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Related Concept Videos

Tandem Mass Spectrometry01:21

Tandem Mass Spectrometry

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Tandem mass spectrometry is a technique that uses multiple mass analyzers in series to obtain a higher selectivity and signal-to-noise ratio for the analyte. Instruments with multiple analyzers separated by an interaction cell enable secondary fragmentation and selected study of the fragment ions.
Secondary fragmentations occur in the interaction cell and can be induced by various factors. Fragmentation induced by collision with inert gases, such as N2, Ar, He, etc., is called collision-induced...
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Met4DX: A Unified and Versatile Data Processing Tool for Multidimensional Untargeted Metabolomics Data.

Yandong Yin1, Mingdu Luo1,2, Zheng-Jiang Zhu1,3

  • 1Interdisciplinary Research Center on Biology and Chemistry, Shanghai Institute of Organic Chemistry, Chinese Academy of Sciences, Shanghai, 200032 P. R. China.

Journal of the American Society for Mass Spectrometry
|October 15, 2024
PubMed
Summary

Met4DX is a new software tool designed to simplify the processing of complex untargeted metabolomics data from liquid chromatography-mass spectrometry (LC-MS) and LC-ion mobility-MS (LC-IM-MS). It enhances metabolite detection and quantification for improved biological discovery.

Keywords:
data processingion mobility-mass spectrometrymass spectrometryuntargeted metabolomics

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Area of Science:

  • Metabolomics
  • Analytical Chemistry
  • Bioinformatics

Background:

  • Untargeted metabolomics using liquid chromatography-mass spectrometry (LC-MS) is crucial for metabolite characterization.
  • Integrating ion mobility (IM) with LC-MS (LC-IM-MS) increases analytical depth but generates complex data.
  • Processing this complex multidimensional data poses significant challenges in metabolite profiling and quantification.

Purpose of the Study:

  • To develop a unified and versatile software tool, Met4DX, for processing 3D and 4D untargeted metabolomics data.
  • To address the challenges associated with complex data processing in LC-IM-MS.
  • To streamline the workflow from raw data to a final feature table with quantification and identification results.

Main Methods:

  • Development of Met4DX software incorporating an MS1-oriented peak detection approach.
  • Implementation of a bottom-up assembly algorithm for sensitive and comprehensive peak detection.
  • Utilization of a uniform quantification strategy for enhanced precision across samples.
  • Integration of peak detection, alignment, and quantification into a single streamlined workflow with a user-friendly interface.

Main Results:

  • Met4DX enables highly sensitive and comprehensive peak detection in untargeted metabolomics data.
  • The software enhances the precision of peak integration through a uniform quantification strategy.
  • Met4DX transforms raw multidimensional MS data into a final feature table with quantification and identification results.
  • The tool simplifies complex data processing with default parameter sets and a user-friendly interface.

Conclusions:

  • Met4DX provides a comprehensive solution for processing multidimensional untargeted metabolomics data.
  • The software facilitates metabolite discovery in biological samples by deciphering complex LC-IM-MS data.
  • Met4DX is freely available, promoting wider accessibility for metabolomics research.