Suppr超能文献

用于无交叉反应多重蛋白质分析的抗体共定位微阵列

Antibody Colocalization Microarray for Cross-Reactivity-Free Multiplexed Protein Analysis.

作者信息

Laforte Véronique, Lo Pik-Shan, Li Huiyan, Juncker David

机构信息

Department of Neurology and Neurosurgery, Montreal Neurological Institute, McGill University, 3801 University St., Montreal, QC, Canada, H3A 2B4.

Department of Biomedical Engineering, McGill University, 3775 University St., Montreal, QC, Canada, H3A 2B4.

出版信息

Methods Mol Biol. 2017;1619:239-261. doi: 10.1007/978-1-4939-7057-5_19.

Abstract

Measuring many proteins at once is of great importance to the idea of personalized medicine, in order to get a snapshot of a person's health status. We describe the antibody colocalization microarray (ACM), a variant of antibody microarrays which avoids reagent-induced cross-reactivity by printing individual detection antibodies atop their corresponding capture antibodies. We discuss experimental parameters that are critical for the success of ACM experiments, namely, the printing positional accuracy needed for the two printing rounds and the need for protecting dried spots during the second printing round. Using small sample volumes (less than 30 μL) and small quantities of reagents, up to 108 different targets can be measured in hundreds of samples with great specificity and sensitivity.

摘要

为了获取个人健康状况的全貌,同时检测多种蛋白质对于个性化医疗理念至关重要。我们介绍了抗体共定位微阵列(ACM),它是抗体微阵列的一种变体,通过在相应的捕获抗体之上打印单个检测抗体来避免试剂诱导的交叉反应。我们讨论了对ACM实验成功至关重要的实验参数,即两轮打印所需的打印位置精度以及第二轮打印期间保护干燥斑点的必要性。使用少量样本体积(小于30 μL)和少量试剂,可以在数百个样本中以高特异性和灵敏度检测多达108种不同的目标。

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