Race to the surface: modelling bacterial and human cell growth on dental implant surfaces

Two barriers to successful dental implant surgery are (1) the possibility of infection and (2) poor compatibility with native human cells. The mouth is colonised by millions of bacteria, living in communities called biofilms. Human cells in the mouth are in competition with these bacteria to occupy the implant surface. Infection can result in the need for implant removal, which is both costly and very painful. New materials for implants are continuously being developed, but are not making it into clinics. Testing innovative materials is challenging due to the highly complex oral environment. We are combining models of oral tissue with bacterial biofilms, to better understand how we can help human cells win the 'race to the surface'

Race to the surface: developing in vitro and in silico models of microbial and mammalian cell growth on implant surfaces

The "race to the surface" describes the competition between bacteria and eukaryotic cells for colonisation of an implant device. This thesis aimed to address gaps in modelling the oral microenvironment surrounding a dental implant material, specifically focusing on three key elements: identification of a suitable hydrogel scaffold, development of a method for calculating biofilm viability on the surface of implant materials, and exploration of a computational model of surface adhesion. For strain values up to 30%, the mechanical stiffness of porcine oral mucosa under compression was determined, with porcine as a model tissue. Acellular alginate and alginate-collagen scaffolds were then characterised to determine the concentrations that were most similar to the stiffness of the porcine mucosa. Further investigations included scanning electron microscopy, rheology, and Fourier-transform infrared spectroscopy to fully characterise the surface topography, gelling behaviour, and chemical bonds within the polymers, respectively. Blended collagen-alginate hydrogels of 2.5 mg/mL collagen with 10 mg/mL alginate and 2.5 mg/mL collagen with 5 mg/mL alginate were found to closely match the mechanical stiffness of the native tissue, as well as demonstrating desirable gelling behaviour through the formation of collagen fibrils and low concentrations of cross-linking agent required. These hydrogels were then shown to support human dermal fibroblast growth upon encapsulation within the scaffold, with high cell viability. Matrix stiffness was found to influence fibroblast morphology, with a higher stiffness resulting in rounded fibroblast morphology and a lower stiffness resulting in a spindle shape. The presence of a stratified epithelium was not confirmed and therefore further optimisation of this model is required. Alongside the refinement of this 3D model, a novel analysis tool was developed for quantifying confocal micrographs of live/dead stained bioflms. The protocol was validated on different bacterial species, and the tool demonstrated a reliable measurement of bioflm growth and cell viability. Advantages of this tool include the low computational time to analyse images, ease of use, and transparency of the image processing methods employed. Finally, a computational model of initial bacterial adhesion to a surface was developed, based on a cellular automaton. The parameters that affected this initial stage of biofilm formation were investigated. The balance between the rate of migration to the surface, division rate, and death rate of a bacterial species had a significant input on the cells adhering to the surface. If the balance of these parameters can be controlled in vitro and in vivo, then this could inform the development of strategies for preventing surface colonisation. Ultimately, the work presented in this thesis will support the development of antimicrobial strategies and novel implant devices to prevent the occurrence of dental implant infection by providing improved methods of analysing the effect of such strategies in vitro