High-Throughput Single Cell Proteomics Enabled by Multiplex Isobaric Labeling in a Nanodroplet Sample Preparation Platform

Abstract

Effective extension of mass spectrometry-based proteomics to single cells remains challenging. Herein we combined microfluidic nanodroplet technology with tandem mass tag (TMT) isobaric labeling to significantly improve analysis throughput and proteome coverage for single mammalian cells. Isobaric labeling facilitated multiplex analysis of single cell-sized protein quantities to a depth of ∼1 600 proteins with a median CV of 10.9% and correlation coefficient of 0.98. To demonstrate in-depth high throughput single cell analysis, the platform was applied to measure protein expression in 72 single cells from three murine cell populations (epithelial, immune, and endothelial cells) in <2 days instrument time with over 2 300 proteins identified. Principal component analysis grouped the single cells into three distinct populations based on protein expression with each population characterized by well-known cell-type specific markers. Our platform enables high throughput and unbiased characterization of single cell heterogeneity at the proteome level.

Figure 1.

Workflow of the nanoPOTS-TMT-based single cell proteomics platform.

Figure 2.

Evaluation of isobaric-labelling-based quantitative proteomics using single-cell-sized (0.2 ng) HeLa digest. TMT channels from 126 to 129C were used to label 0.2-ng digest and channel 131 was used for 10 ng digest as boosting samples. Channel 130N and 130C were left empty. (A) Distribution of protein intensities across all TMT channels in one TMT set. (B) Pairwise correlation of protein intensities across the 7 single-cell level protein digests. (C) The coefficients of variation of protein intensities within each TMT set, between two TMT sets, and two sets after batch correction. (D) Venn diagrams showing the overlap of peptide and protein identifications in 0.2-ng protein digests between TMT sets.

Figure 3.

Effect of boosting ratios (0, 25 ×, and 250 ×) on the quantification performance of single cell proteomics. (A) Total number of identified peptides. (B) Total number of identified proteins; (C) Unsupervised PCA showing cell grouping based on protein expressions in single cultured murine cells (C10, Raw, and SVEC).

Figure 4.

(A) Unsupervised PCA showing the single cell grouping based on protein expression. (B) Heatmap of proteins enriched in each cell population (pairwise t.test<0.05). (C) comparison of cell type specific marker abundances across the three cell populations.