Evidence map›Paper›PMID 33504367›Full record

ArticleGenome biology2021

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

Harrison Specht, Edward Emmott, Aleksandra A Petelski, R Gray Huffman, David H Perlman, Marco Serra, Peter Kharchenko, Antonius Koller, Nikolai Slavov

Open access · goldAbstract read
In one paragraph

Article in Genome biology, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 308 papers.

0numbers the graph read from it
0cells of the map it votes in
308citing papers in PubMed
34.8field-weighted citation impact, top 1% of its field
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

308 citing papers in PubMed, 496 citations in OpenAlex.

  1. Review
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  5. The M1/M2 Test System for Determining Macrophage Phenotypes.International journal of molecular sciences · 2026
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  19. Single-Cell Protein Assays in Context: From 2D to 3D and In Situ Analysis.Annual review of analytical chemistry (Palo Alto, Calif.) · 2026
    Review
  20. Review

248 more citing papers are in PubMed but not listed here.

4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

9 authors at 3 institutions in 3 countries.

Harrison SpechtDepartment of Bioengineering and Barnett Institute, Northeastern University, Boston, MA, 02115, USA. hms89@cornell.edu.
Edward EmmottDepartment of Bioengineering and Barnett Institute, Northeastern University, Boston, MA, 02115, USA.
Aleksandra A PetelskiDepartment of Bioengineering and Barnett Institute, Northeastern University, Boston, MA, 02115, USA.
R Gray HuffmanDepartment of Bioengineering and Barnett Institute, Northeastern University, Boston, MA, 02115, USA.
David H PerlmanDepartment of Bioengineering and Barnett Institute, Northeastern University, Boston, MA, 02115, USA.
Marco SerraDepartment of Biomedical Informatics, Harvard Medical School, Boston, MA, 02115, USA.
Peter KharchenkoDepartment of Biomedical Informatics, Harvard Medical School, Boston, MA, 02115, USA.
Antonius KollerDepartment of Bioengineering and Barnett Institute, Northeastern University, Boston, MA, 02115, USA.
Nikolai SlavovDepartment of Bioengineering and Barnett Institute, Northeastern University, Boston, MA, 02115, USA. nslavov@alum.mit.edu.ORCID 0000-0003-2035-1820
Northeastern University · USHarvard University · USMerck & Co., Inc., Rahway, NJ, USA (United States) · US

Funding

Ribosome-mediated translational regulation during stem cell differentiationDP2GM123497 · NIGMS · NORTHEASTERN UNIVERSITY · PI SLAVOV, NIKOLAI · 2016 to 2016
$2.4M
Discovering proteins that explain single-cell heterogeneity in fibrillar migrationR21CA246150 · NCI · NORTHEASTERN UNIVERSITY · PI ASTHAGIRI, ANAND R · 2020 to 2021
$404k
NCI NIH HHS R21 CA246150NIGMS NIH HHS DP2 GM123497
6 · The paper itself

Abstract

backgroundMacrophages 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.

resultsTo 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.

conclusionsEven 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.

Indexed as

ProteomicsTranscriptomeCell LineCytokinesDietary ProteinsGene Expression ProfilingGene Expression RegulationHEK293 CellsHumansMacrophage ActivationMacrophagesMonocytesPhenotypeProteomeCytokinesDietary ProteinsProteomesingle cell proteins

Identifiers

PMID33504367
PMCPMC7839219
OpenAlexW3121536135

What Socratic holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

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 Socratic graph.