Effect of antimicrobial selection on population establishment
Project Summary: Antimicrobial resistance (AMR) is a global health crisis, with 1.27 million deaths directly attributed to AMR in 2019 alone. As the discovery and development of new antibiotics to treat antimicrobial-resistant infections are at an all-time low, it is becoming increasingly important to better understand AMR development to maintain efficacy in antibiotics currently available. Random mutations occur continuously and are common in large bacterial populations. Some of these mutations can cause increased resistance to antibiotics, and these mutations can be selected for when the antibiotic is present. If treatment for an infection fails due to antimicrobial resistance, this can compromise patient outcomes, increasing the risk of morbidity. To counteract this, alternative antibiotics are given to the patient.
Although, we currently lack data to fully understand how populations resistant to one antibiotic respond to alternative antibiotics in both short and longer terms. However, there are several phenomena in bacterial evolution which we may be able to take advantage of to prevent, or at least limit, the spread of antimicrobial resistance. One such phenomenon is the probability of a bacterial population being able to establish in the first place. For example, the establishment probability of an already resistant population may increase in the presence of a new antibiotic compared to the previously susceptible population. In addition, the opposite may also be true and can be dependent on the antibiotic the population is resistant to and the alternative antibiotic. If we can determine which combinations increase or decrease the probability of population establishment, we may be able to determine antibiotic combinations to avoid or promote.
In this project, we will use an experimental evolution approach to further understand the effect of trimethoprim resistance on the population establishment probability in the presence of another antibiotic. In a previous, project we generated 14-16 trimethoprim-resistant Escherichia coli strains from four clinical isolates isolated from urinary tract infections, sequenced their genomes and carried out antimicrobial susceptibility testing. We will use population establishment assays to determine the probability of these trimethoprim-resistant isolates establishing a population in the presence and absence of other antibiotics used for the treatment of UTIs, such as nitrofurantoin and cephalexin. We will also determine the effect of both these antibiotics on the establishment of the trimethoprim-resistant and trimethoprim-susceptible populations in a co-culture.
It is anticipated the data from this project will be used to determine the likelihood of an antimicrobial-resistant population establishing in the presence of an alternative antibiotic. Additionally, the data will be used to predict antibiotic choice and treatment order that will lead to a low probability of establishment of a resistant population. This will guide prescription policy to limit the emergence of AMR.
Training: Full training will be provided for all techniques used in the project. In addition, the candidate will attend AROM research group meetings and there will be opportunities to present findings to the AROM research group.