In a time of outburst of antibiotic-resistant bacteria, the search for alternatives is essential. Bacteriophages are starting to re-emerge as a viable therapeutic option to treat acute infections where antibiotics are not effective any longer. However, it is key to incorporate bacteriophages into suitable formulations if they are to be applied, for example, topically. Emulsions, and specifically nano-emulsions are well-established vehicles for drug delivery in healthcare applications. This work focuses on the stabilisation of bacteriophages using oil-in-water nano-emulsions in order to develop the basis of a commercial cream or impregnated wound dressing for the treatment of burn wound infections. It was found that nano-emulsions have a dramatic effect on bacterial growth, and such influence was qualitatively determined using a Response Surface Method for design of experiments, followed by a quantitative analysis that allowed for the formulation of a modification of the logistic model of growth. Most importantly, it was discovered that nano-emulsions enhance bacteriophage infectivity both against S. aureus and P. aeruginosa infections in planktonic culture when compared to simple phage suspensions in buffer. The mechanisms why this enhanced infectivity occurs were investigated, and it was concluded that nano-droplets shield bacteriophages against environmental inactivation and they diminish the possible electrostatic repulsion between bacteriophages and bacteria, since they are both negatively charged. Bacteriophage/nano-emulsion formulations were then applied for the eradication of biofilms, which constitute the most common form of existence of bacteria in wounds. A flow system that mimics the continuous but slow supply of nutrients in a wound was used for this purpose. The infectivity of the developed formulations against such biofilms was found to be significant as well, proving the efficacy of stabilised bacteriophages in nano-emulsions. Finally, mathematical modelling approaches were successfully utilised to determine infection parameters and develop a predictive tool for mixed infections treated with bacteriophage ‘’cocktails’’.
|Date of Award||30 Apr 2015|
|Supervisor||Tom Arnot (Supervisor) & Toby Jenkins (Supervisor)|