Molecular Recognition Research Center, Korea Institute of Science and Technology (KIST) & KIST-School, 5, Hwarang-ro 14-gil, Seongbuk-gu, Seoul, 02792, South Korea.
Sensor System Research Center, KIST, Korea.
Angew Chem Int Ed Engl. 2018 Jul 26;57(31):9716-9721. doi: 10.1002/anie.201804412. Epub 2018 Jul 6.
The current gold-standard diagnosis method for avian influenza (AI) is an embryonic egg-based hemagglutination assay followed by immunoblotting or PCR sequencing to confirm subtypes. It requires, however, specialized facilities to handle egg inoculation and incubation, and the subtyping methods relied on costly reagents. Now, the first differential sensing approach to distinguish AI subtypes is demonstrated using series of cell lines and a fluorescent sensor. Susceptibility of AI virus differs depending on genetic backgrounds of host cells. Cells were examined from different organ origins, and the infection patterns against a panel of cells were utilized for AI virus subtyping. To quantify AI infection, a highly cell-permeable fluorescent superoxide sensor was designed to visualize infection. This differential sensing strategy successfully proved discriminations of AI subtypes and demonstrated as a useful primary screening platform to monitor a large number of samples.
目前，禽流感（AI）的金标准诊断方法是基于胚胎鸡蛋的血凝检测，然后通过免疫印迹或 PCR 测序来确认亚型。然而，它需要专门的设施来进行鸡蛋接种和孵育，而且亚型鉴定方法依赖于昂贵的试剂。现在，使用一系列细胞系和荧光传感器，首次展示了用于区分 AI 亚型的差异感应方法。AI 病毒的易感性取决于宿主细胞的遗传背景。检查了来自不同器官来源的细胞，并利用针对一系列细胞的感染模式进行了 AI 病毒的亚型鉴定。为了定量 AI 感染，设计了一种高细胞通透性的荧光超氧化物传感器来可视化感染。这种差异感应策略成功地证明了 AI 亚型的区分，并作为一种有用的初步筛选平台，可用于监测大量样本。
