The rate of environmental change drives adaptation to an antibiotic sink

Mutators can drive the evolution of multi-resistance to antibiotics

Antibiotic combination therapies are an approach used to counter the evolution of resistance; their purported benefit is they can stop the successive emergence of independent resistance mutations in the same genome. Here, we show that bacterial populations with 'mutators', organisms with defects in DNA repair, readily evolve resistance to combination antibiotic treatment when there is a delay in reaching inhibitory concentrations of antibiotic-under conditions where purely wild-type populations cannot. In populations of Escherichia coli subjected to combination treatment, we detected a diverse array of acquired mutations, including multiple alleles in the canonical targets of resistance for the two drugs, as well as mutations in multi-drug efflux pumps and genes involved in DNA replication and repair. Unexpectedly, mutators not only allowed multi-resistance to evolve under combination treatment where it was favoured, but also under single-drug treatments. Using simulations, we show that the increase in mutation rate of the two canonical resistance targets is sufficient to permit multi-resistance evolution in both single-drug and combination treatments. Under both conditions, the mutator allele swept to fixation through hitch-hiking with single-drug resistance, enabling subsequent resistance mutations to emerge. Ultimately, our results suggest that mutators may hinder the utility of combination therapy when mutators are present. Additionally, by raising the rates of genetic mutation, selection for multi-resistance may have the unwanted side-effect of increasing the potential to evolve resistance to future antibiotic treatments.

Change in prey genotype frequency rescues predator from extinction

Indirect evolutionary rescue (IER) is a mechanism where a non-evolving species is saved from extinction in an otherwise lethal environment by evolution in an interacting species. This process has been described in a predator-prey model, where extinction of the predator is prevented by a shift in the frequency of defended towards undefended prey when reduced predator densities lower selection for defended prey. We test here how increased mortality and the initial frequencies of the prey types affect IER. Combining the analysis of model simulations and experiments with rotifers feeding on algae we show IER in the presence of increased predator mortality. We found that IER was dependent on the ability of the prey to evolve as well as on the frequency of the defended prey. High initial frequencies of defended prey resulted in predator extinction despite the possibility for prey evolution, as the increase in undefended prey was delayed too much to allow predator rescue. This frequency dependency for IER was more pronounced for higher predator mortalities. Our findings can help informing the development of conservation and management strategies that consider evolutionary responses in communities to environmental changes.

Host adaptation to novel pathogen introduction: Predicting conditions that promote evolutionary rescue

Novel pathogen introduction can have drastic consequences for naive host populations, and outcomes can be difficult to predict. Evolutionary rescue (ER) provides a foundation for understanding whether hosts are driven to extinction or survive via adaptation. Currently, patterns of host population dynamics alongside evidence of adaptation are used to infer ER. However, the gap between established ER theory and complexity inherent in natural systems makes interpreting empirical patterns difficult because they can be confounded with ecological drivers of survival under current theory. To bridge this gap, we expand ER theory to include biological selective agents, such as pathogens. We find birth processes to be more important than previously theorised in determining ER potential. We employ a novel framework evaluating ER potential within natural systems and gain ability to identify system characteristics that make ER possible. Identifying these characteristics allows a shift from retrospective observation to a predictive mindset, and our findings suggest that ER occurrence may be more limited than previously thought. We use the plague system of Yersinia pestis infecting Cynomys ludovicianus (black-tailed prairie dogs) and Spermophilus beecheyi (California ground squirrels) as a case study.

Compensatory adaptation and diversification subsequent to evolutionary rescue in a model adaptive radiation

Biological populations may survive lethal environmental stress through evolutionary rescue. The rescued populations typically suffer a reduction in growth performance and harbor very low genetic diversity compared with their parental populations. The present study addresses how population size and within-population diversity may recover through compensatory evolution, using the experimental adaptive radiation of bacterium Pseudomonas fluorescens. We exposed bacterial populations to an antibiotic treatment and then imposed a one-individual-size population bottleneck on those surviving the antibiotic stress. During the subsequent compensatory evolution, population size increased and leveled off very rapidly. The increase of diversity was of slower paces and persisted longer. In the very early stage of compensatory evolution, populations of large sizes had a greater chance to diversify; however, this productivity-diversification relationship was not observed in later stages. Population size and diversity from the end of the compensatory evolution was not contingent on initial population growth performance. We discussed the possibility that our results be explained by the emergence of a "holey" fitness landscape under the antibiotic stress.

Understanding the critical rate of environmental change for ecosystems, cyanobacteria as an example

Recently it has been show that in some ecosystems fast rates of change of environmental drivers may trigger a critical transition, whereas change of the same magnitude but at slower rates would not. So far, few studies describe this phenomenon of rate-induced tipping, while it is important to understand this phenomenon in the light of the ongoing rapid environmental change. Here, we demonstrate rate-induced tipping in a simple model of cyanobacteria with realistic parameter settings. We explain graphically that there is a range of initial conditions at which a gradual increase in environmental conditions can cause a collapse of the population, but only if the change is fast enough. In addition, we show that a pulse in the environmental conditions can cause a temporary collapse, but that is dependent on both the rate and the duration of the pulse. Furthermore, we study whether the autocorrelation of stochastic environmental conditions can influence the probability of inducing rate-tipping. As both the rate of environmental change, and autocorrelation of the environmental variability are increasing in parts of the climate, the probability for rate-induced tipping to occur is likely to increase. Our results imply that, even though the identification of rate sensitive ecosystems in the real world will be challenging, we should incorporate critical rates of change in our ecosystem assessments and management.

Evolutionary rescue at different rates of environmental change is affected by trade-offs between short-term performance and long-term survival

As climate change accelerates and habitats free from anthropogenic impacts diminish, populations are forced to migrate or to adapt quickly. Evolutionary rescue (ER) is a phenomenon, in which a population is able to avoid extinction through adaptation. ER is considered to be more likely at slower rates of environmental change. However, the effects of correlated characters on evolutionary rescue are seldom explored yet correlated characters could play a major role in ER. We tested how evolutionary background in different fluctuating environments and the rate of environmental change affect the probability of ER by exposing populations of the bacteria Serratia marcescens to two different rates of steady temperature increase. As suggested by theory, slower environmental change allowed populations to grow more effectively even at extreme temperatures, but at the expense of long-term survival at extreme conditions due to correlated selection. Our results indicate important gap of knowledge on the effects of correlated selection during the environmental change and on evolutionary rescue at differently changing environments.

Adaptation at different points along antibiotic concentration gradients

Antibiotic concentrations vary dramatically in the body and the environment. Hence, understanding the dynamics of resistance evolution along antibiotic concentration gradients is critical for predicting and slowing the emergence and spread of resistance. While it has been shown that increasing the concentration of an antibiotic slows resistance evolution, how adaptation to one antibiotic concentration correlates with fitness at other points along the gradient has not received much attention. Here, we selected populations of Escherichia coli at several points along a concentration gradient for three different antibiotics, asking how rapidly resistance evolved and whether populations became specialized to the antibiotic concentration they were selected on. Populations selected at higher concentrations evolved resistance more slowly but exhibited equal or higher fitness across the whole gradient. Populations selected at lower concentrations evolved resistance rapidly, but overall fitness in the presence of antibiotics was lower. However, these populations readily adapted to higher concentrations upon subsequent selection. Our results indicate that resistance management strategies must account not only for the rates of resistance evolution but also for the fitness of evolved strains.

Repeatable ecological dynamics govern the response of experimental communities to antibiotic pulse perturbation

In an era of pervasive anthropogenic ecological disturbances, there is a pressing need to understand the factors that constitute community response and resilience. A detailed understanding of disturbance response needs to go beyond associations and incorporate features of disturbances, species traits, rapid evolution and dispersal. Multispecies microbial communities that experience antibiotic perturbation represent a key system with important medical dimensions. However, previous microbiome studies on this theme have relied on high-throughput sequencing data from uncultured species without the ability to explicitly account for the role of species traits and immigration. Here, we serially passage a 34-species defined bacterial community through different levels of pulse antibiotic disturbance, manipulating the presence or absence of species immigration. To understand the ecological community response measured using amplicon sequencing, we combine initial trait data measured for each species separately and metagenome sequencing data revealing adaptive mutations during the experiment. We found that the ecological community response was highly repeatable within the experimental treatments, which could be attributed in part to key species traits (antibiotic susceptibility and growth rate). Increasing antibiotic levels were also coupled with an increasing probability of species extinction, making species immigration critical for community resilience. Moreover, we detected signals of antibiotic-resistance evolution occurring within species at the same time scale, leaving evolutionary changes in communities despite recovery at the species compositional level. Together, these observations reveal a disturbance response that presents as classic species sorting, but is nevertheless accompanied by rapid within-species evolution.

Rate of environmental change across scales in ecology

The rate of change (RoC) of environmental drivers matters: biotic and abiotic components respond differently when faced with a fast or slow change in their environment. This phenomenon occurs across spatial scales and thus levels of ecological organization. We investigated the RoC of environmental drivers in the ecological literature and examined publication trends across ecological levels, including prevalent types of evidence and drivers. Research interest in environmental driver RoC has increased over time (particularly in the last decade), however, the amount of research and type of studies were not equally distributed across levels of organization and different subfields of ecology use temporal terminology (e.g. 'abrupt' and 'gradual') differently, making it difficult to compare studies. At the level of individual organisms, evidence indicates that responses and underlying mechanisms are different when environmental driver treatments are applied at different rates, thus we propose including a time dimension into reaction norms. There is much less experimental evidence at higher levels of ecological organization (i.e. population, community, ecosystem), although theoretical work at the population level indicates the importance of RoC for evolutionary responses. We identified very few studies at the community and ecosystem levels, although existing evidence indicates that driver RoC is important at these scales and potentially could be particularly important for some processes, such as community stability and cascade effects. We recommend shifting from a categorical (e.g. abrupt versus gradual) to a quantitative and continuous (e.g. °C/h) RoC framework and explicit reporting of RoC parameters, including magnitude, duration and start and end points to ease cross-scale synthesis and alleviate ambiguity. Understanding how driver RoC affects individuals, populations, communities and ecosystems, and furthermore how these effects can feed back between levels is critical to making improved predictions about ecological responses to global change drivers. The application of a unified quantitative RoC framework for ecological studies investigating environmental driver RoC will both allow cross-scale synthesis to be accomplished more easily and has the potential for the generation of novel hypotheses.

Evolutionary tracking is determined by differential selection on demographic rates and density dependence

Recent ecological forecasts predict that ~25% of species worldwide will go extinct by 2050. However, these estimates are primarily based on environmental changes alone and fail to incorporate important biological mechanisms such as genetic adaptation via evolution. Thus, environmental change can affect population dynamics in ways that classical frameworks can neither describe nor predict. Furthermore, often due to a lack of data, forecasting models commonly describe changes in population demography by summarizing changes in fecundity and survival concurrently with the intrinsic growth rate (r). This has been shown to be an oversimplification as the environment may impose selective pressure on specific demographic rates (birth and death) rather than directly on r (the difference between the birth and death rates). This differential pressure may alter population response to density, in each demographic rate, further diluting the information combined to produce r. Thus, when we consider the potential for persistence via adaptive evolution, populations with the same r can have different abilities to persist amidst environmental change. Therefore, we cannot adequately forecast population response to climate change without accounting for demography and selection on density dependence. Using a continuous-time Markov chain model to describe the stochastic dynamics of the logistic model of population growth and allow for trait evolution via mutations arising during birth events, we find persistence via evolutionary tracking more likely when environmental change alters birth rather than the death rate. Furthermore, species that evolve responses to changes in the strength of density dependence due to environmental change are less vulnerable to extinction than species that undergo selection independent of population density. By incorporating these key demographic considerations into our predictive models, we can better understand how species will respond to climate change.

The limit of resistance to salinity in the freshwater cyanobacterium Microcystis aeruginosa is modulated by the rate of salinity increase

The overall mean levels of different environmental variables are changing rapidly in the present Anthropocene, in some cases creating lethal conditions for organisms. Under this new scenario, it is crucial to know whether the adaptive potential of organisms allows their survival under different rates of environmental change. Here, we used an eco-evolutionary approach, based on a ratchet protocol, to investigate the effect of environmental change rate on the limit of resistance to salinity of three strains of the toxic cyanobacterium Microcystis aeruginosa. Specifically, we performed two ratchet experiments in order to simulate two scenarios of environmental change. In the first scenario, the salinity increase rate was slow (1.5-fold increase), while in the second scenario, the rate was faster (threefold increase). Salinity concentrations ranging 7-10 gL-1 NaCl (depending on the strain) inhibited growth completely. However, when performing the ratchet experiment, an increase in salinity resistance (9.1-13.6 gL-1 NaCl) was observed in certain populations. The results showed that the limit of resistance to salinity that M. aeruginosa strains were able to reach depended on the strain and on the rate of environmental change. In particular, a higher number of populations were able to grow under their initial lethal salinity levels when the rate of salinity increment was slow. In future scenarios of increased salinity in natural freshwater bodies, this could have toxicological implications due to the production of microcystin by this species.

Predicting community dynamics of antibiotic-sensitive and -resistant species in fluctuating environments

Microbes occupy almost every niche within and on their human hosts. Whether colonizing the gut, mouth or bloodstream, microorganisms face temporal fluctuations in resources and stressors within their niche but we still know little of how environmental fluctuations mediate certain microbial phenotypes, notably antimicrobial-resistant ones. For instance, do rapid or slow fluctuations in nutrient and antimicrobial concentrations select for, or against, resistance? We tackle this question using an ecological approach by studying the dynamics of a synthetic and pathogenic microbial community containing two species, one sensitive and the other resistant to an antibiotic drug where the community is exposed to different rates of environmental fluctuation. We provide mathematical models, supported by experimental data, to demonstrate that simple community outcomes, such as competitive exclusion, can shift to coexistence and ecosystem bistability as fluctuation rates vary. Theory gives mechanistic insight into how these dynamical regimes are related. Importantly, our approach highlights a fundamental difference between resistance in single-species populations, the context in which it is usually assayed, and that in communities. While fast environmental changes are known to select against resistance in single-species populations, here we show that they can promote the resistant species in mixed-species communities. Our theoretical observations are verified empirically using a two-species Candida community.

Evolutionary Dynamics in the RNA Bacteriophage Qβ Depends on the Pattern of Change in Selective Pressures

The rate of change in selective pressures is one of the main factors that determines the likelihood that populations can adapt to stress conditions. Generally, the reduction in the population size that accompanies abrupt environmental changes makes it difficult to generate and select adaptive mutations. However, in systems with high genetic diversity, as happens in RNA viruses, mutations with beneficial effects under new conditions can already be present in the population, facilitating adaptation. In this work, we have propagated an RNA bacteriophage (Qβ) at temperatures higher than the optimum, following different patterns of change. We have determined the fitness values and the consensus sequences of all lineages throughout the evolutionary process in order to establish correspondences between fitness variations and adaptive pathways. Our results show that populations subjected to a sudden temperature change gain fitness and fix mutations faster than those subjected to gradual changes, differing also in the particular selected mutations. The life-history of populations prior to the environmental change has great importance in the dynamics of adaptation. The conclusion is that in the bacteriophage Qβ, the standing genetic diversity together with the rate of temperature change determine both the rapidity of adaptation and the followed evolutionary pathways.

Slower environmental change hinders adaptation from standing genetic variation

Evolutionary responses to environmental change depend on the time available for adaptation before environmental degradation leads to extinction. Explicit tests of this relationship are limited to microbes where adaptation usually depends on the sequential fixation of de novo mutations, excluding standing variation for genotype-by-environment fitness interactions that should be key for most natural species. For natural species evolving from standing genetic variation, adaptation at slower rates of environmental change may be impeded since the best genotypes at the most extreme environments can be lost during evolution due to genetic drift or founder effects. To address this hypothesis, we perform experimental evolution with self-fertilizing populations of the nematode Caenorhabditis elegans and develop an inference model to describe natural selection on extant genotypes under environmental change. Under a sudden environmental change, we find that selection rapidly increases the frequency of genotypes with high fitness in the most extreme environment. In contrast, under a gradual environmental change selection first favors genotypes that are worse at the most extreme environment. We demonstrate with a second set of evolution experiments that, as a consequence of slower environmental change and thus longer periods to reach the most extreme environments, genetic drift and founder effects can lead to the loss of the most beneficial genotypes. We further find that maintenance of standing genetic variation can retard the fixation of the best genotypes in the most extreme environment because of interference between them. Taken together, these results show that slower environmental change can hamper adaptation from standing genetic variation and they support theoretical models indicating that standing variation for genotype-by-environment fitness interactions critically alters the pace and outcome of adaptation under environmental change.

Experimental Design, Population Dynamics, and Diversity in Microbial Experimental Evolution

In experimental evolution, laboratory-controlled conditions select for the adaptation of species, which can be monitored in real time. Despite the current popularity of such experiments, nature's most pervasive biological force was long believed to be observable only on time scales that transcend a researcher's life-span, and studying evolution by natural selection was therefore carried out solely by comparative means. Eventually, microorganisms' propensity for fast evolutionary changes proved us wrong, displaying strong evolutionary adaptations over a limited time, nowadays massively exploited in laboratory evolution experiments. Here, we formulate a guide to experimental evolution with microorganisms, explaining experimental design and discussing evolutionary dynamics and outcomes and how it is used to assess ecoevolutionary theories, improve industrially important traits, and untangle complex phenotypes. Specifically, we give a comprehensive overview of the setups used in experimental evolution. Additionally, we address population dynamics and genetic or phenotypic diversity during evolution experiments and expand upon contributing factors, such as epistasis and the consequences of (a)sexual reproduction. Dynamics and outcomes of evolution are most profoundly affected by the spatiotemporal nature of the selective environment, where changing environments might lead to generalists and structured environments could foster diversity, aided by, for example, clonal interference and negative frequency-dependent selection. We conclude with future perspectives, with an emphasis on possibilities offered by fast-paced technological progress. This work is meant to serve as an introduction to those new to the field of experimental evolution, as a guide to the budding experimentalist, and as a reference work to the seasoned expert.

Mechanical interactions in bacterial colonies and the surfing probability of beneficial mutations

Bacterial conglomerates such as biofilms and microcolonies are ubiquitous in nature and play an important role in industry and medicine. In contrast to well-mixed cultures routinely used in microbial research, bacteria in a microcolony interact mechanically with one another and with the substrate to which they are attached. Here, we use a computer model of a microbial colony of rod-shaped cells to investigate how physical interactions between cells determine their motion in the colony and how this affects biological evolution. We show that the probability that a faster-growing mutant ‘surfs’ at the colony's frontier and creates a macroscopic sector depends on physical properties of cells (shape, elasticity and friction). Although all these factors contribute to the surfing probability in seemingly different ways, their effects can be summarized by two summary statistics that characterize the front roughness and cell alignment. Our predictions are confirmed by experiments in which we measure the surfing probability for colonies of different front roughness. Our results show that physical interactions between bacterial cells play an important role in biological evolution of new traits, and suggest that these interactions may be relevant to processes such as de novo evolution of antibiotic resistance.

Adaptations of an RNA virus to increasing thermal stress

Environments can change in incremental fashions, where a shift from one state to another occurs over multiple organismal generations. The rate of the environmental change is expected to influence how and how well populations adapt to the final environmental state. We used a model system, the lytic RNA bacteriophage Φ6, to investigate this question empirically. We evolved viruses for thermostability by exposing them to heat shocks that increased to a maximum temperature at different rates. We observed increases in the ability of many heat-shocked populations to survive high temperature heat shocks. On their first exposure to the highest temperature, populations that experienced a gradual increase in temperature had higher average survival than populations that experienced a rapid temperature increase. However, at the end of the experiment, neither the survival of populations at the highest temperature nor the number of mutations per population varied significantly according to the rate of thermal change. We also evaluated mutations from the endpoint populations for their effects on viral thermostability and growth. As expected, some mutations did increase viral thermostability. However, other mutations decreased thermostability but increased growth rate, suggesting that benefits of an increased replication rate may have sometimes outweighed the benefits of enhanced thermostability. Our study highlights the importance of considering the effects of multiple selective pressures, even in environments where a single factor changes.

Convection shapes the trade-off between antibiotic efficacy and the selection for resistance in spatial gradients

Since penicillin was discovered about 90 years ago, we have become used to using drugs to eradicate unwanted pathogenic cells. However, using drugs to kill bacteria, viruses or cancer cells has the serious side effect of selecting for mutant types that survive the drug attack. A crucial question therefore is how one could eradicate as many cells as possible for a given acceptable risk of drug resistance evolution. We address this general question in a model of drug resistance evolution in spatial drug gradients, which recent experiments and theories have suggested as key drivers of drug resistance. Importantly, our model takes into account the influence of convection, resulting for instance from blood flow. Using stochastic simulations, we study the fates of individual resistance mutations and quantify the trade-off between the killing of wild-type cells and the rise of resistance mutations: shallow gradients and convection into the antibiotic region promote wild-type death, at the cost of increasing the establishment probability of resistance mutations. We can explain these observed trends by modeling the adaptation process as a branching random walk. Our analysis reveals that the trade-off between death and adaptation depends on the relative length scales of the spatial drug gradient and random dispersal, and the strength of convection. Our results show that convection can have a momentous effect on the rate of establishment of new mutations, and may heavily impact the efficiency of antibiotic treatment.

The effect of selection history on extinction risk during severe environmental change

Environments rarely remain the same over time, and populations are therefore frequently at risk of going extinct when changes are significant enough to reduce fitness. Although many studies have investigated what attributes of the new environments and of the populations experiencing these changes will affect their probability of going extinct, limited work has been directed towards determining the role of population history on the probability of going extinct during severe environmental change. Here, we compare the extinction risk of populations with a history of selection in a benign environment, to populations with a history of selection in one or two stressful environments. We exposed spores and lines of the green alga Chlamydomonas reinhardtii from these three different histories to a range of severe environmental changes. We found that the extinction risk was higher for populations with a history of selection in stressful environments compared to populations with a history of selection in a benign environment. This effect was not due to differences in initial population sizes. Finally, the rates of extinction were highly repeatable within histories, indicating strong historical contingency of extinction risk. Hence, information on the selection history of a population can be used to predict their probability of going extinct during environmental change.

Evolutionary rescue and local adaptation under different rates of temperature increase: a combined analysis of changes in phenotype expression and genotype frequency in Paramecium microcosms

Evolutionary rescue (ER) occurs when populations, which have declined due to rapid environmental change, recover through genetic adaptation. The success of this process and the evolutionary trajectory of the population strongly depend on the rate of environmental change. Here we investigated how different rates of temperature increase (from 23 to 32 °C) affect population persistence and evolutionary change in experimental microcosms of the protozoan Paramecium caudatum. Consistent with theory on ER, we found that those populations experiencing the slowest rate of temperature increase were the least likely to become extinct and tended to be the best adapted to the new temperature environment. All high-temperature populations were more tolerant to severe heat stress (35, 37 °C), indicating a common mechanism of heat protection. High-temperature populations also had superior growth rates at optimum temperatures, leading to the absence of a pattern of local adaptation to control (23 °C) and high-temperature (32 °C) environments. However, high-temperature populations had reduced growth at low temperatures (5-9 °C), causing a shift in the temperature niche. In part, the observed evolutionary change can be explained by selection from standing variation. Using mitochondrial markers, we found complete divergence between control and high-temperature populations in the frequencies of six initial founder genotypes. Our results confirm basic predictions of ER and illustrate how adaptation to an extreme local environment can produce positive as well as negative correlated responses to selection over the entire range of the ecological niche.

Rate of novel host invasion affects adaptability of evolving RNA virus lineages

Although differing rates of environmental turnover should be consequential for the dynamics of adaptive change, this idea has been rarely examined outside of theory. In particular, the importance of RNA viruses in disease emergence warrants experiments testing how differing rates of novel host invasion may impact the ability of viruses to adaptively shift onto a novel host. To test whether the rate of environmental turnover influences adaptation, we experimentally evolved 144 Sindbis virus lineages in replicated tissue-culture environments, which transitioned from being dominated by a permissive host cell type to a novel host cell type. The rate at which the novel host 'invaded' the environment varied by treatment. The fitness (growth rate) of evolved virus populations was measured on each host type, and molecular substitutions were mapped via whole genome consensus sequencing. Results showed that virus populations more consistently reached high fitness levels on the novel host when the novel host 'invaded' the environment more gradually, and gradual invasion resulted in less variable genomic outcomes. Moreover, virus populations that experienced a rapid shift onto the novel host converged upon different genotypes than populations that experienced a gradual shift onto the novel host, suggesting a strong effect of historical contingency.

Bacterial adaptation to sublethal antibiotic gradients can change the ecological properties of multitrophic microbial communities

Antibiotics leak constantly into environments due to widespread use in agriculture and human therapy. Although sublethal concentrations are well known to select for antibiotic-resistant bacteria, little is known about how bacterial evolution cascades through food webs, having indirect effect on species not directly affected by antibiotics (e.g. via population dynamics or pleiotropic effects). Here, we used an experimental evolution approach to test how temporal patterns of antibiotic stress, as well as migration within metapopulations, affect the evolution and ecology of microcosms containing one prey bacterium, one phage and two protist predators. We found that environmental variability, autocorrelation and migration had only subtle effects for population and evolutionary dynamics. However, unexpectedly, bacteria evolved greatest fitness increases to both antibiotics and enemies when the sublethal levels of antibiotics were highest, indicating positive pleiotropy. Crucially, bacterial adaptation cascaded through the food web leading to reduced predator-to-prey abundance ratio, lowered predator community diversity and increased instability of populations. Our results show that the presence of natural enemies can modify and even reverse the effects of antibiotics on bacteria, and that antibiotic selection can change the ecological properties of multitrophic microbial communities by having indirect effects on species not directly affected by antibiotics.

Experimental adaptation to marine conditions by a freshwater alga

The marine-freshwater boundary has been suggested as one of the most difficult to cross for organisms. Salt is a major ecological factor and provides an unequalled range of ecological opportunity because marine habitats are much more extensive than freshwater habitats, and because salt strongly affects the structure of microbial communities. We exposed experimental populations of the freshwater alga Chlamydomonas reinhardtii to steadily increasing concentrations of salt. About 98% of the lines went extinct. The ones that survived now thrive in growth medium with 36 g⋅L(-1) NaCl, and in seawater. Our results indicate that adaptation to marine conditions proceeded first through genetic assimilation of an inducible response to relatively low salt concentrations that was present in the ancestors, and subsequently by the evolution of an enhanced inducible response to high salt concentrations. These changes appear to have evolved through reversible and irreversible modifications, respectively. The evolution of marine from freshwater lineages is an example that clearly indicates the possibility of studying certain aspects of major ecological transitions in the laboratory.

The effects of spatial structure, frequency dependence and resistance evolution on the dynamics of toxin-mediated microbial invasions

Recent evidence suggests that interference competition between bacteria shapes the distribution of the opportunistic pathogen Staphylococcus aureus in the lower nasal airway of humans, either by preventing colonization or by driving displacement. This competition within the nasal microbial community would add to known host factors that affect colonization. We tested the role of toxin-mediated interference competition in both structured and unstructured environments, by culturing S. aureus with toxin-producing or nonproducing Staphylococcus epidermidis nasal isolates. Toxin-producing S. epidermidis invaded S. aureus populations more successfully than nonproducers, and invasion was promoted by spatial structure. Complete displacement of S. aureus was prevented by the evolution of toxin resistance. Conversely, toxin-producing S. epidermidis restricted S. aureus invasion. Invasion of toxin-producing S. epidermidis populations by S. aureus resulted from the evolution of toxin resistance, which was favoured by high initial frequency and low spatial structure. Enhanced toxin production also evolved in some invading populations of S. epidermidis. Toxin production therefore promoted invasion by, and constrained invasion into, populations of producers. Spatial structure enhanced both of these invasion effects. Our findings suggest that manipulation of the nasal microbial community could be used to limit colonization by S. aureus, which might limit transmission and infection rates.

Evolutionary rescue can be impeded by temporary environmental amelioration

Rapid evolutionary adaptation has the potential to rescue from extinction populations experiencing environmental changes. Little is known, however, about the impact of short-term environmental fluctuations during long-term environmental deterioration, an intrinsic property of realistic environmental changes. Temporary environmental amelioration arising from such fluctuations could either facilitate evolutionary rescue by allowing population recovery (a positive demographic effect) or impede it by relaxing selection for beneficial mutations required for future survival (a negative population genetic effect). We address this uncertainty in an experiment with populations of a bacteriophage virus that evolved under deteriorating conditions (gradually increasing temperature). Periodic environmental amelioration (short periods of reduced temperature) caused demographic recovery during the early phase of the experiment, but ultimately reduced the frequency of evolutionary rescue. These experimental results suggest that environmental fluctuations could reduce the potential of evolutionary rescue.

Catch Me if You Can: Adaptation from Standing Genetic Variation to a Moving Phenotypic Optimum

Adaptation lies at the heart of Darwinian evolution. Accordingly, numerous studies have tried to provide a formal framework for the description of the adaptive process. Of these, two complementary modeling approaches have emerged: While so-called adaptive-walk models consider adaptation from the successive fixation of de novo mutations only, quantitative genetic models assume that adaptation proceeds exclusively from preexisting standing genetic variation. The latter approach, however, has focused on short-term evolution of population means and variances rather than on the statistical properties of adaptive substitutions. Our aim is to combine these two approaches by describing the ecological and genetic factors that determine the genetic basis of adaptation from standing genetic variation in terms of the effect-size distribution of individual alleles. Specifically, we consider the evolution of a quantitative trait to a gradually changing environment. By means of analytical approximations, we derive the distribution of adaptive substitutions from standing genetic variation, that is, the distribution of the phenotypic effects of those alleles from the standing variation that become fixed during adaptation. Our results are checked against individual-based simulations. We find that, compared to adaptation from de novo mutations, (i) adaptation from standing variation proceeds by the fixation of more alleles of small effect and (ii) populations that adapt from standing genetic variation can traverse larger distances in phenotype space and, thus, have a higher potential for adaptation if the rate of environmental change is fast rather than slow.

Fighting microbial drug resistance: a primer on the role of evolutionary biology in public health

Although microbes have been evolving resistance to antimicrobials for millennia, the spread of resistance in pathogen populations calls for the development of new drugs and treatment strategies. We propose that successful, long-term resistance management requires a better understanding of how resistance evolves in the first place. This is an opportunity for evolutionary biologists to engage in public health, a collaboration that has substantial precedent. Resistance evolution has been an important tool for developing and testing evolutionary theory, especially theory related to the genetic basis of new traits and constraints on adaptation. The present era is no exception. The articles in this issue highlight the breadth of current research on resistance evolution and also its challenges. In this introduction, we review the conceptual advances that have been achieved from studying resistance evolution and describe a path forward.

Evolutionary rescue: linking theory for conservation and medicine

Evolutionary responses that rescue populations from extinction when drastic environmental changes occur can be friend or foe. The field of conservation biology is concerned with the survival of species in deteriorating global habitats. In medicine, in contrast, infected patients are treated with chemotherapeutic interventions, but drug resistance can compromise eradication of pathogens. These contrasting biological systems and goals have created two quite separate research communities, despite addressing the same central question of whether populations will decline to extinction or be rescued through evolution. We argue that closer integration of the two fields, especially of theoretical understanding, would yield new insights and accelerate progress on these applied problems. Here, we overview and link mathematical modelling approaches in these fields, suggest specific areas with potential for fruitful exchange, and discuss common ideas and issues for empirical testing and prediction.

Fisher's geometric model with a moving optimum

Fisher's geometric model has been widely used to study the effects of pleiotropy and organismic complexity on phenotypic adaptation. Here, we study a version of Fisher's model in which a population adapts to a gradually moving optimum. Key parameters are the rate of environmental change, the dimensionality of phenotype space, and the patterns of mutational and selectional correlations. We focus on the distribution of adaptive substitutions, that is, the multivariate distribution of the phenotypic effects of fixed beneficial mutations. Our main results are based on an “adaptive-walk approximation,” which is checked against individual-based simulations. We find that (1) the distribution of adaptive substitutions is strongly affected by the ecological dynamics and largely depends on a single composite parameter γ, which scales the rate of environmental change by the “adaptive potential” of the population; (2) the distribution of adaptive substitution reflects the shape of the fitness landscape if the environment changes slowly, whereas it mirrors the distribution of new mutations if the environment changes fast; (3) in contrast to classical models of adaptation assuming a constant optimum, with a moving optimum, more complex organisms evolve via larger adaptive steps.

Role of sex and migration in adaptation to sink environments

Understanding the effects of sex and migration on adaptation to novel environments remains a key problem in evolutionary biology. Using a single-cell alga Chlamydomonas reinhardtii, we investigated how sex and migration affected rates of evolutionary rescue in a sink environment, and subsequent changes in fitness following evolutionary rescue. We show that sex and migration affect both the rate of evolutionary rescue and subsequent adaptation. However, their combined effects change as the populations adapt to a sink habitat. Both sex and migration independently increased rates of evolutionary rescue, but the effect of sex on subsequent fitness improvements, following initial rescue, changed with migration, as sex was beneficial in the absence of migration but constraining adaptation when combined with migration. These results suggest that sex and migration are beneficial during the initial stages of adaptation, but can become detrimental as the population adapts to its environment.

Evolutionary constraints in variable environments, from proteins to networks

Environmental changes can not only trigger a regulatory response, but also impose evolutionary pressures that can modify the underlying regulatory network. Here, we review recent approaches that are beginning to disentangle this complex interplay between regulatory and evolutionary responses. Systematic genetic reconstructions have shown how evolutionary constraints arise from epistatic interactions between mutations in fixed environments. This approach is now being extended to more complex environments and systems. The first results suggest that epistasis is affected dramatically by environmental changes and, hence, can profoundly affect the course of evolution. Thus, external environments not only define the selection of favored phenotypes, but also affect the internal constraints that can limit the evolution of these phenotypes. These findings also raise new questions relating to the conditions for evolutionary transitions and the evolutionary potential of regulatory networks.

Experimental evolution as an efficient tool to dissect adaptive paths to antibiotic resistance

Antibiotic treatments increasingly fail due to rapid dissemination of drug resistance. Comparative genomics of clinical isolates highlights the role of de novo adaptive mutations and horizontal gene transfer (HGT) in the acquisition of resistance. Yet it cannot fully describe the selective pressures and evolutionary trajectories that yielded today's problematic strains. Experimental evolution offers a compelling addition to such studies because the combination of replicated experiments under tightly controlled conditions with genomics of intermediate time points allows real-time reconstruction of evolutionary trajectories. Recent studies thus established causal links between antibiotic deployment therapies and the course and timing of mutations, the cost of resistance and the likelihood of compensating mutations. They particularly underscored the importance of long-term effects. Similar investigations incorporating horizontal gene transfer (HGT) are wanting, likely because of difficulties associated with its integration into experiments. In this review, we describe current advances in experimental evolution of antibiotic resistance and reflect on ways to incorporate horizontal gene transfer into the approach. We contend it provides a powerful tool for systematic and highly controlled dissection of evolutionary paths to antibiotic resistance that needs to be taken into account for the development of sustainable anti-bacterial treatment strategies.

Local climatic adaptation in a widespread microorganism

Exploring the ability of organisms to locally adapt is critical for determining the outcome of rapid climate changes, yet few studies have addressed this question in microorganisms. We investigated the role of a heterogeneous climate on adaptation of North American populations of the wild yeast Saccharomyces paradoxus. We found abundant among-strain variation for fitness components across a range of temperatures, but this variation was only partially explained by climatic variation in the distribution area. Most of fitness variation was explained by the divergence of genetically distinct groups, distributed along a north-south cline, suggesting that these groups have adapted to distinct climatic conditions. Within-group fitness components were correlated with climatic conditions, illustrating that even ubiquitous microorganisms locally adapt and harbour standing genetic variation for climate-related traits. Our results suggest that global climatic changes could lead to adaptation to new conditions within groups, or changes in their geographical distributions.

Rapid evolution of quantitative traits: theoretical perspectives

An increasing number of studies demonstrate phenotypic and genetic changes in natural populations that are subject to climate change, and there is hope that some of these changes will contribute to avoiding species extinctions ('evolutionary rescue'). Here, we review theoretical models of rapid evolution in quantitative traits that can shed light on the potential for adaptation to a changing climate. Our focus is on quantitative-genetic models with selection for a moving phenotypic optimum. We point out that there is no one-to-one relationship between the rate of adaptation and population survival, because the former depends on relative fitness and the latter on absolute fitness. Nevertheless, previous estimates that sustainable rates of genetically based change usually do not exceed 0.1 haldanes (i.e., phenotypic standard deviations per generation) are probably correct. Survival can be greatly facilitated by phenotypic plasticity, and heritable variation in plasticity can further speed up genetic evolution. Multivariate selection and genetic correlations are frequently assumed to constrain adaptation, but this is not necessarily the case and depends on the geometric relationship between the fitness landscape and the structure of genetic variation. Similar conclusions hold for adaptation to shifting spatial gradients. Recent models of adaptation in multispecies communities indicate that the potential for rapid evolution is strongly influenced by interspecific competition.

Fold or hold: experimental evolution in vitro

We introduce a system for experimental evolution consisting of populations of short oligonucleotides (Oli populations) evolving in a modified quantitative polymerase chain reaction (qPCR). It is tractable at the genetic, genomic, phenotypic and fitness levels. The Oli system uses DNA hairpins designed to form structures that self-prime under defined conditions. Selection acts on the phenotype of self-priming, after which differences in fitness are amplified and quantified using qPCR. We outline the methodological and bioinformatics tools for the Oli system here and demonstrate that it can be used as a conventional experimental evolution model system by test-driving it in an experiment investigating adaptive evolution under different rates of environmental change.

Microbial variome database: point mutations, adaptive or not, in bacterial core genomes

Analysis of genetic differences (gene presence/absence and nucleotide polymorphisms) among strains of a bacterial species is crucial to understanding molecular mechanisms of bacterial pathogenesis and selecting targets for novel antibacterial therapeutics. However, lack of genome-wide association studies on large and epidemiologically well-defined strain collections from the same species makes it difficult to identify the genes under positive selection and define adaptive polymorphisms in those genes. To address this need and to overcome existing limitations, we propose to create a "microbial variome"--a species-specific resource database of genomic variations based on molecular evolutionary analysis. Here, we present prototype variome databases of Escherichia coli and Salmonella enterica subspecies enterica (http://depts.washington.edu/sokurel/variome, last accessed March 26, 2013). The prototypes currently include the point mutations data of core protein-coding genes from completely sequenced genomes of 22 E. coli and 17 S. enterica strains. These publicly available databases allow for single- and multiple-field sorting, filtering, and searching of the gene variability data and the potential adaptive significance. Such resource databases would immensely help experimental research, clinical diagnostics, epidemiology, and environmental control of human pathogens.

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.

Multidrug therapy and evolution of antibiotic resistance: when order matters

The evolution of drug resistance among pathogenic bacteria has led public health workers to rely increasingly on multidrug therapy to treat infections. Here, we compare the efficacy of combination therapy (i.e., using two antibiotics simultaneously) and sequential therapy (i.e., switching two antibiotics) in minimizing the evolution of multidrug resistance. Using in vitro experiments, we show that the sequential use of two antibiotics against Pseudomonas aeruginosa can slow down the evolution of multiple-drug resistance when the two antibiotics are used in a specific order. A simple population dynamics model reveals that using an antibiotic associated with high costs of resistance first minimizes the chance of multidrug resistance evolution during sequential therapy under limited mutation supply rate. As well as presenting a novel approach to multidrug therapy, this work shows that costs of resistance not only influences the persistence of antibiotic-resistant bacteria but also plays an important role in the emergence of resistance.

Herbicide cycling has diverse effects on evolution of resistance in Chlamydomonas reinhardtii

Cycling pesticides has been proposed as a means of retarding the evolution of resistance, but its efficacy has rarely been empirically tested. We evolved populations of Chlamydomonas reinhardtii in the presence of three herbicides: atrazine, glyphosate and carbetamide. Populations were exposed to a weekly, biweekly and triweekly cycling between all three pairwise combinations of herbicides and continuously to each of the three herbicides. We explored the impacts of herbicide cycling on the rate of resistance evolution, the level of resistance selected, the cost of resistance and the degree of generality (cross-resistance) observed. Herbicide cycling resulted in a diversity of outcomes: preventing evolution of resistance for some combinations of herbicides, having no impacts for others and increasing rates of resistance evolution in some instances. Weekly cycling of atrazine and carbetamide resulted in selection of a generalist population. This population had a higher level of resistance, and this generalist resistance was associated with a cost. The level of resistance selected did not vary amongst other regimes. Costs of resistance were generally highest when cycling was more frequent. Our data suggest that the effects of herbicide cycling on the evolution of resistance may be more complex and less favourable than generally assumed.

Population subdivision and adaptation in asexual populations of Saccharomyces cerevisiae

Population subdivision limits competition between individuals, which can have a profound effect on adaptation. Subdivided populations maintain more genetic diversity at any given time compared to well-mixed populations, and thus "explore" larger parts of the genotype space. At the same time, beneficial mutations take longer to spread in such populations, and thus subdivided populations do not "exploit" discovered mutations as efficiently as well-mixed populations. Whether subdivision inhibits or promotes adaptation in a given environment depends on the relative importance of exploration versus exploitation, which in turn depends on the structure of epistasis among beneficial mutations. Here we investigate the relative importance of exploration versus exploitation for adaptation by evolving 976 independent asexual populations of budding yeast with several degrees of geographic subdivision. We find that subdivision systematically inhibits adaptation: even the luckiest demes in subdivided populations on average fail to discover genotypes that are fitter than those discovered by well-mixed populations. Thus, exploitation of discovered mutations is more important for adaptation in our system than a thorough exploration of the mutational neighborhood, and increasing subdivision slows adaptation.