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首页> 外文期刊>Electrophoresis: The Official Journal of the International Electrophoresis Society >Introducing the CPL/MUW proteome database: interpretation of human liver and liver cancer proteome profiles by referring to isolated primary cells.
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Introducing the CPL/MUW proteome database: interpretation of human liver and liver cancer proteome profiles by referring to isolated primary cells.

机译：引入CPL / MUW蛋白质组数据库：通过参考分离的原代细胞来解释人肝和肝癌蛋白质组概况。

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Interpretation of proteome data with a focus on biomarker discovery largely relies on comparative proteome analyses. Here, we introduce a database-assisted interpretation strategy based on proteome profiles of primary cells. Both 2-D-PAGE and shotgun proteomics are applied. We obtain high data concordance with these two different techniques. When applying mass analysis of tryptic spot digests from 2-D gels of cytoplasmic fractions, we typically identify several hundred proteins. Using the same protein fractions, we usually identify more than thousand proteins by shotgun proteomics. The data consistency obtained when comparing these independent data sets exceeds 99% of the proteins identified in the 2-D gels. Many characteristic differences in protein expression of different cells can thus be independently confirmed. Our self-designed SQL database (CPL/MUW - database of the Clinical Proteomics Laboratories at the Medical University of Vienna accessible via www.meduniwien.ac.at/proteomics/database) facilitates (i) quality management of protein identification data, which are based on MS, (ii) the detection of cell type-specific proteins and (iii) of molecular signatures of specific functional cell states. Here, we demonstrate, how the interpretation of proteome profiles obtained from human liver tissue and hepatocellular carcinoma tissue is assisted by the Clinical Proteomics Laboratories at the Medical University of Vienna-database. Therefore, we suggest that the use of reference experiments supported by a tailored database may substantially facilitate data interpretation of proteome profiling experiments.
机译：着重于生物标记物发现的蛋白质组数据解释在很大程度上依赖于比较蛋白质组分析。在这里，我们介绍基于原代细胞蛋白质组概况的数据库辅助解释策略。同时应用了2-D-PAGE和shot弹枪蛋白质组学。我们通过这两种不同的技术获得了高度的数据一致性。当对细胞质级分的二维凝胶中的胰蛋白酶斑点消化物进行质量分析时，我们通常会鉴定出数百种蛋白质。使用相同的蛋白质组分，我们通常通过by弹枪蛋白质组学鉴定出数千种蛋白质。比较这些独立数据集时获得的数据一致性超过了二维凝胶中鉴定的蛋白质的99％。因此可以独立地确认不同细胞的蛋白质表达的许多特征差异。我们自行设计的SQL数据库（CPL / MUW-维也纳医科大学临床蛋白质组学实验室的数据库可通过www.meduniwien.ac.at/proteomics/database访问），有助于（i）蛋白质识别数据的质量管理， （ii）检测细胞类型特异性蛋白，以及（iii）特定功能性细胞状态的分子标记。在这里，我们演示了维也纳医科大学数据库的临床蛋白质组学实验室如何协助从人类肝脏组织和肝细胞癌组织获得的蛋白质组概况的解释。因此，我们建议使用量身定制的数据库支持的参考实验可能会大大促进蛋白质组分析实验的数据解释。

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