In vivo quantitative analysis of natural and synthetic bacterial signalling pathways
Despite being single celled organisms, bacteria display a dramatic level of sub-cellular organisation of both their protein and genetic constituents. They are capable of sensing and integrating information from a vast range of environmental stimuli and using this to tune their behaviour to optimally utilise the environment in which they find themselves. Our research revolves around trying to understand how bacteria sense and integrate environmental information. In general, bacteria use a range of two component signalling pathways for these processes. My research group is trying to understand in a quantitative manner how these multiple, homologous pathways operate in individual cells and then how we can use the components of these pathways to create our own synthetic pathways to achieve desired engineering solutions.
The main thrust of my research involves investigating bacterial signalling systems using fluorescence microscopy. My research utilises the chromosomal replacement of genes encoding components of bacterial signalling pathways with their corresponding fusions to fluorescent proteins. This results in bacteria which express the fluorescent fusion protein at the same levels as the wild type protein. Using sophisticated microscopy and in collaboration with other groups such as that of Dr. Mark Leake (Oxford Biochemistry) we can study the fluorescence signature of the fused protein in individual bacterial cells to obtain quantitative information on the behaviour of the protein of interest with single molecule precision.
Systems biology attempts to model computationally the processes happening within cells. This modelling relies on an accurate understanding of the concentration, stoichiometry and dynamics of protein constituents within individual cells. We are determining these parameters within defined signalling pathways in bacteria and then correlating these data with the observed physiological responses. By doing this it is possible to generate models which predict the response of the bacteria to defined stimuli.
Synthetic biology involves taking existing biological components and reassembling them to produce novel signalling or metabolic pathways. In order to do this it is essential that we have a quantitative understanding of how the different biological components work within their natural pathways. In collaboration with mathematicians and engineers we are attempting to model how different biological modules may be linked together in order to produce quantifiable outputs in response to defined inputs within these novel pathways.
Those pathways which are deemed to have new and interesting properties are then genetically constructed and the behaviour of the biological system compared to that proposed by the model to determine how well our predictions match reality.