A DNA Logic Gate Automaton for detection of Rabies and other Lyssaviruses

Pavithra Vijayakumar; Joanne Macdonald

doi:10.1002/cphc.201700072

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A DNA Logic Gate Automaton for detection of Rabies and other Lyssaviruses

Journal article

Open access

Peer reviewed

A DNA Logic Gate Automaton for detection of Rabies and other Lyssaviruses

Pavithra Vijayakumar and Joanne Macdonald

ChemPhysChem, Vol.18(13), pp.1735-1741

2017

DOI: https://doi.org/10.1002/cphc.201700072

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Abstract

Immediate activation of biosensors is not always desirable, particularly if activation is due to non-specific interactions. Here we demonstrate the use of deoxyribozyme-based logic gate networks arranged into visual displays to precisely control activation of biosensors, and demonstrate a prototype molecular automaton able to discriminate between seven different genotypes of Lyssaviruses, including Rabies virus. The device uses novel mixed-base logic gates to enable detection of the large diversity of Lyssavirus sequence populations, while a NOT logic gate prevents non-specific activation across genotypes. The resultant device provides a user-friendly digital-like, but molecule-powered, dot-matrix text output for unequivocal results read-out that is highly relevant for point of care applications.

Details

Title: A DNA Logic Gate Automaton for detection of Rabies and other Lyssaviruses
Authors: Pavithra Vijayakumar (Author) - Columbia University, United States
Joanne Macdonald (Author) - University of the Sunshine Coast - Faculty of Science, Health, Education and Engineering
Publication details: ChemPhysChem, Vol.18(13), pp.1735-1741
Publisher: Wiley - V C H Verlag GmbH & Co. KGaA
Date published: 2017
DOI: 10.1002/cphc.201700072
ISSN: 1439-7641
Copyright note: Copyright © 2017. This is the accepted version of the following article: Vijayakumar, Pavithra; Macdonald, J (2017). A DNA Logic Gate Automaton for detection of Rabies and other Lyssaviruses. 18:13 1735-1741, which has been published in final form at http://dx.doi.org/10.1002/cphc.201700072
Organisation Unit: School of Science and Engineering - Legacy; University of the Sunshine Coast, Queensland; School of Science, Technology and Engineering; Centre for Bioinnovation
Language: English
Record Identifier: 99451057202621
Output Type: Journal article

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Collaboration types: Domestic collaboration; International collaboration
Web Of Science research areas: Chemistry, Physical; Physics, Atomic, Molecular & Chemical

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