Jump to main content
Jump to site search

Issue 18, 2018
Previous Article Next Article

Highly sensitive detection of nucleic acids using a cascade amplification strategy based on exonuclease III-assisted target recycling and conjugated polyelectrolytes

Author affiliations

Abstract

In this paper, a novel ratiometric and cascade amplification strategy was developed by combining the unique signal amplification and effective fluorescence resonance energy transfer (FRET) property of conjugated polymers with the Exo III-assisted target recycling method. The target DNA (ssDNAc) could be hybridized with the duplex-stranded probe to trigger the cyclic digestion of the probe strands and lead to the continuous release of fluorescein from the probe. The proposed strategy thus shows enhanced sensitivity toward target DNA with a detection limit of 0.38 nM, which is more sensitive than the previously reported comparable biosensors based on conjugated polyelectrolytes. Furthermore, this method exhibited an improved performance to discriminate single mismatched targets through an efficient FRET-based ratiometric detection method using a conjugated polymer as a donor and an optical transducer. More importantly, this cascade amplification approach offers the advantages of simplicity, which avoids multiple utilization of probes and complex assay steps required in traditional amplification methods.

Graphical abstract: Highly sensitive detection of nucleic acids using a cascade amplification strategy based on exonuclease III-assisted target recycling and conjugated polyelectrolytes

Back to tab navigation

Supplementary files

Publication details

The article was received on 04 Jun 2018, accepted on 11 Jun 2018 and first published on 12 Jun 2018


Article type: Paper
DOI: 10.1039/C8AN01024B
Citation: Analyst, 2018,143, 4267-4272
  •   Request permissions

    Highly sensitive detection of nucleic acids using a cascade amplification strategy based on exonuclease III-assisted target recycling and conjugated polyelectrolytes

    B. Bao, Y. Pan, B. Gu, J. Chen, Y. Xu, P. Su, Y. Liu, L. Tong and L. Wang, Analyst, 2018, 143, 4267
    DOI: 10.1039/C8AN01024B

Search articles by author

Spotlight

Advertisements