Omics Scale Quantitative Mass Spectrometry Imaging of Lipids in Brain Tissue using a Multi-Class Internal Standard Mixture

Author:

Vandenbosch Michiel,Mutuku Shadrack M.ORCID,Mantas Maria José Q.,Patterson Nathan H.,Hallmark Tucker,Claesen Marc,Heeren Ron M. A.ORCID,Hatcher Nathan G.,Verbeeck Nico,Ekroos KimORCID,Ellis Shane R.ORCID

Abstract

AbstractMass spectrometry imaging (MSI) has accelerated the understanding of lipid metabolism and spatial distribution in tissues and cells. However, few MSI studies have approached lipid imaging quantitatively and those that have focus on a single lipid class. Herein, we overcome limitation of quantitative MSI (Q-MSI) by using a multi-class internal standard lipid mixture that is sprayed homogenously over the tissue surface with analytical concentrations that reflects endogenous brain lipid levels. Using this approach we have performed Q-MSI for 13 lipid classes representing >200 sum-composition lipid species. This was carried out using both MALDI (negative ion mode) and MALDI-2 (positive ion mode) and pixel-wise normalisation of each lipid species signal to the corresponding class-specific IS an approach analogous to that widely used for shotgun lipidomics from biological extracts. This approach allows pixel concentrations of lipids to be reported in pmol/mm2. Q-MSI of lipids covered 3 orders of magnitude in dynamic range and revealed subtle change sin in distribution compared to conventional total-ion-current normalisation approaches. The robustness of the method was evaluated by repeating experiments in two laboratories on biological replicates using both timsTOF and Orbitrap mass spectrometers operated with a ~4-fold difference in mass resolution power. There was a strong overall correlation in the Q-MSI result obtained using the two approaches with outliers mostly rationalised by isobaric interferences that are only resolved with the Orbitrap system or the higher sensitivity of one instrument for particular lipid species, particularly for lipids detected at low intensity. These data provide insight into how mass resolving power can affect Q-MSI data. This approach opens up the possibility of performing large-scale Q-MSI studies across numerous lipid classes and reveal how absolute lipid concentrations vary throughout and between biological tissues.

Publisher

Cold Spring Harbor Laboratory

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