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Related Concept Videos

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Tandem mass spectrometry is a technique that uses multiple mass analyzers in series to obtain a higher selectivity and reduce chemical noise during analyte detection. 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...
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DynaMet: a fully automated pipeline for dynamic LC-MS data.

Patrick Kiefer1, Uwe Schmitt2, Jonas E N Müller1

  • 1Institute of Microbiology, ETH Zurich , Zurich, Switzerland 8093.

Analytical Chemistry
|September 15, 2015
PubMed
Summary
This summary is machine-generated.

DynaMet automates the analysis of dynamic isotope labeling experiments using liquid chromatography-mass spectrometry (LC-MS). This tool enables robust, untargeted extraction of metabolite labeling profiles for metabolic pathway investigation.

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Area of Science:

  • Metabolomics
  • Systems Biology
  • Biochemistry

Background:

  • Dynamic isotope labeling experiments are vital for understanding metabolic pathway function.
  • Analyzing metabolome-wide labeling data requires robust feature grouping across samples.
  • Liquid chromatography-mass spectrometry (LC-MS) is a common technique for generating this data.

Purpose of the Study:

  • To develop DynaMet, a software for fully automated analysis of dynamic isotope labeling experiments from LC-high-resolution MS raw data.
  • To enable untargeted extraction of metabolite labeling profiles and provide integrated data visualization tools.

Main Methods:

  • Development of DynaMet, an automated analysis pipeline for LC-MS isotope labeling data.
  • Application of DynaMet to time-course labeling experiments in Bacillus methanolicus with (13)C methanol.
  • Validation using time-course labeling experiments in Escherichia coli with (13)C glucose.

Main Results:

  • DynaMet demonstrated high robustness and reproducibility in analyzing biological replicates.
  • The pipeline extracted 386 dynamic labeling features, with 357 successfully fitted by kinetic models.
  • 215 identified features mapped to core metabolism and biosynthetic pathways via KEGG database.

Conclusions:

  • DynaMet provides a powerful, automated solution for metabolome-wide dynamic isotope labeling analysis.
  • The software facilitates the investigation of metabolic pathway operation and metabolite flux.
  • DynaMet is available as a free, open-source Python package for the eMZed2 framework.