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

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. ### Competing Interest Statement The authors have declared no competing interest. * ### Abbreviations (DHB) : 2,5-Dihydroxybenzoic acid (13C6-DHB) : 2,5-Dihydroxybenzoic acid with 13C-labeled aromatic ring (CHCA) : alpha-Cyano-4-hydroxycinnamic acid (9AA) : 9-Aminoacridine (DAN) : 1,5-Diaminonaphthalene (NEDC) : N-(1-naphthyl) ethylenediamine dihydrochloride (ML) : Machine Learning (AI) : Artificial Intelligence (HMDB) : Human Metabolome Database (SIL) : Standard Isotope Labeled (FDR) : False Discovery Rate (NMR) : Nuclear Magnetic Resonance (MALDI) : Matrix Assisted Laser Desorption Ionization (MSI) : Mass Spectrometry Imaging (TIC) : Total Ion Current (UMAP) : Uniform Manifold Approximation and Projection (CFM-ID) : Competitive Fragmentation Modeling for Metabolite Identification (FTICR) : Fourier-transform ion cyclotron resonance (TOF) : Time Of Flight (DBSCAN) : Density-Based Spatial Clustering of Applications with Noise (ITO) : Indium tin oxide (AUC) : Area Under the Curve