Metandem

Metandem analyzes mass spectrometry (MS)-based metabolomics data generated with isobaric stable isotope labeling to quantify and identify metabolites using MS/MS reporter ions in multiplexed experiments.

Key Features:

• Feature Extraction: Automated extraction of relevant features from raw mass spectrometry data.
• Metabolite Quantification: Quantification of metabolites using MS/MS reporter ions derived from isobaric stable isotope labeling for multiplexed comparisons.
• Metabolite Identification: Identification of metabolites by leveraging isobaric labeling patterns.
• Batch Processing and Parameter Optimization: Batch processing of multiple data files with dataset-specific parameter optimization.
• Data Normalization and Statistical Analysis: Median normalization and comprehensive statistical analyses to reduce variability and detect significant changes.
• Platform Compatibility: Evaluated across UPLC-MS/MS, nanoLC-MS/MS, CE-MS/MS, and MALDI-MS and supporting isobaric labeling configurations from duplex to 12-plex.

Scientific Applications:

• Multiplexed Metabolomics: Enables quantitative comparison of multiple samples in a single experiment using isobaric labeling.
• Biomarker Discovery: Supports identification of differential metabolites for biomarker discovery studies.
• Metabolic Pathway Analysis: Facilitates detection of metabolite changes relevant to pathway-level interpretations.
• Systems Biology Studies: Provides quantitative metabolite data suitable for integration into systems biology analyses.

Methodology:

Feature extraction; reporter-ion–based metabolite quantification; metabolite identification using isobaric labeling patterns; batch processing; parameter optimization; median normalization; and statistical analyses.