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Click here to search FindAPhD.com for PhD studentship opportunitiesAbout the Project
From the human gut to deep-sea sediments, microbial communities – or microbiomes – colonize virtually every habitat on earth. These microbiomes are central to ecosystem functioning and to host health, and therefore it is essential that we understand how and why they change over time. To date, the most work predicting microbiome dynamics has focused on their ecology – that is, on predicting how individual microbial abundances change over time.
While fascinating, this work has relied heavily on the assumption that microbial species will behave identically from one timepoint to the next. However, recent evidence suggests microbes are in fact rapidly evolving within microbiomes, with rampant de novo mutation and Horizontal Gene Transfer (HGT) changing the manner in which microbes interact with their environment and one another over a matter of mere days. These evolutionary processes are certain to influence broader microbiome dynamics – yet currently we lack any comprehensive understanding as to how. We know little about how or why microbiomes evolve over time, and less still about the impact evolutionary processes have on microbiomes as a whole.
To goal of this project is to address this gap, developing a new body of microbiome-specific theory to predict how evolution shapes microbial communities. Having developed this theory, we will use it to address three independent but interlinked research questions:
1. How do microbe-microbe interactions evolve within microbiomes?
2. How does resistance to stressors, such as antibiotics, evolve within microbiomes?
3. How does horizontal gene transfer impact microbiome evolution?
In each case, we will focus on two key themes, how do microbiomes evolve, and what impact does this evolution have on broader microbiome properties such as stability? While this project is purely theoretical, you will work closely with experimentalists to test and refine your models with empirical data from synthetic ecosystems and the mammalian gut.
Training/techniques to be provided
Training in theoretical ecology and evolution; mathematical modelling; programming in Python, R, and Matlab
Entry Requirements
Applicants must have obtained or be about to obtain a First or Upper Second class UK honours degree, or the equivalent qualifications gained outside the UK, in a relevant subject area.
How to Apply
For information on how to apply for this project, please visit the Faculty of Biology, Medicine and Health Doctoral Academy website (https://www.bmh.manchester.ac.uk/study/research/apply/). Informal enquiries may be made directly to the primary supervisor. On the online application form select the PhD Division of Evolution, Infection & Genomics.
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 https://www.bmh.manchester.ac.uk/study/research/international/
Equality, Diversity & Inclusion
Equality, diversity and inclusion is fundamental to the success of The University of Manchester, and is at the heart of all of our activities. The full Equality, diversity and inclusion statement can be found on the website
https://www.bmh.manchester.ac.uk/study/research/apply/equality-diversity-inclusion/
Funding Notes
Details of our different fee bands can be found on our website https://www.bmh.manchester.ac.uk/study/research/fees/
References
Coyte K.Z., et al (2022) “Horizontal gene transfer and ecological interactions jointly control microbiome stability” PLoS Biology
Rao C. et al (2021) “Multi-kingdom ecological drivers of microbiota assembly in preterm infants”. Nature. 591 (7851), 633-638
Coyte K. Z et al (2021) “Ecological rules for the assembly of microbiome communities”. PLoS Biology, 19 (2), e3001116
Coyte, K. Z, et al (2015). The ecology of the microbiome: networks, competition, and stability. Science, 350(6261), 663-666.
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