Selection for robustness in mutagenized RNA viruses

Changing fitness effects of mutations through long-term bacterial evolution

The distribution of fitness effects of new mutations shapes evolution, but it is challenging to observe how it changes as organisms adapt. Using Escherichia coli lineages spanning 50,000 generations of evolution, we quantify the fitness effects of insertion mutations in every gene. Macroscopically, the fraction of deleterious mutations changed little over time whereas the beneficial tail declined sharply, approaching an exponential distribution. Microscopically, changes in individual gene essentiality and deleterious effects often occurred in parallel; altered essentiality is only partly explained by structural variation. The identity and effect sizes of beneficial mutations changed rapidly over time, but many targets of selection remained predictable because of the importance of loss-of-function mutations. Taken together, these results reveal the dynamic-but statistically predictable-nature of mutational fitness effects.

Ethanol Drives Evolution of Hsp90-Dependent Robustness by Redundancy in Yeast Domestication

Protein folding promotes and constrains adaptive evolution. We uncover this surprising duality in the role the protein-folding chaperone Hsp90 plays in mediating the interplay between proteome and the genome which acts to maintain the integrity of yeast metabolism in the face of proteotoxic stressors in anthropic niches. Of great industrial relevance, ethanol concentrations generated by fermentation in the making of beer and bread disrupt critical Hsp90-dependent nodes of metabolism and exert strong selective pressure for increased copy number of key genes encoding components of these nodes, yielding the classical genetic signatures of beer and bread domestication. This work establishes a mechanism of adaptive canalization in an ecology of major economic significance and highlights Hsp90-contingent variation as an important source of phantom heritability in complex traits.

Fitness landscape analysis of a tRNA gene reveals that the wild type allele is sub-optimal, yet mutationally robust

Fitness landscape mapping and the prediction of evolutionary trajectories on these landscapes are major tasks in evolutionary biology research. Evolutionary dynamics is tightly linked to the landscape topography, but this relation is not straightforward. Here, we analyze a fitness landscape of a yeast tRNA gene, previously measured under four different conditions. We find that the wild type allele is sub-optimal, and 8–10% of its variants are fitter. We rule out the possibilities that the wild type is fittest on average on these four conditions or located on a local fitness maximum. Notwithstanding, we cannot exclude the possibility that the wild type might be fittest in some of the many conditions in the complex ecology that yeast lives at. Instead, we find that the wild type is mutationally robust (“flat”), while more fit variants are typically mutationally fragile. Similar observations of mutational robustness or flatness have been so far made in very few cases, predominantly in viral genomes.

A Virus Is a Community: Diversity within Negative-Sense RNA Virus Populations

Negative-sense RNA virus populations are composed of diverse viral components that interact to form a community and shape the outcome of virus infections. At the genomic level, RNA virus populations consist not only of a homogeneous population of standard viral genomes but also of an extremely large number of genome variants, termed viral quasispecies, and nonstandard viral genomes, which include copy-back viral genomes, deletion viral genomes, mini viral RNAs, and hypermutated RNAs. At the particle level, RNA virus populations are composed of pleomorphic particles, particles missing or having additional genomes, and single particles or particle aggregates. As we continue discovering more about the components of negative-sense RNA virus populations and their crucial functions during virus infection, it will become more important to study RNA virus populations as a whole rather than their individual parts. In this review, we will discuss what is known about the components of negative-sense RNA virus communities, speculate how the components of the virus community interact, and summarize what vaccines and antiviral therapies are being currently developed to target or harness these components.

Viral Aggregation: The Knowns and Unknowns

Viral aggregation is a complex and pervasive phenomenon affecting many viral families. An increasing number of studies have indicated that it can modulate critical parameters surrounding viral infections, and yet its role in viral infectivity, pathogenesis, and evolution is just beginning to be appreciated. Aggregation likely promotes viral infection by increasing the cellular multiplicity of infection (MOI), which can help overcome stochastic failures of viral infection and genetic defects and subsequently modulate their fitness, virulence, and host responses. Conversely, aggregation can limit the dispersal of viral particles and hinder the early stages of establishing a successful infection. The cost–benefit of viral aggregation seems to vary not only depending on the viral species and aggregating factors but also on the spatiotemporal context of the viral life cycle. Here, we review the knowns of viral aggregation by focusing on studies with direct observations of viral aggregation and mechanistic studies of the aggregation process. Next, we chart the unknowns and discuss the biological implications of viral aggregation in their infection cycle. We conclude with a perspective on harnessing the therapeutic potential of this phenomenon and highlight several challenging questions that warrant further research for this field to advance.

Neutral quasispecies evolution and the maximal entropy random walk

Even if they have no impact on phenotype, neutral mutations are not equivalent in the eyes of evolution: A robust neutral variant-one which remains functional after further mutations-is more likely to spread in a large, diverse population than a fragile one. Quasispecies theory shows that the equilibrium frequency of a genotype is proportional to its eigenvector centrality in the neutral network. This paper explores the link between the selection for mutational robustness and the navigability of neutral networks. I show that sequences of neutral mutations follow a "maximal entropy random walk," a canonical Markov chain on graphs with nonlocal, nondiffusive dynamics. I revisit M. Smith's word-game model of evolution in this light, finding that the likelihood of certain sequences of substitutions can decrease with the population size. These counterintuitive results underscore the fertility of the interface between evolutionary dynamics, information theory, and physics.

Environmental flexibility does not explain metabolic robustness

Cells show remarkable resilience against genetic and environmental perturbations. However, its evolutionary origin remains obscure. In order to leverage methods of systems biology for examining cellular robustness, a computationally accessible way of quantification is needed. Here, we present an unbiased metric of structural robustness in genome-scale metabolic models based on concepts prevalent in reliability engineering and fault analysis. The probability of failure (PoF) is defined as the (weighted) portion of all possible combinations of loss-of-function mutations that disable network functionality. It can be exactly determined if all essential reactions, synthetic lethal pairs of reactions, synthetic lethal triplets of reactions etc. are known. In theory, these minimal cut sets (MCSs) can be calculated for any network, but for large models the problem remains computationally intractable. Herein, we demonstrate that even at the genome scale only the lowest-cardinality MCSs are required to efficiently approximate the PoF with reasonable accuracy. Building on an improved theoretical understanding, we analysed the robustness of 489 E. coli, Shigella, Salmonella, and fungal genome-scale metabolic models (GSMMs). In contrast to the popular "congruence theory", which explains the origin of genetic robustness as a byproduct of selection for environmental flexibility, we found no correlation between network robustness and the diversity of growth-supporting environments. On the contrary, our analysis indicates that amino acid synthesis rather than carbon metabolism dominates metabolic robustness.

Adaptation of turnip mosaic potyvirus to a specific niche reduces its genetic and environmental robustness

Robustness is the preservation of the phenotype in the face of genetic and environmental perturbations. It has been argued that robustness must be an essential fitness component of RNA viruses owed to their small and compacted genomes, high mutation rates and living in ever-changing environmental conditions. Given that genetic robustness might hamper possible beneficial mutations, it has been suggested that genetic robustness can only evolve as a side-effect of the evolution of robustness mechanisms specific to cope with environmental perturbations, a theory known as plastogenetic congruence. However, empirical evidences from different viral systems are contradictory. To test how adaptation to a particular environment affects both environmental and genetic robustness, we have used two strains of turnip mosaic potyvirus (TuMV) that differ in their degree of adaptation to Arabidopsis thaliana at a permissive temperature. We show that the highly adapted strain is strongly sensitive to the effect of random mutations and to changes in temperature conditions. In contrast, the non-adapted strain shows more robustness against both the accumulation of random mutations and drastic changes in temperature conditions. Together, these results are consistent with the predictions of the plastogenetic congruence theory, suggesting that genetic and environmental robustnesses may be two sides of the same coin for TuMV.

Moderate Amounts of Epistasis are Not Evolutionarily Stable in Small Populations

High mutation rates select for the evolution of mutational robustness where populations inhabit flat fitness peaks with little epistasis, protecting them from lethal mutagenesis. Recent evidence suggests that a different effect protects small populations from extinction via the accumulation of deleterious mutations. In drift robustness, populations tend to occupy peaks with steep flanks and positive epistasis between mutations. However, it is not known what happens when mutation rates are high and population sizes are small at the same time. Using a simple fitness model with variable epistasis, we show that the equilibrium fitness has a minimum as a function of the parameter that tunes epistasis, implying that this critical point is an unstable fixed point for evolutionary trajectories. In agent-based simulations of evolution at finite mutation rate, we demonstrate that when mutations can change epistasis, trajectories with a subcritical value of epistasis evolve to decrease epistasis, while those with supercritical initial points evolve towards higher epistasis. These two fixed points can be identified with mutational and drift robustness, respectively.

Risk factors associated with viral nervous necrosis in hybrid groupers in Malaysia and the high similarity of its causative agent nervous necrosis virus to reassortant red-spotted grouper nervous necrosis virus/striped jack nervous necrosis virus strains

Background and Aim:

Viral nervous necrosis (VNN) is a serious disease of several marine fish species. VNN causes 100% mortality in the larval stages, while lower losses have been reported in juvenile and adult fish. This study aimed to detect the occurrence of VNN while identifying its associated risk factors and the genotypes of its causative agent in a hybrid grouper hatchery in Malaysia.

Materials and Methods:

A batch of newly hatched hybrid grouper fry (Epinephelus fuscoguttatus × Epinephelus lanceolatus) were followed from the larval stage to market size. Samples of the hybrid groupers, water, live feed, and artificial fish pellets were collected periodically from day 0 to 180 in the hybrid grouper hatchery. Reverse transcription-polymerase chain reaction (RT-PCR) and nested PCR amplifications were carried out on VNN-related sequences. The phylogenetic tree including the sampled causative agent of VNN was inferred from the coat protein genes from all known Betanodavirus species using Molecular Evolutionary Genetics Analysis (MEGA). Pearson’s correlation coefficient values were calculated to determine the strength of the correlation between the presence of VNN in hybrid grouper samples and its associated risk factors.

Results:

A total of 113 out of 146 pooled and individual samples, including hybrid grouper, water, and artificial fish pellet samples, demonstrated positive results in tests for the presence of VNN-associated viruses. The clinical signs of infection observed in the samples included darkened skin, deformation of the backbone, abdominal distension, skin lesions, and fin erosion. VNN was present throughout the life stages of the hybrid groupers, with the first detection occurring at day 10. VNN-associated risk factors included water temperature, dissolved oxygen content, salinity, ammonia level, fish size (adults more at risk than younger stages), and life stage (age). Detection of VNN-associated viruses in water samples demonstrated evidence of horizontal transmission of the disease. All the nucleotide sequences found in this study had high nucleotide identities of 88% to 100% to each other, striped jack nervous necrosis virus (SJNNV), and the reassortant strain red-spotted grouper NNV/SJNNV (RGNNV/SJNNV) isolate 430.2004 (GenBank accession number JN189932.1) (n=26). The phylogenetic analysis showed that quasispecies was present in each VNN-causing virus-positive sample, which differed based on the type of sample and life stage.

Conclusion:

This study was the first to confirm the existence of a reassortant strain (RGNNV/SJNNV) in hybrid groupers from Malaysia and Southeast Asia. However, the association between the mode of transmission and the risk factors of this virus needs to be investigated further to understand the evolution and potential new host species of the reassortant strain.

The causes of evolvability and their evolution

Evolvability is the ability of a biological system to produce phenotypic variation that is both heritable and adaptive. It has long been the subject of anecdotal observations and theoretical work. In recent years, however, the molecular causes of evolvability have been an increasing focus of experimental work. Here, we review recent experimental progress in areas as different as the evolution of drug resistance in cancer cells and the rewiring of transcriptional regulation circuits in vertebrates. This research reveals the importance of three major themes: multiple genetic and non-genetic mechanisms to generate phenotypic diversity, robustness in genetic systems, and adaptive landscape topography. We also discuss the mounting evidence that evolvability can evolve and the question of whether it evolves adaptively.

Recombination drives the evolution of mutational robustness

Recombination can impose fitness costs as beneficial parental combinations of alleles are broken apart, a phenomenon known as recombination load. Computational models suggest that populations may evolve a reduced recombination load by reducing either the likelihood of recombination events (bring interacting loci in physical proximity) or the strength of interactions between loci (make loci more independent of one another). We review evidence for each of these possibilities and their consequences for the genotype-fitness relationship. In particular, we expect that reducing interaction strengths between loci will lead to genomes that are also robust to mutational perturbations, but reducing recombination rates alone will not. We note that both mechanisms most likely played a role in the evolution of extant populations, and that both can result in the frequently-observed pattern of physical linkage between interacting loci.

Mapping the Peaks: Fitness Landscapes of the Fittest and the Flattest

Populations exposed to a high mutation rate harbor abundant deleterious genetic variation, leading to depressed mean fitness. This reduction in mean fitness presents an opportunity for selection to restore fitness through the evolution of mutational robustness. In extreme cases, selection for mutational robustness can lead to flat genotypes (with low fitness but high robustness) outcompeting fit genotypes (with high fitness but low robustness)-a phenomenon known as survival of the flattest. While this effect was previously explored using the digital evolution system Avida, a complete analysis of the local fitness landscapes of fit and flat genotypes has been lacking, leading to uncertainty about the genetic basis of the survival-of-the-flattest effect. Here, we repeated the survival-of-the-flattest study and analyzed the mutational neighborhoods of fit and flat genotypes. We found that the flat genotypes, compared to the fit genotypes, had a reduced likelihood of deleterious mutations as well as an increased likelihood of neutral and, surprisingly, of lethal mutations. This trend holds for mutants one to four substitutions away from the wild-type sequence. We also found that flat genotypes have, on average, no epistasis between mutations, while fit genotypes have, on average, positive epistasis. Our results demonstrate that the genetic causes of mutational robustness on complex fitness landscapes are multifaceted. While the traditional idea of the survival of the flattest emphasized the evolution of increased neutrality, others have argued for increased mutational sensitivity in response to strong mutational loads. Our results show that both increased neutrality and increased lethality can lead to the evolution of mutational robustness. Furthermore, strong negative epistasis is not required for mutational sensitivity to lead to mutational robustness. Overall, these results suggest that mutational robustness is achieved by minimizing heritable deleterious variation.

Evolutionary Virology at 40

RNA viruses are diverse, abundant, and rapidly evolving. Genetic data have been generated from virus populations since the late 1970s and used to understand their evolution, emergence, and spread, culminating in the generation and analysis of many thousands of viral genome sequences. Despite this wealth of data, evolutionary genetics has played a surprisingly small role in our understanding of virus evolution. Instead, studies of RNA virus evolution have been dominated by two very different perspectives, the experimental and the comparative, that have largely been conducted independently and sometimes antagonistically. Here, we review the insights that these two approaches have provided over the last 40 years. We show that experimental approaches using in vitro and in vivo laboratory models are largely focused on short-term intrahost evolutionary mechanisms, and may not always be relevant to natural systems. In contrast, the comparative approach relies on the phylogenetic analysis of natural virus populations, usually considering data collected over multiple cycles of virus-host transmission, but is divorced from the causative evolutionary processes. To truly understand RNA virus evolution it is necessary to meld experimental and comparative approaches within a single evolutionary genetic framework, and to link viral evolution at the intrahost scale with that which occurs over both epidemiological and geological timescales. We suggest that the impetus for this new synthesis may come from methodological advances in next-generation sequencing and metagenomics.

Collective Infection of Cells by Viral Aggregates Promotes Early Viral Proliferation and Reveals a Cellular-Level Allee Effect

In addition to the conventional release of free, individual virions, virus dispersal can involve multi-virion assemblies that collectively infect cells. However, the implications of collective infection for viral fitness remain largely unexplored. Using vesicular stomatitis virus, here, we compare the fitness of free versus saliva-aggregated viral particles. We find that aggregation has a positive effect on early progeny production, conferring a fitness advantage relative to equal numbers of free particles in most cell types. The advantage of aggregation resides, at least partially, in increasing the cellular multiplicity of infection. In mouse embryonic fibroblasts, the per capita, short-term viral progeny production peaked for a dose of ca. three infectious particles per cell. This reveals an Allee effect restricting early viral proliferation at the cellular level, which should select for dispersal in groups. We find that genetic complementation between deleterious mutants is probably not the mechanism underlying the fitness advantage of collective infection. Instead, this advantage is cell type dependent and correlates with cellular permissivity to the virus, as well as with the ability of host cells to mount an antiviral innate immune response.

Sexual selection contributes to partial restoration of phenotypic robustness in a butterfly

Phenotypic variation is the raw material for selection that is ubiquitous for most traits in natural populations, yet the processes underlying phenotypic evolution or stasis often remain unclear. Here, we report phenotypic evolution in a mutant line of the butterfly Bicyclus anynana after outcrossing with the genetically polymorphic wild type population. The comet mutation modifies two phenotypic traits known to be under sexual selection in this butterfly: the dorsal forewing eyespots and the pheromone-producing structures. The original comet mutant line was inbred and remained phenotypically stable for at least seven years, but when outcrossed to the wild type population the outcrossed comet line surprisingly recovered the wild type phenotype within 8 generations at high (27 °C), but not at low (20 °C), developmental temperatures. Male mating success experiments then revealed that outcrossed comet males with the typical comet phenotype suffered from lower mating success, while mating success of outcrossed comet males resembling wild types was partially restored. We document a fortuitous case where the addition of genetic polymorphism around a spontaneous mutation could have allowed partial restoration of phenotypic robustness. We further argue that sexual selection through mate choice is likely the driving force leading to phenotypic robustness in our system.

Viral Fitness Correlates with the Magnitude and Direction of the Perturbation Induced in the Host's Transcriptome: The Tobacco Etch Potyvirus-Tobacco Case Study

Determining the fitness of viral genotypes has become a standard practice in virology as it is essential to evaluate their evolutionary potential. Darwinian fitness, defined as the advantage of a given genotype with respect to a reference one, is a complex property that captures, in a single figure, differences in performance at every stage of viral infection. To what extent does viral fitness result from specific molecular interactions with host factors and regulatory networks during infection? Can we identify host genes in functional classes whose expression depends on viral fitness? Here, we compared the transcriptomes of tobacco plants infected with seven genotypes of tobacco etch potyvirus that differ in fitness. We found that the larger the fitness differences among genotypes, the more dissimilar the transcriptomic profiles are. Consistently, two different mutations, one in the viral RNA polymerase and another in the viral suppressor of RNA silencing, resulted in significantly similar gene expression profiles. Moreover, we identified host genes whose expression showed a significant correlation, positive or negative, with the virus' fitness. Differentially expressed genes which were positively correlated with viral fitness activate hormone- and RNA silencing-mediated pathways of plant defense. In contrast, those that were negatively correlated with fitness affect metabolism, reducing growth, and development. Overall, these results reveal the high information content of viral fitness and suggest its potential use to predict differences in genomic profiles of infected hosts.

Differences in adaptive dynamics determine the success of virus variants that propagate together

Virus fitness is a complex parameter that results from the interaction of virus-specific characters (e.g. intracellular growth rate, adsorption rate, virion extracellular stability, and tolerance to mutations) with others that depend on the underlying fitness landscape and the internal structure of the whole population. Individual mutants usually have lower fitness values than the complex population from which they come from. When they are propagated and allowed to attain large population sizes for a sufficiently long time, they approach mutation-selection equilibrium with the concomitant fitness gains. The optimization process follows dynamics that vary among viruses, likely due to differences in any of the parameters that determine fitness values. As a consequence, when different mutants spread together, the number of generations experienced by each of them prior to co-propagation may determine its particular fate. In this work we attempt a clarification of the effect of different levels of population diversity in the outcome of competition dynamics. To this end, we analyze the behavior of two mutants of the RNA bacteriophage Qβ that co-propagate with the wild-type virus. When both competitor viruses are clonal, the mutants rapidly outcompete the wild type. However, the outcome in competitions performed with partially optimized virus populations depends on the distance of the competitors to their clonal origin. We also implement a theoretical population dynamics model that describes the evolution of a heterogeneous population of individuals, each characterized by a fitness value, subjected to subsequent cycles of replication and mutation. The experimental results are explained in the framework of our theoretical model under two non-excluding, likely complementary assumptions: (1) The relative advantage of both competitors changes as populations approach mutation-selection equilibrium, as a consequence of differences in their growth rates and (2) one of the competitors is more robust to mutations than the other. The main conclusion is that the nearness of an RNA virus population to mutation-selection equilibrium is a key factor determining the fate of particular mutants arising during replication.

Effects of mutation and selection on plasticity of a promoter activity in Saccharomyces cerevisiae

Phenotypic plasticity is an evolvable property of biological systems that can arise from environment-specific regulation of gene expression. To better understand the evolutionary and molecular mechanisms that give rise to plasticity in gene expression, we quantified the effects of 235 single-nucleotide mutations in the Saccharomyces cerevisiae TDH3 promoter (P_TDH3 ) on the activity of this promoter in media containing glucose, galactose, or glycerol as a carbon source. We found that the distributions of mutational effects differed among environments because many mutations altered the plastic response exhibited by the wild-type allele. Comparing the effects of these mutations with the effects of 30 P_TDH3 polymorphisms on expression plasticity in the same environments provided evidence of natural selection acting to prevent the plastic response in P_TDH3 activity between glucose and galactose from becoming larger. The largest changes in expression plasticity were observed between fermentable (glucose or galactose) and nonfermentable (glycerol) carbon sources and were caused by mutations located in the RAP1 and GCR1 transcription factor binding sites. Mutations altered expression plasticity most frequently between the two fermentable environments, with mutations causing significant changes in plasticity between glucose and galactose distributed throughout the promoter, suggesting they might affect chromatin structure. Taken together, these results provide insight into the molecular mechanisms underlying gene-by-environment interactions affecting gene expression as well as the evolutionary dynamics affecting natural variation in plasticity of gene expression.

Critical Mutation Rate has an Exponential Dependence on Population Size for Eukaryotic-length Genomes with Crossover

The critical mutation rate (CMR) determines the shift between survival-of-the-fittest and survival of individuals with greater mutational robustness (“flattest”). We identify an inverse relationship between CMR and sequence length in an in silico system with a two-peak fitness landscape; CMR decreases to no more than five orders of magnitude above estimates of eukaryotic per base mutation rate. We confirm the CMR reduces exponentially at low population sizes, irrespective of peak radius and distance, and increases with the number of genetic crossovers. We also identify an inverse relationship between CMR and the number of genes, confirming that, for a similar number of genes to that for the plant Arabidopsis thaliana (25,000), the CMR is close to its known wild-type mutation rate; mutation rates for additional organisms were also found to be within one order of magnitude of the CMR. This is the first time such a simulation model has been assigned input and produced output within range for a given biological organism. The decrease in CMR with population size previously observed is maintained; there is potential for the model to influence understanding of populations undergoing bottleneck, stress, and conservation strategy for populations near extinction.

Proofreading-Deficient Coronaviruses Adapt for Increased Fitness over Long-Term Passage without Reversion of Exoribonuclease-Inactivating Mutations

The coronavirus (CoV) RNA genome is the largest among the single-stranded positive-sense RNA viruses. CoVs encode a proofreading 3'-to-5' exoribonuclease within nonstructural protein 14 (nsp14-ExoN) that is responsible for CoV high-fidelity replication. Alanine substitution of ExoN catalytic residues [ExoN(-)] in severe acute respiratory syndrome-associated coronavirus (SARS-CoV) and murine hepatitis virus (MHV) disrupts ExoN activity, yielding viable mutant viruses with defective replication, up to 20-fold-decreased fidelity, and increased susceptibility to nucleoside analogues. To test the stability of the ExoN(-) genotype and phenotype, we passaged MHV-ExoN(-) 250 times in cultured cells (P250), in parallel with wild-type MHV (WT-MHV). Compared to MHV-ExoN(-) P3, MHV-ExoN(-) P250 demonstrated enhanced replication and increased competitive fitness without reversion at the ExoN(-) active site. Furthermore, MHV-ExoN(-) P250 was less susceptible than MHV-ExoN(-) P3 to multiple nucleoside analogues, suggesting that MHV-ExoN(-) was under selection for increased replication fidelity. We subsequently identified novel amino acid changes within the RNA-dependent RNA polymerase and nsp14 of MHV-ExoN(-) P250 that partially accounted for the reduced susceptibility to nucleoside analogues. Our results suggest that increased replication fidelity is selected in ExoN(-) CoVs and that there may be a significant barrier to ExoN(-) reversion. These results also support the hypothesis that high-fidelity replication is linked to CoV fitness and indicate that multiple replicase proteins could compensate for ExoN functions during replication.IMPORTANCE Uniquely among RNA viruses, CoVs encode a proofreading exoribonuclease (ExoN) in nsp14 that mediates high-fidelity RNA genome replication. Proofreading-deficient CoVs with disrupted ExoN activity [ExoN(-)] either are nonviable or have significant defects in replication, RNA synthesis, fidelity, fitness, and virulence. In this study, we showed that ExoN(-) murine hepatitis virus can adapt during long-term passage for increased replication and fitness without reverting the ExoN-inactivating mutations. Passage-adapted ExoN(-) mutants also demonstrate increasing resistance to nucleoside analogues that is explained only partially by secondary mutations in nsp12 and nsp14. These data suggest that enhanced resistance to nucleoside analogues is mediated by the interplay of multiple replicase proteins and support the proposed link between CoV fidelity and fitness.

Evolution of drift robustness in small populations

Most mutations are deleterious and cause a reduction in population fitness known as the mutational load. In small populations, weakened selection against slightly-deleterious mutations results in an additional fitness reduction. Many studies have established that populations can evolve a reduced mutational load by evolving mutational robustness, but it is uncertain whether small populations can evolve a reduced susceptibility to drift-related fitness declines. Here, using mathematical modeling and digital experimental evolution, we show that small populations do evolve a reduced vulnerability to drift, or ‘drift robustness’. We find that, compared to genotypes from large populations, genotypes from small populations have a decreased likelihood of small-effect deleterious mutations, thus causing small-population genotypes to be drift-robust. We further show that drift robustness is not adaptive, but instead arises because small populations can only maintain fitness on drift-robust fitness peaks. These results have implications for genome evolution in organisms with small effective population sizes.

Genetic drift can reduce fitness in small populations by counteracting selection against deleterious mutations. Here, LaBar and Adami demonstrate through a mathematical model and simulations that small populations tend to evolve to drift-robust fitness peaks, which have a low likelihood of slightly-deleterious mutations.

Conditioning and Robustness of RNA Boltzmann Sampling under Thermodynamic Parameter Perturbations

Understanding how RNA secondary structure prediction methods depend on the underlying nearest-neighbor thermodynamic model remains a fundamental challenge in the field. Minimum free energy (MFE) predictions are known to be "ill conditioned" in that small changes to the thermodynamic model can result in significantly different optimal structures. Hence, the best practice is now to sample from the Boltzmann distribution, which generates a set of suboptimal structures. Although the structural signal of this Boltzmann sample is known to be robust to stochastic noise, the conditioning and robustness under thermodynamic perturbations have yet to be addressed. We present here a mathematically rigorous model for conditioning inspired by numerical analysis, and also a biologically inspired definition for robustness under thermodynamic perturbation. We demonstrate the strong correlation between conditioning and robustness and use its tight relationship to define quantitative thresholds for well versus ill conditioning. These resulting thresholds demonstrate that the majority of the sequences are at least sample robust, which verifies the assumption of sampling's improved conditioning over the MFE prediction. Furthermore, because we find no correlation between conditioning and MFE accuracy, the presence of both well- and ill-conditioned sequences indicates the continued need for both thermodynamic model refinements and alternate RNA structure prediction methods beyond the physics-based ones.

Attenuation of RNA viruses by redirecting their evolution in sequence space

RNA viruses pose serious threats to human health. Their success relies on their capacity to generate genetic variability and, consequently, on their adaptive potential. We describe a strategy to attenuate RNA viruses by altering their evolutionary potential. We rationally altered the genomes of Coxsackie B3 and influenza A viruses to redirect their evolutionary trajectories towards detrimental regions in sequence space. Specifically, viral genomes were engineered to harbour more serine and leucine codons with nonsense mutation targets: codons that could generate Stop mutations after a single nucleotide substitution. Indeed, these viruses generated more Stop mutations both in vitro and in vivo, accompanied by significant losses in viral fitness. In vivo, the viruses were attenuated, generated high levels of neutralizing antibodies and protected against lethal challenge. Our study demonstrates that cornering viruses in ‘risky’ areas of sequence space may be implemented as a broad-spectrum vaccine strategy against RNA viruses.

Virus attenuation is used to obtain vaccine strains. Here, the rapid evolution of RNA viruses is exploited by engineering their genomes to encode sites that are a mutation away from a stop codon, a clever method to generate attenuated viruses.

Spatiotemporal microbial evolution on antibiotic landscapes

A key aspect of bacterial survival is the ability to evolve while migrating across spatially varying environmental challenges. Laboratory experiments, however, often study evolution in well-mixed systems. Here, we introduce an experimental device, the microbial evolution and growth arena (MEGA)-plate, in which bacteria spread and evolved on a large antibiotic landscape (120 × 60 centimeters) that allowed visual observation of mutation and selection in a migrating bacterial front. While resistance increased consistently, multiple coexisting lineages diversified both phenotypically and genotypically. Analyzing mutants at and behind the propagating front, we found that evolution is not always led by the most resistant mutants; highly resistant mutants may be trapped behind more sensitive lineages. The MEGA-plate provides a versatile platform for studying microbial adaption and directly visualizing evolutionary dynamics.

Cassava brown streak virus has a rapidly evolving genome: implications for virus speciation, variability, diagnosis and host resistance

Cassava is a major staple food for about 800 million people in the tropics and sub-tropical regions of the world. Production of cassava is significantly hampered by cassava brown streak disease (CBSD), caused by Cassava brown streak virus (CBSV) and Ugandan cassava brown streak virus (UCBSV). The disease is suppressing cassava yields in eastern Africa at an alarming rate. Previous studies have documented that CBSV is more devastating than UCBSV because it more readily infects both susceptible and tolerant cassava cultivars, resulting in greater yield losses. Using whole genome sequences from NGS data, we produced the first coalescent-based species tree estimate for CBSV and UCBSV. This species framework led to the finding that CBSV has a faster rate of evolution when compared with UCBSV. Furthermore, we have discovered that in CBSV, nonsynonymous substitutions are more predominant than synonymous substitution and occur across the entire genome. All comparative analyses between CBSV and UCBSV presented here suggest that CBSV may be outsmarting the cassava immune system, thus making it more devastating and harder to control.

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.

Impact of increased mutagenesis on adaptation to high temperature in bacteriophage Qβ

RNA viruses replicate with very high error rates, which makes them more sensitive to additional increases in this parameter. This fact has inspired an antiviral strategy named lethal mutagenesis, which is based on the artificial increase of the error rate above a threshold incompatible with virus infectivity. A relevant issue concerning lethal mutagenesis is whether incomplete treatments might enhance the adaptive possibilities of viruses. We have addressed this question by subjecting an RNA virus, the bacteriophage Qβ, to different transmission regimes in the presence or the absence of sublethal concentrations of the mutagenic nucleoside analogue 5-azacytidine (AZC). Populations obtained were subsequently exposed to a non-optimal temperature and analyzed to determine their consensus sequences. Our results show that previously mutagenized populations rapidly fixed a specific set of mutations upon propagation at the new temperature, suggesting that the expansion of the mutant spectrum caused by AZC has an influence on later evolutionary behavior.

Antigenic diversification is correlated with increased thermostability in a mammalian virus

The theory of plastogenetic congruence posits that ultimately, the pressure to maintain function in the face of biomolecular destabilization produces robustness. As temperature goes up so does destabilization. Thus, genetic robustness, defined as phenotypic constancy despite mutation, should correlate with survival during thermal challenge. We tested this hypothesis using vesicular stomatitis virus (VSV). We produced two sets of evolved strains after selection for higher thermostability by either preincubation at 37°C or by incubation at 40°C during infection. These VSV populations became more thermostable and also more fit in the absence of thermal selection, demonstrating an absence of tradeoffs. Eleven out of 12 evolved populations had a fixed, nonsynonymous substitution in the nucleocapsid (N) open reading frame. There was a partial correlation between thermostability and mutational robustness that was observed when the former was measured at 42°C, but not at 37°C. These results are consistent with our earlier work and suggest that the relationship between robustness and thermostability is complex. Surprisingly, many of the thermostable strains also showed increased resistance to monoclonal antibody and polyclonal sera, including sera from natural hosts. These data suggest that evolved thermostability may lead to antigenic diversification and an increased ability to escape immune surveillance in febrile hosts, and potentially to an improved robustness. These relationships have important implications not only in terms of viral pathogenesis, but also for the development of vaccine vectors and oncolytic agents.

Adaptive Genetic Robustness of Escherichia coli Metabolic Fluxes

Genetic robustness refers to phenotypic invariance in the face of mutation and is a common characteristic of life, but its evolutionary origin is highly controversial. Genetic robustness could be an intrinsic property of biological systems, a result of direct natural selection, or a byproduct of selection for environmental robustness. To differentiate among these hypotheses, we analyze the metabolic network of Escherichia coli and comparable functional random networks. Treating the flux of each reaction as a trait and computationally predicting trait values upon mutations or environmental shifts, we discover that 1) genetic robustness is greater for the actual network than the random networks, 2) the genetic robustness of a trait increases with trait importance and this correlation is stronger in the actual network than in the random networks, and 3) the above result holds even after the control of environmental robustness. These findings demonstrate an adaptive origin of genetic robustness, consistent with the theoretical prediction that, under certain conditions, direct selection is sufficiently powerful to promote genetic robustness in cellular organisms.

An Evolving Genetic Architecture Interacts with Hill-Robertson Interference to Determine the Benefit of Sex

Sex is ubiquitous in the natural world, but the nature of its benefits remains controversial. Previous studies have suggested that a major advantage of sex is its ability to eliminate interference between selection on linked mutations, a phenomenon known as Hill-Robertson interference. However, those studies may have missed both important advantages and important disadvantages of sexual reproduction because they did not allow the distributions of mutational effects and interactions (i.e., the genetic architecture) to evolve. Here we investigate how Hill-Robertson interference interacts with an evolving genetic architecture to affect the evolutionary origin and maintenance of sex by simulating evolution in populations of artificial gene networks. We observed a long-term advantage of sex-equilibrium mean fitness of sexual populations exceeded that of asexual populations-that did not depend on population size. We also observed a short-term advantage of sex-sexual modifier mutations readily invaded asexual populations-that increased with population size, as was observed in previous studies. We show that the long- and short-term advantages of sex were both determined by differences between sexual and asexual populations in the evolutionary dynamics of two properties of the genetic architecture: the deleterious mutation rate ([Formula: see text]) and recombination load ([Formula: see text]). These differences resulted from a combination of selection to minimize [Formula: see text] which is experienced only by sexuals, and Hill-Robertson interference experienced primarily by asexuals. In contrast to the previous studies, in which Hill-Robertson interference had only a direct impact on the fitness advantages of sex, the impact of Hill-Robertson interference in our simulations was mediated additionally by an indirect impact on the efficiency with which selection acted to reduce [Formula: see text].

Genetic Instability of RNA Viruses

Despite having very limited coding capacity, RNA viruses are able to withstand challenge of antiviral drugs, cause epidemics in previously exposed human populations, and, in some cases, infect multiple host species. They are able to achieve this by virtue of their ability to multiply very rapidly, coupled with their extraordinary degree of genetic heterogeneity. RNA viruses exist not as single genotypes, but as a swarm of related variants, and this genomic diversity is an essential feature of their biology. RNA viruses have a variety of mechanisms that act in combination to determine their genetic heterogeneity. These include polymerase fidelity, error-mitigation mechanisms, genomic recombination, and different modes of genome replication. RNA viruses can vary in their ability to tolerate mutations, or “genetic robustness,” and several factors contribute to this. Finally, there is evidence that some RNA viruses exist close to a threshold where polymerase error rate has evolved to maximize the possible sequence space available, while avoiding the accumulation of a lethal load of deleterious mutations. We speculate that different viruses have evolved different error rates to complement the different “life-styles” they possess.

Coronavirus Host Range Expansion and Middle East Respiratory Syndrome Coronavirus Emergence: Biochemical Mechanisms and Evolutionary Perspectives

Coronaviruses have frequently expanded their host range in recent history, with two events resulting in severe disease outbreaks in human populations. Severe acute respiratory syndrome coronavirus (SARS-CoV) emerged in 2003 in Southeast Asia and rapidly spread around the world before it was controlled by public health intervention strategies. The 2012 Middle East respiratory syndrome coronavirus (MERS-CoV) outbreak represents another prime example of virus emergence from a zoonotic reservoir. Here, we review the current knowledge of coronavirus cross-species transmission, with particular focus on MERS-CoV. MERS-CoV is still circulating in the human population, and the mechanisms governing its cross-species transmission have been only partially elucidated, highlighting a need for further investigation. We discuss biochemical determinants mediating MERS-CoV host cell permissivity, including virus spike interactions with the MERS-CoV cell surface receptor dipeptidyl peptidase 4 (DPP4), and evolutionary mechanisms that may facilitate host range expansion, including recombination, mutator alleles, and mutational robustness. Understanding these mechanisms can help us better recognize the threat of emergence for currently circulating zoonotic strains.

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.

The study of homology between tumor progression genes and members of retroviridae as a tool to predict target-directed therapy failure

Oncogenes are the primary candidates for target-directed therapy, given that they are involved directly in the progression and resistance of tumors. However, the appearance of point mutations can hinder the treatment of patients with these new molecules, raising costs and the need to development new analogs that target the novel mutations. Based on an analysis of homologies, the present study discusses the possibility of predicting the failure of a protein as a pharmacological target, due to its similarities with retrovirus sequences, which have extremely high mutation rates. This analysis was based on the molecular evidence available in the literature, and widely-used and well-established PSI-BLAST, with two iterations and maximum of 500 aligned sequences. The possibility of predicting which newly-discovered genes involved in tumor progression would likely result in the failure of targeted therapy, using free, simple and automated bioinformatics tools, could provide substantial savings in the time and financial resources needed for long-term drug development.

Genetic code evolution reveals the neutral emergence of mutational robustness, and information as an evolutionary constraint

The standard genetic code (SGC) is central to molecular biology and its origin and evolution is a fundamental problem in evolutionary biology, the elucidation of which promises to reveal much about the origins of life. In addition, we propose that study of its origin can also reveal some fundamental and generalizable insights into mechanisms of molecular evolution, utilizing concepts from complexity theory. The first is that beneficial traits may arise by non-adaptive processes, via a process of "neutral emergence". The structure of the SGC is optimized for the property of error minimization, which reduces the deleterious impact of point mutations. Via simulation, it can be shown that genetic codes with error minimization superior to the SGC can emerge in a neutral fashion simply by a process of genetic code expansion via tRNA and aminoacyl-tRNA synthetase duplication, whereby similar amino acids are added to codons related to that of the parent amino acid. This process of neutral emergence has implications beyond that of the genetic code, as it suggests that not all beneficial traits have arisen by the direct action of natural selection; we term these "pseudaptations", and discuss a range of potential examples. Secondly, consideration of genetic code deviations (codon reassignments) reveals that these are mostly associated with a reduction in proteome size. This code malleability implies the existence of a proteomic constraint on the genetic code, proportional to the size of the proteome (P), and that its reduction in size leads to an "unfreezing" of the codon - amino acid mapping that defines the genetic code, consistent with Crick's Frozen Accident theory. The concept of a proteomic constraint may be extended to propose a general informational constraint on genetic fidelity, which may be used to explain variously, differences in mutation rates in genomes with differing proteome sizes, differences in DNA repair capacity and genome GC content between organisms, a selective pressure in the evolution of sexual reproduction, and differences in translational fidelity. Lastly, the utility of the concept of an informational constraint to other diverse fields of research is explored.

Effective lethal mutagenesis of influenza virus by three nucleoside analogs

Lethal mutagenesis is a broad-spectrum antiviral strategy that exploits the high mutation rate and low mutational tolerance of many RNA viruses. This approach uses mutagenic drugs to increase viral mutation rates and burden viral populations with mutations that reduce the number of infectious progeny. We investigated the effectiveness of lethal mutagenesis as a strategy against influenza virus using three nucleoside analogs, ribavirin, 5-azacytidine, and 5-fluorouracil. All three drugs were active against a panel of seasonal H3N2 and laboratory-adapted H1N1 strains. We found that each drug increased the frequency of mutations in influenza virus populations and decreased the virus' specific infectivity, indicating a mutagenic mode of action. We were able to drive viral populations to extinction by passaging influenza virus in the presence of each drug, indicating that complete lethal mutagenesis of influenza virus populations can be achieved when a sufficient mutational burden is applied. Population-wide resistance to these mutagenic agents did not arise after serial passage of influenza virus populations in sublethal concentrations of drug. Sequencing of these drug-passaged viral populations revealed genome-wide accumulation of mutations at low frequency. The replicative capacity of drug-passaged populations was reduced at higher multiplicities of infection, suggesting the presence of defective interfering particles and a possible barrier to the evolution of resistance. Together, our data suggest that lethal mutagenesis may be a particularly effective therapeutic approach with a high genetic barrier to resistance for influenza virus.

IMPORTANCE

Influenza virus is an RNA virus that causes significant morbidity and mortality during annual epidemics. Novel therapies for RNA viruses are needed due to the ease with which these viruses evolve resistance to existing therapeutics. Lethal mutagenesis is a broad-spectrum strategy that exploits the high mutation rate and the low mutational tolerance of most RNA viruses. It is thought to possess a higher barrier to resistance than conventional antiviral strategies. We investigated the effectiveness of lethal mutagenesis against influenza virus using three different drugs. We showed that influenza virus was sensitive to lethal mutagenesis by demonstrating that all three drugs induced mutations and led to an increase in the generation of defective viral particles. We also found that it may be difficult for resistance to these drugs to arise at a population-wide level. Our data suggest that lethal mutagenesis may be an attractive anti-influenza strategy that warrants further investigation.

Estimating Fitness of Viral Quasispecies from Next-Generation Sequencing Data

The quasispecies model is ubiquitous in the study of viruses. While having lead to a number of insights that have stood the test of time, the quasispecies model has mostly been discussed in a theoretical fashion with little support of data. With next-generation sequencing (NGS), this situation is changing and a wealth of data can now be produced in a time- and cost-efficient manner. NGS can, after removal of technical errors, yield an exceedingly detailed picture of the viral population structure. The widespread availability of cross-sectional data can be used to study fitness landscapes of viral populations in the quasispecies model. This chapter highlights methods that estimate the strength of selection in selective sweeps, assesses marginal fitness effects of quasispecies, and finally infers the fitness landscape of a viral quasispecies, all on the basis of NGS data.

Theories of Lethal Mutagenesis: From Error Catastrophe to Lethal Defection

RNA viruses get extinct in a process called lethal mutagenesis when subjected to an increase in their mutation rate, for instance, by the action of mutagenic drugs. Several approaches have been proposed to understand this phenomenon. The extinction of RNA viruses by increased mutational pressure was inspired by the concept of the error threshold. The now classic quasispecies model predicts the existence of a limit to the mutation rate beyond which the genetic information of the wild type could not be efficiently transmitted to the next generation. This limit was called the error threshold, and for mutation rates larger than this threshold, the quasispecies was said to enter into error catastrophe. This transition has been assumed to foster the extinction of the whole population. Alternative explanations of lethal mutagenesis have been proposed recently. In the first place, a distinction is made between the error threshold and the extinction threshold, the mutation rate beyond which a population gets extinct. Extinction is explained from the effect the mutation rate has, throughout the mutational load, on the reproductive ability of the whole population. Secondly, lethal defection takes also into account the effect of interactions within mutant spectra, which have been shown to be determinant for the understanding the extinction of RNA virus due to an augmented mutational pressure. Nonetheless, some relevant issues concerning lethal mutagenesis are not completely understood yet, as so survival of the flattest, i.e. the development of resistance to lethal mutagenesis by evolving towards mutationally more robust regions of sequence space, or sublethal mutagenesis, i.e., the increase of the mutation rate below the extinction threshold which may boost the adaptability of RNA virus, increasing their ability to develop resistance to drugs (including mutagens). A better design of antiviral therapies will still require an improvement of our knowledge about lethal mutagenesis.

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.

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.

On the Nature and Evolutionary Impact of Phenotypic Robustness Mechanisms

Biologists have long observed that physiological and developmental processes are insensitive, or robust, to many genetic and environmental perturbations. A complete understanding of the evolutionary causes and consequences of this robustness is lacking. Recent progress has been made in uncovering the regulatory mechanisms that underlie environmental robustness in particular. Less is known about robustness to the effects of mutations, and indeed the evolution of mutational robustness remains a controversial topic. The controversy has spread to related topics, in particular the evolutionary relevance of cryptic genetic variation. This review aims to synthesize current understanding of robustness mechanisms and to cut through the controversy by shedding light on what is and is not known about mutational robustness. Some studies have confused mutational robustness with non-additive interactions between mutations (epistasis). We conclude that a profitable way forward is to focus investigations (and rhetoric) less on mutational robustness and more on epistasis.

Uneven genetic robustness of HIV-1 integrase

Genetic robustness (tolerance of mutation) may be a naturally selected property in some viruses, because it should enhance adaptability. Robustness should be especially beneficial to viruses like HIV-1 that exhibit high mutation rates and exist in immunologically hostile environments. Surprisingly, however, the HIV-1 capsid protein (CA) exhibits extreme fragility. To determine whether fragility is a general property of HIV-1 proteins, we created a large library of random, single-amino-acid mutants in HIV-1 integrase (IN), covering >40% of amino acid positions. Despite similar degrees of sequence variation in naturally occurring IN and CA sequences, we found that HIV-1 IN was significantly more robust than CA, with random nonsilent IN mutations only half as likely to cause lethal defects. Interestingly, IN and CA were similar in that a subset of mutations with high in vitro fitness were rare in natural populations. IN mutations of this type were more likely to occur in the buried interior of the modeled HIV-1 intasome, suggesting that even very subtle fitness effects suppress variation in natural HIV-1 populations. Lethal mutations, in particular those that perturbed particle production, proteolytic processing, and particle-associated IN levels, were strikingly localized at specific IN subunit interfaces. This observation strongly suggests that binding interactions between particular IN subunits regulate proteolysis during HIV-1 virion morphogenesis. Overall, use of the IN mutant library in conjunction with structural models demonstrates the overall robustness of IN and highlights particular regions of vulnerability that may be targeted in therapeutic interventions.

IMPORTANCE

The HIV-1 integrase (IN) protein is responsible for the integration of the viral genome into the host cell chromosome. To measure the capacity of IN to maintain function in the face of mutation, and to probe structure/function relationships, we created a library of random single-amino-acid IN mutations that could mimic the types of mutations that naturally occur during HIV-1 infection. Previously, we measured the robustness of HIV-1 capsid in this manner and determined that it is extremely intolerant of mutation. In contrast to CA, HIV-1 IN proved relatively robust, with far fewer mutations causing lethal defects. However, when we subsequently mapped the lethal mutations onto a model of the structure of the multisubunit IN-viral DNA complex, we found the lethal mutations that caused virus morphogenesis defects tended to be highly localized at subunit interfaces. This discovery of vulnerable regions of HIV-1 IN could inform development of novel therapeutics.

Costs and benefits of mutational robustness in RNA viruses

The accumulation of mutations in RNA viruses is thought to facilitate rapid adaptation to changes in the environment. However, most mutations have deleterious effects on fitness, especially for viruses. Thus, tolerance to mutations should determine the nature and extent of genetic diversity that can be maintained in the population. Here, we combine population genetics theory, computer simulation, and experimental evolution to examine the advantages and disadvantages of tolerance to mutations, also known as mutational robustness. We find that mutational robustness increases neutral diversity and, as expected, can facilitate adaptation to a new environment. Surprisingly, under certain conditions, robustness may also be an impediment for viral adaptation, if a highly diverse population contains a large proportion of previously neutral mutations that are deleterious in the new environment. These findings may inform therapeutic strategies that cause extinction of otherwise robust viral populations.

Viroids: survivors from the RNA world?

Because RNA can be a carrier of genetic information and a biocatalyst, there is a consensus that it emerged before DNA and proteins, which eventually assumed these roles and relegated RNA to intermediate functions. If such a scenario--the so-called RNA world--existed, we might hope to find its relics in our present world. The properties of viroids that make them candidates for being survivors of the RNA world include those expected for primitive RNA replicons: (a) small size imposed by error-prone replication, (b) high G + C content to increase replication fidelity, (c) circular structure for assuring complete replication without genomic tags, (d) structural periodicity for modular assembly into enlarged genomes, (e) lack of protein-coding ability consistent with a ribosome-free habitat, and (f) replication mediated in some by ribozymes, the fingerprint of the RNA world. With the advent of DNA and proteins, those protoviroids lost some abilities and became the plant parasites we now know.

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.

The genotype-phenotype map of yeast complex traits: basic parameters and the role of natural selection

Most phenotypic traits are controlled by many genes, but a global picture of the genotype-phenotype map (GPM) is lacking. For example, in no species do we know generally how many genes affect a trait and how large these effects are. It is also unclear to what extent GPMs are shaped by natural selection. Here we address these fundamental questions using the reverse genetic data of 220 morphological traits in 4,718 budding yeast strains, each of which lacks a nonessential gene. We show that 1) the proportion of genes affecting a trait varies from <1% to >30%, averaging 6%, 2) most traits are impacted by many more small-effect genes than large-effect genes, and 3) the mean effect of all nonessential genes on a trait decreases precipitously as the estimated importance of the trait to fitness increases. An analysis of 3,116 yeast gene expression traits in 754 gene-deletion strains reveals a similar pattern. These findings illustrate the power of genome-wide reverse genetics in genotype-phenotype mapping, uncover an enormous range of genetic complexity of phenotypic traits, and suggest that the GPM of cellular organisms has been shaped by natural selection for mutational robustness.

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.