On the evolution of mutation in changing environments: recombination and phenotypic switching

Genetic diversity within a tree and alternative indexes for different evolutionary effects

Trees, living for centuries, accumulate somatic mutations in their growing trunks and branches, causing genetic divergence within a single tree. Stem cell lineages in a shoot apical meristem accumulate mutations independently and diverge from each other. In plants, somatic mutations can alter the genetic composition of reproductive organs and gametes, impacting future generations. To evaluate the genetic variation among a tree's reproductive organs, we consider three indexes: mean pairwise phylogenetic distance (), phylogenetic diversity (; sum of branch lengths in molecular phylogeny) and parent-offspring phylogenetic distance (). The tissue architecture of trees facilitated the accumulation of somatic mutations, which have various evolutionary effects, including enhancing fitness under strong sib competition and intense host-pathogen interactions, efficiently eliminating deleterious mutations through epistasis and increasing genetic variance in the population. Choosing appropriate indexes for the genetic diversity of somatic mutations depends on the specific aspect of evolutionary influence being assessed.

Evolutionarily stable strategy analysis and its links to demography and genetics through invasion fitness

Evolutionarily stable strategy (ESS) analysis pioneered by Maynard Smith and Price took off in part because it often does not require explicit assumptions about the genetics and demography of a population in contrast to population genetic models. Though this simplicity is useful, it obscures the degree to which ESS analysis applies to populations with more realistic genetics and demography: for example, how does ESS analysis handle complexities such as kin selection, group selection and variable environments when phenotypes are affected by multiple genes? In this paper, I review the history of the ESS concept and show how early uncertainty about the method lead to important mathematical theory linking ESS analysis to general population genetic models. I use this theory to emphasize the link between ESS analysis and the concept of invasion fitness. I give examples of how invasion fitness can measure kin selection, group selection and the evolution of linked modifier genes in response to variable environments. The ESSs in these examples depend crucially on demographic and genetic parameters, which highlights how ESS analysis will continue to be an important tool in understanding evolutionary patterns as new models address the increasing abundance of genetic and long-term demographic data in natural populations. This article is part of the theme issue 'Half a century of evolutionary games: a synthesis of theory, application and future directions'.

The Extent of Antimicrobial Resistance Due to Efflux Pump Regulation

A key mechanism driving antimicrobial resistance (AMR) stems from the ability of bacteria to up-regulate efflux pumps upon exposure to drugs. The resistance gained by this up-regulation is pliable because of the tight regulation of efflux pump levels. This leads to temporary enhancement in survivability of bacteria due to higher efflux pump levels in the presence of antibiotics, which can be reversed when the cells are no longer exposed to the drug. Knowledge of the extent of resistance thus gained would inform intervention strategies aimed at mitigating AMR. Here, we combine mathematical modeling and experiments to quantify the maximum extent of resistance that efflux pump up-regulation can confer via phenotypic induction in the presence of drugs and genotypic abrogation of regulation. Our model describes the dynamics of drug transport in and out of cells coupled with the associated regulation of efflux pump levels and predicts the increase in the minimum inhibitory concentration (MIC) of drugs due to such regulation. To test the model, we measured the uptake and efflux as well as the MIC of the compound ethidium bromide (EtBr), a substrate of the efflux pump LfrA, in wild-type Mycobacterium smegmatis mc²155, as well as in two laboratory-generated strains. Our model captured the observed EtBr levels and MIC fold-changes quantitatively. Further, the model identified key parameters associated with the resulting resistance, variations in which could underlie the extent to which such resistance arises across different drug-bacteria combinations, potentially offering tunable handles to optimize interventions aimed at minimizing AMR.

Scales of Cancer Evolution: Selfish Genome or Cooperating Cells?

Simple Summary

Cancer continuously evolves its ability to survive in time-varying microenvironment, which results, regarding the therapeutic context, in its therapeutic resistance. As it is accepted that the development of resistance is the direct consequence of intratumour heterogeneity, its evolutionary etiology is intensively studied. Models of carinogenesis are often assessed accordingly to how well they fit into the evolutionary scenario. In the paper, the relevant observations and concepts in cancer research, such as intratumour heterogeneity, cell plasticity, and Markov cell state dynamics, are reviewed and integrated into an evolutionary model. The possibility that the interaction between cancer cells can be interpreted as cooperation is proposed.

Abstract

The exploitation of the evolutionary modus operandi of cancer to steer its progression towards drug sensitive cancer cells is a challenging research topic. Integrating evolutionary principles into cancer therapy requires properly identified selection level, the relevant timescale, and the respective fitness of the principal selection unit on that timescale. Interpretation of some features of cancer progression, such as increased heterogeneity of isogenic cancer cells, is difficult from the most straightforward evolutionary view with the cancer cell as the principal selection unit. In the paper, the relation between the two levels of intratumour heterogeneity, genetic, due to genetic instability, and non-genetic, due to phenotypic plasticity, is reviewed and the evolutionary role of the latter is outlined. In analogy to the evolutionary optimization in a changing environment, the cell state dynamics in cancer clones are interpreted as the risk diversifying strategy bet hedging, optimizing the balance between the exploitation and exploration of the cell state space.

Population diversification in the frog Mantidactylus bellyi on an isolated massif in northern Madagascar based on genetic, morphological, bioacoustic and ecological evidence

In the processes that give rise to new species, changes first occur at the population level. But with the continuous nature of the divergence process, change in biological properties delimiting the shift from “individuals of divergent populations” towards “individuals of distinct species”, as well as abiotic factors driving the change, remain largely ambivalent. Here we study diversification processes at the population level in a semi-aquatic frog, Mantidactylus (Brygoomantis) bellyi, across the diverse vegetation types of Montagne d’Ambre National Park (MANP), Madagascar. Genetic diversity was assessed with seven newly developed microsatellite markers as well as mitochondrial DNA sequences and concordance with patterns of ecological, morphological, and bioacoustic divergence evaluated. We found M. bellyi lacking mitochondrial differentiation within MANP, while microsatellite datasets partitioned them into three highly differentiated, geographically separated subpopulations (with indications for up to five subpopulations). The molecular grouping–primarily clustering individuals by geographic proximity–was coincident with differences in mean depth and width of waters, suggesting a possible role of fluvial characteristics in genetic exchange in this stream-breeding species. Genetic clustering not consistent with differences in call properties, except for dominant call frequencies under the two-subpopulations model. Morphological divergence was mostly consistent with the genetic clustering; subpopulations strongly differed by their snout-vent length, with individuals from high-elevation subpopulations smaller than those from populations below 1000 m above sea level. These results exemplify how mountains and environmental conditions might primarily shape genetic and morphological divergence in frog populations, without strongly affecting their calls.

Stable maintenance of hidden switches as a strategy to increase the gene expression stability

In response to severe genetic and environmental perturbations, wild-type organisms can express hidden alternative phenotypes adaptive to such adverse conditions. While our theoretical understanding of the population-level fitness advantage and evolution of phenotypic switching under variable environments has grown, the mechanism by which these organisms maintain phenotypic switching capabilities under static environments remains to be elucidated. Here, using computational simulations, we analyzed the evolution of gene circuits under natural selection and found that different strategies evolved to increase the gene expression stability near the optimum level. In a population comprising bistable individuals, a strategy of maintaining bistability and raising the potential barrier separating the bistable regimes was consistently taken. Our results serve as evidence that hidden bistable switches can be stably maintained during environmental stasis-an essential property enabling the timely release of adaptive alternatives with small genetic changes in the event of substantial perturbations.

Evolution of transmission modifiers under frequency-dependent selection and transmission in constant or fluctuating environments

Although the Reduction Principle for rates of mutation, migration, and recombination has been proved for large populations under constant selection, the fate of modifiers of these evolutionary forces under frequency-dependent or fluctuating selection is, in general, less well understood. Here we study modifiers of transmission, which include modifiers of mutation and oblique cultural transmission, under frequency-dependent and cyclically fluctuating selection, and develop models for which the Reduction Principle fails. We show that whether increased rates of transmission can evolve from an equilibrium at which there is zero transmission (for example, no mutation) depends on the number of alleles among which transmission is occurring. In addition, properties of the null-transmission state are clarified.

Epigenetic switching as a strategy for quick adaptation while attenuating biochemical noise

Epigenetic switches are bistable, molecular systems built from self-reinforcing feedback loops that can spontaneously switch between heritable phenotypes in the absence of DNA mutation. It has been hypothesized that epigenetic switches first evolved as a mechanism of bet-hedging and adaptation, but the evolutionary trajectories and conditions by which an epigenetic switch can outcompete adaptation through genetic mutation remain unknown. Here, we used computer simulations to evolve a mechanistic, biophysical model of a self-activating genetic circuit, which can both adapt genetically through mutation and exhibit epigenetic switching. We evolved these genetic circuits under a fluctuating environment that alternatively selected for low and high protein expression levels. In all tested conditions, the population first evolved by genetic mutation towards a region of genotypes where genetic adaptation can occur faster after each environmental transition. Once in this region, the self-activating genetic circuit can exhibit epigenetic switching, which starts competing with genetic adaptation. We show a trade-off between either minimizing the adaptation time or increasing the robustness of the phenotype to biochemical noise. Epigenetic switching was superior in a fast fluctuating environment because it adapted faster than genetic mutation after an environmental transition, while still attenuating the effect of biochemical noise on the phenotype. Conversely, genetic adaptation was favored in a slowly fluctuating environment because it maximized the phenotypic robustness to biochemical noise during the constant environment between transitions, even if this resulted in slower adaptation. This simple trade-off predicts the conditions and trajectories under which an epigenetic switch evolved to outcompete genetic adaptation, shedding light on possible mechanisms by which bet-hedging strategies might emerge and persist in natural populations.

Epigenetic switches regulate cell fate decisions during development in multicellular organisms, but their origin predates multicellularity because they are found in viruses, bacteria, and unicellular eukaryotes. It has been suggested that epigenetic switches first evolved as a mechanism of bet-hedging and adaptation to fluctuating environments. To discern the evolutionary pressures that select for epigenetic switches, we used computer simulations to evolve a mechanistic, biophysical model of a self-activating genetic circuit, which can both adapt genetically and exhibit epigenetic switching. Unlike laboratory evolution experiments, this in silico experiment was run many times over a range of evolutionary parameters (population size, selection pressure, mutation step-size, fluctuation frequency) and different model assumptions to uncover statistical regularities in the evolutionary trajectories. Using this computational approach, we could elucidate simple principles that predict the conditions that favor adaptation by epigenetic switching over genetic mutation in a fluctuating environment.

(In)exhaustible Suppliers for Evolution? Epistatic Selection Tunes the Adaptive Potential of Nongenetic Inheritance

Nongenetic inheritance media-from methyl-accepting cytosines to culture-tend to mutate more frequently than DNA sequences. Whether this makes them inexhaustible suppliers for adaptive evolution will depend on the effect of nongenetic mutations (hereafter, epimutations) on fitness-related traits. Here we investigate how these effects might themselves evolve, specifically whether natural selection may set boundaries to the adaptive potential of nongenetic inheritance media because of their higher mutability. In our model, the genetic and epigenetic contributions to a nonneutral phenotype are controlled by an epistatic modifier locus, which evolves under the combined effects of drift and selection. We show that a pure genetic control evolves when the environment is stable-provided that the population is large-such that the phenotype becomes robust to frequent epimutations. When the environment fluctuates, however, selection on the modifier locus also fluctuates and can overall produce a large nongenetic contribution to the phenotype, especially when the epimutation rate matches the rate of environmental variation. We further show that selection on the modifier locus is generally insensitive to recombination, meaning it is mostly direct, that is, not relying on subsequent effects in future generations. These results suggest that unstable inheritance media might significantly contribute to fitness variation of traits subject to highly variable selective pressures but little to traits responding to scarcely variable aspects of the environment. More generally, our study demonstrates that the rate of mutation and the adaptive potential of any inheritance media should not be seen as independent properties.

Evolution of vertical and oblique transmission under fluctuating selection

The evolution and maintenance of social learning, in competition with individual learning, under fluctuating selection have been well-studied in the theory of cultural evolution. Here, we study competition between vertical and oblique cultural transmission of a dichotomous phenotype under constant, periodically cycling, and randomly fluctuating selection. Conditions are derived for the existence of a stable polymorphism in a periodically cycling selection regime. Under such a selection regime, the fate of a genetic modifier of the rate of vertical transmission depends on the length of the cycle and the strength of selection. In general, the evolutionarily stable rate of vertical transmission differs markedly from the rate that maximizes the geometric mean fitness of the population. The evolution of rules of transmission has dramatically different dynamics from the more frequently studied modifiers of recombination, mutation, or migration.

Unified reduction principle for the evolution of mutation, migration, and recombination

Modifier-gene models for the evolution of genetic information transmission between generations of organisms exhibit the reduction principle: Selection favors reduction in the rate of variation production in populations near equilibrium under a balance of constant viability selection and variation production. Whereas this outcome has been proven for a variety of genetic models, it has not been proven in general for multiallelic genetic models of mutation, migration, and recombination modification with arbitrary linkage between the modifier and major genes under viability selection. We show that the reduction principle holds for all of these cases by developing a unifying mathematical framework that characterizes all of these evolutionary models.

Evolution of reduced mutation under frequency-dependent selection

Most models for the evolution of mutation under frequency-dependent selection involve some form of host-parasite interaction. These generally involve cyclic dynamics under which mutation may increase. Here we show that the reduction principle for the evolution of mutation, which is generally true for frequency-independent selection, also holds under frequency-dependent selection on haploids and diploids that does not involve cyclic dynamics.

Norm statement considered harmful: comment on 'evolution of unconditional dispersal in periodic environments'

The mathematical symbol for the norm, which is heavily overloaded with multiple definitions that have both universal and specific properties, lends itself to confusion. This is manifest in the proof of an important theorem for population dynamics by Schreiber and Li on how dispersal increases population growth in a periodic environment. Here the theorem is placed in context, the proof is clarified, and the confusing but inconsequential errors corrected.

The role of migration in the evolution of phenotypic switching

Stochastic switching is an example of phenotypic bet hedging, where an individual can switch between different phenotypic states in a fluctuating environment. Although the evolution of stochastic switching has been studied when the environment varies temporally, there has been little theoretical work on the evolution of phenotypic switching under both spatially and temporally fluctuating selection pressures. Here, we explore the interaction of temporal and spatial change in determining the evolutionary dynamics of phenotypic switching. We find that spatial variation in selection is important; when selection pressures are similar across space, migration can decrease the rate of switching, but when selection pressures differ spatially, increasing migration between demes can facilitate the evolution of higher rates of switching. These results may help explain the diverse array of non-genetic contributions to phenotypic variability and phenotypic inheritance observed in both wild and experimental populations.

Metabolism at evolutionary optimal States

Metabolism is generally required for cellular maintenance and for the generation of offspring under conditions that support growth. The rates, yields (efficiencies), adaptation time and robustness of metabolism are therefore key determinants of cellular fitness. For biotechnological applications and our understanding of the evolution of metabolism, it is necessary to figure out how the functional system properties of metabolism can be optimized, via adjustments of the kinetics and expression of enzymes, and by rewiring metabolism. The trade-offs that can occur during such optimizations then indicate fundamental limits to evolutionary innovations and bioengineering. In this paper, we review several theoretical and experimental findings about mechanisms for metabolic optimization.

Evolution in changing environments: modifiers of mutation, recombination, and migration

The production and maintenance of genetic and phenotypic diversity under temporally fluctuating selection and the signatures of environmental changes in the patterns of this variation have been important areas of focus in population genetics. On one hand, periods of constant selection pull the genetic makeup of populations toward local fitness optima. On the other, to cope with changes in the selection regime, populations may evolve mechanisms that create a diversity of genotypes. By tuning the rates at which variability is produced--such as the rates of recombination, mutation, or migration--populations may increase their long-term adaptability. Here we use theoretical models to gain insight into how the rates of these three evolutionary forces are shaped by fluctuating selection. We compare and contrast the evolution of recombination, mutation, and migration under similar patterns of environmental change and show that these three sources of phenotypic variation are surprisingly similar in their response to changing selection. We show that the shape, size, variance, and asymmetry of environmental fluctuation have different but predictable effects on evolutionary dynamics.

The evolution of phenotypic switching in subdivided populations

Stochastic switching is an example of phenotypic bet hedging, where offspring can express a phenotype different from that of their parents. Phenotypic switching is well documented in viruses, yeast, and bacteria and has been extensively studied when the selection pressures vary through time. However, there has been little work on the evolution of phenotypic switching under both spatially and temporally fluctuating selection pressures. Here we use a population genetic model to explore the interaction of temporal and spatial variation in determining the evolutionary dynamics of phenotypic switching. We find that the stable switching rate is mainly determined by the rate of environmental change and the migration rate. This stable rate is also a decreasing function of the recombination rate, although this is a weaker effect than those of either the period of environmental change or the migration rate. This study highlights the interplay of spatial and temporal environmental variability, offering new insights into how migration can influence the evolution of phenotypic switching rates, mutation rates, or other sources of phenotypic variation.

Genetic variation and the evolution of epigenetic regulation

Epigenetic variation has been observed in a range of organisms, leading to questions of the adaptive significance of this variation. In this study, we present a model to explore the ecological and genetic conditions that select for epigenetic regulation. We find that the rate of temporal environmental change is a key factor controlling the features of this evolution. When the environment fluctuates rapidly between states with different phenotypic optima, epigenetic regulation may evolve but we expect to observe low transgenerational inheritance of epigenetic states, whereas when this fluctuation occurs over longer time scales, regulation may evolve to generate epigenetic states that are inherited faithfully for many generations. In all cases, the underlying genetic variation at the epigenetically regulated locus is a crucial factor determining the range of conditions that allow for evolution of epigenetic mechanisms.

Survivability is more fundamental than evolvability

For a lineage to survive over long time periods, it must sometimes change. This has given rise to the term evolvability, meaning the tendency to produce adaptive variation. One lineage may be superior to another in terms of its current standing variation, or it may tend to produce more adaptive variation. However, evolutionary outcomes depend on more than standing variation and produced adaptive variation: deleterious variation also matters. Evolvability, as most commonly interpreted, is not predictive of evolutionary outcomes. Here, we define a predictive measure of the evolutionary success of a lineage that we call the k-survivability, defined as the probability that the lineage avoids extinction for k generations. We estimate the k-survivability using multiple experimental replicates. Because we measure evolutionary outcomes, the initial standing variation, the full spectrum of generated variation, and the heritability of that variation are all incorporated. Survivability also accounts for the decreased joint likelihood of extinction of sub-lineages when they 1) disperse in space, or 2) diversify in lifestyle. We illustrate measurement of survivability with in silico models, and suggest that it may also be measured in vivo using multiple longitudinal replicates. The k-survivability is a metric that enables the quantitative study of, for example, the evolution of 1) mutation rates, 2) dispersal mechanisms, 3) the genotype-phenotype map, and 4) sexual reproduction, in temporally and spatially fluctuating environments. Although these disparate phenomena evolve by well-understood microevolutionary rules, they are also subject to the macroevolutionary constraint of long-term survivability.

An equilibrium for phenotypic variance in fluctuating environments owing to epigenetics

The connection between random environments and genetic and phenotypic variability has been a major focus in the population genetic literature. By providing differential access to the underlying genetic information, epigenetic variation could play an important role in the interaction between environmental and phenotypic variation. Using simulation, we model epigenetic plasticity during development by investigating the dynamics of genetic regulators of the epigenetic machinery that change the variance of the phenotype, while having no effect on the phenotype's mean. Previous studies have found that increased phenotypic variance is selected for if the environment is fluctuating. Here, we find that when a variance-increasing allele achieves a sufficiently high frequency, it can be out-competed by a variance-reducing allele, with the consequence that the population evolves to an equilibrium phenotypic variability. This equilibrium is shown to be robust to different initial conditions, but to depend heavily on parameters of the model, such as the mutation rate, the fitness landscape and the nature of the environmental fluctuation. Indeed, if there is no mutation at the genes controlling the variance of the phenotype, reduction of this variance is favoured.

Bistability in feedback circuits as a byproduct of evolution of evolvability

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

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

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

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

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

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

Environment-sensitive epigenetics and the heritability of complex diseases

Genome-wide association studies have thus far failed to explain the observed heritability of complex human diseases. This is referred to as the “missing heritability” problem. However, these analyses have usually neglected to consider a role for epigenetic variation, which has been associated with many human diseases. We extend models of epigenetic inheritance to investigate whether environment-sensitive epigenetic modifications of DNA might explain observed patterns of familial aggregation. We find that variation in epigenetic state and environmental state can result in highly heritable phenotypes through a combination of epigenetic and environmental inheritance. These two inheritance processes together can produce familial covariances significantly higher than those predicted by models of purely epigenetic inheritance and similar to those expected from genetic effects. The results suggest that epigenetic variation, inherited both directly and through shared environmental effects, may make a key contribution to the missing heritability.