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Open AccessArticle

SAM Composition and Electrode Roughness Affect Performance of a DNA Biosensor for Antibiotic Resistance

1
Department of Biomedical Engineering, Wolfson Centre, 106 Rottenrow East, University of Strathclyde, Glasgow G1 1XQ, UK
2
FlexMedical Solutions, Eliburn Industrial Park, Livingston, EH54 6GQ, Scotland, UK
*
Author to whom correspondence should be addressed.
Biosensors 2019, 9(1), 22; https://doi.org/10.3390/bios9010022
Received: 11 December 2018 / Revised: 29 January 2019 / Accepted: 4 February 2019 / Published: 7 February 2019
Antibiotic resistance is a growing concern in the treatment of infectious disease worldwide. Point-of-care (PoC) assays which rapidly identify antibiotic resistance in a sample will allow for immediate targeted therapy which improves patient outcomes and helps maintain the effectiveness of current antibiotic stockpiles. Electrochemical assays offer many benefits, but translation from a benchtop measurement system to low-cost portable electrodes can be challenging. Using electrochemical and physical techniques, this study examines how different electrode surfaces and bio-recognition elements, i.e. the self-assembled monolayer (SAM), affect the performance of a biosensor measuring the hybridisation of a probe for antibiotic resistance to a target gene sequence in solution. We evaluate several commercially available electrodes which could be suitable for PoC testing with different SAM layers and show that electrode selection also plays an important role in overall biosensor performance. View Full-Text
Keywords: electrochemical biosensor; DNA detection; point-of-care diagnostics; electrochemical impedance spectroscopy; self-assembled monolayers (SAMs) electrochemical biosensor; DNA detection; point-of-care diagnostics; electrochemical impedance spectroscopy; self-assembled monolayers (SAMs)
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Butterworth, A.; Blues, E.; Williamson, P.; Cardona, M.; Gray, L.; Corrigan, D.K. SAM Composition and Electrode Roughness Affect Performance of a DNA Biosensor for Antibiotic Resistance. Biosensors 2019, 9, 22.

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