Skip to main content

Microbes and Society @ Exeter

Modelling an evolutionary arms race between bacteria and antibiotic producers that could drive new antibiotics production

Network members are also encouraging interdisciplinarity at undergraduate level. Andrew Higginson, a behavioural ecologist, is supporting MSci Natural Sciences student Erin Grant to make eco-evolutionary models of antimicrobial resistance and accurately predict the conditions necessary for the evolution of new antibiotics using computer simulations.

The reality of antibiotic resistance, the overuse of antibiotics and the adaptive genome expression in bacterial populations is now well publicised, albeit not yet fully understood. The development of new antibiotics is needed to keep routine medical procedures safe and to fight common infections, preventing unnecessary deaths caused by antibiotic-resistant bacteria.

Erin’s project aims to offer guidance for antibiotic discovery through simulated evolutionary arms races and requires interdisciplinary work to achieve the best results. Dr Andrew Higginson’s background in simulating ecological processes complements the broad range of Erin’s degree, which includes mathematics and programming. Their thinking is unconstrained by the approach of one discipline, and they are inspired by the eco-evolutionary models that are common in ecology and evolutionary biology.

Erin is constructing a spatial computer simulation of growth, reproduction and competition, between susceptible and resistant bacteria and an antibiotic-producing species, over many generations. In this model, individuals compete for space and food, and reproduction involves mutation of the mechanisms they use in competition, such as antibiotic production. By simulating different conditions, they can predict the conditions under which antibiotic producers may evolve to inhibit the growth of resistant bacteria.

Key researchers

Andrew Higginson photo

Dr Andrew Higginson

I study the evolution of animal behaviour using a combination of mathematical and computational modelling, behavioural experiments (on humans and other animals) and analysis of large datasets. 

View full profile.