Magnitude and sign epistasis among deleterious mutations in a positive-sense plant RNA virus

Genetic Interactions in Various Environmental Conditions in Caenorhabditis elegans

Although it is well known that epistasis plays an important role in many evolutionary processes (e.g., speciation, evolution of sex), our knowledge on the frequency and prevalent sign of epistatic interactions is mainly limited to unicellular organisms or cell cultures of multicellular organisms. This is even more pronounced in regard to how the environment can influence genetic interactions. To broaden our knowledge in that respect we studied gene-gene interactions in a whole multicellular organism, Caenorhabditis elegans. We screened over one thousand gene interactions, each one in standard laboratory conditions, and under three different stressors: heat shock, oxidative stress, and genotoxic stress. Depending on the condition, between 7% and 22% of gene pairs showed significant genetic interactions and an overall sign of epistasis changed depending on the condition. Sign epistasis was quite common, but reciprocal sign epistasis was extremally rare. One interaction was common to all conditions, whereas 78% of interactions were specific to only one environment. Although epistatic interactions are quite common, their impact on evolutionary processes will strongly depend on environmental factors.

Mutational robustness changes during long-term adaptation in laboratory budding yeast populations

As an adapting population traverses the fitness landscape, its local neighborhood (i.e., the collection of fitness effects of single-step mutations) can change shape because of interactions with mutations acquired during evolution. These changes to the distribution of fitness effects can affect both the rate of adaptation and the accumulation of deleterious mutations. However, while numerous models of fitness landscapes have been proposed in the literature, empirical data on how this distribution changes during evolution remains limited. In this study, we directly measure how the fitness landscape neighborhood changes during laboratory adaptation. Using a barcode-based mutagenesis system, we measure the fitness effects of 91 specific gene disruption mutations in genetic backgrounds spanning 8000–10,000 generations of evolution in two constant environments. We find that the mean of the distribution of fitness effects decreases in one environment, indicating a reduction in mutational robustness, but does not change in the other. We show that these distribution-level patterns result from differences in the relative frequency of certain patterns of epistasis at the level of individual mutations, including fitness-correlated and idiosyncratic epistasis.

Multiple Levels of Triggered Factors and the Obligated Requirement of Cell-to-Cell Movement in the Mutation Repair of Cucumber Mosaic Virus with Defects in the tRNA-like Structure

Simple Summary

Based on analysis of the tRNA-like structure (TLS) mutation in cucumber mosaic virus (CMV), mutation repair is correlated with several levels of triggered factors, including the dose of inoculation of virus mutants, the quantity effect on corresponding viral RNA, and the quality effect on corresponding viral RNA. All types of TLS mutation in different RNAs of CMV can be repaired at a low dose around the dilution end-point. At a high dose of inoculation, TLS mutations in RNA2 and RNA3, but not RNA1, can be repaired, which correlates with the relative quantity defect of RNA2 or the genome size defect of RNA3. In addition, all the above types of mutation repair necessarily require cell-to-cell movement, which presents the obligated effect of cell-to-cell movement on mutation repair.

Abstract

Some debilitating mutations in RNA viruses are repairable; however, the triggering factors of mutation repair remain largely unknown. In this study, multiple triggering factors of mutation repair are identified based on genetic damage to the TLS in CMV. TLS mutations in different RNAs distinctively impact viral pathogenicity and present different types of mutation repair. RNA2 relative reduction level or RNA3 sequence change resulting from TLS mutation is correlated with a high rate of mutation repair, and the TLS mutation of RNA1 fails to be repaired at the high inoculum dose. However, the TLS mutation of RNA1 can be repaired at a low dose of inoculation, particularly around the dilution end-point or in the mixed inoculation with RNA2 having a pre-termination mutation of the 2b gene, an RNAi suppressor. Taken together, TLS mutations resulting in quality or quantity defects of the viral genome or TLS mutations at low doses around the dilution end-point are likely to be repaired. Different levels of TLS mutation repair necessarily require cell-to-cell movement, therefore implying its obligated effect on the evolution of low-fitness viruses and providing a new insight into Muller’s ratchet. This study provides important information on virus evolution and the application of mild viral vaccines.

Patterns and Causes of Signed Linkage Disequilibria in Flies and Plants

Most empirical studies of linkage disequilibrium (LD) study its magnitude, ignoring its sign. Here, we examine patterns of signed LD in two population genomic data sets, one from Capsella grandiflora and one from Drosophila melanogaster. We consider how processes such as drift, admixture, Hill–Robertson interference, and epistasis may contribute to these patterns. We report that most types of mutations exhibit positive LD, particularly, if they are predicted to be less deleterious. We show with simulations that this pattern arises easily in a model of admixture or distance-biased mating, and that genome-wide differences across site types are generally expected due to differences in the strength of purifying selection even in the absence of epistasis. We further explore how signed LD decays on a finer scale, showing that loss of function mutations exhibit particularly positive LD across short distances, a pattern consistent with intragenic antagonistic epistasis. Controlling for genomic distance, signed LD in C. grandiflora decays faster within genes, compared with between genes, likely a by-product of frequent recombination in gene promoters known to occur in plant genomes. Finally, we use information from published biological networks to explore whether there is evidence for negative synergistic epistasis between interacting radical missense mutations. In D. melanogaster networks, we find a modest but significant enrichment of negative LD, consistent with the possibility of intranetwork negative synergistic epistasis.

From genotypes to organisms: State-of-the-art and perspectives of a cornerstone in evolutionary dynamics

Understanding how genotypes map onto phenotypes, fitness, and eventually organisms is arguably the next major missing piece in a fully predictive theory of evolution. We refer to this generally as the problem of the genotype-phenotype map. Though we are still far from achieving a complete picture of these relationships, our current understanding of simpler questions, such as the structure induced in the space of genotypes by sequences mapped to molecular structures, has revealed important facts that deeply affect the dynamical description of evolutionary processes. Empirical evidence supporting the fundamental relevance of features such as phenotypic bias is mounting as well, while the synthesis of conceptual and experimental progress leads to questioning current assumptions on the nature of evolutionary dynamics-cancer progression models or synthetic biology approaches being notable examples. This work delves with a critical and constructive attitude into our current knowledge of how genotypes map onto molecular phenotypes and organismal functions, and discusses theoretical and empirical avenues to broaden and improve this comprehension. As a final goal, this community should aim at deriving an updated picture of evolutionary processes soundly relying on the structural properties of genotype spaces, as revealed by modern techniques of molecular and functional analysis.

Increasing temperature alters the within-host competition of viral strains and influences virus genetic variability

Environmental conditions can affect viral accumulation, virulence and adaptation, which have implications in the disease outcomes and efficiency of control measures. Concurrently, mixed viral infections are relevant in plants, being their epidemiology shaped by within-host virus–virus interactions. However, the extent in which the combined effect of variations in abiotic components of the plant ecological niche and the prevalence of mixed infections affect the evolutionary dynamics of viral populations is not well understood. Here, we explore the interplay between ecological and evolutionary factors during viral infections and show that isolates of two strains of Pepino mosaic potexvirus coexisted in tomato plants in a temperature-dependent continuum between neutral and antagonistic interactions. After a long-term infection, the mutational analysis of the evolved viral genomes revealed strain-specific single-nucleotide polymorphisms that were modulated by the interaction between the type of infection and temperature. These results suggest that the temperature is an ecological driver of virus-virus interactions, with an effect on the genetic diversity of individual viruses that are co-infecting an individual host. This research provides insights into the effect that changes in host growth temperatures might have on the evolutionary dynamics of viral populations in mixed infections.

ΦX174 Attenuation by Whole-Genome Codon Deoptimization

Natural selection acting on synonymous mutations in protein-coding genes influences genome composition and evolution. In viruses, introducing synonymous mutations in genes encoding structural proteins can drastically reduce viral growth, providing a means to generate potent, live-attenuated vaccine candidates. However, an improved understanding of what compositional features are under selection and how combinations of synonymous mutations affect viral growth is needed to predictably attenuate viruses and make them resistant to reversion. We systematically recoded all nonoverlapping genes of the bacteriophage ΦX174 with codons rarely used in its Escherichia coli host. The fitness of recombinant viruses decreases as additional deoptimizing mutations are made to the genome, although not always linearly, and not consistently across genes. Combining deoptimizing mutations may reduce viral fitness more or less than expected from the effect size of the constituent mutations and we point out difficulties in untangling correlated compositional features. We test our model by optimizing the same genes and find that the relationship between codon usage and fitness does not hold for optimization, suggesting that wild-type ΦX174 is at a fitness optimum. This work highlights the need to better understand how selection acts on patterns of synonymous codon usage across the genome and provides a convenient system to investigate the genetic determinants of virulence.

Direct coupling analysis of epistasis in allosteric materials

In allosteric proteins, the binding of a ligand modifies function at a distant active site. Such allosteric pathways can be used as target for drug design, generating considerable interest in inferring them from sequence alignment data. Currently, different methods lead to conflicting results, in particular on the existence of long-range evolutionary couplings between distant amino-acids mediating allostery. Here we propose a resolution of this conundrum, by studying epistasis and its inference in models where an allosteric material is evolved in silico to perform a mechanical task. We find in our model the four types of epistasis (Synergistic, Sign, Antagonistic, Saturation), which can be both short or long-range and have a simple mechanical interpretation. We perform a Direct Coupling Analysis (DCA) and find that DCA predicts well the cost of point mutations but is a rather poor generative model. Strikingly, it can predict short-range epistasis but fails to capture long-range epistasis, in consistence with empirical findings. We propose that such failure is generic when function requires subparts to work in concert. We illustrate this idea with a simple model, which suggests that other methods may be better suited to capture long-range effects.

Allostery in proteins is the property of highly specific responses to ligand binding at a distant site. To inform protocols of de novo drug design, it is fundamental to understand the impact of mutations on allosteric regulation and whether it can be predicted from evolutionary correlations. In this work we consider allosteric architectures artificially evolved to optimize the cooperativity of binding at allosteric and active site. We first characterize the emergent pattern of epistasis as well as the underlying mechanical phenomena, finding the four types of epistasis (Synergistic, Sign, Antagonistic, Saturation), which can be both short or long-range. The numerical evolution of these allosteric architectures allows us to benchmark Direct Coupling Analysis, a method which relies on co-evolution in sequence data to infer direct evolutionary couplings, in connection to allostery. We show that Direct Coupling Analysis predicts quantitatively point mutation costs but underestimates strong long-range epistasis. We provide an argument, based on a simplified model, illustrating the reasons for this discrepancy. Our analysis suggests neural networks as more promising tool to measure epistasis.

Recent insights into the genotype-phenotype relationship from massively parallel genetic assays

With the molecular revolution in Biology, a mechanistic understanding of the genotype-phenotype relationship became possible. Recently, advances in DNA synthesis and sequencing have enabled the development of deep mutational scanning assays, capable of scoring comprehensive libraries of genotypes for fitness and a variety of phenotypes in massively parallel fashion. The resulting empirical genotype-fitness maps pave the way to predictive models, potentially accelerating our ability to anticipate the behaviour of pathogen and cancerous cell populations from sequencing data. Besides from cellular fitness, phenotypes of direct application in industry (e.g. enzyme activity) and medicine (e.g. antibody binding) can be quantified and even selected directly by these assays. This review discusses the technological basis of and recent developments in massively parallel genetics, along with the trends it is uncovering in the genotype-phenotype relationship (distribution of mutation effects, epistasis), their possible mechanistic bases and future directions for advancing towards the goal of predictive genetics.

Mutagenesis Scanning Uncovers Evolutionary Constraints on Tobacco Etch Potyvirus Membrane-Associated 6K2 Protein

RNA virus high mutation rate is a double-edged sword. At the one side, most mutations jeopardize proteins functions; at the other side, mutations are needed to fuel adaptation. The relevant question then is the ratio between beneficial and deleterious mutations. To evaluate this ratio, we created a mutant library of the 6K2 gene of tobacco etch potyvirus that contains every possible single-nucleotide substitution. 6K2 protein anchors the virus replication complex to the network of endoplasmic reticulum membranes. The library was inoculated into the natural host Nicotiana tabacum, allowing competition among all these mutants and selection of those that are potentially viable. We identified 11 nonsynonymous mutations that remain in the viral population at measurable frequencies and evaluated their fitness. Some had fitness values higher than the wild-type and some were deleterious. The effect of these mutations in the structure, transmembrane properties, and function of 6K2 was evaluated in silico. In parallel, the effect of these mutations in infectivity, virus accumulation, symptoms development, and subcellular localization was evaluated in the natural host. The α-helix H1 in the N-terminal part of 6K2 turned out to be under purifying selection, while most observed mutations affect the link between transmembrane α-helices H2 and H3, fusing them into a longer helix and increasing its rigidity. In general, these changes are associated with higher within-host fitness and development of milder or no symptoms. This finding suggests that in nature selection upon 6K2 may result from a tradeoff between within-host accumulation and severity of symptoms.

An experimental assay of the interactions of amino acids from orthologous sequences shaping a complex fitness landscape

Characterizing the fitness landscape, a representation of fitness for a large set of genotypes, is key to understanding how genetic information is interpreted to create functional organisms. Here we determined the evolutionarily-relevant segment of the fitness landscape of His3, a gene coding for an enzyme in the histidine synthesis pathway, focusing on combinations of amino acid states found at orthologous sites of extant species. Just 15% of amino acids found in yeast His3 orthologues were always neutral while the impact on fitness of the remaining 85% depended on the genetic background. Furthermore, at 67% of sites, amino acid replacements were under sign epistasis, having both strongly positive and negative effect in different genetic backgrounds. 46% of sites were under reciprocal sign epistasis. The fitness impact of amino acid replacements was influenced by only a few genetic backgrounds but involved interaction of multiple sites, shaping a rugged fitness landscape in which many of the shortest paths between highly fit genotypes are inaccessible.

An intuitive understanding of protein evolution dictates that, with the exception of adaptive substitutions, amino acid states should be freely exchangeable between the same gene from different species. However, the extent to which this assertion holds true has not been tested in a controlled experiment. Here, we show that whether an amino acid state can be exchanged between orthologues depends on other amino acid states in the same protein. Furthermore, we show that the mode of interaction of amino acid states is multidimensional. Assuming that amino acid replacements influence the protein in several independent ways substantially improves our ability to predict the effect of an amino acid state in a protein sequence that has not been observed in nature.

Existing Host Range Mutations Constrain Further Emergence of RNA Viruses

RNA viruses are capable of rapid host shifting, typically due to a point mutation that confers expanded host range. As additional point mutations are necessary for further expansions, epistasis among host range mutations can potentially affect the mutational neighborhood and frequency of niche expansion. We mapped the mutational neighborhood of host range expansion using three genotypes of the double-stranded RNA (dsRNA) bacteriophage φ6 (wild type and two isogenic host range mutants) on the novel host Pseudomonas syringae pv. atrofaciens. Both Sanger sequencing of 50 P. syringae pv. atrofaciens mutant clones for each genotype and population Illumina sequencing revealed the same high-frequency mutations allowing infection of P. syringae pv. atrofaciens. Wild-type φ6 had at least nine different ways of mutating to enter the novel host, eight of which are in p3 (host attachment protein gene), and 13/50 clones had unchanged p3 genes. However, the two isogenic mutants had dramatically restricted neighborhoods: only one or two mutations, all in p3. Deep sequencing revealed that wild-type clones without mutations in p3 likely had changes in p12 (morphogenic protein), a region that was not polymorphic for the two isogenic host range mutants. Sanger sequencing confirmed that 10/13 of the wild-type φ6 clones had nonsynonymous mutations in p12, and 2 others had point mutations in p9 and p5. None of these genes had previously been associated with host range expansion in φ6. We demonstrate, for the first time, epistatic constraint in an RNA virus due to host range mutations themselves, which has implications for models of serial host range expansion.IMPORTANCE RNA viruses mutate rapidly and frequently expand their host ranges to infect novel hosts, leading to serial host shifts. Using an RNA bacteriophage model system (Pseudomonas phage φ6), we studied the impact of preexisting host range mutations on another host range expansion. Results from both clonal Sanger and Illumina sequencing show that extant host range mutations dramatically narrow the neighborhood of potential host range mutations compared to that of wild-type φ6. This research suggests that serial host-shifting viruses may follow a small number of molecular paths to enter additional novel hosts. We also identified new genes involved in φ6 host range expansion, expanding our knowledge of this important model system in experimental evolution.

Analysis of Fitness Trade-Offs in the Host Range Expansion of an RNA Virus, Tobacco Mild Green Mosaic Virus

The acquisition of new hosts provides a virus with more opportunities for transmission and survival but may be limited by across-host fitness trade-offs. Major causes of across-host trade-offs are antagonistic pleiotropy, that is, host differential phenotypic effects of mutations, a Genotype x Environment interaction, and epistasis, a Genotype x Genotype interaction. Here, we analyze if there are trade-offs, and what are the causes, associated with the acquisition by tobacco mild green mosaic virus (TMGMV) of a new host. For this, the multiplication of sympatric field isolates of TMGMV from its wild reservoir host Nicotiana glauca and from pepper crops was quantified in the original and the heterologous hosts. TMGMV isolates from N. glauca were adapted to their host, but pepper isolates were not adapted to pepper, and the acquisition of this new host was associated with a fitness penalty in the original host. Analyses of the collection of field isolates and of mutant genotypes derived from biologically active cDNA clones showed a role of mutations in the coat protein and the 3' untranslated region in determining within-host virus fitness. Fitness depended on host-specific effects of these mutations, on the genetic background in which they occurred, and on higher-order interactions of the type Genotype x Genotype x Environment. These types of effects had been reported to generate across-host fitness trade-offs under experimental evolution. Our results show they may also operate in heterogeneous natural environments and could explain why pepper isolates were not adapted to pepper and their lower fitness in N. glaucaIMPORTANCE The acquisition of new hosts conditions virus epidemiology and emergence; hence it is important to understand the mechanisms behind host range expansion. Experimental evolution studies have identified antagonistic pleiotropy and epistasis as genetic mechanisms that limit host range expansion, but studies from virus field populations are few. Here, we compare the performance of isolates of tobacco mild green mosaic virus from its reservoir host, Nicotiana glauca, and its new host, pepper, showing that acquisition of a new host was not followed by adaptation to it but was associated with a fitness loss in the original host. Analysis of mutations determining host-specific virus multiplication identified antagonistic pleiotropy, epistasis, and host-specific epistasis as mechanisms generating across-host fitness trade-offs that may prevent adaptation to pepper and cause a loss of fitness in N. glauca Thus, mechanisms determining trade-offs, identified under experimental evolution, could also operate in the heterogeneous environment in which natural plant virus populations occur.

Experimental Design, Population Dynamics, and Diversity in Microbial Experimental Evolution

In experimental evolution, laboratory-controlled conditions select for the adaptation of species, which can be monitored in real time. Despite the current popularity of such experiments, nature's most pervasive biological force was long believed to be observable only on time scales that transcend a researcher's life-span, and studying evolution by natural selection was therefore carried out solely by comparative means. Eventually, microorganisms' propensity for fast evolutionary changes proved us wrong, displaying strong evolutionary adaptations over a limited time, nowadays massively exploited in laboratory evolution experiments. Here, we formulate a guide to experimental evolution with microorganisms, explaining experimental design and discussing evolutionary dynamics and outcomes and how it is used to assess ecoevolutionary theories, improve industrially important traits, and untangle complex phenotypes. Specifically, we give a comprehensive overview of the setups used in experimental evolution. Additionally, we address population dynamics and genetic or phenotypic diversity during evolution experiments and expand upon contributing factors, such as epistasis and the consequences of (a)sexual reproduction. Dynamics and outcomes of evolution are most profoundly affected by the spatiotemporal nature of the selective environment, where changing environments might lead to generalists and structured environments could foster diversity, aided by, for example, clonal interference and negative frequency-dependent selection. We conclude with future perspectives, with an emphasis on possibilities offered by fast-paced technological progress. This work is meant to serve as an introduction to those new to the field of experimental evolution, as a guide to the budding experimentalist, and as a reference work to the seasoned expert.

Unraveling the causes of adaptive benefits of synonymous mutations in TEM-1 β-lactamase

While synonymous mutations were long thought to be without phenotypic consequences, there is growing evidence they can affect gene expression, protein folding, and ultimately the fitness of an organism. In only a few cases have the mechanisms by which synonymous mutations affect the phenotype been elucidated. We previously identified 48 mutations in TEM-1 β-lactamase that increased resistance of Escherichia coli to cefotaxime, 10 of which were synonymous. To better understand the molecular mechanisms underlying the beneficial effect of these synonymous mutations, we made a series of measurements for a panel containing the 10 synonymous together with 10 non-synonymous mutations as a reference. Whereas messenger levels were unaffected, we found that total and functional TEM protein levels were higher for 5 out of 10 synonymous mutations. These observations suggest that some of these mutations act on translation or a downstream process. Similar effects were observed for some small-benefit non-synonymous mutations, suggesting a similar causal mechanism. For the synonymous mutations, we found that the cost of resistance scales with TEM protein levels. A resistance landscape for four synonymous mutations revealed strong epistasis: none of the combinations of mutations exceeded the resistance of the largest-effect mutation and there were synthetically neutral combinations. By considering combined effects of these mutations, we could infer that functional TEM protein level is a multi-dimensional phenotype. These results suggest that synonymous mutations may have beneficial effects by increasing the expression of an enzyme with low substrate activity, which may be realized via multiple, yet unknown, post-transcriptional mechanisms.

Ecological Complexity in Plant Virus Host Range Evolution

The host range of a plant virus is the number of species in which it can reproduce. Most studies of plant virus host range evolution have focused on the genetics of host-pathogen interactions. However, the distribution and abundance of plant viruses and their hosts do not always overlap, and these spatial and temporal discontinuities in plant virus-host interactions can result in various ecological processes that shape host range evolution. Recent work shows that the distributions of pathogenic and resistant genotypes, vectors, and other resources supporting transmission vary widely in the environment, producing both expected and unanticipated patterns. The distributions of all of these factors are influenced further by competitive effects, natural enemies, anthropogenic disturbance, the abiotic environment, and herbivory to mention some. We suggest the need for further development of approaches that (i) explicitly consider resource use and the abiotic and biotic factors that affect the strategies by which viruses exploit resources; and (ii) are sensitive across scales. Host range and habitat specificity will largely determine which phyla are most likely to be new hosts, but predicting which host and when it is likely to be infected is enormously challenging because it is unclear how environmental heterogeneity affects the interactions of viruses and hosts.

Efficient escape from local optima in a highly rugged fitness landscape by evolving RNA virus populations

Predicting viral evolution has proven to be a particularly difficult task, mainly owing to our incomplete knowledge of some of the fundamental principles that drive it. Recently, valuable information has been provided about mutation and recombination rates, the role of genetic drift and the distribution of mutational, epistatic and pleiotropic fitness effects. However, information about the topography of virus' adaptive landscapes is still scarce, and to our knowledge no data has been reported so far on how its ruggedness may condition virus' evolvability. Here, we show that populations of an RNA virus move efficiently on a rugged landscape and scape from the basin of attraction of a local optimum. We have evolved a set of Tobacco etch virus genotypes located at increasing distances from a local adaptive optimum in a highly rugged fitness landscape, and we observed that few evolved lineages remained trapped in the local optimum, while many others explored distant regions of the landscape. Most of the diversification in fitness among the evolved lineages was explained by adaptation, while historical contingency and chance events contribution was less important. Our results demonstrate that the ruggedness of adaptive landscapes is not an impediment for RNA viruses to efficiently explore remote parts of it.

An evolutionary tipping point in a changing environment

Populations can persist in directionally changing environments by evolving. Quantitative genetic theory aims to predict critical rates of environmental change beyond which populations go extinct. Here, we point out that all current predictions effectively assume the same specific fitness function. This function causes selection on the standing genetic variance of quantitative traits to become increasingly strong as mean trait values depart from their optima. Hence, there is no bound on the rate of evolution and persistence is determined by the critical rate of environmental change at which populations cease to grow. We then show that biologically reasonable changes to the underlying fitness function can impose a qualitatively different extinction threshold. In particular, inflection points caused by weakening selection create local extrema in the strength of selection and thus in the rate of evolution. These extrema can produce evolutionary tipping points, where long-run population growth rates drop from positive to negative values without ever crossing zero. Generic early-warning signs of tipping points are found to have little power to detect imminent extinction, and require hard-to-gather data. Furthermore, we show how evolutionary tipping points produce evolutionary hysteresis, creating extinction debts.

Strain-dependent mutational effects for Pepino mosaic virus in a natural host

Background

Pepino mosaic virus (PepMV) is an emerging plant pathogen that infects tomatoes worldwide. Understanding the factors that influence its evolutionary success is essential for developing new control strategies that may be more robust against the evolution of new viral strains. One of these evolutionary factors is the distribution of mutational fitness effect (DMFE), that is, the fraction of mutations that are lethal, deleterious, neutral, and beneficial on a given viral strain and host species. The goal of this study was to characterize the DMFE of introduced nonsynonymous mutations on a mild isolate of PepMV from the Chilean 2 strain (PepMV-P22). Additionally, we also explored whether the fitness effect of a given mutation depends on the gene where it appears or on epistatic interactions with the genetic background. To address this latter possibility, a subset of mutations were also introduced in a mild isolate of the European strain (PepMV-P11) and the fitness of the resulting clones measured.

Results

A collection of 25 PepMV clones each containing a single nucleotide nonsynonymous substitution was created by site-directed mutagenesis and the fitness of each mutant was determined. PepMV-P22 genome showed a high degree of robustness against point mutations, with 80% of mutations being either neutral or even beneficial and only 20% being deleterious or lethal. We found that the effect of mutations strongly depended on the gene in which they were introduced. Mutations with the largest average beneficial effects were those affecting the RdRp gene, in contrast to mutations affecting TGB1 and CP genes, for which the average effects were deleterious. Moreover, significant epistatic interactions were observed between nonsynonymous mutations and the genetic background, meaning that the effect of a given nucleotide substitution on a particular genomic context cannot be predicted by knowing its effect in a different one.

Conclusions

Our results indicated that PepMV genome has a surprisingly high robustness against mutations. We also found that fitness consequences of a given mutation differ between the two strains analyzed. This discovery suggests that the strength of selection, and thus the rates of evolution, vary among PepMV strains.

Matters of Size: Genetic Bottlenecks in Virus Infection and Their Potential Impact on Evolution

For virus infections of multicellular hosts, narrow genetic bottlenecks during transmission and within-host spread appear to be widespread. These bottlenecks will affect the maintenance of genetic variation in a virus population and the prevalence of mixed-strain infections, thereby ultimately determining the strength with which different random forces act during evolution. Here we consider different approaches for estimating bottleneck sizes and weigh their merits. We then review quantitative estimates of bottleneck size during cellular infection, within-host spread, horizontal transmission, and finally vertical transmission. In most cases we find that bottlenecks do regularly occur, although in many cases they appear to be virion-concentration dependent. Finally, we consider the evolutionary implications of genetic bottlenecks during virus infection. Although on average strong bottlenecks will lead to declines in fitness, we consider a number of scenarios in which bottlenecks could also be advantageous for viruses.

Fusion of genomic, proteomic and phenotypic data: the case of potyviruses

Data fusion has been widely applied to analyse different sources of information, combining all of them in a single multivariate model. This methodology is mandatory when different omic data sets must be integrated to fully understand an organism using a systems biology approach. Here, a data fusion procedure is presented to combine genomic, proteomic and phenotypic data sets gathered for Tobacco etch virus (TEV). The genomic data correspond to random mutations inserted in most viral genes. The proteomic data represent both the effect of these mutations on the encoded proteins and the perturbation induced by the mutated proteins to their neighbours in the protein-protein interaction network (PPIN). Finally, the phenotypic trait evaluated for each mutant virus is replicative fitness. To analyse these three sources of information a Partial Least Squares (PLS) regression model is fitted in order to extract the latent variables from data that explain (and relate) the significant variables to the fitness of TEV. The final output of this methodology is a set of functional modules of the PPIN relating topology and mutations with fitness. Throughout the re-analysis of these diverse TEV data, we generated valuable information on the mechanism of action of certain mutations and how they translate into organismal fitness. Results show that the effect of some mutations goes beyond the protein they directly affect and spreads on the PPIN to neighbour proteins, thus defining functional modules.

Evaluating the within-host fitness effects of mutations fixed during virus adaptation to different ecotypes of a new host

The existence of genetic variation for resistance in host populations is assumed to be essential to the spread of an emerging virus. Models predict that the rate of spread slows down with the increasing frequency and higher diversity of resistance alleles in the host population. We have been using the experimental pathosystem Arabidopsis thaliana-tobacco etch potyvirus (TEV) to explore the interplay between genetic variation in host's susceptibility and virus diversity. We have recently shown that TEV populations evolving in A. thaliana ecotypes that differ in susceptibility to infection gained within-host fitness, virulence and infectivity in a manner compatible with a gene-for-gene model of host-parasite interactions: hard-to-infect ecotypes were infected by generalist viruses, whereas easy-to-infect ecotypes were infected by every virus. We characterized the genomes of the evolved viruses and found cases of host-driven convergent mutations. To gain further insights in the mechanistic basis of this gene-for-gene model, we have generated all viral mutations individually as well as in specific combinations and tested their within-host fitness effects across ecotypes. Most of these mutations were deleterious or neutral in their local ecotype and only a very reduced number had a host-specific beneficial effect. We conclude that most of the mutations fixed during the evolution experiment were so by drift or by selective sweeps along with the selected driver mutation. In addition, we evaluated the ruggedness of the underlying adaptive fitness landscape and found that mutational effects were mostly multiplicative, with few cases of significant epistasis.

Genetic variation in fitness within a clonal population of a plant RNA virus

A long-standing observation in evolutionary virology is that RNA virus populations are highly polymorphic, composed by a mixture of genotypes whose abundances in the population depend on complex interaction between fitness differences, mutational coupling and genetic drift. It was shown long ago, though in cell cultures, that most of these genotypes had lower fitness than the population they belong, an observation that explained why single-virion passages turned on Muller’s ratchet while very large population passages resulted in fitness increases in novel environments. Here we report the results of an experiment specifically designed to evaluate in vivo the fitness differences among the subclonal components of a clonal population of the plant RNA virus tobacco etch potyvirus (TEV). Over 100 individual biological subclones from a TEV clonal population well adapted to the natural tobacco host were obtained by infectivity assays on a local lesion host. The replicative fitness of these subclones was then evaluated during infection of tobacco relative to the fitness of large random samples taken from the starting clonal population. Fitness was evaluated at increasing number of days post-inoculation. We found that at early days, the average fitness of subclones was significantly lower than the fitness of the clonal population, thus confirming previous observations that most subclones contained deleterious mutations. However, as the number of days of viral replication increases, population size expands exponentially, more beneficial and compensatory mutations are produced, and selection becomes more effective in optimizing fitness, the differences between subclones and the population disappeared.

Distribution of mutational fitness effects and of epistasis in the 5' untranslated region of a plant RNA virus

BACKGROUND

Understanding the causes and consequences of phenotypic variability is a central topic of evolutionary biology. Mutations within non-coding cis-regulatory regions are thought to be of major effect since they affect the expression of downstream genes. To address the evolutionary potential of mutations affecting such regions in RNA viruses, we explored the fitness properties of mutations affecting the 5'-untranslated region (UTR) of a prototypical member of the picorna-like superfamily, Tobacco etch virus (TEV). This 5' UTR acts as an internal ribosomal entry site (IRES) and is essential for expression of all viral genes.

RESULTS

We determined in vitro the folding of 5' UTR using the selective 2'-hydroxyl acylation analyzed by primer extension (SHAPE) technique. Then, we created a collection of single-nucleotide substitutions on this region and evaluated the statistical properties of their fitness effects in vivo. We found that, compared to random mutations affecting coding sequences, mutations at the 5' UTR were of weaker effect. We also created double mutants by combining pairs of these single mutations and found variation in the magnitude and sign of epistatic interactions, with an enrichment of cases of positive epistasis. A correlation exists between the magnitude of fitness effects and the size of the perturbation made in the RNA folding structure, suggesting that the larger the departure from the predicted fold, the more negative impact in viral fitness.

CONCLUSIONS

Evidence that mutational fitness effects on the short 5' UTR regulatory sequence of TEV are weaker than those affecting its coding sequences have been found. Epistasis among pairs of mutations on the 5' UTR ranged between the extreme cases of synthetic lethal and compensatory. A plausible hypothesis to explain all these observations is that the interaction between the 5' UTR and the host translational machinery was shaped by natural selection to be robust to mutations, thus ensuring the homeostatic expression of viral genes even at high mutation rates.

Reciprocal sign epistasis and truncation selection: When is recombination favorable in a pre-breeding program with a selfing species?

Since the dawn of agriculture, humans have applied artificial selection on traits of interest, regardless of their genetic architecture. Yet, still today, most models used to study and streamline this process overlook genetic interactions. In this study, we determined the conditions in which a target genotype can be fixed when truncation selection is applied on an epistatic trait. Previous studies have shown that reciprocal sign epistasis with two fitness peaks of unequal height involves multiple equilibrium states, i.e. below one critical parameter value, such as a critical recombination rate, one genotype may be fixed, and above it, another one may be fixed. Using a haploid bi-locus model, we identified which genotype would be fixed, and how quickly, in an infinite population selected for a phenotypic trait subject to reciprocal sign epistasis with unequal peak heights, depending on two criteria: the recombination rate and percentage of selected individuals. The critical parameter values at which bistability sets in, were also calculated. These results were complemented by stochastic simulations in finite populations. Our results confirmed that, in the case of fitness under reciprocal sign epistasis, high recombination rates induce blockage at the local optimum or attainment of an equilibrium state between the two peaks. However, if linkage disequilibrium is negative in the initial population, recombination is necessary to create the most favorable genotype. Therefore, in this case, reciprocal sign epistasis favors non-null recombination rates, particularly if selection is intense.

Bypass of genetic constraints during mutator evolution to antibiotic resistance

Genetic constraints can block many mutational pathways to optimal genotypes in real fitness landscapes, yet the extent to which this can limit evolution remains to be determined. Interestingly, mutator bacteria elevate only specific types of mutations, and therefore could be very sensitive to genetic constraints. Testing this possibility is not only clinically relevant, but can also inform about the general impact of genetic constraints in adaptation. Here, we evolved 576 populations of two mutator and one wild-type Escherichia coli to doubling concentrations of the antibiotic cefotaxime. All strains carried TEM-1, a β-lactamase enzyme well known by its low availability of mutational pathways. Crucially, one of the mutators does not elevate any of the relevant first-step mutations known to improve cefatoximase activity. Despite this, both mutators displayed a similar ability to evolve more than 1000-fold resistance. Initial adaptation proceeded in parallel through general multi-drug resistance mechanisms. High-level resistance, in contrast, was achieved through divergent paths; with the a priori inferior mutator exploiting alternative mutational pathways in PBP3, the target of the antibiotic. These results have implications for mutator management in clinical infections and, more generally, illustrate that limits to natural selection in real organisms are alleviated by the existence of multiple loci contributing to fitness.

RNA Silencing May Play a Role in but Is Not the Only Determinant of the Multiplicity of Infection

The multiplicity of infection (MOI), i.e., the number of viral genomes that infect a cell, is an important parameter in virus evolution, which for each virus and environment may have an optimum value that maximizes virus fitness. Thus, the MOI might be controlled by virus functions, an underexplored hypothesis in eukaryote-infecting viruses. To analyze if the MOI is controlled by virus functions, we estimated the MOI in plants coinfected by two genetic variants of Tomato bushy stunt virus (TBSV); by TBSV and a TBSV-derived defective interfering RNA (DI-RNA); or by TBSV and a second tombusvirus, Cymbidium ringspot virus (CymRSV). The MOI was significantly larger in TBSV-CymRSV coinfections (~4.0) than in TBSV-TBSV or TBSV-DI-RNA coinfections (~1.7 to 2.2). Coinfections by CymRSV or TBSV with chimeras in which an open reading frame (ORF) of one virus species was replaced by that of the other identified a role of viral proteins in determining the MOI, which ranged from 1.6 to 3.9 depending on the coinfecting genotypes. However, no virus-encoded protein or genomic region was the sole MOI determinant. Coinfections by CymRSV and TBSV mutants in which the expression of the gene-silencing suppressor protein p19 was abolished also showed a possible role of gene silencing in MOI determination. Taken together, these results demonstrate that the MOI is a quantitative trait showing continuous variation and that as such it has a complex determination involving different virus-encoded functions.

IMPORTANCE

The number of viral genomes infecting a cell, or the multiplicity of infection (MOI), is an important parameter in virus evolution affecting recombination rates, selection intensity on viral genes, evolution of multipartite genomes, or hyperparasitism by satellites or defective interfering particles. For each virus and environment, the MOI may have an optimum value that maximizes virus fitness, but little is known about MOI control in eukaryote-infecting viruses. We show here that in plants coinfected by two genotypes of Tomato bushy stunt virus (TBSV), the MOI was lower than in plants coinfected by TBSV and Cymbidium ringspot virus (CymRSV). Coinfections by CymRSV or TBSV with TBSV-CymRSV chimeras showed a role of viral proteins in MOI determination. Coinfections by CymRSV and TBSV mutants not expressing the gene-silencing suppressor protein also showed a role of gene silencing in MOI determination. The results demonstrate that the MOI is a quantitative trait with a complex determination involving different viral functions.

The impact of high-order epistasis in the within-host fitness of a positive-sense plant RNA virus

RNA viruses are the main source of emerging infectious diseases because of the evolutionary potential bestowed by their fast replication, large population sizes and high mutation and recombination rates. However, an equally important property, which is usually neglected, is the topography of the fitness landscape. How many fitness maxima exist and how well they are connected is especially interesting, as this determines the number of accessible evolutionary pathways. To address this question, we have reconstructed a region of the fitness landscape of tobacco etch potyvirus constituted by mutations observed during the experimental adaptation of the virus to the novel host Arabidopsis thaliana. Fitness was measured for many genotypes and showed the existence of multiple peaks and holes in the landscape. We found prevailing epistatic effects between mutations, with cases of reciprocal sign epistasis being common among pairs of mutations. We also found that high-order epistasis was as important as pairwise epistasis in their contribution to fitness. Therefore, results suggest that the landscape was rugged due to the existence of holes caused by lethal genotypes, that a very limited number of potential neutral paths exist and that it contained a single adaptive peak.

Fitness Landscapes of Functional RNAs

The notion of fitness landscapes, a map between genotype and fitness, was proposed more than 80 years ago. For most of this time data was only available for a few alleles, and thus we had only a restricted view of the whole fitness landscape. Recently, advances in genetics and molecular biology allow a more detailed view of them. Here we review experimental and theoretical studies of fitness landscapes of functional RNAs, especially aptamers and ribozymes. We find that RNA structures can be divided into critical structures, connecting structures, neutral structures and forbidden structures. Such characterisation, coupled with theoretical sequence-to-structure predictions, allows us to construct the whole fitness landscape. Fitness landscapes then can be used to study evolution, and in our case the development of the RNA world.

Temporal dynamics of intrahost molecular evolution for a plant RNA virus

Populations of plant RNA viruses are highly polymorphic in infected plants, which may allow rapid within-host evolution. To understand tobacco etch potyvirus (TEV) evolution, longitudinal samples from experimentally evolved populations in the natural host tobacco and from the alternative host pepper were phenotypically characterized and genetically analyzed. Temporal and compartmental variabilities of TEV populations were quantified using high throughput Illumina sequencing and population genetic approaches. Of the two viral phenotypic traits measured, virulence increased in the novel host but decreased in the original one, and viral load decreased in both hosts, though to a lesser extent in the novel one. Dynamics of population genetic diversity were also markedly different among hosts. Population heterozygosity increased in the ancestral host, with a dominance of synonymous mutations fixed, whereas it did not change or even decreased in the new host, with an excess of nonsynonymous mutations. All together, these observations suggest that directional selection is the dominant evolutionary force in TEV populations evolving in a novel host whereas either diversifying selection or random genetic drift may play a fundamental role in the natural host. To better understand these evolutionary dynamics, we developed a computer simulation model that incorporates the effects of mutation, selection, and drift. Upon parameterization with empirical data from previous studies, model predictions matched the observed patterns, thus reinforcing our idea that the empirical patterns of mutation accumulation represent adaptive evolution.

Getting to Know Viral Evolutionary Strategies: Towards the Next Generation of Quasispecies Models

Viral populations are formed by complex ensembles of genomes with broad phenotypic diversity. The adaptive strategies deployed by these ensembles are multiple and often cannot be predicted a priori. Our understanding of viral dynamics is mostly based on two kinds of empirical approaches: one directed towards characterizing molecular changes underlying fitness changes and another focused on population-level responses. Simultaneously, theoretical efforts are directed towards developing a formal picture of viral evolution by means of more realistic fitness landscapes and reliable population dynamics models. New technologies, chiefly the use of next-generation sequencing and related tools, are opening avenues connecting the molecular and the population levels. In the near future, we hope to be witnesses of an integration of these still decoupled approaches, leading into more accurate and realistic quasispecies models able to capture robust generalities and endowed with a satisfactory predictive power.

Emerging viruses: why they are not jacks of all trades?

In order to limit the impact of the recent pandemics ignited by viral host jumps, it is necessary to better understand the ecological and evolutionary factors influencing the early steps of emergence and the interactions between them. Antagonistic pleiotropy, that is, the negative fitness effect in the primary host of mutations allowing the infection of and the multiplication in a new host, has long been thought to be the main limitation to the evolution of generalist viruses and thus to emergence. However, the accumulation of experimental examples contradicting the hypothesis of antagonistic pleiotropy has highlighted the importance of other factors such as the epistasis between mutations increasing the adaptation to a new host. Epistasis is pervasive in viruses, affects the shape of the adaptive landscape and consequently the accessibility of evolutionary pathways. Finally, recent studies have gone steps further in the complexity of viral fitness determinism and stressed the potential importance of the epistatic pleiotropy and of the impact of host living conditions.

The Valley-of-Death: reciprocal sign epistasis constrains adaptive trajectories in a constant, nutrient limiting environment

The fitness landscape is a powerful metaphor for describing the relationship between genotype and phenotype for a population under selection. However, empirical data as to the topography of fitness landscapes are limited, owing to difficulties in measuring fitness for large numbers of genotypes under any condition. We previously reported a case of reciprocal sign epistasis (RSE), where two mutations individually increased yeast fitness in a glucose-limited environment, but reduced fitness when combined, suggesting the existence of two peaks on the fitness landscape. We sought to determine whether a ridge connected these peaks so that populations founded by one mutant could reach the peak created by the other, avoiding the low-fitness "Valley-of-Death" between them. Sequencing clones after 250 generations of further evolution provided no evidence for such a ridge, but did reveal many presumptive beneficial mutations, adding to a growing body of evidence that clonal interference pervades evolving microbial populations.

What can we learn from fitness landscapes?

A combinatorially complete data set consists of studies of all possible combinations of a set of mutant sites in a gene or mutant alleles in a genome. Among the most robust conclusions from these studies is that epistasis between beneficial mutations often shows a pattern of diminishing returns, in which favorable mutations are less fit when combined than would be expected. Another robust inference is that the number of adaptive evolutionary paths is often limited to a relatively small fraction of the theoretical possibilities, owing largely to sign epistasis requiring evolutionary steps that would entail a decrease in fitness. Here we summarize these and other results while also examining issues that remain unresolved and future directions that seem promising.

The spectrum of adaptive mutations in experimental evolution

A primary goal of recent work in experimental evolution is to probe the molecular basis of adaptation. This requires an understanding of the individual mutations in evolving populations: their identity, their physiological and fitness effects, and the interactions between them. The combination of high-throughput methods for laboratory evolution and next-generation sequencing methods now makes it possible to identify and quantify mutations in hundreds of replicate populations over thousands of generations, and to directly measure fitness effects and epistatic interactions. Many laboratories are now leveraging these tools to study the molecular basis of adaptation and the reproducibility of evolutionary outcomes across a variety of model systems. Genetic analyses on evolved populations are shedding light on the statistics of epistasis between evolved mutations. Here we review the current understanding of the spectrum of mutations observed across these systems, with a focus on epistatic interactions between beneficial mutations and constraints on evolutionary outcomes. We emphasize evolution in asexual microbes, where next generation sequencing methods have been widely applied.

Evolution and emergence of plant viruses

Viruses are common agents of plant infectious diseases. During last decades, worldwide agriculture production has been compromised by a series of epidemics caused by new viruses that spilled over from reservoir species or by new variants of classic viruses that show new pathogenic and epidemiological properties. Virus emergence has been generally associated with ecological change or with intensive agronomical practices. However, the complete picture is much more complex since the viral populations constantly evolve and adapt to their new hosts and vectors. This chapter puts emergence of plant viruses into the framework of evolutionary ecology, genetics, and epidemiology. We will stress that viral emergence begins with the stochastic transmission of preexisting genetic variants from the reservoir to the new host, whose fate depends on their fitness on each hosts, followed by adaptation to new hosts or vectors, and finalizes with an efficient epidemiological spread.

Experimental evolution of an emerging plant virus in host genotypes that differ in their susceptibility to infection

This study evaluates the extent to which genetic differences among host individuals from the same species condition the evolution of a plant RNA virus. We performed a threefold replicated evolution experiment in which Tobacco etch potyvirus isolate At17b (TEV-At17b), adapted to Arabidopsis thaliana ecotype Ler-0, was serially passaged in five genetically heterogeneous ecotypes of A. thaliana. After 15 passages we found that evolved viruses improved their fitness, showed higher infectivity and stronger virulence in their local host ecotypes. The genome of evolved lineages was sequenced and putative adaptive mutations identified. Host-driven convergent mutations have been identified. Evidences supported selection for increased translational efficiency. Next, we sought for the specificity of virus adaptation by infecting all five ecotypes with all 15 evolved virus populations. We found that some ecotypes were more permissive to infection than others, and that some evolved virus isolates were more specialist/generalist than others. The bipartite network linking ecotypes with evolved viruses was significantly nested but not modular, suggesting that hard-to-infect ecotypes were infected by generalist viruses whereas easy-to-infect ecotypes were infected by all viruses, as predicted by a gene-for-gene model of infection.

Extensive recombination-induced disruption of genetic interactions is highly deleterious but can be partially reversed by small numbers of secondary recombination events

Although homologous recombination can potentially provide viruses with vastly more evolutionary options than are available through mutation alone, there are considerable limits on the adaptive potential of this important evolutionary process. Primary among these is the disruption of favorable coevolved genetic interactions that can occur following the transfer of foreign genetic material into a genome. Although the fitness costs of such disruptions can be severe, in some cases they can be rapidly recouped by either compensatory mutations or secondary recombination events. Here, we used a maize streak virus (MSV) experimental model to explore both the extremes of recombination-induced genetic disruption and the capacity of secondary recombination to adaptively reverse almost lethal recombination events. Starting with two naturally occurring parental viruses, we synthesized two of the most extreme conceivable MSV chimeras, each effectively carrying 182 recombination breakpoints and containing thorough reciprocal mixtures of parental polymorphisms. Although both chimeras were severely defective and apparently noninfectious, neither had individual movement-, encapsidation-, or replication-associated genome regions that were on their own "lethally recombinant." Surprisingly, mixed inoculations of the chimeras yielded symptomatic infections with viruses with secondary recombination events. These recombinants had only 2 to 6 breakpoints, had predominantly inherited the least defective of the chimeric parental genome fragments, and were obviously far more fit than their synthetic parents. It is clearly evident, therefore, that even when recombinationally disrupted virus genomes have extremely low fitness and there are no easily accessible routes to full recovery, small numbers of secondary recombination events can still yield tremendous fitness gains. Importance: Recombination between viruses can generate strains with enhanced pathological properties but also runs the risk of producing hybrid genomes with decreased fitness due to the disruption of favorable genetic interactions. Using two synthetic maize streak virus genome chimeras containing alternating genome segments derived from two natural viral strains, we examined both the fitness costs of extreme degrees of recombination (both chimeras had 182 recombination breakpoints) and the capacity of secondary recombination events to recoup these costs. After the severely defective chimeras were introduced together into a suitable host, viruses with between 1 and 3 secondary recombination events arose, which had greatly increased replication and infective capacities. This indicates that even in extreme cases where recombination-induced genetic disruptions are almost lethal, and 91 consecutive secondary recombination events would be required to reconstitute either one of the parental viruses, moderate degrees of fitness recovery can be achieved through relatively small numbers of secondary recombination events.

RNA virus evolution at variable error rate

ABSTRACT: 

RNA viruses replicate their genomes with very high error rates, which leads to the generation of a large genetic diversity that makes them highly adaptable to most environmental pressures, including antiviral drugs and immune responses. However, since most mutations are deleterious, an excess of errors can be very negative for RNA viruses, entailing that error rates must be finely regulated. Currently, the manipulation of the error rate is emerging as a promising antiviral therapy that could minimize the problem of virus adaptation to classical treatments. This review provides a detailed analysis of the different outcomes that can result from the variation of the error rate in RNA viruses, on the basis of the more relevant findings obtained in experimental studies.

Adaptive walks and distribution of beneficial fitness effects

We study the adaptation dynamics of a maladapted asexual population on rugged fitness landscapes with many local fitness peaks. The distribution of beneficial fitness effects is assumed to belong to one of the three extreme value domains, viz. Weibull, Gumbel, and Fréchet. We work in the strong selection-weak mutation regime in which beneficial mutations fix sequentially, and the population performs an uphill walk on the fitness landscape until a local fitness peak is reached. A striking prediction of our analysis is that the fitness difference between successive steps follows a pattern of diminishing returns in the Weibull domain and accelerating returns in the Fréchet domain, as the initial fitness of the population is increased. These trends are found to be robust with respect to fitness correlations. We believe that this result can be exploited in experiments to determine the extreme value domain of the distribution of beneficial fitness effects. Our work here differs significantly from the previous ones that assume the selection coefficient to be small. On taking large effect mutations into account, we find that the length of the walk shows different qualitative trends from those derived using small selection coefficient approximation.

Empirical complexities in the genetic foundations of lethal mutagenesis

From population genetics theory, elevating the mutation rate of a large population should progressively reduce average fitness. If the fitness decline is large enough, the population will go extinct in a process known as lethal mutagenesis. Lethal mutagenesis has been endorsed in the virology literature as a promising approach to viral treatment, and several in vitro studies have forced viral extinction with high doses of mutagenic drugs. Yet only one empirical study has tested the genetic models underlying lethal mutagenesis, and the theory failed on even a qualitative level. Here we provide a new level of analysis of lethal mutagenesis by developing and evaluating models specifically tailored to empirical systems that may be used to test the theory. We first quantify a bias in the estimation of a critical parameter and consider whether that bias underlies the previously observed lack of concordance between theory and experiment. We then consider a seemingly ideal protocol that avoids this bias-mutagenesis of virions-but find that it is hampered by other problems. Finally, results that reveal difficulties in the mere interpretation of mutations assayed from double-strand genomes are derived. Our analyses expose unanticipated complexities in testing the theory. Nevertheless, the previous failure of the theory to predict experimental outcomes appears to reside in evolutionary mechanisms neglected by the theory (e.g., beneficial mutations) rather than from a mismatch between the empirical setup and model assumptions. This interpretation raises the specter that naive attempts at lethal mutagenesis may augment adaptation rather than retard it.

Patterns of Epistasis between beneficial mutations in an antibiotic resistance gene

Understanding epistasis is central to biology. For instance, epistatic interactions determine the topography of the fitness landscape and affect the dynamics and determinism of adaptation. However, few empirical data are available, and comparing results is complicated by confounding variation in the system and the type of mutations used. Here, we take a systematic approach by quantifying epistasis in two sets of four beneficial mutations in the antibiotic resistance enzyme TEM-1 β-lactamase. Mutations in these sets have either large or small effects on cefotaxime resistance when present as single mutations. By quantifying the epistasis and ruggedness in both landscapes, we find two general patterns. First, resistance is maximal for combinations of two mutations in both fitness landscapes and declines when more mutations are added due to abundant sign epistasis and a pattern of diminishing returns with genotype resistance. Second, large-effect mutations interact more strongly than small-effect mutations, suggesting that the effect size of mutations may be an organizing principle in understanding patterns of epistasis. By fitting the data to simple phenotype resistance models, we show that this pattern may be explained by the nonlinear dependence of resistance on enzyme stability and an unknown phenotype when mutations have antagonistically pleiotropic effects. The comparison to a previously published set of mutations in the same gene with a joint benefit further shows that the enzyme's fitness landscape is locally rugged but does contain adaptive pathways that lead to high resistance.

Epistasis between antibiotic resistance mutations drives the evolution of extensively drug-resistant tuberculosis

BACKGROUND AND OBJECTIVES

Multidrug resistant (MDR) bacteria are a growing threat to global health. Studies focusing on single antibiotics have shown that drug resistance is often associated with a fitness cost in the absence of drug. However, little is known about the fitness cost associated with resistance to multiple antibiotics.

METHODOLOGY

We used Mycobacterium smegmatis as a model for human tuberculosis (TB) and an in vitro competitive fitness assay to explore the combined fitness effects and interaction between mutations conferring resistance to rifampicin (RIF) and ofloxacin (OFX); two of the most important first- and second-line anti-TB drugs, respectively.

RESULTS

We found that 4 out of 17 M. smegmatis mutants (24%) resistant to RIF and OFX showed a statistically significantly higher or lower competitive fitness than expected when assuming a multiplicative model of fitness effects of each individual mutation. Moreover, 6 out of the 17 double drug-resistant mutants (35%) had a significantly higher fitness than at least one of the corresponding single drug-resistant mutants. The particular combinations of resistance mutations associated with no fitness deficit in M. smegmatis were the most frequent among 151 clinical isolates of MDR and extensively drug-resistant (XDR) Mycobacterium tuberculosis from South Africa.

CONCLUSIONS AND IMPLICATIONS

Our results suggest that epistasis between drug resistance mutations in mycobacteria can lead to MDR strains with no fitness deficit, and that these strains are positively selected in settings with a high burden of drug-resistant TB. Taken together, our findings support a role for epistasis in the evolution and epidemiology of MDR- and XDR-TB.

Epistasis between mutations is host-dependent for an RNA virus

How, and to what extent, does the environment influence the way mutations interact? Do environmental changes affect both the sign and the magnitude of epistasis? Are there any correlations between environments in the variability, sign or magnitude of epistasis? Very few studies have tackled these questions. Here, we addressed them in the context of viral emergence. Most emerging viruses are RNA viruses with small genomes, overlapping reading frames and multifunctional proteins for which epistasis is abundant. Understanding the effect of host species in the sign and magnitude of epistasis will provide insights into the evolutionary ecology of infectious diseases and the predictability of viral emergence.

Genotypic but not phenotypic historical contingency revealed by viral experimental evolution

BACKGROUND

The importance of historical contingency in determining the potential of viral populations to evolve has been largely unappreciated. Identifying the constraints imposed by past adaptations is, however, of importance for understanding many questions in evolutionary biology, such as the evolution of host usage dynamics by multi-host viruses or the emergence of escape mutants that persist in the absence of antiviral treatments. To address this issue, we undertook an experimental approach in which sixty lineages of Tobacco etch potyvirus that differ in their past evolutionary history and degree of adaptation to Nicotiana tabacum were allowed to adapt to this host for 15 rounds of within host multiplication and transfer. We thereafter evaluated the degree of adaptation to the new host as well as to the original ones and characterized the consensus sequence of each lineage.

RESULTS

We found that past evolutionary history did not determine the phenotypic outcome of this common host evolution phase, and that the signal of local adaptation to past hosts had largely disappeared. By contrast, evolutionary history left footprints at the genotypic level, since the majority of host-specific mutations present at the beginning of this experiment were retained in the end-point populations and may have affected which new mutations were consequently fixed. This resulted in further divergence between the sequences despite a shared selective environment.

CONCLUSIONS

The present experiment reinforces the idea that the answer to the question "How important is historical contingency in evolution?" strongly depends on the level of integration of the traits studied. A strong historical contingency was found for TEV genotype, whereas a weak effect of on phenotypic evolution was revealed. In an applied context, our results imply that viruses are not easily trapped into suboptimal phenotypes and that (re)emergence is not evolutionarily constrained.

Evolution at increased error rate leads to the coexistence of multiple adaptive pathways in an RNA virus

Background

When beneficial mutations present in different genomes spread simultaneously in an asexual population, their fixation can be delayed due to competition among them. This interference among mutations is mainly determined by the rate of beneficial mutations, which in turn depends on the population size, the total error rate, and the degree of adaptation of the population. RNA viruses, with their large population sizes and high error rates, are good candidates to present a great extent of interference. To test this hypothesis, in the current study we have investigated whether competition among beneficial mutations was responsible for the prolonged presence of polymorphisms in the mutant spectrum of an RNA virus, the bacteriophage Qβ, evolved during a large number of generations in the presence of the mutagenic nucleoside analogue 5-azacytidine.

Results

The analysis of the mutant spectra of bacteriophage Qβ populations evolved at artificially increased error rate shows a large number of polymorphic mutations, some of them with demonstrated selective value. Polymorphisms distributed into several evolutionary lines that can compete among them, making it difficult the emergence of a defined consensus sequence. The presence of accompanying deleterious mutations, the high degree of recurrence of the polymorphic mutations, and the occurrence of epistatic interactions generate a highly complex interference dynamics.

Conclusions

Interference among beneficial mutations in bacteriophage Qβ evolved at increased error rate permits the coexistence of multiple adaptive pathways that can provide selective advantages by different molecular mechanisms. In this way, interference can be seen as a positive factor that allows the exploration of the different local maxima that exist in rugged fitness landscapes.