Non-Targeted Mass Isotopolome Analysis Using Stable Isotope Patterns to Identify Metabolic Changes

Area of Science:

• Metabolomics
• Analytical Chemistry
• Systems Biology

Background:

• Mass spectrometry (MS) is crucial for understanding biological systems.
• Analyzing raw MS data requires specialized software for interpretation.
• Nontargeted metabolomics provides a broad overview of metabolic states.

Purpose of the Study:

• To describe a data processing workflow for mass spectrometry data.
• To enable comprehensive metabolic analysis, including metabolite levels and isotopic distributions.
• To provide an accessible tool for researchers without bioinformatics backgrounds.

Main Methods:

• Utilizing gas chromatography coupled with mass spectrometry (GC-MS).
• Implementing a novel data processing workflow for nontargeted metabolomics.
• Employing stable isotope labeling for detailed metabolic analysis.

Main Results:

• The workflow successfully generates metabolite levels and mass isotopomer distributions.
• It facilitates similarity and variability analysis of metabolites.
• The software simplifies the interpretation of complex MS data.

Conclusions:

• The developed data analysis software offers an accessible method for metabolic profiling.
• It empowers researchers to analyze MS data effectively, regardless of programming skills.
• This workflow enhances the utility of GC-MS in biological research.