Long-term adaptation of epistatic genetic networks

Gene networks are likely to govern most traits in nature. Mutations at these genes often show functional epistatic interactions that lead to complex genetic architectures and variable fitness effects in different genetic backgrounds. Understanding how epistatic genetic systems evolve in nature remains one of the great challenges in evolutionary biology. Here we combine an analytical framework with individual-based simulations to generate novel predictions about long-term adaptation of epistatic networks. We find that relative to traits governed by independently evolving genes, adaptation with epistatic gene networks is often characterized by longer waiting times to selective sweeps, lower standing genetic variation, and larger fitness effects of adaptive mutations. This may cause epistatic networks to either adapt more slowly or more quickly relative to a nonepistatic system. Interestingly, epistatic networks may adapt faster even when epistatic effects of mutations are on average deleterious. Further, we study the evolution of epistatic properties of adaptive mutations in gene networks. Our results show that adaptive mutations with small fitness effects typically evolve positive synergistic interactions, whereas adaptive mutations with large fitness effects evolve positive synergistic and negative antagonistic interactions at approximately equal frequencies. These results provide testable predictions for adaptation of traits governed by epistatic networks and the evolution of epistasis within networks.     

Evolution of mutation rates in bacteria

Evolutionary success of bacteria relies on the constant fine-tuning of their mutation rates, which optimizes their adaptability to constantly changing environmental conditions. When adaptation is limited by the mutation supply rate, under some conditions, natural selection favours increased mutation rates by acting on allelic variation of the genetic systems that control fidelity of DNA replication and repair. Mutator alleles are carried to high frequency through hitchhiking with the adaptive mutations they generate. However, when fitness gain no longer counterbalances the fitness loss due to continuous generation of deleterious mutations, natural selection favours reduction of mutation rates. Selection and counter-selection of high mutation rates depends on many factors: the number of mutations required for adaptation, the strength of mutator alleles, bacterial population size, competition with other strains, migration, and spatial and temporal environmental heterogeneity. Such modulations of mutation rates may also play a role in the evolution of antibiotic resistance.     

Bacterial Adaptation through Loss of Function

The metabolic capabilities and regulatory networks of bacteria have been optimized by evolution in response to selective pressures present in each species'' native ecological niche. In a new environment, however, the same bacteria may grow poorly due to regulatory constraints or biochemical deficiencies. Adaptation to such conditions can proceed through the acquisition of new cellular functionality due to gain of function mutations or via modulation of cellular networks. Using selection experiments on transposon-mutagenized libraries of bacteria, we illustrate that even under conditions of extreme nutrient limitation, substantial adaptation can be achieved solely through loss of function mutations, which rewire the metabolism of the cell without gain of enzymatic or sensory function. A systematic analysis of similar experiments under more than 100 conditions reveals that adaptive loss of function mutations exist for many environmental challenges. Drawing on a wealth of examples from published articles, we detail the range of mechanisms through which loss-of-function mutations can generate such beneficial regulatory changes, without the need for rare, specific mutations to fine-tune enzymatic activities or network connections. The high rate at which loss-of-function mutations occur suggests that null mutations play an underappreciated role in the early stages of adaption of bacterial populations to new environments.     

The genetic architecture of behavioral canalization

Behaviors are components of fitness and contribute to adaptive evolution. Behaviors represent the interactions of an organism with its environment, yet innate behaviors display robustness in the face of environmental change, which we refer to as ‘behavioral canalization’. We hypothesize that positive selection of hub genes of genetic networks stabilizes the genetic architecture for innate behaviors by reducing variation in the expression of interconnected network genes. Robustness of these stabilized networks would be protected from deleterious mutations by purifying selection or suppressing epistasis. We propose that, together with newly emerging favorable mutations, epistatically suppressed mutations can generate a reservoir of cryptic genetic variation that could give rise to decanalization when genetic backgrounds or environmental conditions change to allow behavioral adaptation.     

Evolutionary rescue by compensatory mutations is constrained by genomic and environmental backgrounds

Since deleterious mutations may be rescued by secondary mutations during evolution, compensatory evolution could identify genetic solutions leading to therapeutic targets. Here, we tested this hypothesis and examined whether these solutions would be universal or would need to be adapted to one's genetic and environmental makeups. We performed experimental evolutionary rescue in a yeast disease model for the Wiskott–Aldrich syndrome in two genetic backgrounds and carbon sources. We found that multiple aspects of the evolutionary rescue outcome depend on the genotype, the environment, or a combination thereof. Specifically, the compensatory mutation rate and type, the molecular rescue mechanism, the genetic target, and the associated fitness cost varied across contexts. The course of compensatory evolution is therefore highly contingent on the initial conditions in which the deleterious mutation occurs. In addition, these results reveal biologically favored therapeutic targets for the Wiskott–Aldrich syndrome, including the target of an unrelated clinically approved drug. Our results experimentally illustrate the importance of epistasis and environmental evolutionary constraints that shape the adaptive landscape and evolutionary rate of molecular networks.     

LESS IS MORE: SELECTIVE ADVANTAGES CAN EXPLAIN THE PREVALENT LOSS OF BIOSYNTHETIC GENES IN BACTERIA

Bacteria that have adapted to nutrient‐rich, stable environments are typically characterized by reduced genomes. The loss of biosynthetic genes frequently renders these lineages auxotroph, hinging their survival on an environmental uptake of certain metabolites. The evolutionary forces that drive this genome degradation, however, remain elusive. Our analysis of 949 metabolic networks revealed auxotrophies are likely highly prevalent in both symbiotic and free‐living bacteria. To unravel whether selective advantages can account for the rampant loss of anabolic genes, we systematically determined the fitness consequences that result from deleting conditionally essential biosynthetic genes from the genomes of Escherichia coli and Acinetobacter baylyi in the presence of the focal nutrient. Pairwise competition experiments with each of 20 mutants auxotrophic for different amino acids, vitamins, and nucleobases against the prototrophic wild type unveiled a pronounced, concentration‐dependent growth advantage of around 13% for virtually all mutants tested. Individually deleting different genes from the same biosynthesis pathway entailed gene‐specific fitness consequences and loss of the same biosynthetic genes from the genomes of E. coli and A. baylyi differentially affected the fitness of the resulting auxotrophic mutants. Taken together, our findings suggest adaptive benefits could drive the loss of conditionally essential biosynthetic genes.     

Evolution of a single niche specialist in variable environments

The pattern (space versus time) and scale (relative to the lifetime of individuals) of environmental variation is thought to play a central role in governing the evolution of the ecological niche and the maintenance of genetic variance in fitness. To evaluate this idea, we serially propagated an initially genetically uniform population of the bacterium Pseudomonas fluorescens for a few hundred generations in environments that differed in both the pattern and scale at which two highly contrasted carbon substrates were experienced. We found that, contrary to expectations, populations often evolved into a single niche specialist adapted to the less-productive substrate in variable environments and that the genetic variance in fitness across different components of the environment was not generally higher in variable environments when compared with constant environments. We provide evidence to suggest that our results reflect a novel constraint on niche evolution imposed by the supply of beneficial mutations available to selection in variable environments.     

The distribution of fitness effects in an uncertain world

The distribution of fitness effects (DFE) among new mutations plays a critical role in adaptive evolution and the maintenance of genetic variation. Although fitness landscape models predict several key features of the DFE, most theory to date focuses on predictable environmental conditions, while ignoring stochastic environmental fluctuations that feature prominently in the ecology of many organisms. Here, we derive an extension of Fisher's geometric model that incorporates two common effects of environmental variation: (1) nonadaptive genotype‐by‐environment interactions (G × E), in which the phenotype of a given genotype varies across environmental contexts; and (2) random fluctuation of the fitness optimum, which generates fluctuating selection. We show that both factors cause a mismatch between the DFE within single generations and the distribution of geometric mean fitness effects (averaged over multiple generations) that governs long‐term evolutionary change. Such mismatches permit strong evolutionary constraints—despite an abundance of beneficial fitness variation within single environmental contexts—and to conflicting DFE estimates from direct versus indirect inference methods. Finally, our results suggest an intriguing parallel between the genetics and ecology of evolutionary constraints, with environmental fluctuations and pleiotropy placing qualitatively similar limits on the availability of adaptive genetic variation.     

MULTIDIMENSIONAL ADAPTIVE EVOLUTION OF A FEED‐FORWARD NETWORK AND THE ILLUSION OF COMPENSATION

When multiple substitutions affect a trait in opposing ways, they are often assumed to be compensatory, not only with respect to the trait, but also with respect to fitness. This type of compensatory evolution has been suggested to underlie the evolution of protein structures and interactions, RNA secondary structures, and gene regulatory modules and networks. The possibility for compensatory evolution results from epistasis. Yet if epistasis is widespread, then it is also possible that the opposing substitutions are individually adaptive. I term this possibility an adaptive reversal. Although possible for arbitrary phenotype‐fitness mappings, it has not yet been investigated whether such epistasis is prevalent in a biologically realistic setting. I investigate a particular regulatory circuit, the type I coherent feed‐forward loop, which is ubiquitous in natural systems and is accurately described by a simple mathematical model. I show that such reversals are common during adaptive evolution, can result solely from the topology of the fitness landscape, and can occur even when adaptation follows a modest environmental change and the network was well adapted to the original environment. The possibility of adaptive reversals warrants a systems perspective when interpreting substitution patterns in gene regulatory networks.     

Heterogeneous adaptive trajectories of small populations on complex fitness landscapes

Background

Small populations are thought to be adaptively handicapped, not only because they suffer more from deleterious mutations but also because they have limited access to new beneficial mutations, particularly those conferring large benefits.

Methodology/Principal Findings

Here, we test this widely held conjecture using both simulations and experiments with small and large bacterial populations evolving in either a simple or a complex nutrient environment. Consistent with expectations, we find that small populations are adaptively constrained in the simple environment; however, in the complex environment small populations not only follow more heterogeneous adaptive trajectories, but can also attain higher fitness than the large populations. Large populations are constrained to near deterministic fixation of rare large-benefit mutations. While such determinism speeds adaptation on the smooth adaptive landscape represented by the simple environment, it can limit the ability of large populations from effectively exploring the underlying topography of rugged adaptive landscapes characterized by complex environments.

Conclusions

Our results show that adaptive constraints often faced by small populations can be circumvented during evolution on rugged adaptive landscapes.     

Environmental variation alters the fitness effects of rifampicin resistance mutations in Pseudomonas aeruginosa

The fitness effects of antibiotic resistance mutations in antibiotic‐free conditions play a key role in determining the long‐term maintenance of resistance. Although resistance is usually associated with a cost, the impact of environmental variation on the cost of resistance is poorly understood. Here, we test the impact of heterogeneity in temperature and resource availability on the fitness effects of antibiotic resistance using strains of the pathogenic bacterium Pseudomonas aeruginosa carrying clinically important rifampicin resistance mutations. Although the rank order of fitness was generally maintained across environments, fitness effects relative to the wild type differed significantly. Changes in temperature had a profound impact on the fitness effects of resistance, whereas changes in carbon substrate had only a weak impact. This suggests that environmental heterogeneity may influence whether the costs of resistance are likely to be ameliorated by second‐site compensatory mutations or by reversion to wild‐type rpoB. Our results highlight the need to consider environmental heterogeneity and genotype‐by‐environment interactions for fitness in models of resistance evolution.     

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.     

Adaptive walks toward a moving optimum

We investigate how the dynamics and outcomes of adaptation by natural selection are affected by environmental stability by simulating adaptive walks in response to an environmental change of fixed magnitude but variable speed. Here we consider monomorphic lineages that adapt by the sequential fixation of beneficial mutations. This is modeled by selecting short RNA sequences for folding stability and secondary structure conservation at increasing temperatures. Using short RNA sequences allows us to describe adaptive outcomes in terms of genotype (sequence) and phenotype (secondary structure) and to follow the dynamics of fitness increase. We find that slower rates of environmental change affect the dynamics of adaptive walks by reducing the fitness effect of fixed beneficial mutations, as well as by increasing the range of time in which the substitutions of largest effect are likely to occur. In addition, adaptation to slower rates of environmental change results in fitter endpoints with fewer possible end phenotypes relative to lineages that adapt to a sudden change. This suggests that care should be taken when experiments using sudden environmental changes are used to make predictions about adaptive responses to gradual change.     

Fitness and adaptation in a novel environment: effect of inbreeding, prior environment, and lineage

Abstract. The ability of populations to undergo adaptive evolution depends on the presence of genetic variation for ecologically important traits. The maintenance of genetic variation may be influenced by many variables, particularly long-term effective population size and the strength and form of selection. The roles of these factors are controversial and there is very little information on their impacts for quantitative characters. The aims of this study were to determine the impacts of population size and variable versus constant prior environmental conditions on fitness and the magnitude of response to selection. Outbred and inbred populations of Drosophila melanogaster were maintained under benign, constant stressful, and variably stressful conditions for seven generations, and then forced to adapt to a novel stress for seven generations. Fitness and adaptability were assayed in each replicate population. Our findings are that: (1) populations inbred in a variable environment were more adaptable than those inbred in a constant environment; (2) populations adapted to a prior stressful environment had greater fitness when reared in a novel stress than those less adapted to stress; (3) inbred populations had lower fitness and were less adaptable than the outbred population they were derived from; and (4) strong lineage effects were detectable across environments in the inbred populations.     

Genotype‐by‐environment interactions due to antibiotic resistance and adaptation in Escherichia coli

Mutations that are beneficial in one environment can have different fitness effects in other environments. In the context of antibiotic resistance, the resulting genotype‐by‐environment interactions potentially make selection on resistance unpredictable in heterogeneous environments. Furthermore, resistant bacteria frequently fix additional mutations during evolution in the absence of antibiotics. How do these two types of mutations interact to determine the bacterial phenotype across different environments? To address this, I used Escherichia coli as a model system, measuring the effects of nine different rifampicin resistance mutations on bacterial growth in 31 antibiotic‐free environments. I did this both before and after approximately 200 generations of experimental evolution in antibiotic‐free conditions (LB medium), and did the same for the antibiotic‐sensitive wild type after adaptation to the same environment. The following results were observed: (i) bacteria with and without costly resistance mutations adapted to experimental conditions and reached similar levels of competitive fitness; (ii) rifampicin resistance mutations and adaptation to LB both indirectly altered growth in other environments; and (iii) resistant‐evolved genotypes were more phenotypically different from the ancestor and from each other than resistant‐nonevolved and sensitive‐evolved genotypes. This suggests genotype‐by‐environment interactions generated by antibiotic resistance mutations, observed previously in short‐term experiments, are more pronounced after adaptation to other types of environmental variation, making it difficult to predict long‐term selection on resistance mutations from fitness effects in a single environment.     

How to balance the offspring quality–quantity tradeoff when environmental cues are unreliable

Maternal effects on offspring size can have a strong effect on fitness, as larger offspring often survive better under harsh environmental conditions. Selection should hence favour mothers that find an optimal solution to the offspring size versus number tradeoff. If environmental conditions are variable, there will not be a single optimal offspring size, as predicted in a constant environment, but plastic responses can be favoured. To be able to adjust offspring size in an adaptive manner, mothers have to use environmental cues to predict offspring environmental conditions. Cues can be unreliable, however, particularly in species where individuals occupy different niches at different life stages. Here we model the evolution of plasticity of offspring size when the environmental cues mothers use to predict the conditions experienced by their offspring are not perfectly reliable. Our results show that plastic strategies are likely to be superior to fixed strategies in a stochastically varying environment when the environmental cues are at least moderately reliable, with the threshold depending on plasticity costs and the difference of resources available to mothers. Plasticity is more likely to occur if resource availability is not too different between environments. For any given scenario, plasticity in offspring size is favoured if offspring survival varies greatly between environmental states. Whenever plastic strategies are optimal, the occurring switches performed by mothers between small and large offspring are predicted to be substantial, as small adjustments are unlikely to reap fitness benefits great enough to overcome the costs of plasticity.     

Phenotypic noise and the cost of complexity

Experimental studies demonstrate the existence of phenotypic diversity despite constant genotype and environment. Theoretical models based on a single phenotypic character predict that during an adaptation event, phenotypic noise should be positively selected far from the fitness optimum because it increases the fitness of the genotype, and then be selected against when the population reaches the optimum. It is suggested that because of this fitness gain, phenotypic noise should promote adaptive evolution. However, it is unclear how the selective advantage of phenotypic noise is linked to the rate of evolution, and whether any advantage would hold for more realistic, multidimensional phenotypes. Indeed, complex organisms suffer a cost of complexity, where beneficial mutations become rarer as the number of phenotypic characters increases. Using a quantitative genetics approach, we first show that for a one-dimensional phenotype, phenotypic noise promotes adaptive evolution on plateaus of positive fitness, independently from the direct selective advantage on fitness. Second, we show that for multidimensional phenotypes, phenotypic noise evolves to a low-dimensional configuration, with elevated noise in the direction of the fitness optimum. Such a dimensionality reduction of the phenotypic noise promotes adaptive evolution and numerical simulations show that it reduces the cost of complexity.     

Expected relative fitness and the adaptive topography of fluctuating selection

Wright's adaptive topography describes gene frequency evolution as a maximization of mean fitness in a constant environment. I extended this to a fluctuating environment by unifying theories of stochastic demography and fluctuating selection, assuming small or moderate fluctuations in demographic rates with a stationary distribution, and weak selection among the types. The demography of a large population, composed of haploid genotypes at a single locus or normally distributed phenotypes, can then be approximated as a diffusion process and transformed to produce the dynamics of population size, N, and gene frequency, p, or mean phenotype, . The expected evolution of p or is a product of genetic variability and the gradient of the long-run growth rate of the population, , with respect to p or . This shows that the expected evolution maximizes , the mean Malthusian fitness in the average environment minus half the environmental variance in population growth rate. Thus, as a function of p or represents an adaptive topography that, despite environmental fluctuations, does not change with time. The haploid model is dominated by environmental stochasticity, so the expected maximization is not realized. Different constraints on quantitative genetic variability, and stabilizing selection in the average environment, allow evolution of the mean phenotype to undergo a stochastic maximization of . Although the expected evolution maximizes the long-run growth rate of the population, for a genotype or phenotype the long-run growth rate is not a valid measure of fitness in a fluctuating environment. The haploid and quantitative character models both reveal that the expected relative fitness of a type is its Malthusian fitness in the average environment minus the environmental covariance between its growth rate and that of the population.     

Genomewide Patterns of Substitution in Adaptively Evolving Populations of the RNA Bacteriophage MS2

Experimental evolution of bacteriophage provides a powerful means of studying the genetics of adaptation, as every substitution contributing to adaptation can be identified and characterized. Here, I use experimental evolution of MS2, an RNA bacteriophage, to study its adaptive response to a novel environment. To this end, three lines of MS2 were adapted to rapid growth and lysis at cold temperature for a minimum of 50 phage generations and subjected to whole-genome sequencing. Using this system, I identified adaptive substitutions, monitored changes in frequency of adaptive mutations through the course of the experiment, and measured the effect on phage growth rate of each substitution. All three lines showed a substantial increase in fitness (a two- to threefold increase in growth rate) due to a modest number of substitutions (three to four). The data show some evidence that the substitutions occurring early in the experiment have larger beneficial effects than later ones, in accordance with the expected diminishing returns relationship between the fitness effects of a mutation and its order of substitution. Patterns of molecular evolution seen here—primarily a paucity of hitchhiking mutations—suggest an abundant supply of beneficial mutations in this system. Nevertheless, some beneficial mutations appear to have been lost, possibly due to accumulation of beneficial mutations on other genetic backgrounds, clonal interference, and negatively epistatic interactions with other beneficial mutations.