Rate and effects of spontaneous mutations that affect fitness in mutator Escherichia coli

Reversions mask the contribution of adaptive evolution in microbiomes

When examining bacterial genomes for evidence of past selection, the results depend heavily on the mutational distance between chosen genomes. Even within a bacterial species, genomes separated by larger mutational distances exhibit stronger evidence of purifying selection as assessed by dN/dS, the normalized ratio of nonsynonymous to synonymous mutations. Here, we show that the classical interpretation of this scale dependence, weak purifying selection, leads to problematic mutation accumulation when applied to available gut microbiome data. We propose an alternative, adaptive reversion model with opposite implications for dynamical intuition and applications of dN/dS. Reversions that occur and sweep within-host populations are nearly guaranteed in microbiomes due to large population sizes, short generation times, and variable environments. Using analytical and simulation approaches, we show that adaptive reversion can explain the dN/dS decay given only dozens of locally fluctuating selective pressures, which is realistic in the context of Bacteroides genomes. The success of the adaptive reversion model argues for interpreting low values of dN/dS obtained from long timescales with caution as they may emerge even when adaptive sweeps are frequent. Our work thus inverts the interpretation of an old observation in bacterial evolution, illustrates the potential of mutational reversions to shape genomic landscapes over time, and highlights the importance of studying bacterial genomic evolution on short timescales.

Reversions mask the contribution of adaptive evolution in microbiomes

When examining bacterial genomes for evidence of past selection, the results obtained depend heavily on the mutational distance between chosen genomes. Even within a bacterial species, genomes separated by larger mutational distances exhibit stronger evidence of purifying selection as assessed byd N / d S , the normalized ratio of nonsynonymous to synonymous mutations. Here, we show that the classical interpretation of this scale-dependence, weak purifying selection, leads to problematic mutation accumulation when applied to available gut microbiome data. We propose an alternative, adaptive reversion model with exactly opposite implications for dynamical intuition and applications ofd N / d S . Reversions that occur and sweep within-host populations are nearly guaranteed in microbiomes due to large population sizes, short generation times, and variable environments. Using analytical and simulation approaches, we show that adaptive reversion can explain thed N / d S decay given only dozens of locally-fluctuating selective pressures, which is realistic in the context of Bacteroides genomes. The success of the adaptive reversion model argues for interpreting low values ofd N / d S obtained from long-time scales with caution, as they may emerge even when adaptive sweeps are frequent. Our work thus inverts the interpretation of an old observation in bacterial evolution, illustrates the potential of mutational reversions to shape genomic landscapes over time, and highlights the importance of studying bacterial genomic evolution on short time scales.

Mutualism at the leading edge: insights into the eco-evolutionary dynamics of host-symbiont communities during range expansion

The evolution of mutualism between host and symbiont communities plays an essential role in maintaining ecosystem function and should therefore have a profound effect on their range expansion dynamics. In particular, the presence of mutualistic symbionts at the leading edge of a host-symbiont community should enhance its propagation in space. We develop a theoretical framework that captures the eco-evolutionary dynamics of host-symbiont communities, to investigate how the evolution of resource exchange may shape community structure during range expansion. We consider a community with symbionts that are mutualistic or parasitic to various degrees, where parasitic symbionts receive the same amount of resource from the host as mutualistic symbionts, but at a lower cost. The selective advantage of parasitic symbionts over mutualistic ones is increased with resource availability (i.e. with host density), promoting mutualism at the range edges, where host density is low, and parasitism at the population core, where host density is higher. This spatial selection also influences the speed of spread. We find that the host growth rate (which depends on the average benefit provided by the symbionts) is maximal at the range edges, where symbionts are more mutualistic, and that host-symbiont communities with high symbiont density at their core (e.g. resulting from more mutualistic hosts) spread faster into new territories. These results indicate that the expansion of host-symbiont communities is pulled by the hosts but pushed by the symbionts, in a unique push-pull dynamic where both the host and symbionts are active and tightly-linked players.

Comparative genomics hints at dispensability of multiple essential genes in two Escherichia coli L-form strains

Despite the critical role of bacterial cell walls in maintaining cell shapes, certain environmental stressors can induce the transition of many bacterial species into a wall-deficient state called L-form. Long-term induced Escherichia coli L-forms lose their rod shape and usually hold significant mutations that affect cell division and growth. Besides this, the genetic background of L-form bacteria is still poorly understood. In the present study, the genomes of two stable L-form strains of E. coli (NC-7 and LWF+) were sequenced and their gene mutation status was determined and compared with their parental strains. Comparative genomic analysis between two L-forms reveals both unique adaptions and common mutated genes, many of which belong to essential gene categories not involved in cell wall biosynthesis, indicating that L-form genetic adaptation impacts crucial metabolic pathways. Missense variants from L-forms and Lenski's long-term evolution experiment (LTEE) were analyzed in parallel using an optimized DeepSequence pipeline to investigate predicted mutation effects (α) on protein functions. We report that the two L-form strains analyzed display a frequency of 6-10% (0% for LTEE) in mutated essential genes where the missense variants have substantial impact on protein functions (α<0.5). This indicates the emergence of different survival strategies in L-forms through changes in essential genes during adaptions to cell wall deficiency. Collectively, our results shed light on the detailed genetic background of two E. coli L-forms and pave the way for further investigations of the gene functions in L-form bacterial models.

A Single Nucleotide Change in the polC DNA Polymerase III in Clostridium thermocellum Is Sufficient To Create a Hypermutator Phenotype

Clostridium thermocellum is a thermophilic, anaerobic bacterium that natively ferments cellulose to ethanol and is a candidate for cellulosic biofuel production. Recently, we identified a hypermutator strain of C. thermocellum with a C669Y mutation in the polC gene, which encodes a DNA polymerase III enzyme. Here, we reintroduced this mutation using recently developed CRISPR tools to demonstrate that this mutation is sufficient to recreate the hypermutator phenotype. The resulting strain shows an approximately 30-fold increase in the mutation rate. This mutation is hypothesized to function by interfering with metal ion coordination in the PHP (polymerase and histidinol phosphatase) domain, which is responsible for proofreading. The ability to selectively increase the mutation rate in C. thermocellum is a useful tool for future directed evolution experiments. IMPORTANCE Cellulosic biofuels are a promising approach to decarbonize the heavy-duty-transportation sector. A longstanding barrier to cost-effective cellulosic biofuel production is the recalcitrance of cellulose to solubilization. Native cellulose-consuming organisms, such as Clostridium thermocellum, are promising candidates for cellulosic biofuel production; however, they often need to be genetically modified to improve product formation. One approach is adaptive laboratory evolution. Our findings demonstrate a way to increase the mutation rate in this industrially relevant organism, which can reduce the time needed for adaptive evolution experiments.

Selection bias in mutation accumulation

Mutation accumulation (MA) experiments, in which de novo mutations are sampled and subsequently characterized, are an essential tool in understanding the processes underlying evolution. In microbial populations, MA protocols typically involve a period of population growth between severe bottlenecks, such that a single individual can form a visible colony. While it has long been appreciated that the action of positive selection during this growth phase cannot be eliminated, it is typically assumed to be negligible. Here, we quantify the effect of both positive and negative selection in MA studies, demonstrating that selective effects can substantially bias the distribution of fitness effects (DFE) and mutation rates estimated from typical MA protocols in microbes. We then present a simple correction for this bias which applies to both beneficial and deleterious mutations, and can be used to correct the observed DFE in multiple environments. We use simulated MA experiments to illustrate the extent to which the MA-inferred DFE differs from the underlying true DFE, and demonstrate that the proposed correction accurately reconstructs the true DFE over a wide range of scenarios; we also provide an example of these corrections applied to experimental data. These results highlight that positive selection during microbial MA experiments is in fact not negligible, but can be corrected to gain a more accurate understanding of fundamental evolutionary parameters. This article is protected by copyright. All rights reserved.

Precise measurement of the fitness effects of spontaneous mutations by droplet digital PCR in Burkholderia cenocepacia

Understanding how mutations affect survivability is a key component to knowing how organisms and complex traits evolve. However, most mutations have a minor effect on fitness and these effects are difficult to resolve using traditional molecular techniques. Therefore, there is a dire need for more accurate and precise fitness measurements methods. Here, we measured the fitness effects in Burkholderia cenocepacia HI2424 mutation accumulation (MA) lines using droplet-digital polymerase chain reaction (ddPCR). Overall, the fitness measurements from ddPCR-MA are correlated positively with fitness measurements derived from traditional phenotypic marker assays (r = 0.297, P = 0.05), but showed some differences. First, ddPCR had significantly lower measurement variance in fitness (F = 3.78, P < 2.6 × 10-13) in control experiments. Second, the mean fitness from ddPCR-MA measurements were significantly lower than phenotypic marker assays (-0.0041 vs -0.0071, P = 0.006). Consistent with phenotypic marker assays, ddPCR-MA measurements observed multiple (27/43) lineages that significantly deviated from mean fitness, suggesting that a majority of the mutations are neutral or slightly deleterious and intermixed with a few mutations that have extremely large effects. Of these mutations, we found a significant excess of mutations within DNA excinuclease and Lys R transcriptional regulators that have extreme deleterious and beneficial effects, indicating that modifications to transcription and replication may have a strong effect on organismal fitness. This study demonstrates the power of ddPCR as a ubiquitous method for high-throughput fitness measurements in both DNA- and RNA-based organisms regardless of cell type or physiology.

Evolution of Pseudomonas aeruginosa toward higher fitness under standard laboratory conditions

Identifying genetic factors that contribute to the evolution of adaptive phenotypes in pathogenic bacteria is key to understanding the establishment of infectious diseases. In this study, we performed mutation accumulation experiments to record the frequency of mutations and their effect on fitness in hypermutator strains of the environmental bacterium Pseudomonas aeruginosa in comparison to the host-niche-adapted Salmonella enterica. We demonstrate that P. aeruginosa, but not S. enterica, hypermutators evolve toward higher fitness under planktonic conditions. Adaptation to increased growth performance was accompanied by a reversible perturbing of the local genetic context of membrane and cell wall biosynthesis genes. Furthermore, we observed a fine-tuning of complex regulatory circuits involving multiple di-guanylate modulating enzymes that regulate the transition between fast growing planktonic and sessile biofilm-associated lifestyles. The redundancy and local specificity of the di-guanylate signaling pathways seem to allow a convergent shift toward increased growth performance across niche-adapted clonal P. aeruginosa lineages, which is accompanied by a pronounced heterogeneity of their motility, virulence, and biofilm phenotypes.

Warmer temperatures enhance beneficial mutation effects

Temperature determines the rates of all biochemical and biophysical processes, and is also believed to be a key driver of macroevolutionary patterns. It is suggested that physiological constraints at low temperatures may diminish the fitness advantages of otherwise beneficial mutations; by contrast, relatively high, benign, temperatures allow beneficial mutations to efficiently show their phenotypic effects. To experimentally test this "mutational effects" mechanism, we examined the fitness effects of mutations across a temperature gradient using bacterial genotypes from the early stage of a mutation accumulation experiment with Escherichia coli. While the incidence of beneficial mutations did not significantly change across environmental temperatures, the number of mutations that conferred strong beneficial fitness effects was greater at higher temperatures. The results therefore support the hypothesis that warmer temperatures increase the chance and magnitude of positive selection, with implications for explaining the geographic patterns in evolutionary rates and understanding contemporary evolution under global warming.

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

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

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

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.

Mutation bias and GC content shape antimutator invasions

Mutators represent a successful strategy in rapidly adapting asexual populations, but theory predicts their eventual extinction due to their unsustainably large deleterious load. While antimutator invasions have been documented experimentally, important discrepancies among studies remain currently unexplained. Here we show that a largely neglected factor, the mutational idiosyncrasy displayed by different mutators, can play a major role in this process. Analysing phylogenetically diverse bacteria, we find marked and systematic differences in the protein-disruptive effects of mutations caused by different mutators in species with different GC compositions. Computer simulations show that these differences can account for order-of-magnitude changes in antimutator fitness for a realistic range of parameters. Overall, our results suggest that antimutator dynamics may be highly dependent on the specific genetic, ecological and evolutionary history of a given population. This context-dependency further complicates our understanding of mutators in clinical settings, as well as their role in shaping bacterial genome size and composition.

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.

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.

Accumulation of Deleterious Mutations During Bacterial Range Expansions

Recent theory predicts that the fitness of pioneer populations can decline when species expand their range, due to high rates of genetic drift on wave fronts making selection less efficient at purging deleterious variants. To test these predictions, we studied the fate of mutator bacteria expanding their range for 1650 generations on agar plates. In agreement with theory, we find that growth abilities of strains with a high mutation rate (HMR lines) decreased significantly over time, unlike strains with a lower mutation rate (LMR lines) that present three to four times fewer mutations. Estimation of the distribution of fitness effect under a spatially explicit model reveals a mean negative effect for new mutations (-0.38%), but it suggests that both advantageous and deleterious mutations have accumulated during the experiment. Furthermore, the fitness of HMR lines measured in different environments has decreased relative to the ancestor strain, whereas that of LMR lines remained unchanged. Contrastingly, strains with a HMR evolving in a well-mixed environment accumulated less mutations than agar-evolved strains and showed an increased fitness relative to the ancestor. Our results suggest that spatially expanding species are affected by deleterious mutations, leading to a drastic impairment of their evolutionary potential.

Extremely Rare Polymorphisms in Saccharomyces cerevisiae Allow Inference of the Mutational Spectrum

The characterization of mutational spectra is usually carried out in one of three ways-by direct observation through mutation accumulation (MA) experiments, through parent-offspring sequencing, or by indirect inference from sequence data. Direct observations of spontaneous mutations with MA experiments are limited, given (i) the rarity of spontaneous mutations, (ii) applicability only to laboratory model species with short generation times, and (iii) the possibility that mutational spectra under lab conditions might be different from those observed in nature. Trio sequencing is an elegant solution, but it is not applicable in all organisms. Indirect inference, usually from divergence data, faces no such technical limitations, but rely upon critical assumptions regarding the strength of natural selection that are likely to be violated. Ideally, new mutational events would be directly observed before the biased filter of selection, and without the technical limitations common to lab experiments. One approach is to identify very young mutations from population sequencing data. Here we do so by leveraging two characteristics common to all new mutations-new mutations are necessarily rare in the population, and absent in the genomes of immediate relatives. From 132 clinical yeast strains, we were able to identify 1,425 putatively new mutations and show that they exhibit extremely low signatures of selection, as well as display a mutational spectrum that is similar to that identified by a large scale MA experiment. We verify that population sequencing data are a potential wealth of information for inferring mutational spectra, and should be considered for analysis where MA experiments are infeasible or especially tedious.

The Nonstationary Dynamics of Fitness Distributions: Asexual Model with Epistasis and Standing Variation

Various models describe asexual evolution by mutation, selection, and drift. Some focus directly on fitness, typically modeling drift but ignoring or simplifying both epistasis and the distribution of mutation effects (traveling wave models). Others follow the dynamics of quantitative traits determining fitness (Fisher's geometric model), imposing a complex but fixed form of mutation effects and epistasis, and often ignoring drift. In all cases, predictions are typically obtained in high or low mutation rate limits and for long-term stationary regimes, thus losing information on transient behaviors and the effect of initial conditions. Here, we connect fitness-based and trait-based models into a single framework, and seek explicit solutions even away from stationarity. The expected fitness distribution is followed over time via its cumulant generating function, using a deterministic approximation that neglects drift. In several cases, explicit trajectories for the full fitness distribution are obtained for arbitrary mutation rates and standing variance. For nonepistatic mutations, especially with beneficial mutations, this approximation fails over the long term but captures the early dynamics, thus complementing stationary stochastic predictions. The approximation also handles several diminishing returns epistasis models (e.g., with an optimal genotype); it can be applied at and away from equilibrium. General results arise at equilibrium, where fitness distributions display a "phase transition" with mutation rate. Beyond this phase transition, in Fisher's geometric model, the full trajectory of fitness and trait distributions takes a simple form; robust to the details of the mutant phenotype distribution. Analytical arguments are explored regarding why and when the deterministic approximation applies.

The Fitness Effects of Spontaneous Mutations Nearly Unseen by Selection in a Bacterium with Multiple Chromosomes

Mutation accumulation (MA) experiments employ the strategy of minimizing the population size of evolving lineages to greatly reduce effects of selection on newly arising mutations. Thus, most mutations fix within MA lines independently of their fitness effects. This approach, more recently combined with genome sequencing, has detailed the rates, spectra, and biases of different mutational processes. However, a quantitative understanding of the fitness effects of mutations virtually unseen by selection has remained an untapped opportunity. Here, we analyzed the fitness of 43 sequenced MA lines of the multi-chromosome bacterium Burkholderia cenocepacia that had each undergone 5554 generations of MA and accumulated an average of 6.73 spontaneous mutations. Most lineages exhibited either neutral or deleterious fitness in three different environments in comparison with their common ancestor. The only mutational class that was significantly overrepresented in lineages with reduced fitness was the loss of the plasmid, though nonsense mutations, missense mutations, and coding insertion-deletions were also overrepresented in MA lineages whose fitness had significantly declined. Although the overall distribution of fitness effects was similar between the three environments, the magnitude and even the sign of the fitness of a number of lineages changed with the environment, demonstrating that the fitness of some genotypes was environmentally dependent. These results present an unprecedented picture of the fitness effects of spontaneous mutations in a bacterium with multiple chromosomes and provide greater quantitative support for the theory that the vast majority of spontaneous mutations are neutral or deleterious.

Neutral null models for diversity in serial transfer evolution experiments

Evolution experiments with microorganisms coupled with genome-wide sequencing now allow for the systematic study of population genetic processes under a wide range of conditions. In learning about these processes in natural, sexual populations, neutral models that describe the behavior of diversity and divergence summaries have played a pivotal role. It is therefore natural to ask whether neutral models, suitably modified, could be useful in the context of evolution experiments. Here, we introduce coalescent models for polymorphism and divergence under the most common experimental evolution assay, a serial transfer experiment. This relatively simple setting allows us to address several issues that could affect diversity patterns in evolution experiments, whether selection is operating or not: the transient behavior of neutral polymorphism in an experiment beginning from a single clone, the effects of randomness in the timing of cell division and noisiness in population size in the dilution stage. In our analyses and discussion, we emphasize the implications for experiments aimed at measuring diversity patterns and making inferences about population genetic processes based on these measurements.

Fitness is strongly influenced by rare mutations of large effect in a microbial mutation accumulation experiment

Our understanding of the evolutionary consequences of mutation relies heavily on estimates of the rate and fitness effect of spontaneous mutations generated by mutation accumulation (MA) experiments. We performed a classic MA experiment in which frequent sampling of MA lines was combined with whole genome resequencing to develop a high-resolution picture of the effect of spontaneous mutations in a hypermutator (ΔmutS) strain of the bacterium Pseudomonas aeruginosa. After ∼644 generations of mutation accumulation, MA lines had accumulated an average of 118 mutations, and we found that average fitness across all lines decayed linearly over time. Detailed analyses of the dynamics of fitness change in individual lines revealed that a large fraction of the total decay in fitness (42.3%) was attributable to the fixation of rare, highly deleterious mutations (comprising only 0.5% of fixed mutations). Furthermore, we found that at least 0.64% of mutations were beneficial and probably fixed due to positive selection. The majority of mutations that fixed (82.4%) were base substitutions and we failed to find any signatures of selection on nonsynonymous or intergenic mutations. Short indels made up a much smaller fraction of the mutations that were fixed (17.4%), but we found evidence of strong selection against indels that caused frameshift mutations in coding regions. These results help to quantify the amount of natural selection present in microbial MA experiments and demonstrate that changes in fitness are strongly influenced by rare mutations of large effect.

An ABC method for estimating the rate and distribution of effects of beneficial mutations

Determining the distribution of adaptive mutations available to natural selection is a difficult task. These are rare events and most of them are lost by chance. Some theoretical works propose that the distribution of newly arising beneficial mutations should be close to exponential. Empirical data are scarce and do not always support an exponential distribution. Analysis of the dynamics of adaptation in asexual populations of microorganisms has revealed that these can be summarized by two effective parameters, the effective mutation rate, U_e, and the effective selection coefficient of a beneficial mutation, S_e. Here, we show that these effective parameters will not always reflect the rate and mean effect of beneficial mutations, especially when the distribution of arising mutations has high variance, and the mutation rate is high. We propose a method to estimate the distribution of arising beneficial mutations, which is motivated by a common experimental setup. The method, which we call One Biallelic Marker Approximate Bayesian Computation, makes use of experimental data consisting of periodic measures of neutral marker frequencies and mean population fitness. Using simulations, we find that this method allows the discrimination of the shape of the distribution of arising mutations and that it provides reasonable estimates of their rates and mean effects in ranges of the parameter space that may be of biological relevance.

Rates of fitness decline and rebound suggest pervasive epistasis

Unraveling the factors that determine the rate of adaptation is a major question in evolutionary biology. One key parameter is the effect of a new mutation on fitness, which invariably depends on the environment and genetic background. The fate of a mutation also depends on population size, which determines the amount of drift it will experience. Here, we manipulate both population size and genotype composition and follow adaptation of 23 distinct Escherichia coli genotypes. These have previously accumulated mutations under intense genetic drift and encompass a substantial fitness variation. A simple rule is uncovered: the net fitness change is negatively correlated with the fitness of the genotype in which new mutations appear—a signature of epistasis. We find that Fisher's geometrical model can account for the observed patterns of fitness change and infer the parameters of this model that best fit the data, using Approximate Bayesian Computation. We estimate a genomic mutation rate of 0.01 per generation for fitness altering mutations, albeit with a large confidence interval, a mean fitness effect of mutations of −0.01, and an effective number of traits nine in mutS⁻E. coli. This framework can be extended to confront a broader range of models with data and test different classes of fitness landscape models.

Competence in Streptococcus pneumoniae is a response to an increasing mutational burden

Competence for genetic transformation in Streptococcus pneumoniae has previously been described as a quorum-sensing trait regulated by a secreted peptide pheromone. Recently we demonstrated that competence is also activated by reduction in the accuracy of protein biosynthesis. We have now investigated whether errors upstream of translation in the form of random genomic mutations can provide a similar stimulus. Here we show that generation of a mutator phenotype in S. pneumoniae through deletions of mutX, hexA or hexB enhanced the expression of competence. Similarly, chemical mutagenesis with the nucleotide analog dPTP promoted development of competence. To investigate the relationship between mutational load and the activation of competence, replicate lineages of the mutX strain were serially passaged under conditions of relaxed selection allowing random accumulation of secondary mutations. Competence increased with propagation in these lineages but not in control lineages having wild-type mutX. Resequencing of these derived strains revealed between 1 and 9 single nucleotide polymorphisms (SNPs) per lineage, which were broadly distributed across the genome and did not involve known regulators of competence. Notably, the frequency of competence development among the sequenced strains correlated significantly with the number of nonsynonymous mutations that had been acquired. Together, these observations provide support for the hypothesis that competence in S. pneumoniae is regulated in response to the accumulated burden of coding mutations in the bacterial genome. In contrast to previously described DNA damage response systems that are activated by physical lesions in the chromosome, this pneumococcal pathway may represent a unique stress response system that monitors the coding integrity of the genome.

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.

Discussion on research methods of bacterial resistant mutation mechanisms under selective culture--uncertainty analysis of data from the Luria-Delbrück fluctuation experiment

Whether bacterial drug-resistance is drug-induced or results from rapid propagation of random spontaneous mutations in the flora prior to exposure, remains a long-term key issue concerned and debated in both genetics and medicinal fields. In a pioneering study, Luria and Delbrück exposed E. coli to T1 phage, to investigate whether the number of resistant colonies followed the Poisson distribution. They deduced that the development of resistant colonies is independent of phage presence. Similar results have since been obtained on solid medium containing antibacterial agents. Luria and Delbrück's conclusions were long considered a gold standard for analyzing drug resistance mutations. More recently, the concept of adaptive mutation has triggered controversy over this approach. Microbiological observation shows that, following exposure to drugs of various concentrations, drug-resistant cells emerge and multiply depending on the time course, and show a process function, inconsistent with the definition of Poisson distribution (which assumes not only that resistance is independent of drug quantity but follows no specific time course). At the same time, since cells tend to aggregate after division rather than separating, colonies growing on drug plates arise from the multiplication of resistant bacteria cells of various initial population sizes. Thus, statistical analysis based on equivalence of initial populations will yield erroneous results. In this paper, 310 data from the Luria-Delbrück fluctuation experiment were reanalyzed from this perspective. In most cases, a high-end abnormal value, resulting from the non-synchronous variation of the two above-mentioned time variables, was observed. Therefore, the mean value cannot be regarded as an unbiased expectation estimate. The ratio between mean value and variance was similarly incomparable, because two different sampling methods were used. In fact, the Luria-Delbrück data appear to follow an aggregated, rather than Poisson distribution. In summary, the statistical analysis of Luria and Delbrück is insufficient to describe rules of resistant mutant development and multiplication. Correction of this historical misunderstanding will enable new insight into bacterial resistance mechanisms.

Rate and molecular spectrum of spontaneous mutations in the bacterium Escherichia coli as determined by whole-genome sequencing

Knowledge of the rate and nature of spontaneous mutation is fundamental to understanding evolutionary and molecular processes. In this report, we analyze spontaneous mutations accumulated over thousands of generations by wild-type Escherichia coli and a derivative defective in mismatch repair (MMR), the primary pathway for correcting replication errors. The major conclusions are (i) the mutation rate of a wild-type E. coli strain is ~1 × 10(-3) per genome per generation; (ii) mutations in the wild-type strain have the expected mutational bias for G:C > A:T mutations, but the bias changes to A:T > G:C mutations in the absence of MMR; (iii) during replication, A:T > G:C transitions preferentially occur with A templating the lagging strand and T templating the leading strand, whereas G:C > A:T transitions preferentially occur with C templating the lagging strand and G templating the leading strand; (iv) there is a strong bias for transition mutations to occur at 5'ApC3'/3'TpG5' sites (where bases 5'A and 3'T are mutated) and, to a lesser extent, at 5'GpC3'/3'CpG5' sites (where bases 5'G and 3'C are mutated); (v) although the rate of small (≤4 nt) insertions and deletions is high at repeat sequences, these events occur at only 1/10th the genomic rate of base-pair substitutions. MMR activity is genetically regulated, and bacteria isolated from nature often lack MMR capacity, suggesting that modulation of MMR can be adaptive. Thus, comparing results from the wild-type and MMR-defective strains may lead to a deeper understanding of factors that determine mutation rates and spectra, how these factors may differ among organisms, and how they may be shaped by environmental conditions.

Dynamic mutation-selection balance as an evolutionary attractor

The vast majority of mutations are deleterious and are eliminated by purifying selection. Yet in finite asexual populations, purifying selection cannot completely prevent the accumulation of deleterious mutations due to Muller's ratchet: once lost by stochastic drift, the most-fit class of genotypes is lost forever. If deleterious mutations are weakly selected, Muller's ratchet can lead to a rapid degradation of population fitness. Evidently, the long-term stability of an asexual population requires an influx of beneficial mutations that continuously compensate for the accumulation of the weakly deleterious ones. Hence any stable evolutionary state of a population in a static environment must involve a dynamic mutation-selection balance, where accumulation of deleterious mutations is on average offset by the influx of beneficial mutations. We argue that such a state can exist for any population size N and mutation rate U and calculate the fraction of beneficial mutations, ε, that maintains the balanced state. We find that a surprisingly low ε suffices to achieve stability, even in small populations in the face of high mutation rates and weak selection, maintaining a well-adapted population in spite of Muller's ratchet. This may explain the maintenance of mitochondria and other asexual genomes.

Antibiotic resistance and stress in the light of Fisher's model

The role of mutations in evolution depends upon the distribution of their effects on fitness. This distribution is likely to depend on the environment. Indeed genotype-by-environment interactions are key for the process of local adaptation and ecological specialization. An important trait in bacterial evolution is antibiotic resistance, which presents a clear case of change in the direction of selection between environments with and without antibiotics. Here, we study the distribution of fitness effects of mutations, conferring antibiotic resistance to Escherichia coli, in benign and stressful environments without drugs. We interpret the distributions in the light of a fitness landscape model that assumes a single fitness peak. We find that mutation effects (s) are well described by a shifted gamma distribution, with a shift parameter that reflects the distance to the fitness peak and varies across environments. Consistent with the theoretical predictions of Fisher's geometrical model, with a Gaussian relationship between phenotype and fitness, we find that the main effect of stress is to increase the variance in s. Our findings are in agreement with the results of a recent meta-analysis, which suggest that a simple fitness landscape model may capture the variation of mutation effects across species and environments.

Fitness effects of mutations in bacteria

Mutation is the primary source of variation in any organism. Without it, natural selection cannot operate and organisms cannot adapt to novel environments. Mutation is also generally a source of defect: many mutations are not neutral but cause fitness decreases in the organisms where they arise. In bacteria, another important source of variation is horizontal gene transfer. This source of variation can also cause beneficial or deleterious effects. Determining the distribution of fitness effects of mutations in different environments and genetic backgrounds is an active research field. In bacteria, knowledge of these distributions is key for understanding important traits. For example, for determining the dynamics of microorganisms with a high genomic mutation rate (mutators), and for understanding the evolution of antibiotic resistance, and the emergence of pathogenic traits. All of these characteristics are extremely relevant for human health both at the individual and population levels. Experimental evolution has been a valuable tool to address these questions. Here, we review some of the important findings of mutation effects in bacteria revealed through laboratory experiments.

Cost of antibiotic resistance and the geometry of adaptation

The distribution of effects of beneficial mutations is key to our understanding of biological adaptation. Yet, empirical estimates of this distribution are scarce, and its functional form is largely unknown. Theoretical models of adaptation predict that the functional form of this distribution should depend on the distance to the optimum. Here, we estimate the rate and distribution of adaptive mutations that compensate for the effect of a single deleterious mutation, which causes antibiotic resistance. Using a system with multiple molecular markers, we estimate the distribution of fitness effects of mutations at two distances from the adaptive peak in 60 populations of Escherichia coli. We find that beneficial mutations, which can contribute to compensatory evolution, occur at very high rates, of the order of 10⁻⁵ per genome per generation and can be detected within a few tens of generations. They cause an average fitness increase of 2.5% and 3.6%, depending on the cost of resistance, which is expected under Fisher's geometrical model of adaptation. Moreover, we provide the first description of the distribution of beneficial mutations, segregating during the process of compensatory evolution, to antibiotic resistances bearing different costs. Hence, these results have important implications to understanding the spread and maintenance of antibiotic resistance in bacteria.

Frequent beneficial mutations during single-colony serial transfer of Streptococcus pneumoniae

The appearance of new mutations within a population provides the raw material for evolution. The consistent decline in fitness observed in classical mutation accumulation studies has provided support for the long-held view that deleterious mutations are more common than beneficial mutations. Here we present results of a study using a mutation accumulation design with the bacterium Streptococcus pneumoniae in which the fitness of the derived populations increased. This rise in fitness was associated specifically with adaptation to survival during brief stationary phase periods between single-colony population bottlenecks. To understand better the population dynamics behind this unanticipated adaptation, we developed a maximum likelihood model describing the processes of mutation and stationary-phase selection in the context of frequent population bottlenecks. Using this model, we estimate that the rate of beneficial mutations may be as high as 4.8×10⁻⁴ events per genome for each time interval corresponding to the pneumococcal generation time. This rate is several orders of magnitude higher than earlier estimates of beneficial mutation rates in bacteria but supports recent results obtained through the propagation of small populations of Escherichia coli. Our findings indicate that beneficial mutations may be relatively frequent in bacteria and suggest that in S. pneumoniae, which develops natural competence for transformation, a steady supply of such mutations may be available for sampling by recombination.

Beneficial mutations have long been considered extremely rare events and were thought to occur with a frequency of approximately one out of a billion times that a bacterium replicates its genome. Rare beneficial mutations would then be amplified by natural selection from the more frequent background of harmful mutations. Mutation accumulation experiments probe the nature of these spontaneous mutations by monitoring changes in fitness of model organisms propagated in the laboratory through numerous generations under conditions where the effects of selection are minimal. Previous mutation accumulation experiments have shown that organisms under study have declined in fitness as random mutations accrue in their genomes, consistent with a predominance of deleterious mutations. We conducted a mutation accumulation study with the bacterial pathogen S. pneumoniae in which a broad measure of fitness instead rose. We demonstrate that this unexpected adaptation was due to frequent beneficial mutations that were further amplified by selection in stationary-phase bacterial colonies. Together with recent work using E. coli, these results demonstrate that beneficial mutations can be common in bacteria and may contribute to our understanding of the evolution of traits such as antibiotic resistance and virulence.

Kick-starting the ratchet: the fate of mutators in an asexual population

Muller's ratchet operates in asexual populations without intergenomic recombination. In this case, deleterious mutations will accumulate and population fitness will decline over time, possibly endangering the survival of the species. Mutator mutations, i.e., mutations that lead to an increased mutation rate, will play a special role for the behavior of the ratchet. First, they are part of the ratchet and can come to dominance through accumulation in the ratchet. Second, the fitness-loss rate of the ratchet is very sensitive to changes in the mutation rate and even a modest increase can easily set the ratchet in motion. In this article we simulate the interplay between fitness loss from Muller's ratchet and the evolution of the mutation rate from the fixation of mutator mutations. As long as the mutation rate is increased in sufficiently small steps, an accelerating ratchet and eventual extinction are inevitable. If this can be countered by antimutators, i.e., mutations that reduce the mutation rate, an equilibrium can be established for the mutation rate at some level that may allow survival. However, the presence of the ratchet amplifies fluctuations in the mutation rate and, even at equilibrium, these fluctuations can lead to dangerous bursts in the ratchet. We investigate the timescales of these processes and discuss the results with reference to the genome degradation of the aphid endosymbiont Buchnera aphidicola.

Mutational robustness of ribosomal protein genes

The distribution of fitness effects (DFE) of mutations is of fundamental importance for understanding evolutionary dynamics and complex diseases and for conserving threatened species. DFEs estimated from DNA sequences have rarely been subject to direct experimental tests. We used a bacterial system in which the fitness effects of a large number of defined single mutations in two ribosomal proteins were measured with high sensitivity. The obtained DFE appears to be unimodal, where most mutations (120 out of 126) are weakly deleterious and the remaining ones are potentially neutral. The DFEs for synonymous and nonsynonymous substitutions are similar, suggesting that in some genes, strong fitness constraints are present at the level of the messenger RNA.

Mutation accumulation in Tetrahymena

Background

The rate and fitness effects of mutations are key in understanding the evolution of every species. Traditionally, these parameters are estimated in mutation accumulation experiments where replicate lines are propagated in conditions that allow mutations to randomly accumulate without the purging effect of natural selection. These experiments have been performed with many model organisms but we still lack empirical estimates of the rate and effects of mutation in the protists.

Results

We performed a mutation accumulation (MA) experiment in Tetrahymena thermophila, a species that can reproduce sexually and asexually in nature, and measured both the mean decline and variance increase in fitness of 20 lines. The results obtained with T. thermophila were compared with T. pyriformis that is an obligate asexual species. We show that MA lines of T. thermophila go to extinction at a rate of 1.25 clonal extinctions per bottleneck. In contrast, populations of T. pyriformis show a much higher resistance to extinction. Variation in gene copy number is likely to be a key factor in explaining these results, and indeed we show that T. pyriformis has a higher mean copy number per cell than T. thermophila. From fitness measurements during the MA experiment, we infer a rate of mutation to copy number variation of 0.0333 per haploid MAC genome of T. thermophila and a mean effect against copy number variation of 0.16. A strong effect of population size in the rate of fitness decline was also found, consistent with the increased power of natural selection.

Conclusions

The rate of clonal extinction measured for T. thermophila is characteristic of a mutational degradation and suggests that this species must undergo sexual reproduction to avoid the deleterious effects detected in the laboratory experiments. We also suggest that an increase in chromosomal copy number associated with the phenotypic assortment of amitotic divisions can provide an alternative mechanism to escape the deleterious effect of random chromosomal copy number variation in species like T. pyriformis that lack the resetting mechanism of sexual reproduction. Our results are relevant to the understanding of cell line longevity and senescence in ciliates.

The population genetics of mutations: good, bad and indifferent

Population genetics is fundamental to our understanding of evolution, and mutations are essential raw materials for evolution. In this introduction to more detailed papers that follow, we aim to provide an oversight of the field. We review current knowledge on mutation rates and their harmful and beneficial effects on fitness and then consider theories that predict the fate of individual mutations or the consequences of mutation accumulation for quantitative traits. Many advances in the past built on models that treat the evolution of mutations at each DNA site independently, neglecting linkage of sites on chromosomes and interactions of effects between sites (epistasis). We review work that addresses these limitations, to predict how mutations interfere with each other. An understanding of the population genetics of mutations of individual loci and of traits affected by many loci helps in addressing many fundamental and applied questions: for example, how do organisms adapt to changing environments, how did sex evolve, which DNA sequences are medically important, why do we age, which genetic processes can generate new species or drive endangered species to extinction, and how should policy on levels of potentially harmful mutagens introduced into the environment by humans be determined?

Measurements of spontaneous rates of mutations in the recent past and the near future

The rate of spontaneous mutation in natural populations is a fundamental parameter for many evolutionary phenomena. Because the rate of mutation is generally low, most of what is currently known about mutation has been obtained through indirect, complex and imprecise methodological approaches. However, in the past few years genome-wide sequencing of closely related individuals has made it possible to estimate the rates of mutation directly at the level of the DNA, avoiding most of the problems associated with using indirect methods. Here, we review the methods used in the past with an emphasis on next generation sequencing, which may soon make the accurate measurement of spontaneous mutation rates a matter of routine.

The effect of spatial structure on adaptation in Escherichia coli

Populations of organisms are generally organized in a given spatial structure. However, the vast majority of population genetic studies are based on populations in which every individual competes globally. Here we use experimental evolution in Escherichia coli to directly test a recently made prediction that spatial structure slows down adaptation and that this cost increases with the mutation rate. This was studied by comparing populations of different mutation rates adapting to a liquid (unstructured) medium with populations that evolved in a Petri dish on solid (structured) medium. We find that mutators adapt faster to both environments and that adaptation is slower if there is spatial structure. We observed no significant difference in the cost of structure between mutator and wild-type populations, which suggests that clonal interference is intense in both genetic backgrounds.