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

Genome and transcriptomic analysis of the adaptation of Escherichia coli to environmental stresses

In natural niches, bacteria are forced to spend most of their lives under various environmental stresses, such as nutrient limitation, heavy metal pollution, heat and antibiotic stress. To cope with adverse environments, bacterial genome can during the life cycle, produce potential adaptive mutants. The genomic changes, especially mutations, in the genes that encode RNA polymerase and transcription factors, might lead to variations in the transcriptome. These variations enable bacteria to cope with environmental stresses through physiological adaptation in response to stress. This paper reviews the recent contributions of genomic and transcriptomic analyses in understanding the adaption mechanism of Escherichia coli to environmental stresses. Various genomic changes have been observed in E. coli strains in laboratory or under natural stresses, including starvation, heavy metals, acidic conditions, heat shock and antibiotics. The mutations include slight changes (one to several nucleotides), deletions, insertions, chromosomal rearrangements and variations in copy numbers. The transcriptome of E. coli largely changes due to genomic mutations. However, the transcriptional profiles vary due to variations in stress selections. Cellular adaptation to the selections is associated with transcriptional changes resulting from genomic mutations. Changes in genome and transcriptome are cooperative and jointly affect the adaptation of E. coli to different environments. This comprehensive review reveals that coordination of genome mutations and transcriptional variations needs to be explored further to provide a better understanding of the mechanisms of bacterial adaptation to stresses.

Establishing African genomics and bioinformatics programs through annual regional workshops

The African BioGenome Project (AfricaBP) Open Institute for Genomics and Bioinformatics aims to overcome barriers to capacity building through its distributed African regional workshops and prioritizes the exchange of grassroots knowledge and innovation in biodiversity genomics and bioinformatics. In 2023, we implemented 28 workshops on biodiversity genomics and bioinformatics, covering 11 African countries across the 5 African geographical regions. These regional workshops trained 408 African scientists in hands-on molecular biology, genomics and bioinformatics techniques as well as the ethical, legal and social issues associated with acquiring genetic resources. Here, we discuss the implementation of transformative strategies, such as expanding the regional workshop model of AfricaBP to involve multiple countries, institutions and partners, including the proposed creation of an African digital database with sequence information relating to both biodiversity and agriculture. This will ultimately help create a critical mass of skilled genomics and bioinformatics scientists across Africa.

Genomic sequencing reveals convergent adaptation during experimental evolution in two budding yeast species

Convergent evolution is central in the origins of multicellularity. Identifying the basis for convergent multicellular evolution is challenging because of the diverse evolutionary origins and environments involved. Haploid Kluyveromyces lactis populations evolve multicellularity during selection for increased settling in liquid media. Strong genomic and phenotypic convergence is observed between K. lactis and previously selected S. cerevisiae populations under similar selection, despite their >100-million-year divergence. We find K. lactis multicellularity is conferred by mutations in genes ACE2 or AIM44, with ACE2 being predominant. They are a subset of the six genes involved in the S. cerevisiae multicellularity. Both ACE2 and AIM44 regulate cell division, indicating that the genetic convergence is likely due to conserved cellular replication mechanisms. Complex population dynamics involving multiple ACE2/AIM44 genotypes are found in most K. lactis lineages. The results show common ancestry and natural selection shape convergence while chance and contingency determine the degree of divergence.

The loci of environmental adaptation in a model eukaryote

While the underlying genetic changes have been uncovered in some cases of adaptive evolution, the lack of a systematic study prevents a general understanding of the genomic basis of adaptation. For example, it is unclear whether protein-coding or noncoding mutations are more important to adaptive evolution and whether adaptations to different environments are brought by genetic changes distributed in diverse genes and biological processes or concentrated in a core set. We here perform laboratory evolution of 3360 Saccharomyces cerevisiae populations in 252 environments of varying levels of stress. We find the yeast adaptations to be primarily fueled by large-effect coding mutations overrepresented in a relatively small gene set, despite prevalent antagonistic pleiotropy across environments. Populations generally adapt faster in more stressful environments, partly because of greater benefits of the same mutations in more stressful environments. These and other findings from this model eukaryote help unravel the genomic principles of environmental adaptation.

Selection leads to remarkable variability in the outcomes of hybridisation across replicate hybrid zones

Hybrid zones have been viewed as an opportunity to see speciation in action. When hybrid zones are replicated, it is assumed that if the same genetic incompatibilities are maintaining reproductive isolation across all instances of secondary contact, those incompatibilities should be identifiable by consistent patterns in the genome. In contrast, changes in allele frequencies due to genetic drift should be idiosyncratic for each hybrid zone. To test this assumption, we simulated 20 replicates of each of 12 hybrid zone scenarios with varied genetic incompatibilities, rates of migration, selection and different starting population size ratios of parental species. We found remarkable variability in the outcomes of hybridisation in replicate hybrid zones, particularly with Bateson-Dobzhansky-Muller incompatibilities and strong selection. We found substantial differences among replicates in the overall genomic composition of individuals, including admixture proportions, inter-specific ancestry complement and number of ancestry junctions. Additionally, we found substantial variation in genomic clines among replicates at focal loci, regardless of locus-specific selection. We conclude that processes other than selection are responsible for some consistent outcomes of hybridisation, whereas selection on incompatibilities can lead to genomically widespread and highly variable outcomes. We highlight the challenge of mapping between pattern and process in hybrid zones and call attention to how selection against incompatibilities will commonly lead to variable outcomes. We hope that this study informs future research on replicate hybrid zones and encourages further development of statistical techniques, theoretical models and exploration of additional axes of variation to understand reproductive isolation.

Escherichia coli adaptation under prolonged resource exhaustion is characterized by extreme parallelism and frequent historical contingency

Like many other non-sporulating bacterial species, Escherichia coli is able to survive prolonged periods of resource exhaustion, by entering a state of growth called long-term stationary phase (LTSP). In July 2015, we initiated a set of evolutionary experiments aimed at characterizing the dynamics of E. coli adaptation under LTSP. In these experiments populations of E. coli were allowed to initially grow on fresh rich media, but were not provided with any new external growth resources since their establishment. Utilizing whole genome sequencing data obtained for hundreds of clones sampled at 12 time points spanning the first six years of these experiments, we reveal several novel aspects of the dynamics of adaptation. First, we show that E. coli continuously adapts genetically, up to six years under resource exhaustion, through the highly convergent accumulation of mutations. We further show that upon entry into LTSP, long-lasting lineages are established. This lineage structure is in itself convergent, with similar lineages arising across independently evolving populations. The high parallelism with which adaptations occur under LTSP, combined with the LTSP populations' lineage structure, enable us to screen for pairs of loci displaying a significant association in the occurrence of mutations, suggestive of a historical contingency. We find that such associations are highly frequent and that a third of convergently mutated loci are involved in at least one such association. Combined our results demonstrate that LTSP adaptation is characterized by remarkably high parallelism and frequent historical contingency.

Analysis of In-Patient Evolution of Escherichia coli Reveals Potential Links to Relapse of Bone and Joint Infections

Bone and joint infections (BJIs) are difficult to treat and affect a growing number of patients, in which relapses are observed in 10-20% of case. These relapses, which call for prolonged antibiotic treatment and increase resistance emergence risk, may originate from ill-understood adaptation of the pathogen to the host. Here, we investigated 3 pairs of Escherichia coli strains from BJI cases and their relapses to unravel adaptations within patients. Whole-genome comparison presented evidence for positive selection and phenotypic characterization showed that biofilm formation remained unchanged, contrary to what is usually described in such cases. Although virulence was not modified, we identified the loss of 2 virulence factors contributing to immune system evasion in one of the studied strains. Other strategies, including global growth optimization and colicin production, likely allowed the strains to outcompete competitors. This work highlights the variety of strategies allowing in-patient adaptation in BJIs.

Beneficial applications of biofilms

Many microorganisms live in the form of a biofilm. Although they are feared in the medical sector, biofilms that are composed of non-pathogenic organisms can be highly beneficial in many applications, including the production of bulk and fine chemicals. Biofilm systems are natural retentostats in which the biocatalysts can adapt and optimize their metabolism to different conditions over time. The adherent nature of biofilms allows them to be used in continuous systems in which the hydraulic retention time is much shorter than the doubling time of the biocatalysts. Moreover, the resilience of organisms growing in biofilms, together with the potential of uncoupling growth from catalytic activity, offers a wide range of opportunities. The ability to work with continuous systems using a potentially self-advancing whole-cell biocatalyst is attracting interest from a range of disciplines, from applied microbiology to materials science and from bioengineering to process engineering. The field of beneficial biofilms is rapidly evolving, with an increasing number of applications being explored, and the surge in demand for sustainable and biobased solutions and processes is accelerating advances in the field. This Review provides an overview of the research topics, challenges, applications and future directions in beneficial and applied biofilm research.

Promoter recruitment drives the emergence of proto-genes in a long-term evolution experiment with Escherichia coli

The phenomenon of de novo gene birth-the emergence of genes from non-genic sequences-has received considerable attention due to the widespread occurrence of genes that are unique to particular species or genomes. Most instances of de novo gene birth have been recognized through comparative analyses of genome sequences in eukaryotes, despite the abundance of novel, lineage-specific genes in bacteria and the relative ease with which bacteria can be studied in an experimental context. Here, we explore the genetic record of the Escherichia coli long-term evolution experiment (LTEE) for changes indicative of "proto-genic" phases of new gene birth in which non-genic sequences evolve stable transcription and/or translation. Over the time span of the LTEE, non-genic regions are frequently transcribed, translated and differentially expressed, with levels of transcription across low-expressed regions increasing in later generations of the experiment. Proto-genes formed downstream of new mutations result either from insertion element activity or chromosomal translocations that fused preexisting regulatory sequences to regions that were not expressed in the LTEE ancestor. Additionally, we identified instances of proto-gene emergence in which a previously unexpressed sequence was transcribed after formation of an upstream promoter, although such cases were rare compared to those caused by recruitment of preexisting promoters. Tracing the origin of the causative mutations, we discovered that most occurred early in the history of the LTEE, often within the first 20,000 generations, and became fixed soon after emergence. Our findings show that proto-genes emerge frequently within evolving populations, can persist stably, and can serve as potential substrates for new gene formation.

Interactions between chaperone and energy storage networks during the evolution of Legionella pneumophila under heat shock

Waterborne transmission of the bacterium Legionella pneumophila has emerged as a major cause of severe nosocomial infections of major public health impact. The major route of transmission involves the uptake of aerosolized bacteria, often from the contaminated hot water systems of large buildings. Public health regulations aimed at controlling the mesophilic pathogen are generally concerned with acute pasteurization and maintaining high temperatures at the heating systems and throughout the plumbing of hot water systems, but L. pneumophila is often able to survive these treatments due to both bacterium-intrinsic and environmental factors. Previous work has established an experimental evolution system to model the observations of increased heat resistance in repeatedly but unsuccessfully pasteurized L. pneumophila populations. Here, we show rapid fixation of novel alleles in lineages selected for resistance to heat shock and shifts in mutational profile related to increases in the temperature of selection. Gene-level and nucleotide-level parallelisms between independently-evolving lineages show the centrality of the DnaJ/DnaK chaperone system in the heat resistance of L. pneumophila. Inference of epistatic interactions through reverse genetics shows an unexpected interaction between DnaJ/DnaK and the polyhydroxybutyrate-accumulation energy storage mechanism used by the species to survive long-term starvation in low-nutrient environments.

Trade-offs, trade-ups, and high mutational parallelism underlie microbial adaptation during extreme cycles of feast and famine

Microbes are evolutionarily robust organisms capable of rapid adaptation to complex stress, which enables them to colonize harsh environments. In nature, microbes are regularly challenged by starvation, which is a particularly complex stress because resource limitation often co-occurs with changes in pH, osmolarity, and toxin accumulation created by metabolic waste. Often overlooked are the additional complications introduced by eventual resource replenishment, as successful microbes must withstand rapid environmental shifts before swiftly capitalizing on replenished resources to avoid invasion by competing species. To understand how microbes navigate trade-offs between growth and survival, ultimately adapting to thrive in environments with extreme fluctuations, we experimentally evolved 16 Escherichia coli populations for 900 days in repeated feast/famine conditions with cycles of 100-day starvation before resource replenishment. Using longitudinal population-genomic analysis, we found that evolution in response to extreme feast/famine is characterized by narrow adaptive trajectories with high mutational parallelism and notable mutational order. Genetic reconstructions reveal that early mutations result in trade-offs for biofilm and motility but trade-ups for growth and survival, as these mutations conferred positively correlated advantages during both short-term and long-term culture. Our results demonstrate how microbes can navigate the adaptive landscapes of regularly fluctuating conditions and ultimately follow mutational trajectories that confer benefits across diverse environments.

Mutational Signatures in Wild Type Escherichia coli Strains Reveal Predominance of DNA Polymerase Errors

While mutational processes operating in the Escherichia coli genome have been revealed by multiple laboratory experiments, the contribution of these processes to accumulation of bacterial polymorphism and evolution in natural environments is unknown. To address this question, we reconstruct signatures of distinct mutational processes from experimental data on E. coli hypermutators, and ask how these processes contribute to differences between naturally occurring E. coli strains. We show that both mutations accumulated in the course of evolution of wild-type strains in nature and in the lab-grown nonmutator laboratory strains are explained predominantly by the low fidelity of DNA polymerases II and III. By contrast, contributions specific to disruption of DNA repair systems cannot be detected, suggesting that temporary accelerations of mutagenesis associated with such disruptions are unimportant for within-species evolution. These observations demonstrate that accumulation of diversity in bacterial strains in nature is predominantly associated with errors of DNA polymerases.

Genomics for monitoring and understanding species responses to global climate change

All life forms across the globe are experiencing drastic changes in environmental conditions as a result of global climate change. These environmental changes are happening rapidly, incur substantial socioeconomic costs, pose threats to biodiversity and diminish a species' potential to adapt to future environments. Understanding and monitoring how organisms respond to human-driven climate change is therefore a major priority for the conservation of biodiversity in a rapidly changing environment. Recent developments in genomic, transcriptomic and epigenomic technologies are enabling unprecedented insights into the evolutionary processes and molecular bases of adaptation. This Review summarizes methods that apply and integrate omics tools to experimentally investigate, monitor and predict how species and communities in the wild cope with global climate change, which is by genetically adapting to new environmental conditions, through range shifts or through phenotypic plasticity. We identify advantages and limitations of each method and discuss future research avenues that would improve our understanding of species' evolutionary responses to global climate change, highlighting the need for holistic, multi-omics approaches to ecosystem monitoring during global climate change.

Changing fitness effects of mutations through long-term bacterial evolution

The distribution of fitness effects of new mutations shapes evolution, but it is challenging to observe how it changes as organisms adapt. Using Escherichia coli lineages spanning 50,000 generations of evolution, we quantify the fitness effects of insertion mutations in every gene. Macroscopically, the fraction of deleterious mutations changed little over time whereas the beneficial tail declined sharply, approaching an exponential distribution. Microscopically, changes in individual gene essentiality and deleterious effects often occurred in parallel; altered essentiality is only partly explained by structural variation. The identity and effect sizes of beneficial mutations changed rapidly over time, but many targets of selection remained predictable because of the importance of loss-of-function mutations. Taken together, these results reveal the dynamic-but statistically predictable-nature of mutational fitness effects.

Genome reduction occurred in early Prochlorococcus with an unusually low effective population size

In the oligotrophic sunlit ocean, the most abundant free-living planktonic bacterial lineages evolve convergently through genome reduction. The cyanobacterium Prochlorococcus responsible for 10% global oxygen production is a prominent example. The dominant theory known as "genome streamlining" posits that they have extremely large effective population sizes (Ne) such that selection for metabolic efficiency acts to drive genome reduction. Because genome reduction largely took place anciently, this theory builds on the assumption that their ancestors' Ne was similarly large. Constraining Ne for ancient ancestors is challenging because experimental measurements of extinct organisms are impossible and alternatively reconstructing ancestral Ne with phylogenetic models gives large uncertainties. Here, we develop a new strategy that leverages agent-based modeling to simulate the changes in the genome-wide ratio of radical to conservative nonsynonymous nucleotide substitution rate (dR/dC) in a possible range of Ne in ancestral populations. This proxy shows expected increases with decreases of Ne only when Ne falls to about 10 k - 100 k or lower, magnitudes characteristic of Ne of obligate endosymbiont species where drift drives genome reduction. Our simulations therefore strongly support a scenario where the primary force of Prochlorococcus genome reduction is drift rather than selection.

A new, all-encompassing aetiology of type 1 diabetes

The aetiology of type 1 diabetes (T1D) is considered multifactorial with the contribution of the MHC on chromosome 6 being most important. Multiple factors also contribute to the aetiology of colorectal neoplasia, but the final event causing the change from normal mucosa to polyp and from polyp to cancer is due to a single somatic mutation event. Repeated formation of colorectal neoplasia within an at-risk population results in a predictable, tapering, exponential neoplasia distribution. Critical mutations driving colorectal neoplasia formation occur in mutation-prone DNA. These observations led to three hypotheses related to T1D. First, a single somatic mutation within the MHC of antigen presenting cells results in a change in phenotype from normal to T1D. Second, the distribution of additional autoimmune diseases (AAIDs) among persons with T1D adheres to a predictable, tapering, exponential distribution. And third, critical mutations driving development of T1D occur in mutation-prone DNA. To address the hypotheses in an orderly fashion, a new analytical method called genome-wide aetiology analysis (GWEA) consisting of nine steps is presented. All data required for GWEA of T1D are obtained from peer-reviewed publications or publicly available genome and proteome databases. Critical GWEA steps include AAID distribution among persons with T1D, analysis of at-risk HLA loci for mutation-prone DNA, determination of the role of non-MHC genes on GWAS, and verification of human data by cell culture or animal experiments. GWEA results show that distribution of AAID among persons with T1D adheres to a predictable, tapering, exponential distribution. A single, critical, somatic mutation within the epitope-binding groove of at-risk HLA loci alters HLA-insulin-peptide-T-cell-receptor (TCR) complex binding affinity and creates a new pathway that leads to loss of self-tolerance. The at-risk HLA loci, in particular binding pockets P1, P4 and P9, are encoded by mutation-prone DNA: GC-rich DNA sequence and somatic hypermutation hotspots. All other genes on GWAS can but do not have to amplify the new autoimmune pathway by facilitating DNA mutations, changing peptide binding affinity, reducing signal inhibition or augmenting signal intensity. Animal experiments agree with human studies. In conclusion, T1D is caused by a somatic mutation within the epitope-binding groove of an at-risk HLA gene that affects HLA-insulin-peptide-TCR complex binding affinity and initiates an autoimmune pathway. The nature of the peptide that binds to a mutated epitope-binding groove of an at-risk HLA gene determines the type of autoimmune disease that develops, that is, one at-risk HLA locus, multiple autoimmune diseases. Thus, T1D and AAIDs, and therefore common autoimmune diseases, share a similar somatic mutation-based aetiology.

Biodiversity and Constrained Information Dynamics in Ecosystems: A Framework for Living Systems

The increase in ecosystem biodiversity can be perceived as one of the universal processes converting energy into information across a wide range of living systems. This study delves into the dynamics of living systems, highlighting the distinction between ex post adaptation, typically associated with natural selection, and its proactive counterpart, ex ante adaptability. Through coalescence experiments using synthetic ecosystems, we (i) quantified ecosystem stability, (ii) identified correlations between some biodiversity indexes and the stability, (iii) proposed a mechanism for increasing biodiversity through moderate inter-ecosystem interactions, and (iv) inferred that the information carrier of ecosystems is species composition, or merged genomic information. Additionally, it was suggested that (v) changes in ecosystems are constrained to a low-dimensional state space, with three distinct alteration trajectories-fluctuations, rapid environmental responses, and long-term changes-converging into this state space in common. These findings suggest that daily fluctuations may predict broader ecosystem changes. Our experimental insights, coupled with an exploration of living systems' information dynamics from an ecosystem perspective, enhance our predictive capabilities for natural ecosystem behavior, providing a universal framework for understanding a broad spectrum of living systems.

Linking genotypic and phenotypic changes in the E. coli long-term evolution experiment using metabolomics

Changes in an organism's environment, genome, or gene expression patterns can lead to changes in its metabolism. The metabolic phenotype can be under selection and contributes to adaptation. However, the networked and convoluted nature of an organism's metabolism makes relating mutations, metabolic changes, and effects on fitness challenging. To overcome this challenge, we use the long-term evolution experiment (LTEE) with E. coli as a model to understand how mutations can eventually affect metabolism and perhaps fitness. We used mass spectrometry to broadly survey the metabolomes of the ancestral strains and all 12 evolved lines. We combined this metabolic data with mutation and expression data to suggest how mutations that alter specific reaction pathways, such as the biosynthesis of nicotinamide adenine dinucleotide, might increase fitness in the system. Our work provides a better understanding of how mutations might affect fitness through the metabolic changes in the LTEE and thus provides a major step in developing a complete genotype-phenotype map for this experimental system.

Promoter capture drives the emergence of proto-genes in Escherichia coli

The phenomenon of de novo gene birth-the emergence of genes from non-genic sequences-has received considerable attention due to the widespread occurrence of genes that are unique to particular species or genomes. Most instances of de novo gene birth have been recognized through comparative analyses of genome sequences in eukaryotes, despite the abundance of novel, lineage-specific genes in bacteria and the relative ease with which bacteria can be studied in an experimental context. Here, we explore the genetic record of the Escherichia coli Long-Term Evolution Experiment (LTEE) for changes indicative of "proto-genic" phases of new gene birth in which non-genic sequences evolve stable transcription and/or translation. Over the time-span of the LTEE, non-genic regions are frequently transcribed, translated and differentially expressed, thereby serving as raw material for new gene emergence. Most proto-genes result either from insertion element activity or chromosomal translocations that fused pre-existing regulatory sequences to regions that were not expressed in the LTEE ancestor. Additionally, we identified instances of proto-gene emergence in which a previously unexpressed sequence was transcribed after formation of an upstream promoter. Tracing the origin of the causative mutations, we discovered that most occurred early in the history of the LTEE, often within the first 20,000 generations, and became fixed soon after emergence. Our findings show that proto-genes emerge frequently within evolving populations, persist stably, and can serve as potential substrates for new gene formation.

Despite genetic isolation in sympatry, post-copulatory reproductive barriers have not evolved between bat- and human-associated common bedbugs (Cimex lectularius L.)

BACKGROUND

The common bedbug Cimex lectularius is a widespread ectoparasite on humans and bats. Two genetically isolated lineages, parasitizing either human (HL) or bat (BL) hosts, have been suggested to differentiate because of their distinct ecology. The distribution range of BL is within that of HL and bedbugs live mostly on synanthropic bat hosts. This sympatric co-occurrence predicts strong reproductive isolation at the post-copulatory level.

RESULTS

We tested the post-copulatory barrier in three BL and three HL populations in reciprocal crosses, using a common-garden blood diet that was novel to both lineages. We excluded pre-copulation isolation mechanisms and studied egg-laying rates after a single mating until the depletion of sperm, and the fitness of the resulting offspring. We found a higher sperm storage capability in BL, likely reflecting the different seasonal availability of HL and BL hosts. We also observed a notable variation in sperm function at the population level within lineages and significant differences in fecundity and offspring fitness between lineages. However, no difference in egg numbers or offspring fitness was observed between within- and between-lineage crosses.

CONCLUSIONS

Differences in sperm storage or egg-laying rates between HL and BL that we found did not affect reproductive isolation. Neither did the population-specific variation in sperm function. Overall, our results show no post-copulatory reproductive isolation between the lineages. How genetic differentiation in sympatry is maintained in the absence of a post-copulatory barrier between BL and HL remains to be investigated.

Evolutionary rescue on genotypic fitness landscapes

Populations facing adverse environments, novel pathogens or invasive competitors may be destined to extinction if they are unable to adapt rapidly. Quantitative predictions of the probability of survival through adaptation, evolutionary rescue, have been previously developed for one of the most natural and well-studied mappings from an organism's traits to its fitness, Fisher's geometric model (FGM). While FGM assumes that all possible trait values are accessible via mutation, in many applications only a finite set of rescue mutations will be available, such as mutations conferring resistance to a parasite, predator or toxin. We predict the probability of evolutionary rescue, via de novo mutation, when this underlying genetic structure is included. We find that rescue probability is always reduced when its genetic basis is taken into account. Unlike other known features of the genotypic FGM, however, the probability of rescue increases monotonically with the number of available mutations and approaches the behaviour of the classical FGM as the number of available mutations approaches infinity.

Species and condition shape the mutational spectrum in experimentally evolved biofilms

IMPORTANCE

Biofilm formation is a vital factor for the survival and adaptation of bacteria in diverse environmental niches. Experimental evolution combined with the advancement of whole-population genome sequencing provides us a powerful tool to understand the genomic dynamic of evolutionary adaptation to different environments, such as during biofilm development. Previous studies described the genetic and phenotypic changes of selected clones from experimentally evolved Bacillus thuringiensis and Bacillus subtilis that were adapted under abiotic and biotic biofilm conditions. However, the full understanding of the dynamic evolutionary landscapes was lacking. Furthermore, the differences and similarities of adaptive mechanisms in B. thuringiensis and B. subtilis were not identified. To overcome these limitations, we performed longitudinal whole-population genome sequencing to study the underlying genetic dynamics at high resolution. Our study provides the first comprehensive mutational landscape of two bacterial species' biofilms that is adapted to an abiotic and biotic surface.

Native microbiome dominates over host factors in shaping the probiotic genetic evolution in the gut

Probiotics often acquire potentially adaptive mutations in vivo, gaining new functional traits through gut selection. While both the host and microbiome can contribute to probiotics' genetic evolution, separating the microbiome and the host's contribution to such selective pressures remains challenging. Here, we introduced germ-free (GF) and specific pathogen-free (SPF) mouse models to track how probiotic strains, i.e., Lactiplantibacillus plantarum HNU082 (Lp082) and Bifidobacterium animalis subsp. lactis V9 (BV9), genetically evolved under selection pressures derived from host factors alone and both host and microbial ecological factors. Notably, compared to the genome of a probiotic strain before consumption, the host only elicited <15 probiotic mutations in probiotic genomes that emerged in the luminal environment of GF mice, while a total of 840 mutations in Lp082 mutants and 21,579 mutations in BV9 were found in SPF mice, <0.25% of those derived from both factors that were never captured by other experimental evolution studies, indicating that keen microbial competitions exhibited the predominant evolutionary force in shaping probiotic genetic composition (>99.75%). For a given probiotic, functional genes occurring in potentially adaptive mutations induced by hosts (GF mice) were all shared with those found in mutants of SPF mice. Collectively, the native microbiome consistently drove a more rapid and divergent genetic evolution of probiotic strains in seven days of colonization than host factors did. Our study further laid a theoretical foundation for genetically engineering probiotics for better gut adaptation through in vitro artificial gut ecosystems without the selection pressures derived from host factors.

The Past Contribution and Future Fate of Genetic Variants under Climate Change in an Island Population of Musa itinerans

AbstractGenetic variation within species is crucial for sessile species to adapt to novel environments when facing dramatic climate changes. However, the debate continues whether standing ancestral variation adaptive to current environmental variability is sufficient to guarantee future suitability. Using wild banana Musa itinerans, we investigated the relative contribution of standing ancestral variation versus new mutations to environmental adaptation and inferred their future fate. On the continental island of Taiwan, local populations immigrated from the Southeast Asian continent during the ice age and have been isolated since then. This allows the classification of genetic variants into standing ancestral variation (polymorphic in Taiwan and the continent) and new mutations (polymorphic only in Taiwan). For temperature-related variables where Taiwan is mainly within the ancestral climatic range, standing ancestral variation had a slightly stronger association than new mutations. New mutations were more important for precipitation-related variables, where northeastern Taiwan had much more winter rainfall than most of continental Southeast Asia. Upon future climate change, new mutations showed higher genetic offset in regions of abrupt transition between allele frequency and local environments, suggesting their greater spatial heterogeneity of future vulnerability.

ShinyBioHEAT: an interactive shiny app to identify phenotype driver genes in E.coli and B.subtilis

SUMMARY

In any population under selective pressure, a central challenge is to distinguish the genes that drive adaptation from others which, subject to population variation, harbor many neutral mutations de novo. We recently showed that such genes could be identified by supplementing information on mutational frequency with an evolutionary analysis of the likely functional impact of coding variants. This approach improved the discovery of driver genes in both lab-evolved and environmental Escherichia coli strains. To facilitate general adoption, we now developed ShinyBioHEAT, an R Shiny web-based application that enables identification of phenotype driving gene in two commonly used model bacteria, E.coli and Bacillus subtilis, with no specific computational skill requirements. ShinyBioHEAT not only supports transparent and interactive analysis of lab evolution data in E.coli and B.subtilis, but it also creates dynamic visualizations of mutational impact on protein structures, which add orthogonal checks on predicted drivers.

AVAILABILITY AND IMPLEMENTATION

Code for ShinyBioHEAT is available at https://github.com/LichtargeLab/ShinyBioHEAT. The Shiny application is additionally hosted at http://bioheat.lichtargelab.org/.

Revisiting the Design of the Long-Term Evolution Experiment with Escherichia coli

The long-term evolution experiment (LTEE) with Escherichia coli began in 1988 and it continues to this day, with its 12 populations having recently reached 75,000 generations of evolution in a simple, well-controlled environment. The LTEE was designed to explore open-ended questions about the dynamics and repeatability of phenotypic and genetic evolution. Here I discuss various aspects of the LTEE's experimental design that have enabled its stability and success, including the choices of the culture regime, growth medium, ancestral strain, and statistical replication. I also discuss some of the challenges associated with a long-running project, such as handling procedural errors (e.g., cross-contamination) and managing the expanding collection of frozen samples. The simplicity of the experimental design and procedures have supported the long-term stability of the LTEE. That stability-along with the inherent creativity of the evolutionary process and the emergence of new genomic technologies-provides a platform that has allowed talented students and collaborators to pose questions, collect data, and make discoveries that go far beyond anything I could have imagined at the start of the LTEE.

Regulation of chromatin organization during animal regeneration

Activation of regeneration upon tissue damages requires the activation of many developmental genes responsible for cell proliferation, migration, differentiation, and tissue patterning. Ample evidence revealed that the regulation of chromatin organization functions as a crucial mechanism for establishing and maintaining cellular identity through precise control of gene transcription. The alteration of chromatin organization can lead to changes in chromatin accessibility and/or enhancer-promoter interactions. Like embryogenesis, each stage of tissue regeneration is accompanied by dynamic changes of chromatin organization in regeneration-responsive cells. In the past decade, many studies have been conducted to investigate the contribution of chromatin organization during regeneration in various tissues, organs, and organisms. A collection of chromatin regulators were demonstrated to play critical roles in regeneration. In this review, we will summarize the progress in the understanding of chromatin organization during regeneration in different research organisms and discuss potential common mechanisms responsible for the activation of regeneration response program.

Identifying Targets of Selection in Laboratory Evolution Experiments

Adaptive evolution navigates a balance between chance and determinism. The stochastic processes of mutation and drift generate phenotypic variation; however, once mutations reach an appreciable frequency in the population, their fate is governed by the deterministic action of selection, enriching for favorable genotypes and purging the less-favorable ones. The net result is that replicate populations will traverse similar-but not identical-pathways to higher fitness. This parallelism in evolutionary outcomes can be leveraged to identify the genes and pathways under selection. However, distinguishing between beneficial and neutral mutations is challenging because many beneficial mutations will be lost due to drift and clonal interference, and many neutral (and even deleterious) mutations will fix by hitchhiking. Here, we review the best practices that our laboratory uses to identify genetic targets of selection from next-generation sequencing data of evolved yeast populations. The general principles for identifying the mutations driving adaptation will apply more broadly.

Interaction between mutation type and gene pleiotropy drives parallel evolution in the laboratory

What causes evolution to be repeatable is a fundamental question in evolutionary biology. Pleiotropy, i.e. the effect of an allele on multiple traits, is thought to enhance repeatability by constraining the number of available beneficial mutations. Additionally, pleiotropy may promote repeatability by allowing large fitness benefits of single mutations via adaptive combinations of phenotypic effects. Yet, this latter evolutionary potential may be reaped solely by specific types of mutations able to realize optimal combinations of phenotypic effects while avoiding the costs of pleiotropy. Here, we address the interaction of gene pleiotropy and mutation type on evolutionary repeatability in a meta-analysis of experimental evolution studies with Escherichia coli. We hypothesize that single nucleotide polymorphisms (SNPs) are principally able to yield large fitness benefits by targeting highly pleiotropic genes, whereas indels and structural variants (SVs) provide smaller benefits and are restricted to genes with lower pleiotropy. By using gene connectivity as proxy for pleiotropy, we show that non-disruptive SNPs in highly pleiotropic genes yield the largest fitness benefits, since they contribute more to parallel evolution, especially in large populations, than inactivating SNPs, indels and SVs. Our findings underscore the importance of considering genetic architecture together with mutation type for understanding evolutionary repeatability. This article is part of the theme issue 'Interdisciplinary approaches to predicting evolutionary biology'.

Linking genotypic and phenotypic changes in the E. coli Long-Term Evolution Experiment using metabolomics

Changes in an organism's environment, genome, or gene expression patterns can lead to changes in its metabolism. The metabolic phenotype can be under selection and contributes to adaptation. However, the networked and convoluted nature of an organism's metabolism makes relating mutations, metabolic changes, and effects on fitness challenging. To overcome this challenge, we use the Long-Term Evolution Experiment (LTEE) with E. coli as a model to understand how mutations can eventually affect metabolism and perhaps fitness. We used mass-spectrometry to broadly survey the metabolomes of the ancestral strains and all 12 evolved lines. We combined this metabolic data with mutation and expression data to suggest how mutations that alter specific reaction pathways, such as the biosynthesis of nicotinamide adenine dinucleotide, might increase fitness in the system. Our work provides a better understanding of how mutations might affect fitness through the metabolic changes in the LTEE and thus provides a major step in developing a complete genotype-phenotype map for this experimental system.

Application of Adaptive Laboratory Evolution in Lipid and Terpenoid Production in Yeast and Microalgae

Due to the complexity of metabolic and regulatory networks in microorganisms, it is difficult to obtain robust phenotypes through artificial rational design and genetic perturbation. Adaptive laboratory evolution (ALE) engineering plays an important role in the construction of stable microbial cell factories by simulating the natural evolution process and rapidly obtaining strains with stable traits through screening. This review summarizes the application of ALE technology in microbial breeding, describes the commonly used methods for ALE, and highlights the important applications of ALE technology in the production of lipids and terpenoids in yeast and microalgae. Overall, ALE technology provides a powerful tool for the construction of microbial cell factories, and it has been widely used in improving the level of target product synthesis, expanding the range of substrate utilization, and enhancing the tolerance of chassis cells. In addition, in order to improve the production of target compounds, ALE also employs environmental or nutritional stress strategies corresponding to the characteristics of different terpenoids, lipids, and strains.

Carriage of Extended Spectrum Beta Lactamase-Producing Escherichia coli: Prevalence and Factors Associated with Fecal Colonization of Dogs from a Pet Clinic in Lower Saxony, Germany

Extended spectrum beta-lactamase (ESBL)-producing Escherichia coli are an emerging problem in veterinary and human medicine. Our study concentrated on the estimation of the prevalence and factors associated with the carriage of ESBL-producing E. coli in dogs who visited a veterinary clinic in northern Germany in 2017. For this reason, 1000 patients (healthy and sick dogs) were tested, resulting in 1000 samples originating from rectal swabs. Additional data were collected using a self-reported questionnaire that was completed by the dog owner. Factors associated with ESBL carriage were considered for further modeling if p < 0.05 using a two-sided Fisher test. Using a backward elimination procedure, the variables for the final multivariable logistic regression model were identified. In total, 8.9% of the dogs tested were positive for carriage of ESBL-producing E. coli. Seven factors were associated with the colonization of dogs with ESBL-E. coli within the multivariable model, namely husbandry system (p = 0.0019, OR = 3.00; 95% CI: 1.50-6.00), contact with puppies (p = 0.0044, OR = 2.43; 95% CI: 1.32-4.46), feeding of raw meat (p = 0.011, OR = 2.28; 95% CI: 1.21-4.31), food residues (p = 0.0151, OR = 2.31; 95% CI: 1.18-4.53) and food supplements (p = 0.0487, OR = 0.426; 95% CI: 0.18-0.96), and antibiotic treatments of dogs (p = 0.0005, OR = 3.030; 95% CI: 1.62-5.68) or owners (p = 0.041, OR = 2.74; 95% CI: 1.04-7.19) prior to the study. These factors refer to the animals themselves as well as to the owners and their habits or medical treatments. Although the causality and direction of transmission from owners to their dogs cannot be proven, the factor of antibiotic treatment of the owner is clearly associated with the dog's status.

What Has Genomics Taught An Evolutionary Biologist?

Genomics, an interdisciplinary field of biology on the structure, function, and evolution of genomes, has revolutionized many subdisciplines of life sciences, including my field of evolutionary biology, by supplying huge data, bringing high-throughput technologies, and offering a new approach to biology. In this review, I describe what I have learned from genomics and highlight the fundamental knowledge and mechanistic insights gained. I focus on three broad topics that are central to evolutionary biology and beyond-variation, interaction, and selection-and use primarily my own research and study subjects as examples. In the next decade or two, I expect that the most important contributions of genomics to evolutionary biology will be to provide genome sequences of nearly all known species on Earth, facilitate high-throughput phenotyping of natural variants and systematically constructed mutants for mapping genotype-phenotype-fitness landscapes, and assist the determination of causality in evolutionary processes using experimental evolution.

Plasticity and Stereotypic Rewiring of the Transcriptome Upon Bacterial Evolution of Antibiotic Resistance

Bacterial evolution of antibiotic resistance frequently has deleterious side effects on microbial growth, virulence, and susceptibility to other antimicrobial agents. However, it is unclear how these trade-offs could be utilized for manipulating antibiotic resistance in the clinic, not least because the underlying molecular mechanisms are poorly understood. Using laboratory evolution, we demonstrate that clinically relevant resistance mutations in Escherichia coli constitutively rewire a large fraction of the transcriptome in a repeatable and stereotypic manner. Strikingly, lineages adapted to functionally distinct antibiotics and having no resistance mutations in common show a wide range of parallel gene expression changes that alter oxidative stress response, iron homeostasis, and the composition of the bacterial outer membrane and cell surface. These common physiological alterations are associated with changes in cell morphology and enhanced sensitivity to antimicrobial peptides. Finally, the constitutive transcriptomic changes induced by resistance mutations are largely distinct from those induced by antibiotic stresses in the wild type. This indicates a limited role for genetic assimilation of the induced antibiotic stress response during resistance evolution. Our work suggests that diverse resistance mutations converge on similar global transcriptomic states that shape genetic susceptibility to antimicrobial compounds.

Parallel Evolution in Predatory Bdellovibrio sp. NC01 during Long-Term Coculture with a Single Prey Strain

Experimental evolution provides a powerful tool for examining how Bdellovibrio evolves in response to unique selective pressures associated with its predatory lifestyle. We tested how Bdellovibrio sp. NC01 adapts to long-term coculture with Pseudomonas sp. NC02, which is less susceptible to predation compared to other Gram-negative bacteria. Analyzing six replicate Bdellovibrio populations across six time points spanning 40 passages and 2,880 h of coculture, we detected 30 to 40 new mutations in each population that exceeded a frequency of 5%. Nonsynonymous substitutions were the most abundant type of new mutation, followed by small indels and synonymous substitutions. After completing the final passage, we detected 20 high-frequency (>75%) mutations across all six evolved Bdellovibrio populations. Eighteen of these alter protein sequences, and most increased in frequency rapidly. Four genes acquired a high-frequency mutation in two or more evolved Bdellovibrio populations, reflecting parallel evolution and positive selection. The genes encode a sodium/phosphate cotransporter family protein (Bd2221), a metallophosphoesterase (Bd0054), a TonB family protein (Bd0396), and a hypothetical protein (Bd1601). Tested prey range and predation efficiency phenotypes did not differ significantly between evolved Bdellovibrio populations and the ancestor; however, all six evolved Bdellovibrio populations demonstrated enhanced starvation survival compared to the ancestor. These results suggest that, instead of evolving improved killing of Pseudomonas sp. NC02, Bdellovibrio evolved to better withstand nutrient limitation in the presence of this prey strain. The mutations identified here point to genes and functions that may be important for Bdellovibrio adaptation to the different selective pressures of long-term coculture with Pseudomonas. IMPORTANCE Bdellovibrio attack and kill Gram-negative bacteria, including drug-resistant pathogens of animals and plants. This lifestyle is unusual among bacteria, and it imposes unique selective pressures on Bdellovibrio. Determining how Bdellovibrio evolve in response to these pressures is valuable for understanding the mechanisms that govern predation. We applied experimental evolution to test how Bdellovibrio sp. NC01 evolved in response to long-term coculture with a single Pseudomonas strain, which NC01 can kill, but with low efficiency. Our experimental design imposed different selective pressures on the predatory bacteria and tracked the evolutionary trajectories of replicate Bdellovibrio populations. Using genome sequencing, we identified Bdellovibrio genes that acquired high-frequency mutations in two or more populations. Using phenotype assays, we determined that evolved Bdellovibrio populations did not improve their ability to kill Pseudomonas, but rather are better able to survive starvation. Overall, our results point to functions that may be important for Bdellovibrio adaptation.

Quantifying the local adaptive landscape of a nascent bacterial community

The fitness effects of all possible mutations available to an organism largely shape the dynamics of evolutionary adaptation. Yet, whether and how this adaptive landscape changes over evolutionary times, especially upon ecological diversification and changes in community composition, remains poorly understood. We sought to fill this gap by analyzing a stable community of two closely related ecotypes ("L" and "S") shortly after they emerged within the E. coli Long-Term Evolution Experiment (LTEE). We engineered genome-wide barcoded transposon libraries to measure the invasion fitness effects of all possible gene knockouts in the coexisting strains as well as their ancestor, for many different, ecologically relevant conditions. We find consistent statistical patterns of fitness effect variation across both genetic background and community composition, despite the idiosyncratic behavior of individual knockouts. Additionally, fitness effects are correlated with evolutionary outcomes for a number of conditions, possibly revealing shifting patterns of adaptation. Together, our results reveal how ecological and epistatic effects combine to shape the adaptive landscape in a nascent ecological community.

Gut microbe Lactiplantibacillus plantarum undergoes different evolutionary trajectories between insects and mammals

BACKGROUND

Animals form complex symbiotic associations with their gut microbes, whose evolution is determined by an intricate network of host and environmental factors. In many insects, such as Drosophila melanogaster, the microbiome is flexible, environmentally determined, and less diverse than in mammals. In contrast, mammals maintain complex multispecies consortia that are able to colonize and persist in the gastrointestinal tract. Understanding the evolutionary and ecological dynamics of gut microbes in different hosts is challenging. This requires disentangling the ecological factors of selection, determining the timescales over which evolution occurs, and elucidating the architecture of such evolutionary patterns.

RESULTS

We employ experimental evolution to track the pace of the evolution of a common gut commensal, Lactiplantibacillus plantarum, within invertebrate (Drosophila melanogaster) and vertebrate (Mus musculus) hosts and their respective diets. We show that in Drosophila, the nutritional environment dictates microbial evolution, while the host benefits L. plantarum growth only over short ecological timescales. By contrast, in a mammalian animal model, L. plantarum evolution results to be divergent between the host intestine and its diet, both phenotypically (i.e., host-evolved populations show higher adaptation to the host intestinal environment) and genomically. Here, both the emergence of hypermutators and the high persistence of mutated genes within the host's environment strongly differed from the low variation observed in the host's nutritional environment alone.

CONCLUSIONS

Our results demonstrate that L. plantarum evolution diverges between insects and mammals. While the symbiosis between Drosophila and L. plantarum is mainly determined by the host diet, in mammals, the host and its intrinsic factors play a critical role in selection and influence both the phenotypic and genomic evolution of its gut microbes, as well as the outcome of their symbiosis.

Experimental Evolution Reveals Unifying Systems-Level Adaptations but Diversity in Driving Genotypes

Genotype-fitness maps of evolution have been well characterized for biological components, such as RNA and proteins, but remain less clear for systems-level properties, such as those of metabolic and transcriptional regulatory networks. Here, we take multi-omics measurements of 6 different E. coli strains throughout adaptive laboratory evolution (ALE) to maximal growth fitness. The results show the following: (i) convergence in most overall phenotypic measures across all strains, with the notable exception of divergence in NADPH production mechanisms; (ii) conserved transcriptomic adaptations, describing increased expression of growth promoting genes but decreased expression of stress response and structural components; (iii) four groups of regulatory trade-offs underlying the adjustment of transcriptome composition; and (iv) correlates that link causal mutations to systems-level adaptations, including mutation-pathway flux correlates and mutation-transcriptome composition correlates. We thus show that fitness landscapes for ALE can be described with two layers of causation: one based on system-level properties (continuous variables) and the other based on mutations (discrete variables). IMPORTANCE Understanding the mechanisms of microbial adaptation will help combat the evolution of drug-resistant microbes and enable predictive genome design. Although experimental evolution allows us to identify the causal mutations underlying microbial adaptation, it remains unclear how causal mutations enable increased fitness and is often explained in terms of individual components (i.e., enzyme rate) as opposed to biological systems (i.e., pathways). Here, we find that causal mutations in E. coli are linked to systems-level changes in NADPH balance and expression of stress response genes. These systems-level adaptation patterns are conserved across diverse E. coli strains and thus identify cofactor balance and proteome reallocation as dominant constraints governing microbial adaptation.

Genome-scale top-down strategy to generate viable genome-reduced phages

Efforts have been made to reduce the genomes of living cells, but phage genome reduction remains challenging. It is of great interest to investigate whether genome reduction can make phages obtain new infectious properties. We developed a CRISPR/Cas9-based iterative phage genome reduction (CiPGr) approach and applied this to four distinct phages, thereby obtaining heterogeneous genome-reduced mutants. We isolated and sequenced 200 mutants with loss of up to 8-23% (3.3-35 kbp) of the original sequences. This allowed the identification of non-essential genes for phage propagation, although loss of these genes is mostly detrimental to phage fitness to various degrees. Notwithstanding this, mutants with higher infectious efficiency than their parental strains were characterized, indicating a trade-off between genome reduction and infectious fitness for phages. In conclusion, this study provides a foundation for future work to leverage the information generated by CiPGr in phage synthetic biology research.

Antibiotic Cycling Affects Resistance Evolution Independently of Collateral Sensitivity

Antibiotic cycling has been proposed as a promising approach to slow down resistance evolution against currently employed antibiotics. It remains unclear, however, to which extent the decreased resistance evolution is the result of collateral sensitivity, an evolutionary trade-off where resistance to one antibiotic enhances the sensitivity to the second, or due to additional effects of the evolved genetic background, in which mutations accumulated during treatment with a first antibiotic alter the emergence and spread of resistance against a second antibiotic via other mechanisms. Also, the influence of antibiotic exposure patterns on the outcome of drug cycling is unknown. Here, we systematically assessed the effects of the evolved genetic background by focusing on the first switch between two antibiotics against Salmonella Typhimurium, with cefotaxime fixed as the first and a broad variety of other drugs as the second antibiotic. By normalizing the antibiotic concentrations to eliminate the effects of collateral sensitivity, we demonstrated a clear contribution of the evolved genetic background beyond collateral sensitivity, which either enhanced or reduced the adaptive potential depending on the specific drug combination. We further demonstrated that the gradient strength with which cefotaxime was applied affected both cefotaxime resistance evolution and adaptation to second antibiotics, an effect that was associated with higher levels of clonal interference and reduced cost of resistance in populations evolved under weaker cefotaxime gradients. Overall, our work highlights that drug cycling can affect resistance evolution independently of collateral sensitivity, in a manner that is contingent on the antibiotic exposure pattern.

Adaptation in Outbred Sexual Yeast is Repeatable, Polygenic and Favors Rare Haplotypes

We carried out a 200 generation Evolve and Resequence (E&R) experiment initiated from an outbred diploid recombined 18-way synthetic base population. Replicate populations were evolved at large effective population sizes (>105 individuals), exposed to several different chemical challenges over 12 weeks of evolution, and whole-genome resequenced. Weekly forced outcrossing resulted in an average between adjacent-gene per cell division recombination rate of ∼0.0008. Despite attempts to force weekly sex, roughly half of our populations evolved cheaters and appear to be evolving asexually. Focusing on seven chemical stressors and 55 total evolved populations that remained sexual we observed large fitness gains and highly repeatable patterns of genome-wide haplotype change within chemical challenges, with limited levels of repeatability across chemical treatments. Adaptation appears highly polygenic with almost the entire genome showing significant and consistent patterns of haplotype change with little evidence for long-range linkage disequilibrium in a subset of populations for which we sequenced haploid clones. That is, almost the entire genome is under selection or drafting with selected sites. At any given locus adaptation was almost always dominated by one of the 18 founder's alleles, with that allele varying spatially and between treatments, suggesting that selection acts primarily on rare variants private to a founder or haplotype blocks harboring multiple mutations.

Extracellular Vesicles from 50,000 Generation Clones of the Escherichia coli Long-Term Evolution Experiment

Extracellular vesicles (EVs) are critical elements of cell-cell communication. Here, we characterized the outer membrane vesicles (OMVs) released by specific clones of Escherichia coli isolated from the Long-Term Evolution Experiment after 50,000 generations (50K) of adaptation to glucose minimal medium. Compared with their ancestor, the evolved clones produce small OMVs but also larger ones which display variable amounts of both OmpA and LPS. Tracking ancestral, fluorescently labelled OMVs revealed that they fuse with both ancestral- and 50K-evolved cells, albeit in different proportions. We quantified that less than 2% of the cells from one 50K-evolved clone acquired the fluorescence delivered by OMVs from the ancestral strain but that one cell concomitantly fuses with several OMVs. Globally, our results showed that OMV production in E. coli is a phenotype that varies along bacterial evolution and question the contribution of OMVs-mediated interactions in bacterial adaptation.

The landscape of transcriptional and translational changes over 22 years of bacterial adaptation

Organisms can adapt to an environment by taking multiple mutational paths. This redundancy at the genetic level, where many mutations have similar phenotypic and fitness effects, can make untangling the molecular mechanisms of complex adaptations difficult. Here, we use the Escherichia coli long-term evolution experiment (LTEE) as a model to address this challenge. To understand how different genomic changes could lead to parallel fitness gains, we characterize the landscape of transcriptional and translational changes across 12 replicate populations evolving in parallel for 50,000 generations. By quantifying absolute changes in mRNA abundances, we show that not only do all evolved lines have more mRNAs but that this increase in mRNA abundance scales with cell size. We also find that despite few shared mutations at the genetic level, clones from replicate populations in the LTEE are remarkably similar in their gene expression patterns at both the transcriptional and translational levels. Furthermore, we show that the majority of the expression changes are due to changes at the transcriptional level with very few translational changes. Finally, we show how mutations in transcriptional regulators lead to consistent and parallel changes in the expression levels of downstream genes. These results deepen our understanding of the molecular mechanisms underlying complex adaptations and provide insights into the repeatability of evolution.

Experimental test of the contributions of initial variation and new mutations to adaptive evolution in a novel environment

Experimental evolution is an approach that allows researchers to study organisms as they evolve in controlled environments. Despite the growing popularity of this approach, there are conceptual gaps among projects that use different experimental designs. One such gap concerns the contributions to adaptation of genetic variation present at the start of an experiment and that of new mutations that arise during an experiment. The primary source of genetic variation has historically depended largely on the study organisms. In the long-term evolution experiment (LTEE) using Escherichia coli, for example, each population started from a single haploid cell, and therefore, adaptation depended entirely on new mutations. Most other microbial evolution experiments have followed the same strategy. By contrast, evolution experiments using multicellular, sexually reproducing organisms typically start with preexisting variation that fuels the response to selection. New mutations may also come into play in later generations of these experiments, but it is generally difficult to quantify their contribution in these studies. Here, we performed an experiment using E. coli to compare the contributions of initial genetic variation and new mutations to adaptation in a new environment. Our experiment had four treatments that varied in their starting diversity, with 18 populations in each treatment. One treatment depended entirely on new mutations, while the other three began with mixtures of clones, whole-population samples, or mixtures of whole-population samples from the LTEE. We tracked a genetic marker associated with different founders in two treatments. These data revealed significant variation in fitness among the founders, and that variation impacted evolution in the early generations of our experiment. However, there were no differences in fitness among the treatments after 500 or 2,000 generations in the new environment, despite the variation in fitness among the founders. These results indicate that new mutations quickly dominated, and eventually they contributed more to adaptation than did the initial variation. Our study thus shows that preexisting genetic variation can have a strong impact on early evolution in a new environment, but new beneficial mutations may contribute more to later evolution and can even drive some initially beneficial variants to extinction.

Mutagenic Characteristics of Six Heavy Metals in Escherichia coli: The Commonality and Specificity

The history of long-term environmental exposure to heavy metals can be recorded in the genome as sporadic and specific mutations. Variable environments introduce diverse and adaptive mutations to organisms. To reveal the information hidden in genomes about environmental exposure to heavy metals, we performed long-term mutation accumulation (MA) experiments with Escherichia coli, analyzed genomes from 36 populations across 1650 generations with 6 heavy metal exposure regimes (arsenic, cadmium, chromium, copper, nickel, and lead), and inferred metal-specific evolution modes at the genomic level. All heavy metals induced genetic mutations with a mean rate of 3.459 × 10-9 per nucleotide per generation. The mutational spectrum exhibited distinct signatures; however, heavy metals also shared common mutation signatures prominently associated with all cancer types. The mutated genes showed an average similarity of 54.4% within the same exposure regime, whereas only 38.8% between exposure regimes. In terms of biological insights, mutated genes were enriched to fundamental cellular processes such as metabolism, motility, and transport. Our study elucidates the mutagenic commonality and specificity of environmental heavy metals, which are highly specific at mutational features and locus, but conserved at gene and functional levels, and may play crucial roles in the convergence of adaptation to heavy metals.

Two modes of evolution shape bacterial strain diversity in the mammalian gut for thousands of generations

How and at what pace bacteria evolve when colonizing healthy hosts remains unclear. Here, by monitoring evolution for more than six thousand generations in the mouse gut, we show that the successful colonization of an invader Escherichia coli depends on the diversity of the existing microbiota and the presence of a closely related strain. Following colonization, two modes of evolution were observed: one in which diversifying selection leads to long-term coexistence of ecotypes and a second in which directional selection propels selective sweeps. These modes can be quantitatively distinguished by the statistics of mutation trajectories. In our experiments, diversifying selection was marked by the emergence of metabolic mutations, and directional selection by acquisition of prophages, which bring their own benefits and costs. In both modes, we observed parallel evolution, with mutation accumulation rates comparable to those typically observed in vitro on similar time scales. Our results show how rapid ecotype formation and phage domestication can be in the mammalian gut.

Here, the authors show that a colonizing bacterial strain evolves in the gut by either generating ecotypes or continuously fixing beneficial mutations. They associate the first mode to metabolic mutations and the second to domestication of bacteriophages that are incorporated into the bacterial genome.

Purifying selection enduringly acts on the sequence evolution of highly expressed proteins in Escherichia coli

The evolutionary speed of a protein sequence is constrained by its expression level, with highly expressed proteins evolving relatively slowly. This negative correlation between expression levels and evolutionary rates (known as the E–R anticorrelation) has already been widely observed in past macroevolution between species from bacteria to animals. However, it remains unclear whether this seemingly general law also governs recent evolution, including past and de novo, within a species. However, the advent of genomic sequencing and high-throughput phenotyping, particularly for bacteria, has revealed fundamental gaps between the 2 evolutionary processes and has provided empirical data opposing the possible underlying mechanisms which are widely believed. These conflicts raise questions about the generalization of the E–R anticorrelation and the relevance of plausible mechanisms. To explore the ubiquitous impact of expression levels on molecular evolution and test the relevance of the possible underlying mechanisms, we analyzed the genome sequences of 99 strains of Escherichia coli for evolution within species in nature. We also analyzed genomic mutations accumulated under laboratory conditions as a model of de novo evolution within species. Here, we show that E–R anticorrelation is significant in both past and de novo evolution within species in E. coli. Our data also confirmed ongoing purifying selection on highly expressed genes. Ongoing selection included codon-level purifying selection, supporting the relevance of the underlying mechanisms. However, the impact of codon-level purifying selection on the constraints in evolution within species might be smaller than previously expected from evolution between species.

Single-cell genomics reveals population structures from in vitro evolutionary studies of Salmonella

Single-cell DNA sequencing has the potential to reveal detailed hierarchical structures in evolving populations of cells. Single cell approaches are increasingly used to study clonal evolution in human ageing and cancer but have not yet been deployed to study evolving clonal microbial populations. Here, we present an approach for single bacterial genomic analysis for in vitro evolution experiments using FACS isolation of individual bacteria followed by whole-genome amplification and sequencing. We apply this to the experimental evolution of a hypermutator strain of Salmonella in response to antibiotic stress (ciprofloxacin). By analysing sequence polymorphisms in individual cells from populations we identified the presence and prevalence of sub-populations which have acquired polymorphisms in genes previously demonstrated to be associated with ciprofloxacin susceptibility. We were also able to identify that the population exposed to antibiotic stress was able to develop resistance whilst maintaining diversity. This population structure could not be resolved from bulk sequence data, and our results show how high-throughput single-cell sequencing can enhance experimental studies of bacterial evolution.

Discovery of positive and purifying selection in metagenomic time series of hypermutator microbial populations

A general method to infer both positive and purifying selection during the real-time evolution of hypermutator pathogens would be broadly useful. To this end, we introduce a Simple Test to Infer Mode of Selection (STIMS) from metagenomic time series of evolving microbial populations. We test STIMS on metagenomic data generated by simulations of bacterial evolution, and on metagenomic data spanning 62,750 generations of Lenski’s long-term evolution experiment with Escherichia coli (LTEE). This benchmarking shows that STIMS detects positive selection in both nonmutator and hypermutator populations, and purifying selection in hypermutator populations. Using STIMS, we find strong evidence of ongoing positive selection on key regulators of the E. coli gene regulatory network, even in some hypermutator populations. STIMS also detects positive selection on regulatory genes in hypermutator populations of Pseudomonas aeruginosa that adapted to subinhibitory concentrations of colistin–an antibiotic of last resort–for just twenty-six days of laboratory evolution. Our results show that the fine-tuning of gene regulatory networks is a general mechanism for rapid and ongoing adaptation. The simplicity of STIMS, together with its intuitive visual interpretation, make it a useful test for positive and purifying selection in metagenomic data sets that track microbial evolution in real-time.

Organisms often evolve elevated mutation rates as they adapt to new environments. That said, the genomic basis of adaptation in asexual hypermutator populations has been difficult to discern, because the few mutations driving adaptation are often associated with large numbers of non-adaptive “hitchhiker” mutations elsewhere in the genome. To address this research gap, we present a Simple Test to Infer Mode of Selection (STIMS) which aggregates the overall signature of selection seen over hundreds of genes. Using STIMS, we find strong positive selection on key regulators of the E. coli gene regulatory network across nonmutator and hypermutator populations of Lenski’s long-term evolution experiment with Escherichia coli. We also find positive selection on regulatory genes in populations of Pseudomonas aeruginosa that evolved hypermutability as they evolved to resist colistin, an antibiotic of last resort. Our work shows that positive and purifying selection can be resolved in hypermutator populations, given sufficient genomic data, and show that regulatory mutations are a major driver of adaptation in experimental populations of microbes.

Idiosyncratic Purifying Selection on Metabolic Enzymes in the Long-Term Evolution Experiment with Escherichia coli

Bacteria, Archaea, and Eukarya all share a common set of metabolic reactions. This implies that the function and topology of central metabolism has been evolving under purifying selection over deep time. Central metabolism may similarly evolve under purifying selection during long-term evolution experiments, although it is unclear how long such experiments would have to run (decades, centuries, millennia) before signs of purifying selection on metabolism appear. I hypothesized that central and superessential metabolic enzymes would show evidence of purifying selection in the long-term evolution experiment with Escherichia coli (LTEE). I also hypothesized that enzymes that specialize on single substrates would show stronger evidence of purifying selection in the LTEE than generalist enzymes that catalyze multiple reactions. I tested these hypotheses by analyzing metagenomic time series covering 62,750 generations of the LTEE. I find mixed support for these hypotheses, because the observed patterns of purifying selection are idiosyncratic and population-specific. To explain this finding, I propose the Jenga hypothesis, named after a children's game in which blocks are removed from a tower until it falls. The Jenga hypothesis postulates that loss-of-function mutations degrade costly, redundant, and non-essential metabolic functions. Replicate populations can therefore follow idiosyncratic trajectories of lost redundancies, despite purifying selection on overall function. I tested the Jenga hypothesis by simulating the evolution of 1,000 minimal genomes under strong purifying selection. As predicted, the minimal genomes converge to different metabolic networks. Strikingly, the core genes common to all 1,000 minimal genomes show consistent signatures of purifying selection in the LTEE.