Facile design of multifunction-integrated linear oligonucleotide probe with multiplex amplification effect for label-free and highly sensitive GMO biosensing.
Yan C, Xu J, Yao B, Yang L, Yao L, Liu G, Chen W.
Talanta. 2022; 236(): 122821

Abstract

Well-defined structures and compositions of nucleic acids afford oligonucleotide probes with unique chemical properties and biological functions for various biosensing applications. Herein, a unique and special oligonucleotide probe, named multifunction-integrated linear oligonucleotide probe (MI-LOP), was facile designed and reported for label-free and turn-on fluorescent detection of the codon component of genetically modified organisms (GMOs). The MI-LOP contains four different functional regions including recognition of target, serving as polymerization template, and creating polymerization primer-linked G-quadruplex (PP-G-quadruplex). Without the aid of any other oligonucleotides, the introduction of target DNA can make each function of the MI-LOP executed one-by-one, during which the species of target DNA, target analogue, and PP-G-quadruplex can be cyclically utilized and in turn induce a multiplex signal amplification responsible for substantial collection of the G-quadruplex moieties under isothermal conditions. The stable G-quadruplexes can combine with N-methyl mesoporphyrin IX (NMM) and function as efficient fluorescence light-up probes, rapidly leading to a dramatic increase in the fluorescence intensity for the amplified detection of the target codon component. Our results strongly demonstrate that the developed MI-LOP with multiplex amplification effect confers the sensing strategy a high sensitivity and specificity for quantitative and qualitative detection of the target codon. And it has also been successfully applied for analyzing target codon in the complex extractions of soybean. The achievements highlight the significance of using oligonucleotide probes as promising analytical tools to promote the basic biochemical research and help in food and environmental analysis. CI - Copyright (c) 2021 Elsevier B.V. All rights reserved.



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