Literature DB >> 33504367

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

Harrison Specht1, Edward Emmott2,3, Aleksandra A Petelski2, R Gray Huffman2, David H Perlman2,4, Marco Serra5, Peter Kharchenko5, Antonius Koller2, Nikolai Slavov6.   

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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Year:  2021        PMID: 33504367      PMCID: PMC7839219          DOI: 10.1186/s13059-021-02267-5

Source DB:  PubMed          Journal:  Genome Biol        ISSN: 1474-7596            Impact factor:   13.583


  45 in total

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Authors:  Alexander Franks; Edoardo Airoldi; Nikolai Slavov
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10.  SCoPE-MS: mass spectrometry of single mammalian cells quantifies proteome heterogeneity during cell differentiation.

Authors:  Bogdan Budnik; Ezra Levy; Guillaume Harmange; Nikolai Slavov
Journal:  Genome Biol       Date:  2018-10-22       Impact factor: 13.583

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  53 in total

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