Danna R. Gifford

The Properties of Adaptive Walks in Evolving Populations of Fungus

A novel method to infer the number and fitness effect of beneficial mutations reveals that the bulk of adaptive evolution is attributable to a few mutations with variable effects on fitness.

The length of adaptive walks is insensitive to starting fitness in Aspergillus nidulans.

Adaptation involves the successive substitution of beneficial mutations by selection, a process known as an adaptive walk. Gradualist models of adaptation, which assume that all mutations are small relative to the distance to a fitness optimum, predict that adaptive walks should be longer when the founding genotype is less well adapted. More recent work modeling adaptation as a sequence of moves in phenotype or genotype space predicts, by contrast, much shorter adaptive walks irrespective of the fitness of the founding genotype. Here, we provide what is, to the best of our knowledge, the first direct test of these alternative models, measuring the length of adaptive walks in evolving lineages of fungus that differ initially in fitness. Contrary to the gradualist view, we show that the length of adaptive walks in the fungus Aspergillus nidulans is insensitive to starting fitness and involves just two mutations on average. This arises because poorly adapted populations tend to fix mutations of larger average effect than those of better‐adapted populations. Our results suggest that the length of adaptive walks may be independent of the fitness of the founding genotype and, moreover, that poorly adapted populations can quickly adapt to novel environments.

Multicopy plasmids potentiate the evolution of antibiotic resistance in bacteria.

Plasmids are thought to play a key role in bacterial evolution by acting as vehicles for horizontal gene transfer, but the role of plasmids as catalysts of gene evolution remains unexplored. We challenged populations of Escherichia coli carrying the blaTEM-1 β-lactamase gene on either the chromosome or a multicopy plasmid (19 copies per cell) with increasing concentrations of ceftazidime. The plasmid accelerated resistance evolution by increasing the rate of appearance of novel TEM-1 mutations, thereby conferring resistance to ceftazidime, and then by amplifying the effect of TEM-1 mutations due to the increased gene dosage. Crucially, this dual effect was necessary and sufficient for the evolution of clinically relevant levels of resistance. Subsequent evolution occurred by mutations in a regulatory RNA that increased the plasmid copy number, resulting in marginal gains in ceftazidime resistance. These results uncover a role for multicopy plasmids as catalysts for the evolution of antibiotic resistance in bacteria.

Evolutionary reversals of antibiotic resistance in experimental populations of Pseudomonas aeruginosa.

Antibiotic resistance mutations are accompanied by a fitness cost, and two mechanisms allow bacteria to adapt to this cost once antibiotic use is halted. First, it is possible for resistance to revert; second, it is possible for bacteria to adapt to the cost of resistance by compensatory mutations. Unfortunately, reversion to antibiotic sensitivity is rare, but the underlying factors that prevent reversion remain obscure. Here, we directly study the evolutionary dynamics of reversion by experimentally mimicking reversion mutations—sensitives—in populations of rifampicin‐resistant Pseudomonas aeruginosa. We show that, in our populations, most sensitives are lost due to genetic drift when they are rare. However, clonal interference from lineages carrying compensatory mutations causes a dramatic increase in the time to fixation of sensitives that escape genetic drift, and mutations surpassing the sensitives’ fitness are capable of driving transiently common sensitive lineages to extinction. Crucially, we show that the constraints on reversion arising from clonal interference are determined by the potential for compensatory adaptation of the resistant population. Although the cost of resistance provides the incentive for reversion, our study demonstrates that both the cost of resistance and the intrinsic evolvability of resistant populations interact to determine the rate and likelihood of reversion.

Model and test in a fungus of the probability that beneficial mutations survive drift

Determining the probability of fixation of beneficial mutations is critically important for building predictive models of adaptive evolution. Despite considerable theoretical work, models of fixation probability have stood untested for nearly a century. However, recent advances in experimental and theoretical techniques permit the development of models with testable predictions. We developed a new model for the probability of surviving genetic drift, a major component of fixation probability, for novel beneficial mutations in the fungus Aspergillus nidulans, based on the life-history characteristics of its colony growth on a solid surface. We tested the model by measuring the probability of surviving drift in 11 adapted strains introduced into wild-type populations of different densities. We found that the probability of surviving drift increased with mutant invasion fitness, and decreased with wild-type density, as expected. The model accurately predicted the survival probability for the majority of mutants, yielding one of the first direct tests of the extinction probability of beneficial mutations.

Divergent evolution peaks under intermediate population bottlenecks during bacterial experimental evolution.

There is growing evidence that parallel molecular evolution is common, but its causes remain poorly understood. Demographic parameters such as population bottlenecks are predicted to be major determinants of parallelism. Here, we test the hypothesis that bottleneck intensity shapes parallel evolution by elucidating the genomic basis of adaptation to antibiotic-supplemented media in hundreds of populations of the bacterium Pseudomonas fluorescens Pf0-1. As expected, bottlenecking decreased the rate of phenotypic and molecular adaptation. Surprisingly, bottlenecking had no impact on the likelihood of parallel adaptive molecular evolution at a genome-wide scale. However, bottlenecking had a profound impact on the genes involved in antibiotic resistance. Specifically, under either intense or weak bottlenecking, resistance predominantly evolved by strongly beneficial mutations which provide high levels of antibiotic resistance. In contrast with intermediate bottlenecking regimes, resistance evolved by a greater diversity of genetic mechanisms, significantly reducing the observed levels of parallel genetic evolution. Our results demonstrate that population bottlenecking can be a major predictor of parallel evolution, but precisely how may be more complex than many simple theoretical predictions.

Parasite diversity drives rapid host dynamics and evolution of resistance in a bacteria-phage system.

Host–parasite evolutionary interactions are typically considered in a pairwise species framework. However, natural infections frequently involve multiple parasites. Altering parasite diversity alters ecological and evolutionary dynamics as parasites compete and hosts resist multiple infection. We investigated the effects of parasite diversity on host–parasite population dynamics and evolution using the pathogen Pseudomonas aeruginosa and five lytic bacteriophage parasites. To manipulate parasite diversity, bacterial populations were exposed for 24 hours to either phage monocultures or diverse communities containing up to five phages. Phage communities suppressed host populations more rapidly but also showed reduced phage density, likely due to interphage competition. The evolution of resistance allowed rapid bacterial recovery that was greater in magnitude with increases in phage diversity. We observed no difference in the extent of resistance with increased parasite diversity, but there was a profound impact on the specificity of resistance; specialized resistance evolved to monocultures through mutations in a diverse set of genes. In summary, we demonstrate that parasite diversity has rapid effects on host–parasite population dynamics and evolution by selecting for different resistance mutations and affecting the magnitude of bacterial suppression and recovery. Finally, we discuss the implications of phage diversity for their use as biological control agents.

Environmental variation alters the fitness effects of rifampicin resistance mutations in Pseudomonas aeruginosa.

The fitness effects of antibiotic resistance mutations in antibiotic‐free conditions play a key role in determining the long‐term maintenance of resistance. Although resistance is usually associated with a cost, the impact of environmental variation on the cost of resistance is poorly understood. Here, we test the impact of heterogeneity in temperature and resource availability on the fitness effects of antibiotic resistance using strains of the pathogenic bacterium Pseudomonas aeruginosa carrying clinically important rifampicin resistance mutations. Although the rank order of fitness was generally maintained across environments, fitness effects relative to the wild type differed significantly. Changes in temperature had a profound impact on the fitness effects of resistance, whereas changes in carbon substrate had only a weak impact. This suggests that environmental heterogeneity may influence whether the costs of resistance are likely to be ameliorated by second‐site compensatory mutations or by reversion to wild‐type rpoB. Our results highlight the need to consider environmental heterogeneity and genotype‐by‐environment interactions for fitness in models of resistance evolution.

Modelling colony population growth in the filamentous fungus Aspergillus nidulans

Filamentous fungi are ubiquitous in nature and have high societal significance, being both major (food-borne) pathogens and important industrial organisms in the production of antibiotics and enzymes. In addition, fungi are important model organisms for fundamental research, such as studies in genetics and evolutionary biology. However, mechanistic models for population growth that would help understand fungal biology and fundamental processes are almost entirely missing. Here we present such a mechanistic model for the species Aspergillus nidulans as an exemplar of models for other filamentous fungi. The model is based on physiological parameters that influence colony growth, namely mycelial growth rate and sporulation rate, to predict the number of individual nuclei present in a colony through time. Using population size data for colonies of differing ages, we find that our mechanistic model accurately predicts the number of nuclei for two growth environments, and show that fungal population size is most dependent on changes in mycelial growth rate.

Here's to the Losers: Evolvable Residents Accelerate the Evolution of High-Fitness Invaders

Recent work has shown that evolvability plays a key role in determining the long-term population dynamics of asexual clones. However, simple considerations suggest that the evolvability of a focal lineage of bacteria should also be influenced by the evolvability of its competitors. First, evolvable competitors should accelerate evolution by impeding the fixation of the focal lineage through a clonal interference–like mechanism. Second, evolvable competitors should increase the strength of selection by rapidly degrading the environment, increasing selection for adaptive mutations. Here we tested these ideas by allowing a high-fitness clone of the bacterium Pseudomonas aeruginosa to invade populations of two low-fitness resident clones that differ in their evolvability. Both competition from mutations in the resident lineage and environmental degradation lead to faster adaptation in the invader through fixing single mutations with a greater fitness advantage. The results suggest that competition from mutations in both the successful invader and the unsuccessful resident shapes the adaptive trajectory of the invader through both direct competition and indirect environmental effects. Therefore, to predict evolutionary outcomes, it will be necessary to consider the evolvability of all members of the community and the effects of adaptation on the quality of the environment. This is particularly relevant to mixed microbial communities where lineages differ in their adaptive potential, a common feature of chronic infections.