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General Strategies for Glycan Microarray Data Processing and Analysis.聚糖微阵列数据处理与分析的一般策略
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Glycan arrays: recent advances and future challenges.糖基阵列:最新进展与未来挑战。
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Profiling human serum antibodies with a carbohydrate antigen microarray.使用碳水化合物抗原微阵列分析人血清抗体。
J Proteome Res. 2009 Sep;8(9):4301-10. doi: 10.1021/pr900515y.
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New development of glycan arrays.聚糖阵列的新进展。
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Carbohydrate microarrays: key developments in glycobiology.碳水化合物微阵列:糖生物学的关键进展。
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10
Microarrays with varying carbohydrate density reveal distinct subpopulations of serum antibodies.具有不同碳水化合物密度的微阵列揭示了血清抗体的不同亚群。
J Proteome Res. 2009 Jul;8(7):3529-38. doi: 10.1021/pr9002245.

用于增强抗体分析的多维聚糖阵列

Multidimensional glycan arrays for enhanced antibody profiling.

作者信息

Zhang Yalong, Campbell Christopher, Li Qian, Gildersleeve Jeffrey C

机构信息

Chemical Biology Laboratory, Center for Cancer Research, NCI-Frederick, 376 Boyles Street, Building 376, Frederick, MD 21702, USA.

出版信息

Mol Biosyst. 2010 Sep;6(9):1583-91. doi: 10.1039/c002259d. Epub 2010 Mar 29.

DOI:10.1039/c002259d
PMID:20711537
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC3462433/
Abstract

Carbohydrate-binding antibodies play a critical role in basic and clinical research. Monoclonal antibodies that bind glycans are used to measure carbohydrate expression, and serum antibodies to glycans can be important elements of the immune response to pathogens and vaccines. Carbohydrate antigen arrays, or glycan arrays, have emerged as powerful tools for the high-throughput analysis of carbohydrate-protein interactions. Our group has focused on the development and application of neoglycoprotein arrays, a unique array format wherein carbohydrates are covalently attached to a carrier protein prior to immobilization on the surface. The neoglycoprotein format permits variations of glycan structure, glycan density, and neoglycoprotein density on a single array. The focus of this study was on the effects of neoglycoprotein density on antibody binding. First, we evaluated binding of five monoclonal antibodies (81FR2.2, HE-195, HE-193, B480, and Z2A) to the blood group A antigen and found that neoglycoprotein density had a substantial effect on recognition. Next, we profiled serum antibodies in 15 healthy individuals and showed that inclusion of multiple neoglycoprotein densities helps distinguish different subpopulations of antibodies. Finally, we evaluated immune responses induced by a prostate cancer vaccine and showed that variations in neoglycoprotein density enable one to detect antibody responses that could not be detected otherwise. Neoglycoprotein density is a useful element of diversity for evaluating antibody recognition and, when combined with variations in glycan structure and glycan density, provides multidimensional glycan arrays with enhanced performance for monoclonal antibody development, biomarker discovery, and vaccine optimization.

摘要

碳水化合物结合抗体在基础研究和临床研究中发挥着关键作用。结合聚糖的单克隆抗体用于测量碳水化合物的表达,而针对聚糖的血清抗体可能是对病原体和疫苗免疫反应的重要组成部分。碳水化合物抗原阵列,即聚糖阵列,已成为高通量分析碳水化合物 - 蛋白质相互作用的强大工具。我们的团队专注于新糖蛋白阵列的开发和应用,这是一种独特的阵列形式,其中碳水化合物在固定到表面之前先与载体蛋白共价连接。新糖蛋白形式允许在单个阵列上改变聚糖结构、聚糖密度和新糖蛋白密度。本研究的重点是新糖蛋白密度对抗体结合的影响。首先,我们评估了五种单克隆抗体(81FR2.2、HE - 195、HE - 193、B480和Z2A)与A血型抗原的结合,发现新糖蛋白密度对识别有显著影响。接下来,我们分析了15名健康个体的血清抗体,表明包含多种新糖蛋白密度有助于区分不同的抗体亚群。最后,我们评估了前列腺癌疫苗诱导的免疫反应,表明新糖蛋白密度的变化能够检测到其他方法无法检测到的抗体反应。新糖蛋白密度是评估抗体识别多样性的一个有用因素,当与聚糖结构和聚糖密度的变化相结合时,可为单克隆抗体开发、生物标志物发现和疫苗优化提供性能增强的多维聚糖阵列。