City, University of London Featured PhD Programmes
Engineering and Physical Sciences Research Council Featured PhD Programmes
University of Sheffield Featured PhD Programmes
FindA University Ltd Featured PhD Programmes
FindA University Ltd Featured PhD Programmes

Using synthetic biology to understand the evolution of antibiotic resistance


Project Description

Imagine an architect, tasked with converting an old stadium into a building with a different function, without demolishing it. While she might contemplate turning the stadium into a housing project, shopping mall, or office space, she will not consider turning it into an airport, because the existing architecture imposes certain constraints: namely, the walls that surround it prevent airplanes from landing.

Evolution operates in much the same way: the molecular structures that already exist inside a cell impose constraints that make it more difficult to evolve certain forms compared to others. This Ph.D will use the tools and techniques of synthetic biology in order to understand how the existing molecular mechanisms determine evolution.

Understanding this relationship is crucial for predicting evolution. The ability to predict evolution is particularly critical when it comes to understanding and predicting the evolution of antibiotic resistance – one of the most important examples of how evolution affects human lives today, already causing over 25,000 deaths per year in the EU alone, in addition to extending hospital stays and increasing health care costs. In order to tackle this problem, we need to develop predictive approaches that will help us not only extend the usefulness of existing antibiotics, but also inform the development of longer-lasting novel drugs.

The aim of this Ph.D is to improve our ability to predict multi-drug resistance evolution by understanding how the existing molecular mechanisms determine evolution. This Ph.D project will involve constructing synthetic regulatory networks and experimentally probing them by introducing mutations into promoters and transcription factors that control the expression of multi-drug resistance pumps (AcrAB-TolC). This will allow us to understand how biophysical mechanisms determine the effects of mutations in transcription factors and promoters, and hence how they drive resistance evolution.

The Ph.D student will work alongside a computational /theoretical postdoc.

Entry Requirements:
Candidates are expected to hold (or be about to obtain) a minimum upper second class honours degree (or equivalent) in a related area / subject. MA or experience in a related discipline (evolutionary biology, microbiology, molecular biology, synthetic/systems biology, etc.) is highly desirable. Candidates with interest in evolutionary biology and microbiology, as well as antimicrobial resistance, are highly encouraged to apply. Experience in microbiology and/or molecular biology is desirable. Interest in biophysics, theoretical evolutionary biology and modelling is a plus.

For international students we also offer a unique 4 year PhD programme that gives you the opportunity to undertake an accredited Teaching Certificate whilst carrying out an independent research project across a range of biological, medical and health sciences. For more information please visit http://www.internationalphd.manchester.ac.uk

Funding Notes

Applications are invited from self-funded students. This project has a Band 2 fee. Details of our different fee bands can be found on our website (View Website). For information on how to apply for this project, please visit the Faculty of Biology, Medicine and Health Doctoral Academy website (View Website).

As an equal opportunities institution we welcome applicants from all sections of the community regardless of gender, ethnicity, disability, sexual orientation and transgender status. All appointments are made on merit.

References

Dean, A. M. & Thornton, J. W. Mechanistic Approaches to the Study of Evolution: the Functional Synthesis. Nature Reviews Genetics 8, 675–688 (2007).

De Visser, J. A. G. M. & Krug, J. Empirical Fitness Landscapes and the Predictability of Evolution. Nature Reviews Genetics 15, 480–490 (2014).

Blair, J. M. A., Webber, M. A., Baylay, A. J., Ogbolu, D. O. & Piddock, L. J. V. Molecular Mechanisms of Antibiotic Resistance. Nature Reviews Microbiology 13, 42–51 (2014).

Lagator, M., Paixao R., Barton N.H., Bollback J.P., Guet C.C. On the Mechanistic Nature of Epistasis in a Canonical cis-Regulatory Element. eLife 6, e25192 (2017).

Email Now

Insert previous message below for editing? 
You haven’t included a message. Providing a specific message means universities will take your enquiry more seriously and helps them provide the information you need.
Why not add a message here
* required field
Send a copy to me for my own records.

Your enquiry has been emailed successfully





FindAPhD. Copyright 2005-2019
All rights reserved.