Back

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

Fulcher, J. M.; Kwon, Y.; Dawar, P.; Kumar, R.; Williams, S. M.; Miller, P.; Liyu, A.; Chen, L.; Orton, D. J.; Olson, H. M.; Yu, F.; Nesvizhskii, A. I.; Fortier, J.; Vij, R.; Jayasinghe, R.; Ding, L.; Zhu, Y.; Pasa-Tolic, L.

2026-02-03 immunology
10.64898/2026.02.01.703169 bioRxiv
Show 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.

Matching journals

The top 6 journals account for 50% of the predicted probability mass.

1
Molecular & Cellular Proteomics
158 papers in training set
Top 0.1%
22.9%
2
Nature Communications
4913 papers in training set
Top 17%
10.3%
3
PLOS ONE
4510 papers in training set
Top 27%
6.5%
4
Journal of Proteome Research
215 papers in training set
Top 0.6%
4.9%
5
Alzheimer's & Dementia
143 papers in training set
Top 1%
4.4%
6
Nature Methods
336 papers in training set
Top 3%
3.7%
50% of probability mass above
7
Analytica Chimica Acta
17 papers in training set
Top 0.2%
3.1%
8
Frontiers in Plant Science
240 papers in training set
Top 3%
2.8%
9
Cell Systems
167 papers in training set
Top 5%
2.5%
10
Analytical Chemistry
205 papers in training set
Top 1%
2.1%
11
Biosensors and Bioelectronics
52 papers in training set
Top 0.6%
2.1%
12
The Plant Journal
197 papers in training set
Top 2%
1.7%
13
Genome Biology
555 papers in training set
Top 4%
1.7%
14
Bioinformatics
1061 papers in training set
Top 7%
1.7%
15
Communications Biology
886 papers in training set
Top 12%
1.4%
16
Scientific Reports
3102 papers in training set
Top 66%
1.2%
17
Genomics, Proteomics & Bioinformatics
171 papers in training set
Top 4%
1.2%
18
EMBO Molecular Medicine
85 papers in training set
Top 3%
1.2%
19
Advanced Science
249 papers in training set
Top 15%
1.0%
20
ACS Central Science
66 papers in training set
Top 2%
0.9%
21
ACS Nano
99 papers in training set
Top 3%
0.8%
22
eLife
5422 papers in training set
Top 55%
0.8%
23
iScience
1063 papers in training set
Top 31%
0.8%
24
Frontiers in Immunology
586 papers in training set
Top 7%
0.8%
25
eBioMedicine
130 papers in training set
Top 5%
0.7%
26
Nature Biotechnology
147 papers in training set
Top 9%
0.5%
27
Genome Medicine
154 papers in training set
Top 10%
0.5%
28
PROTEOMICS
35 papers in training set
Top 1%
0.5%
29
Molecular Systems Biology
142 papers in training set
Top 2%
0.5%
30
Journal of Clinical Microbiology
120 papers in training set
Top 2%
0.5%