Adaptive tuning of mutation rates allows fast response to lethal stress in Escherichia coli

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.

Strain tracking in complex microbiomes using synteny analysis reveals per-species modes of evolution

Microbial species diversify into strains through single-nucleotide mutations and structural changes, such as recombination, insertions and deletions. Most strain-comparison methods quantify differences in single-nucleotide polymorphisms (SNPs) and are insensitive to structural changes. However, recombination is an important driver of phenotypic diversification in many species, including human pathogens. We introduce SynTracker, a tool that compares microbial strains using genome synteny-the order of sequence blocks in homologous genomic regions-in pairs of metagenomic assemblies or genomes. Genome synteny is a rich source of genomic information untapped by current strain-comparison tools. SynTracker has low sensitivity to SNPs, has no database requirement and is robust to sequencing errors. It outperforms existing tools when tracking strains in metagenomic data and is particularly suited for phages, plasmids and other low-data contexts. Applied to single-species datasets and human gut metagenomes, SynTracker, combined with an SNP-based tool, detects strains enriched in either point mutations or structural changes, providing insights into microbial evolution in situ.

Mutational robustness and the role of buffer genes in evolvability

Organisms rely on mutations to fuel adaptive evolution. However, many mutations impose a negative effect on fitness. Cells may have therefore evolved mechanisms that affect the phenotypic effects of mutations, thus conferring mutational robustness. Specifically, so-called buffer genes are hypothesized to interact directly or indirectly with genetic variation and reduce its effect on fitness. Environmental or genetic perturbations can change the interaction between buffer genes and genetic variation, thereby unmasking the genetic variation's phenotypic effects and thus providing a source of variation for natural selection to act on. This review provides an overview of our understanding of mutational robustness and buffer genes, with the chaperone gene HSP90 as a key example. It discusses whether buffer genes merely affect standing variation or also interact with de novo mutations, how mutational robustness could influence evolution, and whether mutational robustness might be an evolved trait or rather a mere side-effect of complex genetic interactions.

Demographic fluctuations and selection during host-parasite co-evolution interactively increase genetic diversity

Host-parasite interactions can cause strong demographic fluctuations accompanied by selective sweeps of resistance/infectivity alleles. Both demographic bottlenecks and frequent sweeps are expected to reduce the amount of segregating genetic variation and therefore might constrain adaptation during co-evolution. Recent studies, however, suggest that the interaction of demographic and selective processes is a key component of co-evolutionary dynamics and may rather positively affect levels of genetic diversity available for adaptation. Here, we provide direct experimental testing of this hypothesis by disentangling the effects of demography, selection and their interaction in an experimental host-parasite system. We grew 12 populations of a unicellular, asexually reproducing algae (Chlorella variabilis) that experienced either growth followed by constant population sizes (three populations), demographic fluctuations (three populations), selection induced by exposure to a virus (three populations), or demographic fluctuations together with virus-induced selection (three populations). After 50 days (~50 generations), we conducted whole-genome sequencing of each algal host population. We observed more genetic diversity in populations that jointly experienced selection and demographic fluctuations than in populations where these processes were experimentally separated. In addition, in those three populations that jointly experienced selection and demographic fluctuations, experimentally measured diversity exceeds expected values of diversity that account for the cultures' population sizes. Our results suggest that eco-evolutionary feedbacks can positively affect genetic diversity and provide the necessary empirical measures to guide further improvements of theoretical models of adaptation during host-parasite co-evolution.

Inactivation of the ribosome assembly factor RimP causes streptomycin resistance and impairs motility in Salmonella

The ribosome is the central hub for protein synthesis and the target of many antibiotics. Although the majority of ribosome-targeting antibiotics inhibit protein synthesis and are bacteriostatic, aminoglycosides promote protein mistranslation and are bactericidal. Understanding the resistance mechanisms of bacteria against aminoglycosides is not only vital for improving the efficacy of this critically important group of antibiotics but also crucial for studying the molecular basis of translational fidelity. In this work, we analyzed Salmonella mutants evolved in the presence of the aminoglycoside streptomycin (Str) and identified a novel gene rimP to be involved in Str resistance. RimP is a ribosome assembly factor critical for the maturation of the 30S small subunit that binds Str. Deficiency in RimP increases resistance against Str and facilitates the development of even higher resistance. Deleting rimP decreases mistranslation and cellular uptake of Str and further impairs flagellar motility. Our work thus highlights a previously unknown mechanism of aminoglycoside resistance via defective ribosome assembly.

Laboratory domestication of Lactiplantibacillus plantarum alters some phenotypic traits but causes non-novel genomic impact

AIMS

Laboratory domestication has been negligibly examined in lactic acid bacteria (LAB). Lactiplantibacillus plantarum is a highly studied and industrially relevant LAB. Here, we passaged L. plantarum JGR2 in a complex medium to study the effects of domestication on the phenotypic properties and the acquisition of mutations.

METHODS AND RESULTS

Lactiplantibacillus plantarum JGR2 was passaged in mMRS medium (deMan Rogossa Sharpe supplemented with 0.05% w/v L-cysteine) in three parallel populations for 70 days. One pure culture from each population was studied for various phenotypic properties and genomic alterations. Auto-aggregation of the evolved strains was significantly reduced, and lactic acid production and ethanol tolerance were increased. Other probiotic properties and antibiotic sensitivity were not altered. Conserved synonymous and non-synonymous mutations were observed in mobile element proteins (transposases), β-galactosidase, and phosphoketolases in all three isolates. The evolved strains lost all the repeat regions and some of the functions associated with them. Most of the conserved mutations were found in the genomes of other wild-type strains available in a public database, indicating the non-novel genomic impact of laboratory passaging.

CONCLUSIONS

Laboratory domestication can affect the phenotypic and genotypic traits of L. plantarum and similar studies are necessary for other important species of LAB.

Deficiency in ribosome biogenesis causes streptomycin resistance and impairs motility in Salmonella

The ribosome is the central hub for protein synthesis and the target of many antibiotics. Whereas the majority of ribosome-targeting antibiotics inhibit protein synthesis and are bacteriostatic, aminoglycosides promote protein mistranslation and are bactericidal. Understanding the resistance mechanisms of bacteria against aminoglycosides is not only vital for improving the efficacy of this critically important group of antibiotics but also crucial for studying the molecular basis of translational fidelity. In this work, we analyzed Salmonella mutants evolved in the presence of the aminoglycoside streptomycin (Str) and identified a novel gene rimP to be involved in Str resistance. RimP is a ribosome assembly factor critical for the maturation of the 30S small subunit that binds Str. Deficiency in RimP increases resistance against Str and facilitates the development of even higher resistance. Deleting rimP decreases mistranslation and cellular uptake of Str, and further impairs flagellar motility. Our work thus highlights a previously unknown mechanism of aminoglycoside resistance via defective ribosome assembly.

Competition and evolutionary selection among core regulatory motifs in gene expression control

Gene products that are beneficial in one environment may become burdensome in another, prompting the emergence of diverse regulatory schemes that carry their own bioenergetic cost. By ensuring that regulators are only expressed when needed, we demonstrate that autoregulation generally offers an advantage in an environment combining mutation and time-varying selection. Whether positive or negative feedback emerges as dominant depends primarily on the demand for the target gene product, typically to ensure that the detrimental impact of inevitable mutations is minimized. While self-repression of the regulator curbs the spread of these loss-of-function mutations, self-activation instead facilitates their propagation. By analyzing the transcription network of multiple model organisms, we reveal that reduced bioenergetic cost may contribute to the preferential selection of autoregulation among transcription factors. Our results not only uncover how seemingly equivalent regulatory motifs have fundamentally different impact on population structure, growth dynamics, and evolutionary outcomes, but they can also be leveraged to promote the design of evolutionarily robust synthetic gene circuits.

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.

Mutation bias and adaptation in bacteria

Genetic mutation, which provides the raw material for evolutionary adaptation, is largely a stochastic force. However, there is ample evidence showing that mutations can also exhibit strong biases, with some mutation types and certain genomic positions mutating more often than others. It is becoming increasingly clear that mutational bias can play a role in determining adaptive outcomes in bacteria in both the laboratory and the clinic. As such, understanding the causes and consequences of mutation bias can help microbiologists to anticipate and predict adaptive outcomes. In this review, we provide an overview of the mechanisms and features of the bacterial genome that cause mutational biases to occur. We then describe the environmental triggers that drive these mechanisms to be more potent and outline the adaptive scenarios where mutation bias can synergize with natural selection to define evolutionary outcomes. We conclude by describing how understanding mutagenic genomic features can help microbiologists predict areas sensitive to mutational bias, and finish by outlining future work that will help us achieve more accurate evolutionary forecasts.

Highly Effective Salt-Activated Alcohol-Based Disinfectants with Enhanced Antimicrobial Activity

Surfaces contaminated with pathogens raise concerns about the increased risk of disease transmission and infection. To clean biocontaminated surfaces, alcohol-based disinfectants have been predominantly used for disinfecting high-touch areas in diverse settings. However, due to its limited antimicrobial activities and concern over the emergence of alcohol-tolerant strains, much effort has been made to develop highly efficient disinfectant formulations. In this study, we hypothesize that the addition of a physical pathogen inactivation mechanism by salt recrystallization (besides the existing chemical inactivation mechanism by alcohol in such formulations) can improve inactivation efficiency by preventing the emergence of alcohol tolerance. To this end, we employed the drying-induced salt recrystallization process to implement the concept of highly efficient alcohol-based disinfectant formulations. To identify the individual and combined effects of isopropyl alcohol (IPA) and NaCl, time-dependent morphological/structural changes of various IPA solutions containing NaCl have been characterized by optical microscopy/X-ray diffraction analysis. Their antimicrobial activities have been tested on surfaces (glass slide, polystyrene Petri dish, and stainless steel) contaminated with Gram-positive/negative bacteria (methicillin-resistant Staphylococcus aureus, Pseudomonas aeruginosa, and Salmonella enterica subsp. enterica Typhimurium) and viruses (A/PR8/34 H1N1 influenza virus and HCoV-OC43 human coronavirus). We found that additional salt crystallization during the drying of the alcohol solution facilitated stronger biocidal effects than IPA-only formulations, regardless of the types of solid surfaces and pathogens, including alcohol-tolerant strains adapted from wild-type Escherichia coli MG1655. Our findings can be useful in developing highly effective disinfectant formulations by minimizing the use of toxic antimicrobial substances to improve public health and safety.

Targeted Hypermutation as a Survival Strategy: A Theoretical Approach

Targeted hypermutation has proven to be a useful survival strategy for bacteria under severe stress and is also used by multicellular organisms in specific instances such as the mammalian immune system. This might appear surprising, given the generally observed deleterious effects of poor replication fidelity/high mutation rate. A previous theoretical model designed to explore the role of replication fidelity in the origin of life was applied to a simulated hypermutation scenario. The results confirmed that the same model is useful for analyzing hypermutation and can predict the effects of the same parameters (survival probability, replication fidelity, mutation effect, and others) on the survival of cellular populations undergoing hypermutation as a result of severe stress.

Recruitment of a Middling Promiscuous Enzyme Drives Adaptive Metabolic Evolution in Escherichia coli

A key step in metabolic pathway evolution is the recruitment of promiscuous enzymes to perform new functions. Despite the recognition that promiscuity is widespread in biology, factors dictating the preferential recruitment of one promiscuous enzyme over other candidates are unknown. Escherichia coli contains four sugar kinases that are candidates for recruitment when the native glucokinase machinery is deleted-allokinase (AlsK), manno(fructo)kinase (Mak), N-acetylmannosamine kinase (NanK), and N-acetylglucosamine kinase (NagK). The catalytic efficiencies of these enzymes are 103- to 105-fold lower than native glucokinases, ranging from 2,400 M-1 s-1 for the most active candidate, NagK, to 15 M-1 s-1 for the least active candidate, AlsK. To investigate the relationship between catalytic activities of promiscuous enzymes and their recruitment, we performed adaptive evolution of a glucokinase-deficient E. coli strain to restore glycolytic metabolism. We observed preferential recruitment of NanK via a trajectory involving early mutations that facilitate glucose uptake and amplify nanK transcription, followed by nonsynonymous substitutions in NanK that enhance the enzyme's promiscuous glucokinase activity. These substitutions reduced the native activity of NanK and reduced organismal fitness during growth on an N-acetylated carbon source, indicating that enzyme recruitment comes at a cost for growth on other substrates. Notably, the two most active candidates, NagK and Mak, were not recruited, suggesting that catalytic activity alone does not dictate evolutionary outcomes. The results highlight our lack of knowledge regarding biological drivers of enzyme recruitment and emphasize the need for a systems-wide approach to identify factors facilitating or constraining this important adaptive process.

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.

Hypermutator emergence in experimental Escherichia coli populations is stress-type dependent

Genotypes exhibiting an increased mutation rate, called hypermutators, can propagate in microbial populations because they can have an advantage due to the higher supply of beneficial mutations needed for adaptation. Although this is a frequently observed phenomenon in natural and laboratory populations, little is known about the influence of parameters such as the degree of maladaptation, stress intensity, and the genetic architecture for adaptation on the emergence of hypermutators. To address this knowledge gap, we measured the emergence of hypermutators over ~1,000 generations in experimental Escherichia coli populations exposed to different levels of osmotic or antibiotic stress. Our stress types were chosen based on the assumption that the genetic architecture for adaptation differs between them. Indeed, we show that the size of the genetic basis for adaptation is larger for osmotic stress compared to antibiotic stress. During our experiment, we observed an increased emergence of hypermutators in populations exposed to osmotic stress but not in those exposed to antibiotic stress, indicating that hypermutator emergence rates are stress type dependent. These results support our hypothesis that hypermutator emergence is linked to the size of the genetic basis for adaptation. In addition, we identified other parameters that covaried with stress type (stress level and IS transposition rates) that might have contributed to an increased hypermutator provision and selection. Our results provide a first comparison of hypermutator emergence rates under varying stress conditions and point towards complex interactions of multiple stress-related factors on the evolution of mutation rates.

Potential and limits of (mal)adaptive mutation rate plasticity in plants

Genetic mutations provide the heritable material for plant adaptation to their environments. At the same time, the environment can affect the mutation rate across plant genomes. However, the extent to which environmental plasticity in mutation rates can facilitate or hinder adaptation remains a longstanding and unresolved question. Emerging discoveries of mechanisms affecting mutation rate variability provide opportunities to consider this question in a new light. Links between chromatin states, transposable elements, and DNA repair suggest cases of adaptive mutation rate plasticity could occur. Yet, numerous evolutionary and biological forces are expected to limit the impact of any such mutation rate plasticity on adaptive evolution. Persistent uncertainty about the significance of mutation rate plasticity on adaptation motivates new experimental and theoretical research relevant to understanding plant responses in changing environments.

A reversible mutation in a genomic hotspot saves bacterial swarms from extinction

Microbial adaptation to changing environmental conditions is frequently mediated by hypermutable sequences. Here we demonstrate that such a hypermutable hotspot within a gene encoding a flagellar unit of Paenibacillus glucanolyticus generated spontaneous non-swarming mutants with increased stress resistance. These mutants, which survived conditions that eliminated wild-type cultures, could be carried by their swarming siblings when the colony spread, consequently increasing their numbers at the spreading edge. Of interest, the hypermutable nature of the aforementioned sequence enabled the non-swarming mutants to serve as "seeds" for a new generation of wild-type cells through reversion of the mutation. Using a mathematical model, we examined the survival dynamics of P. glucanolyticus colonies under fluctuating environments. Our experimental and theoretical results suggest that the non-swarming, stress-resistant mutants can save the colony from extinction. Notably, we identified this hypermutable sequence in flagellar genes of additional Paenibacillus species, suggesting that this phenomenon could be wide-spread and ecologically important.

Accelerated Adaptive Laboratory Evolution by Automated Repeated Batch Processes in Parallelized Bioreactors

Adaptive laboratory evolution (ALE) is a valuable complementary tool for modern strain development. Insights from ALE experiments enable the improvement of microbial cell factories regarding the growth rate and substrate utilization, among others. Most ALE experiments are conducted by serial passaging, a method that involves large amounts of repetitive manual labor and comes with inherent experimental design flaws. The acquisition of meaningful and reliable process data is a burdensome task and is often undervalued and neglected, but also unfeasible in shake flask experiments due to technical limitations. Some of these limitations are alleviated by emerging automated ALE methods on the μL and mL scale. A novel approach to conducting ALE experiments is described that is faster and more efficient than previously used methods. The conventional shake flask approach was translated to a parallelized, L scale stirred-tank bioreactor system that runs controlled, automated, repeated batch processes. The method was validated with a growth optimization experiment of E. coli K-12 MG1655 grown with glycerol minimal media as a benchmark. Off-gas analysis enables the continuous estimation of the biomass concentration and growth rate using a black-box model based on first principles (soft sensor). The proposed method led to the same stable growth rates of E. coli with the non-native carbon source glycerol 9.4 times faster than the traditional manual approach with serial passaging in uncontrolled shake flasks and 3.6 times faster than an automated approach on the mL scale. Furthermore, it is shown that the cumulative number of cell divisions (CCD) alone is not a suitable timescale for measuring and comparing evolutionary progress.

Functional mining of novel terpene synthases from metagenomes

BACKGROUND

Terpenes are one of the most diverse and abundant classes of natural biomolecules, collectively enabling a variety of therapeutic, energy, and cosmetic applications. Recent genomics investigations have predicted a large untapped reservoir of bacterial terpene synthases residing in the genomes of uncultivated organisms living in the soil, indicating a vast array of putative terpenoids waiting to be discovered.

RESULTS

We aimed to develop a high-throughput functional metagenomic screening system for identifying novel terpene synthases from bacterial metagenomes by relieving the toxicity of terpene biosynthesis precursors to the Escherichia coli host. The precursor toxicity was achieved using an inducible operon encoding the prenyl pyrophosphate synthetic pathway and supplementation of the mevalonate precursor. Host strain and screening procedures were finely optimized to minimize false positives arising from spontaneous mutations, which avoid the precursor toxicity. Our functional metagenomic screening of human fecal metagenomes yielded a novel β-farnesene synthase, which does not show amino acid sequence similarity to known β-farnesene synthases. Engineered S. cerevisiae expressing the screened β-farnesene synthase produced 120 mg/L β-farnesene from glucose (2.86 mg/g glucose) with a productivity of 0.721 g/L∙h.

CONCLUSIONS

A unique functional metagenomic screening procedure was established for screening terpene synthases from metagenomic libraries. This research proves the potential of functional metagenomics as a sequence-independent avenue for isolating targeted enzymes from uncultivated organisms in various environmental habitats.

Selective sweep sites and SNP dense regions differentiate Mycobacterium bovis isolates across scales

Mycobacterium bovis, a bacterial zoonotic pathogen responsible for the economically and agriculturally important livestock disease bovine tuberculosis (bTB), infects a broad mammalian host range worldwide. This characteristic has led to bidirectional transmission events between livestock and wildlife species as well as the formation of wildlife reservoirs, impacting the success of bTB control measures. Next Generation Sequencing (NGS) has transformed our ability to understand disease transmission events by tracking variant sites, however the genomic signatures related to host adaptation following spillover, alongside the role of other genomic factors in the M. bovis transmission process are understudied problems. We analyzed publicly available M. bovis datasets collected from 700 hosts across three countries with bTB endemic regions (United Kingdom, United States, and New Zealand) to investigate if genomic regions with high SNP density and/or selective sweep sites play a role in Mycobacterium bovis adaptation to new environments (e.g., at the host-species, geographical, and/or sub-population levels). A simulated M. bovis alignment was created to generate null distributions for defining genomic regions with high SNP counts and regions with selective sweeps evidence. Random Forest (RF) models were used to investigate evolutionary metrics within the genomic regions of interest to determine which genomic processes were the best for classifying M. bovis across ecological scales. We identified in the M. bovis genomes 14 and 132 high SNP density and selective sweep regions, respectively. Selective sweep regions were ranked as the most important in classifying M. bovis across the different scales in all RF models. SNP dense regions were found to have high importance in the badger and cattle specific RF models in classifying badger derived isolates from livestock derived ones. Additionally, the genes detected within these genomic regions harbor various pathogenic functions such as virulence and immunogenicity, membrane structure, host survival, and mycobactin production. The results of this study demonstrate how comparative genomics alongside machine learning approaches are useful to investigate further the nature of M. bovis host-pathogen interactions.

Thermal stress and mutation accumulation increase heat shock protein expression in Daphnia

Understanding the short- and long-term consequences of climate change is a major challenge in biology. For aquatic organisms, temperature changes and drought can lead to thermal stress and habitat loss, both of which can ultimately lead to higher mutation rates. Here, we examine the effect of high temperature and mutation accumulation on gene expression at two loci from the heat shock protein (HSP) gene family, HSP60 and HSP90. HSPs have been posited to serve as 'mutational capacitors' given their role as molecular chaperones involved in protein folding and degradation, thus buffering against a wide range of cellular stress and destabilization. We assayed changes in HSP expression across 5 genotypes of Daphnia magna, a sentinel species in ecology and environmental biology, with and without acute exposure to thermal stress and accumulated mutations. Across genotypes, HSP expression increased ~ 6× in response to heat and ~ 4× with mutation accumulation, individually. Both factors simultaneously (lineages with high mutation loads exposed to high heat) increased gene expression ~ 23×-much more than that predicted by an additive model. Our results corroborate suggestions that HSPs can buffer against not only the effects of heat, but also mutations-a combination of factors both likely to increase in a warming world.

Supplementary Information

The online version contains supplementary material available at 10.1007/s10682-022-10209-1.

Evolutionary action of mutations reveals antimicrobial resistance genes in Escherichia coli

Since antibiotic development lags, we search for potential drug targets through directed evolution experiments. A challenge is that many resistance genes hide in a noisy mutational background as mutator clones emerge in the adaptive population. Here, to overcome this noise, we quantify the impact of mutations through evolutionary action (EA). After sequencing ciprofloxacin or colistin resistance strains grown under different mutational regimes, we find that an elevated sum of the evolutionary action of mutations in a gene identifies known resistance drivers. This EA integration approach also suggests new antibiotic resistance genes which are then shown to provide a fitness advantage in competition experiments. Moreover, EA integration analysis of clinical and environmental isolates of antibiotic resistant of E. coli identifies gene drivers of resistance where a standard approach fails. Together these results inform the genetic basis of de novo colistin resistance and support the robust discovery of phenotype-driving genes via the evolutionary action of genetic perturbations in fitness landscapes.

Complex Ecotype Dynamics Evolve in Response to Fluctuating Resources

Ecotypic diversification and its associated cooperative behaviors are frequently observed in natural microbial populations whose access to resources is often sporadic. However, the extent to which fluctuations in resource availability influence the emergence of cooperative ecotypes is not fully understood. To determine how exposure to repeated resource limitation affects the establishment and long-term maintenance of ecotypes in a structured environment, we followed 32 populations of Escherichia coli evolving to either 1-day or 10-day feast/famine cycles for 900 days. Population-level analysis revealed that compared to populations evolving to 1-day cycles, 10-day populations evolved increased biofilm density, higher parallelism in mutational targets, and increased mutation rates. As previous investigations of evolution in structured environments have identified biofilm formation as the earliest observable phenotype associated with diversification of ecotypes, we revived cultures midway through the evolutionary process and conducted additional genomic, transcriptional, and phenotypic analyses of clones isolated from these evolving populations. We found not only that 10-day feast/famine cycles support multiple ecotypes but also that these ecotypes exhibit cooperative behavior. Consistent with the black queen hypothesis, or evolution of cooperation by gene loss, transcriptomic evidence suggests the evolution of bidirectional cross-feeding behaviors based on essential resources. These results provide insight into how analogous cooperative relationships may emerge in natural microbial communities. IMPORTANCE Despite regular feast and famine conditions representing an environmental pressure that is commonly encountered by microbial communities, the evolutionary outcomes of repeated cycles of feast and famine have been less studied. By experimentally evolving initially isogenic Escherichia coli populations to 10-day feast/famine cycles, we observed rapid diversification into ecotypes with evidence of bidirectional cross-feeding on costly resources and frequency-dependent fitness. Although unidirectional cross-feeding has been repeatedly observed to evolve in laboratory culture, most investigations of bidirectional cooperative behaviors in microbial populations have been conducted in engineered communities. This work demonstrates the de novo evolution of black queen relationships in a microbial population originating from a single ancestor, providing a model for investigation of the eco-evolutionary processes leading to mutualistic cooperation.

Adaptive antimicrobial resistance, a description of microbial variants, and their relevance to periprosthetic joint infection

Periprosthetic joint infection (PJI) is a difficult complication requiring a comprehensive eradication protocol. Cure rates have essentially stalled in the last two decades, using methods of antimicrobial cement joint spacers and parenteral antimicrobial agents. Functional spacers with higher-dose antimicrobial-loaded cement and antimicrobial-loaded calcium sulphate beads have emphasized local antimicrobial delivery on the premise that high-dose local antimicrobial delivery will enhance eradication. However, with increasing antimicrobial pressures, microbiota have responded with adaptive mechanisms beyond traditional antimicrobial resistance genes. In this review we describe adaptive resistance mechanisms that are relevant to the treatment of PJI. Some mechanisms are well known, but others are new. The objective of this review is to inform clinicians of the known adaptive resistance mechanisms of microbes relevant to PJI. We also discuss the implications of these adaptive mechanisms in the future treatment of PJI. Cite this article: Bone Joint J 2022;104-B(5):575-580.

Characterization of Escherichia coli from Water and Food Sold on the Streets of Maputo: Molecular Typing, Virulence Genes, and Antibiotic Resistance

The aim of this study was to investigate the pathogenic potential and antibiotic resistance of 59 Escherichia coli isolates from ready-to-eat (RTE) street food (n = 31) and drinking water (n = 28) sold in the city of Maputo, Mozambique. The isolates were characterized by XbaI subtyping analysis via pulsed field gel electrophoresis. Multiplex PCRs were performed targeting five virulence genes (stx, lt, st, astA, and eae) and three groups of antibiotic-resistant genes, namely ß-lactamases (extended-spectrum ß-lactamase and AmpC), tetracycline (tetA, tetB, and tetM) and sulfamethoxazole/trimethoprim (sul1, sul2, and sul3). The stx virulence gene, encoding the Shiga/Vero (VT) toxin produced by the verotoxin-producing E. coli (VTEC), was identified with similar frequency in isolates from food (5/31) and water (6/28). The highest percentages of resistant isolates from food and water were found for ß-lactams imipenem (35.5 and 39.3%, respectively) and ampicillin (39.3 and 46.4%, respectively). Multidrug resistance was observed in 31.3% of the isolates, being higher in E. coli isolates from water (45.5%) compared to RTE street food isolates (19.2%). Virulence genes were detected in 73% of the multidrug-resistant isolates. Concerning antibiotic-resistant genes, ESBL was the most frequent (57.7%) among β-lactamases while tetA was the most frequent (50%) among non-β-lactamases.

Co-option of stress mechanisms in the origin of evolutionary novelties

It is widely accepted that stressful conditions can facilitate evolutionary change. The mechanisms elucidated thus far accomplish this with a generic increase in heritable variation that facilitates more rapid adaptive evolution, often via plastic modifications of existing characters. Through scrutiny of different meanings of stress in biological research, and an explicit recognition that stressors must be characterized relative to their effect on capacities for maintaining functional integrity, we distinguish between: (1) previously identified stress‐responsive mechanisms that facilitate evolution by maintaining an adaptive fit with the environment, and (2) the co‐option of stress‐responsive mechanisms that are specific to stressors leading to the origin of novelties via compensation. Unlike standard accounts of gene co‐option that identify component sources of evolutionary change, our model documents the cost‐benefit trade‐offs and thereby explains how one mechanism—an immediate response to acute stress—is transformed evolutionarily into another—routine protection from recurring stressors. We illustrate our argument with examples from cell type origination as well as processes and structures at higher levels of organization. These examples suggest a general principle of evolutionary origination based on the capacity to switch between regulatory states related to reproduction and proliferation versus survival and differentiation.

Development of a genome-targeting mutator for the adaptive evolution of microbial cells

Methods that can randomly introduce mutations in the microbial genome have been used for classical genetic screening and, more recently, the evolutionary engineering of microbial cells. However, most methods rely on either cell-damaging agents or disruptive mutations of genes that are involved in accurate DNA replication, of which the latter requires prior knowledge of gene functions, and thus, is not easily transferable to other species. In this study, we developed a new mutator for in vivo mutagenesis that can directly modify the genomic DNA. Mutator protein, MutaEco, in which a DNA-modifying enzyme is fused to the α-subunit of Escherichia coli RNA polymerase, increases the mutation rate without compromising the cell viability and accelerates the adaptive evolution of E. coli for stress tolerance and utilization of unconventional carbon sources. This fusion strategy is expected to accommodate diverse DNA-modifying enzymes and may be easily adapted to various bacterial species.

Evolutionary Dynamics of Asexual Hypermutators Adapting to a Novel Environment

How microbes adapt to a novel environment is a central question in evolutionary biology. Although adaptive evolution must be fueled by beneficial mutations, whether higher mutation rates facilitate the rate of adaptive evolution remains unclear. To address this question, we cultured Escherichia coli hypermutating populations, in which a defective methyl-directed mismatch repair pathway causes a 140-fold increase in single-nucleotide mutation rates. In parallel with wild-type E. coli, populations were cultured in tubes containing Luria-Bertani broth, a complex medium known to promote the evolution of subpopulation structure. After 900 days of evolution, in three transfer schemes with different population-size bottlenecks, hypermutators always exhibited similar levels of improved fitness as controls. Fluctuation tests revealed that the mutation rates of hypermutator lines converged evolutionarily on those of wild-type populations, which may have contributed to the absence of fitness differences. Further genome-sequence analysis revealed that, although hypermutator populations have higher rates of genomic evolution, this largely reflects strong genetic linkage. Despite these linkage effects, the evolved population exhibits parallelism in fixed mutations, including those potentially related to biofilm formation, transcription regulation, and mutation-rate evolution. Together, these results are generally inconsistent with a hypothesized positive relationship between the mutation rate and the adaptive speed of evolution, and provide insight into how clonal adaptation occurs in novel environments.

Mutation rate dynamics reflect ecological change in an emerging zoonotic pathogen

Mutation rates vary both within and between bacterial species, and understanding what drives this variation is essential for understanding the evolutionary dynamics of bacterial populations. In this study, we investigate two factors that are predicted to influence the mutation rate: ecology and genome size. We conducted mutation accumulation experiments on eight strains of the emerging zoonotic pathogen Streptococcus suis. Natural variation within this species allows us to compare tonsil carriage and invasive disease isolates, from both more and less pathogenic populations, with a wide range of genome sizes. We find that invasive disease isolates have repeatedly evolved mutation rates that are higher than those of closely related carriage isolates, regardless of variation in genome size. Independent of this variation in overall rate, we also observe a stronger bias towards G/C to A/T mutations in isolates from more pathogenic populations, whose genomes tend to be smaller and more AT-rich. Our results suggest that ecology is a stronger correlate of mutation rate than genome size over these timescales, and that transitions to invasive disease are consistently accompanied by rapid increases in mutation rate. These results shed light on the impact that ecology can have on the adaptive potential of bacterial pathogens.

Genomic Changes and Genetic Divergence of Vibrio alginolyticus Under Phage Infection Stress Revealed by Whole-Genome Sequencing and Resequencing

Bacteriophages (phages) and their bacterial hosts were the most abundant and genetically highly diverse organisms on the earth. In this study, a series of phage-resistant mutant (PRM) strains derived from Vibrio alginolyticus were isolated and Infrequent-restriction-site PCR (IRS-PCR) was used to investigate the genetic diversity of the PRM strains. Phenotypic variations of eight PRM strains were analyzed using profiles of utilizing carbon sources and chemical sensitivity. Genetic variations of eight PRM strains and coevolved V. alginolyticus populations with phages were analyzed by whole-genome sequencing and resequencing, respectively. The results indicated that eight genetically discrepant PRM stains exhibited abundant and abundant phenotypic variations. Eight PRM strains and coevolved V. alginolyticus populations (VE1, VE2, and VE3) contained numerous single nucleotide variations (SNVs) and insertions/indels (InDels) and exhibited obvious genetic divergence. Most of the SNVs and InDels in coding genes were related to the synthesis of flagellar, extracellular polysaccharide (EPS), which often served as the receptors of phage invasion. The PRM strains and the coevolved cell populations also contained frequent mutations in tRNA and rRNA genes. Two out of three coevolved populations (VE1 and VE2) contained a large mutation segment severely deconstructing gene nrdA, which was predictably responsible for the booming of mutation rate in the genome. In summary, numerous mutations and genetic divergence were detected in the genomes of V. alginolyticus PRM strains and in coevolved cell populations of V. alginolyticus under phage infection stress. The phage infection stress may provide an important force driving genomic evolution of V. alginolyticus.

Genotoxic Agents Produce Stressor-Specific Spectra of Spectinomycin Resistance Mutations Based on Mechanism of Action and Selection in Bacillus subtilis

Mutagenesis is integral for bacterial evolution and the development of antibiotic resistance. Environmental toxins and stressors are known to elevate the rate of mutagenesis through direct DNA toxicity, known as stress-associated mutagenesis, or via a more general stress-induced process that relies on intrinsic bacterial pathways. Here, we characterize the spectra of mutations induced by an array of different stressors using high-throughput sequencing to profile thousands of spectinomycin-resistant colonies of Bacillus subtilis. We found 69 unique mutations in the rpsE and rpsB genes, and that each stressor leads to a unique and specific spectrum of antibiotic-resistance mutations. While some mutations clearly reflected the DNA damage mechanism of the stress, others were likely the result of a more general stress-induced mechanism. To determine the relative fitness of these mutants under a range of antibiotic selection pressures, we used multistrain competitive fitness experiments and found an additional landscape of fitness and resistance. The data presented here support the idea that the environment in which the selection is applied (mutagenic stressors that are present), as well as changes in local drug concentration, can significantly alter the path to spectinomycin resistance in B. subtilis.

Evolutionary ecology theory - microbial population structure

Microbial populations typically show a large degree of intra-population diversity. This diversity is intertwined with the structure of the population. Here, we discuss endogenous and exogenous drivers of population structure in microbes and how the population structure can affect evolutionary dynamics and vice versa. Endogenous structure, which can be genetic or demographic, is driven by the ecology and evolutionary dynamics within the population. Exogenous structure is typically driven by the spatial and temporal properties of the environment. A particular interesting case arises when also this exogenous structure experiences feedbacks from the microbial population.

Interplay of population size and environmental fluctuations: A new explanation for fitness cost rarity in asexuals

Theoretical models of ecological specialisation commonly assume that adaptation to one environment leads to fitness reductions (costs) in others. However, experiments often fail to detect such costs. We addressed this conundrum using experimental evolution with Escherichia coli in several constant and fluctuating environments at multiple population sizes. We found that in fluctuating environments, smaller populations paid significant costs, but larger ones avoided them altogether. Contrastingly, in constant environments, larger populations paid more costs than the smaller ones. Overall, large population sizes and fluctuating environments led to cost avoidance only when present together. Mutational frequency distributions obtained from whole-genome whole-population sequencing revealed that the primary mechanism of cost avoidance was the enrichment of multiple beneficial mutations within the same lineage. Since the conditions revealed by our study for avoiding costs are widespread, it provides a novel explanation of the conundrum of why the costs expected in theory are rarely detected in experiments.

Spatiotemporal Manipulation of the Mismatch Repair System of Pseudomonas putida Accelerates Phenotype Emergence

The development of complex phenotypes in industrially relevant bacteria is a major goal of metabolic engineering, which encompasses the implementation of both rational and random approaches. In the latter case, several tools have been developed toward increasing mutation frequencies, yet the precise control of mutagenesis processes in cell factories continues to represent a significant technical challenge. Pseudomonas species are endowed with one of the most efficient DNA mismatch repair (MMR) systems found in the bacterial domain. Here, we investigated if the endogenous MMR system could be manipulated as a general strategy to artificially alter mutation rates in Pseudomonas species. To bestow a conditional mutator phenotype in the platform bacterium Pseudomonas putida, we constructed inducible mutator devices to modulate the expression of the dominant-negative mutL^E36K allele. Regulatable overexpression of mutL^E36K in a broad-host-range, easy-to-cure plasmid format resulted in a transitory inhibition of the MMR machinery, leading to a significant increase (up to 438-fold) in DNA mutation frequencies and a heritable fixation of mutations in the genome. Following such an accelerated mutagenesis-followed by selection approach, three phenotypes were successfully evolved: resistance to antibiotics streptomycin and rifampicin (either individually or combined) and reversion of a synthetic uracil auxotrophy. Thus, these mutator devices could be applied to accelerate the evolution of metabolic pathways in long-term evolutionary experiments, alternating cycles of (inducible) mutagenesis coupled to selection schemes toward the desired phenotype(s).

Self-selection of evolutionary strategies: adaptive versus non-adaptive forces

The evolution of complex genetic networks is shaped over the course of many generations through multiple mechanisms. These mechanisms can be broken into two predominant categories: adaptive forces, such as natural selection, and non-adaptive forces, such as recombination, genetic drift, and random mutation. Adaptive forces are influenced by the environment, where individuals better suited for their ecological niche are more likely to reproduce. This adaptive force results in a selective pressure which creates a bias in the reproduction of individuals with beneficial traits. Non-adaptive forces, in contrast, are not influenced by the environment: Random mutations occur in offspring regardless of whether they improve the fitness of the offspring. Both adaptive and non-adaptive forces play critical roles in the development of a species over time, and both forces are intrinsically linked to one another. We hypothesize that even under a simple sexual reproduction model, selective pressure will result in changes in the mutation rate and genome size. We tested this hypothesis by evolving Boolean networks using a modified genetic algorithm. Our results demonstrate that changes in environmental signals can result in selective pressure which affects mutation rate.

Stable leaders pave the way for cooperation under time-dependent exploration rates

The exploration of different behaviours is part of the adaptation repertoire of individuals to new environments. Here, we explore how the evolution of cooperative behaviour is affected by the interplay between exploration dynamics and social learning, in particular when individuals engage on prisoner's dilemma along the edges of a social network. We show that when the population undergoes a transition from strong to weak exploration rates a decline in the overall levels of cooperation is observed. However, if the rate of decay is lower in highly connected individuals (Leaders) than for the less connected individuals (Followers) then the population is able to achieve higher levels of cooperation. Finally, we show that minor differences in selection intensities (the degree of determinism in social learning) and individual exploration rates, can translate into major differences in the observed collective dynamics.

Increasing Solvent Tolerance to Improve Microbial Production of Alcohols, Terpenoids and Aromatics

Fuels and polymer precursors are widely used in daily life and in many industrial processes. Although these compounds are mainly derived from petrol, bacteria and yeast can produce them in an environment-friendly way. However, these molecules exhibit toxic solvent properties and reduce cell viability of the microbial producer which inevitably impedes high product titers. Hence, studying how product accumulation affects microbes and understanding how microbial adaptive responses counteract these harmful defects helps to maximize yields. Here, we specifically focus on the mode of toxicity of industry-relevant alcohols, terpenoids and aromatics and the associated stress-response mechanisms, encountered in several relevant bacterial and yeast producers. In practice, integrating heterologous defense mechanisms, overexpressing native stress responses or triggering multiple protection pathways by modifying the transcription machinery or small RNAs (sRNAs) are suitable strategies to improve solvent tolerance. Therefore, tolerance engineering, in combination with metabolic pathway optimization, shows high potential in developing superior microbial producers.

Phenotypic and molecular evolution across 10,000 generations in laboratory budding yeast populations

Laboratory experimental evolution provides a window into the details of the evolutionary process. To investigate the consequences of long-term adaptation, we evolved 205 Saccharomyces cerevisiae populations (124 haploid and 81 diploid) for ~10,000,000 generations in three environments. We measured the dynamics of fitness changes over time, finding repeatable patterns of declining adaptability. Sequencing revealed that this phenotypic adaptation is coupled with a steady accumulation of mutations, widespread genetic parallelism, and historical contingency. In contrast to long-term evolution in E. coli, we do not observe long-term coexistence or populations with highly elevated mutation rates. We find that evolution in diploid populations involves both fixation of heterozygous mutations and frequent loss-of-heterozygosity events. Together, these results help distinguish aspects of evolutionary dynamics that are likely to be general features of adaptation across many systems from those that are specific to individual organisms and environmental conditions.

High-throughput analysis of adaptation using barcoded strains of Saccharomyces cerevisiae

BACKGROUND

Experimental evolution of microbes can be used to empirically address a wide range of questions about evolution and is increasingly employed to study complex phenomena ranging from genetic evolution to evolutionary rescue. Regardless of experimental aims, fitness assays are a central component of this type of research, and low-throughput often limits the scope and complexity of experimental evolution studies. We created an experimental evolution system in Saccharomyces cerevisiae that utilizes genetic barcoding to overcome this challenge.

RESULTS

We first confirm that barcode insertions do not alter fitness and that barcode sequencing can be used to efficiently detect fitness differences via pooled competition-based fitness assays. Next, we examine the effects of ploidy, chemical stress, and population bottleneck size on the evolutionary dynamics and fitness gains (adaptation) in a total of 76 experimentally evolving, asexual populations by conducting 1,216 fitness assays and analyzing 532 longitudinal-evolutionary samples collected from the evolving populations. In our analysis of these data we describe the strengths of this experimental evolution system and explore sources of error in our measurements of fitness and evolutionary dynamics.

CONCLUSIONS

Our experimental treatments generated distinct fitness effects and evolutionary dynamics, respectively quantified via multiplexed fitness assays and barcode lineage tracking. These findings demonstrate the utility of this new resource for designing and improving high-throughput studies of experimental evolution. The approach described here provides a framework for future studies employing experimental designs that require high-throughput multiplexed fitness measurements.

Genomic Stress Responses Drive Lymphocyte Evolvability: An Ancient and Ubiquitous Mechanism

Somatic diversification of antigen receptor genes depends on the activity of enzymes whose homologs participate in a mutagenic DNA repair in unicellular species. Indeed, by engaging error-prone polymerases, gap filling molecules and altered mismatch repair pathways, lymphocytes utilize conserved components of genomic stress response systems, which can already be found in bacteria and archaea. These ancient systems of mutagenesis and repair act to increase phenotypic diversity of microbial cell populations and operate to enhance their ability to produce fit variants during stress. Coopted by lymphocytes, the ancient mutagenic processing systems retained their diversification functions instilling the adaptive immune cells with enhanced evolvability and defensive capacity to resist infection and damage. As reviewed here, the ubiquity and conserved character of specialized variation-generating mechanisms from bacteria to lymphocytes highlight the importance of these mechanisms for evolution of life in general.

Dynamics of genetic variation in transcription factors and its implications for the evolution of regulatory networks in Bacteria

The evolution of regulatory networks in Bacteria has largely been explained at macroevolutionary scales through lateral gene transfer and gene duplication. Transcription factors (TF) have been found to be less conserved across species than their target genes (TG). This would be expected if TFs accumulate mutations faster than TGs. This hypothesis is supported by several lab evolution studies which found TFs, especially global regulators, to be frequently mutated. Despite these studies, the contribution of point mutations in TFs to the evolution of regulatory network is poorly understood. We tested if TFs show greater genetic variation than their TGs using whole-genome sequencing data from a large collection of Escherichia coli isolates. TFs were less diverse than their TGs across natural isolates, with TFs of large regulons being more conserved. In contrast, TFs showed higher mutation frequency in adaptive laboratory evolution experiments. However, over long-term laboratory evolution spanning 60 000 generations, mutation frequency in TFs gradually declined after a rapid initial burst. Extrapolating the dynamics of genetic variation from long-term laboratory evolution to natural populations, we propose that point mutations, conferring large-scale gene expression changes, may drive the early stages of adaptation but gene regulation is subjected to stronger purifying selection post adaptation.

Experimental Evolution of Legume Symbionts: What Have We Learnt?

Rhizobia, the nitrogen-fixing symbionts of legumes, are polyphyletic bacteria distributed in many alpha- and beta-proteobacterial genera. They likely emerged and diversified through independent horizontal transfers of key symbiotic genes. To replay the evolution of a new rhizobium genus under laboratory conditions, the symbiotic plasmid of Cupriavidus taiwanensis was introduced in the plant pathogen Ralstonia solanacearum, and the generated proto-rhizobium was submitted to repeated inoculations to the C. taiwanensis host, Mimosa pudica L.. This experiment validated a two-step evolutionary scenario of key symbiotic gene acquisition followed by genome remodeling under plant selection. Nodulation and nodule cell infection were obtained and optimized mainly via the rewiring of regulatory circuits of the recipient bacterium. Symbiotic adaptation was shown to be accelerated by the activity of a mutagenesis cassette conserved in most rhizobia. Investigating mutated genes led us to identify new components of R. solanacearum virulence and C. taiwanensis symbiosis. Nitrogen fixation was not acquired in our short experiment. However, we showed that post-infection sanctions allowed the increase in frequency of nitrogen-fixing variants among a non-fixing population in the M. pudica-C. taiwanensis system and likely allowed the spread of this trait in natura. Experimental evolution thus provided new insights into rhizobium biology and evolution.

Low mutational load and high mutation rate variation in gut commensal bacteria

Bacteria generally live in species-rich communities, such as the gut microbiota. Yet little is known about bacterial evolution in natural ecosystems. Here, we followed the long-term evolution of commensal Escherichia coli in the mouse gut. We observe the emergence of mutation rate polymorphism, ranging from wild-type levels to 1,000-fold higher. By combining experiments, whole-genome sequencing, and in silico simulations, we identify the molecular causes and explore the evolutionary conditions allowing these hypermutators to emerge and coexist within the microbiota. The hypermutator phenotype is caused by mutations in DNA polymerase III proofreading and catalytic subunits, which increase mutation rate by approximately 1,000-fold and stabilise hypermutator fitness, respectively. Strong mutation rate variation persists for >1,000 generations, with coexistence between lineages carrying 4 to >600 mutations. The in vivo molecular evolution pattern is consistent with fitness effects of deleterious mutations s_d ≤ 10⁻⁴/generation, assuming a constant effect or exponentially distributed effects with a constant mean. Such effects are lower than typical in vitro estimates, leading to a low mutational load, an inference that is observed in in vivo and in vitro competitions. Despite large numbers of deleterious mutations, we identify multiple beneficial mutations that do not reach fixation over long periods of time. This indicates that the dynamics of beneficial mutations are not shaped by constant positive Darwinian selection but could be explained by other evolutionary mechanisms that maintain genetic diversity. Thus, microbial evolution in the gut is likely characterised by partial sweeps of beneficial mutations combined with hitchhiking of slightly deleterious mutations, which take a long time to be purged because they impose a low mutational load. The combination of these two processes could allow for the long-term maintenance of intraspecies genetic diversity, including mutation rate polymorphism. These results are consistent with the pattern of genetic polymorphism that is emerging from metagenomics studies of the human gut microbiota, suggesting that we have identified key evolutionary processes shaping the genetic composition of this community.

Weak-effect deleterious mutations and negative frequency–dependent selection, acting on beneficial mutations, shape the dynamics of molecular evolution within the mouse gut microbiota.

Irregularities in genetic variation and mutation rates with environmental stresses

The appearance of new mutations is determined by the equilibrium between DNA error formation and repair. In bacteria like Escherichia coli, stresses are thought shift this balance towards increased mutagenesis. Recent findings, however, suggest a very uneven relationship between stress and mutations. Only a subset of stressful environments increase the net rate of mutation and different forms of nutritional stress (such as oxygen, carbon or phosphorus limitations) result in markedly different mutation rates after similar reductions in growth rate. Moreover, different stresses result in altered mutational spectra, with some increasing transposition and others increasing indel formation. Single-base substitution rates are lower with some stresses than in unstressed bacteria. Indeed, changes to the mix of mutations with stress are more widespread than a marked increase in net mutation rate. Much remains to be learned on how environments have unique mutational signatures and why some stresses are more mutagenic than others. Even beyond stress-induced genetic variation, the fundamental unresolved question in the stress-mutation relationship is the adaptive value of different types of mutations and mutation rates; is transposition, for example, more advantageous under anaerobic conditions? It remains to be investigated whether stress-specific genetic variation impacts on evolvability differentially in distinct environments.

IAMBEE: a web-service for the identification of adaptive pathways from parallel evolved clonal populations

IAMBEE is a web server designed for the Identification of Adaptive Mutations in Bacterial Evolution Experiments (IAMBEE). Input data consist of genotype information obtained from independently evolved clonal populations or strains that show the same adapted behavior (phenotype). To distinguish adaptive from passenger mutations, IAMBEE searches for neighborhoods in an organism-specific interaction network that are recurrently mutated in the adapted populations. This search for recurrently mutated network neighborhoods, as proxies for pathways is driven by additional information on the functional impact of the observed genetic changes and their dynamics during adaptive evolution. In addition, the search explicitly accounts for the differences in mutation rate between the independently evolved populations. Using this approach, IAMBEE allows exploiting parallel evolution to identify adaptive pathways. The web-server is freely available at http://bioinformatics.intec.ugent.be/iambee/ with no login requirement.

The Essential Role of Hypermutation in Rapid Adaptation to Antibiotic Stress

A common outcome of antibiotic exposure in patients and in vitro is the evolution of a hypermutator phenotype that enables rapid adaptation by pathogens. While hypermutation is a robust mechanism for rapid adaptation, it requires trade-offs between the adaptive mutations and the more common "hitchhiker" mutations that accumulate from the increased mutation rate. Using quantitative experimental evolution, we examined the role of hypermutation in driving the adaptation of Pseudomonas aeruginosa to colistin. Metagenomic deep sequencing revealed 2,657 mutations at ≥5% frequency in 1,197 genes and 761 mutations in 29 endpoint isolates. By combining genomic information, phylogenetic analyses, and statistical tests, we showed that evolutionary trajectories leading to resistance could be reliably discerned. In addition to known alleles such as pmrB, hypermutation allowed identification of additional adaptive alleles with epistatic relationships. Although hypermutation provided a short-term fitness benefit, it was detrimental to overall fitness. Alarmingly, a small fraction of the colistin-adapted population remained colistin susceptible and escaped hypermutation. In a clinical population, such cells could play a role in reestablishing infection upon withdrawal of colistin. We present here a framework for evaluating the complex evolutionary trajectories of hypermutators that applies to both current and emerging pathogen populations.

Differences in mutational processes and intra-tumour heterogeneity between organs: The local selective filter hypothesis

Extensive diversity (genetic, cytogenetic, epigenetic and phenotypic) exists within and between tumours, but reasons behind these variations, as well as their consistent hierarchical pattern between organs, are poorly understood at the moment. We argue that these phenomena are, at least partially, explainable by the evolutionary ecology of organs' theory, in the same way that environmental adversity shapes mutation rates and level of polymorphism in organisms. Organs in organisms can be considered as specialized ecosystems that are, for ecological and evolutionary reasons, more or less efficient at suppressing tumours. When a malignancy does arise in an organ applying strong selection pressure on tumours, its constituent cells are expected to display a large range of possible surviving strategies, from hyper mutator phenotypes relying on bet-hedging to persist (high mutation rates and high diversity), to few poorly variable variants that become invisible to natural defences. In contrast, when tumour suppression is weaker, selective pressure favouring extreme surviving strategies is relaxed, and tumours are moderately variable as a result. We provide a comprehensive overview of this hypothesis. Lay summary: Different levels of mutations and intra-tumour heterogeneity have been observed between cancer types and organs. Anti-cancer defences are unequal between our organs. We propose that mostly aggressive neoplasms (i.e. higher mutational and ITH levels), succeed in emerging and developing in organs with strong defences.

Simulations reveal challenges to artificial community selection and possible strategies for success

Multispecies microbial communities often display "community functions" arising from interactions of member species. Interactions are often difficult to decipher, making it challenging to design communities with desired functions. Alternatively, similar to artificial selection for individuals in agriculture and industry, one could repeatedly choose communities with the highest community functions to reproduce by randomly partitioning each into multiple "Newborn" communities for the next cycle. However, previous efforts in selecting complex communities have generated mixed outcomes that are difficult to interpret. To understand how to effectively enact community selection, we simulated community selection to improve a community function that requires 2 species and imposes a fitness cost on one or both species. Our simulations predict that improvement could be easily stalled unless various aspects of selection are carefully considered. These aspects include promoting species coexistence, suppressing noncontributors, choosing additional communities besides the highest functioning ones to reproduce, and reducing stochastic fluctuations in the biomass of each member species in Newborn communities. These considerations can be addressed experimentally. When executed effectively, community selection is predicted to improve costly community function, and may even force species to evolve slow growth to achieve species coexistence. Our conclusions hold under various alternative model assumptions and are therefore applicable to a variety of communities.

Yeast Spontaneous Mutation Rate and Spectrum Vary with Environment

Mutation is the ultimate genetic source of evolution and biodiversity, but to what extent the environment impacts mutation rate and spectrum is poorly understood. Past studies discovered mutagenesis induced by antibiotic treatment or starvation, but its relevance and importance to long-term evolution is unclear because these severe stressors typically halt cell growth and/or cause substantial cell deaths. Here, we quantify the mutation rate and spectrum in Saccharomyces cerevisiae by whole-genome sequencing following mutation accumulation in each of seven environments with relatively rapid cell growths and minimal cell deaths. We find the point mutation rate per generation to differ by 3.6-fold among the seven environments, generally increasing in environments with slower cell growths. This trend renders the mutation rate per year more constant than that per generation across environments, which has implications for neutral evolution and the molecular clock. Additionally, we find substantial among-environment variations in mutation spectrum, such as the transition to transversion ratio and AT mutational bias. Other main mutation types, including small insertion or deletion, segmental duplication or deletion, and chromosome gain or loss also tend to occur more frequently in environments where yeast grows more slowly. In contrast to these findings from the nuclear genome, the yeast mitochondrial mutation rate rises with the growth rate, consistent with the metabolic rate hypothesis. Together, these observations indicate that environmental changes, which are ubiquitous in nature, influence not only natural selection, but also the amount and type of mutations available to selection, and suggest that ignoring the latter impact, as is currently practiced, may mislead evolutionary inferences.