Conflicting selection alters the trajectory of molecular evolution in a tripartite bacteria–plasmid–phage interaction

Bacteria engage in a complex network of ecological interactions, which includes mobile genetic elements (MGEs) such as phages and plasmids. These elements play a key role in microbial communities as vectors of horizontal gene transfer but can also be important sources of selection for their bacterial hosts. In natural communities, bacteria are likely to encounter multiple MGEs simultaneously and conflicting selection among MGEs could alter the bacterial evolutionary response to each MGE. Here, we test the effect of interactions with multiple MGEs on bacterial molecular evolution in the tripartite interaction between the bacterium, Pseudomonas fluorescens, the lytic bacteriophage, SBW25φ2, and conjugative plasmid, pQBR103, using genome sequencing of experimentally evolved bacteria. We show that individually, both plasmids and phages impose selection leading to bacterial evolutionary responses that are distinct from bacterial populations evolving without MGEs, but that together, plasmids and phages impose conflicting selection on bacteria, constraining the evolutionary responses observed in pairwise interactions. Our findings highlight the likely difficulties of predicting evolutionary responses to multiple selective pressures from the observed evolutionary responses to each selective pressure alone. Understanding evolution in complex microbial communities comprising many species and MGEs will require that we go beyond studies of pairwise interactions.     

Genome Analysis of a Transmissible Lineage of Pseudomonas aeruginosa Reveals Pathoadaptive Mutations and Distinct Evolutionary Paths of Hypermutators

Genome sequencing of bacterial pathogens has advanced our understanding of their evolution, epidemiology, and response to antibiotic therapy. However, we still have only a limited knowledge of the molecular changes in in vivo evolving bacterial populations in relation to long-term, chronic infections. For example, it remains unclear what genes are mutated to facilitate the establishment of long-term existence in the human host environment, and in which way acquisition of a hypermutator phenotype with enhanced rates of spontaneous mutations influences the evolutionary trajectory of the pathogen. Here we perform a retrospective study of the DK2 clone type of P. aeruginosa isolated from Danish patients suffering from cystic fibrosis (CF), and analyze the genomes of 55 bacterial isolates collected from 21 infected individuals over 38 years. Our phylogenetic analysis of 8,530 mutations in the DK2 genomes shows that the ancestral DK2 clone type spread among CF patients through several independent transmission events. Subsequent to transmission, sub-lineages evolved independently for years in separate hosts, creating a unique possibility to study parallel evolution and identification of genes targeted by mutations to optimize pathogen fitness (pathoadaptive mutations). These genes were related to antibiotic resistance, the cell envelope, or regulatory functions, and we find that the prevalence of pathoadaptive mutations correlates with evolutionary success of co-evolving sub-lineages.The long-term co-existence of both normal and hypermutator populations enabled comparative investigations of the mutation dynamics in homopolymeric sequences in which hypermutators are particularly prone to mutations. We find a positive exponential correlation between the length of the homopolymer and its likelihood to acquire mutations and identify two homopolymer-containing genes preferentially mutated in hypermutators. This homopolymer facilitated differential mutagenesis provides a novel genome-wide perspective on the different evolutionary trajectories of hypermutators, which may help explain their emergence in CF infections.     

Phage-resistant mutations impact bacteria susceptibility to future phage infections and antibiotic response

Bacteriophage (phage) therapy in combination with antibiotic treatment serves as a potential strategy to overcome the continued rise in antibiotic resistance across bacterial pathogens. Understanding the impacts of evolutionary and ecological processes to the phage-antibiotic-resistance dynamic could advance the development of such combinatorial therapy. We tested whether the acquisition of mutations conferring phage resistance may have antagonistically pleiotropic consequences for antibiotic resistance. First, to determine the robustness of phage resistance across different phage strains, we infected resistant Escherichia coli cultures with phage that were not previously encountered. We found that phage-resistant E. coli mutants that gained resistance to a single phage strain maintain resistance to other phages with overlapping adsorption methods. Mutations underlying the phage-resistant phenotype affects lipopolysaccharide (LPS) structure and/or synthesis. Because LPS is implicated in both phage infection and antibiotic response, we then determined whether phage-resistant trade-offs exist when challenged with different classes of antibiotics. We found that only 1 out of the 4 phage-resistant E. coli mutants yielded trade-offs between phage and antibiotic resistance. Surprisingly, when challenged with novobiocin, we uncovered evidence of synergistic pleiotropy for some mutants allowing for greater antibiotic resistance, even though antibiotic resistance was never selected for. Our results highlight the importance of understanding the role of selective pressures and pleiotropic interactions in the bacterial response to phage-antibiotic combinatorial therapy.     

Metabolic constraints on the evolution of antibiotic resistance

Despite our continuous improvement in understanding antibiotic resistance, the interplay between natural selection of resistance mutations and the environment remains unclear. To investigate the role of bacterial metabolism in constraining the evolution of antibiotic resistance, we evolved Escherichia coli growing on glycolytic or gluconeogenic carbon sources to the selective pressure of three different antibiotics. Profiling more than 500 intracellular and extracellular putative metabolites in 190 evolved populations revealed that carbon and energy metabolism strongly constrained the evolutionary trajectories, both in terms of speed and mode of resistance acquisition. To interpret and explore the space of metabolome changes, we developed a novel constraint‐based modeling approach using the concept of shadow prices. This analysis, together with genome resequencing of resistant populations, identified condition‐dependent compensatory mechanisms of antibiotic resistance, such as the shift from respiratory to fermentative metabolism of glucose upon overexpression of efflux pumps. Moreover, metabolome‐based predictions revealed emerging weaknesses in resistant strains, such as the hypersensitivity to fosfomycin of ampicillin‐resistant strains. Overall, resolving metabolic adaptation throughout antibiotic‐driven evolutionary trajectories opens new perspectives in the fight against emerging antibiotic resistance.     

Persistence and resistance as complementary bacterial adaptations to antibiotics

Bacterial persistence represents a simple of phenotypic heterogeneity, whereby a proportion of cells in an isogenic bacterial population can survive exposure to lethal stresses such as antibiotics. In contrast, genetically based antibiotic resistance allows for continued growth in the presence of antibiotics. It is unclear, however, whether resistance and persistence are complementary or alternative evolutionary adaptations to antibiotics. Here, we investigate the co‐evolution of resistance and persistence across the genus Pseudomonas using comparative methods that correct for phylogenetic nonindependence. We find that strains of Pseudomonas vary extensively in both their intrinsic resistance to antibiotics (ciprofloxacin and rifampicin) and persistence following exposure to these antibiotics. Crucially, we find that persistence correlates positively to antibiotic resistance across strains. However, we find that different genes control resistance and persistence implying that they are independent traits. Specifically, we find that the number of type II toxin–antitoxin systems (TAs) in the genome of a strain is correlated to persistence, but not resistance. Our study shows that persistence and antibiotic resistance are complementary, but independent, evolutionary adaptations to stress and it highlights the key role played by TAs in the evolution of persistence.     

Acinetobacter baumannii Repeatedly Evolves a Hypermutator Phenotype in Response to Tigecycline That Effectively Surveys Evolutionary Trajectories to Resistance

The evolution of hypermutators in response to antibiotic treatment in both clinical and laboratory settings provides a unique context for the study of adaptive evolution. With increased mutation rates, the number of hitchhiker mutations within an evolving hypermutator population is remarkably high and presents substantial challenges in determining which mutations are adaptive. Intriguingly however, hypermutators also provide an opportunity to explore deeply the accessible evolutionary trajectories that lead to increased organism fitness, in this case the evolution of antibiotic resistance to the clinically relevant antibiotic tigecycline by the hospital pathogen Acinetobacter baumannii. Using a continuous culture system, AB210M, a clinically derived strain of A. baumannii, was evolved to tigecycline resistance. Analysis of the adapted populations showed that nearly all the successful lineages became hypermutators via movement of a mobile element to inactivate mutS. In addition, metagenomic analysis of population samples revealed another 896 mutations that occurred at a frequency greater than 5% in the population, while 38 phenotypically distinct individual colonies harbored a total of 1712 mutations. These mutations were scattered throughout the genome and affected ~40% of the coding sequences. The most highly mutated gene was adeS, a known tigecycline-resistance gene; however, adeS was not solely responsible for the high level of TGC resistance. Sixteen other genes stood out as potentially relevant to increased resistance. The five most prominent candidate genes (adeS, rpsJ, rrf, msbA, and gna) consistently re-emerged in subsequent replicate population studies suggesting they are likely to play a role in adaptation to tigecycline. Interestingly, the repeated evolution of a hypermutator phenotype in response to antibiotic stress illustrates not only a highly adaptive strategy to resistance, but also a remarkably efficient survey of successful evolutionary trajectories.     

Antibiotic resistant pathogen outbreak investigation: an interdisciplinary module to teach fundamentals of evolutionary biology

The evolution of resistance to antibiotics provides a timely and relevant topic for teaching undergraduate students evolutionary biology. Here, we present a module incorporating modified sequencing data from eight antibiotic resistant pathogen outbreaks in hospital settings with bioinformatics and phylogenetic analyses. This module uses whole genome sequencing data from hospital outbreaks investigated by the Centers for Disease Control and Prevention to provide examples of antibiotic resistance spread. Students work in groups to analyze outbreak data to identify the bacterial species and antibiotic resistance genes, to infer a phylogenetic tree examining relatedness among isolates, and to determine a possible source of the outbreak. Students then compile their results in individual reports and provide recommendations for preventing the further spread of antibiotic resistant organisms. In addition to providing genomic outbreak data, we include a teaching concepts guide discussing three integral components of the module: how evolutionary biology concepts of natural selection and competition impact antibiotic resistance; outbreak investigation information to aid in phylogenetic analysis and creation of recommendations; and instructions for the bioinformatics protocol. Completion of this module provides students an opportunity to think critically about the evolution of resistance, practice bioinformatics techniques, and relate evolutionary biology to current events.     

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.     

Parting ways: parasite release in nature leads to sex‐specific evolution of defence

We evaluated the extent to which males and females evolve along similar or different trajectories in response to the same environmental shift. Specifically, we used replicate experimental introductions in nature to consider how release from a key parasite (Gyrodactylus) generates similar or different defence evolution in male vs. female guppies (Poecilia reticulata). After 4–8 generations of evolution, guppies were collected from the ancestral (parasite still present) and derived (parasite now absent) populations and bred for two generations in the laboratory to control for nongenetic effects. These F2 guppies were then individually infected with Gyrodactylus, and infection dynamics were monitored on each fish. We found that parasite release in nature led to sex‐specific evolutionary responses: males did not show much evolution of resistance, whereas females showed the evolution of increased resistance. Given that male guppies in the ancestral population had greater resistance to Gyrodactylus than did females, evolution in the derived populations led to reduction of sexual dimorphism in resistance. We argue that previous selection for high resistance in males constrained (relative to females) further evolution of the trait. We advocate more experiments considering sex‐specific evolutionary responses to environmental change.     

Metagenomic analysis reveals the prevalence and persistence of antibiotic- and heavy metal-resistance genes in wastewater treatment plant

The increased antibiotic resistance among microorganisms has resulted into growing interest for investigating the wastewater treatment plants (WWTPs) as they are reported to be the major source in the dissemination of antibiotic resistance genes (ARGs) and heavy metal resistance genes (HMRGs) in the environment. In this study, we investigated the prevalence and persistence of ARGs and HMRGs as well as bacterial diversity and mobile genetic elements (MGEs) in influent and effluent at the WWTP in Gwangju, South Korea, using high-throughput sequencing based metagenomic approach. A good number of broad-spectrum of resistance genes (both ARG and HMRG) were prevalent and likely persistent, although large portion of them were successfully removed at the wastewater treatment process. The relative abundance of ARGs and MGEs was higher in effluent as compared to that of influent. Our results suggest that the resistance genes with high abundance and bacteria harbouring ARGs and MGEs are likely to persist more through the treatment process. On analyzing the microbial community, the phylum Proteobacteria, especially potentially pathogenic species belonging to the genus Acinetobacter, dominated in WWTP. Overall, our study demonstrates that many ARGs and HMRGs may persist the treatment processes in WWTPs and their association to MGEs may contribute to the dissemination of resistance genes among microorganisms in the environment.     

Parasites and competitors suppress bacterial pathogen synergistically due to evolutionary trade‐offs

Parasites and competitors are important for regulating pathogen densities and subsequent disease dynamics. It is, however, unclear to what extent this is driven by ecological and evolutionary processes. Here, we used experimental evolution to study the eco‐evolutionary feedbacks among Ralstonia solanacearum bacterial pathogen, Ralstonia‐specific phage parasite, and Bacillus amyloliquefaciens competitor bacterium in the laboratory and plant rhizosphere. We found that while the phage had a small effect on pathogen densities on its own, it considerably increased the R. solanacearum sensitivity to antibiotics produced by B. amyloliquefaciens. Instead of density effects, this synergy was due to phage‐driven increase in phage resistance that led to trade‐off with the resistance to B. amyloliquefaciens antibiotics. While no evidence was found for pathogen resistance evolution to B. amyloliquefaciens antibiotics, the fitness cost of adaptation (reduced growth) was highest when the pathogen had evolved in the presence of both parasite and competitor. Qualitatively similar patterns were found between laboratory and greenhouse experiments even though the evolution of phage resistance was considerably attenuated in the tomato rhizosphere. These results suggest that evolutionary trade‐offs can impose strong constraints on disease dynamics and that combining phages and antibiotic‐producing bacteria could be an efficient way to control agricultural pathogens.     

Prediction of Antibiotic Resistance Evolution by Growth Measurement of All Proximal Mutants of Beta-Lactamase

The antibiotic resistance crisis continues to threaten human health. Better predictions of the evolution of antibiotic resistance genes could contribute to the design of more sustainable treatment strategies. However, comprehensive prediction of antibiotic resistance gene evolution via laboratory approaches remains challenging. By combining site-specific integration and high-throughput sequencing, we quantified relative growth under the respective selection of cefotaxime or ceftazidime selection in ∼23,000 Escherichia coli MG1655 strains that each carried a unique, single-copy variant of the extended-spectrum β-lactamase gene bla_CTX-M-14 at the chromosomal att HK022 site. Significant synergistic pleiotropy was observed within four subgenic regions, suggesting key regions for the evolution of resistance to both antibiotics. Moreover, we propose PEAR^P and PEAR^R, two deep-learning models with strong clinical correlations, for the prospective and retrospective prediction of bla_CTX-M-14 evolution, respectively. Single to quintuple mutations of bla_CTX-M-14 predicted to confer resistance by PEAR^P were significantly enriched among the clinical isolates harboring bla_CTX-M-14 variants, and the PEAR^R scores matched the minimal inhibitory concentrations obtained for the 31 intermediates in all hypothetical trajectories. Altogether, we conclude that the measurement of local fitness landscape enables prediction of the evolutionary trajectories of antibiotic resistance genes, which could be useful for a broad range of clinical applications, from resistance prediction to designing novel treatment strategies.     

The emergence of the multi-species NIP1 effector in Rhynchosporium was accompanied by high rates of gene duplications and losses

Plant pathogens secrete effector proteins to manipulate the host and facilitate infection. Cognate hosts trigger strong defence responses upon detection of these effectors. Consequently, pathogens and hosts undergo rapid coevolutionary arms races driven by adaptive evolution of effectors and receptors. Because of their high rate of turnover, most effectors are thought to be species-specific and the evolutionary trajectories are poorly understood. Here, we investigate the necrosis-inducing protein 1 (NIP1) effector in the multihost pathogen genus Rhynchosporium. We retraced the evolutionary history of the NIP1 locus using whole-genome assemblies of 146 strains covering four closely related species. NIP1 orthologues were present in all species but the locus consistently segregated presence–absence polymorphisms suggesting long-term balancing selection. We also identified previously unknown paralogues of NIP1 that were shared among multiple species and showed substantial copy-number variation within R. commune. The NIP1A paralogue was under significant positive selection suggesting that NIP1A is the dominant effector variant coevolving with host immune receptors. Consistent with this prediction, we found that copy number variation at NIP1A had a stronger effect on virulence than NIP1B. Our analyses unravelled the origins and diversification mechanisms of a pathogen effector family shedding light on how pathogens gain adaptive genetic variation.     

Ecology and evolution of antimicrobial resistance in bacterial communities

Accumulating evidence suggests that the response of bacteria to antibiotics is significantly affected by the presence of other interacting microbes. These interactions are not typically accounted for when determining pathogen sensitivity to antibiotics. In this perspective, we argue that resistance and evolutionary responses to antibiotic treatments should not be considered only a trait of an individual bacteria species but also an emergent property of the microbial community in which pathogens are embedded. We outline how interspecies interactions can affect the responses of individual species and communities to antibiotic treatment, and how these responses could affect the strength of selection, potentially changing the trajectory of resistance evolution. Finally, we identify key areas of future research which will allow for a more complete understanding of antibiotic resistance in bacterial communities. We emphasise that acknowledging the ecological context, i.e. the interactions that occur between pathogens and within communities, could help the development of more efficient and effective antibiotic treatments.Subject terms: Microbial ecology, Antibiotics, Bacterial evolution     

Mobile Genetic Element-Encoded Cytolysin Connects Virulence to Methicillin Resistance in MRSA

Bacterial virulence and antibiotic resistance have a significant influence on disease severity and treatment options during bacterial infections. Frequently, the underlying genetic determinants are encoded on mobile genetic elements (MGEs). In the leading human pathogen Staphylococcus aureus, MGEs that contain antibiotic resistance genes commonly do not contain genes for virulence determinants. The phenol-soluble modulins (PSMs) are staphylococcal cytolytic toxins with a crucial role in immune evasion. While all known PSMs are core genome-encoded, we here describe a previously unidentified psm gene, psm-mec, within the staphylococcal methicillin resistance-encoding MGE SCCmec. PSM-mec was strongly expressed in many strains and showed the physico-chemical, pro-inflammatory, and cytolytic characteristics typical of PSMs. Notably, in an S. aureus strain with low production of core genome-encoded PSMs, expression of PSM-mec had a significant impact on immune evasion and disease. In addition to providing high-level resistance to methicillin, acquisition of SCCmec elements encoding PSM-mec by horizontal gene transfer may therefore contribute to staphylococcal virulence by substituting for the lack of expression of core genome-encoded PSMs. Thus, our study reveals a previously unknown role of methicillin resistance clusters in staphylococcal pathogenesis and shows that important virulence and antibiotic resistance determinants may be combined in staphylococcal MGEs.     

Bacterial defenses against a natural antibiotic promote collateral resilience to clinical antibiotics

Bacterial opportunistic human pathogens frequently exhibit intrinsic antibiotic tolerance and resistance, resulting in infections that can be nearly impossible to eradicate. We asked whether this recalcitrance could be driven by these organisms’ evolutionary history as environmental microbes that engage in chemical warfare. Using Pseudomonas aeruginosa as a model, we demonstrate that the self-produced antibiotic pyocyanin (PYO) activates defenses that confer collateral tolerance specifically to structurally similar synthetic clinical antibiotics. Non-PYO-producing opportunistic pathogens, such as members of the Burkholderia cepacia complex, likewise display elevated antibiotic tolerance when cocultured with PYO-producing strains. Furthermore, by widening the population bottleneck that occurs during antibiotic selection and promoting the establishment of a more diverse range of mutant lineages, PYO increases apparent rates of mutation to antibiotic resistance to a degree that can rival clinically relevant hypermutator strains. Together, these results reveal an overlooked mechanism by which opportunistic pathogens that produce natural toxins can dramatically modulate the efficacy of clinical antibiotics and the evolution of antibiotic resistance, both for themselves and other members of clinically relevant polymicrobial communities.

This study shows that pyocyanin, a toxin secreted by the opportunistic pathogen Pseudomonas aeruginosa, induces defense responses that decrease the efficacy of structurally-similar clinical antibiotics and accelerate the evolution of antibiotic resistance, both in the producer and in other members of clinically-relevant polymicrobial communities.     

Mobile elements create strain-level variation in the services conferred by an aphid symbiont

Heritable, facultative symbionts are common in arthropods, often functioning in host defence. Despite moderately reduced genomes, facultative symbionts retain evolutionary potential through mobile genetic elements (MGEs). MGEs form the primary basis of strain-level variation in genome content and architecture, and often correlate with variability in symbiont-mediated phenotypes. In pea aphids (Acyrthosiphon pisum), strain-level variation in the type of toxin-encoding bacteriophages (APSEs) carried by the bacterium Hamiltonella defensa correlates with strength of defence against parasitoids. However, co-inheritance creates difficulties for partitioning their relative contributions to aphid defence. Here we identified isolates of H. defensa that were nearly identical except for APSE type. When holding H. defensa genotype constant, protection levels corresponded to APSE virulence module type. Results further indicated that APSEs move repeatedly within some H. defensa clades providing a mechanism for rapid evolution in anti-parasitoid defences. Strain variation in H. defensa also correlates with the presence of a second symbiont Fukatsuia symbiotica. Predictions that nutritional interactions structured this coinfection were not supported by comparative genomics, but bacteriocin-containing plasmids unique to co-infecting strains may contribute to their common pairing. In conclusion, strain diversity, and joint capacities for horizontal transfer of MGEs and symbionts, are emergent players in the rapid evolution of arthropods.     

The ESKAPE mobilome contributes to the spread of antimicrobial resistance and CRISPR-mediated conflict between mobile genetic elements

Mobile genetic elements (MGEs) mediate the shuffling of genes among organisms. They contribute to the spread of virulence and antibiotic resistance (AMR) genes in human pathogens, such as the particularly problematic group of ESKAPE pathogens. Here, we performed the first systematic analysis of MGEs, including plasmids, prophages, and integrative and conjugative/mobilizable elements (ICEs/IMEs), across all ESKAPE pathogens. We found that different MGE types are asymmetrically distributed across these pathogens, and that most horizontal gene transfer (HGT) events are restricted by phylum or genus. We show that the MGEs proteome is involved in diverse functional processes and distinguish widespread proteins within the ESKAPE context. Moreover, anti-CRISPRs and AMR genes are overrepresented in the ESKAPE mobilome. Our results also underscore species-specific trends shaping the number of MGEs, AMR, and virulence genes across pairs of conspecific ESKAPE genomes with and without CRISPR-Cas systems. Finally, we observed that CRISPR spacers found on prophages, ICEs/IMEs, and plasmids have different targeting biases: while plasmid and prophage CRISPRs almost exclusively target other plasmids and prophages, respectively, ICEs/IMEs CRISPRs preferentially target prophages. Overall, our study highlights the general importance of the ESKAPE mobilome in contributing to the spread of AMR and mediating conflict among MGEs.     

EXPERIMENTAL EVIDENCE FOR THE EVOLUTION OF INDIRECT GENETIC EFFECTS: CHANGES IN THE INTERACTION EFFECT COEFFICIENT,PSI (Ψ), DUE TO SEXUAL SELECTION

Indirect genetics effects (IGEs)—when the genotype of one individual affects the phenotypic expression of a trait in another—may alter evolutionary trajectories beyond that predicted by standard quantitative genetic theory as a consequence of genotypic evolution of the social environment. For IGEs to occur, the trait of interest must respond to one or more indicator traits in interacting conspecifics. In quantitative genetic models of IGEs, these responses (reaction norms) are termed interaction effect coefficients and are represented by the parameter psi (Ψ). The extent to which Ψ exhibits genetic variation within a population, and may therefore itself evolve, is unknown. Using an experimental evolution approach, we provide evidence for a genetic basis to the phenotypic response caused by IGEs on sexual display traits in Drosophila serrata. We show that evolution of the response is affected by sexual but not natural selection when flies adapt to a novel environment. Our results indicate a further mechanism by which IGEs can alter evolutionary trajectories—the evolution of interaction effects themselves.     

Adaptation of Drosophila to a novel laboratory environment reveals temporally heterogeneous trajectories of selected alleles

The genomic basis of adaptation to novel environments is a fundamental problem in evolutionary biology that has gained additional importance in the light of the recent global change discussion. Here, we combined laboratory natural selection (experimental evolution) in Drosophila melanogaster with genome‐wide next generation sequencing of DNA pools (Pool‐Seq) to identify alleles that are favourable in a novel laboratory environment and traced their trajectories during the adaptive process. Already after 15 generations, we identified a pronounced genomic response to selection, with almost 5000 single nucleotide polymorphisms (SNP; genome‐wide false discovery rates < 0.005%) deviating from neutral expectation. Importantly, the evolutionary trajectories of the selected alleles were heterogeneous, with the alleles falling into two distinct classes: (i) alleles that continuously rise in frequency; and (ii) alleles that at first increase rapidly but whose frequencies then reach a plateau. Our data thus suggest that the genomic response to selection can involve a large number of selected SNPs that show unexpectedly complex evolutionary trajectories, possibly due to nonadditive effects.