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Au nanoparticles on two-dimensional MoS2 nanosheets as the photoanode for efficient photoelectrochemical miRNA detection

Abstract

MiRNAs are small regulatory RNAs that play crucial roles in the oncogenic state in various cancers and have shown highly promising clinical appliations as plasma-based markers for cancer classification and prognostication. Due to their electroanalytical advantages, photoelectrochemical biosensors are a very attractive alternative technology for miRNAs sensing and detection. In this work, we demostrated a novel photoelectrochemical (PEC) sensor using the in situ growed Au nanoparticles/two-dimensional molybdenum disulfide (MoS2) nanosheets heterojunction (MoS2-AuNPs) on ITO glass as the photoanode (MoS2-AuNPs/ITO). AuNPs were used as photoelectronic transfer promoter and DNA probe immobilization carrier as well. The thiol modified biotin DNA with a hairpin structure was tethered to the MoS2-AuNPs/ITO surface to form a specifically capturing layer for miRNA detection. The biotin specific protein of streptavidin was used as the signal amplifying species. This PEC sensor is structurally simple and possesses the sensitivity and specificity toward miRNA. The CV and EIS responses were evaluated to monitor the PEC anode fabrication. The stability and reproducibility of this PEC design strategy were both evaluated before it was used in analyzing the samples of miRNA in human serum. Finally, we found that this PEC displayed a broad detection linear range and a low detection limit of 4.21 fM, and it can excellently discriminate the mismatched miRNA. These findings pave the way for developing PEC sensors targeting miRNA by using nobel metals/MoS2 heterojunctions.

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Publication details

The article was accepted on 10 Feb 2018 and first published on 13 Feb 2018


Article type: Paper
DOI: 10.1039/C8AN00105G
Citation: Analyst, 2018, Accepted Manuscript
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    Au nanoparticles on two-dimensional MoS2 nanosheets as the photoanode for efficient photoelectrochemical miRNA detection

    N. Fu, Y. Hu, S. Shi, S. Ren, W. Liu, S. Su, B. Zhao, L. Weng and L. Wang, Analyst, 2018, Accepted Manuscript , DOI: 10.1039/C8AN00105G

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