Evidence map›Paper›PMID 41333401›Full record

ArticleResearch square2025

High-Throughput Label-free Single-Cell Proteomics Enabled by Multicolumn NanoLC with a 5-min Cycle Time.

Chao Wang, Hsien-Jung L Lin, Siqi Huang, Garrett D Haynie, Kenneth S Triggs, YenJou Chang, David V Hansen, Thy Truong, Xiaofeng Xie, Ryan T Kelly

Abstract readPreprint
In one paragraph

Article in Research square, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

10 authors.

Chao WangDepartment of Chemistry and Biochemistry, Brigham Young University, Provo, Utah 84602, United States.
Hsien-Jung L LinDepartment of Chemistry and Biochemistry, Brigham Young University, Provo, Utah 84602, United States.ORCID 0000-0003-4704-3692
Siqi HuangDepartment of Chemistry and Biochemistry, Brigham Young University, Provo, Utah 84602, United States.
Garrett D HaynieDepartment of Chemistry and Biochemistry, Brigham Young University, Provo, Utah 84602, United States.ORCID 0009-0004-4547-5330
Kenneth S TriggsDepartment of Chemistry and Biochemistry, Brigham Young University, Provo, Utah 84602, United States.ORCID 0009-0001-5091-7058
YenJou ChangDepartment of Chemistry and Biochemistry, Brigham Young University, Provo, Utah 84602, United States.
David V HansenDepartment of Chemistry and Biochemistry, Brigham Young University, Provo, Utah 84602, United States.
Thy TruongMicrOmics Technologies, LLC, Spanish Fork, Utah 84660, United States.
Xiaofeng XieMicrOmics Technologies, LLC, Spanish Fork, Utah 84660, United States.
Ryan T KellyDepartment of Chemistry and Biochemistry, Brigham Young University, Provo, Utah 84602, United States.

Funding

Mayo Clinic Center for Clinical ProteomicsU01CA271410 · NCI · MAYO CLINIC ROCHESTER · PI Rafael Fonseca, AKHILESH PANDEY · 2022 to 2026
$5.3M
Structure and function of chloride channels and transportersR01GM085232 · NIGMS · WEILL MEDICAL COLL OF CORNELL UNIV · PI ACCARDI, ALESSIO · 2009 to 2013
$1.7M
Advanced Sample Preparation, Separation and Multiplexed Analysis for In-Depth Proteome Profiling of >1000 Single Cells Per DayR01CA279074 · NCI · BRIGHAM YOUNG UNIVERSITY · PI KELLY, RYAN T · 2023 to 2025
$1.6M
NCI NIH HHS R01 CA279074NCI NIH HHS U01 CA271410NIGMS NIH HHS R01 GM085232
6 · The paper itself

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 large 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 with minimal additional hardware. The system provides stable peptide separation, negligible carryover, and robust retention-time reproducibility across 2,000 consecutive injections. Over the course of this study, we successfully analyzed more than 4,000 samples at nearly 288 samples per day (SPD) throughput. The platform identified ~4,400 proteins per 250 pg digest injection and an average of ~3,200 proteins per single HeLa cell with maxima exceeding 4,300, which is comparable to state-of-the-art longer-gradient workflows. Quantitative benchmarking with mixed-species standards confirmed accurate measurements across ~6,000 proteins. The workflow distinguished proteome profiles across hundreds of single cells, and profiling of RAW264.7 macrophages revealed LPS-induced markers and macrophage activation pathways. Together, these results establish a robust and scalable platform for high-throughput SCP, demonstrating the feasibility of thousands of single-cell analyses within a single study while maintaining deep proteome coverage and biological interpretability.

Identifiers

PMID41333401
PMCPMC12668145

What OpenQuestion holds

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.