Details of Grant 

EPSRC Reference:	EP/C513215/1
Title:	Mathematical modelling of surface spreading bacteria
Principal Investigator:	Ward, Dr JP
Other Investigators:
Researcher Co-Investigators:
Project Partners:
Department:	School of Mathematics
Organisation:	Loughborough University
Scheme:	First Grant Scheme Pre-FEC
Starts:	01 July 2005	Ends:	31 December 2007	Value (£):	117,554
EPSRC Research Topic Classifications:	Cells Medical science & disease Non-linear Systems Mathematics
EPSRC Industrial Sector Classifications:	Healthcare
Related Grants:
Panel History:
Summary on Grant Application Form
The rapid spread of pathogenic bacteria across moist, semi-solid surfaces (called swarming) plays a crucial role in the establishment of a number of infections, including in the lungs of cystic fibrosis (CF) patients and infections of the urinary tract. In the laboratory, an inoculum of cells in a droplet produces swarming colonies on agar plates (swarm plate assays) that exhibit a range of patterns from simple radially expanding colonies to finger formations and branching patterns. Time-lapse images also show pulses of cellular aggregations traversing rapidly along each of the fingers. Although, extensive experimental work has identified many of the biological mechanisms that are involved in regulating swarming activity, little is known on how these complex biological and physical processes interact to generate the wide range of interesting behaviours observed. The proposed research will be centred on the development and analysis of predictive mathematical models, based on biologically and physically relevant assumptions, of bacterial swarming. The main aim of the project is, therefore, to identify the key mechanisms that govern each of the various observed phenomena and, using simulations, to investigate what implications these mechanisms have on possible anti-biotic therapies.iThe modelling will focus on the swarming behaviour of the bacterium Pseudomonas aeruginosa (PA), a pathogen largely responsible for CF patient mortality. This is a well studied paradigm for which swarming process involves the combined action of random motion (via flagellal swimming), nutrient chemotaxis and the release of biosurfactants, the production of which is regulated by cell-cell signalling mechanism called quorum sensing (QS). The biosurfactant acts by reducing the local surface tension causing the droplet to spread. A continuum approach to the modelling will be adopted, in which reaction-diffusion-advection equations for bacterial density and the concentrations of nutrient, QS molecules and biosurfactant will be coupled with a thin-film model to describe fluid flow. Fortunately, estimates of many of the model's parameters are obtainable from earlier work by the Principal Investigator and from other experimental studies. The complexity of the model will necessitate the extensive use of numerical simulations, although analytical methods will be applied on asymptotic reductions of the model.The research will be in three parts. Firstly, the one-dimensional form of the model will be studied to determine the relative effects of the principal mechanisms on the swarming colony expansion rates. Using time-lapse image data, parameter estimates will be made. Asymptotic analysis will be undertaken to determine a functional relationship between colony expansion rate and the model's parameters. The contribution of QS to pulsing cellular aggregates will also be determined. The second part of the programme will study the two-dimensional form of the model, aiming to establish the key destabilising mechanisms leading to finger formation and secondary branching. Many of the results from the first two parts of the programme will be experimentally verifiable using swarm plate assays and genetically engineered mutant strains. The model will be extended in the final part of the programme to assess the effects of the immune system and drug action. Simulations will be directed at determining antibiotic and/or anti-QS treatment regimes that optimise containment of a bacterial infection.The proposed research will further our understanding of bacterial swarming processes and offer significant insights into ways in which they could be controlled. The modelling could prove valuable in shedding light on a wide range of therapetic issues.
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Organisation Website:	http://www.lboro.ac.uk