Dr Liz Aston

Title: Postdoctoral Research Associate
Phone: +44 (0)1782 733593
Email: e.j.aston@keele.ac.uk
Location: Colin Reeves 141
Role:
Contacting me:

I have a background in biology and computer science, obtaining both a BSc in Biological Science and an MSc in Computer Science from the University of Birmingham. I then moved to Keele University where I completed my PhD entitled: 'Critical mutation rates in small populations'. I was supervised by Dr Alastair Channon, with Dr Charles Day as second supervisor, and funded as part of a £500k EPSRC project on information dynamics in evolutionary systems which included members from Manchester, Middlesex and Warwick Universities. Members of the project team subsequently obtained £580k funding from the BBSRC for a project on the theory and practice of evolvability: effects and mechanisms of mutation rate plasticity, with which I undertook a one year postdoc position. Following this, the team were successful in obtaining further funding from the BBSRC for a project on adaptive landscapes of antibiotic resistance: population size and 'survival-of-the-flattest'. With this funding I started a three year postdoc in August 2015 working as a Researcher Co-Investigator.

My main research interest and focus of my PhD and current postdoc is the relationship between critical mutation rates and the size of an evolving population in silico. Specifically, as part of my PhD and contrary to previous studies, I demonstrated that in the case of small populations and a simple two-peak fitness landscape, there is an exponential relationship between population size and the critical mutation rate at which individuals more robust to mutation outcompete individuals that are fitter but less robust ('survival-of-the-flattest'). I have already demonstrated that this relationship is maintained when moving from a haploid to a diploid population. I am currently working on bridging the gap between artificial and biological evolution by developing the model to focus on the small population of a microbe with a newly arisen antibiotic resistance mutation. My work in silico is being carried out alongside laboratory experiments and the development of theory at Manchester and Middlesex respectively as part of the BBSRC-funded interdisciplinary project on adaptive landscapes of antibiotic resistance: population size and 'survival-of-the-flattest'.

Selected Publications

  • Krašovec R, Belavkin RV, Aston JA, Channon A, Aston E, Rash BM, Kadirvel M, Forbes S, Knight CG. 2014. Where antibiotic resistance mutations meet quorum-sensing. Microb Cell, vol. 1(7), 250-252. link> doi> full text>
  • Krašovec R, Belavkin RV, Aston JAD, Channon A, Aston E, Rash BM, Kadirvel M, Forbes S, Knight CG. 2014. Mutation rate plasticity in rifampicin resistance depends on Escherichia coli cell-cell interactions. Nat Commun, vol. 5, 3742. link> doi> full text>
  • Aston E, Channon A, Day C, Knight CG. 2013. Critical mutation rate has an exponential dependence on population size in haploid and diploid populations. PLoS One, vol. 8(12), e83438. link> doi> full text>
  • Channon AD, Aston E, Belavkin RV, Gifford DR, Krašovec R. 2017. Critical Mutation Rate has an Exponential Dependence on Population Size for Eukaryotic-length Genomes with Crossover. Scientific Reports, vol. 7, Article 15519. doi> link> full text>
  • Aston EJ, Channon A, Belavkin RV, Gifford DR, Krasovec R, Knight CG. 2017. Critical Mutation Rate in a Population with Horizontal Gene Transfer. Proceedings of the 14th European Conference on Artificial Life ECAL 2017. The MIT Press,. doi> full text>

Full Publications List show

Journal Articles

  • Channon AD, Aston E, Belavkin RV, Gifford DR, Krašovec R. 2017. Critical Mutation Rate has an Exponential Dependence on Population Size for Eukaryotic-length Genomes with Crossover. Scientific Reports, vol. 7, Article 15519. doi> link> full text>
  • Krašovec R, Richards H, Gifford DR, Hatcher C, Faulkner KJ, Belavkin RV, Channon A, Aston E, McBain AJ, Knight CG. 2017. Spontaneous mutation rate is a plastic trait associated with population density across domains of life. PLoS Biol, vol. 15(8), e2002731. link> doi> full text>
  • Belavkin RV, Channon A, Aston E, Aston J, Krašovec R, Knight CG. Monotonicity of fitness landscapes and mutation rate control. J Math Biol, vol. 73(6-7), 1491-1524. link> doi> full text>
  • Krašovec R, Belavkin RV, Aston JA, Channon A, Aston E, Rash BM, Kadirvel M, Forbes S, Knight CG. 2014. Where antibiotic resistance mutations meet quorum-sensing. Microb Cell, vol. 1(7), 250-252. link> doi> full text>
  • Krašovec R, Belavkin RV, Aston JAD, Channon A, Aston E, Rash BM, Kadirvel M, Forbes S, Knight CG. 2014. Mutation rate plasticity in rifampicin resistance depends on Escherichia coli cell-cell interactions. Nat Commun, vol. 5, 3742. link> doi> full text>
  • Aston E, Channon A, Day C, Knight CG. 2013. Critical mutation rate has an exponential dependence on population size in haploid and diploid populations. PLoS One, vol. 8(12), e83438. link> doi> full text>

Other

  • Aston EJ, Channon A, Belavkin RV, Gifford DR, Krasovec R, Knight CG. 2017. Critical Mutation Rate in a Population with Horizontal Gene Transfer. Proceedings of the 14th European Conference on Artificial Life ECAL 2017. The MIT Press,. doi> full text>
  • Aston E, Channon A, Belavkin RV, Gifford DR, Krašovec R, Knight CG. 2017. Critical Mutation Rate has an Exponential Dependence on Population Size for Eukaryotic-length Genomes with Crossover. Sci Rep (vol. 7, p. 15519). link> doi> full text>
  • Aston E, Channon AD, Belavkin RV, Krasovec R, Knight CG. 2015. Optimal Mutation Rate Control under Selection in Hamming Spaces. Proceedings of the European Conference on Artificial Life 2015 (ECAL 2015) (pp. 640-647). MIT Press. doi> full text>
  • Channon A, Aston E, Day C, Belavkin RV, Knight CG. 2011. Critical mutation rate has an exponential dependence on population size. In T. Lenaerts, M. Giacobini, H. Bersini, P. Bourgine, M. Dorigo & R. Doursat (Eds.). Advances in Artificial Life, ECAL 2011: Proceedings of the Eleventh European Conference on the Synthesis and Simulation of Living Systems (pp. 117-124). Heidelberg: MIT Press. doi> full text>
  • Belavkin RV, Channon A, Aston E, Aston J, Knight CG. 2011. Theory and practice of optimal mutation rate control in hamming spaces of DNA sequences. In T. Lenaerts, M. Giacobini, H. Bersini, P. Bourgine, M. Dorigo & R. Doursat (Eds.). Advances in Artificial Life, ECAL 2011: Proceedings of the Eleventh European Conference on the Synthesis and Simulation of Living Systems (pp. 85-92). Heidelberg: MIT Press. doi> full text>