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Dynamics of Protein Turnover, a Missing Dimension in Proteomics
Open accessAbstract
Functional genomic experiments frequently involve a comparison of the levels of gene expression between two or more genetic, developmental, or physiological states. Such comparisons can be carried out at either the RNA (transcriptome) or protein (proteome) level, but there is often a lack of congruence between parallel analyses using these two approaches. To fully interpret protein abundance data from proteomic experiments, it is necessary to understand the contributions made by the opposing processes of synthesis and degradation to the transition between the states compared. Thus, there is a need for reliable methods to determine the rates of turnover of individual proteins at amounts comparable to those obtained in proteomic experiments. Here, we show that stable isotope-labeled amino acids can be used to define the rate of breakdown of individual proteins by inspection of mass shifts in tryptic fragments. The approach has been applied to an analysis of abundant proteins in glucose-limited yeast cells grown in aerobic chemostat culture at steady state. The average rate of degradation of 50 proteins was 2.2%/h, although some proteins were turned over at imperceptible rates, and others had degradation rates of almost 10%/h. This range of values suggests that protein turnover is a significant missing dimension in proteomic experiments and needs to be considered when assessing protein abundance data and comparing it to the relative abundance of cognate mRNA species.
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Ong, S.-E., Blagoev, B., Kratchmarova, I., Kristensen, D. B., Steen, H., Pandey, A., & Mann, M. (2002) · Molecular & Cellular Proteomics · doi:10.1074/mcp.m200025-mcp200 · Cited by 5,574
The N-end rule: functions, mysteries, uses
Varshavsky, A. (1996) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.93.22.12142 · Cited by 859
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Selbach, M., Schwanhäusser, B., Thierfelder, N., Fang, Z., Khanin, R., & Rajewsky, N. (2008) · Nature · doi:10.1038/nature07228 · Cited by 3,429
Correlation of mRNA and protein in complex biological samples
Maier, T., Güell, M., & Serrano, L. (2009) · FEBS Letters · doi:10.1016/j.febslet.2009.10.036 · Cited by 1,802
Comparing protein abundance and mRNA expression levels on a genomic scale
Greenbaum, D. (2003) · Genome biology · doi:10.1186/gb-2003-4-9-117 · Cited by 1,692
Mass spectrometry–based proteomics turns quantitative
Ong, S.-E., & Mann, M. (2005) · Nature Chemical Biology · doi:10.1038/nchembio736 · Cited by 1,572
Protein Analysis by Shotgun/Bottom-up Proteomics
Zhang, Y., Fonslow, B. R., Shan, B., Baek, M.-C., & Yates, J. R. (2013) · Chemical Reviews · doi:10.1021/cr3003533 · Cited by 1,491
Metadata
- Authors
- Pratt, J. M., Petty, J., Riba-Garcia, I., Robertson, D. H. L., Gaskell, S. J., Oliver, S. G., & Beynon, R. J.
- Venue
- Molecular & Cellular Proteomics
- Publisher
- Elsevier BV
- Published
- 2002-08
- Volume
- 1
- Issue
- 8
- Pages
- 579-591
- ISSN
- 1535-9476 (ISSN-L)
- OpenAlex
- W2102878034
- Cited by
- 396
- References
- 2
- FWCI
- 9.25
- Type
- journal article
- Language
- en
- Open access
- hybrid
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- Pratt, J. M., Petty, J., Riba-Garcia, I., Robertson, D. H. L., Gaskell, S. J., Oliver, S. G., & Beynon, R. J. (2002). Dynamics of Protein Turnover, a Missing Dimension in Proteomics. Molecular & Cellular Proteomics. https://doi.org/10.1074/mcp.m200046-mcp200
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