Open AccessDiscovering New Lipidomic Features Using Cell Type Specific Fluorophore Expression to Provide Spatial and Biological Specificity in a Multimodal Workflow with MALDI Imaging Mass Spectrometry
Author(s) -
Marissa A. Jones,
Sung Hoon Cho,
Nathan Heath Patterson,
Raf Van de Plas,
Jeffrey M. Spraggins,
Mark Boothby,
Richard M. Caprioli
Publication year - 2020
Publication title -
analytical chemistry
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 2.117
H-Index - 332
eISSN - 1520-6882
pISSN - 0003-2700
DOI - 10.1021/acs.analchem.0c00446
Subject(s) - mass spectrometry imaging , chemistry , computational biology , fluorophore , molecular imaging , mass spectrometry , biomolecule , fluorescence , biochemistry , genetics , biology , physics , chromatography , quantum mechanics , in vivo
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.