Accurate detection of lung cancer-related microRNA through CRISPR/Cas9-assisted garland rolling circle amplification

通过CRISPR/Cas9辅助花环滚环扩增技术精准检测肺癌相关microRNA

阅读:12
作者:Xiaoya Liu, Xianxian Zhao, Ye Yuan, Zhenrui Cao, Mingxue Zhu, Tingting Li, Zhongjun Wu

Background

MicroRNA (miRNA) is reported to be closely related to a variety of pathophysiological processes for carcinoma and considered a potential biomarker for the diagnosis of lung cancer with brain metastasis. However, developing an accurate and sensitive miRNA detection method has proven to be a challenge. The

Conclusions

Our method could be used in the screening, diagnosis, and prognosis of multiple diseases without complicated thermal cycling instrumentation.

Methods

In the present study, we developed a novel approach for the sensitive and accurate detection of miRNA through integrating garland RCA and CRISPR/Cas9-assisted signal generation. In this method, target miRNA cyclized dumbbell padlock and triggered the RCA process to form long single-stranded DNA products with a repeated hairpin structure. Double-stranded DNA sequences (dsDNA) were formed with the addition of complementary sequences. With the assistance of the Cas9 enzyme for specific recognition and cleavage of formed dsDNA, RCA products were disassembled into hairpin probes. The generated hairpin probe could be unfolded by target miRNA to initiate the CHA process for signal generation.

Results

Through integration of the RCA and CHA processes, the method demonstrated favorable detection performance. The correlation equation between the signal and concentration of target miRNA was determined to be Y=312.3 × lgC + 2108, with a high correlation coefficient of 0.9786. The approach also exhibited high selectivity to the mismatched miRNAs. Conclusions: Our method could be used in the screening, diagnosis, and prognosis of multiple diseases without complicated thermal cycling instrumentation.

特别声明

1、本页面内容包含部分的内容是基于公开信息的合理引用;引用内容仅为补充信息,不代表本站立场。

2、若认为本页面引用内容涉及侵权,请及时与本站联系,我们将第一时间处理。

3、其他媒体/个人如需使用本页面原创内容,需注明“来源:[生知库]”并获得授权;使用引用内容的,需自行联系原作者获得许可。

4、投稿及合作请联系:info@biocloudy.com。