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Single-cell proteomic and transcriptomic analysis of macrophage heterogeneity

View ORCID ProfileHarrison Specht, View ORCID ProfileEdward Emmott, Aleksandra A. Petelski, R. Gray Huffman, David H. Perlman, Marco Serra, Peter Kharchenko, Antonius Koller, View ORCID ProfileNikolai Slavov
doi: https://doi.org/10.1101/665307
Harrison Specht
1Department of Bioengineering and Barnett Institute, Northeastern University, Boston, MA 02115, USA
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Edward Emmott
1Department of Bioengineering and Barnett Institute, Northeastern University, Boston, MA 02115, USA
2Centre for Proteome Research, Department of Biochemistry, University of Liverpool, Liverpool, L69 7ZB, UK
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Aleksandra A. Petelski
1Department of Bioengineering and Barnett Institute, Northeastern University, Boston, MA 02115, USA
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R. Gray Huffman
1Department of Bioengineering and Barnett Institute, Northeastern University, Boston, MA 02115, USA
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David H. Perlman
1Department of Bioengineering and Barnett Institute, Northeastern University, Boston, MA 02115, USA
3Merck Exploratory Sciences Center, Merck Sharp & Dohme Corp., 320 Bent St. Cambridge, MA 02141
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Marco Serra
4Department of Biomedical Informatics, Harvard Medical School, Boston, MA 02115, USA
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Peter Kharchenko
4Department of Biomedical Informatics, Harvard Medical School, Boston, MA 02115, USA
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Antonius Koller
1Department of Bioengineering and Barnett Institute, Northeastern University, Boston, MA 02115, USA
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Nikolai Slavov
1Department of Bioengineering and Barnett Institute, Northeastern University, Boston, MA 02115, USA
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  • ORCID record for Nikolai Slavov
  • For correspondence: nslavov@alum.mit.edu
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Abstract

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 limitations of quantitative single-cell protein analysis. To overcome this limitation, we developed 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 quantified over 3,042 proteins in 1,490 single monocytes and macrophages in ten 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. This gradient correlates to the inflammatory axis of classically and alternatively activated macrophages. Parallel measurements of transcripts by 10x 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. The joint distributions of proteins and transcripts allowed exploring regulatory interactions, such as between the tumor suppressor p53, its transcript, and the transcripts of genes regulated by p53. Our methodology lays the foundation for 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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Competing Interest Statement

The authors have declared no competing interest.

Footnotes

  • ∈ Data, code & protocols: scope2.slavovlab.net

  • https://scope2.slavovlab.net

Copyright 
The copyright holder for this preprint is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under a CC-BY-NC-ND 4.0 International license.
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Posted December 20, 2020.
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Single-cell proteomic and transcriptomic analysis of macrophage heterogeneity
Harrison Specht, Edward Emmott, Aleksandra A. Petelski, R. Gray Huffman, David H. Perlman, Marco Serra, Peter Kharchenko, Antonius Koller, Nikolai Slavov
bioRxiv 665307; doi: https://doi.org/10.1101/665307
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Single-cell proteomic and transcriptomic analysis of macrophage heterogeneity
Harrison Specht, Edward Emmott, Aleksandra A. Petelski, R. Gray Huffman, David H. Perlman, Marco Serra, Peter Kharchenko, Antonius Koller, Nikolai Slavov
bioRxiv 665307; doi: https://doi.org/10.1101/665307

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