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Detection of enzyme biomarkers originating from either bio-fluids or contaminating microorganisms is of utmost importance in clinical diagnostics and food safety. Herein, we present a simple, low-cost and easy-to-use sensing approach based on the switchable peroxidase-mimicking activity of plasmonic gold nanoparticles (AuNPs) that can catalyse for the oxidation of 3, 3o, 5o5-tetramethylbenzidine (TMB) for the determination of protease enzyme. The AuNP surface is modified with casein, showing dual functionalities. The first function of the coating molecule is to suppress the intrinsic peroxidase-mimicking activity of AuNPs by up to 77.1%, due to surface shielding effects. Secondly, casein also functions as recognition sites for the enzyme biomarker. In the presence of protease, the enzyme binds to and catalyses the degradation of the coating layer on the AuNP surface, resulting in the recovery of peroxidase-mimicking activity. This is shown visually in the development of a blue colored product (oxidised TMB) or spectroscopically as an increase in absorbance at 370 and 650 nm. This mechanism allows for the detection of protease at 44 ngdmL-1 in 90 min. The nanosensor circumvents issues associated with current methods of detection in terms of ease of use, compatibility with point-of-care testing, low-cost production and short analysis time. The sensing approach has also been applied for the detection of protease spiked in ultra-heat treated (UHT) milk and synthetic human urine samples at a limit of detection of 490 and 176 ngdmL-1, respectively, showing great potential in clinical diagnostics, food safety and quality control.


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Unusual switchable peroxidase-mimicking nanozyme for the determination of proteolytic biomarker

Show Author's information Claire McVey1Natasha Logan1Nguyen T. K. Thanh2,3Christopher Elliott1Cuong Cao1,4( )
Institute for Global Food Security, School of Biological Sciences, Queenos University Belfast, 18-30 Malone Road, Belfast, BT9 5BN, UK
Biophysics Group, Department of Physics and Astronomy, University College London, London, WC1E 6BT, UK
UCL Healthcare Biomagnetic and Nanomaterials Laboratories, 21 Albemarle Street, London W1S 4BS, UK
Material and Advanced Technologies for Healthcare, Queenos University Belfast, 18-30 Malone Road, Belfast, BT9 5BN, UK

Abstract

Detection of enzyme biomarkers originating from either bio-fluids or contaminating microorganisms is of utmost importance in clinical diagnostics and food safety. Herein, we present a simple, low-cost and easy-to-use sensing approach based on the switchable peroxidase-mimicking activity of plasmonic gold nanoparticles (AuNPs) that can catalyse for the oxidation of 3, 3o, 5o5-tetramethylbenzidine (TMB) for the determination of protease enzyme. The AuNP surface is modified with casein, showing dual functionalities. The first function of the coating molecule is to suppress the intrinsic peroxidase-mimicking activity of AuNPs by up to 77.1%, due to surface shielding effects. Secondly, casein also functions as recognition sites for the enzyme biomarker. In the presence of protease, the enzyme binds to and catalyses the degradation of the coating layer on the AuNP surface, resulting in the recovery of peroxidase-mimicking activity. This is shown visually in the development of a blue colored product (oxidised TMB) or spectroscopically as an increase in absorbance at 370 and 650 nm. This mechanism allows for the detection of protease at 44 ngdmL-1 in 90 min. The nanosensor circumvents issues associated with current methods of detection in terms of ease of use, compatibility with point-of-care testing, low-cost production and short analysis time. The sensing approach has also been applied for the detection of protease spiked in ultra-heat treated (UHT) milk and synthetic human urine samples at a limit of detection of 490 and 176 ngdmL-1, respectively, showing great potential in clinical diagnostics, food safety and quality control.

Keywords:

gold nanoparticles, peroxidase-mimicking, nanozyme, enzyme detection, biomarkers
Received: 16 August 2018 Revised: 22 October 2018 Accepted: 06 November 2018 Published: 27 November 2018 Issue date: March 2019
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Publication history

Received: 16 August 2018
Revised: 22 October 2018
Accepted: 06 November 2018
Published: 27 November 2018
Issue date: March 2019

Copyright

© The Author(s) 2018

Acknowledgements

Acknowledgements

The author C. M. and N. L. thank the PhD studentship support from the Department of Employment and Learning for Northern Ireland (DEL); C. C. thanks the strong support from the Central Research Support Funds of Queen's University Belfast via a start-up grant, the support from the Agri-Food Quest Competence Centre R&D funding programme sponsored by Invest Northern Ireland Agency (Invest NI), and the support from the Queen's University of Belfast AMR Network (QUBAN) sponsored by the UK's Engineering and Physical Sciences Research Council (EPSRC).

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