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基于表面增强拉曼光谱的夹心免疫分析法用于寨卡病毒和登革热病毒生物标志物的多重检测

Surface-Enhanced Raman Spectroscopy-Based Sandwich Immunoassays for Multiplexed Detection of Zika and Dengue Viral Biomarkers.

作者信息

Sánchez-Purrà Maria, Carré-Camps Marc, de Puig Helena, Bosch Irene, Gehrke Lee, Hamad-Schifferli Kimberly

机构信息

Department of Engineering, University of Massachusetts Boston , 100 Morrissey Blvd., Boston, Massachusetts 02125, United States.

IQS School of Engineering , Via Augusta 390, Barcelona, 08018, Spain.

出版信息

ACS Infect Dis. 2017 Oct 13;3(10):767-776. doi: 10.1021/acsinfecdis.7b00110. Epub 2017 Sep 6.

Abstract

Zika and dengue are mosquito-borne diseases that present similar nonspecific symptoms but possess dramatically different outcomes. The first line of defense in epidemic outbreaks are rapid point-of-care diagnostics. Because many outbreaks occur in areas that are resource poor, assays that are easy to use, inexpensive, and require no power have become invaluable in patient treatment, quarantining, and surveillance. Paper-based sandwich immunoassays such as lateral flow assays (LFAs) are attractive as point-of-care solutions as they have the potential for wider deployability than lab-based assays such as PCR. However, their low sensitivity imposes limitations on their ability to detect low biomarker levels and early diagnosis. Here, we exploit the high sensitivity of surface-enhanced Raman spectroscopy (SERS) in a multiplexed assay that can distinguish between Zika and dengue nonstructural protein 1 (NS1) biomarkers. SERS-encoded gold nanostars were conjugated to specific antibodies for both diseases and used in a dipstick immunoassay, which exhibited 15-fold and 7-fold lower detection limits for Zika NS1 and dengue NS1, respectively. This platform combines the simplicity of a LFA with the high sensitivity of SERS and could not only improve Zika diagnosis but also detect diseases sooner after infection when biomarker levels are low.

摘要

寨卡病毒病和登革热都是蚊媒疾病,它们表现出相似的非特异性症状,但后果却截然不同。疫情爆发时的第一道防线是快速即时诊断。由于许多疫情发生在资源匮乏地区,因此易于使用、成本低廉且无需电力的检测方法在患者治疗、隔离和监测中变得至关重要。基于纸的夹心免疫分析,如侧向流动分析(LFA),作为即时诊断解决方案很有吸引力,因为它们比基于实验室的检测方法(如PCR)具有更广泛的部署潜力。然而,它们的低灵敏度限制了其检测低生物标志物水平和早期诊断的能力。在这里,我们在一种多重分析中利用表面增强拉曼光谱(SERS)的高灵敏度来区分寨卡病毒和登革热非结构蛋白1(NS1)生物标志物。将SERS编码的金纳米星与针对这两种疾病的特异性抗体偶联,并用于试纸条免疫分析,该分析对寨卡病毒NS1和登革热NS1的检测限分别低15倍和7倍。该平台将LFA的简单性与SERS的高灵敏度相结合,不仅可以改善寨卡病毒病的诊断,还可以在感染后生物标志物水平较低时更早地检测出疾病。

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