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基于 Glycocapture 的蛋白质组学用于分泌组分析。

Glycocapture-based proteomics for secretome analysis.

机构信息

Institute for Molecular Medicine and Cell Research, University of Freiburg, Stefan-Meier-Strasse 17, Freiburg, Germany.

出版信息

Proteomics. 2013 Feb;13(3-4):512-25. doi: 10.1002/pmic.201200414. Epub 2013 Jan 14.

DOI:10.1002/pmic.201200414
PMID:23197367
Abstract

Protein glycosylation represents the most abundant extracellular posttranslational modification in multicellular organisms. These glycoproteins unequivocally comprise the major biomolecules involved in extracellular processes, such as growth factors, signaling proteins for cellular communication, enzymes, and proteases for on- and off-site processing. It is now known that altered protein glycosylation is a hallmark event in many different pathologies. Glycoproteins are found mostly in the so-called secretome, which comprises classically and nonclassically secreted proteins and protein fragments that are released from the cell surface through ectodomain shedding. Due to biological complexity and technical difficulty, comparably few studies have taken an in-depth investigation of cellular secretomes using system-wide approaches. The cellular secretomes are considered to be a valuable source of therapeutic targets and novel biomarkers. It is not surprising that many existing biomarkers, including biomarkers for breast, ovarian, prostate, and colorectal cancers are glycoproteins. Focused analysis of secreted glycoproteins could thus provide valuable information for early disease diagnosis, and surveillance. Furthermore, since most secreted proteins are glycosylated and glycosylation predominantly targets secreted proteins, the glycan/sugar moiety itself can be used as a chemical "handle" for the targeted analysis of cellular secretomes, thereby reducing sample complexity and allowing detection of low abundance proteins in proteomic workflows. This review will focus on various glycoprotein enrichment strategies that facilitate proteomics-based technologies for the quantitative analysis of cell secretomes and cell surface proteomes.

摘要

蛋白质糖基化是多细胞生物中最丰富的细胞外翻译后修饰。这些糖蛋白无疑包含了参与细胞外过程的主要生物分子,如生长因子、细胞通讯的信号蛋白、用于原位和异位加工的酶和蛋白酶。现在已知,蛋白质糖基化的改变是许多不同病理过程的一个标志事件。糖蛋白主要存在于所谓的分泌组中,分泌组包括经典和非经典分泌蛋白以及通过细胞外结构域脱落从细胞表面释放的蛋白片段。由于生物学复杂性和技术难度,使用系统方法对细胞分泌组进行深入研究的比较少。细胞分泌组被认为是治疗靶点和新型生物标志物的有价值来源。许多现有的生物标志物,包括乳腺癌、卵巢癌、前列腺癌和结直肠癌的生物标志物都是糖蛋白,这并不奇怪。因此,对分泌糖蛋白的集中分析可以为早期疾病诊断和监测提供有价值的信息。此外,由于大多数分泌蛋白都被糖基化,糖基化主要针对分泌蛋白,聚糖/糖部分本身可以用作细胞分泌组靶向分析的化学“把手”,从而降低样品复杂性并允许在蛋白质组学工作流程中检测低丰度蛋白。这篇综述将重点介绍各种糖蛋白富集策略,这些策略促进了基于蛋白质组学的技术对细胞分泌组和细胞表面蛋白质组的定量分析。

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Glycocapture-based proteomics for secretome analysis.基于 Glycocapture 的蛋白质组学用于分泌组分析。
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引用本文的文献

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Secretomics-A Key to a Comprehensive Picture of Unconventional Protein Secretion.分泌组学——全面了解非常规蛋白质分泌的关键
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2
Chemical Glycoproteomics.化学糖蛋白质组学
Chem Rev. 2016 Dec 14;116(23):14277-14306. doi: 10.1021/acs.chemrev.6b00023. Epub 2016 Nov 18.
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Glycoproteins and glycoproteomics in pancreatic cancer.胰腺癌中的糖蛋白与糖蛋白质组学
World J Gastroenterol. 2016 Nov 14;22(42):9288-9299. doi: 10.3748/wjg.v22.i42.9288.
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Targeted discovery and validation of plasma biomarkers of Parkinson's disease.帕金森病血浆生物标志物的靶向发现与验证。
J Proteome Res. 2014 Nov 7;13(11):4535-45. doi: 10.1021/pr500421v. Epub 2014 Jun 11.
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A universal chemical enrichment method for mapping the yeast N-glycoproteome by mass spectrometry (MS).一种通过质谱法(MS)绘制酵母N-糖蛋白质组图谱的通用化学富集方法。
Mol Cell Proteomics. 2014 Jun;13(6):1563-72. doi: 10.1074/mcp.M113.036251. Epub 2014 Apr 1.
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Endoplasmic reticulum glucosidases and protein quality control factors cooperate to establish biotrophy in Ustilago maydis.内质网糖苷酶和蛋白质质量控制因子共同作用于建立玉米黑粉菌的生物寄生。
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