Microbial Experimental Evolution Research Articles

Identifying Signatures of Selection in Genetic Time Series

Both genetic drift and natural selection cause the frequencies of alleles in a population to vary over time. Discriminating between these two evolutionary forces, based on a time series of samples from a population, remains an outstanding problem with increasing relevance to modern data sets. Even in the idealized situation when the sampled locus is independent of all other loci, this problem is difficult to solve, especially when the size of the population from which the samples are drawn is unknown. A standard χ(2)-based likelihood-ratio test was previously proposed to address this problem. Here we show that the χ(2)-test of selection substantially underestimates the probability of type I error, leading to more false positives than indicated by its P-value, especially at stringent P-values. We introduce two methods to correct this bias. The empirical likelihood-ratio test (ELRT) rejects neutrality when the likelihood-ratio statistic falls in the tail of the empirical distribution obtained under the most likely neutral population size. The frequency increment test (FIT) rejects neutrality if the distribution of normalized allele-frequency increments exhibits a mean that deviates significantly from zero. We characterize the statistical power of these two tests for selection, and we apply them to three experimental data sets. We demonstrate that both ELRT and FIT have power to detect selection in practical parameter regimes, such as those encountered in microbial evolution experiments. Our analysis applies to a single diallelic locus, assumed independent of all other loci, which is most relevant to full-genome selection scans in sexual organisms, and also to evolution experiments in asexual organisms as long as clonal interference is weak. Different techniques will be required to detect selection in time series of cosegregating linked loci.

Identifying structural variation in haploid microbial genomes from short-read resequencing data using breseq.

BackgroundMutations that alter chromosomal structure play critical roles in evolution and disease, including in the origin of new lifestyles and pathogenic traits in microbes. Large-scale rearrangements in genomes are often mediated by recombination events involving new or existing copies of mobile genetic elements, recently duplicated genes, or other repetitive sequences. Most current software programs for predicting structural variation from short-read DNA resequencing data are intended primarily for use on human genomes. They typically disregard information in reads mapping to repeat sequences, and significant post-processing and manual examination of their output is often required to rule out false-positive predictions and precisely describe mutational events.ResultsWe have implemented an algorithm for identifying structural variation from DNA resequencing data as part of the breseq computational pipeline for predicting mutations in haploid microbial genomes. Our method evaluates the support for new sequence junctions present in a clonal sample from split-read alignments to a reference genome, including matches to repeat sequences. Then, it uses a statistical model of read coverage evenness to accept or reject these predictions. Finally, breseq combines predictions of new junctions and deleted chromosomal regions to output biologically relevant descriptions of mutations and their effects on genes. We demonstrate the performance of breseq on simulated Escherichia coli genomes with deletions generating unique breakpoint sequences, new insertions of mobile genetic elements, and deletions mediated by mobile elements. Then, we reanalyze data from an E. coli K-12 mutation accumulation evolution experiment in which structural variation was not previously identified. Transposon insertions and large-scale chromosomal changes detected by breseq account for ~25% of spontaneous mutations in this strain. In all cases, we find that breseq is able to reliably predict structural variation with modest read-depth coverage of the reference genome (>40-fold).ConclusionsUsing breseq to predict structural variation should be useful for studies of microbial epidemiology, experimental evolution, synthetic biology, and genetics when a reference genome for a closely related strain is available. In these cases, breseq can discover mutations that may be responsible for important or unintended changes in genomes that might otherwise go undetected.Electronic supplementary materialThe online version of this article (doi:10.1186/1471-2164-15-1039) contains supplementary material, which is available to authorized users.

NEW MODEL SYSTEMS FOR EXPERIMENTAL EVOLUTION

Microbial experimental evolution uses a few well-characterized model systems to answer fundamental questions about how evolution works. This special section highlights novel model systems for experimental evolution, with a focus on marine model systems that can be used to understand evolutionary responses to global change in the oceans.

Evolution in Microbes

This review presents a broad survey of experimental microbial evolution, covering diverse topics including trade-offs, epistasis, fluctuating conditions, spatial dynamics, cooperation, aging, and stochastic switching. Emphasis is placed on examples that highlight key conceptual points or address theoretical predictions. Experimental evolution is discussed from two points of view. First, population trajectories are described as adaptive walks on a fitness landscape, whose genetic structure can be probed by experiments. Second, populations are viewed from a physiological perspective, and their nongenetic heterogeneity is examined. Bringing together these two viewpoints remains a major challenge for the future.

Intra-tumor heterogeneity: lessons from microbial evolution and clinical implications

Multiple subclonal populations of tumor cells can coexist within the same tumor. This intra-tumor heterogeneity will have clinical implications and it is therefore important to identify factors that drive or suppress such heterogeneous tumor progression. Evolutionary biology can provide important insights into this process. In particular, experimental evolution studies of microbial populations, which exist as clonal populations that can diversify into multiple subclones, have revealed important evolutionary processes driving heterogeneity within a population. There are transferrable lessons that can be learnt from these studies that will help us to understand the process of intra-tumor heterogeneity in the clinical setting. In this review, we summarize drivers of microbial diversity that have been identified, such as mutation rate and environmental influences, and discuss how knowledge gained from microbial experimental evolution studies may guide us to identify and understand important selective factors that promote intra-tumor heterogeneity. Furthermore, we discuss how these factors could be used to direct and optimize research efforts to improve patient care, focusing on therapeutic resistance. Finally, we emphasize the need for longitudinal studies to address the impact of these potential tumor heterogeneity-promoting factors on drug resistance, metastatic potential and clinical outcome.

FUNCTIONAL GENETIC DIVERGENCE IN HIGH CO2ADAPTEDEMILIANIA HUXLEYIPOPULATIONS

Predicting the impacts of environmental change on marine organisms, food webs, and biogeochemical cycles presently relies almost exclusively on short-term physiological studies, while the possibility of adaptive evolution is often ignored. Here, we assess adaptive evolution in the coccolithophore Emiliania huxleyi, a well-established model species in biological oceanography, in response to ocean acidification. We previously demonstrated that this globally important marine phytoplankton species adapts within 500 generations to elevated CO2 . After 750 and 1000 generations, no further fitness increase occurred, and we observed phenotypic convergence between replicate populations. We then exposed adapted populations to two novel environments to investigate whether or not the underlying basis for high CO2 -adaptation involves functional genetic divergence, assuming that different novel mutations become apparent via divergent pleiotropic effects. The novel environment "high light" did not reveal such genetic divergence whereas growth in a low-salinity environment revealed strong pleiotropic effects in high CO2 adapted populations, indicating divergent genetic bases for adaptation to high CO2 . This suggests that pleiotropy plays an important role in adaptation of natural E. huxleyi populations to ocean acidification. Our study highlights the potential mutual benefits for oceanography and evolutionary biology of using ecologically important marine phytoplankton for microbial evolution experiments.

Cancer in light of experimental evolution.

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

Evolutionary perspectives in a mutualism of sepiolid squid and bioluminescent bacteria: combined usage of microbial experimental evolution and temporal population genetics.

The symbiosis between marine bioluminescent Vibrio bacteria and the sepiolid squid Euprymna is a model for studying animal-bacterial Interactions. Vibrio symbionts native to particular Euprymna species are competitively dominant, capable of outcompeting foreign Vibrio strains from other Euprymna host species. Despite competitive dominance, secondary colonization events by invading nonnative Vibrio fischeri have occurred. Competitive dominance can be offset through superior nonnative numbers and advantage of early start host colonization by nonnatives, granting nonnative vibrios an opportunity to establish beachheads in foreign Euprymna hosts. Here, we show that nonnative V. fischeri are capable of rapid adaptation to novel sepiolid squid hosts by serially passaging V. fischeri JRM200 (native to Hawaiian Euprymna scolopes) lines through the novel Australian squid host E. tasmanica for 500 generations. These experiments were complemented by a temporal population genetics survey of V. fischeri, collected from E. tasmanica over a decade, which provided a perspective from the natural history of V. fischeri evolution over 15,000-20,000 generations in E. tasmanica. No symbiont anagenic evolution within squids was observed, as competitive dominance does not purge V. fischeri genetic diversity through time. Instead, abiotic factors affecting abundance of V. fischeri variants in the planktonic phase sustain temporal symbiont diversity, a property itself of ecological constraints imposed by V. fischeri host adaptation.

Systems-biology approaches for predicting genomic evolution

Is evolution predictable at the molecular level? The ambitious goal to answer this question requires an understanding of the mutational effects that govern the complex relationship between genotype and phenotype. In practice, it involves integrating systems-biology modelling, microbial laboratory evolution experiments and large-scale mutational analyses - a feat that is made possible by the recent availability of the necessary computational tools and experimental techniques. This Review investigates recent progresses in mapping evolutionary trajectories and discusses the degree to which these predictions are realistic.

Many Possible Worlds: Expanding the Ecological Scenarios in Experimental Evolution

Experimental microbial evolution has focused on the particular ecological scenario where a population is placed suddenly in an environment where its fitness is low, and then adapts while the environment remains stable. In line with this, most microbial evolution studies use fitness measures that report how evolved genotypes fare when competed directly against their own distant ancestor while other studies compare life history traits (such as growth rates) of ancestral and evolved genotypes. This standard way of measuring and reporting changes in fitness has resulted in a consistent body of literature that explains adaptation when populations evolve in this “standard ecological scenario.” Here, I suggest that for experimental evolution to investigate adaptation in other ecological scenarios, such as fluctuating or persistently changing environments, measures of fitness must be expanded such that they not only continue to be comparable between experiments, but also account for evolution and demographic effects in all environments that an evolving lineage experiences. I examine two non-standard measures of fitness—fitness flux and the total number of reproductive events—as potential ways to quantify adaptation by integrating historical information about selection over many environments. This approach could allow us to make quantitative and biologically-meaningful comparisons of adaptation across diverse ecological scenarios. I use the case study of understanding how phytoplankton communities may respond to global change, where environmental variables change continuously, to explore concrete ways of using non-standard fitness measures that consider both demographic effects and selection in changing, rather than in changed, environments.

Competition limits adaptation and productivity in a photosynthetic alga at elevated CO 2

When competitive exclusion between lineages and genetic adaptation within lineages occur on the same timescale, the two processes have the potential to interact. I use experimental microbial evolution where strains of a photosynthetic microbe that differ in their physiological response to CO2 enrichment are grown either alone or in communities for hundreds of generations under CO2 enrichment. After about 300 generations of growth, strains that experienced competition while adapting to environmental change are both less productive and less fit than corresponding strains that adapted to that same environmental change in the absence of competitors. In addition, I find that excluding competitors not only limits that strain's adaptive response to abiotic change, but also decreases community productivity; I quantify this effect using the Price equation. Finally, these data allow me to empirically test the common hypothesis that phytoplankton that are most able to take advantage of carbon enrichment in single-strain populations over the short term will increase in frequency within multi-strain communities over longer timescales.

Comment on ''Effects of long-term high CO<sub>2</sub> exposure on two species of coccolithophore'' by Müller et al. (2010)

Abstract. Populations can respond to environmental change over tens or hundreds of generations by shifts in phenotype that can be the result of a sustained physiological response, evolutionary (genetic) change, shifts in community composition, or some combination of these factors. Microbes evolve on human timescales, and evolution may contribute to marine phytoplankton responses to global change over the coming decades. However, it is still unknown whether evolutionary responses are likely to contribute significantly to phenotypic change in marine microbial communities under high pCO2 regimes or other aspects of global change. Recent work by Müller et al. (2010) highlights that long-term responses of marine microbes to global change must be empirically measured and the underlying cause of changes in phenotype explained. Here, I briefly discuss how tools from experimental microbial evolution may be used to detect and measure evolutionary responses in marine phytoplankton grown in high CO2 environments and other environments of interest. I outline why the particular biology of marine microbes makes conventional experimental evolution challenging right now and make a case that marine microbes are good candidates for the development of new model systems in experimental evolution. I suggest that "black box" frameworks that focus on partitioning phenotypic change, such as the Price equation, may be useful in cases where direct measurements of evolutionary responses alone are difficult, and that such approaches could be used to test hypotheses about the underlying causes of phenotypic shifts in marine microbe communities responding to global change.

Toward a General Theory of Adaptive Radiation

The history of life has been punctuated by unusually spectacular periods of evolutionary diversification called adaptive radiation. Darwin's finches in the Galapagos, cichlid fishes in African Rift and Nicaraguan crater lakes, and the emergence of mammals at the end of the Cretaceous are hallmark examples. Although we have learned much from these and other case studies about the mechanisms thought to drive adaptive radiations, convincing experimental tests of theory are often lacking for the simple reason that it is usually impossible to "rewind the tape of life," as Stephen Jay Gould was fond of saying, and run it again. This situation has changed dramatically in recent years with the increasing emphasis on the use of microbial populations which, because of their small size and rapid generation times, make possible the construction of replicated, manipulative experiments to study evolution in the laboratory. Here I review the contributions that microbial experimental evolution has made to our understanding of the ecological and genetic mechanisms underlying adaptive radiation. I focus on three major gaps in the theory of adaptive radiation--the paucity of direct tests of mechanism, the genetics of diversification, and the limits and constraints on the progress of radiations--with the aim of pointing the way toward the development of a more general theory of adaptive radiation.

Genome-wide Mutational Diversity in an Evolving Population of Escherichia coli

The level of genetic variation in a population is the result of a dynamic tension between evolutionary forces. Mutations create variation, certain frequency-dependent interactions may preserve diversity, and natural selection purges variation. New sequencing technologies offer unprecedented opportunities to discover and characterize the diversity present in evolving microbial populations on a whole-genome scale. By sequencing mixed-population samples, we have identified single-nucleotide polymorphisms (SNPs) present at various points in the history of an Escherichia coli population that has evolved for almost 20 years from a founding clone. With 50-fold genome coverage, we were able to catch beneficial mutations as they swept to fixation, discover contending beneficial alleles that were eliminated by clonal interference, and detect other minor variants possibly adapted to a new ecological niche. Additionally, there was a dramatic increase in genetic diversity late in the experiment after a mutator phenotype evolved. Still finer-resolution details of the structure of genetic variation and how it changes over time in microbial evolution experiments will enable new applications and quantitative tests of population genetic theory.

Adaptation in Sexuals vs. Asexuals: Clonal Interference and the Fisher-Muller Model

Fisher and Muller's theory that recombination speeds adaptation by eliminating competition among beneficial mutations has proved a popular explanation for the advantage of sex. Recent theoretical studies have attempted to quantify the speed of adaptation under the Fisher-Muller model, partly in an attempt to understand the role of "clonal interference" in microbial experimental evolution. We reexamine adaptation in sexuals vs. asexuals, using a model of DNA sequence evolution. In this model, a modest number of sites can mutate to beneficial alleles and the fitness effects of these mutations are unequal. We study (1) transition probabilities to different beneficial mutations; (2) waiting times to the first and the last substitutions of beneficial mutations; and (3) trajectories of mean fitness through time. We find that some of these statistics are surprisingly similar between sexuals and asexuals. These results highlight the importance of the choice of substitution model in assessing the Fisher-Muller advantage of sex.

SIZE DOESN'T MATTER: MICROBIAL SELECTION EXPERIMENTS ADDRESS ECOLOGICAL PHENOMENA

Experimental evolution is relevant to ecology because it can connect physiology, and in particular metabolism, to questions in ecology. The investigation of the linkage between the environment and the evolution of metabolism is tractable because these experiments manipulate a very simple environment to produce predictable evolutionary outcomes. In doing so, microbial selection experiments can examine the causal elements of natural selection: how specific traits in varying environments will yield different fitnesses. Here, we review the methodology of microbial evolution experiments and address three issues that are relevant to ecologists: genotype-by-environment interactions, ecological diversification due to specialization, and negative frequency-dependent selection. First, we expect that genotype-by-environment interactions will be ubiquitous in biological systems. Second, while antagonistic pleiotropy is implicated in some cases of ecological specialization, other mechanisms also seem to be at work. Third, while negative frequency-dependent selection can maintain ecological diversity in laboratory systems, a mechanistic (biochemical) analysis of these systems suggests that negative frequency dependence may only apply within a narrow range of environments if resources are substitutable. Finally, we conclude that microbial experimental evolution needs to avail itself of molecular techniques that could enable a mechanistic understanding of ecological diversification in these simple systems.

POPULATION GENETICS AND EVOLUTION

These lecture notes introduce key concepts of mathematical population genetics within the most elementary setting and describe a few recent applications to microbial evolution experiments. Pointers to the literature for further reading are provided, and some of the derivations are left as exercises for the reader.