Synchronous waves of failed soft sweeps in the laboratory: remarkably rampant clonal interference of alleles at a single locus

Fitness effects of somatic mutations accumulating during vegetative growth

The unique life form of plants promotes the accumulation of somatic mutations that can be passed to offspring in the next generation, because the same meristem cells responsible for vegetative growth also generate gametes for sexual reproduction. However, little is known about the consequences of somatic mutation accumulation for offspring fitness. We evaluate the fitness effects of somatic mutations in Mimulus guttatus by comparing progeny from self-pollinations made within the same flower (autogamy) to progeny from self-pollinations made between stems on the same plant (geitonogamy). The effects of somatic mutations are evident from this comparison, as autogamy leads to homozygosity of a proportion of somatic mutations, but progeny from geitonogamy remain heterozygous for mutations unique to each stem. In two different experiments, we find consistent fitness effects of somatic mutations from individual stems. Surprisingly, several progeny groups from autogamous crosses displayed increases in fitness compared to progeny from geitonogamy crosses, likely indicating that beneficial somatic mutations occurred in some stems. These results support the hypothesis that somatic mutations accumulate during vegetative growth, but they are filtered by different forms of selection that occur throughout development, resulting in the culling of expressed deleterious mutations and the retention of beneficial mutations.

Mutational Switch-Backs Can Accelerate Evolution of Francisella to a Combination of Ciprofloxacin and Doxycycline

Combination antimicrobial therapy has been considered a promising strategy to combat the evolution of antimicrobial resistance. Francisella tularensis is the causative agent of tularemia and in addition to being found in the nature, is recognized as a threat agent that requires vigilance. We investigated the evolutionary outcome of adapting the Live Vaccine Strain (LVS) of F. tularensis subsp. holarctica to two non-interacting drugs, ciprofloxacin and doxycycline, individually, sequentially, and in combination. Despite their individual efficacies and independence of mechanisms, evolution to the combination arose on a shorter time scale than evolution to the two drugs sequentially. We conducted a longitudinal mutational analysis of the populations evolving to the drug combination, genetically reconstructed the identified evolutionary pathway, and carried out biochemical validation. We discovered that, after the appearance of an initial weak generalist mutation (FupA/B), each successive mutation alternated between adaptation to one drug or the other. In combination, these mutations allowed the population to more efficiently ascend the fitness peak through a series of evolutionary switch-backs. Clonal interference, weak pleiotropy, and positive epistasis also contributed to combinatorial evolution. This finding suggests that the use of this non-interacting drug pair against F. tularensis may render both drugs ineffective because of mutational switch-backs that accelerate evolution of dual resistance.

Polygenic Adaptation and Clonal Interference Enable Sustained Diversity in Experimental Pseudomonas aeruginosa Populations

How biodiversity arises and can be maintained in asexual microbial populations growing on a single resource remains unclear. Many models presume that beneficial genotypes will outgrow others and purge variation via selective sweeps. Environmental structure like that found in biofilms, which are associated with persistence during infection and other stressful conditions, may oppose this process and preserve variation. We tested this hypothesis by evolving Pseudomonas aeruginosa populations in biofilm-promoting arginine media for 3 months, using both a bead model of the biofilm life cycle and planktonic serial transfer. Surprisingly, adaptation and diversification were mostly uninterrupted by fixation events that eliminate diversity, with hundreds of mutations maintained at intermediate frequencies. The exceptions included genotypes with mutator alleles that also accelerated genetic diversification. Despite the rarity of hard sweeps, a remarkable 40 genes acquired parallel mutations in both treatments and often among competing genotypes within a population. These incomplete soft sweeps include several transporters (including pitA, pntB, nosD, and pchF) suggesting adaptation to the growth media that becomes highly alkaline during growth. Further, genes involved in signal transduction (including gacS, aer2, bdlA, and PA14_71750) reflect likely adaptations to biofilm-inducing conditions. Contrary to evolution experiments that select mutations in a few genes, these results suggest that some environments may expose a larger fraction of the genome and select for many adaptations at once. Thus, even growth on a sole carbon source can lead to persistent genetic and phenotypic variation despite strong selection that would normally purge diversity.

Genetic Context Significantly Influences the Maintenance and Evolution of Degenerate Pathways

Understanding the evolution of novel physiological traits is highly relevant for expanding the characterization and manipulation of biological systems. Acquisition of new traits can be achieved through horizontal gene transfer (HGT). Here, we investigate drivers that promote or deter the maintenance of HGT-driven degeneracy, occurring when processes accomplish identical functions through nonidentical components. Subsequent evolution can optimize newly acquired functions; for example, beneficial alleles identified in an engineered Methylorubrum extorquens strain allowed it to utilize a “Foreign” formaldehyde oxidation pathway substituted for its Native pathway for methylotrophic growth. We examined the fitness consequences of interactions between these alleles when they were combined with the Native pathway or both (Dual) pathways. Unlike the Foreign pathway context where they evolved, these alleles were often neutral or deleterious when moved into these alternative genetic backgrounds. However, there were instances where combinations of multiple alleles resulted in higher fitness outcomes than individual allelic substitutions could provide. Importantly, the genetic context accompanying these allelic substitutions significantly altered the fitness landscape, shifting local fitness peaks and restricting the set of accessible evolutionary trajectories. These findings highlight how genetic context can negatively impact the probability of maintaining native and HGT-introduced functions together, making it difficult for degeneracy to evolve. However, in cases where the cost of maintaining degeneracy was mitigated by adding evolved alleles impacting the function of these pathways, we observed rare opportunities for pathway coevolution to occur. Together, our results highlight the importance of genetic context and resulting epistasis in retaining or losing HGT-acquired degenerate functions.

Substitutions Are Boring: Some Arguments about Parallel Mutations and High Mutation Rates

Extant genomes are largely shaped by global transposition, copy-number fluctuation, and rearrangement of DNA sequences rather than by substitutions of single nucleotides. Although many of these large-scale mutations have low probabilities and are unlikely to repeat, others are recurrent or predictable in their effects, leading to stereotyped genome architectures and genetic variation in both eukaryotes and prokaryotes. Such recurrent, parallel mutation modes can profoundly shape the paths taken by evolution and undermine common models of evolutionary genetics. Similar patterns are also evident at the smaller scales of individual genes or short sequences. The scale and extent of this 'non-substitution' variation has recently come into focus through the advent of new genomic technologies; however, it is still not widely considered in genotype-phenotype association studies. In this review we identify common features of these disparate mutational phenomena and comment on the importance and interpretation of these mutational patterns.

Identification of parallel and divergent optimization solutions for homologous metabolic enzymes

Metabolic pathway assembly typically involves the expression of enzymes from multiple organisms in a single heterologous host. Ensuring that each enzyme functions effectively can be challenging, since many potential factors can disrupt proper pathway flux. Here, we compared the performance of two enzyme homologs in a pathway engineered to allow Escherichia coli to grow on 4-hydroxybenzoate (4-HB), a byproduct of lignocellulosic biomass deconstruction. Single chromosomal copies of the 4-HB 3-monooxygenase genes pobA and praI, from Pseudomonas putida KT2440 and Paenibacillus sp. JJ-1B, respectively, were introduced into a strain able to metabolize protocatechuate (PCA), the oxidation product of 4-HB. Neither enzyme initially supported consistent growth on 4-HB. Experimental evolution was used to identify mutations that improved pathway activity. For both enzymes, silent mRNA mutations were identified that increased enzyme expression. With pobA, duplication of the genes for PCA metabolism allowed growth on 4-HB. However, with praI, growth required a mutation in the 4-HB/PCA transporter pcaK that increased intracellular concentrations of 4-HB, suggesting that flux through PraI was limiting. These findings demonstrate the value of directed evolution strategies to rapidly identify and overcome diverse factors limiting enzyme activity.

Parallel Evolution of High-Level Aminoglycoside Resistance in Escherichia coli Under Low and High Mutation Supply Rates

Antibiotic resistance is a major concern in public health worldwide, thus there is much interest in characterizing the mutational pathways through which susceptible bacteria evolve resistance. Here we use experimental evolution to explore the mutational pathways toward aminoglycoside resistance, using gentamicin as a model, under low and high mutation supply rates. Our results show that both normo and hypermutable strains of Escherichia coli are able to develop resistance to drug dosages > 1,000-fold higher than the minimal inhibitory concentration for their ancestors. Interestingly, such level of resistance was often associated with changes in susceptibility to other antibiotics, most prominently with increased resistance to fosfomycin. Whole-genome sequencing revealed that all resistant derivatives presented diverse mutations in five common genetic elements: fhuA, fusA and the atpIBEFHAGDC, cyoABCDE, and potABCD operons. Despite the large number of mutations acquired, hypermutable strains did not pay, apparently, fitness cost. In contrast to recent studies, we found that the mutation supply rate mainly affected the speed (tempo) but not the pattern (mode) of evolution: both backgrounds acquired the mutations in the same order, although the hypermutator strain did it faster. This observation is compatible with the adaptive landscape for high-level gentamicin resistance being relatively smooth, with few local maxima; which might be a common feature among antibiotics for which resistance involves multiple loci.

Local Fitness Landscapes Predict Yeast Evolutionary Dynamics in Directionally Changing Environments

The fitness landscape is a concept that is widely used for understanding and predicting evolutionary adaptation. The topography of the fitness landscape depends critically on the environment, with potentially far-reaching consequences for evolution under changing conditions. However, few studies have assessed directly how empirical fitness landscapes change across conditions, or validated the predicted consequences of such change. We previously evolved replicate yeast populations in the presence of either gradually increasing, or constant high, concentrations of the heavy metals cadmium (Cd), nickel (Ni), and zinc (Zn), and analyzed their phenotypic and genomic changes. Here, we reconstructed the local fitness landscapes underlying adaptation to each metal by deleting all repeatedly mutated genes both by themselves and in combination. Fitness assays revealed that the height, and/or shape, of each local fitness landscape changed considerably across metal concentrations, with distinct qualitative differences between unconditionally (Cd) and conditionally toxic metals (Ni and Zn). This change in topography had particularly crucial consequences in the case of Ni, where a substantial part of the individual mutational fitness effects changed in sign across concentrations. Based on the Ni landscape analyses, we made several predictions about which mutations had been selected when during the evolution experiment. Deep sequencing of population samples from different time points generally confirmed these predictions, demonstrating the power of landscape reconstruction analyses for understanding and ultimately predicting evolutionary dynamics, even under complex scenarios of environmental change.

Mutator genomes decay, despite sustained fitness gains, in a long-term experiment with bacteria

Understanding the extreme variation among bacterial genomes remains an unsolved challenge in evolutionary biology, despite long-standing debate about the relative importance of natural selection, mutation, and random drift. A potentially important confounding factor is the variation in mutation rates between lineages and over evolutionary history, which has been documented in several species. Mutation accumulation experiments have shown that hypermutability can erode genomes over short timescales. These results, however, were obtained under conditions of extremely weak selection, casting doubt on their general relevance. Here, we circumvent this limitation by analyzing genomes from mutator populations that arose during a long-term experiment with Escherichia coli, in which populations have been adaptively evolving for >50,000 generations. We develop an analytical framework to quantify the relative contributions of mutation and selection in shaping genomic characteristics, and we validate it using genomes evolved under regimes of high mutation rates with weak selection (mutation accumulation experiments) and low mutation rates with strong selection (natural isolates). Our results show that, despite sustained adaptive evolution in the long-term experiment, the signature of selection is much weaker than that of mutational biases in mutator genomes. This finding suggests that relatively brief periods of hypermutability can play an outsized role in shaping extant bacterial genomes. Overall, these results highlight the importance of genomic draft, in which strong linkage limits the ability of selection to purge deleterious mutations. These insights are also relevant to other biological systems evolving under strong linkage and high mutation rates, including viruses and cancer cells.

Population Parameters Underlying an Ongoing Soft Sweep in Southeast Asian Malaria Parasites

Multiple kelch13 alleles conferring artemisinin resistance (ART-R) are currently spreading through Southeast Asian malaria parasite populations, providing a unique opportunity to observe an ongoing soft selective sweep, investigate why resistance alleles have evolved multiple times and determine fundamental population genetic parameters for Plasmodium. We sequenced kelch13 (n = 1,876), genotyped 75 flanking SNPs, and measured clearance rate (n = 3,552) in parasite infections from Western Thailand (2001–2014). We describe 32 independent coding mutations including common mutations outside the kelch13 propeller associated with significant reductions in clearance rate. Mutations were first observed in 2003 and rose to 90% by 2014, consistent with a selection coefficient of ∼0.079. ART-R allele diversity rose until 2012 and then dropped as one allele (C580Y) spread to high frequency. The frequency with which adaptive alleles arise is determined by the rate of mutation and the population size. Two factors drive this soft sweep: (1) multiple kelch13 amino-acid mutations confer resistance providing a large mutational target—we estimate the target is 87–163 bp. (2) The population mutation parameter (Θ = 2N_eμ) can be estimated from the frequency distribution of ART-R alleles and is ∼5.69, suggesting that short term effective population size is 88 thousand to 1.2 million. This is 52–705 times greater than N_e estimated from fluctuation in allele frequencies, suggesting that we have previously underestimated the capacity for adaptive evolution in Plasmodium. Our central conclusions are that retrospective studies may underestimate the complexity of selective events and the N_e relevant for adaptation for malaria is considerably higher than previously estimated.

High-Throughput Identification of Adaptive Mutations in Experimentally Evolved Yeast Populations

High-throughput sequencing has enabled genetic screens that can rapidly identify mutations that occur during experimental evolution. The presence of a mutation in an evolved lineage does not, however, constitute proof that the mutation is adaptive, given the well-known and widespread phenomenon of genetic hitchhiking, in which a non-adaptive or even detrimental mutation can co-occur in a genome with a beneficial mutation and the combined genotype is carried to high frequency by selection. We approximated the spectrum of possible beneficial mutations in Saccharomyces cerevisiae using sets of single-gene deletions and amplifications of almost all the genes in the S. cerevisiae genome. We determined the fitness effects of each mutation in three different nutrient-limited conditions using pooled competitions followed by barcode sequencing. Although most of the mutations were neutral or deleterious, ~500 of them increased fitness. We then compared those results to the mutations that actually occurred during experimental evolution in the same three nutrient-limited conditions. On average, ~35% of the mutations that occurred during experimental evolution were predicted by the systematic screen to be beneficial. We found that the distribution of fitness effects depended on the selective conditions. In the phosphate-limited and glucose-limited conditions, a large number of beneficial mutations of nearly equivalent, small effects drove the fitness increases. In the sulfate-limited condition, one type of mutation, the amplification of the high-affinity sulfate transporter, dominated. In the absence of that mutation, evolution in the sulfate-limited condition involved mutations in other genes that were not observed previously—but were predicted by the systematic screen. Thus, gross functional screens have the potential to predict and identify adaptive mutations that occur during experimental evolution.

Experimental evolution allows us to observe evolution in real time. New advances in genome sequencing make it trivial to discover the mutations that have arisen in evolved cultures; however, linking those mutations to particular adaptive traits remains difficult. We evaluated the fitness impacts of thousands of single-gene losses and amplifications in yeast. We discovered that only a fraction of the hundreds of possible beneficial mutations were actually detected in evolution experiments performed previously. Our results provide evidence that 35% of the mutations identified in experimentally evolved populations are advantageous and that the distribution of beneficial fitness effects depends on the genetic background and the selective conditions. Furthermore, we show that it is possible to select for alternative mutations that improve fitness by blocking particularly high-fitness routes to adaptation.

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.

Love the one you're with: replicate viral adaptations converge on the same phenotypic change

Parallelism is important because it reveals how inherently stochastic adaptation is. Even as we come to better understand evolutionary forces, stochasticity limits how well we can predict evolutionary outcomes. Here we sought to quantify parallelism and some of its underlying causes by adapting a bacteriophage (ID11) with nine different first-step mutations, each with eight-fold replication, for 100 passages. This was followed by whole-genome sequencing five isolates from each endpoint. A large amount of variation arose—281 mutational events occurred representing 112 unique mutations. At least 41% of the mutations and 77% of the events were adaptive. Within wells, populations generally experienced complex interference dynamics. The genome locations and counts of mutations were highly uneven: mutations were concentrated in two regulatory elements and three genes and, while 103 of the 112 (92%) of the mutations were observed in ≤4 wells, a few mutations arose many times. 91% of the wells and 81% of the isolates had a mutation in the D-promoter. Parallelism was moderate compared to previous experiments with this system. On average, wells shared 27% of their mutations at the DNA level and 38% when the definition of parallel change is expanded to include the same regulatory feature or residue. About half of the parallelism came from D-promoter mutations. Background had a small but significant effect on parallelism. Similarly, an analyses of epistasis between mutations and their ancestral background was significant, but the result was mostly driven by four individual mutations. A second analysis of epistasis focused on de novo mutations revealed that no isolate ever had more than one D-promoter mutation and that 56 of the 65 isolates lacking a D-promoter mutation had a mutation in genes D and/or E. We assayed time to lysis in four of these mutually exclusive mutations (the two most frequent D-promoter and two in gene D) across four genetic backgrounds. In all cases lysis was delayed. We postulate that because host cells were generally rare (i.e., high multiplicity of infection conditions developed), selection favored phage that delayed lysis to better exploit their current host (i.e., ‘love the one you’re with’). Thus, the vast majority of wells (at least 64 of 68, or 94%) arrived at the same phenotypic solution, but through a variety of genetic changes. We conclude that answering questions about the range of possible adaptive trajectories, parallelism, and the predictability of evolution requires attention to the many biological levels where the process of adaptation plays out.

Empirical analysis of RNA robustness and evolution using high-throughput sequencing of ribozyme reactions

RNA molecules provide a realistic but tractable model of a genotype to phenotype relationship. This relationship has been extensively investigated computationally using secondary structure prediction algorithms. Enzymatic RNA molecules, or ribozymes, offer access to genotypic and phenotypic information in the laboratory. Advancements in high-throughput sequencing technologies have enabled the analysis of sequences in the lab that now rivals what can be accomplished computationally. This has motivated a resurgence of in vitro selection experiments and opened new doors for the analysis of the distribution of RNA functions in genotype space. A body of computational experiments has investigated the persistence of specific RNA structures despite changes in the primary sequence, and how this mutational robustness can promote adaptations. This article summarizes recent approaches that were designed to investigate the role of mutational robustness during the evolution of RNA molecules in the laboratory, and presents theoretical motivations, experimental methods and approaches to data analysis.

Large-Effect Beneficial Synonymous Mutations Mediate Rapid and Parallel Adaptation in a Bacterium

Contrary to previous understanding, recent evidence indicates that synonymous codon changes may sometimes face strong selection. However, it remains difficult to generalize the nature, strength, and mechanism(s) of such selection. Previously, we showed that synonymous variants of a key enzyme-coding gene (fae) of Methylobacterium extorquens AM1 decreased enzyme production and reduced fitness dramatically. We now show that during laboratory evolution, these variants rapidly regained fitness via parallel yet variant-specific, highly beneficial point mutations in the N-terminal region of fae. These mutations (including four synonymous mutations) had weak but consistently positive impacts on transcript levels, enzyme production, or enzyme activity. However, none of the proposed mechanisms (including internal ribosome pause sites or mRNA structure) predicted the fitness impact of evolved or additional, engineered point mutations. This study shows that synonymous mutations can be fixed through strong positive selection, but the mechanism for their benefit varies depending on the local sequence context.

Antisense Transcription of Retrotransposons in Drosophila: An Origin of Endogenous Small Interfering RNA Precursors

Movement of transposons causes insertions, deletions, and chromosomal rearrangements potentially leading to premature lethality in Drosophila melanogaster. To repress these elements and combat genomic instability, eukaryotes have evolved several small RNA-mediated defense mechanisms. Specifically, in Drosophila somatic cells, endogenous small interfering (esi)RNAs suppress retrotransposon mobility. EsiRNAs are produced by Dicer-2 processing of double-stranded RNA precursors, yet the origins of these precursors are unknown. We show that most transposon families are transcribed in both the sense (S) and antisense (AS) direction in Dmel-2 cells. LTR retrotransposons Dm297, mdg1, and blood, and non-LTR retrotransposons juan and jockey transcripts, are generated from intraelement transcription start sites with canonical RNA polymerase II promoters. We also determined that retrotransposon antisense transcripts are less polyadenylated than sense. RNA-seq and small RNA-seq revealed that Dicer-2 RNA interference (RNAi) depletion causes a decrease in the number of esiRNAs mapping to retrotransposons and an increase in expression of both S and AS retrotransposon transcripts. These data support a model in which double-stranded RNA precursors are derived from convergent transcription and processed by Dicer-2 into esiRNAs that silence both sense and antisense retrotransposon transcripts. Reduction of sense retrotransposon transcripts potentially lowers element-specific protein levels to prevent transposition. This mechanism preserves genomic integrity and is especially important for Drosophila fitness because mobile genetic elements are highly active.

Elucidating the molecular architecture of adaptation via evolve and resequence experiments

Evolve and resequence (E&R) experiments use experimental evolution to adapt populations to a novel environment, then next-generation sequencing to analyse genetic changes. They enable molecular evolution to be monitored in real time on a genome-wide scale. Here, we review the field of E&R experiments across diverse systems, ranging from simple non-living RNA to bacteria, yeast and the complex multicellular organism Drosophila melanogaster. We explore how different evolutionary outcomes in these systems are largely consistent with common population genetics principles. Differences in outcomes across systems are largely explained by different starting population sizes, levels of pre-existing genetic variation, recombination rates and adaptive landscapes. We highlight emerging themes and inconsistencies that future experiments must address.

Selective Sweeps and Parallel Pathoadaptation Drive Pseudomonas aeruginosa Evolution in the Cystic Fibrosis Lung

Pulmonary infections caused by Pseudomonas aeruginosa are a recalcitrant problem in cystic fibrosis (CF) patients. While the clinical implications and long-term evolutionary patterns of these infections are well studied, we know little about the short-term population dynamics that enable this pathogen to persist despite aggressive antimicrobial therapy. Here, we describe a short-term population genomic analysis of 233 P. aeruginosa isolates collected from 12 sputum specimens obtained over a 1-year period from a single patient. Whole-genome sequencing and antimicrobial susceptibility profiling identified the expansion of two clonal lineages. The first lineage originated from the coalescence of the entire sample less than 3 years before the end of the study and gave rise to a high-diversity ancestral population. The second expansion occurred 2 years later and gave rise to a derived population with a strong signal of positive selection. These events show characteristics consistent with recurrent selective sweeps. While we cannot identify the specific mutations responsible for the origins of the clonal lineages, we find that the majority of mutations occur in loci previously associated with virulence and resistance. Additionally, approximately one-third of all mutations occur in loci that are mutated multiple times, highlighting the importance of parallel pathoadaptation. One such locus is the gene encoding penicillin-binding protein 3, which received three independent mutations. Our functional analysis of these alleles shows that they provide differential fitness benefits dependent on the antibiotic under selection. These data reveal that bacterial populations can undergo extensive and dramatic changes that are not revealed by lower-resolution analyses.

IMPORTANCE

Pseudomonas aeruginosa is a bacterial opportunistic pathogen responsible for significant morbidity and mortality in cystic fibrosis (CF) patients. Once it has colonized the lung in CF, it is highly resilient and rarely eradicated. This study presents a deep sampling examination of the fine-scale evolutionary dynamics of P. aeruginosa in the lungs of a chronically infected CF patient. We show that diversity of P. aeruginosa is driven by recurrent clonal emergence and expansion within this patient and identify potential adaptive variants associated with these events. This high-resolution sequencing strategy thus reveals important intraspecies dynamics that explain a clinically important phenomenon not evident at a lower-resolution analysis of community structure.

Stochastic modeling indicates that aging and somatic evolution in the hematopoetic system are driven by non-cell-autonomous processes

Age-dependent tissue decline and increased cancer incidence are widely accepted to be rate-limited by the accumulation of somatic mutations over time. Current models of carcinogenesis are dominated by the assumption that oncogenic mutations have defined advantageous fitness effects on recipient stem and progenitor cells, promoting and rate-limiting somatic evolution. However, this assumption is markedly discrepant with evolutionary theory, whereby fitness is a dynamic property of a phenotype imposed upon and widely modulated by environment. We computationally modeled dynamic microenvironment-dependent fitness alterations in hematopoietic stem cells (HSC) within the Sprengel-Liebig system known to govern evolution at the population level. Our model for the first time integrates real data on age-dependent dynamics of HSC division rates, pool size, and accumulation of genetic changes and demonstrates that somatic evolution is not rate-limited by the occurrence of mutations, but instead results from aged microenvironment-driven alterations in the selective/fitness value of previously accumulated genetic changes. Our results are also consistent with evolutionary models of aging and thus oppose both somatic mutation-centric paradigms of carcinogenesis and tissue functional decline. In total, we demonstrate that aging directly promotes HSC fitness decline and somatic evolution via non-cell-autonomous mechanisms.

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.

Parallel and Divergent Evolutionary Solutions for the Optimization of an Engineered Central Metabolism in Methylobacterium extorquens AM1

Bioengineering holds great promise to provide fast and efficient biocatalysts for methanol-based biotechnology, but necessitates proven methods to optimize physiology in engineered strains. Here, we highlight experimental evolution as an effective means for optimizing an engineered Methylobacterium extorquens AM1. Replacement of the native formaldehyde oxidation pathway with a functional analog substantially decreased growth in an engineered Methylobacterium, but growth rapidly recovered after six hundred generations of evolution on methanol. We used whole-genome sequencing to identify the basis of adaptation in eight replicate evolved strains, and examined genomic changes in light of other growth and physiological data. We observed great variety in the numbers and types of mutations that occurred, including instances of parallel mutations at targets that may have been "rationalized" by the bioengineer, plus other "illogical" mutations that demonstrate the ability of evolution to expose unforeseen optimization solutions. Notably, we investigated mutations to RNA polymerase, which provided a massive growth benefit but are linked to highly aberrant transcriptional profiles. Overall, we highlight the power of experimental evolution to present genetic and physiological solutions for strain optimization, particularly in systems where the challenges of engineering are too many or too difficult to overcome via traditional engineering methods.

Genetic and phenotypic comparison of facultative methylotrophy between Methylobacterium extorquens strains PA1 and AM1

Methylobacterium extorquens AM1, a strain serendipitously isolated half a century ago, has become the best-characterized model system for the study of aerobic methylotrophy (the ability to grow on reduced single-carbon compounds). However, with 5 replicons and 174 insertion sequence (IS) elements in the genome as well as a long history of domestication in the laboratory, genetic and genomic analysis of M. extorquens AM1 face several challenges. On the contrary, a recently isolated strain - M. extorquens PA1- is closely related to M. extorquens AM1 (100% 16S rRNA identity) and contains a streamlined genome with a single replicon and only 20 IS elements. With the exception of the methylamine dehydrogenase encoding gene cluster (mau), genes known to be involved in methylotrophy are well conserved between M. extorquens AM1 and M. extorquens PA1. In this paper we report four primary findings regarding methylotrophy in PA1. First, with a few notable exceptions, the repertoire of methylotrophy genes between PA1 and AM1 is extremely similar. Second, PA1 grows faster with higher yields compared to AM1 on C₁ and multi-C substrates in minimal media, but AM1 grows faster in rich medium. Third, deletion mutants in PA1 throughout methylotrophy modules have the same C₁ growth phenotypes observed in AM1. Finally, the precision of our growth assays revealed several unexpected growth phenotypes for various knockout mutants that serve as leads for future work in understanding their basis and generality across Methylobacterium strains.

Deleterious passengers in adapting populations

Most new mutations are deleterious and are eventually eliminated by natural selection. But in an adapting population, the rapid amplification of beneficial mutations can hinder the removal of deleterious variants in nearby regions of the genome, altering the patterns of sequence evolution. Here, we analyze the interactions between beneficial "driver" mutations and linked deleterious "passengers" during the course of adaptation. We derive analytical expressions for the substitution rate of a deleterious mutation as a function of its fitness cost, as well as the reduction in the beneficial substitution rate due to the genetic load of the passengers. We find that the fate of each deleterious mutation varies dramatically with the rate and spectrum of beneficial mutations and the deleterious substitution rate depends nonmonotonically on the population size and the rate of adaptation. By quantifying this dependence, our results allow us to estimate which deleterious mutations will be likely to fix and how many of these mutations must arise before the progress of adaptation is significantly reduced.

Multiple phenotypic changes associated with large-scale horizontal gene transfer

Horizontal gene transfer often leads to phenotypic changes within recipient organisms independent of any immediate evolutionary benefits. While secondary phenotypic effects of horizontal transfer (i.e., changes in growth rates) have been demonstrated and studied across a variety of systems using relatively small plasmids and phage, little is known about the magnitude or number of such costs after the transfer of larger regions. Here we describe numerous phenotypic changes that occur after a large-scale horizontal transfer event (∼1 Mb megaplasmid) within Pseudomonas stutzeri including sensitization to various stresses as well as changes in bacterial behavior. These results highlight the power of horizontal transfer to shift pleiotropic relationships and cellular networks within bacterial genomes. They also provide an important context for how secondary effects of transfer can bias evolutionary trajectories and interactions between species. Lastly, these results and system provide a foundation to investigate evolutionary consequences in real time as newly acquired regions are ameliorated and integrated into new genomic contexts.

Single-cell genomics reveals hundreds of coexisting subpopulations in wild Prochlorococcus

Extensive genomic diversity within coexisting members of a microbial species has been revealed through selected cultured isolates and metagenomic assemblies. Yet, the cell-by-cell genomic composition of wild uncultured populations of co-occurring cells is largely unknown. In this work, we applied large-scale single-cell genomics to study populations of the globally abundant marine cyanobacterium Prochlorococcus. We show that they are composed of hundreds of subpopulations with distinct "genomic backbones," each backbone consisting of a different set of core gene alleles linked to a small distinctive set of flexible genes. These subpopulations are estimated to have diverged at least a few million years ago, suggesting ancient, stable niche partitioning. Such a large set of coexisting subpopulations may be a general feature of free-living bacterial species with huge populations in highly mixed habitats.

The dynamics of diverse segmental amplifications in populations of Saccharomyces cerevisiae adapting to strong selection

Population adaptation to strong selection can occur through the sequential or parallel accumulation of competing beneficial mutations. The dynamics, diversity, and rate of fixation of beneficial mutations within and between populations are still poorly understood. To study how the mutational landscape varies across populations during adaptation, we performed experimental evolution on seven parallel populations of Saccharomyces cerevisiae continuously cultured in limiting sulfate medium. By combining quantitative polymerase chain reaction, array comparative genomic hybridization, restriction digestion and contour-clamped homogeneous electric field gel electrophoresis, and whole-genome sequencing, we followed the trajectory of evolution to determine the identity and fate of beneficial mutations. During a period of 200 generations, the yeast populations displayed parallel evolutionary dynamics that were driven by the coexistence of independent beneficial mutations. Selective amplifications rapidly evolved under this selection pressure, in particular common inverted amplifications containing the sulfate transporter gene SUL1. Compared with single clones, detailed analysis of the populations uncovers a greater complexity whereby multiple subpopulations arise and compete despite a strong selection. The most common evolutionary adaptation to strong selection in these populations grown in sulfate limitation is determined by clonal interference, with adaptive variants both persisting and replacing one another.

The first steps of adaptation of Escherichia coli to the gut are dominated by soft sweeps

The accumulation of adaptive mutations is essential for survival in novel environments. However, in clonal populations with a high mutational supply, the power of natural selection is expected to be limited. This is due to clonal interference - the competition of clones carrying different beneficial mutations - which leads to the loss of many small effect mutations and fixation of large effect ones. If interference is abundant, then mechanisms for horizontal transfer of genes, which allow the immediate combination of beneficial alleles in a single background, are expected to evolve. However, the relevance of interference in natural complex environments, such as the gut, is poorly known. To address this issue, we have developed an experimental system which allows to uncover the nature of the adaptive process as Escherichia coli adapts to the mouse gut. This system shows the invasion of beneficial mutations in the bacterial populations and demonstrates the pervasiveness of clonal interference. The observed dynamics of change in frequency of beneficial mutations are consistent with soft sweeps, where different adaptive mutations with similar phenotypes, arise repeatedly on different haplotypes without reaching fixation. Despite the complexity of this ecosystem, the genetic basis of the adaptive mutations revealed a striking parallelism in independently evolving populations. This was mainly characterized by the insertion of transposable elements in both coding and regulatory regions of a few genes. Interestingly, in most populations we observed a complete phenotypic sweep without loss of genetic variation. The intense clonal interference during adaptation to the gut environment, here demonstrated, may be important for our understanding of the levels of strain diversity of E. coli inhabiting the human gut microbiota and of its recombination rate.

Adaptation to novel environments involves the accumulation of beneficial mutations. If these are rare the process will proceed slowly with each one sweeping to fixation on its own. On the contrary if they are common in clonal populations, individuals carrying different beneficial alleles will experience intense competition and only those clones carrying the stronger effect mutations will leave a future line of descent. This phenomenon is known as clonal interference and the extent to which it occurs in natural environments is unknown. One of the most complex natural environments for E. coli is the mammalian intestine, where it evolves in the presence of many species comprising the gut microbiota. We have studied the dynamics of adaptation of E. coli populations evolving in this relevant ecosystem. We show that clonal interference is pervasive in the mouse gut and that the targets of natural selection are similar in independently E. coli evolving populations. These results illustrate how experimental evolution in natural environments allows us to dissect the mechanisms underlying adaptation and its complex dynamics and further reveal the importance of mobile genetic elements in contributing to the adaptive diversification of bacterial populations in the gut.

Explaining microbial genomic diversity in light of evolutionary ecology

Comparisons of closely related microorganisms have shown that individual genomes can be highly diverse in terms of gene content. In this Review, we discuss several studies showing that much of this variation is associated with social and ecological interactions, which have an important role in the population biology of wild populations of bacteria and archaea. These interactions create frequency-dependent selective pressures that can either stabilize gene frequencies at intermediate levels in populations or promote fast gene turnover, which presents as low gene frequencies in genome surveys. Thus, interpretation of gene-content diversity requires the delineation of populations according to cohesive gene flow and ecology, as micro-evolutionary changes arise in response to local selection pressures and population dynamics.

Mapping the fitness landscape of gene expression uncovers the cause of antagonism and sign epistasis between adaptive mutations

How do adapting populations navigate the tensions between the costs of gene expression and the benefits of gene products to optimize the levels of many genes at once? Here we combined independently-arising beneficial mutations that altered enzyme levels in the central metabolism of Methylobacterium extorquens to uncover the fitness landscape defined by gene expression levels. We found strong antagonism and sign epistasis between these beneficial mutations. Mutations with the largest individual benefit interacted the most antagonistically with other mutations, a trend we also uncovered through analyses of datasets from other model systems. However, these beneficial mutations interacted multiplicatively (i.e., no epistasis) at the level of enzyme expression. By generating a model that predicts fitness from enzyme levels we could explain the observed sign epistasis as a result of overshooting the optimum defined by a balance between enzyme catalysis benefits and fitness costs. Knowledge of the phenotypic landscape also illuminated that, although the fitness peak was phenotypically far from the ancestral state, it was not genetically distant. Single beneficial mutations jumped straight toward the global optimum rather than being constrained to change the expression phenotypes in the correlated fashion expected by the genetic architecture. Given that adaptation in nature often results from optimizing gene expression, these conclusions can be widely applicable to other organisms and selective conditions. Poor interactions between individually beneficial alleles affecting gene expression may thus compromise the benefit of sex during adaptation and promote genetic differentiation.

The pace and outcome of a series of adaptive steps in an evolving lineage depends upon how well different beneficial mutations stack on top of each other. We found that independent beneficial mutations that affected gene expression for a metabolic pathway did not work well together, and were often jointly deleterious. The most beneficial mutations interacted the most poorly with others, which was a trend we found common in other biological systems. Through generating a model that accounted for enzymatic benefits and expression costs, we uncovered that this antagonism was caused by a phenotype to fitness mapping that had an intermediate peak. This allowed us to predict the fitness effect of double mutants and to uncover that the single winning mutations tended to move straight to the peak in a single step. These findings demonstrate the importance of considering the phenotypic changes that cause nonlinear interactions between mutations upon fitness, and thus influence how populations evolve.

The fates of mutant lineages and the distribution of fitness effects of beneficial mutations in laboratory budding yeast populations

The outcomes of evolution are determined by which mutations occur and fix. In rapidly adapting microbial populations, this process is particularly hard to predict because lineages with different beneficial mutations often spread simultaneously and interfere with one another's fixation. Hence to predict the fate of any individual variant, we must know the rate at which new mutations create competing lineages of higher fitness. Here, we directly measured the effect of this interference on the fates of specific adaptive variants in laboratory Saccharomyces cerevisiae populations and used these measurements to infer the distribution of fitness effects of new beneficial mutations. To do so, we seeded marked lineages with different fitness advantages into replicate populations and tracked their subsequent frequencies for hundreds of generations. Our results illustrate the transition between strongly advantageous lineages that decisively sweep to fixation and more moderately advantageous lineages that are often outcompeted by new mutations arising during the course of the experiment. We developed an approximate likelihood framework to compare our data to simulations and found that the effects of these competing beneficial mutations were best approximated by an exponential distribution, rather than one with a single effect size. We then used this inferred distribution of fitness effects to predict the rate of adaptation in a set of independent control populations. Finally, we discuss how our experimental design can serve as a screen for rare, large-effect beneficial mutations.

Molecular specificity, convergence and constraint shape adaptive evolution in nutrient-poor environments

One of the central goals of evolutionary biology is to explain and predict the molecular basis of adaptive evolution. We studied the evolution of genetic networks in Saccharomyces cerevisiae (budding yeast) populations propagated for more than 200 generations in different nitrogen-limiting conditions. We find that rapid adaptive evolution in nitrogen-poor environments is dominated by the de novo generation and selection of copy number variants (CNVs), a large fraction of which contain genes encoding specific nitrogen transporters including PUT4, DUR3 and DAL4. The large fitness increases associated with these alleles limits the genetic heterogeneity of adapting populations even in environments with multiple nitrogen sources. Complete identification of acquired point mutations, in individual lineages and entire populations, identified heterogeneity at the level of genetic loci but common themes at the level of functional modules, including genes controlling phosphatidylinositol-3-phosphate metabolism and vacuole biogenesis. Adaptive strategies shared with other nutrient-limited environments point to selection of genetic variation in the TORC1 and Ras/PKA signaling pathways as a general mechanism underlying improved growth in nutrient-limited environments. Within a single population we observed the repeated independent selection of a multi-locus genotype, comprised of the functionally related genes GAT1, MEP2 and LST4. By studying the fitness of individual alleles, and their combination, as well as the evolutionary history of the evolving population, we find that the order in which these mutations are acquired is constrained by epistasis. The identification of repeatedly selected variation at functionally related loci that interact epistatically suggests that gene network polymorphisms (GNPs) may be a frequent outcome of adaptive evolution. Our results provide insight into the mechanistic basis by which cells adapt to nutrient-limited environments and suggest that knowledge of the selective environment and the regulatory mechanisms important for growth and survival in that environment greatly increase the predictability of adaptive evolution.

We studied adaptive evolution in different nitrogen-limited environments using long-term selection of asexually reproducing Saccharomyces cerevisiae populations in chemostats. Using next generation sequencing and DNA microarrays, we identified all acquired genetic variation associated with increased fitness, in both individual lineages and entire populations. We find that amplification alleles that include nutrient transporter genes specific to the molecular form of the nitrogen present in the environment are a common mechanism underlying increased fitness. In addition, we identified a general strategy for adaptation to nitrogen-limited environments that entails remodeling of phospholipid biogenesis required for producing important cellular components including vacuoles and autophagosomes. More general strategies for adaptation to nutrient-limited environments point to a role for re-wiring of signaling pathways that coordinate cell growth with nutrient availability. We reconstructed the evolutionary dynamics of a population evolving in ammonium-limited conditions and find that a multi-locus genotype is repeatedly selected within the population and constrained by epistasis. We propose that this genotype constitutes a “gene network polymorphism (GNP),” which may be a common outcome of adaptive evolution. Our study suggests that when the selective pressure is understood the molecular basis of adaptive evolution in large microbial populations may be predicted with reasonable precision.