A complete description of protein metabolism requires knowledge of the rates of protein production and destruction within cells. Using an epitope-tagged strain collection, we measured the halflife of >3,750 proteins in the yeast proteome after inhibition of translation. By integrating our data with previous measurements of protein and mRNA abundance and translation rate, we provide evidence that many proteins partition into one of two regimes for protein metabolism: one optimized for efficient production or a second optimized for regulatory efficiency. Incorporation of protein half-life information into a simple quantitative model for protein production improves our ability to predict steady-state protein abundance values. Analysis of a simple dynamic protein production model reveals a remarkable correlation between transcriptional regulation and protein half-life within some groups of coregulated genes, suggesting that cells coordinate these two processes to achieve uniform effects on protein abundances. Our experimental data and theoretical analysis underscore the importance of an integrative approach to the complex interplay between protein degradation, transcriptional regulation, and other determinants of protein metabolism.degradation ͉ proteomics ͉ cycloheximide ͉ epitope-tagged T he availability of whole-genome sequences and the advent of microarray technology have made global analyses of mRNA expression mainstream. However, most biological processes are mediated by proteins, which are subject to posttranscriptional regulation that is generally not observable at mRNA levels. A complete understanding of biological systems requires knowledge of protein properties, which is ultimately the goal of proteomics.Despite tremendous technical advances and effort in proteomics, the chemical heterogeneity of proteins and the large dynamic range of protein abundance make it challenging to establish global proteomic assays. This obstacle has been circumvented in the yeast Saccharomyces cerevisiae with the availability of two collections of yeast strains expressing epitope-tagged fusion proteins, one by using the tandem affinity purification (TAP) tag and a second employing the GFP (1, 2). In an initial study, we analyzed the TAP-tagged strain collection by Western blotting to quantify steady-state levels of protein abundance in actively dividing yeast cells. These data augmented previous efforts to quantify protein abundance by using mass spectrometry and 2D gel electrophoresis and provided a more comprehensive estimate of protein levels in a eukaryotic cell (3, 4).The availability of high-throughput protein abundance data has facilitated analysis of the relationship between protein abundance and mRNA levels. Although a statistically significant correlation is observed between these parameters, individual genes with similar mRNA levels can produce proteins with very different abundances. This complication makes it difficult to extrapolate from mRNA levels and microarray experiments to protein abundance. Three potential...

Background: The rapid increase in the amount of protein and DNA sequence information available has become almost overwhelming to researchers. So much information is now accessible that high-quality, functional gene analysis and categorization has become a major goal for many laboratories. To aid in this categorization, there is a need for non-commercial software that is able to both align sequences and also calculate pairwise levels of similarity/identity.

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