How ecological interactions shape mutation rates to antimicrobial resistance

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 [1]. 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 [2]. 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 [3]. The reduction in mutation rate in dense populations requires proteins dealing with oxidatively damaged nucleotides in the cell [1]. Using simple synthetic microbial communities in the laboratory [4] 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 world-class bioscience, that is advancing the frontiers of bioscience discovery. It is rooted in existing BBSRC grant funding and will help in understanding the rules of life and the BBSRC theme of integrative microbiome research. It will use and develop transformative technologies, by taking systems approaches to the biosciences, involving collaboration, partnerships and knowledge exchange between wet-laboratory and computational work, developing the student to become the next generation of people and talent.

[1] Krasovec, 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
[2] Krasovec, 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
[3] Krasovec, 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