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Exploring functional protein covariation across single cells using nPOP
BACKGROUND: Many biological processes, such as cell division cycle and drug resistance, are reflected in protein covariation across single cells. This covariation can be quantified and interpreted by single-cell mass spectrometry with sufficiently high throughput and accuracy. RESULTS: Here, we desc...
Autores principales: | , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
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BioMed Central
2022
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Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9756690/ https://www.ncbi.nlm.nih.gov/pubmed/36527135 http://dx.doi.org/10.1186/s13059-022-02817-5 |
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author | Leduc, Andrew Huffman, R. Gray Cantlon, Joshua Khan, Saad Slavov, Nikolai |
author_facet | Leduc, Andrew Huffman, R. Gray Cantlon, Joshua Khan, Saad Slavov, Nikolai |
author_sort | Leduc, Andrew |
collection | PubMed |
description | BACKGROUND: Many biological processes, such as cell division cycle and drug resistance, are reflected in protein covariation across single cells. This covariation can be quantified and interpreted by single-cell mass spectrometry with sufficiently high throughput and accuracy. RESULTS: Here, we describe nPOP, a method that enables simultaneous sample preparation of thousands of single cells, including lysing, digesting, and labeling individual cells in volumes of 8–20 nl. nPOP uses piezo acoustic dispensing to isolate individual cells in 300 pl volumes and performs all subsequent sample preparation steps in small droplets on a fluorocarbon-coated glass slide. Protein covariation analysis identifies cell cycle dynamics that are similar and dynamics that differ between cell types, even within subpopulations of melanoma cells delineated by markers for drug resistance priming. Melanoma cells expressing these markers accumulate in the G1 phase of the cell cycle, display distinct protein covariation across the cell cycle, accumulate glycogen, and have lower abundance of glycolytic enzymes. The non-primed melanoma cells exhibit gradients of protein abundance, suggesting transition states. Within this subpopulation, proteins functioning in oxidative phosphorylation covary with each other and inversely with proteins functioning in glycolysis. This protein covariation suggests divergent reliance on energy sources and its association with other biological functions. These results are validated by different mass spectrometry methods. CONCLUSIONS: nPOP enables flexible, automated, and highly parallelized sample preparation for single-cell proteomics. This allows for quantifying protein covariation across thousands of single cells and revealing functionally concerted biological differences between closely related cell states. Support for nPOP is available at https://scp.slavovlab.net/nPOP. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s13059-022-02817-5. |
format | Online Article Text |
id | pubmed-9756690 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-97566902022-12-17 Exploring functional protein covariation across single cells using nPOP Leduc, Andrew Huffman, R. Gray Cantlon, Joshua Khan, Saad Slavov, Nikolai Genome Biol Research BACKGROUND: Many biological processes, such as cell division cycle and drug resistance, are reflected in protein covariation across single cells. This covariation can be quantified and interpreted by single-cell mass spectrometry with sufficiently high throughput and accuracy. RESULTS: Here, we describe nPOP, a method that enables simultaneous sample preparation of thousands of single cells, including lysing, digesting, and labeling individual cells in volumes of 8–20 nl. nPOP uses piezo acoustic dispensing to isolate individual cells in 300 pl volumes and performs all subsequent sample preparation steps in small droplets on a fluorocarbon-coated glass slide. Protein covariation analysis identifies cell cycle dynamics that are similar and dynamics that differ between cell types, even within subpopulations of melanoma cells delineated by markers for drug resistance priming. Melanoma cells expressing these markers accumulate in the G1 phase of the cell cycle, display distinct protein covariation across the cell cycle, accumulate glycogen, and have lower abundance of glycolytic enzymes. The non-primed melanoma cells exhibit gradients of protein abundance, suggesting transition states. Within this subpopulation, proteins functioning in oxidative phosphorylation covary with each other and inversely with proteins functioning in glycolysis. This protein covariation suggests divergent reliance on energy sources and its association with other biological functions. These results are validated by different mass spectrometry methods. CONCLUSIONS: nPOP enables flexible, automated, and highly parallelized sample preparation for single-cell proteomics. This allows for quantifying protein covariation across thousands of single cells and revealing functionally concerted biological differences between closely related cell states. Support for nPOP is available at https://scp.slavovlab.net/nPOP. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s13059-022-02817-5. BioMed Central 2022-12-16 /pmc/articles/PMC9756690/ /pubmed/36527135 http://dx.doi.org/10.1186/s13059-022-02817-5 Text en © The Author(s) 2022 https://creativecommons.org/licenses/by/4.0/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/ (https://creativecommons.org/licenses/by/4.0/) . The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/ (https://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 Leduc, Andrew Huffman, R. Gray Cantlon, Joshua Khan, Saad Slavov, Nikolai Exploring functional protein covariation across single cells using nPOP |
title | Exploring functional protein covariation across single cells using nPOP |
title_full | Exploring functional protein covariation across single cells using nPOP |
title_fullStr | Exploring functional protein covariation across single cells using nPOP |
title_full_unstemmed | Exploring functional protein covariation across single cells using nPOP |
title_short | Exploring functional protein covariation across single cells using nPOP |
title_sort | exploring functional protein covariation across single cells using npop |
topic | Research |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9756690/ https://www.ncbi.nlm.nih.gov/pubmed/36527135 http://dx.doi.org/10.1186/s13059-022-02817-5 |
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