Quantum dots-labeled strip biosensor for rapid and sensitive detection of microRNA based on target-recycled nonenzymatic amplification strategy

MicroRNAs (miRNAs) have been proved to be potential biomarkers in early cancer diagnosis. It is of great significance for rapid and sensitive detection of miRNAs, particularly with point-of-care (POC) diagnosis. Herein, it is the first time to construct quantum dots (QDs)-labeled strip biosensor based on target-recycled nonenzymatic amplification strategy for miRNA detection. In the system, QDs were served as bright, photostable signal labels, which endow this biosensor with good detection efficiency. Moreover, a target-recycled amplification strategy relies on sequence-specific hairpins strand displacement process without the assistance of enzymes, was introduced to further improve the sensitivity. Meanwhile eliminating the requirement of environment-susceptible enzyme protein makes it easy to preserve and enhances the stability and reproducibility of this sensor. Benefiting from these outstanding characteristics, this platform exhibited a good detection sensitivity range from 2fmol to 200fmol with a limit of 200amol, using only 20μL of sample within 80min. The assay was also 10-fold more sensitive than that with a conventional colloidal gold-based test strip for miRNA detection. Additionally, the analysis of miRNA in various tumor cell extracts was in accordance with the performance of quantitative realtime polymerase chain reaction (qRT-PCR). Clinical tumor samples were also tested, and 16 of 20 samples gave out positive signals, which demonstrated the practical application capacity of the biosensor. Therefore, the proposed biosensor holds great promise for potential POC applications and early cancer diagnosis. •A fluorescent strip biosensor for visual detection of miRNA is constructed.•This biosensor permits a detection limit of 200amol within 80min.•Enzyme-free, convenient, rapid and sensitive detection of miRNA is achieved.•This method can be sound basis to further develop point-of-care diagnosis.