Dynamics of Protein Turnover, a Missing Dimension in Proteomics

• Published in: Molecular & cellular proteomics 2002-08, Vol.1 (8), p.579-591
• Main Authors: Pratt, J M, Petty, J, Riba-Garcia, I, Robertson, DHL, Gaskell, S J, Oliver, S G, Beynon, R J
• Format: Article
• Language: English
• Subjects: Amino Acids - chemistry; Amino Acids - metabolism; Fungal Proteins - chemistry; Fungal Proteins - metabolism; Peptide Mapping; Proteomics; Radioisotopes - metabolism; Spectrometry, Mass, Matrix-Assisted Laser Desorption-Ionization; Statistics as Topic; Yeasts - chemistry; Yeasts - metabolism
• ISSN: 1535-9476; 1535-9484; 1535-9484
• DOI: 10.1074/mcp.M200046-MCP200

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.