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

Evolutionary graph theory beyond single mutation dynamics: on how network-structured populations cross fitness landscapes

Spatially resolved datasets are revolutionizing knowledge in molecular biology, yet are under-utilized for questions in evolutionary biology. To gain insight from these large-scale datasets of spatial organization, we need mathematical representations and modeling techniques that can both capture their complexity, but also allow for mathematical tractability. Evolutionary graph theory utilizes the mathematical representation of networks as a proxy for heterogeneous population structure and has started to reshape our understanding of how spatial structure can direct evolutionary dynamics. However, previous results are derived for the case of a single new mutation appearing in the population and the role of network structure in shaping fitness landscape crossing is still poorly understood. Here we study how network-structured populations cross fitness landscapes and show that even a simple extension to a two-mutational landscape can exhibit complex evolutionary dynamics that cannot be predicted using previous single-mutation results. We show how our results can be intuitively understood through the lens of how the two main evolutionary properties of a network, the amplification and acceleration factors, change the expected fate of the intermediate mutant in the population and further discuss how to link these models to spatially resolved datasets of cellular organization.

A theory of evolutionary dynamics on any complex population structure reveals stem cell niche architecture as a spatial suppressor of selection

How the spatial arrangement of a population shapes its evolutionary dynamics has been of long-standing interest in population genetics. Most previous studies assume a small number of demes or symmetrical structures that, most often, act as well-mixed populations. Other studies use network theory to study more heterogeneous spatial structures, however they usually assume small, regular networks, or strong constraints on the strength of selection considered. Here we build network generation algorithms, conduct evolutionary simulations and derive general analytic approximations for probabilities of fixation in populations with complex spatial structure. We build a unifying evolutionary theory across network families and derive the relevant selective parameter, which is a combination of network statistics, predictive of evolutionary dynamics. We also illustrate how to link this theory with novel datasets of spatial organization and use recent imaging data to build the cellular spatial networks of the stem cell niches of the bone marrow. Across a wide variety of parameters, we find these networks to be strong suppressors of selection, delaying mutation accumulation in this tissue. We also find that decreases in stem cell population size also decrease the suppression strength of the tissue spatial structure.

Extinction scenarios in evolutionary processes: a multinomial Wright-Fisher approach

We study a discrete-time multi-type Wright-Fisher population process. The mean-field dynamics of the stochastic process is induced by a general replicator difference equation. We prove several results regarding the asymptotic behavior of the model, focusing on the impact of the mean-field dynamics on it. One of the results is a limit theorem that describes sufficient conditions for an almost certain path to extinction, first eliminating the type which is the least fit at the mean-field equilibrium. The effect is explained by the metastability of the stochastic system, which under the conditions of the theorem spends almost all time before the extinction event in a neighborhood of the equilibrium. In addition to the limit theorems, we propose a maximization principle for a general deterministic replicator dynamics and study its implications for the stochastic model.

Phenotype switching of the mutation rate facilitates adaptive evolution

The mutation rate plays an important role in adaptive evolution. It can be modified by mutator and anti-mutator alleles. Recent empirical evidence hints that the mutation rate may vary among genetically identical individuals: evidence from bacteria suggests that the mutation rate can be affected by expression noise of a DNA repair protein and potentially also by translation errors in various proteins. Importantly, this non-genetic variation may be heritable via a transgenerational epigenetic mode of inheritance, giving rise to a mutator phenotype that is independent from mutator alleles. Here, we investigate mathematically how the rate of adaptive evolution is affected by the rate of mutation rate phenotype switching. We model an asexual population with two mutation rate phenotypes, non-mutator and mutator. An offspring may switch from its parental phenotype to the other phenotype. We find that switching rates that correspond to so-far empirically described non-genetic systems of inheritance of the mutation rate lead to higher rates of adaptation on both artificial and natural fitness landscapes. These switching rates can maintain within the same individuals both a mutator phenotype and intermediary mutations, a combination that facilitates adaptation. Moreover, non-genetic inheritance increases the proportion of mutators in the population, which in turn increases the probability of hitchhiking of the mutator phenotype with adaptive mutations. This in turns facilitates the acquisition of additional adaptive mutations. Our results rationalize recently observed noise in the expression of proteins that affect the mutation rate and suggest that non-genetic inheritance of this phenotype may facilitate evolutionary adaptive processes.

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'.

Fine-scale spatial distribution of deltamethrin resistance and population structure of Anopheles funestus and Anopheles arabiensis populations in Southern Mozambique

BACKGROUND

Insecticide resistance in malaria vectors can be spatially highly heterogeneous, yet population structure analyses frequently find relatively high levels of gene flow among mosquito populations. Few studies have contemporaneously assessed phenotypic, genotypic and population structure analysis on mosquito populations and none at fine geographical scales. In this study, genetic diversity, population structure, and insecticide resistance profiles of Anopheles funestus and Anopheles arabiensis were examined across mosquito populations from and within neighbouring villages.

METHODS

Mosquitoes were collected from 11 towns in southern Mozambique, as well as from different neighbourhoods within the town of Palmeira, during the peak malaria transmission season in 2016. CDC bottle bioassay and PCR assays were performed with Anopheles mosquitoes at each site to determine phenotypic and molecular insecticide resistance profiles, respectively. Microsatellite analysis was conducted on a subsample of mosquitoes to estimate genetic diversity and population structure.

RESULTS

Phenotypic insecticide resistance to deltamethrin was observed in An. funestus sensu stricto (s.s.) throughout the area, though a high level of mortality variation was seen. However, 98% of An. funestus s.s. were CYP6P9a homozygous resistant. An. arabiensis was phenotypically susceptible to deltamethrin and 99% were kdr homozygous susceptible. Both Anopheles species exhibited high allelic richness and heterozygosity. Significant deviations from Hardy-Weinberg equilibrium were observed, and high linkage disequilibrium was seen for An. funestus s.s., supporting population subdivision. However, the FST values were low for both anophelines (- 0.00457 to 0.04213), Nm values were high (9.4-71.8 migrants per generation), AMOVA results showed almost 100% genetic variation among and within individuals, and Structure analysis showed no clustering of An. funestus s.s. and An. arabiensis populations. These results suggest high gene flow among mosquito populations.

CONCLUSION

Despite a relatively high level of phenotypic variation in the An. funestus population, molecular analysis shows the population is admixed. These data indicate that CYP6P9a resistance markers do not capture all phenotypic variation in the area, but also that resistance genes of high impact are likely to easily spread in the area. Conversely, other strategies, such as transgenic mosquito release programmes will likely not face challenges in this locality.

Stay in shape: Assessing the adaptive potential of shell morphology and its sensitivity to temperature in the invasive New Zealand mud snail Potamopyrgus antipodarum through phenotypic plasticity and natural selection in Europe

Climate change may force organisms to adapt genetically or plastically to new environmental conditions. Invasive species show remarkable potential for rapid adaptation. The ovoviviparous New Zealand mud snail (NZMS), Potamopyrgus antipodarum, has successfully established across Europe with two clonally reproducing mitochondrial lineages since its arrival in the first half of the 19th century. Its remarkable variation in shell morphology was shown to be fitness relevant. We investigated the effects of temperature on shell morphology across 11 populations from Germany and the Iberian Peninsula in a common garden across three temperatures. We analyzed size and shape using geometric morphometrics. For both, we compared reaction norms and estimated heritabilities. For size, the interaction of temperature and haplotype explained about 50% of the total variance. We also observed more genotype by environment interactions indicating a higher degree of population differentiation than in shape. Across the three temperatures, size followed the expectations of the temperature‐size rule, with individuals growing larger in cold environments. Changes in shape may have compensated for changes in size affecting space for brooding embryos. Heritability estimates were relatively high. As indicated by the very low coefficients of variation for clonal repeatability (CV_A), they can probably not be compared in absolute terms. However, they showed some sensitivity to temperature, in haplotype t more so than in z, which was only found in Portugal. The low CV_A values indicate that genetic variation among European populations is still restricted with a low potential to react to selection. A considerable fraction of the genetic variation was due to differences between the clonal lineages. The NZMS has apparently not been long enough in Europe to accumulate significant genetic variation relevant for morphological adaptation. As temperature is obviously not the sole factor influencing shell morphology, their interaction will probably not be a factor limiting population persistence under a warming climate in Europe.

Evolutionary Ecology of Natural Comammox Nitrospira Populations

Microbes commonly exist in diverse and complex communities where species interact, and their genomic repertoires evolve over time. Our understanding of species interaction and evolution has increased during the last decades, but most studies of evolutionary dynamics are based on single species in isolation or in experimental systems composed of few interacting species. Here, we use the microbial ecosystem found in groundwater-fed sand filter as a model to avoid this limitation. In these open systems, diverse microbial communities experience relatively stable conditions, and the coupling between chemical and biological processes is generally well defined. Metagenomic analysis of 12 sand filters communities revealed systematic co-occurrence of at least five comammox Nitrospira species, likely promoted by low ammonium concentrations. These Nitrospira species showed intrapopulation sequence diversity, although possible clonal expansion was detected in a few abundant local comammox populations. Nitrospira species showed low homologous recombination and strong purifying selection, the latter process being especially strong in genes essential in energy metabolism. Positive selection was detected for genes related to resistance to foreign DNA and phages. We found that, compared to other habitats, groundwater-fed sand filters impose strong purifying selection and low recombination on comammox Nitrospira populations. These results suggest that evolutionary processes are more affected by habitat type than by species identity. Together, this study improves our understanding of species interaction and evolution in complex microbial communities and sheds light on the environmental dependency of evolutionary processes. IMPORTANCE Microbial species interact with each other and their environment (ecological processes) and undergo changes in their genomic repertoire over time (evolutionary processes). How these two classes of processes interact is largely unknown, especially for complex communities, as most studies of microbial evolutionary dynamics consider single species in isolation or a few interacting species in simplified experimental systems. In this study, these limitations are circumvented by examining the microbial communities found in stable and well-described groundwater-fed sand filters. Combining metagenomics and strain-level analyses, we identified the microbial interactions and evolutionary processes affecting comammox Nitrospira, a recently discovered bacterial type capable of performing the whole nitrification process. We found that abundant and co-occurrent Nitrospira populations in groundwater-fed sand filters are characterized by low recombination and strong purifying selection. In addition, by comparing these observations with those obtained from Nitrospira species inhabiting other environments, we revealed that evolutionary processes are more affected by habitat type than by species identity.

Recombination mapping of the Brazilian stingless bee Frieseomelitta varia confirms high recombination rates in social hymenoptera

Background

Meiotic recombination is a fundamental genetic process that shuffles allele combinations and promotes accurate segregation of chromosomes. Analyses of the ubiquitous variation of recombination rates within and across species suggest that recombination is evolving adaptively. All studied insects with advanced eusociality have shown exceptionally high recombination rates, which may represent a prominent case of adaptive evolution of recombination. However, our understanding of the relationship between social evolution and recombination rates is incomplete, partly due to lacking empirical data. Here, we present a linkage map of the monandrous, advanced eusocial Brazilian stingless bee, Frieseomelitta varia, providing the first recombination analysis in the diverse Meliponini (Hymenoptera, Apidae).

Results

Our linkage map includes 1417 markers in 19 linkage groups. This map spans approximately 2580 centimorgans, and comparisons to the physical genome assembly indicate that it covers more than 75 % of the 275 Megabasepairs (Mbp) F. varia genome. Thus, our study results in a genome-wide recombination rate estimate of 9.3–12.5 centimorgan per Mbp. This value is higher than estimates from nonsocial insects and comparable to other highly social species, although it does not support our prediction that monandry and strong queen-worker caste divergence of F. varia lead to even higher recombination rates than other advanced eusocial species.

Conclusions

Our study expands the association between elevated recombination and sociality in the order Hymenoptera and strengthens the support for the hypothesis that advanced social evolution in hymenopteran insects invariably selects for high genomic recombination rates.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12864-021-07987-3.

Cooperate or Not Cooperate in Predictable but Periodically Varying Situations? Cooperation in Fast Oscillating Environment

In this work, the cooperation problem between two populations in a periodically varying environment is discussed. In particular, the two-population prisoner's dilemma game with periodically oscillating payoffs is discussed, such that the time-average of these oscillations over the period of environmental variations vanishes. The possible overlaps of these oscillations generate completely new dynamical effects that drastically change the phase space structure of the two-population evolutionary dynamics. Due to these effects, the emergence of some level of cooperators in both populations is possible under certain conditions on the environmental variations. In the domain of stable coexistence the dynamics of cooperators in each population form stable cycles. Thus, the cooperators in each population promote the existence of cooperators in the other population. However, the survival of cooperators in both populations is not guaranteed by a large initial fraction of them.

The fundamentals of cultural adaptation: implications for human adaptation

The process of human adaptation to novel environments is a uniquely complex interplay between cultural and genetic changes. However, mechanistically, we understand little about these processes. To begin to untangle these threads of human adaptation we use mathematical models to describe and investigate cultural selective sweeps. We show that cultural sweeps differ in important ways from the genetic equivalents. The models show that the dynamics of cultural selective sweeps and, consequently, their differences from genetic sweeps depend critically on cultural transmission mechanisms. Further, we consider the effect of processes unique to culture such as foresight and innovations in response to an environmental change on adaptation. Finally we show that a 'cultural evolutionary rescue', or the survival of an endangered population by means of cultural adaptation, is possible. We suggest that culture might make a true, genetic, evolutionary rescue plausible for human populations.

Genetic differentiation and population structure of Anopheles funestus from Uganda and the southern African countries of Malawi, Mozambique, Zambia and Zimbabwe

Background

Anopheles funestus (s.s.) is a primary vector of the malaria parasite Plasmodium falciparum in Africa, a human pathogen that causes almost half a million deaths each year. The population structure of An. funestus was examined in samples from Uganda and the southern African countries of Malawi, Mozambique, Zambia and Zimbabwe.

Methods

Twelve microsatellites were used to estimate the genetic diversity and differentiation of An. funestus from 13 representative locations across five countries. These were comprised of four sites from Uganda, three from Malawi and two each from Mozambique, Zambia and Zimbabwe.

Results

All loci were highly polymorphic across the populations with high allelic richness and heterozygosity. A high genetic diversity was observed with 2–19 alleles per locus and an average number of seven alleles. Overall, expected heterozygosity (H_e) ranged from 0.65 to 0.79. When samples were pooled three of the 12 microsatellite loci showed Hardy–Weinberg equilibrium. Unsupervised Bayesian clustering analysis of microsatellite data revealed two clusters with An. funestus samples from Mozambique, Uganda and Zambia falling into one group and Malawi and Zimbabwe into another. The overall genetic differentiation between the populations was moderate (F_ST = 0.116). Pairwise differentiation between the pairs was low but significant. A weak but significant correlation was established between genetic and geographical distance for most populations.

Conclusions

High genetic diversity revealed by the loci with low to moderate differentiation, identified two clusters among the An. funestus populations. Further research on the population dynamics of An. funestus in east and southern Africa is essential to understand the implications of this structuring and what effect it may have on the efficient implementation of mosquito vector control strategies.

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.

Antibiotics: Combatting Tolerance To Stop Resistance

Antibiotic resistance poses an alarming and ever-increasing threat to modern health care. Although the current antibiotic crisis is widely acknowledged, actions taken so far have proved insufficient to slow down the rampant spread of resistant pathogens. Problematically, routine screening methods and strategies to restrict therapy failure almost exclusively focus on genetic resistance, while evidence for dangers posed by other bacterial survival strategies is mounting. Antibiotic tolerance, occurring either population-wide or in a subpopulation of cells, allows bacteria to transiently overcome antibiotic treatment and is overlooked in clinical practice. In addition to prolonging treatment and causing relapsing infections, recent studies have revealed that tolerance also accelerates the emergence of resistance. These critical findings emphasize the need for strategies to combat tolerance, not only to improve treatment of recurrent infections but also to effectively address the problem of antibiotic resistance at the root.

Antibiotics: Combatting Tolerance To Stop Resistance

Antibiotic resistance poses an alarming and ever-increasing threat to modern health care. Although the current antibiotic crisis is widely acknowledged, actions taken so far have proved insufficient to slow down the rampant spread of resistant pathogens. Problematically, routine screening methods and strategies to restrict therapy failure almost exclusively focus on genetic resistance, while evidence for dangers posed by other bacterial survival strategies is mounting.

Antibiotic resistance poses an alarming and ever-increasing threat to modern health care. Although the current antibiotic crisis is widely acknowledged, actions taken so far have proved insufficient to slow down the rampant spread of resistant pathogens. Problematically, routine screening methods and strategies to restrict therapy failure almost exclusively focus on genetic resistance, while evidence for dangers posed by other bacterial survival strategies is mounting. Antibiotic tolerance, occurring either population-wide or in a subpopulation of cells, allows bacteria to transiently overcome antibiotic treatment and is overlooked in clinical practice. In addition to prolonging treatment and causing relapsing infections, recent studies have revealed that tolerance also accelerates the emergence of resistance. These critical findings emphasize the need for strategies to combat tolerance, not only to improve treatment of recurrent infections but also to effectively address the problem of antibiotic resistance at the root.

Population structure promotes the evolution of costly sex in artificial gene networks

We build on previous observations that Hill-Robertson interference generates an advantage of sex that, in structured populations, can be large enough to explain the evolutionary maintenance of costly sex. We employed a gene network model that explicitly incorporates interactions between genes. Mutations in the gene networks have variable effects that depend on the genetic background in which they appear. Consequently, our simulations include two costs of sex-recombination and migration loads-that were missing from previous studies of the evolution of costly sex. Our results suggest a critical role for population structure that lies in its ability to align the long- and short-term advantages of sex. We show that the addition of population structure favored the evolution of sex by disproportionately decreasing the equilibrium mean fitness of asexual populations, primarily by increasing the strength of Muller's Ratchet. Population structure also increased the ability of the short-term advantage of sex to counter the primary limit to the evolution of sex in the gene network model-recombination load. On the other hand, highly structured populations experienced migration load in the form of Dobzhansky-Muller incompatibilities, decreasing the effective rate of migration between demes and, consequently, accelerating the accumulation of drift load in the sexual populations.

Evolutionary Rescue Through Partly Heritable Phenotypic Variability

Environmental variation is commonplace, but unpredictable. Populations that encounter a deleterious environment can sometimes avoid extinction by rapid evolutionary adaptation. Phenotypic variability, whereby a single genotype can express multiple different phenotypes, might play an important role in rescuing such populations from extinction. This type of evolutionary bet-hedging need not confer a direct benefit to a single individual, but it may increase the chance of long-term survival of a lineage. Here, we develop a population genetic model to explore how partly heritable phenotypic variability influences the probability of evolutionary rescue and the mean duration of population persistence in changing environments. We find that the probability of population persistence depends nonmonotonically on the degree of phenotypic heritability between generations: some heritability can help avert extinction, but too much heritability removes any benefit of phenotypic variability. Partly heritable phenotypic variation is particularly advantageous when it extends the persistence time of a declining population and thereby increases the chance of rescue via beneficial mutations at linked loci. We discuss the implications of these results in the context of therapies designed to eradicate populations of pathogens or aberrant cellular lineages.

Bacterial persistence promotes the evolution of antibiotic resistance by increasing survival and mutation rates

Persisters are transiently antibiotic-tolerant cells that complicate the treatment of bacterial infections. Both theory and experiments have suggested that persisters facilitate genetic resistance by constituting an evolutionary reservoir of viable cells. Here, we provide evidence for a strong positive correlation between persistence and the likelihood to become genetically resistant in natural and lab strains of E. coli. This correlation can be partly attributed to the increased availability of viable cells associated with persistence. However, our data additionally show that persistence is pleiotropically linked with mutation rates. Our theoretical model further demonstrates that increased survival and mutation rates jointly affect the likelihood of evolving clinical resistance. Overall, these results suggest that the battle against antibiotic resistance will benefit from incorporating anti-persister therapies.

Cultural complexity and evolution in fluctuating environments

The effect of environmental change on the rate of innovation and level of cultural complexity in a population is a theoretically understudied piece of an important puzzle at the heart of cultural evolution. Many mathematical models of cultural complexity have focused on the role of demographic factors such as population size or density. However, statistical studies often point to environmental variability as an important factor determining complexity in many cases. The aim of this study is to explore the interaction between environmental fluctuations and the rate of cultural innovation within a population and to examine the relationship between rates of innovation and the probability of maintaining a complex cultural repertoire in a changing environment. Two models are presented that draw on previous models used to examine rates of genetic mutation. The models show that, as in a genetic system, the stable rate of cultural innovation in a population decreases with environmental stability and increases in unstable environments. This effect is similar but quantitatively different for different modes of cultural transmission (success bias, conformity bias and random oblique learning). The model shows that innovation can increase diversity but that this relationship depends critically on learning mode and learning parameters.This article is part of the theme issue 'Bridging cultural gaps: interdisciplinary studies in human cultural evolution'.

Characterization, phylogenetic distribution and evolutionary trajectories of diverse hydrocarbon degrading microorganisms isolated from refinery sludge

Phylogenic association between bacteria living under harsh conditions can provide important information on adaptive mechanism, survival strategy and their potential application. Indigenous microorganisms isolated from toxic refinery oily sludge with ability to degrade a diverse range of hydrocarbons were identified and characterized. The strains including Pseudomonas aeruginosa RS1, Microbacterium sp. RS2, Bacillus sp. RS3, Acinetobacter baumannii RS4 and Stenotrophomonas sp. RS5 could utilize n-alkanes, cycloalkanes, polynuclear aromatic hydrocarbons (PAHs) with 2-4 rings and also substituted PAHs as sole substrate. The phylogenetic position of Bacillus sp. RS3 and Pseudomonas sp. RS1 was tested by applying the maximum likelihood (ML) method to the aligned 16S rRNA nucleotide sequences of PAH and aliphatic hydrocarbon degrading strains belonging to the corresponding genus. The base substitution matrix created with each set of organisms capable of degrading aromatic and aliphatic hydrocarbons showed significant transitional event with high values of transition: transversion ratio (R) under all conditions. The guanine-cytosine (GC) content of the hydrocarbon degrading test strains was also found to be highest for the clade which harbored them. The test strains consistently occupied a distinct terminal end within the phylogenetic tree constructed by ML analysis. This study reveals that the refinery sludge imposed environmental stress on the bacterial strains which possibly caused significant genetic alteration and phenotypic adaptation. Due to the divergent evolution of the Pseudomonas and Bacillus strains in the sludge, they appeared distinctly different from other hydrocarbon degrading strains of the same genus.

What drives the evolution of condition-dependent recombination in diploids? Some insights from simulation modelling

While the evolutionary advantages of non-zero recombination rates have prompted diverse theoretical explanations, the evolution of essential recombination features remains underexplored. We focused on one such feature, the condition dependence of recombination, viewed as the variation in within-generation sensitivity of recombination to external (environment) and/or internal (genotype) conditions. Limited empirical evidence for its existence comes mainly from diploids, whereas theoretical models show that it only easily evolves in haploids. The evolution of condition-dependent recombination can be explained by its advantage for the selected system (indirect effect), or by benefits to modifier alleles, ensuring this strategy regardless of effects on the selected system (direct effect). We considered infinite panmictic populations of diploids exposed to a cyclical two-state environment. Each organism had three selected loci. Examining allele dynamics at a fourth, selectively neutral recombination modifier locus, we frequently observed that a modifier allele conferring condition-dependent recombination between the selected loci displaced the allele conferring the optimal constant recombination rate. Our simulations also confirm the results of theoretical studies showing that condition-dependent recombination cannot evolve in diploids on the basis of direct fitness-dependent effects alone. Therefore, the evolution of condition-dependent recombination in diploids can be driven by indirect effects alone, i.e. by modifier effects on the selected system.This article is part of the themed issue 'Evolutionary causes and consequences of recombination rate variation in sexual organisms'.

Adaptive phenotypic plasticity in a clonal invader

Organisms featuring wide trait variability and occurring in a wide range of habitats, such as the ovoviviparous New Zealand freshwater snail Potamopyrgus antipodarum, are ideal models to study adaptation. Since the mid‐19th century, P. antipodarum, characterized by extremely variable shell morphology, has successfully invaded aquatic areas on four continents. Because these obligately and wholly asexual invasive populations harbor low genetic diversity compared to mixed sexual/asexual populations in the native range, we hypothesized that (1) this phenotypic variation in the invasive range might be adaptive with respect to colonization of novel habitats, and (2) that at least some of the variation might be caused by phenotypic plasticity. We surveyed 425 snails from 21 localities across northwest Europe to attempt to disentangle genetic and environmental effects on shell morphology. We analyzed brood size as proxy for fitness and shell geometric morphometrics, while controlling for genetic background. Our survey revealed 10 SNP genotypes nested into two mtDNA haplotypes and indicated that mainly lineage drove variation in shell shape but not size. Physicochemical parameters affected both shell shape and size and the interaction of these traits with brood size. In particular, stronger stream flow rates were associated with larger shells. Our measurements of brood size suggested that relatively larger slender snails with relatively large apertures were better adapted to strong flow than counterparts with broader shells and relatively small apertures. In conclusion, the apparent potential to modify shell morphology plays likely a key role in the invasive success of P. antipodarum; the two main components of shell morphology, namely shape and size, being differentially controlled, the former mainly genetically and the latter predominantly by phenotypic plasticity.

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.

Biology-Culture Co-evolution in Finite Populations

Language is the result of two concurrent evolutionary processes: biological and cultural inheritance. An influential evolutionary hypothesis known as the moving target problem implies inherent limitations on the interactions between our two inheritance streams that result from a difference in pace: the speed of cultural evolution is thought to rule out cognitive adaptation to culturally evolving aspects of language. We examine this hypothesis formally by casting it as as a problem of adaptation in time-varying environments. We present a mathematical model of biology-culture co-evolution in finite populations: a generalisation of the Moran process, treating co-evolution as coupled non-independent Markov processes, providing a general formulation of the moving target hypothesis in precise probabilistic terms. Rapidly varying culture decreases the probability of biological adaptation. However, we show that this effect declines with population size and with stronger links between biology and culture: in realistically sized finite populations, stochastic effects can carry cognitive specialisations to fixation in the face of variable culture, especially if the effects of those specialisations are amplified through cultural evolution. These results support the view that language arises from interactions between our two major inheritance streams, rather than from one primary evolutionary process that dominates another.

Transitions in optimal adaptive strategies for populations in fluctuating environments

Biological populations are subject to fluctuating environmental conditions. Different adaptive strategies can allow them to cope with these fluctuations: specialization to one particular environmental condition, adoption of a generalist phenotype that compromises between conditions, or population-wise diversification (bet hedging). Which strategy provides the largest selective advantage in the long run depends on the range of accessible phenotypes and the statistics of the environmental fluctuations. Here, we analyze this problem in a simple mathematical model of population growth. First, we review and extend a graphical method to identify the nature of the optimal strategy when the environmental fluctuations are uncorrelated. Temporal correlations in environmental fluctuations open up new strategies that rely on memory but are mathematically challenging to study: We present analytical results to address this challenge. We illustrate our general approach by analyzing optimal adaptive strategies in the presence of trade-offs that constrain the range of accessible phenotypes. Our results extend several previous studies and have applications to a variety of biological phenomena, from antibiotic resistance in bacteria to immune responses in vertebrates.

The evolutionary advantage of heritable phenotypic heterogeneity

Phenotypic plasticity is an evolutionary driving force in diverse biological processes, including the adaptive immune system, the development of neoplasms, and the persistence of pathogens despite drug pressure. It is essential, therefore, to understand the evolutionary advantage of an allele that confers on cells the ability to express a range of phenotypes. Here, we study the fate of a new mutation that allows the expression of multiple phenotypic states, introduced into a finite population of individuals that can express only a single phenotype. We show that the advantage of such a mutation depends on the degree of phenotypic heritability between generations, called phenotypic memory. We analyze the fixation probability of the phenotypically plastic allele as a function of phenotypic memory, the variance of expressible phenotypes, the rate of environmental changes, and the population size. We find that the fate of a phenotypically plastic allele depends fundamentally on the environmental regime. In constant environments, plastic alleles are advantageous and their fixation probability increases with the degree of phenotypic memory. In periodically fluctuating environments, by contrast, there is an optimum phenotypic memory that maximizes the probability of the plastic allele's fixation. This same optimum memory also maximizes geometric mean fitness, in steady state. We interpret these results in the context of previous studies in an infinite-population framework. We also discuss the implications of our results for the design of therapies that can overcome persistence and, indirectly, drug resistance.

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.

Thioridazine as Chemotherapy for Mycobacterium avium Complex Diseases

Mycobacterium avium-intracellulare complex (MAC) causes an intractable intracellular infection that presents as chronic pulmonary disease. Currently, therapy consists of ethambutol and macrolides and takes several years to complete. The neuroleptic phenothiazine thioridazine kills mycobacteria by inhibiting the electron transport chain. In several experiments with bacterial populations of up to 10¹² CFU/ml, we failed to isolate any bacteria resistant to 3 times the MIC of thioridazine, suggesting the absence of resistant mutants at bacterial burdens severalfold higher than those encountered in patients. In the hollow-fiber model of intracellular MAC (HFS-MAC), thioridazine achieved an extracellular half-life of 16.8 h and an intracellular half-life of 19.7 h. Thioridazine concentrations were >28,000-fold higher inside infected macrophages than in the HFS-MAC central compartment (equivalent to plasma). Thioridazine maximal kill was 5.20 ± 0.75 log₁₀ CFU/ml on day 7 (r² = 0.96) and 7.19 ± 0.31 log₁₀ CFU/ml on day 14 (r² = 0.99), the highest seen with any drug in the system. Dose fractionation studies revealed that thioridazine efficacy and acquired drug resistance were driven by the peak concentation-to-MIC ratio, with a 50% effective concentration (EC₅₀) of 2.78 ± 0.44 for microbial killing. Acquired drug resistance was encountered by day 21 with suboptimal doses, demonstrating that fluctuating drug concentrations drive evolution faster than static concentrations in mutation frequency studies. However, the thioridazine EC₅₀ changed 16.14-fold when the concentration of fetal bovine serum was changed from 0% to 50%, suggesting that intracellular potency could be heavily curtailed by protein binding. Efficacy in patients will depend on the balance between trapping of the drug in the pulmonary system and the massive intracellular concentrations versus very high protein binding of thioridazine.

Not So Simple After All: Bacteria, Their Population Genetics, and Recombination

The pervasive nature of bacterial recombination has become clear. Despite this, the population genetics of bacteria persist in being viewed as simple. Here, I argue against that characterization. After summarizing the history of the topic, I survey the evidence for remarkable and unexplained variation in recombination rate among and within bacterial species. I finally argue that despite recent assertions that recombination means bacterial genes are "public goods," in bacteria the level of selection is the gene, and genes can be understood to have niches with dimensions including the other contents of the genome in which they find themselves.

An Evolving Genetic Architecture Interacts with Hill-Robertson Interference to Determine the Benefit of Sex

Sex is ubiquitous in the natural world, but the nature of its benefits remains controversial. Previous studies have suggested that a major advantage of sex is its ability to eliminate interference between selection on linked mutations, a phenomenon known as Hill-Robertson interference. However, those studies may have missed both important advantages and important disadvantages of sexual reproduction because they did not allow the distributions of mutational effects and interactions (i.e., the genetic architecture) to evolve. Here we investigate how Hill-Robertson interference interacts with an evolving genetic architecture to affect the evolutionary origin and maintenance of sex by simulating evolution in populations of artificial gene networks. We observed a long-term advantage of sex-equilibrium mean fitness of sexual populations exceeded that of asexual populations-that did not depend on population size. We also observed a short-term advantage of sex-sexual modifier mutations readily invaded asexual populations-that increased with population size, as was observed in previous studies. We show that the long- and short-term advantages of sex were both determined by differences between sexual and asexual populations in the evolutionary dynamics of two properties of the genetic architecture: the deleterious mutation rate ([Formula: see text]) and recombination load ([Formula: see text]). These differences resulted from a combination of selection to minimize [Formula: see text] which is experienced only by sexuals, and Hill-Robertson interference experienced primarily by asexuals. In contrast to the previous studies, in which Hill-Robertson interference had only a direct impact on the fitness advantages of sex, the impact of Hill-Robertson interference in our simulations was mediated additionally by an indirect impact on the efficiency with which selection acted to reduce [Formula: see text].

Adaptive Landscape by Environment Interactions Dictate Evolutionary Dynamics in Models of Drug Resistance

The adaptive landscape analogy has found practical use in recent years, as many have explored how their understanding can inform therapeutic strategies that subvert the evolution of drug resistance. A major barrier to applications of these concepts is a lack of detail concerning how the environment affects adaptive landscape topography, and consequently, the outcome of drug treatment. Here we combine empirical data, evolutionary theory, and computer simulations towards dissecting adaptive landscape by environment interactions for the evolution of drug resistance in two dimensions-drug concentration and drug type. We do so by studying the resistance mediated by Plasmodium falciparum dihydrofolate reductase (DHFR) to two related inhibitors-pyrimethamine and cycloguanil-across a breadth of drug concentrations. We first examine whether the adaptive landscapes for the two drugs are consistent with common definitions of cross-resistance. We then reconstruct all accessible pathways across the landscape, observing how their structure changes with drug environment. We offer a mechanism for non-linearity in the topography of accessible pathways by calculating of the interaction between mutation effects and drug environment, which reveals rampant patterns of epistasis. We then simulate evolution in several different drug environments to observe how these individual mutation effects (and patterns of epistasis) influence paths taken at evolutionary "forks in the road" that dictate adaptive dynamics in silico. In doing so, we reveal how classic metrics like the IC50 and minimal inhibitory concentration (MIC) are dubious proxies for understanding how evolution will occur across drug environments. We also consider how the findings reveal ambiguities in the cross-resistance concept, as subtle differences in adaptive landscape topography between otherwise equivalent drugs can drive drastically different evolutionary outcomes. Summarizing, we discuss the results with regards to their basic contribution to the study of empirical adaptive landscapes, and in terms of how they inform new models for the evolution of drug resistance.

Experimental evolution of recombination and crossover interference in Drosophila caused by directional selection for stress-related traits

BACKGROUND

Population genetics predicts that tight linkage between new and/or pre-existing beneficial and deleterious alleles should decrease the efficiency of natural selection in finite populations. By decoupling beneficial and deleterious alleles and facilitating the combination of beneficial alleles, recombination accelerates the formation of high-fitness genotypes. This may impose indirect selection for increased recombination. Despite the progress in theoretical understanding, interplay between recombination and selection remains a controversial issue in evolutionary biology. Even less satisfactory is the situation with crossover interference, which is a deviation of double-crossover frequency in a pair of adjacent intervals from the product of recombination rates in the two intervals expected on the assumption of crossover independence. Here, we report substantial changes in recombination and interference in three long-term directional selection experiments with Drosophila melanogaster: for desiccation (~50 generations), hypoxia, and hyperoxia tolerance (>200 generations each).

RESULTS

For all three experiments, we found a high interval-specific increase of recombination frequencies in selection lines (up to 40-50% per interval) compared to the control lines. We also discovered a profound effect of selection on interference as expressed by an increased frequency of double crossovers in selection lines. Our results show that changes in interference are not necessarily coupled with increased recombination.

CONCLUSIONS

Our results support the theoretical predictions that adaptation to a new environment can promote evolution toward higher recombination. Moreover, this is the first evidence of selection for different recombination-unrelated traits potentially leading, not only to evolution toward increased crossover rates, but also to changes in crossover interference, one of the fundamental features of recombination.