Evolution in microbes

An interdisciplinary perspective of the built-environment microbiome

The built environment provides an excellent setting for interdisciplinary research on the dynamics of microbial communities. The system is simplified compared to many natural settings, and to some extent the entire environment can be manipulated, from architectural design to materials use, air flow, human traffic, and capacity to disrupt microbial communities through cleaning. Here, we provide an overview of the ecology of the microbiome in the built environment. We address niche space and refugia, population, and community (metagenomic) dynamics, spatial ecology within a building, including the major microbial transmission mechanisms, as well as evolution. We also address landscape ecology, connecting microbiomes between physically separated buildings. At each stage, we pay particular attention to the actual and potential interface between disciplines, such as ecology, epidemiology, materials science, and human social behavior. We end by identifying some opportunities for future interdisciplinary research on the microbiome of the built environment.

Evolutionary trajectories of β-lactam resistance in Enterococcus faecalis strains

Resistance to ampicillin and imipenem in Enterococcus faecalis is infrequent. However, the evolution of resistance can occur through prolonged antibiotic exposure during the treatment of chronic infections. In this study, we conducted a long-term evolution experiment using four genetically diverse strains of E. faecalis with varying susceptibilities to ampicillin and imipenem. Each strain was subjected to increasing concentrations of either ampicillin or imipenem over 200 days, with three independent replicates for each strain. Selective pressure from imipenem led to the rapid selection of highly resistant lineages across all genetic backgrounds, compared to ampicillin. In addition to high resistance, we describe, for the first time, the evolution of a β-lactam-dependent phenotype observed in lineages from all backgrounds. Whole-genome sequencing and bioinformatic analysis revealed mutations in three main functional classes: genes involved in cell wall synthesis and degradation, genes in the walK/R two-component system, and genes in the c-di-AMP pathway. Our analysis identified new mutations in genes known to be involved in resistance as well as novel genes potentially associated with resistance. Furthermore, the newly described β-lactam-dependent phenotype was correlated with the inactivation of c-di-AMP degradation, resulting in high levels of this second messenger. Together, these data highlight the diverse genetic mechanisms underlying resistance to ampicillin and imipenem in E. faecalis. The emergence of high resistance levels and β-lactam dependency underscores the importance of understanding evolutionary dynamics in the development of antibiotic resistance.

IMPORTANCE

Enterococcus faecalis is a major human pathogen, and treatment is frequently compromised by poor response to first-line antibiotics such as ampicillin. Understanding the factors that play a role in susceptibility/resistance to these drugs will help guide the development of much-needed treatments.

Evolutionary trajectories of β-lactam resistance in Enterococcus faecalis strains

Resistance to ampicillin and imipenem in Enterococcus faecalis is infrequent. However, the evolution of resistance can occur through prolonged antibiotic exposure during the treatment of chronic infections. In this study, we conducted a Long-Term Evolution Experiment (LTEE) using four genetically diverse strains of E. faecalis with varying susceptibilities to ampicillin and imipenem. Each strain was subjected to increasing concentrations of either ampicillin or imipenem over 200 days, with three independent replicates for each strain. Selective pressure from imipenem led to the rapid selection of highly resistant lineages across all genetic backgrounds, compared to ampicillin. In addition to high resistance, we describe, for the first time, the evolution of a β-lactam dependent phenotype observed in lineages from all backgrounds. WGS and bioinformatic analysis revealed mutations in three main functional classes: genes involved in cell wall synthesis and degradation, genes in the walK/R two-component system, and genes in the c-di-AMP pathway. Our analysis identified new mutations in genes known to be involved in resistance as well as novel genes potentially associated with resistance. Furthermore, the newly described β-lactam dependent phenotype was correlated with the inactivation of c-di-AMP degradation, resulting in high levels of this second messenger. Together, these data highlight the diverse genetic mechanisms underlying resistance to ampicillin and imipenem in E. faecalis . The emergence of high resistance levels and β-lactam dependency underscores the importance of understanding evolutionary dynamics in the development of antibiotic resistance.

Importance

E. faecalis is a major human pathogen, and treatment is frequently compromised by poor response to first-line antibiotics such ampicillin. Understanding the factors that play a role in susceptibility/resistance to these drugs will help guide the development of much needed treatments.

Evolution of a bistable genetic system in fluctuating and nonfluctuating environments

Epigenetic mechanisms can generate bacterial lineages capable of spontaneously switching between distinct phenotypes. Currently, mathematical models and simulations propose epigenetic switches as a mechanism of adaptation to deal with fluctuating environments. However, bacterial evolution experiments for testing these predictions are lacking. Here, we exploit an epigenetic switch in Salmonella enterica, the opvAB operon, to show clear evidence that OpvAB bistability persists in changing environments but not in stable conditions. Epigenetic control of transcription in the opvAB operon produces OpvABOFF (phage-sensitive) and OpvABON (phage-resistant) cells in a reversible manner and may be interpreted as an example of bet-hedging to preadapt Salmonella populations to the encounter with phages. Our experimental observations and computational simulations illustrate the adaptive value of epigenetic variation as an evolutionary strategy for mutation avoidance in fluctuating environments. In addition, our study provides experimental support to game theory models predicting that phenotypic heterogeneity is advantageous in changing and unpredictable environments.

Rewiring Saccharomyces cerevisiae metabolism for optimised Taxol® precursors production

Saccharomyces cerevisiae has been conveniently used to produce Taxol® anticancer drug early precursors. However, the harmful impact of oxidative stress by the first cytochrome P450-reductase enzymes (CYP725A4-POR) of Taxol® pathway has hampered sufficient progress in yeast. Here, we evolved an oxidative stress-resistant yeast strain with three-fold higher titre of their substrate, taxadiene. The performance of the evolved and parent strains were then evaluated in galactose-limited chemostats before and under the oxidative stress by an oxidising agent. The interaction of evolution and oxidative stress was comprehensively evaluated through transcriptomics and metabolite profiles integration in yeast enzyme-constrained genome scale model. Overall, the evolved strain showed improved respiration, reduced overflow metabolites production and oxidative stress re-induction tolerance. The cross-protection mechanism also potentially contributed to better heme, flavin and NADPH availability, essential for CYP725A4 and POR optimal activity in yeast. The results imply that the evolved strain is a robust cell factory for future efforts towards Taxol© production.

Bayesian inference of relative fitness on high-throughput pooled competition assays

The tracking of lineage frequencies via DNA barcode sequencing enables the quantification of microbial fitness. However, experimental noise coming from biotic and abiotic sources complicates the computation of a reliable inference. We present a Bayesian pipeline to infer relative microbial fitness from high-throughput lineage tracking assays. Our model accounts for multiple sources of noise and propagates uncertainties throughout all parameters in a systematic way. Furthermore, using modern variational inference methods based on automatic differentiation, we are able to scale the inference to a large number of unique barcodes. We extend this core model to analyze multi-environment assays, replicate experiments, and barcodes linked to genotypes. On simulations, our method recovers known parameters within posterior credible intervals. This work provides a generalizable Bayesian framework to analyze lineage tracking experiments. The accompanying open-source software library enables the adoption of principled statistical methods in experimental evolution.

Quinoline derivatives volunteering against antimicrobial resistance: rational approaches, design strategies, structure activity relationship and mechanistic insights

Emergence of antimicrobial resistance has become a great threat to human species as there is shortage of development of new antimicrobial agents. So, its mandatary to combat AMR by initiating research and developing new novel antimicrobial agents. Among phytoconstituents, Quinoline (nitrogen containing heterocyclic) have played a wide role in providing new bioactive molecules. So, this review provides rational approaches, design strategies, structure activity relationship and mechanistic insights of newly developed quinoline derivatives as antimicrobial agents.

Collateral sensitivity: An evolutionary trade-off between antibiotic resistance mechanisms, attractive for dealing with drug-resistance crisis

Background

The discovery and development of antimicrobial drugs were one of the most significant advances in medicine, but the evolution of microbial resistance limited the efficiency of these drugs.

Aim

This paper reviews the collateral sensitivity in bacteria and its potential and limitation as a new target for treating infections.

Results and Discussion

Knowledge mechanisms of resistance to antimicrobial agents are useful to trace a practical approach to treat and control of resistant pathogens. The effect of a resistance mechanism to certain antibiotics on the susceptibility or resistance to other drugs is a key point that may be helpful for applying a strategy to control resistance challenges. In an evolutionary trade-off known as collateral sensitivity, the resistance mechanism to a certain drug may be mediated by the hypersensitivity to other drugs. Collateral sensitivity has been described for different drugs in various bacteria, but the molecular mechanisms affecting susceptibility are not well demonstrated. Collateral sensitivity could be studied to detect its potential in the battle against resistance crisis as well as in the treatment of pathogens adapting to antibiotics. Collateral sensitivity-based antimicrobial therapy may have the potential to limit the emergence of antibiotic resistance.

Collective behavior and nongenetic inheritance allow bacterial populations to adapt to changing environments

Collective behaviors require coordination among a group of individuals. As a result, individuals that are too phenotypically different from the rest of the group can be left out, reducing heterogeneity, but increasing coordination. If individuals also reproduce, the offspring can have different phenotypes from their parent(s). This raises the question of how these two opposing processes-loss of diversity by collective behaviors and generation of it through growth and inheritance-dynamically shape the phenotypic composition of an isogenic population. We examine this question theoretically using collective migration of chemotactic bacteria as a model system, where cells of different swimming phenotypes are better suited to navigate in different environments. We find that the differential loss of phenotypes caused by collective migration is environment-dependent. With cell growth, this differential loss enables migrating populations to dynamically adapt their phenotype compositions to the environment, enhancing migration through multiple environments. Which phenotypes are produced upon cell division depends on the level of nongenetic inheritance, and higher inheritance leads to larger composition adaptation and faster migration at steady state. However, this comes at the cost of slower responses to new environments. Due to this trade-off, there is an optimal level of inheritance that maximizes migration speed through changing environments, which enables a diverse population to outperform a nondiverse one. Growing populations might generally leverage the selection-like effects provided by collective behaviors to dynamically shape their own phenotype compositions, without mutations.

Phenotypic-dependent variability and the emergence of tolerance in bacterial populations

Ecological and evolutionary dynamics have been historically regarded as unfolding at broadly separated timescales. However, these two types of processes are nowadays well-documented to intersperse much more tightly than traditionally assumed, especially in communities of microorganisms. Advancing the development of mathematical and computational approaches to shed novel light onto eco-evolutionary problems is a challenge of utmost relevance. With this motivation in mind, here we scrutinize recent experimental results showing evidence of rapid evolution of tolerance by lag in bacterial populations that are periodically exposed to antibiotic stress in laboratory conditions. In particular, the distribution of single-cell lag times-i.e., the times that individual bacteria from the community remain in a dormant state to cope with stress-evolves its average value to approximately fit the antibiotic-exposure time. Moreover, the distribution develops right-skewed heavy tails, revealing the presence of individuals with anomalously large lag times. Here, we develop a parsimonious individual-based model mimicking the actual demographic processes of the experimental setup. Individuals are characterized by a single phenotypic trait: their intrinsic lag time, which is transmitted with variation to the progeny. The model-in a version in which the amplitude of phenotypic variations grows with the parent's lag time-is able to reproduce quite well the key empirical observations. Furthermore, we develop a general mathematical framework allowing us to describe with good accuracy the properties of the stochastic model by means of a macroscopic equation, which generalizes the Crow-Kimura equation in population genetics. Even if the model does not account for all the biological mechanisms (e.g., genetic changes) in a detailed way-i.e., it is a phenomenological one-it sheds light onto the eco-evolutionary dynamics of the problem and can be helpful to design strategies to hinder the emergence of tolerance in bacterial communities. From a broader perspective, this work represents a benchmark for the mathematical framework designed to tackle much more general eco-evolutionary problems, thus paving the road to further research avenues.

Waddington's Landscapes in the Bacterial World

Conrad Waddington’s epigenetic landscape, a visual metaphor for the development of multicellular organisms, is appropriate to depict the formation of phenotypic variants of bacterial cells. Examples of bacterial differentiation that result in morphological change have been known for decades. In addition, bacterial populations contain phenotypic cell variants that lack morphological change, and the advent of fluorescent protein technology and single-cell analysis has unveiled scores of examples. Cell-specific gene expression patterns can have a random origin or arise as a programmed event. When phenotypic cell-to-cell differences are heritable, bacterial lineages are formed. The mechanisms that transmit epigenetic states to daughter cells can have strikingly different levels of complexity, from the propagation of simple feedback loops to the formation of complex DNA methylation patterns. Game theory predicts that phenotypic heterogeneity can facilitate bacterial adaptation to hostile or unpredictable environments, serving either as a division of labor or as a bet hedging that anticipates future challenges. Experimental observation confirms the existence of both types of strategies in the bacterial world.

Cross-Resistance and the Mechanisms of Cephalosporin-Resistant Bacteria in Urinary Tract Infections Isolated in Indonesia

Urinary tract infection (UTI) by antibiotic-resistant strains has become increasingly problematic, with trends that differ from country to country. This study examined cross-resistance and the mechanisms of cephalosporin resistance in UTI-causative bacteria isolated in Indonesia. Antibiotic susceptibility tests based on Clinical Laboratory Standards Institute (CLSI) standards were done for UTI-causative strains (n = 50) isolated from patients in Indonesia in 2015-2016 and showed resistance against the third-generation cephalosporin. Mechanistic studies were carried out to confirm the presence of extended-spectrum β-lactamase (ESBL) genes, carbapenemase-related genes, the fosA3 gene related to fosfomycin resistance, and mutations of quinolone-resistance-related genes. Isolated UTI-causative bacteria included Escherichia coli (64.0%), Pseudomonas aeruginosa (16.0%), Klebsiella pneumoniae (10.0%), and others (10.0%). These strains showed 96.0% susceptibility to amikacin, 76.0% to fosfomycin, 90.0% to imipenem, 28.0% to levofloxacin, 92.0% to meropenem, and 74.0% to tazobactam/piperacillin. ESBL was produced by 68.0% of these strains. Mechanistic studies found no strains with carbapenemase genes but 6.0% of strains had the fosA3 gene. Seventy-two % of the strains had mutations in the gyrA gene and 74.0% in the parC gene. Most E. coli strains (87.5%) had Ser-83 → Leu and Asp-87 → Asn in gyrA and 93.8% of E. coli had Ser-80 → Ile in parC. There were significant correlations among mutations in gyrA and parC, and fosA3 gene detection (P < 0.05), respectively. To our knowledge, this is the first mechanistic study of antibiotic-cross-resistant UTI-causative bacteria in Indonesia. Further studies with a longer period of observation are necessary, especially for changes in carbapenem resistance without carbapenemase-related genes.

Searching for principles of microbial physiology

Why do evolutionarily distinct microorganisms display similar physiological behaviours? Why are transitions from high-ATP yield to low(er)-ATP yield metabolisms so widespread across species? Why is fast growth generally accompanied with low stress tolerance? Do these regularities occur because most microbial species are subject to the same selective pressures and physicochemical constraints? If so, a broadly-applicable theory might be developed that predicts common microbiological behaviours. Microbial systems biologists have been working out the contours of this theory for the last two decades, guided by experimental data. At its foundations lie basic principles from evolutionary biology, enzyme biochemistry, metabolism, cell composition and steady-state growth. The theory makes predictions about fitness costs and benefits of protein expression, physicochemical constraints on cell growth and characteristics of optimal metabolisms that maximise growth rate. Comparisons of the theory with experimental data indicates that microorganisms often aim for maximisation of growth rate, also in the presence of stresses; they often express optimal metabolisms and metabolic proteins at optimal concentrations. This review explains the current status of the theory for microbiologists; its roots, predictions, experimental evidence and future directions.

Virulence and antimicrobial resistance genes are enriched in the plasmidome of clinical Escherichia coli isolates compared with wastewater isolates from western Kenya

Many low-middle income countries in Africa have poorly-developed infectious disease monitoring systems. Here, we employed whole genome sequencing (WGS) to investigate the presence/absence of antimicrobial resistance (AMR) and virulence-associated (VA) genes in a collection of clinical and municipal wastewater Escherichia coli isolates from Kakamega, west Kenya. We were particularly interested to see whether, given the association between infection and water quality, the isolates from these geographically-linked environments might display similar genomic signatures. Phylogenetic analysis based on the core genes common to all of the isolates revealed two broad divisions, corresponding to the commensal/enterotoxigenic E. coli on the one hand, and uropathogenic E. coli on the other. Although the clinical and wastewater isolates each contained a very similar mean number of antibiotic resistance-encoding genes, the clinical isolates were enriched in genes required for in-host survival. Furthermore, and although the chromosomally encoded repertoire of these genes was similar in all sequenced isolates, the genetic composition of the plasmids from clinical and wastewater E. coli was more habitat-specific, with the clinical isolate plasmidome enriched in AMR and VA genes. Intriguingly, the plasmid-borne VA genes were often duplicates of genes already present on the chromosome, whereas the plasmid-borne AMR determinants were more specific. This reinforces the notion that plasmids are a primary means by which infection-related AMR and VA-associated genes are acquired and disseminated among these strains.

The Genomic Basis of Rapid Adaptation to Antibiotic Combination Therapy in Pseudomonas aeruginosa

Combination therapy is a common antibiotic treatment strategy that aims at minimizing the risk of resistance evolution in several infectious diseases. Nonetheless, evidence supporting its efficacy against the nosocomial opportunistic pathogen Pseudomonas aeruginosa remains elusive. Identification of the possible evolutionary paths to resistance in multidrug environments can help to explain treatment outcome. For this purpose, we here performed whole-genome sequencing of 127 previously evolved populations of P. aeruginosa adapted to sublethal doses of distinct antibiotic combinations and corresponding single-drug treatments, and experimentally characterized several of the identified variants. We found that alterations in the regulation of efflux pumps are the most favored mechanism of resistance, regardless of the environment. Unexpectedly, we repeatedly identified intergenic variants in the adapted populations, often with no additional mutations and usually associated with genes involved in efflux pump expression, possibly indicating a regulatory function of the intergenic regions. The experimental analysis of these variants demonstrated that the intergenic changes caused similar increases in resistance against single and multidrug treatments as those seen for efflux regulatory gene mutants. Surprisingly, we could find no substantial fitness costs for a majority of these variants, most likely enhancing their competitiveness toward sensitive cells, even in antibiotic-free environments. We conclude that the regulation of efflux is a central target of antibiotic-mediated selection in P. aeruginosa and that, importantly, changes in intergenic regions may represent a usually neglected alternative process underlying bacterial resistance evolution, which clearly deserves further attention in the future.

How Do Cells Adapt? Stories Told in Landscapes

Cells adapt to changing environments. Perturb a cell and it returns to a point of homeostasis. Perturb a population and it evolves toward a fitness peak. We review quantitative models of the forces of adaptation and their visualizations on landscapes. While some adaptations result from single mutations or few-gene effects, others are more cooperative, more delocalized in the genome, and more universal and physical. For example, homeostasis and evolution depend on protein folding and aggregation, energy and protein production, protein diffusion, molecular motor speeds and efficiencies, and protein expression levels. Models provide a way to learn about the fitness of cells and cell populations by making and testing hypotheses.

Epistasis between antibiotic tolerance, persistence, and resistance mutations

Understanding the evolution of microorganisms under antibiotic treatments is a burning issue. Typically, several resistance mutations can accumulate under antibiotic treatment, and the way in which resistance mutations interact, i.e., epistasis, has been extensively studied. We recently showed that the evolution of antibiotic resistance in Escherichia coli is facilitated by the early appearance of tolerance mutations. In contrast to resistance, which reduces the effectiveness of the drug concentration, tolerance increases resilience to antibiotic treatment duration in a nonspecific way, for example when bacteria transiently arrest their growth. Both result in increased survival under antibiotics, but the interaction between resistance and tolerance mutations has not been studied. Here, we extend our analysis to include the evolution of a different type of tolerance and a different antibiotic class and measure experimentally the epistasis between tolerance and resistance mutations. We derive the expected model for the effect of tolerance and resistance mutations on the dynamics of survival under antibiotic treatment. We find that the interaction between resistance and tolerance mutations is synergistic in strains evolved under intermittent antibiotic treatment. We extend our analysis to mutations that result in antibiotic persistence, i.e., to tolerance that is conferred only on a subpopulation of cells. We show that even when this population heterogeneity is included in our analysis, a synergistic interaction between antibiotic persistence and resistance mutations remains. We expect our general framework for the epistasis in killing conditions to be relevant for other systems as well, such as bacteria exposed to phages or cancer cells under treatment.

Evolutionary Stability of Salmonella Competition with the Gut Microbiota: How the Environment Fosters Heterogeneity in Exploitative and Interference Competition

Following ingestion, gastrointestinal pathogens compete against the gastrointestinal microbiota and overcome host immune defenses in order to cause infections. Besides employing direct killing mechanisms, the commensal microbiota occupies metabolic niches to outcompete invading pathogens. Salmonella enterica serovar Typhimurium (S. Typhimurium) uses several strategies to successfully colonize the gut and establish infection, of which an increasing number is based on phenotypic heterogeneity within the S. Typhimurium population. The utilization of myo-inositol (MI) and the production of colicin confer a selective advantage over the microbiota in terms of exploitative and interference competition, respectively. In this review, we summarize the genetic basis underlying bistability of MI catabolism and colicin production. As demonstrated by single-cell analyses, a stochastic switch in the expression of the genes responsible for colicin production and MI degradation constitutes the heterogeneity of the two phenotypes. Both genetic systems are tightly regulated to avoid their expression under non-appropriate conditions and possible detrimental effects on bacterial fitness. Moreover, evolutionary mechanisms underlying formation and stability of these phenotypes in S. Typhimurium are discussed. We propose that both MI catabolism and colicin production create a bet-hedging strategy, which provides an adaptive benefit for S. Typhimurium in the fluctuating environment of the mammalian gut.

Effects of spaceflight and simulated microgravity on microbial growth and secondary metabolism

Spaceflight and ground-based microgravity analog experiments have suggested that microgravity can affect microbial growth and metabolism. Although the effects of microgravity and its analogs on microorganisms have been studied for more than 50 years, plausible conflicting and diverse results have frequently been reported in different experiments, especially regarding microbial growth and secondary metabolism. Until now, only the responses of a few typical microbes to microgravity have been investigated; systematic studies of the genetic and phenotypic responses of these microorganisms to microgravity in space are still insufficient due to technological and logistical hurdles. The use of different test strains and secondary metabolites in these studies appears to have caused diverse and conflicting results. Moreover, subtle changes in the extracellular microenvironments around microbial cells play a key role in the diverse responses of microbial growth and secondary metabolisms. Therefore, "indirect" effects represent a reasonable pathway to explain the occurrence of these phenomena in microorganisms. This review summarizes current knowledge on the changes in microbial growth and secondary metabolism in response to spaceflight and its analogs and discusses the diverse and conflicting results. In addition, recommendations are given for future studies on the effects of microgravity in space on microbial growth and secondary metabolism.

Enhancement of Metallosphaera sedula Bioleaching by Targeted Recombination and Adaptive Laboratory Evolution

Thermophilic and lithoautotrophic archaea such as Metallosphaera sedula occupy acidic, metal-rich environments and are used in biomining processes. Biotechnological approaches could accelerate these processes and improve metal recovery by biomining organisms, but systems for genetic manipulation in these organisms are currently lacking. To gain a better understanding of the interplay between metal resistance, autotrophy, and lithotrophic metabolism, a genetic system was developed for M. sedula and used to evaluate parameters governing the efficiency of copper bioleaching. Additionally, adaptive laboratory evolution was used to select for naturally evolved M. sedula cell lines with desirable phenotypes for biomining, and these adapted cell lines were shown to have increased bioleaching capacity and efficiency. Genomic methods were used to analyze mutations that led to resistance in the experimentally evolved cell lines, while transcriptomics was used to examine changes in stress-inducible gene expression specific to the environmental conditions.

Alternative Evolutionary Paths to Bacterial Antibiotic Resistance Cause Distinct Collateral Effects

When bacteria evolve resistance against a particular antibiotic, they may simultaneously gain increased sensitivity against a second one. Such collateral sensitivity may be exploited to develop novel, sustainable antibiotic treatment strategies aimed at containing the current, dramatic spread of drug resistance. To date, the presence and molecular basis of collateral sensitivity has only been studied in few bacterial species and is unknown for opportunistic human pathogens such as Pseudomonas aeruginosa. In the present study, we assessed patterns of collateral effects by experimentally evolving 160 independent populations of P. aeruginosa to high levels of resistance against eight commonly used antibiotics. The bacteria evolved resistance rapidly and expressed both collateral sensitivity and cross-resistance. The pattern of such collateral effects differed to those previously reported for other bacterial species, suggesting interspecific differences in the underlying evolutionary trade-offs. Intriguingly, we also identified contrasting patterns of collateral sensitivity and cross-resistance among the replicate populations adapted to the same drug. Whole-genome sequencing of 81 independently evolved populations revealed distinct evolutionary paths of resistance to the selective drug, which determined whether bacteria became cross-resistant or collaterally sensitive towards others. Based on genomic and functional genetic analysis, we demonstrate that collateral sensitivity can result from resistance mutations in regulatory genes such as nalC or mexZ, which mediate aminoglycoside sensitivity in β-lactam-adapted populations, or the two-component regulatory system gene pmrB, which enhances penicillin sensitivity in gentamicin-resistant populations. Our findings highlight substantial variation in the evolved collateral effects among replicates, which in turn determine their potential in antibiotic therapy.

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

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

The evolutionary advantage of heritable phenotypic heterogeneity

Phenotypic plasticity is an evolutionary driving force in diverse biological processes, including the adaptive immune system, the development of neoplasms, and the persistence of pathogens despite drug pressure. It is essential, therefore, to understand the evolutionary advantage of an allele that confers on cells the ability to express a range of phenotypes. Here, we study the fate of a new mutation that allows the expression of multiple phenotypic states, introduced into a finite population of individuals that can express only a single phenotype. We show that the advantage of such a mutation depends on the degree of phenotypic heritability between generations, called phenotypic memory. We analyze the fixation probability of the phenotypically plastic allele as a function of phenotypic memory, the variance of expressible phenotypes, the rate of environmental changes, and the population size. We find that the fate of a phenotypically plastic allele depends fundamentally on the environmental regime. In constant environments, plastic alleles are advantageous and their fixation probability increases with the degree of phenotypic memory. In periodically fluctuating environments, by contrast, there is an optimum phenotypic memory that maximizes the probability of the plastic allele's fixation. This same optimum memory also maximizes geometric mean fitness, in steady state. We interpret these results in the context of previous studies in an infinite-population framework. We also discuss the implications of our results for the design of therapies that can overcome persistence and, indirectly, drug resistance.

Taking chances and making mistakes: non-genetic phenotypic heterogeneity and its consequences for surviving in dynamic environments

Natural selection has shaped the strategies for survival and growth of microorganisms. The success of microorganisms depends not only on slow evolutionary tuning but also on the ability to adapt to unpredictable changes in their environment. In principle, adaptive strategies range from purely deterministic mechanisms to those that exploit the randomness intrinsic to many cellular and molecular processes. Depending on the environment and selective pressures, particular strategies can lie somewhere along this continuum. In recent years, non-genetic cell-to-cell differences have received a lot of attention, not least because of their potential impact on the ability of microbial populations to survive in dynamic environments. Using several examples, we describe the origins of spontaneous and induced mechanisms of phenotypic adaptation. We identify some of the commonalities of these examples and consider the potential role of chance and constraints in microbial phenotypic adaptation.

On the mechanistic nature of epistasis in a canonical cis-regulatory element

Understanding the relation between genotype and phenotype remains a major challenge. The difficulty of predicting individual mutation effects, and particularly the interactions between them, has prevented the development of a comprehensive theory that links genotypic changes to their phenotypic effects. We show that a general thermodynamic framework for gene regulation, based on a biophysical understanding of protein-DNA binding, accurately predicts the sign of epistasis in a canonical cis-regulatory element consisting of overlapping RNA polymerase and repressor binding sites. Sign and magnitude of individual mutation effects are sufficient to predict the sign of epistasis and its environmental dependence. Thus, the thermodynamic model offers the correct null prediction for epistasis between mutations across DNA-binding sites. Our results indicate that a predictive theory for the effects of cis-regulatory mutations is possible from first principles, as long as the essential molecular mechanisms and the constraints these impose on a biological system are accounted for.

DOI:http://dx.doi.org/10.7554/eLife.25192.001

Mutations are changes to DNA that provide the raw material upon which evolution can act. Therefore, to understand evolution, we need to know the effects of mutations, and how those mutations interact with each other (a phenomenon referred to as epistasis). So far, few mathematical models allow scientists to predict the effects of mutations, and even fewer are able to predict epistasis.

Biological systems are complex and consist of many proteins and other molecules. Genes are the sections of DNA that provide the instructions needed to produce these molecules, and some genes encode proteins that can bind to DNA to control whether other genes are switched on or off. Lagator, Paixão et al. have now used mathematical models and experiments to understand how the environment inside the cells of a bacterium known as E. coli, specifically the amount of particular proteins, affects epistasis.

These mathematical models are able to predict interactions between mutations in the most abundant class of DNA-binding sites in proteins. This approach found that the nature of the interaction between mutations can be explained through biophysical laws, combined with the basic knowledge of the logic of how genes regulate each other’s activities. Furthermore, the models allow Lagator, Paixão et al. to predict interactions between mutations in several different environments, such as the presence of a new food source or a toxin, defined by the amounts of relevant DNA-binding proteins in cells.

By providing new ways of understanding how genes are regulated in bacteria, and how gene regulation is affected by mutations, these findings contribute to our understanding of how organisms evolve. In addition, this work may help us to build artificial networks of genes that interact with each other to produce a desired response, such as more efficient production of fuel from ethanol or the break down of hazardous chemicals.

DOI:http://dx.doi.org/10.7554/eLife.25192.002

Lack of Ecological and Life History Context Can Create the Illusion of Social Interactions in Dictyostelium discoideum

Studies of social microbes often focus on one fitness component (reproductive success within the social complex), with little information about or attention to other stages of the life cycle or the ecological context. This can lead to paradoxical results. The life cycle of the social amoeba Dictyostelium discoideum includes a multicellular stage in which not necessarily clonal amoebae aggregate upon starvation to form a possibly chimeric (genetically heterogeneous) fruiting body made of dead stalk cells and spores. The lab-measured reproductive skew in the spores of chimeras indicates strong social antagonism that should result in low genotypic diversity, which is inconsistent with observations from nature. Two studies have suggested that this inconsistency stems from the one-dimensional assessment of fitness (spore production) and that the solution lies in tradeoffs between multiple life-history traits, e.g.: spore size versus viability; and spore-formation (via aggregation) versus staying vegetative (as non-aggregated cells). We develop an ecologically-grounded, socially-neutral model (i.e. no social interactions between genotypes) for the life cycle of social amoebae in which we theoretically explore multiple non-social life-history traits, tradeoffs and tradeoff-implementing mechanisms. We find that spore production comes at the expense of time to complete aggregation, and, depending on the experimental setup, spore size and viability. Furthermore, experimental results regarding apparent social interactions within chimeric mixes can be qualitatively recapitulated under this neutral hypothesis, without needing to invoke social interactions. This allows for simple potential resolutions to the previously paradoxical results. We conclude that the complexities of life histories, including social behavior and multicellularity, can only be understood in the appropriate multidimensional ecological context, when considering all stages of the life cycle.

Fitness in social microbes is often measured in terms of reproductive success in the social stage, with little regard to other stages of the life cycle (e.g. solitary) or to the ecological context. This approach can lead to seemingly paradoxical results that point to complex social interactions (e.g., social cheating) among individuals in the population. However, recent experimental studies in Dictyostelium discoideum, one of the most studied social microbes, have highlighted various tradeoffs among previously ignored non-social traits that should affect fitness. We develop an ecologically-motivated socially-neutral model for the life cycle of D. discoideum that combines these proposed traits and tradeoffs and proposes new ones to determine whether existing observations can be explained without the need to invoke social interactions. We confirm this expectation and conclude that the complexities of social behavior can only be understood in the appropriate ecological context, when considering a complete description of the life cycle.

A case study in evolutionary contingency

Biological evolution is a fundamentally historical phenomenon in which intertwined stochastic and deterministic processes shape lineages with long, continuous histories that exist in a changing world that has a history of its own. The degree to which these characteristics render evolution historically contingent, and evolutionary outcomes thereby unpredictably sensitive to history has been the subject of considerable debate in recent decades. Microbial evolution experiments have proven among the most fruitful means of empirically investigating the issue of historical contingency in evolution. One such experiment is the Escherichia coli Long-Term Evolution Experiment (LTEE), in which twelve populations founded from the same clone of E. coli have evolved in parallel under identical conditions. Aerobic growth on citrate (Cit(+)), a novel trait for E. coli, evolved in one of these populations after more than 30,000 generations. Experimental replays of this population's evolution from various points in its history showed that the Cit(+) trait was historically contingent upon earlier mutations that potentiated the trait by rendering it mutationally accessible. Here I review this case of evolutionary contingency and discuss what it implies about the importance of historical contingency arising from the core processes of evolution.

Mechanisms of Competition in Biofilm Communities

Bacterial biofilms are dense and often mixed-species surface-attached communities in which bacteria coexist and compete for limited space and nutrients. Here we present the different antagonistic interactions described in biofilm environments and their underlying molecular mechanisms, along with ecological and evolutionary insights as to how competitive interactions arise and are maintained within biofilms.

The idiosyncrasy of spatial structure in bacterial competition

Background

The spatial structure of a habitat can have a strong impact on community dynamics. Different experimental approaches exist to explore the effect of spatial structure on bacterial communities. To investigate the effect of ‘space’, a single implementation of spatial structure is often contrasted to bacterial community dynamics in well-mixed cultures. While such comparisons are useful, it is likely that the observed dynamics will be particular to the specific experimental implementation of spatial structure. In order to address this question, we track the community dynamics of a two-strain Escherichia coli community in various spatial habitats and relate the observed dynamics to the structure of a habitat.

Results

By tracking the community dynamics of rpoS wild-type and mutant E. coli in radially expanding colonies on solid and semi-solid agar plates, we find that the mutant strain outcompetes the wild-type on semi-solid agar plates, whereas the two strains coexist on solid agar. We compare these results to previous studies in which the same two strains were shown to coexist in habitats spatially structured by microfabrication, while the mutant outcompeted the wild-type in well-mixed batch cultures. Together, these observations show that different implementations of space may result in qualitatively different community dynamics. Furthermore, we argue that the same competitive outcome (e.g. coexistence) may arise from distinct underlying dynamics in different experimental implementations of spatial structure.

Conclusions

Our observations demonstrate that different experimental implementations of spatial structure may not only lead to quantitatively different communities (changes in the relative abundance of types) but can also lead to qualitatively different outcomes of long-term community dynamics (coexistence versus extinction and loss of biodiversity).

Metabolism at evolutionary optimal States

Metabolism is generally required for cellular maintenance and for the generation of offspring under conditions that support growth. The rates, yields (efficiencies), adaptation time and robustness of metabolism are therefore key determinants of cellular fitness. For biotechnological applications and our understanding of the evolution of metabolism, it is necessary to figure out how the functional system properties of metabolism can be optimized, via adjustments of the kinetics and expression of enzymes, and by rewiring metabolism. The trade-offs that can occur during such optimizations then indicate fundamental limits to evolutionary innovations and bioengineering. In this paper, we review several theoretical and experimental findings about mechanisms for metabolic optimization.

Populations adapt to fluctuating selection using derived and ancestral allelic diversity

Populations can adapt to changing environments by using allelic diversity, yet whether diversity is recently derived or ancestral is often debated. Although evolution could productively use both types of diversity in a changing environment, their relative frequency has not been quantified. We address this question experimentally using budding yeast strains that harbor a tandem repeat containing URA3 gene, which we expose to cyclical selection and counterselection. We characterize and quantify the dynamics of frameshift events in the URA3 gene in eight populations over 12 cycles of selection and find that ancestral alleles account for 10-20% of all adaptive events. Using a general model of fluctuating selection, we determine how these results depend on mutation rates, population sizes, and fluctuation timescales. We quantify the contribution of derived alleles to the adaptation process using the de novo mutation rate along the population's ancestral lineage, a novel measure that is applicable in a wide range of settings. We find that the adaptive dynamics undergoes a sharp transition from selection on ancestral alleles to selection on derived alleles as fluctuation timescales increase. Our results demonstrate that fluctuations can select between different modes of adaptation over evolutionary timescales.

Survival probability of beneficial mutations in bacterial batch culture

The survival of rare beneficial mutations can be extremely sensitive to the organism's life history and the trait affected by the mutation. Given the tremendous impact of bacteria in batch culture as a model system for the study of adaptation, it is important to understand the survival probability of beneficial mutations in these populations. Here we develop a life-history model for bacterial populations in batch culture and predict the survival of mutations that increase fitness through their effects on specific traits: lag time, fission time, viability, and the timing of stationary phase. We find that if beneficial mutations are present in the founding population at the beginning of culture growth, mutations that reduce the mortality of daughter cells are the most likely to survive drift. In contrast, of mutations that occur de novo during growth, those that delay the onset of stationary phase are the most likely to survive. Our model predicts that approximately fivefold population growth between bottlenecks will optimize the occurrence and survival of beneficial mutations of all four types. This prediction is relatively insensitive to other model parameters, such as the lag time, fission time, or mortality rate of the population. We further estimate that bottlenecks that are more severe than this optimal prediction substantially reduce the occurrence and survival of adaptive mutations.

An evolutionary perspective on the Crabtree effect

The capability to ferment sugars into ethanol is a key metabolic trait of yeasts. Crabtree-positive yeasts use fermentation even in the presence of oxygen, where they could, in principle, rely on the respiration pathway. This is surprising because fermentation has a much lower ATP yield than respiration (2 ATP vs. approximately 18 ATP per glucose). While genetic events in the evolution of the Crabtree effect have been identified, the selective advantages provided by this trait remain controversial. In this review we analyse explanations for the emergence of the Crabtree effect from an evolutionary and game-theoretical perspective. We argue that an increased rate of ATP production is likely the most important factor behind the emergence of the Crabtree effect.

Non-equilibrium physics and evolution--adaptation, extinction, and ecology: a key issues review

Evolutionary dynamics in nature constitute an immensely complex non-equilibrium process. We review the application of physical models of evolution, by focusing on adaptation, extinction, and ecology. In each case, we examine key concepts by working through examples. Adaptation is discussed in the context of bacterial evolution, with a view toward the relationship between growth rates, mutation rates, selection strength, and environmental changes. Extinction dynamics for an isolated population are reviewed, with emphasis on the relation between timescales of extinction, population size, and temporally correlated noise. Ecological models are discussed by focusing on the effect of spatial interspecies interactions on diversity. Connections between physical processes--such as diffusion, turbulence, and localization--and evolutionary phenomena are highlighted.

Seeing is believing: what experiments with microbes reveal about evolution

Darwin's theory of natural selection is among the most powerful ideas in science, yet evolutionary ideas remain challenged to this day. This is in part because evolution often cannot be directly observed. Simple experiments with microbes can change that by enabling direct observation of evolutionary processes.