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A protein molecular weight map of ES2 clear cell ovarian carcinoma cells using a two-dimensional liquid separations/mass mapping technique
Authors:Wang Haixing  Kachman Maureen T  Schwartz Donald R  Cho Kathleen R  Lubman David M
Institution:Department of Chemistry, School of Medicine, The University of Michigan, Ann Arbor, MI 48109, USA.
Abstract:A molecular weight map of the protein content of ES2 human clear cell ovarian carcinoma cells has been produced using a two-dimensional (2-D) liquid separations/mass mapping technique. This method uses a 2-D liquid separation of proteins from whole cell lysates coupled on-line to an electrospray ionization-time of flight (ESI-TOF) mass spectrometer to map the accurate intact molecular weight (M(r)) of the protein content of the cells. The two separation dimensions involve the use of liquid isoelectric focusing as the first phase and nonporous silica reversed-phase high-performance liquid chromatography (HPLC) as the second phase of separation. The detection by ESI-TOF-MS provides an image of pI versus M(r) analogous to 2-D gel electrophoresis. Each protein is then identified based upon matrix-assisted laser desorption/ionization (MALDI)-TOF-MS peptide mapping and intact M(r) so that a standard map is produced against which other ovarian carcinoma cell lines can be compared. The accurate intact M(r) together with the pI fraction, and peptide map serve to tag the protein for future interlysate comparisons. An internal standard is also used to provide a means for quantitation for future interlysate studies. In the ES2 cell line under study it is shown that nearly 900 M(r) bands are detected over 17 pI fractions from pH 4 to 12 and a M(r) range up to 85 kDa and that around 290 of these bands can be identified using mass spectrometric based techniques. The protein M(r) is detected within an accuracy of 150 ppm and it is shown that many of the proteins in this human cancer sample are modified compared to the database. The protein M(r) map may serve as a highly reproducible standard Web-based method for comparing proteins from related human cell lines.
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