Unpredictability of the fitness effects of antimicrobial resistance mutations across environments in Escherichia coli

The evolution of antimicrobial resistance (AMR) in bacteria is a major public health concern, and antibiotic restriction is often implemented to reduce the spread of resistance. These measures rely on the existence of deleterious fitness effects (i.e., costs) imposed by AMR mutations during growth in the absence of antibiotics. According to this assumption, resistant strains will be outcompeted by susceptible strains that do not pay the cost during the period of restriction. The fitness effects of AMR mutations are generally studied in laboratory reference strains grown in standard growth environments; however, the genetic and environmental context can influence the magnitude and direction of a mutation's fitness effects. In this study, we measure how three sources of variation impact the fitness effects of Escherichia coli AMR mutations: the type of resistance mutation, the genetic background of the host, and the growth environment. We demonstrate that while AMR mutations are generally costly in antibiotic-free environments, their fitness effects vary widely and depend on complex interactions between the mutation, genetic background, and environment. We test the ability of the Rough Mount Fuji fitness landscape model to reproduce the empirical data in simulation. We identify model parameters that reasonably capture the variation in fitness effects due to genetic variation. However, the model fails to accommodate the observed variation when considering multiple growth environments. Overall, this study reveals a wealth of variation in the fitness effects of resistance mutations owing to genetic background and environmental conditions, that will ultimately impact their persistence in natural populations.

Rapid adaptation of recombining populations on tunable fitness landscapes

How does standing genetic variation affect polygenic adaptation in recombining populations? Despite a large body of work in quantitative genetics, epistatic and weak additive fitness effects among simultaneously segregating genetic variants are difficult to capture experimentally or to predict theoretically. In this study, we simulated adaptation on fitness landscapes with tunable ruggedness driven by standing genetic variation in recombining populations. We confirmed that recombination hinders the movement of a population through a rugged fitness landscape. When surveying the effect of epistasis on the fixation of alleles, we found that the combined effects of high ruggedness and high recombination probabilities lead to preferential fixation of alleles that had a high initial frequency. This indicates that positive epistatic alleles escape from being broken down by recombination when they start at high frequency. We further extract direct selection coefficients and pairwise epistasis along the adaptive path. When taking the final fixed genotype as the reference genetic background, we observe that, along the adaptive path, beneficial direct selection appears stronger and pairwise epistasis weaker than in the underlying fitness landscape. Quantitatively, the ratio of epistasis and direct selection is smaller along the adaptive path (≈ 1 ) than expected. Thus, adaptation on a rugged fitness landscape may lead to spurious signals of direct selection generated through epistasis. Our study highlights how the interplay of epistasis and recombination constrains the adaptation of a diverse population to a new environment.

Dominance and multi-locus interaction

Dominance is usually considered a constant value that describes the relative difference in fitness or phenotype between heterozygotes and the average of homozygotes at a focal polymorphic locus. However, the observed dominance can vary with the genetic background of the focal locus. Here, alleles at other loci modify the observed phenotype through position effects or dominance modifiers that are sometimes associated with pathogen resistance, lineage, sex, or mating type. Theoretical models have illustrated how variable dominance appears in the context of multi-locus interaction (epistasis). Here, we review empirical evidence for variable dominance and how the observed patterns may be captured by proposed epistatic models. We highlight how integrating epistasis and dominance is crucial for comprehensively understanding adaptation and speciation.

In search of the Goldilocks zone for hybrid speciation II: hard times for hybrid speciation?

Hybridization opens a unique window for observing speciation mechanisms and is a potential engine of speciation. One controversially discussed outcome of hybridization is homoploid hybrid speciation by reciprocal sorting, where a hybrid population maintains a mixed combination of the parental genetic incompatibilities, preventing further gene exchange between the newly formed population and the two parental sources. Previous work showed that, for specific linkage architectures (i.e., the genomic location and order of hybrid incompatibilities), reciprocal sorting could reliably result in hybrid speciation. Yet, the sorting of incompatibilities creates a risk of population extinction. To understand how the demographic consequences of the purging of incompatibilities interact with the formation of a hybrid species, we model an isolated hybrid population resulting from a single admixture event. We study how population size, linkage architecture, and the strength of the incompatibility affect survival of the hybrid population, resolution/purging of the genetic incompatibilities and the probability of observing hybrid speciation. We demonstrate that the extinction risk is highest for intermediately strong hybrid incompatibilities. In addition, the linkage architecture displaying the highest hybrid speciation probabilities changes drastically with population size. Overall, this indicates that population dynamics can strongly affect the outcome of hybridization and the hybrid speciation probability.

Solving the stochastic dynamics of population growth

Population growth is a fundamental process in ecology and evolution. The population size dynamics during growth are often described by deterministic equations derived from kinetic models. Here, we simulate several population growth models and compare the size averaged over many stochastic realizations with the deterministic predictions. We show that these deterministic equations are generically bad predictors of the average stochastic population dynamics. Specifically, deterministic predictions overestimate the simulated population sizes, especially those of populations starting with a small number of individuals. Describing population growth as a stochastic birth process, we prove that the discrepancy between deterministic predictions and simulated data is due to unclosed-moment dynamics. In other words, the deterministic approach does not consider the variability of birth times, which is particularly important with small population sizes. We show that some moment-closure approximations describe the growth dynamics better than the deterministic prediction. However, they do not reduce the error satisfactorily and only apply to some population growth models. We explicitly solve the stochastic growth dynamics, and our solution applies to any population growth model. We show that our solution exactly quantifies the dynamics of a community composed of different strains and correctly predicts the fixation probability of a strain in a serial dilution experiment. Our work sets the foundations for a more faithful modeling of community and population dynamics. It will allow the development of new tools for a more accurate analysis of experimental and empirical results, including the inference of important growth parameters.

In search of the Goldilocks zone for hybrid speciation II: hard times for hybrid speciation?

Hybridization opens a unique window for observing speciation mechanisms and is a potential engine of speciation. One controversially discussed outcome of hybridization is homoploid hybrid speciation by reciprocal sorting, where a hybrid population maintains a mixed combination of the parental genetic incompatibilities, preventing further gene exchange between the newly formed population and the two parental sources. Previous work showed that, for specific linkage architectures (i.e., the genomic location and order of hybrid incompatibilities), reciprocal sorting could reliably result in hybrid speciation. Yet, the sorting of incompatibilities creates a risk of population extinction. To understand how demographic consequences of the purging of incompatibilities interact with the formation of a hybrid species, we model an isolated hybrid population resulting from a single admixture event. We study how population size, linkage architecture and the strength of the incompatibility affect survival of the hybrid population, resolution/purging of the genetic incompatibilities and the probability of observing hybrid speciation. We demonstrate that the extinction risk is highest for intermediately strong hybrid incompatibilities. In addition, the linkage architecture displaying the highest hybrid speciation probabilities changes drastically with population size. Overall, this indicates that population dynamics can strongly affect the outcome of hybridization and the hybrid speciation probability.

Evolutionary rescue in a fluctuating environment: periodic versus quasi-periodic environmental changes

No environment is constant over time, and environmental fluctuations impact the outcome of evolutionary dynamics. Survival of a population not adapted to some environmental conditions is threatened unless, for example, a mutation rescues it, an eco-evolutionary process termed evolutionary rescue. We here investigate evolutionary rescue in an environment that fluctuates between a favourable state, in which the population grows, and a harsh state, in which the population declines. We develop a stochastic model that includes both population dynamics and genetics. We derive analytical predictions for the mean extinction time of a non-adapted population given that it is not rescued, the probability of rescue by a mutation, and the mean appearance time of a rescue mutant, which we validate using numerical simulations. We find that stochastic environmental fluctuations, resulting in quasi-periodic environmental changes, accelerate extinction and hinder evolutionary rescue compared with deterministic environmental fluctuations, resulting in periodic environmental changes. We demonstrate that high equilibrium population sizes and per capita growth rates maximize the chances of evolutionary rescue. We show that an imperfectly harsh environment, which does not fully prevent births but makes the death rate to birth rate ratio much greater than unity, has almost the same rescue probability as a perfectly harsh environment, which fully prevents births. Finally, we put our results in the context of antimicrobial resistance and conservation biology.

Epistasis decreases with increasing antibiotic pressure but not temperature

Predicting mutational effects is essential for the control of antibiotic resistance (ABR). Predictions are difficult when there are strong genotype-by-environment (G × E), gene-by-gene (G × G or epistatic) or gene-by-gene-by-environment (G × G × E) interactions. We quantified G × G × E effects in Escherichia coli across environmental gradients. We created intergenic fitness landscapes using gene knock-outs and single-nucleotide ABR mutations previously identified to vary in the extent of G × E effects in our environments of interest. Then, we measured competitive fitness across a complete combinatorial set of temperature and antibiotic dosage gradients. In this way, we assessed the predictability of 15 fitness landscapes across 12 different but related environments. We found G × G interactions and rugged fitness landscapes in the absence of antibiotic, but as antibiotic concentration increased, the fitness effects of ABR genotypes quickly overshadowed those of gene knock-outs, and the landscapes became smoother. Our work reiterates that some single mutants, like those conferring resistance or susceptibility to antibiotics, have consistent effects across genetic backgrounds in stressful environments. Thus, although epistasis may reduce the predictability of evolution in benign environments, evolution may be more predictable in adverse environments. This article is part of the theme issue 'Interdisciplinary approaches to predicting evolutionary biology'.

Metagenomics and metabarcoding experimental choices and their impact on microbial community characterization in freshwater recirculating aquaculture systems

BACKGROUND

Microbial communities in recirculating aquaculture systems (RAS) play a role in system success, nutrient cycling, and water quality. Considering the increasing socio-economic role of fish farming, e.g., regarding food security, an in-depth understanding of aquaculture microbial communities is also relevant from a management perspective, especially regarding the growth, development, and welfare of the farmed animal. However, the current data on the composition of microbial communities within RAS is patchy, which is partly attributable to diverging method choices that render comparative analyses challenging. Therefore, there is a need for accurate, standardized, and user-friendly methods to study microbial communities in aquaculture systems.

RESULTS

We compared sequencing approach performances (3 types of 16S short amplicon sequencing, PacBio long-read amplicon sequencing, and amplification-free shotgun metagenomics) in the characterization of microbial communities in two commercial RAS fish farms. Results showed that 16S primer choice and amplicon length affect some values (e.g., diversity measures, number of assigned taxa or distinguishing ASVs) but have no impact on spatio-temporal patterns between sample types, farms and time points. This implies that 16S rRNA approaches are adequate for community studies. The long-read amplicons underperformed regarding the quantitative resolution of spatio-temporal patterns but were suited to identify functional services, e.g., nitrification cycling and the detection of pathogens. Finally, shotgun metagenomics extended the picture to fungi, viruses, and bacteriophages, opening avenues for exploring inter-domain interactions. All sequencing datasets agreed on major prokaryotic players, such as Actinobacteriota, Bacteroidota, Nitrospirota, and Proteobacteria.

CONCLUSION

The different sequencing approaches yielded overlapping and highly complementary results, with each contributing unique data not obtainable with the other approaches. We conclude that a tiered approach constitutes a strategy for obtaining the maximum amount of information on aquaculture microbial communities and can inform basic research on community evolution dynamics. For specific and/or applied questions, single-method approaches are more practical and cost-effective and could lead to better farm management practices.

Towards evolutionary predictions: Current promises and challenges

Evolution has traditionally been a historical and descriptive science, and predicting future evolutionary processes has long been considered impossible. However, evolutionary predictions are increasingly being developed and used in medicine, agriculture, biotechnology and conservation biology. Evolutionary predictions may be used for different purposes, such as to prepare for the future, to try and change the course of evolution or to determine how well we understand evolutionary processes. Similarly, the exact aspect of the evolved population that we want to predict may also differ. For example, we could try to predict which genotype will dominate, the fitness of the population or the extinction probability of a population. In addition, there are many uses of evolutionary predictions that may not always be recognized as such. The main goal of this review is to increase awareness of methods and data in different research fields by showing the breadth of situations in which evolutionary predictions are made. We describe how diverse evolutionary predictions share a common structure described by the predictive scope, time scale and precision. Then, by using examples ranging from SARS-CoV2 and influenza to CRISPR-based gene drives and sustainable product formation in biotechnology, we discuss the methods for predicting evolution, the factors that affect predictability and how predictions can be used to prevent evolution in undesirable directions or to promote beneficial evolution (i.e. evolutionary control). We hope that this review will stimulate collaboration between fields by establishing a common language for evolutionary predictions.

The extinction time under mutational meltdown driven by high mutation rates

Mutational meltdown describes an eco‐evolutionary process in which the accumulation of deleterious mutations causes a fitness decline that eventually leads to the extinction of a population. Possible applications of this concept include medical treatment of RNA virus infections based on mutagenic drugs that increase the mutation rate of the pathogen. To determine the usefulness and expected success of such an antiviral treatment, estimates of the expected time to mutational meltdown are necessary. Here, we compute the extinction time of a population under high mutation rates, using both analytical approaches and stochastic simulations. Extinction is the result of three consecutive processes: (a) initial accumulation of deleterious mutations due to the increased mutation pressure; (b) consecutive loss of the fittest haplotype due to Muller's ratchet; (c) rapid population decline toward extinction. We find accurate analytical results for the mean extinction time, which show that the deleterious mutation rate has the strongest effect on the extinction time. We confirm that intermediate‐sized deleterious selection coefficients minimize the extinction time. Finally, our simulations show that the variation in extinction time, given a set of parameters, is surprisingly small.

The Adaptive Potential of the Middle Domain of Yeast Hsp90

The distribution of fitness effects (DFEs) of new mutations across different environments quantifies the potential for adaptation in a given environment and its cost in others. So far, results regarding the cost of adaptation across environments have been mixed, and most studies have sampled random mutations across different genes. Here, we quantify systematically how costs of adaptation vary along a large stretch of protein sequence by studying the distribution of fitness effects of the same ≈2,300 amino-acid changing mutations obtained from deep mutational scanning of 119 amino acids in the middle domain of the heat shock protein Hsp90 in five environments. This region is known to be important for client binding, stabilization of the Hsp90 dimer, stabilization of the N-terminal-Middle and Middle-C-terminal interdomains, and regulation of ATPase–chaperone activity. Interestingly, we find that fitness correlates well across diverse stressful environments, with the exception of one environment, diamide. Consistent with this result, we find little cost of adaptation; on average only one in seven beneficial mutations is deleterious in another environment. We identify a hotspot of beneficial mutations in a region of the protein that is located within an allosteric center. The identified protein regions that are enriched in beneficial, deleterious, and costly mutations coincide with residues that are involved in the stabilization of Hsp90 interdomains and stabilization of client-binding interfaces, or residues that are involved in ATPase–chaperone activity of Hsp90. Thus, our study yields information regarding the role and adaptive potential of a protein sequence that complements and extends known structural information.

Patterns of selection against centrosome amplification in human cell lines

The presence of extra centrioles, termed centrosome amplification, is a hallmark of cancer. The distribution of centriole numbers within a cancer cell population appears to be at an equilibrium maintained by centriole overproduction and selection, reminiscent of mutation-selection balance. It is unknown to date if the interaction between centriole overproduction and selection can quantitatively explain the intra- and inter-population heterogeneity in centriole numbers. Here, we define mutation-selection-like models and employ a model selection approach to infer patterns of centriole overproduction and selection in a diverse panel of human cell lines. Surprisingly, we infer strong and uniform selection against any number of extra centrioles in most cell lines. Finally we assess the accuracy and precision of our inference method and find that it increases non-linearly as a function of the number of sampled cells. We discuss the biological implications of our results and how our methodology can inform future experiments.

Homage to Felsenstein 1981, or why are there so few/many species?

If there are no constraints on the process of speciation, then the number of species might be expected to match the number of available niches and this number might be indefinitely large. One possible constraint is the opportunity for allopatric divergence. In 1981, Felsenstein used a simple and elegant model to ask if there might also be genetic constraints. He showed that progress towards speciation could be described by the build-up of linkage disequilibrium among divergently selected loci and between these loci and those contributing to other forms of reproductive isolation. Therefore, speciation is opposed by recombination, because it tends to break down linkage disequilibria. Felsenstein then introduced a crucial distinction between "two-allele" models, which are subject to this effect, and "one-allele" models, which are free from the recombination constraint. These fundamentally important insights have been the foundation for both empirical and theoretical studies of speciation ever since.

Deleterious mutation accumulation and the long-term fate of chromosomal inversions

Chromosomal inversions contribute widely to adaptation and speciation, yet they present a unique evolutionary puzzle as both their allelic content and frequency evolve in a feedback loop. In this simulation study, we quantified the role of the allelic content in determining the long-term fate of the inversion. Recessive deleterious mutations accumulated on both arrangements with most of them being private to a given arrangement. This led to increasing overdominance, allowing for the maintenance of the inversion polymorphism and generating strong non-adaptive divergence between arrangements. The accumulation of mutations was mitigated by gene conversion but nevertheless led to the fitness decline of at least one homokaryotype under all considered conditions. Surprisingly, this fitness degradation could be permanently halted by the branching of an arrangement into multiple highly divergent haplotypes. Our results highlight the dynamic features of inversions by showing how the non-adaptive evolution of allelic content can play a major role in the fate of the inversion.

The limits to parapatric speciation 3: evolution of strong reproductive isolation in presence of gene flow despite limited ecological differentiation

Gene flow tends to impede the accumulation of genetic divergence. Here, we determine the limits for the evolution of postzygotic reproductive isolation in a model of two populations that are connected by gene flow. We consider two selective mechanisms for the creation and maintenance of a genetic barrier: local adaptation leads to divergence among incipient species due to selection against migrants, and Dobzhansky–Muller incompatibilities (DMIs) reinforce the genetic barrier through selection against hybrids. In particular, we are interested in the maximum strength of the barrier under a limited amount of local adaptation, a challenge that many incipient species may initially face. We first confirm that with classical two-locus DMIs, the maximum amount of local adaptation is indeed a limit to the strength of a genetic barrier. However, with three or more loci and cryptic epistasis, this limit holds no longer. In particular, we identify a minimal configuration of three epistatically interacting mutations that is sufficient to confer strong reproductive isolation.

This article is part of the theme issue ‘Towards the completion of speciation: the evolution of reproductive isolation beyond the first barriers’.

Low mutational load and high mutation rate variation in gut commensal bacteria

Bacteria generally live in species-rich communities, such as the gut microbiota. Yet little is known about bacterial evolution in natural ecosystems. Here, we followed the long-term evolution of commensal Escherichia coli in the mouse gut. We observe the emergence of mutation rate polymorphism, ranging from wild-type levels to 1,000-fold higher. By combining experiments, whole-genome sequencing, and in silico simulations, we identify the molecular causes and explore the evolutionary conditions allowing these hypermutators to emerge and coexist within the microbiota. The hypermutator phenotype is caused by mutations in DNA polymerase III proofreading and catalytic subunits, which increase mutation rate by approximately 1,000-fold and stabilise hypermutator fitness, respectively. Strong mutation rate variation persists for >1,000 generations, with coexistence between lineages carrying 4 to >600 mutations. The in vivo molecular evolution pattern is consistent with fitness effects of deleterious mutations s_d ≤ 10⁻⁴/generation, assuming a constant effect or exponentially distributed effects with a constant mean. Such effects are lower than typical in vitro estimates, leading to a low mutational load, an inference that is observed in in vivo and in vitro competitions. Despite large numbers of deleterious mutations, we identify multiple beneficial mutations that do not reach fixation over long periods of time. This indicates that the dynamics of beneficial mutations are not shaped by constant positive Darwinian selection but could be explained by other evolutionary mechanisms that maintain genetic diversity. Thus, microbial evolution in the gut is likely characterised by partial sweeps of beneficial mutations combined with hitchhiking of slightly deleterious mutations, which take a long time to be purged because they impose a low mutational load. The combination of these two processes could allow for the long-term maintenance of intraspecies genetic diversity, including mutation rate polymorphism. These results are consistent with the pattern of genetic polymorphism that is emerging from metagenomics studies of the human gut microbiota, suggesting that we have identified key evolutionary processes shaping the genetic composition of this community.

Weak-effect deleterious mutations and negative frequency–dependent selection, acting on beneficial mutations, shape the dynamics of molecular evolution within the mouse gut microbiota.

Comprehensive fitness maps of Hsp90 show widespread environmental dependence

Gene-environment interactions have long been theorized to influence molecular evolution. However, the environmental dependence of most mutations remains unknown. Using deep mutational scanning, we engineered yeast with all 44,604 single codon changes encoding 14,160 amino acid variants in Hsp90 and quantified growth effects under standard conditions and under five stress conditions. To our knowledge, these are the largest determined comprehensive fitness maps of point mutants. The growth of many variants differed between conditions, indicating that environment can have a large impact on Hsp90 evolution. Multiple variants provided growth advantages under individual conditions; however, these variants tended to exhibit growth defects in other environments. The diversity of Hsp90 sequences observed in extant eukaryotes preferentially contains variants that supported robust growth under all tested conditions. Rather than favoring substitutions in individual conditions, the long-term selective pressure on Hsp90 may have been that of fluctuating environments, leading to robustness under a variety of conditions.

Renal control of disease tolerance to malaria

Malaria, the disease caused by Plasmodium spp. infection, remains a major global cause of morbidity and mortality. Host protection from malaria relies on immune-driven resistance mechanisms that kill Plasmodium However, these mechanisms are not sufficient per se to avoid the development of severe forms of disease. This is accomplished instead via the establishment of disease tolerance to malaria, a defense strategy that does not target Plasmodium directly. Here we demonstrate that the establishment of disease tolerance to malaria relies on a tissue damage-control mechanism that operates specifically in renal proximal tubule epithelial cells (RPTEC). This protective response relies on the induction of heme oxygenase-1 (HMOX1; HO-1) and ferritin H chain (FTH) via a mechanism that involves the transcription-factor nuclear-factor E2-related factor-2 (NRF2). As it accumulates in plasma and urine during the blood stage of Plasmodium infection, labile heme is detoxified in RPTEC by HO-1 and FTH, preventing the development of acute kidney injury, a clinical hallmark of severe malaria.

Conflict between heterozygote advantage and hybrid incompatibility in haplodiploids (and sex chromosomes)

In many diploid species, the sex chromosomes play a special role in mediating reproductive isolation. In haplodiploids, where females are diploid and males haploid, the whole genome behaves similarly to the X/Z chromosomes of diploids. Therefore, haplodiploid systems can serve as a model for the role of sex chromosomes in speciation and hybridization. A previously described population of Finnish Formica wood ants displays genome-wide signs of ploidally and sexually antagonistic selection resulting from hybridization. Here, hybrid females have increased survivorship but hybrid males are inviable. To understand how the unusual hybrid population may be maintained, we developed a mathematical model with hybrid incompatibility, female heterozygote advantage, recombination and assortative mating. The rugged fitness landscape resulting from the co-occurrence of heterozygote advantage and hybrid incompatibility results in a sexual conflict in haplodiploids, which is caused by the ploidy difference. Thus, whereas heterozygote advantage always promotes long-term polymorphism in diploids, we find various outcomes in haplodiploids in which the population stabilizes either in favour of males, females or via maximizing the number of introgressed individuals. We discuss these outcomes with respect to the potential long-term fate of the Finnish wood ant population and provide approximations for the extension of the model to multiple incompatibilities. Moreover, we highlight the general implications of our results for speciation and hybridization in haplodiploids versus diploids and how the described fitness relationships could contribute to the outstanding role of sex chromosomes as hotspots of sexual antagonism and genes involved in speciation.

The Combined Effect of Oseltamivir and Favipiravir on Influenza A Virus Evolution

Influenza virus inflicts a heavy death toll annually and resistance to existing antiviral drugs has generated interest in the development of agents with novel mechanisms of action. Favipiravir is an antiviral drug that acts by increasing the genome-wide mutation rate of influenza A virus (IAV). Potential synergistic benefits of combining oseltamivir and favipiravir have been demonstrated in animal models of influenza, but the population-level effects of combining the drugs are unknown. In order to elucidate the underlying evolutionary processes at play, we performed genome-wide sequencing of IAV experimental populations subjected to serial passaging in vitro under a combined protocol of oseltamivir and favipiravir. We describe the interplay between mutation, selection, and genetic drift that ultimately culminates in population extinction. In particular, selective sweeps around oseltamivir resistance mutations reduce genome-wide variation while deleterious mutations hitchhike to fixation given the increased mutational load generated by favipiravir. This latter effect reduces viral fitness and accelerates extinction compared with IAV populations treated with favipiravir alone, but risks spreading both established and newly emerging mutations, including possible drug resistance mutations, if transmission occurs before the viral populations are eradicated.

Two sides of the same coin: A population genetics perspective on lethal mutagenesis and mutational meltdown

The extinction of RNA virus populations upon application of a mutagenic drug is frequently referred to as evidence for the existence of an error threshold, above which the population cannot sustain the mutational load. To explain the extinction process after reaching this threshold, models of lethal mutagenesis have been proposed, in which extinction is described as a deterministic (and thus population size-independent) process. As a separate body of literature, the population genetics community has developed models of mutational meltdown, which focus on the stochastic (and thus population-size dependent) processes governing extinction. However, recent extensions of both models have blurred these boundaries. Here, we first clarify definitions in terms of assumptions, expectations, and relevant parameter spaces, and then assess similarities and differences. As concepts from both fields converge, we argue for a unified theoretical framework that is focused on the evolutionary processes at play, rather than dispute over terminology.

An experimental evaluation of drug-induced mutational meltdown as an antiviral treatment strategy

The rapid evolution of drug resistance remains a critical public health concern. The treatment of influenza A virus (IAV) has proven particularly challenging, due to the ability of the virus to develop resistance against current antivirals and vaccines. Here, we evaluate a novel antiviral drug therapy, favipiravir, for which the mechanism of action in IAV involves an interaction with the viral RNA-dependent RNA polymerase resulting in an effective increase in the viral mutation rate. We used an experimental evolution framework, combined with novel population genetic method development for inference from time-sampled data, to evaluate the effectiveness of favipiravir against IAV. Evaluating whole genome polymorphism data across 15 time points under multiple drug concentrations and in controls, we present the first evidence for the ability of IAV populations to effectively adapt to low concentrations of favipiravir. In contrast, under high concentrations, we observe population extinction, indicative of mutational meltdown. We discuss the observed dynamics with respect to the evolutionary forces at play and emphasize the utility of evolutionary theory to inform drug development.

Thinking too positive? Revisiting current methods of population genetic selection inference

In the age of next-generation sequencing, the availability of increasing amounts and improved quality of data at decreasing cost ought to allow for a better understanding of how natural selection is shaping the genome than ever before. However, alternative forces, such as demography and background selection (BGS), obscure the footprints of positive selection that we would like to identify. In this review, we illustrate recent developments in this area, and outline a roadmap for improved selection inference. We argue (i) that the development and obligatory use of advanced simulation tools is necessary for improved identification of selected loci, (ii) that genomic information from multiple time points will enhance the power of inference, and (iii) that results from experimental evolution should be utilized to better inform population genomic studies.

A systematic survey of an intragenic epistatic landscape

Mutations are the source of evolutionary variation. The interactions of multiple mutations can have important effects on fitness and evolutionary trajectories. We have recently described the distribution of fitness effects of all single mutations for a nine-amino-acid region of yeast Hsp90 (Hsp82) implicated in substrate binding. Here, we report and discuss the distribution of intragenic epistatic effects within this region in seven Hsp90 point mutant backgrounds of neutral to slightly deleterious effect, resulting in an analysis of more than 1,000 double mutants. We find negative epistasis between substitutions to be common, and positive epistasis to be rare--resulting in a pattern that indicates a drastic change in the distribution of fitness effects one step away from the wild type. This can be well explained by a concave relationship between phenotype and genotype (i.e., a concave shape of the local fitness landscape), suggesting mutational robustness intrinsic to the local sequence space. Structural analyses indicate that, in this region, epistatic effects are most pronounced when a solvent-inaccessible position is involved in the interaction. In contrast, all 18 observations of positive epistasis involved at least one mutation at a solvent-exposed position. By combining the analysis of evolutionary and biophysical properties of an epistatic landscape, these results contribute to a more detailed understanding of the complexity of protein evolution.

Genomics and the origin of species

Speciation is a fundamental evolutionary process, the knowledge of which is crucial for understanding the origins of biodiversity. Genomic approaches are an increasingly important aspect of this research field. We review current understanding of genome-wide effects of accumulating reproductive isolation and of genomic properties that influence the process of speciation. Building on this work, we identify emergent trends and gaps in our understanding, propose new approaches to more fully integrate genomics into speciation research, translate speciation theory into hypotheses that are testable using genomic tools and provide an integrative definition of the field of speciation genomics.

Influenza virus drug resistance: a time-sampled population genetics perspective

The challenge of distinguishing genetic drift from selection remains a central focus of population genetics. Time-sampled data may provide a powerful tool for distinguishing these processes, and we here propose approximate Bayesian, maximum likelihood, and analytical methods for the inference of demography and selection from time course data. Utilizing these novel statistical and computational tools, we evaluate whole-genome datasets of an influenza A H1N1 strain in the presence and absence of oseltamivir (an inhibitor of neuraminidase) collected at thirteen time points. Results reveal a striking consistency amongst the three estimation procedures developed, showing strongly increased selection pressure in the presence of drug treatment. Importantly, these approaches re-identify the known oseltamivir resistance site, successfully validating the approaches used. Enticingly, a number of previously unknown variants have also been identified as being positively selected. Results are interpreted in the light of Fisher's Geometric Model, allowing for a quantification of the increased distance to optimum exerted by the presence of drug, and theoretical predictions regarding the distribution of beneficial fitness effects of contending mutations are empirically tested. Further, given the fit to expectations of the Geometric Model, results suggest the ability to predict certain aspects of viral evolution in response to changing host environments and novel selective pressures.

Shifting fitness landscapes in response to altered environments

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

Can reinforcement complete speciation?

Hybridization is common in nature, even between "good" species. This observation poses the question of why reinforcement is not always successful in leading to the evolution of complete reproductive isolation. To study this question, we developed a new "quasi-linkage disequilibrium" (QLD) approximation to obtain the first analytic results for the evolution of modifiers that increase mate discrimination against hybrids and heterospecifics. When such modifiers have small effects, they evolve more readily under a one-allele than a two-allele mechanism (sensu Felsenstein 1981). The strength of selection on the modifier decreases as hybrids decrease in frequency, and so further reinforcement may not occur once hybridization is sufficiently rare. The outcome is qualitatively different when modifiers have large effects, however, for example, when a single mutation can cause complete reproductive isolation. In this case, modifiers in a two-allele mechanism can be selected as or more strongly than those in a one-allele mechanism. Furthermore, they can spread under quite general conditions. Thus, whether complete closure of genetic introgression by reinforcement occurs may depend on the size of effects that mutations have on the sensory systems used in mate choice.

Multiple deletions of mtDNA remove the light strand origin of replication

Idiopathic inflammatory myopathies are progressive, debilitating muscle diseases. The pathogenesis of these disorders is multifactorial and appears to include mutations of the mitochondrial genome, which are usually indicated by morphological changes of mitochondria. The vast majority of all mitochondrial DNA deletions found are located between the origins of replication in the "major region" between nt5760-nt190. Using long distance PCR and sequencing techniques, we detected deletions which were unusually large (ca. 10500-12800 bp) and show uncommon 5'-breakpoints between nt800 and nt3326. Unlike most other deletions, their breakpoints are far upstream of the "major region." The atypical location of these deletions suggests a different pathomechanism. The impact of the mitochondrial DNA deletions in the pathogenetic cascade remains uncertain.

A new development in haematological cell counting: the Sysmex NE-8000, automaton for cell count and physical five-part leukocyte differentiation

We compared the results of the Sysmex NE-8000 with those of the Sysmex E-4000 and the Technicon H-6000. Both for the whole blood cell count and the leukocyte differentiation we obtained intra- and inter-assay coefficients of variation fully comparable with those for other cell counters. The carry-over between samples was negligibly small. The linearity range was broad, which implies a universal application in routine haematological analysis. The numerical results from the Sysmex NE-8000 and the Technicon H-6000 corresponded closely, with exception of the mean corpuscular volume and the haematocrit, whereas these parameters showed excellent agreement between the NE-8000 and the E-4000. In the differentiation of leukocytes, the NE-8000 and H-6000 showed good correlation and conformity for lymphocytes, neutrophils and eosinophils; for monocytes and basophils the conformity was poor. We also found a good correlation between the NE-8000 and E-4000 for lymphocytes and neutrophils, whereas the correlation was less for the middle cell ratio and the sum of monocytes, eosinophils and basophils. Furthermore, we compared Receiver Operating Characteristic curves for the different leukocyte subtypes on the NE-8000, the H-6000 and the E-4000, and investigated the flagging frequency in inpatients, outpatients and blood donors.