A New Comprehensive Platform for Profile-Mode-Based Untargeted Metabolomics for Efficient Data Mining to Improve Compound Extraction and Identification
文献类型： 外文期刊
作者： Wang, Xing-Cai 1 ; Zhai, Meng 2 ; Li, Shu-Fang 3 ; Lv, Hang 2 ; Ma, Hui 2 ; Yang, Chang 1 ; Zheng, Qing-Xia 4 ; Liu, Ping-Ping 4 ; Lu, Peng 4 ; Yu, Yong-Jie 2 ; Fu, Hai-Yan 5 ; She, Yuanbin 1 ;
作者机构： 1.Zhejiang Univ Technol, Coll Chem Engn, State Key Lab Green Chem Synth & Convers Technol, Hangzhou 310032, Peoples R China
2.Ningxia Med Univ, Coll Pharm, Yinchuan 750004, Peoples R China
3.Henan Acad Agr Sci, Inst Qual Stand & Testing Technol Agroprod, Zhengzhou 450002, Peoples R China
4.Zhengzhou Tobacco Res Inst, CNTC, Zhengzhou 450001, Peoples R China
5.South Cent Minzu Univ, Sch Pharmaceut Sci, Wuhan 430074, Peoples R China
期刊名称：ANALYTICAL CHEMISTRY （ 影响因子：6.7； 五年影响因子：6.6 ）
ISSN： 0003-2700
年卷期： 2025 年 97 卷 27 期
页码：
收录情况： SCI
摘要： The profile mode of ultra-high-performance liquid chromatography-high-resolution mass spectrometry (UHPLC-HRMS) is commonly utilized in metabolomics for its ability to comprehensively retain compound information in mass spectra. However, current data-analysis methods have not been optimized for the entire profile-mode-based untargeted metabolomics. To address this issue, we developed a set of novel algorithms, including centroiding transformation, extracted ion chromatogram construction, and feature extraction. We integrated them into a new automatic data analysis platform, AntDAS-Profiler. The performance of these newly developed algorithms was demonstrated by distinguishing chrysanthemums from various production origins. Additionally, AntDAS-Profiler was comprehensively compared with several state-of-the-art tools such as MS-DIAL, XCMS, and MZmine. Results suggested that AntDAS-Profiler can provide researchers with a comprehensive solution for UHPLC-HRMS profile-mode-based metabolomics. AntDAS-Profiler can be accessed at http://www.pmdb.org.cn/antdasprofiler.
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