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Graphene-based biosensors for detection of bacteria and their metabolic activities

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Graphene-based biosensors for detection of bacteria and their metabolic activities

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Title: Graphene-based biosensors for detection of bacteria and their metabolic activities
Author: Huang, Yinxi; Dong, Xiaochen; Liu, Yuxin; Li, Lain-Jong; Chen, Peng
Copyright year: 2011
Abstract: Graphene, which is a recently discovered single-atom-thick planar sheet of carbon atoms perfectly arranged in a honeycomb lattice, has great potential in biosensing owing to its extraordinary electrical, physical, and optical properties. In this work, we demonstrate a graphene based biosensor to electrically detect E. coli bacteria with high sensitivity and specificity. The large-sized graphene film was grown by chemical vapor deposition and functionalized with anti-E. coli antibodies and passivation layer. Significant conductance increase of the graphene device was observed after exposure to E. coli bacteria at a concentration as low as 10 cfu/mL, while no significant response was triggered by high concentration of the another bacterial strain. In addition, this biosensor was employed to detect the glucose induced metabolic activities of the bound E. coli bacteria in real time. This simple, fast, sensitive, and label-free nanoelectronic biosensor, in principle, could serve as a high throughput platform for detection of any pathogenic bacteria, and for functional studies or screening of antibacterial drugs.
Subject: DRNTU::Science::Chemistry::Organic chemistry::Antibiotics
Type: Journal Article
Series/ Journal Title: Journal of materials chemistry
School: School of Chemical and Biomedical Engineering
Rights: © 2011 The Royal Society of Chemistry. This is the author created version of a work that has been peer reviewed and accepted for publication by Journal of Materials Chemistry, The Royal Society of Chemistry. It incorporates referee’s comments but changes resulting from the publishing process, such as copyediting, structural formatting, may not be reflected in this document. The published version is available at: [DOI: http://dx.doi.org/10.1039/c1jm11436k].
Version: Accepted version

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