Bakery yeasts, a new model for studies in ecology and evolution.

Yeasts have been involved in bread making since ancient times and have thus played an important role in the history and nutrition of humans. Bakery-associated yeasts have only recently attracted the attention of researchers outside of the bread industry. More than 30 yeast species are involved in bread making, and significant progress has been achieved in describing these species. Here, we present a review of bread-making processes and history, and we describe the diversity of yeast species and the genetic diversity of Saccharomyces cerevisiae isolated from bakeries. We then describe the metabolic functioning and diversity of these yeasts and their relevance to improvements in bread quality. Finally, we examine yeast and bacterial interactions in sourdoughs. The purpose of this review is to show that bakery yeast species are interesting models for studying domestication and other evolutionary and ecological processes. Studying these yeasts can contribute much to our fundamental understanding of speciation, evolutionary dynamics, and community assembly, and this knowledge could ultimately be used to adjust, modify, and improve the production of bread and the conservation of microbial diversity.

Feedback between environment and traits under selection in a seasonal environment: consequences for experimental evolution.

Batch cultures are frequently used in experimental evolution to study the dynamics of adaptation. Although they are generally considered to simply drive a growth rate increase, other fitness components can also be selected for. Indeed, recurrent batches form a seasonal environment where different phases repeat periodically and different traits can be under selection in the different seasons. Moreover, the system being closed, organisms may have a strong impact on the environment. Thus, the study of adaptation should take into account the environment and eco-evolutionary feedbacks. Using data from an experimental evolution on yeast Saccharomyces cerevisiae, we developed a mathematical model to understand which traits are under selection, and what is the impact of the environment for selection in a batch culture. We showed that two kinds of traits are under selection in seasonal environments: life-history traits, related to growth and mortality, but also transition traits, related to the ability to react to environmental changes. The impact of environmental conditions can be summarized by the length of the different seasons which weight selection on each trait: the longer a season is, the higher the selection on associated traits. Since phenotypes drive season length, eco-evolutionary feedbacks emerge. Our results show how evolution in successive batches can affect season lengths and strength of selection on different traits.

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.

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 population's 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.

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.

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 Taylor's 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 Taylor's Law. We tested whether this prediction applied to the spatial version of Taylor's 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 Taylor's Law with a slope of 2 held for these simple bacterial communities, but competitive interactions between the two species did not reduce the spatial Taylor's Law slope. These results contribute to the widespread usefulness of Taylor's Law in population ecology, epidemiology and pest control.

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.