A rugged yet easily navigable fitness landscape.

Fitness landscape theory predicts that rugged landscapes with multiple peaks impair Darwinian evolution, but experimental evidence is limited. In this study, we used genome editing to map the fitness of >260,000 genotypes of the key metabolic enzyme dihydrofolate reductase in the presence of the antibiotic trimethoprim, which targets this enzyme. The resulting landscape is highly rugged and harbors 514 fitness peaks. However, its highest peaks are accessible to evolving populations via abundant fitness-increasing paths. Different peaks share large basins of attraction that render the outcome of adaptive evolution highly contingent on chance events. Our work shows that ruggedness need not be an obstacle to Darwinian evolution but can reduce its predictability. If true in general, the complexity of optimization problems on realistic landscapes may require reappraisal.

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.

Efflux pump activity potentiates the evolution of antibiotic resistance across S. aureus isolates.

The rise of antibiotic resistance in many bacterial pathogens has been driven by the spread of a few successful strains, suggesting that some bacteria are genetically pre-disposed to evolving resistance. Here, we test this hypothesis by challenging a diverse set of 222 isolates of Staphylococcus aureus with the antibiotic ciprofloxacin in a large-scale evolution experiment. We find that a single efflux pump, norA, causes widespread variation in evolvability across isolates. Elevated norA expression potentiates evolution by increasing the fitness benefit provided by DNA topoisomerase mutations under ciprofloxacin treatment. Amplification of norA provides a further mechanism of rapid evolution in isolates from the CC398 lineage. Crucially, chemical inhibition of NorA effectively prevents the evolution of resistance in all isolates. Our study shows that pre-existing genetic diversity plays a key role in shaping resistance evolution, and it may be possible to predict which strains are likely to evolve resistance and to optimize inhibitor use to prevent this outcome.

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.

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

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.

Identifying and exploiting genes that potentiate the evolution of antibiotic resistance.

There is an urgent need to develop novel approaches for predicting and preventing the evolution of antibiotic resistance. Here, we show that the ability to evolve de novo resistance to a clinically important ß-lactam antibiotic, ceftazidime, varies drastically across the genus Pseudomonas. This variation arises because strains possessing the ampR global transcriptional regulator evolve resistance at a high rate. This does not arise because of mutations in ampR. Instead, this regulator potentiates evolution by allowing mutations in conserved peptidoglycan biosynthesis genes to induce high levels of ß-lactamase expression. Crucially, blocking this evolutionary pathway by co-administering ceftazidime with the ß-lactamase inhibitor avibactam can be used to eliminate pathogenic P. aeruginosa populations before they can evolve resistance. In summary, our study shows that identifying potentiator genes that act as evolutionary catalysts can be used to both predict and prevent the evolution of antibiotic resistance.

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.

Host-parasite coevolution: why changing population size matters.

Host-parasite coevolution is widely assumed to have a major influence on biological evolution, especially as these interactions impose high selective pressure on the reciprocally interacting antagonists. The exact nature of the underlying dynamics is yet under debate and may be determined by recurrent selective sweeps (i.e., arms race dynamics), negative frequency-dependent selection (i.e., Red Queen dynamics), or a combination thereof. These interactions are often associated with reciprocally induced changes in population size, which, in turn, should have a strong impact on co-adaptation processes, yet are neglected in most current work on the topic. Here, we discuss potential consequences of temporal variations in population size on host-parasite coevolution. The limited empirical data available and the current theoretical literature in this field highlight that the consideration of such interaction-dependent population size changes is likely key for the full understanding of the coevolutionary dynamics, and, thus, a more realistic view on the complex nature of species interactions.

Host-parasite coevolution in populations of constant and variable size.

BACKGROUND: The matching-allele and gene-for-gene models are widely used in mathematical 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. RESULTS: 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. CONCLUSION: 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.

Host-Pathogen Coevolution: The Selective Advantage of Bacillus thuringiensis Virulence and Its Cry Toxin Genes.

Reciprocal coevolution between host and pathogen is widely seen as a major driver of evolution and biological innovation. Yet, to date, the underlying genetic mechanisms and associated trait functions that are unique to rapid coevolutionary change are generally unknown. We here combined experimental evolution of the bacterial biocontrol agent Bacillus thuringiensis and its nematode host Caenorhabditis elegans with large-scale phenotyping, whole genome analysis, and functional genetics to demonstrate the selective benefit of pathogen virulence and the underlying toxin genes during the adaptation process. We show that: (i) high virulence was specifically favoured during pathogen-host coevolution rather than pathogen one-sided adaptation to a nonchanging host or to an environment without host; (ii) the pathogen genotype BT-679 with known nematocidal toxin genes and high virulence specifically swept to fixation in all of the independent replicate populations under coevolution but only some under one-sided adaptation; (iii) high virulence in the BT-679-dominated populations correlated with elevated copy numbers of the plasmid containing the nematocidal toxin genes; (iv) loss of virulence in a toxin-plasmid lacking BT-679 isolate was reconstituted by genetic reintroduction or external addition of the toxins. We conclude that sustained coevolution is distinct from unidirectional selection in shaping the pathogen's genome and life history characteristics. To our knowledge, this study is the first to characterize the pathogen genes involved in coevolutionary adaptation in an animal host-pathogen interaction system.

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.