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

A shifting mutational landscape in 6 nutritional states: Stress-induced mutagenesis as a series of distinct stress input-mutation output relationships

Environmental stresses increase genetic variation in bacteria, plants, and human cancer cells. The linkage between various environments and mutational outcomes has not been systematically investigated, however. Here, we established the influence of nutritional stresses commonly found in the biosphere (carbon, phosphate, nitrogen, oxygen, or iron limitation) on both the rate and spectrum of mutations in Escherichia coli. We found that each limitation was associated with a remarkably distinct mutational profile. Overall mutation rates were not always elevated, and nitrogen, iron, and oxygen limitation resulted in major spectral changes but no net increase in rate. Our results thus suggest that stress-induced mutagenesis is a diverse series of stress input-mutation output linkages that is distinct in every condition. Environment-specific spectra resulted in the differential emergence of traits needing particular mutations in these settings. Mutations requiring transpositions were highest under iron and oxygen limitation, whereas base-pair substitutions and indels were highest under phosphate limitation. The unexpected diversity of input-output effects explains some important phenomena in the mutational biases of evolving genomes. The prevalence of bacterial insertion sequence transpositions in the mammalian gut or in anaerobically stored cultures is due to environmentally determined mutation availability. Likewise, the much-discussed genomic bias towards transition base substitutions in evolving genomes can now be explained as an environment-specific output. Altogether, our conclusion is that environments influence genetic variation as well as selection.

Experimental evolution and the dynamics of adaptation and genome evolution in microbial populations

Evolution is an on-going process, and it can be studied experimentally in organisms with rapid generations. My team has maintained 12 populations of Escherichia coli in a simple laboratory environment for >25 years and 60 000 generations. We have quantified the dynamics of adaptation by natural selection, seen some of the populations diverge into stably coexisting ecotypes, described changes in the bacteria's mutation rate, observed the new ability to exploit a previously untapped carbon source, characterized the dynamics of genome evolution and used parallel evolution to identify the genetic targets of selection. I discuss what the future might hold for this particular experiment, briefly highlight some other microbial evolution experiments and suggest how the fields of experimental evolution and microbial ecology might intersect going forward.

Genetic drift, selection and the evolution of the mutation rate

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

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

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

Host-selected mutations converging on a global regulator drive an adaptive leap towards symbiosis in bacteria

Host immune and physical barriers protect against pathogens but also impede the establishment of essential symbiotic partnerships. To reveal mechanisms by which beneficial organisms adapt to circumvent host defenses, we experimentally evolved ecologically distinct bioluminescent Vibrio fischeri by colonization and growth within the light organs of the squid Euprymna scolopes. Serial squid passaging of bacteria produced eight distinct mutations in the binK sensor kinase gene, which conferred an exceptional selective advantage that could be demonstrated through both empirical and theoretical analysis. Squid-adaptive binK alleles promoted colonization and immune evasion that were mediated by cell-associated matrices including symbiotic polysaccharide (Syp) and cellulose. binK variation also altered quorum sensing, raising the threshold for luminescence induction. Preexisting coordinated regulation of symbiosis traits by BinK presented an efficient solution where altered BinK function was the key to unlock multiple colonization barriers. These results identify a genetic basis for microbial adaptability and underscore the importance of hosts as selective agents that shape emergent symbiont populations.

What is adaptation by natural selection? Perspectives of an experimental microbiologist

Ever since Darwin, the role of natural selection in shaping the morphological, physiological, and behavioral adaptations of animals and plants across generations has been central to understanding life and its diversity. New discoveries have shown with increasing precision how genetic, molecular, and biochemical processes produce and express those organismal features during an individual's lifetime. When it comes to microorganisms, however, understanding the role of natural selection in producing adaptive solutions has historically been, and sometimes continues to be, contentious. This tension is curious because microbes enable one to observe the power of adaptation by natural selection with exceptional rigor and clarity, as exemplified by the burgeoning field of experimental microbial evolution. I trace the development of this field, describe an experiment with Escherichia coli that has been running for almost 30 years, and highlight other experiments in which natural selection has led to interesting dynamics and adaptive changes in microbial populations.

Core Genes Evolve Rapidly in the Long-Term Evolution Experiment with Escherichia coli

Bacteria can evolve rapidly under positive selection owing to their vast numbers, allowing their genes to diversify by adapting to different environments. We asked whether the same genes that evolve rapidly in the long-term evolution experiment (LTEE) with Escherichia coli have also diversified extensively in nature. To make this comparison, we identified ∼2000 core genes shared among 60 E. coli strains. During the LTEE, core genes accumulated significantly more nonsynonymous mutations than flexible (i.e., noncore) genes. Furthermore, core genes under positive selection in the LTEE are more conserved in nature than the average core gene. In some cases, adaptive mutations appear to modify protein functions, rather than merely knocking them out. The LTEE conditions are novel for E. coli, at least in relation to its evolutionary history in nature. The constancy and simplicity of the environment likely favor the complete loss of some unused functions and the fine-tuning of others.

Mismatch Repair Incompatibilities in Diverse Yeast Populations

An elevated mutation rate can provide cells with a source of mutations to adapt to changing environments. We identified a negative epistatic interaction involving naturally occurring variants in the MLH1 and PMS1 mismatch repair (MMR) genes of Saccharomyces cerevisiae We hypothesized that this MMR incompatibility, created through mating between divergent S. cerevisiae, yields mutator progeny that can rapidly but transiently adapt to an environmental stress. Here we analyzed the MLH1 and PMS1 genes across 1010 S. cerevisiae natural isolates spanning a wide range of ecological sources (tree exudates, Drosophila, fruits, and various fermentation and clinical isolates) and geographical sources (Europe, America, Africa, and Asia). We identified one homozygous clinical isolate and 18 heterozygous isolates containing the incompatible MMR genotype. The MLH1-PMS1 gene combination isolated from the homozygous clinical isolate conferred a mutator phenotype when expressed in the S288c laboratory background. Using a novel reporter to measure mutation rates, we showed that the overall mutation rate in the homozygous incompatible background was similar to that seen in compatible strains, indicating the presence of suppressor mutations in the clinical isolate that lowered its mutation rate. This observation and the identification of 18 heterozygous isolates, which can lead to MMR incompatible genotypes in the offspring, are consistent with an elevated mutation rate rapidly but transiently facilitating adaptation. To avoid long-term fitness costs, the incompatibility is apparently buffered by mating or by acquiring suppressors. These observations highlight effective strategies in eukaryotes to avoid long-term fitness costs associated with elevated mutation rates.

Genomic heterogeneity of Salmonella enterica serovar Typhimurium bacteriuria from chronic infection

We sequenced the genomes of 14 sequential Salmonella enterica serovar Typhimurium isolates obtained over a five year period from a patient with persistent Salmonella bacteriuria. The isolates formed five distinct lineages; two of which co-existed over four years. We inferred that the observed within-patient variation resulted from mutation events.

Convergence and Divergence in a Long-Term Experiment with Bacteria

Suitably designed experiments offer the possibility of quantifying evolutionary convergence because the fraction of replicate populations that converge is known. Here I review an experiment with Escherichia coli, in which 12 populations were founded from the same ancestral strain and have evolved for almost 30 years and more than 65,000 generations under the same conditions. The tension between divergence and convergence has been a major focus of this experiment. I summarize analyses of competitive fitness, correlated responses to different environments, cell morphology, the capacity to use a previously untapped resource, mutation rates, genomic changes, and within-population polymorphisms. These analyses reveal convergence, divergence, and often a complicated mix thereof. Complications include concordance in the direction of evolutionary change with sustained quantitative variation among populations, and the potential for a given trait to exhibit divergence on one timescale and convergence on another. Despite these complications, which also occur in nature, experiments provide a powerful way to study evolutionary convergence based on analyzing replicate lineages that experience the same environment.

Evolution of evolvability and phenotypic plasticity in virtual cells

BACKGROUND

Changing environmental conditions pose a challenge for the survival of species. To meet this challenge organisms adapt their phenotype by physiological regulation (phenotypic plasticity) or by evolving. Regulatory mechanisms that ensure a constant internal environment in the face of continuous external fluctuations (homeostasis) are ubiquitous and essential for survival. However, more drastic and enduring environmental change, often requires lineages to adapt by mutating. In vitro evolutionary experiments with microbes show that adaptive, large phenotypic changes occur remarkably quickly, requiring only a few mutations. It has been proposed that the high evolvability demonstrated by these microbes, is an evolved property. If both regulation (phenotypic plasticity) and evolvability can evolve as strategies to adapt to change, what are the conditions that favour the emergence of either of these strategy? Does evolution of one strategy hinder or facilitate evolution of the other strategy?

RESULTS

Here we investigate this with computational evolutionary modelling in populations of Virtual Cells. During a preparatory evolutionary phase, Virtual Cells evolved homeostasis regulation for internal metabolite concentrations in a fluctuating environment. The resulting wild-type Virtual Cell strains (WT-VCS) were then exposed to periodic, drastic environmental changes, while maintaining selection on homeostasis regulation. In different sets of simulations the nature and frequencies of environmental change were varied. Pre-evolved WT-VCS were highly evolvable, showing rapid evolutionary adaptation after novel environmental change. Moreover, continued low frequency changes resulted in evolutionary restructuring of the genome that enables even faster adaptation with very few mutations. In contrast, when change frequency is high, lineages evolve phenotypic plasticity that allows them to be fit in different environments without mutations. Yet, evolving phenotypic plasticity is a comparatively slow process. Under intermediate change frequencies, both strategies occur.

CONCLUSIONS

We conclude that evolving a homeostasis mechanisms predisposes lineage to be evolvable to novel environmental conditions. Moreover, after continued evolution, evolvability can be a viable alternative with comparable fitness to regulated phenotypic plasticity in all but the most rapidly changing environments.

Error-prone DnaE2 Balances the Genome Mutation Rates in Myxococcus xanthus DK1622

dnaE is an alpha subunit of the tripartite protein complex of DNA polymerase III that is responsible for the replication of bacterial genome. The dnaE gene is often duplicated in many bacteria, and the duplicated dnaE gene was reported dispensable for cell survivals and error-prone in DNA replication in a mystery. In this study, we found that all sequenced myxobacterial genomes possessed two dnaE genes. The duplicate dnaE genes were both highly conserved but evolved divergently, suggesting their importance in myxobacteria. Using Myxococcus xanthus DK1622 as a model, we confirmed that dnaE1 (MXAN_5844) was essential for cell survival, while dnaE2 (MXAN_3982) was dispensable and encoded an error-prone enzyme for replication. The deletion of dnaE2 had small effects on cellular growth and social motility, but significantly decreased the development and sporulation abilities, which could be recovered by the complementation of dnaE2. The expression of dnaE1 was always greatly higher than that of dnaE2 in either the growth or developmental stage. However, overexpression of dnaE2 could not make dnaE1 deletable, probably due to their protein structural and functional divergences. The dnaE2 overexpression not only improved the growth, development and sporulation abilities, but also raised the genome mutation rate of M. xanthus. We argued that the low-expressed error-prone DnaE2 played as a balancer for the genome mutation rates, ensuring low mutation rates for cell adaptation in new environments but avoiding damages from high mutation rates to cells.

Sustained fitness gains and variability in fitness trajectories in the long-term evolution experiment with Escherichia coli

Many populations live in environments subject to frequent biotic and abiotic changes. Nonetheless, it is interesting to ask whether an evolving population's mean fitness can increase indefinitely, and potentially without any limit, even in a constant environment. A recent study showed that fitness trajectories of Escherichia coli populations over 50 000 generations were better described by a power-law model than by a hyperbolic model. According to the power-law model, the rate of fitness gain declines over time but fitness has no upper limit, whereas the hyperbolic model implies a hard limit. Here, we examine whether the previously estimated power-law model predicts the fitness trajectory for an additional 10 000 generations. To that end, we conducted more than 1100 new competitive fitness assays. Consistent with the previous study, the power-law model fits the new data better than the hyperbolic model. We also analysed the variability in fitness among populations, finding subtle, but significant, heterogeneity in mean fitness. Some, but not all, of this variation reflects differences in mutation rate that evolved over time. Taken together, our results imply that both adaptation and divergence can continue indefinitely—or at least for a long time—even in a constant environment.

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

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

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.

Diversifying selection of the anthocyanin biosynthetic downstream gene UFGT accelerates floral diversity of island Scutellaria species

BACKGROUND

Adaptive divergence, which usually explains rapid diversification within island species, might involve the positive selection of genes. Anthocyanin biosynthetic pathway (ABP) genes are important for floral diversity, and are related to stress resistance and pollination, which could be responsible for species diversification. Previous studies have shown that upstream genes of ABP are subject to selective constraints and have a slow evolutionary rate, while the constraints on downstream genes are lower.

RESULTS

In this study, we confirmed these earlier observations of heterogeneous evolutionary rate in upstream gene CHS and the downstream gene UFGT, both of which were expressed in Scutellaria sp. inflorescence buds. We found a higher evolutionary rate and positive selection for UFGT. The codons under positive selection corresponded to the diversified regions, and the presence or absence of an α-helix might produce conformation changes in the Rossmann-like fold structure. The significantly high evolutionary rates for UFGT genes in Taiwanese lineages suggested rapid accumulation of amino acid mutations in island species. The results showed positive selection in closely related species and explained the high diversification of floral patterns in these recently diverged species. In contrast, non-synonymous mutation rate decreases in long-term divergent species could reduce mutational load and prevent the accumulation of deleterious mutations.

CONCLUSIONS

Together with the positive selection of transcription factors for ABP genes described in a previous study, these results confirmed that positive selection takes place at a translational level and suggested that the high divergence of ABP genes is related to the floral diversity in island Scutellaria species.

Deterministic evolution of an asexual population under the action of beneficial and deleterious mutations on additive fitness landscapes

We study a continuous time model for the frequency distribution of an infinitely large asexual population in which both beneficial and deleterious mutations occur and fitness is additive. When beneficial mutations are ignored, the exact solution for the frequency distribution is known to be a Poisson distribution. Here we include beneficial mutations and obtain exact expressions for the frequency distribution at all times using an eigenfunction expansion method. We find that the stationary distribution is non-Poissonian and related to the Bessel function of the first kind. We also provide suitable approximations for the stationary distribution and the time to relax to the steady state. Our exact results, especially at mutation-selection equilibrium, can be useful in developing semi-deterministic approaches to understand stochastic evolution.

Elucidation of the regulatory role of the fructose operon reveals a novel target for enhancing the NADPH supply in Corynebacterium glutamicum

The performance of Corynebacterium glutamicum cell factories producing compounds which rely heavily on NADPH has been reported to depend on the sugar being metabolized. While some aspects of this phenomenon have been elucidated, there are still many unresolved questions as to how sugar metabolism is linked to redox and to the general metabolism. We here provide new insights into the regulation of the metabolism of this important platform organism by systematically characterizing mutants carrying various lesions in the fructose operon. Initially, we found that a strain where the dedicated fructose uptake system had been inactivated (KO-ptsF) was hampered in growth on sucrose minimal medium, and suppressor mutants appeared readily. Comparative genomic analysis in conjunction with enzymatic assays revealed that suppression was linked to inactivation of the pfkB gene, encoding a fructose-1-phosphate kinase. Detailed characterization of KO-ptsF, KO-pfkB and double knock-out (DKO) derivatives revealed a strong role for sugar-phosphates, especially fructose-1-phosphate (F1P), in governing sugar as well as redox metabolism due to effects on transcriptional regulation of key genes. These findings allowed us to propose a simple model explaining the correlation between sugar phosphate concentration, gene expression and ultimately the observed phenotype. To guide us in our analysis and help us identify bottlenecks in metabolism we debugged an existing genome-scale model onto which we overlaid the transcriptome data. Based on the results obtained we managed to enhance the NADPH supply and transform the wild-type strain into delivering the highest yield of lysine ever obtained on sucrose and fructose, thus providing a good example of how regulatory mechanisms can be harnessed for bioproduction.

Competition and fixation of cohorts of adaptive mutations under Fisher geometrical model

One of the simplest models of adaptation to a new environment is Fisher’s Geometric Model (FGM), in which populations move on a multidimensional landscape defined by the traits under selection. The predictions of this model have been found to be consistent with current observations of patterns of fitness increase in experimentally evolved populations. Recent studies investigated the dynamics of allele frequency change along adaptation of microbes to simple laboratory conditions and unveiled a dramatic pattern of competition between cohorts of mutations, i.e., multiple mutations simultaneously segregating and ultimately reaching fixation. Here, using simulations, we study the dynamics of phenotypic and genetic change as asexual populations under clonal interference climb a Fisherian landscape, and ask about the conditions under which FGM can display the simultaneous increase and fixation of multiple mutations—mutation cohorts—along the adaptive walk. We find that FGM under clonal interference, and with varying levels of pleiotropy, can reproduce the experimentally observed competition between different cohorts of mutations, some of which have a high probability of fixation along the adaptive walk. Overall, our results show that the surprising dynamics of mutation cohorts recently observed during experimental adaptation of microbial populations can be expected under one of the oldest and simplest theoretical models of adaptation—FGM.

Tempo and mode of genome evolution in a 50,000-generation experiment

Adaptation by natural selection depends on the rates, effects, and interactions of many mutations, making it difficult to determine what proportion of mutations in an evolving lineage are beneficial. We analysed 264 complete genomes from 12 Escherichia coli populations to characterize their dynamics over 50,000 generations. The populations that retained the ancestral mutation rate support a model where most fixed mutations are beneficial, the fraction of beneficial mutations declines as fitness rises, and neutral mutations accumulate at a constant rate. We also compared these populations to mutation-accumulation lines evolved under a bottlenecking regime that minimizes selection. Nonsynonymous mutations, intergenic mutations, insertions, and deletions are overrepresented in the long-term populations, further supporting the inference that most mutations that reached high frequency were favoured by selection. These results illuminate the shifting balance of forces that govern genome evolution in populations adapting to a new environment.

Open-Ended Evolution: Perspectives from the OEE Workshop in York

We describe the content and outcomes of the First Workshop on Open-Ended Evolution: Recent Progress and Future Milestones (OEE1), held during the ECAL 2015 conference at the University of York, UK, in July 2015. We briefly summarize the content of the workshop's talks, and identify the main themes that emerged from the open discussions. Two important conclusions from the discussions are: (1) the idea of pluralism about OEE-it seems clear that there is more than one interesting and important kind of OEE; and (2) the importance of distinguishing observable behavioral hallmarks of systems undergoing OEE from hypothesized underlying mechanisms that explain why a system exhibits those hallmarks. We summarize the different hallmarks and mechanisms discussed during the workshop, and list the specific systems that were highlighted with respect to particular hallmarks and mechanisms. We conclude by identifying some of the most important open research questions about OEE that are apparent in light of the discussions. The York workshop provides a foundation for a follow-up OEE2 workshop taking place at the ALIFE XV conference in Cancún, Mexico, in July 2016. Additional materials from the York workshop, including talk abstracts, presentation slides, and videos of each talk, are available at http://alife.org/ws/oee1 .

Rates and mechanisms of bacterial mutagenesis from maximum-depth sequencing

In 1943, Luria and Delbrück used a phage resistance assay to establish spontaneous mutation as a driving force of microbial diversity¹. Mutation rates are still studied using such assays, but these can only examine the small minority of mutations conferring survival in a particular condition. Newer approaches, such as long-term evolution followed by whole-genome sequencing ^{2, 3}, may be skewed by mutational “hot” or “cold” spots ^{3, 4}. Both approaches are affected by numerous caveats ^{5, 6, 7} (see Supplemental Information). We devise a method, Maximum-Depth Sequencing (MDS), to detect extremely rare variants in a population of cells through error-corrected, high-throughput sequencing. We directly measure locus-specific mutation rates in E. coli and show that they vary across the genome by at least an order of magnitude. Our data suggest that certain types of nucleotide misincorporation occur 10⁴-fold more frequently than the basal rate of mutations, but are repaired in vivo. Our data also suggest specific mechanisms of antibiotic-induced mutagenesis, including downregulation of mismatch repair via oxidative stress; transcription-replication conflicts; and in the case of fluoroquinolones, direct damage to DNA.

Evolution of Genome Size in Asexual Digital Organisms

Genome sizes have evolved to vary widely, from 250 bases in viroids to 670 billion bases in some amoebas. This remarkable variation in genome size is the outcome of complex interactions between various evolutionary factors such as mutation rate and population size. While comparative genomics has uncovered how some of these evolutionary factors influence genome size, we still do not understand what drives genome size evolution. Specifically, it is not clear how the primordial mutational processes of base substitutions, insertions, and deletions influence genome size evolution in asexual organisms. Here, we use digital evolution to investigate genome size evolution by tracking genome edits and their fitness effects in real time. In agreement with empirical data, we find that mutation rate is inversely correlated with genome size in asexual populations. We show that at low point mutation rate, insertions are significantly more beneficial than deletions, driving genome expansion and the acquisition of phenotypic complexity. Conversely, the high mutational load experienced at high mutation rates inhibits genome growth, forcing the genomes to compress their genetic information. Our analyses suggest that the inverse relationship between mutation rate and genome size is a result of the tradeoff between evolving phenotypic innovation and limiting the mutational load.

How Archiving by Freezing Affects the Genome-Scale Diversity of Escherichia coli Populations

In the experimental evolution of microbes such as Escherichia coli, many replicate populations are evolved from a common ancestor. Freezing a population sample supplemented with the cryoprotectant glycerol permits later analysis or restarting of an evolution experiment. Typically, each evolving population, and thus each sample archived in this way, consists of many unique genotypes and phenotypes. The effect of archiving on such a heterogeneous population is unknown. Here, we identified optimal archiving conditions for E. coli. We also used genome sequencing of archived samples to study the effects that archiving has on genomic population diversity. We observed no allele substitutions and mostly small changes in allele frequency. Nevertheless, principal component analysis of genome-scale allelic diversity shows that archiving affects diversity across many loci. We showed that this change in diversity is due to selection rather than drift. In addition, ∼1% of rare alleles that occurred at low frequencies were lost after treatment. Our observations imply that archived populations may be used to conduct fitness or other phenotypic assays of populations, in which the loss of a rare allele may have negligible effects. However, caution is appropriate when sequencing populations restarted from glycerol stocks, as well as when using glycerol stocks to restart or replay evolution. This is because the loss of rare alleles can alter the future evolutionary trajectory of a population if the lost alleles were strongly beneficial.

Mutation at a distance caused by homopolymeric guanine repeats in Saccharomyces cerevisiae

Mutation provides the raw material from which natural selection shapes adaptations. The rate at which new mutations arise is therefore a key factor that determines the tempo and mode of evolution. However, an accurate assessment of the mutation rate of a given organism is difficult because mutation rate varies on a fine scale within a genome. A central challenge of evolutionary genetics is to determine the underlying causes of this variation. In earlier work, we had shown that repeat sequences not only are prone to a high rate of expansion and contraction but also can cause an increase in mutation rate (on the order of kilobases) of the sequence surrounding the repeat. We perform experiments that show that simple guanine repeats 13 bp (base pairs) in length or longer (G 13+ ) increase the substitution rate 4- to 18-fold in the downstream DNA sequence, and this correlates with DNA replication timing (R = 0.89). We show that G 13+ mutagenicity results from the interplay of both error-prone translesion synthesis and homologous recombination repair pathways. The mutagenic repeats that we study have the potential to be exploited for the artificial elevation of mutation rate in systems biology and synthetic biology applications.

Yeast petites and small colony variants: for everything there is a season

The yeast petite mutant was first found in the yeast Saccharomyces cerevisiae. The colony is small because of a block in the aerobic respiratory chain pathway, which generates ATP. The petite yeasts are thus unable to grow on nonfermentable carbon sources (such as glycerol or ethanol), and form small anaerobic-sized colonies when grown in the presence of fermentable carbon sources (such as glucose). The petite phenotype results from mutations in the mitochondrial genome, loss of mitochondria, or mutations in the host cell genome. The latter mutations affect nuclear-encoded genes involved in oxidative phosphorylation and these mutants are termed neutral petites. They all produce wild-type progeny when crossed with a wild-type strain. The staphylococcal small colony variant (SCV) is a slow-growing mutant that typically exhibits the loss of many phenotypic characteristics and pathogenic traits. SCVs are mostly small, nonpigmented, and nonhaemolytic. Their small size is often due to an inability to synthesize electron transport chain components and so cannot generate ATP by oxidative phosphorylation. Evidence suggests that they are responsible for persistent and/or recurrent infections. This chapter compares the physiological and genetic basis of the petite mutants and SCVs. The review focuses principally on two representatives, the eukaryote S. cerevisiae and the prokaryote Staphylococcus aureus. There is, clearly, commonality in the physiological response. Interestingly, the similarity, based on their physiological states, has not been commented on previously. The finding of an overlapping physiological response that occurs across a taxonomic divide is novel.

Adaptation by Deletogenic Replication Slippage in a Nascent Symbiont

As a consequence of population level constraints in the obligate, host-associated lifestyle, intracellular symbiotic bacteria typically exhibit high rates of molecular sequence evolution and extensive genome degeneration over the course of their host association. While the rationale for genome degeneration is well understood, little is known about the molecular mechanisms driving this change. To understand these mechanisms we compared the genome of Sodalis praecaptivus, a nonhost associated bacterium that is closely related to members of the Sodalis-allied clade of insect endosymbionts, with the very recently derived insect symbiont Candidatus Sodalis pierantonius. The characterization of indel mutations in the genome of Ca. Sodalis pierantonius shows that the replication system in this organism is highly prone to deletions resulting from polymerase slippage events in regions encoding G+C-rich repetitive sequences. This slippage-prone phenotype is mechanistically associated with the loss of certain components of the bacterial DNA recombination machinery at an early stage in symbiotic life and is expected to facilitate rapid adaptation to the novel host environment. This is analogous to the emergence of mutator strains in both natural and laboratory populations of bacteria, which tend to reach high frequencies in clonal populations due to linkage between the mutator allele and the resulting adaptive mutations.

Adaptation to Parasites and Costs of Parasite Resistance in Mutator and Nonmutator Bacteria

Parasitism creates selection for resistance mechanisms in host populations and is hypothesized to promote increased host evolvability. However, the influence of these traits on host evolution when parasites are no longer present is unclear. We used experimental evolution and whole-genome sequencing of Escherichia coli to determine the effects of past and present exposure to parasitic viruses (phages) on the spread of mutator alleles, resistance, and bacterial competitive fitness. We found that mutator alleles spread rapidly during adaptation to any of four different phage species, and this pattern was even more pronounced with multiple phages present simultaneously. However, hypermutability did not detectably accelerate adaptation in the absence of phages and recovery of fitness costs associated with resistance. Several lineages evolved phage resistance through elevated mucoidy, and during subsequent evolution in phage-free conditions they rapidly reverted to nonmucoid, phage-susceptible phenotypes. Genome sequencing revealed that this phenotypic reversion was achieved by additional genetic changes rather than by genotypic reversion of the initial resistance mutations. Insertion sequence (IS) elements played a key role in both the acquisition of resistance and adaptation in the absence of parasites; unlike single nucleotide polymorphisms, IS insertions were not more frequent in mutator lineages. Our results provide a genetic explanation for rapid reversion of mucoidy, a phenotype observed in other bacterial species including human pathogens. Moreover, this demonstrates that the types of genetic change underlying adaptation to fitness costs, and consequently the impact of evolvability mechanisms such as increased point-mutation rates, depend critically on the mechanism of resistance.

Network-Based Analysis of eQTL Data to Prioritize Driver Mutations

In clonal systems, interpreting driver genes in terms of molecular networks helps understanding how these drivers elicit an adaptive phenotype. Obtaining such a network-based understanding depends on the correct identification of driver genes. In clonal systems, independent evolved lines can acquire a similar adaptive phenotype by affecting the same molecular pathways, a phenomenon referred to as parallelism at the molecular pathway level. This implies that successful driver identification depends on interpreting mutated genes in terms of molecular networks. Driver identification and obtaining a network-based understanding of the adaptive phenotype are thus confounded problems that ideally should be solved simultaneously. In this study, a network-based eQTL method is presented that solves both the driver identification and the network-based interpretation problem. As input the method uses coupled genotype-expression phenotype data (eQTL data) of independently evolved lines with similar adaptive phenotypes and an organism-specific genome-wide interaction network. The search for mutational consistency at pathway level is defined as a subnetwork inference problem, which consists of inferring a subnetwork from the genome-wide interaction network that best connects the genes containing mutations to differentially expressed genes. Based on their connectivity with the differentially expressed genes, mutated genes are prioritized as driver genes. Based on semisynthetic data and two publicly available data sets, we illustrate the potential of the network-based eQTL method to prioritize driver genes and to gain insights in the molecular mechanisms underlying an adaptive phenotype. The method is available at http://bioinformatics.intec.ugent.be/phenetic_eqtl/index.html

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.

Population-reaction model and microbial experimental ecosystems for understanding hierarchical dynamics of ecosystems

Understanding ecosystem dynamics is crucial as contemporary human societies face ecosystem degradation. One of the challenges that needs to be recognized is the complex hierarchical dynamics. Conventional dynamic models in ecology often represent only the population level and have yet to include the dynamics of the sub-organism level, which makes an ecosystem a complex adaptive system that shows characteristic behaviors such as resilience and regime shifts. The neglect of the sub-organism level in the conventional dynamic models would be because integrating multiple hierarchical levels makes the models unnecessarily complex unless supporting experimental data are present. Now that large amounts of molecular and ecological data are increasingly accessible in microbial experimental ecosystems, it is worthwhile to tackle the questions of their complex hierarchical dynamics. Here, we propose an approach that combines microbial experimental ecosystems and a hierarchical dynamic model named population-reaction model. We present a simple microbial experimental ecosystem as an example and show how the system can be analyzed by a population-reaction model. We also show that population-reaction models can be applied to various ecological concepts, such as predator-prey interactions, climate change, evolution, and stability of diversity. Our approach will reveal a path to the general understanding of various ecosystems and organisms.

Genomic investigations of evolutionary dynamics and epistasis in microbial evolution experiments

Microbial evolution experiments enable us to watch adaptation in real time, and to quantify the repeatability and predictability of evolution by comparing identical replicate populations. Further, we can resurrect ancestral types to examine changes over evolutionary time. Until recently, experimental evolution has been limited to measuring phenotypic changes, or to tracking a few genetic markers over time. However, recent advances in sequencing technology now make it possible to extensively sequence clones or whole-population samples from microbial evolution experiments. Here, we review recent work exploiting these techniques to understand the genomic basis of evolutionary change in experimental systems. We first focus on studies that analyze the dynamics of genome evolution in microbial systems. We then survey work that uses observations of sequence evolution to infer aspects of the underlying fitness landscape, concentrating on the epistatic interactions between mutations and the constraints these interactions impose on adaptation.

Synonymous Genetic Variation in Natural Isolates of Escherichia coli Does Not Predict Where Synonymous Substitutions Occur in a Long-Term Experiment

Synonymous genetic differences vary by more than 20-fold among genes in natural isolates of Escherichia coli. One hypothesis to explain this heterogeneity is that genes with high levels of synonymous variation mutate at higher rates than genes with low synonymous variation. If so, then one would expect to observe similar mutational patterns in evolution experiments. In fact, however, the pattern of synonymous substitutions in a long-term evolution experiment with E. coli does not support this hypothesis. In particular, the extent of synonymous variation across genes in that experiment does not reflect the variation observed in natural isolates of E. coli. Instead, gene length alone predicts with high accuracy the prevalence of synonymous changes in the experimental populations. We hypothesize that patterns of synonymous variation in natural E. coli populations are instead caused by differences across genomic regions in their effective population size that, in turn, reflect different histories of recombination, horizontal gene transfer, selection, and population structure.

Fitness Trade-Offs Determine the Role of the Molecular Chaperonin GroEL in Buffering Mutations

Molecular chaperones fold many proteins and their mutated versions in a cell and can sometimes buffer the phenotypic effect of mutations that affect protein folding. Unanswered questions about this buffering include the nature of its mechanism, its influence on the genetic variation of a population, the fitness trade-offs constraining this mechanism, and its role in expediting evolution. Answering these questions is fundamental to understand the contribution of buffering to increase genetic variation and ecological diversification. Here, we performed experimental evolution, genome resequencing, and computational analyses to determine the trade-offs and evolutionary trajectories of Escherichia coli expressing high levels of the essential chaperonin GroEL. GroEL is abundantly present in bacteria, particularly in bacteria with large loads of deleterious mutations, suggesting its role in mutational buffering. We show that groEL overexpression is costly to large populations evolving in the laboratory, leading to groE expression decline within 66 generations. In contrast, populations evolving under the strong genetic drift characteristic of endosymbiotic bacteria avoid extinction or can be rescued in the presence of abundant GroEL. Genomes resequenced from cells evolved under strong genetic drift exhibited significantly higher tolerance to deleterious mutations at high GroEL levels than at native levels, revealing that GroEL is buffering mutations in these cells. GroEL buffered mutations in a highly diverse set of proteins that interact with the environment, including substrate and ion membrane transporters, hinting at its role in ecological diversification. Our results reveal the fitness trade-offs of mutational buffering and how genetic variation is maintained in populations.

Metabolism at evolutionary optimal States

Metabolism is generally required for cellular maintenance and for the generation of offspring under conditions that support growth. The rates, yields (efficiencies), adaptation time and robustness of metabolism are therefore key determinants of cellular fitness. For biotechnological applications and our understanding of the evolution of metabolism, it is necessary to figure out how the functional system properties of metabolism can be optimized, via adjustments of the kinetics and expression of enzymes, and by rewiring metabolism. The trade-offs that can occur during such optimizations then indicate fundamental limits to evolutionary innovations and bioengineering. In this paper, we review several theoretical and experimental findings about mechanisms for metabolic optimization.

Stress-induced mutagenesis and complex adaptation

Because mutations are mostly deleterious, mutation rates should be reduced by natural selection. However, mutations also provide the raw material for adaptation. Therefore, evolutionary theory suggests that the mutation rate must balance between adaptability-the ability to adapt-and adaptedness-the ability to remain adapted. We model an asexual population crossing a fitness valley and analyse the rate of complex adaptation with and without stress-induced mutagenesis (SIM)-the increase of mutation rates in response to stress or maladaptation. We show that SIM increases the rate of complex adaptation without reducing the population mean fitness, thus breaking the evolutionary trade-off between adaptability and adaptedness. Our theoretical results support the hypothesis that SIM promotes adaptation and provide quantitative predictions of the rate of complex adaptation with different mutational strategies.

A Comparison of Methods to Measure Fitness in Escherichia coli

In order to characterize the dynamics of adaptation, it is important to be able to quantify how a population’s mean fitness changes over time. Such measurements are especially important in experimental studies of evolution using microbes. The Long-Term Evolution Experiment (LTEE) with Escherichia coli provides one such system in which mean fitness has been measured by competing derived and ancestral populations. The traditional method used to measure fitness in the LTEE and many similar experiments, though, is subject to a potential limitation. As the relative fitness of the two competitors diverges, the measurement error increases because the less-fit population becomes increasingly small and cannot be enumerated as precisely. Here, we present and employ two alternatives to the traditional method. One is based on reducing the fitness differential between the competitors by using a common reference competitor from an intermediate generation that has intermediate fitness; the other alternative increases the initial population size of the less-fit, ancestral competitor. We performed a total of 480 competitions to compare the statistical properties of estimates obtained using these alternative methods with those obtained using the traditional method for samples taken over 50,000 generations from one of the LTEE populations. On balance, neither alternative method yielded measurements that were more precise than the traditional method.

Adaptation, Clonal Interference, and Frequency-Dependent Interactions in a Long-Term Evolution Experiment with Escherichia coli

Twelve replicate populations of Escherichia coli have been evolving in the laboratory for >25 years and 60,000 generations. We analyzed bacteria from whole-population samples frozen every 500 generations through 20,000 generations for one well-studied population, called Ara-1. By tracking 42 known mutations in these samples, we reconstructed the history of this population's genotypic evolution over this period. The evolutionary dynamics of Ara-1 show strong evidence of selective sweeps as well as clonal interference between competing lineages bearing different beneficial mutations. In some cases, sets of several mutations approached fixation simultaneously, often conveying no information about their order of origination; we present several possible explanations for the existence of these mutational cohorts. Against a backdrop of rapid selective sweeps both earlier and later, two genetically diverged clades coexisted for >6000 generations before one went extinct. In that time, many additional mutations arose in the clade that eventually prevailed. We show that the clades evolved a frequency-dependent interaction, which prevented the immediate competitive exclusion of either clade, but which collapsed as beneficial mutations accumulated in the clade that prevailed. Clonal interference and frequency dependence can occur even in the simplest microbial populations. Furthermore, frequency dependence may generate dynamics that extend the period of coexistence that would otherwise be sustained by clonal interference alone.

Endosymbiont evolution: predictions from theory and surprises from genomes

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

Evolutionary insight from whole-genome sequencing of Pseudomonas aeruginosa from cystic fibrosis patients

ABSTRACT 

The opportunistic pathogen Pseudomonas aeruginosa causes chronic airway infections in patients with cystic fibrosis (CF), and it is directly associated with the morbidity and mortality connected with this disease. The ability of P. aeruginosa to establish chronic infections in CF patients is suggested to be due to the large genetic repertoire of P. aeruginosa and its ability to genetically adapt to the host environment. Here, we review the recent work that has applied whole-genome sequencing to understand P. aeruginosa population genomics, within-host microevolution and diversity, mutational mechanisms, genetic adaptation and transmission events. Finally, we summarize the advances in relation to medical applications and laboratory evolution experiments.

Concordance and discordance of sequence survey methods for molecular epidemiology

The post-genomic era is characterized by the direct acquisition and analysis of genomic data with many applications, including the enhancement of the understanding of microbial epidemiology and pathology. However, there are a number of molecular approaches to survey pathogen diversity, and the impact of these different approaches on parameter estimation and inference are not entirely clear. We sequenced whole genomes of bacterial pathogens, Burkholderia pseudomallei, Yersinia pestis, and Brucella spp. (60 new genomes), and combined them with 55 genomes from GenBank to address how different molecular survey approaches (whole genomes, SNPs, and MLST) impact downstream inferences on molecular evolutionary parameters, evolutionary relationships, and trait character associations. We selected isolates for sequencing to represent temporal, geographic origin, and host range variability. We found that substitution rate estimates vary widely among approaches, and that SNP and genomic datasets yielded different but strongly supported phylogenies. MLST yielded poorly supported phylogenies, especially in our low diversity dataset, i.e., Y. pestis. Trait associations showed that B. pseudomallei and Y. pestis phylogenies are significantly associated with geography, irrespective of the molecular survey approach used, while Brucella spp. phylogeny appears to be strongly associated with geography and host origin. We contrast inferences made among monomorphic (clonal) and non-monomorphic bacteria, and between intra- and inter-specific datasets. We also discuss our results in light of underlying assumptions of different approaches.

Detecting rare structural variation in evolving microbial populations from new sequence junctions using breseq

New mutations leading to structural variation (SV) in genomes—in the form of mobile element insertions, large deletions, gene duplications, and other chromosomal rearrangements—can play a key role in microbial evolution. Yet, SV is considerably more difficult to predict from short-read genome resequencing data than single-nucleotide substitutions and indels (SN), so it is not yet routinely identified in studies that profile population-level genetic diversity over time in evolution experiments. We implemented an algorithm for detecting polymorphic SV as part of the breseq computational pipeline. This procedure examines split-read alignments, in which the two ends of a single sequencing read match disjoint locations in the reference genome, in order to detect structural variants and estimate their frequencies within a sample. We tested our algorithm using simulated Escherichia coli data and then applied it to 500- and 1000-generation population samples from the Lenski E. coli long-term evolution experiment (LTEE). Knowledge of genes that are targets of selection in the LTEE and mutations present in previously analyzed clonal isolates allowed us to evaluate the accuracy of our procedure. Overall, SV accounted for ~25% of the genetic diversity found in these samples. By profiling rare SV, we were able to identify many cases where alternative mutations in key genes transiently competed within a single population. We also found, unexpectedly, that mutations in two genes that rose to prominence at these early time points always went extinct in the long term. Because it is not limited by the base-calling error rate of the sequencing technology, our approach for identifying rare SV in whole-population samples may have a lower detection limit than similar predictions of SNs in these data sets. We anticipate that this functionality of breseq will be useful for providing a more complete picture of genome dynamics during evolution experiments with haploid microorganisms.