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蛋白质组微阵列技术及其应用:更高、更宽、更深。

Proteome microarray technology and application: higher, wider, and deeper.

机构信息

Shanghai Center for Systems Biomedicine, Key Laboratory of Systems Biomedicine (Ministry of Education), Shanghai Jiao Tong University , Shanghai , China.

School of Pharmacy, Shanghai Jiao Tong University , Shanghai , China.

出版信息

Expert Rev Proteomics. 2019 Oct;16(10):815-827. doi: 10.1080/14789450.2019.1662303. Epub 2019 Sep 4.

Abstract

: Protein microarray is a powerful tool for both biological study and clinical research. The most useful features of protein microarrays are their miniaturized size (low reagent and sample consumption), high sensitivity and their capability for parallel/high-throughput analysis. The major focus of this review is functional proteome microarray. : For proteome microarray, this review will discuss some recently constructed proteome microarrays and new concepts that have been used for constructing proteome microarrays and data interpretation in past few years, such as PAGES, M-NAPPA strategy, VirD technology, and the first protein microarray database. this review will summarize recent proteomic scale applications and address the limitations and future directions of proteome microarray technology. : Proteome microarray is a powerful tool for basic biological and clinical research. It is expected to see improvements in the currently used proteome microarrays and the construction of more proteome microarrays for other species by using traditional strategies or novel concepts. It is anticipated that the maximum number of features on a single microarray and the number of possible applications will be increased, and the information that can be obtained from proteome microarray experiments will more in-depth in the future.

摘要

蛋白质微阵列是生物研究和临床研究的有力工具。蛋白质微阵列最有用的特点是其微型化(试剂和样品消耗低)、高灵敏度和并行/高通量分析的能力。本篇综述的主要重点是功能性蛋白质组微阵列。

对于蛋白质组微阵列,本文将讨论一些最近构建的蛋白质组微阵列和过去几年中用于构建蛋白质组微阵列和数据解释的新概念,如 PAGES、M-NAPPA 策略、VirD 技术和第一个蛋白质微阵列数据库。本文将总结最近蛋白质组规模的应用,并探讨蛋白质组微阵列技术的局限性和未来方向。

蛋白质组微阵列是基础生物学和临床研究的有力工具。预计将看到当前使用的蛋白质组微阵列的改进,并通过使用传统策略或新的概念构建更多用于其他物种的蛋白质组微阵列。预计单个微阵列上的特征数量和可能的应用数量将会增加,并且从蛋白质组微阵列实验中获得的信息将会更加深入。

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