Scout-triggered MRM from untargeted data: An R-based strategy for multiplexed targeted metabolomics

Area of Science:

• Metabolomics
• Analytical Chemistry
• Biomarker Discovery

Background:

• Transitioning from untargeted metabolomics discovery to targeted validation is challenging.
• Liquid chromatography-mass spectrometry (LC-MS) methods suffer from poor transferability and retention time (RT) variation.
• Automated, robust methods are needed to bridge the discovery-validation gap.

Purpose of the Study:

• To present Scout-MRM Builder, an R package for automated targeted method creation from untargeted high-resolution MS2 data.
• To implement a Scout-Triggered Multiple Reaction Monitoring (StMRM) strategy using N-Alkylpyridinium-3-Sulfonate (NAPS) standards as dynamic RT markers.
• To enable robust and reproducible targeted metabolomics analysis with enhanced method transferability.

Main Methods:

• Developed Scout-MRM Builder, an R package utilizing a StMRM strategy.
• Employed NAPS standards as dynamic RT markers to trigger specific transition lists.
• Automated ion pair extraction, scout identification, and generation of StMRM methods, including pseudo-MRM transitions.
• Applied the method to porcine liver extracts and a liver ischemia-reperfusion injury model.

Main Results:

• Generated a single StMRM method monitoring 1312 transitions from 558 untargeted features.
• Achieved high reproducibility, with 89.9% of transitions showing <20% relative standard deviation (RSD).
• Obtained results comparable to untargeted analysis in a liver injury model, identifying a common set of potential biomarkers.

Conclusions:

• Scout-MRM Builder effectively bridges the gap between metabolomics discovery and validation.
• The StMRM strategy ensures robustness against RT shifts, enhancing method reliability.
• Provides a powerful framework for robust, large-scale targeted metabolomics analysis with improved transferability.