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破译细胞分泌组的方法。

Methodologies to decipher the cell secretome.

作者信息

Mukherjee Paromita, Mani Sridhar

机构信息

Department of Genetics, Albert Einstein College of Medicine, Bronx, New York, 10461, USA.

出版信息

Biochim Biophys Acta. 2013 Nov;1834(11):2226-32. doi: 10.1016/j.bbapap.2013.01.022. Epub 2013 Jan 31.

Abstract

The cell secretome is a collection of proteins consisting of transmembrane proteins (TM) and proteins secreted by cells into the extracellular space. A significant portion (~13-20%) of the human proteome consists of secretory proteins. The secretory proteins play important roles in cell migration, cell signaling and communication. There is a plethora of methodologies available like Serial Analysis of Gene Expression (SAGE), DNA microarrays, antibody arrays and bead-based arrays, mass spectrometry, RNA sequencing and yeast, bacterial and mammalian secretion traps to identify the cell secretomes. There are many advantages and disadvantages in using any of the above methods. This review aims to discuss the methodologies available along with their potential advantages and disadvantages to identify secretory proteins. This review is a part of a Special issue on The Secretome. This article is part of a Special Issue entitled: An Updated Secretome.

摘要

细胞分泌蛋白质组是由跨膜蛋白(TM)和细胞分泌到细胞外空间的蛋白质组成的蛋白质集合。人类蛋白质组中相当一部分(约13-20%)由分泌蛋白组成。分泌蛋白在细胞迁移、细胞信号传导和通讯中发挥着重要作用。有大量方法可用于识别细胞分泌蛋白质组,如基因表达序列分析(SAGE)、DNA微阵列、抗体阵列和基于珠子的阵列、质谱分析、RNA测序以及酵母、细菌和哺乳动物分泌陷阱。使用上述任何一种方法都有许多优点和缺点。本综述旨在讨论可用于识别分泌蛋白的方法及其潜在的优缺点。本综述是关于分泌蛋白质组特刊的一部分。本文是题为:更新后的分泌蛋白质组的特刊的一部分。

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本文引用的文献

1
Targeted proteomics of the secretory pathway reveals the secretome of mouse embryonic fibroblasts and human embryonic stem cells.
Mol Cell Proteomics. 2012 Dec;11(12):1829-39. doi: 10.1074/mcp.M112.020503. Epub 2012 Sep 15.
2
Transcriptome complexity and riboregulation in the human pathogen Helicobacter pylori.
Front Cell Infect Microbiol. 2012 Feb 21;2:14. doi: 10.3389/fcimb.2012.00014. eCollection 2012.
3
Functional annotation of the human fat cell secretome.
Arch Physiol Biochem. 2012 Jul;118(3):84-91. doi: 10.3109/13813455.2012.685745. Epub 2012 May 23.
4
6
RNA-Seq reveals different mRNA abundance of transporters and their alternative transcript isoforms during liver development.
Toxicol Sci. 2012 Jun;127(2):592-608. doi: 10.1093/toxsci/kfs107. Epub 2012 Mar 27.
7
RNA-Seq quantification of the human small airway epithelium transcriptome.
BMC Genomics. 2012 Feb 29;13:82. doi: 10.1186/1471-2164-13-82.
8
Biomarkers quantification with antibody arrays in cancer early detection.
Clin Lab Med. 2012 Mar;32(1):33-45. doi: 10.1016/j.cll.2011.11.001. Epub 2011 Dec 15.
9
Comprehensive analysis of RNA-Seq data reveals extensive RNA editing in a human transcriptome.
Nat Biotechnol. 2012 Feb 12;30(3):253-60. doi: 10.1038/nbt.2122.
10
Using gene expression to predict differences in the secretome of human omental vs. subcutaneous adipose tissue.
Obesity (Silver Spring). 2012 Jun;20(6):1158-67. doi: 10.1038/oby.2012.14. Epub 2012 Jan 28.

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