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A Sensitive and Low background Fluorescent Sensing Strategy Based on g-C3N4-MnO2 Sandwich Nanocomposite and Liposome Amplification for Ricin Detection

Abstract

Ricin is an extremely potent ribosomal inactivating protein and serve as a likely food biocontaminant or biological weapon. Thus, simple, sensitive and accurate analytical assays capable of detecting ricin are urgently needed to establish. Herein, we present a novel method for ricin B-chain (RTB) detection by using a highly efficient hybrid probe formed by linking glucose oxidase (GOD)-encapsulated liposome (GOD-L) to magnetic beads (MBs) through the hybridization between aptamer and blocker and a new low background g-C3N4-MnO2 sandwich nanocomposite through fluorescence resonance energy transfer (FRET) between g-C3N4 nanosheet and MnO2. In the presence of RTB, the strong binding between RTB and aptamer can release the blocker linked liposome from the surface of MBs. After magnetic separation, the decomposed liposome can release GOD to catalyze the oxidation of glucose, generating a certain amount of H2O2. Then, H2O2 can reduce MnO2 of the g-C3N4-MnO2 nanocomposite to Mn2+, which leads to the elimination of FRET. And thus, the fluorescence of g-C3N4 nanosheet was turned-on. Because of the excellent signal amplification ability of liposome and the characteristic of highly sensitive respone of g-C3N4-MnO2 nanocomposite toward H2O2, RTB could be detected sensitively based on the significantly enhanced fluorescent intensity. The linear range was from 0.25 μg/mL to 50 μg/mL and the limit of detection (LOD) was 190 ng/mL. Moreover, the proposed assay was successfully applied in the detection of entire ricin toxin in Castor seed.

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Publication details

The article was received on 03 Jul 2018, accepted on 27 Sep 2018 and first published on 30 Sep 2018


Article type: Paper
DOI: 10.1039/C8AN01217B
Citation: Analyst, 2018, Accepted Manuscript
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    A Sensitive and Low background Fluorescent Sensing Strategy Based on g-C3N4-MnO2 Sandwich Nanocomposite and Liposome Amplification for Ricin Detection

    C. Men, C. H. Li, X. M. Wei, J. J. Liu, Y. X. Liu, C. Z. Huang and S. J. Zhen, Analyst, 2018, Accepted Manuscript , DOI: 10.1039/C8AN01217B

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