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Evolution of multi-drug resistant gram negative clones

About This PhD Project

Project Description

Increasing antibiotic resistance in bacterial infections is a serious threat to modern medicine, so understanding why some bacteria become resistant to multiple antibiotics whereas others do not is an important challenge for microbiologists, doctors and vets. In pathogenic E. coli — the most common cause of blood and urine infections worldwide and recognised by the World Health Organisation as a top global health threat — antibiotic resistance is associated with acquisition of plasmids that carry several different antibiotic resistance genes. Not all E. coli strains seem to be able to maintain such plasmids, and what we see are dominant MDR clones (1), which is probably because gaining plasmids is typically very costly because the genes the plasmids carry interfere with the workings of the bacterial cell (2). Our work has led us to hypothesise that this variation between strains of E. coli is due to differences in how the various strains regulate the expression of their genes allowing some to mitigate for the disruption caused to the cell by the plasmid (3).

we will test this idea in the laboratory using evolution experiments and cutting-edge sequencing technology. We will compare the costs of acquiring a plasmid and the level of antibiotic resistance provided in various clonal backgrounds. We predict that costs will be higher in clones that don’t typically carry plasmids. We will compare the disruption caused to the cell by acquiring a plasmid in different clones by measuring patterns of how they express their genes. We predict that disruption to the cell caused by gaining the plasmid will be greater in clones that don’t typically carry plasmids, and that this will scale with the costs we measure of carrying the plasmid. We will experimentally evolve bacteria carrying plasmids in the lab to observe in real time how natural selection compensates for the cost of acquiring a plasmid. We will test how the mutations observed during experimental evolution affect the expression of genes in cells with and without plasmids, to understand the molecular mechanisms by which evolution allows bacteria to maintain plasmids.
This project will advance our fundamental understanding of how and why pathogenic strains of E. coli that are highly resistant to antibiotics evolve. In future this insight could help us to identify potential superbugs before they emerge, or suggest novel targets for drugs that force bacteria to lose their antibiotic resistance plasmids making them susceptible to conventional treatments.

Applicants should have a strong background in microbiology/infectious diseases, and an understanding of antimicrobial resistance in gram negative pathogens. They should have a commitment to antimicrobial resistance and microbial evolution research and hold or realistically expect to obtain at least an Upper Second Class Honours Degree or equivalent in microbiology/evolutionary biology/bioinformatics.


McNally A, Kallonen T, Connor C, Abudahab K, Aanensen DM, Horner C, Peacock SJ, Parkhill J, Croucher NJ, Corander J. 2019. Diversification of Colonization Factors in a Multidrug-Resistant Escherichia coli Lineage Evolving under Negative Frequency-Dependent Selection. MBio. 10(2). pii: e00644-19.

MGJ de Vos, M Zagorski, A McNally, T Bollenbach. 2017. Interaction networks, ecological stability, and collective antibiotic tolerance in polymicrobial infections. Proc Nat Acad Sci.114: 10666-10671.

Harrison F, McNally A, da Silva AC, Heeb S, Diggle SP. Optimised chronic infection models demonstrate that siderophore 'cheating' in Pseudomonas aeruginosa is context specific. ISME J. 2017 Nov;11(11):2492-2509.

McNally, A., Oren, Y., Kelly, D., Avram, A., Dobrindt, U., Dunn, S., Seecharan, T., Vehkala, M., Prentice, M.B., Ashour, A., Pupko, T., Pascoe, B., Sheppard, S.K., Literak, I., Guenther, S., Schaeffler, K., Wieler, L.H., Zong, Z., McInerney, J.O., Corander, J. (2016). Combined analysis of variation in core, accessory, and regulatory genome regions provides a super-resolution view into the evolution of bacterial populations. Plos Genetics. 12:e1006280.

Sandra Reuter, Thomas R Connor, Lars Barquist, Danielle Walker, Theresa Feltwell , Simon Harris, Maria Fookes, Miquette E Hall, Thilo M Fuchs, Muriel DuFour, Michael Prentice, Brendan W Wren, Elisabeth Carniel, Mikael Skurnik, Juliana P Falcão, Hiroshi Fukushima, Holger C Scholz, Julian Parkhill, Mark Achtman, Alan McNally, Nicholas R Thomson. (2014). Parallel independent evolution of pathogenicity within the genus Yersinia. Proc Nat Acad Sci USA. 111:6768 – 73.

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