Evolvability of an RNA virus is determined by its mutational neighbourhood

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.

Adaptation of Escherichia coli to glucose promotes evolvability in lactose

The selective history of a population can influence its subsequent evolution, an effect known as historical contingency. We previously observed that five of six replicate populations that were evolved in a glucose-limited environment for 2000 generations, then switched to lactose for 1000 generations, had higher fitness increases in lactose than populations started directly from the ancestor. To test if selection in glucose systematically increased lactose evolvability, we started 12 replay populations--six from a population subsample and six from a single randomly selected clone--from each of the six glucose-evolved founder populations. These replay populations and 18 ancestral populations were evolved for 1000 generations in a lactose-limited environment. We found that replay populations were initially slightly less fit in lactose than the ancestor, but were more evolvable, in that they increased in fitness at a faster rate and to higher levels. This result indicates that evolution in the glucose environment resulted in genetic changes that increased the potential of genotypes to adapt to lactose. Genome sequencing identified four genes--iclR, nadR, spoT, and rbs--that were mutated in most glucose-evolved clones and are candidates for mediating increased evolvability. Our results demonstrate that short-term selective costs during selection in one environment can lead to changes in evolvability that confer longer term benefits.

Replaying the tape of life in the twenty-first century

Should the tape of life be replayed, would it produce similar living beings? A classical answer has long been ‘no’, but accumulating data are now challenging this view. Repeatability in experimental evolution, in phenotypic evolution of diverse species and in the genes underlying phenotypic evolution indicates that despite unpredictability at the level of basic evolutionary processes (such as apparition of mutations), a certain kind of predictability can emerge at higher levels over long time periods. For instance, a survey of the alleles described in the literature that cause non-deleterious phenotypic differences among animals, plants and yeasts indicates that similar phenotypes have often evolved in distinct taxa through independent mutations in the same genes. Does this mean that the range of possibilities for evolution is limited? Does this mean that we can predict the outcomes of a replayed tape of life? Imagining other possible paths for evolution runs into four important issues: (i) resolving the influence of contingency, (ii) imagining living organisms that are different from the ones we know, (iii) finding the relevant concepts for predicting evolution, and (iv) estimating the probability of occurrence for complex evolutionary events that occurred only once during the evolution of life on earth.

High definition viral vaccine strain identity and stability testing using full-genome population data--The next generation of vaccine quality control

BACKGROUND

Vaccines are the most effective prophylactic public health tools. With the help of vaccines, prevention of infectious disease spread and, in concert with other measures, even eradication has become possible. Until now, licensing and quality control require the determination of consensus genome sequences of replication competent infectious agents contained in vaccines. Recent improvements in sequencing technologies now enable the sequencing of complete genomes and the genetic analysis of populations with high reliability and resolution. The latter is particularly important for RNA viruses, which consist of fluctuating heterogeneous populations rather than genetically stable entities. This information now has to be integrated into the existing regulatory framework, challenging both licensing authorities and vaccine producers to develop new quality control criteria.

METHODS

Commercially available modified-live oral rabies vaccines and their precursor strains were deep-sequenced to assess strain identity and relations between strains based on population diversity. Strain relations were inferred based on the Manhattan distances calculated between the compositions of the viral populations of the strains.

RESULTS

We provide a novel approach to assess viral strain relations with high resolution and reliability by deep sequencing with subsequent analysis of the overall genetic diversity within the viral populations. A comparison of our novel approach of inferring strain relations based on population data with consensus sequence analysis clearly shows that consensus sequence analysis of diverse viral populations can be misleading. Therefore, for quality control of viral vaccines deep sequencing analysis is to be preferred over consensus sequence analysis.

CONCLUSIONS

The presented methodology allows for routine integration of deep sequencing data in vaccine quality control and licensing for highly reliable assessment of strain identity and stability.

Molecular architecture of silk fibroin of Indian golden silkmoth, Antheraea assama

The golden silk spun by Indian golden silkmoth Antheraea assama, is regarded for its shimmering golden luster, tenacity and value as biomaterial. This report describes the gene coding for golden silk H-fibroin (AaFhc), its expression, full-length sequence and structurally important motifs discerning the underlying genetic and biochemical factors responsible for its much sought-after properties. The coding region, with biased isocodons, encodes highly repetitious crystalline core, flanked by a pair of 5′ and 3′ non-repetitious ends. AaFhc mRNA expression is strictly territorial, confined to the posterior silk gland, encoding a protein of size 230 kDa, which makes homodimers making the elementary structural units of the fibrous core of the golden silk. Characteristic polyalanine repeats that make tight β-sheet crystals alternate with non-polyalanine repeats that make less orderly antiparallel β-sheets, β-turns and partial α-helices. Phylogenetic analysis of the conserved N-terminal amorphous motif and the comparative analysis of the crystalline region with other saturniid H-fibroins reveal that AaFhc has longer, numerous and relatively uniform repeat motifs with lower serine content that assume tighter β-crystals and denser packing, which are speculated to be responsible for its acclaimed properties of higher tensile strength and higher refractive index responsible for golden luster.

Similarities between Human Immunodeficiency Virus Type 1 and Hepatitis C Virus Genetic and Phenotypic Protease Quasispecies Diversity

Human immunodeficiency virus type 1 (HIV-1) and hepatitis C virus (HCV) are two highly variable RNA viruses that cause chronic infections in humans. Although HCV likely preceded the AIDS epidemic by some decades, the global spread of both viruses is a relatively recent event. Nevertheless, HCV global diversity is higher than that of HIV-1. To identify differences in mutant diversity, we compared the HIV-1 protease and HCV NS3 protease quasispecies. Three protease gene quasispecies samples per virus, isolated from a total of six infected patients, were genetically and phenotypically analyzed at high resolution (HIV-1, 308 individual clones; HCV, 299 clones). Single-nucleotide variant frequency did not differ between quasispecies from the two viruses (HIV-1, 2.4 × 10(-3) ± 0.4 × 10(-3); HCV, 2.1 × 10(-3) ± 0.5 × 10(-3)) (P = 0.1680). The proportion of synonymous substitutions to potential synonymous sites was similar (3.667 ± 0.6667 and 2.183 ± 0.9048, respectively) (P = 0.2573), and Shannon's entropy values did not differ between HIV-1 and HCV (0.84 ± 0.02 and 0.83 ± 0.12, respectively) (P = 0.9408). Of note, 65% (HIV-1) and 67% (HCV) of the analyzed enzymes displayed detectable protease activity, suggesting that both proteases have a similar mutational robustness. In both viruses, there was a rugged protease enzymatic activity landscape characterized by a sharp peak, representing the master sequence, surrounded by a collection of diverse variants present at lower frequencies. These results indicate that nucleotide quasispecies diversification during chronic infection is not responsible for the higher worldwide genetic diversity observed in HCV.

IMPORTANCE

HCV global diversity is higher than that of HIV-1. We asked whether HCV genetic diversification during infection is responsible for the higher worldwide genetic diversity observed in HCV. To this end, we analyzed and compared the genotype and enzymatic activities of HIV-1 and HCV protease quasispecies existing in infected individuals. Our results indicate that HIV-1 and HCV protease quasispecies have very similar genetic diversity and comparable rugged enzymatic activity landscapes. Therapy for HCV has expanded, with new therapeutic agents such as the direct-acting antivirals (DAAs). DAAs, which target HCV NS3 protease and other virus proteins, have improved cure rates. However, major questions remain to be elucidated regarding the virologic correlates of HCV eradication. The findings shown here may help our understanding of the different therapeutic responses observed during chronic HCV infection.

BAsE-Seq: a method for obtaining long viral haplotypes from short sequence reads

We present a method for obtaining long haplotypes, of over 3 kb in length, using a short-read sequencer, Barcode-directed Assembly for Extra-long Sequences (BAsE-Seq). BAsE-Seq relies on transposing a template-specific barcode onto random segments of the template molecule and assembling the barcoded short reads into complete haplotypes. We applied BAsE-Seq on mixed clones of hepatitis B virus and accurately identified haplotypes occurring at frequencies greater than or equal to 0.4%, with >99.9% specificity. Applying BAsE-Seq to a clinical sample, we obtained over 9,000 viral haplotypes, which provided an unprecedented view of hepatitis B virus population structure during chronic infection. BAsE-Seq is readily applicable for monitoring quasispecies evolution in viral diseases.

A genomic and evolutionary approach reveals non-genetic drug resistance in malaria

BACKGROUND

Drug resistance remains a major public health challenge for malaria treatment and eradication. Individual loci associated with drug resistance to many antimalarials have been identified, but their epistasis with other resistance mechanisms has not yet been elucidated.

RESULTS

We previously described two mutations in the cytoplasmic prolyl-tRNA synthetase (cPRS) gene that confer resistance to halofuginone. We describe here the evolutionary trajectory of halofuginone resistance of two independent drug resistance selections in Plasmodium falciparum. Using this novel methodology, we discover an unexpected non-genetic drug resistance mechanism that P. falciparum utilizes before genetic modification of the cPRS. P. falciparum first upregulates its proline amino acid homeostasis in response to halofuginone pressure. We show that this non-genetic adaptation to halofuginone is not likely mediated by differential RNA expression and precedes mutation or amplification of the cPRS gene. By tracking the evolution of the two drug resistance selections with whole genome sequencing, we further demonstrate that the cPRS locus accounts for the majority of genetic adaptation to halofuginone in P. falciparum. We further validate that copy-number variations at the cPRS locus also contribute to halofuginone resistance.

CONCLUSIONS

We provide a three-step model for multi-locus evolution of halofuginone drug resistance in P. falciparum. Informed by genomic approaches, our results provide the first comprehensive view of the evolutionary trajectory malaria parasites take to achieve drug resistance. Our understanding of the multiple genetic and non-genetic mechanisms of drug resistance informs how we will design and pair future anti-malarials for clinical use.

BAsE-Seq: a method for obtaining long viral haplotypes from short sequence reads

We present a method for obtaining long haplotypes, of over 3 kb in length, using a short-read sequencer, Barcode-directed Assembly for Extra-long Sequences (BAsE-Seq). BAsE-Seq relies on transposing a template-specific barcode onto random segments of the template molecule and assembling the barcoded short reads into complete haplotypes. We applied BAsE-Seq on mixed clones of hepatitis B virus and accurately identified haplotypes occurring at frequencies greater than or equal to 0.4%, with >99.9% specificity. Applying BAsE-Seq to a clinical sample, we obtained over 9,000 viral haplotypes, which provided an unprecedented view of hepatitis B virus population structure during chronic infection. BAsE-Seq is readily applicable for monitoring quasispecies evolution in viral diseases.

A genomic and evolutionary approach reveals non-genetic drug resistance in malaria

Background

Drug resistance remains a major public health challenge for malaria treatment and eradication. Individual loci associated with drug resistance to many antimalarials have been identified, but their epistasis with other resistance mechanisms has not yet been elucidated.

Results

We previously described two mutations in the cytoplasmic prolyl-tRNA synthetase (cPRS) gene that confer resistance to halofuginone. We describe here the evolutionary trajectory of halofuginone resistance of two independent drug resistance selections in Plasmodium falciparum. Using this novel methodology, we discover an unexpected non-genetic drug resistance mechanism that P. falciparum utilizes before genetic modification of the cPRS. P. falciparum first upregulates its proline amino acid homeostasis in response to halofuginone pressure. We show that this non-genetic adaptation to halofuginone is not likely mediated by differential RNA expression and precedes mutation or amplification of the cPRS gene. By tracking the evolution of the two drug resistance selections with whole genome sequencing, we further demonstrate that the cPRS locus accounts for the majority of genetic adaptation to halofuginone in P. falciparum. We further validate that copy-number variations at the cPRS locus also contribute to halofuginone resistance.

Conclusions

We provide a three-step model for multi-locus evolution of halofuginone drug resistance in P. falciparum. Informed by genomic approaches, our results provide the first comprehensive view of the evolutionary trajectory malaria parasites take to achieve drug resistance. Our understanding of the multiple genetic and non-genetic mechanisms of drug resistance informs how we will design and pair future anti-malarials for clinical use.

Electronic supplementary material

The online version of this article (doi:10.1186/s13059-014-0511-2) contains supplementary material, which is available to authorized users.

Negative Epistasis and Evolvability in TEM-1 β-Lactamase--The Thin Line between an Enzyme's Conformational Freedom and Disorder

Epistasis is a key factor in evolution since it determines which combinations of mutations provide adaptive solutions and which mutational pathways toward these solutions are accessible by natural selection. There is growing evidence for the pervasiveness of sign epistasis--a complete reversion of mutational effects, particularly in protein evolution--yet its molecular basis remains poorly understood. We describe the structural basis of sign epistasis between G238S and R164S, two adaptive mutations in TEM-1 β-lactamase--an enzyme that endows antibiotics resistance. Separated by 10 Å, these mutations initiate two separate trajectories toward increased hydrolysis rates and resistance toward second and third-generation cephalosporins antibiotics. Both mutations allow the enzyme's active site to adopt alternative conformations and accommodate the new antibiotics. By solving the corresponding set of crystal structures, we found that R164S causes local disorder whereas G238S induces discrete conformations. When combined, the mutations in 238 and 164 induce local disorder whereby nonproductive conformations that perturb the enzyme's catalytic preorganization dominate. Specifically, Asn170 that coordinates the deacylating water molecule is misaligned, in both the free form and the inhibitor-bound double mutant. This local disorder is not restored by stabilizing global suppressor mutations and thus leads to an evolutionary cul-de-sac. Conformational dynamism therefore underlines the reshaping potential of protein's structures and functions but also limits protein evolvability because of the fragility of the interactions networks that maintain protein structures.

Group Selection and Contribution of Minority Variants during Virus Adaptation Determines Virus Fitness and Phenotype

Understanding how a pathogen colonizes and adapts to a new host environment is a primary aim in studying emerging infectious diseases. Adaptive mutations arise among the thousands of variants generated during RNA virus infection, and identifying these variants will shed light onto how changes in tropism and species jumps can occur. Here, we adapted Coxsackie virus B3 to a highly permissive and less permissive environment. Using deep sequencing and bioinformatics, we identified a multi-step adaptive process to adaptation involving residues in the receptor footprints that correlated with receptor availability and with increase in virus fitness in an environment-specific manner. We show that adaptation occurs by selection of a dominant mutation followed by group selection of minority variants that together, confer the fitness increase observed in the population, rather than selection of a single dominant genotype.

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.

Delayed transmission selects for increased survival of vesicular stomatitis virus

Life-history theory predicts that traits for survival and reproduction cannot be simultaneously maximized in evolving populations. For this reason, in obligate parasites such as infectious viruses, selection for improved between-host survival during transmission may lead to evolution of decreased within-host reproduction. We tested this idea using experimental evolution of RNA virus populations, passaged under differing transmission times in the laboratory. A single ancestral genotype of vesicular stomatitis virus (VSV), a negative-sense RNA Rhabdovirus, was used to found multiple virus lineages evolved in either ordinary 24-h cell-culture passage, or in delayed passages of 48 h. After 30 passages (120 generations of viral evolution), we observed that delayed transmission selected for improved extracellular survival, which traded-off with lowered viral fecundity (slower exponential population growth and smaller mean plaque size). To further examine the confirmed evolutionary trade-off, we obtained consensus whole-genome sequences of evolved virus populations, to infer phenotype-genotype associations. Results implied that increased virus survival did not occur via convergence; rather, improved virion stability was gained via independent mutations in various VSV structural proteins. Our study suggests that RNA viruses can evolve different molecular solutions for enhanced survival despite their limited genetic architecture, but suffer generalized reproductive trade-offs that limit overall fitness gains.

A framework for inferring fitness landscapes of patient-derived viruses using quasispecies theory

Fitness is a central quantity in evolutionary models of viruses. However, it remains difficult to determine viral fitness experimentally, and existing in vitro assays can be poor predictors of in vivo fitness of viral populations within their hosts. Next-generation sequencing can nowadays provide snapshots of evolving virus populations, and these data offer new opportunities for inferring viral fitness. Using the equilibrium distribution of the quasispecies model, an established model of intrahost viral evolution, we linked fitness parameters to the composition of the virus population, which can be estimated by next-generation sequencing. For inference, we developed a Bayesian Markov chain Monte Carlo method to sample from the posterior distribution of fitness values. The sampler can overcome situations where no maximum-likelihood estimator exists, and it can adaptively learn the posterior distribution of highly correlated fitness landscapes without prior knowledge of their shape. We tested our approach on simulated data and applied it to clinical human immunodeficiency virus 1 samples to estimate their fitness landscapes in vivo. The posterior fitness distributions allowed for differentiating viral haplotypes from each other, for determining neutral haplotype networks, in which no haplotype is more or less credibly fit than any other, and for detecting epistasis in fitness landscapes. Our implemented approach, called QuasiFit, is available at http://www.cbg.ethz.ch/software/quasifit.

The impact of macroscopic epistasis on long-term evolutionary dynamics

Genetic interactions can strongly influence the fitness effects of individual mutations, yet the impact of these epistatic interactions on evolutionary dynamics remains poorly understood. Here we investigate the evolutionary role of epistasis over 50,000 generations in a well-studied laboratory evolution experiment in Escherichia coli. The extensive duration of this experiment provides a unique window into the effects of epistasis during long-term adaptation to a constant environment. Guided by analytical results in the weak-mutation limit, we develop a computational framework to assess the compatibility of a given epistatic model with the observed patterns of fitness gain and mutation accumulation through time. We find that a decelerating fitness trajectory alone provides little power to distinguish between competing models, including those that lack any direct epistatic interactions between mutations. However, when combined with the mutation trajectory, these observables place strong constraints on the set of possible models of epistasis, ruling out many existing explanations of the data. Instead, we find that the data are consistent with a "two-epoch" model of adaptation, in which an initial burst of diminishing-returns epistasis is followed by a steady accumulation of mutations under a constant distribution of fitness effects. Our results highlight the need for additional DNA sequencing of these populations, as well as for more sophisticated models of epistasis that are compatible with all of the experimental data.

RNA replication errors and the evolution of virus pathogenicity and virulence

RNA viruses of plants and animals have polymerases that are error-prone and produce complex populations of related, but non-identical, genomes called quasispecies. While there are vast variations in mutation rates among these viruses, selection has optimized the exact error rate of each species to provide maximum speed of replication and amount of variation without losing the ability to replicate because of excessive mutation. High mutation rates result in the selection of populations increasingly robust, which means they are increasingly resistant to show phenotypic changes after mutation. It is possible to manipulate the mutation rate, either by the use of mutagens or by selection (or genetic manipulation) of fidelity mutants. These polymerases usually, but not always, perform as well as wild type (wt) during cell infection, but show major phenotypic changes during in vivo infection. Both high and low fidelity variants are attenuated when the wt virus is virulent in the host. Alternatively when wt infection is non-apparent, the variants show major restrictions to spread in the infected host. Manipulation of mutation rates may become a new strategy to develop attenuated vaccines for humans and animals.

Length of adaptive walk on uncorrelated and correlated fitness landscapes

We consider the adaptation dynamics of an asexual population that walks uphill on a rugged fitness landscape which is endowed with a large number of local fitness peaks. We work in a parameter regime where only those mutants that are a single mutation away are accessible, as a result of which the population eventually gets trapped at a local fitness maximum and the adaptive walk terminates. We study how the number of adaptive steps taken by the population before reaching a local fitness peak depends on the initial fitness of the population, the extreme value distribution of the beneficial mutations, and correlations among the fitnesses. Assuming that the relative fitness difference between successive steps is small, we analytically calculate the average walk length for both uncorrelated and correlated fitnesses in all extreme value domains for a given initial fitness. We present numerical results for the model where the fitness differences can be large and find that the walk length behavior differs from that in the former model in the Fréchet domain of extreme value theory. We also discuss the relevance of our results to microbial experiments.

Robustness as a non-localizable relational phenomenon

A current challenge in neuroscience, systems and theoretical biology is to understand what properties allow organisms to exhibit and sustain behaviours despite perturbations (behavioural robustness). Indeed, there are still significant theoretical difficulties in this endeavour due to the context-dependent nature of the problem. Contrary to the common view of biological robustness as a phenomenon that emerges internally, this article discusses the hypothesis that behavioural robustness is rooted in dynamical processes that distribute between internal controls, the organism body and the environment. This review highlights the varied perspectives and how they have led to the current focus on robustness as a relational phenomenon. A new perspective is proposed in which robustness is better understood in the context of agent-environment dynamical couplings, in which such couplings are not always the full determinants of robustness. The challenges and limitations of the proposed approach are identified.

Microbial evolution. Global epistasis makes adaptation predictable despite sequence-level stochasticity

Epistatic interactions between mutations can make evolutionary trajectories contingent on the chance occurrence of initial mutations. We used experimental evolution in Saccharomyces cerevisiae to quantify this contingency, finding differences in adaptability among 64 closely related genotypes. Despite these differences, sequencing of 104 evolved clones showed that initial genotype did not constrain future mutational trajectories. Instead, reconstructed combinations of mutations revealed a pattern of diminishing-returns epistasis: Beneficial mutations have consistently smaller effects in fitter backgrounds. Taken together, these results show that beneficial mutations affecting a variety of biological processes are globally coupled; they interact strongly, but only through their combined effect on fitness. As a consequence, fitness evolution follows a predictable trajectory even though sequence-level adaptation is stochastic.

Genetic barrier and variant fitness in hepatitis C as critical parameters for drug resistance development

The approval of direct-acting antiviral agents (DAAs) has marked a pivotal change in the treatment landscape of chronic hepatitis C. As for DAAs targeting other viral diseases, there are concerns regarding the development of resistant viral variants. Their selection allows the virus to escape from drug pressure with subsequent treatment failure. The emergence of resistant variants depends on multiple factors that range from genetic barriers to mutations to the fitness of viral variants. This article illustrates the basic mechanisms underlying development of resistance to specific antiviral agents with a special emphasis on NS3 protease inhibitors. The role of fitness deficits and compensation for variant selection and persistence is discussed together with technical issues in sequencing as well as clinical implications in the use of DAAs now and in the future.

Realistic three dimensional fitness landscapes generated by self organizing maps for the analysis of experimental HIV-1 evolution

Human Immunodeficiency Virus type 1 (HIV-1) because of high mutation rates, large population sizes, and rapid replication, exhibits complex evolutionary strategies. For the analysis of evolutionary processes, the graphical representation of fitness landscapes provides a significant advantage. The experimental determination of viral fitness remains, in general, difficult and consequently most published fitness landscapes have been artificial, theoretical or estimated. Self-Organizing Maps (SOM) are a class of Artificial Neural Network (ANN) for the generation of topological ordered maps. Here, three-dimensional (3D) data driven fitness landscapes, derived from a collection of sequences from HIV-1 viruses after “in vitro” passages and labelled with the corresponding experimental fitness values, were created by SOM. These maps were used for the visualization and study of the evolutionary process of HIV-1 “in vitro” fitness recovery, by directly relating fitness values with viral sequences. In addition to the representation of the sequence space search carried out by the viruses, these landscapes could also be applied for the analysis of related variants like members of viral quasiespecies. SOM maps permit the visualization of the complex evolutionary pathways in HIV-1 fitness recovery. SOM fitness landscapes have an enormous potential for the study of evolution in related viruses of “in vitro” works or from “in vivo” clinical studies with human, animal or plant viral infections.

Evolvability and robustness in populations of RNA virus Φ6

Microbes can respond quickly to environmental disturbances through adaptation. However, processes determining the constraints on this adaptation are not well understood. One process that could affect the rate of adaptation to environmental perturbations is genetic robustness, the ability to maintain phenotype despite mutation. Genetic robustness has been theoretically linked to evolvability but rarely tested empirically using evolving populations. We used populations of the RNA bacteriophage ϕ6 previously characterized as differing in robustness, and passaged them through a repeated environmental disturbance: periodic 45°C heat shock. The robust populations evolved faster to withstand the disturbance, relative to the less robust (brittle) populations. The robust populations also achieved relatively greater thermotolerance by the end of the experimental evolution. Sequencing revealed that thermotolerance occurred via a key mutation in gene P5 (viral lysis protein), previously shown to be associated with heat shock survival in the virus. Whereas this identical mutation fixed in all of the independently evolving robust populations, it was absent in some brittle populations, which instead fixed a less beneficial mutation. We concluded that robust populations adapted faster to the environmental change, and more easily accessed mutations of large benefit. Our study shows that genetic robustness can play a role in determining the relative ability for microbes to adapt to changing environments.

Mutational and fitness landscapes of an RNA virus revealed through population sequencing

RNA viruses exist as genetically diverse populations. It is thought that diversity and genetic structure of viral populations determine the rapid adaptation observed in RNA viruses and hence their pathogenesis. However, our understanding of the mechanisms underlying virus evolution has been limited by the inability to accurately describe the genetic structure of virus populations. Next-generation sequencing technologies generate data of sufficient depth to characterize virus populations, but are limited in their utility because most variants are present at very low frequencies and are thus indistinguishable from next-generation sequencing errors. Here we present an approach that reduces next-generation sequencing errors and allows the description of virus populations with unprecedented accuracy. Using this approach, we define the mutation rates of poliovirus and uncover the mutation landscape of the population. Furthermore, by monitoring changes in variant frequencies on serially passaged populations, we determined fitness values for thousands of mutations across the viral genome. Mapping of these fitness values onto three-dimensional structures of viral proteins offers a powerful approach for exploring structure-function relationships and potentially uncovering new functions. To our knowledge, our study provides the first single-nucleotide fitness landscape of an evolving RNA virus and establishes a general experimental platform for studying the genetic changes underlying the evolution of virus populations.

Evolutionary biochemistry: revealing the historical and physical causes of protein properties

The repertoire of proteins and nucleic acids in the living world is determined by evolution; their properties are determined by the laws of physics and chemistry. Explanations of these two kinds of causality - the purviews of evolutionary biology and biochemistry, respectively - are typically pursued in isolation, but many fundamental questions fall squarely at the interface of fields. Here we articulate the paradigm of evolutionary biochemistry, which aims to dissect the physical mechanisms and evolutionary processes by which biological molecules diversified and to reveal how their physical architecture facilitates and constrains their evolution. We show how an integration of evolution with biochemistry moves us towards a more complete understanding of why biological molecules have the properties that they do.

The genetic code constrains yet facilitates Darwinian evolution

An important goal of evolutionary biology is to understand the constraints that shape the dynamics and outcomes of evolution. Here, we address the extent to which the structure of the standard genetic code constrains evolution by analyzing adaptive mutations of the antibiotic resistance gene TEM-1 β-lactamase and the fitness distribution of codon substitutions in two influenza hemagglutinin inhibitor genes. We find that the architecture of the genetic code significantly constrains the adaptive exploration of sequence space. However, the constraints endow the code with two advantages: the ability to restrict access to amino acid mutations with a strong negative effect and, most remarkably, the ability to enrich for adaptive mutations. Our findings support the hypothesis that the standard genetic code was shaped by selective pressure to minimize the deleterious effects of mutation yet facilitate the evolution of proteins through imposing an adaptive mutation bias.

Codon usage determines the mutational robustness, evolutionary capacity, and virulence of an RNA virus

RNA viruses exist as dynamic and diverse populations shaped by constant mutation and selection. Yet little is known about how the mutant spectrum contributes to virus evolvability and pathogenesis. Because several codon choices are available for a given amino acid, a central question concerns whether viral sequences have evolved to optimize not only the protein coding consensus, but also the DNA/RNA sequences accessible through mutation. Here we directly test this hypothesis by comparing wild-type poliovirus to synthetic viruses carrying re-engineered capsid sequences with hundreds of synonymous mutations. Strikingly, such rewiring of the population's mutant network reduced its robustness and attenuated the virus in an animal model of infection. We conclude that the position of a virus in sequence space defines its mutant spectrum, evolutionary trajectory, and pathogenicity. This organizing principle for RNA virus populations confers tolerance to mutations and facilitates replication and spread within the dynamic host environment.

Evolution of increased survival in RNA viruses specialized on cancer-derived cells

Viruses and other pathogens can diverge in their evolved host-use strategies because of exposure to different host types and conflicts between within-host reproduction and between-host survival. Most host-pathogen studies have emphasized the role of intrahost reproduction in the evolution of pathogen virulence, whereas the role of extra-host survival has received less attention. Here, we examine the evolution of free-living virion survival in RNA virus populations differing in their histories of host use. To do so, we used lineages of vesicular stomatitis virus (VSV) that were experimentally evolved in laboratory tissue culture for 100 generations on cancer-derived cells, noncancerous cells, or alternating passages of the two host types. We observed that free-living survival improved when VSV populations specialized on human epithelial carcinoma (HeLa) cells, whereas this trait was not associated with selection on noncancer cells or combinations of the cell types. We attributed this finding to shorter-lived HeLa monolayers and/or rapid cell-to-cell spread of viruses on HeLa cells in tissue culture, both of which could select for enhanced virus stability between host-cell replenishment. We also showed evidence that increases in virion survival were associated with decreases in virulence, which suggests a trade-off between survival and virulence for the VSV populations on one cell type. Our results shed new light on the causes and consequences of "sit and wait" infection strategies in RNA viruses.

Intrahost mechanisms governing emergence of resistance-breaking variants of Potato virus Y

The emergence of resistance breaking (RB) variants starting from the avirulent Potato virus Y NN strain (PVY(NN)) was analyzed after imposing different selective host constraints. Tobacco resistance to PVY(NN) is conferred by va in both NC745 and VAM genotypes, but VAM carries an extra resistance gene, va2. RB-variants emerged only in NC745 and unexpectedly accumulated higher in the original host, tobacco B21, than the parental PVY(NN). However, the recovery of RB-variants was interfered by PVY(NN) in mixed infections. Further analysis indicated that RB-variants also arose in tobacco VAM, but they were limited to subliminal local infections. Their inability to breakout was associated with absence of a mutational adaptation in the viral VPg gene, which implied a loss of fitness in tobacco B21. Altogether, the emergence of RB-variants was conditioned by inherited host constraints, interference by co-infecting avirulent virus genotypes, and fitness tradeoff of virus adaptations.

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.

Congruent evolution of fitness and genetic robustness in vesicular stomatitis virus

Quasispecies theory is a case of mutation-selection balance for evolution at high mutation rates, such as those observed in RNA viruses. One of the main predictions of this model is the selection for robustness, defined as the ability of an organism to remain phenotypically unchanged in the face of mutation. We have used a collection of vesicular stomatitis virus strains that had been evolving either under positive selection or under random drift. We had previously shown that the former increase in fitness while the latter have overall fitness decreases (I. S. Novella, J. B. Presloid, T. Zhou, S. D. Smith-Tsurkan, B. E. Ebendick-Corpus, R. N. Dutta, K. L. Lust, and C. O. Wilke, J. Virol. 84:4960-4968, 2010). Here, we determined the robustness of these strains and demonstrated that strains under positive selection not only increase in fitness but also increase in robustness. In contrast, strains under drift not only decreased in fitness but also decreased in robustness. There was a good overall correlation between fitness and robustness. We also tested whether there was a correlation between fitness and thermostability, and we observed that the correlation was imperfect, indicating that the fitness effects of mutations are exerted in part at a level other than changing the resistance of the protein to temperature.

Multiple scales of selection influence the evolutionary emergence of novel pathogens

When pathogens encounter a novel environment, such as a new host species or treatment with an antimicrobial drug, their fitness may be reduced so that adaptation is necessary to avoid extinction. Evolutionary emergence is the process by which new pathogen strains arise in response to such selective pressures. Theoretical studies over the last decade have clarified some determinants of emergence risk, but have neglected the influence of fitness on evolutionary rates and have not accounted for the multiple scales at which pathogens must compete successfully. We present a cross-scale theory for evolutionary emergence, which embeds a mechanistic model of within-host selection into a stochastic model for emergence at the population scale. We explore how fitness landscapes at within-host and between-host scales can interact to influence the probability that a pathogen lineage will emerge successfully. Results show that positive correlations between fitnesses across scales can greatly facilitate emergence, while cross-scale conflicts in selection can lead to evolutionary dead ends. The local genotype space of the initial strain of a pathogen can have disproportionate influence on emergence probability. Our cross-scale model represents a step towards integrating laboratory experiments with field surveillance data to create a rational framework to assess emergence risk.

Mechanisms and selection of evolvability: experimental evidence

The vast number of species we see around us today, all stemming from a common ancestor, clearly demonstrates the capacity of organisms to adapt to new environments. Understanding the underlying basis of differences in the capacity of genotypes to adapt - that is, their evolvability - has become a major research field. Several mechanisms have been demonstrated to influence evolvability, including differences in mutation rate, mutational robustness, and some kinds of gene interactions. However, the benefits of increased evolvability are indirect, so that the conditions required for selection of evolvability traits are expected to be more limited than for traits that confer immediately beneficial phenotypes. Moreover, just because a trait can affect evolvability does not mean that it actually does so in a particular environment. Instead, some other function of the trait may better explain its success. Nevertheless, there is accumulating experimental evidence that some traits can increase the evolvability of a genotype and that these traits do influence evolutionary outcomes. We discuss recent theory and experiments that demonstrate the potential for traits that influence evolvability to arise and be selected.

Understanding specialism when the Jack of all trades can be the master of all

Specialism is widespread in nature, generating and maintaining diversity, but recent work has demonstrated that generalists can be equally fit as specialists in some shared environments. This no-cost generalism challenges the maxim that 'the jack of all trades is the master of none', and requires evolutionary genetic mechanisms explaining the existence of specialism and no-cost generalism, and the persistence of specialism in the face of selection for generalism. Examining three well-described mechanisms with respect to epistasis and pleiotropy indicates that sign (or antagonistic) pleiotropy without epistasis cannot explain no-cost generalism and that magnitude pleiotropy without epistasis (including directional selection and mutation accumulation) cannot explain the persistence of specialism. However, pleiotropy with epistasis can explain all. Furthermore, epistatic pleiotropy may allow past habitat use to influence future use of novel environments, thereby affecting disease emergence and populations' responses to habitat change.

Challenges and opportunities in estimating viral genetic diversity from next-generation sequencing data

Many viruses, including the clinically relevant RNA viruses HIV (human immunodeficiency virus) and HCV (hepatitis C virus), exist in large populations and display high genetic heterogeneity within and between infected hosts. Assessing intra-patient viral genetic diversity is essential for understanding the evolutionary dynamics of viruses, for designing effective vaccines, and for the success of antiviral therapy. Next-generation sequencing (NGS) technologies allow the rapid and cost-effective acquisition of thousands to millions of short DNA sequences from a single sample. However, this approach entails several challenges in experimental design and computational data analysis. Here, we review the entire process of inferring viral diversity from sample collection to computing measures of genetic diversity. We discuss sample preparation, including reverse transcription and amplification, and the effect of experimental conditions on diversity estimates due to in vitro base substitutions, insertions, deletions, and recombination. The use of different NGS platforms and their sequencing error profiles are compared in the context of various applications of diversity estimation, ranging from the detection of single nucleotide variants (SNVs) to the reconstruction of whole-genome haplotypes. We describe the statistical and computational challenges arising from these technical artifacts, and we review existing approaches, including available software, for their solution. Finally, we discuss open problems, and highlight successful biomedical applications and potential future clinical use of NGS to estimate viral diversity.

Viral population dynamics and virulence thresholds

Viral factors and host barriers influence virally induced disease, and asymptomatic versus symptomatic infection is governed by a 'virulence threshold'. Understanding modulation of virulence thresholds could lend insight into disease outcome and aid in rational therapeutic and vaccine design. RNA viruses are an excellent system to study virulence thresholds in the context of quasispecies population dynamics. RNA viruses have high error frequencies and our understanding of viral population dynamics has been shaped by quasispecies evolutionary theory. In turn, research using RNA viruses as replicons with short generation times and high mutation rates has been an invaluable tool to test models of quasispecies theory. The challenge and new frontier of RNA virus population dynamics research is to combine multiple theoretical models and experimental data to describe viral population behavior as it changes, moving within and between hosts, to predict disease and pathogen emergence. Several excellent studies have begun to undertake this challenge using novel approaches.

Life-history evolution and density-dependent growth in experimental populations of yeast

We studied the evolution of the correlation between growth rate r and yield K in experimental lineages of the yeast Saccharomyces cerevisiae. First, we isolated a single clone every approximately 250 generations from each of eight populations selected in a glucose-limited medium for 5000 generations at approximately 6.6 population doublings per day (20 clones per line × 8 lines) and measured its growth rate and yield in a new, galactose-limited medium (with ∼1.3 doubling per day). For most lines, r on galactose increased throughout the 5000 generations of selection on glucose whereas K on galactose declined. Next, we selected these 160 glucose-adapted clones in the galactose environment for approximately 120 generations and measured changes in r and K in galactose. In general, growth rate increased and yield declined, and clones that initially grew slowly on galactose improved more than did faster clones. We found a negative correlation between r and K among clones both within each line and across all clones. We provide evidence that this relationship is not heritable and is a negative environmental correlation rather than a genetic trade-off.

A quantitative quasispecies theory-based model of virus escape mutation under immune selection

Viral infections involve a complex interplay of the immune response and escape mutation of the virus quasispecies inside a single host. Although fundamental aspects of such a balance of mutation and selection pressure have been established by the quasispecies theory decades ago, its implications have largely remained qualitative. Here, we present a quantitative approach to model the virus evolution under cytotoxic T-lymphocyte immune response. The virus quasispecies dynamics are explicitly represented by mutations in the combined sequence space of a set of epitopes within the viral genome. We stochastically simulated the growth of a viral population originating from a single wild-type founder virus and its recognition and clearance by the immune response, as well as the expansion of its genetic diversity. Applied to the immune escape of a simian immunodeficiency virus epitope, model predictions were quantitatively comparable to the experimental data. Within the model parameter space, we found two qualitatively different regimes of infectious disease pathogenesis, each representing alternative fates of the immune response: It can clear the infection in finite time or eventually be overwhelmed by viral growth and escape mutation. The latter regime exhibits the characteristic disease progression pattern of human immunodeficiency virus, while the former is bounded by maximum mutation rates that can be suppressed by the immune response. Our results demonstrate that, by explicitly representing epitope mutations and thus providing a genotype-phenotype map, the quasispecies theory can form the basis of a detailed sequence-specific model of real-world viral pathogens evolving under immune selection.

Parallel genetic changes and nonparallel gene-environment interactions characterize the evolution of drug resistance in yeast

Beneficial mutations are required for adaptation to novel environments, yet the range of mutational pathways that are available to a population has been poorly characterized, particularly in eukaryotes. We assessed the genetic changes of the first mutations acquired during adaptation to a novel environment (exposure to the fungicide, nystatin) in 35 haploid lines of Saccharomyces cerevisiae. Through whole-genome resequencing we found that the genomic scope for adaptation was narrow; all adapted lines acquired a mutation in one of four late-acting genes in the ergosterol biosynthesis pathway, with very few other mutations found. Lines that acquired different ergosterol mutations in the same gene exhibited very similar tolerance to nystatin. All lines were found to have a cost relative to wild type in an unstressful environment; the level of this cost was also strongly correlated with the ergosterol gene bearing the mutation. Interestingly, we uncovered both positive and negative effects on tolerance to other harsh environments for mutations in the different ergosterol genes, indicating that these beneficial mutations have effects that differ in sign among environmental challenges. These results demonstrate that although the genomic target was narrow, different adaptive mutations can lead populations down different evolutionary pathways, with respect to their ability to tolerate (or succumb to) other environmental challenges.

Viral quasispecies evolution

Evolution of RNA viruses occurs through disequilibria of collections of closely related mutant spectra or mutant clouds termed viral quasispecies. Here we review the origin of the quasispecies concept and some biological implications of quasispecies dynamics. Two main aspects are addressed: (i) mutant clouds as reservoirs of phenotypic variants for virus adaptability and (ii) the internal interactions that are established within mutant spectra that render a virus ensemble the unit of selection. The understanding of viruses as quasispecies has led to new antiviral designs, such as lethal mutagenesis, whose aim is to drive viruses toward low fitness values with limited chances of fitness recovery. The impact of quasispecies for three salient human pathogens, human immunodeficiency virus and the hepatitis B and C viruses, is reviewed, with emphasis on antiviral treatment strategies. Finally, extensions of quasispecies to nonviral systems are briefly mentioned to emphasize the broad applicability of quasispecies theory.

Fitness of Arabidopsis thaliana mutation accumulation lines whose spontaneous mutations are known

Despite the fundamental importance of mutation to the evolutionary process, we have little knowledge of the direct consequences of specific spontaneous mutations to the fitness of the organism. Combining results of whole-genome sequencing with repeated field assays of survival and reproduction, we quantify the combined effects on fitness of spontaneous mutations identified in Arabidopsis thaliana. We demonstrate that the effects are beneficial, deleterious, or neutral depending on the environmental context. Some lines, bearing mutations disrupting known loci, differ strongly in fitness from the founder or premutation genotype. Those effects vary across environments, for example, a line with a major deletion spanning a transcription factor gene expressed lower fitness than the founder under most conditions but exceeded the founder's fitness in one environment. The large contribution of genotype by environment interaction (G × E) to mutation effects on fitness implies spatial and/or temporal variation in selection on new mutations and could contribute to the maintenance of standing genetic variation.

Population subdivision and adaptation in asexual populations of Saccharomyces cerevisiae

Population subdivision limits competition between individuals, which can have a profound effect on adaptation. Subdivided populations maintain more genetic diversity at any given time compared to well-mixed populations, and thus "explore" larger parts of the genotype space. At the same time, beneficial mutations take longer to spread in such populations, and thus subdivided populations do not "exploit" discovered mutations as efficiently as well-mixed populations. Whether subdivision inhibits or promotes adaptation in a given environment depends on the relative importance of exploration versus exploitation, which in turn depends on the structure of epistasis among beneficial mutations. Here we investigate the relative importance of exploration versus exploitation for adaptation by evolving 976 independent asexual populations of budding yeast with several degrees of geographic subdivision. We find that subdivision systematically inhibits adaptation: even the luckiest demes in subdivided populations on average fail to discover genotypes that are fitter than those discovered by well-mixed populations. Thus, exploitation of discovered mutations is more important for adaptation in our system than a thorough exploration of the mutational neighborhood, and increasing subdivision slows adaptation.

Bistability in feedback circuits as a byproduct of evolution of evolvability

Simulations of the evolution of simple gene regulatory networks reveal that fluctuating environmental selection can lead to the emergence of bistability under certain conditions where fluctuation and mutational rates are in tune.

Bistability-mediated stochastic switching is observed in many microbial phenotypes. While experimental and theoretical work has shown population-level fitness benefits of this phenomenon under fluctuating environments, it is not known if and how fluctuating selection can result in incremental evolution of bistability at single cell level.

Using a stochastic model of a simple network and in silico evolution, we study the effect of fluctuating selection on gene expression dynamics. Under intermediary fluctuation rates, we find evolution of evolvability and reduced adaptation time.

Increased evolvability is underlined by system parameters evolving toward a nonlinear regime where phenotypic diversity is increased and small changes in genotype cause large changes in expression level.

Only under noisy dynamics, the evolution of increased nonlinearity results in the emergence and maintenance of bistability. These results provide evidence for bistability emerging under fluctuating selection and that such emergence occurs as a byproduct of evolution of evolvability.

Noisy bistable dynamics in gene regulation can underlie stochastic switching and is demonstrated to be beneficial under fluctuating environments. It is not known, however, if fluctuating selection alone can result in bistable dynamics. Using a stochastic model of simple feedback networks, we apply fluctuating selection on gene expression and run in silico evolutionary simulations. We find that independent of the specific nature of the environment–fitness relationship, the main outcome of fluctuating selection is the evolution of increased evolvability in the network; system parameters evolve toward a nonlinear regime where phenotypic diversity is increased and small changes in genotype cause large changes in expression level. In the presence of noise, the evolution of increased nonlinearity results in the emergence and maintenance of bistability. Our results provide the first direct evidence that bistability and stochastic switching in a gene regulatory network can emerge as a mechanism to cope with fluctuating environments. They strongly suggest that such emergence occurs as a byproduct of evolution of evolvability and exploitation of noise by evolution.

The impact of interspecific competition on lineage evolution and a rapid peak shift by interdemic genetic mixing in experimental bacterial populations

Epistatic interactions between genes in the genome constrain the accessible evolutionary paths of lineages. Two factors involving epistasis that can affect the evolutionary path and fate of lineages were investigated. The first factor concerns the impact of competition with another species lineage that has different epistatic constraints. Five enteric bacterial populations were evolved by point mutation in medium containing a single limiting resource. Single-species and two-species cultures were used to determine whether different asexual lineages have different capacities for producing variants due to epistatic constraints, and whether their survival is determined by local inter-lineage competition with different species. Local inter-lineage competition quickly resulted in one successful lineage, with another lineage becoming extinct before finding a higher peak. The second factor concerns a peak-shifting process, and whether the sexual recombination between different demes can cause peak shifts was investigated. An Escherichia coli population consisting of a male (Hfr) and female strain (F(-)) was evolved in a single limiting resource and compared to evolving populations containing the male or female strain alone. The E. coli sexual lineage was successful due to its ability to escape lower peaks and reach a higher peak, not because of a rapid approach to the nearest local peak the male or female asexual lineage could reach. The data in this study demonstrate that lineage survivability can be determined by the ability to produce beneficial mutations and checked by local competition between lineages of different species. Interspecific competition may prevent a population from evolving through crossing fitness valleys or adaptive ridges if it requires many generations to achieve peak shifts. The data also show that genomic recombination between different conspecific lineages can rapidly carry the combined lineage to a higher peak.

Specific and nonspecific host adaptation during arboviral experimental evolution

During the past decade or so, there has been a substantial body of work to dissect arboviral evolution and to develop models of adaptation during host switching. Regardless of what species serve as host or vectors, and of the geographic distribution and the mechanisms of replication, arboviruses tend to have slow evolutionary rates in nature. The hypothesis that this is the result of replication in the disparate environments provided by host and vector did not receive solid experimental support in any of the many viral species tested. Instead, it seems that from the virus's point of view, either the two environments are sufficiently similar or one of the environments so dominates viral evolution that there is tolerance for suboptimal adaptation to the other environment. Replication in alternating environments has an unexpected cost in that there is decreased genetic variance that translates into a compromised adaptability for bypassed environments. Arboviruses under strong and continuous positive selection may have unusual patterns of genomic changes, with few or no mutations accumulated in the consensus sequence or with dN/dS values typically consistent with random drift in DNA-based organisms.