FACS-assisted single-cell lipidome analysis of phosphatidylcholines and sphingomyelins in cells of different lineages

Abstract

Recent advances in single-cell genomics and transcriptomics technologies have transformed our understanding of cellular heterogeneity in growth, development, ageing, and disease; however, methods for single-cell lipidomics have comparatively lagged behind in development. We have developed a method for the detection and quantification of a wide range of phosphatidylcholine and sphingomyelin species from single cells that combines fluorescence-assisted cell sorting with automated chip-based nanoESI and shotgun lipidomics. We show herein that our method is capable of quantifying more than 50 different phosphatidylcholine and sphingomyelin species from single cells and can easily distinguish between cells of different lineages or cells treated with exogenous fatty acids. Moreover, our method can detect more subtle differences in the lipidome between cell lines of the same cancer type. Our approach can be run in parallel with other single-cell technologies to deliver near-complete, high-throughput multi-omics data on cells with a similar phenotype and has the capacity to significantly advance our current knowledge on cellular heterogeneity.

Keywords: glycerophospholipids; lipidomics; lipids; mass spectrometry; nanoelectrospray ionization; omega-3 fatty acids; prostate cancer; shotgun lipidomics; single-cell heterogeneity; sphingolipids.

Fig. 1

Flowchart summarizing the method used for preparation of bulk cell lipid extracts and FACS-obtained cells from C2C12 and HepG2 cells. FACS, fluorescence-assisted cell sorting.

Fig. 2

Precursor ion scan of m/z 184 obtained from fifty (A, C, n = 3 biological replicates) and singly isolated (B, D, n = 7) C2C12 cells obtained by fluorescence-assisted cell sorting. Cells were grown under normal culture conditions (A, B) or cultured overnight in the presence of 50 μM docosahexaenoic acid (DHA, C, D). Signal-to-noise (S/N) was calculated using the S-to-N Script in Analyst (v1.6.3, SCIEX, Framingham, MA). Internal standards (ISTD), phosphatidylcholine (PC) 17:0/17:0, & dihydrosphingomyelin (DHSM) 12:0 were added at a concentration of 1000 and 1.38 fmol for fifty and single cells, respectively.

Fig. 3

Heatmaps of phosphatidylcholine (PC) and sphingomyelin (SM) species detected in single-isolated (A) C2C12 and (B) HepG2 cells. Cells were cultured under normal conditions (CON) or after overnight culture with 50 μM docosahexaenoic acid (DHA). Lipids were quantified from internal standards as described under method details and are present as relative quantified amount (fmol).

Fig. 4

A: t-distributed stochastic neighbor embedding (t-SNE) of all single-cell data from both C2C12 & HepG2 cells grown in both control (CON) and docosahexaenoic acid (DHA)-supplemented media. B: Principal components analysis of the same data. Loadings plots for principal component 1 (C) and 2 (D) showing correlation between phospholipid species and component.

Fig. 5

Comparison of phosphatidylcholine (PC) and sphingomyelin (SM) species detected in either bulk cell extract or fifty cells obtained by fluorescence-assisted cell sorting (FACS) for both (A) C2C12 cells and (B) HepG2 cells treated grown in control (CON)- or docosahexaenoic acid (DHA)-supplemented media. Lipids shown are present at >1% relative abundance in either sample, values are mean±SEM (n = 3). Welch t test, ∗ P < 0.05. Statistical output from all PC and SM species detected is available in the Supporting information (supplemental Table S2).

Fig. 6

Analysis of phosphatidylcholine (PC) and sphingomyelin (SM) species from four different prostate cell lines, including cancerous (DU145, PC3, & LNCaP) and nontumorigenic (PNT1) cells: (A) the ten most abundant PC species detected from the four prostate cell lines. Data was acquired from fifty cells obtained by fluorescence-assisted cell sorting (n = 3) and expressed as a percent of total PC (±SEM). B: PC and SM species detected from single cells across the four prostate cell lines (n = 18). Data are expressed as relative intensity within each cell. C: t-distributed stochastic neighbor embedding (tSNE) plot of the single-cell data acquired from the four prostate cell lines.