Experimental evolution reveals hidden diversity in evolutionary pathways

Microbial Experimental Evolution - a proving ground for evolutionary theory and a tool for discovery

Microbial experimental evolution uses controlled laboratory populations to study the mechanisms of evolution. The molecular analysis of evolved populations enables empirical tests that can confirm the predictions of evolutionary theory, but can also lead to surprising discoveries. As with other fields in the life sciences, microbial experimental evolution has become a tool, deployed as part of the suite of techniques available to the molecular biologist. Here, I provide a review of the general findings of microbial experimental evolution, especially those relevant to molecular microbiologists that are new to the field. I also relate these results to design considerations for an evolution experiment and suggest future directions for those working at the intersection of experimental evolution and molecular biology.

Repeated Phenotypic Evolution by Different Genetic Routes in Pseudomonas fluorescens SBW25

Repeated evolution of functionally similar phenotypes is observed throughout the tree of life. The extent to which the underlying genetics are conserved remains an area of considerable interest. Previously, we reported the evolution of colony switching in two independent lineages of Pseudomonas fluorescens SBW25. The phenotypic and genotypic bases of colony switching in the first lineage (Line 1) have been described elsewhere. Here, we deconstruct the evolution of colony switching in the second lineage (Line 6). We show that, as for Line 1, Line 6 colony switching results from an increase in the expression of a colanic acid-like polymer (CAP). At the genetic level, nine mutations occur in Line 6. Only one of these—a nonsynonymous point mutation in the housekeeping sigma factor rpoD—is required for colony switching. In contrast, the genetic basis of colony switching in Line 1 is a mutation in the metabolic gene carB. A molecular model has recently been proposed whereby the carB mutation increases capsulation by redressing the intracellular balance of positive (ribosomes) and negative (RsmAE/CsrA) regulators of a positive feedback loop in capsule expression. We show that Line 6 colony switching is consistent with this model; the rpoD mutation generates an increase in ribosomal gene expression, and ultimately an increase in CAP expression.

Parallel evolution of HIV-1 in a long-term experiment

One of the most intriguing puzzles in biology is the degree to which evolution is repeatable. The repeatability of evolution, or parallel evolution, has been studied in a variety of model systems, but has rarely been investigated with clinically relevant viruses. To investigate parallel evolution of HIV-1, we passaged two replicate HIV-1 populations for almost 1 year in each of two human T-cell lines. For each of the four evolution lines, we determined the genetic composition of the viral population at nine time points by deep sequencing the entire genome. Mutations that were carried by the majority of the viral population accumulated continuously over 1 year in each evolution line. Many majority mutations appeared in more than one evolution line, that is, our experiments showed an extreme degree of parallel evolution. In one of the evolution lines, 62% of the majority mutations also occur in another line. The parallelism impairs our ability to reconstruct the evolutionary history by phylogenetic methods. We show that one can infer the correct phylogenetic topology by including minority mutations in our analysis. We also find that mutation diversity at the beginning of the experiment is predictive of the frequency of majority mutations at the end of the experiment.

Experimental Evolution of Innovation and Novelty

How does novelty, a new, genetically based function, evolve? A compelling answer has been elusive because there are few model systems where both the genetic mechanisms generating novel functions and the ecological conditions that govern their origin and spread can be studied in detail. This review article considers what we have learned about the evolution of novelty from microbial selection experiments. This work reveals that the genetic routes to novelty can be more highly variable than standard models have led us to believe and underscores the importance of considering both genetics and ecology in this process.

Predicting mutational routes to new adaptive phenotypes

Predicting evolutionary change poses numerous challenges. Here we take advantage of the model bacterium Pseudomonas fluorescens in which the genotype-to-phenotype map determining evolution of the adaptive 'wrinkly spreader' (WS) type is known. We present mathematical descriptions of three necessary regulatory pathways and use these to predict both the rate at which each mutational route is used and the expected mutational targets. To test predictions, mutation rates and targets were determined for each pathway. Unanticipated mutational hotspots caused experimental observations to depart from predictions but additional data led to refined models. A mismatch was observed between the spectra of WS-causing mutations obtained with and without selection due to low fitness of previously undetected WS-causing mutations. Our findings contribute toward the development of mechanistic models for forecasting evolution, highlight current limitations, and draw attention to challenges in predicting locus-specific mutational biases and fitness effects.

Inferring population genetics parameters of evolving viruses using time-series data

With the advent of deep sequencing techniques, it is now possible to track the evolution of viruses with ever-increasing detail. Here, we present Flexible Inference from Time-Series (FITS)-a computational tool that allows inference of one of three parameters: the fitness of a specific mutation, the mutation rate or the population size from genomic time-series sequencing data. FITS was designed first and foremost for analysis of either short-term Evolve & Resequence (E&R) experiments or rapidly recombining populations of viruses. We thoroughly explore the performance of FITS on simulated data and highlight its ability to infer the fitness/mutation rate/population size. We further show that FITS can infer meaningful information even when the input parameters are inexact. In particular, FITS is able to successfully categorize a mutation as advantageous or deleterious. We next apply FITS to empirical data from an E&R experiment on poliovirus where parameters were determined experimentally and demonstrate high accuracy in inference.

Mutational Evolution of Pseudomonas aeruginosa Resistance to Ribosome-Targeting Antibiotics

The present work examines the evolutionary trajectories of replicate Pseudomonas aeruginosa cultures in presence of the ribosome-targeting antibiotics tobramycin and tigecycline. It is known that large number of mutations across different genes - and therefore a large number of potential pathways - may be involved in resistance to any single antibiotic. Thus, evolution toward resistance might, to a large degree, rely on stochasticity, which might preclude the use of predictive strategies for fighting antibiotic resistance. However, the present results show that P. aeruginosa populations evolving in parallel in the presence of antibiotics (either tobramycin or tigecycline) follow a set of trajectories that present common elements. In addition, the pattern of resistance mutations involved include common elements for these two ribosome-targeting antimicrobials. This indicates that mutational evolution toward resistance (and perhaps other properties) is to a certain degree deterministic and, consequently, predictable. These findings are of interest, not just for P. aeruginosa, but in understanding the general rules involved in the evolution of antibiotic resistance also. In addition, the results indicate that bacteria can evolve toward higher levels of resistance to antibiotics against which they are considered to be intrinsically resistant, as tigecycline in the case of P. aeruginosa and that this may confer cross-resistance to other antibiotics of therapeutic value. Our results are particularly relevant in the case of patients under empiric treatment with tigecycline, which frequently suffer P. aeruginosa superinfections.

Hampered motility promotes the evolution of wrinkly phenotype in Bacillus subtilis

BACKGROUND

Selection for a certain trait in microbes depends on the genetic background of the strain and the selection pressure of the environmental conditions acting on the cells. In contrast to the sessile state in the biofilm, various bacterial cells employ flagellum-dependent motility under planktonic conditions suggesting that the two phenotypes are mutually exclusive. However, flagellum dependent motility facilitates the prompt establishment of floating biofilms on the air-medium interface, called pellicles. Previously, pellicles of B. subtilis were shown to be preferably established by motile cells, causing a reduced fitness of non-motile derivatives in the presence of the wild type strain.

RESULTS

Here, we show that lack of active flagella promotes the evolution of matrix overproducers that can be distinguished by the characteristic wrinkled colony morphotype. The wrinkly phenotype is associated with amino acid substitutions in the master repressor of biofilm-related genes, SinR. By analyzing one of the mutations, we show that it alters the tetramerization and DNA binding properties of SinR, allowing an increased expression of the operon responsible for exopolysaccharide production. Finally, we demonstrate that the wrinkly phenotype is advantageous when cells lack flagella, but not in the wild type background.

CONCLUSIONS

Our experiments suggest that loss of function phenotypes could expose rapid evolutionary adaptation in bacterial biofilms that is otherwise not evident in the wild type strains.

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

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

Experimental Evolution as a High-Throughput Screen for Genetic Adaptations

Experimental evolution is a method in which populations of organisms, often microbes, are founded by one or more ancestors of known genotype and then propagated under controlled conditions to study the evolutionary process. These evolving populations are influenced by all population genetic forces, including selection, mutation, drift, and recombination, and the relative contributions of these forces may be seen as mysterious. Here, I describe why the outcomes of experimental evolution should be viewed with greater certainty because the force of selection typically dominates. Importantly, any mutant rising rapidly to high frequency in large populations must have acquired adaptive traits in the selective environment. Sequencing the genomes of these mutants can identify genes or pathways that contribute to an adaptation. I review the logic and simple mathematics why this evolve-and-resequence approach is a powerful way to find the mutations or mutation combinations that best increase fitness in any new environment.

Identifying and exploiting genes that potentiate the evolution of antibiotic resistance

There is an urgent need to develop novel approaches for predicting and preventing the evolution of antibiotic resistance. Here we show that the ability to evolve de novo resistance to a clinically important β-lactam antibiotic, ceftazidime, varies drastically across the genus Pseudomonas. This variation arises because strains possessing the ampR global transcriptional regulator evolve resistance at a high rate. This does not arise because of mutations in ampR. Instead, this regulator potentiates evolution by allowing mutations in conserved peptidoglycan biosynthesis genes to induce high levels of β-lactamase expression. Crucially, blocking this evolutionary pathway by co-administering ceftazidime with the β-lactamase inhibitor avibactam can be used to eliminate pathogenic P. aeruginosa populations before they can evolve resistance. In summary, our study shows that identifying potentiator genes that act as evolutionary catalysts can be used to both predict and prevent the evolution of antibiotic resistance.

Parallel Evolution of High-Level Aminoglycoside Resistance in Escherichia coli Under Low and High Mutation Supply Rates

Antibiotic resistance is a major concern in public health worldwide, thus there is much interest in characterizing the mutational pathways through which susceptible bacteria evolve resistance. Here we use experimental evolution to explore the mutational pathways toward aminoglycoside resistance, using gentamicin as a model, under low and high mutation supply rates. Our results show that both normo and hypermutable strains of Escherichia coli are able to develop resistance to drug dosages > 1,000-fold higher than the minimal inhibitory concentration for their ancestors. Interestingly, such level of resistance was often associated with changes in susceptibility to other antibiotics, most prominently with increased resistance to fosfomycin. Whole-genome sequencing revealed that all resistant derivatives presented diverse mutations in five common genetic elements: fhuA, fusA and the atpIBEFHAGDC, cyoABCDE, and potABCD operons. Despite the large number of mutations acquired, hypermutable strains did not pay, apparently, fitness cost. In contrast to recent studies, we found that the mutation supply rate mainly affected the speed (tempo) but not the pattern (mode) of evolution: both backgrounds acquired the mutations in the same order, although the hypermutator strain did it faster. This observation is compatible with the adaptive landscape for high-level gentamicin resistance being relatively smooth, with few local maxima; which might be a common feature among antibiotics for which resistance involves multiple loci.

Adaptive radiation of Pseudomonas fluorescens SBW25 in experimental microcosms provides an understanding of the evolutionary ecology and molecular biology of A-L interface biofilm formation

Combined experimental evolutionary and molecular biology approaches have been used to investigate the adaptive radiation of Pseudomonas fluorescens SBW25 in static microcosms leading to the colonisation of the air-liquid interface by biofilm-forming mutants such as the Wrinkly Spreader (WS). In these microcosms, the ecosystem engineering of the early wild-type colonists establishes the niche space for subsequent WS evolution and colonisation. Random WS mutations occurring in the developing population that deregulate diguanylate cyclases and c-di-GMP homeostasis result in cellulose-based biofilms at the air-liquid interface. These structures allow Wrinkly Spreaders to intercept O2 diffusing into the liquid column and limit the growth of competitors lower down. As the biofilm matures, competition increasingly occurs between WS lineages, and niche divergence within the biofilm may support further diversification before system failure when the structure finally sinks. A combination of pleiotropic and epistasis effects, as well as secondary mutations, may explain variations in WS phenotype and fitness. Understanding how mutations subvert regulatory networks to express intrinsic genome potential and key innovations providing a selective advantage in novel environments is key to understanding the versatility of bacteria, and how selection and ecological opportunity can rapidly lead to substantive changes in phenotype and in community structure and function.

Metabolism and the Evolution of Social Behavior

How does metabolism influence social behavior? This fundamental question at the interface of molecular biology and social evolution is hard to address with experiments in animals, and therefore, we turned to a simple microbial system: swarming in the bacterium Pseudomonas aeruginosa. Using genetic engineering, we excised a locus encoding a key metabolic regulator and disrupted P. aeruginosa's metabolic prudence, the regulatory mechanism that controls expression of swarming public goods and protects this social behavior from exploitation by cheaters. Then, using experimental evolution, we followed the joint evolution of the genome, the metabolome and the social behavior as swarming re-evolved. New variants emerged spontaneously with mutations that reorganized the metabolome and compensated in distinct ways for the disrupted metabolic prudence. These experiments with a unicellular organism provide a detailed view of how metabolism-currency of all physiological processes-can determine the costs and benefits of a social behavior and ultimately influence how an organism behaves towards other organisms of the same species.

Different Genomic Changes Underlie Adaptive Evolution in Populations of Contrasting History

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

Complex chromosomal neighborhood effects determine the adaptive potential of a gene under selection

How the organization of genes on a chromosome shapes adaptation is essential for understanding evolutionary paths. Here, we investigate how adaptation to rapidly increasing levels of antibiotic depends on the chromosomal neighborhood of a drug-resistance gene inserted at different positions of the Escherichia coli chromosome. Using a dual-fluorescence reporter that allows us to distinguish gene amplifications from other up-mutations, we track in real-time adaptive changes in expression of the drug-resistance gene. We find that the relative contribution of several mutation types differs systematically between loci due to properties of neighboring genes: essentiality, expression, orientation, termination, and presence of duplicates. These properties determine rate and fitness effects of gene amplification, deletions, and mutations compromising transcriptional termination. Thus, the adaptive potential of a gene under selection is a system-property with a complex genetic basis that is specific for each chromosomal locus, and it can be inferred from detailed functional and genomic data.

DOI:http://dx.doi.org/10.7554/eLife.25100.001

Conflicting selection alters the trajectory of molecular evolution in a tripartite bacteria-plasmid-phage interaction

Bacteria engage in a complex network of ecological interactions, which includes mobile genetic elements (MGEs) such as phages and plasmids. These elements play a key role in microbial communities as vectors of horizontal gene transfer but can also be important sources of selection for their bacterial hosts. In natural communities, bacteria are likely to encounter multiple MGEs simultaneously and conflicting selection among MGEs could alter the bacterial evolutionary response to each MGE. Here, we test the effect of interactions with multiple MGEs on bacterial molecular evolution in the tripartite interaction between the bacterium, Pseudomonas fluorescens, the lytic bacteriophage, SBW25φ2, and conjugative plasmid, pQBR103, using genome sequencing of experimentally evolved bacteria. We show that individually, both plasmids and phages impose selection leading to bacterial evolutionary responses that are distinct from bacterial populations evolving without MGEs, but that together, plasmids and phages impose conflicting selection on bacteria, constraining the evolutionary responses observed in pairwise interactions. Our findings highlight the likely difficulties of predicting evolutionary responses to multiple selective pressures from the observed evolutionary responses to each selective pressure alone. Understanding evolution in complex microbial communities comprising many species and MGEs will require that we go beyond studies of pairwise interactions.

Environment determines evolutionary trajectory in a constrained phenotypic space

Constraints on phenotypic variation limit the capacity of organisms to adapt to the multiple selection pressures encountered in natural environments. To better understand evolutionary dynamics in this context, we select Escherichia coli for faster migration through a porous environment, a process which depends on both motility and growth. We find that a trade-off between swimming speed and growth rate constrains the evolution of faster migration. Evolving faster migration in rich medium results in slow growth and fast swimming, while evolution in minimal medium results in fast growth and slow swimming. In each condition parallel genomic evolution drives adaptation through different mutations. We show that the trade-off is mediated by antagonistic pleiotropy through mutations that affect negative regulation. A model of the evolutionary process shows that the genetic capacity of an organism to vary traits can qualitatively depend on its environment, which in turn alters its evolutionary trajectory.

DOI:http://dx.doi.org/10.7554/eLife.24669.001

In nature organisms face many challenges, and species adapt to their environment by changing heritable traits over the course of many generations. How organisms adapt is often limited by trade-offs, in which improving one trait can only come at the expense of another.

In the laboratory, scientists use well-controlled environments to study how populations adapt to specific challenges without interference from their natural habitat. Most experiments, however, only look at simple challenges and do not take into account that organisms in the wild face many pressures at the same time. Fraebel et al. wanted to know what happens when an organism’s performance depends on two traits that are restricted by a trade-off. The experiments used populations of the bacterium Escherichia coli, which can go through hundreds of generations in a week, providing ample opportunity to study mutations and their impact on heritable traits.

Through a combination of mathematical modeling and experiments, Fraebel et al. found that the environment is crucial for determining how bacteria adapt when their swimming speed and population growth rate are restricted by a trade-off. When nutrients are plentiful, E. coli populations evolve to spread faster by swimming more quickly despite growing more slowly. Yet, if nutrients are scarcer, the bacteria evolve to spread faster by growing more quickly despite swimming more slowly. In each scenario, the experiments identified single mutations that changed both swimming speed and growth rate by modifying regulatory activity in the cell.

A better understanding of how an organism’s genetic architecture, its environment and trade-offs are connected may help identify the traits that are most easily changed by mutations. The ultimate goal would be to be able to predict evolutionary responses to complex selection pressures.

DOI:http://dx.doi.org/10.7554/eLife.24669.002

Evolutionary convergence in experimental Pseudomonas populations

Model microbial systems provide opportunity to understand the genetic bases of ecological traits, their evolution, regulation and fitness contributions. Experimental populations of Pseudomonas fluorescens rapidly diverge in spatially structured microcosms producing a range of surface-colonising forms. Despite divergent molecular routes, wrinkly spreader (WS) niche specialist types overproduce a cellulosic polymer allowing mat formation at the air-liquid interface and access to oxygen. Given the range of ways by which cells can form mats, such phenotypic parallelism is unexpected. We deleted the cellulose-encoding genes from the ancestral genotype and asked whether this mutant could converge on an alternate phenotypic solution. Two new traits were discovered. The first involved an exopolysaccharide encoded by pgaABCD that functions as cell-cell glue similar to cellulose. The second involved an activator of an amidase (nlpD) that when defective causes cell chaining. Both types form mats, but were less fit in competition with cellulose-based WS types. Surprisingly, diguanylate cyclases linked to cellulose overexpression underpinned evolution of poly-beta-1,6-N-acetyl-d-glucosamine (PGA)-based mats. This prompted genetic analyses of the relationships between the diguanylate cyclases WspR, AwsR and MwsR, and both cellulose and PGA. Our results suggest that c-di-GMP regulatory networks may have been shaped by evolution to accommodate loss and gain of exopolysaccharide modules facilitating adaptation to new environments.

The evolution of antimicrobial peptide resistance in Pseudomonas aeruginosa is shaped by strong epistatic interactions

Colistin is an antimicrobial peptide that has become the only remaining alternative for the treatment of multidrug-resistant Gram-negative bacterial infections, but little is known of how clinical levels of colistin resistance evolve. We use in vitro experimental evolution and whole-genome sequencing of colistin-resistant Pseudomonas aeruginosa isolates from cystic fibrosis patients to reconstruct the molecular evolutionary pathways open for high-level colistin resistance. We show that the evolution of resistance is a complex, multistep process that requires mutation in at least five independent loci that synergistically create the phenotype. Strong intergenic epistasis limits the number of possible evolutionary pathways to resistance. Mutations in transcriptional regulators are essential for resistance evolution and function as nodes that potentiate further evolution towards higher resistance by functionalizing and increasing the effect of the other mutations. These results add to our understanding of clinical antimicrobial peptide resistance and the prediction of resistance evolution.

Colistin is an antibiotic used in the treatment of Pseudomonas aeruginosa infections in cystic fibrosis patients. Here, Jochumsen et al. reconstruct the pathways for the molecular evolution of colistin resistance in P. aeruginosa and show that the number of pathways is highly constrained by interactions among genes.

The Genomic Basis of Evolutionary Innovation in Pseudomonas aeruginosa

Novel traits play a key role in evolution, but their origins remain poorly understood. Here we address this problem by using experimental evolution to study bacterial innovation in real time. We allowed 380 populations of Pseudomonas aeruginosa to adapt to 95 different carbon sources that challenged bacteria with either evolving novel metabolic traits or optimizing existing traits. Whole genome sequencing of more than 80 clones revealed profound differences in the genetic basis of innovation and optimization. Innovation was associated with the rapid acquisition of mutations in genes involved in transcription and metabolism. Mutations in pre-existing duplicate genes in the P. aeruginosa genome were common during innovation, but not optimization. These duplicate genes may have been acquired by P. aeruginosa due to either spontaneous gene amplification or horizontal gene transfer. High throughput phenotype assays revealed that novelty was associated with increased pleiotropic costs that are likely to constrain innovation. However, mutations in duplicate genes with close homologs in the P. aeruginosa genome were associated with low pleiotropic costs compared to mutations in duplicate genes with distant homologs in the P. aeruginosa genome, suggesting that functional redundancy between duplicates facilitates innovation by buffering pleiotropic costs.

Lineage Tracking for Probing Heritable Phenotypes at Single-Cell Resolution

Determining the phenotype and genotype of single cells is central to understand microbial evolution. DNA sequencing technologies allow the detection of mutants at high resolution, but similar approaches for phenotypic analyses are still lacking. We show that a drop-based millifluidic system enables the detection of heritable phenotypic changes in evolving bacterial populations. At time intervals, cells were sampled and individually compartmentalized in 100 nL drops. Growth through 15 generations was monitored using a fluorescent protein reporter. Amplification of heritable changes–via growth–over multiple generations yields phenotypically distinct clusters reflecting variation relevant for evolution. To demonstrate the utility of this approach, we follow the evolution of Escherichia coli populations during 30 days of starvation. Phenotypic diversity was observed to rapidly increase upon starvation with the emergence of heritable phenotypes. Mutations corresponding to each phenotypic class were identified by DNA sequencing. This scalable lineage-tracking technology opens the door to large-scale phenotyping methods with special utility for microbiology and microbial population biology.

Experimental evolution in biofilm populations

Biofilms are a major form of microbial life in which cells form dense surface associated communities that can persist for many generations. The long-life of biofilm communities means that they can be strongly shaped by evolutionary processes. Here, we review the experimental study of evolution in biofilm communities. We first provide an overview of the different experimental models used to study biofilm evolution and their associated advantages and disadvantages. We then illustrate the vast amount of diversification observed during biofilm evolution, and we discuss (i) potential ecological and evolutionary processes behind the observed diversification, (ii) recent insights into the genetics of adaptive diversification, (iii) the striking degree of parallelism between evolution experiments and real-life biofilms and (iv) potential consequences of diversification. In the second part, we discuss the insights provided by evolution experiments in how biofilm growth and structure can promote cooperative phenotypes. Overall, our analysis points to an important role of biofilm diversification and cooperation in bacterial survival and productivity. Deeper understanding of both processes is of key importance to design improved antimicrobial strategies and diagnostic techniques.

This review paper provides an overview of (i) the different experimental models used to study biofilm evolution, (ii) the vast amount of diversification observed during biofilm evolution (including potential causes and consequences) and (iii) recent insights in how growth in biofilms can lead to the evolution of cooperative phenotypes.

Combinations of mutations in envZ, ftsI, mrdA, acrB and acrR can cause high-level carbapenem resistance in Escherichia coli

OBJECTIVES

The worldwide spread of ESBL-producing Enterobacteriaceae has led to an increased use of carbapenems, the group of β-lactams with the broadest spectrum of activity. Bacterial resistance to carbapenems is mainly due to acquired carbapenemases or a combination of ESBL production and reduced drug influx via loss of outer-membrane porins. Here, we have studied the development of carbapenem resistance in Escherichia coli in the absence of β-lactamases.

METHODS

We selected mutants with high-level carbapenem resistance through repeated serial passage in the presence of increasing concentrations of meropenem or ertapenem for ∼60 generations. Isolated clones were whole-genome sequenced, and the order in which the identified mutations arose was determined in the passaged populations. Key mutations were reconstructed, and bacterial growth rates of populations and isolated clones and resistance levels to 23 antibiotics were measured.

RESULTS

High-level resistance to carbapenems resulted from a combination of downstream effects of envZ mutation and target mutations in AcrAB-TolC-mediated drug export, together with PBP genes [mrdA (PBP2) after meropenem exposure or ftsI (PBP3) after ertapenem exposure].

CONCLUSIONS

Our results show that antibiotic resistance evolution can occur via several parallel pathways and that new mechanisms may appear after the most common pathways (i.e. β-lactamases and loss of porins) have been eliminated. These findings suggest that strategies to target the most commonly observed resistance mechanisms might be hampered by the appearance of previously unknown parallel pathways to resistance.

Can the experimental evolution programme help us elucidate the genetic basis of adaptation in nature?

There have been a variety of approaches taken to try to characterize and identify the genetic basis of adaptation in nature, spanning theoretical models, experimental evolution studies and direct tests of natural populations. Theoretical models can provide formalized and detailed hypotheses regarding evolutionary processes and patterns, from which experimental evolution studies can then provide important proofs of concepts and characterize what is biologically reasonable. Genetic and genomic data from natural populations then allow for the identification of the particular factors that have and continue to play an important role in shaping adaptive evolution in the natural world. Further to this, experimental evolution studies allow for tests of theories that may be difficult or impossible to test in natural populations for logistical and methodological reasons and can even generate new insights, suggesting further refinement of existing theories. However, as experimental evolution studies often take place in a very particular set of controlled conditions--that is simple environments, a small range of usually asexual species, relatively short timescales--the question remains as to how applicable these experimental results are to natural populations. In this review, we discuss important insights coming from experimental evolution, focusing on four key topics tied to the evolutionary genetics of adaptation, and within those topics, we discuss the extent to which the experimental work compliments and informs natural population studies. We finish by making suggestions for future work in particular a need for natural population genomic time series data, as well as the necessity for studies that combine both experimental evolution and natural population approaches.

AmrZ regulates cellulose production in Pseudomonas syringae pv. tomato DC3000

In Pseudomonas syringae pv. tomato DC3000, the second messenger c-di-GMP has been previously shown to stimulate pellicle formation and cellulose biosynthesis. A screen for genes involved in cellulose production under high c-di-GMP intracellular levels led to the identification of insertions in two genes, wssB and wssE, belonging to the Pto DC3000 cellulose biosynthesis operon wssABCDEFGHI. Interestingly, beside cellulose-deficient mutants, colonies with a rougher appearance than the wild type also arouse among the transposants. Those mutants carry insertions in amrZ, a gene encoding a transcriptional regulator in different Pseudomonas. Here, we provide evidence that AmrZ is involved in the regulation of bacterial cellulose production at transcriptional level by binding to the promoter region of the wssABCDEFGHI operon and repressing cellulose biosynthesis genes. Mutation of amrZ promotes wrinkly colony morphology, increased cellulose production and loss of motility in Pto DC3000. AmrZ regulon includes putative c-di-GMP metabolising proteins, like AdcA and MorA, which may also impact those phenotypes. Furthermore, an amrZ but not a cellulose-deficient mutant turned out to be impaired in pathogenesis, indicating that AmrZ is a key regulator of Pto DC3000 virulence probably by controlling bacterial processes other than cellulose production.

Replaying the tape of life in the twenty-first century

Should the tape of life be replayed, would it produce similar living beings? A classical answer has long been ‘no’, but accumulating data are now challenging this view. Repeatability in experimental evolution, in phenotypic evolution of diverse species and in the genes underlying phenotypic evolution indicates that despite unpredictability at the level of basic evolutionary processes (such as apparition of mutations), a certain kind of predictability can emerge at higher levels over long time periods. For instance, a survey of the alleles described in the literature that cause non-deleterious phenotypic differences among animals, plants and yeasts indicates that similar phenotypes have often evolved in distinct taxa through independent mutations in the same genes. Does this mean that the range of possibilities for evolution is limited? Does this mean that we can predict the outcomes of a replayed tape of life? Imagining other possible paths for evolution runs into four important issues: (i) resolving the influence of contingency, (ii) imagining living organisms that are different from the ones we know, (iii) finding the relevant concepts for predicting evolution, and (iv) estimating the probability of occurrence for complex evolutionary events that occurred only once during the evolution of life on earth.

Fifty years of co-evolution and beyond: integrating co-evolution from molecules to species

Fifty years after Ehrlich and Raven's seminal paper, the idea of co-evolution continues to grow as a key concept in our understanding of organic evolution. This concept has not only provided a compelling synthesis between evolutionary biology and community ecology, but has also inspired research that extends beyond its original scope. In this article, we identify unresolved questions about the co-evolutionary process and advocate for the integration of co-evolutionary research from molecular to interspecific interactions. We address two basic questions: (i) What is co-evolution and how common is it? (ii) What is the unit of co-evolution? Both questions aim to explore the heart of the co-evolutionary process. Despite the claim that co-evolution is ubiquitous, we argue that there is in fact little evidence to support the view that reciprocal natural selection and coadaptation are common in nature. We also challenge the traditional view that co-evolution only occurs between traits of interacting species. Co-evolution has the potential to explain evolutionary processes and patterns that result from intra- and intermolecular biochemical interactions within cells, intergenomic interactions (e.g. nuclear-cytoplasmic) within species, as well as intergenomic interactions mediated by phenotypic traits between species. Research that bridges across these levels of organization will help to advance our understanding of the importance of the co-evolutionary processes in shaping the diversity of life on Earth.

Evolutionary adaptation after crippling cell polarization follows reproducible trajectories

Cells are organized by functional modules, which typically contain components whose removal severely compromises the module's function. Despite their importance, these components are not absolutely conserved between parts of the tree of life, suggesting that cells can evolve to perform the same biological functions with different proteins. We evolved Saccharomyces cerevisiae for 1000 generations without the important polarity gene BEM1. Initially the bem1∆ lineages rapidly increase in fitness and then slowly reach >90% of the fitness of their BEM1 ancestors at the end of the evolution. Sequencing their genomes and monitoring polarization reveals a common evolutionary trajectory, with a fixed sequence of adaptive mutations, each improving cell polarization by inactivating proteins. Our results show that organisms can be evolutionarily robust to physiologically destructive perturbations and suggest that recovery by gene inactivation can lead to rapid divergence in the parts list for cell biologically important functions.

DOI:http://dx.doi.org/10.7554/eLife.09638.001

Cells use the genetic instructions provided by genes in particular combinations called ‘modules’ to perform particular jobs. Very different organisms can share many of the same modules because certain abilities are fundamental to the survival of all cells and so they have been retained over the course of evolution. That said, these modules may not necessarily involve the same genes because it is often possible to achieve the same result using different components.

One way to study how those modules can diversify is to deliberately disrupt one of the genes in a module, and observe how the organism and its descendants respond over many generations. Other genes in these organisms may acquire genetic mutations that enable the genes to take on the role of the missing protein. However, the removal of a single component can be detrimental to the survival of the organisms or may affect many different processes. This can make it difficult to understand what is going on.

A gene called BEM1 is crucial for yeast cells to establish polarity, that is, to allow the different sides of a cell to become distinct from one another. This activity is essential for the yeast to replicate itself. Previous studies have shown that the BEM1 gene had a different role in other species of fungi, which suggests that yeast may have other genes that previously assumed the role that BEM1 does now. In this study, Laan et al. removed BEM1 from yeast and allowed the population of mutant cells to evolve for a thousand generations. The approach differs from previous studies because Laan et al. deliberately selected for yeast that had acquired multiple genetic mutations that can together almost fully compensate for the loss of BEM1.

Initially, the mutant cells grew very slowly, were abnormal in shape and likely to burst open. However, by the end of the experiment, the cells were able to grow almost as well as the original yeast cells had before the gene deletion. Genetic analysis revealed that the deletion of BEM1 triggers the inactivation of other genes that are also involved in the regulation of polarity, which largely restored the ability of the disrupted polarity module to work. This restoration follows a ‘reproducible trajectory’, as the same genes were switched off in the same order in different populations of yeast that were studied at the same time.

The work is an example of reproducible evolution, whereby a specific order of changes to gene activity repeatedly enables cells with severe defects in important processes to adapt and restore a gene module, using whatever components they have left. The next challenge will be to understand how the particular roles of important modules affect their adaptability.

DOI:http://dx.doi.org/10.7554/eLife.09638.002

Whole-Genome Resequencing Reveals Extensive Natural Variation in the Model Green Alga Chlamydomonas reinhardtii

We performed whole-genome resequencing of 12 field isolates and eight commonly studied laboratory strains of the model organism Chlamydomonas reinhardtii to characterize genomic diversity and provide a resource for studies of natural variation. Our data support previous observations that Chlamydomonas is among the most diverse eukaryotic species. Nucleotide diversity is ∼3% and is geographically structured in North America with some evidence of admixture among sampling locales. Examination of predicted loss-of-function mutations in field isolates indicates conservation of genes associated with core cellular functions, while genes in large gene families and poorly characterized genes show a greater incidence of major effect mutations. De novo assembly of unmapped reads recovered genes in the field isolates that are absent from the CC-503 assembly. The laboratory reference strains show a genomic pattern of polymorphism consistent with their origin as the recombinant progeny of a diploid zygospore. Large duplications or amplifications are a prominent feature of laboratory strains and appear to have originated under laboratory culture. Extensive natural variation offers a new source of genetic diversity for studies of Chlamydomonas, including naturally occurring alleles that may prove useful in studies of gene function and the dissection of quantitative genetic traits.