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Graphene Doped Mn 2 O 3 Nanofibers as a Facile Electroanalytical DNA Point Mutation Detection Platform for Early Diagnosis of Breast/Ovarian Cancer
Author(s) -
Tripathy Suryasnata,
Gangwar Rahul,
Supraja Patta,
Rao AVSS Narayana,
Vanjari Siva Rama Krishna,
Singh Shiv Govind
Publication year - 2018
Publication title -
electroanalysis
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.574
H-Index - 128
eISSN - 1521-4109
pISSN - 1040-0397
DOI - 10.1002/elan.201800220
Subject(s) - graphene , point mutation , differential pulse voltammetry , materials science , mutation , dna , nanotechnology , electrode , chemistry , electrochemistry , cyclic voltammetry , gene , biochemistry
This paper demonstrates a simple, label‐free detection methodology for detecting single point DNA mutations. Single point mutation detection is a key enabler for diagnosis and prevention of several genetic disorders that manifest into cancers. Specifically for this purpose, herein, an electrochemical biosensor utilizing electrospun graphene doped manganese III oxide nanofibers (GMnO) is developed. The charge transfer resistance offered by GMnO is extremely sensitive to the localized change in the conductivity. This sensitivity, attributed to the low band gap of Mn 2 O 3 and high charge transfer kinetics of graphene, is explored in the proposed mutation detection platform. As a proof of concept, ultrasensitive detection of BRCA1 gene specific point mutation is demonstrated. The target specific single stranded probe DNA is immobilized onto GMnO modified glassy carbon working electrodes via chemisorption. Post target‐DNA hybridization, differential pulse voltammetry is employed to facilitate detection of targeted point mutation, wherein, difference in peak currents is used to distinguish the target DNA as normal or mutant. Efficiency of the proposed method is evaluated against a target concentration ranging from 10 pM−1 μM. With respect to the mutated target DNA, the LoD of the proposed device is found to be 0.8±0.069 pM. The proposed approach can be extended for detecting any mutation/hybridization of interest by simply adapting an appropriate functionalization protocol.