Bakshi, Shrishty, Li, Kezheng, Dong, Pin orcid.org/0000-0003-0102-236X et al. (4 more authors) (2024) Bio-inspired polydopamine layer as a versatile functionalisation protocol for silicon-based photonic biosensors. Talanta. 125300. ISSN 0039-9140
Abstract
Photonic biosensors have made major advances in recent years, achieving very high sensitivity, and progressing towards point-of-care deployment. By using photonic resonances, sensors can be label-free, which is particularly attractive for a low-cost technological realisation. A key remaining issue is the biological interface and the efficient and reliable immobilisation of binder molecules such as antibodies; many protocols are currently in use that have led to widely varying sensor performance. Here, we study a very simple and robust surface functionalisation protocol for silicon photonics, which is based on polydopamine, and we demonstrate both its simplicity and its high performance. The use of polydopamine (PDA) is inspired by molluscs, especially mussels, that employ dopamine to adhere to virtually any surface, especially in an aqueous environment. We studied the versatility of the PDA protocol by showing compatibility with 5 different disease biomarkers (Immunoglobulin (IgG), C-reactive protein (CRP), Tumour Necrosis factor-α (TNF-α), Interleukin-6 (IL-6), Matrix metalloproteinase (MMP-9) and show that the protocol is resistant to hydrolysis during incubation; the loss of functionality due to hydrolysis is a major issue for many of the functionalisation protocols commonly used for silicon-based sensors. The study using guided mode resonance-based sensors highlights the wide dynamic range of the protocol (0.01 ng/mL to 1 μg/mL), using IgG, CRP and MMP-9 protein biomarkers as exemplars. In addition, we show that the surface chemistry allows performing measurements in 10% human serum with a sensitivity as low as 10 ng/mL for IgG. We suggest that adopting this protocol will make it easier for researchers to achieve biofunctionalisation and that the biosensor community will be able to achieve more consistent results.
Metadata
Item Type: | Article |
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Authors/Creators: |
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Copyright, Publisher and Additional Information: | © 2023 The Authors. Published by Elsevier B.V. |
Dates: |
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Institution: | The University of York |
Academic Units: | The University of York > Faculty of Sciences (York) > Physics (York) The University of York > Faculty of Sciences (York) > Electronic Engineering (York) |
Depositing User: | Pure (York) |
Date Deposited: | 16 Jan 2024 16:30 |
Last Modified: | 26 Nov 2024 00:59 |
Published Version: | https://doi.org/10.1016/j.talanta.2023.125300 |
Status: | Published |
Refereed: | Yes |
Identification Number: | 10.1016/j.talanta.2023.125300 |
Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:207783 |
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