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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。

Microarrays with varying carbohydrate density reveal distinct subpopulations of serum antibodies.

作者信息

Oyelaran Oyindasola, Li Qian, Farnsworth David, Gildersleeve Jeffrey C

机构信息

Laboratory of Medicinal Chemistry, National Cancer Institute, 376 Boyles Street, Building 376, Frederick, Maryland 21702, USA.

出版信息

J Proteome Res. 2009 Jul;8(7):3529-38. doi: 10.1021/pr9002245.

Abstract

Antigen arrays have become important tools for profiling complex mixtures of proteins such as serum antibodies. These arrays can be used to better understand immune responses, discover new biomarkers, and guide the development of vaccines. Nevertheless, they are not perfect and improved array designs would enhance the information derived from this technology. In this study, we describe and evaluate a strategy for varying antigen density on an array and then use the array to study binding of lectins, monoclonal antibodies, and serum antibodies. To vary density, neoglycoproteins containing differing amounts of carbohydrate were synthesized and used to make a carbohydrate microarray with variations in both structure and density. We demonstrate that this method provides variations in density on the array surface within a range that is relevant for biological recognition events. The array was used to evaluate density dependent binding properties of three lectins (Vicia villosa lectin B4, Helix pomatia agglutinin, and soybean agglutinin) and three monoclonal antibodies (HBTn-1, B1.1, and Bric111) that bind the tumor-associated Tn antigen. In addition, serum antibodies were profiled from 30 healthy donors. The results show that variations in antigen density are required to detect the full spectrum of antibodies that bind a particular antigen and can be used to reveal differences in antibody populations between individuals that are not detectable using a single antigen density.

摘要

抗原阵列已成为分析血清抗体等复杂蛋白质混合物的重要工具。这些阵列可用于更好地理解免疫反应、发现新的生物标志物以及指导疫苗的研发。然而,它们并非完美无缺,改进的阵列设计将增强从该技术中获得的信息。在本研究中,我们描述并评估了一种在阵列上改变抗原密度的策略,然后使用该阵列研究凝集素、单克隆抗体和血清抗体的结合情况。为了改变密度,合成了含有不同碳水化合物量的新糖蛋白,并用于制作结构和密度均有变化的碳水化合物微阵列。我们证明,该方法可在与生物识别事件相关的范围内提供阵列表面密度的变化。该阵列用于评估三种凝集素(野豌豆凝集素B4、欧洲蜗牛凝集素和大豆凝集素)和三种结合肿瘤相关Tn抗原的单克隆抗体(HBTn-1、B1.1和Bric111)的密度依赖性结合特性。此外,还分析了30名健康供体的血清抗体。结果表明,需要改变抗原密度才能检测到结合特定抗原的全部抗体谱,并且可用于揭示个体之间抗体群体的差异,而这些差异使用单一抗原密度是无法检测到的。

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