Remy Froissart, CNRS

Bacterial evolution towards antibiotic resistance is becoming an increasingly pressing global problem. For example, nearly 5 million people die each year worldwide from infection with bacteria associated with one or more antibiotic resistances (Murray et al 2022 Lancet) and predictions are that 10 million people will die each year by 2050 (O'Neill 2016 Rev. Antimicriobiol. Resist). According to the World Health Organisation, a 'post-antibiotic' era - in which common infections and minor injuries can kill - could therefore soon be upon us if nothing is done. Some 20 bacterial species pose a particular threat to global public health, with carbapenem-resistant E. coli at the forefront.

To face this health threat, it is urgent to find new therapies capable of controlling antibiotic-resistant bacterial genotypes while taking into account the evolutionary processes in our therapeutic approaches (evolutionary medicine) in order to not fall into the same dead ends as we did with chemical antibiotics. Among the various alternative or complementary strategies to antibiotics, treatments involving therapeutic bacteriophages are currently in the midst of a renaissance phase of fundamental and applied research.

In the framework of a collaboration with the Hospices Civiles de Lyon and within the Phag-One project, the thesis project proposes to study the effect of the adaptation of several bacteriophages to one or several targetted bacterial genotypes (specialist versus generalist bacteriophages) not only on the efficacy and mechanisms of infection (virulence) but also on the capacity of the bacteriophages to inhibit the appearance of resistant bacteria.

The thesis will be carried out in a laboratory (Virostyle team, UMR 5290 MIVEGEC) where we are interested in understanding the antagonistic co-evolution between bacteriophages and Salmonella or E.coli. The work will be multi-disciplinary in that it will involve experiments in evolutionary biology (experimental evolution), microbiology (bacteriology and virology) and molecular biology. An interest in bioinformatics will be a plus. Collaboration with modellers will be possible.