Clonal Interference Research Articles

The Dynamics of Genetic Draft in Rapidly Adapting Populations

The accumulation of beneficial mutations on competing genetic backgrounds in rapidly adapting populations has a striking impact on evolutionary dynamics. This effect, known as clonal interference, causes erratic fluctuations in the frequencies of observed mutations, randomizes the fixation times of successful mutations, and leaves distinct signatures on patterns of genetic variation. Here, we show how this form of "genetic draft" affects the forward-time dynamics of site frequencies in rapidly adapting asexual populations. We calculate the probability that mutations at individual sites shift in frequency over a characteristic timescale, extending Gillespie's original model of draft to the case where many strongly selected beneficial mutations segregate simultaneously. We then derive the sojourn time of mutant alleles, the expected fixation time of successful mutants, and the site frequency spectrum of beneficial and neutral mutations. Finally, we show how this form of draft affects inferences in the McDonald-Kreitman test and how it relates to recent observations that some aspects of genetic diversity are described by the Bolthausen-Sznitman coalescent in the limit of very rapid adaptation.

Contribution of Selection for Protein Folding Stability in Shaping the Patterns of Polymorphisms in Coding Regions

The patterns of polymorphisms in genomes are imprints of the evolutionary forces at play in nature. In particular, polymorphisms have been extensively used to infer the fitness effects of mutations and their dynamics of fixation. However, the role and contribution of molecular biophysics to these observations remain unclear. Here, we couple robust findings from protein biophysics, enzymatic flux theory, the selection against the cytotoxic effects of protein misfolding, and explicit population dynamics simulations in the polyclonal regime. First, we recapitulate results on the dynamics of clonal interference and on the shape of the DFE, thus providing them with a molecular and mechanistic foundation. Second, we predict that if evolution is indeed under the dynamic equilibrium of mutation–selection balance, the fraction of stabilizing and destabilizing mutations is almost equal among single-nucleotide polymorphisms segregating at high allele frequencies. This prediction is proven true for polymorphisms in the human coding region. Overall, our results show how selection for protein folding stability predominantly shapes the patterns of polymorphisms in coding regions.

Immune networks: multitasking capabilities near saturation

Pattern-diluted associative networks were recently introduced as models for the immune system, with nodes representing T-lymphocytes and stored patterns representing signalling protocols between T- and B-lymphocytes. It was shown earlier that in the regime of extreme pattern dilution, a system with NT T-lymphocytes can manage a number of B-lymphocytes simultaneously, with δ < 1. Here we study this model in the extensive load regime NB = αNT, with a high degree of pattern dilution, in agreement with immunological findings. We use graph theory and statistical mechanical analysis based on replica methods to show that in the finite-connectivity regime, where each T-lymphocyte interacts with a finite number of B-lymphocytes as NT → ∞, the T-lymphocytes can coordinate effective immune responses to an extensive number of distinct antigen invasions in parallel. As α increases, the system eventually undergoes a second order transition to a phase with clonal cross-talk interference, where the system’s performance degrades gracefully. Mathematically, the model is equivalent to a spin system on a finitely connected graph with many short loops, so one would expect the available analytical methods, which all assume locally tree-like graphs, to fail. Yet it turns out to be solvable. Our results are supported by numerical simulations.

The effect of mating system on invasiveness: some genetic load may be advantageous when invading new environments

The role of adaptation in determining invasion success has been acknowledged recently, notably through the accumulation of case studies of rapid evolution during bioinvasions. Despite this growing body of empirical evidence, there is still a need to develop the theoretical background of invasions with adaptation. Specifically, the impact of mating system on the dynamics of adaptation during invasion of a new environment remains only partially understood. Here, we analyze a simulation demo-genetic model of bioinvasion accounting for partial asexuality rates. We simulate two levels of recurrent immigration from a source population at mutation–drift–selection equilibrium to a new empty environment with a different adaptive landscape (black-hole sink). Adaptation relies on a quantitative trait coded explicitly by 10 loci under mutation, selection and genetic drift. Using this model, we confirm previous results on the positive effects on invasiveness of migration, mutation and similarity of local phenotypic optima. We further show how the invasion dynamics of the introduced population is affected by the rate of asexuality. Purely asexual species have lower invasion success in terms of probability and time to invasion than species with other mating systems. Among species with mixed mating systems, the greatest invasiveness is observed for species with high asexual rates. We suggest that this pattern is due to inflated genetic variance in the source population through the Hill-Robertson effect (i.e., clonal interference). An interesting consequence is that species with the highest genetic load in their source environment have greatest invasiveness in the new environment.

Pervasive genetic hitchhiking and clonal interference in forty evolving yeast populations

The dynamics of adaptation determines which mutations fix in a population, and hence how reproducible evolution will be. This is central to understanding the spectra of mutations recovered in evolution of antibiotic resistance1, the response of pathogens to immune selection2,3, and the dynamics of cancer progression4,5. In laboratory evolution experiments, demonstrably beneficial mutations are found repeatedly6–8, but are often accompanied by other mutations with no obvious benefit. Here we use whole-genome whole-population sequencing to examine the dynamics of genome sequence evolution at high temporal resolution in 40 replicate Saccharomyces cerevisiae populations growing in rich medium for 1,000 generations. We find pervasive genetic hitchhiking: multiple mutations arise and move synchronously through the population as mutational “cohorts.” Multiple clonal cohorts are often present simultaneously, competing with each other in the same population. Our results show that patterns of sequence evolution are driven by a balance between these chance effects of hitchhiking and interference, which increase stochastic variation in evolutionary outcomes, and the deterministic action of selection on individual mutations, which favors parallel evolutionary solutions in replicate populations.

Frequent Coinfection Reduces RNA Virus Population Genetic Diversity

The masking of deleterious mutations by complementation and the reassortment of virus segments (virus sex) are expected to increase population genetic diversity among coinfecting viruses. Conversely, clonally reproducing or noncoinfecting virus populations may experience clonal interference where viral clones compete with one another, preventing selective sweeps. This dynamic reduces the efficiency of selection and increases the genetic diversity. To determine the relative influences of these forces on population genetic diversity, we evolved 6 populations of bacteriophage φ6 under conditions promoting or preventing coinfection. Following 300 generations, we isolated and partially sequenced 10 clones from each population. We found greater diversity among asexual populations than sexual populations. Moreover, sexual populations did not show greater relative fitnesses than asexual populations, implying that reduced genetic variation did not result from purifying selection. However, sexual populations were less genetically robust than asexual populations and likely more prone to the deleterious epistatic effects of mutations. As such, a neutral mutation on the asexually evolved (robust) background could be profoundly deleterious on the sexually evolved (brittle) background. This could facilitate sexual populations undergoing greater purifying selection to remove deleterious mutations, but this selection is not reflected by increases in average population fitness. Our results bolster a growing literature suggesting that RNA virus segmentation is probably not a mechanism that evolved because it provides a generalized benefit of sex.

EVOLUTIONARY REVERSALS OF ANTIBIOTIC RESISTANCE IN EXPERIMENTAL POPULATIONS OFPSEUDOMONAS AERUGINOSA

Antibiotic resistance mutations are accompanied by a fitness cost, and two mechanisms allow bacteria to adapt to this cost once antibiotic use is halted. First, it is possible for resistance to revert; second, it is possible for bacteria to adapt to the cost of resistance by compensatory mutations. Unfortunately, reversion to antibiotic sensitivity is rare, but the underlying factors that prevent reversion remain obscure. Here, we directly study the evolutionary dynamics of reversion by experimentally mimicking reversion mutations-sensitives-in populations of rifampicin-resistant Pseudomonas aeruginosa. We show that, in our populations, most sensitives are lost due to genetic drift when they are rare. However, clonal interference from lineages carrying compensatory mutations causes a dramatic increase in the time to fixation of sensitives that escape genetic drift, and mutations surpassing the sensitives' fitness are capable of driving transiently common sensitive lineages to extinction. Crucially, we show that the constraints on reversion arising from clonal interference are determined by the potential for compensatory adaptation of the resistant population. Although the cost of resistance provides the incentive for reversion, our study demonstrates that both the cost of resistance and the intrinsic evolvability of resistant populations interact to determine the rate and likelihood of reversion.

Synchronous Waves of Failed Soft Sweeps in the Laboratory: Remarkably Rampant Clonal Interference of Alleles at a Single Locus

It has increasingly been recognized that adapting populations of microbes contain not one, but many lineages continually arising and competing at once. This process, termed "clonal interference," alters the rate and dynamics of adaptation and biases winning mutations toward those with the largest selective effect. Here we uncovered a dramatic example of clonal interference between multiple similar mutations occurring at the same locus within replicate populations of Methylobacterium extorquens AM1. Because these mutational events involved the transposition of an insertion sequence into a narrow window of a single gene, they were both readily detectable at low frequencies and could be distinguished due to differences in insertion sites. This allowed us to detect up to 17 beneficial alleles of this type coexisting in a single population. Despite conferring a large selective benefit, the majority of these alleles rose and then fell in frequency due to other lineages emerging that were more fit. By comparing allele-frequency dynamics to the trajectories of fitness gains by these populations, we estimated the fitness values of the genotypes that contained these mutations. Collectively across all populations, these alleles arose upon backgrounds with a wide range of fitness values. Within any single population, however, multiple alleles tended to rise and fall synchronously during a single wave of multiple genotypes with nearly identical fitness values. These results suggest that alleles of large benefit arose repeatedly in failed "soft sweeps" during narrow windows of adaptation due to the combined effects of epistasis and clonal interference.

Pre‐tumour clones, periodic selection and clonal interference in the origin and progression of gastrointestinal cancer: potential for biomarker development

Classically, the risk of cancer progression in premalignant conditions of the gastrointestinal tract is assessed by examining the degree of histological dysplasia. However, there are many putative pro-cancer genetic changes that have occurred in histologically normal tissue well before the onset of dysplasia. Here we summarize the evidence for such pre-tumour clones and the existing technology that can be used to locate these clones and characterize them at the genetic level. We also discuss the mechanisms by which pre-tumour clones may spread through large areas of normal tissue, and highlight emerging theories on how multiple clones compete and interact within the gastrointestinal mucosa. It is important to gain an understanding of these processes, as it is envisaged that certain pre-tumour changes may be powerful predictive markers, with the potential to identify patients at high risk of developing cancer at a much earlier stage.

Genetic Diversity and the Structure of Genealogies in Rapidly Adapting Populations

Positive selection distorts the structure of genealogies and hence alters patterns of genetic variation within a population. Most analyses of these distortions focus on the signatures of hitchhiking due to hard or soft selective sweeps at a single genetic locus. However, in linked regions of rapidly adapting genomes, multiple beneficial mutations at different loci can segregate simultaneously within the population, an effect known as clonal interference. This leads to a subtle interplay between hitchhiking and interference effects, which leads to a unique signature of rapid adaptation on genetic variation both at the selected sites and at linked neutral loci. Here, we introduce an effective coalescent theory (a "fitness-class coalescent") that describes how positive selection at many perfectly linked sites alters the structure of genealogies. We use this theory to calculate several simple statistics describing genetic variation within a rapidly adapting population and to implement efficient backward-time coalescent simulations, which can be used to predict how clonal interference alters the expected patterns of molecular evolution.

The effects of linkage on comparative estimators of selection

BackgroundA major goal of molecular evolution is to determine how natural selection has shaped the evolution of a gene. One approach taken by methods such as K A /K S and the McDonald-Kreitman (MK) test is to compare the frequency of non-synonymous and synonymous changes. These methods, however, rely on the assumption that a change in frequency of one mutation will not affect changes in frequency of other mutations.ResultsWe demonstrate that linkage between sites can bias measures of selection based on synonymous and non-synonymous changes. Using forward simulation of a Wright-Fisher process, we show that hitch-hiking of deleterious mutations with advantageous mutations can lead to overestimation of the number of adaptive substitutions, while background selection and clonal interference can distort the site frequency spectrum to obscure the signal for positive selection. We present three diagnostics for detecting these effects of linked selection and apply them to the human influenza (H3N2) hemagglutinin gene.ConclusionVarious forms of linked selection have characteristic effects on MK-type statistics. The extent of background selection, hitch-hiking and clonal interference can be evaluated using the diagnostic statistics presented here. The diagnostics can also be used to determine how well we expect the MK statistics to perform and whether one form of the statistic may be preferable to another.

The maintenance of sex: Ronald Fisher meets the Red Queen

BackgroundSex in higher diploids carries a two-fold cost of males that should reduce its fitness relative to cloning, and result in its extinction. Instead, sex is widespread and clonal species face early obsolescence. One possible reason is that sex is an adaptation that allows organisms to respond more effectively to endless changes in their environment. The purpose of this study was to model mutation and selection in a diploid organism in an evolving environment and ascertain their support for sex.ResultsWe used a computational approach to model finite populations where a haploid environment subjects a diploid host to endlessly evolving change. Evolution in both populations is primarily through adoption of novel advantageous mutations within a large allele space. Sex outcompetes cloning by two complementary mechanisms. First, sexual diploids adopt advantageous homozygous mutations more rapidly than clonal ones under conditions of lag load (the gap between the actual adaptation of the diploid population and its theoretical optimum). This rate advantage can offset the higher fecundity of cloning. Second, a relative advantage to sex emerges where populations are significantly polymorphic, because clonal polymorphism runs the risk of clonal interference caused by selection on numerous lines of similar adaptation. This interference extends allele lifetime and reduces the rate of adaptation. Sex abolishes the interference, making selection faster and elevating population fitness. Differences in adaptation between sexual and clonal populations increase markedly with the number of loci under selection, the rate of mutation in the host, and a rapidly evolving environment. Clonal interference in these circumstances leads to conditions where the greater fecundity of clones is unable to offset their poor adaptation. Sexual and clonal populations then either co-exist, or sex emerges as the more stable evolutionary strategy.ConclusionsSex can out-compete clones in a rapidly evolving environment, such as that characterized by pathogens, where clonal interference reduces the adaptation of clonal populations and clones adopt advantageous mutations more slowly. Since all organisms carry parasitic loads, the model is of potentially general applicability.

The quantitative theory of within-host viral evolution

During the 1990s, a group of virologists and physicists began development of a quantitative theory to explain the rapid evolution of human immunodeficiency virus type 1 (HIV-1). This theory also proved to be instrumental in understanding the rapid emergence of drug resistance in patients. Over the past two decades, this theory expanded to account for a broad array of factors important to viral evolution and propelled development of a generalized theory applicable to a broad range of asexual and partly sexual populations with many evolving sites. Here, we discuss the conceptual and theoretical tools developed to calculate the speed and other parameters of evolution, with a particular focus on the concept of ‘clonal interference’ and its applications to untreated patients.

Reply to McDonald

To the Editor—We thank Dr McDonald for his interest in our work and concur that the role of particular ribotypes in the clinical outcome of Clostridium difficile infection (CDI) is complex [1]. Our study identified several factors that predicted severe CDI in unadjusted analysis, including ribotype 027/078 (Table 2 in our article) [2]. We agree that including intermediate white blood cell (WBC) counts in our final model (Table 4 in our article) may have potentially attenuated direct effects of ribotype on outcome. In Table 3 of our article, we show, however, that adjustment for any of the significant predictors rendered ribotype 027/078 effect on CDI severity nonsignificant [2], indicating that WBC count was not required for the conclusions drawn in our study. To directly address the possibility that WBC count was influenced by ribotype-specific host responses requires temporal patient data, including treatment, which we did not collect. To indirectly address this issue, we performed additional analyses for our combined dataset (N = 412 cases with complete data) in the following 4 contexts: We added abnormal WBC count ( 12 000 cells/mL) to the definition of severe CDI. We determined whether ribotype 027/078 predicted an abnormal WBC count. We excluded both WBC count and albumin levels from the analysis, as is appropriate if they are potentially confounded. We again added abnormal WBC to the severe CDI definition and excluded albumin level from the analysis. Ribotype 027/078 was not significant in any of these contexts (adjusted analyses). Although these results do not exclude the possibility raised by McDonald, they do add support to our original conclusion that predictors other than ribotype may be more important in explaining the variability of CDI severity. We did not explore the influence of treatment on outcome, so the influence of ribotype was either not strong enough to overcome these effects or they were relatively minor. Why the incidence and severity of CDI increased in the early 2000s remains unclear. However, epidemic spread of clonal pathogens need not result from advantageous phenotypes (toxin production, sporulation, antibiotic resistance, etc). Such population expansions may result simply by chance, as transmission rates overcome clonal interference. Temporal fluctuations in ribotype prevalence support a “drift” scenario [3]. Such fluctuations suggest that many ribotypes reach a high local prevalence, which would increase transmission and potentiate a high global prevalence. This phenomenon does not necessitate strong selection, although increased antibiotic resistance suggests that strong selective pressure from fluoroquinolones and other antimicrobials has been important [4, 5]. As noted by McDonald, the prevalences of both 027 CDI cases and severe outcome are declining in apparent synchrony. However, both declines have occurred in light of heightened surveillance, improved diagnostics, more effective/aggressive infection control practices and therapies, and the popularization of antimicrobial stewardship. Correlations among these shifting practices, ribotype prevalence, and clinical outcome are understudied and require more data from properly designed studies that recognize the potential role of chance (null hypothesis). As 027 prevalence wanes in Europe [6], it appears that the C. difficile population is changing back to a more even distribution. These are exciting times in C. difficile epidemiology, but the complexity of ribotype-specific influences on disease progression and/or severity remains mottled.

FREQ-Seq: A Rapid, Cost-Effective, Sequencing-Based Method to Determine Allele Frequencies Directly from Mixed Populations

Understanding evolutionary dynamics within microbial populations requires the ability to accurately follow allele frequencies through time. Here we present a rapid, cost-effective method (FREQ-Seq) that leverages Illumina next-generation sequencing for localized, quantitative allele frequency detection. Analogous to RNA-Seq, FREQ-Seq relies upon counts from the >105 reads generated per locus per time-point to determine allele frequencies. Loci of interest are directly amplified from a mixed population via two rounds of PCR using inexpensive, user-designed oligonucleotides and a bar-coded bridging primer system that can be regenerated in-house. The resulting bar-coded PCR products contain the adapters needed for Illumina sequencing, eliminating further library preparation. We demonstrate the utility of FREQ-Seq by determining the order and dynamics of beneficial alleles that arose as a microbial population, founded with an engineered strain of Methylobacterium, evolved to grow on methanol. Quantifying allele frequencies with minimal bias down to 1% abundance allowed effective analysis of SNPs, small in-dels and insertions of transposable elements. Our data reveal large-scale clonal interference during the early stages of adaptation and illustrate the utility of FREQ-Seq as a cost-effective tool for tracking allele frequencies in populations.

Clonal Interference in the Evolution of Influenza

The seasonal influenza A virus undergoes rapid evolution to escape human immune response. Adaptive changes occur primarily in antigenic epitopes, the antibody-binding domains of the viral hemagglutinin. This process involves recurrent selective sweeps, in which clusters of simultaneous nucleotide fixations in the hemagglutinin coding sequence are observed about every 4 years. Here, we show that influenza A (H3N2) evolves by strong clonal interference. This mode of evolution is a red queen race between viral strains with different beneficial mutations. Clonal interference explains and quantifies the observed sweep pattern: we find an average of at least one strongly beneficial amino acid substitution per year, and a given selective sweep has three to four driving mutations on average. The inference of selection and clonal interference is based on frequency time series of single-nucleotide polymorphisms, which are obtained from a sample of influenza genome sequences over 39 years. Our results imply that mode and speed of influenza evolution are governed not only by positive selection within, but also by background selection outside antigenic epitopes: immune adaptation and conservation of other viral functions interfere with each other. Hence, adapting viral proteins are predicted to be particularly brittle. We conclude that a quantitative understanding of influenza’s evolutionary and epidemiological dynamics must be based on all genomic domains and functions coupled by clonal interference.

Harnessing recombination to speed adaptive evolution in Escherichia coli

Evolutionary engineering typically involves asexual propagation of a strain to improve a desired phenotype. However, asexual populations suffer from extensive clonal interference, a phenomenon where distinct lineages of beneficial clones compete and are often lost from the population given sufficient time. Improved adaptive mutants can likely be generated by genetic exchange between lineages, thereby reducing clonal interference. We present a system that allows continuous in situ recombination by using an Esherichia coli F-based conjugation system lacking surface exclusion. Evolution experiments revealed that Hfr-mediated recombination significantly speeds adaptation in certain circumstances. These results show that our system is stable, effective, and suitable for use in evolutionary engineering applications.

The Role of Clonal Interference in the Evolutionary Dynamics of Plasmid-Host Adaptation

ABSTRACTPromiscuous plasmids replicate in a wide range of bacteria and therefore play a key role in the dissemination of various host-beneficial traits, including antibiotic resistance. Despite the medical relevance, little is known about the evolutionary dynamics through which drug resistance plasmids adapt to new hosts and thereby persist in the absence of antibiotics. We previously showed that the incompatibility group P-1 (IncP-1) minireplicon pMS0506 drastically improved its stability in novel host Shewanella oneidensis MR-1 after 1,000 generations under antibiotic selection for the plasmid. The only mutations found were those affecting the N terminus of the plasmid replication initiation protein TrfA1. Our aim in this study was to gain insight into the dynamics of plasmid evolution. Changes in stability and genotype frequencies of pMS0506 were monitored in evolving populations of MR-1 (pMS0506). Genotypes were determined by sequencing trfA1 amplicons from individual clones and by 454 pyrosequencing of whole plasmids from entire populations. Stability of pMS0506 drastically improved by generation 200. Many evolved plasmid genotypes with point mutations as well as in-frame and frameshift deletions and duplications in trfA1 were observed in all lineages with both sequencing methods. Strikingly, multiple genotypes were simultaneously present at high frequencies (>10%) in each population. Their relative abundances changed over time, but after 1,000 generations only one or two genotypes dominated the populations. This suggests that hosts with different plasmid genotypes were competing with each other, thus affecting the evolutionary trajectory. Plasmids can thus rapidly improve their stability, and clonal interference plays a significant role in plasmid-host adaptation dynamics.

Hepatitis C quasispecies adaptation in the setting of a variable fidelity polymerase

Hepatitis C quasispecies adaptation in the setting of a variable fidelity polymerase Daniel Schmidt-Martin,1 Orla Crosbie,2 Elizabeth Kenny-Walsh,2 Liam J Fanning11Molecular Virology Diagnostic and Research Laboratory, Department of Medicine, University College Cork, Clinical Sciences Building, Cork University Hospital, 2Department of Gastroenterology and Hepatology, Cork, IrelandAbstract: Hepatitis C (HCV) is a virus characterized by an RNA-dependent RNA polymerase that lacks a proofreading mechanism and, as a result, generates a quasispecies. There is emerging evidence that this RNA-dependent RNA polymerase may in fact have variable fidelity. Here, we review the relevant concepts, including fitness landscapes, clonal interference, robustness, selection, adaptation, mutation rates, and their optimization, and provide a unique interpretation of a number of relevant theoretical models, evolving the theory of replicative homeostasis in light of their findings. We suggest that a variable fidelity polymerase can find its own optimal mutation rate, which is governed by the sequence itself and certain population dynamics. We propose that this concept can explain features of viral kinetics and clearance, both spontaneously and following treatment of chronic HCV. We point to evidence that supports this theory and explain how it refines replicative homeostasis and conclude by discussing particular areas of potential research that might augment our understanding of viral host interactions at an individual cellular level.Keywords: fitness landscapes, adaptation, evolution, quasispecies, hepatitis C, replicative homeostasis

Experimental Evolution of Legionella pneumophila in Mouse Macrophages Leads to Strains with Altered Determinants of Environmental Survival

The Gram-negative bacterium, Legionella pneumophila, is a protozoan parasite and accidental intracellular pathogen of humans. We propose a model in which cycling through multiple protozoan hosts in the environment holds L. pneumophila in a state of evolutionary stasis as a broad host-range pathogen. Using an experimental evolution approach, we tested this hypothesis by restricting L. pneumophila to growth within mouse macrophages for hundreds of generations. Whole-genome resequencing and high-throughput genotyping identified several parallel adaptive mutations and population dynamics that led to improved replication within macrophages. Based on these results, we provide a detailed view of the population dynamics of an experimentally evolving bacterial population, punctuated by frequent instances of transient clonal interference and selective sweeps. Non-synonymous point mutations in the flagellar regulator, fleN, resulted in increased uptake and broadly increased replication in both macrophages and amoebae. Mutations in multiple steps of the lysine biosynthesis pathway were also independently isolated, resulting in lysine auxotrophy and reduced replication in amoebae. These results demonstrate that under laboratory conditions, host restriction is sufficient to rapidly modify L. pneumophila fitness and host range. We hypothesize that, in the environment, host cycling prevents L. pneumophila host-specialization by maintaining pathways that are deleterious for growth in macrophages and other hosts.