The feedback between selection and demography shapes genomic diversity during coevolution

Critically evaluating the relative importance of phage in shaping microbial community composition

The ubiquity of bacteriophages (phages) and the major evolutionary and ecological impacts they can have on their microbial hosts has resulted in phages often cited as key drivers shaping microbial community composition (the relative abundances of species). However, the evidence for the importance of phages is mixed. Here, we critically review the theory and data exploring the role of phages in communities, identifying the conditions when phages are likely to be important drivers of community composition. At ecological scales, we conclude that phages are often followers rather than drivers of microbial population and community dynamics. While phages can affect strain diversity within species, there is yet to be strong evidence suggesting that fluctuations in species' strains affects community composition.

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 favour 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 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.

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.

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.

Retrotransposon-mediated evolutionary rewiring of a pathogen response orchestrates a resistance phenotype in an insect host

Ongoing host-pathogen interactions can trigger a coevolutionary arms race, while genetic diversity within the host can facilitate its adaptation to pathogens. Here, we used the diamondback moth (Plutella xylostella) and its pathogen Bacillus thuringiensis (Bt) as a model for exploring an adaptive evolutionary mechanism. We found that insect host adaptation to the primary Bt virulence factors was tightly associated with a short interspersed nuclear element (SINE - named SE2) insertion into the promoter of the transcriptionally activated MAP4K4 gene. This retrotransposon insertion coopts and potentiates the effect of the transcription factor forkhead box O (FOXO) in inducing a hormone-modulated Mitogen-activated protein kinase (MAPK) signaling cascade, leading to an enhancement of a host defense mechanism against the pathogen. This work demonstrates that reconstructing a cis-trans interaction can escalate a host response mechanism into a more stringent resistance phenotype to resist pathogen infection, providing a new insight into the coevolutionary mechanism of host organisms and their microbial pathogens.

Are genetic variation and demographic performance linked?

Quantifying relationships between genetic variation and population viability is important from both basic biological and applied conservation perspectives, yet few populations have been monitored with both long-term demographic and population genetics approaches. To empirically test whether and how genetic variation and population dynamics are related, we present one such paired approach. First, we use eight years of historical demographic data from five populations of Boechera fecunda (Brassicaceae), a rare, self-compatible perennial plant endemic to Montana, USA, and use integral projection models to estimate the stochastic population growth rate (λ S) and extinction risk of each population. We then combine these demographic estimates with previously published metrics of genetic variation in the same populations to test whether genetic diversity within populations is linked to demographic performance. Our results show that in this predominantly inbred species, standing genetic variation and demography are weakly positively correlated. However, the inbreeding coefficient was not strongly correlated with demographic performance, suggesting that more inbred populations are not necessarily less viable or at higher extinction risk than less inbred populations. A contemporary re-census of these populations revealed that neither genetic nor demographic parameters were consistently strong predictors of current population density, although populations showing lower probabilities of extinction in demographic models had larger population sizes at present. In the absence of evidence for inbreeding depression decreasing population viability in this species, we recommend conservation of distinct, potentially locally adapted populations of B. fecunda rather than alternatives such as translocations or reintroductions.

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 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.

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.

Evolving Interactions and Emergent Functions in Microbial Consortia

Microbial communities are constantly challenged with environmental stressors, such as antimicrobials, pollutants, and global warming. How do they respond to these changes? Answering this question is crucial given that microbial communities perform essential functions for life on Earth. Our research aims to understand and predict communities' responses to change by addressing the following questions. (i) How do eco-evolutionary feedbacks influence microbial community dynamics? (ii) How do multiple interacting species in a microbial community alter evolutionary processes? (iii) To what extent do microbial communities respond to change by ecological versus evolutionary processes? To answer these questions, we use microbial communities of reduced complexity coupled with experimental evolution, genome sequencing, and mathematical modeling. The overall expectation from this integrative research approach is to generate general concepts that extend beyond specific bacterial species and provide fundamental insights into the consequences of evolution on the functioning of whole microbial communities.

Evolutionary ecology theory - microbial population structure

Microbial populations typically show a large degree of intra-population diversity. This diversity is intertwined with the structure of the population. Here, we discuss endogenous and exogenous drivers of population structure in microbes and how the population structure can affect evolutionary dynamics and vice versa. Endogenous structure, which can be genetic or demographic, is driven by the ecology and evolutionary dynamics within the population. Exogenous structure is typically driven by the spatial and temporal properties of the environment. A particular interesting case arises when also this exogenous structure experiences feedbacks from the microbial population.

Novel genomic approaches to study antagonistic coevolution between hosts and parasites

Host-parasite coevolution is ubiquitous, shaping genetic and phenotypic diversity and the evolutionary trajectory of interacting species. With the advances of high throughput sequencing technologies applicable to model and non-model organisms alike, it is now feasible to study in greater detail (a) the genetic underpinnings of coevolution, (b) the speed and type of dynamics at coevolving loci, and (c) the genomic consequences of coevolution. This review focuses on three recently developed approaches that leverage information from host and parasite full genome data simultaneously to pinpoint coevolving loci and draw inference on the coevolutionary history. First, co-genome-wide association study (co-GWAS) methods allow pinpointing the loci underlying host-parasite interactions. These methods focus on detecting associations between genetic variants and the outcome of experimental infection tests or on correlations between genomes of naturally infected hosts and their infecting parasites. Second, extensions to population genomics methods can detect genes under coevolution and infer the coevolutionary history, such as fitness costs. Third, correlations between host and parasite population size in time are indicative of coevolution, and polymorphism levels across independent spatially distributed populations of hosts and parasites can reveal coevolutionary loci and infer coevolutionary history. We describe the principles of these three approaches and discuss their advantages and limitations based on coevolutionary theory. We present recommendations for their application to various host (prokaryotes, fungi, plants, and animals) and parasite (viruses, bacteria, fungi, and macroparasites) species. We conclude by pointing out methodological and theoretical gaps to be filled to extract maximum information from full genome data and thereby to shed light on the molecular underpinnings of coevolution.

Host-parasite co-evolution and its genomic signature

Studies in diverse biological systems have indicated that host-parasite co-evolution is responsible for the extraordinary genetic diversity seen in some genomic regions, such as major histocompatibility (MHC) genes in jawed vertebrates and resistance genes in plants. This diversity is believed to evolve under balancing selection on hosts by parasites. However, the mechanisms that link the genomic signatures in these regions to the underlying co-evolutionary process are only slowly emerging. We still lack a clear picture of the co-evolutionary concepts and of the genetic basis of the co-evolving phenotypic traits in the interacting antagonists. Emerging genomic tools that provide new options for identifying underlying genes will contribute to a fuller understanding of the co-evolutionary process.

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.

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.