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A Quantitative Spatial Proteomics Analysis of Proteome Turnover in Human Cells
Measuring the properties of endogenous cell proteins, such as expression level, subcellular localization, and turnover rates, on a whole proteome level remains a major challenge in the postgenome era. Quantitative methods for measuring mRNA expression do not reliably predict corresponding protein le...
Autores principales: | , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
The American Society for Biochemistry and Molecular Biology
2012
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3316722/ https://www.ncbi.nlm.nih.gov/pubmed/21937730 http://dx.doi.org/10.1074/mcp.M111.011429 |
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author | Boisvert, François-Michel Ahmad, Yasmeen Gierliński, Marek Charrière, Fabien Lamont, Douglas Scott, Michelle Barton, Geoff Lamond, Angus I. |
author_facet | Boisvert, François-Michel Ahmad, Yasmeen Gierliński, Marek Charrière, Fabien Lamont, Douglas Scott, Michelle Barton, Geoff Lamond, Angus I. |
author_sort | Boisvert, François-Michel |
collection | PubMed |
description | Measuring the properties of endogenous cell proteins, such as expression level, subcellular localization, and turnover rates, on a whole proteome level remains a major challenge in the postgenome era. Quantitative methods for measuring mRNA expression do not reliably predict corresponding protein levels and provide little or no information on other protein properties. Here we describe a combined pulse-labeling, spatial proteomics and data analysis strategy to characterize the expression, localization, synthesis, degradation, and turnover rates of endogenously expressed, untagged human proteins in different subcellular compartments. Using quantitative mass spectrometry and stable isotope labeling with amino acids in cell culture, a total of 80,098 peptides from 8,041 HeLa proteins were quantified, and their spatial distribution between the cytoplasm, nucleus and nucleolus determined and visualized using specialized software tools developed in PepTracker. Using information from ion intensities and rates of change in isotope ratios, protein abundance levels and protein synthesis, degradation and turnover rates were calculated for the whole cell and for the respective cytoplasmic, nuclear, and nucleolar compartments. Expression levels of endogenous HeLa proteins varied by up to seven orders of magnitude. The average turnover rate for HeLa proteins was ∼20 h. Turnover rate did not correlate with either molecular weight or net charge, but did correlate with abundance, with highly abundant proteins showing longer than average half-lives. Fast turnover proteins had overall a higher frequency of PEST motifs than slow turnover proteins but no general correlation was observed between amino or carboxyl terminal amino acid identities and turnover rates. A subset of proteins was identified that exist in pools with different turnover rates depending on their subcellular localization. This strongly correlated with subunits of large, multiprotein complexes, suggesting a general mechanism whereby their assembly is controlled in a different subcellular location to their main site of function. |
format | Online Article Text |
id | pubmed-3316722 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2012 |
publisher | The American Society for Biochemistry and Molecular Biology |
record_format | MEDLINE/PubMed |
spelling | pubmed-33167222012-04-10 A Quantitative Spatial Proteomics Analysis of Proteome Turnover in Human Cells Boisvert, François-Michel Ahmad, Yasmeen Gierliński, Marek Charrière, Fabien Lamont, Douglas Scott, Michelle Barton, Geoff Lamond, Angus I. Mol Cell Proteomics Special Issue: Prospects in Space and Time Measuring the properties of endogenous cell proteins, such as expression level, subcellular localization, and turnover rates, on a whole proteome level remains a major challenge in the postgenome era. Quantitative methods for measuring mRNA expression do not reliably predict corresponding protein levels and provide little or no information on other protein properties. Here we describe a combined pulse-labeling, spatial proteomics and data analysis strategy to characterize the expression, localization, synthesis, degradation, and turnover rates of endogenously expressed, untagged human proteins in different subcellular compartments. Using quantitative mass spectrometry and stable isotope labeling with amino acids in cell culture, a total of 80,098 peptides from 8,041 HeLa proteins were quantified, and their spatial distribution between the cytoplasm, nucleus and nucleolus determined and visualized using specialized software tools developed in PepTracker. Using information from ion intensities and rates of change in isotope ratios, protein abundance levels and protein synthesis, degradation and turnover rates were calculated for the whole cell and for the respective cytoplasmic, nuclear, and nucleolar compartments. Expression levels of endogenous HeLa proteins varied by up to seven orders of magnitude. The average turnover rate for HeLa proteins was ∼20 h. Turnover rate did not correlate with either molecular weight or net charge, but did correlate with abundance, with highly abundant proteins showing longer than average half-lives. Fast turnover proteins had overall a higher frequency of PEST motifs than slow turnover proteins but no general correlation was observed between amino or carboxyl terminal amino acid identities and turnover rates. A subset of proteins was identified that exist in pools with different turnover rates depending on their subcellular localization. This strongly correlated with subunits of large, multiprotein complexes, suggesting a general mechanism whereby their assembly is controlled in a different subcellular location to their main site of function. The American Society for Biochemistry and Molecular Biology 2012-03 2011-09-21 /pmc/articles/PMC3316722/ /pubmed/21937730 http://dx.doi.org/10.1074/mcp.M111.011429 Text en © 2012 by The American Society for Biochemistry and Molecular Biology, Inc. Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/by-nc/3.0/) applies to Author Choice Articles |
spellingShingle | Special Issue: Prospects in Space and Time Boisvert, François-Michel Ahmad, Yasmeen Gierliński, Marek Charrière, Fabien Lamont, Douglas Scott, Michelle Barton, Geoff Lamond, Angus I. A Quantitative Spatial Proteomics Analysis of Proteome Turnover in Human Cells |
title | A Quantitative Spatial Proteomics Analysis of Proteome Turnover in Human Cells |
title_full | A Quantitative Spatial Proteomics Analysis of Proteome Turnover in Human Cells |
title_fullStr | A Quantitative Spatial Proteomics Analysis of Proteome Turnover in Human Cells |
title_full_unstemmed | A Quantitative Spatial Proteomics Analysis of Proteome Turnover in Human Cells |
title_short | A Quantitative Spatial Proteomics Analysis of Proteome Turnover in Human Cells |
title_sort | quantitative spatial proteomics analysis of proteome turnover in human cells |
topic | Special Issue: Prospects in Space and Time |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3316722/ https://www.ncbi.nlm.nih.gov/pubmed/21937730 http://dx.doi.org/10.1074/mcp.M111.011429 |
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