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

revised on 07.04.2020 and posted on 08.04.2020 by Marissa A. Jones, Sung Hoon Cho, Nathan Heath Patterson, Raf Van de Plas, Jeffrey Spraggins, Mark R. Boothby, Richard M. Caprioli

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.


NSF DGE-1445197

Imaging Mass Spectrometry Research Resource at Vanderbilt University

National Institute of General Medical Sciences

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R01 AI113292

R01 HL106812


Email Address of Submitting Author


Vanderbilt University


United States

ORCID For Submitting Author


Declaration of Conflict of Interest

We declare no conflict of interest.

Version Notes

This is a second version.