Sign in
BioinformaticsbioRxiv
Preprint

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

Gerard BaqueriD, Miguel BernúsiD, Lluc SementéiD, René J. M. van Zeijl, María García‐AltaresiD, Bram HeijsiD, Omar BoutureiraiD, Xavier CorreigiD, Pere RàfolsiD

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.

PDFDOI

02 /Specification & Classification

Click any tag to browse matching papers

Reproducibility ledger

Nobody has reported trying to reproduce this paper yet. Did you replicate an experiment or run the code? Your report saves the next lab a week.

Sign in to file a reproducibility report.

Similarity Map
SelectedSame fieldCross-field
THISBaquer '20Mahamdi '26Bjärterot '25Stancliffe '26Saharuka '24Sammour '21
73% semantic matchBioinformatics
Gerard Baquer, Lluc Sementé, María García‐Altares+4 more·Journal of Cheminformatics·Jul 22, 2020· 11 citations