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Novel approach to fabrication of DNA Biosensor Based on a Carboxylated Graphene Oxide Decorated with Fe3O4 NPs for the Detection of Typhoidal Salmonella

Journal 2023 · IF 1.5 · 发表于 2023 年 6 月 26 日
作者: Shichao Xu,Hao Duo,Chunming Zheng,Shihuai Zhao,Shidong Song,Gabriel Simon
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摘要

Diseases caused by typhoidal salmonella have led to a wide range of panic. It is thereby critically urgent to develop high-efficiency, ultrasensitive techniques for typhoidal salmonella detection. Carboxylated graphene oxide (CGO), features as one of the most crucial substrates to immobilize probe DNA for the fabrication of DNA biosensor, has been studied extensively so far. However, the reagents involved in the protocols proposed previously due to their strong alkalinity and extremely high reducing properties would impose significant impact to their performance and application. Herein, we develop a novel strategy for effective carboxylation graphene oxide with sodium citrate and chloroacetic acid. X-ray photoelectron spectroscopy (XPS) results demonstrate the density of carboxyl is improved more than twice, in consistent with the results of nuclear magnetic resonance (NMR). Furthermore, decorated with cost-effective Fe 3 O 4 NPs, the conductivity of CGO could be enhanced remarkably, furthermore, far more 5’-end amino labeled probe DNA would be stably grafted. The performance of stepwise modification of the bioelectrodes is carried out by cyclic voltammetry (CV) and electrochemical impedance spectroscopes (EIS). Differential pulse voltammetry (DPV) studies exhibit a linear response ranging from 10 -17 to 10 -9 M for target DNA analysis with the detection limit up to 3.16×10 -18 M, using methylene blue (MB) as a redox indicator under optimal conditions. In addition, the as-prepared biosensor provides predominant capability for discriminating the similar target DNA sequences. Eventually, the proposed biosensor is surveyed by real samples and it shows outstanding performance. Consequently, the developed ssDNA/Fe 3 O 4 NPs/CGO/GCE can be a promising candidate for real patient samples analysis.

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