Genome dynamics during experimental evolution

Directed evolution of Escherichia coli with lower-than-natural plasmid mutation rates

Unwanted evolution of designed DNA sequences limits metabolic and genome engineering efforts. Engineered functions that are burdensome to host cells and slow their replication are rapidly inactivated by mutations, and unplanned mutations with unpredictable effects often accumulate alongside designed changes in large-scale genome editing projects. We developed a directed evolution strategy, Periodic Reselection for Evolutionarily Reliable Variants (PResERV), to discover mutations that prolong the function of a burdensome DNA sequence in an engineered organism. Here, we used PResERV to isolate Escherichia coli cells that replicate ColE1-type plasmids with higher fidelity. We found mutations in DNA polymerase I and in RNase E that reduce plasmid mutation rates by 6- to 30-fold. The PResERV method implicitly selects to maintain the growth rate of host cells, and high plasmid copy numbers and gene expression levels are maintained in some of the evolved E. coli strains, indicating that it is possible to improve the genetic stability of cellular chassis without encountering trade-offs in other desirable performance characteristics. Utilizing these new antimutator E. coli and applying PResERV to other organisms in the future promises to prevent evolutionary failures and unpredictability to provide a more stable genetic foundation for synthetic biology.

Experimental Design, Population Dynamics, and Diversity in Microbial Experimental Evolution

In experimental evolution, laboratory-controlled conditions select for the adaptation of species, which can be monitored in real time. Despite the current popularity of such experiments, nature's most pervasive biological force was long believed to be observable only on time scales that transcend a researcher's life-span, and studying evolution by natural selection was therefore carried out solely by comparative means. Eventually, microorganisms' propensity for fast evolutionary changes proved us wrong, displaying strong evolutionary adaptations over a limited time, nowadays massively exploited in laboratory evolution experiments. Here, we formulate a guide to experimental evolution with microorganisms, explaining experimental design and discussing evolutionary dynamics and outcomes and how it is used to assess ecoevolutionary theories, improve industrially important traits, and untangle complex phenotypes. Specifically, we give a comprehensive overview of the setups used in experimental evolution. Additionally, we address population dynamics and genetic or phenotypic diversity during evolution experiments and expand upon contributing factors, such as epistasis and the consequences of (a)sexual reproduction. Dynamics and outcomes of evolution are most profoundly affected by the spatiotemporal nature of the selective environment, where changing environments might lead to generalists and structured environments could foster diversity, aided by, for example, clonal interference and negative frequency-dependent selection. We conclude with future perspectives, with an emphasis on possibilities offered by fast-paced technological progress. This work is meant to serve as an introduction to those new to the field of experimental evolution, as a guide to the budding experimentalist, and as a reference work to the seasoned expert.

Unstable Allotetraploid Tobacco Genome due to Frequent Homeologous Recombination, Segmental Deletion, and Chromosome Loss

The types of mutations and their corresponding frequencies are difficult to measure in complex genomes. In this study, a high-throughput method was developed to identify spontaneous loss-of-function alleles for the resistance gene N and the transgenic avirulence gene P50 in allotetraploid tobacco. A total of 2134 loss-of-function alleles of the N gene were identified after screening 14 million F1 hybrids. Analysis of these mutants revealed striking evolutionary patterns for genes in polyploids. Only 14 of the loss-of-function mutations were caused by spontaneous point mutations or indels, while the others were caused by homeologous recombination (with a frequency of ∼1/12 000) or chromosome loss (∼1/15 000). Loss of the chromosome with the P50 insertion occurred at a similar frequency (∼1/13 000), and the frequency of spontaneous segmental deletion in this chromosome was ∼1/16 000. Both homeologous recombination and chromosome loss considerably decreased the viability of the mutants. Our data suggest that the high mutation rate in polyploids is probably due to the occurrence of homeologous recombination and the tolerance of large mutations such as chromosome loss in polyploid genomes. Frequent mutations tend to drive polyploids to extinction unless a novel mutation helps the polyploid to effectively compete with diploids or find a new ecological niche.

Clonal Heterogeneity Influences the Fate of New Adaptive Mutations

The joint contribution of pre-existing and de novo genetic variation to clonal adaptation is poorly understood but essential to designing successful antimicrobial or cancer therapies. To address this, we evolve genetically diverse populations of budding yeast, S. cerevisiae, consisting of diploid cells with unique haplotype combinations. We study the asexual evolution of these populations under selective inhibition with chemotherapeutic drugs by time-resolved whole-genome sequencing and phenotyping. All populations undergo clonal expansions driven by de novo mutations but remain genetically and phenotypically diverse. The clones exhibit widespread genomic instability, rendering recessive de novo mutations homozygous and refining pre-existing variation. Finally, we decompose the fitness contributions of pre-existing and de novo mutations by creating a large recombinant library of adaptive mutations in an ensemble of genetic backgrounds. Both pre-existing and de novo mutations substantially contribute to fitness, and the relative fitness of pre-existing variants sets a selective threshold for new adaptive mutations.

Parallels between experimental and natural evolution of legume symbionts

The emergence of symbiotic interactions has been studied using population genomics in nature and experimental evolution in the laboratory, but the parallels between these processes remain unknown. Here we compare the emergence of rhizobia after the horizontal transfer of a symbiotic plasmid in natural populations of Cupriavidus taiwanensis, over 10 MY ago, with the experimental evolution of symbiotic Ralstonia solanacearum for a few hundred generations. In spite of major differences in terms of time span, environment, genetic background, and phenotypic achievement, both processes resulted in rapid genetic diversification dominated by purifying selection. We observe no adaptation in the plasmid carrying the genes responsible for the ecological transition. Instead, adaptation was associated with positive selection in a set of genes that led to the co-option of the same quorum-sensing system in both processes. Our results provide evidence for similarities in experimental and natural evolutionary transitions and highlight the potential of comparisons between both processes to understand symbiogenesis.

It is unclear if experimental evolution is a good model for natural processes. Here, Clerissi et al. find parallels between the evolution of symbiosis in rhizobia after horizontal transfer of a plasmid over 10 million years ago and experimentally evolved symbionts.

The Experimental Study of Bacterial Evolution and Its Implications for the Modern Synthesis of Evolutionary Biology

Since the 1940s, microbiologists, biochemists and population geneticists have experimented with the genetic mechanisms of microorganisms in order to investigate evolutionary processes. These evolutionary studies of bacteria and other microorganisms gained some recognition from the standard-bearers of the modern synthesis of evolutionary biology, especially Theodosius Dobzhansky and Ledyard Stebbins. A further period of post-synthesis bacterial evolutionary research occurred between the 1950s and 1980s. These experimental analyses focused on the evolution of population and genetic structure, the adaptive gain of new functions, and the evolutionary consequences of competition dynamics. This large body of research aimed to make evolutionary theory testable and predictive, by giving it mechanistic underpinnings. Although evolutionary microbiologists promoted bacterial experiments as methodologically advantageous and a source of general insight into evolution, they also acknowledged the biological differences of bacteria. My historical overview concludes with reflections on what bacterial evolutionary research achieved in this period, and its implications for the still-developing modern synthesis.

Keeping it together: absence of genetic variation and DNA incorporation by the predatory bacteria Micavibrio aeruginosavorus and Bdellovibrio bacteriovorus during predation

The use of predatory bacteria as a potential live therapeutic to control human infection is gaining increased attention. Earlier work with Micavibrio spp. and Bdellovibrio spp. has demonstrated the ability of these predators to control drug-resistant Gram-negative pathogens, Tier-1 select agents and biofilms. Additional studies also confirmed that introducing high doses of the predators into animals does not negatively impact animal well-being and might assist in reducing bacterial burden in vivo. The survival of predators requires extreme proximity to the prey cell, which might bring about horizontal transfer of genetic material, such as genes encoding for pathogenic genetic islands that would indirectly facilitate the spread of genetic material to other organisms. In this study, we examined the genetic makeup of several lab isolates of the predators Bdellovibriobacteriovorus and Micavibrioaeruginosavorus that were cultured repeatedly and stored over a course of 13 years. We also conducted controlled experiments in which the predators were sequentially co-cultured on Klebsiella pneumoniae followed by genetic analysis of the predator. In both cases, we saw little genetic variation and no evidence of horizontally transferred chromosomal DNA from the prey during predator-prey interaction. Culturing the predators repeatedly did not cause any change in predation efficacy.

Machine learning identifies signatures of host adaptation in the bacterial pathogen Salmonella enterica

Emerging pathogens are a major threat to public health, however understanding how pathogens adapt to new niches remains a challenge. New methods are urgently required to provide functional insights into pathogens from the massive genomic data sets now being generated from routine pathogen surveillance for epidemiological purposes. Here, we measure the burden of atypical mutations in protein coding genes across independently evolved Salmonella enterica lineages, and use these as input to train a random forest classifier to identify strains associated with extraintestinal disease. Members of the species fall along a continuum, from pathovars which cause gastrointestinal infection and low mortality, associated with a broad host-range, to those that cause invasive infection and high mortality, associated with a narrowed host range. Our random forest classifier learned to perfectly discriminate long-established gastrointestinal and invasive serovars of Salmonella. Additionally, it was able to discriminate recently emerged Salmonella Enteritidis and Typhimurium lineages associated with invasive disease in immunocompromised populations in sub-Saharan Africa, and within-host adaptation to invasive infection. We dissect the architecture of the model to identify the genes that were most informative of phenotype, revealing a common theme of degradation of metabolic pathways in extraintestinal lineages. This approach accurately identifies patterns of gene degradation and diversifying selection specific to invasive serovars that have been captured by more labour-intensive investigations, but can be readily scaled to larger analyses.

Testing the Role of Multicopy Plasmids in the Evolution of Antibiotic Resistance

Multicopy plasmids are extremely abundant in prokaryotes but their role in bacterial evolution remains poorly understood. We recently showed that the increase in gene copy number per cell provided by multicopy plasmids could accelerate the evolution of plasmid-encoded genes. In this work, we present an experimental system to test the ability of multicopy plasmids to promote gene evolution. Using simple molecular biology methods, we constructed a model system where an antibiotic resistance gene can be inserted into Escherichia coli MG1655, either in the chromosome or on a multicopy plasmid. We use an experimental evolution approach to propagate the different strains under increasing concentrations of antibiotics and we measure survival of bacterial populations over time. The choice of the antibiotic molecule and the resistance gene is so that the gene can only confer resistance through the acquisition of mutations. This "evolutionary rescue" approach provides a simple method to test the potential of multicopy plasmids to promote the acquisition of antibiotic resistance. In the next step of the experimental system, the molecular bases of antibiotic resistance are characterized. To identify mutations responsible for the acquisition of antibiotic resistance we use deep DNA sequencing of samples obtained from whole populations and clones. Finally, to confirm the role of the mutations in the gene under study, we reconstruct them in the parental background and test the resistance phenotype of the resulting strains.

Differential strengths of molecular determinants guide environment specific mutational fates

Organisms maintain competitive fitness in the face of environmental challenges through molecular evolution. However, it remains largely unknown how different biophysical factors constrain molecular evolution in a given environment. Here, using deep mutational scanning, we quantified empirical fitness of >2000 single site mutants of the Gentamicin-resistant gene (GmR) in Escherichia coli, in a representative set of physical (non-native temperatures) and chemical (small molecule supplements) environments. From this, we could infer how different biophysical parameters of the mutations constrain molecular function in different environments. We find ligand binding, and protein stability to be the best predictors of mutants' fitness, but their relative predictive power differs across environments. While protein folding emerges as the strongest predictor at minimal antibiotic concentration, ligand binding becomes a stronger predictor of mutant fitness at higher concentration. Remarkably, strengths of environment-specific selection pressures were largely predictable from the degree of mutational perturbation of protein folding and ligand binding. By identifying structural constraints that act as determinants of fitness, our study thus provides coarse mechanistic insights into the environment specific accessibility of mutational fates.

Fundamental principles in bacterial physiology-history, recent progress, and the future with focus on cell size control: a review

Bacterial physiology is a branch of biology that aims to understand overarching principles of cellular reproduction. Many important issues in bacterial physiology are inherently quantitative, and major contributors to the field have often brought together tools and ways of thinking from multiple disciplines. This article presents a comprehensive overview of major ideas and approaches developed since the early 20th century for anyone who is interested in the fundamental problems in bacterial physiology. This article is divided into two parts. In the first part (sections 1-3), we review the first 'golden era' of bacterial physiology from the 1940s to early 1970s and provide a complete list of major references from that period. In the second part (sections 4-7), we explain how the pioneering work from the first golden era has influenced various rediscoveries of general quantitative principles and significant further development in modern bacterial physiology. Specifically, section 4 presents the history and current progress of the 'adder' principle of cell size homeostasis. Section 5 discusses the implications of coarse-graining the cellular protein composition, and how the coarse-grained proteome 'sectors' re-balance under different growth conditions. Section 6 focuses on physiological invariants, and explains how they are the key to understanding the coordination between growth and the cell cycle underlying cell size control in steady-state growth. Section 7 overviews how the temporal organization of all the internal processes enables balanced growth. In the final section 8, we conclude by discussing the remaining challenges for the future in the field.

Population size changes and selection drive patterns of parallel evolution in a host-virus system

Predicting the repeatability of evolution remains elusive. Theory and empirical studies suggest that strong selection and large population sizes increase the probability for parallel evolution at the phenotypic and genotypic levels. However, selection and population sizes are not constant, but rather change continuously and directly affect each other even on short time scales. Here, we examine the degree of parallel evolution shaped through eco-evolutionary dynamics in an algal host population coevolving with a virus. We find high degrees of parallelism at the level of population size changes (ecology) and at the phenotypic level between replicated populations. At the genomic level, we find evidence for parallelism, as the same large genomic region was duplicated in all replicated populations, but also substantial novel sequence divergence between replicates. These patterns of genome evolution can be explained by considering population size changes as an important driver of rapid evolution.

Innovation in an E. coli evolution experiment is contingent on maintaining adaptive potential until competition subsides

Key innovations are disruptive evolutionary events that enable a species to escape constraints and rapidly diversify. After 15 years of the Lenski long-term evolution experiment with Escherichia coli, cells in one of the twelve populations evolved the ability to utilize citrate, an abundant but previously untapped carbon source in the environment. Descendants of these cells became dominant in the population and subsequently diversified as a consequence of invading this vacant niche. Mutations responsible for the appearance of rudimentary citrate utilization and for refining this ability have been characterized. However, the complete nature of the genetic and/or ecological events that set the stage for this key innovation is unknown. In particular, it is unclear why it took so long for citrate utilization to evolve and why it still has evolved in only one of the twelve E. coli populations after 30 years of the Lenski experiment. In this study, we recapitulated the initial mutation needed to evolve citrate utilization in strains isolated from throughout the first 31,500 generations of the history of this population. We found that there was already a slight fitness benefit for this mutation in the original ancestor of the evolution experiment and in other early isolates. However, evolution of citrate utilization was blocked at this point due to competition with other mutations that improved fitness in the original niche. Subsequently, an anti-potentiated genetic background evolved in which it was deleterious to evolve rudimentary citrate utilization. Only later, after further mutations accumulated that restored the benefit of this first-step mutation and the overall rate of adaptation in the population slowed, was citrate utilization likely to evolve. Thus, intense competition and the types of mutations that it favors can lead to short-sighted evolutionary trajectories that hide a stepping stone needed to access a key innovation from many future generations.

Experimental evolution of diverse Escherichia coli metabolic mutants identifies genetic loci for convergent adaptation of growth rate

Cell growth is determined by substrate availability and the cell’s metabolic capacity to assimilate substrates into building blocks. Metabolic genes that determine growth rate may interact synergistically or antagonistically, and can accelerate or slow growth, depending on genetic background and environmental conditions. We evolved a diverse set of Escherichia coli single-gene deletion mutants with a spectrum of growth rates and identified mutations that generally increase growth rate. Despite the metabolic differences between parent strains, mutations that enhanced growth largely mapped to core transcription machinery, including the β and β’ subunits of RNA polymerase (RNAP) and the transcription elongation factor, NusA. The structural segments of RNAP that determine enhanced growth have been previously implicated in antibiotic resistance and in the control of transcription elongation and pausing. We further developed a computational framework to characterize how the transcriptional changes that occur upon acquisition of these mutations affect growth rate across strains. Our experimental and computational results provide evidence for cases in which RNAP mutations shift the competitive balance between active transcription and gene silencing. This study demonstrates that mutations in specific regions of RNAP are a convergent adaptive solution that can enhance the growth rate of cells from distinct metabolic states.

The loss of a metabolic function caused by gene deletion can be compensated, in certain cases, by the concurrent mutation of a second gene. Whether such gene pairs share a local chemical or regulatory relationship or interact via a non-local mechanism has implications for the co-evolution of genetic changes, development of alternatives to gene therapy, and the design of combination antimicrobial therapies that select against resistance. Yet, we lack a comprehensive knowledge of adaptive responses to metabolic mutations, and our understanding of the mechanisms underlying genetic rescue remains limited. We present results of a laboratory evolution approach that has the potential to address both challenges, showing that mutations in specific regions of RNA polymerase enhance growth rates of distinct mutant strains of Escherichia coli with a spectrum of growth defects. Several of these adaptive mutations are deleterious when engineered directly into the original wild-type strain under alternative cultivation conditions, and thus have epistatic rescue properties when paired with the corresponding primary metabolic gene deletions. Our combination of adaptive evolution, directed genetic engineering, and mathematical analysis of transcription and growth rate distinguishes between rescue interactions that are specific or non-specific to a particular deletion. Our study further supports a model for RNA polymerase as a locus of convergent adaptive evolution from different sub-optimal metabolic starting points.

Laboratory evolution reveals regulatory and metabolic trade-offs of glycerol utilization in Saccharomyces cerevisiae

Most microbial species, including model eukaryote Saccharomyces cerevisiae, possess genetic capability to utilize many alternative nutrient sources. Yet, it remains an open question whether these manifest into assimilatory phenotypes. Despite possessing all necessary pathways, S. cerevisiae grows poorly or not at all when glycerol is the sole carbon source. Here we discover, through multiple evolved lineages, genetic determinants underlying glycerol catabolism and the associated fitness trade-offs. Most evolved lineages adapted through mutations in the HOG pathway, but showed hampered osmotolerance. In the other lineages, we find that only three mutations cause the improved phenotype. One of these contributes counter-intuitively by decoupling the TCA cycle from oxidative phosphorylation, and thereby hampers ethanol utilization. Transcriptomics, proteomics and metabolomics analysis of the re-engineered strains affirmed the causality of the three mutations at molecular level. Introduction of these mutations resulted in improved glycerol utilization also in industrial strains. Our findings not only have a direct relevance for improving glycerol-based bioprocesses, but also illustrate how a metabolic pathway can remain unexploited due to fitness trade-offs in other, ecologically important, traits.

Spontaneous Changes in Ploidy Are Common in Yeast

Changes in ploidy are relatively rare, but play important roles in the development of cancer and the acquisition of long-term adaptations. Genome duplications occur across the tree of life, and can alter the rate of adaptive evolution. Moreover, by allowing the subsequent loss of individual chromosomes and the accumulation of mutations, changes in ploidy can promote genomic instability and/or adaptation. Although many studies have been published in the last years about changes in chromosome number and their evolutionary consequences, tracking and measuring the rate of whole-genome duplications have been extremely challenging. We have systematically studied the appearance of diploid cells among haploid yeast cultures evolving for over 100 generations in different media. We find that spontaneous diploidization is a relatively common event, which is usually selected against, but under certain stressful conditions may become advantageous. Furthermore, we were able to detect and distinguish between two different mechanisms of diploidization, one that requires whole-genome duplication (endoreduplication) and a second that involves mating-type switching despite the use of heterothallic strains. Our results have important implications for our understanding of evolution and adaptation in fungal pathogens and the development of cancer, and for the use of yeast cells in biotechnological applications.

Genome Variations of Evolved Escherichia coli ET8 With a Rhodopsin-Based Phototrophic Metabolism

We reported that the phototrophic metabolism via plasmid-originated Gloeobacter rhodopsin(GR)-expression is improved in Escherichia coli ET5 harboring pKJ606-GR by a genomic point mutation (dgcQ^C1082A ) encoding a transmembrane cell signaling protein (Microb. Cell Fact. 16:111, 2017). Another evolved descendant is isolated from the chemostat, and the genome variation of the strain named ET8 harboring pKJ606-GR is investigated in this study. Whole genome sequencing analysis identifies a single point mutation (C3831976A) located in the non-coding upstream region of kdtA and an IS4 insertional mutation at galU^G706 without any mutations in the plasmid. ET8 strain shows enhanced kdtA transcription and no growth in the D-galactose or lactose sole carbon sourced minimal media. Size of ET8 strain are almost identical to that of the ancestor. Phototrophic growth and proton pumping in ET8 expressing GR (ET8 + GR) are increased 1.5-fold and threefold, respectively, compared with those in the ancestor (W3110 + GR). To verify the effects of the genomic mutations, either the kdtA-upregulation or the galU-disruption is conducted in the ancestor. Both the kdtA-upregulation and the galU-disruption result in the drastic increases of proton-pumping. The physiological properties arising from the genomic variations of the evolved host with the new phototrophic metabolism are further discussed.

Adaptation of Escherichia coli to long-term batch culture in various rich media

Experimental evolution studies have characterized the genetic strategies microbes utilize to adapt to their environments, mainly focusing on how microbes adapt to constant and/or defined environments. Using a system that incubates Escherichia coli in different complex media in long-term batch culture, we have focused on how heterogeneity and environment affects adaptive landscapes. In this system, there is no passaging of cells, and therefore genetic diversity is lost only through negative selection, without the experimentally-imposed bottlenecking common in other platforms. In contrast with other experimental evolution systems, because of cycling of nutrients and waste products, this is a heterogeneous environment, where selective pressures change over time, similar to natural environments. We determined that incubation in each environment leads to different adaptations by observing the growth advantage in stationary phase (GASP) phenotype. Re-sequencing whole genomes of populations identified both mutant alleles in a conserved set of genes and differences in evolutionary trajectories between environments. Reconstructing identified mutations in the parental strain background confirmed the adaptive advantage of some alleles, but also identified a surprising number of neutral or even deleterious mutations. This result indicates that complex epistatic interactions may be under positive selection within these heterogeneous environments.

Whole-genome sequencing reveals the mechanisms for evolution of streptomycin resistance in Lactobacillus plantarum

In this research, we investigated the evolution of streptomycin resistance in Lactobacillus plantarum ATCC14917, which was passaged in medium containing a gradually increasing concentration of streptomycin. After 25 d, the minimum inhibitory concentration (MIC) of L. plantarum ATCC14917 had reached 131,072 µg/mL, which was 8,192-fold higher than the MIC of the original parent isolate. The highly resistant L. plantarum ATCC14917 isolate was then passaged in antibiotic-free medium to determine the stability of resistance. The MIC value of the L. plantarum ATCC14917 isolate decreased to 2,048 µg/mL after 35 d but remained constant thereafter, indicating that resistance was irreversible even in the absence of selection pressure. Whole-genome sequencing of parent isolates, control isolates, and isolates following passage was used to study the resistance mechanism of L. plantarum ATCC14917 to streptomycin and adaptation in the presence and absence of selection pressure. Five mutated genes (single nucleotide polymorphisms and structural variants) were verified in highly resistant L. plantarum ATCC14917 isolates, which were related to ribosomal protein S12, LPXTG-motif cell wall anchor domain protein, LrgA family protein, Ser/Thr phosphatase family protein, and a hypothetical protein that may correlate with resistance to streptomycin. After passage in streptomycin-free medium, only the mutant gene encoding ribosomal protein S12 remained; the other 4 mutant genes had reverted to the wild type as found in the parent isolate. Although the MIC value of L. plantarum ATCC14917 was reduced in the absence of selection pressure, it remained 128-fold higher than the MIC value of the parent isolate, indicating that ribosomal protein S12 may play an important role in streptomycin resistance. Using the mobile elements database, we demonstrated that streptomycin resistance-related genes in L. plantarum ATCC14917 were not located on mobile elements. This research offers a way of combining laboratory evolution techniques and whole-genome sequencing for evaluating antibiotic resistance in probiotics.

The rate and potential relevance of new mutations in a colonizing plant lineage

By following the evolution of populations that are initially genetically homogeneous, much can be learned about core biological principles. For example, it allows for detailed studies of the rate of emergence of de novo mutations and their change in frequency due to drift and selection. Unfortunately, in multicellular organisms with generation times of months or years, it is difficult to set up and carry out such experiments over many generations. An alternative is provided by "natural evolution experiments" that started from colonizations or invasions of new habitats by selfing lineages. With limited or missing gene flow from other lineages, new mutations and their effects can be easily detected. North America has been colonized in historic times by the plant Arabidopsis thaliana, and although multiple intercrossing lineages are found today, many of the individuals belong to a single lineage, HPG1. To determine in this lineage the rate of substitutions-the subset of mutations that survived natural selection and drift-, we have sequenced genomes from plants collected between 1863 and 2006. We identified 73 modern and 27 herbarium specimens that belonged to HPG1. Using the estimated substitution rate, we infer that the last common HPG1 ancestor lived in the early 17th century, when it was most likely introduced by chance from Europe. Mutations in coding regions are depleted in frequency compared to those in other portions of the genome, consistent with purifying selection. Nevertheless, a handful of mutations is found at high frequency in present-day populations. We link these to detectable phenotypic variance in traits of known ecological importance, life history and growth, which could reflect their adaptive value. Our work showcases how, by applying genomics methods to a combination of modern and historic samples from colonizing lineages, we can directly study new mutations and their potential evolutionary relevance.

Evaluating genetic drift in time-series evolutionary analysis

The Wright-Fisher model is the most popular population model for describing the behaviour of evolutionary systems with a finite population size. Approximations have commonly been used but the model itself has rarely been tested against time-resolved genomic data. Here, we evaluate the extent to which it can be inferred as the correct model under a likelihood framework. Given genome-wide data from an evolutionary experiment, we validate the Wright-Fisher drift model as the better option for describing evolutionary trajectories in a finite population. This was found by evaluating its performance against a Gaussian model of allele frequency propagation. However, we note a range of circumstances under which standard Wright-Fisher drift cannot be correctly identified.

Resurrection of Dormant Daphnia magna: Protocol and Applications

Long-term studies enable the identification of eco-evolutionary processes that occur over extended time periods. In addition, they provide key empirical data that may be used in predictive modelling to forecast evolutionary responses of natural ecosystems to future environmental changes. However, excluding a few exceptional cases, long-term studies are scarce because of logistic difficulties associated with accessing temporal samples. Temporal dynamics are frequently studied in the laboratory or in controlled mesocosm experiments with exceptional studies that reconstruct the evolution of natural populations in the wild.

Here, a standard operating procedure (SOP) is provided to revive or resurrect dormant Daphnia magna, a widespread zooplankton keystone species in aquatic ecosystems, to dramatically advance the state-of-the-art longitudinal data collection in natural systems. The field of Resurrection Ecology was defined in 1999 by Kerfoot and co-workers, even though the first attempts at hatching diapausing zooplankton eggs date back to the late 1980s. Since Kerfoot's seminal paper, the methodology of resurrecting zooplankton species has been increasingly frequently applied, though propagated among laboratories only via direct knowledge transfer. Here, an SOP is described that provides a step-by-step protocol on the practice of resurrecting dormant Daphnia magna eggs.

Two key studies are provided in which the fitness response of resurrected Daphnia magna populations to warming is measured, capitalizing on the ability to study historical and modern populations in the same settings. Finally, the application of next generation sequencing technologies to revived or still dormant stages is discussed. These technologies provide unprecedented power in dissecting the processes and mechanisms of evolution if applied to populations that have experienced changes in selection pressure over time.

Malaria parasite evolution in a test tube

Experimental evolution studies reveal drug targets and resistance mechanisms

Demographic analysis of cyanobacteria based on the mutation rates estimated from an ancient ice core

Despite the crucial role of cyanobacteria in various ecosystems, little is known about their evolutionary histories, especially microevolutionary dynamics, because of the lack of knowledge regarding their mutation rates. Here we directly estimated cyanobacterial mutation rates based on ancient DNA analyses of ice core samples collected from Kyrgyz Republic that dates back to ~12,500 cal years before present. We successfully sequenced the 16S rRNA and 16S-23S internal transcribed spacer (ITS) region. Two cyanobacterial operational taxonomic units (OTUs) were detected from the ancient ice core samples, and these OTUs are shared with those from the modern glacier surface. The mutation rate of ITS region was estimated by comparing ancient and modern populations, and were at the magnitude of 10^-7substitutions/sites/year. By using a model selection framework, we also demonstrated that the ancient sequences from the ice sample were not contaminated from modern samples. Bayesian demographic analysis based on coalescent theory revealed that cyanobacterial population sizes increased over Asia regions during the Holocene. Thus, our results enhance our understanding of the enigmatic timescale of cyanobacterial microevolution, which has the potential to elucidate the environmental responses of cyanobacteria to the drastic climatic change events of the Quaternary.

Adaptation of Arabidopsis thaliana to the Yangtze River basin

Background

Organisms need to adapt to keep pace with a changing environment. Examining recent range expansion aids our understanding of how organisms evolve to overcome environmental constraints. However, how organisms adapt to climate changes is a crucial biological question that is still largely unanswered. The plant Arabidopsis thaliana is an excellent system to study this fundamental question. Its origin is in the Iberian Peninsula and North Africa, but it has spread to the Far East, including the most south-eastern edge of its native habitats, the Yangtze River basin, where the climate is very different.

Results

We sequenced 118 A. thaliana strains from the region surrounding the Yangtze River basin. We found that the Yangtze River basin population is a unique population and diverged about 61,409 years ago, with gene flows occurring at two different time points, followed by a population dispersion into the Yangtze River basin in the last few thousands of years. Positive selection analyses revealed that biological regulation processes, such as flowering time, immune and defense response processes could be correlated with the adaptation event. In particular, we found that the flowering time gene SVP has contributed to A. thaliana adaptation to the Yangtze River basin based on genetic mapping.

Conclusions

A. thaliana adapted to the Yangtze River basin habitat by promoting the onset of flowering, a finding that sheds light on how a species can adapt to locales with very different climates.

Electronic supplementary material

The online version of this article (doi:10.1186/s13059-017-1378-9) contains supplementary material, which is available to authorized users.

Evolutionary Remodeling of Bacterial Motility Checkpoint Control

Regulatory networks play a central role in the relationship between genotype and phenotype in all organisms. However, the mechanisms that underpin the evolutionary plasticity of these networks remain poorly understood. Here, we used experimental selection for enhanced bacterial motility in a porous environment to explore the adaptability of one of the most complex networks known in bacteria. We found that the resulting phenotypic changes are mediated by adaptive mutations in several functionally different proteins, including multiple components of the flagellar motor. Nevertheless, this evolutionary adaptation could be explained by a single mechanism, namely remodeling of the checkpoint regulating flagellar gene expression. Supported by computer simulations, our findings suggest that the specific “bow-tie” topology of the checkpoint facilitates evolutionary tuning of the cost-benefit trade-off between motility and growth. We propose that bow-tie regulatory motifs, which are widespread in cellular networks, play a general role in evolutionary adaptation.

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Multiple mutations enhance swimming behavior under selection

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A universal trade-off relationship between motility and growth is observed

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Checkpoint remodeling provides a mechanism of evolutionary adaptation

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Bow-tie topology facilitates evolvability of the motility network

Evolution as an ecosystem process: insights from genomics

Evolution is a fundamental ecosystem process. The study of genomic variation of organisms can not only improve our understanding of evolutionary processes, but also of contemporary and future ecosystem dynamics. We argue that integrative research between the fields of genomics and ecosystem ecology could generate new insights. Specifically, studies of biodiversity and ecosystem functioning, evolutionary rescue, and eco-evolutionary dynamics could all benefit from information about variation in genome structure and the genetic architecture of traits, whereas genomic studies could benefit from information about the ecological context of evolutionary dynamics. We propose new ways to help link research on functional genomic diversity with (reciprocal) interactions between phenotypic evolution and ecosystem change. Despite numerous challenges, we anticipate that the wealth of genomic data being collected on natural populations will improve our understanding of ecosystems.

Sexual recombination and increased mutation rate expedite evolution of Escherichia coli in varied fitness landscapes

Sexual recombination and mutation rate are theorized to play different roles in adaptive evolution depending on the fitness landscape; however, direct experimental support is limited. Here we examine how these factors affect the rate of adaptation utilizing a “genderless” strain of Escherichia coli capable of continuous in situ sexual recombination. The results show that the populations with increased mutation rate, and capable of sexual recombination, outperform all the other populations. We further characterize two sexual and two asexual populations with increased mutation rate and observe maintenance of beneficial mutations in the sexual populations through mutational sweeps. Furthermore, we experimentally identify the molecular signature of a mating event within the sexual population that combines two beneficial mutations to generate a fitter progeny; this evidence suggests that the recombination event partially alleviates clonal interference. We present additional data suggesting that stochasticity plays an important role in the combinations of mutations observed.

Sexual recombination and mutation rate may play different roles in adaptive evolution depending on the fitness landscape. Here, Peabody et al. examine how the two factors affect the rate of adaptation of an E. coli strain capable of sexual recombination, under different conditions during experimental evolution.

Stochastic Community Assembly: Does It Matter in Microbial Ecology?

Understanding the mechanisms controlling community diversity, functions, succession, and biogeography is a central, but poorly understood, topic in ecology, particularly in microbial ecology. Although stochastic processes are believed to play nonnegligible roles in shaping community structure, their importance relative to deterministic processes is hotly debated. The importance of ecological stochasticity in shaping microbial community structure is far less appreciated. Some of the main reasons for such heavy debates are the difficulty in defining stochasticity and the diverse methods used for delineating stochasticity. Here, we provide a critical review and synthesis of data from the most recent studies on stochastic community assembly in microbial ecology. We then describe both stochastic and deterministic components embedded in various ecological processes, including selection, dispersal, diversification, and drift. We also describe different approaches for inferring stochasticity from observational diversity patterns and highlight experimental approaches for delineating ecological stochasticity in microbial communities. In addition, we highlight research challenges, gaps, and future directions for microbial community assembly research.

Adaptive laboratory evolution of Corynebacterium glutamicum towards higher growth rates on glucose minimal medium

In this work, we performed a comparative adaptive laboratory evolution experiment of the important biotechnological platform strain Corynebacterium glutamicum ATCC 13032 and its prophage-free variant MB001 towards improved growth rates on glucose minimal medium. Both strains displayed a comparable adaptation behavior and no significant differences in genomic rearrangements and mutation frequencies. Remarkably, a significant fitness leap by about 20% was observed for both strains already after 100 generations. Isolated top clones (UBw and UBm) showed an about 26% increased growth rate on glucose minimal medium. Genome sequencing of evolved clones and populations resulted in the identification of key mutations in pyk (pyruvate kinase), fruK (1-phosphofructokinase) and corA encoding a Mg²⁺ importer. The reintegration of selected pyk and fruK mutations resulted in an increased glucose consumption rate and ptsG expression causative for the accelerated growth on glucose minimal medium, whereas corA mutations improved growth under Mg²⁺ limiting conditions. Overall, this study resulted in the identification of causative key mutations improving the growth of C. glutamicum on glucose. These identified mutational hot spots as well as the two evolved top strains, UBw and UBm, represent promising targets for future metabolic engineering approaches.

Stochastic Community Assembly: Does It Matter in Microbial Ecology?

Understanding the mechanisms controlling community diversity, functions, succession, and biogeography is a central, but poorly understood, topic in ecology, particularly in microbial ecology. Although stochastic processes are believed to play nonnegligible roles in shaping community structure, their importance relative to deterministic processes is hotly debated. The importance of ecological stochasticity in shaping microbial community structure is far less appreciated. Some of the main reasons for such heavy debates are the difficulty in defining stochasticity and the diverse methods used for delineating stochasticity. Here, we provide a critical review and synthesis of data from the most recent studies on stochastic community assembly in microbial ecology. We then describe both stochastic and deterministic components embedded in various ecological processes, including selection, dispersal, diversification, and drift. We also describe different approaches for inferring stochasticity from observational diversity patterns and highlight experimental approaches for delineating ecological stochasticity in microbial communities. In addition, we highlight research challenges, gaps, and future directions for microbial community assembly research.

Evolution on the bright side of life: microorganisms and the evolution of mutualism

Mutualistic interactions, where two interacting species have a net beneficial effect on each other's fitness, play a crucial role in the survival and evolution of many species. Despite substantial empirical and theoretical work in past decades, the impact of these interactions on natural selection is not fully understood. In addition, mutualisms between microorganisms have been largely ignored, even though they are ecologically important and can be used as tools to bridge the gap between theory and empirical work. Here, I describe two problems with our current understanding of natural selection in mutualism and highlight the properties of microbial mutualisms that could help solve them. One problem is that bias and methodological problems have limited our understanding of the variety of mechanisms by which species may adapt to mutualism. Another problem is that it is rare for experiments testing coevolution in mutualism to address whether each species has adapted to evolutionary changes in its partner. These problems can be addressed with genome resequencing and time-shift experiments, techniques that are easier to perform in microorganisms. In addition, microbial mutualisms may inspire novel insights and hypotheses about natural selection in mutualism.

Genomics of Adaptation Depends on the Rate of Environmental Change in Experimental Yeast Populations

The rate of directional environmental change may have profound consequences for evolutionary dynamics and outcomes. Yet, most evolution experiments impose a sudden large change in the environment, after which the environment is kept constant. We previously cultured replicate Saccharomyces cerevisiae populations for 500 generations in the presence of either gradually increasing or constant high concentrations of the heavy metals cadmium, nickel, and zinc. Here, we investigate how each of these treatments affected genomic evolution. Whole-genome sequencing of evolved clones revealed that adaptation occurred via a combination of SNPs, small indels, and whole-genome duplications and other large-scale structural changes. In contrast to some theoretical predictions, gradual and abrupt environmental change caused similar numbers of genomic changes. For cadmium, which is toxic already at comparatively low concentrations, mutations in the same genes were used for adaptation to both gradual and abrupt increase in concentration. Conversely, for nickel and zinc, which are toxic at high concentrations only, mutations in different genes were used for adaptation depending on the rate of change. Moreover, evolution was more repeatable following a sudden change in the environment, particularly for nickel and zinc. Our results show that the rate of environmental change and the nature of the selection pressure are important drivers of evolutionary dynamics and outcomes, which has implications for a better understanding of societal problems such as climate change and pollution.

Bacterial Genetic Architecture of Ecological Interactions in Co-culture by GWAS-Taking Escherichia coli and Staphylococcus aureus as an Example

How a species responds to such a biotic environment in the community, ultimately leading to its evolution, has been a topic of intense interest to ecological evolutionary biologists. Until recently, limited knowledge was available regarding the genotypic changes that underlie phenotypic changes. Our study implemented GWAS (Genome-Wide Association Studies) to illustrate the genetic architecture of ecological interactions that take place in microbial populations. By choosing 45 such interspecific pairs of Escherichia coli and Staphylococcus aureus strains that were all genotyped throughout the entire genome, we employed Q-ROADTRIPS to analyze the association between single SNPs and microbial abundance measured at each time point for bacterial populations reared in monoculture and co-culture, respectively. We identified a large number of SNPs and indels across the genomes (35.69 G clean data of E. coli and 50.41 G of S. aureus). We reported 66 and 111 SNPs that were associated with interaction in E. coli and S. aureus, respectively. 23 out of 66 polymorphic changes resulted in amino acid alterations.12 significant genes, such as murE, treA, argS, and relA, which were also identified in previous evolutionary studies. In S. aureus, 111 SNPs detected in coding sequences could be divided into 35 non-synonymous and 76 synonymous SNPs. Our study illustrated the potential of genome-wide association methods for studying rapidly evolving traits in bacteria. Genetic association study methods will facilitate the identification of genetic elements likely to cause phenotypes of interest and provide targets for further laboratory investigation.

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.

Key Metabolites and Mechanistic Changes for Salt Tolerance in an Experimentally Evolved Sulfate-Reducing Bacterium, Desulfovibrio vulgaris

Rapid genetic and phenotypic adaptation of the sulfate-reducing bacterium Desulfovibrio vulgaris Hildenborough to salt stress was observed during experimental evolution. In order to identify key metabolites important for salt tolerance, a clone, ES10-5, which was isolated from population ES10 and allowed to experimentally evolve under salt stress for 5,000 generations, was analyzed and compared to clone ES9-11, which was isolated from population ES9 and had evolved under the same conditions for 1,200 generations. These two clones were chosen because they represented the best-adapted clones among six independently evolved populations. ES10-5 acquired new mutations in genes potentially involved in salt tolerance, in addition to the preexisting mutations and different mutations in the same genes as in ES9-11. Most basal abundance changes of metabolites and phospholipid fatty acids (PLFAs) were lower in ES10-5 than ES9-11, but an increase of glutamate and branched PLFA i17:1ω9c under high-salinity conditions was persistent. ES9-11 had decreased cell motility compared to the ancestor; in contrast, ES10-5 showed higher cell motility under both nonstress and high-salinity conditions. Both genotypes displayed better growth energy efficiencies than the ancestor under nonstress or high-salinity conditions. Consistently, ES10-5 did not display most of the basal transcriptional changes observed in ES9-11, but it showed increased expression of genes involved in glutamate biosynthesis, cation efflux, and energy metabolism under high salinity. These results demonstrated the role of glutamate as a key osmolyte and i17:1ω9c as the major PLFA for salt tolerance in D. vulgaris The mechanistic changes in evolved genotypes suggested that growth energy efficiency might be a key factor for selection.IMPORTANCE High salinity (e.g., elevated NaCl) is a stressor that affects many organisms. Salt tolerance, a complex trait involving multiple cellular pathways, is attractive for experimental evolutionary studies. Desulfovibrio vulgaris Hildenborough is a model sulfate-reducing bacterium (SRB) that is important in biogeochemical cycling of sulfur, carbon, and nitrogen, potentially for bio-corrosion, and for bioremediation of toxic heavy metals and radionuclides. The coexistence of SRB and high salinity in natural habitats and heavy metal-contaminated field sites laid the foundation for the study of salt adaptation of D. vulgaris Hildenborough with experimental evolution. Here, we analyzed a clone that evolved under salt stress for 5,000 generations and compared it to a clone evolved under the same condition for 1,200 generations. The results indicated the key roles of glutamate for osmoprotection and of i17:1ω9c for increasing membrane fluidity during salt adaptation. The findings provide valuable insights about the salt adaptation mechanism changes during long-term experimental evolution.

Refactoring the Genetic Code for Increased Evolvability

The standard genetic code is robust to mutations during transcription and translation. Point mutations are likely to be synonymous or to preserve the chemical properties of the original amino acid. Saturation mutagenesis experiments suggest that in some cases the best-performing mutant requires replacement of more than a single nucleotide within a codon. These replacements are essentially inaccessible to common error-based laboratory engineering techniques that alter a single nucleotide per mutation event, due to the extreme rarity of adjacent mutations. In this theoretical study, we suggest a radical reordering of the genetic code that maximizes the mutagenic potential of single nucleotide replacements. We explore several possible genetic codes that allow a greater degree of accessibility to the mutational landscape and may result in a hyperevolvable organism that could serve as an ideal platform for directed evolution experiments. We then conclude by evaluating the challenges of constructing such recoded organisms and their potential applications within the field of synthetic biology.

The conservative nature of the genetic code prevents bioengineers from efficiently accessing the full mutational landscape of a gene via common error-prone methods. Here, we present two computational approaches to generate alternative genetic codes with increased accessibility. These new codes allow mutational transitions to a larger pool of amino acids and with a greater extent of chemical differences, based on a single nucleotide replacement within the codon, thus increasing evolvability both at the single-gene and at the genome levels. Given the widespread use of these techniques for strain and protein improvement, along with more fundamental evolutionary biology questions, the use of recoded organisms that maximize evolvability should significantly improve the efficiency of directed evolution, library generation, and fitness maximization.

Experimental evolution and proximate mechanisms in biology

Biological functions – studied by molecular, systems and behavioral biology – are referred to as proximate mechanisms. Why and how they have emerged from the course of evolution are referred to as ultimate mechanisms. Despite the conceptual and technical schism between the disciplines that focus on each, studies from one side can benefit the other. Experimental evolution is an emerging field at the crossroads of functional and evolutionary biology. Herein microorganisms and mammalian cell lines evolve in well-controlled laboratory environments over multiple generations. Phenotypic changes arising from the process are then characterized in genetics and function to understand the evolutionary process. While providing empirical tests to evolutionary questions, such studies also offer opportunities of new insights into proximate mechanisms. Experimental evolution optimizes biological systems by means of adaptation; the adapted systems with their mutations present unique perturbed states of the systems that generate new and often unexpected output/performance. Hence, learning about these states not only adds to but also might deepen knowledge on the proximate processes. To demonstrate this point, five examples in experimental evolution are introduced, and their relevance to functional biology explicated. In some examples, from evolution experiments, updates were made to known proximate processes – gene regulation and cell polarization. In some examples, new contexts were found for known proximate processes – cell division and drug resistance of cancer. In one example, a new cellular mechanism was discovered. These cases identify ways the approach of experimental evolution can be used to ask questions in functional biology.

Sources of spontaneous mutagenesis in bacteria

Mutations in an organism's genome can arise spontaneously, that is, in the absence of exogenous stress and prior to selection. Mutations are often neutral or deleterious to individual fitness but can also provide genetic diversity driving evolution. Mutagenesis in bacteria contributes to the already serious and growing problem of antibiotic resistance. However, the negative impacts of spontaneous mutagenesis on human health are not limited to bacterial antibiotic resistance. Spontaneous mutations also underlie tumorigenesis and evolution of drug resistance. To better understand the causes of genetic change and how they may be manipulated in order to curb antibiotic resistance or the development of cancer, we must acquire a mechanistic understanding of the major sources of mutagenesis. Bacterial systems are particularly well-suited to studying mutagenesis because of their fast growth rate and the panoply of available experimental tools, but efforts to understand mutagenic mechanisms can be complicated by the experimental system employed. Here, we review our current understanding of mutagenic mechanisms in bacteria and describe the methods used to study mutagenesis in bacterial systems.

Rapid Genetic Adaptation during the First Four Months of Survival under Resource Exhaustion

Many bacteria, including the model bacterium Escherichia coli can survive for years within spent media, following resource exhaustion. We carried out evolutionary experiments, followed by whole genome sequencing of hundreds of evolved clones to study the dynamics by which E. coli adapts during the first 4 months of survival under resource exhaustion. Our results reveal that bacteria evolving under resource exhaustion are subject to intense selection, manifesting in rapid mutation accumulation, enrichment in functional mutation categories and extremely convergent adaptation. In the most striking example of convergent adaptation, we found that across five independent populations adaptation to conditions of resource exhaustion occurs through mutations to the three same specific positions of the RNA polymerase core enzyme. Mutations to these three sites are strongly antagonistically pleiotropic, in that they sharply reduce exponential growth rates in fresh media. Such antagonistically pleiotropic mutations, combined with the accumulation of additional mutations, severely reduce the ability of bacteria surviving under resource exhaustion to grow exponentially in fresh media. We further demonstrate that the three positions at which these resource exhaustion mutations occur are conserved for the ancestral E. coli allele, across bacterial phyla, with the exception of nonculturable bacteria that carry the resource exhaustion allele at one of these positions, at very high frequencies. Finally, our results demonstrate that adaptation to resource exhaustion is not limited by mutational input and that bacteria are able to rapidly adapt under resource exhaustion in a temporally precise manner through allele frequency fluctuations.

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.

Extreme mutation bias and high AT content in Plasmodium falciparum

For reasons that remain unknown, the Plasmodium falciparum genome has an exceptionally high AT content compared to other Plasmodium species and eukaryotes in general - nearly 80% in coding regions and approaching 90% in non-coding regions. Here, we examine how this phenomenon relates to genome-wide patterns of de novo mutation. Mutation accumulation experiments were performed by sequential cloning of six P. falciparum isolates growing in human erythrocytes in vitro for 4 years, with 279 clones sampled for whole genome sequencing at different time points. Genome sequence analysis of these samples revealed a significant excess of G:C to A:T transitions compared to other types of nucleotide substitution, which would naturally cause AT content to equilibrate close to the level seen across the P. falciparum reference genome (80.6% AT). These data also uncover an extremely high rate of small indel mutation relative to other species, primarily associated with repetitive AT-rich sequences, in addition to larger-scale structural rearrangements focused in antigen-coding var genes. In conclusion, high AT content in P. falciparum is driven by a systematic mutational bias and ultimately leads to an unusual level of microstructural plasticity, raising the question of whether this contributes to adaptive evolution.

Tools for Genomic and Transcriptomic Analysis of Microbes at Single-Cell Level

Microbiologists traditionally study population rather than individual cells, as it is generally assumed that the status of individual cells will be similar to that observed in the population. However, the recent studies have shown that the individual behavior of each single cell could be quite different from that of the whole population, suggesting the importance of extending traditional microbiology studies to single-cell level. With recent technological advances, such as flow cytometry, next-generation sequencing (NGS), and microspectroscopy, single-cell microbiology has greatly enhanced the understanding of individuality and heterogeneity of microbes in many biological systems. Notably, the application of multiple ‘omics’ in single-cell analysis has shed light on how individual cells perceive, respond, and adapt to the environment, how heterogeneity arises under external stress and finally determines the fate of the whole population, and how microbes survive under natural conditions. As single-cell analysis involves no axenic cultivation of target microorganism, it has also been demonstrated as a valuable tool for dissecting the microbial ‘dark matter.’ In this review, current state-of-the-art tools and methods for genomic and transcriptomic analysis of microbes at single-cell level were critically summarized, including single-cell isolation methods and experimental strategies of single-cell analysis with NGS. In addition, perspectives on the future trends of technology development in the field of single-cell analysis was also presented.

Using experimental evolution to identify druggable targets that could inhibit the evolution of antimicrobial resistance

With multi-drug and pan-drug-resistant bacteria becoming increasingly common in hospitals, antibiotic resistance has threatened to return us to a pre-antibiotic era that would completely undermine modern medicine. There is an urgent need to develop new antibiotics and strategies to combat resistance that are substantially different from earlier drug discovery efforts. One such strategy that would complement current and future antibiotics would be a class of co-drugs that target the evolution of resistance and thereby extend the efficacy of specific classes of antibiotics. A critical step in the development of such strategies lies in understanding the critical evolutionary trajectories responsible for resistance and which proteins or biochemical pathways within those trajectories would be good candidates for co-drug discovery. We identify the most important steps in the evolution of resistance for a specific pathogen and antibiotic combination by evolving highly polymorphic populations of pathogens to resistance in a novel bioreactor that favors biofilm development. As the populations evolve to increasing drug concentrations, we use deep sequencing to elucidate the network of genetic changes responsible for resistance and subsequent in vitro biochemistry and often structure determination to determine how the adaptive mutations produce resistance. Importantly, the identification of the molecular steps, their frequency within the populations and their chronology within the evolutionary trajectory toward resistance is critical to assessing their relative importance. In this work, we discuss findings from the evolution of the ESKAPE pathogen, Pseudomonas aeruginosa to the drug of last resort, colistin to illustrate the power of this approach.

Induction of allopurinol resistance in Leishmania infantum isolated from dogs

Resistance to allopurinol in zoonotic canine leishmaniasis has been recently shown to be associated with disease relapse in naturally-infected dogs. However, information regarding the formation of resistance and its dynamics is lacking. This study describes the successful in-vitro induction of allopurinol resistance in Leishmania infantum cultured under increasing drug pressure. Allopurinol susceptibility and growth rate of induced parasites were monitored over 23 weeks and parasite clones were tested at selected time points and compared to their parental lines, both as promastigotes and as amastigotes. Allopurinol resistance was formed in strains from two parasite stocks producing a 20-fold rise in IC₅₀ along three distinct growth phases. In addition, characteristic differential clustering of single nucleotide polymorphisms (SNP) was found in drug sensitive and resistant parasite clones. Results confirm that genetic polymorphism, as well as clonal heterogeneity, contribute to in-vitro resistance to allopurinol, which is likely to occur in natural infection.

Visceral leishmaniasis caused by the parasite Leishmania infantum is a neglected tropical disease transmitted from animal hosts to humans by sand fly bites. This potentially fatal disease affects thousands of people annually and threatens millions who live in disease risk areas. Domestic dogs are considered as the main reservoir of this parasite which can also cause a severe chronic canine disease. Allopurinol is the main drug used for long term treatment of this disease but it often does not eliminate infection in dogs. We have recently demonstrated that allopurinol resistant parasites can be isolated from naturally infected dogs that have developed clinical recurrence of disease during allopurinol treatment. In this study we aimed to see if resistance can be induced in susceptible parasite strains isolated from sick dogs by growing them in increasing drug concentrations under laboratory conditions. The changes in allopurinol susceptibility were measured and the impact of drug on parasite growth was monitored over 23 weeks. Induction of resistance was successful producing parasites 20-folds less susceptible to the drug. The pattern of change in drug susceptibility suggests that a genetic change is responsible for the increased resistance which is likely to mimic the formation of resistance in dogs.

Different Genomic Changes Underlie Adaptive Evolution in Populations of Contrasting History

Experimental evolution is a powerful tool to understand the adaptive potential of populations under environmental change. Here, we study the importance of the historical genetic background in the outcome of evolution at the genome-wide level. Using the natural clinal variation of Drosophila subobscura, we sampled populations from two contrasting latitudes (Adraga, Portugal and Groningen, Netherlands) and introduced them in a new common environment in the laboratory. We characterized the genome-wide temporal changes underlying the evolutionary dynamics of these populations, which had previously shown fast convergence at the phenotypic level, but not at chromosomal inversion frequencies. We found that initially differentiated populations did not converge either at genome-wide level or at candidate SNPs with signs of selection. In contrast, populations from Portugal showed convergence to the control population that derived from the same geographical origin and had been long-established in the laboratory. Candidate SNPs showed a variety of different allele frequency change patterns across generations, indicative of an underlying polygenic basis. We did not detect strong linkage around candidate SNPs, but rather a small but long-ranging effect. In conclusion, we found that history played a major role in genomic variation and evolution, with initially differentiated populations reaching the same adaptive outcome through different genetic routes.