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竞争性激活交叉扩增结合基于智能手机的定量分析用于单核苷酸多态性的即时检测

Competitive activation cross amplification combined with smartphone-based quantification for point-of-care detection of single nucleotide polymorphism.

作者信息

Wen Junping, Gou Hongchao, Wang Siyuan, Lin Qijie, Chen Kaifeng, Wu Yuqian, Huang Xuehuan, Shen Haiyan, Qu Xiaoyun, Lin Jianhan, Liao Ming, Zhang Jianmin

机构信息

National and Regional Joint Engineering Laboratory for Medicament of Zoonoses Prevention and Control, Key Laboratory of Zoonoses, Ministry of Agriculture, Key Laboratory of Zoonoses Prevention and Control of Guangdong Province, Key Laboratory of Animal Vaccine Development, Ministry of Agriculture, Guangdong Laboratory for Lingnan Modern Agriculture, College of Veterinary Medicine, South China Agricultural University, Guangzhou, 510642, China.

Institute of Animal Health, Guangdong Academy of Agricultural Sciences, Guangzhou, 510640, China.

出版信息

Biosens Bioelectron. 2021 Jul 1;183:113200. doi: 10.1016/j.bios.2021.113200. Epub 2021 Mar 26.

Abstract

In this study, we firstly propose a novel smartphone-assisted visualization SNP genotyping method termed competitive activation cross amplification (CACA). The mutation detection strategy depends on the ingenious design of both a start primer and a verification probe with ribonucleotide insertion through competitive combination and perfect matching with the target DNA, Meanwhile, the RNase H2 enzyme was utilized to specifically cleave ribonucleotide insertion and achieve extremely specific dual verification. Simultaneously, the results allow both colorimetric and fluorescence product dual-mode visualization by using self-designed 3D-printed dual function cassette. We validated this novel CACA by analyzing the Salmonella Pullorum rfbS gene at the 237th site, successfully solve the current bottleneck of specific identification and visual detection of this pathogen. The concentration detection limits of the plasmid and genomic DNA were 1500 copies/μL and 3.98 pg/μL, respectively, and as low as the presence of 0.1% mutant-type can be distinguished from 99.9% wild-type. Combined with a powerful hand-warmer, which can provide heating more than 60 °C for 20 h to realize power-free, dual function cassette and smartphone quantitation, our novel CACA platform firstly realizes user-friendly, cost-effective, portable, rapid, and accurate POC detection of SNP.

摘要

在本研究中,我们首次提出了一种新型的智能手机辅助可视化单核苷酸多态性(SNP)基因分型方法,称为竞争性激活交叉扩增(CACA)。突变检测策略依赖于起始引物和验证探针的巧妙设计,通过与目标DNA的竞争性结合和完美匹配实现核糖核苷酸插入,同时利用核糖核酸酶H2特异性切割核糖核苷酸插入并实现高度特异性的双重验证。此外,利用自行设计的3D打印双功能盒,结果可以实现比色和荧光产物双模式可视化。我们通过分析鸡白痢沙门氏菌rfbS基因第237位的位点验证了这种新型的CACA,成功解决了目前该病原体特异性鉴定和可视化检测的瓶颈。质粒和基因组DNA的浓度检测限分别为1500拷贝/μL和3.98 pg/μL,并且能够区分低至0.1%的突变型和99.9%的野生型。结合强大的暖手器,可为双功能盒和智能手机定量提供超过60°C的加热20小时以实现无电操作,我们的新型CACA平台首次实现了用户友好、经济高效、便携、快速且准确的SNP即时检测。

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