Clonal adaptive radiation in a constant environment

RpoS and the bacterial general stress response

SUMMARYThe general stress response (GSR) is a widespread strategy developed by bacteria to adapt and respond to their changing environments. The GSR is induced by one or multiple simultaneous stresses, as well as during entry into stationary phase and leads to a global response that protects cells against multiple stresses. The alternative sigma factor RpoS is the central GSR regulator in E. coli and conserved in most γ-proteobacteria. In E. coli, RpoS is induced under conditions of nutrient deprivation and other stresses, primarily via the activation of RpoS translation and inhibition of RpoS proteolysis. This review includes recent advances in our understanding of how stresses lead to RpoS induction and a summary of the recent studies attempting to define RpoS-dependent genes and pathways.

Impact of evolution on lifestyle in microbiome

This chapter analyses the interaction between microbiota and humans from an evolutionary point of view. Long-term interactions between gut microbiota and host have been generated as a result of dietary choices through coevolutionary processes, where mutuality of advantage is essential. Likewise, the characteristics of the intestinal environment have made it possible to describe different intrahost evolutionary mechanisms affecting microbiota. For its part, the intestinal microbiota has been of great importance in the evolution of mammals, allowing the diversification of dietary niches, phenotypic plasticity and the selection of host phenotypes. Although the origin of the human intestinal microbial community is still not known with certainty, mother-offspring transmission plays a key role, and it seems that transmissibility between individuals in adulthood also has important implications. Finally, it should be noted that certain aspects inherent to modern lifestyle, including refined diets, antibiotic intake, exposure to air pollutants, microplastics, and stress, could negatively affect the diversity and composition of our gut microbiota. This chapter aims to combine current knowledge to provide a comprehensive view of the interaction between microbiota and humans throughout evolution.

RpoS role in antibiotic resistance, tolerance and persistence in E. coli natural isolates

BACKGROUND

The intrinsic concentration of RpoS, the second most abundant sigma factor, varies widely across the E. coli species. Bacterial isolates that express high levels of RpoS display high resistance to environmental stresses, such as temperature, pH and osmolarity shifts, but are less nutritional competent, making them less capable of utilising alternative nutrient sources. The role of RpoS in antibiotic resistance and persistence in standard laboratory domesticated strains has been examined in several studies, most demonstrating a positive role for RpoS.

RESULTS

Using disk diffusion assays we examined bacterial resistance to 15 different antibiotics, including β -lactams (penicillins, monobactams, carbapenems and cephalosporins), aminoglycosides, quinolones and anti-folates, in a representative collection of 328 E. coli natural isolates displaying a continuum of different levels of RpoS. There was an overall trend that isolates with higher levels of RpoS were slightly more resistant to these antibiotics. In addition, the effect of RpoS on bacterial tolerance and persistence to 3 different antibiotics - ampicillin, ciprofloxacin and kanamycin was evaluated through time-kill curves. Again, there was a small beneficial effect of RpoS on tolerance and persistence to these antibiotics, but this difference was not statistically significant. Finally, a K-12 strain expressing high levels of RpoS was compared with its isogenic RpoS-null counterpart, and no significant effect of RpoS was found.

CONCLUSION

Based on a representative collection of the species E. coli, RpoS was found to have a very small impact on antibiotic resistance, tolerance, or persistence.

Trade-offs between the instantaneous growth rate and long-term fitness: Consequences for microbial physiology and predictive computational models

Microbial systems biology has made enormous advances in relating microbial physiology to the underlying biochemistry and molecular biology. By meticulously studying model microorganisms, in particular Escherichia coli and Saccharomyces cerevisiae, increasingly comprehensive computational models predict metabolic fluxes, protein expression, and growth. The modeling rationale is that cells are constrained by a limited pool of resources that they allocate optimally to maximize fitness. As a consequence, the expression of particular proteins is at the expense of others, causing trade-offs between cellular objectives such as instantaneous growth, stress tolerance, and capacity to adapt to new environments. While current computational models are remarkably predictive for E. coli and S. cerevisiae when grown in laboratory environments, this may not hold for other growth conditions and other microorganisms. In this contribution, we therefore discuss the relationship between the instantaneous growth rate, limited resources, and long-term fitness. We discuss uses and limitations of current computational models, in particular for rapidly changing and adverse environments, and propose to classify microbial growth strategies based on Grimes's CSR framework.

Intrahost evolution of the gut microbiota

A massive number of microorganisms, belonging to different species, continuously divide inside the guts of animals and humans. The large size of these communities and their rapid division times imply that we should be able to watch microbial evolution in the gut in real time, in a similar manner to what has been done in vitro. Here, we review recent findings on how natural selection shapes intrahost evolution (also known as within-host evolution), with a focus on the intestines of mice and humans. The microbiota of a healthy host is not as static as initially thought from the information measured at only one genomic marker. Rather, the genomes of each gut-colonizing species can be highly dynamic, and such dynamism seems to be related to the microbiota species diversity. Genetic and bioinformatic tools, and analysis of time series data, allow quantification of the selection strength on emerging mutations and horizontal transfer events in gut ecosystems. The drivers and functional consequences of gut evolution can now begin to be grasped. The rules of this intrahost microbiota evolution, and how they depend on the biology of each species, need to be understood for more effective development of microbiota therapies to help maintain or restore host health.

Ecotype formation and prophage domestication during gut bacterial evolution

How much bacterial evolution occurs in our intestines and which factors control it are currently burning questions. The formation of new ecotypes, some of which capable of coexisting for long periods of time, is highly likely in our guts. Horizontal gene transfer driven by temperate phages that can perform lysogeny is also widespread in mammalian intestines. Yet, the roles of mutation and especially lysogeny as key drivers of gut bacterial adaptation remain poorly understood. The mammalian gut contains hundreds of bacterial species, each with many strains and ecotypes, whose abundance varies along the lifetime of a host. A continuous high input of mutations and horizontal gene transfer events mediated by temperate phages drives that diversity. Future experiments to study the interaction between mutations that cause adaptation in microbiomes and lysogenic events with different costs and benefits will be key to understand the dynamic microbiomes of mammals. Also see the video abstract here: https://youtu.be/Zjqsiyb5Pk0.

A Broad Continuum of E. coli Traits in Nature Associated with the Trade-off Between Self-preservation and Nutritional Competence

A trade-off between reproduction and survival is a characteristic of many organisms. In bacteria, growth is constrained when cellular resources are channelled towards environmental stress protection. At the core of this trade-off in Escherichia coli is RpoS, a sigma factor that diverts transcriptional resources towards general stress resistance. The constancy of RpoS levels in natural isolates is unknown. A uniform RpoS content in E. coli would impart a narrow range of resistance properties to the species, whereas a diverse set of RpoS levels in nature should result in a diverse range of stress susceptibilities. We explore the diversity of trade-off settings and phenotypes by measuring the level of RpoS protein in strains of E. coli cohabiting in a natural environment. Strains from a stream polluted with domestic waste were investigated in monthly samples. Analyses included E. coli phylogroup classification, RpoS protein level, RpoS-dependent stress phenotypes and the sequencing of rpoS mutations. The most striking finding was the continuum of RpoS levels, with a 100-fold range of RpoS amounts consistently found in individuals in the stream. Approximately 1.8% of the sampled strains carried null or non-synonymous mutations in rpoS. The natural isolates also exhibited a broad (>100-fold) range of stress resistance responses. Our results are consistent with the view that a multiplicity of survival-multiplication trade-off settings is a feature of the species E. coli. The phenotypic diversity resulting from the trade-off permits bet-hedging and the adaptation of E. coli strains to a very broad range of environments.

Molecular signatures of resource competition: Clonal interference favors ecological diversification and can lead to incipient speciation

Microbial ecosystems harbor an astonishing diversity that can persist for long times. To understand how such diversity is structured and maintained, ecological and evolutionary processes need to be integrated at similar timescales. Here, we study a model of resource competition that allows for evolution via de novo mutation, and focus on rapidly adapting asexual populations with large mutational inputs, as typical of many bacteria species. We characterize the adaptation and diversification of an initially maladapted population and show how the eco-evolutionary dynamics are shaped by the interaction between simultaneously emerging lineages - clonal interference. We find that in large populations, more intense clonal interference can foster diversification under sympatry, increasing the probability that phenotypically and genetically distinct clusters coexist. In smaller populations, the accumulation of deleterious and compensatory mutations can push further the diversification process and kick-start speciation. Our findings have implications beyond microbial populations, providing novel insights about the interplay between ecology and evolution in clonal populations.

Adaptive and nonadaptive plasticity in changing environments: Implications for sexual species with different life history strategies

Populations adapt to novel environmental conditions by genetic changes or phenotypic plasticity. Plastic responses are generally faster and can buffer fitness losses under variable conditions. Plasticity is typically modeled as random noise and linear reaction norms that assume simple one-to-one genotype-phenotype maps and no limits to the phenotypic response. Most studies on plasticity have focused on its effect on population viability. However, it is not clear, whether the advantage of plasticity depends solely on environmental fluctuations or also on the genetic and demographic properties (life histories) of populations. Here we present an individual-based model and study the relative importance of adaptive and nonadaptive plasticity for populations of sexual species with different life histories experiencing directional stochastic climate change. Environmental fluctuations were simulated using differentially autocorrelated climatic stochasticity or noise color, and scenarios of directional climate change. Nonadaptive plasticity was simulated as a random environmental effect on trait development, while adaptive plasticity as a linear, saturating, or sinusoidal reaction norm. The last two imposed limits to the plastic response and emphasized flexible interactions of the genotype with the environment. Interestingly, this assumption led to (a) smaller phenotypic than genotypic variance in the population (many-to-one genotype-phenotype map) and the coexistence of polymorphisms, and (b) the maintenance of higher genetic variation-compared to linear reaction norms and genetic determinism-even when the population was exposed to a constant environment for several generations. Limits to plasticity led to genetic accommodation, when costs were negligible, and to the appearance of cryptic variation when limits were exceeded. We found that adaptive plasticity promoted population persistence under red environmental noise and was particularly important for life histories with low fecundity. Populations producing more offspring could cope with environmental fluctuations solely by genetic changes or random plasticity, unless environmental change was too fast.

Experimental Evolution in Plant-Microbe Systems: A Tool for Deciphering the Functioning and Evolution of Plant-Associated Microbial Communities

In natural environments, microbial communities must constantly adapt to stressful environmental conditions. The genetic and phenotypic mechanisms underlying the adaptive response of microbial communities to new (and often complex) environments can be tackled with a combination of experimental evolution and next generation sequencing. This combination allows to analyse the real-time evolution of microbial populations in response to imposed environmental factors or during the interaction with a host, by screening for phenotypic and genotypic changes over a multitude of identical experimental cycles. Experimental evolution (EE) coupled with comparative genomics has indeed facilitated the monitoring of bacterial genetic evolution and the understanding of adaptive evolution processes. Basically, EE studies had long been done on single strains, allowing to reveal the dynamics and genetic targets of natural selection and to uncover the correlation between genetic and phenotypic adaptive changes. However, species are always evolving in relation with other species and have to adapt not only to the environment itself but also to the biotic environment dynamically shaped by the other species. Nowadays, there is a growing interest to apply EE on microbial communities evolving under natural environments. In this paper, we provide a non-exhaustive review of microbial EE studies done with systems of increasing complexity (from single species, to synthetic communities and natural communities) and with a particular focus on studies between plants and plant-associated microorganisms. We highlight some of the mechanisms controlling the functioning of microbial species and their adaptive responses to environment changes and emphasize the importance of considering bacterial communities and complex environments in EE studies.

The Origin of Niches and Species in the Bacterial World

Niches are spaces for the biological units of selection, from cells to complex communities. In a broad sense, "species" are biological units of individuation. Niches do not exist without individual organisms, and every organism has a niche. We use "niche" in the Hutchinsonian sense as an abstraction of a multidimensional environmental space characterized by a variety of conditions, both biotic and abiotic, whose quantitative ranges determine the positive or negative growth rates of the microbial individual, typically a species, but also parts of the communities of species contained in this space. Microbial organisms ("species") constantly diversify, and such diversification (radiation) depends on the possibility of opening up unexploited or insufficiently exploited niches. Niche exploitation frequently implies "niche construction," as the colonized niche evolves with time, giving rise to new potential subniches, thereby influencing the selection of a series of new variants in the progeny. The evolution of niches and organisms is the result of reciprocal interacting processes that form a single unified process. Centrifugal microbial diversification expands the limits of the species' niches while a centripetal or cohesive process occurs simultaneously, mediated by horizontal gene transfers and recombinatorial events, condensing all of the information recovered during the diversifying specialization into "novel organisms" (possible future species), thereby creating a more complex niche, where the selfishness of the new organism(s) establishes a "homeostatic power" limiting the niche's variation. Once the niche's full carrying capacity has been reached, reproductive isolation occurs, as no foreign organisms can outcompete the established population/community, thereby facilitating speciation. In the case of individualization-speciation of the microbiota, its contribution to the animal' gut structure is a type of "niche construction," the result of crosstalk between the niche (host) and microorganism(s). Lastly, there is a parallelism between the hierarchy of niches and that of microbial individuals. The increasing anthropogenic effects on the biosphere (such as globalization) might reduce the diversity of niches and bacterial individuals, with the potential emergence of highly transmissible multispecialists (which are eventually deleterious) resulting from the homogenization of the microbiosphere, a possibility that should be explored and prevented.

Diversity in E. coli (p)ppGpp Levels and Its Consequences

(p)ppGpp is at the core of global bacterial regulation as it controls growth, the most important aspect of life. It would therefore be expected that at least across a species the intrinsic (basal) levels of (p)ppGpp would be reasonably constant. On the other hand, the historical contingency driven by the selective pressures on bacterial populations vary widely resulting in broad genetic polymorphism. Given that (p)ppGpp controls the expression of many genes including those involved in the bacterial response to environmental challenges, it is not surprising that the intrinsic levels of (p)ppGpp would also vary considerably. In fact, null mutations or less severe genetic polymorphisms in genes associated with (p)ppGpp synthesis and hydrolysis are common. Such variation can be observed in laboratory strains, in natural isolates as well as in evolution experiments. High (p)ppGpp levels result in low growth rate and high tolerance to environmental stresses. Other aspects such as virulence and antimicrobial resistance are also influenced by the intrinsic levels of (p)ppGpp. A case in point is the production of Shiga toxin by certain E. coli strains which is inversely correlated to (p)ppGpp basal level. Conversely, (p)ppGpp concentration is positively correlated to increased tolerance to different antibiotics such as β-lactams, vancomycin, and others. Here we review the variations in intrinsic (p)ppGpp levels and its consequences across the E. coli species.

Modeling microbial metabolic trade-offs in a chemostat

Microbes face intense competition in the natural world, and so need to wisely allocate their resources to multiple functions, in particular to metabolism. Understanding competition among metabolic strategies that are subject to trade-offs is therefore crucial for deeper insight into the competition, cooperation, and community assembly of microorganisms. In this work, we evaluate competing metabolic strategies within an ecological context by considering not only how the environment influences cell growth, but also how microbes shape their chemical environment. Utilizing chemostat-based resource-competition models, we exhibit a set of intuitive and general procedures for assessing metabolic strategies. Using this framework, we are able to relate and unify multiple metabolic models, and to demonstrate how the fitness landscape of strategies becomes intrinsically dynamic due to species-environment feedback. Such dynamic fitness landscapes produce rich behaviors, and prove to be crucial for ecological and evolutionarily stable coexistence in all the models we examined.

Cell population heterogeneity driven by stochastic partition and growth optimality

A fundamental question in biology is how cell populations evolve into different subtypes based on homogeneous processes at the single cell level. Here we show that population bimodality can emerge even when biological processes are homogenous at the cell level and the environment is kept constant. Our model is based on the stochastic partitioning of a cell component with an optimal copy number. We show that the existence of unimodal or bimodal distributions depends on the variance of partition errors and the growth rate tolerance around the optimal copy number. In particular, our theory provides a consistent explanation for the maintenance of aneuploid states in a population. The proposed model can also be relevant for other cell components such as mitochondria and plasmids, whose abundances affect the growth rate and are subject to stochastic partition at cell division.

Temporal scaling of aging as an adaptive strategy of Escherichia coli

Natural selection is thought to shape the evolution of aging patterns, although how life-history trajectories orchestrate the inherently stochastic processes associated with aging is unclear. Tracking clonal growth-arrested Escherichia coli cohorts in an homogeneous environment at single-cell resolution, we demonstrate that the Gompertz law of exponential mortality characterizes bacterial lifespan distributions. By disentangling the rate of aging from age-independent components of longevity, we find that increasing cellular maintenance through the general stress pathway reduces the aging rate and rescales the lifespan distribution at the expense of growth. This trade-off between aging and growth underpins the evolutionary tuning of the general stress response pathway in adaptation to the organism's feast-or-famine lifestyle. It is thus necessary to involve both natural selection and stochastic physiology to explain aging patterns.

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.

Trade-off shapes diversity in eco-evolutionary dynamics

We introduce an Interaction- and Trade-off-based Eco-Evolutionary Model (ITEEM), in which species are competing in a well-mixed system, and their evolution in interaction trait space is subject to a life-history trade-off between replication rate and competitive ability. We demonstrate that the shape of the trade-off has a fundamental impact on eco-evolutionary dynamics, as it imposes four phases of diversity, including a sharp phase transition. Despite its minimalism, ITEEM produces a remarkable range of patterns of eco-evolutionary dynamics that are observed in experimental and natural systems. Most notably we find self-organization towards structured communities with high and sustained diversity, in which competing species form interaction cycles similar to rock-paper-scissors games.

An enormous potential for niche construction through bacterial cross-feeding in a homogeneous environment

Microorganisms modify their environment by excreting by-products of metabolism, which can create new ecological niches that can help microbial populations diversify. A striking example comes from experimental evolution of genetically identical Escherichia coli populations that are grown in a homogeneous environment with the single carbon source glucose. In such experiments, stable communities of genetically diverse cross-feeding E. coli cells readily emerge. Some cells that consume the primary carbon source glucose excrete a secondary carbon source, such as acetate, that sustains other community members. Few such cross-feeding polymorphisms are known experimentally, because they are difficult to screen for. We studied the potential of bacterial metabolism to create new ecological niches based on cross-feeding. To do so, we used genome scale models of the metabolism of E. coli and metabolisms of similar complexity, to identify unique pairs of primary and secondary carbon sources in these metabolisms. We then combined dynamic flux balance analysis with analytical calculations to identify which pair of carbon sources can sustain a polymorphic cross-feeding community. We identified almost 10,000 such pairs of carbon sources, each of them corresponding to a unique ecological niche. Bacterial metabolism shows an immense potential for the construction of new ecological niches through cross feeding.

Biodiversity can emerge in a completely homogeneous environment from populations with initially genetically identical individuals. This striking observation comes from experimental evolution of bacteria, which create new ecological niches when they excrete nutrient-rich waste products that can sustain the life of other bacteria. It is difficult to estimate the potential of any one organism for such metabolic niche construction experimentally, because it is challenging to screen for novel metabolic abilities on a large scale. We therefore used experimentally validated models of bacterial metabolism to predict how many novel niches organisms like Escherichia coli can construct, if a novel niche must be able to sustain a stable community of microbes that differ in the nutrients they consume. We identify thousands of such niches. They differ in their primary carbon source and a secondary carbon source that is excreted by some microbes and used by others. Because we restricted ourselves to chemically simple environments, we may even have underestimated the enormous potential of microbes for niche construction.

Taxon-Function Decoupling as an Adaptive Signature of Lake Microbial Metacommunities Under a Chronic Polymetallic Pollution Gradient

Adaptation of microbial communities to anthropogenic stressors can lead to reductions in microbial diversity and disequilibrium of ecosystem services. Such adaptation can change the molecular signatures of communities with differences in taxonomic and functional composition. Understanding the relationship between taxonomic and functional variation remains a critical issue in microbial ecology. Here, we assessed the taxonomic and functional diversity of a lake metacommunity system along a polymetallic pollution gradient caused by 60 years of chronic exposure to acid mine drainage (AMD). Our results highlight three adaptive signatures. First, a signature of taxon—function decoupling was detected in the microbial communities of moderately and highly polluted lakes. Second, parallel shifts in taxonomic composition occurred between polluted and unpolluted lakes. Third, variation in the abundance of functional modules suggested a gradual deterioration of ecosystem services (i.e., photosynthesis) and secondary metabolism in highly polluted lakes. Overall, changes in the abundance of taxa, function, and more importantly the polymetallic resistance genes such as copA, copB, czcA, cadR, cCusA, were correlated with trace metal content (mainly Cadmium) and acidity. Our findings highlight the impact of polymetallic pollution gradient at the lowest trophic levels.

Adaptation of Escherichia coli to long-term batch culture in various rich media

Experimental evolution studies have characterized the genetic strategies microbes utilize to adapt to their environments, mainly focusing on how microbes adapt to constant and/or defined environments. Using a system that incubates Escherichia coli in different complex media in long-term batch culture, we have focused on how heterogeneity and environment affects adaptive landscapes. In this system, there is no passaging of cells, and therefore genetic diversity is lost only through negative selection, without the experimentally-imposed bottlenecking common in other platforms. In contrast with other experimental evolution systems, because of cycling of nutrients and waste products, this is a heterogeneous environment, where selective pressures change over time, similar to natural environments. We determined that incubation in each environment leads to different adaptations by observing the growth advantage in stationary phase (GASP) phenotype. Re-sequencing whole genomes of populations identified both mutant alleles in a conserved set of genes and differences in evolutionary trajectories between environments. Reconstructing identified mutations in the parental strain background confirmed the adaptive advantage of some alleles, but also identified a surprising number of neutral or even deleterious mutations. This result indicates that complex epistatic interactions may be under positive selection within these heterogeneous environments.

The effect of metabolic stress on genome stability of a synthetic biology chassis Escherichia coli K12 strain

Background

Synthetic organism-based biotechnologies are increasingly being proposed for environmental applications, such as in situ sensing. Typically, the novel function of these organisms is delivered by compiling genetic fragments in the genome of a chassis organism. To behave predictably, these chassis are designed with reduced genomes that minimize biological complexity. However, in these proposed applications it is expected that even when contained within a device, organisms will be exposed to fluctuating, often stressful, conditions and it is not clear whether their genomes will retain stability.

Results

Here we employed a chemostat design which enabled us to maintained two strains of E. coli K12 under sustained starvation stress: first the reduced genome synthetic biology chassis MDS42 and then, the control parent strain MG1655. We estimated mutation rates and utilised them as indicators of an increase in genome instability. We show that within 24 h the spontaneous mutation rate had increased similarly in both strains, destabilizing the genomes. High rates were maintained for the duration of the experiment. Growth rates of a cohort of randomly sampled mutants from both strains were utilized as a proxy for emerging phenotypic, and by association genetic variation. Mutant growth rates were consistently less than rates in non-mutants, an indicator of reduced fitness and the presence of mildly deleterious mutations in both the strains. In addition, the effect of these mutations on the populations as a whole varied by strain.

Conclusions

Overall, this study shows that genome reductions in the MDS42 did not stabilize the chassis under metabolic stress. Over time, this could compromise the effectiveness of synthetic organisms built on chassis in environmental applications.

Electronic supplementary material

The online version of this article (10.1186/s12934-018-0858-2) contains supplementary material, which is available to authorized users.

The emergence of metabolic heterogeneity and diverse growth responses in isogenic bacterial cells

Microorganisms adapt to frequent environmental changes through population diversification. Previous studies demonstrated phenotypic diversity in a clonal population and its important effects on microbial ecology. However, the dynamic changes of phenotypic composition have rarely been characterized. Also, cellular variations and environmental factors responsible for phenotypic diversity remain poorly understood. Here, we studied phenotypic diversity driven by metabolic heterogeneity. We characterized metabolic activities and growth kinetics of starved Escherichia coli cells subject to nutrient upshift at single-cell resolution. We observed three subpopulations with distinct metabolic activities and growth phenotypes. One subpopulation was metabolically active and immediately grew upon nutrient upshift. One subpopulation was metabolically inactive and non-viable. The other subpopulation was metabolically partially active, and did not grow upon nutrient upshift. The ratio of these subpopulations changed dynamically during starvation. A long-term observation of cells with partial metabolic activities indicated that their metabolism was later spontaneously restored, leading to growth recovery. Further investigations showed that oxidative stress can induce the emergence of a subpopulation with partial metabolic activities. Our findings reveal the emergence of metabolic heterogeneity and associated dynamic changes in phenotypic composition. In addition, the results shed new light on microbial dormancy, which has important implications in microbial ecology and biomedicine.

The fitness costs and benefits of antibiotic resistance in drug-free microenvironments encountered in the human body

The relationship between bacterial drug resistance and growth fitness is a contentious topic, but some antibiotic resistance mutations clearly have a fitness cost in the laboratory. Whether these costs translate into deleterious effects in natural habitats is less certain however. Previously, fitness effects of resistance mutations were mostly characterized in nutrient-rich, fast-growth conditions, which bacteria rarely encounter in natural habitats. Carbon, phosphate, iron or oxygen limitations are conditions met by bacterial pathogens in various compartments of the human body. Here, we measured the fitness of four different rpoB mutations commonly found in rifampicin-resistant bacterial isolates. The fitness properties and the emergence of these and other alleles were studied in Escherichia coli populations growing under nutrient excess and in four different nutrient-limited states. Consistent with previous findings, all four mutations exhibited deleterious fitness effects under nutrient-rich conditions. In stark contrast, we found positive or neutral fitness effects under nutrient-limited conditions. Two particular rpoB alleles had a remarkable fitness increase under phosphate limitation and these alleles arose to high frequencies specifically under phosphate limitation. These findings suggest that it is not meaningful to draw general conclusions on fitness costs without considering bacterial microenvironments in humans and other animals.

Evolutionary implications of Liebig's law of the minimum: Selection under low concentrations of two nonsubstitutable nutrients

Interactions between different axes of an organism's niche determine the evolutionary trajectory of a population. An extreme case of these interactions is predicted from ecological theory in Liebig's law of the minimum. This law states that in environments where multiple nutrients are in relatively low concentrations, only one nutrient will affect the growth of the organism. This implies that the evolutionary response of the population would be dictated by the most growth-limiting nutrient. Alternatively, it is possible that an initial adaptation to the most limiting nutrient results in other nutrients present in low concentration affecting the evolutionary dynamics of the population. To test these hypotheses, we conducted twelve evolution experiments in chemostats using Escherichia coli populations: four under nitrogen limitation, four under magnesium limitation, and four in which both nitrogen and magnesium are in low concentrations. In the last environment, only magnesium seems to limit growth (Low Nitrogen Magnesium Limited environment, LNML). We observe a decrease in nitrogen concentration in the LNML environment over the course of our evolution experiment indicating that nitrogen might become limiting in these environments. Genetic reconstruction results show that clones adapted to magnesium limitation have genes involved in nitrogen starvation, that is, glnG (nitrogen starvation transcriptional regulator) and amtB (transport protein) to be upregulated only in the LNML environment as compared to magnesium-limiting environments. Together, our results highlights that in low-nutrient environments, adaptation to the growth-limiting nutrient results in other nutrients at low concentrations to play a role in the evolutionary dynamics of the population.

Inactivation of Transcriptional Regulators during Within-Household Evolution of Escherichia coli

We analyzed the within-household evolution of two household-associated Escherichia coli strains from pandemic clonal group ST131-H30, using isolates recovered from five individuals within two families, each of which had a distinct strain. Family 1's strain was represented by a urine isolate from the index patient (older sister) with recurrent cystitis and a blood isolate from her younger sister with fatal urosepsis. Family 2's strain was represented by a urine isolate from the index patient (father) with pyelonephritis and renal abscesses, blood and kidney drainage isolates from the daughter with emphysematous pyelonephritis, and urine and fecal isolates from the mother with cystitis. Collectively, the several variants of each family's strain had accumulated a total of 8 (family 1) and 39 (family 2) point mutations; no two isolates were identical. Of the 47 total mutations, 36 resulted in amino acid changes or truncation of coded proteins. Fourteen such mutations (39%) targeted genes encoding transcriptional regulators, and 9 (25%) involved DNA-binding transcription factors (TFs), which significantly exceeded the relative contribution of TF genes to the isolates' genomes (∼6%). At least one-half of the transcriptional regulator mutations were inactivating, based on phenotypic and/or transcriptional analysis. In particular, inactivating mutations in the global regulator LrhA (repressor of type 1 fimbriae and flagella) occurred in the blood isolates from both households and increased the virulence of E. coli strains in a murine sepsis model. The results indicate that E. coli undergoes adaptive evolution between and/or within hosts, generating subpopulations with distinctive phenotypes and virulence potential.IMPORTANCE The clonal evolution of bacterial strains associated with interhost transmission is poorly understood. We characterized the genome sequences of clonal descendants of two Escherichia coli strains, recovered at different time points from multiple individuals within two households who had different types of urinary tract infection. We found evidence that the E. coli strains underwent extensive mutational diversification between and within these individuals, driven disproportionately by inactivation of transcriptional regulators. In urosepsis isolates, the mutations observed in the global regulator LrhA increased bacterial virulence in a murine sepsis model. Our findings help in understanding the adaptive dynamics and strategies of E. coli during short-term natural evolution.

A shifting mutational landscape in 6 nutritional states: Stress-induced mutagenesis as a series of distinct stress input-mutation output relationships

Environmental stresses increase genetic variation in bacteria, plants, and human cancer cells. The linkage between various environments and mutational outcomes has not been systematically investigated, however. Here, we established the influence of nutritional stresses commonly found in the biosphere (carbon, phosphate, nitrogen, oxygen, or iron limitation) on both the rate and spectrum of mutations in Escherichia coli. We found that each limitation was associated with a remarkably distinct mutational profile. Overall mutation rates were not always elevated, and nitrogen, iron, and oxygen limitation resulted in major spectral changes but no net increase in rate. Our results thus suggest that stress-induced mutagenesis is a diverse series of stress input-mutation output linkages that is distinct in every condition. Environment-specific spectra resulted in the differential emergence of traits needing particular mutations in these settings. Mutations requiring transpositions were highest under iron and oxygen limitation, whereas base-pair substitutions and indels were highest under phosphate limitation. The unexpected diversity of input-output effects explains some important phenomena in the mutational biases of evolving genomes. The prevalence of bacterial insertion sequence transpositions in the mammalian gut or in anaerobically stored cultures is due to environmentally determined mutation availability. Likewise, the much-discussed genomic bias towards transition base substitutions in evolving genomes can now be explained as an environment-specific output. Altogether, our conclusion is that environments influence genetic variation as well as selection.

Emergence of microbial diversity due to cross-feeding interactions in a spatial model of gut microbial metabolism

Background

The human gut contains approximately 10¹⁴ bacteria, belonging to hundreds of different species. Together, these microbial species form a complex food web that can break down nutrient sources that our own digestive enzymes cannot handle, including complex polysaccharides, producing short chain fatty acids and additional metabolites, e.g., vitamin K. Microbial diversity is important for colonic health: Changes in the composition of the microbiota have been associated with inflammatory bowel disease, diabetes, obesity and Crohn’s disease, and make the microbiota more vulnerable to infestation by harmful species, e.g., Clostridium difficile. To get a grip on the controlling factors of microbial diversity in the gut, we here propose a multi-scale, spatiotemporal dynamic flux-balance analysis model to study the emergence of metabolic diversity in a spatial gut-like, tubular environment. The model features genome-scale metabolic models (GEM) of microbial populations, resource sharing via extracellular metabolites, and spatial population dynamics and evolution.

Results

In this model, cross-feeding interactions emerge readily, despite the species’ ability to metabolize sugars autonomously. Interestingly, the community requires cross-feeding for producing a realistic set of short-chain fatty acids from an input of glucose, If we let the composition of the microbial subpopulations change during invasion of adjacent space, a complex and stratified microbiota evolves, with subspecies specializing on cross-feeding interactions via a mechanism of compensated trait loss. The microbial diversity and stratification collapse if the flux through the gut is enhanced to mimic diarrhea.

Conclusions

In conclusion, this in silico model is a helpful tool in systems biology to predict and explain the controlling factors of microbial diversity in the gut. It can be extended to include, e.g., complex nutrient sources, and host-microbiota interactions via the intestinal wall.

Electronic supplementary material

The online version of this article (doi:10.1186/s12918-017-0430-4) contains supplementary material, which is available to authorized users.

Stability of Cross-Feeding Polymorphisms in Microbial Communities

Cross-feeding, a relationship wherein one organism consumes metabolites excreted by another, is a ubiquitous feature of natural and clinically-relevant microbial communities and could be a key factor promoting diversity in extreme and/or nutrient-poor environments. However, it remains unclear how readily cross-feeding interactions form, and therefore our ability to predict their emergence is limited. In this paper we developed a mathematical model parameterized using data from the biochemistry and ecology of an E. coli cross-feeding laboratory system. The model accurately captures short-term dynamics of the two competitors that have been observed empirically and we use it to systematically explore the stability of cross-feeding interactions for a range of environmental conditions. We find that our simple system can display complex dynamics including multi-stable behavior separated by a critical point. Therefore whether cross-feeding interactions form depends on the complex interplay between density and frequency of the competitors as well as on the concentration of resources in the environment. Moreover, we find that subtly different environmental conditions can lead to dramatically different results regarding the establishment of cross-feeding, which could explain the apparently unpredictable between-population differences in experimental outcomes. We argue that mathematical models are essential tools for disentangling the complexities of cross-feeding interactions.

Population Phylogenomics of Extraintestinal Pathogenic Escherichia coli

The emergence of genomics over the last 10 years has provided new insights into the evolution and virulence of extraintestinal Escherichia coli. By combining population genetics and phylogenetic approaches to analyze whole-genome sequences, it became possible to link genomic features to specific phenotypes, such as the ability to cause urinary tract infections. An E. coli chromosome can vary extensively in length, ranging from 4.3 to 6.2 Mb, encoding 4,084 to 6,453 proteins. This huge diversity is structured as a set of less than 2,000 genes (core genome) that are conserved between all the strains and a set of variable genes. Based on the core genome, the history of the species can be reliably reconstructed, revealing the recent emergence of phylogenetic groups A and B1 and the more ancient groups B2, F, and D. Urovirulence is most often observed in B2/F/D group strains and is a multigenic process involving numerous combinations of genes and specific alleles with epistatic interactions, all leading down multiple evolutionary paths. The genes involved mainly code for adhesins, toxins, iron capture systems, and protectins, as well as metabolic pathways and mutation-rate-control systems. However, the barrier between commensal and uropathogenic E. coli strains is difficult to draw as the factors that are responsible for virulence have probably also been selected to allow survival of E. coli as a commensal in the intestinal tract. Genomic studies have also demonstrated that infections are not the result of a unique and stable isolate, but rather often involve several isolates with variable levels of diversity that dynamically changes over time.

Quantitative high-throughput population dynamics in continuous-culture by automated microscopy

We present a high-throughput method to measure abundance dynamics in microbial communities sustained in continuous-culture. Our method uses custom epi-fluorescence microscopes to automatically image single cells drawn from a continuously-cultured population while precisely controlling culture conditions. For clonal populations of Escherichia coli our instrument reveals history-dependent resilience and growth rate dependent aggregation.

Competition and fixation of cohorts of adaptive mutations under Fisher geometrical model

One of the simplest models of adaptation to a new environment is Fisher’s Geometric Model (FGM), in which populations move on a multidimensional landscape defined by the traits under selection. The predictions of this model have been found to be consistent with current observations of patterns of fitness increase in experimentally evolved populations. Recent studies investigated the dynamics of allele frequency change along adaptation of microbes to simple laboratory conditions and unveiled a dramatic pattern of competition between cohorts of mutations, i.e., multiple mutations simultaneously segregating and ultimately reaching fixation. Here, using simulations, we study the dynamics of phenotypic and genetic change as asexual populations under clonal interference climb a Fisherian landscape, and ask about the conditions under which FGM can display the simultaneous increase and fixation of multiple mutations—mutation cohorts—along the adaptive walk. We find that FGM under clonal interference, and with varying levels of pleiotropy, can reproduce the experimentally observed competition between different cohorts of mutations, some of which have a high probability of fixation along the adaptive walk. Overall, our results show that the surprising dynamics of mutation cohorts recently observed during experimental adaptation of microbial populations can be expected under one of the oldest and simplest theoretical models of adaptation—FGM.

Characterization of acetic acid-detoxifying Escherichia coli evolved under phosphate starvation conditions

BACKGROUND

During prolonged incubation of Escherichia coli K-12 in batch culture under aerobic, phosphate (Pi) starvation conditions, excess glucose is converted into acetic acid, which may trigger cell death. Following serial cultures, we isolated five evolved strains in two populations that survived prolonged incubation.

METHODS

We sequenced the genomes of the ancestral and evolved strains, and determined the effects of the genetic changes, tested alone and in combination, on characteristic phenotypes in pure and in mixed cultures.

RESULTS

Evolved strains used two main strategies: (1) the constitutive expression of the Trk- and Kdp-dependent K(+) transport systems, and (2) the inactivation of the ArcA global regulator. Both processes helped to maintain a residual activity of the tricarboxylic acid cycle, which decreased the production of acetic acid and eventually allowed its re-consumption. Evolved strains acquired a few additional genetic changes besides the trkH, kdpD and arcA mutations, which might increase the scavenging of organophosphates (phnE (+), lapB, and rseP) and the resistance to oxidative (rsxC) and acetic acid stresses (e14(-)/icd (+)).

CONCLUSIONS

Evolved strains rapidly acquired mutations (phnE (+) lapB rpoS trkH and phnE (+) rseP kdpD) that were globally beneficial to growth on glucose and organophosphates, but detrimental to long-term viability. The spread of these mutant strains might give the ancestral strain time to accumulate up to five genetic changes (phnE (+) arcA rsxC crfC e14(-)/icd (+)), which allowed growth on glucose and organophosphates, and provided a long-term survival. The latter strain, which expressed several mechanisms of protection against endogenous and exogenous stresses, might provide a platform for producing toxic recombinant proteins and chemicals during prolonged incubation under aerobic, Pi starvation conditions.

Trade-Offs of Escherichia coli Adaptation to an Intracellular Lifestyle in Macrophages

The bacterium Escherichia coli exhibits remarkable genomic and phenotypic variation, with some pathogenic strains having evolved to survive and even replicate in the harsh intra-macrophage environment. The rate and effects of mutations that can cause pathoadaptation are key determinants of the pace at which E. coli can colonize such niches and become pathogenic. We used experimental evolution to determine the speed and evolutionary paths undertaken by a commensal strain of E. coli when adapting to intracellular life. We estimated the acquisition of pathoadaptive mutations at a rate of 10⁻⁶ per genome per generation, resulting in the fixation of more virulent strains in less than a hundred generations. Whole genome sequencing of independently evolved clones showed that the main targets of intracellular adaptation involved loss of function mutations in genes implicated in the assembly of the lipopolysaccharide core, iron metabolism and di- and tri-peptide transport, namely rfaI, fhuA and tppB, respectively. We found a substantial amount of antagonistic pleiotropy in evolved populations, as well as metabolic trade-offs, commonly found in intracellular bacteria with reduced genome sizes. Overall, the low levels of clonal interference detected indicate that the first steps of the transition of a commensal E. coli into intracellular pathogens are dominated by a few pathoadaptive mutations with very strong effects.

Parallelism in adaptive radiations of experimental Escherichia coli populations

Adaptive radiations are major contributors to species diversity. Although the underlying mechanisms of adaptive radiations, specialization and trade-offs, are relatively well understood, the tempo and repeatability of adaptive radiations remain elusive. Ecological specialization can occur through the expansion into novel niches or through partitioning of an existing niche. To test how the mode of resource specialization affects the tempo and repeatability of adaptive radiations, we selected replicate bacterial populations in environments that promoted the evolution of diversity either through niche expansion or through niche partitioning, and in a third low-quality single-resource environment, in which diversity was not expected to evolve. Colony size diversity evolved equally fast in environments that provided ecological opportunities regardless of the mode of resource specialization. In the low-quality environments, diversity did not consistently evolve. We observed the largest fitness improvement in the low-quality environment and the smallest the glucose-limited environment. We did not observe a change in the rate of evolutionary change in either trait or environment, suggesting that the pool of beneficial mutations was not exhausted. Overall, the mode of resource specialization did not affect the tempo or repeatability of adaptive radiations. These results demonstrate the limitations of eco-evolutionary feedbacks to affect evolutionary outcomes.

Applying the emergency risk management process to tackle the crisis of antibiotic resistance

We advocate that antibiotic resistance be reframed as a disaster risk management problem. Antibiotic-resistant infections represent a risk to life as significant as other commonly occurring natural disasters (e.g., earthquakes). Despite efforts by global health authorities, antibiotic resistance continues to escalate. Therefore, new approaches and expertise are needed to manage the issue. In this perspective we: (1) make a call for the emergency management community to recognize the antibiotic resistance risk and join in addressing this problem; (2) suggest using the risk management process to help tackle antibiotic resistance; (3) show why this approach has value and why it is different to existing approaches; and (4) identify public perception of antibiotic resistance as an important issue that warrants exploration.

Metabolism at evolutionary optimal States

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

Horizontal gene transfer, dispersal and haloarchaeal speciation

The Halobacteria are a well-studied archaeal class and numerous investigations are showing how their diversity is distributed amongst genomes and geographic locations. Evidence indicates that recombination between species continuously facilitates the arrival of new genes, and within species, it is frequent enough to spread acquired genes amongst all individuals in the population. To create permanent independent diversity and generate new species, barriers to recombination are probably required. The data support an interpretation that rates of evolution (e.g., horizontal gene transfer and mutation) are faster at creating geographically localized variation than dispersal and invasion are at homogenizing genetic differences between locations. Therefore, we suggest that recurrent episodes of dispersal followed by variable periods of endemism break the homogenizing forces of intrapopulation recombination and that this process might be the principal stimulus leading to divergence and speciation in Halobacteria.

Survival kinetics of starving bacteria is biphasic and density-dependent

In the lifecycle of microorganisms, prolonged starvation is prevalent and sustaining life during starvation periods is a vital task. In the literature, it is commonly assumed that survival kinetics of starving microbes follows exponential decay. This assumption, however, has not been rigorously tested. Currently, it is not clear under what circumstances this assumption is true. Also, it is not known when such survival kinetics deviates from exponential decay and if it deviates, what underlying mechanisms for the deviation are. Here, to address these issues, we quantitatively characterized dynamics of survival and death of starving E. coli cells. The results show that the assumption--starving cells die exponentially--is true only at high cell density. At low density, starving cells persevere for extended periods of time, before dying rapidly exponentially. Detailed analyses show intriguing quantitative characteristics of the density-dependent and biphasic survival kinetics, including that the period of the perseverance is inversely proportional to cell density. These characteristics further lead us to identification of key underlying processes relevant for the perseverance of starving cells. Then, using mathematical modeling, we show how these processes contribute to the density-dependent and biphasic survival kinetics observed. Importantly, our model reveals a thrifty strategy employed by bacteria, by which upon sensing impending depletion of a substrate, the limiting substrate is conserved and utilized later during starvation to delay cell death. These findings advance quantitative understanding of survival of microbes in oligotrophic environments and facilitate quantitative analysis and prediction of microbial dynamics in nature. Furthermore, they prompt revision of previous models used to analyze and predict population dynamics of microbes.

Simple phenotypic sweeps hide complex genetic changes in populations

Changes in allele frequencies and the fixation of beneficial mutations are central to evolution. The precise relationship between mutational and phenotypic sweeps is poorly described however, especially when multiple alleles are involved. Here, we investigate these relationships in a bacterial population over 60 days in a glucose-limited chemostat in a large population. High coverage metagenomic analysis revealed a disconnection between smooth phenotypic sweeps and the complexity of genetic changes in the population. Phenotypic adaptation was due to convergent evolution and involved soft sweeps by 7–26 highly represented alleles of several genes in different combinations. Allele combinations spread from undetectably low baselines, indicating that minor subpopulations provide the basis of most innovations. A hard sweep was also observed, involving a single combination of rpoS, mglD, malE, sdhC, and malT mutations sweeping to greater than 95% of the population. Other mutant genes persisted but at lower abundance, including hfq, consistent with its demonstrated frequency-dependent fitness under glucose limitation. Other persistent, newly identified low-frequency mutations were in the aceF, galF, ribD and asm genes, in noncoding regulatory regions, three large indels and a tandem duplication; these were less affected by fluctuations involving more dominant mutations indicating separate evolutionary paths. Our results indicate a dynamic subpopulation structure with a minimum of 42 detectable mutations maintained over 60 days. We also conclude that the massive population-level mutation supply in combination with clonal interference leads to the soft sweeps observed, but not to the exclusion of an occasional hard sweep.

Mutations in global regulators lead to metabolic selection during adaptation to complex environments

Adaptation to ecologically complex environments can provide insights into the evolutionary dynamics and functional constraints encountered by organisms during natural selection. Adaptation to a new environment with abundant and varied resources can be difficult to achieve by small incremental changes if many mutations are required to achieve even modest gains in fitness. Since changing complex environments are quite common in nature, we investigated how such an epistatic bottleneck can be avoided to allow rapid adaptation. We show that adaptive mutations arise repeatedly in independently evolved populations in the context of greatly increased genetic and phenotypic diversity. We go on to show that weak selection requiring substantial metabolic reprogramming can be readily achieved by mutations in the global response regulator arcA and the stress response regulator rpoS. We identified 46 unique single-nucleotide variants of arcA and 18 mutations in rpoS, nine of which resulted in stop codons or large deletions, suggesting that subtle modulations of ArcA function and knockouts of rpoS are largely responsible for the metabolic shifts leading to adaptation. These mutations allow a higher order metabolic selection that eliminates epistatic bottlenecks, which could occur when many changes would be required. Proteomic and carbohydrate analysis of adapting E. coli populations revealed an up-regulation of enzymes associated with the TCA cycle and amino acid metabolism, and an increase in the secretion of putrescine. The overall effect of adaptation across populations is to redirect and efficiently utilize uptake and catabolism of abundant amino acids. Concomitantly, there is a pronounced spread of more ecologically limited strains that results from specialization through metabolic erosion. Remarkably, the global regulators arcA and rpoS can provide a “one-step” mechanism of adaptation to a novel environment, which highlights the importance of global resource management as a powerful strategy to adaptation.

Changing environmental conditions are the norm in biology. However, understanding adaptation to complex environments presents many challenges. For example, adaptation to resource-rich environments can potentially have many successful evolutionary trajectories to increased fitness. Even in conditions of plenty, the utilization of numerous but novel resources can require multiple mutations before a benefit is accrued. We evolved two bacterial species isolated from the gut of healthy humans in two different, resource-rich media commonly used in the laboratory. We anticipated that under weak selection the population would evolve tremendous genetic diversity. Despite such a complex genetic background we were able to identify a strong degree of parallel evolution and using a combination of population proteomic and population genomic approaches we show that two global regulators, arcA and rpoS, are the principle targets of selection. Up-regulation of the different metabolic pathways that are controlled by these global regulators in combination with up-regulation of transporters that transport nutrients into the cell revealed increased use of the novel resources. Thus global regulators can provide a one-step model to shift metabolism efficiently and provide rapid a one-step reprogramming of the cell metabolic profile.

The functional basis of adaptive evolution in chemostats

Two of the central problems in biology are determining the molecular basis of adaptive evolution and understanding how cells regulate their growth. The chemostat is a device for culturing cells that provides great utility in tackling both of these problems: it enables precise control of the selective pressure under which organisms evolve and it facilitates experimental control of cell growth rate. The aim of this review is to synthesize results from studies of the functional basis of adaptive evolution in long-term chemostat selections using Escherichia coli and Saccharomyces cerevisiae. We describe the principle of the chemostat, provide a summary of studies of experimental evolution in chemostats, and use these studies to assess our current understanding of selection in the chemostat. Functional studies of adaptive evolution in chemostats provide a unique means of interrogating the genetic networks that control cell growth, which complements functional genomic approaches and quantitative trait loci (QTL) mapping in natural populations. An integrated approach to the study of adaptive evolution that accounts for both molecular function and evolutionary processes is critical to advancing our understanding of evolution. By renewing efforts to integrate these two research programs, experimental evolution in chemostats is ideally suited to extending the functional synthesis to the study of genetic networks.

The enduring utility of continuous culturing in experimental evolution

Studying evolution in the laboratory provides a means of understanding the processes, dynamics and outcomes of adaptive evolution in precisely controlled and readily replicated conditions. The advantages of experimental evolution are maximized when the selection is well defined, which enables linking genotype, phenotype and fitness. One means of maintaining a defined selection is continuous culturing: chemostats enable the study of adaptive evolution in constant nutrient-limited environments, whereas cells in turbidostats evolve in constant nutrient abundance. Although the experimental effort required for continuous culturing is considerable relative to the experimental simplicity of serial batch culture, the opposite is true of the environments they produce: continuous culturing results in simplified and invariant conditions whereas serially diluted batch cultures are complex and dynamic. The comparative simplicity of the selective environment that is unique to continuous culturing provides an ideal experimental system for addressing key questions in adaptive evolution.

Cancer: evolution within a lifetime

Subclonal cancer populations change spatially and temporally during the disease course. Studies are revealing branched evolutionary cancer growth with low-frequency driver events present in subpopulations of cells, providing escape mechanisms for targeted therapeutic approaches. Despite such complexity, evidence is emerging for parallel evolution of subclones, mediated through distinct somatic events converging on the same gene, signal transduction pathway, or protein complex in different subclones within the same tumor. Tumors may follow gradualist paths (microevolution) as well as major shifts in evolutionary trajectories (macroevolution). Although macroevolution has been subject to considerable controversy in post-Darwinian evolutionary theory, we review evidence that such nongradual, saltatory leaps, driven through chromosomal rearrangements or genome doubling, may be particularly relevant to tumor evolution. Adapting cancer care to the challenges imposed by tumor micro- and macroevolution and developing deeper insight into parallel evolutionary events may prove central to improving outcome and reducing drug development costs.

The rpoS gene is predominantly inactivated during laboratory storage and undergoes source-sink evolution in Escherichia coli species

The rpoS gene codes for an alternative RNA polymerase sigma factor, which acts as a general regulator of the stress response. Inactivating alleles of rpoS in collections of natural Escherichia coli isolates have been observed at very variable frequencies, from less than 1% to more than 70% of strains. rpoS is easily inactivated in nutrient-deprived environments such as stab storage, which makes it difficult to determine the true frequency of rpoS inactivation in nature. We studied the evolutionary history of rpoS and compared it to the phylogenetic history of bacteria in two collections of 82 human commensal and extraintestinal E. coli strains. These strains were representative of the phylogenetic diversity of the species and differed only by their storage conditions. In both collections, the phylogenetic histories of rpoS and of the strains were congruent, indicating that horizontal gene transfer had not occurred at the rpoS locus, and rpoS was under strong purifying selection, with a ratio of the nonsynonymous mutation rate (Ka) to the synonymous substitution rate (Ks) substantially smaller than 1. Stab storage was associated with a high frequency of inactivating alleles, whereas almost no amino acid sequence variation was observed in RpoS in the collection studied directly after isolation of the strains from the host. Furthermore, the accumulation of variations in rpoS was typical of source-sink dynamics. In conclusion, rpoS is rarely inactivated in natural E. coli isolates within their mammalian hosts, probably because such strains rapidly become evolutionary dead ends. Our data should encourage bacteriologists to freeze isolates immediately and to avoid the use of stab storage.