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Combinatorial discovery of microtopographical landscapes that resist biofilm formation through quorum sensing mediated autolubrication

Author

Listed:
  • Manuel Romero

    (University of Nottingham
    University of Nottingham
    Universidade de Santiago de Compostela)

  • Jeni Luckett

    (University of Nottingham)

  • Jean-Frédéric Dubern

    (University of Nottingham
    University of Nottingham)

  • Grazziela P. Figueredo

    (University of Nottingham)

  • Elizabeth Ison

    (University of Nottingham
    University of Nottingham)

  • Alessandro M. Carabelli

    (University of Nottingham)

  • David J. Scurr

    (University of Nottingham)

  • Andrew L. Hook

    (University of Nottingham)

  • Lisa Kammerling

    (University of Nottingham)

  • Ana C. Silva

    (University of Nottingham
    University of Nottingham
    Li Ka Shing Centre)

  • Xuan Xue

    (University of Nottingham
    Xi’an Jiaotong - Liverpool University)

  • Chester Blackburn

    (University of Nottingham)

  • Aurélie Carlier

    (Maastricht University)

  • Aliaksei Vasilevich

    (Eindhoven University of Technology)

  • Phani K. Sudarsanam

    (Eindhoven University of Technology)

  • Steven Vermeulen

    (Maastricht University
    Eindhoven University of Technology)

  • David A. Winkler

    (La Trobe University)

  • Amir M. Ghaemmaghami

    (University of Nottingham)

  • Jan de Boer

    (Eindhoven University of Technology)

  • Morgan R. Alexander

    (University of Nottingham)

  • Paul Williams

    (University of Nottingham
    University of Nottingham)

Abstract

Bio-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 Pseudomonas aeruginosa is markedly different on anti-attachment microtopographies compared with pro-attachment or flat surfaces. Inactivation of Rhl-dependent quorum sensing in P. aeruginosa through deletion of rhlI or rhlR restored biofilm formation on the anti-attachment topographies due to the loss of rhamnolipid biosurfactant production. Exogenous provision of N-butanoyl-homoserine lactone to the rhlI mutant inhibited biofilm formation, as did genetic complementation of the rhlI, rhlR or rhlA 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 P. aeruginosa colonization. Our findings highlight the potential of simple topographical patterning of implanted medical devices for preventing biofilm associated infections.

Suggested Citation

  • Manuel Romero & Jeni Luckett & Jean-Frédéric Dubern & Grazziela P. Figueredo & Elizabeth Ison & Alessandro M. Carabelli & David J. Scurr & Andrew L. Hook & Lisa Kammerling & Ana C. Silva & Xuan Xue & , 2025. "Combinatorial discovery of microtopographical landscapes that resist biofilm formation through quorum sensing mediated autolubrication," Nature Communications, Nature, vol. 16(1), pages 1-18, December.
  • Handle: RePEc:nat:natcom:v:16:y:2025:i:1:d:10.1038_s41467-025-60567-x
    DOI: 10.1038/s41467-025-60567-x
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