A New Comprehensive Platform for Profile-Mode-Based Untargeted Metabolomics for Efficient Data Mining to Improve Compound Extraction and Identification

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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Publication Details

Journal
Analytical Chemistry
Published
2025-06-16
DOI
https://doi.org/10.1021/acs.analchem.4c05768
Citations
1
Primary Topic
Metabolomics and Mass Spectrometry Studies
Type
article
Field-Weighted Citation Impact
0.81

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article

A New Comprehensive Platform for Profile-Mode-Based Untargeted Metabolomics for Efficient Data Mining to Improve Compound Extraction and Identification

Shufang Li, Xing-Cai Wang, Peng Lü, Yuanbin She et al.
1 citations
Analytical Chemistry
Metabolomics and Mass Spectrometry Studies
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article

A New Comprehensive Platform for Profile-Mode-Based Untargeted Metabolomics for Efficient Data Mining to Improve Compound Extraction and Identification

Shufang Li, Xing-Cai Wang, Peng Lü, Yuanbin She, Hui Ma, Yong‐Jie Yu, Qingxia Zheng, Chang Yang, Hang Lv, Haiyan Fu, Meng Zhai, Pingping Liu
article en
1 citations

Abstract

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.

Analytical ChemistryVol. 97(27)
Minzu University of China (CN), Tobacco Research Institute (CN), Henan Academy of Agricultural Sciences (CN), Ningxia Medical University (CN), Institute of Quality Standards and Testing Technology for Agro Products (CN), Chemical Synthesis Lab (SG), Zhejiang University of Technology (CN)
National Natural Science Foundation of China, Ningxia Medical University, Key Research and Development Program of Ningxia
Openalex Percentile: Top 27%
Metabolomics and Mass Spectrometry Studies
0.81
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