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Issue 7, 2019
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Target-assisted FRET signal amplification for ultrasensitive detection of microRNA

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Abstract

MicroRNA (miRNA) is a type of noncoding RNA and plays a crucial role in gene expression regulation. Sensitive identification and detection of miRNA can offer vast information for transcriptome analysis and cancer studies. Conventional PCR and molecular hybridization techniques suffer from low specificity when used for miRNA detection due to the short nucleotide length of miRNA. The extremely low abundance of miRNA in real biological samples also sets higher demands for the sensitivity of detection methods. A novel method based on target-assisted fluorescence resonance energy transfer (FRET) signal amplification was proposed for the simple and ultrasensitive detection of miRNA. A hairpin fluorescence DNA probe could hybridize with target miRNA to expose the hybridization site for the primer. After being duplexed with the nanogold-labeled primer, the fluorescent dye in the DNA probe was quenched via the FRET mechanism. In the presence of a DNA polymerase, primer-activated strand displacement released the miRNA, and then the miRNA strand could recognize and function with another DNA probe. The recycling of target miRNA and a high quenching efficiency of nanogold greatly improved the sensitivity. The detection limit of the method (1.5 fM) was lower than that of the reported strategies using a target cycling reaction, allowing trace detection of miRNA in real samples. By making full use of miRNA sequences, the method could also recognize single-base mismatches and distinguish homologous miRNAs.

Graphical abstract: Target-assisted FRET signal amplification for ultrasensitive detection of microRNA

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Publication details

The article was received on 22 Nov 2018, accepted on 10 Jan 2019 and first published on 10 Jan 2019


Article type: Paper
DOI: 10.1039/C8AN02266F
Citation: Analyst, 2019,144, 2304-2311

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    Target-assisted FRET signal amplification for ultrasensitive detection of microRNA

    B. Wang, Z. You and D. Ren, Analyst, 2019, 144, 2304
    DOI: 10.1039/C8AN02266F

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