Position: EBPOD Postdoctoral Fellow
Department: EMBL-EBI/Department of Medicine
Keywords: transmission, bacteria, epidemiology, antimicrobial resistance, bioinformatics
Bacterial infections are at risk of becoming complicated or untreatable as a result of increasing antimicrobial resistance. My research interests are focused on understanding bacterial transmission dynamics and broader epidemiological trends
by sequencing the DNA of the bacteria and analysing it computationally. In this way we can identify transmission chains that would have previously remained cryptic, or identify shifts in populations over time.
My current research aims to develop a computational framework for the rapid detection of bacterial transmission, particularly plasmids. Plasmids are extra bits of DNA that bacteria are able to share and often carry genes that confer resistance to antibiotics. It is still non-trivial to detect plasmid transmission, as plasmids are often very different from each other and are difficult to resolve computationally because of their genetic composition. By using a “pan-genome” approach, we hope to generate a method to create a plasmid index that can be queried in order to automatically detect if bacteria are likely to contain similar plasmids. If successful, this method could provide an early alert system for transmission, helping to reduce response times between outbreaks and interventions.
Get in touch: leah [at] ebi.ac.uk, twitter @loolibear