Predicting of Prokaryotic Defence Distributions

ended

Bacteria are crucial for health, nutrient cycling and biotechnology but face a constant pressure from the viruses that infect them (phages). As such, bacteria have evolved a sophisticated suite of defence mechanisms that allow them to evade phages. These defence mechanisms can be classified into two basic classes: selfish or altruistic. A selfish system protects individuals, whereas an altruistic system protects the population. Interestingly, the distribution of this defensive arsenal is uneven, with large variations in the types carried, even among closely related species. This proposal aims to understand the basis of this distribution by using a multi-disciplinary approach that combines the precision of a model laboratory system with cutting-edge metagenomics techniques. Specifically, I will use abortive infection as a model for altruistic defence and CRISPR as a model for selfish defence and test the role of spatial structure in determining the abundance of each type. High spatial structure is predicted to be a key determinant of altruistic defences as it results in proximate bacteria being closely related. I will then apply the findings from the first objectives to classify a novel, recently discovered, defence system. Together, these results will enable researchers to better understand microbial immunity, with key consequences for industry and healthcare. The outgoing phase will take place at the University of Otago, New Zealand, using molecular biology expertise in abortive infection and CRISPR systems. The return phase will take place at the University of Exeter, UK, benefitting from expertise in ecology and evolution. The proposed project will allow me to complement my strong background in genomics and ecology with molecular biology and novel bioinformatic approaches. By working in two world-class research laboratories I will further develop independence and a strong collaborative network for the future.