Discovering new lipidomic features using cell type specific fluorophore expression to provide spatial and biological specificity in a multimodal workflow with MALDI IMS

31 January 2020, Version 3
This content is a preprint and has not undergone peer review at the time of posting.


Identifying the spatial distributions of biomolecules in tissue is crucial for understanding integrated function. Imaging Mass Spectrometry (IMS) allows simultaneous mapping of thousands of biosynthetic products such as lipids but has needed a means of identifying specific cell-types or functional states to correlate with molecular localization. We report here advances starting from identity marking with a genetically encoded fluorophore. The fluorescence emission data were integrated with IMS data through multimodal image processing with advanced registration techniques and data-driven image fusion. In an unbiased analysis of spleens, this integrated technology enabled identification of ether lipid species preferentially enriched in germinal centers. We propose that this use of genetic marking for microanatomical regions of interest can be paired with molecular information from IMS for any tissue, cell-type, or activity state for which fluorescence is driven by a gene-tracking allele and ultimately with outputs of other means of spatial mapping.


Multimodal Imaging Approach
immunology/immune response
Germinal center
Cell type specific expression
image fusion
Data-driven image fusion
Transgenic Fluorophore Protein
light zone

Supplementary materials

200128 SIAppendix2


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