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Issue 6, 2019
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A cascade toehold-mediated strand displacement strategy for label-free and sensitive non-enzymatic recycling amplification detection of the HIV-1 gene

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Abstract

In this work, a label-free fluorescence biosensor for simple detection of the HIV-1 gene was proposed by using toehold-mediated strand displacement reactions (TMSDRs) combined with a non-enzymatic target recycling amplification strategy. In this system, two TMSDRs were used. In the presence of the HIV-1 gene, an autocatalytic DNA machine can be activated. This leads to the generation of numerous free G-rich sequences, which can associate with a fluorescent dye N-methylmesoporphyrin IX (NMM) to yield an amplified fluorescence signal for the target detection. This sensing platform showed a high sensitivity towards the HIV-1 gene with a detection limit as low as 1.9 pM without any labelling, immobilization, or washing steps. The designed sensing system also exhibits an excellent selectivity for the HIV-1 gene compared with other interference DNA sequences. Furthermore, the presented biosensor is robust and has been successfully applied for the detection of the HIV-1 gene in a real biological sample with satisfactory results, suggesting that this method is promising for simple and early clinical diagnosis of HIV infection. Thanks to its simplicity, cost-effectiveness and ultrasensitivity, our proposed sensing strategy provides a universal platform for the detection of other genes by substituting the target-recognition element.

Graphical abstract: A cascade toehold-mediated strand displacement strategy for label-free and sensitive non-enzymatic recycling amplification detection of the HIV-1 gene

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Supplementary files

Article information


Submitted
03 Dec 2018
Accepted
30 Jan 2019
First published
31 Jan 2019

Analyst, 2019,144, 2173-2178
Article type
Paper

A cascade toehold-mediated strand displacement strategy for label-free and sensitive non-enzymatic recycling amplification detection of the HIV-1 gene

Q. Li, Z. Liu, D. Zhou, J. Pan, C. Liu and J. Chen, Analyst, 2019, 144, 2173
DOI: 10.1039/C8AN02340A

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