471
Views
0
CrossRef citations to date
0
Altmetric
Review Articles

Advances in the Functional Nucleic Acid Biosensors for Detection of Lead Ions

, , , , &
Pages 309-325 | Published online: 25 Jul 2021
 

Abstract

Lead ions (Pb2+) are destructive to the natural environment and public health, so the efficient detection of Pb2+ is particularly important. Although the instrumental analysis methods have high accuracy, they require high cost and precise operation, which limits their wide application. Therefore, many strategies have been extensively studied for detecting Pb2+ by biosensors. Functional nucleic acids have become an efficient tool in this field. This review focuses on the recent biosensors of detecting Pb2+ based on functional nucleic acids from 2010 to 2020, in which DNAzyme, DNA G-quadruplex and aptamer will be introduced. The biosensors are divided into three categories that colorimetric, fluorometric and electrochemical biosensors according to the different reported signals. The action mechanism and detection effect of each biosensor are explained. Finally, the present situation of nucleic acid biosensor for the detection of Pb2+ is summarized and the future research direction is prospected.

Declaration of interest statement

The authors declare that they have no conflict of interest.

Additional information

Funding

This work was supported by National Natural Science Foundation of China [21807034]; National Natural Science Foundation of Hebei Province [B2020209079].

Log in via your institution

Log in to Taylor & Francis Online

PDF download + Online access

  • 48 hours access to article PDF & online version
  • Article PDF can be downloaded
  • Article PDF can be printed
USD 61.00 Add to cart

Issue Purchase

  • 30 days online access to complete issue
  • Article PDFs can be downloaded
  • Article PDFs can be printed
USD 451.00 Add to cart

* Local tax will be added as applicable

Related Research

People also read lists articles that other readers of this article have read.

Recommended articles lists articles that we recommend and is powered by our AI driven recommendation engine.

Cited by lists all citing articles based on Crossref citations.
Articles with the Crossref icon will open in a new tab.