Inherently electroactive graphene oxide nanoplatelets as labels for single nucleotide polymorphism detection

Alessandra Bonanni, Chun Kiang Chua, Guanjia Zhao, Zdeněk Sofer, Martin Pumera

Research output: Contribution to journalArticle

78 Citations (Scopus)

Abstract

Graphene materials are being widely used in electrochemistry due to their versatility and excellent properties as platforms for biosensing. However, no records show the use of inherent redox properties of graphene oxide as a label for detection. Here for the first time we used graphene oxide nanoplatelets (GONPs) as electroactive labels for DNA analysis. The working signal comes from the reduction of the oxygen-containing groups present on the surface of GONPs. The different ability of the graphene oxide nanoplatelets to conjugate to DNA hybrids obtained with complementary, noncomplementary, and one-mismatch sequences allows the discrimination of single-nucleotide polymorphism correlated with Alzheimer's disease. We believe that our findings are very important to open a new route in the use of graphene oxide in electrochemistry.

Original languageEnglish
Pages (from-to)8546-8551
Number of pages6
JournalACS Nano
Volume6
Issue number10
DOIs
Publication statusPublished - 2012 Oct 23

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nucleotides
Nucleotides
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graphene
oxides
Electrochemistry
electrochemistry
DNA
deoxyribonucleic acid
versatility
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Oxygen
oxygen

All Science Journal Classification (ASJC) codes

  • Materials Science(all)
  • Engineering(all)
  • Physics and Astronomy(all)

Cite this

Bonanni, Alessandra ; Chua, Chun Kiang ; Zhao, Guanjia ; Sofer, Zdeněk ; Pumera, Martin. / Inherently electroactive graphene oxide nanoplatelets as labels for single nucleotide polymorphism detection. In: ACS Nano. 2012 ; Vol. 6, No. 10. pp. 8546-8551.
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Inherently electroactive graphene oxide nanoplatelets as labels for single nucleotide polymorphism detection. / Bonanni, Alessandra; Chua, Chun Kiang; Zhao, Guanjia; Sofer, Zdeněk; Pumera, Martin.

In: ACS Nano, Vol. 6, No. 10, 23.10.2012, p. 8546-8551.

Research output: Contribution to journalArticle

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