Experimental evolution reveals hidden diversity in evolutionary pathways

Mutations upstream from sdaC and malT in Escherichia coli uncover a complex interplay between the cAMP receptor protein and different sigma factors

In Escherichia coli, one of the best understood microorganisms, much can still be learned about the basic interactions between transcription factors and promoters. When a cAMP-deficient cya mutant is supplied with maltose as the main carbon source, mutations develop upstream from the two genes malT and sdaC. Here, we explore the regulation of the two promoters, using fluorescence-based genetic reporters in combination with both spontaneously evolved and systematically engineered cis-acting mutations. We show that in the cya mutant, regulation of malT and sdaC evolves toward cAMP-independence and increased expression in the stationary phase. Furthermore, we show that the location of the cAMP receptor protein (Crp) binding site upstream of malT is important for alternative sigma factor usage. This provides new insights into the architecture of bacterial promoters and the global interplay between Crp and sigma factors in different growth phases.IMPORTANCEThis work provides new general insights into (1) the architecture of bacterial promoters, (2) the importance of the location of Class I Crp-dependent promoters, and (3) the global interplay between Crp and sigma factors in different growth phases.

Perspectives on Principles of Cellular Behavior from the Biophysics of Protists

Cells are the fundamental unit of biological organization. Although it may be easy to think of them as little more than the simple building blocks of complex organisms such as animals, single cells are capable of behaviors of remarkable apparent sophistication. This is abundantly clear when considering the diversity of form and function among the microbial eukaryotes, the protists. How might we navigate this diversity in the search for general principles of cellular behavior? Here, we review cases in which the intensive study of protists from the perspective of cellular biophysics has driven insight into broad biological questions of morphogenesis, navigation and motility, and decision making. We argue that applying such approaches to questions of evolutionary cell biology presents rich, emerging opportunities. Integrating and expanding biophysical studies across protist diversity, exploiting the unique characteristics of each organism, will enrich our understanding of general underlying principles.

Short-term evolution of antibiotic responses in highly dynamic environments favors loss of regulation

Microbes inhabit natural environments that are remarkably dynamic, with sudden environmental shifts that require immediate action by the cell. To cope with changing environments, microbes are equipped with regulated response mechanisms that are only activated when needed. However, when exposed to extreme environments such as clinical antibiotic treatments, complete loss of regulation is frequently observed. Although recent studies suggest that the initial evolution of microbes in new environments tends to favor mutations in regulatory pathways, it is not clear how this evolution is affected by how quickly conditions change (i.e. dynamics), or which mechanisms are commonly used to implement new regulation. Here, we perform experimental evolution on continuous cultures of E. coli carrying the tetracycline resistance tet operon to identify specific types of mutations that adapt drug responses to different dynamical regimens of drug administration. When cultures are evolved under gradually increasing tetracycline concentrations, we observe no mutations in the tet operon, but a predominance of fine-tuning mutations increasing the affinity of alternative efflux pump AcrB to tetracycline. When cultures are instead periodically exposed to large drug doses, all populations developed transposon insertions in repressor TetR, resulting in loss of regulation of efflux pump TetA. We use a mathematical model of the dynamics of antibiotic responses to show that sudden exposure to large drug concentrations can overwhelm regulated responses, which cannot induce resistance fast enough, resulting in fitness advantage for constitutive expression of resistance. These results help explain the loss of regulation of antibiotic resistance by opportunistic pathogens evolving in clinical environments. Our experiment supports the notion that initial evolution in new ecological niches proceeds largely through regulatory mutations and suggests that transposon insertions are a main mechanism driving this process.

Evolution of haploid and diploid populations reveals common, strong, and variable pleiotropic effects in non-home environments

Adaptation is driven by the selection for beneficial mutations that provide a fitness advantage in the specific environment in which a population is evolving. However, environments are rarely constant or predictable. When an organism well adapted to one environment finds itself in another, pleiotropic effects of mutations that made it well adapted to its former environment will affect its success. To better understand such pleiotropic effects, we evolved both haploid and diploid barcoded budding yeast populations in multiple environments, isolated adaptive clones, and then determined the fitness effects of adaptive mutations in 'non-home' environments in which they were not selected. We find that pleiotropy is common, with most adaptive evolved lineages showing fitness effects in non-home environments. Consistent with other studies, we find that these pleiotropic effects are unpredictable: they are beneficial in some environments and deleterious in others. However, we do find that lineages with adaptive mutations in the same genes tend to show similar pleiotropic effects. We also find that ploidy influences the observed adaptive mutational spectra in a condition-specific fashion. In some conditions, haploids and diploids are selected with adaptive mutations in identical genes, while in others they accumulate mutations in almost completely disjoint sets of genes.

Colony morphotype diversification as a signature of bacterial evolution

The appearance of colony morphotypes is a signature of genetic diversification in evolving bacterial populations. Colony structure highly depends on the cell-cell interactions and polymer production that are adjusted during evolution in an environment that allows the development of spatial structures. Nucci and colleagues describe the emergence of a rough and dry morphotype of a noncapsulated Klebsiella variicola strain during a laboratory evolution study, resembling genetic changes observed in clinical isolates.

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

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

Bacteria evolve macroscopic multicellularity by the genetic assimilation of phenotypically plastic cell clustering

The evolutionary transition from unicellularity to multicellularity was a key innovation in the history of life. Experimental evolution is an important tool to study the formation of undifferentiated cellular clusters, the likely first step of this transition. Although multicellularity first evolved in bacteria, previous experimental evolution research has primarily used eukaryotes. Moreover, it focuses on mutationally driven (and not environmentally induced) phenotypes. Here we show that both Gram-negative and Gram-positive bacteria exhibit phenotypically plastic (i.e., environmentally induced) cell clustering. Under high salinity, they form elongated clusters of ~ 2 cm. However, under habitual salinity, the clusters disintegrate and grow planktonically. We used experimental evolution with Escherichia coli to show that such clustering can be assimilated genetically: the evolved bacteria inherently grow as macroscopic multicellular clusters, even without environmental induction. Highly parallel mutations in genes linked to cell wall assembly formed the genomic basis of assimilated multicellularity. While the wildtype also showed cell shape plasticity across high versus low salinity, it was either assimilated or reversed after evolution. Interestingly, a single mutation could genetically assimilate multicellularity by modulating plasticity at multiple levels of organization. Taken together, we show that phenotypic plasticity can prime bacteria for evolving undifferentiated macroscopic multicellularity.

Barcoding Populations of Pseudomonas fluorescens SBW25

In recent years, evolutionary biologists have developed an increasing interest in the use of barcoding strategies to study eco-evolutionary dynamics of lineages within evolving populations and communities. Although barcoded populations can deliver unprecedented insight into evolutionary change, barcoding microbes presents specific technical challenges. Here, strategies are described for barcoding populations of the model bacterium Pseudomonas fluorescens SBW25, including the design and cloning of barcoded regions, preparation of libraries for amplicon sequencing, and quantification of resulting barcoded lineages. In so doing, we hope to aid the design and implementation of barcoding methodologies in a broad range of model and non-model organisms.

Evolution of cyclic di-GMP signalling on a short and long term time scale

Diversifying radiation of domain families within specific lineages of life indicates the importance of their functionality for the organisms. The foundation for the diversifying radiation of the cyclic di-GMP signalling network that occurred within the bacterial kingdom is most likely based in the outmost adaptability, flexibility and plasticity of the system. Integrative sensing of multiple diverse extra- and intracellular signals is made possible by the N-terminal sensory domains of the modular cyclic di-GMP turnover proteins, mutations in the protein scaffolds and subsequent signal reception by diverse receptors, which eventually rewires opposite host-associated as well as environmental life styles including parallel regulated target outputs. Natural, laboratory and microcosm derived microbial variants often with an altered multicellular biofilm behaviour as reading output demonstrated single amino acid substitutions to substantially alter catalytic activity including substrate specificity. Truncations and domain swapping of cyclic di-GMP signalling genes and horizontal gene transfer suggest rewiring of the network. Presence of cyclic di-GMP signalling genes on horizontally transferable elements in particular observed in extreme acidophilic bacteria indicates that cyclic di-GMP signalling and biofilm components are under selective pressure in these types of environments. On a short and long term evolutionary scale, within a species and in families within bacterial orders, respectively, the cyclic di-GMP signalling network can also rapidly disappear. To investigate variability of the cyclic di-GMP signalling system on various levels will give clues about evolutionary forces and discover novel physiological and metabolic pathways affected by this intriguing second messenger signalling system.

Transient mutation bias increases the predictability of evolution on an empirical genotype-phenotype landscape

Predicting how a population will likely navigate a genotype-phenotype landscape requires consideration of selection in combination with mutation bias, which can skew the likelihood of following a particular trajectory. Strong and persistent directional selection can drive populations to ascend toward a peak. However, with a greater number of peaks and more routes to reach them, adaptation inevitably becomes less predictable. Transient mutation bias, which operates only on one mutational step, can influence landscape navigability by biasing the mutational trajectory early in the adaptive walk. This sets an evolving population upon a particular path, constraining the number of accessible routes and making certain peaks and routes more likely to be realized than others. In this work, we employ a model system to investigate whether such transient mutation bias can reliably and predictably place populations on a mutational trajectory to the strongest selective phenotype or usher populations to realize inferior phenotypic outcomes. For this we use motile mutants evolved from ancestrally non-motile variants of the microbe Pseudomonas fluorescens SBW25, of which one trajectory exhibits significant mutation bias. Using this system, we elucidate an empirical genotype-phenotype landscape, where the hill-climbing process represents increasing strength of the motility phenotype, to reveal that transient mutation bias can facilitate rapid and predictable ascension to the strongest observed phenotype in place of equivalent and inferior trajectories. This article is part of the theme issue 'Interdisciplinary approaches to predicting evolutionary biology'.

Mutation bias and the predictability of evolution

Predicting evolutionary outcomes is an important research goal in a diversity of contexts. The focus of evolutionary forecasting is usually on adaptive processes, and efforts to improve prediction typically focus on selection. However, adaptive processes often rely on new mutations, which can be strongly influenced by predictable biases in mutation. Here, we provide an overview of existing theory and evidence for such mutation-biased adaptation and consider the implications of these results for the problem of prediction, in regard to topics such as the evolution of infectious diseases, resistance to biochemical agents, as well as cancer and other kinds of somatic evolution. We argue that empirical knowledge of mutational biases is likely to improve in the near future, and that this knowledge is readily applicable to the challenges of short-term prediction. This article is part of the theme issue 'Interdisciplinary approaches to predicting evolutionary biology'.

Alternating selection for dispersal and multicellularity favors regulated life cycles

The evolution of complex multicellularity opened paths to increased morphological diversity and organizational novelty. This transition involved three processes: cells remained attached to one another to form groups, cells within these groups differentiated to perform different tasks, and the groups evolved new reproductive strategies.1,2,3,4,5 Recent experiments identified selective pressures and mutations that can drive the emergence of simple multicellularity and cell differentiation,6,7,8,9,10,11 but the evolution of life cycles, particularly how simple multicellular forms reproduce, has been understudied. The selective pressure and mechanisms that produced a regular alternation between single cells and multicellular collectives are still unclear.12 To probe the factors regulating simple multicellular life cycles, we examined a collection of wild isolates of the budding yeast S. cerevisiae.12,13 We found that all these strains can exist as multicellular clusters, a phenotype that is controlled by the mating-type locus and strongly influenced by the nutritional environment. Inspired by this variation, we engineered inducible dispersal in a multicellular laboratory strain and demonstrated that a regulated life cycle has an advantage over constitutively single-celled or constitutively multicellular life cycles when the environment alternates between favoring intercellular cooperation (a low sucrose concentration) and dispersal (a patchy environment generated by emulsion). Our results suggest that the separation of mother and daughter cells is under selection in wild isolates and is regulated by their genetic composition and the environments they encounter and that alternating patterns of resource availability may have played a role in the evolution of life cycles.

Distribution of mutation rates challenges evolutionary predictability

Natural selection is commonly assumed to act on extensive standing genetic variation. Yet, accumulating evidence highlights the role of mutational processes creating this genetic variation: to become evolutionarily successful, adaptive mutants must not only reach fixation, but also emerge in the first place, i.e. have a high enough mutation rate. Here, we use numerical simulations to investigate how mutational biases impact our ability to observe rare mutational pathways in the laboratory and to predict outcomes in experimental evolution. We show that unevenness in the rates at which mutational pathways produce adaptive mutants means that most experimental studies lack power to directly observe the full range of adaptive mutations. Modelling mutation rates as a distribution, we show that a substantially larger target size ensures that a pathway mutates more commonly. Therefore, we predict that commonly mutated pathways are conserved between closely related species, but not rarely mutated pathways. This approach formalizes our proposal that most mutations have a lower mutation rate than the average mutation rate measured experimentally. We suggest that the extent of genetic variation is overestimated when based on the average mutation rate.

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

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

Towards evolutionary predictions: Current promises and challenges

Evolution has traditionally been a historical and descriptive science, and predicting future evolutionary processes has long been considered impossible. However, evolutionary predictions are increasingly being developed and used in medicine, agriculture, biotechnology and conservation biology. Evolutionary predictions may be used for different purposes, such as to prepare for the future, to try and change the course of evolution or to determine how well we understand evolutionary processes. Similarly, the exact aspect of the evolved population that we want to predict may also differ. For example, we could try to predict which genotype will dominate, the fitness of the population or the extinction probability of a population. In addition, there are many uses of evolutionary predictions that may not always be recognized as such. The main goal of this review is to increase awareness of methods and data in different research fields by showing the breadth of situations in which evolutionary predictions are made. We describe how diverse evolutionary predictions share a common structure described by the predictive scope, time scale and precision. Then, by using examples ranging from SARS-CoV2 and influenza to CRISPR-based gene drives and sustainable product formation in biotechnology, we discuss the methods for predicting evolution, the factors that affect predictability and how predictions can be used to prevent evolution in undesirable directions or to promote beneficial evolution (i.e. evolutionary control). We hope that this review will stimulate collaboration between fields by establishing a common language for evolutionary predictions.

Optimal transcriptional regulation of dynamic bacterial responses to sudden drug exposures

Cellular responses to the presence of toxic compounds in their environment require prompt expression of the correct levels of the appropriate enzymes, which are typically regulated by transcription factors that control gene expression for the duration of the response. The characteristics of each response dictate the choice of regulatory parameters such as the affinity of the transcription factor to its binding sites and the strength of the promoters it regulates. Although much is known about the dynamics of cellular responses, we still lack a framework to understand how different regulatory strategies evolved in natural systems relate to the selective pressures acting in each particular case. Here, we analyze a dynamical model of a typical antibiotic response in bacteria, where a transcriptionally repressed enzyme is induced by a sudden exposure to the drug that it processes. We identify strategies of gene regulation that optimize this response for different types of selective pressures, which we define as a set of costs associated with the drug, enzyme, and repressor concentrations during the response. We find that regulation happens in a limited region of the regulatory parameter space. While responses to more costly (toxic) drugs favor the usage of strongly self-regulated repressors, responses where expression of enzyme is more costly favor the usage of constitutively expressed repressors. Only a very narrow range of selective pressures favor weakly self-regulated repressors. We use this framework to determine which costs and benefits are most critical for the evolution of a variety of natural cellular responses that satisfy the approximations in our model and to analyze how regulation is optimized in new environments with different demands.

Identification of Cyclic-di-GMP-Modulating Protein Residues by Bidirectionally Evolving a Social Behavior in Pseudomonas fluorescens

Modulation of the intracellular cyclic di-GMP (c-di-GMP) pool is central to the formation of structured bacterial communities. Genome annotations predict the presence of dozens of conserved c-di-GMP catalytic enzymes in many bacterial species, but the functionality and regulatory control of the vast majority remain underexplored. Here, we begin to fill this gap by utilizing an experimental evolution system in Pseudomonas fluorescens Pf0-1, which repeatedly produces a unique social behavior through bidirectional transitions between two distinct phenotypes converging on c-di-GMP modulation. Parallel evolution of 33 lineages captured 147 unique mutations among 191 evolved isolates in genes that are empirically demonstrated, bioinformatically predicted, or previously unknown to impact the intracellular pool of c-di-GMP. Quantitative chemistry confirmed that each mutation causing the phenotypic shift either amplifies or reduces c-di-GMP production. We identify missense or in-frame deletion mutations in numerous diguanylate cyclase genes that largely fall outside the conserved catalytic domain. We also describe a novel relationship between a regulatory component of branched-chain amino acid biosynthesis and c-di-GMP production, and predict functions of several other unexpected proteins that clearly impact c-di-GMP production. Sequential mutations that continuously disrupt or recover c-di-GMP production across discrete functional elements suggest a complex and underappreciated interconnectivity within the c-di-GMP regulome of P. fluorescens. IMPORTANCE Microbial communities comprise densely packed cells where competition for space and resources is fierce. Aging colonies of Pseudomonas fluorescens are known to repeatedly produce mutants with two distinct phenotypes that physically work together to spread away from the overcrowded population. We demonstrate that the mutants with one phenotype produce high levels of cyclic di-GMP (c-di-GMP) and those with the second phenotype produce low levels. C-di-GMP is an intracellular signaling molecule which regulates many bacterial traits that cause tremendous clinical and environmental problems. Here, we analyze 147 experimentally selected mutations, which manifest either of the two phenotypes, to identify key residues in diverse proteins that force or shut down c-di-GMP production. Our data indicate that the intracellular pool of c-di-GMP is modulated through the catalytic activities of many independent c-di-GMP enzymes, which appear to be in tune with several proteins with no known links to c-di-GMP modulation.

Pseudomonas aeruginosa Strains from Both Clinical and Environmental Origins Readily Adopt a Stable Small-Colony-Variant Phenotype Resulting from Single Mutations in c-di-GMP Pathways

A subpopulation of small-colony variants (SCVs) is a frequently observed feature of Pseudomonas aeruginosa isolates obtained from colonized cystic fibrosis lungs. Since most SCVs have until now been isolated from clinical samples, it remains unclear how widespread the ability of P. aeruginosa strains to develop this phenotype is and what the genetic mechanism(s) behind the emergence of SCVs are according to the origin of the isolate. In the present work, we investigated the ability of 22 P. aeruginosa isolates from various environmental origins to spontaneously adopt an SCV-like smaller alternative morphotype distinguishable from that of the ancestral parent strain under laboratory culture conditions. We found that all the P. aeruginosa strains tested could adopt an SCV phenotype, regardless of their origin. Whole-genome sequencing of SCVs obtained from clinical and environmental sources revealed single mutations exclusively in two distinct c-di-GMP signaling pathways, the Wsp and YfiBNR pathways. We conclude that the ability to switch to an SCV phenotype is a conserved feature of P. aeruginosa and results from the acquisition of a stable genetic mutation, regardless of the origin of the strain. IMPORTANCE P. aeruginosa is an opportunistic pathogen that thrives in many environments. It poses a significant health concern, notably because this bacterium is the most prevalent pathogen found in the lungs of people with cystic fibrosis. In infected hosts, its persistence is considered related to the emergence of an alternative small-colony-variant (SCV) phenotype. By reporting the distribution of P. aeruginosa SCVs in various nonclinical environments and the involvement of c-di-GMP in SCV emergence from both clinical and environmental strains, this work contributes to understanding a conserved adaptation mechanism used by P. aeruginosa to adapt readily in all environments. Hindering this adaptation strategy could help control persistent infection by P. aeruginosa.

Density-dependent effects are the main determinants of variation in growth dynamics between closely related bacterial strains

Although closely related, bacterial strains from the same species show significant diversity in their growth and death dynamics. Yet, our understanding of the relationship between the kinetic parameters that dictate these dynamics is still lacking. Here, we measured the growth and death dynamics of 11 strains of Escherichia coli originating from different hosts and show that the growth patterns are clustered into three major classes with typical growth rates, maximal fold change, and death rates. To infer the underlying phenotypic parameters that govern the dynamics, we developed a phenomenological mathematical model that accounts not only for growth rate and its dependence on resource availability, but also for death rates and density-dependent growth inhibition. We show that density-dependent growth is essential for capturing the variability in growth dynamics between the strains. Indeed, the main parameter determining the dynamics is the typical density at which they slow down their growth, rather than the maximal growth rate or death rate. Moreover, we show that the phenotypic landscape resides within a two-dimensional plane spanned by resource utilization efficiency, death rate, and density-dependent growth inhibition. In this phenotypic plane, we identify three clusters that correspond to the growth pattern classes. Overall, our results reveal the tradeoffs between growth parameters that constrain bacterial adaptation.

Evolutionary Principles of Bacterial Signaling Capacity and Complexity

Microbes rely on signal transduction systems to sense and respond to environmental changes for survival and reproduction. It is generally known that niche adaptation plays an important role in shaping the signaling repertoire. However, the evolution of bacterial signaling capacity lacks systematic studies with a temporal direction. In particular, it is unclear how complexity evolved from simplicity or vice versa for signaling networks. Here, we examine the evolutionary processes of major signal transduction systems in Campylobacterota (formerly Epsilonproteobacteria), a phylum with sufficient evolutionary depth and ecological diversity. We discovered that chemosensory system increases complexity by horizontal gene transfer (HGT) of entire chemosensory classes, and different chemosensory classes rarely mix their components. Two-component system gains complexity by atypical histidine kinases fused with receiver domain to achieve multistep or branched signal transduction process. The presence and complexity of c-di-GMP-mediated system is related to the size of signaling network, and c-di-GMP pathways are easy to rewire, since enzymes and effectors can be linked without direct protein-protein interaction. Overall, signaling capacity and complexity rise and drop together in Campylobacterota, determined by sensory demand, genetic resources, and coevolution within the genomic context. These findings reflect plausible evolutionary principles for other cellular networks and genome evolution of the Bacteria domain.

Adaptation and phenotypic diversification of Bacillus thuringiensis biofilm are accompanied by fuzzy spreader morphotypes

Bacillus cereus group (Bacillus cereus sensu lato) has a diverse ecology, including various species that produce biofilms on abiotic and biotic surfaces. While genetic and morphological diversification enables the adaptation of multicellular communities, this area remains largely unknown in the Bacillus cereus group. In this work, we dissected the experimental evolution of Bacillus thuringiensis 407 Cry- during continuous recolonization of plastic beads. We observed the evolution of a distinct colony morphotype that we named fuzzy spreader (FS) variant. Most multicellular traits of the FS variant displayed higher competitive ability versus the ancestral strain, suggesting an important role for diversification in the adaptation of B. thuringiensis to the biofilm lifestyle. Further genetic characterization of FS variant revealed the disruption of a guanylyltransferase gene by an insertion sequence (IS) element, which could be similarly observed in the genome of a natural isolate. The evolved FS and the deletion mutant in the guanylyltransferase gene (Bt407ΔrfbM) displayed similarly altered aggregation and hydrophobicity compared to the ancestor strain, suggesting that the adaptation process highly depends on the physical adhesive forces.

Advantages of laboratory natural selection in the applied sciences

In the past three decades, laboratory natural selection has become a widely used technique in biological research. Most studies which have utilized this technique are in the realm of basic science, often testing hypotheses related to mechanisms of evolutionary change or ecological dynamics. While laboratory natural selection is currently utilized heavily in this setting, there is a significant gap with its usage in applied studies, especially when compared to the other selection experiment methodologies like artificial selection and directed evolution. This is despite avenues of research in the applied sciences which seem well suited to laboratory natural selection. In this review, we place laboratory natural selection in context with other selection experiments, identify the characteristics which make it well suited for particular kinds of applied research and briefly cover key examples of the usefulness of selection experiments within applied science. Finally, we identify three promising areas of inquiry for laboratory natural selection in the applied sciences: bioremediation technology, identifying mechanisms of drug resistance and optimizing biofuel production. Although laboratory natural selection is currently less utilized in applied science when compared to basic research, the method has immense promise in the field moving forward.

Rugose small colony variant and its hyper-biofilm in Pseudomonas aeruginosa: Adaption, evolution, and biotechnological potential

One of the hallmarks of the environmental bacterium Pseudomonas aeruginosa is its excellent ecological flexibility, which can thrive in diverse ecological niches. In different ecosystems, P. aeruginosa may use different strategies to survive, such as forming biofilms in crude oil environment, converting to mucoid phenotype in the cystic fibrosis (CF) lung, or becoming persisters when treated with antibiotics. Rugose small colony variants (RSCVs) are the adaptive mutants of P. aeruginosa, which can be frequently isolated from chronic infections. During the past years, there has been a renewed interest in using P. aeruginosa as a model organism to investigate the RSCVs formation, persistence and pathogenesis, as RSCVs represent a hyper-biofilm formation, high adaptability, high-tolerance sub-population in biofilms. This review will briefly summarize recent advances regarding the phenotypic, genetic and host interaction associated with RSCVs, with an emphasis on P. aeruginosa. Meanwhile, some non-pathogenic bacteria such as Pseudomonas fluorescence, Pseudomonas putida and Bacillus subtilis will be also included. Remarkable emphasis is given on intrinsic functions of such hyper-biofilm formation characteristic as well as its potential applications in several biocatalytic transformations including wastewater treatment, microbial fermentation, and plastic degradation. Hopefully, this review will attract the interest of researchers in various fields and shape future research focused not only on evolutionary biology but also on biotechnological applications related to RSCVs.

A mutational hotspot that determines highly repeatable evolution can be built and broken by silent genetic changes

Mutational hotspots can determine evolutionary outcomes and make evolution repeatable. Hotspots are products of multiple evolutionary forces including mutation rate heterogeneity, but this variable is often hard to identify. In this work, we reveal that a near-deterministic genetic hotspot can be built and broken by a handful of silent mutations. We observe this when studying homologous immotile variants of the bacteria Pseudomonas fluorescens, AR2 and Pf0-2x. AR2 resurrects motility through highly repeatable de novo mutation of the same nucleotide in >95% lines in minimal media (ntrB A289C). Pf0-2x, however, evolves via a number of mutations meaning the two strains diverge significantly during adaptation. We determine that this evolutionary disparity is owed to just 6 synonymous variations within the ntrB locus, which we demonstrate by swapping the sites and observing that we are able to both break (>95% to 0%) and build (0% to 80%) a deterministic mutational hotspot. Our work reveals a key role for silent genetic variation in determining adaptive outcomes.

High-throughput characterization of mutations in genes that drive clonal evolution using multiplex adaptome capture sequencing

Understanding how cells are likely to evolve can guide medical interventions and bioengineering efforts that must contend with unwanted mutations. The adaptome of a cell-the neighborhood of genetic changes that are most likely to drive adaptation in a given environment-can be mapped by tracking rare beneficial variants during the early stages of clonal evolution. We used multiplex adaptome capture sequencing (mAdCap-seq), a procedure that combines unique molecular identifiers and hybridization-based enrichment, to characterize mutations in eight Escherichia coli genes known to be under selection in a laboratory environment. We tracked 301 mutations at frequencies as low as 0.01% and inferred the fitness effects of 240 of these mutations. There were distinct molecular signatures of selection on protein structure and function for the three genes with the most beneficial mutations. Our results demonstrate how mAdCap-seq can be used to deeply profile a targeted portion of a cell's adaptome.

Forecasting of phenotypic and genetic outcomes of experimental evolution in Pseudomonas protegens

Experimental evolution with microbes is often highly repeatable under identical conditions, suggesting the possibility to predict short-term evolution. However, it is not clear to what degree evolutionary forecasts can be extended to related species in non-identical environments, which would allow testing of general predictive models and fundamental biological assumptions. To develop an extended model system for evolutionary forecasting, we used previous data and models of the genotype-to-phenotype map from the wrinkly spreader system in Pseudomonas fluorescens SBW25 to make predictions of evolutionary outcomes on different biological levels for Pseudomonas protegens Pf-5. In addition to sequence divergence (78% amino acid and 81% nucleotide identity) for the genes targeted by mutations, these species also differ in the inability of Pf-5 to make cellulose, which is the main structural basis for the adaptive phenotype in SBW25. The experimental conditions were changed compared to the SBW25 system to test if forecasts were extendable to a non-identical environment. Forty-three mutants with increased ability to colonize the air-liquid interface were isolated, and the majority had reduced motility and was partly dependent on the Pel exopolysaccharide as a structural component. Most (38/43) mutations are expected to disrupt negative regulation of the same three diguanylate cyclases as in SBW25, with a smaller number of mutations in promoter regions, including an uncharacterized polysaccharide synthase operon. A mathematical model developed for SBW25 predicted the order of the three main pathways and the genes targeted by mutations, but differences in fitness between mutants and mutational biases also appear to influence outcomes. Mutated regions in proteins could be predicted in most cases (16/22), but parallelism at the nucleotide level was low and mutational hot spot sites were not conserved. This study demonstrates the potential of short-term evolutionary forecasting in experimental populations and provides testable predictions for evolutionary outcomes in other Pseudomonas species.

Repeated Exposure of Aspergillus niger Spores to the Antifungal Bacterium Collimonas fungivorans Ter331 Selects for Delayed Spore Germination

The bacterial strain Collimonas fungivorans Ter331 (CfTer331) inhibits mycelial growth and spore germination in Aspergillus niger N402 (AnN402). The mechanisms underlying this antagonistic bacterial-fungal interaction have been extensively studied, but knowledge on the long-term outcome of this interaction is currently lacking. Here, we used experimental evolution to explore the dynamics of fungal adaptation to recurrent exposure to CfTer331. Specifically, five single-spore isolates (SSIs) of AnN402 were evolved under three selection scenarios in liquid culture, i.e., (i) in the presence of CfTer331 for 80 growth cycles, (ii) in the absence of the bacterium for 80 cycles, and (iii) in the presence of CfTer331 for 40 cycles and then in its absence for 40 cycles. The evolved SSI lineages were then evaluated for phenotypic changes from the founder fungal strain, such as germinability with or without CfTer331. The analysis showed that recurrent exposure to CfTer331 selected for fungal lineages with reduced germinability and slower germination, even in the absence of CfTer331. In contrast, when AnN402 evolved in the absence of the bacteria, lineages with increased germinability and faster germination were favored. SSIs that were first evolved in the presence of CfTer331 and then in its absence showed intermediate phenotypes but overall were more similar to SSIs that evolved in the absence of CfTer331 for 80 cycles. This suggests that traits acquired from exposure to CfTer331 were reversible upon removal of the selection pressure. Overall, our study provides insights into the effects on fungi from the long-term coculture with bacteria. IMPORTANCE The use of antagonistic bacteria for managing fungal diseases is becoming increasingly popular, and thus there is a need to understand the implications of their long-term use against fungi. Most efforts have so far focused on characterizing the antifungal properties and mode of action of the bacterial antagonists, but the possible outcomes of the persisting interaction between antagonistic bacteria and fungi are not well understood. In this study, we used experimental evolution in order to explore the evolutionary aspects of an antagonistic bacterial-fungal interaction, using the antifungal bacterium Collimonas fungivorans and the fungus Aspergillus niger as a model system. We show that evolution in the presence or absence of the bacteria selects for fungal lineages with opposing and conditionally beneficial traits, such as slow and fast spore germination, respectively. Overall, our studies reveal that fungal responses to biotic factors related to antagonism could be to some extent predictable and reversible.

From genotypes to organisms: State-of-the-art and perspectives of a cornerstone in evolutionary dynamics

Understanding how genotypes map onto phenotypes, fitness, and eventually organisms is arguably the next major missing piece in a fully predictive theory of evolution. We refer to this generally as the problem of the genotype-phenotype map. Though we are still far from achieving a complete picture of these relationships, our current understanding of simpler questions, such as the structure induced in the space of genotypes by sequences mapped to molecular structures, has revealed important facts that deeply affect the dynamical description of evolutionary processes. Empirical evidence supporting the fundamental relevance of features such as phenotypic bias is mounting as well, while the synthesis of conceptual and experimental progress leads to questioning current assumptions on the nature of evolutionary dynamics-cancer progression models or synthetic biology approaches being notable examples. This work delves with a critical and constructive attitude into our current knowledge of how genotypes map onto molecular phenotypes and organismal functions, and discusses theoretical and empirical avenues to broaden and improve this comprehension. As a final goal, this community should aim at deriving an updated picture of evolutionary processes soundly relying on the structural properties of genotype spaces, as revealed by modern techniques of molecular and functional analysis.

Dynamics of bacterial adaptation

Determining pattern in the dynamics of population evolution is a long-standing focus of evolutionary biology. Complementing the study of natural populations, microbial laboratory evolution experiments have become an important tool for addressing these dynamics because they allow detailed and replicated analysis of evolution in response to controlled environmental and genetic conditions. Key findings include a tendency for smoothly declining rates of adaptation during selection in constant environments, at least in part a reflection of antagonism between accumulating beneficial mutations, and a large number of beneficial mutations available to replicate populations leading to significant, but relatively low genetic parallelism, even as phenotypic characteristics show high similarity. Together, there is a picture of adaptation as a process with a varied and largely unpredictable genetic basis leading to much more similar phenotypic outcomes. Increasing sophistication of sequencing and genetic tools will allow insight into mechanisms behind these and other patterns.

Fitness variation across subtle environmental perturbations reveals local modularity and global pleiotropy of adaptation

Building a genotype-phenotype-fitness map of adaptation is a central goal in evolutionary biology. It is difficult even when adaptive mutations are known because it is hard to enumerate which phenotypes make these mutations adaptive. We address this problem by first quantifying how the fitness of hundreds of adaptive yeast mutants responds to subtle environmental shifts. We then model the number of phenotypes these mutations collectively influence by decomposing these patterns of fitness variation. We find that a small number of inferred phenotypes can predict fitness of the adaptive mutations near their original glucose-limited evolution condition. Importantly, inferred phenotypes that matter little to fitness at or near the evolution condition can matter strongly in distant environments. This suggests that adaptive mutations are locally modular - affecting a small number of phenotypes that matter to fitness in the environment where they evolved - yet globally pleiotropic - affecting additional phenotypes that may reduce or improve fitness in new environments.

Compost spatial heterogeneity promotes evolutionary diversification of a bacterium

Spatial resource heterogeneity is expected to be a key driver for the evolution of diversity. However, direct empirical support for this prediction is limited to studies carried out in simplified laboratory environments. Here, we investigate how altering spatial heterogeneity of potting compost-by the addition of water and mixing-affects the evolutionary diversification of a bacterial species, Pseudomonas fluorescens, that is naturally found in the environment. There was a greater propensity of resource specialists to evolve in the unmanipulated compost, while more generalist phenotypes dominated the compost-water mix. Genomic data were consistent with these phenotypic findings. Competition experiments strongly suggest these results are due to diversifying selection as a result of resource heterogeneity, as opposed to other covariables. Overall, our findings corroborate theoretical and in vitro findings, but in semi-natural, more realistic conditions.

Adverse effects of adaptive mutation to survive static culture conditions on successful fitness of the rice pathogen Burkholderia glumae in a host

Bacteria often possess relatively flexible genome structures and adaptive genetic variants that allow survival in unfavorable growth conditions. Bacterial survival tactics in disadvantageous microenvironments include mutations that are beneficial against threats in their niche. Here, we report that the aerobic rice bacterial pathogen Burkholderia glumae BGR1 changes a specific gene for improved survival in static culture conditions. Static culture triggered formation of colony variants with deletions or point mutations in the gene bspP (BGLU_RS28885), which putatively encodes a protein that contains PDC2, PAS-9, SpoIIE, and HATPase domains. The null mutant of bspP survived longer in static culture conditions and produced a higher level of bis-(3'-5')-cyclic dimeric guanosine monophosphate than the wild type. Expression of the bacterial cellulose synthase regulator (bcsB) gene was upregulated in the mutant, consistent with the observation that the mutant formed pellicles faster than the wild type. Mature pellicle formation was observed in the bspP mutant before pellicle formation in wild-type BGR1. However, the population density of the bspP null mutant decreased substantially when grown in Luria-Bertani medium with vigorous agitation due to failure of oxalate-mediated detoxification of the alkaline environment. The bspP null mutant was less virulent and exhibited less effective colonization of rice plants than the wild type. All phenotypes caused by mutations in bspP were recovered to those of the wild type by genetic complementation. Thus, although wild-type B. glumae BGR1 prolonged viability by spontaneous mutation under static culture conditions, such genetic changes negatively affected colonization in rice plants. These results suggest that adaptive gene sacrifice of B. glumae to survive unfavorable growth conditions is not always desirable as it can adversely affect adaptability in the host.

Three biofilm types produced by a model pseudomonad are differentiated by structural characteristics and fitness advantage

Model bacterial biofilm systems suggest that bacteria produce one type of biofilm, which is then modified by environmental and physiological factors, although the diversification of developing populations might result in the appearance of adaptive mutants producing altered structures with improved fitness advantage. Here we compare the air-liquid (A-L) interface viscous mass (VM) biofilm produced by Pseudomonas fluorescens SBW25 and the wrinkly spreader (WS) and complementary biofilm-forming strain (CBFS) biofilm types produced by adaptive SBW25 mutants in order to better understand the link between these physical structures and the fitness advantage they provide in experimental microcosms. WS, CBFS and VM biofilms can be differentiated by strength, attachment levels and rheology, as well as by strain characteristics associated with biofilm formation. Competitive fitness assays demonstrate that they provide similar advantages under static growth conditions but respond differently to increasing levels of physical disturbance. Pairwise competitions between biofilms suggest that these strains must be competing for at least two growth-limiting resources at the A-L interface, most probably O₂ and nutrients, although VM and CBFS cells located lower down in the liquid column might provide an additional fitness advantage through the colonization of a less competitive zone below the biofilm. Our comparison of different SBW25 biofilm types illustrates more generally how varied biofilm characteristics and fitness advantage could become among adaptive mutants arising from an ancestral biofilm-forming strain and raises the question of how significant these changes might be in a range of medical, biotechnological and industrial contexts where diversification and change may be problematic.

The evolutionary plasticity of chromosome metabolism allows adaptation to constitutive DNA replication stress

Many biological features are conserved and thus considered to be resistant to evolutionary change. While rapid genetic adaptation following the removal of conserved genes has been observed, we often lack a mechanistic understanding of how adaptation happens. We used the budding yeast, Saccharomyces cerevisiae, to investigate the evolutionary plasticity of chromosome metabolism, a network of evolutionary conserved modules. We experimentally evolved cells constitutively experiencing DNA replication stress caused by the absence of Ctf4, a protein that coordinates the enzymatic activities at replication forks. Parallel populations adapted to replication stress, over 1000 generations, by acquiring multiple, concerted mutations. These mutations altered conserved features of two chromosome metabolism modules, DNA replication and sister chromatid cohesion, and inactivated a third, the DNA damage checkpoint. The selected mutations define a functionally reproducible evolutionary trajectory. We suggest that the evolutionary plasticity of chromosome metabolism has implications for genome evolution in natural populations and cancer.

Penetrating the air-liquid interface is the key to colonization and wrinkly spreader fitness

In radiating populations of Pseudomonas fluorescens SBW25, adaptive wrinkly spreader (WS) mutants are able to gain access to the air-liquid (A-L) interface of static liquid microcosms and achieve a significant competitive fitness advantage over other non-biofilm-forming competitors. Aerotaxis and flagella-based swimming allows SBW25 cells to move into the high-O₂ region located at the top of the liquid column and maintain their position by countering the effects of random cell diffusion, convection and disturbance (i.e. physical displacement). However, wild-type cells showed significantly lower levels of enrichment in this region compared to the archetypal WS, indicating that WS cells employ an additional mechanism to transfer to the A-L interface where displacement is no longer an issue and a biofilm can develop at the top of the liquid column. Preliminary experiments suggest that this might be achieved through the expression of an as yet unidentified surface active agent that is weakly associated with WS cells and alters liquid surface tension, as determined by quantitative tensiometry. The effect of physical displacement on the colonization of the high-O₂ region and A-L interface was reduced through the addition of agar or polyethylene glycol to increase liquid viscosity, and under these conditions the competitive fitness of the WS was significantly reduced. These observations suggest that the ability to transfer to the A-L interface from the high-O₂ region and remain there without further expenditure of energy (through, for example, the deployment of flagella) is a key evolutionary innovation of the WS, as it allows subsequent biofilm development and significant population increase, thereby affording these adaptive mutants a competitive fitness advantage over non-biofilm-forming competitors located within the liquid column.

Stochastic Gene Expression Influences the Selection of Antibiotic Resistance Mutations

Bacteria can resist antibiotics by expressing enzymes that remove or deactivate drug molecules. Here, we study the effects of gene expression stochasticity on efflux and enzymatic resistance. We construct an agent-based model that stochastically simulates multiple biochemical processes in the cell and we observe the growth and survival dynamics of the cell population. Resistance-enhancing mutations are introduced by varying parameters that control the enzyme expression or efficacy. We find that stochastic gene expression can cause complex dynamics in terms of survival and extinction for these mutants. Regulatory mutations, which augment the frequency and duration of resistance gene transcription, can provide limited resistance by increasing mean expression. Structural mutations, which modify the enzyme or efflux efficacy, provide most resistance by improving the binding affinity of the resistance protein to the antibiotic; increasing the enzyme's catalytic rate alone may contribute to resistance if drug binding is not rate limiting. Overall, we identify conditions where regulatory mutations are selected over structural mutations, and vice versa. Our findings show that stochastic gene expression is a key factor underlying efflux and enzymatic resistances and should be taken into consideration in future antibiotic research.

CRISPR interference to interrogate genes that control biofilm formation in Pseudomonas fluorescens

Bacterial biofilm formation involves signaling and regulatory pathways that control the transition from motile to sessile lifestyle, production of extracellular polymeric matrix, and maturation of the biofilm 3D structure. Biofilms are extensively studied because of their importance in biomedical, ecological and industrial settings. Gene inactivation is a powerful approach for functional studies but it is often labor intensive, limiting systematic gene surveys to the most tractable bacterial hosts. Here, we adapted the CRISPR interference (CRISPRi) system for use in diverse strain isolates of P. fluorescens, SBW25, WH6 and Pf0-1. We found that CRISPRi is applicable to study complex phenotypes such as cell morphology, motility and biofilm formation over extended periods of time. In SBW25, CRISPRi-mediated silencing of genes encoding the GacA/S two-component system and regulatory proteins associated with the cylic di-GMP signaling messenger produced swarming and biofilm phenotypes similar to those obtained after gene inactivation. Combined with detailed confocal microscopy of biofilms, our study also revealed novel phenotypes associated with extracellular matrix biosynthesis as well as the potent inhibition of SBW25 biofilm formation mediated by the PFLU1114 operon. We conclude that CRISPRi is a reliable and scalable approach to investigate gene networks in the diverse P. fluorescens group.

Trusting the hand that feeds: microbes evolve to anticipate a serial transfer protocol as individuals or collectives

BACKGROUND

Experimental evolution of microbes often involves a serial transfer protocol, where microbes are repeatedly diluted by transfer to a fresh medium, starting a new growth cycle. This has revealed that evolution can be remarkably reproducible, where microbes show parallel adaptations both on the level of the phenotype as well as the genotype. However, these studies also reveal a strong potential for divergent evolution, leading to diversity both between and within replicate populations. We here study how in silico evolved Virtual Microbe "wild types" (WTs) adapt to a serial transfer protocol to investigate generic evolutionary adaptations, and how these adaptations can be manifested by a variety of different mechanisms.

RESULTS

We show that all WTs evolve to anticipate the regularity of the serial transfer protocol by adopting a fine-tuned balance of growth and survival. This anticipation is done by evolving either a high yield mode, or a high growth rate mode. We find that both modes of anticipation can be achieved by individual lineages and by collectives of microbes. Moreover, these different outcomes can be achieved with or without regulation, although the individual-based anticipation without regulation is less well adapted in the high growth rate mode.

CONCLUSIONS

All our in silico WTs evolve to trust the hand that feeds by evolving to anticipate the periodicity of a serial transfer protocol, but can do so by evolving two distinct growth strategies. Furthermore, both these growth strategies can be accomplished by gene regulation, a variety of different polymorphisms, and combinations thereof. Our work reveals that, even under controlled conditions like those in the lab, it may not be possible to predict individual evolutionary trajectories, but repeated experiments may well result in only a limited number of possible outcomes.

Probabilistic Models for Predicting Mutational Routes to New Adaptive Phenotypes

Understanding the translation of genetic variation to phenotypic variation is a fundamental problem in genetics and evolutionary biology. The introduction of new genetic variation through mutation can lead to new adaptive phenotypes, but the complexity of the genotype-to-phenotype map makes it challenging to predict the phenotypic effects of mutation. Metabolic models, in conjunction with flux balance analysis, have been used to predict evolutionary optimality. These methods however rely on large scale models of metabolism, describe a limited set of phenotypes, and assume that selection for growth rate is the prime evolutionary driver. Here we describe a method for computing the relative likelihood that mutational change will translate into a phenotypic change between two molecular pathways. The interactions of molecular components in the pathways are modeled with ordinary differential equations. Unknown parameters are offset by probability distributions that describe the concentrations of molecular components, the reaction rates for different molecular processes, and the effects of mutations. Finally, the likelihood that mutations in a pathway will yield phenotypic change is estimated with stochastic simulations. One advantage of this method is that only basic knowledge of the interaction network underlying a phenotype is required. However, it can also incorporate available information about concentrations and reaction rates as well as mutational biases and mutational robustness of molecular components. The method estimates the relative probabilities that different pathways produce phenotypic change, which can be combined with fitness models to predict evolutionary outcomes.

Causes and Biophysical Consequences of Cellulose Production by Pseudomonas fluorescens SBW25 at the Air-Liquid Interface

This work reveals a hitherto unrecognized behavior that manifests at the air-liquid interface that depends on production of cellulose and hints at undiscovered dimensions to bacterial life at surfaces. Additionally, the study links activation of known diguanylate cyclase-encoding pathways to cellulose expression and to signals encountered at the meniscus. Further significance stems from recognition of the consequences of fluid instabilities arising from surface production of cellulose for transport of water-soluble products over large distances.

Cellulose-overproducing wrinkly spreader mutants of Pseudomonas fluorescens SBW25 have been the focus of much investigation, but conditions promoting the production of cellulose in ancestral strain SBW25 and its effects and consequences have escaped in-depth investigation through lack of an in vitro phenotype. Here, using a custom-built device, we reveal that in static broth microcosms, ancestral SBW25 encounters environmental signals at the air-liquid interface that activate, via three diguanylate cyclase-encoding pathways (Wsp, Aws, and Mws), production of cellulose. Secretion of the polymer at the meniscus leads to modification of the environment and growth of numerous microcolonies that extend from the surface. Accumulation of cellulose and associated microbial growth leads to Rayleigh-Taylor instability resulting in bioconvection and rapid transport of water-soluble products over tens of millimeters. Drawing upon data, we built a mathematical model that recapitulates experimental results and captures the interactions between biological, chemical and physical processes.

IMPORTANCE This work reveals a hitherto unrecognized behavior that manifests at the air-liquid interface that depends on production of cellulose and hints at undiscovered dimensions to bacterial life at surfaces. Additionally, the study links activation of known diguanylate cyclase-encoding pathways to cellulose expression and to signals encountered at the meniscus. Further significance stems from recognition of the consequences of fluid instabilities arising from surface production of cellulose for transport of water-soluble products over large distances.

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.