Nonlinear frequency-dependent selection promotes long-term coexistence between bacteria species.

Negative frequency-dependent selection (NFDS) is an important mechanism for species coexistence and for the maintenance of genetic polymorphism. Long-term coexistence nevertheless requires NFDS interactions to be resilient to further evolution of the interacting species or genotypes. For closely related genotypes, NFDS interactions have been shown to be preserved through successive rounds of evolution in coexisting lineages. On the contrary, the evolution of NFDS interactions between distantly related species has received less attention. Here, we tracked the co-evolution of Escherichia coli and Citrobacter freundii that initially differ in their ecological characteristics. We showed that these two bacterial species engaged in an NFDS interaction particularly resilient to further evolution: despite a very strong asymmetric rate of adaptation, their coexistence was maintained owing to an NFDS pattern where fitness increases steeply as the frequency decreases towards zero. Using a model, we showed how and why such NFDS pattern can emerge. These findings provide a robust explanation for the long-term maintenance of species at very low frequencies.

Evolution of bacteria specialization along an antibiotic dose gradient.

Antibiotic and pesticide resistance of pathogens are major and pressing worldwide issues. Resistance evolution is often considered in simplified ecological contexts: treated versus nontreated environments. In contrast, antibiotic usually present important dose gradients: from ecosystems to hospitals to polluted soils, in treated patients across tissues. However, we do not know whether adaptation to low or high doses involves different phenotypic traits, and whether these traits trade-off with each other. In this study, we investigated the occurrence of such fitness trade-offs along a dose gradient by evolving experimentally resistant lines of Escherichia coli at different antibiotic concentrations for ∼400 generations. Our results reveal fast evolution toward specialization following the first mutational step toward resistance, along with pervasive trade-offs among different evolution doses. We found clear and regular fitness patterns of specialization, which converged rapidly from different initial starting points. These findings are consistent with a simple fitness peak shift model as described by the classical evolutionary ecology theory of adaptation across environmental gradients. We also found that the fitness costs of resistance tend to be compensated through time at low doses whereas they increase through time at higher doses. This cost evolution follows a linear trend with the log-dose of antibiotic along the gradient. These results suggest a general explanation for the variability of the fitness costs of resistance and their evolution. Overall, these findings call for more realistic models of resistance management incorporating dose-specialization.

Fisher's geometrical model and the mutational patterns of antibiotic resistance across dose gradients.

Fisher's geometrical model (FGM) has been widely used to depict the fitness effects of mutations. It is a general model with few underlying assumptions that gives a large and comprehensive view of adaptive processes. It is thus attractive in several situations, for example adaptation to antibiotics, but comes with limitations, so that more mechanistic approaches are often preferred to interpret experimental data. It might be possible however to extend FGM assumptions to better account for mutational data. This is theoretically challenging in the context of antibiotic resistance because resistance mutations are assumed to be rare. In this article, we show with Escherichia coli how the fitness effects of resistance mutations screened at different doses of nalidixic acid vary across a dose-gradient. We found experimental patterns qualitatively consistent with the basic FGM (rate of resistance across doses, gamma distributed costs) but also unexpected patterns such as a decreasing mean cost of resistance with increasing screen dose. We show how different extensions involving mutational modules and variations in trait covariance across environments, can be discriminated based on these data. Overall, simple extensions of the FGM accounted well for complex mutational effects of resistance mutations across antibiotic doses.