Analysis of the urine proteome via a combination of multi-dimensional approaches

被引:29
作者
Zerefos, Panagiotis G. [1 ]
Aivaliotis, Michalis [1 ]
Baumann, Marc [2 ]
Vlahou, Antonia [1 ]
机构
[1] Acad Athens, Biomed Res Fdn, Div Biotechnol, Athens 11527, Greece
[2] Biomed Helsinki, Prot Chem Unit, Helsinki, Finland
关键词
Electrophoresis; LC-MS; MS; Multi-dimensional separation; Technology; Urine; FLIGHT-MASS-SPECTROMETRY; PREPARATIVE ELECTROPHORESIS; BIOMARKER DISCOVERY; PROTEINS; MAP; FRACTIONATION; DATABASE; DISEASE; IDENTIFICATIONS; ESTABLISHMENT;
D O I
10.1002/pmic.201100212
中图分类号
Q5 [生物化学];
学科分类号
071010 ; 081704 ;
摘要
Urine is a biological fluid that is non-invasively and easily harvested, and exhibits high stability from the proteomics point of view. At the downside, the overall low protein content of urine as well as the presence of low- and high-abundance proteins underscores the need for protein enrichment. As a continuation of previous efforts towards the comprehensive characterization of the urine proteome, the current study targeted the mining of urine proteins through the combined application of different protein separation methodologies, specifically, liquid chromatography and preparative electrophoresis along with 1D gel electrophoresis and protein identification by mass spectrometry. In order to enhance comparison and integration of different experimental data sets, the standard urine sample developed within the European Kidney and Urine Proteomics (EuroKUP) COST Action, was employed. As a contribution to the existing knowledge, we focused on maintaining and providing information about experimental mass of the identified proteins as well as information pertaining to their relative abundance as allowed by technical limitations thus providing an initial view of different isoforms representation and facilitating their future characterization. The difficulties in comparing proteome mining data sets become once more evident, underscoring the need for adopting standardized ways for data reporting as well as for potential new approaches for data analysis involving a thorough investigation of received information at the peptide level.
引用
收藏
页码:391 / 400
页数:10
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