Demographic fluctuations and selection during host-parasite co-evolution interactively increase genetic diversity

Host-parasite interactions can cause strong demographic fluctuations accompanied by selective sweeps of resistance/infectivity alleles. Both demographic bottlenecks and frequent sweeps are expected to reduce the amount of segregating genetic variation and therefore might constrain adaptation during co-evolution. Recent studies, however, suggest that the interaction of demographic and selective processes is a key component of co-evolutionary dynamics and may rather positively affect levels of genetic diversity available for adaptation. Here, we provide direct experimental testing of this hypothesis by disentangling the effects of demography, selection and their interaction in an experimental host-parasite system. We grew 12 populations of a unicellular, asexually reproducing algae (Chlorella variabilis) that experienced either growth followed by constant population sizes (three populations), demographic fluctuations (three populations), selection induced by exposure to a virus (three populations), or demographic fluctuations together with virus-induced selection (three populations). After 50 days (~50 generations), we conducted whole-genome sequencing of each algal host population. We observed more genetic diversity in populations that jointly experienced selection and demographic fluctuations than in populations where these processes were experimentally separated. In addition, in those three populations that jointly experienced selection and demographic fluctuations, experimentally measured diversity exceeds expected values of diversity that account for the cultures' population sizes. Our results suggest that eco-evolutionary feedbacks can positively affect genetic diversity and provide the necessary empirical measures to guide further improvements of theoretical models of adaptation during host-parasite co-evolution.

Evolution of exploitation and replication of giant viruses and virophages

Tripartite biotic interactions are inherently complex, and the strong interdependence of species and often one-sided exploitation can make these systems vulnerable to extinction. The persistence of species depends then on the balance between exploitation and avoidance of exploitation beyond the point where sustainable resource use is no longer possible. We used this general prediction to test the potential role of trait evolution for persistence in a tripartite microbial system consisting of a marine heterotrophic flagellate preyed upon by a giant virus, which in turn is parasitized by a virophage. Host and virophage may benefit from this interaction because the virophage reduces the harmful effects of the giant virus on the host population and the virophage can persist integrated into the host genome when giant viruses are scarce. We grew hosts and virus in the presence and absence of the virophage over ∼280 host generations and tested whether levels of exploitation and replication in the giant virus and/or virophage population evolved over the course of the experiment, and whether the changes were such that they could avoid overexploitation and extinction. We found that the giant virus evolved toward lower levels of replication and the virophage evolved toward increased replication but decreased exploitation of the giant virus. These changes reduced overall host exploitation by the virus and virus exploitation by the virophage and are predicted to facilitate persistence.

Cell-to-cell heterogeneity drives host-virus coexistence in a bloom-forming alga

Algal blooms drive global biogeochemical cycles of key nutrients and serve as hotspots for biological interactions in the ocean. The massive blooms of the cosmopolitan coccolithophore Emiliania huxleyi are often infected by the lytic E. huxleyi virus, which is a major mortality agent triggering bloom demise. This multi-annual "boom and bust" pattern of E. huxleyi blooms suggests that coexistence is essential for these host-virus dynamics. To investigate host-virus coexistence, we developed a new model system from an E. huxleyi culture that recovered from viral infection. The recovered population coexists with the virus, as host cells continue to divide in parallel to viral production. By applying single-molecule fluorescence in situ hybridization (smFISH) to quantify the fraction of infected cells, and assessing infection-specific lipid biomarkers, we identified a small subpopulation of cells that were infected and produced new virions, whereas most of the host population could resist infection. To further assess population heterogeneity, we generated clonal strain collections using single-cell sorting and subsequently phenotyped their susceptibility to E. huxleyi virus infection. This unraveled substantial cell-to-cell heterogeneity across a continuum of susceptibility to resistance, highlighting that infection outcome may vary depending on the individual cell. These results add a new dimension to our understanding of the complexity of host-virus interactions that are commonly assessed in bulk and described by binary definitions of resistance or susceptibility. We propose that phenotypic heterogeneity drives the host-virus coexistence and demonstrate how the coexistence with a lytic virus provides an ecological advantage for the host by killing competing strains.

Efficient assays to quantify the life history traits of algal viruses

IMPORTANCE

Viruses play a crucial role in microbial ecosystems by liberating nutrients and regulating the growth of their hosts. These effects are governed by viral life history traits, i.e., by the traits determining viral reproduction and survival. Understanding these traits is essential to predicting viral effects, but measuring them is generally labor intensive. In this study, we present efficient methods to quantify the full life cycle of lytic viruses. We developed these methods for viruses infecting unicellular Chlorella algae but expect them to be applicable to other lytic viruses that can be quantified by flow cytometry. By making viral phenotypes accessible, our methods will support research into the diversity and ecological effects of microbial viruses.

Active viral infection during blooms of a dinoflagellate indicates dinoflagellate-viral co-adaptation

IMPORTANCE

This study represents the first that investigates in situ virus infection in dinoflagellate blooms. Our findings reveal highly similar viral assemblages that infected the bloom species Prorocentrum shikokuense and a co-adapted metabolic relationship between the host and the viruses in the blooms, which varied between the prolonged and the short-lived blooms of the same dinoflagellate species. These findings fill the gap in knowledge regarding the identity and behavior of viruses in a dinoflagellate bloom and shed light on what appears to be the complex mode of infection. The novel insight will be potentially valuable for fully understanding and modeling the role of viruses in regulating blooms of dinoflagellates and other algae.

Seasonality and Strain Specificity Drive Rapid Co-evolution in an Ostreococcus-Virus System from the Western Baltic Sea

Marine viruses are a major driver of phytoplankton mortality and thereby influence biogeochemical cycling of carbon and other nutrients. Phytoplankton-targeting viruses are important components of ecosystem dynamics, but broad-scale experimental investigations of host-virus interactions remain scarce. Here, we investigated in detail a picophytoplankton (size 1 µm) host's responses to infections by species-specific viruses from distinct geographical regions and different sampling seasons. Specifically, we used Ostreococcus tauri and O. mediterraneus and their viruses (size ca. 100 nm). Ostreococcus sp. is globally distributed and, like other picoplankton species, play an important role in coastal ecosystems at certain times of the year. Further, Ostreococcus sp. is a model organism, and the Ostreococcus-virus system is well-known in marine biology. However, only few studies have researched its evolutionary biology and the implications thereof for ecosystem dynamics. The Ostreococcus strains used here stem from different regions of the Southwestern Baltic Sea that vary in salinity and temperature and were obtained during several cruises spanning different sampling seasons. Using an experimental cross-infection set-up, we explicitly confirm species and strain specificity in Ostreococcus sp. from the Baltic Sea. Moreover, we found that the timing of virus-host co-existence was a driver of infection patterns as well. In combination, these findings prove that host-virus co-evolution can be rapid in natural systems.

Host-pathogen coevolution promotes the evolution of general, broad-spectrum resistance and reduces foreign pathogen spillover risk

Genetic variation for disease resistance within host populations can strongly impact the spread of endemic pathogens. In plants, recent work has shown that within-population variation in resistance can also affect the transmission of foreign spillover pathogens if that resistance is general. However, most hosts also possess specific resistance mechanisms that provide strong defenses against coevolved endemic pathogens. Here we use a modeling approach to ask how antagonistic coevolution between hosts and their endemic pathogen at the specific resistance locus can affect the frequency of general resistance, and therefore a host's vulnerability to foreign pathogens. We develop a two-locus model with variable recombination that incorporates both general (resistance to all pathogens) and specific (resistance to endemic pathogens only). We find that introducing coevolution into our model greatly expands the regions where general resistance can evolve, decreasing the risk of foreign pathogen invasion. Furthermore, coevolution greatly expands which conditions maintain polymorphisms at both resistance loci, thereby driving greater genetic diversity within host populations. This genetic diversity often leads to positive correlations between host resistance to foreign and endemic pathogens, similar to those observed in natural populations. However, if resistance loci become linked, the resistance correlations can shift to negative. If we include a third, linkage modifying locus into our model, we find that selection often favors complete linkage. Our model demonstrates how coevolutionary dynamics with an endemic pathogen can mold the resistance structure of host populations in ways that affect its susceptibility to foreign pathogen spillovers, and that the nature of these outcomes depends on resistance costs, as well as the degree of linkage between resistance genes.

Bacteria-phage coevolution with a seed bank

Dormancy is an adaptation to living in fluctuating environments. It allows individuals to enter a reversible state of reduced metabolic activity when challenged by unfavorable conditions. Dormancy can also influence species interactions by providing organisms with a refuge from predators and parasites. Here we test the hypothesis that, by generating a seed bank of protected individuals, dormancy can modify the patterns and processes of antagonistic coevolution. We conducted a factorially designed experiment where we passaged a bacterial host (Bacillus subtilis) and its phage (SPO1) in the presence versus absence of a seed bank consisting of dormant endospores. Owing in part to the inability of phages to attach to spores, seed banks stabilized population dynamics and resulted in minimum host densities that were 30-fold higher compared to bacteria that were unable to engage in dormancy. By supplying a refuge to phage-sensitive strains, we show that seed banks retained phenotypic diversity that was otherwise lost to selection. Dormancy also stored genetic diversity. After characterizing allelic variation with pooled population sequencing, we found that seed banks retained twice as many host genes with mutations, whether phages were present or not. Based on mutational trajectories over the course of the experiment, we demonstrate that seed banks can dampen bacteria-phage coevolution. Not only does dormancy create structure and memory that buffers populations against environmental fluctuations, it also modifies species interactions in ways that can feed back onto the eco-evolutionary dynamics of microbial communities.

Evolutionary repeatability of emergent properties of ecological communities

Most species belong to ecological communities where their interactions give rise to emergent community-level properties, such as diversity and productivity. Understanding and predicting how these properties change over time has been a major goal in ecology, with important practical implications for sustainability and human health. Less attention has been paid to the fact that community-level properties can also change because member species evolve. Yet, our ability to predict long-term eco-evolutionary dynamics hinges on how repeatably community-level properties change as a result of species evolution. Here, we review studies of evolution of both natural and experimental communities and make the case that community-level properties at least sometimes evolve repeatably. We discuss challenges faced in investigations of evolutionary repeatability. In particular, only a handful of studies enable us to quantify repeatability. We argue that quantifying repeatability at the community level is critical for approaching what we see as three major open questions in the field: (i) Is the observed degree of repeatability surprising? (ii) How is evolutionary repeatability at the community level related to repeatability at the level of traits of member species? (iii) What factors affect repeatability? We outline some theoretical and empirical approaches to addressing these questions. Advances in these directions will not only enrich our basic understanding of evolution and ecology but will also help us predict eco-evolutionary dynamics. This article is part of the theme issue 'Interdisciplinary approaches to predicting evolutionary biology'.

Context-dependent costs and benefits of endosymbiotic interactions in a ciliate-algae system

Endosymbiosis, an interaction between two species where one lives within the other, has evolved multiple times independently, but the underlying mechanisms remain unclear. Evolutionary theory suggests that for an endosymbiotic interaction to remain stable over time, births of both partners should be higher than their deaths in symbiosis and deaths of both partners should be higher than their births when living independently. However, experimentally measuring this can be difficult and conclusions tend to focus on the host. Using a ciliate-algal system (Paramecium bursaria host and Chlorella endosymbionts), we estimated the benefits and costs of endosymbiosis for both organisms using fitness measurements in different biotic environments to test under which environmental conditions the net effects of the interaction were positive for both partners. We found that the net effects of harbouring endosymbionts were positive for the ciliate hosts as it allowed them to survive in conditions of low-quality bacteria food. The algae benefitted by being endosymbiotic when predators such as the hosts were present, but the net effects were dependent on the total density of hosts, decreasing as hosts densities increased. Overall, we show that including context-dependency of endosymbiosis is essential in understanding how these interactions have evolved.

Plant-microbe eco-evolutionary dynamics in a changing world

Both plants and their associated microbiomes can respond strongly to anthropogenic environmental changes. These responses can be both ecological (e.g. a global change affecting plant demography or microbial community composition) and evolutionary (e.g. a global change altering natural selection on plant or microbial populations). As a result, global changes can catalyse eco-evolutionary feedbacks. Here, we take a plant-focused perspective to discuss how microbes mediate plant ecological responses to global change and how these ecological effects can influence plant evolutionary response to global change. We argue that the strong and functionally important relationships between plants and their associated microbes are particularly likely to result in eco-evolutionary feedbacks when perturbed by global changes and discuss how improved understanding of plant-microbe eco-evolutionary dynamics could inform conservation or even agriculture.

How does genetic architecture affect eco-evolutionary dynamics? A theoretical perspective

Recent studies have revealed the importance of feedbacks between contemporary rapid evolution (i.e. evolution that occurs through changes in allele frequencies) and ecological dynamics. Despite its inherent interdisciplinary nature, however, studies on eco-evolutionary feedbacks have been mostly ecological and tended to focus on adaptation at the phenotypic level without considering the genetic architecture of evolutionary processes. In empirical studies, researchers have often compared ecological dynamics when the focal species under selection has a single genotype with dynamics when it has multiple genotypes. In theoretical studies, common approaches are models of quantitative traits where mean trait values change adaptively along the fitness gradient and Mendelian traits with two alleles at a single locus. On the other hand, it is well known that genetic architecture can affect short-term evolutionary dynamics in population genetics. Indeed, recent theoretical studies have demonstrated that genetic architecture (e.g. the number of loci, linkage disequilibrium and ploidy) matters in eco-evolutionary dynamics (e.g. evolutionary rescue where rapid evolution prevents extinction and population cycles driven by (co)evolution). I propose that theoretical approaches will promote the synthesis of functional genomics and eco-evolutionary dynamics through models that combine population genetics and ecology as well as nonlinear time-series analyses using emerging big data.

This article is part of the theme issue ‘Genetic basis of adaptation and speciation: from loci to causative mutations’.

Simultaneous Giant Virus and Virophage Quantification Using Droplet Digital PCR

Viruses are an abundant component of aquatic systems, but their detection and quantification remain a challenge. Virophages co-replicate with giant viruses in the shared host cell, and can inhibit the production of new giant virus particles, thereby increasing the survival of the infected host population. Here, we present a protocol for Droplet Digital PCR (ddPCR) to quantify simultaneously giant virus and virophage in a mixed sample, enabling the rapid, culture-free and high throughput detection of virus and virophage. As virophage can be present as free virus particles or integrated into the virus host's genome as well as associated with organic particles, we developed a simple method that enables discrimination between free and particle-associated virophages. The latter include aggregated virophage particles as well as virophage integrated into the host genome. We used, for our experiments, a host-virus-virophage system consisting of Cafeteria burkhardae, CroV and mavirus. Our results show that ddPCR can be an efficient method to quantify virus and virophage, and we discuss potential applications of the method for studying ecological and evolutionary processes of virus and virophages.

Evolutionary transition from a single RNA replicator to a multiple replicator network

In prebiotic evolution, self-replicating molecules are believed to have evolved into complex living systems by expanding their information and functions open-endedly. Theoretically, such evolutionary complexification could occur through successive appearance of novel replicators that interact with one another to form replication networks. Here we perform long-term evolution experiments of RNA that replicates using a self-encoded RNA replicase. The RNA diversifies into multiple coexisting host and parasite lineages, whose frequencies in the population initially fluctuate and gradually stabilize. The final population, comprising five RNA lineages, forms a replicator network with diverse interactions, including cooperation to help the replication of all other members. These results support the capability of molecular replicators to spontaneously develop complexity through Darwinian evolution, a critical step for the emergence of life.

Long-term experimental evolution shows that a single polymerase-encoding RNA replicator can evolve into a complex replicator network, shedding light on how a molecular replicator could have developed complexity before the emergence of life.

Strong Selection and High Mutation Supply Characterize Experimental Chlorovirus Evolution

Characterizing how viruses evolve expands our understanding of the underlying fundamental processes, such as mutation, selection and drift. One group of viruses whose evolution has not yet been extensively studied is the Phycodnaviridae, a globally abundant family of aquatic large double-stranded (ds) DNA viruses. Here we studied the evolutionary change of Paramecium bursaria chlorella virus 1 during experimental coevolution with its algal host. We used pooled genome sequencing of six independently evolved populations to characterize genomic change over five time points. Across six experimental replicates involving either strong or weak demographic fluctuations, we found single nucleotide polymorphisms (SNPs) at sixty-seven sites. The occurrence of genetic variants was highly repeatable, with just two of the SNPs found in only a single experimental replicate. Three genes A122/123R, A140/145R and A540L showed an excess of variable sites, providing new information about potential targets of selection during Chlorella–Chlorovirus coevolution. Our data indicated that the studied populations were not mutation-limited and experienced strong positive selection. Our investigation highlighted relevant processes governing the evolution of aquatic large dsDNA viruses, which ultimately contributes to a better understanding of the functioning of natural aquatic ecosystems.

Cheating Promotes Coexistence in a Two-Species One-Substrate Culture Model

Cheating in microbial communities is often regarded as a precursor to a “tragedy of the commons,” ultimately leading to over-exploitation by a few species and destabilization of the community. While current evidence suggests that cheaters are evolutionarily and ecologically abundant, they can also play important roles in communities, such as promoting cooperative behaviors of other species. We developed a closed culture model with two microbial species and a single, complex nutrient substrate (the metaphorical “common”). One of the organisms, an enzyme producer, degrades the substrate, releasing an essential and limiting resource that it can use both to grow and produce more enzymes, but at a cost. The second organism, a cheater, does not produce the enzyme but can access the diffused resource produced by the other species, allowing it to benefit from the public good without contributing to it. We investigated evolutionarily stable states of coexistence between the two organisms and described how enzyme production rates and resource diffusion influence organism abundances. Our model shows that, in the long-term evolutionary scale, monocultures of the producer species drive themselves extinct because selection always favors mutant invaders that invest less in enzyme production, ultimately driving down the release of resources. However, the presence of a cheater buffers this process by reducing the fitness advantage of lower enzyme production, thereby preventing runaway selection in the producer, and promoting coexistence. Resource diffusion rate controls cheater growth, preventing it from outcompeting the producer. These results show that competition from cheaters can force producers to maintain adequate enzyme production to sustain both itself and the cheater. This is similar to what is known in evolutionary game theory as a “snowdrift game” – a metaphor describing a snow shoveler and a cheater following in their clean tracks. We move further to show that cheating can stabilize communities and possibly be a precursor to cooperation, rather than extinction.

Coevolutionary theory of hosts and parasites

Host and parasite evolution are closely intertwined, with selection for adaptations and counter‐adaptations forming a coevolutionary feedback loop. Coevolutionary dynamics are often difficult to intuit due to these feedbacks and are hard to demonstrate empirically in most systems. Theoretical models have therefore played a crucial role in shaping our understanding of host–parasite coevolution. Theoretical models vary widely in their assumptions, approaches and aims, and such variety makes it difficult, especially for non‐theoreticians and those new to the field, to: (1) understand how model approaches relate to one another; (2) identify key modelling assumptions; (3) determine how model assumptions relate to biological systems; and (4) reconcile the results of different models with contrasting assumptions. In this review, we identify important model features, highlight key results and predictions and describe how these pertain to model assumptions. We carry out a literature survey of theoretical studies published since the 1950s (n = 219 papers) to support our analysis. We identify two particularly important features of models that tend to have a significant qualitative impact on the outcome of host–parasite coevolution: population dynamics and the genetic basis of infection. We also highlight the importance of other modelling features, such as stochasticity and whether time proceeds continuously or in discrete steps, that have received less attention but can drastically alter coevolutionary dynamics. We finish by summarizing recent developments in the field, specifically the trend towards greater model complexity, and discuss likely future directions for research.

Delayed Lysis Time at High Multiplicities of Particles in a Chlorovirus-Chlorella Interaction

When viruses infect microbial cells, their phenotypes depend on the host's genotype and on the environmental conditions. Here we describe such an effect in laboratory strains of the chlorovirus PBCV-1 and its algal host Chlorella variabilis. We studied the growth of six virus isolates, and found that the mean lysis time was 1.34±0.05 times longer at multiplicity of particles (MOP) 10 than at MOP 1. We could not detect any associated changes in burst size. This is a novel plastic trait for chloroviruses, and we hypothesize that it is caused by our specific laboratory algae.

Population size impacts host-pathogen coevolution

Ongoing host-pathogen interactions are characterized by rapid coevolutionary changes forcing species to continuously adapt to each other. The interacting species are often defined by finite population sizes. In theory, finite population size limits genetic diversity and compromises the efficiency of selection owing to genetic drift, in turn constraining any rapid coevolutionary responses. To date, however, experimental evidence for such constraints is scarce. The aim of our study was to assess to what extent population size influences the dynamics of host-pathogen coevolution. We used Caenorhabditus elegans and its pathogen Bacillus thuringiensis as a model for experimental coevolution in small and large host populations, as well as in host populations which were periodically forced through a bottleneck. By carefully controlling host population size for 23 host generations, we found that host adaptation was constrained in small populations and to a lesser extent in the bottlenecked populations. As a result, coevolution in large and small populations gave rise to different selection dynamics and produced different patterns of host-pathogen genotype-by-genotype interactions. Our results demonstrate a major influence of host population size on the ability of the antagonists to co-adapt to each other, thereby shaping the dynamics of antagonistic coevolution.

Effect of mutation supply on population dynamics and trait evolution in an experimental microbial community

Mutation supply can influence evolutionary and thereby ecological dynamics in important ways which have received little attention. Mutation supply influences features of population genetics, such as the pool of adaptive mutations, evolutionary pathways and importance of processes, such as clonal interference. The resultant trait evolutionary dynamics, in turn, can alter population size and species interactions. However, controlled experiments testing for the importance of mutation supply on rapid adaptation and thereby population and community dynamics have primarily been restricted to the first of these aspects. To close this knowledge gap, we performed a serial passage experiment with wild-type Pseudomonas fluorescens and a mutant with reduced mutation rate. Bacteria were grown at two resource levels in combination with the presence of a ciliate predator. A higher mutation supply enabled faster adaptation to the low-resource environment and anti-predatory defence. This was associated with higher population size at the ecological level and better access to high-recurrence mutational targets at the genomic level with higher mutation supply. In contrast, mutation rate did not affect growth under high-resource level. Our results demonstrate that intrinsic mutation rate influences population dynamics and trait evolution particularly when population size is constrained by extrinsic conditions.

Eco-evolutionary consequences of habitat warming and fragmentation in communities

Eco-evolutionary dynamics can mediate species and community responses to habitat warming and fragmentation, two of the largest threats to biodiversity and ecosystems. The eco-evolutionary consequences of warming and fragmentation are typically studied independently, hindering our understanding of their simultaneous impacts. Here, we provide a new perspective rooted in trade-offs among traits for understanding their eco-evolutionary consequences. On the one hand, temperature influences traits related to metabolism, such as resource acquisition and activity levels. Such traits are also likely to have trade-offs with other energetically costly traits, like antipredator defences or dispersal. On the other hand, fragmentation can influence a variety of traits (e.g. dispersal) through its effects on the spatial environment experienced by individuals, as well as properties of populations, such as genetic structure. The combined effects of warming and fragmentation on communities should thus reflect their collective impact on traits of individuals and populations, as well as trade-offs at multiple trophic levels, leading to unexpected dynamics when effects are not additive and when evolutionary responses modulate them. Here, we provide a road map to navigate this complexity. First, we review single-species responses to warming and fragmentation. Second, we focus on consumer-resource interactions, considering how eco-evolutionary dynamics can arise in response to warming, fragmentation, and their interaction. Third, we illustrate our perspective with several example scenarios in which trait trade-offs could result in significant eco-evolutionary dynamics. Specifically, we consider the possible eco-evolutionary consequences of (i) evolution in thermal performance of a species involved in a consumer-resource interaction, (ii) ecological or evolutionary changes to encounter and attack rates of consumers, and (iii) changes to top consumer body size in tri-trophic food chains. In these scenarios, we present a number of novel, sometimes counter-intuitive, potential outcomes. Some of these expectations contrast with those solely based on ecological dynamics, for example, evolutionary responses in unexpected directions for resource species or unanticipated population declines in top consumers. Finally, we identify several unanswered questions about the conditions most likely to yield strong eco-evolutionary dynamics, how better to incorporate the role of trade-offs among traits, and the role of eco-evolutionary dynamics in governing responses to warming in fragmented communities.

Bacteriophage-host depth distribution patterns in soil are maintained after nutrient stimulation in vitro

Previous research has revealed the ecological importance of viruses in different ecosystems. However, bacteriophage-host distribution patterns in soil depth profiles have not been investigated. Environmental factors such as nutrient availability and physiological stress can impact the mode (either lytic or lysogenic) of viral reproduction and subsequent influence of virus infection on ecological processes. Soil depth profiles with distinct geochemical properties are ideal models to investigate the virus-host relationships as a function of environmental trophic status and cell abundance. Batch enrichment experiments using soil collected at varying depths (0-140 cm) as inoculum were performed to explore the interactions between viruses and co-occurring microbial hosts under nutrient stimulation. Both viral and bacterial abundance increased in the nutrient media compared with those in the original soils. Bacterial abundance was similar in mixed-cultures of soils regardless of sampling depth, whereas viral abundance was negatively correlated with the depth of soil samples which caused a decreasing virus-to-bacteria ratio. The lysogenetic fraction increased with soil depth in a similar manner as in the original soils assessed directly without nutrient stimulation. The bacterial diversity decreased with soil depth, and was influenced primarily by soil type, viral abundance, and virus-to-bacteria ratio. The bacterial communities were dominated by Bacilli, Beta-, Gamma-Proteobacteria, and Clostridia after nutrient stimulation. Viral and bacterial community structure also varied with soil horizons (i.e., depth). The results showed that the patterns for virus-host interactions shaped by the geochemical properties in the original environment were conserved or similar after in vitro nutrient stimulation. These findings suggest that short-term changes in trophic status alone may not significantly alter the balance of viral reproductive strategies in terrestrial ecosystems as in the antecedent environmental conditions that the host community has long adapted to, and other factors such as stress, host diversity or adaptation may be necessary to trigger community-level shifts in the interactions between viruses and hosts that responded most favorably to nutrient addition.

Overcoming the growth-infectivity trade-off in a bacteriophage slows bacterial resistance evolution

The use of lytic bacteriophages for treating harmful bacteria (phage therapy) is faced with the challenge of bacterial resistance evolution. Phage strains with certain traits, for example, rapid growth and relatively broad infectivity ranges, may enjoy an advantage in slowing bacterial resistance evolution. Here, we show the possibility for laboratory selection programs ("evolutionary training") to yield phage genotypes with both high growth rate and broad infectivity, traits between which a trade-off has been assumed. We worked with a lytic phage that infects the bacterium Pseudomonas fluorescens and adopted three types of training strategies: evolution on susceptible bacteria, coevolution with bacteria, and rotation between evolution and coevolution phases. Overall, there was a trade-off between growth rate and infectivity range in the evolved phage isolates, including those from the rotation training programs. A small number of phages had both high growth rate and broad infectivity, and those trade-off-overcoming phages could slow or even completely prevent resistance evolution in initially susceptible bacterial populations. Our findings show the promise of well-designed evolutionary training programs, in particular an evolution/coevolution rotation selection regime, for obtaining therapeutically useful phage materials.

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.

Genetic and plastic rewiring of food webs under climate change

Climate change is altering ecological and evolutionary processes across biological scales. These simultaneous effects of climate change pose a major challenge for predicting the future state of populations, communities and ecosystems. This challenge is further exacerbated by the current lack of integration of research focused on these different scales.

We propose that integrating the fields of quantitative genetics and food web ecology will reveal new insights on how climate change may reorganize biodiversity across levels of organization. This is because quantitative genetics links the genotypes of individuals to population‐level phenotypic variation due to genetic (G), environmental (E) and gene‐by‐environment (G × E) factors. Food web ecology, on the other hand, links population‐level phenotypes to the structure and dynamics of communities and ecosystems.

We synthesize data and theory across these fields and find evidence that genetic (G) and plastic (E and G × E) phenotypic variation within populations will change in magnitude under new climates in predictable ways. We then show how changes in these sources of phenotypic variation can rewire food webs by altering the number and strength of species interactions, with consequences for ecosystem resilience. We also find evidence suggesting there are predictable asymmetries in genetic and plastic trait variation across trophic levels, which set the pace for phenotypic change and food web responses to climate change. Advances in genomics now make it possible to partition G, E and G × E phenotypic variation in natural populations, allowing tests of the hypotheses we propose.

By synthesizing advances in quantitative genetics and food web ecology, we provide testable predictions for how the structure and dynamics of biodiversity will respond to climate change.

A thermal trade-off between viral production and degradation drives virus-phytoplankton population dynamics

Marine viruses interact with microbial hosts in dynamic environments shaped by variation in abiotic factors, including temperature. However, the impacts of temperature on viral infection of phytoplankton are not well understood. Here we coupled mathematical modelling with experiments to explore the effect of temperature on virus-phytoplankton interactions. Our model shows the negative consequences of high temperatures on infection and suggests a temperature-dependent threshold between viral production and degradation. Modelling long-term dynamics in environments with different average temperatures revealed the potential for long-term host-virus coexistence, epidemic free or habitat loss states. We generalised our model to variation in global sea surface temperatures corresponding to present and future seas and show that climate change may differentially influence virus-host dynamics depending on the virus-host pair. Temperature-dependent changes in the infectivity of virus particles may lead to shifts in virus-host habitats in warmer oceans, analogous to projected changes in the habitats of macro-, microorganisms and pathogens.

Host population dynamics in the face of an evolving pathogen

Interactions between hosts and pathogens are dynamic at both ecological and evolutionary levels. In the resultant 'eco-evolutionary dynamics' ecological and evolutionary processes affect each other. For example, the house finch Haemorhous mexicanus and its recently emerged pathogen, the bacterium Mycoplasma gallisepticum, form a system in which evidence suggests that changes in bacterial virulence through time enhance levels of host immunity in ways that drive the evolution of virulence in an arms race. We use data from two associated citizen science projects in order to determine whether this arms race has had any detectable effect at the population level in the north-eastern United States. We used data from two citizen science projects, based on observations of birds at bird feeders, which provide information on the long-term changes in sizes of aggregations of house finches (host population density), and the probabilities that these house finches have observable disease (disease prevalence). The initial emergence of M. gallisepticum caused a rapid halving of house finch densities; this was then followed by house finch populations remaining stable or slowly declining. Disease prevalence also decreased sharply after the initial emergence and has remained low, although with fluctuations through time. Surprisingly, while initially higher local disease prevalence was found at sites with higher local densities of finches, this relationship has reversed over time. The ability of a vertebrate host species, with a generation time of at least 1 year, to maintain stable populations in the face of evolved higher virulence of a bacterium, with generation times measurable in minutes, suggests that genetic changes in the host are insufficient to explain the observed population-level patterns. We suggest that acquired immunity plays an important role in the observed interaction between house finches and M. gallisepticum.

Adaptation and competition in deteriorating environments

Evolution might rescue populations from extinction in changing environments. Using experimental evolution with microalgae, we investigated if competition influences adaptation to an abiotic stressor, and vice versa, if adaptation to abiotic change influences competition. In a first set of experiments, we propagated monocultures of five species with and without increasing salt stress for approximately 180 generations. When assayed in monoculture, two of the five species showed signatures of adaptation, that is, lines with a history of salt stress had higher population growth rates at high salt than lines without prior exposure to salt. When assayed in mixtures of species, however, only one of these two species had increased population size at high salt, indicating that competition can alter how adaptation to abiotic change influences population dynamics. In a second experiment, we cultivated two species in monocultures and in pairs, with and without increasing salt. While we found no effect of competition on adaptation to salt, our experiment revealed that evolutionary responses to salt can influence competition. Specifically, one of the two species had reduced competitive ability in the no-salt environment after long-term exposure to salt stress. Collectively, our results highlight the complex interplay of adaptation to abiotic change and competitive interactions.

Evolutionary graph theory derived from eco-evolutionary dynamics

A biologically motivated individual-based framework for evolution in network-structured populations is developed that can accommodate eco-evolutionary dynamics. This framework is used to construct a network birth and death model. The evolutionary graph theory model, which considers evolutionary dynamics only, is derived as a special case, highlighting additional assumptions that diverge from real biological processes. This is achieved by introducing a negative ecological feedback loop that suppresses ecological dynamics by forcing births and deaths to be coupled. We also investigate how fitness, a measure of reproductive success used in evolutionary graph theory, is related to the life-history of individuals in terms of their birth and death rates. In simple networks, these ecologically motivated dynamics are used to provide new insight into the spread of adaptive mutations, both with and without clonal interference. For example, the star network, which is known to be an amplifier of selection in evolutionary graph theory, can inhibit the spread of adaptive mutations when individuals can die naturally.

The role of changes in environmental quality in multitrait plastic responses to environmental and social change in the model microalga Chlamydomonas reinhardtii

Intraspecific variation plays a key role in species' responses to environmental change; however, little is known about the role of changes in environmental quality (the population growth rate an environment supports) on intraspecific trait variation. Here, we hypothesize that intraspecific trait variation will be higher in ameliorated environments than in degraded ones. We first measure the range of multitrait phenotypes over a range of environmental qualities for three strains and two evolutionary histories of Chlamydomonas reinhardtii in laboratory conditions. We then explore how environmental quality and trait variation affect the predictability of lineage frequencies when lineage pairs are grown in indirect co-culture. Our results show that environmental quality has the potential to affect intraspecific variability both in terms of the variation in expressed trait values, and in terms of the genotype composition of rapidly growing populations. We found low phenotypic variability in degraded or same-quality environments and high phenotypic variability in ameliorated conditions. This variation can affect population composition, as monoculture growth rate is a less reliable predictor of lineage frequencies in ameliorated environments. Our study highlights that understanding whether populations experience environmental change as an increase or a decrease in quality relative to their recent history affects the changes in trait variation during plastic responses, including growth responses to the presence of conspecifics. This points toward a fundamental role for changes in overall environmental quality in driving phenotypic variation within closely related populations, with implications for microevolution.

Virus-host coexistence in phytoplankton through the genomic lens

Virus-microbe interactions in the ocean are commonly described by "boom and bust" dynamics, whereby a numerically dominant microorganism is lysed and replaced by a virus-resistant one. Here, we isolated a microalga strain and its infective dsDNA virus whose dynamics are characterized instead by parallel growth of both the microalga and the virus. Experimental evolution of clonal lines revealed that this viral production originates from the lysis of a minority of virus-susceptible cells, which are regenerated from resistant cells. Whole-genome sequencing demonstrated that this resistant-susceptible switch involved a large deletion on one chromosome. Mathematical modeling explained how the switch maintains stable microalga-virus population dynamics consistent with their observed growth pattern. Comparative genomics confirmed an ancient origin of this "accordion" chromosome despite a lack of sequence conservation. Together, our results show how dynamic genomic rearrangements may account for a previously overlooked coexistence mechanism in microalgae-virus interactions.

Understanding the evolution of interspecies interactions in microbial communities

Microbial communities are complex multi-species assemblages that are characterized by a multitude of interspecies interactions, which can range from mutualism to competition. The overall sign and strength of interspecies interactions have important consequences for emergent community-level properties such as productivity and stability. It is not well understood how interspecies interactions change over evolutionary timescales. Here, we review the empirical evidence that evolution is an important driver of microbial community properties and dynamics on timescales that have traditionally been regarded as purely ecological. Next, we briefly discuss different modelling approaches to study evolution of communities, emphasizing the similarities and differences between evolutionary and ecological perspectives. We then propose a simple conceptual model for the evolution of interspecies interactions in communities. Specifically, we propose that to understand the evolution of interspecies interactions, it is important to distinguish between direct and indirect fitness effects of a mutation. We predict that in well-mixed environments, traits will be selected exclusively for their direct fitness effects, while in spatially structured environments, traits may also be selected for their indirect fitness effects. Selection of indirectly beneficial traits should result in an increase in interaction strength over time, while selection of directly beneficial traits should not have such a systematic effect. We tested our intuitions using a simple quantitative model and found support for our hypotheses. The next step will be to test these hypotheses experimentally and provide input for a more refined version of the model in turn, thus closing the scientific cycle of models and experiments. This article is part of the theme issue 'Conceptual challenges in microbial community ecology'.

Inference of coevolutionary dynamics and parameters from host and parasite polymorphism data of repeated experiments

There is a long-standing interest in understanding host-parasite coevolutionary dynamics and associated fitness effects. Increasing amounts of genomic data for both interacting species offer a promising source to identify candidate loci and to infer the main parameters of the past coevolutionary history. However, so far no method exists to perform the latter. By coupling a gene-for-gene model with coalescent simulations, we first show that three types of biological costs, namely, resistance, infectivity and infection, define the allele frequencies at the internal equilibrium point of the coevolution model. These in return determine the strength of selective signatures at the coevolving host and parasite loci. We apply an Approximate Bayesian Computation (ABC) approach on simulated datasets to infer these costs by jointly integrating host and parasite polymorphism data at the coevolving loci. To control for the effect of genetic drift on coevolutionary dynamics, we assume that 10 or 30 repetitions are available from controlled experiments or several natural populations. We study two scenarios: 1) the cost of infection and population sizes (host and parasite) are unknown while costs of infectivity and resistance are known, and 2) all three costs are unknown while populations sizes are known. Using the ABC model choice procedure, we show that for both scenarios, we can distinguish with high accuracy pairs of coevolving host and parasite loci from pairs of neutrally evolving loci, though the statistical power decreases with higher cost of infection. The accuracy of parameter inference is high under both scenarios especially when using both host and parasite data because parasite polymorphism data do inform on costs applying to the host and vice-versa. As the false positive rate to detect pairs of genes under coevolution is small, we suggest that our method complements recently developed methods to identify host and parasite candidate loci for functional studies.

Destabilizing evolutionary and eco-evolutionary feedbacks drive empirical eco-evolutionary cycles

We develop a method to identify how ecological, evolutionary, and eco-evolutionary feedbacks influence system stability. We apply our method to nine empirically parametrized eco-evolutionary models of exploiter-victim systems from the literature and identify which particular feedbacks cause some systems to converge to a steady state or to exhibit sustained oscillations. We find that ecological feedbacks involving the interactions between all species and evolutionary and eco-evolutionary feedbacks involving only the interactions between exploiter species (predators or pathogens) are typically stabilizing. In contrast, evolutionary and eco-evolutionary feedbacks involving the interactions between victim species (prey or hosts) are destabilizing more often than not. We also find that while eco-evolutionary feedbacks rarely altered system stability from what would be predicted from just ecological and evolutionary feedbacks, eco-evolutionary feedbacks have the potential to alter system stability at faster or slower speeds of evolution. As the number of empirical studies demonstrating eco-evolutionary feedbacks increases, we can continue to apply these methods to determine whether the patterns we observe are common in other empirical communities.

Eco-evolutionary agriculture: Host-pathogen dynamics in crop rotations

Since its origins, thousands of years ago, agriculture has been challenged by the presence of evolving plant pathogens. Temporal rotations of host and non-host crops have helped farmers to control epidemics among other utilities, but further efforts for strategy assessment are needed. Here, we present a methodology for developing crop rotation strategies optimal for control of pathogens informed by numerical simulations of eco-evolutionary dynamics in one field. This approach can integrate agronomic criteria used in crop rotations—soil quality and cash yield—and the analysis of pathogen evolution in systems where hosts are artificially selected. Our analysis shows which rotation patterns perform better in maximising crop yield when an unspecified infection occurs, with yield being dependent on both soil quality and the strength of the epidemic. Importantly, the use of non-host crops, which both improve soil quality and control the epidemic results in similar rational rotation strategies for diverse agronomic and infection conditions. We test the repeatability of the best rotation patterns over multiple decades, an essential end-user goal. Our results provide sustainable strategies for optimal resource investment for increased food production and lead to further insights into the minimisation of pesticide use in a society demanding ever more efficient agriculture.

The invention of agriculture is a major evolutionary transition in the social evolution of the human race. Transforming the lifestyle from nomadic to sedentary, agriculture provided humankind with the stability necessary to make rapid advancements. However, agriculture, as we know it, is now in danger. While agriculture is a grand artificial selection experiment, it is in a constant battle with the brute force of natural selection, generating highly infectious plant pathogens. Traditional techniques such as slash-burn techniques are not sustainable for feeding the ever-increasing population. Crop rotation, on the other hand, has been developed over thousands of years as a sustainable method. We provide a computational model of how crop rotations can be used to tackle pathogen infection and what properties of rotation patterns make them sustainable in the long run. We hope that this study, together with other sustainable methods such as minimal pesticide use and biocontrol, can make agriculture more efficient.

How long do Red Queen dynamics survive under genetic drift? A comparative analysis of evolutionary and eco-evolutionary models

Background

Red Queen dynamics are defined as long term co-evolutionary dynamics, often with oscillations of genotype abundances driven by fluctuating selection in host-parasite systems. Much of our current understanding of these dynamics is based on theoretical concepts explored in mathematical models that are mostly (i) deterministic, inferring an infinite population size and (ii) evolutionary, thus ecological interactions that change population sizes are excluded. Here, we recall the different mathematical approaches used in the current literature on Red Queen dynamics. We then compare models from game theory (evo) and classical theoretical ecology models (eco-evo), that are all derived from individual interactions and are thus intrinsically stochastic. We assess the influence of this stochasticity through the time to the first loss of a genotype within a host or parasite population.

Results

The time until the first genotype is lost (“extinction time”), is shorter when ecological dynamics, in the form of a changing population size, is considered. Furthermore, when individuals compete only locally with other individuals extinction is even faster. On the other hand, evolutionary models with a fixed population size and competition on the scale of the whole population prolong extinction and therefore stabilise the oscillations. The stabilising properties of intra-specific competitions become stronger when population size is increased and the deterministic part of the dynamics gain influence. In general, the loss of genotype diversity can be counteracted with mutations (or recombination), which then allow the populations to recurrently undergo negative frequency-dependent selection dynamics and selective sweeps.

Conclusion

Although the models we investigated are equal in their biological motivation and interpretation, they have diverging mathematical properties both in the derived deterministic dynamics and the derived stochastic dynamics. We find that models that do not consider intraspecific competition and that include ecological dynamics by letting the population size vary, lose genotypes – and thus Red Queen oscillations – faster than models with competition and a fixed population size.

The feedback between selection and demography shapes genomic diversity during coevolution

Species interactions and coevolution are integral to ecological communities, but we lack empirical information on when and how these interactions generate and purge genetic diversity. Using genomic time series data from host-virus experiments, we found that coevolution occurs through consecutive selective sweeps in both species, with temporal consistency across replicates. Sweeps were accompanied by phenotypic change (resistance or infectivity increases) and expansions in population size. In the host, population expansion enabled rapid generation of genetic diversity in accordance with neutral processes. Viral molecular evolution was, in contrast, confined to few genes, all putative targets of selection. This study demonstrates that molecular evolution during species interactions is shaped by both eco-evolutionary feedback dynamics and interspecific differences in how genetic diversity is generated and maintained.

Eco-evolutionary feedbacks between prey densities and linkage disequilibrium in the predator maintain diversity

Diversity occurs at multiple scales. Within a single population, there is diversity in genotypes and phenotypes. At a larger scale, within ecological communities, there is diversity in species. A number of studies have investigated how diversity at these two scales influence each other through what has been termed eco-evolutionary feedbacks. Here we study a three-species ecological module called apparent competition, in which the predator is evolving in a trait that determines its interaction with two prey species. Unlike previous studies on apparent competition, which employed evolutionary frameworks with very simple genetics, we study an eco-evolutionary model in which the predator's trait is determined by two recombining diallelic loci, so that its mean and variance can evolve, as well as associations (linkage disequilibrium) between the loci. We ask how eco-evolutionary feedbacks with these two loci affect the coexistence of the prey species and the maintenance of polymorphisms within the predator species. We uncover a novel eco-evolutionary feedback between the prey densities and the linkage disequilibrium between the predator's loci. Through a stability analysis, we demonstrate how these feedbacks affect polymorphisms at both loci and, among others, may generate stable cycling.

Co-adaptation impacts the robustness of predator-prey dynamics against perturbations

Global change threatens the maintenance of ecosystem functions that are shaped by the persistence and dynamics of populations. It has been shown that the persistence of species increases if they possess larger trait adaptability. Here, we investigate whether trait adaptability also affects the robustness of population dynamics of interacting species and thereby shapes the reliability of ecosystem functions that are driven by these dynamics. We model co-adaptation in a predator-prey system as changes to predator offense and prey defense due to evolution or phenotypic plasticity. We investigate how trait adaptation affects the robustness of population dynamics against press perturbations to environmental parameters and against pulse perturbations targeting species abundances and their trait values. Robustness of population dynamics is characterized by resilience, elasticity, and resistance. In addition to employing established measures for resilience and elasticity against pulse perturbations (extinction probability and return time), we propose the warping distance as a new measure for resistance against press perturbations, which compares the shapes and amplitudes of pre- and post-perturbation population dynamics. As expected, we find that the robustness of population dynamics depends on the speed of adaptation, but in nontrivial ways. Elasticity increases with speed of adaptation as the system returns more rapidly to the pre-perturbation state. Resilience, in turn, is enhanced by intermediate speeds of adaptation, as here trait adaptation dampens biomass oscillations. The resistance of population dynamics strongly depends on the target of the press perturbation, preventing a simple relationship with the adaptation speed. In general, we find that low robustness often coincides with high amplitudes of population dynamics. Hence, amplitudes may indicate the robustness against perturbations also in other natural systems with similar dynamics. Our findings show that besides counteracting extinctions, trait adaptation indeed strongly affects the robustness of population dynamics against press and pulse perturbations.

Ecological and Evolutionary Processes Shaping Viral Genetic Diversity

The contemporary genomic diversity of viruses is a result of the continuous and dynamic interaction of past ecological and evolutionary processes. Thus, genome sequences of viruses can be a valuable source of information about these processes. In this review, we first describe the relevant processes shaping viral genomic variation, with a focus on the role of host–virus coevolution and its potential to give rise to eco-evolutionary feedback loops. We further give a brief overview of available methodology designed to extract information about these processes from genomic data. Short generation times and small genomes make viruses ideal model systems to study the joint effect of complex coevolutionary and eco-evolutionary interactions on genetic evolution. This complexity, together with the diverse array of lifetime and reproductive strategies in viruses ask for extensions of existing inference methods, for example by integrating multiple information sources. Such integration can broaden the applicability of genetic inference methods and thus further improve our understanding of the role viruses play in biological communities.

Synthetic Mutualism and the Intervention Dilemma

Ecosystems are complex networks of interacting individuals co-evolving with their environment. As such, changes to an interaction can influence the whole ecosystem. However, to predict the outcome of these changes, considerable understanding of processes driving the system is required. Synthetic biology provides powerful tools to aid this understanding, but these developments also allow us to change specific interactions. Of particular interest is the ecological importance of mutualism, a subset of cooperative interactions. Mutualism occurs when individuals of different species provide a reciprocal fitness benefit. We review available experimental techniques of synthetic biology focused on engineered synthetic mutualistic systems. Components of these systems have defined interactions that can be altered to model naturally occurring relationships. Integrations between experimental systems and theoretical models, each informing the use or development of the other, allow predictions to be made about the nature of complex relationships. The predictions range from stability of microbial communities in extreme environments to the collapse of ecosystems due to dangerous levels of human intervention. With such caveats, we evaluate the promise of synthetic biology from the perspective of ethics and laws regarding biological alterations, whether on Earth or beyond. Just because we are able to change something, should we?

Eco-evolutionary feedbacks promote fluctuating selection and long-term stability of antagonistic networks

Studies have shown the potential for rapid adaptation in coevolving populations and that the structure of species interaction networks can modulate the vulnerability of ecological systems to perturbations. Although the feedback loop between population dynamics and coevolution of traits is crucial for understanding long-term stability in ecological assemblages, modelling eco-evolutionary dynamics in species-rich assemblages is still a challenge. We explore how eco-evolutionary feedbacks influence trait evolution and species abundances in 23 empirical antagonistic networks. We show that, if selection due to antagonistic interactions is stronger than other selective pressures, eco-evolutionary feedbacks lead to higher mean species abundances and lower temporal variation in abundances. By contrast, strong selection of antagonistic interactions leads to higher temporal variation of traits and on interaction strengths. Our results present a theoretical link between the study of the species persistence and coevolution in networks of interacting species, pointing out the ways by which coevolution may decrease the vulnerability of species within antagonistic networks to demographic fluctuation.

The genomic basis of Red Queen dynamics during rapid reciprocal host-pathogen coevolution

Pathogens are omnipresent and by definition detrimental to their hosts. Pathogens thus exert high selection on their hosts, which, if adapting, can exert similar levels of selection on the pathogen, resulting in ongoing cycles of reciprocal adaptation between the antagonists. Such coevolutionary interactions have a central influence on the evolution of organisms. Surprisingly, we still know little about the exact selection dynamics and the genome regions involved. Our study uses a controlled experimental approach with an animal host to dissect coevolutionary selection. We find that distinct selective processes underlie rapid coadaptation in the two antagonists, including antagonistic frequency-dependent selection on toxin gene copy number in the pathogen, while the host response is likely influenced by changes in multiple genome regions.

Red Queen dynamics, involving coevolutionary interactions between species, are ubiquitous, shaping the evolution of diverse biological systems. To date, information on the underlying selection dynamics and the involved genome regions is mainly available for bacteria–phage systems or only one of the antagonists of a eukaryotic host–pathogen interaction. We add to our understanding of these important coevolutionary interactions using an experimental host–pathogen model, which includes the nematode Caenorhabditis elegans and its pathogen Bacillus thuringiensis. We combined experimental evolution with time-shift experiments, in which a focal host or pathogen is tested against a coevolved antagonist from the past, present, or future, followed by genomic analysis. We show that (i) coevolution occurs rapidly within few generations, (ii) temporal coadaptation at the phenotypic level is found in parallel across replicate populations, consistent with antagonistic frequency-dependent selection, (iii) genomic changes in the pathogen match the phenotypic pattern and include copy number variations of a toxin-encoding plasmid, and (iv) host genomic changes do not match the phenotypic pattern and likely involve selective responses at more than one locus. By exploring the dynamics of coevolution at the phenotypic and genomic level for both host and pathogen simultaneously, our findings demonstrate a more complex model of the Red Queen, consisting of distinct selective processes acting on the two antagonists during rapid and reciprocal coadaptation.