Johan Ramsayer

The probability of evolutionary rescue: towards a quantitative comparison between theory and evolution experiments.

Evolutionary rescue occurs when a population genetically adapts to a new stressful environment that would otherwise cause its extinction. Forecasting the probability of persistence under stress, including emergence of drug resistance as a special case of interest, requires experimentally validated quantitative predictions. Here, we propose general analytical predictions, based on diffusion approximations, for the probability of evolutionary rescue. We assume a narrow genetic basis for adaptation to stress, as is often the case for drug resistance. First, we extend the rescue model of Orr & Unckless (Am. Nat. 2008 172, 160–169) to a broader demographic and genetic context, allowing the model to apply to empirical systems with variation among mutation effects on demography, overlapping generations and bottlenecks, all common features of microbial populations. Second, we confront our predictions of rescue probability with two datasets from experiments with Saccharomyces cerevisiae (yeast) and Pseudomonas fluorescens (bacterium). The tests show the qualitative agreement between the model and observed patterns, and illustrate how biologically relevant quantities, such as the per capita rate of rescue, can be estimated from fits of empirical data. Finally, we use the results of the model to suggest further, more quantitative, tests of evolutionary rescue theory.

A window of opportunity to control the bacterial pathogen Pseudomonas aeruginosa combining antibiotics and phages

The evolution of antibiotic resistance in bacteria is a global concern and the use of bacteriophages alone or in combined therapies is attracting increasing attention as an alternative. Evolutionary theory predicts that the probability of bacterial resistance to both phages and antibiotics will be lower than to either separately, due for example to fitness costs or to trade-offs between phage resistance mechanisms and bacterial growth. In this study, we assess the population impacts of either individual or combined treatments of a bacteriophage and streptomycin on the nosocomial pathogen Pseudomonas aeruginosa. We show that combining phage and antibiotics substantially increases bacterial control compared to either separately, and that there is a specific time delay in antibiotic introduction independent of antibiotic dose, that minimizes both bacterial density and resistance to either antibiotics or phage. These results have implications for optimal combined therapeutic approaches.

Resource availability affects the structure of a natural bacteria- bacteriophage community

Antagonistic networks are known to be structured in the wild, but knowledge on how this structure may change as a response to environmental perturbations is scarce. We describe a natural bipartite network between bacteria and lytic bacteriophages, and investigate how it is affected by environmental productivity in the form of different resource levels for the bacteria. We report that low amounts of resource decrease phage generality and lead to less robust and less stable communities. We discuss how resource levels in nature may alter the structure of complex communities.

Evolutionary rescue in populations of Pseudomonas fluorescens across an antibiotic gradient

Environmental change represents a major threat to species persistence. When change is rapid, a populations only means of persisting may be to evolve resistance. Understanding such ‘evolutionary rescues’ is important for conservation in the face of global change, but also in the agricultural and medical sciences, where the objective is rather population control or eradication. Theory predicts that evolutionary rescue is fostered by large populations and genetic variation, but this has yet to be tested. We replicated hundreds of populations of the bacterium Pseudomonas fluorescens SBW25 submitted to a range of doses of the antibiotic streptomycin. Consistent with theory, population size, and initial genetic diversity influenced population persistence and the evolution of antibiotic resistance. Although all treated populations suffered initial declines, those experiencing the smallest decreases were most likely to be evolutionarily rescued. Our results contribute to our understanding of how evolution may or may not save populations and species from extinction.

Taylor's Law holds in experimental bacterial populations but competition does not influence the slope

Populations vary in time and in space, and temporal variation may differ from spatial variation. Yet, in the past half century, field data have confirmed both the temporal and spatial forms of Taylors power Law, a linear relationship between log(variance) and log(mean) of population size. Recent theory predicted that competitive species interactions should reduce the slope of the temporal version of Taylors Law. We tested whether this prediction applied to the spatial version of Taylors Law using simple, well-controlled laboratory populations of two species of bacteria that were cultured either separately or together for 24 h in media of widely varying nutrient richness. Experimentally, the spatial form of Taylors Law with a slope of 2 held for these simple bacterial communities, but competitive interactions between the two species did not reduce the spatial Taylors Law slope. These results contribute to the widespread usefulness of Taylors Law in population ecology, epidemiology and pest control.

Hot spots become cold spots: coevolution in variable temperature environments

Antagonistic coevolution between hosts and parasites is a key process in the genesis and maintenance of biological diversity. Whereas coevolutionary dynamics show distinct patterns under favourable environmental conditions, the effects of more realistic, variable conditions are largely unknown. We investigated the impact of a fluctuating environment on antagonistic coevolution in experimental microcosms of Pseudomonas fluorescens SBW25 and lytic phage SBWΦ2. High‐frequency temperature fluctuations caused no deviations from typical coevolutionary arms race dynamics. However, coevolution was stalled during periods of high temperature under intermediate‐ and low‐frequency fluctuations, generating temporary coevolutionary cold spots. Temperature variation affected population density, providing evidence that eco‐evolutionary feedbacks act through variable bacteria–phage encounter rates. Our study shows that environmental fluctuations can drive antagonistic species interactions into and out of coevolutionary cold and hot spots. Whether coevolution persists or stalls depends on the frequency of change and the environmental optima of both interacting players.