Epistasis and its relationship to canalization in the RNA virus phi 6

Although deleterious mutations are believed to play a critical role in evolution, assessing their realized effect has been difficult. A key parameter governing the effect of deleterious mutations is the nature of epistasis, the interaction between the mutations. RNA viruses should provide one of the best systems for investigating the nature of epistasis because the high mutation rate allows a thorough investigation of mutational effects and interactions. Nonetheless, previous investigations of RNA viruses by S. Crotty and co-workers and by S. F. Elena have been unable to detect a significant effect of epistasis. Here we provide evidence that positive epistasis is characteristic of deleterious mutations in the RNA bacteriophage phi 6. We estimated the effects of deleterious mutations by performing mutation-accumulation experiments on five viral genotypes of decreasing fitness. We inferred positive epistasis because viral genotypes with low fitness were found to be less sensitive to deleterious mutations. We further examined environmental sensitivity in these genotypes and found that low-fitness genotypes were also less sensitive to environmental perturbations. Our results suggest that even random mutations impact the degree of canalization, the buffering of a phenotype against genetic and environmental perturbations. In addition, our results suggest that genetic and environmental canalization have the same developmental basis and finally that an understanding of the nature of epistasis may first require an understanding of the nature of canalization.     

Epistasis among Deleterious Mutations in the HIV-1 Protease

A central goal in molecular evolution is to understand how genetic interactions between protein mutations shape protein function and fitness. While intergenic epistasis has been extensively explored in eukaryotes, bacteria, and viruses, intragenic epistatic interactions have been insufficiently studied. Here, we employ a model system in which lambda phage fitness correlates with the enzymatic activity of human immunodeficiency virus type 1 (HIV-1) protease to systematically determine the epistatic interactions between intragenic pairs of deleterious protein substitutions. We generated 114 genotypes of the HIV-1 protease, each carrying pairs of nucleotide substitution mutations whose separated and combined deleterious effects on fitness were then determined. A high proportion (39%) of pairs displayed lethality. Several pairs exhibited significant interactions for fitness, including positive and negative epistasis. Significant negative epistatic interactions predominated (15%) over positive interactions (2%). However, the average ± SD epistatic effect, ē = 0.0025 ± 0.1334, was not significantly different from zero (p = 0.8368). Notably, epistatic interactions, regardless of epistatic direction, tend to be more frequent in the context of less deleterious mutations. In the present study, the high frequencies of lethality and negative epistasis indicate that the HIV-1 protease is highly sensitive to the effects of deleterious mutations. Therefore, proteins may not be as robust to mutational change as is usually expected.     

A phylogenetic method for detecting positive epistasis in gene sequences and its application to RNA virus evolution

RNA virus genomes are compact, often containing multiple overlapping reading frames and functional secondary structure. Consequently, it is thought that evolutionary interactions between nucleotide sites are commonplace in the genomes of these infectious agents. However, the role of epistasis in natural populations of RNA viruses remains unclear. To investigate the pervasiveness of epistasis in RNA viruses, we used a parsimony-based computational method to identify pairs of co-occurring mutations along phylogenies of 177 RNA virus genes. This analysis revealed widespread evidence for positive epistatic interactions at both synonymous and nonsynonymous nucleotide sites and in both clonal and recombining viruses, with the majority of these interactions spanning very short sequence regions. These findings have important implications for understanding the key aspects of RNA virus evolution, including the dynamics of adaptation. Additionally, many comparative analyses that utilize the phylogenetic relationships among gene sequences assume that mutations represent independent, uncorrelated events. Our results show that this assumption may often be invalid.     

Epistasis between mutations is host-dependent for an RNA virus

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

Pervasive Pairwise Intragenic Epistasis among Sequential Mutations in TEM-1 β-Lactamase

Interactions between mutations play a central role in shaping the fitness landscape, but a clear picture of intragenic epistasis has yet to emerge. To further reveal the prevalence and patterns of intragenic epistasis, we present a survey of epistatic interactions between sequential mutations in TEM-1 β-lactamase. We measured the fitness effect of ~ 12,000 pairs of consecutive amino acid substitutions and used our previous study of the fitness effects of single amino acid substitutions to calculate epistasis for over 8000 mutation pairs. Since sequential mutations are prone to physically interact, we postulated that our study would be surveying specific epistasis instead of nonspecific epistasis. We found widespread negative epistasis, especially in beta-strands, and a high frequency of negative sign epistasis among individually beneficial mutations. Negative epistasis (52%) occurred 7.6 times as frequently as positive epistasis (6.8%). Buried residues experienced more negative epistasis that surface-exposed residues. However, TEM-1 exhibited a couple of hotspots for positive epistasis, most notably L221/ R222 at which many combinations of mutations positively interacted. This study is the first to systematically examine pairwise epistasis throughout an entire protein performing its native function in its native host.     

Plasticity and epistasis strongly affect bacterial fitness after losing multiple metabolic genes

Many bacterial lineages lack seemingly essential metabolic genes. Previous work suggested selective benefits could drive the loss of biosynthetic functions from bacterial genomes when the corresponding metabolites are sufficiently available in the environment. However, the factors that govern this “genome streamlining” remain poorly understood. Here we determine the effect of plasticity and epistasis on the fitness of Escherichia coli genotypes from whose genome biosynthetic genes for one, two, or three different amino acids have been deleted. Competitive fitness experiments between auxotrophic mutants and prototrophic wild‐type cells in one of two carbon environments revealed that plasticity and epistasis strongly affected the mutants’ fitness individually and interactively. Positive and negative epistatic interactions were prevalent, yet on average cancelled each other out. Moreover, epistasis correlated negatively with the expected effects of combined auxotrophy‐causing mutations, thus producing a pattern of diminishing returns. Moreover, computationally analyzing 1,432 eubacterial metabolic networks revealed that most pairs of auxotrophies co‐occurred significantly more often than expected by chance, suggesting epistatic interactions and/or environmental factors favored these combinations. Our results demonstrate that both the genetic background and environmental conditions determine the adaptive value of a loss‐of‐biochemical‐function mutation and that fitness gains decelerate, as more biochemical functions are lost.     

Fitness ranking of individual mutants drives patterns of epistatic interactions in HIV-1

Fitness interactions between mutations, referred to as epistasis, can strongly impact evolution. For RNA viruses and retroviruses with their high mutation rates, epistasis may be particularly important to overcome fitness losses due to the accumulation of deleterious mutations and thus could influence the frequency of mutants in a viral population. As human immunodeficiency virus type 1 (HIV-1) resistance to azidothymidine (AZT) requires selection of sequential mutations, it is a good system to study the impact of epistasis. Here we present a thorough analysis of a classical AZT-resistance pathway (the 41-215 cluster) of HIV-1 variants by fitness measurements in single round infection assays covering physiological drug concentrations ex vivo. The sign and value of epistasis varied and did not predict the epistatic effect on the mutant frequency. This complex behavior is explained by the fitness ranking of the variants that strongly depends on environmental factors, i.e., the presence and absence of drugs and the host cells used. Although some interactions compensate fitness losses, the observed small effect on the relative mutant frequencies suggests that epistasis might be inefficient as a buffering mechanism for fitness losses in vivo. While the use of epistasis-based hypotheses to make general assumptions on the evolutionary dynamics of viral populations is appealing, our data caution their interpretation without further knowledge on the characteristics of the viral mutant spectrum under different environmental conditions.     

In silico predicted robustness of viroid RNA secondary structures. II. Interaction between mutation pairs

Viroids are plant subviral pathogens whose genomes are constituted by a single-stranded and covalently closed small RNA molecule that does not encode for any protein. Most of the 29 described viroid species fold into a rodlike or quasi-rodlike structure, whereas a few of them fold as highly branched structures. In a previous study, we used RNA thermodynamic secondary structure prediction algorithms to compare the mutational robustness of all viroid species. Here we used the same approach to explore the sign and strength of epistasis among pairs of random mutations. We found that antagonistic interactions were more abundant than synergistic ones. However, despite their lower frequency, synergistic interactions tended to be more intense. Mutational robustness and the intensity of epistasis were correlated such that viroid species with large average mutational effects showed stronger antagonistic epistasis, whereas viroids with mild average mutational effects showed weaker antagonistic interactions. The strength of antagonistic epistasis decreased with genome complexity as a consequence of the gained robustness of duplicated genomes. In good agreement with our previous finding of an evolutionary trend toward increased robustness, we now found a trend toward reduced antagonistic epistasis.     

Prevalence of epistasis in the evolution of influenza A surface proteins

The surface proteins of human influenza A viruses experience positive selection to escape both human immunity and, more recently, antiviral drug treatments. In bacteria and viruses, immune-escape and drug-resistant phenotypes often appear through a combination of several mutations that have epistatic effects on pathogen fitness. However, the extent and structure of epistasis in influenza viral proteins have not been systematically investigated. Here, we develop a novel statistical method to detect positive epistasis between pairs of sites in a protein, based on the observed temporal patterns of sequence evolution. The method rests on the simple idea that a substitution at one site should rapidly follow a substitution at another site if the sites are positively epistatic. We apply this method to the surface proteins hemagglutinin and neuraminidase of influenza A virus subtypes H3N2 and H1N1. Compared to a non-epistatic null distribution, we detect substantial amounts of epistasis and determine the identities of putatively epistatic pairs of sites. In particular, using sequence data alone, our method identifies epistatic interactions between specific sites in neuraminidase that have recently been demonstrated, in vitro, to confer resistance to the drug oseltamivir; these epistatic interactions are responsible for widespread drug resistance among H1N1 viruses circulating today. This experimental validation demonstrates the predictive power of our method to identify epistatic sites of importance for viral adaptation and public health. We conclude that epistasis plays a large role in shaping the molecular evolution of influenza viruses. In particular, sites with , which would normally not be identified as positively selected, can facilitate viral adaptation through epistatic interactions with their partner sites. The knowledge of specific interactions among sites in influenza proteins may help us to predict the course of antigenic evolution and, consequently, to select more appropriate vaccines and drugs.     

Epistasis and the adaptability of an RNA virus

We have explored the patterns of fitness recovery in the vesicular stomatitis RNA virus. We show that, in our experimental setting, reversions to the wild-type genotype were rare and fitness recovery was at least partially driven by compensatory mutations. We compared compensatory adaptation for genotypes carrying (1) mutations with varying deleterious fitness effects, (2) one or two deleterious mutations, and (3) pairs of mutations showing differences in the strength and sign of epistasis. In all cases, we found that the rate of fitness recovery and the proportion of reversions were positively affected by population size. Additionally, we observed that mutations with large fitness effect were always compensated faster than mutations with small fitness effect. Similarly, compensatory evolution was faster for genotypes carrying a single deleterious mutation than for those carrying pairs of mutations. Finally, for genotypes carrying two deleterious mutations, we found evidence of a negative correlation between the epistastic effect and the rate of compensatory evolution.     

EPISTASIS BETWEEN NEW MUTATIONS AND GENETIC BACKGROUND AND A TEST OF GENETIC CANALIZATION

Abstract The importance for fitness of epistatic interactions among mutations is poorly known, yet epistasis can exert important effects on the dynamics of evolving populations. We showed previously that epistatic interactions are common between pairs of random insertion mutations in the bacterium Escherichia coli . In this paper, we examine interactions between these mutations and other mutations by transducing each of twelve insertion mutations into two genetic backgrounds, one ancestral and the other having evolved in, and adapted to, a defined laboratory environment for 10,000 generations. To assess the effect of the mutation on fitness, we allowed each mutant to compete against its unmutated counterpart in that same environment. Overall, there was a strong positive correlation between the mutational effects on the two genetic backgrounds. Nonetheless, three of the twelve mutations had significantly different effects on the two backgrounds, indicating epistasis. There was no significant tendency for the mutations to be less harmful on the derived background. Thus, there is no evidence supporting the hypothesis that the derived bacteria had adapted, in part, by becoming buffered against the harmful effects of mutations.     

Epistasis buffers the fitness effects of rifampicin- resistance mutations in Pseudomonas aeruginosa

Epistatic interactions between resistance mutations in antibiotic-free environments potentially play a crucial role in the spread of resistance in pathogen populations by determining the fitness cost associated with resistance. We used an experimental evolution approach to test for epistatic interactions between 14 different pairs of rifampicin mutations in the pathogenic bacterium Pseudomonas aeruginosa in 42 different rifampicin-free environments. First, we show that epistasis between rifampicin-resistance mutations tends to be antagonistic: the fitness effect of having two mutations is generally smaller than that predicted from the effects of individual mutations on the wild-type. Second, we show that sign epistasis between resistance mutations is both common and strong; most notably, pairs of deleterious resistance mutations often partially or completely compensate for each others' costs, revealing a novel mechanism for compensatory adaptation. These results suggest that antagonistic epistasis between intragenic resistance mutations may be a key determinant of the cost of antibiotic resistance and compensatory adaptation in pathogen populations.     

Initial mutations direct alternative pathways of protein evolution

Whether evolution is erratic due to random historical details, or is repeatedly directed along similar paths by certain constraints, remains unclear. Epistasis (i.e. non-additive interaction between mutations that affect fitness) is a mechanism that can contribute to both scenarios. Epistasis can constrain the type and order of selected mutations, but it can also make adaptive trajectories contingent upon the first random substitution. This effect is particularly strong under sign epistasis, when the sign of the fitness effects of a mutation depends on its genetic background. In the current study, we examine how epistatic interactions between mutations determine alternative evolutionary pathways, using in vitro evolution of the antibiotic resistance enzyme TEM-1 β-lactamase. First, we describe the diversity of adaptive pathways among replicate lines during evolution for resistance to a novel antibiotic (cefotaxime). Consistent with the prediction of epistatic constraints, most lines increased resistance by acquiring three mutations in a fixed order. However, a few lines deviated from this pattern. Next, to test whether negative interactions between alternative initial substitutions drive this divergence, alleles containing initial substitutions from the deviating lines were evolved under identical conditions. Indeed, these alternative initial substitutions consistently led to lower adaptive peaks, involving more and other substitutions than those observed in the common pathway. We found that a combination of decreased enzymatic activity and lower folding cooperativity underlies negative sign epistasis in the clash between key mutations in the common and deviating lines (Gly238Ser and Arg164Ser, respectively). Our results demonstrate that epistasis contributes to contingency in protein evolution by amplifying the selective consequences of random mutations.     

Interaction between directional epistasis and average mutational effects.

We investigate the relationship between the average fitness decay due to single mutations and the strength of epistatic interactions in genetic sequences. We observe that epistatic interactions between mutations are correlated to the average fitness decay, both in RNA secondary structure prediction as well as in digital organisms replicating in silico. This correlation implies that, during adaptation, epistasis and average mutational effect cannot be optimized independently. In experiments with RNA sequences evolving on a neutral network, the selective pressure to decrease the mutational load then leads to a reduction in the amount of sequences with strong antagonistic interactions between deleterious mutations in the population.     

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

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

The Evolution of Epistasis and Its Links With Genetic Robustness, Complexity and Drift in a Phenotypic Model of Adaptation

The epistatic interactions among mutations have a large effect on the evolution of populations. In this article we provide a formalism under which epistatic interactions among pairs of mutations have a distribution whose mean can be modulated. We find that the mean epistasis is correlated to the effect of mutations or genetic robustness, which suggests that such formalism is in good agreement with most in silico models of evolution where the same pattern is observed. We further show that the evolution of epistasis is highly dependant on the intensity of drift and of how complex the organisms are, and that either positive or negative epistasis could be selected for, depending on the balance between the efficiency of selection and the intensity of drift.     

The causes of epistasis in genetic networks

Epistasis refers to the nonadditive interactions between genes in determining phenotypes. Considerable efforts have shown that, even for a given organism, epistasis may vary both in intensity and sign. Recent comparative studies supported that the overall sign of epistasis switches from positive to negative as the complexity of an organism increases, and it has been hypothesized that this change shall be a consequence of the underlying gene network properties. Why should this be the case? What characteristics of genetic networks determine the sign of epistasis? Here we show, by evolving genetic networks that differ in their complexity and robustness against perturbations but that perform the same tasks, that robustness increased with complexity and that epistasis was positive for small nonrobust networks but negative for large robust ones. Our results indicate that robustness and negative epistasis emerge as a consequence of the existence of redundant elements in regulatory structures of genetic networks and that the correlation between complexity and epistasis is a byproduct of such redundancy, allowing for the decoupling of epistasis from the underlying network complexity.     

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

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

Mapping the Fitness Landscape of Gene Expression Uncovers the Cause of Antagonism and Sign Epistasis between Adaptive Mutations

How do adapting populations navigate the tensions between the costs of gene expression and the benefits of gene products to optimize the levels of many genes at once? Here we combined independently-arising beneficial mutations that altered enzyme levels in the central metabolism of Methylobacterium extorquens to uncover the fitness landscape defined by gene expression levels. We found strong antagonism and sign epistasis between these beneficial mutations. Mutations with the largest individual benefit interacted the most antagonistically with other mutations, a trend we also uncovered through analyses of datasets from other model systems. However, these beneficial mutations interacted multiplicatively (i.e., no epistasis) at the level of enzyme expression. By generating a model that predicts fitness from enzyme levels we could explain the observed sign epistasis as a result of overshooting the optimum defined by a balance between enzyme catalysis benefits and fitness costs. Knowledge of the phenotypic landscape also illuminated that, although the fitness peak was phenotypically far from the ancestral state, it was not genetically distant. Single beneficial mutations jumped straight toward the global optimum rather than being constrained to change the expression phenotypes in the correlated fashion expected by the genetic architecture. Given that adaptation in nature often results from optimizing gene expression, these conclusions can be widely applicable to other organisms and selective conditions. Poor interactions between individually beneficial alleles affecting gene expression may thus compromise the benefit of sex during adaptation and promote genetic differentiation.     

The rank ordering of genotypic fitness values predicts genetic constraint on natural selection on landscapes lacking sign epistasis

Sewall Wright's genotypic fitness landscape makes explicit one mechanism by which epistasis for fitness can constrain evolution by natural selection. Wright distinguished between landscapes possessing multiple fitness peaks and those with only a single peak and emphasized that the former class imposes substantially greater constraint on natural selection. Here I present novel formalism that more finely partitions the universe of possible fitness landscapes on the basis of the rank ordering of their genotypic fitness values. In this report I focus on fitness landscapes lacking sign epistasis (i.e., landscapes that lack mutations the sign of whose fitness effect varies epistatically), which constitute a subset of Wright's single peaked landscapes. More than one fitness rank ordering lacking sign epistasis exists for L > 2 (where L is the number of interacting loci), and I find that a highly statistically significant effect exists between landscape membership in fitness rank-ordering partition and two different proxies for genetic constraint, even within this subset of landscapes. This statistical association is robust to population size, permitting general inferences about some of the characteristics of fitness rank orderings responsible for genetic constraint on natural selection.