Recombination and drug resistance in microbial populations

Many bacteria and viruses exchange genetic material with each other, but it is not clear what forces drive the evolution of these forms of recombination. A case in point is natural transformation, where bacteria take up DNA molecules from the environment and integrate these into their own genome. Some scholars have argued that transformation is selected in bacteria for the same reasons that sex and recombination has evolved in eukaryotes, i.e. to increase genetic variation within populations. Others think the DNA that is taken up mostly serves a more direct function (either to facilitate DNA repair or simply as food), and that recombination is only an accidental by-product.

We investigate the evolution and maintenance of natural transformation and other forms of microbial recombination through both mathematical models and experimental evolution. Currently, the focus of our models is to understand (1) the impact of complex fitness landscapes in bringing about an advantage of recombination during microbial adaptation (Moradigaravand & Engelstädter 2012; Moradigaravand et al. 2014), and 2) how various ecological factors influence the impact of recombination on microbial evolution. For example, our models indicate that natural transformation can differ fundamentally in its effect on populations from other forms of recombination because the pool of free DNA that serves as a source of new genetic material may differ from the genetic pool within the living bacteria (Moradigaravand & Engelstädter 2013; Engelstädter & Moradigaravand 2014). We have also investigated the evolutio
nary dynamics of integrons, which are widespread bacterial ‘gene-capture devices’ capable of integrating and reshuffling gene cassettes that may code for drug resistance determinants (Engelstädter et al. 2016).

Colonies of Acinetobacter baylyi

We complement our theoretical work by an experimental evolution approach with which we test some of our model predictions. To this end, with the help of collaborator Pål Johnsen and his group at the University of Tromsø, we have established an experimental system using the bacterium Acinetobacter baylyi. This bacterium undergoes natural transformation at a very high rate and is therefore well suited to address questions about the evolution of sex in bacteria. Several evolution experiments investigating the role of natural transformation during adaptive evolution are currently underway.

Finally, we are also very interested in the evolution of antibiotic resistance in bacteria, especially in how recombination affects this important evolutionary process. Currently, our research focuses on the evolutionary dynamics of compensatory mutations that ameliorate fitness costs of resistance mutations (Schulz zur Wiesch et al. 2010) and on how drug concentrations affect the fitness landscape in multidrug resistance evolution (Engelstädter 2014).

Selected publications:

Engelstädter J., Harms, K. & Johnsen, P.J.
The evolutionary dynamics of integrons in changing environments.
The ISME Journal 10: 1296-1307 (2016)

Abel zur Wiesch, P., Abel, S., Gkotzis, S., Ocampo, P., Engelstädter, J., Hinkley, T., Magnus, C., Waldor, M.K., Udekwu, K. & Cohen, T.
Classic reaction kinetics can explain complex patterns of antibiotic action.
Science Translational Medicine 7: 287 (2015)

Engelstädter, J. & Moradigaravand, D.
Adaptation through genetic time travel? Fluctuating selection can drive the evolution of bacterial transformation.
Proceedings of the Royal Society B 281: 20132609 (2014)

Moradigaravand, D. & Engelstädter, J.
The evolution of natural competence: disentangling costs and benefits of sex in bacteria.
The American Naturalist 182: E112-E126 (2013)

Moradigaravand, D. & Engelstädter, J.
The effect of bacterial recombination on adaptation on fitness landscapes with limited peak accessibility.
PLoS Computational Biology 8: e1002735 (2012)

Abel zur Wiesch, P.K., Kouyos, R.D., Engelstädter, J., Regoes, R.R. & Bonhoeffer, S.
Population biological principles of resistance evolution in infectious diseases.
The Lancet Infectious Diseases 11: 236-247 (2011)

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