Label-free virus detection using silicon photonic microring resonators.

Label-free virus detection using silicon photonic microring resonators.
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DOI:
10.1016/j.bios.2011.10.056
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发表时间:
2012-01-15
影响因子:
12.6
通讯作者:
Bailey, Ryan C.
Bailey, Ryan C.
中科院分区:
工程技术1区
文献类型:
--
作者:
McClellan, Melinda S.;Domier, Leslie L.;Bailey, Ryan C.

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病毒通过多种机制对人类构成持续威胁,包括疾病、生物恐怖主义以及动植物食物资源的破坏。许多用于检测病毒和病毒感染的当代技术都存在局限性,例如血清学方法需要大量的样品制备或感染和可测量的免疫反应之间的漫长窗口。为了开发一种快速、经济高效且与许多其他病毒检测方法相比减少样品制备的方法,我们报告了硅光子微环谐振器的应用,用于直接、无标记地检测纯化样品以及复杂的真实分析矩阵中的完整病毒。作为一个模型系统,我们展示了豆荚斑驳病毒的定量检测,这是一种具有重要农业意义的病原体,检测限为 10 ng/mL。只需用研钵和杵研磨缓冲液中的少量叶子样品,就可以在健康对照中识别出受感染的叶子,总分析时间不到 45 分钟。考虑到基于半导体的技术固有的可扩展性和复用能力,我们认为硅光子微环谐振器非常适合作为许多病毒检测应用的有前途的分析工具。
Viruses represent a continual threat to humans through a number of mechanisms, which include disease, bioterrorism, and destruction of both plant and animal food resources. Many contemporary techniques used for the detection of viruses and viral infections suffer from limitations such as the need for extensive sample preparation or the lengthy window between infection and measurable immune response, for serological methods. In order to develop a method that is fast, cost-effective, and features reduced sample preparation compared to many other virus detection methods, we report the application of silicon photonic microring resonators for the direct, label-free detection of intact viruses in both purified samples as well as in a complex, real-world analytical matrix. As a model system, we demonstrate the quantitative detection of Bean pod mottle virus, a pathogen of great agricultural importance, with a limit of detection of 10 ng/mL. By simply grinding a small amount of leaf sample in buffer with a mortar and pestle, infected leaves can be identified over a healthy control with a total analysis time of less than 45 min. Given the inherent scalability and multiplexing capability of the semiconductor-based technology, we feel that silicon photonic microring resonators are well-positioned as a promising analytical tool for a number of viral detection applications.
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