Metandem: An online software tool for mass spectrometry-based isobaric labeling metabolomics

Area of Science:

• Analytical Chemistry
• Bioinformatics
• Metabolomics

Background:

• Mass spectrometry-based stable isotope labeling offers multiplexing and accurate quantification.
• Analyzing isobaric labeling metabolomics data, especially for quantification using MS/MS reporter ions, presents significant bioinformatics challenges.

Purpose of the Study:

• To introduce Metandem, a novel online software tool designed for comprehensive analysis of isobaric labeling-based metabolomics data.
• To provide a user-friendly platform integrating multiple data analysis steps for stable isotope labeling experiments.

Main Methods:

• Development of Metandem, an online software tool with a data analysis pipeline.
• Integration of feature extraction, metabolite quantification, identification, batch processing, parameter optimization, normalization, and statistical analysis.
• Systematic evaluation across UPLC-MS/MS, nanoLC-MS/MS, CE-MS/MS, and MALDI-MS platforms using various plex isobaric labeling experiments.

Main Results:

• Metandem successfully processes data from diverse mass spectrometry platforms and isobaric labeling configurations (duplex to 12-plex).
• The tool demonstrated comprehensive functionality, including quantification, identification, and statistical analysis, on various biological samples.
• Metandem provides a robust solution for analyzing challenging stable isotope labeling metabolomics datasets.

Conclusions:

• Metandem offers a powerful and accessible solution for the bioinformatics challenges in isobaric labeling metabolomics.
• The tool's comprehensive features and platform compatibility enhance the analysis of complex stable isotope labeling data.
• Metandem is freely available online, promoting wider adoption and advancement in metabolomics research.