Discovering New Lipidomic Features Using Cell Type Specific Fluorophore Expression to Provide Spatial and Biological Specificity in a Multimodal Workflow with MALDI Imaging Mass Spectrometry

Journal Article (2020)
Author(s)

Marissa A. Jones (Vanderbilt University Medical Center, VanderBilt University)

Sung Hoon Cho (Vanderbilt University Medical Center)

Nathan Heath Patterson (Vanderbilt University Medical Center, VanderBilt University)

Raf Van De Plas (Vanderbilt University Medical Center, VanderBilt University, TU Delft - Team Raf Van de Plas)

Jeffrey M. Spraggins (Vanderbilt University Medical Center, VanderBilt University)

Mark R. Boothby (Vanderbilt University Medical Center, VanderBilt University)

Richard M. Caprioli (VanderBilt University, Vanderbilt University Medical Center)

Research Group
Team Raf Van de Plas
DOI related publication
https://doi.org/10.1021/acs.analchem.0c00446
More Info
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Publication Year
2020
Language
English
Research Group
Team Raf Van de Plas
Issue number
10
Volume number
92
Pages (from-to)
7079-7086
Downloads counter
261

Abstract

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.

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