Analysis of nuclear proteome in C57 mouse liver tissue by a nano-flow 2-D-LC-ESI-MS/MS approach.
The analysis of whole cell or tissue extracts is too complex for current protein identification technology and not suitable for the study of proteins with low copy levels. To concentrate and enrich low abundance proteins, organelle proteomics is a promising strategy. This approach can not only reduce the protein sample complexity but also provide information about protein location in cells, organs, or tissues under analysis. Nano-flow two-dimensional strong-cation exchange chromatography (SCX)-RPLC-ESI-MS/MS is an ideal platform for analyzing organelle extracts because of its advantages of sample non-bias, low amounts of sample required, powerful separation capability, and high detection sensitivity. In this study, we apply nano-scale multidimensional protein identification technology to the analysis of C57 mouse liver nuclear proteins. Organelle isolation has been optimized to obtain highly pure nuclei. Evaluation of nucleus integrity and purity has been performed to demonstrate the effectiveness of the optimized isolation procedure. The extracted nuclear proteins were identified by five independent nano-flow on-line SCX-RPLC-ESI-MS/MS analyses to improve the proteome coverage. Finally, a total of 462 proteins were identified. Corresponding analyses of protein molecular mass and pI distribution and biological function categorization have been undertaken to further validate our identification strategy.
Zhang
Jie
J
Department of Chemistry, Research Center for Proteome, Fudan University, Shanghai, China.
Xu
Xiuqing
X
Shen
Huali
H
Zhang
Xiangmin
X
D000818:Animals; D002853:Chromatography, Liquid; D008099:Liver / Q000737:chemistry*; D051379:Mice; D008810:Mice, Inbred C57BL; D049329:Nanostructures / Q000737:chemistry*; D009687:Nuclear Proteins / Q000737:chemistry*; D020543:Proteome / Q000737:chemistry*; D021241:Spectrometry, Mass, Electrospray Ionization; D053719:Tandem Mass Spectrometry
D009687:Nuclear Proteins; D020543:Proteome