The Genetics of Adaptation for Eight Microvirid Bacteriophages

Theories of adaptive molecular evolution have recently experienced significant expansion, and their predictions and assumptions have begun to be subjected to rigorous empirical testing. However, these theories focus largely on predicting the first event in adaptive evolution, the fixation of a single beneficial mutation. To address long-term adaptation it is necessary to include new assumptions, but empirical data are needed for guidance. To empirically characterize the general properties of adaptive walks, eight recently isolated relatives of the single-stranded DNA (ssDNA) bacteriophage φX174 (family Microviridae) were adapted to identical selective conditions. Three of the eight genotypes were adapted in replicate, for a total of 11 adaptive walks. We measured fitness improvement and identified the genetic changes underlying the observed adaptation. Nearly all phages were evolvable; nine of the 11 lineages showed a significant increase in fitness. However, fitness plateaued quickly, and adaptation was achieved through only three substitutions on average. Parallel evolution was rampant, both across replicates of the same genotype as well as across different genotypes, yet adaptation of replicates never proceeded through the exact same set of mutations. Despite this, final fitnesses did not vary significantly among replicates. Final fitnesses did vary significantly across genotypes but not across phylogenetic groupings of genotypes. A positive correlation was found between the number of substitutions in an adaptive walk and the magnitude of fitness improvement, but no correlation was found between starting and ending fitness. These results provide an empirical framework for future adaptation theory.     

Multiple genetic pathways to similar fitness limits during viral adaptation to a new host

The gain in fitness during adaptation depends on the supply of beneficial mutations. Despite a good theoretical understanding of how evolution proceeds for a defined set of mutations, there is little understanding of constraints on net fitness-whether fitness will reach a limit despite ongoing selection and mutation, and if there is a limit, what determines it. Here, the dsDNA bacteriophage SP6, a virus of Salmonella, was adapted to Escherichia coli K-12. From an isolate capable of modest growth on E. coli, four lines were adapted for rapid growth by protocols differing in use of mutagen, propagation method, and duration, but using the same media, temperature, and a continual excess of the novel host. Nucleotide changes underlying those adaptations differed greatly in number and identity, but the four lines achieved similar absolute fitness at the end, an increase of more than 4000-fold phage descendants per hour. Thus, the fitness landscape allows multiple genetic paths to the same approximate fitness limit. The existence and causes of fitness limits have ramifications to genome engineering, vaccine design, and "lethal mutagenesis" treatments to cure viral infections.     

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.     

Adaptation in sexuals vs. asexuals: clonal interference and the Fisher-Muller model

Fisher and Muller's theory that recombination speeds adaptation by eliminating competition among beneficial mutations has proved a popular explanation for the advantage of sex. Recent theoretical studies have attempted to quantify the speed of adaptation under the Fisher-Muller model, partly in an attempt to understand the role of "clonal interference" in microbial experimental evolution. We reexamine adaptation in sexuals vs. asexuals, using a model of DNA sequence evolution. In this model, a modest number of sites can mutate to beneficial alleles and the fitness effects of these mutations are unequal. We study (1) transition probabilities to different beneficial mutations; (2) waiting times to the first and the last substitutions of beneficial mutations; and (3) trajectories of mean fitness through time. We find that some of these statistics are surprisingly similar between sexuals and asexuals. These results highlight the importance of the choice of substitution model in assessing the Fisher-Muller advantage of sex.     

Impact of genetic architecture on the relative rates of X versus autosomal adaptive substitution

Molecular evolutionary theory predicts that the ratio of autosomal to X-linked adaptive substitution (K(A)/K(x)) is primarily determined by the average dominance coefficient of beneficial mutations. Although this theory has profoundly influenced analysis and interpretation of comparative genomic data, its predictions are based upon two unverified assumptions about the genetic basis of adaptation. The theory assumes that 1) the rate of adaptively driven molecular evolution is limited by the availability of beneficial mutations, and 2) the scaling of evolutionary parameters between the X and the autosomes (e.g., the beneficial mutation rate, and the fitness effect distribution of beneficial alleles, per X-linked versus autosomal locus) is constant across molecular evolutionary timescales. Here, we show that the genetic architecture underlying bouts of adaptive substitution can influence both assumptions, and consequently, the theoretical relationship between K(A)/K(x) and mean dominance. Quantitative predictions of prior theory apply when 1) many genomically dispersed genes potentially contribute beneficial substitutions during individual steps of adaptive walks, and 2) the population beneficial mutation rate, summed across the set of potentially contributing genes, is sufficiently small to ensure that adaptive substitutions are drawn from new mutations rather than standing genetic variation. Current research into the genetic basis of adaptation suggests that both assumptions are plausibly violated. We find that the qualitative positive relationship between mean dominance and K(A)/K(x) is relatively robust to the specific conditions underlying adaptive substitution, yet the quantitative relationship between dominance and K(A)/K(x) is quite flexible and context dependent. This flexibility may partially account for the puzzlingly variable X versus autosome substitution patterns reported in the empirical evolutionary genomics literature. The new theory unites the previously separate analysis of adaptation using new mutations versus standing genetic variation and makes several useful predictions about the interaction between genetic architecture, evolutionary genetic constraints, and effective population size in determining the ratio of adaptive substitution between autosomal and X-linked genes.     

Exceptional Convergent Evolution in a Virus

Replicate lineages of the bacteriophage X 174 adapted to growth at high temperature on either of two hosts exhibited high rates of identical, independent substitutions. Typically, a dozen or more substitutions accumulated in the 5.4-kilobase genome during propagation. Across the entire data set of nine lineages, 119 independent substitutions occurred at 68 nucleotide sites. Over half of these substitutions, accounting for one third of the sites, were identical with substitutions in other lineages. Some convergent substitutions were specific to the host used for phage propagation, but others occurred across both hosts. Continued adaptation of an evolved phage at high temperature, but on the other host, led to additional changes that included reversions of previous substitutions. Phylogenetic reconstruction using the complete genome sequence not only failed to recover the correct evolutionary history because of these convergent changes, but the true history was rejected as being a significantly inferior fit to the data. Replicate lineages subjected to similar environmental challenges showed similar rates of substitution and similar rates of fitness improvement across corresponding times of adaptation. Substitution rates and fitness improvements were higher during the initial period of adaptation than during a later period, except when the host was changed.     

Parallel Genetic Evolution Within and Between Bacteriophage Species of Varying Degrees of Divergence

Parallel evolution is the acquisition of identical adaptive traits in independently evolving populations. Understanding whether the genetic changes underlying adaptation to a common selective environment are parallel within and between species is interesting because it sheds light on the degree of evolutionary constraints. If parallel evolution is perfect, then the implication is that forces such as functional constraints, epistasis, and pleiotropy play an important role in shaping the outcomes of adaptive evolution. In addition, population genetic theory predicts that the probability of parallel evolution will decline with an increase in the number of adaptive solutions—if a single adaptive solution exists, then parallel evolution will be observed among highly divergent species. For this reason, it is predicted that close relatives—which likely overlap more in the details of their adaptive solutions—will show more parallel evolution. By adapting three related bacteriophage species to a novel environment we find (1) a high rate of parallel genetic evolution at orthologous nucleotide and amino acid residues within species, (2) parallel beneficial mutations do not occur in a common order in which they fix or appear in an evolving population, (3) low rates of parallel evolution and convergent evolution between species, and (4) the probability of parallel and convergent evolution between species is strongly effected by divergence.     

The Properties of Adaptive Walks in Evolving Populations of Fungus

The rarity of beneficial mutations has frustrated efforts to develop a quantitative theory of adaptation. Recent models of adaptive walks, the sequential substitution of beneficial mutations by selection, make two compelling predictions: adaptive walks should be short, and fitness increases should become exponentially smaller as successive mutations fix. We estimated the number and fitness effects of beneficial mutations in each of 118 replicate lineages of Aspergillus nidulans evolving for approximately 800 generations at two population sizes using a novel maximum likelihood framework, the results of which were confirmed experimentally using sexual crosses. We find that adaptive walks do indeed tend to be short, and fitness increases become smaller as successive mutations fix. Moreover, we show that these patterns are associated with a decreasing supply of beneficial mutations as the population adapts. We also provide empirical distributions of fitness effects among mutations fixed at each step. Our results provide a first glimpse into the properties of multiple steps in an adaptive walk in asexual populations and lend empirical support to models of adaptation involving selection towards a single optimum phenotype. In practical terms, our results suggest that the bulk of adaptation is likely to be accomplished within the first few steps.     

Profiles of adaptation in two similar viruses.

The related bacteriophages phiX174 and G4 were adapted to the inhibitory temperature of 44 degrees and monitored for nucleotide changes throughout the genome. Phage were evolved by serial transfer at low multiplicity of infection on rapidly dividing bacteria to select genotypes with the fastest rates of reproduction. Both phage showed overall greater fitness effects per substitution during the early stages of adaptation. The fitness of phiX174 improved from -0.7 to 5.6 doublings of phage concentration per generation. Five missense mutations were observed. The earliest two mutations accounted for 85% of the ultimate fitness gain. In contrast, G4 required adaptation to the intermediate temperature of 41.5 degrees before it could be maintained at 44 degrees. Its fitness at 44 degrees increased from -2.7 to 3.2, nearly the same net gain as in phiX174, but with three times the opportunity for adaptation. Seventeen mutations were observed in G4: 14 missense, 2 silent, and 1 intergenic. The first 3 missense substitutions accounted for over half the ultimate fitness increase. Although the expected pattern of periodic selective sweeps was the most common one for both phage, some mutations were lost after becoming frequent, and long-term polymorphism was observed. This study provides the greatest detail yet in combining fitness profiles with the underlying pattern of genetic changes, and the results support recent theories on the range of fitness effects of substitutions fixed during adaptation.     

SHIFTING FITNESS LANDSCAPES IN RESPONSE TO ALTERED ENVIRONMENTS

The role of adaptation in molecular evolution has been contentious for decades. Here, we shed light on the adaptive potential in Saccharomyces cerevisiae by presenting systematic fitness measurements for all possible point mutations in a region of Hsp90 under four environmental conditions. Under elevated salinity, we observe numerous beneficial mutations with growth advantages up to 7% relative to the wild type. All of these beneficial mutations were observed to be associated with high costs of adaptation. We thus demonstrate that an essential protein can harbor adaptive potential upon an environmental challenge, and report a remarkable fit of the data to a version of Fisher's geometric model that focuses on the fitness trade‐offs between mutations in different environments.     

Adaptive molecular evolution for 13,000 phage generations: a possible arms race

Bacteriophage phiX174 was evolved on a continuous supply of sensitive hosts for 180 days ( approximately 13,000 phage generations). The average rate of nucleotide substitution was nearly 0.2% (11 substitutions)/20 days, and, surprisingly, substitutions accumulated in a clock-like manner throughout the study, except for a low rate during the first 20 days. Rates of silent and missense substitutions varied over time and among genes. Approximately 40% of the 71 missense changes and 25% of the 58 silent changes have been observed in previous adaptations; the rate of parallel substitution was highest in the early phase of the evolution, but 7% of the later changes had evolved in previous studies of much shorter duration. Several lines of evidence suggest that most of the changes were adaptive, even many of the silent substitutions. The sustained, high rate of adaptive evolution for 180 days defies a model of adaptation to a constant environment. We instead suggest that continuing molecular evolution reflects a potentially indefinite arms race, stemming from high levels of co-infection and the resulting conflict among genomes competing within the same cell.     

Mutational neighbourhood and mutation supply rate constrain adaptation in Pseudomonas aeruginosa

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

FISHER'S GEOMETRIC MODEL WITH A MOVING OPTIMUM

Fisher's geometric model has been widely used to study the effects of pleiotropy and organismic complexity on phenotypic adaptation. Here, we study a version of Fisher's model in which a population adapts to a gradually moving optimum. Key parameters are the rate of environmental change, the dimensionality of phenotype space, and the patterns of mutational and selectional correlations. We focus on the distribution of adaptive substitutions, that is, the multivariate distribution of the phenotypic effects of fixed beneficial mutations. Our main results are based on an “adaptive‐walk approximation,” which is checked against individual‐based simulations. We find that (1) the distribution of adaptive substitutions is strongly affected by the ecological dynamics and largely depends on a single composite parameter γ, which scales the rate of environmental change by the “adaptive potential” of the population; (2) the distribution of adaptive substitution reflects the shape of the fitness landscape if the environment changes slowly, whereas it mirrors the distribution of new mutations if the environment changes fast; (3) in contrast to classical models of adaptation assuming a constant optimum, with a moving optimum, more complex organisms evolve via larger adaptive steps.     

Fitness evolution and the rise of mutator alleles in experimental Escherichia coli populations

We studied the evolution of high mutation rates and the evolution of fitness in three experimental populations of Escherichia coli adapting to a glucose-limited environment. We identified the mutations responsible for the high mutation rates and show that their rate of substitution in all three populations was too rapid to be accounted for simply by genetic drift. In two of the populations, large gains in fitness relative to the ancestor occurred as the mutator alleles rose to fixation, strongly supporting the conclusion that mutator alleles fixed by hitchhiking with beneficial mutations at other loci. In one population, no significant gain in fitness relative to the ancestor occurred in the population as a whole while the mutator allele rose to fixation, but a substantial and significant gain in fitness occurred in the mutator subpopulation as the mutator neared fixation. The spread of the mutator allele from rarity to fixation took >1000 generations in each population. We show that simultaneous adaptive gains in both the mutator and wild-type subpopulations (clonal interference) retarded the mutator fixation in at least one of the populations. We found little evidence that the evolution of high mutation rates accelerated adaptation in these populations.     

Models of experimental evolution: the role of genetic chance and selective necessity

We present a theoretical framework within which to analyze the results of experimental evolution. Rapidly evolving organisms such as viruses, bacteria, and protozoa can be induced to adapt to laboratory conditions on very short human time scales. Artificial adaptive radiation is characterized by a list of common observations; we offer a framework in which many of these repeated questions and patterns can be characterized analytically. We allow for stochasticity by including rare mutations and bottleneck effects, demonstrating how these increase variability in the evolutionary trajectory. When the product Np, the population size times the per locus error rate, is small, the rate of evolution is limited by the chance occurrence of beneficial mutations; when Np is large and selective pressure is strong, the rate-limiting step is the waiting time while existing beneficial mutations sweep through the population. We derive the rate of divergence (substitution rate) and rate of fitness increase for the case when Np is large and illustrate our approach with an application to an experimental data set. A minimal assumption of independent additive fitness contributions provides a good fit to the experimental evolution of the bacteriophage phiX174.     

Lack of Evidence for Sign Epistasis Between Beneficial Mutations in an RNA Bacteriophage

In previous work (Betancourt, Genetics 181:1535, 2009), I propagated three large laboratory populations of an RNA phage (MS2) as they adapted to a controlled laboratory environment. These populations were large enough so that evolution might be expected to be mostly repeatable, but they nevertheless fixed different suites of mutations over the course of the experiment. Here, I investigate one possible explanation for these results: epistasis, in which the effect of a mutation depends on its genetic background, may have prevented populations with different initial substitutions from fixing the same set of subsequent mutations. I show that two mutations that previously occurred in different genetic backgrounds are beneficial on either background. This result suggests that sign epistasis-in which a mutation is beneficial on one background, but deleterious on another-is not the cause of different evolutionary trajectories observed in the Betancourt (2009) experiment. However, they can be explained by either magnitude epistasis-in which mutations have stronger or weaker beneficial effects depending on the background-or by the simultaneous fixation of multiple beneficial mutations. Surprisingly, the large populations of the previous experiment showed less parallel evolution than the small populations of this experiment, which lends support to the fixation of multiple beneficial mutations contributing to the patterns seen in both experiments.     

The population genetics of adaptation: the adaptation of DNA sequences

I describe several patterns characterizing the genetics of adaptation at the DNA level. Following Gillespie (1983, 1984, 1991), I consider a population presently fixed for the ith best allele at a locus and study the sequential substitution of favorable mutations that results in fixation of the fittest DNA sequence locally available. Given a wild type sequence that is less than optimal, I derive the fitness rank of the next allele typically fixed by natural selection as well as the mean and variance of the jump in fitness that results when natural selection drives a substitution. Looking over the whole series of substitutions required to reach the best allele, I show that the mean fitness jumps occurring throughout an adaptive walk are constrained to a twofold window of values, assuming only that adaptation begins from a reasonably fit allele. I also show that the first substitution and the substitution of largest effect account for a large share of the total fitness increase during adaptation. I further show that the distribution of selection coefficients fixed throughout such an adaptive walk is exponential (ignoring mutations of small effect), a finding reminiscent of that seen in Fisher's geometric model of adaptation. Last, I show that adaptation by natural selection behaves in several respects as the average of two idealized forms of adaptation, perfect and random.     

Neural networks enable efficient and accurate simulation-based inference of evolutionary parameters from adaptation dynamics

The rate of adaptive evolution depends on the rate at which beneficial mutations are introduced into a population and the fitness effects of those mutations. The rate of beneficial mutations and their expected fitness effects is often difficult to empirically quantify. As these 2 parameters determine the pace of evolutionary change in a population, the dynamics of adaptive evolution may enable inference of their values. Copy number variants (CNVs) are a pervasive source of heritable variation that can facilitate rapid adaptive evolution. Previously, we developed a locus-specific fluorescent CNV reporter to quantify CNV dynamics in evolving populations maintained in nutrient-limiting conditions using chemostats. Here, we use CNV adaptation dynamics to estimate the rate at which beneficial CNVs are introduced through de novo mutation and their fitness effects using simulation-based likelihood–free inference approaches. We tested the suitability of 2 evolutionary models: a standard Wright–Fisher model and a chemostat model. We evaluated 2 likelihood-free inference algorithms: the well-established Approximate Bayesian Computation with Sequential Monte Carlo (ABC-SMC) algorithm, and the recently developed Neural Posterior Estimation (NPE) algorithm, which applies an artificial neural network to directly estimate the posterior distribution. By systematically evaluating the suitability of different inference methods and models, we show that NPE has several advantages over ABC-SMC and that a Wright–Fisher evolutionary model suffices in most cases. Using our validated inference framework, we estimate the CNV formation rate at the GAP1 locus in the yeast Saccharomyces cerevisiae to be 10^−4.7 to 10⁻⁴ CNVs per cell division and a fitness coefficient of 0.04 to 0.1 per generation for GAP1 CNVs in glutamine-limited chemostats. We experimentally validated our inference-based estimates using 2 distinct experimental methods—barcode lineage tracking and pairwise fitness assays—which provide independent confirmation of the accuracy of our approach. Our results are consistent with a beneficial CNV supply rate that is 10-fold greater than the estimated rates of beneficial single-nucleotide mutations, explaining the outsized importance of CNVs in rapid adaptive evolution. More generally, our study demonstrates the utility of novel neural network–based likelihood–free inference methods for inferring the rates and effects of evolutionary processes from empirical data with possible applications ranging from tumor to viral evolution.

This study shows that simulation-based inference of evolutionary dynamics using neural networks can yield parameter values for fitness and mutation rate that are difficult to determine experimentally, including those of copy number variants (CNVs) during experimental adaptive evolution of yeast.     

The Fitness Effects of Random Mutations in Single-Stranded DNA and RNA Bacteriophages

Mutational fitness effects can be measured with relatively high accuracy in viruses due to their small genome size, which facilitates full-length sequencing and genetic manipulation. Previous work has shown that animal and plant RNA viruses are very sensitive to mutation. Here, we characterize mutational fitness effects in single-stranded (ss) DNA and ssRNA bacterial viruses. First, we performed a mutation-accumulation experiment in which we subjected three ssDNA (ΦX174, G4, F1) and three ssRNA phages (Qβ, MS2, and SP) to plaque-to-plaque transfers and chemical mutagenesis. Genome sequencing and growth assays indicated that the average fitness effect of the accumulated mutations was similar in the two groups. Second, we used site-directed mutagenesis to obtain 45 clones of ΦX174 and 42 clones of Qβ carrying random single-nucleotide substitutions and assayed them for fitness. In ΦX174, 20% of such mutations were lethal, whereas viable ones reduced fitness by 13% on average. In Qβ, these figures were 29% and 10%, respectively. It seems therefore that high mutational sensitivity is a general property of viruses with small genomes, including those infecting animals, plants, and bacteria. Mutational fitness effects are important for understanding processes of fitness decline, but also of neutral evolution and adaptation. As such, these findings can contribute to explain the evolution of ssDNA and ssRNA viruses.