MALDI IMS-Derived Molecular Contour Maps: Augmenting Histology Whole-Slide Images

Imaging mass spectrometry (IMS) provides untargeted,
highly multiplexed
maps of molecular distributions in tissue. Ion images are routinely
presented as heatmaps and can be overlaid onto complementary microscopy
images that provide greater context. However, heatmaps use transparency
blending to visualize both images, obscuring subtle quantitative differences
and distribution gradients. Here, we developed a contour mapping approach
that combines information from IMS ion intensity distributions with
that of stained microscopy. As a case study, we applied this approach
to imaging data from Staphylococcus aureus-infected
murine kidney. In a univariate, or single molecular species, use-case
of the contour map representation of IMS data, certain lipids colocalizing
with regions of infection were selected using Pearson’s correlation
coefficient. Contour maps of these lipids overlaid with stained microscopy
showed enhanced visualization of lipid distributions and spatial gradients
in and around the bacterial abscess as compared to traditional heatmaps.
The full IMS data set comprising hundreds of individual ion images
was then grouped into a smaller subset of representative patterns
using non-negative matrix factorization (NMF). Contour maps of these
multivariate NMF images revealed distinct molecular profiles of the
major abscesses and surrounding immune response. This contour mapping
workflow also enabled a molecular visualization of the transition
zone at the host–pathogen interface, providing potential clues
about the spatial molecular dynamics beyond what histological staining
alone provides. In summary, we developed a new IMS-based contour mapping
approach to augment classical stained microscopy images, providing
an enhanced and more interpretable visualization of IMS-microscopy
multimodal molecular imaging data sets.