Discovering Matrix Adducts for Enhanced Metabolite Profiling with Stable Isotope-Labeled MALDI-MSI

Abstract

Matrix-assisted laser desorption ionization mass spectrometry imaging (MALDI-MSI) is a widely used technique for spatial metabolomics analysis, but the matrix introduces spectral interferences that impede data processing. In this study, we present an experimental and computational workflow utilizing isotopic labeling to discover and annotate matrix adducts in MALDI-MSI. Our approach enables the removal of matrix-related signals, improving metabolite annotation accuracy, extending metabolome coverage, and facilitating the interpretation of tissue morphology.