Principal Supervisor: Dr Alan McNally - Institute of Microbiology and Infection
Co-supervisor: Prof Ian Henderson
PhD project title: Quantifying the true extent of cross-species movement of Multi-Drug Resistant E. coli
University of Registration: University of Birmingham
Current knowledge of the population structure of E. coli is limited by low genomic resolution and sampling biases. Low resolution MLST data suggest that MDR in E. coli is not randomly distributed throughout the population, but is largely concentrated in a small number of dominant lineages, namely ST131, ST73, ST95, and ST69. These lineages belong to the extra-intestinal pathogenic E. coli (ExPEC) pathogroup, and cause a high burden of invasive disease that is increasingly difficult to treat clinically. These lineages are also highly divergent from each other at a genome phylogeny level. The wider distribution of MDR plasmids in the E. coli population across environmental niches is poorly resolved. Population genetics data sets clearly show the presence of MDR plasmids in many other STs that are rarely associated with human infection. Screens to isolate environmental MDR E. coli have shown that ST131, ST73, ST95 and ST69 E. coli can also be isolated from livestock, horses, domesticated animals, wild birds, and wild rodents, as well as from environmental soil and water samples, but a full population genetic analysis that includes non-MDR E. coli has never been performed on these reservoirs. As such our knowledge of emergence of MDR E. coli lineages is skewed by multiple sampling biases causing overrepresentation of human infection lineages and MDR lineages.
In the absence of such data an assumption has been made that the MDR ExPEC that cause human disease are the same strains that circulate in environmental and veterinary habitats. These assumptions are made on strains harbouring identical MLST types or resistance profiles. To date only a single study has been conducted using high-resolution genomics on human and poultry ExPEC isolates, and this suggested that the bacterial populations in these two hosts were distinct but that there was significant sharing of MDR plasmids. The most comprehensive genomic analysis performed to date of an MDR Gram negative pathogen (Salmonella Typhimurium DT104) believed to transmit between humans and animals showed very little cross species transfer of the pathogen, and that largely there were two distinct circulating epidemics of the pathogen, one in each habitat.
Therefore, current understanding of how MDR ExPEC lineages emerge from the wider E. coli population is limited by significant under-sampling of the genomes of non-pathogenic and non-MDR associated lineages from environmental and other non-human reservoirs causing biases in the existing population genomic estimates. Similarly the role for MDR plasmids in ExPEC emergence remains unresolved, and the question remains: are MDR clones of ExPEC transmitting between human and animal habitats, or are MDR plasmids transmitting between distinct human and animals populaions of ExPEC? This project combines observational cutting-edge population genomics and genome wide association techniques with Bayesian ancestral reconstruction analyses to understand the extent to which MDR ExPEC move across ecological barriers.
Our specific objectives are:
- Determine the population genomic structure of E. coli across environmental, veterinary and clinical niches: Are the dominant MDR ExPEC lineages also dominant in environmental and veterinary habitats?
- Use phylogenetic and pan-genome analyses to determine the extent of bacterial and plasmid movement between habitats. Are human clinical MDR ExPEC closely related to veterinary and environmental MDR ExPEC at a phylogenetic level? Can we see accessory genome sharing between the distinct ecological populations?
- Determine the extent of movement of MDR ExPEC populations between human and animal habitats. How frequent is movement of MDR ExPEC bacteria from humans to environment to animals and back again?
BBSRC Strategic Research Priority: Food Security
Techniques that will be undertaken during the project:
Isolation of bacteria from environmental and veterinary samples Genome sequencing Bioinformatic analysis of genomic data Bayesian ancestral state reconstruction from genome data
Contact: Dr Alan McNally, University of Birmingham