ABSTRACT
Bio-instructive materials that prevent bacterial biofilm formation and drive an appropriate host immune response have the potential to significantly reduce the burden of medical device-associated infections. As bacterial surface attachment is sensitive to surface topography, we experimentally surveyed 2,176 combinatorially generated shapes using an unbiased high-throughput micro topographical polystyrene polymer chip screen. This identified topographies that reduced colonization in vitro by up to 15-fold compared with a flat surface for both motile and non-motile bacterial pathogens. Equivalent reductions were achieved on polyurethane, a polymer commonly used in medical devices. Using machine learning methods, a set of design rules based on generalisable topo-descriptors was established for predicting bacteria-resistant micro topographies. In a murine foreign body infection model, anti-attachment topographies were shown to be refractory to P. aeruginosa colonization and serendipitously, the fibrotic response to the implant was reduced, offering control of foreign body response using simple topographical patterning of non-eluting implants.
Competing Interest Statement
The authors have declared no competing interest.
Footnotes
↵† joint senior authors
-Author list updated and new in vivo data included -link to online materials added