Genome dynamics during experimental evolution

Performance of Saccharomyces cerevisiae strains against the application of adaptive laboratory evolution strategies for butanol tolerance

Although the industrial production of butanol has been carried out for decades by bacteria of the Clostridium species, recent studies have shown the use of the yeast Saccharomyces cerevisiae as a promising alternative. While the production of n-butanol by this yeast is still very far from its tolerability (up to 2% butanol), the improvement in the tolerance can lead to an increase in butanol production. The aim of the present work was to evaluate the adaptive capacity of the laboratory strain X2180-1B and the Brazilian ethanol-producing strain CAT-1 when submitted to two strategies of adaptive laboratory Evolution (ALE) in butanol. The strains were submitted, in parallel, to ALE with successive passages or with UV irradiation, using 1% butanol as selection pressure. Despite initially showing greater tolerance to butanol, the CAT-1 strain did not show great improvements after being submitted to ALE. Already the laboratory strain X2180-1B showed an incredible increase in butanol tolerance, starting from a condition of inability to grow in 1% butanol, to the capacity to grow in this same condition. With emphasis on the X2180_n100#28 isolated colony that presented the highest maximum specific growth rate among all isolated colonies, we believe that this colony has good potential to be used as a model yeast for understanding the mechanisms that involve tolerance to alcohols and other inhibitory compounds.

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.

Genomic Modifications of Lactic Acid Bacteria and Their Applications in Dairy Fermentation

Lactic Acid Bacteria (LAB) have a long history of safe use in milk fermentation and are generally recognized as health-promoting microorganisms when present in fermented foods. LAB are also important components of the human intestinal microbiota and are widely used as probiotics. Considering their safe and health-beneficial properties, LAB are considered appropriate vehicles that can be genetically modified for food, industrial and pharmaceutical applications. Here, this review describes (1) the potential opportunities for application of genetically modified LAB strains in dairy fermentation and (2) the various genomic modification tools for LAB strains, such as random mutagenesis, adaptive laboratory evolution, conjugation, homologous recombination, recombineering, and CRISPR (clustered regularly interspaced short palindromic repeat)- Cas (CRISPR-associated protein) based genome engineering. Lastly, this review also discusses the potential future developments of these genomic modification technologies and their applications in dairy fermentations.

Reversions mask the contribution of adaptive evolution in microbiomes

When examining bacterial genomes for evidence of past selection, the results obtained depend heavily on the mutational distance between chosen genomes. Even within a bacterial species, genomes separated by larger mutational distances exhibit stronger evidence of purifying selection as assessed byd N / d S , the normalized ratio of nonsynonymous to synonymous mutations. Here, we show that the classical interpretation of this scale-dependence, weak purifying selection, leads to problematic mutation accumulation when applied to available gut microbiome data. We propose an alternative, adaptive reversion model with exactly opposite implications for dynamical intuition and applications ofd N / d S . Reversions that occur and sweep within-host populations are nearly guaranteed in microbiomes due to large population sizes, short generation times, and variable environments. Using analytical and simulation approaches, we show that adaptive reversion can explain thed N / d S decay given only dozens of locally-fluctuating selective pressures, which is realistic in the context of Bacteroides genomes. The success of the adaptive reversion model argues for interpreting low values ofd N / d S obtained from long-time scales with caution, as they may emerge even when adaptive sweeps are frequent. Our work thus inverts the interpretation of an old observation in bacterial evolution, illustrates the potential of mutational reversions to shape genomic landscapes over time, and highlights the importance of studying bacterial genomic evolution on short time scales.

Synthetic genomes unveil the effects of synonymous recoding

Engineering the genetic code of an organism provides the basis for (i) making any organism safely resistant to natural viruses and (ii) preventing genetic information flow into and out of genetically modified organisms while (iii) allowing the biosynthesis of genetically encoded unnatural polymers1-4. Achieving these three goals requires the reassignment of multiple of the 64 codons nature uses to encode proteins. However, synonymous codon replacement-recoding-is frequently lethal, and how recoding impacts fitness remains poorly explored. Here, we explore these effects using whole-genome synthesis, multiplexed directed evolution, and genome-transcriptome-translatome-proteome co-profiling on multiple recoded genomes. Using this information, we assemble a synthetic Escherichia coli genome in seven sections using only 57 codons to encode proteins. By discovering the rules responsible for the lethality of synonymous recoding and developing a data-driven multi-omics-based genome construction workflow that troubleshoots synthetic genomes, we overcome the lethal effects of 62,007 synonymous codon swaps and 11,108 additional genomic edits. We show that synonymous recoding induces transcriptional noise including new antisense RNAs, leading to drastic transcriptome and proteome perturbation. As the elimination of select codons from an organism's genetic code results in the widespread appearance of cryptic promoters, we show that synonymous codon choice may naturally evolve to minimize transcriptional noise. Our work provides the first genome-scale description of how synonymous codon changes influence organismal fitness and paves the way for the construction of functional genomes that provide genetic firewalls from natural ecosystems and safely produce biopolymers, drugs, and enzymes with an expanded chemistry.

Temporal genomics in Hawaiian crickets reveals compensatory intragenomic coadaptation during adaptive evolution

Theory predicts that compensatory genetic changes reduce negative indirect effects of selected variants during adaptive evolution, but evidence is scarce. Here, we test this in a wild population of Hawaiian crickets using temporal genomics and a high-quality chromosome-level cricket genome. In this population, a mutation, flatwing, silences males and rapidly spread due to an acoustically-orienting parasitoid. Our sampling spanned a social transition during which flatwing fixed and the population went silent. We find long-range linkage disequilibrium around the putative flatwing locus was maintained over time, and hitchhiking genes had functions related to negative flatwing-associated effects. We develop a combinatorial enrichment approach using transcriptome data to test for compensatory, intragenomic coevolution. Temporal changes in genomic selection were distributed genome-wide and functionally associated with the population's transition to silence, particularly behavioural responses to silent environments. Our results demonstrate how 'adaptation begets adaptation'; changes to the sociogenetic environment accompanying rapid trait evolution can generate selection provoking further, compensatory adaptation.

Genomics of hybrid parallel origin in Aquilegia ecalcarata

BACKGROUND

The parallel evolution of similar traits or species provides strong evidence for the role of natural selection in evolution. Traits or species that evolved repeatedly can be driven by separate de novo mutations or interspecific gene flow. Although parallel evolution has been reported in many studies, documented cases of parallel evolution caused by gene flow are scarce by comparison. Aquilegia ecalcarata and A. kansuensis belong to the genus of Aquilegia, and are the closest related sister species. Mutiple origins of A. ecalcarata have been reported in previous studies, but whether they have been driven by separate de novo mutations or gene flow remains unclear.

RESULTS

In this study, We conducted genomic analysis from 158 individuals of two repeatedly evolving pairs of A. ecalcarata and A. kansuensis. All samples were divided into two distinct clades with obvious geographical distribution based on phylogeny and population structure. Demographic modeling revealed that the origin of the A. ecalcarata in the Eastern of China was caused by gene flow, and the Eastern A. ecalcarata occurred following introgression from Western A. ecalcarata population. Analysis of Treemix and D-statistic also revealed that a strong signal of gene flow was detected from Western A. ecalcarata to Eastern A. ecalcarata. Genetic divergence and selective sweep analyses inferred parallel regions of genomic divergence and identified many candidate genes associated with ecologically adaptive divergence between species pair. Comparative analysis of parallel diverged regions and gene introgression confirms that gene flow contributed to the parallel evolution of A. ecalcarata.

CONCLUSIONS

Our results further confirmed the multiple origins of A. ecalcarata and highlighted the roles of gene flow. These findings provide new evidence for parallel origin after hybridization as well as insights into the ecological adaptation mechanisms underlying the parallel origins of species.

A very brief note on why bacterial evolution has physiology

The majority of bacteria live and evolve in surface biofilms. Both growth in biofilms and horizontal transfer of DNA are regulated by quorum-sensing pheromone signals. The common regulation of bacterial surface growth and DNA transfers illustrates how physiology contributes to bacterial evolution.

Wild Patagonian yeast improve the evolutionary potential of novel interspecific hybrid strains for lager brewing

Lager yeasts are limited to a few strains worldwide, imposing restrictions on flavour and aroma diversity and hindering our understanding of the complex evolutionary mechanisms during yeast domestication. The recent finding of diverse S. eubayanus lineages from Patagonia offers potential for generating new lager yeasts with different flavour profiles. Here, we leverage the natural genetic diversity of S. eubayanus and expand the lager yeast repertoire by including three distinct Patagonian S. eubayanus lineages. We used experimental evolution and selection on desirable traits to enhance the fermentation profiles of novel S. cerevisiae x S. eubayanus hybrids. Our analyses reveal an intricate interplay of pre-existing diversity, selection on species-specific mitochondria, de-novo mutations, and gene copy variations in sugar metabolism genes, resulting in high ethanol production and unique aroma profiles. Hybrids with S. eubayanus mitochondria exhibited greater evolutionary potential and superior fitness post-evolution, analogous to commercial lager hybrids. Using genome-wide screens of the parental subgenomes, we identified genetic changes in IRA2, IMA1, and MALX genes that influence maltose metabolism, and increase glycolytic flux and sugar consumption in the evolved hybrids. Functional validation and transcriptome analyses confirmed increased maltose-related gene expression, influencing greater maltotriose consumption in evolved hybrids. This study demonstrates the potential for generating industrially viable lager yeast hybrids from wild Patagonian strains. Our hybridization, evolution, and mitochondrial selection approach produced hybrids with high fermentation capacity and expands lager beer brewing options.

Optimal trade-off between boosted tolerance and growth fitness during adaptive evolution of yeast to ethanol shocks

BACKGROUND

The selection of Saccharomyces cerevisiae strains with higher alcohol tolerance can potentially increase the industrial production of ethanol fuel. However, the design of selection protocols to obtain bioethanol yeasts with higher alcohol tolerance poses the challenge of improving industrial strains that are already robust to high ethanol levels. Furthermore, yeasts subjected to mutagenesis and selection, or laboratory evolution, often present adaptation trade-offs wherein higher stress tolerance is attained at the expense of growth and fermentation performance. Although these undesirable side effects are often associated with acute selection regimes, the utility of using harsh ethanol treatments to obtain robust ethanologenic yeasts still has not been fully investigated.

RESULTS

We conducted an adaptive laboratory evolution by challenging four populations (P1-P4) of the Brazilian bioethanol yeast, Saccharomyces cerevisiae PE-2_H4, through 68-82 cycles of 2-h ethanol shocks (19-30% v/v) and outgrowths. Colonies isolated from the final evolved populations (P1c-P4c) were subjected to whole-genome sequencing, revealing mutations in genes enriched for the cAMP/PKA and trehalose degradation pathways. Fitness analyses of the isolated clones P1c-P3c and reverse-engineered strains demonstrated that mutations were primarily selected for cell viability under ethanol stress, at the cost of decreased growth rates in cultures with or without ethanol. Under this selection regime for stress survival, the population P4 evolved a protective snowflake phenotype resulting from BUD3 disruption. Despite marked adaptation trade-offs, the combination of reverse-engineered mutations cyr1A1474T/usv1Δ conferred 5.46% higher fitness than the parental PE-2_H4 for propagation in 8% (v/v) ethanol, with only a 1.07% fitness cost in a culture medium without alcohol. The cyr1A1474T/usv1Δ strain and evolved P1c displayed robust fermentations of sugarcane molasses using cell recycling and sulfuric acid treatments, mimicking Brazilian bioethanol production.

CONCLUSIONS

Our study combined genomic, mutational, and fitness analyses to understand the genetic underpinnings of yeast evolution to ethanol shocks. Although fitness analyses revealed that most evolved mutations impose a cost for cell propagation, combination of key mutations cyr1A1474T/usv1Δ endowed yeasts with higher tolerance for growth in the presence of ethanol. Moreover, alleles selected for acute stress survival comprising the P1c genotype conferred stress tolerance and optimal performance under conditions simulating the Brazilian industrial ethanol production.

Mutation Rate and Effective Population Size of the Model Cooperative Bacterium Myxococcus xanthus

Intrinsic rates of genetic mutation have diverged greatly across taxa and exhibit statistical associations with several other parameters and features. These include effective population size (Ne), genome size, and gametic multicellularity, with the latter being associated with both increased mutation rates and decreased effective population sizes. However, data sufficient to test for possible relationships between microbial multicellularity and mutation rate (µ) are lacking. Here, we report estimates of two key population-genetic parameters, Ne and µ, for Myxococcus xanthus, a bacterial model organism for the study of aggregative multicellular development, predation, and social swarming. To estimate µ, we conducted an ∼400-day mutation accumulation experiment with 46 lineages subjected to regular single colony bottlenecks prior to clonal regrowth. Upon conclusion, we sequenced one clonal-isolate genome per lineage. Given collective evolution for 85,323 generations across all lines, we calculate a per base-pair mutation rate of ∼5.5 × 10-10 per site per generation, one of the highest mutation rates among free-living eubacteria. Given our estimate of µ, we derived Ne at ∼107 from neutral diversity at four-fold degenerate sites across two dozen M. xanthus natural isolates. This estimate is below average for eubacteria and strengthens an already clear negative correlation between µ and Ne in prokaryotes. The higher and lower than average mutation rate and Ne for M. xanthus, respectively, amplify the question of whether any features of its multicellular life cycle-such as group-size reduction during fruiting-body development-or its highly structured spatial distribution have significantly influenced how these parameters have evolved.

Base editor-mediated large-scale screening of functional mutations in bacteria for industrial phenotypes

Base editing, the targeted introduction of point mutations into cellular DNA, holds promise for improving genome-scale functional genome screening to single-nucleotide resolution. Current efforts in prokaryotes, however, remain confined to loss-of-function screens using the premature stop codons-mediated gene inactivation library, which falls far short of fully releasing the potential of base editors. Here, we developed a base editor-mediated functional single nucleotide variant screening pipeline in Escherichia coli. We constructed a library with 31,123 sgRNAs targeting 462 stress response-related genes in E. coli, and screened for adaptive mutations under isobutanol and furfural selective conditions. Guided by the screening results, we successfully identified several known and novel functional mutations. Our pipeline might be expanded to the optimization of other phenotypes or the strain engineering in other microorganisms.

Freshwater genome-reduced bacteria exhibit pervasive episodes of adaptive stasis

The emergence of bacterial species is rooted in their inherent potential for continuous evolution and adaptation to an ever-changing ecological landscape. The adaptive capacity of most species frequently resides within the repertoire of genes encoding the secreted proteome (SP), as it serves as a primary interface used to regulate survival/reproduction strategies. Here, by applying evolutionary genomics approaches to metagenomics data, we show that abundant freshwater bacteria exhibit biphasic adaptation states linked to the eco-evolutionary processes governing their genome sizes. While species with average to large genomes adhere to the dominant paradigm of evolution through niche adaptation by reducing the evolutionary pressure on their SPs (via the augmentation of functionally redundant genes that buffer mutational fitness loss) and increasing the phylogenetic distance of recombination events, most of the genome-reduced species exhibit a nonconforming state. In contrast, their SPs reflect a combination of low functional redundancy and high selection pressure, resulting in significantly higher levels of conservation and invariance. Our findings indicate that although niche adaptation is the principal mechanism driving speciation, freshwater genome-reduced bacteria often experience extended periods of adaptive stasis. Understanding the adaptive state of microbial species will lead to a better comprehension of their spatiotemporal dynamics, biogeography, and resilience to global change.

Vaginal microbiomes show ethnic evolutionary dynamics and positive selection of Lactobacillus adhesins driven by a long-term niche-specific process

The vaginal microbiome's composition varies among ethnicities. However, the evolutionary landscape of the vaginal microbiome in the multi-ethnic context remains understudied. We perform a systematic evolutionary analysis of 351 vaginal microbiome samples from 35 multi-ethnic pregnant women, in addition to two validation cohorts, totaling 462 samples from 90 women. Microbiome alpha diversity and community state dynamics show strong ethnic signatures. Lactobacillaceae have a higher ratio of non-synonymous to synonymous polymorphism and lower nucleotide diversity than non-Lactobacillaceae in all ethnicities, with a large repertoire of positively selected genes, including the mucin-binding and cell wall anchor genes. These evolutionary dynamics are driven by the long-term evolutionary process unique to the human vaginal niche. Finally, we propose an evolutionary model reflecting the environmental niches of microbes. Our study reveals the extensive ethnic signatures in vaginal microbial ecology and evolution, highlighting the importance of studying the host-microbiome ecosystem from an evolutionary perspective.

Antibacterial activity of nonantibiotics is orthogonal to standard antibiotics

Numerous nonantibiotic drugs have potent antibacterial activity and can adversely affect the human microbiome. The mechanistic underpinning of this toxicity remains largely unknown. We investigated the antibacterial activity of 200 drugs using genetic screens with thousands of barcoded Escherichia coli knockouts. We analyzed 2 million gene-drug interactions underlying drug-specific toxicity. Network-based analysis of drug-drug similarities revealed that antibiotics clustered into modules that are consistent with the mode of action of their established classes, whereas nonantibiotics remained unconnected. Half of the nonantibiotics clustered into separate modules, potentially revealing shared and unexploited targets for new antimicrobials. Analysis of efflux systems revealed that they widely affect antibiotics and nonantibiotics alike, suggesting that the impact of nonantibiotics on antibiotic cross-resistance should be investigated closely in vivo.

The evolutionary genomics of adaptation to stress in wild rhizobium bacteria

Microbiota comprise the bulk of life's diversity, yet we know little about how populations of microbes accumulate adaptive diversity across natural landscapes. Adaptation to stressful soil conditions in plants provides seminal examples of adaptation in response to natural selection via allelic substitution. For microbes symbiotic with plants however, horizontal gene transfer allows for adaptation via gene gain and loss, which could generate fundamentally different evolutionary dynamics. We use comparative genomics and genetics to elucidate the evolutionary mechanisms of adaptation to physiologically stressful serpentine soils in rhizobial bacteria in western North American grasslands. In vitro experiments demonstrate that the presence of a locus of major effect, the nre operon, is necessary and sufficient to confer adaptation to nickel, a heavy metal enriched to toxic levels in serpentine soil, and a major axis of environmental soil chemistry variation. We find discordance between inferred evolutionary histories of the core genome and nreAXY genes, which often reside in putative genomic islands. This suggests that the evolutionary history of this adaptive variant is marked by frequent losses, and/or gains via horizontal acquisition across divergent rhizobium clades. However, different nre alleles confer distinct levels of nickel resistance, suggesting allelic substitution could also play a role in rhizobium adaptation to serpentine soil. These results illustrate that the interplay between evolution via gene gain and loss and evolution via allelic substitution may underlie adaptation in wild soil microbiota. Both processes are important to consider for understanding adaptive diversity in microbes and improving stress-adapted microbial inocula for human use.

Asynchronous abundance fluctuations can drive giant genotype frequency fluctuations

Large stochastic population abundance fluctuations are ubiquitous across the tree of life1-7, impacting the predictability of population dynamics and influencing eco-evolutionary outcomes. It has generally been thought that these large abundance fluctuations do not strongly impact evolution (in contrast to genetic drift), as the relative frequencies of alleles in the population will be unaffected if the abundance of all alleles fluctuate in unison. However, we argue that large abundance fluctuations can lead to significant genotype frequency fluctuations if different genotypes within a population experience these fluctuations asynchronously. By serially diluting mixtures of two closely related E. coli strains, we show that such asynchrony can occur, leading to giant frequency fluctuations that far exceed expectations from models of genetic drift. We develop a flexible, effective model that explains the abundance fluctuations as arising from correlated offspring numbers between individuals, and the large frequency fluctuations result from even slight decoupling in offspring numbers between genotypes. This model accurately describes the observed abundance and frequency fluctuation scaling behaviors. Our findings suggest chaotic dynamics underpin these giant fluctuations, causing initially similar trajectories to diverge exponentially; subtle environmental changes can be magnified, leading to batch correlations in identical growth conditions. Furthermore, we present evidence that such decoupling noise is also present in mixed-genotype S. cerevisiae populations. We demonstrate that such decoupling noise can strongly influence evolutionary outcomes, in a manner distinct from genetic drift. Given the generic nature of asynchronous fluctuations, we anticipate they are widespread in biological populations, significantly affecting evolutionary and ecological dynamics.

Genotype-by-environment interactions govern fitness changes associated with adaptive mutations in two-component response systems

Introduction: Two-component response systems (TCRS) are the main mechanism by which prokaryotes acclimate to changing environments. These systems are composed of a membrane bound histidine kinase (HK) that senses external signals and a response regulator (RR) that activates transcription of response genes. Despite their known role in acclimation, little is known about the role TCRS play in environmental adaptation. Several experimental evolution studies have shown the acquisition of mutations in TCRS during adaptation, therefore here we set out to characterize the adaptive mechanism resulting from these mutations and evaluate whether single nucleotide changes in one gene could induce variable genotype-by-environment (GxE) interactions. Methods: To do this, we assessed fitness changes and differential gene expression for four adaptive mutations in cusS, the gene that encodes the HK CusS, acquired by Escherichia coli during silver adaptation. Results: Fitness assays showed that as the environment changed, each mutant displayed a unique fitness profile with greatest fitness in the original selection environment. RNAseq then indicated that, in ± silver nitrate, each mutant induces a primary response that upregulates cusS, its RR cusR, and constitutively expresses the target response genes cusCFBA. This then induces a secondary response via differential expression of genes regulated by the CusR through TCRS crosstalk. Finally, each mutant undergoes fitness tuning through unique tertiary responses that result in gene expression patterns specific for the genotype, the environment and optimized for the original selection conditions. Discussion: This three-step response shows that different mutations in a single gene leads to individualized phenotypes governed by unique GxE interactions that not only contribute to transcriptional divergence but also to phenotypic plasticity.

Global regulator IrrE on stress tolerance: a review

Stress tolerance is a vital attribute for all living beings to cope with environmental adversities. IrrE (also named PprI) from Deinococcus radiodurans enhances resistance to extreme radiation stress by functioning as a global regulator, mediating the transcription of genes involved in deoxyribonucleic acid (DNA) damage response (DDR). The expression of IrrE augmented the resilience of various species to heat, radiation, oxidation, osmotic stresses and inhibitors, encompassing bacterial, fungal, plant, and mammalian cells. Moreover, IrrE was employed in a global regulator engineering strategy to broaden its applications in stress tolerance. The regulatory impacts of heterologously expressed IrrE have been investigated at the molecular and systems level, including the regulation of genes, proteins, modules, or pathways involved in DNA repair, detoxification proteins, protective molecules, native regulators and other aspects. In this review, we discuss the regulatory role and mechanism of IrrE in the antiradiation response of D. radiodurans. Furthermore, the applications and regulatory effects of heterologous expression of IrrE to enhance abiotic stress tolerance are summarized in particular.

Parallel evolution of the G protein-coupled receptor GrlG and the loss of fruiting body formation in the social amoeba Dictyostelium discoideum evolved under low relatedness

Aggregative multicellularity relies on cooperation among formerly independent cells to form a multicellular body. Previous work with Dictyostelium discoideum showed that experimental evolution under low relatedness profoundly decreased cooperation, as indicated by the loss of fruiting body formation in many clones and an increase of cheaters that contribute proportionally more to spores than to the dead stalk. Using whole-genome sequencing and variant analysis of these lines, we identified 38 single nucleotide polymorphisms in 29 genes. Each gene had 1 variant except for grlG (encoding a G protein-coupled receptor), which had 10 unique SNPs and 5 structural variants. Variants in the 5' half of grlG-the region encoding the signal peptide and the extracellular binding domain-were significantly associated with the loss of fruiting body formation; the association was not significant in the 3' half of the gene. These results suggest that the loss of grlG was adaptive under low relatedness and that at least the 5' half of the gene is important for cooperation and multicellular development. This is surprising given some previous evidence that grlG encodes a folate receptor involved in predation, which occurs only during the single-celled stage. However, non-fruiting mutants showed little increase in a parallel evolution experiment where the multicellular stage was prevented from happening. This shows that non-fruiting mutants are not generally selected by any predation advantage but rather by something-likely cheating-during the multicellular stage.

Master regulators of biological systems in higher dimensions

A longstanding goal of biology is to identify the key genes and species that critically impact evolution, ecology, and health. Network analysis has revealed keystone species that regulate ecosystems and master regulators that regulate cellular genetic networks. Yet these studies have focused on pairwise biological interactions, which can be affected by the context of genetic background and other species present, generating higher-order interactions. The important regulators of higher-order interactions are unstudied. To address this, we applied a high-dimensional geometry approach that quantifies epistasis in a fitness landscape to ask how individual genes and species influence the interactions in the rest of the biological network. We then generated and also reanalyzed 5-dimensional datasets (two genetic, two microbiome). We identified key genes (e.g., the rbs locus and pykF) and species (e.g., Lactobacilli) that control the interactions of many other genes and species. These higher-order master regulators can induce or suppress evolutionary and ecological diversification by controlling the topography of the fitness landscape. Thus, we provide a method and mathematical justification for exploration of biological networks in higher dimensions.

In Vitro Microevolution and Co-Selection Assessment of Florfenicol Impact on Escherichia coli Resistance Development

The issue of antimicrobial resistance is becoming an increasingly serious challenge in both human and veterinary medicine. Prudent antimicrobial use in veterinary medicine is warranted and supported by international guidelines, with the Antimicrobial Advice Ad Hoc Expert Group (AMEG) placing particular emphasis on the critically important group B antimicrobials. These antimicrobials are commonly employed, especially in the poultry and swine industry. The impact of florfenicol, a veterinary antibiotic, was studied on the resistance development of Escherichia coli. The aim of the study was to investigate the effect of the use of florfenicol on the development of phenotypic and genomic resistances, not only to the drug itself but also to other drugs. The minimum inhibitory concentrations (MICs) of the antibiotics were investigated at 1×, 10×, 100× and 1000× concentrations using the adapted Microbial Evolution and Growth Arena (MEGA-plate) method. The results demonstrate that florfenicol can select for resistance to fluoroquinolone antibiotics (167× MIC value increase) and cephalosporins (67× MIC value increase). A total of 44 antimicrobial resistance genes were identified, the majority of which were consistent across the samples. Chromosomal point mutations, including alterations in resistance-associated and regulatory genes (acrB, acrR, emrR and robA), are thought to trigger multiple drug efflux pump activations, leading to phenotypically increased resistance. The study underscores the impact of florfenicol and its role in the development of antimicrobial resistance, particularly concerning fluoroquinolone antibiotics and cephalosporins. This study is the first to report florfenicol's dose-dependent enhancement of other antibiotics' MICs, linked to mutations in SOS-box genes (mdtABC-tolC, emrAB-tolC and acrAB-tolC) and increased multidrug efflux pump genes. Mutations in the regulatory genes acrR, emrR and rpbA support the possibility of increased gene expression. The results are crucial for understanding antimicrobial resistance and its development, highlighting the promising potential of in vitro evolutionary and coselection studies for future research.

Selection of a de novo gene that can promote survival of Escherichia coli by modulating protein homeostasis pathways

Cellular novelty can emerge when non-functional loci become functional genes in a process termed de novo gene birth. But how proteins with random amino acid sequences beneficially integrate into existing cellular pathways remains poorly understood. We screened ~108 genes, generated from random nucleotide sequences and devoid of homology to natural genes, for their ability to rescue growth arrest of Escherichia coli cells producing the ribonuclease toxin MazF. We identified ~2,000 genes that could promote growth, probably by reducing transcription from the promoter driving toxin expression. Additionally, one random protein, named Random antitoxin of MazF (RamF), modulated protein homeostasis by interacting with chaperones, leading to MazF proteolysis and a consequent loss of its toxicity. Finally, we demonstrate that random proteins can improve during evolution by identifying beneficial mutations that turned RamF into a more efficient inhibitor. Our work provides a mechanistic basis for how de novo gene birth can produce functional proteins that effectively benefit cells evolving under stress.

Signification and Application of Mutator and Antimutator Phenotype-Induced Genetic Variations in Evolutionary Adaptation and Cancer Therapeutics

Mutations present a dichotomy in their implications for cellular processes. They primarily arise from DNA replication errors or damage repair processes induced by environmental challenges. Cumulative mutations underlie genetic variations and drive evolution, yet also contribute to degenerative diseases such as cancer and aging. The mutator phenotype elucidates the heightened mutation rates observed in malignant tumors. Evolutionary adaptation, analogous to bacterial and eukaryotic systems, manifests through mutator phenotypes during changing environmental conditions, highlighting the delicate balance between advantageous mutations and their potentially detrimental consequences. Leveraging the genetic tractability of Saccharomyces cerevisiae offers unique insights into mutator phenotypes and genome instability akin to human cancers. Innovative reporter assays in yeast model organisms enable the detection of diverse genome alterations, aiding a comprehensive analysis of mutator phenotypes. Despite significant advancements, our understanding of the intricate mechanisms governing spontaneous mutation rates and preserving genetic integrity remains incomplete. This review outlines various cellular pathways affecting mutation rates and explores the role of mutator genes and mutation-derived phenotypes, particularly prevalent in malignant tumor cells. An in-depth comprehension of mutator and antimutator activities in yeast and higher eukaryotes holds promise for effective cancer control strategies.

Dual thermal ecotypes coexist within a nearly genetically identical population of the unicellular marine cyanobacterium Synechococcus

The extent and ecological significance of intraspecific functional diversity within marine microbial populations is still poorly understood, and it remains unclear if such strain-level microdiversity will affect fitness and persistence in a rapidly changing ocean environment. In this study, we cultured 11 sympatric strains of the ubiquitous marine picocyanobacterium Synechococcus isolated from a Narragansett Bay (RI) phytoplankton community thermal selection experiment. Thermal performance curves revealed selection at cool and warm temperatures had subdivided the initial population into thermotypes with pronounced differences in maximum growth temperatures. Curiously, the genomes of all 11 isolates were almost identical (average nucleotide identities of >99.99%, with >99% of the genome aligning) and no differences in gene content or single nucleotide variants were associated with either cool or warm temperature phenotypes. Despite a very high level of genomic similarity, sequenced epigenomes for two strains showed differences in methylation on genes associated with photosynthesis. These corresponded to measured differences in photophysiology, suggesting a potential pathway for future mechanistic research into thermal microdiversity. Our study demonstrates that present-day marine microbial populations can harbor cryptic but environmentally relevant thermotypes which may increase their resilience to future rising temperatures.

Inference of the demographic histories and selective effects of human gut commensal microbiota over the course of human history

Despite the importance of gut commensal microbiota to human health, there is little knowledge about their evolutionary histories, including their population demographic histories and their distributions of fitness effects (DFE) of new mutations. Here, we infer the demographic histories and DFEs of 27 of the most highly prevalent and abundant commensal gut microbial species in North Americans over timescales exceeding human generations using a collection of lineages inferred from a panel of healthy hosts. We find overall reductions in genetic variation among commensal gut microbes sampled from a Western population relative to an African rural population. Additionally, some species in North American microbiomes display contractions in population size and others expansions, potentially occurring at several key historical moments in human history. DFEs across species vary from highly to mildly deleterious, with accessory genes experiencing more drift compared to core genes. Within genera, DFEs tend to be more congruent, reflective of underlying phylogenetic relationships. Taken together, these findings suggest that human commensal gut microbes have distinct evolutionary histories, possibly reflecting the unique roles of individual members of the microbiome.

Competitive interactions facilitate resistance development against antimicrobials

While the evolution of antimicrobial resistance is well studied in free-living bacteria, information on resistance development in dense and diverse biofilm communities is largely lacking. Therefore, we explored how the social interactions in a duo-species biofilm composed of the brewery isolates Pseudomonas rhodesiae and Raoultella terrigena influence the adaptation to the broad-spectrum antimicrobial sulfathiazole. Previously, we showed that the competition between these brewery isolates enhances the antimicrobial tolerance of P. rhodesiae. Here, we found that this enhanced tolerance in duo-species biofilms is associated with a strongly increased antimicrobial resistance development in P. rhodesiae. Whereas P. rhodesiae was not able to evolve resistance against sulfathiazole in monospecies conditions, it rapidly evolved resistance in the majority of the duo-species communities. Although the initial presence of R. terrigena was thus required for P. rhodesiae to acquire resistance, the resistance mechanisms did not depend on the presence of R. terrigena. Whole genome sequencing of resistant P. rhodesiae clones showed no clear mutational hot spots. This indicates that the acquired resistance phenotype depends on complex interactions between low-frequency mutations in the genetic background of the strains. We hypothesize that the increased tolerance in duo-species conditions promotes resistance by enhancing the selection of partially resistant mutants and opening up novel evolutionary trajectories that enable such genetic interactions. This hypothesis is reinforced by experimentally excluding potential effects of increased initial population size, enhanced mutation rate, and horizontal gene transfer. Altogether, our observations suggest that the community mode of life and the social interactions therein strongly affect the accessible evolutionary pathways toward antimicrobial resistance.IMPORTANCEAntimicrobial resistance is one of the most studied bacterial properties due to its enormous clinical and industrial relevance; however, most research focuses on resistance development of a single species in isolation. In the present study, we showed that resistance evolution of brewery isolates can differ greatly between single- and mixed-species conditions. Specifically, we observed that the development of antimicrobial resistance in certain species can be significantly enhanced in co-culture as compared to the single-species conditions. Overall, the current study emphasizes the need of considering the within bacterial interactions in microbial communities when evaluating antimicrobial treatments and resistance evolution.

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.

Phenotype Design Space Provides a Mechanistic Framework Relating Molecular Parameters to Phenotype Diversity Available for Selection

Two long-standing challenges in theoretical population genetics and evolution are predicting the distribution of phenotype diversity generated by mutation and available for selection, and determining the interaction of mutation, selection and drift to characterize evolutionary equilibria and dynamics. More fundamental for enabling such predictions is the current inability to causally link genotype to phenotype. There are three major mechanistic mappings required for such a linking - genetic sequence to kinetic parameters of the molecular processes, kinetic parameters to biochemical system phenotypes, and biochemical phenotypes to organismal phenotypes. This article introduces a theoretical framework, the Phenotype Design Space (PDS) framework, for addressing these challenges by focusing on the mapping of kinetic parameters to biochemical system phenotypes. It provides a quantitative theory whose key features include (1) a mathematically rigorous definition of phenotype based on biochemical kinetics, (2) enumeration of the full phenotypic repertoire, and (3) functional characterization of each phenotype independent of its context-dependent selection or fitness contributions. This framework is built on Design Space methods that relate system phenotypes to genetically determined parameters and environmentally determined variables. It also has the potential to automate prediction of phenotype-specific mutation rate constants and equilibrium distributions of phenotype diversity in microbial populations undergoing steady-state exponential growth, which provides an ideal reference to which more realistic cases can be compared. Although the framework is quite general and flexible, the details will undoubtedly differ for different functions, organisms and contexts. Here a hypothetical case study involving a small molecular system, a primordial circadian clock, is used to introduce this framework and to illustrate its use in a particular case. The framework is built on fundamental biochemical kinetics. Thus, the foundation is based on linear algebra and reasonable physical assumptions, which provide numerous opportunities for experimental testing and further elaboration to deal with complex multicellular organisms that are currently beyond its scope. The discussion provides a comparison of results from the PDS framework with those from other approaches in theoretical population genetics.

Methyl halide transferase-based gas reporters for quantification of filamentous bacteria in microdroplet emulsions

The application of microfluidic techniques in experimental and environmental studies is a rapidly emerging field. Water-in-oil microdroplets can serve readily as controllable micro-vessels for studies that require spatial structure. In many applications, it is useful to monitor cell growth without breaking or disrupting the microdroplets. To this end, optical reporters based on color, fluorescence, or luminescence have been developed. However, optical reporters suffer from limitations when used in microdroplets such as inaccurate readings due to strong background interference or limited sensitivity during early growth stages. In addition, optical detection is typically not amenable to filamentous or biofilm-producing organisms that have significant nonlinear changes in opacity and light scattering during growth. To overcome such limitations, we show that volatile methyl halide gases produced by reporter cells expressing a methyl halide transferase (MHT) can serve as an alternative nonoptical detection approach suitable for microdroplets. In this study, an MHT-labeled Streptomyces venezuelae reporter strain was constructed and characterized. Protocols were established for the encapsulation and incubation of S. venezuelae in microdroplets. We observed the complete life cycle for S. venezuelae including the vegetative expansion of mycelia, mycelial fragmentation, and late-stage sporulation. Methyl bromide (MeBr) production was detected by gas chromatography-mass spectrometry (GC-MS) from S. venezuelae gas reporters incubated in either liquid suspension or microdroplets and used to quantitatively estimate bacterial density. Overall, using MeBr production as a means of quantifying bacterial growth provided a 100- to 1,000-fold increase in sensitivity over optical or fluorescence measurements of a comparable reporter strain expressing fluorescent proteins. IMPORTANCE Quantitative measurement of bacterial growth in microdroplets in situ is desirable but challenging. Current optical reporter systems suffer from limitations when applied to filamentous or biofilm-producing organisms. In this study, we demonstrate that volatile methyl halide gas production can serve as a quantitative nonoptical growth assay for filamentous bacteria encapsulated in microdroplets. We constructed an S. venezuelae gas reporter strain and observed a complete life cycle for encapsulated S. venezuelae in microdroplets, establishing microdroplets as an alternative growth environment for Streptomyces spp. that can provide spatial structure. We detected MeBr production from both liquid suspension and microdroplets with a 100- to 1,000-fold increase in signal-to-noise ratio compared to optical assays. Importantly, we could reliably detect bacteria with densities down to 106 CFU/mL. The combination of quantitative gas reporting and microdroplet systems provides a valuable approach to studying fastidious organisms that require spatial structure such as those found typically in soils.

Development of heat-shock resistance in Legionella pneumophila modeled by experimental evolution

Because it can grow in buildings with complex hot water distribution systems (HWDS), healthcare facilities recognize the waterborne bacterium Legionella pneumophila as a major nosocomial infection threat and often try to clear the systems with a pasteurization process known as superheat-and-flush. After this treatment, many facilities find that the contaminating populations slowly recover, suggesting the possibility of in situ evolution favoring increased survival in high-temperature conditions. To mimic this process in a controlled environment, an adaptive laboratory evolution model was used to select a wild-type strain of L. pneumophila for survival to transient exposures to temperatures characteristic of routine hot water use or failed pasteurization processes in HWDS. Over their evolution, these populations became insensitive to exposure to 55°C and developed the ability to survive short exposures to 59°C heat shock. Heat-adapted lineages maintained a higher expression of heat-shock genes during low-temperature incubation in freshwater, suggesting a pre-adaptation to heat stress. Although there were distinct mutation profiles in each of the heat-adapted lineages, each acquired multiple mutations in the DnaJ/DnaK/ClpB disaggregase complex, as well as mutations in chaperone htpG and protease clpX. These mutations were specific to heat-shock survival and were not seen in control lineages included in the experimental model without exposure to heat shock. This study supports in situ observations of adaptation to heat stress and demonstrates the potential of L. pneumophila to develop resistance to control measures. IMPORTANCE As a bacterium that thrives in warm water ecosystems, Legionella pneumophila is a key factor motivating regulations on hot water systems. Two major measures to control Legionella are high circulating temperatures intended to curtail growth and the use of superheat-and-flush pasteurization processes to eliminate established populations. Facilities often suffer recolonization of their hot water systems; hospitals are particularly at risk due to the severe nosocomial pneumoniae caused by Legionella. To understand these long-term survivors, we have used an adaptive laboratory evolution model to replicate this process. We find major differences between the mutational profiles of heat-adapted and heat-naïve L. pneumophila populations including mutations in major heat-shock genes like chaperones and proteases. This model demonstrates that well-validated treatment protocols are needed to clear contaminated systems and-in an analog to antibiotic resistance-the importance of complete eradication of the resident population to prevent selection for more persistent bacteria.

Universality of evolutionary trajectories under arbitrary forms of self-limitation and competition

The assumption of constant population size is central in population genetics. It led to a large body of results that is robust to modeling choices and that has proven successful to understand evolutionary dynamics. In reality, allele frequencies and population size are both determined by the interaction between a population and the environment. Relaxing the constant-population assumption has two big drawbacks. It increases the technical difficulty of the analysis, and it requires specifying a mechanism for the saturation of the population size, possibly making the results contingent on model details. Here we develop a framework that encompasses a great variety of systems with an arbitrary mechanism for population growth limitation. By using techniques based on scale separation for stochastic processes, we are able to calculate analytically properties of evolutionary trajectories, such as the fixation probability. Remarkably, these properties assume a universal form with respect to our framework, which depends on only three parameters related to the intergeneration timescale, the invasion fitness, and the carrying capacity of the strains. In other words, different systems, such as Lotka-Volterra or a chemostat model (contained in our framework), share the same evolutionary outcomes after a proper remapping of their parameters. An important and surprising consequence of our results is that the direction of selection can be inverted, with a population evolving to reach lower values of invasion fitness.

Selective Pressure by Rifampicin Modulates Mutation Rates and Evolutionary Trajectories of Mycobacterial Genomes

Resistance to the frontline antibiotic rifampicin constitutes a challenge to the treatment and control of tuberculosis. Here, we analyzed the mutational landscape of Mycobacterium smegmatis during long-term evolution with increasing concentrations of rifampicin, using a mutation accumulation assay combined with whole-genome sequencing. Antibiotic treatment enhanced the acquisition of mutations, doubling the genome-wide mutation rate of the wild-type cells. While antibiotic exposure led to extinction of almost all wild-type lines, the hypermutable phenotype of the ΔnucS mutant strain (noncanonical mismatch repair deficient) provided an efficient response to the antibiotic, leading to high rates of survival. This adaptative advantage resulted in the emergence of higher levels of rifampicin resistance, an accelerated acquisition of drug resistance mutations in rpoB (β RNA polymerase), and a wider diversity of evolutionary pathways that led to drug resistance. Finally, this approach revealed a subset of adaptive genes under positive selection with rifampicin that could be associated with the development of antibiotic resistance. IMPORTANCE Rifampicin is the most important first-line antibiotic against mycobacterial infections, including tuberculosis, one of the top causes of death worldwide. Acquisition of rifampicin resistance constitutes a major global public health problem that makes the control of the disease challenging. Here, we performed an experimental evolution assay under antibiotic selection to analyze the response and adaptation of mycobacteria, leading to the acquisition of rifampicin resistance. This approach explored the total number of mutations that arose in the mycobacterial genomes under long-term rifampicin exposure, using whole-genome sequencing. Our results revealed the effect of rifampicin at a genomic level, identifying different mechanisms and multiple pathways leading to rifampicin resistance in mycobacteria. Moreover, this study detected that an increase in the rate of mutations led to enhanced levels of drug resistance and survival. In summary, all of these results could be useful to understand and prevent the emergence of drug-resistant isolates in mycobacterial infections.

Developmental Selection and the Perception of Mutation Bias

The notion that mutations are random relative to their fitness effects is central to the Neo-Darwinian view of evolution. However, a recent interpretation of the patterns of mutation accumulation in the genome of Arabidopsis thaliana has challenged this notion, arguing for the presence of a targeted DNA repair mechanism that causes a nonrandom association of mutation rates and fitness effects. Specifically, this mechanism was suggested to cause a reduction in the rates of mutations on essential genes, thus lowering the rates of deleterious mutations. Central to this argument were attempts to rule out selection at the population level. Here, we offer an alternative and parsimonious interpretation of the patterns of mutation accumulation previously attributed to mutation bias, showing how they can instead or additionally be caused by developmental selection, that is selection occurring at the cellular level during the development of a multicellular organism. Thus, the depletion of deleterious mutations in A. thaliana may indeed be the result of a selective process, rather than a bias in mutation. More broadly, our work highlights the importance of considering development in the interpretation of population-genetic analyses of multicellular organisms, and it emphasizes that efforts to identify mechanisms involved in mutational biases should explicitly account for developmental selection.

Prolonging genetic circuit stability through adaptive evolution of overlapping genes

The development of synthetic biological circuits that maintain functionality over application-relevant time scales remains a significant challenge. Here, we employed synthetic overlapping sequences in which one gene is encoded or 'entangled' entirely within an alternative reading frame of another gene. In this design, the toxin-encoding relE was entangled within ilvA, which encodes threonine deaminase, an enzyme essential for isoleucine biosynthesis. A functional entanglement construct was obtained upon modification of the ribosome-binding site of the internal relE gene. Using this optimized design, we found that the selection pressure to maintain functional IlvA stabilized the production of burdensome RelE for >130 generations, which compares favorably with the most stable kill-switch circuits developed to date. This stabilizing effect was achieved through a complete alteration of the allowable landscape of mutations such that mutations inactivating the entangled genes were disfavored. Instead, the majority of lineages accumulated mutations within the regulatory region of ilvA. By reducing baseline relE expression, these more 'benign' mutations lowered circuit burden, which suppressed the accumulation of relE-inactivating mutations, thereby prolonging kill-switch function. Overall, this work demonstrates the utility of sequence entanglement paired with an adaptive laboratory evolution campaign to increase the evolutionary stability of burdensome synthetic circuits.

Synthetic Denitrifying Communities Reveal a Positive and Dynamic Biodiversity-Ecosystem Functioning Relationship during Experimental Evolution

Biodiversity is vital for ecosystem functions and services, and many studies have reported positive, negative, or neutral biodiversity-ecosystem functioning (BEF) relationships in plant and animal systems. However, if the BEF relationship exists and how it evolves remains elusive in microbial systems. Here, we selected 12 Shewanella denitrifiers to construct synthetic denitrifying communities (SDCs) with a richness gradient spanning 1 to 12 species, which were subjected to approximately 180 days (with 60 transfers) of experimental evolution with generational changes in community functions continuously tracked. A significant positive correlation was observed between community richness and functions, represented by productivity (biomass) and denitrification rate, however, such a positive correlation was transient, only significant in earlier days (0 to 60) during the evolution experiment (180 days). Also, we found that community functions generally increased throughout the evolution experiment. Furthermore, microbial community functions with lower richness exhibited greater increases than those with higher richness. Biodiversity effect analysis revealed positive BEF relationships largely attributable to complementary effects, which were more pronounced in communities with lower richness than those with higher richness. This study is one of the first studies that advances our understanding of BEF relationships and their evolutionary mechanisms in microbial systems, highlighting the crucial role of evolution in predicting the BEF relationship in microbial systems. IMPORTANCE Despite the consensus that biodiversity supports ecosystem functioning, not all experimental models of macro-organisms support this notion with positive, negative, or neutral biodiversity-ecosystem functioning (BEF) relationships reported. The fast-growing, metabolically versatile, and easy manipulation nature of microbial communities allows us to explore well the BEF relationship and further interrogate if the BEF relationship remains constant during long-term community evolution. Here, we constructed multiple synthetic denitrifying communities (SDCs) by randomly selecting species from a candidate pool of 12 Shewanella denitrifiers. These SDCs differ in species richness, spanning 1 to 12 species, and were monitored continuously for community functional shifts during approximately 180-day parallel cultivation. We demonstrated that the BEF relationship was dynamic with initially (day 0 to 60) greater productivity and denitrification among SDCs of higher richness. However, such pattern was reversed thereafter with greater productivity and denitrification increments in lower-richness SDCs, likely due to a greater accumulation of beneficial mutations during the experimental evolution.

Rapid evolutionary repair by secondary perturbation of a primary disrupted transcriptional network

The discrete steps of transcriptional rewiring have been proposed to occur neutrally to ensure steady gene expression under stabilizing selection. A conflict-free switch of a regulon between regulators may require an immediate compensatory evolution to minimize deleterious effects. Here, we perform an evolutionary repair experiment on the Lachancea kluyveri yeast sef1Δ mutant using a suppressor development strategy. Complete loss of SEF1 forces cells to initiate a compensatory process for the pleiotropic defects arising from misexpression of TCA cycle genes. Using different selective conditions, we identify two adaptive loss-of-function mutations of IRA1 and AZF1. Subsequent analyses show that Azf1 is a weak transcriptional activator regulated by the Ras1-PKA pathway. Azf1 loss-of-function triggers extensive gene expression changes responsible for compensatory, beneficial, and trade-off phenotypes. The trade-offs can be alleviated by higher cell density. Our results not only indicate that secondary transcriptional perturbation provides rapid and adaptive mechanisms potentially stabilizing the initial stage of transcriptional rewiring but also suggest how genetic polymorphisms of pleiotropic mutations could be maintained in the population.

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.

On the evolution of natural product biosynthesis

Natural products are the raw material for drug discovery programmes. Bioactive natural products are used extensively in medicine and agriculture and have found utility as antibiotics, immunosuppressives, anti-cancer drugs and anthelminthics. Remarkably, the natural role and what mechanisms drive evolution of these molecules is relatively poorly understood. The exponential increase in genome and chemical data in recent years, coupled with technical advances in bioinformatics and genetics have enabled progress to be made in understanding the evolution of biosynthetic gene clusters and the products of their enzymatic machinery. Here we discuss the diversity of natural products, incorporating the mechanisms that govern evolution of metabolic pathways and how this can be applied to biosynthetic gene clusters. We build on the nomenclature of natural products in terms of primary, integrated, secondary and specialised metabolism and place this within an ecology-evolutionary-developmental biology framework. This eco-evo-devo framework we believe will help to clarify the nature and use of the term specialised metabolites in the future.

Insertion Sequences Determine Plasmid Adaptation to New Bacterial Hosts

Plasmids facilitate the vertical and horizontal spread of antimicrobial resistance genes between bacteria. The host range and adaptation of plasmids to new hosts determine their impact on the spread of resistance. In this work, we explore the mechanisms driving plasmid adaptation to novel hosts in experimental evolution. Using the small multicopy plasmid pB1000, usually found in Pasteurellaceae, we studied its adaptation to a host from a different bacterial family, Escherichia coli. We observed two different mechanisms of adaptation. One mechanism is single nucleotide polymorphisms (SNPs) in the origin of replication (oriV) of the plasmid, which increase the copy number in E. coli cells, elevating the stability, and resistance profile. The second mechanism consists of two insertion sequences (ISs), IS1 and IS10, which decrease the fitness cost of the plasmid by disrupting an uncharacterized gene on pB1000 that is harmful to E. coli. Both mechanisms increase the stability of pB1000 independently, but only their combination allows long-term maintenance. Crucially, we show that the mechanisms have a different impact on the host range of the plasmid. SNPs in oriV prevent the replication in the original host, resulting in a shift of the host range. In contrast, the introduction of ISs either shifts or expands the host range, depending on the IS. While IS1 leads to expansion, IS10 cannot be reintroduced into the original host. This study gives new insights into the relevance of ISs in plasmid-host adaptation to understand the success in spreading resistance. IMPORTANCE ColE1-like plasmids are small, mobilizable plasmids that can be found across at least four orders of Gammaproteobacteria and are strongly associated with antimicrobial resistance genes. Plasmid pB1000 carries the gene bla_ROB-1, conferring high-level resistance to penicillins and cefaclor. pB1000 has been described in various species of the family Pasteurellaceae, for example, in Haemophilus influenzae, which can cause diseases such as otitis media, meningitis, and pneumonia. To understand the resistance spread through horizontal transfer, it is essential to study the mechanisms of plasmid adaptation to novel hosts. In this work we identify that a gene from pB1000, which encodes a peptide that is toxic for E. coli, and the low plasmid copy number (PCN) of pB1000 in E. coli cells are essential targets in the described plasmid-host adaptation and therefore limit the spread of pB1000-encoded bla_ROB-1. Furthermore, we show how the interplay of two adaptation mechanisms leads to successful plasmid maintenance in a different bacterial family.

Chromosomal Position of Ribosomal Protein Genes Affects Long-Term Evolution of Vibrio cholerae

It is unclear how gene order within the chromosome influences genome evolution. Bacteria cluster transcription and translation genes close to the replication origin (oriC). In Vibrio cholerae, relocation of s10-spc-α locus (S10), the major locus of ribosomal protein genes, to ectopic genomic positions shows that its relative distance to the oriC correlates to a reduction in growth rate, fitness, and infectivity. To test the long-term impact of this trait, we evolved 12 populations of V. cholerae strains bearing S10 at an oriC-proximal or an oriC-distal location for 1,000 generations. During the first 250 generations, positive selection was the main force driving mutation. After 1,000 generations, we observed more nonadaptative mutations and hypermutator genotypes. Populations fixed inactivating mutations at many genes linked to virulence: flagellum, chemotaxis, biofilm, and quorum sensing. Throughout the experiment, all populations increased their growth rates. However, those bearing S10 close to oriC remained the fittest, indicating that suppressor mutations cannot compensate for the genomic position of the main ribosomal protein locus. Selection and sequencing of the fastest-growing clones allowed us to characterize mutations inactivating, among other sites, flagellum master regulators. Reintroduction of these mutations into the wild-type context led to a ≈10% growth improvement. In conclusion, the genomic location of ribosomal protein genes conditions the evolutionary trajectory of V. cholerae. While genomic content is highly plastic in prokaryotes, gene order is an underestimated factor that conditions cellular physiology and evolution. A lack of suppression enables artificial gene relocation as a tool for genetic circuit reprogramming. IMPORTANCE The bacterial chromosome harbors several entangled processes such as replication, transcription, DNA repair, and segregation. Replication begins bidirectionally at the replication origin (oriC) until the terminal region (ter) organizing the genome along the ori-ter axis gene order along this axis could link genome structure to cell physiology. Fast-growing bacteria cluster translation genes near oriC. In Vibrio cholerae, moving them away was feasible but at the cost of losing fitness and infectivity. Here, we evolved strains harboring ribosomal genes close or far from oriC. Growth rate differences persisted after 1,000 generations. No mutation was able to compensate for the growth defect, showing that ribosomal gene location conditions their evolutionary trajectory. Despite the high plasticity of bacterial genomes, evolution has sculpted gene order to optimize the ecological strategy of the microorganism. We observed growth rate improvement throughout the evolution experiment that occurred at expense of energetically costly processes such the flagellum biosynthesis and virulence-related functions. From the biotechnological point of view, manipulation of gene order enables altering bacterial growth with no escape events.

Experimental approaches to study evolutionary cell biology using yeasts

The past century has witnessed tremendous advances in understanding how cells function. Nevertheless, how cellular processes have evolved is still poorly understood. Many studies have highlighted surprising molecular diversity in how cells from diverse species execute the same processes, and advances in comparative genomics are likely to reveal much more molecular diversity than was believed possible until recently. Extant cells remain therefore the product of an evolutionary history that we vastly ignore. Evolutionary cell biology has emerged as a discipline aiming to address this knowledge gap by combining evolutionary, molecular, and cellular biology thinking. Recent studies have shown how even essential molecular processes, such as DNA replication, can undergo fast adaptive evolution under certain laboratory conditions. These developments open new lines of research where the evolution of cellular processes can be investigated experimentally. Yeasts naturally find themselves at the forefront of this research line. Not only do they allow the observation of fast evolutionary adaptation, but they also provide numerous genomic, synthetic, and cellular biology tools already developed by a large community. Here we propose that yeasts can serve as an "evolutionary cell lab" to test hypotheses, principles, and ideas in evolutionary cell biology. We discuss various experimental approaches available for this purpose, and how biology at large can benefit from them.

Using artificial neural networks to ask 'why' questions of minds and brains

Neuroscientists have long characterized the properties and functions of the nervous system, and are increasingly succeeding in answering how brains perform the tasks they do. But the question 'why' brains work the way they do is asked less often. The new ability to optimize artificial neural networks (ANNs) for performance on human-like tasks now enables us to approach these 'why' questions by asking when the properties of networks optimized for a given task mirror the behavioral and neural characteristics of humans performing the same task. Here we highlight the recent success of this strategy in explaining why the visual and auditory systems work the way they do, at both behavioral and neural levels.

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.

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.

Microbial population dynamics decouple growth response from environmental nutrient concentration

How the growth rate of a microbial population responds to the environmental availability of chemical nutrients and other resources is a fundamental question in microbiology. Models of this response, such as the widely used Monod model, are generally characterized by a maximum growth rate and a half-saturation concentration of the resource. What values should we expect for these half-saturation concentrations, and how should they depend on the environmental concentration of the resource? We survey growth response data across a wide range of organisms and resources. We find that the half-saturation concentrations vary across orders of magnitude, even for the same organism and resource. To explain this variation, we develop an evolutionary model to show that demographic fluctuations (genetic drift) can constrain the adaptation of half-saturation concentrations. We find that this effect fundamentally differs depending on the type of population dynamics: Populations undergoing periodic bottlenecks of fixed size will adapt their half-saturation concentrations in proportion to the environmental resource concentrations, but populations undergoing periodic dilutions of fixed size will evolve half-saturation concentrations that are largely decoupled from the environmental concentrations. Our model not only provides testable predictions for laboratory evolution experiments, but it also reveals how an evolved half-saturation concentration may not reflect the organism's environment. In particular, this explains how organisms in resource-rich environments can still evolve fast growth at low resource concentrations. Altogether, our results demonstrate the critical role of population dynamics in shaping fundamental ecological traits.

Evolutionary rescue of resistant mutants is governed by a balance between radial expansion and selection in compact populations

Mutation-mediated treatment resistance is one of the primary challenges for modern antibiotic and anti-cancer therapy. Yet, many resistance mutations have a substantial fitness cost and are subject to purifying selection. How emerging resistant lineages may escape purifying selection via subsequent compensatory mutations is still unclear due to the difficulty of tracking such evolutionary rescue dynamics in space and time. Here, we introduce a system of fluorescence-coupled synthetic mutations to show that the probability of evolutionary rescue, and the resulting long-term persistence of drug resistant mutant lineages, is dramatically increased in dense microbial populations. By tracking the entire evolutionary trajectory of thousands of resistant lineages in expanding yeast colonies we uncover an underlying quasi-stable equilibrium between the opposing forces of radial expansion and natural selection, a phenomenon we term inflation-selection balance. Tailored computational models and agent-based simulations corroborate the fundamental nature of the observed effects and demonstrate the potential impact on drug resistance evolution in cancer. The described phenomena should be considered when predicting multi-step evolutionary dynamics in any mechanically compact cellular population, including pathogenic microbial biofilms and solid tumors. The insights gained will be especially valuable for the quantitative understanding of response to treatment, including emerging evolution-based therapy strategies.

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.

On the hidden temporal dynamics of plant adaptation

Adaptation to a wide range of environments is a major driver of plant diversity. It is now possible to catalog millions of potential adaptive genomic differences segregating between environments within a plant species in a single experiment. Understanding which of these changes contributes to adaptive phenotypic divergence between plant populations is a major goal of evolutionary biologists and crop breeders. In this review, we briefly highlight the approaches frequently used to understand the genetic basis of adaptive phenotypes in plants, and we discuss some of the limitations of these methods. We propose that direct observation of the process of adaptation using multigenerational studies and whole genome sequencing is a crucial missing component of recent studies of plant adaptation because it complements several shortcomings of sampling-based techniques.