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A mass spectrum-oriented computational method for ion mobility-resolved untargeted metabolomics.

Mingdu Luo1,2, Yandong Yin1, Zhiwei Zhou1

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

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We developed Met4DX, a computational framework for ion mobility-resolved metabolomics data analysis. Met4DX enhances metabolite detection and isomer differentiation, advancing untargeted metabolomics discovery.

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Area of Science:

  • Analytical Chemistry
  • Biochemistry
  • Computational Biology

Background:

  • Ion mobility (IM) coupled with liquid chromatography-mass spectrometry enhances untargeted metabolomics by improving coverage, sensitivity, and resolving power, especially for metabolite isomers.
  • The high dimensionality of IM-resolved metabolomics data poses significant computational challenges, hindering its broad application.

Purpose of the Study:

  • To develop an advanced computational framework for processing and analyzing four-dimensional (4D) data generated by IM-resolved metabolomics.
  • To improve peak detection, metabolite quantification, and identification in complex metabolomics datasets.
  • To enable the differentiation of co-eluted metabolite isomers.

Main Methods:

  • Development of a mass spectrum-oriented bottom-up assembly algorithm for assembling 4D peaks.
  • Creation of the end-to-end computational framework, Met4DX.
  • Benchmarking and validation of Met4DX against existing tools using IM-resolved metabolomics data.

Main Results:

  • Met4DX demonstrates superior performance in coverage, sensitivity, peak fidelity, and quantification precision compared to current methods.
  • The framework successfully detects and differentiates co-eluted metabolite isomers with subtle differences in chromatographic and ion mobility dimensions.
  • Met4DX effectively deciphers complex 4D metabolomics data.

Conclusions:

  • Met4DX significantly advances the analysis of IM-resolved metabolomics data, overcoming previous computational limitations.
  • The developed framework enhances metabolite discovery in biological systems by providing more accurate and sensitive data analysis.
  • Met4DX facilitates a deeper understanding of the metabolome, particularly in distinguishing complex isomeric structures.