Summary
Understanding the rapid adaptation of infectious pathogens is crucial to design better management policies and anticipate future changes. Yet, existing models often fail to explain these dynamics. I will address this major challenge of evolutionary biology in the bacterial species Escherichia coli. E. coli is a commensal of the human gut and an opportunistic pathogen causing infections responsible for more than a million deaths worldwide per year. E. coli has rapidly evolved over the last four decades. From the 1980s, starting from an almost fully sensitive population, multiple antibiotic resistances have emerged and stabilised at an intermediate frequency. Concomitantly, virulence, the propensity to cause infections, increased. The evolutionary processes causing these changes are largely unknown. To elucidate the drivers of the evolution of commensal E. coli, I will develop a prospective cohort of 200 longitudinally followed healthy volunteers—the largest cohort of its kind. We will analyse these data in the light of an integrative statistical and mathematical framework describing the ecology of E. coli from the within-host to the population level. These models will generate testable predictions on the evolution of genomic variants determining virulence, resistance, and colonisation ability. These predictions will be validated on an exceptional existing dataset composed of 1000 bacterial genomes sampled from healthy human hosts from 1980 to 2025 encompassing around 100,000 generations of bacterial evolution. This original interdisciplinary framework draws from epidemiology, evolutionary biology and genomics for a better understanding of the evolution of bacteria. This project is a step towards better predictions of evolutionary dynamics and better stewardship policies for infectious pathogens.
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| Web resources: | https://cordis.europa.eu/project/id/949208 |
| Start date: | 01-06-2021 |
| End date: | 31-05-2026 |
| Total budget - Public funding: | 1 499 893,00 Euro - 1 499 893,00 Euro |
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Original description
Understanding the rapid adaptation of infectious pathogens is crucial to design better management policies and anticipate future changes. Yet, existing models often fail to explain these dynamics. I will address this major challenge of evolutionary biology in the bacterial species Escherichia coli. E. coli is a commensal of the human gut and an opportunistic pathogen causing infections responsible for more than a million deaths worldwide per year. E. coli has rapidly evolved over the last four decades. From the 1980s, starting from an almost fully sensitive population, multiple antibiotic resistances have emerged and stabilised at an intermediate frequency. Concomitantly, virulence, the propensity to cause infections, increased. The evolutionary processes causing these changes are largely unknown. To elucidate the drivers of the evolution of commensal E. coli, I will develop a prospective cohort of 200 longitudinally followed healthy volunteers—the largest cohort of its kind. We will analyse these data in the light of an integrative statistical and mathematical framework describing the ecology of E. coli from the within-host to the population level. These models will generate testable predictions on the evolution of genomic variants determining virulence, resistance, and colonisation ability. These predictions will be validated on an exceptional existing dataset composed of 1000 bacterial genomes sampled from healthy human hosts from 1980 to 2025 encompassing around 100,000 generations of bacterial evolution. This original interdisciplinary framework draws from epidemiology, evolutionary biology and genomics for a better understanding of the evolution of bacteria. This project is a step towards better predictions of evolutionary dynamics and better stewardship policies for infectious pathogens.Status
SIGNEDCall topic
ERC-2020-STGUpdate Date
27-04-2024
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