Experimental evolution and the dynamics of genomic mutation rate modifiers

Genome wide analyses reveal the role of mutator phenotypes in Mycobacterium tuberculosis drug resistance emergence

Antimicrobial combination therapy is widely used to combat Mycobacterium tuberculosis (Mtb), yet resistance rates continue to rise. Mutator strains, with defects in DNA repair genes, drive resistance in other bacterial infections, but their role in Mtb remains unclear. Here, we study the contribution of single nucleotide polymorphisms (SNPs) in DNA Repair, Replication, and Recombination (3 R) genes to Mtb resistance. Through large-scale bioinformatics analysis of 53,589 whole-genomes, we identified 18 novel SNPs in lineages 2 and 4 linked to genotypic drug resistance in 3 R genes, covering 12.5% of clinical isolates with available genome sequences. Notably, a number of the detected SNPs were positively selected during Mtb evolution. Experimental tests showed that mutM, fpgg2, xthA, and nucS mutants had increased the mutation frequency compared to the wild type. Our findings highlight the role of 3 R gene mutations in resistance, emphasizing the need for surveillance to improve early detection and control strategies.

Quantitative analysis of relationship between mutation rate and speed of adaptation under antibiotic exposure in Escherichia coli

Mutations are the ultimate source of biological evolution that creates genetic variation in populations. Mutations can create new advantageous traits but can also potentially interfere with pre-existing organismal functions. Therefore, organisms may have evolved mutation rates to appropriate levels to maintain or improve their fitness. In this study, we aimed to experimentally quantify the relationship between the mutation rate and evolution of antibiotic resistance. We conducted an evolution experiment using 12 Escherichia coli mutator strains with increased mutation rates and five antibiotics. Our results demonstrated that the rate of adaptation generally increased with higher mutation rates, except in a single mutator strain with the highest mutation rate, which exhibited a significant decline in evolutionary speed. To further elucidate these findings, we developed a simple population dynamics model that successfully recapitulated the observed dependence of adaptation speed on mutation rate. These findings provide important insights into the evolution of mutation rate accompanied by the evolution.

Non-hypermutator cancers access driver mutations through reversals in germline mutational bias

Cancer is an evolutionary disease driven by mutations in asexually-reproducing somatic cells. In asexual microbes, bias reversals in the mutation spectrum can speed adaptation by increasing access to previously undersampled beneficial mutations. By analyzing tumors from 20 tissues, along with normal tissue and the germline, we demonstrate this effect in cancer. Non-hypermutated tumors reverse the germline mutation bias and have consistent spectra across tissues. These spectra changes carry the signature of hypoxia, and they facilitate positive selection in cancer genes. Hypermutated and non-hypermutated tumors thus acquire driver mutations differently: hypermutated tumors by higher mutation rates and non-hypermutated tumors by changing the mutation spectrum to reverse the germline mutation bias.

The divergence of mutation rates and spectra across the Tree of Life

Owing to advances in genome sequencing, genome stability has become one of the most scrutinized cellular traits across the Tree of Life. Despite its centrality to all things biological, the mutation rate (per nucleotide site per generation) ranges over three orders of magnitude among species and several-fold within individual phylogenetic lineages. Within all major organismal groups, mutation rates scale negatively with the effective population size of a species and with the amount of functional DNA in the genome. This relationship is most parsimoniously explained by the drift-barrier hypothesis, which postulates that natural selection typically operates to reduce mutation rates until further improvement is thwarted by the power of random genetic drift. Despite this constraint, the molecular mechanisms underlying DNA replication fidelity and repair are free to wander, provided the performance of the entire system is maintained at the prevailing level. The evolutionary flexibility of the mutation rate bears on the resolution of several prior conundrums in phylogenetic and population-genetic analysis and raises challenges for future applications in these areas.

Revisiting the Role of Genetic Variation in Adaptation

AbstractEvolutionary biologists have thought about the role of genetic variation during adaptation for a very long time-before we understood the organization of the genetic code, the provenance of genetic variation, and how such variation influenced the phenotypes on which natural selection acts. Half a century after the discovery of the structure of DNA and the unraveling of the genetic code, we have a rich understanding of these problems and the means to both delve deeper and widen our perspective across organisms and natural populations. The 2022 Vice Presidential Symposium of the American Society of Naturalists highlighted examples of recent insights into the role of genetic variation in adaptive processes, which are compiled in this special section. The work was conducted in different parts of the world, included theoretical and empirical studies with diverse organisms, and addressed distinct aspects of how genetic variation influences adaptation. In our introductory article to the special section, we discuss some important recent insights about the generation and maintenance of genetic variation, its impacts on phenotype and fitness, its fate in natural populations, and its role in driving adaptation. By placing the special section articles in the broader context of recent developments, we hope that this overview will also serve as a useful introduction to the field.

Parallel evolution in Crassostrea oysters along the latitudinal gradient is associated with variation in multiple genes involved in adipogenesis

Parallel diversification provides a proper framework for studying the role of natural selection in evolution. Yet, empirical studies from ecological 'non-model' species of invertebrates are limited at the whole genome level. Here, we presented a chromosome-scale genome assembly for Crassostrea angulata and investigated the parallel genomic evolution in oysters. Specifically, we used population genomics approaches to compare two southern-northern oyster species pairs (C. angulata-C. gigas and southern-northern C. ariakensis) along the coast of China. The estimated divergence time of C. angulata and C. gigas is earlier than that of southern and northern C. ariakensis, which aligns with the overall elevated genome-wide divergence. However, the southern-northern C. ariakensis FST profile represented more extremely divergent "islands". Combined with recent reciprocal hybridization studies, we proposed that they are currently at an early stage of speciation. These two southern-northern oyster species pairs exhibited significant repeatability in patterns of genome-wide differentiation, especially in genomic regions with extremely high and low divergence. This suggested that divergent and purifying selection has contributed to the genomic parallelism between southern and northern latitudes. Top differentiated genomic regions shared in these two oyster species pairs contained candidate genes enriched for functions in energy metabolism, especially adipogenesis, which are closely related to reproductive behaviours. These genes might be good candidates for further investigation in vivo. In conclusion, our results suggest that similar divergent selection and shared genomic features could predictably transform standing genetic variation within one species pair into differences in another.

Shifts in mutation spectra enhance access to beneficial mutations

Biased mutation spectra are pervasive, with wide variation in the magnitude of mutational biases that influence genome evolution and adaptation. How do such diverse biases evolve? Our experiments show that changing the mutation spectrum allows populations to sample previously undersampled mutational space, including beneficial mutations. The resulting shift in the distribution of fitness effects is advantageous: Beneficial mutation supply and beneficial pleiotropy both increase, while deleterious load reduces. More broadly, simulations indicate that reducing or reversing the direction of a long-term bias is always selectively favored. Such changes in mutation bias can occur easily via altered function of DNA repair genes. A phylogenetic analysis shows that these genes are repeatedly gained and lost in bacterial lineages, leading to frequent bias shifts in opposite directions. Thus, shifts in mutation spectra may evolve under selection and can directly alter the outcome of adaptive evolution by facilitating access to beneficial mutations.

Lanza V, Rodríguez-Beltrán J, Galán JC, San Millán A, Cantón R, Coque TM. Evolutionary Pathways and Trajectories in Antibiotic Resistance

Evolution is the hallmark of life. Descriptions of the evolution of microorganisms have provided a wealth of information, but knowledge regarding "what happened" has precluded a deeper understanding of "how" evolution has proceeded, as in the case of antimicrobial resistance. The difficulty in answering the "how" question lies in the multihierarchical dimensions of evolutionary processes, nested in complex networks, encompassing all units of selection, from genes to communities and ecosystems. At the simplest ontological level (as resistance genes), evolution proceeds by random (mutation and drift) and directional (natural selection) processes; however, sequential pathways of adaptive variation can occasionally be observed, and under fixed circumstances (particular fitness landscapes), evolution is predictable. At the highest level (such as that of plasmids, clones, species, microbiotas), the systems' degrees of freedom increase dramatically, related to the variable dispersal, fragmentation, relatedness, or coalescence of bacterial populations, depending on heterogeneous and changing niches and selective gradients in complex environments. Evolutionary trajectories of antibiotic resistance find their way in these changing landscapes subjected to random variations, becoming highly entropic and therefore unpredictable. However, experimental, phylogenetic, and ecogenetic analyses reveal preferential frequented paths (highways) where antibiotic resistance flows and propagates, allowing some understanding of evolutionary dynamics, modeling and designing interventions. Studies on antibiotic resistance have an applied aspect in improving individual health, One Health, and Global Health, as well as an academic value for understanding evolution. Most importantly, they have a heuristic significance as a model to reduce the negative influence of anthropogenic effects on the environment.

An Escherichia coli FdrA Variant Derived from Syntrophic Coculture with a Methanogen Increases Succinate Production Due to Changes in Allantoin Degradation

Wild-type Escherichia coli was adapted to syntrophic growth with Methanobacterium formicicum for glycerol fermentation over 44 weeks. Succinate production by E. coli started to increase in the early stages of syntrophic growth. Genetic analysis of the cultured E. coli population by pooled sequencing at eight time points suggests that (i) rapid evolution occurred through repeated emergence of mutators that introduced a large number of nucleotide variants and (ii) many mutators increased to high frequencies but remained polymorphic throughout the continuous cultivation. The evolved E. coli populations exhibited gains both in fitness and succinate production, but only for growth under glycerol fermentation with M. formicicum (the condition for this laboratory evolution) and not under other growth conditions. The mutant alleles of the 69 single nucleotide polymorphisms (SNPs) identified in the adapted E. coli populations were constructed individually in the ancestral wild-type E. coli. We analyzed the phenotypic changes caused by 84 variants, including 15 nonsense variants, and found that FdrA_D296Y was the most significant variant leading to increased succinate production. Transcription of fdrA was induced under anaerobic allantoin degradation conditions, and FdrA was shown to play a crucial role in oxamate production. The FdrA_D296Y variant increased glyoxylate conversion to malate by accelerating oxamate production, which promotes carbon flow through the C4 branch, leading to increased succinate production.

IMPORTANCE Here, we demonstrate the ability of E. coli to perform glycerol fermentation in coculture with the methanogen M. formicicum to produce succinate. We found that the production of succinate by E. coli significantly increased during successive cocultivation. Genomic DNA sequencing, evaluation of relative fitness, and construction of SNPs were performed, from which FdrA_D296Y was identified as the most significant variant to enable increased succinate production by E. coli. The function of FdrA is uncertain. In this study, experiments with gene expression assays and metabolic analysis showed for the first time that FdrA could be the “orphan enzyme” oxamate:carbamoyltransferase in anaerobic allantoin degradation. Furthermore, we demonstrate that the anaerobic allantoin degradation pathway is linked to succinate production via the glyoxylate pathway during glycerol fermentation.

Adaptation and genomic erosion in fragmented Pseudomonas aeruginosa populations in the sinuses of people with cystic fibrosis

Pseudomonas aeruginosa notoriously adapts to the airways of people with cystic fibrosis (CF), yet how infection-site biogeography and associated evolutionary processes vary as lifelong infections progress remains unclear. Here we test the hypothesis that early adaptations promoting aggregation influence evolutionary-genetic trajectories by examining longitudinal P. aeruginosa from the sinuses of six adults with CF. Highly host-adapted lineages harbored mutator genotypes displaying signatures of early genome degradation associated with recent host restriction. Using an advanced imaging technique (MiPACT-HCR [microbial identification after passive clarity technique]), we find population structure tracks with genome degradation, with the most host-adapted, genome-degraded P. aeruginosa (the mutators) residing in small, sparse aggregates. We propose that following initial adaptive evolution in larger populations under strong selection for aggregation, P. aeruginosa persists in small, fragmented populations that experience stronger effects of genetic drift. These conditions enrich for mutators and promote degenerative genome evolution. Our findings underscore the importance of infection-site biogeography to pathogen evolution.

Measuring mutagenicity in ecotoxicology: A case study of Cd exposure in Chironomus riparius

Existing mutagenicity tests for metazoans lack the direct observation of enhanced germline mutation rates after exposure to anthropogenic substances, therefore being inefficient. Cadmium (Cd) is a metal described as a mutagen in mammalian cells and listed as a group 1 carcinogenic and mutagenic substance. But Cd mutagenesis mechanism is not yet clear. Therefore, in the present study, we propose a method coupling short-term mutation accumulation (MA) lines with subsequent whole genome sequencing (WGS) and a dedicated data analysis pipeline to investigate if chronic Cd exposure on Chironomus riparius can alter the rate at which de novo point mutations appear. Results show that Cd exposure did not affect the basal germline mutation rate nor the mutational spectrum in C. riparius, thereby arguing that exposed organisms might experience a range of other toxic effects before any mutagenic effect may occur. We show that it is possible to establish a practical and easily implemented pipeline to rapidly detect germ cell mutagens in a metazoan test organism. Furthermore, our data implicate that it is questionable to transfer mutagenicity assessments based on in vitro methods to complex metazoans.

Mechanisms That Shape Microbial Pangenomes

Analyses of multiple whole-genome sequences from the same species have revealed that differences in gene content can be substantial, particularly in prokaryotes. Such variation has led to the recognition of pangenomes, the complete set of genes present in a species - consisting of core genes, present in all individuals, and accessory genes whose presence is variable. Questions now arise about how pangenomes originate and evolve. We describe how gene content variation can arise as a result of the combination of several processes, including random drift, selection, gain/loss balance, and the influence of ecological and epistatic interactions. We believe that identifying the contributions of these processes to pangenomes will need novel theoretical approaches and empirical data.

Evolutionary epidemiology of Streptococcus iniae: Linking mutation rate dynamics with adaptation to novel immunological landscapes

Pathogens continuously adapt to changing host environments where variation in their virulence and antigenicity is critical to their long-term evolutionary success. The emergence of novel variants is accelerated in microbial mutator strains (mutators) deficient in DNA repair genes, most often from mismatch repair and oxidized-guanine repair systems (MMR and OG respectively). Bacterial MMR/OG mutants are abundant in clinical samples and show increased adaptive potential in experimental infection models, yet the role of mutators in the epidemiology and evolution of infectious disease is not well understood. Here we investigated the role of mutation rate dynamics in the evolution of a broad host range pathogen, Streptococcus iniae, using a set of 80 strains isolated globally over 40 years. We have resolved phylogenetic relationships using non-recombinant core genome variants, measured in vivo mutation rates by fluctuation analysis, identified variation in major MMR/OG genes and their regulatory regions, and phenotyped the major traits determining virulence in streptococci. We found that both mutation rate and MMR/OG genotype are remarkably conserved within phylogenetic clades but significantly differ between major phylogenetic lineages. Further, variation in MMR/OG loci correlates with occurrence of atypical virulence-associated phenotypes, infection in atypical hosts (mammals), and atypical (osseous) tissue of a vaccinated primary host. These findings suggest that mutators are likely to facilitate adaptations preceding major diversification events and may promote emergence of variation permitting colonization of a novel host tissue, novel host taxa (host jumps), and immune-escape in the vaccinated host.

Experimental Evolution of Legume Symbionts: What Have We Learnt?

Rhizobia, the nitrogen-fixing symbionts of legumes, are polyphyletic bacteria distributed in many alpha- and beta-proteobacterial genera. They likely emerged and diversified through independent horizontal transfers of key symbiotic genes. To replay the evolution of a new rhizobium genus under laboratory conditions, the symbiotic plasmid of Cupriavidus taiwanensis was introduced in the plant pathogen Ralstonia solanacearum, and the generated proto-rhizobium was submitted to repeated inoculations to the C. taiwanensis host, Mimosa pudica L.. This experiment validated a two-step evolutionary scenario of key symbiotic gene acquisition followed by genome remodeling under plant selection. Nodulation and nodule cell infection were obtained and optimized mainly via the rewiring of regulatory circuits of the recipient bacterium. Symbiotic adaptation was shown to be accelerated by the activity of a mutagenesis cassette conserved in most rhizobia. Investigating mutated genes led us to identify new components of R. solanacearum virulence and C. taiwanensis symbiosis. Nitrogen fixation was not acquired in our short experiment. However, we showed that post-infection sanctions allowed the increase in frequency of nitrogen-fixing variants among a non-fixing population in the M. pudica-C. taiwanensis system and likely allowed the spread of this trait in natura. Experimental evolution thus provided new insights into rhizobium biology and evolution.

Selection on mutators is not frequency-dependent

The evolutionary fate of mutator mutations – genetic variants that raise the genome-wide mutation rate – in asexual populations is often described as being frequency (or number) dependent. Mutators can invade a population by hitchhiking with a sweeping beneficial mutation, but motivated by earlier experiments results, it has been repeatedly suggested that mutators must be sufficiently frequent to produce such a driver mutation before non-mutators do. Here, we use stochastic, agent-based simulations to show that neither the strength nor the sign of selection on mutators depend on their initial frequency, and while the overall probability of hitchhiking increases predictably with frequency, the per-capita probability of fixation remains unchanged.

The fitness cost of mismatch repair mutators in Saccharomyces cerevisiae: partitioning the mutational load

Mutational load is the depression in a population's mean fitness that results from the continual influx of deleterious mutations. Here, we directly estimate the mutational load in a population of haploid Saccharomyces cerevisiae that are deficient for mismatch repair. We partition the load in haploids into two components. To estimate the load due to nonlethal mutations, we measure the competitive fitness of hundreds of randomly selected clones from both mismatch-repair-deficient and -proficient populations. Computation of the mean clone fitness for the mismatch-repair-deficient strain permits an estimation of the nonlethal load, and the histogram of fitness provides an interesting visualization of a loaded population. In a separate experiment, in order to estimate the load due to lethal mutations (i.e. the lethal mutation rate), we manipulate thousands of individual pairs of mother and daughter cells and track their fates. These two approaches yield point estimates for the two contributors to load, and the addition of these estimates is nearly equal to the separately measured short-term competitive fitness deficit for the mismatch-repair-deficient strain. This correspondence suggests that there is no need to invoke direct fitness effects to explain the fitness difference between mismatch-repair-deficient and -proficient strains. Assays in diploids are consistent with deleterious mutations in diploids tending towards recessivity. These results enhance our understanding of mutational load, a central population genetics concept, and we discuss their implications for the evolution of mutation rates.

Why So Variable: Can Genetic Variance in Flowering Thresholds Be Maintained by Fluctuating Selection?

We use integral projection models (IPMs) and individual-based simulations to study the evolution of genetic variance in two monocarpic plant systems. Previous approaches combining IPMs with an adaptive dynamics-style invasion analysis predicted that genetic variability in the size threshold for flowering will not be maintained, which conflicts with empirical evidence. We ask whether this discrepancy can be resolved by making more realistic assumptions about the underlying genetic architecture, assuming a multilocus quantitative trait in an outcrossing diploid species. To do this, we embed the infinitesimal model of quantitative genetics into an IPM for a size-structured cosexual plant species. The resulting IPM describes the joint dynamics of individual size and breeding value of the evolving trait. We apply this general framework to the monocarpic perennials Oenothera glazioviana and Carlina vulgaris. The evolution of heritable variation in threshold size is explored in both individual-based models (IBMs) and IPMs, using a mutation rate modifier approach. In the Oenothera model, where the environment is constant, there is selection against producing genetically variable offspring. In the Carlina model, where the environment varies between years, genetically variable offspring provide a selective advantage, allowing the maintenance of genetic variability. The contrasting predictions of adaptive dynamics and quantitative genetics models for the same system suggest that fluctuating selection may be more effective at maintaining genetic variation than previously thought.

Interference Effects of Deleterious and Beneficial Mutations in Large Asexual Populations

Linked beneficial and deleterious mutations are known to decrease the fixation probability of a favorable mutation in large asexual populations. While the hindering effect of strongly deleterious mutations on adaptive evolution has been well studied, how weakly deleterious mutations, either in isolation or with superior beneficial mutations, influence the rate of adaptation has not been fully explored. When the selection against the deleterious mutations is weak, the beneficial mutant can fix in many genetic backgrounds, besides the one it arose on. Here, taking this factor into account, I obtain an accurate analytical expression for the fixation probability of a beneficial mutant in an asexual population at mutation-selection balance. I then exploit this result along with clonal interference theory to investigate the joint effect of linked beneficial and deleterious mutations on the rate of adaptation, and identify parameter regions where it is reduced due to interference by either beneficial or deleterious or both types of mutations. I also study the evolution of mutation rates in adapting asexual populations, and find that linked beneficial mutations have a stronger influence than the deleterious mutations on mutator fixation.

Genomic clustering of fitness-affecting mutations favors the evolution of chromosomal instability

Most solid cancers are characterized by chromosomal instability (CIN)-an elevated rate of large-scale chromosomal aberrations and ploidy changes. Chromosomal instability may arise through mutations in a range of genomic integrity loci and is commonly associated with fast disease progression, poor prognosis, and multidrug resistance. However, the evolutionary forces promoting CIN-inducing alleles (hereafter, CIN mutators) during carcinogenesis remain poorly understood. Here, we develop a stochastic, individual-based model of indirect selection experienced by CIN mutators via genomic associations with fitness-affecting mutations. Because mutations associated with CIN affect large swaths of the genome and have the potential to simultaneously comprise many individual loci, we show that indirect selection on CIN mutators is critically influenced by genome organization. In particular, we find strong support for a key role played by the spatial clustering of loci with either beneficial or deleterious mutational effects. Genomic clustering of selected loci allows CIN mutators to generate favorable chromosomal changes that facilitate their rapid expansion within a neoplasm and, in turn, accelerate carcinogenesis. We then examine the distribution of oncogenic and tumor-suppressing loci in the human genome and find both to be potentially more clustered along the chromosome than expected, leading us to speculate that human genome may be susceptible to CIN hitchhiking. More quantitative data on fitness effects of individual mutations will be necessary, though, to assess the true levels of clustering in the human genome and the effectiveness of indirect selection for CIN. Finally, we use our model to examine how therapeutic strategies that increase the deleterious burden of genetically unstable cells by raising either the rate of CIN or the cost of deleterious mutations affect CIN evolution. We find that both can inhibit CIN hitchhiking and delay carcinogenesis in some circumstances, yet, in line with earlier work, we find the latter to be considerably more effective.

Migration promotes mutator alleles in subdivided populations

Mutator alleles that elevate the genomic mutation rate may invade nonrecombining populations by hitchhiking with beneficial mutations. Mutators have been repeatedly observed to take over adapting laboratory populations and have been found at high frequencies in both microbial pathogen and cancer populations in nature. Recently, we have shown that mutators are only favored by selection in sufficiently large populations and transition to being disfavored as population size decreases. This population size-dependent sign inversion in selective effect suggests that population structure may also be an important determinant of mutation rate evolution. Although large populations may favor mutators, subdividing such populations into sufficiently small subpopulations (demes) might effectively inhibit them. On the other hand, migration between small demes that otherwise inhibit hitchhiking may promote mutator fixation in the whole metapopulation. Here, we use stochastic, agent-based simulations and evolution experiments with the yeast Saccharomyces cerevisiae to show that mutators can, indeed, be favored by selection in subdivided metapopulations composed of small demes connected by sufficient migration. In fact, we show that population structure plays a previously unsuspected role in promoting mutator success in subdivided metapopulations when migration is rare.

Mutation and Selection in Bacteria: Modelling and Calibration

Temporal evolution of a clonal bacterial population is modelled taking into account reversible mutation and selection mechanisms. For the mutation model, an efficient algorithm is proposed to verify whether experimental data can be explained by this model. The selection–mutation model has unobservable fitness parameters, and, to estimate them, we use an Approximate Bayesian Computation algorithm. The algorithms are illustrated using in vitro data for phase variable genes of Campylobacter jejuni.

Experimental Design, Population Dynamics, and Diversity in Microbial Experimental Evolution

In experimental evolution, laboratory-controlled conditions select for the adaptation of species, which can be monitored in real time. Despite the current popularity of such experiments, nature's most pervasive biological force was long believed to be observable only on time scales that transcend a researcher's life-span, and studying evolution by natural selection was therefore carried out solely by comparative means. Eventually, microorganisms' propensity for fast evolutionary changes proved us wrong, displaying strong evolutionary adaptations over a limited time, nowadays massively exploited in laboratory evolution experiments. Here, we formulate a guide to experimental evolution with microorganisms, explaining experimental design and discussing evolutionary dynamics and outcomes and how it is used to assess ecoevolutionary theories, improve industrially important traits, and untangle complex phenotypes. Specifically, we give a comprehensive overview of the setups used in experimental evolution. Additionally, we address population dynamics and genetic or phenotypic diversity during evolution experiments and expand upon contributing factors, such as epistasis and the consequences of (a)sexual reproduction. Dynamics and outcomes of evolution are most profoundly affected by the spatiotemporal nature of the selective environment, where changing environments might lead to generalists and structured environments could foster diversity, aided by, for example, clonal interference and negative frequency-dependent selection. We conclude with future perspectives, with an emphasis on possibilities offered by fast-paced technological progress. This work is meant to serve as an introduction to those new to the field of experimental evolution, as a guide to the budding experimentalist, and as a reference work to the seasoned expert.

High mutation rates limit evolutionary adaptation in Escherichia coli

Mutation is fundamental to evolution, because it generates the genetic variation on which selection can act. In nature, genetic changes often increase the mutation rate in systems that range from viruses and bacteria to human tumors. Such an increase promotes the accumulation of frequent deleterious or neutral alleles, but it can also increase the chances that a population acquires rare beneficial alleles. Here, we study how up to 100-fold increases in Escherichia coli's genomic mutation rate affect adaptive evolution. To do so, we evolved multiple replicate populations of asexual E. coli strains engineered to have four different mutation rates for 3000 generations in the laboratory. We measured the ability of evolved populations to grow in their original environment and in more than 90 novel chemical environments. In addition, we subjected the populations to whole genome population sequencing. Although populations with higher mutation rates accumulated greater genetic diversity, this diversity conveyed benefits only for modestly increased mutation rates, where populations adapted faster and also thrived better than their ancestors in some novel environments. In contrast, some populations at the highest mutation rates showed reduced adaptation during evolution, and failed to thrive in all of the 90 alternative environments. In addition, they experienced a dramatic decrease in mutation rate. Our work demonstrates that the mutation rate changes the global balance between deleterious and beneficial mutational effects on fitness. In contrast to most theoretical models, our experiments suggest that this tipping point already occurs at the modest mutation rates that are found in the wild.

Sign of selection on mutation rate modifiers depends on population size

The influence of population size (N) on natural selection acting on alleles that affect fitness has been understood for almost a century. As N declines, genetic drift overwhelms selection and alleles with direct fitness effects are rendered neutral. Often, however, alleles experience so-called indirect selection, meaning they affect not the fitness of an individual but the fitness distribution of its offspring. Some of the best-studied examples of indirect selection include alleles that modify aspects of the genetic system such as recombination and mutation rates. Here, we use analytics, simulations, and experimental populations of Saccharomyces cerevisiae to examine the influence of N on indirect selection acting on alleles that increase the genomic mutation rate (mutators). Mutators experience indirect selection via genomic associations with beneficial and deleterious mutations they generate. We show that, as N declines, indirect selection driven by linked beneficial mutations is overpowered by drift before drift can neutralize the cost of the deleterious load. As a result, mutators transition from being favored by indirect selection in large populations to being disfavored as N declines. This surprising phenomenon of sign inversion in selective effect demonstrates that indirect selection on mutators exhibits a profound and qualitatively distinct dependence on N.

The sources of adaptive variation

The role of natural selection in the evolution of adaptive phenotypes has undergone constant probing by evolutionary biologists, employing both theoretical and empirical approaches. As Darwin noted, natural selection can act together with other processes, including random changes in the frequencies of phenotypic differences that are not under strong selection, and changes in the environment, which may reflect evolutionary changes in the organisms themselves. As understanding of genetics developed after 1900, the new genetic discoveries were incorporated into evolutionary biology. The resulting general principles were summarized by Julian Huxley in his 1942 book Evolution: the modern synthesis Here, we examine how recent advances in genetics, developmental biology and molecular biology, including epigenetics, relate to today's understanding of the evolution of adaptations. We illustrate how careful genetic studies have repeatedly shown that apparently puzzling results in a wide diversity of organisms involve processes that are consistent with neo-Darwinism. They do not support important roles in adaptation for processes such as directed mutation or the inheritance of acquired characters, and therefore no radical revision of our understanding of the mechanism of adaptive evolution is needed.

Statistical Package for Growth Rates Made Easy

Growth rates are an important tool in microbiology because they provide high throughput fitness measurements. The release of GrowthRates, a program that uses the output of plate reader files to automatically calculate growth rates, has facilitated experimental procedures in many areas. However, many sources of variation within replicate growth rate data exist and can decrease data reliability. We have developed a new statistical package, CompareGrowthRates (CGR), to enhance the program GrowthRates and accurately measure variation in growth rate data sets. We define a metric, Variability-score (V-score), that can help determine if variation within a data set might result in false interpretations. CGR also uses the bootstrap method to determine the fraction of bootstrap replicates in which a strain will grow the fastest. We illustrate the usage of CGR with growth rate data sets similar to those in Mira, Meza, et al. (Adaptive landscapes of resistance genes change as antibiotic concentrations change. Mol Biol Evol. 32(10): 2707-2715). These statistical methods are compatible with the analytic methods described in Growth Rates Made Easy and can be used with any set of growth rate output from GrowthRates.

Fixation probability of a nonmutator in a large population of asexual mutators

In an adapted population of mutators in which most mutations are deleterious, a nonmutator that lowers the mutation rate is under indirect selection and can sweep to fixation. Using a multitype branching process, we calculate the fixation probability of a rare nonmutator in a large population of asexual mutators. We show that when beneficial mutations are absent, the fixation probability is a nonmonotonic function of the mutation rate of the mutator: it first increases sublinearly and then decreases exponentially. We also find that beneficial mutations can enhance the fixation probability of a nonmutator. Our analysis is relevant to an understanding of recent experiments in which a reduction in the mutation rates has been observed.

Genetic drift, selection and the evolution of the mutation rate

As one of the few cellular traits that can be quantified across the tree of life, DNA-replication fidelity provides an excellent platform for understanding fundamental evolutionary processes. Furthermore, because mutation is the ultimate source of all genetic variation, clarifying why mutation rates vary is crucial for understanding all areas of biology. A potentially revealing hypothesis for mutation-rate evolution is that natural selection primarily operates to improve replication fidelity, with the ultimate limits to what can be achieved set by the power of random genetic drift. This drift-barrier hypothesis is consistent with comparative measures of mutation rates, provides a simple explanation for the existence of error-prone polymerases and yields a formal counter-argument to the view that selection fine-tunes gene-specific mutation rates.

Adaptive tuning of mutation rates allows fast response to lethal stress in Escherichia coli

While specific mutations allow organisms to adapt to stressful environments, most changes in an organism's DNA negatively impact fitness. The mutation rate is therefore strictly regulated and often considered a slowly-evolving parameter. In contrast, we demonstrate an unexpected flexibility in cellular mutation rates as a response to changes in selective pressure. We show that hypermutation independently evolves when different Escherichia coli cultures adapt to high ethanol stress. Furthermore, hypermutator states are transitory and repeatedly alternate with decreases in mutation rate. Specifically, population mutation rates rise when cells experience higher stress and decline again once cells are adapted. Interestingly, we identified cellular mortality as the major force driving the quick evolution of mutation rates. Together, these findings show how organisms balance robustness and evolvability and help explain the prevalence of hypermutation in various settings, ranging from emergence of antibiotic resistance in microbes to cancer relapses upon chemotherapy.

Known mutator alleles do not markedly increase mutation rate in clinical Saccharomyces cerevisiae strains

Natural selection has the potential to act on all phenotypes, including genomic mutation rate. Classic evolutionary theory predicts that in asexual populations, mutator alleles, which cause high mutation rates, can fix due to linkage with beneficial mutations. This phenomenon has been demonstrated experimentally and may explain the frequency of mutators found in bacterial pathogens. By contrast, in sexual populations, recombination decouples mutator alleles from beneficial mutations, preventing mutator fixation. In the facultatively sexual yeast Saccharomyces cerevisiae, segregating alleles of MLH1 and PMS1 have been shown to be incompatible, causing a high mutation rate when combined. These alleles had never been found together naturally, but were recently discovered in a cluster of clinical isolates. Here we report that the incompatible mutator allele combination only marginally elevates mutation rate in these clinical strains. Genomic and phylogenetic analyses provide no evidence of a historically elevated mutation rate. We conclude that the effect of the mutator alleles is dampened by background genetic modifiers. Thus, the relationship between mutation rate and microbial pathogenicity may be more complex than once thought. Our findings provide rare observational evidence that supports evolutionary theory suggesting that sexual organisms are unlikely to harbour alleles that increase their genomic mutation rate.

Evolution of mutation rates in hypermutable populations of Escherichia coli propagated at very small effective population size

Mutation is the ultimate source of the genetic variation-including variation for mutation rate itself-that fuels evolution. Natural selection can raise or lower the genomic mutation rate of a population by changing the frequencies of mutation rate modifier alleles associated with beneficial and deleterious mutations. Existing theory and observations suggest that where selection is minimized, rapid systematic evolution of mutation rate either up or down is unlikely. Here, we report systematic evolution of higher and lower mutation rates in replicate hypermutable Escherichia coli populations experimentally propagated at very small effective size-a circumstance under which selection is greatly reduced. Several populations went extinct during this experiment, and these populations tended to evolve elevated mutation rates. In contrast, populations that survived to the end of the experiment tended to evolve decreased mutation rates. We discuss the relevance of our results to current ideas about the evolution, maintenance and consequences of high mutation rates.

Role of epistasis on the fixation probability of a non-mutator in an adapted asexual population

The mutation rate of a well adapted population is prone to reduction so as to have a lower mutational load. We aim to understand the role of epistatic interactions between the fitness affecting mutations in this process. Using a multitype branching process, the fixation probability of a single non-mutator emerging in a large asexual mutator population is analytically calculated here. The mutator population undergoes deleterious mutations at constant, but at a much higher rate than that of the non-mutator. We find that antagonistic epistasis lowers the chances of mutation rate reduction, while synergistic epistasis enhances it. Below a critical value of epistasis, the fixation probability behaves non-monotonically with variation in the mutation rate of the background population. Moreover, the variation of this critical value of the epistasis parameter with the strength of the mutator is discussed in the appendix. For synergistic epistasis, when selection is varied, the fixation probability reduces overall, with damped oscillations.

Evolutionary dynamics of viral escape under antibodies stress: A biophysical model

Viruses constantly face the selection pressure of antibodies, either from innate immune response of the host or from administered antibodies for treatment. We explore the interplay between the biophysical properties of viral proteins and the population and demographic variables in the viral escape. The demographic and population genetics aspect of the viral escape have been explored before; however one important assumption was the a priori distribution of fitness effects (DFE). Here, we relax this assumption by instead considering a realistic biophysics-based genotype-phenotype relationship for RNA viruses escaping antibodies stress. In this model the DFE is itself an evolvable property that depends on the genetic background (epistasis) and the distribution of biophysical effects of mutations, which is informed by biochemical experiments and theoretical calculations in protein engineering. We quantitatively explore in silico the viability of viral populations under antibodies pressure and derive the phase diagram that defines the fate of the virus population (extinction or escape from stress) in a range of viral mutation rates and antibodies concentrations. We find that viruses are most resistant to stress at an optimal mutation rate (OMR) determined by the competition between supply of beneficial mutation to facilitate escape from stressors and lethal mutagenesis caused by excess of destabilizing mutations. We then show the quantitative dependence of the OMR on genome length and viral burst size. We also recapitulate the experimental observation that viruses with longer genomes have smaller mutation rate per nucleotide.

Mutation-Driven Divergence and Convergence Indicate Adaptive Evolution of the Intracellular Human-Restricted Pathogen, Bartonella bacilliformis

Among all species of Bartonella, human-restricted Bartonella bacilliformis is the most virulent but harbors one of the most reduced genomes. Carrión’s disease, the infection caused by B. bacilliformis, has been afflicting poor rural populations for centuries in the high-altitude valleys of the South American Andes, where the pathogen’s distribution is probably restricted by its sand fly vector’s range. Importantly, Carrión’s disease satisfies the criteria set by the World Health Organization for a disease amenable to elimination. However, to date, there are no genome-level studies to identify potential footprints of B. bacilliformis (patho)adaptation. Our comparative genomic approach demonstrates that the evolution of this intracellular pathogen is shaped predominantly via mutation. Analysis of strains having publicly-available genomes shows high mutational divergence of core genes leading to multiple sub-species. We infer that the sub-speciation event might have happened recently where a possible adaptive divergence was accelerated by intermediate emergence of a mutator phenotype. Also, within a sub-species the pathogen shows inter-clonal adaptive evolution evidenced by non-neutral accumulation of convergent amino acid mutations. A total of 67 non-recombinant core genes (over-representing functional categories like DNA repair, glucose metabolic process, ATP-binding and ligase) were identified as candidates evolving via adaptive mutational convergence. Such convergence, both at the level of genes and their encoded functions, indicates evolution of B. bacilliformis clones along common adaptive routes, while there was little diversity within a single clone.

How host-restriction, intracellularity and genome reduction interplay to exert or maintain virulence is poorly characterized. The fact that B. bacilliformis is the most pathogenic Bartonella and has a highly reduced genome makes it an attractive model to gain insights into (patho)adaptive evolution of intracellular pathogens. Also, B. bacilliformis is known to lack many virulence genes present in other Bartonella, indicating unique strategies of (patho)adaptation. Our study reveals a prevalent nature of mutational force in B. bacilliformis evolution with two distinct outcomes: (a) mutational divergence leading to sub-speciation, possibly recently, via accelerated accumulation and fixation of favorable mutations mediated by a mutator phenotype; and (b) mutational convergence between clones of a sub-species exhibiting shared functional trajectories of adaptive evolution. Our findings highlight positions accumulating adaptive mutations in candidate genes, offering future functional studies to elucidate B. bacilliformis virulence evolution, and of broad application to intracellular pathogens with a reduced gene repertoire.

The evolutionary dynamics of integrons in changing environments

Integrons are genetic elements that are common in bacteria and are hotspots for genome evolution. They facilitate the acquisition and reassembly of gene cassettes encoding a variety of functions, including drug resistance. Despite their importance in clinical settings, the selective forces responsible for the evolution and maintenance of integrons are poorly understood. We present a mathematical model of integron evolution within bacterial populations subject to fluctuating antibiotic exposures. Bacteria carrying a functional integrase that mediates reshuffling of cassette genes and thereby modulates gene expression patterns compete with bacteria without a functional integrase. Our results indicate that for a wide range of parameters, the functional integrase can be stably maintained in the population despite substantial fitness costs. This selective advantage arises because gene-cassette shuffling generates genetic diversity, thus enabling the population to respond rapidly to changing selective pressures. We also show that horizontal gene transfer promotes stable maintenance of the integrase and can also lead to de novo assembly of integrons. Our model generates testable predictions for integron evolution, including loss of functional integrases in stable environments and selection for intermediate gene-shuffling rates in changing environments. Our results highlight the need for experimental studies of integron population biology.

Fixation probability of rare nonmutator and evolution of mutation rates

Although mutations drive the evolutionary process, the rates at which the mutations occur are themselves subject to evolutionary forces. Our purpose here is to understand the role of selection and random genetic drift in the evolution of mutation rates, and we address this question in asexual populations at mutation-selection equilibrium neglecting selective sweeps. Using a multitype branching process, we calculate the fixation probability of a rare nonmutator in a large asexual population of mutators and find that a nonmutator is more likely to fix when the deleterious mutation rate of the mutator population is high. Compensatory mutations in the mutator population are found to decrease the fixation probability of a nonmutator when the selection coefficient is large. But, surprisingly, the fixation probability changes nonmonotonically with increasing compensatory mutation rate when the selection is mild. Using these results for the fixation probability and a drift-barrier argument, we find a novel relationship between the mutation rates and the population size. We also discuss the time to fix the nonmutator in an adapted population of asexual mutators, and compare our results with experiments.

Endosymbiont evolution: predictions from theory and surprises from genomes

Genome data have created new opportunities to untangle evolutionary processes shaping microbial variation. Among bacteria, long-term mutualists of insects represent the smallest and (typically) most AT-rich genomes. Evolutionary theory provides a context to predict how an endosymbiotic lifestyle may alter fundamental evolutionary processes--mutation, selection, genetic drift, and recombination--and thus contribute to extreme genomic outcomes. These predictions can then be explored by comparing evolutionary rates, genome size and stability, and base compositional biases across endosymbiotic and free-living bacteria. Recent surprises from such comparisons include genome reduction among uncultured, free-living species. Some studies suggest that selection generally drives this streamlining, while drift drives genome reduction in endosymbionts; however, this remains an hypothesis requiring additional data. Unexpected evidence of selection acting on endosymbiont GC content hints that even weak selection may be effective in some long-term mutualists. Moving forward, intraspecific analysis offers a promising approach to distinguish underlying mechanisms, by testing the null hypothesis of neutrality and by quantifying mutational spectra. Such analyses may clarify whether endosymbionts and free-living bacteria occupy distinct evolutionary trajectories or, alternatively, represent varied outcomes of similar underlying forces.