The evolutionary emergence of stochastic phenotype switching in bacteria

Stochastic phenotype switching - or bet hedging - is a pervasive feature of living systems and common in bacteria that experience fluctuating (unpredictable) environmental conditions. Under such conditions, the capacity to generate variable offspring spreads the risk of being maladapted in the present environment, against offspring likely to have some chance of survival in the future. While a rich subject for theoretical studies, little is known about the selective causes responsible for the evolutionary emergence of stochastic phenotype switching. Here we review recent work - both theoretical and experimental - that sheds light on ecological factors that favour switching types over non-switching types. Of particular relevance is an experiment that provided evidence for an adaptive origin of stochastic phenotype switching by subjecting bacterial populations to a selective regime that mimicked essential features of the host immune response. Central to the emergence of switching types was frequent imposition of 'exclusion rules' and 'population bottlenecks' - two complementary faces of frequency dependent selection. While features of the immune response, exclusion rules and bottlenecks are likely to operate in many natural environments. Together these factors define a set of selective conditions relevant to the evolution of stochastic switching, including antigenic variation and bacterial persistence.     

Evolution in alternating environments with tunable interlandscape correlations

Natural populations are often exposed to temporally varying environments. Evolutionary dynamics in varying environments have been extensively studied, although understanding the effects of varying selection pressures remains challenging. Here, we investigate how cycling between a pair of statistically related fitness landscapes affects the evolved fitness of an asexually reproducing population. We construct pairs of fitness landscapes that share global fitness features but are correlated with one another in a tunable way, resulting in landscape pairs with specific correlations. We find that switching between these landscape pairs, depending on the ruggedness of the landscape and the interlandscape correlation, can either increase or decrease steady‐state fitness relative to evolution in single environments. In addition, we show that switching between rugged landscapes often selects for increased fitness in both landscapes, even in situations where the landscapes themselves are anticorrelated. We demonstrate that positively correlated landscapes often possess a shared maximum in both landscapes that allows the population to step through sub‐optimal local fitness maxima that often trap single landscape evolution trajectories. Finally, we demonstrate that switching between anticorrelated paired landscapes leads to ergodic‐like dynamics where each genotype is populated with nonzero probability, dramatically lowering the steady‐state fitness in comparison to single landscape evolution.     

Viability selection on body size in a non-marine ostracod

One of the most important research topics in evolutionary ecology is body size evolution. Actually, several hypotheses have been proposed to explain the many observed patterns—also known as “rules”—of body size variation in across latitude, temperature, and time. The temperature–size rule (TSR), describes an inverse relationship between body size and temperature. We took advantage of the “natural laboratory” that the crustacean populations at the Chilean altiplano offers, to study the TSR in ostracods. We studied three populations of Limnocythere atacamae that are physically separated by several kilometers, and differ mainly by their permanent thermal regime. We found larger individuals in the hotspring compared to the cold ponds. Also, in the hotspring we found a significant quadratic selection coefficient, suggesting stabilizing selection in this population. The fitness profiles showed stabilizing selection in the hotspring, and positive directional selection in the ponds. Our results suggest the existence of an optimal body size above the population means. This optimal size is apparently attained in the hotspring population. Then, natural selection appears to be promoting a shift in the mean phenotype that, for some reason, is not attained in the cold environments. Genetic slippage and population bottleneck would explain this absence of response to selection.     

The evolution of bet-hedging adaptations to rare scenarios

When faced with a variable environment, organisms may switch between different strategies according to some probabilistic rule. In an infinite population, evolution is expected to favor the rule that maximizes geometric mean fitness. If some environments are encountered only rarely, selection may not be strong enough for optimal switching probabilities to evolve. Here we calculate the evolution of switching probabilities in a finite population by analyzing fixation probabilities of alleles specifying switching rules. We calculate the conditions required for the evolution of phenotypic switching as a form of bet-hedging as a function of the population size N, the rate theta at which a rare environment is encountered, and the selective advantage s associated with switching in the rare environment. We consider a simplified model in which environmental switching and phenotypic switching are one-way processes, and mutation is symmetric and rare with respect to the timescale of fixation events. In this case, the approximate requirements for bet-hedging to be favored by a ratio of at least R are that sN>log(R) and thetaN>square root R .     

Bacterial persistence: a model of survival in changing environments

The persistence phenotype is an epigenetic trait exhibited by a subpopulation of bacteria, characterized by slow growth coupled with an ability to survive antibiotic treatment. The phenotype is acquired via a spontaneous, reversible switch between normal and persister cells. These observations suggest that clonal bacterial populations may use persister cells, whose slow division rate under growth conditions leads to lower population fitness, as an "insurance policy" against antibiotic encounters. We present a model of Escherichia coli persistence, and using experimentally derived parameters for both wild type and a mutant strain (hipQ) with markedly different switching rates, we show how fitness loss due to slow persister growth pays off as a risk-reducing strategy. We demonstrate that wild-type persistence is suited for environments in which antibiotic stress is a rare event. The optimal rate of switching between normal and persister cells is found to depend strongly on the frequency of environmental changes and only weakly on the selective pressures of any given environment. In contrast to typical examples of adaptations to features of a single environment, persistence appears to constitute an adaptation that is tuned to the distribution of environmental change.     

A quantitative test of Hamilton's rule for the evolution of altruism

The evolution of altruism is a fundamental and enduring puzzle in biology. In a seminal paper Hamilton showed that altruism can be selected for when rb - c > 0, where c is the fitness cost to the altruist, b is the fitness benefit to the beneficiary, and r is their genetic relatedness. While many studies have provided qualitative support for Hamilton's rule, quantitative tests have not yet been possible due to the difficulty of quantifying the costs and benefits of helping acts. Here we use a simulated system of foraging robots to experimentally manipulate the costs and benefits of helping and determine the conditions under which altruism evolves. By conducting experimental evolution over hundreds of generations of selection in populations with different c/b ratios, we show that Hamilton's rule always accurately predicts the minimum relatedness necessary for altruism to evolve. This high accuracy is remarkable given the presence of pleiotropic and epistatic effects as well as mutations with strong effects on behavior and fitness (effects not directly taken into account in Hamilton's original 1964 rule). In addition to providing the first quantitative test of Hamilton's rule in a system with a complex mapping between genotype and phenotype, these experiments demonstrate the wide applicability of kin selection theory.     

Idiosyncratic evolution of maternal effects in response to juvenile malnutrition in Drosophila

Maternal effects often affect fitness traits, but there is little experimental evidence pertaining to their contribution to response to selection imposed by novel environments. We studied the evolution of maternal effects in Drosophila populations selected for tolerance to chronic larval malnutrition. To this end, we performed pairwise reciprocal F₁ crosses between six selected (malnutrition tolerant) populations and six unselected control populations and assessed the effect of cross direction on larval growth and developmental rate, adult weight and egg‐to‐adult viability expressed under the malnutrition regime. Each pair of reciprocal crosses revealed large maternal effects (possibly including cytoplasmic genetic effects) on at least one trait, but the magnitude, sign and which traits were affected varied among populations. Thus, maternal effects contributed significantly to the response to selection imposed by the malnutrition regime, but these changes were idiosyncratic, suggesting a rugged adaptive landscape. Furthermore, although the selected populations evolved both faster growth and higher viability, the maternal effects on growth rate and viability were negatively correlated across populations. Thus, genes mediating maternal effects can evolve to partially counteract the response to selection mediated by the effects of alleles on their own carriers’ phenotype, and maternal effects may contribute to evolutionary trade‐offs between components of offspring fitness.     

Bistability in feedback circuits 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.     

GENOTYPE-ENVIRONMENT INTERACTION AND THE EVOLUTION OF PHENOTYPIC PLASTICITY

Studies of spatial variation in the environment have primarily focused on how genetic variation can be maintained. Many one-locus genetic models have addressed this issue, but, for several reasons, these models are not directly applicable to quantitative (polygenic) traits. One reason is that for continuously varying characters, the evolution of the mean phenotype expressed in different environments (the norm of reaction) is also of interest. Our quantitative genetic models describe the evolution of phenotypic response to the environment, also known as phenotypic plasticity (Gause, 1947), and illustrate how the norm of reaction (Schmalhausen, 1949) can be shaped by selection. These models utilize the statistical relationship which exists between genotype-environment interaction and genetic correlation to describe evolution of the mean phenotype under soft and hard selection in coarse-grained environments. Just as genetic correlations among characters within a single environment can constrain the response to simultaneous selection, so can a genetic correlation between states of a character which are expressed in two environments. Unless the genetic correlation across environments is ± 1, polygenic variation is exhausted, or there is a cost to plasticity, panmictic populations under a bivariate fitness function will eventually attain the optimum mean phenotype for a given character in each environment. However, very high positive or negative correlations can substantially slow the rate of evolution and may produce temporary maladaptation in one environment before the optimum joint phenotype is finally attained. Evolutionary trajectories under hard and soft selection can differ: in hard selection, the environments with the highest initial mean fitness contribute most individuals to the mating pool. In both hard and soft selection, evolution toward the optimum in a rare environment is much slower than it is in a common one. A subdivided population model reveals that migration restriction can facilitate local adaptation. However, unless there is no migration or one of the special cases discussed for panmictic populations holds, no geographical variation in the norm of reaction will be maintained at equilibrium. Implications of these results for the interpretation of spatial patterns of phenotypic variation in natural populations are discussed.     

Phenotype Switching and Mutations in Random Environments

Cell populations can benefit from changing phenotype when the environment changes. One mechanism for generating these changes is stochastic phenotype switching, whereby cells switch stochastically from one phenotype to another according to genetically determined rates, irrespective of the current environment, with the matching of phenotype to environment then determined by selective pressure. This mechanism has been observed in numerous contexts, but identifying the precise connection between switching rates and environmental changes remains an open problem. Here, we introduce a simple model to study the evolution of phenotype switching in a finite population subject to random environmental shocks. We compare the successes of competing genotypes with different switching rates, and analyze how the optimal switching rates depend on the frequency of environmental changes. If environmental changes are as rare as mutations, then the optimal switching rates mimic the rates of environmental changes. If the environment changes more frequently, then the optimal genotype either maximally favors fitness in the more common environment or has the maximal switching rate to each phenotype. Our results also explain why the optimum is relatively insensitive to fitness in each environment.     

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

Phenotypic switching has been observed in laboratory studies of yeast and bacteria, in which the rate of such switching appears to adjust to match the frequency of environmental changes. Among possible mechanisms of switching are epigenetic influences on gene expression and variation in levels of methylation; thus environmental and/or genetic factors may contribute to the rate of switching. Most previous analyses of the evolution of phenotypic switching have compared exponential growth rates of noninteracting populations, and recombination has been ignored. Our genetic model of the evolution of switching rates is framed in terms of a mutation-modifying gene, environments that cause periodic changes in fitness, and recombination between the mutation modifier and the gene under selection. Exact results are obtained for all recombination rates and symmetric fitnesses that strongly generalize earlier results obtained under complete linkage and strong constraints on the relation between fitness and period of switching. Our analytical and numerical results suggest a general principle that recombination reduces the stable rate of switching in symmetric and asymmetric fitness regimes and when the period of switching is random. As the recombination rate increases, it becomes less likely that there is a stable nonzero rate of switching.     

Experimental evolution: Assortative mating and sexual selection,independent of local adaptation,lead to reproductive isolation in the nematode Caenorhabditis remanei

Using experimental evolution, we investigated the contributions of ecological divergence, sexual selection, and genetic drift to the evolution of reproductive isolation in Caenorhabditis remanei. The nematodes were reared on two different environments for 100 generations. They were assayed for fitness on both environments after 30, 64, and 100 generations, and hybrid fitness were analyzed after 64 and 100 generations. Mating propensity within and between populations was also analyzed. The design allowed us to determine whether local adaptation was synchronous with pre‐ and postzygotic reproductive isolation. Prezygotic isolation evolved quickly but was unconnected with adaptation to the divergent environments. Instead, prezygotic isolation was driven by mate preferences favoring individuals from the same replicate population. A bottleneck treatment, meant to enhance the opportunity for genetic drift, had no effect on prezygotic isolation. Postzygotic isolation occurred in crosses where at least one population had a large fitness advantage in its “home” environment. Taken together, our results suggest that prezygotic isolation did not depend on drift or adaptation to divergent environments, but instead resulted from differences in sexual interactions within individual replicates. Furthermore, our results suggest that postzygotic isolation can occur between populations even when only one population has greater fitness in its home environment.     

A microbial modified prisoner's dilemma game: how frequency-dependent selection can lead to random phase variation

Random phase variation (RPV) is a control strategy in which the expression of a cell state or phenotype randomly alternates between discrete 'on' and 'off' states. Though this mode of control is common for bacterial virulence factors like pili and toxins, precise conditions under which RPV confers an advantage have not been well defined. In Part I of this study, we predicted that fluctuating environments select for RPV if transitions between different selective environments cannot be reliably sensed (J. Theor. Biol. (2005)). However, selective forces both inside and outside of human hosts are also likely to be frequency dependent in the sense that the fitnesses of some bacterial states are greatest when rare. Here we show that RPV at slow rates can provide a survival advantage in such a frequency-dependent environment by generating population heterogeneity, essentially mimicking a polymorphism. More surprisingly, RPV at a faster 'optimal' rate can shift the population composition toward an optimal growth rate that exceeds that possible for polymorphic populations, but this optimal strategy is not evolutionarily stable. The population would be most fit if all cells randomly phase varied at the optimal rate, but individual cells have a growth-rate incentive to defect (mutate) to other switching rates or non-phase variable phenotype expression, leading to an overall loss of fitness of the individual and the population. This scenario describes a modified Prisoner's Dilemma game (Evolution and the Theory of Games, Cambridge University Press, Cambridge, New York, 1982, viii, 224pp.; Nature 398 (6726) (1999) 367), with random phase variation at optimal switching rates serving as the cooperation strategy.     

The relative roles of adaptation and phylogeny in determination of larval traits in diversifying anuran lineages

I measured phenotypic traits important to the fitness of larval anurans to assess the relative roles of ancestral trait value and selective regime in determining present-day phenotypes. The positions of 14 species from three taxonomic families and three different habitats in a phenotypic space defined by 19 traits provided measures of taxonomic and ecological similarity. The distribution of phenotypic distances among species revealed that neither taxonomy nor habitat overwhelmingly determined phenotype. There appear to be multiple ways in which anurans can exploit pond types. However, the direction of phenotypic movement was not random from one species to the next. Independent contrasts revealed significant correlations in the evolution of traits that were consistent among lineages. These correlations reflected well-known trade-offs that result from functional relationships among the constituent traits. Although there is no simple pattern in the distribution of mean phenotypes across environments and lineages, the pattern of the evolutionary trajectories that created that distribution is consistent with a predictive theory of multivariate evolution.     

The Population and Evolutionary Dynamics of Homologous Gene Recombination in Bacteria

In bacteria, recombination is a rare event, not a part of the reproductive process. Nevertheless, recombination—broadly defined to include the acquisition of genes from external sources, i.e., horizontal gene transfer (HGT)—plays a central role as a source of variation for adaptive evolution in many species of bacteria. Much of niche expansion, resistance to antibiotics and other environmental stresses, virulence, and other characteristics that make bacteria interesting and problematic, is achieved through the expression of genes and genetic elements obtained from other populations of bacteria of the same and different species, as well as from eukaryotes and archaea. While recombination of homologous genes among members of the same species has played a central role in the development of the genetics and molecular biology of bacteria, the contribution of homologous gene recombination (HGR) to bacterial evolution is not at all clear. Also, not so clear are the selective pressures responsible for the evolution and maintenance of transformation, the only bacteria-encoded form of HGR. Using a semi-stochastic simulation of mutation, recombination, and selection within bacterial populations and competition between populations, we explore (1) the contribution of HGR to the rate of adaptive evolution in these populations and (2) the conditions under which HGR will provide a bacterial population a selective advantage over non-recombining or more slowly recombining populations. The results of our simulation indicate that, under broad conditions: (1) HGR occurring at rates in the range anticipated for bacteria like Streptococcus pneumoniae, Escherichia coli, Haemophilus influenzae, and Bacillus subtilis will accelerate the rate at which a population adapts to environmental conditions; (2) once established in a population, selection for this capacity to increase rates of adaptive evolution can maintain bacteria-encoded mechanisms of recombination and prevent invasion of non-recombining populations, even when recombination engenders a modest fitness cost; and (3) because of the density- and frequency-dependent nature of HGR in bacteria, this capacity to increase rates of adaptive evolution is not sufficient as a selective force to provide a recombining population a selective advantage when it is rare. Under realistic conditions, homologous gene recombination will increase the rate of adaptive evolution in bacterial populations and, once established, selection for higher rates of evolution will promote the maintenance of bacteria-encoded mechanisms for HGR. On the other hand, increasing rates of adaptive evolution by HGR is unlikely to be the sole or even a dominant selective pressure responsible for the original evolution of transformation.     

Adapting in larger numbers can increase the vulnerability of Escherichia coli populations to environmental changes

Larger populations generally adapt faster to their existing environment. However, it is unknown if the population size experienced during evolution influences the ability to face sudden environmental changes. To investigate this issue, we subjected replicate Escherichia coli populations of different sizes to experimental evolution in an environment containing a cocktail of three antibiotics. In this environment, the ability to actively efflux molecules outside the cell is expected to be a major fitness‐affecting trait. We found that all the populations eventually reached similar fitness in the antibiotic cocktail despite adapting at different speeds, with the larger populations adapting faster. Surprisingly, although efflux activity (EA) enhanced in the smaller populations, it decayed in the larger ones. The evolution of EA was largely shaped by pleiotropic responses to selection and not by drift. This demonstrates that quantitative differences in population size can lead to qualitative differences (decay/enhancement) in the fate of a character during adaptation to identical environments. Furthermore, the larger populations showed inferior fitness upon sudden exposure to several alternative stressful environments. These observations provide a novel link between population size and vulnerability to environmental changes. Counterintuitively, adapting in larger numbers can render bacterial populations more vulnerable to abrupt environmental changes.     

Phage selection for bacterial cheats leads to population decline

While predators and parasites are known for their effects on bacterial population biology, their impact on the dynamics of bacterial social evolution remains largely unclear. Siderophores are iron-chelating molecules that are key to the survival of certain bacterial species in iron-limited environments, but their production can be subject to cheating by non-producing genotypes. In a selection experiment conducted over approximately 20 bacterial generations and involving 140 populations of the pathogenic bacterium Pseudomonas aeruginosa PAO1, we assessed the impact of a lytic phage on competition between siderophore producers and non-producers. We show that the presence of lytic phages favours the non-producing genotype in competition, regardless of whether iron use relies on siderophores. Interestingly, phage pressure resulted in higher siderophore production, which constitutes a cost to the producers and may explain why they were outcompeted by non-producers. By the end of the experiment, however, cheating load reduced the fitness of mixed populations relative to producer monocultures, and only monocultures of producers managed to grow in the presence of phage in situations where siderophores were necessary to access iron. These results suggest that public goods production may be modulated in the presence of natural enemies with consequences for the evolution of social strategies.     

Genetic bottlenecks and population passages cause profound fitness differences in RNA viruses.

Repeated clone-to-clone (genetic bottleneck) passages of an RNA phage and vesicular stomatitis virus have been shown previously to result in loss of fitness due to Muller's ratchet. We now demonstrate that Muller's ratchet also operates when genetic bottleneck passages are carried out at 37 rather than 32 degrees C. Thus, these fitness losses do not depend on growth of temperature-sensitive (ts) mutants at lowered temperatures. We also demonstrate that during repeated genetic bottleneck passages, accumulation of deleterious mutations does occur in a stepwise (ratchet-like) manner as originally proposed by Muller. One selected clone which had undergone significant loss of fitness after only 20 genetic bottleneck passages was passaged again in clone-to-clone series. Additional large losses of fitness were observed in five of nine independent bottleneck series; the relative fitnesses of the other four series remained close to the starting fitness. In sharp contrast, when the same selected clone was transferred 20 more times as large populations (10(5) to 10(6) PFU transferred at each passage), significant increases in fitness were observed in all eight passage series. Finally, we selected several clones which had undergone extreme losses of fitness during 20 bottleneck passages. When these low-fitness clones were passaged many times as large virus populations, they always regained very high relative fitness. We conclude that transfer of large populations of RNA viruses regularly selects those genomes within the quasispecies population which have the highest relative fitness, whereas bottleneck transfers have a high probability of leading to loss of fitness by random isolation of genomes carrying debilitating mutations. Both phenomena arise from, and underscore, the extreme mutability and variability of RNA viruses.     

PAEDOMORPHOSIS IN AMBYSTOMA TALPOIDEUM: MAINTENANCE OF POPULATION VARIATION AND ALTERNATIVE LIFE-HISTORY PATHWAYS

A “common garden” experiment using artifical ponds was performed to test if differences in frequency of paedomorphosis and metamorphosis among six natural populations of the salamander Ambystoma talpoideum resulted from the drying regime of the aquatic habitat acting as an agent of selection. Our experiment supports the hypothesis of genetic differentiation in the propensity to metamorphose among the populations, but gave mixed evidence that pond-drying regime is the selective force directing evolution of this trait. Some populations appear to have evolved phenotypic plasticity whereas others may have a genetic polymorphism in their propensity to metamorphose as ponds dry.     

Fold or hold: experimental evolution in vitro

We introduce a system for experimental evolution consisting of populations of short oligonucleotides (Oli populations) evolving in a modified quantitative polymerase chain reaction (qPCR). It is tractable at the genetic, genomic, phenotypic and fitness levels. The Oli system uses DNA hairpins designed to form structures that self‐prime under defined conditions. Selection acts on the phenotype of self‐priming, after which differences in fitness are amplified and quantified using qPCR. We outline the methodological and bioinformatics tools for the Oli system here and demonstrate that it can be used as a conventional experimental evolution model system by test‐driving it in an experiment investigating adaptive evolution under different rates of environmental change.