Supplementary data to accompany "Abundant metabolite-matrix adducts illuminate the dark metabolome of MALDI-mass-spectrometry imaging datasets"

This dataset accompanies the publication "Abundant metabolite-matrix adducts illuminate the dark metabolome of MALDI-mass-spectrometry imaging datasets". The dataset includes all files, scripts and results that are included in the associated publication. Spatial metabolomics using mass spectrometry imaging (MSI) is a powerful tool to map hundreds or thousands of metabolites across biological systems. One major challenge is the complexity of the data, which includes signals from experimental artifacts. Formation of adducts (<em>e.g. </em>with Na+or K+) or abundant matrix-cluster, in the case of matrix-assisted laser desorption ionization (MALDI)-MSI, strongly increase peak counts. We developed <em>mass2adduct</em>, a universally applicable tool for adduct abundance estimations in high-mass-resolution spatial metabolomics datasets. Our study illustrates that MALDI-MSI data density is remarkably driven by adduct formation and revealed a major influence of so far unrecognized metabolite-matrix adducts on total peak counts. Current data analyses neglect those matrix adducts and therefore overestimate total metabolite numbers, thereby inflating the dark metabolome size. mass2adduct zenodo doi (10.5281/zenodo.1405088) mass2adduct gihub: https://github.com/kbseah/mass2adduct