Single Cell Profiling Using Ionic Liquid Matrix-Enhanced Secondary Ion Mass Spectrometry for Neuronal Cell Type Differentiation

Thanh D. Do, Troy J. Comi, Sage J.B. Dunham, Stanislav S. Rubakhin, Jonathan V. Sweedler

Research output: Contribution to journalArticlepeer-review


A high-throughput single cell profiling method has been developed for matrix-enhanced-secondary ion mass spectrometry (ME-SIMS) to investigate the lipid profiles of neuronal cells. Populations of cells are dispersed onto the substrate, their locations determined using optical microscopy, and the cell locations used to guide the acquisition of SIMS spectra from the cells. Up to 2,000 cells can be assayed in one experiment at a rate of 6 s per cell. Multiple saturated and unsaturated phosphatidylcholines (PCs) and their fragments are detected and verified with tandem mass spectrometry from individual cells when ionic liquids are employed as a matrix. Optically guided single cell profiling with ME-SIMS is suitable for a range of cell sizes, from Aplysia californica neurons larger than 75 μm to 7-μm rat cerebellar neurons. ME-SIMS analysis followed by t-distributed stochastic neighbor embedding of peaks in the lipid molecular mass range (m/z 700-850) distinguishes several cell types from the rat central nervous system, largely based on the relative proportions of four dominant lipids, PC(32:0), PC(34:1), PC(36:1), and PC(38:5). Furthermore, subpopulations within each cell type are tentatively classified consistent with their endogenous lipid ratios. The results illustrate the efficacy of a new approach to classify single cell populations and subpopulations using SIMS profiling of lipid and metabolite contents. These methods are broadly applicable for high throughput single cell chemical analyses.

Original languageEnglish (US)
Pages (from-to)3078-3086
Number of pages9
JournalAnalytical Chemistry
Issue number5
StatePublished - Mar 7 2017

ASJC Scopus subject areas

  • Analytical Chemistry


Dive into the research topics of 'Single Cell Profiling Using Ionic Liquid Matrix-Enhanced Secondary Ion Mass Spectrometry for Neuronal Cell Type Differentiation'. Together they form a unique fingerprint.

Cite this