Evolutionary rescue can prevent extinction following environmental change

The ubiquity of global change and its impacts on biodiversity poses a clear and urgent challenge for evolutionary biologists. In many cases, environmental change is so widespread and rapid that individuals can neither accommodate to them physiologically nor migrate to a more favourable site. Extinction will ensue unless the population adapts fast enough to counter the rate of decline. According to theory, whether populations can be rescued by evolution depends upon several crucial variables: population size, the supply of genetic variation, and the degree of maladaptation to the new environment. Using techniques in experimental evolution we tested the conditions for evolutionary rescue (ER). Hundreds of yeast populations were exposed to normally lethal concentrations of salt in conditions, where the frequency of rescue mutations was estimated and population size was manipulated. In a striking match with theory, we show that ER is possible, and that the recovery of the population may occur within 25 generations. We observed a clear threshold in population size for ER whereby the ancestral population size must be sufficiently large to counter stochastic extinction and contain resistant individuals. These results demonstrate that rapid evolution is an important component of the response of small populations to environmental change.     

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.     

The clarifying role of time series data in the population genetics of HIV

HIV can evolve remarkably quickly in response to antiretroviral therapies and the immune system. This evolution stymies treatment effectiveness and prevents the development of an HIV vaccine. Consequently, there has been a great interest in using population genetics to disentangle the forces that govern the HIV adaptive landscape (selection, drift, mutation, and recombination). Traditional population genetics approaches look at the current state of genetic variation and infer the processes that can generate it. However, because HIV evolves rapidly, we can also sample populations repeatedly over time and watch evolution in action. In this paper, we demonstrate how time series data can bound evolutionary parameters in a way that complements and informs traditional population genetic approaches. Specifically, we focus on our recent paper (Feder et al., 2016, eLife), in which we show that, as improved HIV drugs have led to fewer patients failing therapy due to resistance evolution, less genetic diversity has been maintained following the fixation of drug resistance mutations. Because soft sweeps of multiple drug resistance mutations spreading simultaneously have been previously documented in response to the less effective HIV therapies used early in the epidemic, we interpret the maintenance of post-sweep diversity in response to poor therapies as further evidence of soft sweeps and therefore a high population mutation rate (θ) in these intra-patient HIV populations. Because improved drugs resulted in rarer resistance evolution accompanied by lower post-sweep diversity, we suggest that both observations can be explained by decreased population mutation rates and a resultant transition to hard selective sweeps. A recent paper (Harris et al., 2018, PLOS Genetics) proposed an alternative interpretation: Diversity maintenance following drug resistance evolution in response to poor therapies may have been driven by recombination during slow, hard selective sweeps of single mutations. Then, if better drugs have led to faster hard selective sweeps of resistance, recombination will have less time to rescue diversity during the sweep, recapitulating the decrease in post-sweep diversity as drugs have improved. In this paper, we use time series data to show that drug resistance evolution during ineffective treatment is very fast, providing new evidence that soft sweeps drove early HIV treatment failure.     

Aggressive Chemotherapy and the Selection of Drug Resistant Pathogens

Drug resistant pathogens are one of the key public health challenges of the 21^st century. There is a widespread belief that resistance is best managed by using drugs to rapidly eliminate target pathogens from patients so as to minimize the probability that pathogens acquire resistance de novo. Yet strong drug pressure imposes intense selection in favor of resistance through alleviation of competition with wild-type populations. Aggressive chemotherapy thus generates opposing evolutionary forces which together determine the rate of drug resistance emergence. Identifying treatment regimens which best retard resistance evolution while maximizing health gains and minimizing disease transmission requires empirical analysis of resistance evolution in vivo in conjunction with measures of clinical outcomes and infectiousness. Using rodent malaria in laboratory mice, we found that less aggressive chemotherapeutic regimens substantially reduced the probability of onward transmission of resistance (by >150-fold), without compromising health outcomes. Our experiments suggest that there may be cases where resistance evolution can be managed more effectively with treatment regimens other than those which reduce pathogen burdens as fast as possible.     

Dynamics of genomic change during evolutionary rescue in the seed beetle Callosobruchus maculatus

Rapid adaptation can prevent extinction when populations are exposed to extremely marginal or stressful environments. Factors that affect the likelihood of evolutionary rescue from extinction have been identified, but much less is known about the evolutionary dynamics (e.g., rates and patterns of allele frequency change) and genomic basis of successful rescue, particularly in multicellular organisms. We conducted an evolve‐and‐resequence experiment to investigate the dynamics of evolutionary rescue at the genetic level in the cowpea seed beetle, Callosobruchus maculatus, when it is experimentally shifted to a stressful host plant, lentil. Low survival (~1%) at the onset of the experiment caused population decline. But adaptive evolution quickly rescued the population, with survival rates climbing to 69% by the F5 generation and 90% by the F10 generation. Population genomic data showed that rescue likely was caused by rapid evolutionary change at multiple loci, with many alleles fixing or nearly fixing within five generations of selection on lentil. Selection on these loci was only moderately consistent in time, but parallel evolutionary changes were evident in sublines formed after the lentil line had passed through a bottleneck. By comparing estimates of selection and genomic change on lentil across five independent C. maculatus lines (the new lentil‐adapted line, three long‐established lines and one case of failed evolutionary rescue), we found that adaptation on lentil occurred via somewhat idiosyncratic evolutionary changes. Overall, our results suggest that evolutionary rescue in this system can be caused by very strong selection on multiple loci driving rapid and pronounced genomic change.     

Compatibility of Evolutionary Responses to Constituent Antibiotics Drive Resistance Evolution to Drug Pairs

Antibiotic combinations are considered a relevant strategy to tackle the global antibiotic resistance crisis since they are believed to increase treatment efficacy and reduce resistance evolution (WHO treatment guidelines for drug-resistant tuberculosis: 2016 update.). However, studies of the evolution of bacterial resistance to combination therapy have focused on a limited number of drugs and have provided contradictory results (Lipsitch, Levin BR. 1997; Hegreness et al. 2008; Munck et al. 2014). To address this gap in our understanding, we performed a large-scale laboratory evolution experiment, adapting eight replicate lineages of Escherichia coli to a diverse set of 22 different antibiotics and 33 antibiotic pairs. We found that combination therapy significantly limits the evolution of de novode novo resistance in E. coli, yet different drug combinations vary substantially in their propensity to select for resistance. In contrast to current theories, the phenotypic features of drug pairs are weak predictors of resistance evolution. Instead, the resistance evolution is driven by the relationship between the evolutionary trajectories that lead to resistance to a drug combination and those that lead to resistance to the component drugs. Drug combinations requiring a novel genetic response from target bacteria compared with the individual component drugs significantly reduce resistance evolution. These data support combination therapy as a treatment option to decelerate resistance evolution and provide a novel framework for selecting optimized drug combinations based on bacterial evolutionary responses.     

Evolution of resistance to anti-cancer therapy during general dosing schedules

Anti-cancer drugs targeted to specific oncogenic pathways have shown promising therapeutic results in the past few years; however, drug resistance remains an important obstacle for these therapies. Resistance to these drugs can emerge due to a variety of reasons including genetic or epigenetic changes which alter the binding site of the drug target, cellular metabolism or export mechanisms. Obtaining a better understanding of the evolution of resistant populations during therapy may enable the design of more effective therapeutic regimens which prevent or delay progression of disease due to resistance. In this paper, we use stochastic mathematical models to study the evolutionary dynamics of resistance under time-varying dosing schedules and pharmacokinetic effects. The populations of sensitive and resistant cells are modeled as multi-type non-homogeneous birth-death processes in which the drug concentration affects the birth and death rates of both the sensitive and resistant cell populations in continuous time. This flexible model allows us to consider the effects of generalized treatment strategies as well as detailed pharmacokinetic phenomena such as drug elimination and accumulation over multiple doses. We develop estimates for the probability of developing resistance and moments of the size of the resistant cell population. With these estimates, we optimize treatment schedules over a subspace of tolerated schedules to minimize the risk of disease progression due to resistance as well as locate ideal schedules for controlling the population size of resistant clones in situations where resistance is inevitable. Our methodology can be used to describe dynamics of resistance arising due to a single (epi)genetic alteration in any tumor type.     

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.     

PLASMIDS AND EVOLUTIONARY RESCUE BY DRUG RESISTANCE

Antibiotic resistance provides evolutionary rescue for bacterial populations under the threat of extinction through antibiotics. It can arise de novo through mutation in the population, or be obtained from other bacterial populations via the transfer of a resistance‐conferring plasmid. We use stochastic modeling methods to establish whether the most likely source of rescue is via a plasmid or via the chromosome, and show that contrary to what is assumed plasmids are not necessarily beneficial locations for resistance genes. Competition at the plasmid level of selection is of great importance—the spread of a resistant plasmid in the population can be slowed or entirely stopped by a nonresistant version of the same plasmid. We suggest that future studies on antibiotic‐resistant plasmids should explicitly consider competition at this level of selection.     

Refugia and the evolutionary epidemiology of drug resistance

Drug resistance is a long-standing economic, veterinary and human health concern in human and animal populations. Efficacy of prophylactic drug treatments targeting a particular pathogen is often short-lived, as drug-resistant pathogens evolve and reach high frequency in a treated population. Methods to combat drug resistance are usually costly, including use of multiple drugs that are applied jointly or sequentially, or development of novel classes of drugs. Alternatively, there is growing interest in exploiting untreated host populations, refugia, for the management of drug resistance. Refugia do not experience selection for resistance, and serve as a reservoir for native, drug-susceptible pathogens. The force of infection from refugia may dilute the frequency of resistant pathogens in the treated population, potentially at an acceptable cost in terms of overall disease burden. We examine this concept using a simple mathematical model that captures the core mechanisms of transmission and selection common to many host–pathogen systems. We identify the roles of selection and gene flow in determining the utility of refugia.     

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.     

Bacteria primed by antimicrobial peptides develop tolerance and persist

Antimicrobial peptides (AMPs) are key components of innate immune defenses. Because of the antibiotic crisis, AMPs have also come into focus as new drugs. Here, we explore whether prior exposure to sub-lethal doses of AMPs increases bacterial survival and abets the evolution of resistance. We show that Escherichia coli primed by sub-lethal doses of AMPs develop tolerance and increase persistence by producing curli or colanic acid, responses linked to biofilm formation. We develop a population dynamic model that predicts that priming delays the clearance of infections and fuels the evolution of resistance. The effects we describe should apply to many AMPs and other drugs that target the cell surface. The optimal strategy to tackle tolerant or persistent cells requires high concentrations of AMPs and fast and long-lasting expression. Our findings also offer a new understanding of non-inherited drug resistance as an adaptive response and could lead to measures that slow the evolution of resistance.     

Evolutionary rescue in randomly mating,selfing, and clonal populations

Severe environmental change can drive a population extinct unless the population adapts in time to the new conditions (“evolutionary rescue”). How does biparental sexual reproduction influence the chances of population persistence compared to clonal reproduction or selfing? In this article, we set up a one‐locus two‐allele model for adaptation in diploid species, where rescue is contingent on the establishment of the mutant homozygote. Reproduction can occur by random mating, selfing, or clonally. Random mating generates and destroys the rescue mutant; selfing is efficient at generating it but at the same time depletes the heterozygote, which can lead to a low mutant frequency in the standing genetic variation. Due to these (and other) antagonistic effects, we find a nontrivial dependence of population survival on the rate of sex/selfing, which is strongly influenced by the dominance coefficient of the mutation before and after the environmental change. Importantly, since mating with the wild‐type breaks the mutant homozygote up, a slow decay of the wild‐type population size can impede rescue in randomly mating populations.     

Evolutionary rescue beyond the models

Laboratory model systems and mathematical models have shed considerable light on the fundamental properties and processes of evolutionary rescue. But it remains to determine the extent to which these model-based findings can help biologists predict when evolution will fail or succeed in rescuing natural populations that are facing novel conditions that threaten their persistence. In this article, we present a prospectus for transferring our basic understanding of evolutionary rescue to wild and other non-laboratory populations. Current experimental and theoretical results emphasize how the interplay between inheritance processes and absolute fitness in changed environments drive population dynamics and determine prospects of extinction. We discuss the challenge of inferring these elements of the evolutionary rescue process in field and natural settings. Addressing this challenge will contribute to a more comprehensive understanding of population persistence that combines processes of evolutionary rescue with developmental and ecological mechanisms.     

Bacterial recombination promotes the evolution of multi-drug-resistance in functionally diverse populations

Bacterial recombination is believed to be a major factor explaining the prevalence of multi-drug-resistance (MDR) among pathogenic bacteria. Despite extensive evidence for exchange of resistance genes from retrospective sequence analyses, experimental evidence for the evolutionary benefits of bacterial recombination is scarce. We compared the evolution of MDR between populations of Acinetobacter baylyi in which we manipulated both the recombination rate and the initial diversity of strains with resistance to single drugs. In populations lacking recombination, the initial presence of multiple strains resistant to different antibiotics inhibits the evolution of MDR. However, in populations with recombination, the inhibitory effect of standing diversity is alleviated and MDR evolves rapidly. Moreover, only the presence of DNA harbouring resistance genes promotes the evolution of resistance, ruling out other proposed benefits for recombination. Together, these results provide direct evidence for the fitness benefits of bacterial recombination and show that this occurs by mitigation of functional interference between genotypes resistant to single antibiotics. Although analogous to previously described mechanisms of clonal interference among alternative beneficial mutations, our results actually highlight a different mechanism by which interactions among co-occurring strains determine the benefits of recombination for bacterial evolution.     

A theoretical examination of the relative importance of evolution management and drug development for managing resistance

Drug resistance is a serious public health problem that threatens to thwart our ability to treat many infectious diseases. Repeatedly, the introduction of new drugs has been followed by the evolution of resistance. In principle, there are two complementary ways to address this problem: (i) enhancing drug development and (ii) slowing the evolution of drug resistance through evolutionary management. Although these two strategies are not mutually exclusive, it is nevertheless worthwhile considering whether one might be inherently more effective than the other. We present a simple mathematical model that explores how interventions aimed at these two approaches affect the availability of effective drugs. Our results identify an interesting feature of evolution management that, all else equal, tends to make it more effective than enhancing drug development. Thus, although enhancing drug development will necessarily be a central part of addressing the problem of resistance, our results lend support to the idea that evolution management is probably a very significant component of the solution as well.     

Antagonistic coevolution limits population persistence of a virus in a thermally deteriorating environment

Understanding the conditions under which rapid evolutionary adaptation can prevent population extinction in deteriorating environments (i.e. evolutionary rescue) is a crucial aim in the face of global climate change. Despite a rapidly growing body of work in this area, little attention has been paid to the importance of interspecific coevolutionary interactions. Antagonistic coevolution commonly observed between hosts and parasites is likely to retard evolutionary rescue because it often reduces population sizes, and results in the evolution of costly host defence and parasite counter-defence. We used experimental populations of a bacterium Pseudomonas fluorescens SBW25 and a bacteriophage virus (SBW25Φ2), to study how host-parasite coevolution impacts viral population persistence in the face of gradually increasing temperature, an environmental stress for the virus but not the bacterium. The virus persisted much longer when it evolved in the presence of an evolutionarily constant host genotype (i.e. in the absence of coevolution) than when the bacterium and virus coevolved. Further experiments suggest that both a reduction in population size and costly infectivity strategies contributed to viral extinction as a result of coevolution. The results highlight the importance of interspecific evolutionary interactions for the evolutionary responses of populations to global climate change.     

细菌药物耐受

细菌药物耐受(Drug tolerance)是指在没有发生耐药突变的情况下细菌耐受抗生素杀菌的能力,表现为细菌群体难以或不能被杀菌型药物清除。细菌药物耐受的调控机制包括群体异质性和压力应答两种途径。药物耐受性的本质是细菌通过调控或遗传突变的方式改变生理代谢状态,从而抵制药物引起的细胞死亡途径。比如,处于缓慢生长或生长停滞生理状态的细菌往往能够抵抗药物的杀菌作用。临床研究发现细菌药物耐受是导致持续性感染疾病迁延难愈、复发率高的病原学机制之一。同时,研究证明耐受性的形成是细菌耐药性(Drug resistance)产生的进化途径之一。因此,揭示细菌药物耐受的机制将有助于人们深入了解抗生素的杀菌机理,以及细菌耐药性形成的适应性进化机制,并为新型杀菌药物以及药物增效剂靶标的发现和抗生素合理使用策略的开发奠定理论基础。     

Evolution and maintenance of haploid–diploid life cycles in natural populations: The case of the marine brown alga Ectocarpus

The evolutionary stability of haploid–diploid life cycles is still controversial. Mathematical models indicate that niche differences between ploidy phases may be a necessary condition for the evolution and maintenance of these life cycles. Nevertheless, experimental support for this prediction remains elusive. In the present work, we explored this hypothesis in natural populations of the brown alga Ectocarpus. Consistent with the life cycle described in culture, Ectocarpus crouaniorum in NW France and E. siliculosus in SW Italy exhibited an alternation between haploid gametophytes and diploid sporophytes. Our field data invalidated, however, the long‐standing view of an isomorphic alternation of generations. Gametophytes and sporophytes displayed marked differences in size and, conforming to theoretical predictions, occupied different spatiotemporal niches. Gametophytes were found almost exclusively on the alga Scytosiphon lomentaria during spring whereas sporophytes were present year‐round on abiotic substrata. Paradoxically, E. siliculosus in NW France exhibited similar habitat usage despite the absence of alternation of ploidy phases. Diploid sporophytes grew both epilithically and epiphytically, and this mainly asexual population gained the same ecological advantage postulated for haploid–diploid populations. Consequently, an ecological interpretation of the niche differences between haploid and diploid individuals does not seem to satisfactorily explain the evolution of the Ectocarpus life cycle.