Suppr超能文献

影响糖基化芯片结合谱变异性的因素。

Factors contributing to variability of glycan microarray binding profiles.

机构信息

Chemical Biology Laboratory, Center for Cancer Research, National Cancer Institute, Frederick, MD 21702, USA.

出版信息

Faraday Discuss. 2019 Oct 30;219(0):90-111. doi: 10.1039/c9fd00021f.

Abstract

Protein-carbohydrate interactions play significant roles in a wide variety of biological systems. Glycan microarrays are commonly utilized to interrogate the selectivity, sensitivity, and breadth of these complex protein-carbohydrate interactions. During the past two decades, numerous distinct glycan microarray platforms have been developed, each assembled from a variety of slide-surface chemistries, glycan-attachment chemistries, glycan presentations, linkers, and glycan densities. Comparative analyses of glycan microarray data have shown that while many protein-carbohydrate interactions behave predictably across microarrays, there are instances when various array formats produce different results. For optimal construction and use of this technology, it is important to understand sources of variances across array platforms. In this study, we performed a systematic comparison of microarray data from 8 lectins across a range of concentrations on the CFG and neoglycoprotein array platforms. While there was good general agreement on the binding specificity of the lectins on the two arrays, there were some cases of large discrepancies. Differences in glycan density and linker composition contributed significantly to variability. The results provide insights for interpreting microarray data and designing future glycan microarrays.

摘要

蛋白质-碳水化合物相互作用在广泛的生物系统中起着重要作用。糖芯片通常用于研究这些复杂的蛋白质-碳水化合物相互作用的选择性、灵敏度和广度。在过去的二十年中,已经开发出了许多不同的糖芯片平台,每个平台都由各种玻片表面化学、糖基附着化学、糖基呈现方式、连接子和糖基密度组成。对糖芯片数据的比较分析表明,尽管许多蛋白质-碳水化合物相互作用在芯片上表现出可预测的行为,但在某些情况下,各种芯片格式会产生不同的结果。为了优化该技术的构建和使用,了解不同芯片平台之间的差异来源非常重要。在这项研究中,我们对 CFG 和新糖蛋白芯片平台上一系列浓度的 8 种凝集素的芯片数据进行了系统比较。虽然两种芯片上的凝集素的结合特异性具有良好的总体一致性,但也存在一些差异较大的情况。糖密度和连接子组成的差异对变异性有很大影响。研究结果为解释芯片数据和设计未来的糖芯片提供了见解。

相似文献

5
Cross-platform comparison of glycan microarray formats.聚糖微阵列格式的跨平台比较。
Glycobiology. 2014 Jun;24(6):507-17. doi: 10.1093/glycob/cwu019. Epub 2014 Mar 22.
9
Glycan microarrays from construction to applications.糖基微阵列:从构建到应用。
Chem Soc Rev. 2022 Oct 3;51(19):8276-8299. doi: 10.1039/d2cs00452f.
10
Glycan Array Technology.糖基阵列技术。
Adv Biochem Eng Biotechnol. 2021;175:435-456. doi: 10.1007/10_2019_112.

引用本文的文献

3
New synthesis of oligosaccharides modelling the M epitope of the O-polysaccharide.模拟O-多糖M表位的寡糖的新合成。
Front Chem. 2024 Jun 21;12:1424157. doi: 10.3389/fchem.2024.1424157. eCollection 2024.
4
Serum antibody screening using glycan arrays.糖芯片血清抗体筛查。
Chem Soc Rev. 2024 Mar 4;53(5):2603-2642. doi: 10.1039/d3cs00693j.

本文引用的文献

1
Microbe-focused glycan array screening platform.聚糖微阵列筛选平台。
Proc Natl Acad Sci U S A. 2019 Feb 5;116(6):1958-1967. doi: 10.1073/pnas.1800853116. Epub 2019 Jan 22.
5
The Glycan Microarray Story from Construction to Applications.糖基微阵列:从构建到应用的故事
Acc Chem Res. 2017 Apr 18;50(4):1069-1078. doi: 10.1021/acs.accounts.7b00043. Epub 2017 Mar 17.
9
Multi-dimensional glycan microarrays with glyco-macroligands.带有糖基大环配体的多维聚糖微阵列。
Glycoconj J. 2015 Oct;32(7):483-95. doi: 10.1007/s10719-015-9580-z. Epub 2015 May 10.
10
Glycan microarrays of fluorescently-tagged natural glycans.荧光标记天然聚糖的聚糖微阵列。
Glycoconj J. 2015 Oct;32(7):465-73. doi: 10.1007/s10719-015-9584-8. Epub 2015 Apr 16.

文献AI研究员

20分钟写一篇综述,助力文献阅读效率提升50倍。

立即体验

用中文搜PubMed

大模型驱动的PubMed中文搜索引擎

马上搜索

文档翻译

学术文献翻译模型,支持多种主流文档格式。

立即体验