Evolvability of an RNA virus is determined by its mutational neighbourhood

Quasispecies Dynamics of RNA Viruses

RNA viruses, such as human immunodeficiency virus, hepatitis C virus, influenza virus, and poliovirus replicate with very high mutation rates and exhibit very high genetic diversity. The extremely high genetic diversity of RNA virus populations originates that they replicate as complex mutant spectra known as viral quasispecies. The quasispecies dynamics of RNA viruses are closely related to viral pathogenesis and disease, and antiviral treatment strategies. Over the past several decades, the quasispecies concept has been expanded to provide an adequate framework to explain complex behavior of RNA virus populations. Recently, the quasispecies concept has been used to study other complex biological systems, such as tumor cells, bacteria, and prions. Here, we focus on some questions regarding viral and theoretical quasispecies concepts, as well as more practical aspects connected to pathogenesis and resistance to antiviral treatments. A better knowledge of virus diversification and evolution may be critical in preventing and treating the spread of pathogenic viruses.

Advances in plant virus evolution: translating evolutionary insights into better disease management

Recent studies in plant virus evolution are revealing that genetic structure and behavior of virus and viroid populations can explain important pathogenic properties of these agents, such as host resistance breakdown, disease severity, and host shifting, among others. Genetic variation is essential for the survival of organisms. The exploration of how these subcellular parasites generate and maintain a certain frequency of mutations at the intra- and inter-host levels is revealing novel molecular virus-plant interactions. They emphasize the role of host environment in the dynamic genetic composition of virus populations. Functional genomics has identified host factors that are transcriptionally altered after virus infections. The analyses of these data by means of systems biology approaches are uncovering critical plant genes specifically targeted by viruses during host adaptation. Also, a next-generation resequencing approach of a whole virus genome is opening new avenues to study virus recombination and the relationships between intra-host virus composition and pathogenesis. Altogether, the analyzed data indicate that systematic disruption of some specific parameters of evolving virus populations could lead to more efficient ways of disease prevention, eradication, or tolerable virus-plant coexistence.

Interactions among flower-size QTL of Mimulus guttatus are abundant but highly variable in nature

The frequency and character of interactions among genes influencing complex traits remain unknown. Our ignorance is most acute for segregating variation within natural populations, the epistasis most relevant for quantitative trait evolution. Here, we report a comprehensive survey of interactions among a defined set of flower-size QTL: loci polymorphic within a single natural population of yellow monkeyflower (Mimulus guttatus). We find that epistasis is typical. Observed phenotypes routinely differ from those predicted on the basis of direct allelic affects in the isogenic background, although the direction of deviations is highly variable. Across QTL pairs, there are significantly positive and negative interactions for every trait. Across traits, specific locus pairs routinely exhibit both positive and negative interactions. There was a tendency for negative epistasis to accompany positive direct effects and vice versa for the trait of corolla width, which may be due, at least in part, to the fact that QTL were identified from their direct effects on this trait.

Effects of bacteriophage traits on plaque formation

Background

The appearance of plaques on a bacterial lawn is one of the enduring imageries in modern day biology. The seeming simplicity of a plaque has invited many hypotheses and models in trying to describe and explain the details of its formation. However, until now, there has been no systematic experimental exploration on how different bacteriophage (phage) traits may influence the formation of a plaque. In this study, we constructed a series of isogenic λ phages that differ in their adsorption rate, lysis timing, or morphology so that we can determine the effects if these changes on three plaque properties: size, progeny productivity, and phage concentration within plaques.

Results

We found that the adsorption rate has a diminishing, but negative impact on all three plaque measurements. Interestingly, there exists a concave relationship between the lysis time and plaque size, resulting in an apparent optimal lysis time that maximizes the plaque size. Although suggestive in appearance, we did not detect a significant effect of lysis time on plaque productivity. Nonetheless, the combined effects of plaque size and productivity resulted in an apparent convex relationship between the lysis time and phage concentration within plaques. Lastly, we found that virion morphology also affected plaque size. We compared our results to the available models on plaque size and productivity. For the models in their current forms, a few of them can capture the qualitative aspects of our results, but not consistently in both plaque properties.

Conclusions

By using a collection of isogenic phage strains, we were able to investigate the effects of individual phage traits on plaque size, plaque productivity, and average phage concentration in a plaque while holding all other traits constant. The controlled nature of our study allowed us to test several model predictions on plaque size and plaque productivity. It seems that a more realistic theoretical approach to plaque formation is needed in order to capture the complex interaction between phage and its bacterium host in a spatially restricted environment.

Impact of epistasis and pleiotropy on evolutionary adaptation

Evolutionary adaptation is often likened to climbing a hill or peak. While this process is simple for fitness landscapes where mutations are independent, the interaction between mutations (epistasis) as well as mutations at loci that affect more than one trait (pleiotropy) are crucial in complex and realistic fitness landscapes. We investigate the impact of epistasis and pleiotropy on adaptive evolution by studying the evolution of a population of asexual haploid organisms (haplotypes) in a model of N interacting loci, where each locus interacts with K other loci. We use a quantitative measure of the magnitude of epistatic interactions between substitutions, and find that it is an increasing function of K. When haplotypes adapt at high mutation rates, more epistatic pairs of substitutions are observed on the line of descent than expected. The highest fitness is attained in landscapes with an intermediate amount of ruggedness that balance the higher fitness potential of interacting genes with their concomitant decreased evolvability. Our findings imply that the synergism between loci that interact epistatically is crucial for evolving genetic modules with high fitness, while too much ruggedness stalls the adaptive process.

Negative epistasis between beneficial mutations in an evolving bacterial population

Epistatic interactions between mutations play a prominent role in evolutionary theories. Many studies have found that epistasis is widespread, but they have rarely considered beneficial mutations. We analyzed the effects of epistasis on fitness for the first five mutations to fix in an experimental population of Escherichia coli. Epistasis depended on the effects of the combined mutations--the larger the expected benefit, the more negative the epistatic effect. Epistasis thus tended to produce diminishing returns with genotype fitness, although interactions involving one particular mutation had the opposite effect. These data support models in which negative epistasis contributes to declining rates of adaptation over time. Sign epistasis was rare in this genome-wide study, in contrast to its prevalence in an earlier study of mutations in a single gene.

Adaptive landscapes in evolving populations of Pseudomonas fluorescens

The repeatability of adaptive evolution depends on the ruggedness of the underlying adaptive landscape. We contrasted the relative ruggedness of two adaptive landscapes by measuring the variance in fitness and metabolic phenotype within and among genetically distinct strains of Pseudomonas fluorescens in two environments differing only in the carbon source provided (glucose vs. xylose). Fitness increased in all lines, plateauing in one environment but not the other. The pattern of variance in fitness among replicate lines was unique to the selection environment; it increased over the course of the experiment in xylose but not in glucose. Metabolic phenotypes displayed two results: (1) populations adapted via changes that were distinctive to their selection environment, and (2) endpoint phenotypes were less variable in glucose than in xylose. These results indicate that although the response to selection is highly repeatable at the level of fitness, the underlying genetic routes taken were different for each environment and more variable in xylose. We suggest that this reflects a more rugged adaptive landscape in xylose compared to glucose. Our study demonstrates the utility of using replicate selection lines with different evolutionary starting points to try and quantify the relative ruggedness of adaptive landscapes.

Fitness recovery and compensatory evolution in natural mutant lines of C. elegans

Deleterious mutation accumulation plays a central role in evolutionary genetics, conservation biology, human health, and evolutionary medicine (e.g., methods of viral attenuation for live vaccines). It is therefore important to understand whether and how quickly populations with accumulated deleterious mutational loads can recover fitness through adaptive evolution. We used laboratory experimental evolution with four long-term mutation-accumulation (MA) lines of Caenorhabditis elegans nematodes to study the dynamics of such fitness evolution. We previously showed that when homozygous mutant populations are evolved in large population sizes, they can rapidly achieve wild-type fitness through the accumulation of new beneficial or compensatory epistatic mutations. Here, we expand this approach to demonstrate that when replicate lineages are initiated from the same mutant genotype, phenotypic evolution is only sometimes repeatable. MA genotypes that recovered ancestral fitness in the previous experiment did not always do so here. Further, the pattern of adaptive evolution in independently evolved replicates was contingent upon the MA genotype and varied among fitness-related traits. Our findings suggest that new beneficial mutations can drive rapid fitness evolution, but that the adaptive process is rendered somewhat unpredictable by its susceptibility to chance events and sensitivity to the evolutionary history of the starting population.

Second-order selection for evolvability in a large Escherichia coli population

In theory, competition between asexual lineages can lead to second-order selection for greater evolutionary potential. To test this hypothesis, we revived a frozen population of Escherichia coli from a long-term evolution experiment and compared the fitness and ultimate fates of four genetically distinct clones. Surprisingly, two clones with beneficial mutations that would eventually take over the population had significantly lower competitive fitness than two clones with mutations that later went extinct. By replaying evolution many times from these clones, we showed that the eventual winners likely prevailed because they had greater potential for further adaptation. Genetic interactions that reduce the benefit of certain regulatory mutations in the eventual losers appear to explain, at least in part, why they were outcompeted.

Evolutionary advantage of small populations on complex fitness landscapes

Recent experimental and theoretical studies have shown that small asexual populations evolving on complex fitness landscapes may achieve a higher fitness than large ones due to the increased heterogeneity of adaptive trajectories. Here, we introduce a class of haploid three-locus fitness landscapes that allow the investigation of this scenario in a precise and quantitative way. Our main result derived analytically shows how the probability of choosing the path of the largest initial fitness increase grows with the population size. This makes large populations more likely to get trapped at local fitness peaks and implies an advantage of small populations at intermediate time scales. The range of population sizes where this effect is operative coincides with the onset of clonal interference. Additional studies using ensembles of random fitness landscapes show that the results achieved for a particular choice of three-locus landscape parameters are robust and also persist as the number of loci increases. Our study indicates that an advantage for small populations is likely whenever the fitness landscape contains local maxima. The advantage appears at intermediate time scales, which are long enough for trapping at local fitness maxima to have occurred but too short for peak escape by the creation of multiple mutants.

Error catastrophe for viruses infecting cells: analysis of the phase transition in terms of error classes

RNA viruses offer a very exciting arena in which to study evolution in 'real time' owing to both their high replication rate-many generations per day are possible-and their high mutation rate, leading to a large phenotypic variety. They can be regarded as a swarm of genetically related mutants around a dominant or master genetic sequence. This system is called a 'viral quasi-species'. Thus, a common framework to describe RNA viral dynamics is by means of the quasi-species equation (QSE). The QSE is in fact a system of a very large number of nonlinear coupled equations. Here, we consider a simpler formulation in terms of 'error classes', which groups all the sequences differing from the master sequence by the same number of genomic differences into one population class. From this, based on the analogies with Bose condensation, we use thermodynamic inspired observables to analyse and characterize the 'phase transition' through the so-called 'RNA virus error catastrophe'.

Haploids adapt faster than diploids across a range of environments

Despite a great deal of theoretical attention, we have limited empirical data about how ploidy influences the rate of adaptation. We evolved isogenic haploid and diploid populations of Saccharomyces cerevisiae for 200 generations in seven different environments. We measured the competitive fitness of all ancestral and evolved lines against a common competitor and find that in all seven environments, haploid lines adapted faster than diploids, significantly so in three environments. We apply theory that relates the rates of adaptation and measured effective population sizes to the properties of beneficial mutations. We obtained rough estimates of the average selection coefficients in haploids between 2% and 10% for these first selected mutations. Results were consistent with semi-dominant to dominant mutations in four environments and recessive to additive mutations in two other environments. These results are consistent with theory that predicts haploids should evolve faster than diploids at large population sizes.

Mutant spectra in virus behavior

RNA viruses replicate as complex mutant spectra, also termed ‘mutant clouds’, known as viral quasispecies. While this is a widely observed viral population structure, it is less known that a number of biologically relevant features of this important group of viral pathogens depend on (or are strongly influenced by) the complexity and composition of mutant spectra. Among them, fitness increase or decrease depending on intrapopulation complementation or interference, selection triggered by memory genomes, pathogenic potential of viruses, disease evolution and the response to antiviral treatments. Quasispecies represent the recognition of complex behavior in viruses, and it is an oversimplification to equate such a population structure with the classic polymorphism of population biology. Darwinian principles acting on genome collectivities that replicate with high error rates provide a unique population structure prone to flexible and largely unpredictable behavior.

Genetic architecture and the evolution of sex

Theoretical investigations of the advantages of sex have tended to treat the genetic architecture of organisms as static and have not considered that genetic architecture might coevolve with reproductive mode. As a result, some potential advantages of sex may have been missed. Using a gene network model, we recently showed that recombination imposes selection for robustness to mutation and that negative epistasis can evolve as a by-product of this selection. These results motivated a detailed exploration of the mutational deterministic hypothesis, a hypothesis in which the advantage of sex depends critically on epistasis. We found that sexual populations do evolve higher mean fitness and lower genetic load than asexual populations at equilibrium, and, under moderate stabilizing selection and large population size, these equilibrium sexual populations resist invasion by asexuals. However, we found no evidence that these long- and short-term advantages to sex were explained by the negative epistasis that evolved in our experiments. The long-term advantage of sex was that sexual populations evolved a lower deleterious mutation rate, but this property was not sufficient to account for the ability of sexual populations to resist invasion by asexuals. The ability to resist asexual invasion was acquired simultaneously with an increase in recombinational robustness that minimized the cost of sex. These observations provide the first direct evidence that sexual reproduction does indeed select for conditions that favor its own maintenance. Furthermore, our results highlight the importance of considering a dynamic view of the genetic architecture to understand the evolution of sex and recombination.

Evolutionary dynamics on strongly correlated fitness landscapes

We study the evolutionary dynamics of a maladapted population of self-replicating sequences on strongly correlated fitness landscapes. Each sequence is assumed to be composed of blocks of equal length and its fitness is given by a linear combination of four independent block fitnesses. A mutation affects the fitness contribution of a single block leaving the other blocks unchanged and hence inducing correlations between the parent and mutant fitness. On such strongly correlated fitness landscapes, we calculate the dynamical properties such as the number of jumps in the most populated sequence and the temporal distribution of the last jump, which is shown to exhibit an inverse square dependence as in evolution on uncorrelated fitness landscapes. We also obtain exact results for the distribution of records and extremes for correlated random variables.

Quasispecies theory and the behavior of RNA viruses

A large number of medically important viruses, including HIV, hepatitis C virus, and influenza, have RNA genomes. These viruses replicate with extremely high mutation rates and exhibit significant genetic diversity. This diversity allows a viral population to rapidly adapt to dynamic environments and evolve resistance to vaccines and antiviral drugs. For the last 30 years, quasispecies theory has provided a population-based framework for understanding RNA viral evolution. A quasispecies is a cloud of diverse variants that are genetically linked through mutation, interact cooperatively on a functional level, and collectively contribute to the characteristics of the population. Many predictions of quasispecies theory run counter to traditional views of microbial behavior and evolution and have profound implications for our understanding of viral disease. Here, we discuss basic principles of quasispecies theory and describe its relevance for our understanding of viral fitness, virulence, and antiviral therapeutic strategy.

Quasispecies-like behavior observed in catalytic RNA populations evolving in a test tube

BACKGROUND

During the RNA World, molecular populations were probably very small and highly susceptible to the force of strong random drift. In conjunction with Muller's Ratchet, this would have imposed difficulties for the preservation of the genetic information and the survival of the populations. Mechanisms that allowed these nascent populations to overcome this problem must have been advantageous.

RESULTS

Using continuous in vitro evolution experimentation with an increased mutation rate imposed by MnCl2, it was found that clonal 100-molecule populations of ribozymes clearly exhibit certain characteristics of a quasispecies. This is the first time this has been seen with a catalytic RNA. Extensive genotypic sampling from two replicate lineages was gathered and phylogenetic networks were constructed to elucidate the structure of the evolving RNA populations. A common distribution was found in which a mutant sequence was present at high frequency, surrounded by a cloud of mutant with lower frequencies. This is a typical distribution of quasispecies. Most of the mutants in these clouds were connected by short Hamming distance values, indicating their close relatedness.

CONCLUSIONS

The quasispecies nature of mutant RNA clouds facilitates the recovery of genotypes under pressure of being removed from the population by random drift. The empirical populations therefore evolved a genotypic resiliency despite a high mutation rate by adopting the characteristics of quasispecies, implying that primordial RNA pools could have used this strategy to avoid extinction.

Genomic evolution of vesicular stomatitis virus strains with differences in adaptability

Virus strains with a history of repeated genetic bottlenecks frequently show a diminished ability to adapt compared to strains that do not have such a history. These differences in adaptability suggest differences in either the rate at which beneficial mutations are produced, the effects of beneficial mutations, or both. We tested these possibilities by subjecting four populations (two controls and two mutants with lower adaptabilities) to multiple replicas of a regimen of positive selection and then determining the fitnesses of the progeny through time and the changes in the consensus, full-length sequences of 56 genomes. We observed that at a given number of passages, the overall fitness gains observed for control populations were larger than fitness gains in mutant populations. However, these changes did not correlate with differences in the numbers of mutations accumulated in the two types of genomes. This result is consistent with beneficial mutations having a lower beneficial effect on mutant strains. Despite the overall fitness differences, some replicas of one mutant strain at passage 50 showed fitness increases similar to those observed for the wild type. We hypothesized that these evolved, high-fitness mutants may have a lower robustness than evolved, high-fitness controls. Robustness is the ability of a virus to avoid phenotypic changes in the face of mutation. We confirmed our hypothesis in mutation-accumulation experiments that showed a normalized fitness loss that was significantly larger in mutant bottlenecked populations than in control populations.

Fitness epistasis and constraints on adaptation in a human immunodeficiency virus type 1 protein region

Fitness epistasis, the interaction among alleles at different loci in their effects on fitness, has potentially important consequences for adaptive evolution. We investigated fitness epistasis among amino acids of a functionally important region of the human immunodeficiency virus type 1 (HIV-1) exterior envelope glycoprotein (gp120). Seven mutations putatively involved in the adaptation of the second conserved to third variable protein region (C2-V3) to the use of an alternative host-cell chemokine coreceptor (CXCR4) for cell entry were engineered singly and in combinations on the wild-type genetic background and their effects on viral infectivity were measured. Epistasis was found to be common and complex, involving not only pairwise interactions, but also higher-order interactions. Interactions could also be surprisingly strong, changing fitness by more than 9 orders of magnitude, which is explained by some single mutations being practically lethal. A consequence of the observed epistasis is that many of the minimum-length mutational trajectories between the wild type and the mutant with highest fitness on cells expressing the alternative coreceptor are selectively inaccessible. These results may help explain the difficulty of evolving viruses that use the alternative coreceptor in culture and the delayed evolution of this phenotype in natural infection. Knowledge of common, complex, and strong fitness interactions among amino acids is necessary for a full understanding of protein evolution.

Escherichia coli rpoB mutants have increased evolvability in proportion to their fitness defects

Evolvability is the capacity of an organism or population for generating descendants with increased fitness. Simulations and comparative studies have shown that evolvability can vary among individuals and identified characteristics of genetic architectures that can promote evolvability. However, little is known about how the evolvability of biological organisms typically varies along a lineage at each mutational step in its history. Evolvability might increase upon sustaining a deleterious mutation because there are many compensatory paths in the fitness landscape to reascend the same fitness peak or because shifts to new peaks become possible. We use genetic marker divergence trajectories to parameterize and compare the evolvability—defined as the fitness increase realized by an evolving population initiated from a test genotype—of a series of Escherichia coli mutants on multiple timescales. Each mutant differs from a common progenitor strain by a mutation in the rpoB gene, which encodes the β subunit of RNA polymerase. Strains with larger fitness defects are proportionally more evolvable in terms of both the beneficial mutations accessible in their immediate mutational neighborhoods and integrated over evolutionary paths that traverse multiple beneficial mutations. Our results establish quantitative expectations for how a mutation with a given deleterious fitness effect should influence evolvability, and they will thus inform future studies of how deleterious, neutral, and beneficial mutations targeting other cellular processes impact the evolutionary potential of microorganisms.

Formal reasoning on qualitative models of coinfection of HIV and Tuberculosis and HAART therapy

BACKGROUND

Several diseases, many of which nowadays pandemic, consist of multifactorial pathologies. Paradigmatic examples come from the immune response to pathogens, in which cases the effects of different infections combine together, yielding complex mutual feedback, often a positive one that boosts infection progression in a scenario that can easily become lethal. HIV is one such infection, which weakens the immune system favouring the insurgence of opportunistic infections, amongst which Tuberculosis (TB). The treatment with antiretroviral therapies has shown effective in reducing mortality. An in-depth understanding of complex systems, like the one consisting of HIV, TB and related therapies, is an open great challenge, on the boundaries of bioinformatics, computational and systems biology.

RESULTS

We present a simplified formalisation of the highly dynamic system consisting of HIV, TB and related therapies, at the cellular level. The progression of the disease (AIDS) depends hence on interactions between viruses, cells, chemokines, the high mutation rate of viruses, the immune response of individuals and the interaction between drugs and infection dynamics. We first discuss a deterministic model of dual infection (HIV and TB) which is able to capture the long-term dynamics of CD4 T cells, viruses and Tumour Necrosis Factor (TNF). We contrast this model with a stochastic approach which captures intrinsic fluctuations of the biological processes. Furthermore, we also integrate automated reasoning techniques, i.e. probabilistic model checking, in our formal analysis. Beyond numerical simulations, model checking allows general properties (effectiveness of anti-HIV therapies) to be verified against the models by means of an automated procedure. Our work stresses the growing importance and flexibility of model checking techniques in bioinformatics. In this paper we i) describe HIV as a complex case of infectious diseases; ii) provide a number of different formal descriptions that suitably account for aspects of interests; iii) suggest that the integration of different models together with automated reasoning techniques can improve the understanding of infections and therapies through formal analysis methodologies.

CONCLUSION

We argue that the described methodology suitably supports the study of viral infections in a formal, automated and expressive manner. We envisage a long-term contribution of this kind of approaches to clinical Bioinformatics and Translational Medicine.

Adaptation rates of lytic viruses depend critically on whether host cells survive the bottleneck

We use a branching process approach to estimate the substitution rate, the rate at which beneficial mutations occur and fix, in populations of lytic viruses whose growth is controlled by periodic population bottlenecks. Our model predicts that substitution rates, and by extension adaptation rates, are profoundly affected by the survival of infected host cells at the bottleneck. In particular, we find that direct transfer (or environmental) bottlenecks, in which some fraction of both free virus and host cells are preserved, are associated with relatively slow adaptation rates for the virus. In contrast, viruses can adapt much more quickly when only free virus is transferred to a new host population, as is typical in an epidemiological setting. Finally, when premature lysis of the host-cell population is induced at the bottleneck, we predict that adaptation rates for the virus will, in general, be faster still. These results hold irrespective of the life-history trait affected by the beneficial mutation. The substitution rates in the presence of environmental bottlenecks are predicted to be as much as an order of magnitude lower than in the other two cases.

Mutational neighbourhood and mutation supply rate constrain adaptation in Pseudomonas aeruginosa

Understanding adaptation by natural selection requires understanding the genetic factors that determine which beneficial mutations are available for selection. Here, using experimental evolution of rifampicin-resistant Pseudomonas aeruginosa, we show that different genotypes vary in their capacity for adaptation to the cost of antibiotic resistance. We then use sequence data to show that the beneficial mutations associated with fitness recovery were specific to particular genetic backgrounds, suggesting that genotypes had access to different sets of beneficial mutations. When we manipulated the supply rate of beneficial mutations, by altering effective population size during evolution, we found that it constrained adaptation in some selection lines by restricting access to rare beneficial mutations, but that the effect varied among the genotypes in our experiment. These results suggest that mutational neighbourhood varies even among genotypes that differ by a single amino acid change, and this determines their capacity for adaptation as well as the influence of population biology processes that alter mutation supply rate.

Flipping DNA to generate and regulate microbial consortia

Communities of interdependent microbes, found in diverse natural contexts, have recently attracted the attention of bioengineers. Such consortia have potential applications in biosynthesis, with metabolic tasks distributed over several phenotypes, and in live-cell microbicide therapies where phenotypic diversity might aid in immune evasion. Here we investigate one route to generate synthetic microbial consortia and to regulate their phenotypic diversity, through programmed genetic interconversions. In our theoretical model, genotypes involve ordered combinations of DNA elements representing promoters, protein-coding genes, and transcription terminators; genotypic interconversions are driven by a recombinase enzyme that inverts DNA segments; and selectable phenotypes correspond to distinct patterns of gene expression. We analyze the microbial population as it evolves along a graph whose nodes are distinct genotypes and whose edges are interconversions. We show that the steady-state proportion of each genotype depends on its own growth advantage, as well as on its connectivity to other genotypes. Multiple phenotypes with identical or distinct growth rates can be indefinitely maintained in the population, while their proportion can be regulated by varying the rate of DNA flipping. Recombinase-based synthetic constructs have already been implemented; the graph-theoretic framework developed here will be useful in adapting them to generate microbial consortia.

The impact of population size on the evolution of asexual microbes on smooth versus rugged fitness landscapes

BACKGROUND

It is commonly thought that large asexual populations evolve more rapidly than smaller ones, due to their increased rate of beneficial mutations. Less clear is how population size influences the level of fitness an asexual population can attain. Here, we simulate the evolution of bacteria in repeated serial passage experiments to explore how features such as fitness landscape ruggedness, the size of the mutational target under selection, and the mutation supply rate, interact to affect the evolution of microbial populations of different sizes.

RESULTS

We find that if the fitness landscape has many local peaks, there can be a trade-off between the rate of adaptation and the potential to reach high fitness peaks. This result derives from the fact that whereas large populations evolve mostly deterministically and often become trapped on local fitness peaks, smaller populations can follow more stochastic evolutionary paths and thus locate higher fitness peaks. We also find that the target size of adaptation and the mutation rate interact with population size to influence the trade-off between rate of adaptation and final fitness.

CONCLUSION

Our study suggests that the optimal population size for adaptation depends on the details of the environment and on the importance of either the ability to evolve rapidly or to reach high fitness levels.

A framework for evolutionary systems biology

BACKGROUND

Many difficult problems in evolutionary genomics are related to mutations that have weak effects on fitness, as the consequences of mutations with large effects are often simple to predict. Current systems biology has accumulated much data on mutations with large effects and can predict the properties of knockout mutants in some systems. However experimental methods are too insensitive to observe small effects.

RESULTS

Here I propose a novel framework that brings together evolutionary theory and current systems biology approaches in order to quantify small effects of mutations and their epistatic interactions in silico. Central to this approach is the definition of fitness correlates that can be computed in some current systems biology models employing the rigorous algorithms that are at the core of much work in computational systems biology. The framework exploits synergies between the realism of such models and the need to understand real systems in evolutionary theory. This framework can address many longstanding topics in evolutionary biology by defining various 'levels' of the adaptive landscape. Addressed topics include the distribution of mutational effects on fitness, as well as the nature of advantageous mutations, epistasis and robustness. Combining corresponding parameter estimates with population genetics models raises the possibility of testing evolutionary hypotheses at a new level of realism.

CONCLUSION

EvoSysBio is expected to lead to a more detailed understanding of the fundamental principles of life by combining knowledge about well-known biological systems from several disciplines. This will benefit both evolutionary theory and current systems biology. Understanding robustness by analysing distributions of mutational effects and epistasis is pivotal for drug design, cancer research, responsible genetic engineering in synthetic biology and many other practical applications.

The evolutionary dynamics of evolvability in a gene network model

Evolvability, the ability of populations to adapt, has recently emerged as a major unifying concept in biology. Although the study of evolvability offers new insights into many important biological questions, the conceptual bases of evolvability, and the mechanisms of its evolution, remain controversial. We used simulated evolution of a model of gene network dynamics to test the contentious hypothesis that natural selection can favour high evolvability, in particular in sexual populations. Our results conclusively demonstrate that fluctuating natural selection can increase the capacity of model gene networks to adapt to new environments. Detailed studies of the evolutionary dynamics of these networks establish a broad range of validity for this result and quantify the evolutionary forces responsible for changes in evolvability. Analysis of the genotype-phenotype map of these networks also reveals mechanisms connecting evolvability, genetic architecture and robustness. Our results suggest that the evolution of evolvability can have a pervasive influence on many aspects of organisms.

A linear relationship between fitness and the logarithm of the critical bottleneck size in vesicular stomatitis virus populations

We explored the relationship between fitness change and population size during transmission in vesicular stomatitis populations of very high fitness. The results show a linear correlation between the logarithm of the critical bottleneck size (population size at which there are no significant fitness changes after 20 passages) and the initial fitness of the population. In addition, limits to fitness increases during large-population passages of very-high-fitness strains were abolished by increasing the population size during transmission, indicating that beneficial variation is still available in these populations.

Fixation probability for lytic viruses: the attachment-lysis model

The fixation probability of a beneficial mutation is extremely sensitive to assumptions regarding the organism's life history. In this article we compute the fixation probability using a life-history model for lytic viruses, a key model organism in experimental studies of adaptation. The model assumes that attachment times are exponentially distributed, but that the lysis time, the time between attachment and host cell lysis, is constant. We assume that the growth of the wild-type viral population is controlled by periodic sampling (population bottlenecks) and also include the possibility that clearance may occur at a constant rate, for example, through washout in a chemostat. We then compute the fixation probability for mutations that increase the attachment rate, decrease the lysis time, increase the burst size, or reduce the probability of clearance. The fixation probability of these four types of beneficial mutations can be vastly different and depends critically on the time between population bottlenecks. We also explore mutations that affect lysis time, assuming that the burst size is constrained by the lysis time, for experimental protocols that sample either free phage or free phage and artificially lysed infected cells. In all cases we predict that the fixation probability of beneficial alleles is remarkably sensitive to the time between population bottlenecks.

Robustness promotes evolvability of thermotolerance in an RNA virus

BACKGROUND

The ability for an evolving population to adapt to a novel environment is achieved through a balance of robustness and evolvability. Robustness is the invariance of phenotype in the face of perturbation and evolvability is the capacity to adapt in response to selection. Genetic robustness has been posited, depending on the underlying mechanism, to either decrease the efficacy of selection, or increase the possibility of future adaptation. However, the true effect of genetic robustness on evolvability in biological systems remains uncertain.

RESULTS

Here we demonstrate that genetic robustness increases evolvability of thermotolerance in laboratory populations of the RNA virus phi6. We observed that populations founded by robust clones evolved greater resistance to heat shock, relative to populations founded by brittle (less-robust) clones. Thus, we provide empirical evidence for the idea that robustness can promote evolvability in this environment, and further suggest that evolvability can arise indirectly via selection for robustness, rather than through direct selective action.

CONCLUSION

Our data imply that greater tolerance of mutational change is associated with virus adaptability in a new niche, a finding generally relevant to evolutionary biology, and informative for elucidating how viruses might evolve to emerge in new habitats and/or overcome novel therapies.

Improvisation in evolution of genes and genomes: whose structure is it anyway?

Significant progress has been made in recent years in a variety of seemingly unrelated fields such as sequencing, protein structure prediction, and high-throughput transcriptomics and metabolomics. At the same time, new microscopic models have been developed that made it possible to analyze the evolution of genes and genomes from first principles. The results from these efforts enable, for the first time, a comprehensive insight into the evolution of complex systems and organisms on all scales--from sequences to organisms and populations. Every newly sequenced genome uncovers new genes, families, and folds. Where do these new genes come from? How do gene duplication and subsequent divergence of sequence and structure affect the fitness of the organism? What role does regulation play in the evolution of proteins and folds? Emerging synergism between data and modeling provides first robust answers to these questions.

Changes in the intraisolate genetic structure of Beet necrotic yellow vein virus populations associated with plant resistance breakdown

The causal agent of rhizomania disease, Beet necrotic yellow vein virus (BNYVV), typically produces asymptomatic root-limited infections in sugar beets (Beta vulgaris) carrying the Rz1-allele. Unfortunately, this dominant resistance has been recently overcome. Multiple cDNA clones of the viral pathogenic determinant p25, derived from populations infecting susceptible or resistant plants, were sequenced to identify host effects on the viral population structure. Populations isolated from compatible plant-virus interactions (susceptible plant-wild type virus and resistant plant-resistant breaking variants) were large and relatively homogeneous, whereas those from the incompatible interaction (resistant plant-avirulent type virus) were small and highly heterogeneous. All populations from susceptible plants had the same dominant haplotype, whereas those from resistant cultivars had a different haplotype surrounded by a spectrum of mutants. Selection and diversification analyses suggest an evolutionary trajectory of BNYVV with positive selection for changes required to overcome resistance, followed by elimination of hitchhiking mutations through purifying selection.

Heterogeneous adaptive trajectories of small populations on complex fitness landscapes

Background

Small populations are thought to be adaptively handicapped, not only because they suffer more from deleterious mutations but also because they have limited access to new beneficial mutations, particularly those conferring large benefits.

Methodology/Principal Findings

Here, we test this widely held conjecture using both simulations and experiments with small and large bacterial populations evolving in either a simple or a complex nutrient environment. Consistent with expectations, we find that small populations are adaptively constrained in the simple environment; however, in the complex environment small populations not only follow more heterogeneous adaptive trajectories, but can also attain higher fitness than the large populations. Large populations are constrained to near deterministic fixation of rare large-benefit mutations. While such determinism speeds adaptation on the smooth adaptive landscape represented by the simple environment, it can limit the ability of large populations from effectively exploring the underlying topography of rugged adaptive landscapes characterized by complex environments.

Conclusions

Our results show that adaptive constraints often faced by small populations can be circumvented during evolution on rugged adaptive landscapes.

Predicting evolution from genomics: experimental evolution of bacteriophage T7

A wealth of molecular biology has been exploited in designing and interpreting experimental evolution studies with bacteriophage T7. The modest size of its genome (40 kb dsDNA) and the ease of making genetic constructs, combined with the many genetic resources for its host (Escherichia coli), have enabled comprehensive and detailed studies of experimental adaptations. In several studies, the genome was specifically altered (gene knockouts, gene replacements, reordering of genetic elements) such that a priori knowledge of genetics and biochemistry of the phage could be used to predict the pathways of compensatory evolution when the modified phage is adapted to recover fitness. In other work, the phage has been adapted to specific environmental conditions chosen to select phenotypic outcomes with a quantitative basis, and the molecular bases of that evolution have been explored. Predicting the outcomes of these adaptations has been challenging. In hindsight, one-third to one-half of the compensatory nucleotide changes observed during the adaptation can be rationalized based on T7 biology. This rationalization usually only applies at the genetic level-a gene product may be known to be involved in the affected pathway, but it usually remains unknown how the observed change affects activity. The progress is encouraging, but the prediction of experimental evolution pathways remains far from complete, and is still sometimes confounded by observation when an adaptation yields a completely unexpected outcome.

Evolution of a single niche specialist in variable environments

The pattern (space versus time) and scale (relative to the lifetime of individuals) of environmental variation is thought to play a central role in governing the evolution of the ecological niche and the maintenance of genetic variance in fitness. To evaluate this idea, we serially propagated an initially genetically uniform population of the bacterium Pseudomonas fluorescens for a few hundred generations in environments that differed in both the pattern and scale at which two highly contrasted carbon substrates were experienced. We found that, contrary to expectations, populations often evolved into a single niche specialist adapted to the less-productive substrate in variable environments and that the genetic variance in fitness across different components of the environment was not generally higher in variable environments when compared with constant environments. We provide evidence to suggest that our results reflect a novel constraint on niche evolution imposed by the supply of beneficial mutations available to selection in variable environments.

Evolution of host specificity drives reproductive isolation among RNA viruses

Ecological speciation hypotheses claim that assortative mating evolves as a consequence of divergent natural selection for ecologically important traits. Reproductive isolation is expected to be particularly likely to evolve by this mechanism in species such as phytophagous insects that mate in the habitats in which they eat. We tested this expectation by monitoring the evolution of reproductive isolation in laboratory populations of an RNA virus that undergoes genetic exchange only when multiple virus genotypes coinfect the same host. We subjected four populations of the RNA bacteriophage phi6 to 150 generations of natural selection on a novel host. Although there was no direct selection acting on host range in our experiment, three of the four populations lost the ability to infect one or more alternative hosts. In the most extreme case, one of the populations evolved a host range that does not contain any of the hosts infectible by the wild-type phi6. Whole genome sequencing confirmed that the resulting reproductive isolation was due to a single nucleotide change, highlighting the ease with which an emerging RNA virus can decouple its evolutionary fate from that of its ancestor. Our results uniquely demonstrate the evolution of reproductive isolation in allopatric experimental populations. Furthermore, our data confirm the biological credibility of simple "no-gene" mechanisms of assortative mating, in which this trait arises as a pleiotropic effect of genes responsible for ecological adaptation.

Evolutionary dynamics of the most populated genotype on rugged fitness landscapes

We consider an asexual population evolving on rugged fitness landscapes which are defined on the multidimensional genotypic space and have many local optima. We track the most populated genotype as it changes when the population jumps from a fitness peak to a better one during the process of adaptation. This is done using the dynamics of the shell model which is a simplified version of the quasispecies model for infinite populations and standard Wright-Fisher dynamics for large finite populations. We show that the population fraction of a genotype obtained within the quasispecies model and the shell model match for fit genotypes and at short times, but the dynamics of the two models are identical for questions related to the most populated genotype. We calculate exactly several properties of the jumps in infinite populations, some of which were obtained numerically in previous works. We also present our preliminary simulation results for finite populations. In particular, we measure the jump distribution in time and find that it decays as t(-2) as in the quasispecies problem.

A Long-Term Evolutionary Pressure on the Amount of Noncoding DNA

A significant part of eukaryotic noncoding DNA is viewed as the passive result of mutational processes, such as the proliferation of mobile elements. However, sequences lacking an immediate utility can nonetheless play a major role in the long-term evolvability of a lineage, for instance by promoting genomic rearrangements. They could thus be subject to an indirect selection. Yet, such a long-term effect is difficult to isolate either in vivo or in vitro. Here, by performing in silico experimental evolution, we demonstrate that, under low mutation rates, the indirect selection of variability promotes the accumulation of noncoding sequences: Even in the absence of self-replicating elements and mutational bias, noncoding sequences constituted an important fraction of the evolved genome because the indirectly selected genomes were those that were variable enough to discover beneficial mutations. On the other hand, high mutation rates lead to compact genomes, much like the viral ones, although no selective cost of genome size was applied: The indirectly selected genomes were those that were small enough for the genetic information to be reliably transmitted. Thus, the spontaneous evolution of the amount of noncoding DNA strongly depends on the mutation rate. Our results suggest the existence of an additional pressure on the amount of noncoding DNA, namely the indirect selection of an appropriate trade-off between the fidelity of the transmission of the genetic information and the exploration of the mutational neighborhood. Interestingly, this trade-off resulted robustly in the accumulation of noncoding DNA so that the best individual leaves one offspring without mutation (or only neutral ones) per generation.

Modeling HIV quasispecies evolutionary dynamics

BACKGROUND

During the HIV infection several quasispecies of the virus arise, which are able to use different coreceptors, in particular the CCR5 and CXCR4 coreceptors (R5 and X4 phenotypes, respectively). The switch in coreceptor usage has been correlated with a faster progression of the disease to the AIDS phase. As several pharmaceutical companies are starting large phase III trials for R5 and X4 drugs, models are needed to predict the co-evolutionary and competitive dynamics of virus strains.

RESULTS

We present a model of HIV early infection which describes the dynamics of R5 quasispecies and a model of HIV late infection which describes the R5 to X4 switch. We report the following findings: after superinfection (multiple infections at different times) or coinfection (simultaneous infection by different strains), quasispecies dynamics has time scales of several months and becomes even slower at low number of CD4+ T cells. Phylogenetic inference of chemokine receptors suggests that viral mutational pathway may generate a large variety of R5 variants able to interact with chemokine receptors different from CXCR4. The decrease of CD4+ T cells, during AIDS late stage, can be described taking into account the X4-related Tumor Necrosis Factor dynamics.

CONCLUSION

The results of this study bridge the gap between the within-patient and the inter-patients (i.e. world-wide) evolutionary processes during HIV infection and may represent a framework relevant for modeling vaccination and therapy.

Selection for robustness in mutagenized RNA viruses

Mutational robustness is defined as the constancy of a phenotype in the face of deleterious mutations. Whether robustness can be directly favored by natural selection remains controversial. Theory and in silico experiments predict that, at high mutation rates, slow-replicating genotypes can potentially outcompete faster counterparts if they benefit from a higher robustness. Here, we experimentally validate this hypothesis, dubbed the "survival of the flattest," using two populations of the vesicular stomatitis RNA virus. Characterization of fitness distributions and genetic variability indicated that one population showed a higher replication rate, whereas the other was more robust to mutation. The faster replicator outgrew its robust counterpart in standard competition assays, but the outcome was reversed in the presence of chemical mutagens. These results show that selection can directly favor mutational robustness and reveal a novel viral resistance mechanism against treatment by lethal mutagenesis.