High-throughput label-free single-cell proteomics enabled by multicolumn NanoLC

Abstract

Mass spectrometry (MS)-based single-cell proteomics (SCP) enables proteome-wide analysis at single-cell resolution, offering insights into cellular heterogeneity, biological processes, and disease mechanisms. However, conventional nanoLC-MS workflows are constrained by long gradients and low throughput, limiting their application to small cohorts. Here, we present a multicolumn nanoLC–MS platform that achieves 5-minute separation windows with 100% duty cycles at ~100 nL/min, enabling the analysis of up to 288 single cells per day. The system provides stable peptide separation, negligible carryover, and robust retention-time reproducibility across nearly 1200 consecutive injections. We successfully analyze more than 4000 samples at nearly 288 samples per day (SPD) throughput. The platform identifies ~5000 proteins per 250 pg digest injection and an average of ~4000 proteins per single HeLa cell with maxima exceeding 5100, which is comparable to state-of-the-art longer-gradient workflows. Quantitative benchmarking with mixed-species standards confirm the quantitative accuracy is largely maintained during extended acquisition. Applying the workflow to 783 LPS-treated RAW264.7 macrophages reveals substantial cellular heterogeneity under a uniform inflammatory stimulus. Together, these results establish a robust and scalable platform for high-throughput SCP, enabling thousands of single-cell analyses within a single study while maintaining deep proteome coverage and biological interpretability. Single-cell proteomics reveals cellular diversity, but the throughput has been limited. Here, the authors develop a high-throughput multicolumn nanoLC system that analyzes up to 288 cells per day, identifies ~ 4,000 proteins per cell and profiles inflammatory responses in macrophages.

The authors' abstract, as published at the source. Nature Communications, 2026 · DOI ↗