Literature DB >> 17313104

Analysis of nuclear proteome in C57 mouse liver tissue by a nano-flow 2-D-LC-ESI-MS/MS approach.

Jie Zhang1, Xiuqing Xu, Huali Shen, Xiangmin Zhang.   

Abstract

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.

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Year:  2006        PMID: 17313104     DOI: 10.1002/jssc.200600065

Source DB:  PubMed          Journal:  J Sep Sci        ISSN: 1615-9306            Impact factor:   3.645


  2 in total

1.  An update on the mouse liver proteome.

Authors:  Giuseppe Gazzana; Jürgen Borlak
Journal:  Proteome Sci       Date:  2009-09-08       Impact factor: 2.480

Review 2.  Recent development of multi-dimensional chromatography strategies in proteome research.

Authors:  Jia Tang; Mingxia Gao; Chunhui Deng; Xiangming Zhang
Journal:  J Chromatogr B Analyt Technol Biomed Life Sci       Date:  2008-02-02       Impact factor: 3.205

  2 in total

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