Bacteria evolve very quickly, on a daily basis, which means there can be thousands of new generations of bacteria with antimicrobial resistance genes within a week. This makes the challenge of antimicrobial resistance (AMR) even more complex to solve.
As bacteria grow, changes occur within their genetic code, leading to variations in bacterial populations. These mutations can allow bacteria to become resistant against antibiotics, which poses a huge problem to modern medicine.
Dr Elizabeth ‘Lilly’ Cummins a post-doctoral researcher at the IOI, is examining how these bacterial pathogens evolve to become resistant to antibiotics, and how this evolution can be interrupted.
Lilly’s background is in mathematics. After graduating in mathematical sciences, she was keen to pursue research with real-world applications. She studied mathematical medicine in her masters and used her transferable skills in programming to forge a career in bioinformatics and AMR.
Lilly works in a ‘dry lab’ (labs where applied mathematical analyses are done to model real-world scenarios), undertaking bioinformatic analysis of the sequencing data from the ‘wet labs’ (the labs which handle chemicals and pathogens).
She works in the AMR evolution team, led by Prof Sam Sheppard, on an MRC funded collaboration with researchers at the University of Birmingham, Professor Alan McNally and Dr Rebecca Hall – who work in a wet lab. Lilly validates findings from the wet lab by putting them into the context of the real world. This can only be done with bioinformatics that handle large sequencing data sets of naturally occurring bacteria.
While a lot of work has already been done to establish which bacterial genes make a pathogen resistant to antibiotics, Lilly is interested in the evolutionary events that lead to a resistance gene being acquired. Her work looks in particular at pathogens which have evolved to be resistant to multiple medications, as they are more threatening and classified by the World Health Organisation as ‘high priority’. Examples of these include E. coli, which causes the majority of urinary tract infections (UTIs) and can lead to blood stream infections.
In Lilly's team researchers aim is to be able to use sequencing to forecast bacterial resistance. The goal would be to sequence a pathogen’s genome and then assess whether it has the potential to become resistant. This is useful because it means that the pathogen could be channelled into evolutionary dead-ends, stopping them from developing resistance – so preventing resistance from occurring in the first place rather than finding cures for drug-resistant infections.
Teamwork is one of the best things about my work. Any number of problems can arise during bioinformatic analysis, from software installation and programming bugs to developing new methods for dealing with unusual data sets, but being able to share the issue among the group and look at it from different angles means solutions can be found.
As one of the only postdoc researchers in the group, Lilly relishes working with doctoral students as they develop academically.
Indeed, this is one of the best things about the IOI – different research programmes have clear and distinct aims, but they are all working towards a common goal. Individual researchers have specialities, and are brought together to become a productive academic unit, working together to fight AMR.