School of Life Science and Technology, Huazhong University of Science and Technology, Wuhan 430074, China.
Biosensors (Basel). 2022 Mar 13;12(3):173. doi: 10.3390/bios12030173.
The sudden outbreak of COVID-19 rapidly developed into a global pandemic, which caused tens of millions of infections and millions of deaths. Although SARS-CoV-2 is known to cause COVID-19, effective approaches to detect SARS-CoV-2 using a convenient, rapid, accurate, and low-cost method are lacking. To date, most of the diagnostic methods for patients with early infections are limited to the detection of viral nucleic acids via polymerase chain reaction (PCR), or antigens, using an enzyme-linked immunosorbent assay or a chemiluminescence immunoassay. This study developed a novel method that uses localized surface plasmon resonance (LSPR) sensors, optical imaging, and artificial intelligence methods to directly detect the SARS-CoV-2 virus particles without any sample preparation. The virus concentration can be qualitatively and quantitatively detected in the range of 125.28 to 106 vp/mL through a few steps within 12 min with a limit of detection (LOD) of 100 vp/mL. The accuracy of the SARS-CoV-2 positive or negative assessment was found to be greater than 97%, and this was demonstrated by establishing a regression machine learning model for the virus concentration prediction (R2 > 0.95).
新冠疫情的突然爆发迅速演变成全球大流行，导致数千万人感染和数百万人死亡。虽然已知 SARS-CoV-2 会导致 COVID-19，但缺乏使用方便、快速、准确和低成本的方法来检测 SARS-CoV-2。迄今为止，大多数针对早期感染患者的诊断方法仅限于通过聚合酶链反应（PCR）检测病毒核酸，或使用酶联免疫吸附试验或化学发光免疫分析检测抗原。本研究开发了一种新方法，使用局域表面等离子体共振（LSPR）传感器、光学成像和人工智能方法，无需任何样品制备即可直接检测 SARS-CoV-2 病毒颗粒。通过在 12 分钟内进行几步操作，该方法可以在 125.28 到 106 vp/mL 的范围内定性和定量检测病毒浓度，检测限（LOD）为 100 vp/mL。通过建立用于病毒浓度预测的回归机器学习模型（R2 > 0.95），发现 SARS-CoV-2 阳性或阴性评估的准确率大于 97%。
