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Mass spectrometry imaging (MSI) has accelerated our understanding of lipid metabolism and spatial distribution in tissues and cells. However, few MSI studies have approached lipid imaging quantitatively and those that have focused on a single lipid class. We overcome this limitation by using a multiclass internal standard (IS) mixture sprayed homogeneously over the tissue surface with concentrations that reflect those of endogenous lipids. This enabled quantitative MSI (Q-MSI) of 13 lipid classes and subclasses representing almost 200 sum-composition lipid species using both MALDI (negative ion mode) and MALDI-2 (positive ion mode) and pixel-wise normalization of each lipid species in a manner analogous to that widely used in shotgun lipidomics. The Q-MSI approach covered 3 orders of magnitude in dynamic range (lipid concentrations reported in pmol/mm 2 ) and revealed subtle changes in distribution compared to data without normalization. The robustness of the method was evaluated by repeating experiments in two laboratories using both timsTOF and Orbitrap mass spectrometers with an ∼4-fold difference in mass resolution power. There was a strong overall correlation in the Q-MSI results obtained by using the two approaches. Outliers were mostly rationalized by isobaric interferences or the higher sensitivity of one instrument for a particular lipid species. These data provide insight into how the 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 subclasses and revealing how absolute lipid concentrations vary throughout and between biological tissues.

Here we report the development and optimization of a mass spectrometry imaging (MSI) platform that combines an atmospheric-pressure matrix-assisted laser desorption/ionization platform with plasma postionization (AP-MALDI-PPI) and trapped ion mobility spectrometry (TIMS). We discuss optimal parameters for operating the source, characterize the behavior of a variety of lipid classes in positive- and negative-ion modes, and explore the capabilities for lipid imaging using murine brain tissue. The instrument generates high signal-to-noise for numerous lipid species, with mass spectra sharing many similarities to those obtained using laser postionization (MALDI-2). The system is especially well suited for detecting lipids such as phosphatidylethanolamine (PE), as well as numerous sphingolipid classes and glycerolipids. For the first time, the coupling of plasma-based postionization with ion mobility is presented, and we show the value of ion mobility for the resolution and identification of species within rich spectra that contain numerous isobaric/isomeric signals that are not resolved in the m / z dimension alone, including isomeric PE and demethylated phosphatidylcholine lipids produced by in-source fragmentation. The reported instrument provides a powerful and user-friendly approach for MSI of lipids.