4.7 Article

Single strand DNA functionalized single wall carbon nanotubes as sensitive electrochemical labels for arsenite detection

期刊

TALANTA
卷 141, 期 -, 页码 122-127

出版社

ELSEVIER
DOI: 10.1016/j.talanta.2015.03.040

关键词

Electrochemical; SWCNTs; Signal transduction; Arsenite; Biosensor

资金

  1. National Natural Science Foundation of China [21305164]
  2. State Key Laboratory of Chemo/Biosensing and Chemometrics, Hunan University [2013019]
  3. Scientific Research Fund of Hunan Provincial Education Department [13C1138]

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In this work, a simple and sensitive electrochemical strategy for arsenite detection based on the ability of arsenite bound to single,strand DNA (ssDNA) and the signal transduction of single wall carbon nanotubes (SWCNTs) is developed. To realize this purpose, the ssDNA/SWCNTs complexes were formed at first by making ssDNA wrapped around SWCNTs via pi-stacking. In the presence of arsenite, the arsenite could strongly bind with the G/T bases of ssDNA and decrease the pi-pi interaction between ssDNA and SWCNTs, resulting in a certain amount of ssDNA dissociating from the complexes. The separated SWCNTs were selectively assembled on the self-assembled monolayer (SAM) modified Au electrode. Then the SWCNTs onto the SAM-modified Au electrode substantially restored heterogeneous electron transfer that was almost totally blocked by the SAM. The assembled SWCNTs could generate a considerably sensitive and specific tactic for signal transduction, which was related to the concentration of the arsenite. Through detecting the currents mediated by SWCNTs, a linear response to concentration of arsenite ranging from 0.5 to 10 ppb and a detection limit of 0.5 ppb was readily achieved with desirable specificity and sensitivity. Such a SWCNTs-based biosensor creates a simple, sensitive, nonradioactive route for detection of arsenite. In addition, this demonstration provides a new approach to fabrication of stable biosensors with favorable electrochemical properties believed to be appealing to electroanalytical applications. (C) 2015 Elsevier B.V. All rights reserved.

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