Mathematical Medicine and Biology
Doctorate (PhD or DPhil)
| Level | Doctorate (PhD or DPhil) |
|---|---|
| Student | Dr JAMES PRESTON |
| Status | Complete |
| Part Time | No |
| Years | 2015 - 2019 |
| Project Title | Modelling the dynamics between Enteropathogenic Escherichia coli infections, the immune response and antibiotic therapies |
| Project Description | Enteropathogenic Escherichia coli (EPEC) is a virulent strain of bacteria that is a leading cause of death in children with diarrhoea, especially in countries with underdeveloped healthcare. EPEC attach to host intestinal epithelial cells (IECs) and secrete proteins into them that subvert the immune response. In particular, these proteins inhibit pro-inflammatory signalling, IEC apoptosis and phagocytosis by leukocytes. It is estimated that there are approximately 800,000 fatalities worldwide per year due to EPEC. Therefore, finding effective treatments for EPEC infections is crucial to the improvement of human health across the globe. In order to find effective treatments, a detailed understanding of EPEC and its infection strategy is needed. Researchers at the Centre for Biomolecular Sciences at the University of Nottingham have recently discovered experimentally that EPEC internalise host pro-inflammatory cytokines, granting dynamic control of protein secretion and reduced susceptibility to aminoglycosides (a class of antibiotic). However, while biological studies have uncovered vital information on many of the mechanisms of EPEC’s infection strategy, much is still unknown about the infection strategy. In this thesis, we first formulate and analyse a mathematical model describing a general infection resulting from interactions between host epithelial cells and non-specific bacteria in the human gut. The model comprises a set of ODEs describing the dynamics between a bacterial infection and the innate immune response. We then extend the model to account for EPEC-specific mechanisms with analysis providing insight into the effectiveness of the various aspects of EPEC’s infection strategy, allowing the effectiveness of an EPEC infection to be compared to that of a general infection. The EPEC model was then adapted into an in silico multi-scale hybrid model that includes mechanisms on the macro-, cell-, and sub-cellular scales, implemented deterministically and stochastically, with the aim of exploring the dynamics between EPEC and the host’s immune system both spatially and temporally. Finally, the hybrid model is extended to explore the effects of bacterial biofilms on the success of the infection. In each of the EPEC models, we account for the effects of antibiotics and the recent experimental discoveries discussed above. Analysis of the models via steady state, stability, sensitivity and bifurcation analyses and numerical simulations allows us to make predictions on the effectiveness of antibacterial treatment strategies. Our models predict effective treatment strategies targeting bacterial protein synthesis and replication, the immune response, the application of antibiotic, the positioning of bacteria and the ability of bacteria to form biofilms. We hope our predictions will inform, and reduce the time and cost of, future experimental work |
| Awarding Institution | University of Nottingham |
| Director of Studies | REUBEN O'DEA |
| Second Supervisor | BINDI BROOK |