This project is investigating bacterial genome evolution, generating data that will provide a scientific basis for pollution management. It will quantify the prevalence of point mutations compared with horizontal gene transfer events in generating antimicrobial resistance (AMR).
The dramatic increase in AMR forms a global challenge to public health and it is increasingly understood that the natural environment plays a key role in AMR evolution.
Bacteria can acquire antibiotic resistance via mutations in their genes, which are passed on to their immediate offspring via cell division, enabling the spread of antibiotic resistance. Bacteria are also able to take up genes from other bacteria, including other species, via horizontal gene transfer (HGT).
HGT occurs via 3 mechanisms called transformation, transduction and conjugation (learn more about these mechanisms here) and might contribute to the rise of certain types of antibiotic resistance as much as mutations. However, it is still unclear how environmental factors shape the ratio of “vertical” (mutation-based) to “horizontal” resistance evolution.
Using lab experiments, this research is cultivating bacteria in diverse communities and using microbial genetics to understand how resistance evolves. Crucially, it is exploring whether this depends on environmental conditions such as antibiotic concentration.
The main aim of this work is to combine antibiotic selection with whole-genome re-sequencing in a bacterial pathogen to identify the prevalence of distinct genetic mechanisms (horizontal gene transfer versus (vertical) point mutations) responsible for resistance. Specifically, it will:
Vary antibiotic concentrations to alter the cost of resistance, enabling us to measure the prevalence of mutation-based relative to horizontal gene transfer-based AMR;
Test whether resistance evolution via lateral gene transfer is promoted in more diverse microbiomes, relative to mutation, by varying species diversity in experimental microcosms.
The project will use fluorescent markers and genome sequencing to measure the type and rate of genetic change under different realistic pollution scenarios.
Work is beginning by exploring the effects of antibiotic concentration on the evolution of resistance in E.coli under exposure to a natural sewage community. Antibiotic concentration is an interesting environmental factor because it not only influences the chance of an antibiotic resistance mutation spreading throughout the E.coli population, but also causes changes to the abundance of the other species in the community.
Given that environmental concentrations of particular antibiotics vary according to land use, findings emerging from this study will have important implications for the management of AMR in the environment.