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 halflife 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 (ϳ60 d). Our proteomics platform demonstrates the first large-scale analysis of mitochondrial protein turnover rates in vivo, with potential applications in translational research. Molecular & Cellular

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Mitochondria are a common energy source for organs and organisms; their diverse functions are specialized according to the unique phenotypes of their hosting environment. Perturbation of mitochondrial homeostasis accompanies significant pathological phenotypes. However, the connections between mitochondrial proteome properties and function remain to be experimentally established on a systematic level. This uncertainty impedes the contextualization and translation of proteomic data to the molecular derivations of mitochondrial diseases. We present a collection of mitochondrial features and functions from four model systems, including two cardiac mitochondrial proteomes from distinct genomes (human and mouse), two unique organ mitochondrial proteomes from identical genetic codons (mouse heart and mouse liver), as well as a relevant metazoan out-group (drosophila). The data, composed of mitochondrial protein abundance and their biochemical activities, capture the core functionalities of these mitochondria. This investigation allowed us to redefine the core mitochondrial proteome from organs and organisms, as well as the relevant contributions from genetic information and hosting milieu. Our study has identified significant enrichment of disease-associated genes and their products. Furthermore, correlational analyses suggest that mitochondrial proteome design is primarily driven by cellular environment. Taken together, these results connect proteome feature with mitochondrial function, providing a prospective resource for mitochondrial pathophysiology and developing novel therapeutic targets in medicine.

Rationale Omics sciences enable a systems-level perspective in characterizing cardiovascular biology. Integration of diverse proteomics data via a computational strategy will catalyze the assembly of contextualized knowledge, foster discoveries through multidisciplinary investigations, and minimize unnecessary redundancy in research efforts. Objective The goal of this project is to develop a consolidated cardiac proteome knowledgebase with novel bioinformatics pipeline and web portals, thereby serving as a new resource to advance cardiovascular biology and medicine. Methods and Results We created Cardiac Organellar Protein Atlas Knowledgebase (COPaKB), a centralized platform of high quality cardiac proteomic data, bioinformatics tools and relevant cardiovascular phenotypes. Currently, COPaKB features eight organellar modules, comprising 4,203 LC-MS/MS experiments from human, mouse, drosophila and C. elegans as well as expression images of 10,924 proteins in human myocardium. In addition, the Java-coded bioinformatics tools provided by COPaKB enable cardiovascular investigators in all disciplines to retrieve and analyze pertinent organellar protein properties of interest. Conclusions COPaKB (www.HeartProteome.org) provides an innovative and interactive resource, which connects research interests with the new biological discoveries in protein sciences. With an array of intuitive tools in this unified web server, non-proteomics investigators can conveniently collaborate with proteomics specialists to dissect the molecular signatures of cardiovascular phenotypes.

Proteasomes are ubiquitously expressed multicatalytic complexes that serve as key regulators of protein homeostasis. There are several lines of evidence indicating that proteasomes exist in heterogeneous subpopulations in cardiac muscle, differentiated, in part, by post-translational modifications (PTMs). PTMs regulate numerous facets of proteasome function, including catalytic activities, complex assembly, interactions with associating partners, subcellular localization, substrate preference, and complex turnover. Classical technologies used to identify PTMs on proteasomes have lacked the ability to determine site specificity, quantify stoichiometry, and perform large-scale, multi-PTM analysis. Recent advancements in proteomic technologies have largely overcome these limitations. We present here a discussion on the importance of PTMs in modulating proteasome function in cardiac physiology and pathophysiology, followed by the presentation of a state-of-the-art proteomic workflow for identifying and quantifying PTMs of cardiac proteasomes.