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蛋白质组学技术在血清中疾病生物标志物鉴定中的应用:进展与挑战。

Proteomic technologies for the identification of disease biomarkers in serum: advances and challenges ahead.

机构信息

Wadhwani Research Center for Biosciences and Bioengineering, Department of Biosciences and Bioengineering, Indian Institute of Technology Bombay, Powai, Mumbai, India.

出版信息

Proteomics. 2011 Jun;11(11):2139-61. doi: 10.1002/pmic.201000460. Epub 2011 May 4.

Abstract

Serum is an ideal biological sample that contains an archive of information due to the presence of a variety of proteins released by diseased tissue, and serum proteomics has gained considerable interest for the disease biomarker discovery. Easy accessibility and rapid protein changes in response to disease pathogenesis makes serum an attractive sample for clinical research. Despite these advantages, the analysis of serum proteome is very challenging due to the wide dynamic range of proteins, difficulty in finding low-abundance target analytes due to the presence of high-abundance serum proteins, high levels of salts and other interfering compounds, variations among individuals and paucity of reproducibility. Sample preparation introduces pre-analytical variations and poses major challenges to analyze the serum proteome. The label-free detection techniques such as surface plasmon resonance, microcantilever, few nanotechniques and different resonators are rapidly emerging for the analysis of serum proteome and they have exhibited potential to overcome few limitations of the conventional techniques. In this article, we will discuss the current status of serum proteome analysis for the biomarker discovery and address key technological advancements, with a focus on challenges and amenable solutions.

摘要

血清是一种理想的生物样本,由于存在各种由病变组织释放的蛋白质,因此包含了大量的信息档案,血清蛋白质组学在疾病生物标志物的发现方面引起了相当大的兴趣。由于易于获取且对疾病发病机制的快速蛋白质变化,血清是临床研究的有吸引力的样本。尽管有这些优势,但由于蛋白质的广泛动态范围,由于存在高丰度的血清蛋白质而难以找到低丰度的靶标分析物,高浓度的盐和其他干扰化合物,个体之间的差异以及缺乏重现性,因此分析血清蛋白质组非常具有挑战性。样品制备会引入分析前的变化,并对分析血清蛋白质组构成主要挑战。基于表面等离子体共振、微悬臂、纳米技术和不同谐振器的无标记检测技术正在迅速涌现,用于分析血清蛋白质组,并且它们已经表现出克服传统技术的一些局限性的潜力。在本文中,我们将讨论用于生物标志物发现的血清蛋白质组分析的现状,并解决关键的技术进步,重点是挑战和可行的解决方案。

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