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一种专门分析细胞和组织分泌蛋白组的新技术。

A novel technique to specifically analyze the secretome of cells and tissues.

作者信息

Zwickl Hannes, Traxler Elisabeth, Staettner Stefan, Parzefall Wolfram, Grasl-Kraupp Bettina, Karner Josef, Schulte-Hermann Rolf, Gerner Christopher

机构信息

Department of Internal Medicine Clinic I, Institute of Cancer Research, Medical University of Vienna, Vienna, Austria.

出版信息

Electrophoresis. 2005 Jul;26(14):2779-85. doi: 10.1002/elps.200410387.

Abstract

The secretome of cells and tissues may reflect a broad variety of pathological conditions and thus represents a rich source of biomarkers. The identity of secreted proteins, usually isolated from cell supernatants or body fluids, is hardly accessible by direct proteome analysis, because these proteins are often masked by high amounts of proteins actually not secreted by the investigated cells. Here, we present a novel method for the specific detection of proteins secreted by human tissue specimen as well as cultured cells and chose liver as a model. The method is based on the metabolic labelling of proteins synthesized during a limited incubation period. Then, the cell supernatant is filtered, precipitated, and subjected to two-dimensional gel electrophoresis. Whereas fluorography detected a large number of proteins derived from residual plasma and dead cells, the autoradiographs selectively displayed genuinely secreted proteins. We demonstrate the feasibility of this approach by means of the secretomes of the hepatocellular carcinoma-derived cell line HepG2 and human liver slices. The selective identification of cell- and tissue-specific protein secretion profiles may help to identify novel sets of biomarkers for wide clinical applications.

摘要

细胞和组织的分泌蛋白质组可能反映多种病理状况,因此是丰富的生物标志物来源。通常从细胞上清液或体液中分离出的分泌蛋白的身份,通过直接蛋白质组分析很难确定,因为这些蛋白质常常被大量实际上并非由所研究细胞分泌的蛋白质所掩盖。在此,我们提出一种特异性检测人组织标本以及培养细胞分泌蛋白的新方法,并选择肝脏作为模型。该方法基于在有限孵育期内对合成蛋白质的代谢标记。然后,对细胞上清液进行过滤、沉淀,并进行二维凝胶电泳。荧光显影检测到大量源自残留血浆和死亡细胞的蛋白质,而放射自显影片则选择性地显示真正分泌的蛋白质。我们通过肝癌衍生细胞系HepG2和人肝切片的分泌蛋白质组证明了该方法的可行性。细胞和组织特异性蛋白质分泌谱的选择性鉴定可能有助于识别用于广泛临床应用的新型生物标志物组。

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