High parasite diversity maintained after an alga-virus coevolutionary arms race.

Arms race dynamics are a common outcome of host-parasite coevolution. While they can theoretically be maintained indefinitely, realistic arms races are expected to be finite. Once an arms race has ended, for example due to the evolution of a generalist resistant host, the system may transition into coevolutionary dynamics that favor long-term diversity. In microbial experiments, host-parasite arms races often transition into a stable coexistence of generalist resistant hosts, (semi-)susceptible hosts, and parasites. While long-term host diversity is implicit in these cases, parasite diversity is usually overlooked. In this study, we examined parasite diversity after the end of an experimental arms race between a unicellular alga (Chlorella variabilis) and its lytic virus (PBCV-1). First, we isolated virus genotypes from multiple time points from two replicate microcosms. A time-shift experiment confirmed that the virus isolates had escalating host ranges, i.e. that the arms races had occurred. We then examined the phenotypic and genetic diversity of virus isolates from the post-arms race phase. Post-arms race virus isolates had diverse host ranges, survival probabilities, and growth rates; they also clustered into distinct genetic groups. Importantly, host range diversity was maintained throughout the post-arms race phase, and the frequency of host range phenotypes fluctuated over time. We hypothesize that this dynamic polymorphism was maintained by a combination of fluctuating selection and demographic stochasticity. Together with previous work in prokaryotic systems, our results link experimental observations of arms races to natural observations of long-term host and parasite diversity.

Range of trait variation in prey determines evolutionary contributions to predator growth rates.

Evolutionary and ecological dynamics can occur on similar timescales and thus influence each other. While it has been shown that the relative contribution of ecological and evolutionary change to population dynamics can vary, it still remains unknown what influences these differences. Here, we test whether prey populations with increased variation in their defense and competitiveness traits will have a stronger impact of evolution for predator growth rates. We controlled trait variation by pairing distinct clonal lineages of the green alga Chlamydomonas reinhardtii with known traits as prey with the rotifer Brachionus calyciforus as predator and compared those results with a mechanistic model matching the empirical system. We measured the impact of evolution (shift in prey clonal frequency) and ecology (shift in prey population density) for predator growth rate and its dependency on trait variation using an approach based on a two-way ANOVA. Our experimental results indicated that higher trait variation, i.e., a greater distance in trait space, increased the relative contribution of prey evolution to predator growth rate over 3-4 predator generations, which was also observed in model simulations spanning longer time periods. In our model, we also observed clone-specific results, where a more competitive undefended prey resulted in a higher evolutionary contribution, independent of the trait distance. Our results suggest that trait combinations and total prey trait variation combine to influence the contribution of evolution to predator population dynamics, and that trait variation can be used to identify and better predict the role of eco-evolutionary dynamics in predator-prey systems.

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.

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.

Statistical methods to identify mechanisms in studies of eco-evolutionary dynamics.

While the reciprocal effects of ecological and evolutionary dynamics are increasingly recognized as an important driver for biodiversity, detection of such eco-evolutionary feedbacks, their underlying mechanisms, and their consequences remains challenging. Eco-evolutionary dynamics occur at different spatial and temporal scales and can leave signatures at different levels of organization (e.g., gene, protein, trait, community) that are often difficult to detect. Recent advances in statistical methods combined with alternative hypothesis testing provides a promising approach to identify potential eco-evolutionary drivers for observed data even in non-model systems that are not amenable to experimental manipulation. We discuss recent advances in eco-evolutionary modeling and statistical methods and discuss challenges for fitting mechanistic models to eco-evolutionary data.

Population dynamics hide phenotypic changes driven by subtle chemical exposures: implications for risk assessments.

Ecological risk assessment of chemicals focuses on the response of different taxa in isolation not taking ecological and evolutionary interplay in communities into account. Its consideration would, however, allow for an improved assessment by testing for implications within and across trophic levels and changes in the phenotypic and genotypic diversity within populations. We present a simple experimental system that can be used to evaluate the ecological and evolutionary responses to chemical exposure at microbial community levels. We exposed a microbial model system of the ciliate Tetrahymena thermophila (predator) and the bacterium Pseudomonas fluorescens (prey) to iron released from Magnetic Particles (MP-Fedis), which are Phosphorus (P) adsorbents used in lake restoration. Our results show that while the responses of predator single population size differed across concentrations of MP-Fedis and the responses of prey from communities differed also across concentration of MP-Fedis, the community responses (species ratio) were similar for the different MP-Fedis concentrations. Looking further at an evolutionary change in the bacterial preys' defence, we found that MP-Fedis drove different patterns and dynamics of defence evolution. Overall, our study shows how similar community dynamics mask changes at evolutionary levels that would be overlooked in the design of current risk assessment protocols where evolutionary approaches are not considered.

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.

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.

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.

Change in prey genotype frequency rescues predator from extinction.

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

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.

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 (dsDNA) 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.

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.

The evolution of convex trade-offs enables the transition towards multicellularity.

The evolutionary transition towards multicellular life often involves growth in groups of undifferentiated cells followed by differentiation into soma and germ-like cells. Theory predicts that germ soma differentiation is facilitated by a convex trade-off between survival and reproduction. However, this has never been tested and these transitions remain poorly understood at the ecological and genetic level. Here, we study the evolution of cell groups in ten isogenic lines of the unicellular green algae Chlamydomonas reinhardtii with prolonged exposure to a rotifer predator. We confirm that growth in cell groups is heritable and characterized by a convex trade-off curve between reproduction and survival. Identical mutations evolve in all cell group isolates; these are linked to survival and reducing associated cell costs. Overall, we show that just 500 generations of predator selection were sufficient to lead to a convex trade-off and incorporate evolved changes into the prey genome.

Evolutionary dynamics of transposable elements in bdelloid rotifers.

Transposable elements (TEs) are selfish genomic parasites whose ability to spread autonomously is facilitated by sexual reproduction in their hosts. If hosts become obligately asexual, TE frequencies and dynamics are predicted to change dramatically, but the long-term outcome is unclear. Here, we test current theory using whole-genome sequence data from eight species of bdelloid rotifers, a class of invertebrates in which males are thus far unknown. Contrary to expectations, we find a variety of active TEs in bdelloid genomes, at an overall frequency within the range seen in sexual species. We find no evidence that TEs are spread by cryptic recombination or restrained by unusual DNA repair mechanisms. Instead, we find that that TE content evolves relatively slowly in bdelloids and that gene families involved in RNAi-mediated TE suppression have undergone significant expansion, which might mitigate the deleterious effects of active TEs and compensate for the consequences of long-term asexuality.

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

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

Antagonistic species interaction drives selection for sex in a predator-prey system.

The evolutionary maintenance of sexual reproduction has long challenged biologists as the majority of species reproduce sexually despite inherent costs. Providing a general explanation for the evolutionary success of sex has thus proven difficult and resulted in numerous hypotheses. A leading hypothesis suggests that antagonistic species interaction can generate conditions selecting for increased sex due to the production of rare or novel genotypes that are beneficial for rapid adaptation to recurrent environmental change brought on by antagonism. To test this ecology-based hypothesis, we conducted experimental evolution in a predator (rotifer)-prey (algal) system by using continuous cultures to track predator-prey dynamics and in situ rates of sex in the prey over time and within replicated experimental populations. Overall, we found that predator-mediated fluctuating selection for competitive versus defended prey resulted in higher rates of genetic mixing in the prey. More specifically, our results showed that fluctuating population sizes of predator and prey, coupled with a trade-off in the prey, drove the sort of recurrent environmental change that could provide a benefit to sex in the prey, despite inherent costs. We end with a discussion of potential population genetic mechanisms underlying increased selection for sex in this system, based on our application of a general theoretical framework for measuring the effects of sex over time, and interpreting how these effects can lead to inferences about the conditions selecting for or against sexual reproduction in a system with antagonistic species interaction.

Towards a General Understanding of Bacterial Interactions.

Understanding the general rules of microbial interactions is central for advancing microbial ecology. Recent studies show that interaction range, interaction strength, and community context determine bacterial interactions and the coexistence and evolution of bacteria. We highlight how these factors could contribute to a general understanding of bacterial interactions.

Co-evolution as an important component explaining microbial predator-prey interaction.

Predator-prey relationships belong to the most important and well-studied ecological interactions in nature. Understanding the underlying mechanisms is important to predict community dynamics and to estimate coexistence probability. Historically, evolution has been considered to be too slow to affect such ecological interactions. However, evolution can occur within ecological time scales, potentially affecting predator-prey communities. In an antagonistic pair-wise relationship the prey might evolve to minimize the effect caused by the predator (e.g. mortality), while the predator might evolve to maximize the effect (e.g. food intake). Evolution of one of the species or even co-evolution of both species in predator-prey relationships is often difficult to estimate from population dynamics without measuring of trait changes in predator and/or prey population. Particularly in microbial systems, where microorganisms evolve quickly, determining whether co-evolution occurs in predator-prey systems is challenging. We simulate observational data using quantitative trait evolution models and show that the interaction between bacteria and ciliates can be best explained as a co-evolutionary process, where both the prey and predator evolve. Evolution by prey alone explains the data less well, whereas the models with predator evolution alone or no evolution are both failing. We conclude that that ecology and evolution both interact in shaping community dynamics in microcosms. Ignoring the contribution of evolution might lead to incorrect conclusions.

Genomics of host-pathogen interactions: challenges and opportunities across ecological and spatiotemporal scales.

Evolutionary genomics has recently entered a new era in the study of host-pathogen interactions. A variety of novel genomic techniques has transformed the identification, detection and classification of both hosts and pathogens, allowing a greater resolution that helps decipher their underlying dynamics and provides novel insights into their environmental context. Nevertheless, many challenges to a general understanding of host-pathogen interactions remain, in particular in the synthesis and integration of concepts and findings across a variety of systems and different spatiotemporal and ecological scales. In this perspective we aim to highlight some of the commonalities and complexities across diverse studies of host-pathogen interactions, with a focus on ecological, spatiotemporal variation, and the choice of genomic methods used. We performed a quantitative review of recent literature to investigate links, patterns and potential tradeoffs between the complexity of genomic, ecological and spatiotemporal scales undertaken in individual host-pathogen studies. We found that the majority of studies used whole genome resolution to address their research objectives across a broad range of ecological scales, especially when focusing on the pathogen side of the interaction. Nevertheless, genomic studies conducted in a complex spatiotemporal context are currently rare in the literature. Because processes of host-pathogen interactions can be understood at multiple scales, from molecular-, cellular-, and physiological-scales to the levels of populations and ecosystems, we conclude that a major obstacle for synthesis across diverse host-pathogen systems is that data are collected on widely diverging scales with different degrees of resolution. This disparity not only hampers effective infrastructural organization of the data but also data granularity and accessibility. Comprehensive metadata deposited in association with genomic data in easily accessible databases will allow greater inference across systems in the future, especially when combined with open data standards and practices. The standardization and comparability of such data will facilitate early detection of emerging infectious diseases as well as studies of the impact of anthropogenic stressors, such as climate change, on disease dynamics in humans and wildlife.