Literature DB >> 30683412

A graphene oxide-based paper chip integrated with the hybridization chain reaction for peanut and soybean allergen gene detection.

Dan Yuan1, Jilie Kong2, Xueen Fang3, Qin Chen4.   

Abstract

Allergen genes of the peanut and soybean were selected as model targets. Four hairpin DNA probes, H1, H2, H3, H4 were designed. Cy3-labeled H1 and H2 were used to detect peanut DNA, while FAM-labeled H3 and H4 were used to detect soybean DNA. Graphene oxide (GO) was used as the adsorption material for capturing the hairpin probes, and as a selective fluorescence quencher to reduce the background signal. To develop an allergen gene detection system with a GO-based paper chip format, we integrated the hybridization chain reaction (HCR) with fluorescence resonance energy transfer (FRET) in our design. The results showed that in the absence of peanut DNA (TP) and soybean DNA (TS), the detection probes attached to the GO surface, which quenched their fluorescence. In the presence of TP or TS, however, complementary probe binding to the targets initiated HCR, producing long double-stranded DNA products that could not be absorbed onto the GO surface. Hence, a strong red or green fluorescent signal was generated. The detection limit for both peanut and soybean DNA was 1 nM using this method, indicating the high sensitivity of our approach. This method also exhibited good specificity and a single chip could be used to simultaneously detect two different targets.
Copyright © 2018 Elsevier B.V. All rights reserved.

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Keywords:  Allergen genes; Fluorescence resonance energy transfer; Graphene oxide; Hybridization chain reaction; Peanut; Soybean

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Year:  2018        PMID: 30683412     DOI: 10.1016/j.talanta.2018.12.036

Source DB:  PubMed          Journal:  Talanta        ISSN: 0039-9140            Impact factor:   6.057


  1 in total

1.  An enzyme free fluorescence resonance transfer strategy based on hybrid chain reaction and triplex DNA for Vibrio parahaemolyticus.

Authors:  Xiao-Hui Tan; Yu-Bin Li; Yan Liao; Hua-Zhong Liu
Journal:  Sci Rep       Date:  2020-11-26       Impact factor: 4.379

  1 in total

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