Combinatorial discovery of microtopographical landscapes that resist biofilm formation through quorum sensing mediated autolubrication
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jats:titleAbstract</jats:title> jats:pBio-instructive materials that intrinsically inhibit biofilm formation have significant anti-biofouling potential in industrial and healthcare settings. Since bacterial surface attachment is sensitive to surface topography, we experimentally surveyed 2176 combinatorially generated shapes embossed into polymers using an unbiased screen. This identified microtopographies that, in vitro, reduce colonization by pathogens associated with medical device-related infections by up to 15-fold compared to a flat polymer surface. Machine learning provided design rules, based on generalisable descriptors, for predicting biofilm-resistant microtopographies. On tracking single bacterial cells we observed that the motile behaviour of jats:italicPseudomonas aeruginosa</jats:italic> is markedly different on anti-attachment microtopographies compared with pro-attachment or flat surfaces. Inactivation of Rhl-dependent quorum sensing in jats:italicP. aeruginosa</jats:italic> through deletion of jats:italicrhlI</jats:italic> or jats:italicrhlR</jats:italic> restored biofilm formation on the anti-attachment topographies due to the loss of rhamnolipid biosurfactant production. Exogenous provision of jats:italicN</jats:italic>-butanoyl-homoserine lactone to the jats:italicrhlI</jats:italic> mutant inhibited biofilm formation, as did genetic complementation of the jats:italicrhlI</jats:italic>, jats:italicrhlR</jats:italic> or jats:italicrhlA</jats:italic> mutants. These data are consistent with confinement-induced anti-adhesive rhamnolipid biosurfactant ‘autolubrication’. In a murine foreign body infection model, anti-attachment topographies are refractory to jats:italicP. aeruginosa</jats:italic> colonization. Our findings highlight the potential of simple topographical patterning of implanted medical devices for preventing biofilm associated infections.</jats:p>
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Acknowledgements: This work was supported by the Engineering and Physical Sciences Research Council [grant nos. EP/N006615/1, EP/X001156/1, EP/P029868/1 and EP/K005138/1] the Wellcome Trust [grant nos. 103882 and 103884], the Biotechnology and Biological Sciences Research Council [BB/R012415/1], the European Union Horizon 2020 Programme (H2020-MSCA-ITN-2015; Grant agreement 676338], the Dutch Science Foundation (NWO) [grant VENI 15075], and the Dutch province of Limburg. M.R. was also supported by the Maria Zambrano program and Research Consolidation grant (CNS2023-145299) from the Spanish Ministry of Science, Innovation and Universities. We thank Dr Emily F Smith at the Nanoscale and Microscale Research Centre (NMRC - University of Nottingham) for acquiring XPS spectra and Dr Marta M Paino with XPS data interpretation. TopoChips were imaged in the School of Life Sciences Imaging Unit (SLIM - University of Nottingham). We thank Nick Beijer and Nadia Roumans for TopoChip fabrication assistance, Chris Gell and Arsalan Latif for their help with data acquisition.
Funder: Dutch Science Foundation (NWO) [grant VENI 15075];Maria Zambrano program and Research Consolidation grant [CNS2023-145299]; Spanish Ministry of Science, Innovation and Universities.
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Wellcome Trust (Wellcome) (103882, 103884)
RCUK | Biotechnology and Biological Sciences Research Council (BBSRC) (BB/R012415/1)
EC | Horizon 2020 Framework Programme (EU Framework Programme for Research and Innovation H2020) (H2020-MSCA-ITN-2015)