A team of scientists from the University of Cologne (Germany) and the University of Uppsala (Sweden) has created a model that can describe and predict the evolution of antibiotic resistance in bacteria. Resistance to antibiotics evolves through a variety of mechanisms. A central and still unresolved question is how resistance evolution affects cell growth at different drug concentrations. The new model predicts growth rates and resistance levels of common resistant bacterial mutants at different drug doses. These predictions are confirmed by empirical growth inhibition curves and genomic data from Escherichia coli populations. The study has been published in the journal ‘Nature Ecology & Evolution‘.
Antibiotic resistance arises through evolution. Bacteria change their genome and become less sensitive to drugs. Resistance mutations, however, often come at a cost to bacteria in the absence of antibiotics. The mutant cells have higher growth in the presence of the drug, but in a drug-free environment, their growth rate is lower than that of the antibiotic-susceptible wild type. ‘The cells have to optimize their decision about resistance. We have created a model that describes this process,’ said main author Fernanda Pinheiro from the Institute of Biological Physics at the University of Cologne.
The process can be compared to building and marketing houses, she explained: ‘Houses are built with a fixed budget. Depending on the location, you have to invest more or less to insulate against cold and, in return, make compromises in design. But an ugly house also sells poorly. Similarly, the