The evolution of mutation rate in finite asexual populations

Simulating the Effect of Environmental Change on Evolving Populations

This study uses evolutionary simulations to explore the strategies that emerge to enable populations to cope with random environmental changes in situations where lifetime learning approaches are not available to accommodate them. In particular, it investigates how the average magnitude of change per unit time and the persistence of the changes (and hence the resulting autocorrelation of the environmental time series) affect the change tolerances, population diversities, and extinction timescales that emerge. Although it is the change persistence (often discussed in terms of environmental noise color) that has received most attention in the recent literature, other factors, particularly the average change magnitude, interact with this and can be more important drivers of the adaptive strategies that emerge. Moreover, when running simulations, the choice of change representation and normalization can also affect the outcomes. Detailed simulations are presented that are designed to explore all these issues. They also reveal significant dependences on the associated mutation rates and the extent to which they can evolve, and they clarify how evolution often leads populations into strategies with higher risks of extinction. Overall, this study shows how modeling the effect of environmental change requires more care than may have previously been realized.

Transgenerational adaptation to ocean acidification determines the susceptibility of filter-feeding rotifers to nanoplastics

The adaptation of marine organisms to the impending challenges presented by ocean acidification (OA) is essential for their future survival, and mechanisms underlying OA adaptation have been reported in several marine organisms. In the natural environment, however, marine organisms are often exposed to a combination of environmental stressors, and the interactions between adaptive responses have yet to be elucidated. Here, we investigated the susceptibility of filter-feeding rotifers to short-term (ST) and long-term (LT) (≥180 generations) high CO2 conditions coupled with nanoplastic (NPs) exposure (ST+ and LT+). Adaptation of rotifers to elevated CO2 caused differences in ingestion and accumulation of NPs, resulting in a significantly different mode of action on in vivo endpoints between the ST+ and LT+ groups. Moreover, microRNA-mediated epigenetic regulation was strongly correlated with the varied adaptive responses between the ST+ and LT+ groups, revealing novel regulatory targets and pathways. Our results indicate that pre-exposure history to increased CO2 levels is an important factor in the susceptibility of rotifers to NPs.

Life history and deleterious mutation rate coevolution

The cost of germline maintenance gives rise to a trade-off between lowering the deleterious mutation rate and investing in life history functions. Therefore, life history and the mutation rate coevolve, but this coevolution is not well understood. We develop a mathematical model to analyse the evolution of resource allocation traits, which simultaneously affect life history and the deleterious mutation rate. First, we show that the invasion fitness of such resource allocation traits can be approximated by the basic reproductive number of the least-loaded class; the expected lifetime production of offspring without deleterious mutations born to individuals without deleterious mutations. Second, we apply the model to investigate (i) the coevolution of reproductive effort and germline maintenance and (ii) the coevolution of age-at-maturity and germline maintenance. This analysis provides two resource allocation predictions when exposure to environmental mutagens is higher. First, selection favours higher allocation to germline maintenance, even if it comes at the expense of life history functions, and leads to a shift in allocation towards reproduction rather than survival. Second, life histories tend to be faster, characterised by individuals with shorter lifespans and smaller body sizes at maturity. Our results suggest that mutation accumulation via the cost of germline maintenance can be a major force shaping life-history traits.

Epidemic spreading under mutually independent intra- and inter-host pathogen evolution

The dynamics of epidemic spreading is often reduced to the single control parameter R₀ (reproduction-rate), whose value, above or below unity, determines the state of the contagion. If, however, the pathogen evolves as it spreads, R₀ may change over time, potentially leading to a mutation-driven spread, in which an initially sub-pandemic pathogen undergoes a breakthrough mutation. To predict the boundaries of this pandemic phase, we introduce here a modeling framework to couple the inter-host network spreading patterns with the intra-host evolutionary dynamics. We find that even in the extreme case when these two process are driven by mutually independent selection forces, mutations can still fundamentally alter the pandemic phase-diagram. The pandemic transitions, we show, are now shaped, not just by R₀, but also by the balance between the epidemic and the evolutionary timescales. If mutations are too slow, the pathogen prevalence decays prior to the appearance of a critical mutation. On the other hand, if mutations are too rapid, the pathogen evolution becomes volatile and, once again, it fails to spread. Between these two extremes, however, we identify a broad range of conditions in which an initially sub-pandemic pathogen can breakthrough to gain widespread prevalence.

Rapid evolution of mutation rate and spectrum in response to environmental and population-genetic challenges

Ecological and demographic factors can significantly shape the evolution of microbial populations both directly and indirectly, as when changes in the effective population size affect the efficiency of natural selection on the mutation rate. However, it remains unclear how rapidly the mutation-rate responds evolutionarily to the entanglement of ecological and population-genetic factors over time. Here, we directly assess the mutation rate and spectrum of Escherichia coli clones isolated from populations evolving in response to 1000 days of different transfer volumes and resource-replenishment intervals. The evolution of mutation rates proceeded rapidly in response to demographic and/or environmental changes, with substantial bidirectional shifts observed as early as 59 generations. These results highlight the remarkable rapidity by which mutation rates are shaped in asexual lineages in response to environmental and population-genetic forces, and are broadly consistent with the drift-barrier hypothesis for the evolution of mutation rates, while also highlighting situations in which mutator genotypes may be promoted by positive selection.

How rapidly the mutation rate responds evolutionarily to ecological and population-genetic factors over time is unclear. Here, the authors show that the evolution of mutation rates in E. coli proceeds rapidly in response to these factors with substantial bidirectional shifts.

A modified fluctuation assay reveals a natural mutator phenotype that drives mutation spectrum variation within Saccharomyces cerevisiae

Although studies of Saccharomyces cerevisiae have provided many insights into mutagenesis and DNA repair, most of this work has focused on a few laboratory strains. Much less is known about the phenotypic effects of natural variation within S. cerevisiae’s DNA repair pathways. Here, we use natural polymorphisms to detect historical mutation spectrum differences among several wild and domesticated S. cerevisiae strains. To determine whether these differences are likely caused by genetic mutation rate modifiers, we use a modified fluctuation assay with a CAN1 reporter to measure de novo mutation rates and spectra in 16 of the analyzed strains. We measure a 10-fold range of mutation rates and identify two strains with distinctive mutation spectra. These strains, known as AEQ and AAR, come from the panel’s ‘Mosaic beer’ clade and share an enrichment for C > A mutations that is also observed in rare variation segregating throughout the genomes of several Mosaic beer and Mixed origin strains. Both AEQ and AAR are haploid derivatives of the diploid natural isolate CBS 1782, whose rare polymorphisms are enriched for C > A as well, suggesting that the underlying mutator allele is likely active in nature. We use a plasmid complementation test to show that AAR and AEQ share a mutator allele in the DNA repair gene OGG1, which excises 8-oxoguanine lesions that can cause C > A mutations if left unrepaired.

The rate and molecular spectrum of mutation are selectively maintained in yeast

What determines the rate (μ) and molecular spectrum of mutation is a fundamental question. The prevailing hypothesis asserts that natural selection against deleterious mutations has pushed μ to the minimum achievable in the presence of genetic drift, or the drift barrier. Here we show that, contrasting this hypothesis, μ substantially exceeds the drift barrier in diverse organisms. Random mutation accumulation (MA) in yeast frequently reduces μ, and deleting the newly discovered mutator gene PSP2 nearly halves μ. These results, along with a comparison between the MA and natural yeast strains, demonstrate that μ is maintained above the drift barrier by stabilizing selection. Similar comparisons show that the mutation spectrum such as the universal AT mutational bias is not intrinsic but has been selectively preserved. These findings blur the separation of mutation from selection as distinct evolutionary forces but open the door to alleviating mutagenesis in various organisms by genome editing.

How natural selection shapes the rate and molecular spectrum of mutations is debated. Yeast mutation accumulation experiments identify a gene promoting mutagenesis and show stabilizing selection maintaining the mutation rate above the drift barrier. Selection also preserves the mutation spectrum.

The evolutionary impact of population size, mutation rate and virulence on pathogen niche width

Understanding the evolution of pathogen niche width is important for predicting disease spread and the probability that pathogens can emerge in novel hosts. Findings from previous theoretical studies often suggest that pathogens will evolve to be specialists in specific host environments. However, several of these studies make unrealistic assumptions regarding demographic stochasticity and the ability of pathogens to select their hosts. Here, an individual-based model was used to predict how population size, virulence and pathogen mutation rate affects the evolution niche specialism in pathogens. Pathogen specialism evolved regardless of virulence or populations size; thus, the findings of this study are somewhat consistent with those of previous work. However, because specialist pathogens had only a weak selective advantage over generalist pathogens, high mutation rates caused random trait variation to accumulate, preventing the evolution of specialism. Mutation rate varies greatly across different species and strains of pathogen. By showing that high mutation rates may prevent pathogen specialism evolving, this study highlights an intrinsic pathogen trait that may influence the evolution of pathogen niche width.

Estimation of the SNP Mutation Rate in Two Vegetatively Propagating Species of Duckweed

Mutation rate estimates for vegetatively reproducing organisms are rare, despite their frequent occurrence across the tree of life. Here we report mutation rate estimates in two vegetatively reproducing duckweed species, Lemna minor and Spirodela polyrhiza We use a modified approach to estimating mutation rates by taking into account the reduction in mutation detection power that occurs when new individuals are produced from multiple cell lineages. We estimate an extremely low per generation mutation rate in both species of duckweed and note that allelic coverage at de novo mutation sites is very skewed. We also find no substantial difference in mutation rate between mutation accumulation lines propagated under benign conditions and those grown under salt stress. Finally, we discuss the implications of interpreting mutation rate estimates in vegetatively propagating organisms.

Hypermutator Pseudomonas aeruginosa Exploits Multiple Genetic Pathways To Develop Multidrug Resistance during Long-Term Infections in the Airways of Cystic Fibrosis Patients

Pseudomonas aeruginosa exploits intrinsic and acquired resistance mechanisms to resist almost every antibiotic used in chemotherapy. Antimicrobial resistance in P. aeruginosa isolates recovered from cystic fibrosis (CF) patients is further enhanced by the occurrence of hypermutator strains, a hallmark of chronic infections in CF patients. However, the within-patient genetic diversity of P. aeruginosa populations related to antibiotic resistance remains unexplored. Here, we show the evolution of the mutational resistome profile of a P. aeruginosa hypermutator lineage by performing longitudinal and transversal analyses of isolates collected from a CF patient throughout 20 years of chronic infection. Our results show the accumulation of thousands of mutations, with an overall evolutionary history characterized by purifying selection. However, mutations in antibiotic resistance genes appear to have been positively selected, driven by antibiotic treatment. Antibiotic resistance increased as infection progressed toward the establishment of a population constituted by genotypically diversified coexisting sublineages, all of which converged to multidrug resistance. These sublineages emerged by parallel evolution through distinct evolutionary pathways, which affected genes of the same functional categories. Interestingly, ampC and ftsI, encoding the β-lactamase and penicillin-binding protein 3, respectively, were found to be among the most frequently mutated genes. In fact, both genes were targeted by multiple independent mutational events, which led to a wide diversity of coexisting alleles underlying β-lactam resistance. Our findings indicate that hypermutators, apart from boosting antibiotic resistance evolution by simultaneously targeting several genes, favor the emergence of adaptive innovative alleles by clustering beneficial/compensatory mutations in the same gene, hence expanding P. aeruginosa strategies for persistence.

The effect of bacterial mutation rate on the evolution of CRISPR-Cas adaptive immunity

CRISPR-Cas immune systems are present in around half of bacterial genomes. Given the specificity and adaptability of this immune mechanism, it is perhaps surprising that they are not more widespread. Recent insights into the requirement for specific host factors for the function of some CRISPR-Cas subtypes, as well as the negative epistasis between CRISPR-Cas and other host genes, have shed light on potential reasons for the partial distribution of this immune strategy in bacteria. In this study, we examined how mutations in the bacterial mismatch repair system, which are frequently observed in natural and clinical isolates and cause elevated host mutation rates, influence the evolution of CRISPR-Cas–mediated immunity. We found that hosts with a high mutation rate very rarely evolved CRISPR-based immunity to phage compared to wild-type hosts. We explored the reason for this effect and found that the higher frequency at which surface mutants pre-exist in the mutator host background causes them to rapidly become the dominant phenotype under phage infection. These findings suggest that natural variation in bacterial mutation rates may, therefore, influence the distribution of CRISPR-Cas adaptive immune systems.

This article is part of a discussion meeting issue ‘The ecology and evolution of prokaryotic CRISPR-Cas adaptive immune systems’.

A percolation model of natural selection

A new approach has been proposed and developed: the selection of optimal variants in the evolutionary mutation flow is considered as an analogue of a percolation filter. Interaction of mutations in a series of generations and random processes of drift determine the collective behavior of nodes (individuals - carriers and converters of mutations) and bonds (mutations) in the space of percolation lattice. It is shown that the choice of the development trajectory at the population level depends on the spectrum of supporting and prohibiting mutations under the influence of conjugate deterministic and random factors. From the point of view of the fluctuation-bifurcation process, new concepts of the lower and upper thresholds of the percolation selection grid are defined in the hierarchical structure of speciation. The upper threshold determines the state of self-organized criticality, which, when overcome, leads to irreversible self-organization processes in the population caused by the accumulation of mutations.

Adapting the engine to the fuel: mutator populations can reduce the mutational load by reorganizing their genome structure

Background

Mutators are common in bacterial populations, both in natural isolates and in the lab. The fate of these lineages, which mutation rate is increased up to 100 ×, has long been studied using population genetics models, showing that they can spread in a population following an environmental change. However in stable conditions, they suffer from the increased mutational load, hence being overcome by non-mutators. However, these results don’t take into account the fact that an elevated mutation rate can impact the genetic structure, hence changing the sensitivity of the population to mutations. Here we used Aevol, an in silico experimental evolution platform in which genomic structures are free to evolve, in order to study the fate of mutator populations evolving for a long time in constant conditions.

Results

Starting from wild-types that were pre-evolved for 300,000 generations, we let 100 mutator populations (point mutation rate ×100) evolve for 100,000 further generations in constant conditions. As expected all populations initially undergo a fitness loss. However, after that the mutator populations started to recover. Most populations ultimately recovered their ancestors fitness, and a significant fraction became even fitter than the non-mutator control clones that evolved in parallel. By analyzing the genomes of the mutators, we show that the fitness recovery is due to two mechanisms: i. an increase in robustness through compaction of the coding part of the mutator genomes, ii. an increase of the selection coefficient that decreases the mean-fitness of the population. Strikingly the latter is due to the accumulation of non-coding sequences in the mutators genomes.

Conclusion

Our results show that the mutational burden that is classically thought to be associated with mutator phenotype is escapable. On the long run mutators adapted their genomes and reshaped the distribution of mutation effects. Therewith the lineage is able to recover fitness even though the population still suffers the elevated mutation rate. Overall these results change our view of mutator dynamics: by being able to reduce the deleterious effect of the elevated mutation rate, mutator populations may be able to last for a very long time; A situation commonly observed in nature.

The Mutator Phenotype: Adapting Microbial Evolution to Cancer Biology

The mutator phenotype hypothesis was postulated almost 40 years ago to reconcile the observation that while cancer cells display widespread mutational burden, acquisition of mutations in non-transformed cells is a rare event. Moreover, it also suggested that cancer evolution could be fostered by increased genome instability. Given the evolutionary conservation throughout the tree of life and the genetic tractability of model organisms, yeast and bacterial species pioneered studies to dissect the functions of genes required for genome maintenance (caretaker genes) or for cell growth control (gatekeeper genes). In this review, we first provide an overview of what we learned from model organisms about the roles of these genes and the genome instability that arises as a consequence of their dysregulation. We then discuss our current understanding of how mutator phenotypes shape the evolution of bacteria and yeast species. We end by bringing clinical evidence that lessons learned from single-cell organisms can be applied to tumor evolution.

Evolution of Stress-Induced Mutagenesis in the Presence of Horizontal Gene Transfer

Stress-induced mutagenesis has been observed in multiple species of bacteria and yeast. It has been suggested that in asexual populations, a mutator allele that increases the mutation rate during stress can sweep to fixation with the beneficial mutations it generates. However, even asexual microbes can undergo horizontal gene transfer and rare recombination, which typically interfere with the spread of mutator alleles. Here we examine the effect of horizontal gene transfer on the evolutionary advantage of stress-induced mutator alleles. Our results demonstrate that stress-induced mutator alleles are favored by selection even in the presence of horizontal gene transfer and more so when the mutator alleles also increase the rate of horizontal gene transfer. We suggest that when regulated by stress, mutation and horizontal gene transfer can be complementary rather than competing adaptive strategies and that stress-induced mutagenesis has important implications for evolutionary biology, ecology, and epidemiology, even in the presence of horizontal gene transfer and rare recombination.

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.

PAM-OBG: A monoamine oxidase B specific prodrug that inhibits MGMT and generates DNA interstrand crosslinks, potentiating temozolomide and chemoradiation therapy in intracranial glioblastoma

Via extensive analyses of genetic databases, we have characterized the DNA-repair capacity of glioblastoma with respect to patient survival. In addition to elevation of O⁶-methylguanine DNA methyltransferase (MGMT), down-regulation of three DNA repair pathways; canonical mismatch repair (MMR), Non-Homologous End-Joining (NHEJ), and Homologous Recombination (HR) are correlated with poor patient outcome. We have designed and tested both in vitro and in vivo, a monoamine oxidase B (MAOB) specific prodrug, PAM-OBG, that is converted by glioma MAOB into the MGMT inhibitor O⁶-benzylguanine (O⁶BG) and the DNA crosslinking agent acrolein. In cultured glioma cells, we show that PAM-OBG is converted to O⁶BG, inhibiting MGMT and sensitizing cells to DNA alkylating agents such as BCNU, CCNU, and Temozolomide (TMZ). In addition, we demonstrate that the acrolein generated is highly toxic in glioma treated with an inhibitor of Nucleotide Excision Repair (NER). In mouse intracranial models of primary human glioma, we show that PAM-OBG increases survival of mice treated with either BCNU or CCNU by a factor of six and that in a chemoradiation model utilizing six rounds of TMZ/2Gy radiation, pre-treatment with PAM-OBG more than doubled survival time.

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.

Phylogenetic context determines the role of competition in adaptive radiation

Understanding ecological mechanisms regulating the evolution of biodiversity is of much interest to ecologists and evolutionary biologists. Adaptive radiation constitutes an important evolutionary process that generates biodiversity. Competition has long been thought to influence adaptive radiation, but the directionality of its effect and associated mechanisms remain ambiguous. Here, we report a rigorous experimental test of the role of competition on adaptive radiation using the rapidly evolving bacterium Pseudomonas fluorescens SBW25 interacting with multiple bacterial species that differed in their phylogenetic distance to the diversifying bacterium. We showed that the inhibitive effect of competitors on the adaptive radiation of P. fluorescens decreased as their phylogenetic distance increased. To explain this phylogenetic dependency of adaptive radiation, we linked the phylogenetic distance between P. fluorescens and its competitors to their niche and competitive fitness differences. Competitive fitness differences, which showed weak phylogenetic signal, reduced P. fluorescens abundance and thus diversification, whereas phylogenetically conserved niche differences promoted diversification. These results demonstrate the context dependency of competitive effects on adaptive radiation, and highlight the importance of past evolutionary history for ongoing evolutionary processes.

Mutation Rate Evolution in Partially Selfing and Partially Asexual Organisms

Different factors can influence the evolution of the mutation rate of a species: costs associated with DNA replication fidelity, indirect selection caused by the mutations produced (that should generally favor lower mutation rates, given that most mutations affecting fitness are deleterious), and genetic drift, which may render selection acting on weak mutators inefficient. In this paper, we use a two-locus model to compute the strength of indirect selection acting on a modifier locus that affects the mutation rate toward a deleterious allele at a second, linked, locus, in a population undergoing partial selfing or partial clonality. The results show that uniparental reproduction increases the effect of indirect selection for lower mutation rates. Extrapolating to the case of a whole genome with many deleterious alleles, and introducing a direct cost to DNA replication fidelity, the results can be used to compute the evolutionarily stable mutation rate, U In the absence of mutational bias toward higher U, the analytical prediction fits well with individual-based, multilocus simulation results. When such a bias is added into the simulations, however, genetic drift may lead to the maintenance of higher mutation rates, and this effect may be amplified in highly selfing or highly clonal populations due to their reduced effective population size.

Variability in fitness effects can preclude selection of the fittest

Evolutionary biologists often predict the outcome of natural selection on an allele by measuring its effects on lifetime survival and reproduction of individual carriers. However, alleles affecting traits like sex, evolvability, and cooperation can cause fitness effects that depend heavily on differences in the environmental, social, and genetic context of individuals carrying the allele. This variability makes it difficult to summarize the evolutionary fate of an allele based solely on its effects on any one individual. Attempts to average over this variability can sometimes salvage the concept of fitness. In other cases evolutionary outcomes can only be predicted by considering the entire genealogy of an allele, thus limiting the utility of individual fitness altogether. We describe a number of intriguing new evolutionary phenomena that have emerged in studies that explicitly model long-term lineage dynamics and discuss implications for the evolution of infectious diseases.

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.

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.

Dynamics and Fate of Beneficial Mutations Under Lineage Contamination by Linked Deleterious Mutations

Beneficial mutations drive adaptive evolution, yet their selective advantage does not ensure their fixation. Haldane's application of single-type branching process theory showed that genetic drift alone could cause the extinction of newly arising beneficial mutations with high probability. With linkage, deleterious mutations will affect the dynamics of beneficial mutations and might further increase their extinction probability. Here, we model the lineage dynamics of a newly arising beneficial mutation as a multitype branching process. Our approach accounts for the combined effects of drift and the stochastic accumulation of linked deleterious mutations, which we call lineage contamination We first study the lineage-contamination phenomenon in isolation, deriving dynamics and survival probabilities (the complement of extinction probabilities) of beneficial lineages. We find that survival probability is zero when [Formula: see text] where U is deleterious mutation rate and [Formula: see text] is the selective advantage of the beneficial mutation in question, and is otherwise depressed below classical predictions by a factor bounded from below by [Formula: see text] We then put the lineage contamination phenomenon into the context of an evolving population by incorporating the effects of background selection. We find that, under the combined effects of lineage contamination and background selection, ensemble survival probability is never zero but is depressed below classical predictions by a factor bounded from below by [Formula: see text] where [Formula: see text] is mean selective advantage of beneficial mutations, and [Formula: see text] This factor, and other bounds derived from it, are independent of the fitness effects of deleterious mutations. At high enough mutation rates, lineage contamination can depress fixation probabilities to values that approach zero. This fact suggests that high mutation rates can, perhaps paradoxically, (1) alleviate competition among beneficial mutations, or (2) potentially even shut down the adaptive process. We derive critical mutation rates above which these two events become likely.

Effect of mismatch repair on the mutation rate of bacteriophage ϕX174

Viral mutation rates vary widely in nature, yet the mechanistic and evolutionary determinants of this variability remain unclear. Small DNA viruses mutate orders of magnitude faster than their hosts despite using host-encoded polymerases for replication, which suggests these viruses may avoid post-replicative repair. Supporting this, the genome of bacteriophage ϕX174 is completely devoid of GATC sequence motifs, which are required for methyl-directed mismatch repair in Escherichia coli. Here, we show that restoration of the randomly expected number of GATC sites leads to an eightfold reduction in the rate of spontaneous mutation of the phage, without severely impairing its replicative capacity over the short term. However, the efficacy of mismatch repair in the presence of GATC sites is limited by inefficient methylation of the viral DNA. Therefore, both GATC avoidance and DNA under-methylation elevate the mutation rate of the phage relative to that of the host. We also found that the effects of GATC sites on the phage mutation rate vary extensively depending on their specific location within the phage genome. Finally, the mutation rate reduction afforded by GATC sites is fully reverted under stress conditions, which up-regulate repair pathways and expression of error-prone host polymerases such as heat and treatment with the base analog 5-fluorouracil, suggesting that access to repair renders the phage sensitive to stress-induced mutagenesis.

Evolution of Mutation Rates in Rapidly Adapting Asexual Populations

Mutator and antimutator alleles often arise and spread in both natural microbial populations and laboratory evolution experiments. The evolutionary dynamics of these mutation rate modifiers are determined by indirect selection on linked beneficial and deleterious mutations. These indirect selection pressures have been the focus of much earlier theoretical and empirical work, but we still have a limited analytical understanding of how the interplay between hitchhiking and deleterious load influences the fates of modifier alleles. Our understanding is particularly limited when clonal interference is common, which is the regime of primary interest in laboratory microbial evolution experiments. Here, we calculate the fixation probability of a mutator or antimutator allele in a rapidly adapting asexual population, and we show how this quantity depends on the population size, the beneficial and deleterious mutation rates, and the strength of a typical driver mutation. In the absence of deleterious mutations, we find that clonal interference enhances the fixation probability of mutators, even as they provide a diminishing benefit to the overall rate of adaptation. When deleterious mutations are included, natural selection pushes the population toward a stable mutation rate that can be suboptimal for the adaptation of the population as a whole. The approach to this stable mutation rate is not necessarily monotonic: even in the absence of epistasis, selection can favor mutator and antimutator alleles that "overshoot" the stable mutation rate by substantial amounts.

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.

Fidelity drive: a mechanism for chaperone proteins to maintain stable mutation rates in prokaryotes over evolutionary time

We show a mechanism by which chaperone proteins can play a key role in maintaining the long-term evolutionary stability of mutation rates in prokaryotes with perfect genetic linkage. Since chaperones can reduce the phenotypic effects of mutations, higher mutation rate, by affecting chaperones, can increase the phenotypic effects of mutations. This in turn leads to greater mutation effect among the proteins that control mutation repair and DNA replication, resulting in large changes in mutation rate. The converse of this is that when mutation rate is low and chaperones are functioning well, then the rate of change in mutation rate will also be low, leading to low mutation rates being evolutionarily frozen. We show that the strength of this recursion is critical to determining the long-term evolutionary patterns of mutation rate among prokaryotes. If this recursion is weak, then mutation rates can grow without bound, leading to the extinction of the lineage. However, if this recursion is strong, then we can reproduce empirical patterns of prokaryotic mutation rates, where mutation rates remain stable over evolutionary time, and where most mutation rates are low, but with a significant fraction of high mutators.

Experimental evolution and the dynamics of genomic mutation rate modifiers

Because genes that affect mutation rates are themselves subject to mutation, mutation rates can be influenced by natural selection and other evolutionary forces. The population genetics of mutation rate modifier alleles has been a subject of theoretical interest for many decades. Here, we review experimental contributions to our understanding of mutation rate modifier dynamics. Numerous evolution experiments have shown that mutator alleles (modifiers that elevate the genomic mutation rate) can readily rise to high frequencies via genetic hitchhiking in non-recombining microbial populations. Whereas these results certainly provide an explanatory framework for observations of sporadically high mutation rates in pathogenic microbes and in cancer lineages, it is nonetheless true that most natural populations have very low mutation rates. This raises the interesting question of how mutator hitchhiking is suppressed or its phenotypic effect reversed in natural populations. Very little experimental work has addressed this question; with this in mind, we identify some promising areas for future experimental investigation.

Frequency-dependent selection can lead to evolution of high mutation rates

Theoretical and experimental studies have shown that high mutation rates can be advantageous, especially in novel or fluctuating environments. Here we examine how frequency-dependent competition may lead to fluctuations in trait frequencies that exert upward selective pressure on mutation rates. We use a mathematical model to show that cyclical trait dynamics generated by "rock-paper-scissors" competition can cause the mutation rate in a population to converge to a high evolutionarily stable mutation rate, reflecting a trade-off between generating novelty and reproducing past success. Introducing recombination lowers the evolutionarily stable mutation rate but allows stable coexistence between mutation rates above and below the evolutionarily stable rate. Even considering strong mutational load and ignoring the costs of faithful replication, evolution favors positive mutation rates if the selective advantage of prevailing in competition exceeds the ratio of recombining to nonrecombining offspring. We discuss a number of genomic mechanisms that may meet our theoretical requirements for the adaptive evolution of mutation. Overall, our results suggest that local mutation rates may be higher on genes influencing cyclical competition and that global mutation rates in asexual species may be higher in populations subject to strong cyclical competition.

Delayed lysis confers resistance to the nucleoside analogue 5-fluorouracil and alleviates mutation accumulation in the single-stranded DNA bacteriophage ϕX174

Rates of spontaneous mutation determine viral fitness and adaptability. In RNA viruses, treatment with mutagenic nucleoside analogues selects for polymerase variants with increased fidelity, showing that viral mutation rates can be adjusted in response to imposed selective pressures. However, this type of resistance is not possible in viruses that do not encode their own polymerases, such as single-stranded DNA viruses. We previously showed that serial passaging of bacteriophage ϕX174 in the presence of the nucleoside analogue 5-fluorouracil (5-FU) favored substitutions in the lysis protein E (P. Domingo-Calap, M. Pereira-Gomez, and R. Sanjuán, J. Virol. 86:: 9640-9646, 2012, doi:10.1128/JVI.00613-12). Here, we found that approximately half (6/12) of the amino acid replacements in the N-terminal region of this protein led to delayed lysis, and two of these changes (V2A and D8A) also conferred partial resistance to 5-FU. By delaying lysis, the V2A and D8A substitutions allowed the virus to increase the burst size per cell in the presence of 5-FU. Furthermore, these substitutions tended to alleviate drug-induced mutagenesis by reducing the number of rounds of copying required for population growth, revealing a new mechanism of resistance. This form of mutation rate regulation may also be utilized by other viruses whose replication mode is similar to that of bacteriophage ϕX174.

IMPORTANCE

Many viruses display high rates of spontaneous mutations due to defects in proofreading or postreplicative repair, allowing them to rapidly adapt to changing environments. Viral mutation rates may have been optimized to achieve high adaptability without incurring an excessive genetic load. Supporting this, RNA viruses subjected to chemical mutagenesis treatments have been shown to evolve higher-fidelity polymerases. However, many viruses cannot modulate replication fidelity because they do not encode their own polymerase. Here, we show a new mechanism for regulating viral mutation rates. We found that, under mutagenic conditions, the single-stranded bacteriophage ϕX174 evolved delayed lysis, and that this allowed the virus to increase the amount of progeny produced per cell. As a result, the viral population was amplified in fewer infection cycles, reducing the chances for mutation appearance.

The advantage of arriving first: characteristic times in finite size populations of error-prone replicators

We study the evolution of a finite size population formed by mutationally isolated lineages of error-prone replicators in a two-peak fitness landscape. Computer simulations are performed to gain a stochastic description of the system dynamics. More specifically, for different population sizes, we compute the probability of each lineage being selected in terms of their mutation rates and the amplification factors of the fittest phenotypes. We interpret the results as the compromise between the characteristic time a lineage takes to reach its fittest phenotype by crossing the neutral valley and the selective value of the sequences that form the lineages. A main conclusion is drawn: for finite population sizes, the survival probability of the lineage that arrives first to the fittest phenotype rises significantly.

Multigenerational demographic responses of sexual and asexual Artemia to chronic genotoxicity by a reference mutagen

Genotoxins are capable of multigenerational impacts on natural populations via DNA damage and mutations. Sexual reproduction is assumed to reduce the long term consequences of genotoxicity for individual fitness and should therefore reduce population level effects. However, rather few empirical studies have quantified the magnitude of this effect. We tried to analyse the multigenerational demographic responses of sexual Artemia franciscana and asexual Artemia parthenogenetica due to chronic genotoxicity by a reference mutagen, ethyl methane sulfonate (EMS). A prospective (elasticity analysis) and retrospective (differences and contributions) perturbation analysis was carried out to understand the interactions of life history traits with population growth rate λ by comparing elasticities, differences and contributions of vital rates to λ. None of the previous studies have compared the effects of chronic genotoxicity using prospective and retrospective perturbation analyses in a sexual and asexual species over generations. The behaviour of a population with lower growth rate in the presence of genotoxicants in the field was studied by simulating reduced fertilities in the LTRE design. The results of prospective and retrospective perturbation analyses of effects on λ showed that population growth rate was proportionally more sensitive to juvenile survival whereas the effect of EMS on juvenile fertility contributed more to the variations in population growth rate in both the species and this effect was due to the high growth rate of Artemia. Simulations of lower population growth rate in the model showed that adult fertility and survival are also of importance. Sexual reproduction substantially mitigated the long term consequences of genetic damage, although these would be greater if population growth rate were lower. So multigenerational population level consequences of genotoxicity were much greater in an asexual species. So asexual species, and those with a parthenogenetic phase in their life cycle, may be particularly vulnerable to the effects of environmental mutagens. Ecological risk assessments should include information from multigenerational studies, as responses to genotoxicity may vary depending on the life history strategies and reproductive modes of the species under consideration. Single generation studies may under or over-estimate risks.

Large-scale detection of in vivo transcription errors

Accurate transmission and expression of genetic information are crucial for the survival of all living organisms. Recently, the coupling of mutation accumulation experiments and next-generation sequencing has greatly expanded our knowledge of the genomic mutation rate in both prokaryotes and eukaryotes. However, because of their transient nature, transcription errors have proven extremely difficult to quantify, and current estimates of transcription fidelity are derived from artificial constructs applied to just a few organisms. Here we report a unique cDNA library preparation technique that allows error detection in natural transcripts at the transcriptome-wide level. Application of this method to the model organism Caenorhabditis elegans revealed a base misincorporation rate in mRNAs of ~4 × 10(-6) per site, with a very biased molecular spectrum. Because the proposed method is readily applicable to other organisms, this innovation provides unique opportunities for studying the incidence of transcription errors across the tree of life.

Evolutionary invasion and escape in the presence of deleterious mutations

Replicators such as parasites invading a new host species, species invading a new ecological niche, or cancer cells invading a new tissue often must mutate to adapt to a new environment. It is often argued that a higher mutation rate will favor evolutionary invasion and escape from extinction. However, most mutations are deleterious, and even lethal. We study the probability that the lineage will survive and invade successfully as a function of the mutation rate when both the initial strain and an adaptive mutant strain are threatened by lethal mutations. We show that mutations are beneficial, i.e. a non-zero mutation rate increases survival compared to the limit of no mutations, if in the no-mutation limit the survival probability of the initial strain is smaller than the average survival probability of the strains which are one mutation away. The mutation rate that maximizes survival depends on the characteristics of both the initial strain and the adaptive mutant, but if one strain is closer to the threshold governing survival then its properties will have greater influence. These conclusions are robust for more realistic or mechanistic depictions of the fitness landscapes such as a more detailed viral life history, or non-lethal deleterious mutations.

Correlation between mutation rate and genome size in riboviruses: mutation rate of bacteriophage Qβ

Genome sizes and mutation rates covary across all domains of life. In unicellular organisms and DNA viruses, they show an inverse relationship known as Drake’s rule. However, it is still unclear whether a similar relationship exists between genome sizes and mutation rates in RNA genomes. Coronaviruses, the RNA viruses with the largest genomes (∼30 kb), encode a proofreading 3′ exonuclease that allows them to increase replication fidelity. However, it is unknown whether, conversely, the RNA viruses with the smallest genomes tend to show particularly high mutation rates. To test this, we measured the mutation rate of bacteriophage Qβ, a 4.2-kb levivirus. Amber reversion-based Luria–Delbrück fluctuation tests combined with mutant sequencing gave an estimate of 1.4 × 10⁻⁴ substitutions per nucleotide per round of copying, the highest mutation rate reported for any virus using this method. This estimate was confirmed using a direct plaque sequencing approach and after reanalysis of previously published estimates for this phage. Comparison with other riboviruses (all RNA viruses except retroviruses) provided statistical support for a negative correlation between mutation rates and genome sizes. We suggest that the mutation rates of RNA viruses might be optimized for maximal adaptability and that the value of this optimum may in turn depend inversely on genome size.

Fixation of mutators in asexual populations: the role of genetic drift and epistasis

We study the evolutionary dynamics of an asexual population of nonmutators and mutators on a class of epistatic fitness landscapes. We consider the situation in which all mutations are deleterious and mutators are produced from nonmutators continually at a constant rate. We find that in an infinitely large population, a minimum nonmutator-to-mutator conversion rate is required to fix the mutators but an arbitrarily small conversion rate results in the fixation of mutators in a finite population. We calculate analytical expressions for the mutator fraction at mutation-selection balance and fixation time for mutators in a finite population when the difference between the mutation rate for mutator and nonmutator is smaller (regime I) and larger (regime II) than the selection coefficient. Our main result is that in regime I, the mutator fraction and the fixation time are independent of epistasis but in regime II, mutators are rarer and take longer to fix when the decrease in fitness with the number of deleterious mutations occurs at an accelerating rate (synergistic epistasis) than at a diminishing rate (antagonistic epistasis). Our analytical results are compared with numerics and their implications are discussed.

Stress-induced hypermutation as a physical property of life, a force of natural selection and its role in four thought experiments

The independence of genetic mutation rate from selection is central to neo-Darwinian evolutionary theory. However, it has been continuously challenged for more than 30 years by experimental evidence of genetic mutation rate transiently increasing in response to stress (stress-induced hypermutation, SIH). The prominent concept of evolved evolvability (EE) explains that natural selection for strategies more competitive at evolutionary adaptation itself gives rise to mechanisms dynamically adjusting mutation rates to environmental stress. Here, we theoretically investigate the alternative (not mutually exclusive) hypothesis that SIH is an inherent physical property of all genetically reproducing life. We define stress as any condition lowering the capability of utilizing metabolic resources for genome storage and replication. This thermodynamical analysis indicates stress-induced increases in the genetic mutation rate in genome storage and in genome replication as inherent physical properties of genetically reproducing life. Further integrating SIH into an overall organismic thermodynamic budget identifies SIH as a force of natural selection, alongside death rate, replication rate and constitutive mutation rate differences. We execute four thought experiments with a non-recombinant lesion mutant strain to predict experimental observations due to SIH in response to different stresses and stress combinations. We find (1) acceleration of adaptation over models without SIH, (2) possibility of adaptation at high stresses which are not explicable by mutation in genome replication alone and (3) different adaptive potential under high growth-inhibiting versus high lethal stresses. The predictions are directly comparable to culture experiments (colony size time courses, antibacterial resistance assay and occurrence of lesion-reversion mutant colonies) and genome sequence analysis. Considering suggestions of drug-mediated disruption of SIH and attempts to target mutation-associated sites with chemotherapeutic agents to prevent resistance, our findings seem to be relevant knowledge for resistance-averse drug development and administration.

Non-random mutation: the evolution of targeted hypermutation and hypomutation

A widely accepted tenet of evolutionary biology is that spontaneous mutations occur randomly with regard to their fitness effect. However, since the mutation rate varies along a genome and this variation can be subject to selection, organisms might evolve lower mutation rates at loci where mutations are most deleterious or increased rates where mutations are most needed. In fact, mechanisms of targeted hypermutation are known in organisms ranging from bacteria to humans. Here we review the main forces driving the evolution of local mutation rates and identify the main limiting factors. Both targeted hyper- and hypomutation can evolve, although the former is restricted to loci under very frequent positive selection and the latter is severely limited by genetic drift. Nevertheless, we show how an association of repair with transcription or chromatin-associated proteins could overcome the drift limit and lead to non-random hypomutation along the genome in most organisms.

Mutational spectrum drives the rise of mutator bacteria

Understanding how mutator strains emerge in bacterial populations is relevant both to evolutionary theory and to reduce the threat they pose in clinical settings. The rise of mutator alleles is understood as a result of their hitchhiking with linked beneficial mutations, although the factors that govern this process remain unclear. A prominent but underappreciated fact is that each mutator allele increases only a specific spectrum of mutational changes. This spectrum has been speculated to alter the distribution of fitness effects of beneficial mutations, potentially affecting hitchhiking. To study this possibility, we analyzed the fitness distribution of beneficial mutations generated from different mutator and wild-type Escherichia coli strains. Using antibiotic resistance as a model system, we show that mutational spectra can alter these distributions substantially, ultimately determining the competitive ability of each strain across environments. Computer simulation showed that the effect of mutational spectrum on hitchhiking dynamics follows a non-linear function, implying that even slight spectrum-dependent fitness differences are sufficient to alter mutator success frequency by several orders of magnitude. These results indicate an unanticipated central role for the mutational spectrum in the evolution of bacterial mutation rates. At a practical level, this study indicates that knowledge of the molecular details of resistance determinants is crucial for minimizing mutator evolution during antibiotic therapy.

Natural and laboratory populations of bacteria can readily give rise to strains with high mutation rates. The evolution of these mutator bacteria—of particular concern in clinical situations—has been understood exclusively in terms of their increased capacity to generate beneficial mutations, such as those that confer antibiotic resistance. Current models, however, have largely overlooked that each mutator allele increases only characteristic types of mutations, a prominent fact whose evolutionary consequences remain unexplored. Using laboratory Escherichia coli populations, we show that this mutational bias determines the competitiveness of different mutators across environments. Computer simulation showed that this effect can markedly influence the evolutionary fate of mutator alleles. These results indicate that this unrecognized factor can be a major determinant in the evolution of mutator bacteria and suggest future experimental approaches for improving antibiotic therapy design.

Mutation rate dynamics in a bacterial population reflect tension between adaptation and genetic load

Mutations are the ultimate source of heritable variation for evolution. Understanding how mutation rates themselves evolve is thus essential for quantitatively understanding many evolutionary processes. According to theory, mutation rates should be minimized for well-adapted populations living in stable environments, whereas hypermutators may evolve if conditions change. However, the long-term fate of hypermutators is unknown. Using a phylogenomic approach, we found that an adapting Escherichia coli population that first evolved a mutT hypermutator phenotype was later invaded by two independent lineages with mutY mutations that reduced genome-wide mutation rates. Applying neutral theory to synonymous substitutions, we dated the emergence of these mutations and inferred that the mutT mutation increased the point-mutation rate by ∼150-fold, whereas the mutY mutations reduced the rate by ∼40-60%, with a corresponding decrease in the genetic load. Thus, the long-term fate of the hypermutators was governed by the selective advantage arising from a reduced mutation rate as the potential for further adaptation declined.

Cancer in light of experimental evolution

Cancer initiation, progression, and the emergence of therapeutic resistance are evolutionary phenomena of clonal somatic cell populations. Studies in microbial experimental evolution and the theoretical work inspired by such studies are yielding deep insights into the evolutionary dynamics of clonal populations, yet there has been little explicit consideration of the relevance of this rapidly growing field to cancer biology. Here, we examine how the understanding of mutation, selection, and spatial structure in clonal populations that is emerging from experimental evolution may be applicable to cancer. Along the way, we discuss some significant ways in which cancer differs from the model systems used in experimental evolution. Despite these differences, we argue that enhanced prediction and control of cancer may be possible using ideas developed in the context of experimental evolution, and we point out some prospects for future research at the interface between these traditionally separate areas.

Contrasting dynamics of a mutator allele in asexual populations of differing size

Mutators have been shown to hitchhike in asexual populations when the anticipated beneficial mutation supply rate of the mutator subpopulation, NU(b) (for subpopulation of size N and beneficial mutation rate U(b)) exceeds that of the wild-type subpopulation. Here, we examine the effect of total population size on mutator dynamics in asexual experimental populations of Saccharomyces cerevisiae. Although mutators quickly hitchhike to fixation in smaller populations, mutator fixation requires more and more time as population size increases; this observed delay in mutator hitchhiking is consistent with the expected effect of clonal interference. Interestingly, despite their higher beneficial mutation supply rate, mutators are supplanted by the wild type in very large populations. We postulate that this striking reversal in mutator dynamics is caused by an interaction between clonal interference, the fitness cost of the mutator allele, and infrequent large-effect beneficial mutations in our experimental populations. Our work thus identifies a potential set of circumstances under which mutator hitchhiking can be inhibited in natural asexual populations, despite recent theoretical predictions that such populations should have a net tendency to evolve ever-higher genomic mutation rates.

Hypermutation and stress adaptation in bacteria

Hypermutability is a phenotype characterized by a moderate to high elevation of spontaneous mutation rates and could result from DNA replication errors, defects in error correction mechanisms and many other causes. The elevated mutation rates are helpful to organisms to adapt to sudden and unforeseen threats to survival. At the same time hypermutability also leads to the generation of many deleterious mutations which offset its adaptive value and therefore disadvantageous. Nevertheless, it is very common in nature, especially among clinical isolates of pathogens. Hypermutability is inherited by indirect (second order) selection along with the beneficial mutations generated. At large population sizes and high mutation rates many cells in the population could concurrently acquire beneficial mutations of varying adaptive (fitness) values. These lineages compete with the ancestral cells and also among themselves for fixation. The one with the 'fittest' mutation gets fixed ultimately while the others are lost. This has been called 'clonal interference' which puts a speed limit on adaptation. The original clonal interference hypothesis has been modified recently. Nonheritable (transient) hypermtability conferring significant adaptive benefits also occur during stress response although its molecular basis remains controversial. The adaptive benefits of heritable hypermutability are discussed with emphasis on host-pathogen interactions.