EVOLUTIONARY SYSTEMS GENETICS OF MICROBES
- Dabos, Laura - Postdoctoral Fellow
- Devin Altès, Guillem August - PhD Student
- Sánchez Maroto Capilla, Laura - PhD Student
Our research activities deal with understanding the fundamental principles governing microbial evolution. To this end, we employ a combination of computational (e.g. simulations, comparative genomics) and experimental methods (e.g. multiplexed genome engineering, high-throughput DNA sequencing, experimental evolution). In brief, our approach involves conducting adaptation experiments in the lab to watch evolution in real time. Using next-generation sequencing, we monitor genome changes in the experimental lines over hundreds of generations. The results from these experiments and analyses are then compared with predictions from computational models, which in turn inform the design of further experiments. With this combination we ultimately seek to gain insights into the factors that guide populations through different adaptive paths (see Figure 1). While our research is primarily inspired by fundamental questions, we employ a variety of microbial systems (human and plant pathogens, biotechnologically relevant strains) with the ultimate goal of producing insights and resources to help controlling the evolution of microbes in clinical, industrial, and agricultural settings.
Figure 1. Predicting evolution. Several mutational paths are often available for populations to adapt to novel environments. The choice among different routes has traditionally been understood as the result of the interplay between selection and drift. Recent work, however, has emphasized the role of mutational biases in favouring particular routes (coloured arrows). In the lab, a central topic we seek to understand is how the complex interplay between mutation biases and genetic and environmental interactions determine the outcome of evolution.
An important model system in the lab are bacterial mutators, i.e. mutants with highly-elevated and highly-biased mutation rates due to defects in the DNA Repair machinery. Mutators are quite common among human pathogens, being considered a major risk factor for antibiotic resistance evolution, and we suspect that they may play similar roles in plant pathogens. In addition, given the central role that mutation rate plays in evolution, they represent an ideal case study to investigate many fundamental theories in evolutionary genetics, such as the maintenance of genetic diversity, the extinction of small populations or the evolution of sex.
If you are interested in any of these topics, we are expanding and welcome applications from highly motivated students and postdocs who may wish to join the lab. Informal enquiries are encouraged and can be made by email to the address above.
Couce, A., Tenaillon, O. 2019. Mutation bias and GC content shape antimutator invasions. Nature Communications 10, 3114. DOI: 10.1038/s41467-019-11217-6
Couce, A., Viraphong Caudwell, L., Feinauer, C., Hindré, T., Feugeas, J.-P., Weigt, M., Lenski, R.E., Schneider, D., Tenaillon, O. 2017. Mutator genomes decay, despite sustained fitness gains, in a long-term experiment with bacteria. Proceedings of the National Academy of Sciences 114, E9026–E9035. DOI: 10.1073/pnas.1705887114
Couce, A., Rodríguez-Rojas, A., Blázquez, J. 2016. Determinants of Genetic Diversity of Spontaneous Drug Resistance in Bacteria. Genetics 203, 1369–1380. DOI: 10.1534/genetics.115.185355
Couce, A., Rodríguez-Rojas, A., Blázquez, J. 2015. Bypass of genetic constraints during mutator evolution to antibiotic resistance. Proceedings of the Royal Society B: Biological Sciences 282, 20142698. DOI: 10.1098/rspb.2014.2698
Couce, A., Tenaillon, O.A. 2015. The rule of declining adaptability in microbial evolution experiments. Frontiers in Genetics 6, 99. DOI: 10.3389/fgene.2015.00099
Couce, A., Guelfo, J.R., Blázquez, J. 2013. Mutational Spectrum Drives the Rise of Mutator Bacteria. PLOS Genetics 9, e1003167. DOI: 10.1371/journal.pgen.1003167