chang-liang3; Bi, Qi-rui3; Wang, Shu4; Zeng, Zhong-da1; Guo, De-an2,3
刊名PHYTOMEDICINE
出版日期2024-12-01
卷号135页码:12
关键词Botanical natural products Automatic compound annotation LC-MS/MS AutoAnnotatoR
ISSN号0944-7113
DOI10.1016/j.phymed.2024.156193
通讯作者Zeng, Zhong-da(adawin.tsang@qq.com) ; Guo, De-an(daguo@simm.ac.cn)
英文摘要Background: Despite the widespread implementation of analytical hardware capable of recording large-scale datasets for botanical natural products, the data processing procedures for compound annotation remain a bothersome obstacle that demand a tremendous amount of time and expert knowledge. Methods: Herein, an automatic LC-MS/MS data analysis workflow with AutoAnnotatoR was introduced for the compound annotation of plant derived natural products, which has the merits of great efficiency, high accuracy, saving time and simplified process. This procedure enabled automatic matching of MS2 data with characteristic fragment ions, as well as MS1 data with compound libraries, which improves the accuracy of structural elucidation. Notably, the optimization of collision energy for each target ion was successfully performed for the first time, facilitating the acquisition of comprehensive fragmentation information. Results: The automatic analysis workflow with AutoAnnotatoR was successfully applied for the annotation of alkaloids from 10 botanical origins of Fritillaria species. Consequently, a total of 2684 chemical constituents were tentatively characterized, with 23 components being unambiguously validated by reference standards and 2434 being probable novel chemicals. Conclusion: The entire data analysis procedure takes only a few hours, vastly improving analysis speed while assuring high accuracy. This method provides a powerful tool for the rapid and precise annotation of complex natural products. The workflow is publicly accessible on Github as an open-source R package called AutoAnnotatoR (https://github.com/anyaling2022/AutoAnnotatoR).
WOS关键词ALKALOIDS ; MS ; IDENTIFICATION ; EXPECTORANT ; BULBUS ; TOOL
资助项目National Natural Science Foundation of China[82130111] ; Qi-Huang Scholar Chief Scientist Program of National Administration of Traditional Chinese Medicine Leading Talents Support Program (2020)
WOS研究方向Plant Sciences ; Pharmacology & Pharmacy ; Integrative & Complementary Medicine
语种英语
WOS记录号WOS:001354824400001
出版者ELSEVIER GMBH
源URL[http://119.78.100.183/handle/2S10ELR8/314421]  
专题中国科学院上海药物研究所
通讯作者Zeng, Zhong-da; Guo, De-an
作者单位1.Dalian Univ, Coll Environm & Chem Engn, Dalian 116622, Liaoning, Peoples R China
2.Univ Chinese Acad Sci, 19A Yuquan Rd, Beijing 100049, Peoples R China
3.Chinese Acad Sci, Shanghai Inst Mat Med, Shanghai Res Ctr Modernizat Tradit Chinese Med, Natl Engn Res Ctr TCM Standardizat Technol, Haike Rd 501, Shanghai 201203, Peoples R China
4.Sichuan Univ, West China Sch Pharm, 17 Renmin South Rd, Chengdu 610041, Peoples R China
推荐引用方式
GB/T 7714		 An, Ya-ling,Li, Jia-yuan,Wei, Wen-long,et al. An automatic LC-MS/MS data analysis workflow for herbal compound annotation with AutoAnnotatoR: A case study of ten botanical origins of Fritillaria species[J]. PHYTOMEDICINE,2024,135:12.
APA An, Ya-ling.,Li, Jia-yuan.,Wei, Wen-long.,Li, Yun.,Zhang, Jian-qing.,...&Guo, De-an.(2024).An automatic LC-MS/MS data analysis workflow for herbal compound annotation with AutoAnnotatoR: A case study of ten botanical origins of Fritillaria species.PHYTOMEDICINE,135,12.
MLA An, Ya-ling,et al."An automatic LC-MS/MS data analysis workflow for herbal compound annotation with AutoAnnotatoR: A case study of ten botanical origins of Fritillaria species".PHYTOMEDICINE 135(2024):12.

入库方式： OAI收割

来源：上海药物研究所

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