Abstract
For label-free expression profiling of tissue proteomes, efficient protein extraction, thorough and quantitative sample cleanup and digestion procedures, as well as sufficient and reproducible chromatographic separation, are highly desirable but remain challenging. However, optimal methodology has remained elusive, especially for proteomes that are rich in membrane proteins, such as the mitochondria. Here, we describe a straightforward and reproducible sample preparation procedure, coupled with a highly selective and sensitive nano-LC/Orbitrap analysis, which enables reliable and comprehensive expression profiling of tissue mitochondria. The mitochondrial proteome of swine heart was selected as a test system. Efficient protein extraction was accomplished using a strong buffer containing both ionic and nonionic detergents. Overnight precipitation was used for cleanup of the extract, and the sample was subjected to an optimized 2-step, on-pellet digestion approach. In the first step, the protein pellet was dissolved via a 4 h tryptic digestion under vigorous agitation, which nano-LC/LTQ/ETD showed to produce large and incompletely cleaved tryptic peptides. The mixture was then reduced, alkylated, and digested into its full complement of tryptic peptides with additional trypsin. This solvent precipitation/on-pellet digestion procedure achieved significantly higher and more reproducible peptide recovery of the mitochondrial preparation than observed using a prevalent alternative procedure for label-free expression profiling, SDS-PAGE/in-gel digestion (87% vs 54%). Furthermore, uneven peptide losses were lower than observed with SDS-PAGE/in-gel digestion. The resulting peptides were sufficiently resolved by a 5 h gradient using a nano-LC configuration that features a low-void-volume, high chromatographic reproducibility, and an LTQ/Orbitrap analyzer for protein identification and quantification. The developed method was employed for label-free comparison of the mitochondrial proteomes of myocardium from healthy animals versus those with hibernating myocardium. Each experimental group consisted of a relatively large number of animals (n = 10), and samples were analyzed in random order to minimize quantitative false-positives. With this approach, 904 proteins were identified and quantified with high confidence, and those mitochondrial proteins that were altered significantly between groups were compared with the results of a parallel 2D-DIGE analysis. The sample preparation and analytical strategy developed here represents an advancement that can be adapted to analyze other tissue proteomes.