Some species in the bacterial genus Acinetobacter are responsible for causing serious infections that can be difficult to treat due to high levels of antibiotic resistance. Understanding how these pathogens have evolved will provide insights into how we can combat them in the future. This project will take two approaches to studying Acinetobacter evolution. Firstly, it is thought that one way that bacteria can adapt quickly to a changing environment is through large-scale genome rearrangements, which impact how much different genes are expressed. You will characterise these different arrangements in this project. Secondly, comparison of genome sequences can be used to identify signs of natural selection through differences in substitution patterns. You will characterise these patterns in the species analysed in this project.
Using our unique collection of Acinetobacter genomes, combined with publicly available genomes, the program socru will be used to identify genome rearrangements. From this, you will identify all genes impacted by rearrangement and devise a metric to assess potential transcriptional impact. You will identify non-recombinant single gene families and assess evidence for selection such as dN/dS ratios and McDonald-Kreitman tests. You will have the opportunity to study gene families of particular interest in more detail.
Your supervisory team (Dr Ben Evans, UEA, UK; Prof Dan Brewer, UEA, UK; Dr Louis-Patrick Hararoui, Sherbrooke, Canada; Dr Santiago Castillo-Ramirez, UNAM, Mexico) will provide specific expertise in Acinetobacter, evolutionary genomics, and bioinformatics. In addition to training provided by the supervisory team, you will have the opportunity to attend internal and external training courses, such as in microbial genomics, evolution and programming, and to present your work at lab meetings, national and international conferences. You will develop skills in programming (e.g. Python), data analyses and presentation (e.g. using R), and scientific communication. You will have the opportunity to apply for funds from the Turing Scheme to visit the members of the supervisory team based outside of the UK.
Minimum 2:1 in an undergraduate degree with experience of bioinformatics or computer science. Knowledge in microbiology or evolutionary biology, as well as programming skills, would be beneficial.