Toward Omics-Scale Quantitative Mass Spectrometry Imaging of Lipids in Brain Tissue Using a Multiclass Internal Standard Mixture

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/mm2) 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.