The influence of population size on host-parasite coevolution

Host-parasite coevolution is defined as reciprocal adaptation between coexisting hosts and parasites. It associates with strong antagonistic selection, leading to fast changes in fitness-related traits, such as host resistance or parasite virulence, which in turn affects overall host population performance and parasite prevalence. The resulting dynamics of the interaction inherently causes population size fluctuations. Infection outbreaks followed by parasite disappearance, host mass extinctions and periodic oscillations in host and parasite abundance are all examples of changes in population size under natural conditions. These demographic variations enhance stochasticity and affect the process of evolution. Despite a large body of evidence suggesting that fluctuating population size is an inevitable consequence of host-parasite interplay, population size is usually assumed to be constant or infinite (ignoring stochasticity) in current studies on coevolution(Chapter I). The main goal of this thesis is to enhance a more realistic view on host-parasite coevolution by theoretically and experimentally testing the influence of fluctuating population size and associated stochasticity. First, together with colleagues, I examined the consequences of changing population size in a theoretical model by relaxing conventionally made assumptions of infinite and constant population size (Chapter II). We found that fluctuating population size combined with stochasticity dramatically changed host-parasite coevolution dynamics by (i) greatly increasing fixation rates and, therefore, (ii) preventing continuous genotype oscillations, which in case of infinite or constant population size would sustain (in accordance with negative-frequency dependent selection). As an experimental approach, central for this thesis, I carried out an evolution experiment with two interacting model organisms - the nematode Caenorhabditis elegans and the pathogenic bacterium Bacillus thuringiensis (Chapter III). I developed for this purpose a high-throughput protocol, which allowed propagation of many replicate populations for 23 host generations under three different demographic regimes: small populations (increased stochasticity), large populations (“deterministic” situation), and populations periodically forced to bottlenecks (fluctuating population size). After the experiment, I phenotypically characterized evolved host and parasite populations by exposing them to the ancestral antagonist and found the following evolutionary changes in fitness related-traits: (i) an increase in host fecundity, (ii) a decrease in host survival, and (iii) the accumulation of population divergence in parasite virulence. Additionally, I performed a time-shift experiment by confronting coevolved host and parasite populations from three different time points of the coevolution experiment in all possible combinations in order to infer the temporal dynamics of coevolution. The time-shift experiment revealed (iv) a striking pattern of negative frequency-dependent selection providing the first experimental demonstration of this type of dynamics for experimentally coevolved host and parasite. Moreover, (v) negative frequency-dependent selection was found in large populations and only partially in populations subjected to bottlenecks but not in small populations, suggesting that fluctuating population size and increased stochasticity can alter coevolutionary dynamics, in accordance with the results of the theoretical model. Finally, I performed a functional analysis of two toxin genes of B. thuringiensis, which had been identified as candidate genes in a separate evolution experiment, and confirmed their contribution to the pathogenicity of this bacterium (Chapter IV). Taken together, my PhD project emphasizes the selective impact of coevolution on trait evolution in both antagonists, especially under large population sizes

Host-parasite coevolution in populations of constant and variable size

The matching-allele and gene-for-gene models are widely used in math- ematical approaches that study the dynamics of host-parasite interactions. Agrawal and Lively (Evolutionary Ecology Research 4:79-90, 2002) captured these two models in a single framework and numerically explored the associated time discrete dynamics of allele frequencies. Here, we present a detailed analytical investigation of this unifying framework in continuous time and provide a generalization. We extend the model to take into account changing population sizes, which result from the antagonistic nature of the interaction and follow the Lotka-Volterra equations. Under this extension, the population dynamics become most complex as the model moves away from pure matching-allele and becomes more gene-for-gene-like. While the population densities oscillate with a single oscillation frequency in the pure matching-allele model, a second oscillation frequency arises under gene-for-gene-like conditions. These observations hold for general interaction parameters and allow to infer generic patterns of the dynamics. Our results suggest that experimentally inferred dynamical patterns of host-parasite coevolution should typically be much more complex than the popular illustrations of Red Queen dynamics. A single parasite that infects more than one host can substantially alter the cyclic dynamics

Lotka–Volterra dynamics kills the Red Queen: population size fluctuations and associated stochasticity dramatically change host-parasite coevolution

Background: Host-parasite coevolution is generally believed to follow Red Queen dynamics consisting of ongoing oscillations in the frequencies of interacting host and parasite alleles. This belief is founded on previous theoretical work, which assumes infinite or constant population size. To what extent are such sustained oscillations realistic? Results: Here, we use a related mathematical modeling approach to demonstrate that ongoing Red Queen dynamics is unlikely. In fact, they collapse rapidly when two critical pieces of realism are acknowledged: (i) population size fluctuations, caused by the antagonism of the interaction in concordance with the Lotka-Volterra relationship; and (ii) stochasticity, acting in any finite population. Together, these two factors cause fast allele fixation. Fixation is not restricted to common alleles, as expected from drift, but also seen for originally rare alleles under a wide parameter space, potentially facilitating spread of novel variants. Conclusion: Our results call for a paradigm shift in our understanding of host-parasite coevolution, strongly suggesting that these are driven by recurrent selective sweeps rather than continuous allele oscillations

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

Compensatory mutations modulate the competitiveness and dynamics of plasmid-mediated colistin resistance in Escherichia coli clones

The emergence of mobile colistin resistance (mcr) threatens to undermine the clinical efficacy of the last antibiotic that can be used to treat serious infections caused by Gram-negative pathogens. Here we measure the fitness cost of a newly discovered MCR-3 using in vitro growth and competition assays. mcr-3 expression confers a lower fitness cost than mcr-1, as determined by competitive ability and cell viability. Consistent with these findings, plasmids carrying mcr-3 have higher stability than mcr-1 plasmids across a range of Escherichia coli strains. Crucially, mcr-3 plasmids can stably persist, even in the absence of colistin. Recent compensatory evolution has helped to offset the cost of mcr-3 expression, as demonstrated by the high fitness of mcr-3.5 as opposed to mcr-3.1. Reconstructing all of the possible evolutionary trajectories from mcr-3.1 to mcr-3.5 reveals a complex fitness landscape shaped by negative epistasis between compensatory and neutral mutations. Our findings highlight the importance of fitness costs and compensatory evolution in driving the dynamics and stability of mobile colistin resistance in bacterial populations, and they highlight the need to understand how processes (other than colistin use) impact mcr dynamics

Balancing mcr-1 expression and bacterial survival is a delicate equilibrium between essential cellular defence mechanisms

MCR-1 is a lipid A modifying enzyme that confers resistance to the antibiotic colistin. Here, we analyse the impact of MCR-1 expression on E. coli morphology, fitness, competitiveness, immune stimulation and virulence. Increased expression of mcr-1 results in decreased growth rate, cell viability, competitive ability and significant degradation in cell membrane and cytoplasmic structures, compared to expression of catalytically inactive MCR-1 (E246A) or MCR-1 soluble component. Lipopolysaccharide (LPS) extracted from mcr-1 strains induces lower production of IL-6 and TNF, when compared to control LPS. Compared to their parent strains, high-level colistin resistance mutants (HLCRMs) show reduced fitness (relative fitness is 0.41–0.78) and highly attenuated virulence in a Galleria mellonella infection model. Furthermore, HLCRMs are more susceptible to most antibiotics than their respective parent strains. Our results show that the bacterium is challenged to find a delicate equilibrium between expression of MCR-1-mediated colistin resistance and minimalizing toxicity and thus ensuring cell survival

Understanding the role of eco-evolutionary feedbacks in host-parasite coevolution

It is widely recognised that eco-evolutionary feedbacks can have important implications for evolution. However, many models of host-parasite coevolution omit eco-evolutionary feedbacks for the sake of simplicity, typically by assuming the population sizes of both species are constant. It is often difficult to determine whether the results of these models are qualitatively robust if eco-evolutionary feedbacks are included. Here, by allowing interspecific encounter probabilities to depend on population densities without otherwise varying the structure of the models, we provide a simple method that can test whether eco-evolutionary feedbacks per se affect evolutionary outcomes. Applying this approach to explicit genetic and quantitative trait models from the literature, our framework shows that qualitative changes to the outcome can be directly attributable to eco-evolutionary feedbacks. For example, shifting the dynamics between stable monomorphism or polymorphism and cycling, as well as changing the nature of the cycles. Our approach, which can be readily applied to many different models of host-parasite coevolution, offers a straightforward method for testing whether eco-evolutionary feedbacks qualitatively change coevolutionary outcomes

Daphnia parasite dynamics across multiple Caullerya epidemics indicate selection against common parasite genotypes

Studies of parasite population dynamics in natural systems are crucial for our understanding of host–parasite coevolutionary processes. Some field studies have reported that host genotype frequencies in natural populations change over time according to parasite-driven negative frequency-dependent selection. However, the temporal patterns of parasite genotypes have rarely been investigated. Moreover, parasite-driven negative frequency-dependent selection is contingent on the existence of genetic specificity between hosts and parasites. In the present study, the population dynamics and host-genotype specificity of the ichthyosporean Caullerya mesnili, a common endoparasite of Daphnia water fleas, were analysed based on the observed sequence variation in the first internal transcribed spacer (ITS1) of the ribosomal DNA. The Daphnia population of lake Greifensee (Switzerland) was sampled and subjected to parasite screening and host genotyping during C. mesnili epidemics of four consecutive years. The ITS1 of wild-caught C. mesnili-infected Daphnia was sequenced using the 454 pyrosequencing platform. The relative frequencies of C. mesnili ITS1 sequences differed significantly among years: the most abundant C. mesnili ITS1 sequence decreased and rare sequences increased over the course of the study, a pattern consistent with negative frequency-dependent selection. However, only a weak signal of host-genotype specificity between C. mesnili and Daphnia genotypes was detected. Use of cutting edge genomic techniques will allow further investigation of the underlying micro-evolutionary relationships within the Daphnia–C. mesnili system