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An aptamer based voltammetric biosensor for endotoxins using a functionalized graphene and molybdenum disulfide composite as a new nanocarrier

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Abstract

Lipopolysaccharides (LPS), known as endotoxins, can cause a strong inflammatory response and lead to multiple organ failure in severe cases. This work reports a simple label-free voltammetric aptasensor for highly sensitive determination of LPS using a polyethyleneimine (PEI) functionalized reduced graphene oxide (rGO) and molybdenum disulfide (MoS2) composite (PEI-rGO-MoS2) as a new nanocarrier for electroactive toluidine blue (TB). The PEI-rGO-MoS2 nanocomposite with high electrical conductivity and large specific surface area can greatly increase the loading of TB and facilitate electron transfer from TB to an electrode. Then gold nanoparticles (AuNPs) were utilized to immobilize a thiolated LPS binding aptamer (LBA), which not only exhibited excellent biocompatibility, but also significantly amplified the electrochemical signal of TB. The proposed aptasensor exhibited high sensitivity for LPS and showed a wide linear range from 5.0 × 10−5 ng mL−1 to 2.0 × 102 ng mL−1 with a low limit of detection (LOD) of 3.01 × 10−5 ng mL−1, which overcame the shortcomings of traditional detection methods and achieved fast and accurate detection of LPS. Moreover, it exhibited excellent recovery and specificity upon spiking LPS in serum samples, indicating that this method has promising application in the field of trace analysis of LPS in clinical detection.

Graphical abstract: An aptamer based voltammetric biosensor for endotoxins using a functionalized graphene and molybdenum disulfide composite as a new nanocarrier

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Publication details

The article was received on 06 Nov 2018, accepted on 22 Nov 2018 and first published on 23 Nov 2018


Article type: Paper
DOI: 10.1039/C8AN02139B
Citation: Analyst, 2019, Advance Article
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    An aptamer based voltammetric biosensor for endotoxins using a functionalized graphene and molybdenum disulfide composite as a new nanocarrier

    Y. Yuan, L. Li, M. Zhao, J. Zhou, Z. Chen and L. Bai, Analyst, 2019, Advance Article , DOI: 10.1039/C8AN02139B

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