Background: Our work shows that an adhesin (EcpD) from the food-borne pathogen E. coli O157:H7 targets pectic arabinans in plant cell walls. Although E. coli O157:H7 is primarily found in farmed animals, it can also be transmitted through the food chain in vegetables and so the interaction is important as it represents a specific binding mechanism that cannot occur with animal cells. In nature, EcpD is a surface-expressed protein that requires a chaperone (EcpB, alternatively EcpE) for secretion through the outer membrane of E. coli cells, and when in complex with the main structural protein (EcpA), likely undergoes strand-exchange for polymerization. Based on this information, we have made a series of preliminary constructs to determine the feasibility of protein purification.
Aims & Objectives: The aim of the project is to understand the interaction of EcpD with target arabinans, in order to assess the role it contributes in transmission of E. coli O157:H7 through the food chain. A first objective is to determine the affinity of EcpD for arabinose oligomers and obtain protein structural data. The adhesin is ubiquitous in E. coli isolates and as such a second objective is to carry out a comparative analysis with other EcpD variants to determine how widespread binding is. These objectives will use a combination of biophysical approaches, e.g. isothermal titration calorimetry, surface plasmon resonance, NMR and crystallography, combined with bioinformatics analysis. A third objective is to understand the wider context of E. coli O157:H7 interaction with vegetables in the food chain and the subsequent risks to public health. This part will be carried out with our partner Food Standards Scotland (FSS) reviewing food-borne outbreak and E. coli O157:H7 incidence data.
Training: The supervisors have combined expertise and will provide training in protein science, microbiology, plant cell wall biology for the laboratory work, as well as aspects of bioinformatics. Work with the FSS will involve literature and data surveys and analysis. The work will contribute to reports in this area. Additional training will be provided for translational skills and in bioinformatics, statistical analysis and computational science.
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