Ya-Ling An, Jia-Yuan Li, Wen-Long Wei, Yun Li, Jian-Qing Zhang, Chang-Liang Yao, Qi-Rui Bi, Shu Wang, Zhong-da Zeng, De-An Guo
{"title":"利用 AutoAnnotatoR 对中草药化合物进行注释的自动 LC-MS/MS 数据分析工作流程:一项关于 10 种鱼腥草植物来源的案例研究。","authors":"Ya-Ling An, Jia-Yuan Li, Wen-Long Wei, Yun Li, Jian-Qing Zhang, Chang-Liang Yao, Qi-Rui Bi, Shu Wang, Zhong-da Zeng, De-An Guo","doi":"10.1016/j.phymed.2024.156193","DOIUrl":null,"url":null,"abstract":"<p><strong>Background: </strong>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.</p><p><strong>Methods: </strong>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 MS<sup>2</sup> data with characteristic fragment ions, as well as MS<sup>1</sup> 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.</p><p><strong>Results: </strong>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.</p><p><strong>Conclusion: </strong>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).</p>","PeriodicalId":20212,"journal":{"name":"Phytomedicine","volume":"135 ","pages":"156193"},"PeriodicalIF":6.7000,"publicationDate":"2024-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"An automatic LC-MS/MS data analysis workflow for herbal compound annotation with AutoAnnotatoR: A case study of ten botanical origins of Fritillaria species.\",\"authors\":\"Ya-Ling An, Jia-Yuan Li, Wen-Long Wei, Yun Li, Jian-Qing Zhang, Chang-Liang Yao, Qi-Rui Bi, Shu Wang, Zhong-da Zeng, De-An Guo\",\"doi\":\"10.1016/j.phymed.2024.156193\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><strong>Background: </strong>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.</p><p><strong>Methods: </strong>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 MS<sup>2</sup> data with characteristic fragment ions, as well as MS<sup>1</sup> 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.</p><p><strong>Results: </strong>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.</p><p><strong>Conclusion: </strong>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).</p>\",\"PeriodicalId\":20212,\"journal\":{\"name\":\"Phytomedicine\",\"volume\":\"135 \",\"pages\":\"156193\"},\"PeriodicalIF\":6.7000,\"publicationDate\":\"2024-12-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Phytomedicine\",\"FirstCategoryId\":\"3\",\"ListUrlMain\":\"https://doi.org/10.1016/j.phymed.2024.156193\",\"RegionNum\":1,\"RegionCategory\":\"医学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"2024/10/28 0:00:00\",\"PubModel\":\"Epub\",\"JCR\":\"Q1\",\"JCRName\":\"CHEMISTRY, MEDICINAL\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Phytomedicine","FirstCategoryId":"3","ListUrlMain":"https://doi.org/10.1016/j.phymed.2024.156193","RegionNum":1,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"2024/10/28 0:00:00","PubModel":"Epub","JCR":"Q1","JCRName":"CHEMISTRY, MEDICINAL","Score":null,"Total":0}
An automatic LC-MS/MS data analysis workflow for herbal compound annotation with AutoAnnotatoR: A case study of ten botanical origins of Fritillaria species.
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).
期刊介绍:
Phytomedicine is a therapy-oriented journal that publishes innovative studies on the efficacy, safety, quality, and mechanisms of action of specified plant extracts, phytopharmaceuticals, and their isolated constituents. This includes clinical, pharmacological, pharmacokinetic, and toxicological studies of herbal medicinal products, preparations, and purified compounds with defined and consistent quality, ensuring reproducible pharmacological activity. Founded in 1994, Phytomedicine aims to focus and stimulate research in this field and establish internationally accepted scientific standards for pharmacological studies, proof of clinical efficacy, and safety of phytomedicines.