The chance that an organism mutates, for instance that a microbe mutates to resist an antibiotic, can depend on that organism’s environment. We have recently discovered that the density of the population that an organism belongs to is closely associated with this mutation rate – high density populations of a wide range of organisms have roughly ten-fold lower rates of resistance than sparser populations . How these environmental interactions play out can be complex, involving both nutrient and biotic environments. For instance, adding nutrients can both increase population density, associated with reduced mutation rates, and increase stress, associated with raised mutation rate . But the key question is how cells affect one another’s mutation rate.
This project will focus on understanding how those biotic interactions affect cells’ rates of mutation to antimicrobial resistance. We already have some experimental genetic clues: A strain of the bacterium E. coli lacking a gene involved in the activated methyl cycle can affect the mutation rate of a wildtype strain it grows with . The reduction in mutation rate in dense populations requires proteins dealing with oxidatively damaged nucleotides in the cell . Using simple synthetic microbial communities in the laboratory  and mechanistic models, this project will test hypotheses for how cells affect one another’s mutation rates.
This interdisciplinary study of evolution, can provide new insights into the mechanics of how evolution works. This represents a unique opportunity for applicants interested in both computational biology approaches and lab work, allowing the student to address fundamental questions of evolutionary biology, while training in computational and wet-lab techniques: a combination which lends itself to multiple future career paths. https://www.research.manchester.ac.uk/portal/Chris.Knight.html https://www.research.manchester.ac.uk/portal/rok.krasovec.html https://www.research.manchester.ac.uk/portal/pawel.paszek.html https://www.research.manchester.ac.uk/portal/andrew.mcbain.html
Applications are invited from UK/EU nationals only. Applicants must have obtained, or be about to obtain, at least an upper second class honours degree (or equivalent) in a relevant subject.
This project is to be funded under the BBSRC Doctoral Training Partnership. If you are interested in this project, please make direct contact with the Principal Supervisor to arrange to discuss the project further as soon as possible. You MUST also submit an online application form - full details on how to apply can be found on the BBSRC DTP 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.
 Krašovec, R., Richards, H., Gifford, D.K., Hatcher, C., Faulkner, K.J., Belavkin, R.V., Channon, A., Aston, E., McBain, A.J. and Knight, C.G. (2017) Spontaneous Mutation Rate Is a Plastic Trait Associated with Population Density across Domains of Life. PLOS Biology, 15, e2002731. http://doi.org/cb9s
 Krašovec, R., Richards, H., Gifford, D.R., Belavkin, R.V., Channon, A., Aston, E., McBain, A.J. and Knight, C.G. (2018) Opposing effects of population density and stress on Escherichia coli mutation rate. The ISME Journal, 12, 2981-2987l. http://doi.org/cst8
 Krašovec, R., Belavkin, R.V., Aston, J.A.D., Channon, A., Aston, E., Rash, B.M., Kadirvel, M., Forbes, S. and Knight, C.G. (2014) Mutation-rate plasticity in rifampicin resistance depends on Escherichia coli cell–cell interactions. Nature Communications, 5, 3742 http://doi.org/skb
Chodkowski, J.L. and Shade, A. (2017) A Synthetic Community System for Probing Microbial Interactions Driven by Exometabolites. mSystems, http://doi.org/dbjq