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MIA: non-targeted mass isotopolome analysis.

Daniel Weindl1, Andre Wegner1, Karsten Hiller1

  • 1Luxembourg Centre for Systems Biomedicine, University of Luxembourg, L-4362 Esch-sur-Alzette, Luxembourg.

Bioinformatics (Oxford, England)
|June 9, 2016
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Summary

MIA software non-targetedly detects and visualizes isotopic enrichment in gas chromatography-electron ionization mass spectrometry (GC-EI-MS) data. This tool aids in understanding metabolic flux changes and tracing stable isotope-labeled compounds.

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Area of Science:

  • Metabolomics
  • Analytical Chemistry
  • Systems Biology

Background:

  • Stable isotope labeling is crucial for metabolic flux analysis.
  • Non-targeted analysis of isotopic enrichment in complex datasets remains challenging.

Purpose of the Study:

  • To develop a software tool for non-targeted detection and visualization of isotopic enrichment in GC-EI-MS data.
  • To provide an intuitive platform for mass isotopomer distribution analysis across multiple datasets.

Main Methods:

  • Developed MIA (Metabolite Isotope Analyzer) software.
  • Implemented a graphical user interface for visual analysis.
  • Utilized C++, Qt5, NTFD, and the MetaboliteDetector framework.

Main Results:

  • MIA enables non-targeted detection and visualization of isotopic enrichment.
  • Facilitates visual mass isotopomer distribution analysis across datasets.
  • Reveals changes in metabolic fluxes and the fate of labeled tracers.

Conclusions:

  • MIA is a valuable tool for researchers studying metabolic pathways using stable isotope labeling.
  • The software simplifies the analysis of complex GC-EI-MS data, aiding in the elucidation of metabolic dynamics.