High-throughput label-free single-cell proteomics enabled by multicolumn NanoLC.
5 affiliations
- 1Department of Chemistry and Biochemistry, Brigham Young University, Provo, UT, USA
- 2Brigham Young University
- 3MicrOmics Technologies
- 4MicrOmics Technologies, LLC, Spanish Fork, UT, USA
- 5Department of Chemistry and Biochemistry, Brigham Young University, Provo, UT, USA. [email protected]
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.
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BibTeX
@article{wang2026highthroughput,
title = {{High-throughput label-free single-cell proteomics enabled by multicolumn NanoLC.}},
author = {Chao Wang and Hsien‐Jung L. Lin and Siqi Huang and Garrett Haynie and Kenneth Triggs and Ella E. Norton and R. J. S. Miercort and Yen-Jou Chang and David V. Hansen and Thy Truong and Xiaofeng Xie and Ryan Kelly},
journal = {Nature communications},
year = {2026},
month = sep,
doi = {10.1038/s41467-026-78059-x},
url = {https://europepmc.org/article/MED/42918804},
note = {CC BY-NC-ND},
}
RIS
TY - JOUR
TI - High-throughput label-free single-cell proteomics enabled by multicolumn NanoLC.
AU - Chao Wang
AU - Hsien‐Jung L. Lin
AU - Siqi Huang
AU - Garrett Haynie
AU - Kenneth Triggs
AU - Ella E. Norton
AU - R. J. S. Miercort
AU - Yen-Jou Chang
AU - David V. Hansen
AU - Thy Truong
AU - Xiaofeng Xie
AU - Ryan Kelly
PY - 2026
DA - 2026/09/23
JO - Nature communications
DO - 10.1038/s41467-026-78059-x
UR - https://europepmc.org/article/MED/42918804
AB - 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.
SN - 2041-1723
ER -