Research Institute of Green Science and Technology, Shizuoka University, 836 Ohya Suruga-ku, Shizuoka, 422-8529, Japan.
Department of Bioscience, Graduate School of Science and Technology, Shizuoka University, 836 Ohya Suruga-ku, Shizuoka, 422-8529, Japan.
Biosens Bioelectron. 2020 Jun 1;157:112169. doi: 10.1016/j.bios.2020.112169. Epub 2020 Mar 26.
Sensitive and accurate detection methods for infectious viruses are the pressing need for effective disease diagnosis and treatment. Herein, based on VO nanoparticles-encapsulated liposomes (VONP-LPs) we demonstrate a dual-modality sensing platform for ultrasensitive detection of the virus. The sensing performance relies on intrinsic peroxidase and electrochemical redox property of VO nanoparticles (VO NPs). The target-specific antibody-conjugated VONP-LPs and magnetic nanoparticles (MNPs) enrich the virus by magnetic separation and the separated VONP-LPs bound viruses are hydrolyzed to release the encapsulated VO NPs. These released nanoparticles from captured liposomes act as peroxidase mimics and electrochemical redox indicator resulting in noticeable colorimetric and robust electrochemical dual-signal. Utilizing the superiority of dual-modality sensor with two quantitative analysis forms, norovirus like particles (NoV-LPs) can be detected by electrochemical signals with a wide linear range and low detection limit. To verify the applicability in real samples, norovirus (NoV) collected from actual clinical samples are effectively-identified with excellent accuracy. This proposed detection method can be a promising next-generation bioassay platform for early-stage diagnosis of virus disease and surveillance for public health.
灵敏准确的传染病原体检测方法是有效进行疾病诊断和治疗的迫切需求。在此,我们基于 VO 纳米粒子包被的脂质体(VONP-LPs),展示了一种用于病毒超灵敏检测的双模式传感平台。该传感性能依赖于 VO 纳米粒子(VO NPs)的固有过氧化物酶和电化学氧化还原特性。目标特异性抗体偶联的 VONP-LPs 和磁性纳米粒子(MNPs)通过磁分离富集病毒,分离的 VONP-LPs 结合的病毒被水解以释放包封的 VO NPs。从捕获的脂质体中释放出的这些纳米粒子作为过氧化物酶模拟物和电化学氧化还原指示剂,导致明显的比色和强电化学双重信号。利用双模态传感器的两种定量分析形式的优势,通过电化学信号可以检测诺如病毒样颗粒(NoV-LPs),具有较宽的线性范围和较低的检测限。为了验证在实际样品中的适用性,从实际临床样本中收集的诺如病毒(NoV)得到了有效识别,具有优异的准确性。该检测方法有望成为用于病毒病早期诊断和公共卫生监测的下一代生物分析平台。