Water as turnover label to study mitochondrial dynamics
Kim TY, Wang D, Kim AK, Lau E, Lin AJ, Liem DA, Zhang J, Zong NC, Lam MP, Ping P. (2012) Metabolic labeling reveals proteome dynamics of mouse mitochondria.Mol Cell Proteomics. 2012 Dec;11(12):1586-94. doi: 10.1074/mcp.M112.021162. Epub 2012 Aug 21.
Departments of Physiology and Medicine, David Geffen School of Medicine, UCLA, Los Angeles, CA 90095, USA.
Mitochondrial dysfunction is associated with many human diseases. Mitochondrial damage is exacerbated by inadequate protein quality control and often further contributes to pathogenesis. The maintenance of mitochondrial functions requires a delicate balance of continuous protein synthesis and degradation, i.e. protein turnover. To understand mitochondrial protein dynamics in vivo, we designed a metabolic heavy water ((2)H(2)O) labeling strategy customized to examine individual protein turnover in the mitochondria in a systematic fashion. Mice were fed with (2)H(2)O at a minimal level (<5% body water) without physiological impacts. Mitochondrial proteins were analyzed from 9 mice at each of the 13 time points between 0 and 90 days (d) of labeling. A novel multiparameter fitting approach computationally determined the normalized peak areas of peptide mass isotopomers at initial and steady-state time points and permitted the protein half-life to be determined without plateau-level (2)H incorporation. We characterized the turnover rates of 458 proteins in mouse cardiac and hepatic mitochondria and found median turnover rates of 0.0402 d(-1) and 0.163 d(-1), respectively, corresponding to median half-lives of 17.2 d and 4.26 d. Mitochondria in the heart and those in the liver exhibited distinct turnover kinetics, with limited synchronization within functional clusters. We observed considerable interprotein differences in turnover rates in both organs, with half-lives spanning from hours to months (∼60 d). Our proteomics platform demonstrates the first large-scale analysis of mitochondrial protein turnover rates in vivo, with potential applications in translational research.