Single-Cell Proteomics of Human Peripheral Blood Mononuclear Cells Exceeding 600 Cells per Day

Single-cell proteomic (scProteomic) measurements of peripheral blood mononuclear cells (PBMCs) are of considerable value in human health, given their involvement in the maintenance of healthy and diseased states. However, the high heterogeneity and relatively small size of immune cell types demand maximal throughput and sensitivity in proteomic measurements that have yet to be fully realized. Here, we describe an approach that addresses sensitivity and throughput through the implementation of Real-Time spectral Library Searching (RTLS), TMTpro 32-plex labelling, an updated nested-nanodroplet processing in One pot for Trace Samples (N2), and a dual-column liquid chromatography system. By prioritizing tandem mass spectrometry (MS2) features with high similarity to library spectra, RTLS enables greater identification depth and feature reproducibility than a standard shotgun MS2 approach in low-input and single-cell samples. The platform permitted 660 single PBMCs to be measured per day, with an average of 750 protein identifications per cell and 1,648 proteins in total, achieving the necessary throughput and depth to characterize immune cell populations. Application of this scProteomic method and a new cell typing informatics approach to 2,130 PBMCs enabled the identification of both major and low-frequency cell types (~1-2%), as well as associated proteomic markers.

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Publication Details

Journal
bioRxiv (Cold Spring Harbor Laboratory)
Published
2026-02-03
DOI
https://doi.org/10.64898/2026.02.01.703169
Primary Topic
Advanced Proteomics Techniques and Applications
Type
article
Field-Weighted Citation Impact
0.00

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article

Single-Cell Proteomics of Human Peripheral Blood Mononuclear Cells Exceeding 600 Cells per Day

Pranav Dawar, Fengchao Yu, Julie M. Fortier, Andrey Liyu et al.
bioRxiv (Cold Spring Harbor Laboratory)
Advanced Proteomics Techniques and Applications
article

Single-Cell Proteomics of Human Peripheral Blood Mononuclear Cells Exceeding 600 Cells per Day

Pranav Dawar, Fengchao Yu, Julie M. Fortier, Andrey Liyu, Ravi Vij, Heather M Olson, Reyka Jayasinghe, Rashmi Kumar, Li Ding, Ljiljana Pasa-Tolic, Ying Zhu, Daniel J Orton, Liang Chen, James M Fulcher, Yumi Kwon, Patricia Miller, Alexey I Nesvizhskii, Sarah M Williams
article en

Abstract

Single-cell proteomic (scProteomic) measurements of peripheral blood mononuclear cells (PBMCs) are of considerable value in human health, given their involvement in the maintenance of healthy and diseased states. However, the high heterogeneity and relatively small size of immune cell types demand maximal throughput and sensitivity in proteomic measurements that have yet to be fully realized. Here, we describe an approach that addresses sensitivity and throughput through the implementation of Real-Time spectral Library Searching (RTLS), TMTpro 32-plex labelling, an updated nested-nanodroplet processing in One pot for Trace Samples (N2), and a dual-column liquid chromatography system. By prioritizing tandem mass spectrometry (MS2) features with high similarity to library spectra, RTLS enables greater identification depth and feature reproducibility than a standard shotgun MS2 approach in low-input and single-cell samples. The platform permitted 660 single PBMCs to be measured per day, with an average of 750 protein identifications per cell and 1,648 proteins in total, achieving the necessary throughput and depth to characterize immune cell populations. Application of this scProteomic method and a new cell typing informatics approach to 2,130 PBMCs enabled the identification of both major and low-frequency cell types (~1-2%), as well as associated proteomic markers.

bioRxiv (Cold Spring Harbor Laboratory)
Pacific Northwest National Laboratory (US), Washington University in St. Louis (US), University of Michigan (US), Environmental Molecular Sciences Laboratory (US), Genomic Health (United States) (US)
U.S. Department of Energy, National Institutes of Health, Office of Science, Biological and Environmental Research
Openalex Percentile: Top 70%
Advanced Proteomics Techniques and Applications
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