Large-scale identification of proteins in human salivary proteome by liquid chromatography/mass spectrometry and two-dimensional gel electrophoresis-mass spectrometry |
| |
Authors: | Hu Shen Xie Yongming Ramachandran Prasanna Ogorzalek Loo Rachel R Li Yang Loo Joseph A Wong David T |
| |
Affiliation: | School of Dentistry & Dental Research Institute, University of California, Los Angeles, CA 90095, USA. |
| |
Abstract: | Human saliva contains a large number of proteins and peptides (salivary proteome) that help maintain homeostasis in the oral cavity. Global analysis of human salivary proteome is important for understanding oral health and disease pathogenesis. In this study, large-scale identification of salivary proteins was demonstrated by using shotgun proteomics and two-dimensinal gel electrophoresis-mass spectrometry (2-DE-MS). For the shotgun approach, whole saliva proteins were prefractionated according to molecular weight. The smallest fraction, presumably containing salivary peptides, was directly separated by capillary liquid chromatography (LC). However, the large protein fractions were digested into peptides for subsequent LC separation. Separated peptides were analyzed by on-line electrospray tandem mass spectrometry (MS/MS) using a quadrupole-time of flight mass spectrometer, and the obtained spectra were automatically processed to search human protein sequence database for protein identification. Additionally, 2-DE was used to map out the proteins in whole saliva. Protein spots 105 in number were excised and in-gel digested; and the resulting peptide fragments were measured by matrix-assisted laser desorption/ionization-mass spectrometry and sequenced by LC-MS/MS for protein identification. In total, we cataloged 309 proteins from human whole saliva by using these two proteomic approaches. |
| |
Keywords: | Two‐ dimensional gel electrophoresis Liquid chromatography mass spectrometry Matrix‐assisted laser desorption/ionization – mass spectrometry Salivary proteome Shotgun proteomics |
本文献已被 PubMed 等数据库收录! |
|