Testing optimality with experimental evolution: lysis time in a bacteriophage

Optimality models collapse the vagaries of genetics into simple trade-offs to calculate phenotypes expected to evolve by natural selection. Optimality approaches are commonly criticized for this neglect of genetic details, but resolution of this disagreement has been difficult. The importance of genetic details may be tested by experimental evolution of a trait for which an optimality model exists and in which genetic details can be studied. Here we evolved lysis time in bacteriophage T7, a virus of Escherichia coli. Lysis time is equivalent to the age of reproduction in an organism that reproduces once and then dies. Delaying lysis increases the number of offspring but slows generation time, and this trade-off renders the optimum sensitive to environmental conditions: earlier lysis is favored when bacterial hosts are dense, later lysis is favored when hosts are sparse. In experimental adaptations, T7 evolved close to the optimum in conditions favoring early lysis but not in conditions favoring late lysis. One of the late lysis adaptations exhibited no detectable phenotypic evolution despite genetic evolution; the other evolved only partly toward the expected optimum. Overall, the lysis time of the adapted phages remained closer to their starting values than predicted by the model. From the perspective of the optimality model, the experimental conditions were expected to select changes only along the postulated trade-off, but a trait outside the trade-off evolved as well. Evidence suggests that the model's failure ultimately stems from a violation of the trade-off, rather than a paucity of mutations.     

Evolutionary Robustness of an Optimal Phenotype: Re-evolution of Lysis in a Bacteriophage Deleted for Its Lysin Gene

Optimality models are frequently used to create expectations about phenotypic evolution based on the fittest possible phenotype. However, they often ignore genetic details, which could confound these expectations. We experimentally analyzed the ability of organisms to evolve towards an optimum in an experimentally tractable system, lysis time in bacteriophage T7. T7 lysozyme helps lyse the host cell by degrading its cell wall at the end of infection, allowing viral escape to infect new hosts. Artificial deletion of lysozyme greatly reduced fitness and delayed lysis, but after evolution both phenotypes approached wild-type values. Phage with a lysis-deficient lysozyme evolved similarly. Several mutations were involved in adaptation, but most of the change in lysis timing and fitness increase was mediated by changes in gene 16, an internal virion protein not formerly considered to play a role in lysis. Its muralytic domain, which normally aids genome entry through the cell wall, evolved to cause phage release. Theoretical models suggest there is an optimal lysis time, and lysis more rapid or delayed than this optimum decreases fitness. Artificially constructed lines with very rapid lysis had lower fitness than wild-type T7, in accordance with the model. However, while a slow-lysing line also had lower fitness than wild-type, this low fitness resulted at least partly from genetic details that violated model assumptions.     

Host availability and the evolution of parasite life-history strategies

Parasites exploit an inherently patchy resource, their hosts, which are discrete entities that may only be available for infection within a relatively short time window. However, there has been little consideration of how heterogeneities in host availability may affect the phenotypic or genotypic composition of parasite populations or how parasites may evolve to cope with them. Here we conduct a selection experiment involving an entomopathogenic nematode (Steinernema feltiae) and show for the first time that the infection rate of a parasite can evolve rapidly to maximize the chances of infecting within an environment characterized by the rate of host availability. Furthermore, we show that the parasite's infection rate trades off with other fitness traits, such as fecundity and survival. Crucially, the outcome of competition between strains with different infection strategies depends on the rate of host availability; frequently available hosts favor "fast" infecting nematodes, whereas infrequently available hosts favor "slow" infecting nematodes. A simple evolutionarily stable strategy (ESS) analysis based on classic epidemiological models fails to capture this behavior, predicting instead that the fastest infecting phenotype should always dominate. However, a novel model incorporating more realistic, discrete bouts of host availability shows that strain coexistence is highly likely. Our results demonstrate that heterogeneities in host availability play a key role in the evolution of parasite life-history traits and in the maintenance of phenotypic variability. Parasite life-history strategies are likely to evolve rapidly in response to changes in host availability induced by disease management programs or by natural dynamics in host abundance. Incorporating parasite evolution in response to host availability would therefore enhance the predictive ability of current epidemiological models of infectious disease.     

The evolution of social interactions changes predictions about interacting phenotypes

In many traits involved in social interactions, such as courtship and aggression, the phenotype is an outcome of interactions between individuals. Such traits whose expression in an individual is partly determined by the phenotype of its social partner are called "interacting phenotypes." Quantitative genetic models suggested that interacting phenotypes can evolve much faster than nonsocial traits. Current models, however, consider the interaction between phenotypes of social partners as a fixed phenotypic response rule, represented by an interaction coefficient (ψ). Here, we extend existing theoretical models and incorporate the interaction coefficient as a trait that can evolve. We find that the evolution of the interaction coefficient can change qualitatively the predictions about the rate and direction of evolution of interacting phenotypes. We argue that it is crucial to determine whether and how the phenotypic response of an individual to its social partner can evolve to make accurate predictions about the evolution of traits involved in social interactions.     

Erratum: Causes and Consequences of Bacteriophage Diversification via Genetic Exchanges across Lifestyles and Bacterial Taxa

Bacteriophages (phages) evolve rapidly by acquiring genes from other phages. This results in mosaic genomes. Here, we identify numerous genetic transfers between distantly related phages and aim at understanding their frequency, consequences, and the conditions favoring them. Gene flow tends to occur between phages that are enriched for recombinases, transposases, and nonhomologous end joining, suggesting that both homologous and illegitimate recombination contribute to gene flow. Phage family and host phyla are strong barriers to gene exchange, but phage lifestyle is not. Even if we observe four times more recent transfers between temperate phages than between other pairs, there is extensive gene flow between temperate and virulent phages, and between the latter. These predominantly involve virulent phages with large genomes previously classed as low gene flux, and lead to the preferential transfer of genes encoding functions involved in cell energetics, nucleotide metabolism, DNA packaging and injection, and virion assembly. Such exchanges may contribute to the observed twice larger genomes of virulent phages. We used genetic transfers, which occur upon coinfection of a host, to compare phage host range. We found that virulent phages have broader host ranges and can mediate genetic exchanges between narrow host range temperate phages infecting distant bacterial hosts, thus contributing to gene flow between virulent phages, as well as between temperate phages. This gene flow drastically expands the gene repertoires available for phage and bacterial evolution, including the transfer of functional innovations across taxa.     

Optimal foraging predicts the ecology but not the evolution of host specialization in bacteriophages

We explore the ability of optimal foraging theory to explain the observation among marine bacteriophages that host range appears to be negatively correlated with host abundance in the local marine environment. We modified Charnov's classic diet composition model to describe the ecological dynamics of the related generalist and specialist bacteriophages phiX174 and G4, and confirmed that specialist phages are ecologically favored only at high host densities. Our modified model accurately predicted the ecological dynamics of phage populations in laboratory microcosms, but had only limited success predicting evolutionary dynamics. We monitored evolution of attachment rate, the phenotype that governs diet breadth, in phage populations adapting to both low and high host density microcosms. Although generalist phiX174 populations evolved even broader diets at low host density, they did not show a tendency to evolve the predicted specialist foraging strategy at high host density. Similarly, specialist G4 populations were unable to evolve the predicted generalist foraging strategy at low host density. These results demonstrate that optimal foraging models developed to explain the behaviorally determined diets of predators may have only limited success predicting the genetically determined diets of bacteriophage, and that optimal foraging probably plays a smaller role than genetic constraints in the evolution of host specialization in bacteriophages.     

Parasite host range and the evolution of host resistance

Parasite host range plays a pivotal role in the evolution and ecology of hosts and the emergence of infectious disease. Although the factors that promote host range and the epidemiological consequences of variation in host range are relatively well characterized, the effect of parasite host range on host resistance evolution is less well understood. In this study, we tested the impact of parasite host range on host resistance evolution. To do so, we used the host bacterium Pseudomonas fluorescens SBW25 and a diverse suite of coevolved viral parasites (lytic bacteriophage Φ2) with variable host ranges (defined here as the number of host genotypes that can be infected) as our experimental model organisms. Our results show that resistance evolution to coevolved phages occurred at a much lower rate than to ancestral phage (approximately 50% vs. 100%), but the host range of coevolved phages did not influence the likelihood of resistance evolution. We also show that the host range of both single parasites and populations of parasites does not affect the breadth of the resulting resistance range in a naïve host but that hosts that evolve resistance to single parasites are more likely to resist other (genetically) more closely related parasites as a correlated response. These findings have important implications for our understanding of resistance evolution in natural populations of bacteria and viruses and other host–parasite combinations with similar underlying infection genetics, as well as the development of phage therapy.     

Genetic details, optimization and phage life histories

Optimality models assume that phenotypes evolve by natural selection largely independently of underlying genetic mechanisms. This neglect of genetic mechanisms is considered an advantage by some evolutionary biologists but a fatal flaw by others. The controversy has gone unresolved, in part, from a lack of complex phenotypes that meet optimality criteria and for which the underlying genetic mechanisms are known. Here, we look at both perspectives for lysis time in bacteriophages. We find that the basic assumptions of the optimality model are compatible with the genetic details, but the optimality model is limited in its ability to accommodate lysis time plasticity because the mechanistic underpinnings of plasticity are poorly known.     

The genetic architecture of ecological specialization: correlated gene effects on host use and habitat choice in pea aphids

Genetic correlations among phenotypic characters result when two traits are influenced by the same genes or sets of genes. By reducing the degree to which traits in two environments can evolve independently (e.g., Lande 1979; Via and Lande 1985), such correlations are likely to play a central role in both the evolution of ecological specialization and in its link to speciation. For example, negative genetic correlations between fitness traits in different environments (i.e., genetic trade-offs) are thought to influence the evolution of specialization, while positive genetic correlations between performance and characters influencing assortative mating can accelerate the evolution of reproductive isolation between ecologically specialized populations. We first discuss how the genetic architecture of a suite of traits may affect the evolutionary role of genetic correlations among them and review how the mechanisms of correlations can be analyzed using quantitative trait locus (QTL) mapping. We then consider the implications of such data for understanding the evolution of specialization and its link to speciation. We illustrate this approach with a QTL analysis of key characters in two races of pea aphids that are highly specialized on different host plants and partially reproductively isolated. Our results suggest that antagonism among QTL effects on performance in the two environments leads to a genetic trade-off in this system. We also found evidence for parallel QTL effects on host-plant acceptance and fecundity on the accepted host, which could produce assortative mating. These results suggest that the genetic architecture of traits associated with host use may have played a central role in the evolution of specialization and reproductive isolation in pea aphids.     

The genera of bacteriophages and their receptors are the major determinants of host range

The host range of phages is a key to understand their impact on bacterial ecology and evolution. Because of the complexity of phage–host interactions, the variables that determine the breadth of a phage host range remain poorly understood. Here, we propose a novel holistic approach to identify the host range determinants of a new collection of phages infecting Salmonella, isolated from animal, environmental and wastewater samples that were able to infect 58 of the 71 Salmonella strains in our collection. By using a set of statistic approaches (non-metric dimensional scaling, Bray–Curtis distance, PERMANOVA), we analysed phenotypic (host range on wild-type and receptor mutants) and genetic data (taxonomic assignment and receptor binding proteins) to evaluate the impact of isolation strain and niche, phage receptor and genus on the host range. Statistical analysis revealed that two phage characteristics influence the host range by explaining the most variance: the receptor by 45% and the genus by 51%. Interestingly, phage genus and receptor in combination explained 79% of the variance, establishing these characteristics as the major determinants of the host range. This study demonstrates the power and the novelty of applying statistical approaches to phenotypic and genetic data to investigate the ecology of phage–host interactions.     

Developmental interactions and the constituents of quantitative variation

Development is the process by which genotypes are transformed into phenotypes. Consequently, development determines the relationship between allelic and phenotypic variation in a population and, therefore, the patterns of quantitative genetic variation and covariation of traits. Understanding the developmental basis of quantitative traits may lead to insights into the origin and evolution of quantitative genetic variation, the evolutionary fate of populations, and, more generally, the relationship between development and evolution. Herein, we assume a hierarchical, modular structure of trait development and consider how epigenetic interactions among modules during ontogeny affect patterns of phenotypic and genetic variation. We explore two developmental models, one in which the epigenetic interactions between modules result in additive effects on character expression and a second model in which these epigenetic interactions produce nonadditive effects. Using a phenotype landscape approach, we show how changes in the developmental processes underlying phenotypic expression can alter the magnitude and pattern of quantitative genetic variation. Additive epigenetic effects influence genetic variances and covariances, but allow trait means to evolve independently of the genetic variances and covariances, so that phenotypic evolution can proceed without changing the genetic covariance structure that determines future evolutionary response. Nonadditive epigenetic effects, however, can lead to evolution of genetic variances and covariances as the mean phenotype evolves. Our model suggests that an understanding of multivariate evolution can be considerably enriched by knowledge of the mechanistic basis of character development.     

Understanding the evolution and stability of the G-matrix

The G-matrix summarizes the inheritance of multiple, phenotypic traits. The stability and evolution of this matrix are important issues because they affect our ability to predict how the phenotypic traits evolve by selection and drift. Despite the centrality of these issues, comparative, experimental, and analytical approaches to understanding the stability and evolution of the G-matrix have met with limited success. Nevertheless, empirical studies often find that certain structural features of the matrix are remarkably constant, suggesting that persistent selection regimes or other factors promote stability. On the theoretical side, no one has been able to derive equations that would relate stability of the G-matrix to selection regimes, population size, migration, or to the details of genetic architecture. Recent simulation studies of evolving G-matrices offer solutions to some of these problems, as well as a deeper, synthetic understanding of both the G-matrix and adaptive radiations.     

Genotypic and phenotypic variation in transmission traits of a complex life cycle parasite

Characterizing genetic variation in parasite transmission traits and its contribution to parasite vigor is essential for understanding the evolution of parasite life‐history traits. We measured genetic variation in output, activity, survival, and infection success of clonal transmission stages (cercaria larvae) of a complex life cycle parasite (Diplostomum pseudospathaceum). We further tested if variation in host nutritional stage had an effect on these traits by keeping hosts on limited or ad libitum diet. The traits we measured were highly variable among parasite genotypes indicating significant genetic variation in these life‐history traits. Traits were also phenotypically variable, for example, there was significant variation in the measured traits over time within each genotype. However, host nutritional stage had no effect on the parasite traits suggesting that a short‐term reduction in host resources was not limiting the cercarial output or performance. Overall, these results suggest significant interclonal and phenotypic variation in parasite transmission traits that are not affected by host nutritional status.     

Bacteriophage adsorption rate and optimal lysis time

The first step of bacteriophage (phage) infection is the attachment of the phage virion onto a susceptible host cell. This adsorption process is usually described by mass-action kinetics, which implicitly assume an equal influence of host density and adsorption rate on the adsorption process. Therefore, an environment with high host density can be considered as equivalent to a phage endowed with a high adsorption rate, and vice versa. On the basis of this assumption, the effect of adsorption rate on the evolution of phage optimal lysis time can be reinterpreted from previous optimality models on the evolution of optimal lysis time. That is, phage strains with a higher adsorption rate would have a shorter optimal lysis time and vice versa. Isogenic phage lambda-strains with different combinations of six different lysis times (ranging from 29.3 to 68 min), two adsorption rates (9.9 x 10(-9) and 1.3 x 10(-9) phage(-1) cell(-1) ml(-1) min(-1)), and two markers (resulting in "blue" or "white" plaques) were constructed. Various pairwise competitions among these strains were conducted to test the model prediction. As predicted by the reinterpreted model, the results showed that the optimal lysis time is shorter for phage strains with a high adsorption rate and vice versa. Competition between high- and low-adsorption strains also showed that, under current conditions and phenotype configurations, the adsorption rate has a much larger impact on phage relative fitness than the lysis time.     

驯化噬菌体提高噬菌体对碳青霉烯类耐药肺炎克雷伯菌的杀菌能力

【目的】本研究旨在通过驯化提高噬菌体的裂解能力并降低其宿主菌耐受性产生的速度,从而提高对重要病原菌-碳青霉烯类耐药肺炎克雷伯菌(carbapenem-resistant Klebsiella pneumoniae, CRKp)的杀菌效果。【方法】以临床CRKp菌株Kp2092为宿主菌,利用双层琼脂平板法从污水中分离噬菌体并分析其裂解谱;对其中的广谱强裂解性噬菌体通过透射电镜观察其形态特征并进行全基因组测序;通过噬菌体-宿主连续培养进行噬菌体驯化,并比较驯化前后噬菌体生物学特性的差异。【结果】分离得到的9株肺炎克雷伯菌噬菌体中,噬菌体P55anc裂解能力强且裂解谱广,透射电镜观察发现其为短尾噬菌体。P55anc基因组全长40 301 bp,包含51个编码序列,其中27个具有已知功能,主要涉及核酸代谢、噬菌体结构蛋白、DNA包装和细胞裂解等。噬菌体P55anc经9 d的驯化后,得到3株驯化噬菌体。驯化后噬菌体杀菌能力增强,主要表现为细菌生长曲线显著下降、噬菌体暴发量增多、裂解谱扩大,且宿主菌对其产生抗性的概率显著降低。与此同时,驯化后的噬菌体在热处理、紫外暴露以及血清等环境下保持较好的稳定性。【结论】利用噬菌体-宿主连续培养的方法可对噬菌体进行驯化和筛选,驯化后的噬菌体杀菌效果更强,且在不同压力处理下的稳定性良好,而细菌产生噬菌体抗性的概率也降低。     

Parasite-host fitness trade-offs change with parasite identity: genotype-specific interactions in a plant-pathogen system

Simultaneous effects of host and parasite in determining quantitative traits of infection have long been neglected in theoretical and experimental investigations of host-parasite coevolution with the notable exception of gene-for-gene resistance studies. A cross-infection experiment, using five lines of the plant Arabidopsis thaliana and two strains of its oomycete pathogen Hyaloperonospora parasitica, revealed that three traits traditionally considered those of the parasite (number of infected leaves, transmission success, and time until 50% transmission), differed among specific combinations of host and parasite lines, being determined by the two protagonists of the infection. However, the two parasite strains did not differ significantly for most measured phenotypic traits of the infection. Globally, transmission increased with increasing virulence among the different host-parasite combinations, as assumed by most models of evolution of virulence. Surprisingly, however, there was no general relationship between parasite and host fitness, estimated respectively as transmission and seed production. Only one of the two strains showed the expected significant negative genetic correlation between these two variables. Our results thus highlight the importance of taking into account both host and parasite genetic variation because their interaction can lead to unexpected evolutionary outcomes.     

The coevolutionary dynamics of antagonistic interactions mediated by quantitative traits with evolving variances

Quantitative traits frequently mediate coevolutionary interactions between predator and prey or parasite and host. Previous efforts to understand and predict the coevolutionary dynamics of these interactions have generally assumed that standing genetic variation is fixed or absent altogether. We develop a genetically explicit model of coevolution that bridges the gap between these approaches by allowing genetic variation itself to evolve. Analysis of this model shows that the evolution of genetic variance has important consequences for the dynamics and outcome of coevolution. Of particular importance is our demonstration that coevolutionary cycles can emerge in the absence of stabilizing selection, an outcome not possible in previous models of coevolution mediated by quantitative traits. Whether coevolutionary cycles evolve depends upon the strength of selection, the number of loci, and the rate of mutation in each of the interacting species. Our results also generate novel predictions for the expected sign and magnitude of linkage disequilibria in each species.     

Bacteria-phage coevolution and the emergence of generalist pathogens

Understanding the genetic constraints on pathogen evolution will help to predict the emergence of generalist pathogens that can infect a range of different host genotypes. Here we show that generalist viral pathogens are more likely to emerge during coevolution between the bacterium Pseudomonas fluorescens and the lytic phage SBW25Φ2 than when the same pathogen is challenged to adapt to a nonevolving population of novel hosts. When phages were able to adapt to nonevolving novel hosts, the resulting phenotypes had relatively narrow host ranges compared with coevolved phages. Evolved (rather than coevolved) phages also had lower virulence, although they attained virulence similar to that of coevolved phages after continued adaptation to a nonevolving population of the same host. We explain these results by using sequence data showing that the evolution of broad host range is associated with several different amino acid substitutions and therefore occurs only through repeated rounds of selection for novel infectivity alleles. These findings suggest that generalist bacteriophages are more likely to emerge through long-term coevolution with their hosts than through spontaneous adaptation to a single novel host. These results are likely to be relevant to host-parasite systems where parasite generalism can evolve through the acquisition of multiple mutations or alleles, as appears to be the case for many plant-bacteria and bacteria-virus interactions.     

Evolution in heterogeneous environments and the potential of maintenance of genetic variation in traits of adaptive significance

The maintenance of genetic variation in traits of adaptive significance has been a major dilemma of evolutionary biology. Considering the pattern of increased genetic variation associated with environmental clines and heterogeneous environments, selection in heterogeneous environments has been proposed to facilitate the maintenance of genetic variation. Some models examining whether genetic variation can be maintained, in heterogeneous environments are reviewed. Genetic mechanisms that constrain evolution in quantitative genetic traits indicate that genetic variation can be maintained but when is not clear. Furthermore, no comprehensive models have been developed, likely due to the genetic and environmental complexity of this issue. Therefore, I have suggested two empirical approaches to provide insight for future theoretical and empirical research. Traditional path analysis has been a very powerful approach for understanding phenotypic selection. However, it requires substantial information on the biology of the study system to construct a causal model and alternatives. Exploratory path analysis is a data driven approach that uses the statistical relationships in the data to construct a set of models. For example, it can be used for understanding phenotypic selection in different environments, where there is no prior information to develop path models in the different environments. Data from Brassica rapa grown in different nutrients indicated that selection changed in the different environments. Experimental evolutionary studies will provide direct tests as to when genetic variation is maintained.     

EVOLVABILITY OF INDIVIDUAL TRAITS IN A MULTIVARIATE CONTEXT: PARTITIONING THE ADDITIVE GENETIC VARIANCE INTO COMMON AND SPECIFIC COMPONENTS

Genetic covariation among multiple traits will bias the direction of evolution. Although a trait's phenotypic context is crucial for understanding evolutionary constraints, the evolutionary potential of one (focal) trait, rather than the whole phenotype, is often of interest. The extent to which a focal trait can evolve independently depends on how much of the genetic variance in that trait is unique. Here, we present a hypothesis‐testing framework for estimating the genetic variance in a focal trait that is independent of variance in other traits. We illustrate our analytical approach using two Drosophila bunnanda trait sets: a contact pheromone system comprised of cuticular hydrocarbons (CHCs), and wing shape, characterized by relative warps of vein position coordinates. Only 9% of the additive genetic variation in CHCs was trait specific, suggesting individual traits are unlikely to evolve independently. In contrast, most (72%) of the additive genetic variance in wing shape was trait specific, suggesting relative warp representations of wing shape could evolve independently. The identification of genetic variance in focal traits that is independent of other traits provides a way of studying the evolvability of individual traits within the broader context of the multivariate phenotype.