Advancing Single-cell Proteomics with the Spectral Library-based Multiplex Segmented SIM Platform (SLB-SIM)

Dissecting the proteome of individual cell types at single-cell resolution is challenging but vital for advancing biomedicine. MS-based single-cell proteomics enables unbiased protein profiling but faces hurdles from low protein amounts and a lack of amplification strategies.

We developed an integrated single-cell proteomics platform combining SLB-msSIM with DIRECT sample preparation, enabling highly sensitive and robust analysis of cellular heterogeneity in cancer. Individual cells were lysed via freeze-thaw cycles and sonication, followed by reduction, alkylation, and overnight tryptic digestion. Peptides were analyzed on a Q Exactive HF-X Orbitrap coupled to an UltiMate 3000 RSLCnano. SLB-msSIM applies multiplex precursor isolation with high-resolution MS1 detection (multiplexing degree 17, m/z 400–1250). Bulk DDA data generated a spectral library. Single-cell data were processed in Skyline, with peptide ID based on precursor mass, isotopic profile, and retention time. Protein quantification was achieved by summing normalized peptide intensities, and outliers were removed using the median absolute deviation method.

SLB-msSIM enabled sensitive single-cell proteomics, identifying ~3,700–4,300 proteins per cell with high reproducibility. Over 88% of proteins were consistently detected across cells. Pancreatic cancer cells showed higher and more heterogeneous protein content than normal cells, reflecting metastatic diversity and upregulated cancer hallmarks. In TGFβ1-induced EMT experiments, single-cell profiling captured dynamic proteome changes and partial EMT reversal, demonstrating the platform’s ability to resolve heterogeneity and functional differences.

SLB-msSIM identifies ~3,700–4,300 proteins per cell, revealing functional heterogeneity, dynamic proteome shifts, and single-cell trajectories in cancer and EMT models. This robust platform advances understanding of cellular diversity and offers insights into cancer biology and therapeutic strategies.