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使用表面等离子体共振成像技术研究抗体-抗原结合的肽微阵列的特性。

Characterisation of peptide microarrays for studying antibody-antigen binding using surface plasmon resonance imagery.

机构信息

Dynamics of Macromolecular Complexes, Laboratoire de Biologie et Pharmacologie Appliquée, UMR 8113 du CNRS, Institut d'Alembert, Ecole Normale Supérieure de Cachan, Cachan, France.

出版信息

PLoS One. 2010 Aug 13;5(8):e12152. doi: 10.1371/journal.pone.0012152.

DOI:10.1371/journal.pone.0012152
PMID:20730101
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC2921342/
Abstract

BACKGROUND

Non-specific binding to biosensor surfaces is a major obstacle to quantitative analysis of selective retention of analytes at immobilized target molecules. Although a range of chemical antifouling monolayers has been developed to address this problem, many macromolecular interactions still remain refractory to analysis due to the prevalent high degree of non-specific binding. We describe how we use the dynamic process of the formation of self assembling monolayers and optimise physical and chemical properties thus reducing considerably non-specific binding and allowing analysis of specific binding of analytes to immobilized target molecules.

METHODOLOGY/PRINCIPAL FINDINGS: We illustrate this approach by the production of specific protein arrays for the analysis of interactions between the 65kDa isoform of human glutamate decarboxylase (GAD65) and a human monoclonal antibody. Our data illustrate that we have effectively eliminated non-specific interactions with the surface containing the immobilised GAD65 molecules. The findings have several implications. First, this approach obviates the dubious process of background subtraction and gives access to more accurate kinetic and equilibrium values that are no longer contaminated by multiphase non-specific binding. Second, an enhanced signal to noise ratio increases not only the sensitivity but also confidence in the use of SPR to generate kinetic constants that may then be inserted into van't Hoff type analyses to provide comparative DeltaG, DeltaS and DeltaH values, making this an efficient, rapid and competitive alternative to ITC measurements used in drug and macromolecular-interaction mechanistic studies. Third, the accuracy of the measurements allows the application of more intricate interaction models than simple Langmuir monophasic binding.

CONCLUSIONS

The detection and measurement of antibody binding by the type 1 diabetes autoantigen GAD65 represents an example of an antibody-antigen interaction where good structural, mechanistic and immunological data are available. Using SPRi we were able to characterise the kinetics of the interaction in greater detail than ELISA/RIA methods. Furthermore, our data indicate that SPRi is well suited to a multiplexed immunoassay using GAD65 proteins, and may be applicable to other biomarkers.

摘要

背景

生物传感器表面的非特异性结合是定量分析固定化靶分子对分析物选择性保留的主要障碍。尽管已经开发了一系列化学抗污单层来解决这个问题,但由于普遍存在的高度非特异性结合,许多大分子相互作用仍然难以分析。我们描述了如何利用自组装单层形成的动态过程,并优化物理和化学性质,从而大大减少非特异性结合,并允许分析分析物与固定化靶分子的特异性结合。

方法/主要发现:我们通过生产用于分析人谷氨酸脱羧酶(GAD65)65kDa 同工型与人单克隆抗体之间相互作用的特定蛋白质阵列来说明这种方法。我们的数据表明,我们已经有效地消除了与含有固定化 GAD65 分子的表面的非特异性相互作用。这些发现有几个含义。首先,这种方法避免了背景扣除的可疑过程,并获得了更准确的动力学和平衡值,这些值不再受到多相非特异性结合的污染。其次,增强的信噪比不仅提高了灵敏度,而且提高了使用 SPR 生成动力学常数的信心,这些常数可以插入范特霍夫型分析中,以提供比较的ΔG、ΔS 和ΔH 值,使这成为一种高效、快速和有竞争力的替代 ITC 测量,用于药物和大分子相互作用机制研究。第三,测量的准确性允许应用比简单的朗缪尔单相结合更复杂的相互作用模型。

结论

1 型糖尿病自身抗原 GAD65 的抗体结合检测和测量代表了一种抗体-抗原相互作用的例子,其中有良好的结构、机制和免疫学数据。我们使用 SPRi 能够比 ELISA/RIA 方法更详细地描述相互作用的动力学。此外,我们的数据表明,SPRi 非常适合使用 GAD65 蛋白进行多重免疫分析,并且可能适用于其他生物标志物。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ece9/2921342/095e6954ded9/pone.0012152.g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ece9/2921342/48e544db0df9/pone.0012152.g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ece9/2921342/b3353a078ffe/pone.0012152.g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ece9/2921342/77033832f5ec/pone.0012152.g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ece9/2921342/095e6954ded9/pone.0012152.g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ece9/2921342/48e544db0df9/pone.0012152.g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ece9/2921342/b3353a078ffe/pone.0012152.g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ece9/2921342/77033832f5ec/pone.0012152.g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ece9/2921342/095e6954ded9/pone.0012152.g004.jpg

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