The evolution of mutation rates: separating causes from consequences

Simulating the Effect of Environmental Change on Evolving Populations

This study uses evolutionary simulations to explore the strategies that emerge to enable populations to cope with random environmental changes in situations where lifetime learning approaches are not available to accommodate them. In particular, it investigates how the average magnitude of change per unit time and the persistence of the changes (and hence the resulting autocorrelation of the environmental time series) affect the change tolerances, population diversities, and extinction timescales that emerge. Although it is the change persistence (often discussed in terms of environmental noise color) that has received most attention in the recent literature, other factors, particularly the average change magnitude, interact with this and can be more important drivers of the adaptive strategies that emerge. Moreover, when running simulations, the choice of change representation and normalization can also affect the outcomes. Detailed simulations are presented that are designed to explore all these issues. They also reveal significant dependences on the associated mutation rates and the extent to which they can evolve, and they clarify how evolution often leads populations into strategies with higher risks of extinction. Overall, this study shows how modeling the effect of environmental change requires more care than may have previously been realized.

Low mutation rates promote the evolution of advantageous traits by preventing interference from deleterious mutations

We studied how mutation rates promote the evolution of advantageous traits in an asexual population. First, to examine the effects of mutation rates on the evolution of an advantageous trait (high competitive ability), we carried out simulation analyses with competition between individuals for survival. Second, to examine the mechanism underlying the promotion of advantageous trait evolution, we calculated the probabilities that new favorable effects of mutations on the phenotype were acquired and that existing favorable effects were maintained. In the simulation analyses, advantageous traits evolved in the population with a low mutation rate; however, when the mutation rate was extremely low, advantageous traits evolved slowly because few beneficial mutations occurred. Then, the numerical calculations showed that the probability of acquiring new favorable effects of mutations on the phenotype and the probability of maintaining existing favorable effects are high if the mutation rate is low. The former occurs because, if the mutation rate is high, multiple mutations may occur in a genome, and even if beneficial mutations occur, their favorable effects may be masked by simultaneously occurring deleterious mutations. However, if the mutation rate is low, it is likely that only one beneficial mutation occurs, and its favorable effect on the phenotype is direct. In conclusion, low mutation rates are advantageous because they promote favorable phenotypic effects of mutations without interference from deleterious mutations; these low rates not only prevent the occurrence of deleterious mutations but also help maintain existing beneficial mutations and promote the evolution of advantageous traits.

Mutation rate variability as a driving force in adaptive evolution

Mutation rate is a key determinant of the pace as well as outcome of evolution, and variability in this rate has been shown in different scenarios to play a key role in evolutionary adaptation and resistance evolution under stress caused by selective pressure. Here we investigate the dynamics of resistance fixation in a bacterial population with variable mutation rates, and we show that evolutionary outcomes are most sensitive to mutation rate variations when the population is subject to environmental and demographic conditions that suppress the evolutionary advantage of high-fitness subpopulations. By directly mapping a biophysical fitness function to the system-level dynamics of the population, we show that both low and very high, but not intermediate, levels of stress in the form of an antibiotic result in a disproportionate effect of hypermutation on resistance fixation. We demonstrate how this behavior is directly tied to the extent of genetic hitchhiking in the system, the propagation of high-mutation rate cells through association with high-fitness mutations. Our results indicate a substantial role for mutation rate flexibility in the evolution of antibiotic resistance under conditions that present a weak advantage over wildtype to resistant cells.

Viral mutation rates: modelling the roles of within-host viral dynamics and the trade-off between replication fidelity and speed

Many viruses, particularly RNA viruses, mutate at a very high rate per genome per replication. One possible explanation is that high mutation rates are selected to meet the challenge of fluctuating environments, including the host immune response. Alternatively, recent studies argue that viruses evolve under a trade-off between replication speed and fidelity such that fast replication is selected, and, along with it, high mutation rates. Here, in addition to these factors, we consider the role of viral life-history properties: namely, the within-host dynamics of viruses resulting from their interaction with the host. We develop mathematical models incorporating factors occurring within and between hosts, including deleterious and advantageous mutations, host death owing to virulence and clearance of viruses by the host. Beneficial mutations confer both a within-host and a transmission advantage. First, we find that advantageous mutations have only a weak effect on the optimal genomic mutation rate. Second, viral life-history properties have a large effect on the mutation rate. Third, when the speed-fidelity trade-off is included, there can be two locally optimal mutation rates. Our analysis provides a way to consider how life-history properties combine with biochemical trade-offs to shape mutation rates.