Suppr超能文献

表面增强拉曼光谱作为一种生物检测平台:基础、设计与应用

SERS as a bioassay platform: fundamentals, design, and applications.

作者信息

Porter Marc D, Lipert Robert J, Siperko Lorraine M, Wang Gufeng, Narayanan Radha

机构信息

Department of Chemistry, University of Utah, Salt Lake City, UT 84018, USA.

出版信息

Chem Soc Rev. 2008 May;37(5):1001-11. doi: 10.1039/b708461g. Epub 2008 Mar 18.

Abstract

Bioanalytical science is experiencing a period of unprecedented growth. Drivers behind this growth include the need to detect markers central to human and veterinary diagnostics at ever-lower levels and greater speeds. A set of parallel arguments applies to pathogens with respect to bioterrorism prevention and food and water safety. This tutorial review outlines our recent explorations on the use of surface enhanced Raman scattering (SERS) for detection of proteins, viruses, and microorganisms in heterogeneous immunoassays. It will detail the design and fabrication of the assay platform, including the capture substrate and nanoparticle-based labels. The latter, which is the cornerstone of our strategy, relies on the construction of gold nanoparticles modified with both an intrinsically strong Raman scatterer and an antibody. This labelling motif, referred to as extrinsic Raman labels (ERLs), takes advantage of the well-established signal enhancement of scatterers when coated on nanometre-sized gold particles, whereas the antibody imparts antigenic specificity. We will also examine the role of plasmon coupling between the ERLs and capture substrate, and challenges related to particle stability, nonspecific adsorption, and assay speed.

摘要

生物分析科学正经历着前所未有的发展时期。这一发展背后的驱动因素包括需要以更低的水平和更快的速度检测对人类和兽医诊断至关重要的标志物。关于生物恐怖主义预防以及食品和水安全,一系列类似的观点也适用于病原体。本教程综述概述了我们最近在表面增强拉曼散射(SERS)用于异质免疫分析中检测蛋白质、病毒和微生物方面的探索。它将详细介绍分析平台的设计和制造,包括捕获底物和基于纳米颗粒的标记物。后者是我们策略的基石,依赖于构建同时修饰有内在强拉曼散射体和抗体的金纳米颗粒。这种标记基序,称为外在拉曼标记(ERL),利用了散射体涂覆在纳米尺寸金颗粒上时已得到充分证实的信号增强,而抗体赋予抗原特异性。我们还将研究ERL与捕获底物之间的等离子体耦合作用,以及与颗粒稳定性、非特异性吸附和分析速度相关的挑战。

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