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Related Experiment Video

Updated: Sep 19, 2025

Untargeted Metabolomics from Biological Sources Using Ultraperformance Liquid Chromatography-High Resolution Mass Spectrometry UPLC-HRMS
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A New Comprehensive Platform for Profile-Mode-Based Untargeted Metabolomics for Efficient Data Mining to Improve

Xing-Cai Wang1, Meng Zhai2, Shu-Fang Li3

  • 1State Key Laboratory of Green Chemical Synthesis and Conversion Technology, College of Chemical Engineering, Zhejiang University of Technology, Hangzhou 310032, China.

Analytical Chemistry
|June 16, 2025
PubMed
Summary

A new data analysis platform, AntDAS-Profiler, offers improved untargeted metabolomics using ultra-high-performance liquid chromatography-high-resolution mass spectrometry (UHPLC-HRMS) profile data. It enhances compound identification and analysis for diverse applications.

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Area of Science:

  • Analytical Chemistry
  • Metabolomics
  • Biochemistry

Background:

  • Profile mode UHPLC-HRMS is crucial for comprehensive metabolomics data acquisition.
  • Existing data analysis methods are suboptimal for profile-mode untargeted metabolomics.
  • Accurate data processing is essential for reliable metabolomic profiling.

Purpose of the Study:

  • To develop novel algorithms and an automated platform for profile-mode UHPLC-HRMS data analysis.
  • To enhance the accuracy and comprehensiveness of untargeted metabolomics.
  • To provide a robust solution for complex biological sample analysis.

Main Methods:

  • Development of novel algorithms: centroiding transformation, extracted ion chromatogram (EIC) construction, and feature extraction.
  • Integration of algorithms into the AntDAS-Profiler automatic data analysis platform.
  • Validation using chrysanthemum samples from different origins and comparison with existing tools (MS-DIAL, XCMS, MZmine).

Main Results:

  • AntDAS-Profiler successfully distinguished chrysanthemum samples based on their origin.
  • The platform demonstrated robust performance in profile-mode untargeted metabolomics.
  • Comparative analysis indicated AntDAS-Profiler's potential as a comprehensive solution.

Conclusions:

  • AntDAS-Profiler offers a significant advancement for analyzing UHPLC-HRMS profile-mode data in metabolomics.
  • The developed algorithms and platform improve the identification and characterization of metabolites.
  • This tool provides researchers with a powerful resource for untargeted metabolomic studies.