Objective
"The evolution of antibiotic resistance poses an important threat to human health and welfare. Antibiotic resistance is accompanied by fitness costs that have been shown to play a key role in the spread of resistance. These costs are variable, but the underlying ecological and genetic causes of this variation remain obscure. Unfortunately, bacteria can adapt to the cost of resistance by compensatory mutations, and this permits resistance to be maintained in pathogen populations after antibiotics have been withdrawn from use. Resistance mutations vary in their potential for compensatory adaptation, but the causes of this variation remain unknown. In this project, we will determine how the molecular mechanisms of antibiotic resistance and the (i) ecological and (ii) genetic context in which resistance evolves interact to determine (a) the fitness costs associated with antibiotic resistance and (b) the potential and mechanisms for adaptation to the cost of resistance. Conceptually, we will approach this problem using an interdisciplinary approach that combines theory from population genetics and systems biology into the same evolutionary framework. To carry out this research program, we will use high-throughput experimental evolution of resistance to the broad-spectrum antibiotic rifampicin in bacteria from the genus Pseudomonas. This research approach will allow us to measure both the costs of resistance and the (i) rate and (ii) mechanisms of compensation for this cost at an unprecedented scale. The results of this research program will provide key insights into the underlying drivers of resistance emergence and persistence, and it may ultimately be possible to apply the insights from this research program to help combat resistance in pathogen populations. At a more conceptual level, this research will provide an important experimental test of the roles of chance, necessity, and historical contingency in shaping the rate and mechanisms of adaptation."
Fields of science
CORDIS classifies projects with EuroSciVoc, a multilingual taxonomy of fields of science, through a semi-automatic process based on NLP techniques.
CORDIS classifies projects with EuroSciVoc, a multilingual taxonomy of fields of science, through a semi-automatic process based on NLP techniques.
- natural sciencesbiological sciencesmicrobiologybacteriology
- natural sciencesbiological sciencesgeneticsmutation
- medical and health sciencesbasic medicinepharmacology and pharmacypharmaceutical drugsantibiotics
- medical and health sciencesbasic medicinepharmacology and pharmacydrug resistanceantibiotic resistance
Call for proposal
ERC-2011-StG_20101109
See other projects for this call
Funding Scheme
ERC-SG - ERC Starting GrantHost institution
OX1 2JD Oxford
United Kingdom