Biofilms are surface-associated microbial communities that can be detrimental or beneficial to human habitation. Wastewater treatment plants crucially require biofilms to function, and we would be exposed to a wide range of pathogens if not for the protection provided by our resident microbiome, which is largely biofilms. On the other hand, biofilms are also the root cause of many chronic infections, and biofouling in industry causes substantial economic losses. There is a growing need to control (rather than simply kill) biofilms, and here computational modelling can help by predicting the effects of external changes and interventions on the composition, and therefore pathogenicity, of naturally occurring biofilms much more rapidly than (costly, lengthy) experiments.
The goal of this project is to develop an advanced biofilm model that includes multiple species, reflecting the community nature of almost all naturally-occurring biofilms, and also fluid flow which can apply shear stress - shedding microbes near the surface - and transport materials and metabolites to and from the biofilm. Combining agent-based models with flow is not trivial, however, and would be an example of a fluid-structure interaction problem for which Leeds houses the computational fluids CDT, for which fluid-structure interaction is a cornerstone. Once developed, it would then be possible to see how transport of nutrients affects biofilm morphology, how shear stress limits biofilm thickness, and possibly how microbubbles can disrupt pathogenic biofilms, this latter being an area of current experimental research within Leeds. As well as contact with other research groups within Leeds, it is also envisaged that the model will be used to generate hypotheses for future experimental verification in the UK and globally. There is also scope to develop parallelised code to run on one of Leeds' high-performance computing clusters.