Source-sink dynamics shape the evolution of antibiotic resistance and its pleiotropic fitness cost.
Understanding the conditions that favour the evolution and maintenance of antibiotic resistance is the central goal of epidemiology. A crucial feature explaining the adaptation to harsh, or 'sink', environments is the supply of beneficial mutations via migration from a 'source' population. Given that antibiotic resistance is frequently associated with antagonistic pleiotropic fitness costs, increased migration rate is predicted not only to increase the rate of resistance evolution but also to increase the probability of fixation of resistance mutations with minimal fitness costs. Here we report in vitro experiments using the nosocomial pathogenic bacterium Pseudomonas aeruginosa that support these predictions: increasing rate of migration into environments containing antibiotics increased the rate of resistance evolution and decreased the associated costs of resistance. Consistent with previous theoretical work, we found that resistance evolution arose more rapidly in the presence of a single antibiotic than two. Evolution of resistance was also more rapid when bacteria were subjected to sequential exposure with two antibiotics (cycling therapy) compared with simultaneous exposure (bi-therapy). Furthermore, pleiotropic fitness costs of resistance to two antibiotics were higher than for one antibiotic, and were also higher under bi-therapy than cycling therapy, although the cost of resistance depended on the order of the antibiotics through time. These results may be relevant to the clinical setting where immigration is known to be important between chemotherapeutically treated patients, and demonstrate the importance of ecological and evolutionary dynamics in the control of antibiotic resistance.
Perron
Gabriel G
GG
Department of Zoology, University of Oxford, South Parks Road, Oxford OX1 3PS, UK. gabriel.guimond-perron@zoo.ox.ac.uk
Gonzalez
Andrew
A
Buckling
Angus
A
D000900:Anti-Bacterial Agents / Q000494:pharmacology*; D005075:Biological Evolution; D024881:Drug Resistance, Bacterial / Q000187:drug effects; D008826:Microbial Sensitivity Tests; D008954:Models, Biological; D011550:Pseudomonas aeruginosa / Q000187:drug effects* / Q000254:growth & development
D000900:Anti-Bacterial Agents