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 (e.g. 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 mass2adduct, 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