Dr Danna R Gifford MSc, DPhil

MRC Skills Development Fellow

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Understanding the emergence and spread of antimicrobial resistance is one of the grand challenges for global human health, but it is also a fascinating biological problem, concerning the evolution of populations experiencing complex environmental conditions.

My research combines experimental, mathematical, and bioinformatic approaches to predict how and when bacteria will evolve antibiotic resistance under biologically-realistic growth conditions. The aim of this research is to develop a rational framework for designing combination therapies to suppress resistance evolution and regain usefulness of antibiotics where resistance has become wide-spread. This work is crucial for establishing combination therapies as a viable solution to the antibiotic resistance crisis. The project is funded through a UKRI Rutherford Fellowship, involving collaborations with Tobias Galla, Chris Knight, and Simon Lovell.

I am also involved in a multi-disciplinary BBSRC project to study the adaptive landscapes of antibiotic resistance evolution. This project combines wet-lab experimental evolution with mathematical models and advanced computer simulations to predict how population size and mutational target size interact to shape resistance evolution. I am also collaborating with Rok Krašovec on the effects of mutation rate plasticity on the evolutionary genomics of E. coli.

Prospective applicants

If you are interested discussing the possibility of a graduate or postdoctoral positions, please contact me with a brief statement outlining your research interests, your research experience, and a recent CV.

Postdocs: There will soon be two Wellcome ISSF two-year postdocs advertised, one wet-lab and one theoretical, to work on antimicrobial resistance evolution. Please contact me for further details.

PhD students: I am happy to discuss student-proposed projects with prospective students in the areas of antimicrobial resistance, evolutionary genomics, and experimental evolution.

Externally-funded studentship projects

Prospective students interested in applying for externally-funded studentships should contact me regarding available funding sources (e.g. BSAC, SfAM, Wellcome, and others).


Project 1: Evolution by adaptive loss of gene function

Paradoxically, the first step of organisms' evolutionary adaptation to a new environment often involves losing existing genes, rather than gaining new ones—a phenomenon observed across the tree of life (Albalat and Cañestro 2016). Adaptation via loss-of-function is a particularly common process in microbial evolution observed for diverse selective pressures, e.g. novel carbon sources (Gifford et al. 2016), toxins such as antibiotics (Gifford et al. 2018) or heavy metals (Gorter et al. 2018), and new host environments (Winstanley et al. 2016). Despite the ubiquity of this process, we currently know little about how different environments shape loss of gene function, and the consequences of different loss-of-function mutations for organismal fitness in different environments.

Understanding evolution via loss-of-function will help us gain a handle not only on these important processes in natural selection, but will also have practical applications in, e.g. bioengineering, where preventing microbes from losing introduced genes is critical. We will first characterise fitness effects of single-gene deletant Escherichia coli strains in the Keio collection (Yamamoto et al. 2009) in a diverse set of environmental conditions, to identify the fitness effects of loss of gene function. Subsequently, we will constrast evolution at the genomic scale in high and low fitness strains in these environments. Finally, we will evolve wild-type strains with diverse genetic backgrounds in the same environments, to determine the probability that evolution would actually proceed via loss of function in the first instance.

This research will fill a gap in our current knowledge about the repeatability of adaptation via loss of function, its contribution to the adaptive process relative to other types of DNA changes, and its knock-on effects for survival and adaptation in other environments. Microbial experimental evolution offers the tools and throughput needed to uncover these processes over evolutionary time.  Genomic and experimental tools, including high-throughput sequencing and fitness assays, will enable us to address clear hypotheses, filling important gaps in our current knowledge on this key adaptive process.The successful candidate will be someone motivated by fundamental questions in evolution, with an interest in working at the interface of microbial genomics and ecology. They will have the opportunity to explore these questions using established microbial model systems, while being supported with training in both in microbiology, experimental evolution and bioinformatics.

  • lbalat, R. and Cañestro, C. (2016) Evolution by gene loss. Nature Reviews Genetics,  doi:10.1038/nrg.2016.39
  • Gifford, D.R., Toll‐Riera, M., and MacLean, R.C. (2016) Epistatic interactions between ancestral genotype and beneficial mutations shape evolvability in Pseudomonas aeruginosa. Evolution, 70(7), 1659-1666, doi:10.1111/evo.12958
  • Gifford, D.R., Furió, V., Papkou, A., Vogwill, T., Oliver, A., and MacLean, R.C. (2018) Identifying and exploiting genes that potentiate the evolution of antibiotic resistance. Nature Ecology & Evolution, 2(6), 1033, doi:10.1038/s41559-018-0547-x
  • Gorter, F.A., Derks, M.F., van den Heuvel, J., Aarts, M.G., Zwaan, B.J., de Ridder, D., and De Visser, J.A.G.M. (2017). Genomics of adaptation depends on the rate of environmental change in experimental yeast populations. Molecular Biology and Evolution, 34(10), 2613-2626, doi:10.1093/molbev/msx185
  • Yamamoto, N., Nakahigashi, K., Nakamichi, T., Yoshino, M., Takai, Y., Touda, Y., ... and Datsenko, K. A. (2009). Update on the Keio collection of Escherichia coli single‐gene deletion mutants. Molecular systems biology, 5(1), 335, doi:10.1038/msb.2009.92
  • Cao, H., Butler, K., Hossain, M., and Lewis, J. D. (2014). Variation in the fitness effects of mutations with population density and size in Escherichia coli. PLOS ONE, 9(8), e105369.



DPhil (2014): Department of Zoology, University of Oxford

MSc. Biology (2011): University of Ottawa (Canada)

Honours BSc with Specialization in Biology & Minor in Statistics (2008): University of Ottawa (Canada)

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