ac9b04814_si_001.pdf (2 MB)
Rolling Circular Amplification (RCA)-Assisted CRISPR/Cas9 Cleavage (RACE) for Highly Specific Detection of Multiple Extracellular Vesicle MicroRNAs
journal contributionposted on 2020-01-09, 14:03 authored by Ruixuan Wang, Xianxian Zhao, Xiaohui Chen, Xiaopei Qiu, Guangchao Qing, Hong Zhang, Liangliang Zhang, Xiaolin Hu, Zhuoqi He, Daidi Zhong, Ying Wang, Yang Luo
Multiplexed detection of extracellular vesicle (EV)-derived microRNAs (miRNAs) plays a critical role in facilitating disease diagnosis and prognosis evaluation. Herein, we developed a highly specific nucleic acid detection platform for simultaneous quantification of several EV-derived miRNAs in constant temperature by integrating the advantages of a clustered regularly interspaced short palindromic repeats/CRISPR associated nucleases (CRISPR/Cas) system and rolling circular amplification (RCA) techniques. Particularly, the proposed approach demonstrated single-base resolution attributed to the dual-specific recognition from both padlock probe-mediated ligation and protospacer adjacent motif (PAM)-triggered cleavage. The high consistency between the proposed approach RCA-assisted CRISPR/Cas9 cleavage (RACE) and reverse transcription quantitative polymerase chain reaction (RT-qPCR) in detecting EV-derived miRNAs’ abundance from both cultured cancer cells and clinical lung cancer patients validated its robustness, revealing its potentials in the screening, diagnosis, and prognosis of various diseases. In summary, RACE is a powerful tool for multiplexed, specific detection of nucleic acids in point-of-care diagnostics and field-deployable analysis.
PAMapproachdual-specific recognitioncleavagelung cancer patientsfield-deployable analysiscancer cellspadlock probe-mediated ligationEV-derived miRNAsextracellular vesicleSpecific Detectionpolymerase chain reactionMultiple Extracellular Vesicle MicroRNAs Multiplexed detectionprognosis evaluationsingle-base resolutionRolling Circular AmplificationRCARACEpoint-of-care diagnosticsacid detection platformCRISPRdisease diagnosis