#PROTEIN TURNOVER INVOLVES SERIAL#
#PROTEIN TURNOVER INVOLVES SOFTWARE#

In vivo, isotopic labeling can be achieved through different strategies. In contrast, stable isotopic labeling of mammalian tissues in vivo requires expensive isotopically-labeled food or water, and the collection of many tissues requires sacrificing an organism for each measurement.

#PROTEIN TURNOVER INVOLVES SERIAL#

This method is most feasible for cultured cells 14, 15, 16, 17, 18, 19 and tissues in vitro 6, where the cost of isotopically-labeled media is modest and serial sampling can occur without necessarily sacrificing the entire culture. For steady-state protein turnover studies, stable isotope labels are introduced to the organism of interest and proteins sampled over time to monitor the rate of stable isotope incorporation. Mass spectrometry-based proteomics typically and capably performs proteome-wide identification and quantification at a snapshot in time 11, whereas measuring proteome synthesis rates, degradation rates, or combined turnover rates comprise a challenging subfield 12, 13. Simultaneously measuring individual protein turnover rates for thousands of proteins requires the broad identification and quantification capabilities of state-of-the-art proteomics. Most techniques for measuring protein turnover are limited to bulk determination of average turnover rate in a cell population or tissue, or individual analysis of a small number of isolated proteins 7, 8, 9, 10.

Information about each protein’s turnover rate is also relevant to medical and surgical therapies because protein turnover impacts pharmacokinetics and pharmacodynamics 4, as well as tissue remodeling during wound healing 5 and following graft transplantation 6. The rate of protein turnover can change in response to physiologic stimuli 1, development and aging 2, and disease 3. Cells are continually creating and destroying proteins to maintain proteostasis. Protein turnover is a fundamental process in all living organisms.

#PROTEIN TURNOVER INVOLVES SOFTWARE#

This extensive dataset and the corresponding visualization software provide a reference to guide future studies of mammalian protein turnover in response to physiologic perturbation, disease, or therapeutic intervention. We additionally develop a data visualization platform, named ApplE Turnover, that enables facile searching for any protein of interest in a tissue of interest and then displays its half-life, confidence interval, and supporting measurements. Using stable isotope labeling and mass spectrometry, we determine the in vivo turnover rates of thousands of proteins-including those of the extracellular matrix-in a set of biologically important mouse tissues. The unique synthesis and degradation rates of each protein help to define tissue phenotype, and knowledge of tissue- and protein-specific half-lives is directly relevant to protein-related drug development as well as the administration of medical therapies. Protein turnover is critical to cellular physiology as well as to the growth and maintenance of tissues.

Protein turnover involves