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Single-cell lipidomics with high structural specificity by mass spectrometry

Abstract

Single-cell analysis is critical to revealing cell-to-cell heterogeneity that would otherwise be lost in ensemble analysis. Detailed lipidome characterization for single cells is still far from mature, especially when considering the highly complex structural diversity of lipids and the limited sample amounts available from a single cell. We report the development of a general strategy enabling single-cell lipidomic analysis with high structural specificity. Cell fixation is applied to retain lipids in the cell during batch treatments prior to single-cell analysis. In addition to tandem mass spectrometry analysis revealing the class and fatty acyl-chain for lipids, batch photochemical derivatization and single-cell droplet treatment are performed to identify the C=C locations and sn-positions of lipids, respectively. Electro-migration combined with droplet-assisted electrospray ionization enables single-cell mass spectrometry analysis with easy operation but high efficiency in sample usage. Four subtypes of human breast cancer cells are correctly classified through quantitative analysis of lipid C=C location or sn-position isomers in ~160 cells. Most importantly, the single-cell deep lipidomics strategy successfully discriminates gefitinib-resistant cells from a population of wild-type human lung cancer cells (HCC827), highlighting its unique capability to promote precision medicine.

Highlights
  • A strategy enabling single-cell lipidomic analysis with high structural specificity is developed, which integrates cell fixation, batch photochemical derivatization, and single-cell droplet treatment for the identification of lipid C=C locations and sn-positions.
  • By employing electro-migration and droplet-assisted electrospray ionization, it enables user-friendly and highly efficient single- cell mass spectrometry analysis, thereby promoting in-depth investigations of the lipidome at the single-cell level.
  • The strategy successfully classifies four subtypes of human breast cancer cells and distinguishes gefitinib-resistant cells from wild-type lung cancer cells through analyzing lipid isomers.
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Application Details

Nat Commun. 2021 May 17;12(1):2869. (IF: 14.7 )

DOI: 10.1038/s41467-021-23161-5.

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