The liver proteome can serve as a reference to better understand both disease mechanisms and possible therapeutics,since the liver is an important organ in the body that performs a large number of tasks.Here we identify the organelle proteome of C57BL/6J mouse liver nuclei as a promising strategy to enrich low abundance proteins,in the sense that analysis of whole liver cells is rather complex for current techniques and may not be suitable for proteins with low abundance.Evaluation of nucleus integrity and purity was performed to demonstrate the effectiveness of the optimized isolation procedure.The extracted nuclear proteins were identified by 2-DE MS analyses,and a total of 748 proteins were identified.Bioinformatic analyses were performed to demonstrate the physicochemical properties,cellular locations and functions of the proteins.
Integration of pathway and protein-protein interaction(PPI) data can provide more information that could lead to new biological insights. PPIs are usually represented by a simple binary model, whereas pathways are represented by more complicated models. We developed a series of rules for transforming protein interactions from pathway to binary model, and the protein interactions from seven pathway databases, including PID, Bio Carta, Reactome, Net Path, INOH, SPIKE and KEGG, were transformed based on these rules. These pathway-derived binary protein interactions were integrated with PPIs from other five PPI databases including HPRD, Int Act, Bio GRID, MINT and DIP, to develop integrated dataset(named Path PPI). More detailed interaction type and modification information on protein interactions can be preserved in Path PPI than other existing datasets. Comparison analysis results indicate that most of the interaction overlaps values(OAB) among these pathway databases were less than 5%, and these databases must be used conjunctively. The Path PPI data was provided at http://proteomeview. hupo.org.cn/Path PPI/Path PPI.html.
