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Issue 18, 2015
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Colorimetric detection of sequence-specific microRNA based on duplex-specific nuclease-assisted nanoparticle amplification

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Abstract

Developing simple and rapid methods for sequence-specific microRNA (miRNA) analysis is imperative to the miRNA study and use in clinical diagnosis. We have developed a colorimetric method for miRNA detection based on duplex-specific nuclease (DSN)-assisted signal amplification coupled to the aggregation of gold nanoparticles (AuNPs). The proposed method involves two processes: target-mediated probe digestion by a DSN enzyme and probe-triggered AuNP aggregation as a switch for signal output. The reaction system consists of a rationally designed probe complex formed by two partly complementary DNA probes, and two sets of different oligonucleotide-modified AuNPs with sequences complementary to a DNA probe in the probe complex. In the presence of target miRNA, the probe complex is invaded, resulting in the formation of a miRNA-probe heteroduplex as the substrate of the DSN enzyme, and releasing the other probe to link to the AuNPs. The proposed method allows quantitative detection of miR-122 in the range of 20 pM to 1 nM with a detection limit of ∼16 pM, and shows an excellent ability to discriminate single-base differences. Moreover, the detection assay can be applied to accurately quantify miR-122 in cancerous cell lysates which is in excellent agreement with the results from a commercial miRNA detection kit. This method is simple, cost-effective, highly selective, and free of dye label and separation procedures.

Graphical abstract: Colorimetric detection of sequence-specific microRNA based on duplex-specific nuclease-assisted nanoparticle amplification

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Supplementary files

Article information


Submitted
06 Jul 2015
Accepted
29 Jul 2015
First published
29 Jul 2015

Analyst, 2015,140, 6306-6312
Article type
Paper
Author version available

Colorimetric detection of sequence-specific microRNA based on duplex-specific nuclease-assisted nanoparticle amplification

Q. Wang, R. Li, B. Yin and B. Ye, Analyst, 2015, 140, 6306
DOI: 10.1039/C5AN01350J

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