Head Pr Dominique Schneider
Biological systems emerge from Darwinian evolution, which is characterized by genetic modifications randomly occurring within genomes, followed by selection of the fittest mutant individuals in a given environment. Simultaneous studies of both components can be accomplished efficiently by experimental evolution, allowing analysis and comparison of an ancestor and its offspring over long evolutionary times. The use of microorganisms, with short generation times and large populations, makes it possible to study the dynamics of evolutionary processes in the laboratory, under controlled conditions and with high replication.
Our team uses experimental evolution to investigate the ecological and molecular mechanisms underlying the dynamics of microbial evolutionary processes. We are particularly interested in understanding how genomic changes are related to metabolic and expression regulatory network dynamics to allow adaptation, diversification, co-existence of bacterial ecotypes and modifications of virulence and antibiotic resistance traits. Establishing the link between, on one hand, changes in genomes and expression profiles and, on the other hand, changes in phenotypes like fitness and virulence is a prerequisite to understand how natural selection is able to re-shape and improve entire genomes, and which functions are more plastic over evolutionary time. Using such an evolutionary perspective is fully complementary to most Systems Biology approaches and addresses how evolvable are genomic and network features and what are the molecular bases of such evolvability.
Such approaches are developed in close collaboration with the two other research themes developed in our team. In particular, we develop experimental evolution to investigate the dynamics of antibiotic resistance and virulence in pathogenic bacteria (Francisella tularensis, Pseudomonas aeruginosa, Legionella pneumophila), and metabolic network are also investigated in the context of experimental evolution.
The work of our group is therefore integrative and interdisciplinary, at the frontier of ecology, evolution, microbiology, genetics, systems biology, medical science, and computer science. We develop interdisciplinary collaborations, in particular with modelling and computer scientists, population geneticists and medical practitioners involved in infectious disease management and prevention including the survey of the hospital environment. In particular, we develop collaborative modelling approaches both to analyze the “omic” data that we produce and to generate general principles of evolutionary processes by in silico evolution of digital organisms. The objective is to apply and integrate the investigation of evolutionary processes into a framework of Darwinian medicine to understand better the interplay between bacterial pathogens, treatment resistance and human patients.
Different specific topics are investigated in the context of evolution experiments: