See Yoong Wong
Exploring the Relationship between Polymer Surface Chemistry and Bacterial Attachment Using ToF-SIMS and Self-Organizing maps
Wong, See Yoong; Hook, Andrew L.; Gardner, Wil; Chang, Chien‐Yi; Mei, Ying; Davies, Martyn C.; Williams, Paul; Alexander, Morgan R.; Ballabio, Davide; Muir, Benjamin W.; Winkler, David A.; Pigram, Paul J.
Authors
Dr ANDREW HOOK ANDREW.HOOK@NOTTINGHAM.AC.UK
Associate Professor
Wil Gardner
Chien‐Yi Chang
Ying Mei
Martyn C. Davies
Professor PAUL WILLIAMS PAUL.WILLIAMS@NOTTINGHAM.AC.UK
PROFESSOR OF MOLECULAR MICROBIOLOGY
Professor MORGAN ALEXANDER MORGAN.ALEXANDER@NOTTINGHAM.AC.UK
PROFESSOR OF BIOMEDICAL SURFACES
Davide Ballabio
Benjamin W. Muir
David A. Winkler
Paul J. Pigram
Abstract
Biofilm formation is a major cause of hospital-acquired infections. Research into biofilm-resistant materials is therefore critical to reduce the frequency of these events. Polymer microarrays offer a high-throughput approach to enable the efficient discovery of novel biofilm-resistant polymers. Herein, bacterial attachment and surface chemistry are studied for a polymer microarray to improve the understanding of Pseudomonas aeruginosa biofilm formation on a diverse set of polymeric surfaces. The relationships between time-of-flight secondary ion mass spectrometry (ToF-SIMS) data and biofilm formation are analyzed using linear multivariate analysis (partial least squares [PLS] regression) and a nonlinear self-organizing map (SOM). The SOM models revealed several combinations of fragment ions that are positively or negatively associated with bacterial biofilm formation, which are not identified by PLS. With these insights, a second PLS model is calculated, in which interactions between key fragments (identified by the SOM) are explicitly considered. Inclusion of these terms improved the PLS model performance and shows that, without such terms, certain key fragment ions correlated with bacterial attachment may not be identified. The chemical insights provided by the combination of PLS regression and SOM will be useful for the design of materials that support negligible pathogen attachment.
Citation
Wong, S. Y., Hook, A. L., Gardner, W., Chang, C., Mei, Y., Davies, M. C., Williams, P., Alexander, M. R., Ballabio, D., Muir, B. W., Winkler, D. A., & Pigram, P. J. (2023). Exploring the Relationship between Polymer Surface Chemistry and Bacterial Attachment Using ToF-SIMS and Self-Organizing maps. Advanced Materials Interfaces, 10(9), Article 2202334. https://doi.org/10.1002/admi.202202334
Journal Article Type | Article |
---|---|
Acceptance Date | Jan 9, 2023 |
Online Publication Date | Feb 15, 2023 |
Publication Date | Mar 24, 2023 |
Deposit Date | Apr 26, 2023 |
Publicly Available Date | Apr 27, 2023 |
Journal | Advanced Materials Interfaces |
Electronic ISSN | 2196-7350 |
Publisher | Wiley |
Peer Reviewed | Peer Reviewed |
Volume | 10 |
Issue | 9 |
Article Number | 2202334 |
DOI | https://doi.org/10.1002/admi.202202334 |
Keywords | Artificial neural networks; bacterial attachment; mass segmentation; microarrays; polymers; self-organizing maps; ToF-SIMS |
Public URL | https://nottingham-repository.worktribe.com/output/17386129 |
Publisher URL | https://onlinelibrary.wiley.com/doi/10.1002/admi.202202334 |
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Exploring the Relationship between Polymer Surface Chemistry and Bacterial Attachment Using ToF-SIMS and Self-Organizing maps
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Publisher Licence URL
https://creativecommons.org/licenses/by/4.0/
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