Abstract

The ability to decipher the dynamic protein component of any system is determined by the inherent limitations of the technologies used, the complexity of the sample, and the existence of an annotated genome. In the absence of an annotated genome, large-scale proteomic investigations can be technically difficult. Yet the functional and biological species differences across animal models can lead to selection of partially or nonannotated organisms over those with an annotated genome. The outweighing of biology over technology leads us to investigate the degree to which a parallel approach can facilitate proteome coverage in the absence of complete genome annotation. When studying species without complete genome annotation, a particular challenge is how to ensure high proteome coverage while meeting the bioinformatic stringencies of high-throughput proteomics. A protein inventory of Oryctolagus cuniculus mitochondria was created by overlapping "protein-centric" and "peptide-centric" one-dimensional and two-dimensional liquid chromatography strategies; with additional partitioning into membrane-enriched and soluble fractions. With the use of these five parallel approaches, 2934 unique peptides were identified, corresponding to 558 nonredundant protein groups. 230 of these proteins (41%) were identified by only a single technical approach, confirming the need for parallel techniques to improve annotation. To determine the extent of coverage, a side-by-side comparison with human and mouse cardiomyocyte mitochondrial studies was performed. A nonredundant list of 995 discrete proteins was compiled, of which 244 (25%) were common across species. The current investigation identified 142 unique protein groups, the majority of which were detected here by only one technical approach, in particular peptide- and protein-centric two-dimensional liquid chromatography. Although no single approach achieved more than 40% coverage, the combination of three approaches (protein- and peptide-centric two-dimensional liquid chromatography and subfractionation) contributed 96% of all identifications. Parallel techniques ensured minimal false discovery, and reduced single peptide-based identifications while maximizing sequence coverage in the absence of the annotated rabbit proteome.

Highlights

  • From the Departments of ‡Medicine, §Biological Chemistry, ¶Biomedical Engineering and ʈThe Technical Implementation and Coordination Core of NHLBI proteomics Centre, Johns Hopkins University, Baltimore Maryland, USA 21224

  • Instead there is a close relationship between heart rate and mitochondrial content, oxygen consumption and oxidative capacity [1,2,3]

  • With the rabbit whole genome shotgun not complete, there is incomplete annotation of the proteins associated. The challenges that this presents to proteomic studies are often outweighed by the physiology and pathophysiology of the species being more similar to human

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Summary

Introduction

From the Departments of ‡Medicine, §Biological Chemistry, ¶Biomedical Engineering and ʈThe Technical Implementation and Coordination Core of NHLBI proteomics Centre, Johns Hopkins University, Baltimore Maryland, USA 21224. Instead there is a close relationship between heart rate and mitochondrial content, oxygen consumption and oxidative capacity [1,2,3]. These species differences increase the possibility for differences in their respective cardiomyocyte proteomes. With the rabbit whole genome shotgun not complete, there is incomplete annotation of the proteins associated The challenges that this presents to proteomic studies are often outweighed by the physiology and pathophysiology of the species being more similar to human. Rabbit myocardium is a suitable cardiac model, as it is the smallest mammalian species that accurately mimics several human physiological parameters including heart rate, electron transport chain coupling and mitochondrial density [2]. Of the numerous protein inventories created of the mitochondria, where proteomics and GFP targeting are the most commonly used techniques, species with sequenced genomes are utilized

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