High-throughput Single-cell Proteomics Enabled by an Integrated Hyperplexing and Automatic Labelling Approach without Fractionation

Abstract

Single-cell proteomics (scProteomics) enables comprehensive analysis of protein composition, expression and functions at the single-cell level. While label-free techniques have generated promising results, achieving high-throughput scProteomics remains a substantial challenge. In this study, we present an approach that increases scProteomics throughput by approximately 30-fold through the true integration of isobaric tags (IBT) with tandem mass tags (TMT), a method we term Integral-Hyperplex. Due to remarkable differences in signal response between TMT16 and IBT16 reporter ions, we implemented two normalization strategies to ensure accurate and integrated quantification: (1) the inclusion of a normalization channel in both IBT and TMT groups to serve as internal standards; and (2) the generation of protein-specific conversion factors between IBT16 and TMT16 signals. We validated the quantification accuracy of the Integral-Hyperplex method by labeling HeLa digests at varying ratios. Furthermore, we demonstrated fully automated labeling on the active-matrix digital microfluidics chip, consuming only 12 nL of labeling reagent per single cell and with a reaction volume as low as 20 nL. Our approach was validated through proof-of-principle quantification experiments across three types of single cells. Approximately 2,000 protein groups were quantified per cell, and the three cell types can be well clustered, confirming the reliability of the Integral-Hyperplex approach. Approximately 300 samples can be analyzed per day due to insufficient resolution of timsTOF SCP. Throughput can be further enhanced using TMT32, additional labeling reagents, and more advanced mass spectrometers such as Orbitrap Astral and timsTOF Ultra 2, and our approach is theoretically capable of analyzing up to [~]2,000 single cells per day.