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Anal Chem. 2019 Sep 3;91(17):11380-11387. doi: 10.1021/acs.analchem.9b02663. Epub 2019 Aug 19.

Toward Single-Organelle Lipidomics in Live Cells.

Author information

1
Neuro-Oncology Branch, Center for Cancer Research , National Cancer Institute, National Institutes of Health , Bethesda , Maryland 20892 , United States.
2
Advanced Cytometry Instrumentation Systems, LLC , 19 Elm Street , Buffalo , New York 14203 , United States.
3
Institute for Lasers, Photonics and Biophotonics , University at Buffalo, State University of New York , Buffalo , New York 14260 , United States.
4
Thermo Fisher Scientific , 2 Radcliff Road, Tewksbury , Massachusetts 01876 , United States.

Abstract

Detailed studies of lipids in biological systems, including their role in cellular structure, metabolism, and disease development, comprise an increasingly prominent discipline called lipidomics. However, the conventional lipidomics tools, such as mass spectrometry, cannot investigate lipidomes until they are extracted, and thus they cannot be used for probing the lipid distribution nor for studying in live cells. Furthermore, conventional techniques rely on the lipid extraction from relatively large samples, which averages the data across the cellular populations and masks essential cell-to-cell variations. Further advancement of the discipline of lipidomics critically depends on the capability of high-resolution lipid profiling in live cells and, potentially, in single organelles. Here we report a micro-Raman assay designed for single-organelle lipidomics. We demonstrate how Raman microscopy can be used to measure the local intracellular biochemical composition and lipidome hallmarks-lipid concentration and unsaturation level, cis/trans isomer ratio, sphingolipids and cholesterol levels in live cells-with a sub-micrometer resolution, which is sufficient for profiling of subcellular structures. These lipidome data were generated by a newly developed biomolecular component analysis software, which provides a shared platform for data analysis among different research groups. We outline a robust, reliable, and user-friendly protocol for quantitative analysis of lipid profiles in subcellular structures. This method expands the capabilities of Raman-based lipidomics toward the analysis of single organelles within either live or fixed cells, thus allowing an unprecedented measure of organellar lipid heterogeneity and opening new quantitative ways to study the phenotypic variability in normal and diseased cells.

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