Abstract

With the use of DNA as building blocks, a variety of microRNA amplification-based sensing systems have been developed. Nevertheless, ultrasensitive, selective and rapid detection of microRNAs with a high signal-to-background ratio and point mutation discrimination ability remains a challenge. Herein, we propose a novel wheel drive-based DNA sensing system (NWDS) based on a self-assembled, self-quenched nanoprobe (SQP) to conduct highly specific and ultrasensitive one-step measurement of microRNAs. In this work, a signalling recognition DNA hairpin (DH) sequence with a self-complementary stem domain of 14 base pairs was used, which contained three functional regions, namely a recognition region for the target miRNA-21, a sticky region with 9 complementary nucleotides to the 3′terminus of a DNA wheel (DW) and a region for the hybridization with a quenching DNA primer (DP). The SQP was ingeniously self-assembled at room temperature by the DH and DP, which was capable of eliminating unwanted background signals. MiRNA-21 was employed as a target model to specifically activate the SQP, leading to specific hybridization between the HP and DW. With the assistance of a polymerase, an SQP-based wheel driving took place to induce hybridization/polymerization displacement cycles, initiating target recycling and DP displacement. As a result, a large amount of the newly formed hybrid SQP/DW accumulated to generate a substantially enhanced fluorescence signal. In this way, the newly proposed NWDS exhibits ultrasensitivity with a detection limit of 5.62 aM across a wide linear dynamic response range up to 200 nM, excellent selectivity with the capability to discriminate homologous miRNAs and one-base, two-base and three-base mismatched sequences, and an outstanding analytical performance in complex systems. In addition, the significant simultaneous advantages of one-step operation, rapid detection within 15 min and a high signal-to-background ratio of 26 offer a unique opportunity to promote the early diagnosis of cancer-related diseases and molecular biological analysis.

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