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Single-cell proteomic and transcriptomic analysis of macrophage heterogeneity using SCoPE2
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 SCoPE...
Autores principales: | , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7839219/ https://www.ncbi.nlm.nih.gov/pubmed/33504367 http://dx.doi.org/10.1186/s13059-021-02267-5 |
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author | Specht, Harrison Emmott, Edward Petelski, Aleksandra A. Huffman, R. Gray Perlman, David H. Serra, Marco Kharchenko, Peter Koller, Antonius Slavov, Nikolai |
author_facet | Specht, Harrison Emmott, Edward Petelski, Aleksandra A. Huffman, R. Gray Perlman, David H. Serra, Marco Kharchenko, Peter Koller, Antonius Slavov, Nikolai |
author_sort | Specht, Harrison |
collection | PubMed |
description | 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. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s13059-021-02267-5. |
format | Online Article Text |
id | pubmed-7839219 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-78392192021-01-27 Single-cell proteomic and transcriptomic analysis of macrophage heterogeneity using SCoPE2 Specht, Harrison Emmott, Edward Petelski, Aleksandra A. Huffman, R. Gray Perlman, David H. Serra, Marco Kharchenko, Peter Koller, Antonius Slavov, Nikolai Genome Biol Research 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. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s13059-021-02267-5. BioMed Central 2021-01-27 /pmc/articles/PMC7839219/ /pubmed/33504367 http://dx.doi.org/10.1186/s13059-021-02267-5 Text en © The Author(s) 2021 Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated in a credit line to the data. |
spellingShingle | Research Specht, Harrison Emmott, Edward Petelski, Aleksandra A. Huffman, R. Gray Perlman, David H. Serra, Marco Kharchenko, Peter Koller, Antonius Slavov, Nikolai Single-cell proteomic and transcriptomic analysis of macrophage heterogeneity using SCoPE2 |
title | Single-cell proteomic and transcriptomic analysis of macrophage heterogeneity using SCoPE2 |
title_full | Single-cell proteomic and transcriptomic analysis of macrophage heterogeneity using SCoPE2 |
title_fullStr | Single-cell proteomic and transcriptomic analysis of macrophage heterogeneity using SCoPE2 |
title_full_unstemmed | Single-cell proteomic and transcriptomic analysis of macrophage heterogeneity using SCoPE2 |
title_short | Single-cell proteomic and transcriptomic analysis of macrophage heterogeneity using SCoPE2 |
title_sort | single-cell proteomic and transcriptomic analysis of macrophage heterogeneity using scope2 |
topic | Research |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7839219/ https://www.ncbi.nlm.nih.gov/pubmed/33504367 http://dx.doi.org/10.1186/s13059-021-02267-5 |
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