Multidimensional Separation and Labeling Strategies for Protein Identification

• Main Authors: Ying-Ting Chen, 陳映婷
• Other Authors: Shu-Hui Chen
• Format: Others
• Language: zh-TW
• Published: 2009
• Online Access: http://ndltd.ncl.edu.tw/handle/30324372747471148382

碩士 === 國立成功大學 === 化學系碩博士班 === 97 === The sample separation is a critical step in proteome analysis due to the limitation of mass spectrometry. The more simplicity in sample composition, the more peptide information we can get. In this study, we try to reduce the sample complexity by using multidimensional separation method to obtain a good result of protein identification. Also, we separate the total proteins of human breast cancer cells (MCF-7) at protein level to purify our target protein－ estrogen receptor. We also combined ”stable isotope dimethyl labeling” to do the modification at protein level followed with trypsin digestion and mass spectrometry identification. In multidimensional system, we compared the number of identified proteins using two separation platforms: ZIC-HILIC-nano C18 and C18-nano C18, which only differed in first dimension. 500 μg MCF-7 whole cell lysates were digested into peptides and both systems were used for separation before mass spectrometry identification. Total of 1030 proteins with 3059 peptides were identified using ZIC-HILIC-nano C18 system and 615 proteins with 1094 peptides were identified using C18-nano C18 system. Among these results, there were 457 proteins with 902 peptides existed in both platforms. The HILIC-nano C18 system showed greater separation power since the orthogonality of two separation dimensions. We also compared the protein separation ability by C4 and C18 columns. We chose C4 column for separation because the mobile phase cannot elute all proteins from C18 and lots of samples retained on beads. After separating MCF-7 whole cell lysate using C4 column, all fractions were collected and ERα were detected using western blotting. The result showed that separation at protein level followed with stable isotope dimethyl labeling is a potential strategy in targeting proteomics.