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Proteome studies focus almost exclusively on measuring abundance of proteins and documenting the fact that abundance changes in specific circumstances. This requires detection of statistically significant changes in the protein pool sizes to show that ‘something has occurred’. Protein abundance data are then sandwiched in systems biology models as a layer between transcript responses and metabolite levels. Analysing protein synthesis and degradation rates with progressive stable isotope labelling provides a new window into the control of protein abundance and the energy expended in maintaining the steady-state proteome across genotypes, development and environments¹. It provides the first and second derivative of protein abundance with respect to time: how fast are proteins turning over to achieve steady-state or gaining or lowering abundances and do these speeds differ in response to development or the environment? This approach can also enable the relative age distribution of a protein population to be assessed. This has implications for the energetic effort employed by the cell to build or maintain a particular activity and gives clues to the impact of age on the function in different protein types. We are using progressive ¹⁵N labelling of Arabidopsis to provide a birds-eye view of the activity of the proteolysis network as it maintains and sculpts the plant proteome. Using peptide mass spectrometry, the progressive labelling of new peptides and the decrease in the abundance of peptides with natural isotope profiles enabled the degradation rate of 1228 leaf proteins to be determined by combining over 60,000 peptide relative isotope abundance (RIA) measurements². The exponential constant of the decay rate (K_D) for each protein during growth showed a wide distribution, ranging from 0 to 2 per day, which was equivalent to protein half-lives of several hours to several months. We are also using this approach to dissect the in vivo action of proteases through analysis of knockout mutants³.We have found new rapidly degrading subunits in a variety of protein complexes, identified the set of plant proteins whose degradation rate correlated positively or negatively with leaf growth rate, calculated the protein turnover energy costs for different leaves and their key determinants within the proteome, and are beginning to interpret transcriptome analyses from the point-of-view of maintenance of the proteome. [mehr]