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.

Wong, S., Hook, A., Gardner, W., Chang, C., Mei, Y., Davies, M., et al. (2023). Exploring the Relationship between Polymer Surface Chemistry and Bacterial Attachment Using ToF-SIMS and Self-Organizing maps. ADVANCED MATERIALS INTERFACES, 10(9 (March 24, 2023)) [10.1002/admi.202202334].

Exploring the Relationship between Polymer Surface Chemistry and Bacterial Attachment Using ToF-SIMS and Self-Organizing maps

Ballabio D.;
2023

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.
Articolo in rivista - Articolo scientifico
artificial neural networks; bacterial attachment; mass segmentation; microarrays; polymers; self-organizing maps; ToF-SIMS;
English
15-feb-2023
2023
10
9 (March 24, 2023)
2202334
open
Wong, S., Hook, A., Gardner, W., Chang, C., Mei, Y., Davies, M., et al. (2023). Exploring the Relationship between Polymer Surface Chemistry and Bacterial Attachment Using ToF-SIMS and Self-Organizing maps. ADVANCED MATERIALS INTERFACES, 10(9 (March 24, 2023)) [10.1002/admi.202202334].
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/10281/404779
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