放大器
底漆(化妆品)
病毒学
生物
分子生物学
等位基因
聚合酶链反应
遗传学
化学
基因
有机化学
作者
Yunxiang Wang,Hong Chen,Hongjuan Wei,Zhen Rong,Shengqi Wang
出处
期刊:Lab on a Chip
[The Royal Society of Chemistry]
日期:2022-01-01
卷期号:22 (8): 1531-1541
被引量:17
摘要
Several virulent variants of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) have emerged along with the spread of this virus throughout the population. Some variants can exhibit increased transmissibility and reduced immune neutralization reactivity. These changes are deeply concerning issues that may hinder the ongoing effort of epidemic control measures, especially mass vaccination campaigns. The accurate discrimination of SARS-CoV-2 and its emerging variants is essential to contain the coronavirus disease 2019 pandemic. Herein, we report a low-cost, facile, and highly sensitive diagnostic platform that can simultaneously distinguish wild-type (WT) SARS-CoV-2 and its two mutations, namely, D614G and N501Y, within 2 h. WT or mutant (M) nucleic acid fragments at each allelic locus were selectively amplified by the tetra-primer amplification refractory mutation system (ARMS)-PCR assay. Allele-specific amplicons were simultaneously detected by two test lines on a quantum dot nanobead (QB)-based dual-color fluorescent test strip, which could be interpreted by the naked eye or by a home-made fluorescent strip readout device that was wirelessly connected to a smartphone for quantitative data analysis and result presentation. The WT and M viruses were indicated and were strictly discriminated by the presence of a green or red band on test line 1 for the D614G site and test line 2 for the N501Y site. The limits of detection (LODs) for the WT and M D614G were estimated as 78.91 and 33.53 copies per μL, respectively. This assay was also modified for the simultaneous detection of the N and ORF1ab genes of SARS-CoV-2 with LODs of 1.90 and 6.07 copies per μL, respectively. The proposed platform can provide a simple, accurate, and affordable diagnostic approach for the screening of SARS-CoV-2 and its variants of concern even in resource-limited settings.
科研通智能强力驱动
Strongly Powered by AbleSci AI