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Cited by 493Advanced Proteomics Techniques and ApplicationsSingle-cell and spatial transcriptomicsMass Spectrometry Techniques and Applications

Single-cell proteomic and transcriptomic analysis of macrophage heterogeneity using SCoPE2

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Specht, Harrison, Emmott, Edward, Petelski, Aleksandra A., Huffman, R. Gray, Perlman, David H., Serra, Marco, Kharchenko, Peter, Koller, Antonius +1 more·2021·Genome Biology
DOI 10.1186/s13059-021-02267-5PMC PMC7839219

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Abstract

Background: Macrophages are innate immune cells with diverse functional and molecular phenotypes. This diversity is largely unexplored at the level of single-cell proteomes because of the limitations of quantitative single-cell protein analysis. Results: To overcome this limitation, we develop SCoPE2, which substantially increases quantitative accuracy and throughput while lowering cost and hands-on time by introducing automated and miniaturized sample preparation. These advances enable us to analyze the emergence of cellular heterogeneity as homogeneous monocytes differentiate into macrophage-like cells in the absence of polarizing cytokines. SCoPE2 quantifies over 3042 proteins in 1490 single monocytes and macrophages in 10 days of instrument time, and the quantified proteins allow us to discern single cells by cell type. Furthermore, the data uncover a continuous gradient of proteome states for the macrophages, suggesting that macrophage heterogeneity may emerge in the absence of polarizing cytokines. Parallel measurements of transcripts by 10× Genomics suggest that our measurements sample 20-fold more protein copies than RNA copies per gene, and thus, SCoPE2 supports quantification with improved count statistics. This allowed exploring regulatory interactions, such as interactions between the tumor suppressor p53, its transcript, and the transcripts of genes regulated by p53. Conclusions: Even in a homogeneous environment, macrophage proteomes are heterogeneous. This heterogeneity correlates to the inflammatory axis of classically and alternatively activated macrophages. Our methodology lays the foundation for automated and quantitative single-cell analysis of proteins by mass spectrometry and demonstrates the potential for inferring transcriptional and post-transcriptional regulation from variability across single cells.

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  • Single-cell proteomics still faces limitations such as lower proteome coverage and higher per-sample cost.

    “However, single-cell proteomics still faces limitations such as lower proteome coverage and higher per-sample cost184,185.”

    From Artificial intelligence-driven multi-omics approaches in Alzheimer's disease: Progress, challenges, and future directions (2025) · cites this paper as [185]

    The Introduction says comprehensive protein quantification in single cells remains limited, supporting the coverage limitation. It also says earlier SCoPE-MS methods fell short on cost, but the Discussion describes SCoPE2 as affordable and does not establish the claimed higher per-sample cost relative to another technology. (LLM, conf=0.83)

    Experimental — accuracy not yet measured

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Cited by

Sorted by citations

Authors
Specht, H., Emmott, E., Petelski, A. A., Huffman, R. G., Perlman, D. H., Serra, M., Kharchenko, P., Koller, A., & Slavov, N.
Affiliations
  • Northeastern University (US)
  • Merck & Co., Inc., Rahway, NJ, USA (United States) (US)
  • Harvard University (US)
Corresponding author
Specht, Harrison
ORCID
Venue
Genome Biology
Publisher
Springer Science and Business Media LLC
Published
2021-01-27
Volume
22
Issue
1
Pages
50-50
ISSN
  • 1465-6906 (ISSN-L)
  • 1474-760X
DOI
10.1186/s13059-021-02267-5
PMC
PMC7839219
OpenAlex
W3121536135
Cited by
493
References
3
Citations by year
2026: 63 · 2025: 60 · 2024: 102 · 2023: 113 · 2022: 81 · 2021: 70 · 2020: 2 · 2019: 1
FWCI
34.14
Type
journal article
Language
en
Open access
Licence
Locations
  • Genome biology (publishedVersion, cc-by)
  • PubMed Central (publishedVersion, cc-by)
  • PubMed (publishedVersion)
  • DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
Funders
  • National Institute of General Medical Sciences (1DP2GM123497)
  • Merck Sharp and Dohme (Merck Exploratory Science Center Fellowship)
  • Sanofi Genzyme (iAward)
  • Paul G. Allen Family Foundation (Allen Distinguished Investigator award)
Topics
  • Physical Sciences › Chemistry › Spectroscopy › Advanced Proteomics Techniques and Applications
  • Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Single-cell and spatial transcriptomics
  • Physical Sciences › Chemistry › Spectroscopy › Mass Spectrometry Techniques and Applications
Keywords
macrophage heterogeneity, single-cell proteomics, monocyte differentiation, macrophage polarization, p53, post-transcriptional regulation, transcriptome, automated sample preparation
MeSH terms
Cell Line, Dietary Proteins, Gene Expression Regulation, Humans, Macrophage Activation, Macrophages, Monocytes, Phenotype, Cytokines, Proteome, Gene Expression Profiling, Proteomics, HEK293 Cells, Transcriptome

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