Experimental evolution with E. coli in diverse resource environments. I. Fluctuating environments promote divergence of replicate populations

Pathogen contingency loci and the evolution of host specificity: Simple sequence repeats mediate Bartonella adaptation to a wild rodent host

Parasites, including pathogens, can adapt to better exploit their hosts on many scales, ranging from within an infection of a single individual to series of infections spanning multiple host species. However, little is known about how the genomes of parasites in natural communities evolve when they face diverse hosts. We investigated how Bartonella bacteria that circulate in rodent communities in the dunes of the Negev Desert in Israel adapt to different species of rodent hosts. We propagated 15 Bartonella populations through infections of either a single host species (Gerbillus andersoni or Gerbillus pyramidum) or alternating between the two. After 20 rodent passages, strains with de novo mutations replaced the ancestor in most populations. Mutations in two mononucleotide simple sequence repeats (SSRs) that caused frameshifts in the same adhesin gene dominated the evolutionary dynamics. They appeared exclusively in populations that encountered G. andersoni and altered the dynamics of infections of this host. Similar SSRs in other genes are conserved and exhibit ON/OFF variation in Bartonella isolates from the Negev Desert dunes. Our results suggest that SSR-based contingency loci could be important not only for rapidly and reversibly generating antigenic variation to escape immune responses but that they may also mediate the evolution of host specificity.

Environmental memory alters the fitness effects of adaptive mutations in fluctuating environments

Evolution in a static laboratory environment often proceeds via large-effect beneficial mutations that may become maladaptive in other environments. Conversely, natural settings require populations to endure environmental fluctuations. A sensible assumption is that the fitness of a lineage in a fluctuating environment is the time average of its fitness over the sequence of static conditions it encounters. However, transitions between conditions may pose entirely new challenges, which could cause deviations from this time average. To test this, we tracked hundreds of thousands of barcoded yeast lineages evolving in static and fluctuating conditions and subsequently isolated 900 mutants for pooled fitness assays in 15 environments. Here we find that fitness in fluctuating environments indeed often deviates from the time average, leading to fitness non-additivity. Moreover, closer examination reveals that fitness in one component of a fluctuating environment is often strongly influenced by the previous component. We show that this environmental memory is especially common for mutants with high variance in fitness across tested environments. We use a simple mathematical model and whole-genome sequencing to propose mechanisms underlying this effect, including lag time evolution and sensing mutations. Our results show that environmental fluctuations impact fitness and suggest that variance in static environments can explain these impacts.

Escherichia coli adaptation under prolonged resource exhaustion is characterized by extreme parallelism and frequent historical contingency

Like many other non-sporulating bacterial species, Escherichia coli is able to survive prolonged periods of resource exhaustion, by entering a state of growth called long-term stationary phase (LTSP). In July 2015, we initiated a set of evolutionary experiments aimed at characterizing the dynamics of E. coli adaptation under LTSP. In these experiments populations of E. coli were allowed to initially grow on fresh rich media, but were not provided with any new external growth resources since their establishment. Utilizing whole genome sequencing data obtained for hundreds of clones sampled at 12 time points spanning the first six years of these experiments, we reveal several novel aspects of the dynamics of adaptation. First, we show that E. coli continuously adapts genetically, up to six years under resource exhaustion, through the highly convergent accumulation of mutations. We further show that upon entry into LTSP, long-lasting lineages are established. This lineage structure is in itself convergent, with similar lineages arising across independently evolving populations. The high parallelism with which adaptations occur under LTSP, combined with the LTSP populations' lineage structure, enable us to screen for pairs of loci displaying a significant association in the occurrence of mutations, suggestive of a historical contingency. We find that such associations are highly frequent and that a third of convergently mutated loci are involved in at least one such association. Combined our results demonstrate that LTSP adaptation is characterized by remarkably high parallelism and frequent historical contingency.

Rediversification following ecotype isolation reveals hidden adaptive potential

Microbial communities play a critical role in ecological processes, and their diversity is key to their functioning. However, little is known about whether communities can regenerate ecological diversity following ecotype removal or extinction and how the rediversified communities would compare to the original ones. Here, we show that simple two-ecotype communities from the E. coli long-term evolution experiment (LTEE) consistently rediversified into two ecotypes following the isolation of one of the ecotypes, coexisting via negative frequency-dependent selection. Communities separated by more than 30,000 generations of evolutionary time rediversify in similar ways. The rediversified ecotype appears to share a number of growth traits with the ecotype it replaces. However, the rediversified community is also different from the original community in ways relevant to the mechanism of ecotype coexistence-for example, in stationary phase response and survival. We found substantial variation in the transcriptional states between the two original ecotypes, whereas the differences within the rediversified community were comparatively smaller, although the rediversified community showed unique patterns of differential expression. Our results suggest that evolution may leave room for alternative diversification processes even in a maximally reduced community of only two strains. We hypothesize that the presence of alternative evolutionary pathways may be even more pronounced in communities of many species where there are even more potential niches, highlighting an important role for perturbations, such as species removal, in evolving ecological communities.

Effective fitness under fluctuating selection with genetic drift

The natural environment fluctuates for virtually every population of organisms. As a result, the fitness of a mutant may vary temporally. While commonly used for summarizing the effect of fluctuating selection on the mutant, geometric mean fitness can be misleading under some circumstances due to the influence of genetic drift. Here, we show by mathematical proof and computer simulation that, with genetic drift, the geometric mean fitness does not accurately reflect the overall effect of fluctuating selection. We propose an alternative measure based on the average expected allele frequency change caused by selection and demonstrate that this measure-effective fitness-better captures the overall effect of fluctuating selection in the presence of drift.

Mutational hotspots lead to robust but suboptimal adaptive outcomes in certain environments

The observed mutational spectrum of adaptive outcomes can be constrained by many factors. For example, mutational biases can narrow the observed spectrum by increasing the rate of mutation at isolated sites in the genome. In contrast, complex environments can shift the observed spectrum by defining fitness consequences of mutational routes. We investigate the impact of different nutrient environments on the evolution of motility in Pseudomonas fluorescens Pf0-2x (an engineered non-motile derivative of Pf0-1) in the presence and absence of a strong mutational hotspot. Previous work has shown that this mutational hotspot can be built and broken via six silent mutations, which provide rapid access to a mutation that rescues swimming motility and confers the strongest swimming phenotype in specific environments. Here, we evolved a hotspot and non-hotspot variant strain of Pf0-2x for motility under nutrient-rich (LB) and nutrient-limiting (M9) environmental conditions. We observed the hotspot strain consistently evolved faster across all environmental conditions and its mutational spectrum was robust to environmental differences. However, the non-hotspot strain had a distinct mutational spectrum that changed depending on the nutrient environment. Interestingly, while alternative adaptive mutations in nutrient-rich environments were equal to, or less effective than, the hotspot mutation, the majority of these mutations in nutrient-limited conditions produced superior swimmers. Our competition experiments mirrored these findings, underscoring the role of environment in defining both the mutational spectrum and the associated phenotype strength. This indicates that while mutational hotspots working in concert with natural selection can speed up access to robust adaptive mutations (which can provide a competitive advantage in evolving populations), they can limit exploration of the mutational landscape, restricting access to potentially stronger phenotypes in specific environments.

Strong environmental memory revealed by experimental evolution in static and fluctuating environments

Evolution in a static environment, such as a laboratory setting with constant and uniform conditions, often proceeds via large-effect beneficial mutations that may become maladaptive in other environments. Conversely, natural settings require populations to endure environmental fluctuations. A sensible assumption is that the fitness of a lineage in a fluctuating environment is the time-average of its fitness over the sequence of static conditions it encounters. However, transitions between conditions may pose entirely new challenges, which could cause deviations from this time-average. To test this, we tracked hundreds of thousands of barcoded yeast lineages evolving in static and fluctuating conditions and subsequently isolated 900 mutants for pooled fitness assays in 15 environments. We find that fitness in fluctuating environments indeed often deviates from the expectation based on static components, leading to fitness non-additivity. Moreover, closer examination reveals that fitness in one component of a fluctuating environment is often strongly influenced by the previous component. We show that this environmental memory is especially common for mutants with high variance in fitness across tested environments, even if the components of the focal fluctuating environment are excluded from this variance. We employ a simple mathematical model and whole-genome sequencing to propose mechanisms underlying this effect, including lag time evolution and sensing mutations. Our results demonstrate that environmental fluctuations have large impacts on fitness and suggest that variance in static environments can explain these impacts.

Revisiting the Design of the Long-Term Evolution Experiment with Escherichia coli

The long-term evolution experiment (LTEE) with Escherichia coli began in 1988 and it continues to this day, with its 12 populations having recently reached 75,000 generations of evolution in a simple, well-controlled environment. The LTEE was designed to explore open-ended questions about the dynamics and repeatability of phenotypic and genetic evolution. Here I discuss various aspects of the LTEE's experimental design that have enabled its stability and success, including the choices of the culture regime, growth medium, ancestral strain, and statistical replication. I also discuss some of the challenges associated with a long-running project, such as handling procedural errors (e.g., cross-contamination) and managing the expanding collection of frozen samples. The simplicity of the experimental design and procedures have supported the long-term stability of the LTEE. That stability-along with the inherent creativity of the evolutionary process and the emergence of new genomic technologies-provides a platform that has allowed talented students and collaborators to pose questions, collect data, and make discoveries that go far beyond anything I could have imagined at the start of the LTEE.

Experimental evolution of evolutionary potential in fluctuating environments

Variation is the raw material for evolution. Evolutionary potential is determined by the amount of genetic variation, but evolution can also alter the visibility of genetic variation to natural selection. Fluctuating environments are suggested to maintain genetic variation but they can also affect environmental variance, and thus, the visibility of genetic variation to natural selection. However, experimental studies testing these ideas are relatively scarce. In order to determine differences in evolutionary potential we quantified variance attributable to population, genotype and environment for populations of the bacterium Serratia marcescens. These populations had been experimentally evolved in constant and two fluctuating environments. We found that strains that evolved in fluctuating environments exhibited larger environmental variation suggesting that adaptation to fluctuations has decreased the visibility of genetic variation to selection.

Parallel engineering of environmental bacteria and performance over years under jungle-simulated conditions

Engineered bacteria could perform many functions in the environment, for example, to remediate pollutants, deliver nutrients to crops or act as in-field biosensors. Model organisms can be unreliable in the field, but selecting an isolate from the thousands that naturally live there and genetically manipulating them to carry the desired function is a slow and uninformed process. Here, we demonstrate the parallel engineering of isolates from environmental samples by using the broad-host-range XPORT conjugation system (Bacillus subtilis mini-ICEBs1) to transfer a genetic payload to many isolates in parallel. Bacillus and Lysinibacillus species were obtained from seven soil and water samples from different locations in Israel. XPORT successfully transferred a genetic function (reporter expression) into 25 of these isolates. They were then screened to identify the best-performing chassis based on the expression level, doubling time, functional stability in soil, and environmentally-relevant traits of its closest annotated reference species, such as the ability to sporulate and temperature tolerance. From this library, we selected Bacillus frigoritolerans A3E1, re-introduced it to soil, and measured function and genetic stability in a contained environment that replicates jungle conditions. After 21 months of storage, the engineered bacteria were viable, could perform their function, and did not accumulate disruptive mutations.

The effect of migration and variation on populations of Escherichia coli adapting to complex fluctuating environments

Migration, a critical evolutionary force, can have contrasting effects on adaptation. It can aid as well as impede adaptation. The effects of migration on microbial adaptation have been studied primarily in simple constant environments. Very little is known about the effects of migration on adaptation to complex, fluctuating environments. In our study, we subjected replicate populations of Escherichia coli, adapting to complex and unpredictably fluctuating environments to different proportions of clonal ancestral immigrants. Contrary to the results from simple/constant environments, the presence of clonal immigrants reduced all measured proxies of fitness. However, migration from a source population with a greater variance in fitness resulted in no change in fitness with respect to the no-migration control, except at the highest level of migration. Thus, the presence of variation in the immigrants could counter the adverse effects of migration in complex and unpredictably fluctuating environments. Our study demonstrates that the effects of migration are strongly dependent on the nature of the destination environment and the genetic makeup of immigrants. These results enhance our understanding of the influences of migrating populations, which could help better predict the consequences of migration.

Hidden paths to endless forms most wonderful: ecology latently shapes evolution of multicellular development in predatory bacteria

Ecological causes of developmental evolution, for example from predation, remain much investigated, but the potential importance of latent phenotypes in eco-evo-devo has received little attention. Using the predatory bacterium Myxococcus xanthus, which undergoes aggregative fruiting body development upon starvation, we tested whether adaptation to distinct growth environments that do not induce development latently alters developmental phenotypes under starvation conditions that do induce development. In an evolution experiment named MyxoEE-3, growing M. xanthus populations swarmed across agar surfaces while adapting to conditions varying at factors such as surface stiffness or prey identity. Such ecological variation during growth was found to greatly impact the latent evolution of development, including fruiting body morphology, the degree of morphological trait correlation, reaction norms, degrees of developmental plasticity and stochastic diversification. For example, some prey environments promoted retention of developmental proficiency whereas others led to its systematic loss. Our results have implications for understanding evolutionary interactions among predation, development and motility in myxobacterial life cycles, and, more broadly, how ecology can profoundly shape the evolution of developmental systems latently rather than by direct selection on developmental features.

Fitness of evolving bacterial populations is contingent on deep and shallow history but only shallow history creates predictable patterns

Long-term evolution experiments have tested the importance of genetic and environmental factors in influencing evolutionary outcomes. Differences in phylogenetic history, recent adaptation to distinct environments and chance events, all influence the fitness of a population. However, the interplay of these factors on a population's evolutionary potential remains relatively unexplored. We tracked the outcome of 2000 generations of evolution of four natural isolates of Escherichia coli bacteria that were engineered to also create differences in shallow history by adding previously identified mutations selected in a separate long-term experiment. Replicate populations started from each progenitor evolved in four environments. We found that deep and shallow phylogenetic histories both contributed significantly to differences in evolved fitness, though by different amounts in different selection environments. With one exception, chance effects were not significant. Whereas the effect of deep history did not follow any detectable pattern, effects of shallow history followed a pattern of diminishing returns whereby fitter ancestors had smaller fitness increases. These results are consistent with adaptive evolution being contingent on the interaction of several evolutionary forces but demonstrate that the nature of these interactions is not fixed and may not be predictable even when the role of chance is small.

Net effect of environmental fluctuations in multiple global-change drivers across the tree of life

Jensen's inequality predicts that the response of any given system to average constant conditions is different from its average response to varying ones. Environmental fluctuations in abiotic conditions are pervasive on Earth; yet until recently, most ecological research has addressed the effects of multiple environmental drivers by assuming constant conditions. One could thus expect to find significant deviations in the magnitude of their effects on ecosystems when environmental fluctuations are considered. Drawing on experimental studies published during the last 30 years reporting more than 950 response ratios (n = 5,700), we present a comprehensive analysis of the role that environmental fluctuations play across the tree of life. In contrast to the predominance of interactive effects of global-change drivers reported in the literature, our results show that their cumulative effects were additive (58%), synergistic (26%), and antagonistic (16%) when environmental fluctuations were present. However, the dominant type of interaction varied by trophic level (autotrophs: interactive; heterotrophs: additive) and phylogenetic group (additive in Animalia; additive and positive antagonism in Chromista; negative antagonism and synergism in Plantae). In addition, we identify the need to tackle how complex communities respond to fluctuating environments, widening the phylogenetic and biogeographic ranges considered, and to consider other drivers beyond warming and acidification as well as longer timescales. Environmental fluctuations must be taken into account in experimental and modeling studies as well as conservation plans to better predict the nature, magnitude, and direction of the impacts of global change on organisms and ecosystems.

Trade-offs predicted by metabolic network structure give rise to evolutionary specialization and phenotypic diversification

Mitigating trade-offs between different resource-utilization functions is key to an organism's ecological and evolutionary success. These trade-offs often reflect metabolic constraints with a complex molecular underpinning; therefore, their consequences for evolutionary processes have remained elusive. Here, we investigate how metabolic architecture induces resource utilization constraints and how these constraints, in turn, elicit evolutionary specialization and diversification. Guided by the metabolic network structure of the bacterium Lactococcus cremoris, we selected two carbon sources (fructose and galactose) with predicted co-utilization constraints. By evolving L. cremoris on either fructose, galactose or a mix of both sugars, we imposed selection favoring divergent metabolic specializations or co-utilization of both resources, respectively. Phenotypic characterization revealed the evolution of either fructose or galactose specialists in the single-sugar treatments. In the mixed sugar regime, we observed adaptive diversification: both specialists coexisted, and no generalist evolved. Divergence from the ancestral phenotype occurred at key pathway junctions in the central carbon metabolism. Fructose specialists evolved mutations in the fbp and pfk genes that appear to balance anabolic and catabolic carbon fluxes. Galactose specialists evolved increased expression of pgmA (the primary metabolic bottleneck of galactose metabolism) and silencing of ptnABCD (the main glucose transporter) and ldh (regulator/enzyme of downstream carbon metabolism). Overall, our study shows how metabolic network architecture and historical contingency serve to predict targets of selection and inform the functional interpretation of evolved mutations. The elucidation of the relationship between molecular constraints and phenotypic trade-offs contributes to an integrative understanding of evolutionary specialization and diversification.

Evolutionary engineering to improve Wickerhamomyces subpelliculosus and Kazachstania gamospora for baking

The conventional baker's yeast, Saccharomyces cerevisiae, is the indispensable baking yeast of all times. Its monopoly coupled to its major drawbacks, such as streamlined carbon substrate utilisation base and a poor ability to withstand a number of baking associated stresses, prompt the need to search for alternative yeasts to leaven bread in the era of increasingly complex consumer lifestyles. Our previous work identified the inefficient baking attributes of Wickerhamomyces subpelliculosus and Kazachstania gamospora as well as preliminarily observations of improving the fermentative capacity of these potential alternative baker's yeasts using evolutionary engineering. Here we report on the characterisation and improvement in baking traits in five out of six independently evolved lines incubated for longer time and passaged for at least 60 passages relative to their parental strains as well as the conventional baker's yeast. In addition, the evolved clones produced bread with a higher loaf volume when compared to bread baked with either the ancestral strain or the control conventional baker's yeast. Remarkably, our approach improved the yeasts' ability to withstand baking associated stresses, a key baking trait exhibited poorly in both the conventional baker's yeast and their ancestral strains. W. subpelliculosus evolved the best characteristics attractive for alternative baker's yeasts as compared to the evolved K. gamospora strains. These results demonstrate the robustness of evolutionary engineering in development of alternative baker's yeasts.

Cheating Promotes Coexistence in a Two-Species One-Substrate Culture Model

Cheating in microbial communities is often regarded as a precursor to a “tragedy of the commons,” ultimately leading to over-exploitation by a few species and destabilization of the community. While current evidence suggests that cheaters are evolutionarily and ecologically abundant, they can also play important roles in communities, such as promoting cooperative behaviors of other species. We developed a closed culture model with two microbial species and a single, complex nutrient substrate (the metaphorical “common”). One of the organisms, an enzyme producer, degrades the substrate, releasing an essential and limiting resource that it can use both to grow and produce more enzymes, but at a cost. The second organism, a cheater, does not produce the enzyme but can access the diffused resource produced by the other species, allowing it to benefit from the public good without contributing to it. We investigated evolutionarily stable states of coexistence between the two organisms and described how enzyme production rates and resource diffusion influence organism abundances. Our model shows that, in the long-term evolutionary scale, monocultures of the producer species drive themselves extinct because selection always favors mutant invaders that invest less in enzyme production, ultimately driving down the release of resources. However, the presence of a cheater buffers this process by reducing the fitness advantage of lower enzyme production, thereby preventing runaway selection in the producer, and promoting coexistence. Resource diffusion rate controls cheater growth, preventing it from outcompeting the producer. These results show that competition from cheaters can force producers to maintain adequate enzyme production to sustain both itself and the cheater. This is similar to what is known in evolutionary game theory as a “snowdrift game” – a metaphor describing a snow shoveler and a cheater following in their clean tracks. We move further to show that cheating can stabilize communities and possibly be a precursor to cooperation, rather than extinction.

Seasonal genotype dynamics of a marine dinoflagellate: Pelagic populations are homogeneous and as diverse as benthic seed banks

Genetic diversity is the basis for evolutionary adaptation and selection under changing environmental conditions. Phytoplankton populations are genotypically diverse, can become genetically differentiated within small spatiotemporal scales and many species form resting stages. Resting stage accumulations in sediments (seed banks) are expected to serve as reservoirs for genetic information, but so far their role in maintaining phytoplankton diversity and in evolution has remained unclear. In this study we used the toxic dinoflagellate Alexandrium ostenfeldii (Dinophyceae) as a model organism to investigate if (i) the benthic seed bank is more diverse than the pelagic population and (ii) the pelagic population is seasonally differentiated. Resting stages (benthic) and plankton (pelagic) samples were collected at a coastal bloom site in the Baltic Sea, followed by cell isolation and genotyping using microsatellite markers (MS) and restriction site associated DNA sequencing (RAD). High clonal diversity (98%-100%) combined with intermediate to low gene diversity (0.58-0.03, depending on the marker) was found. Surprisingly, the benthic and pelagic fractions of the population were equally diverse, and the pelagic fraction was temporally homogeneous, despite seasonal fluctuation of environmental selection pressures. The results of this study suggest that continuous benthic-pelagic coupling, combined with frequent sexual reproduction, as indicated by persistent linkage equilibrium, prevent the dominance of single clonal lineages in a dynamic environment. Both processes harmonize the pelagic with the benthic population and thus prevent seasonal population differentiation. At the same time, frequent sexual reproduction and benthic-pelagic coupling maintain high clonal diversity in both habitats.

Social selection within aggregative multicellular development drives morphological evolution

Aggregative multicellular development is a social process involving complex forms of cooperation among unicellular organisms. In some aggregative systems, development culminates in the construction of spore-packed fruiting bodies and often unfolds within genetically and behaviourally diverse conspecific cellular environments. Here, we use the bacterium Myxococcus xanthus to test whether the character of the cellular environment during aggregative development shapes its morphological evolution. We manipulated the cellular composition of Myxococcus development in an experiment in which evolving populations initiated from a single ancestor repeatedly co-developed with one of several non-evolving partners-a cooperator, three cheaters and three antagonists. Fruiting body morphology was found to diversify not only as a function of partner genotype but more broadly as a function of partner social character, with antagonistic partners selecting for greater fruiting body formation than cheaters or the cooperator. Yet even small degrees of genetic divergence between distinct cheater partners sufficed to drive treatment-level morphological divergence. Co-developmental partners also determined the magnitude and dynamics of stochastic morphological diversification and subsequent convergence. In summary, we find that even just a few genetic differences affecting developmental and social features can greatly impact morphological evolution of multicellular bodies and experimentally demonstrate that microbial warfare can promote cooperation.

Fluctuating Environments Maintain Genetic Diversity through Neutral Fitness Effects and Balancing Selection

Genetic variation is the raw material upon which selection acts. The majority of environmental conditions change over time and therefore may result in variable selective effects. How temporally fluctuating environments impact the distribution of fitness effects and in turn population diversity is an unresolved question in evolutionary biology. Here, we employed continuous culturing using chemostats to establish environments that switch periodically between different nutrient limitations and compared the dynamics of selection to static conditions. We used the pooled Saccharomyces cerevisiae haploid gene deletion collection as a synthetic model for populations comprising thousands of unique genotypes. Using barcode sequencing, we find that static environments are uniquely characterized by a small number of high-fitness genotypes that rapidly dominate the population leading to dramatic decreases in genetic diversity. By contrast, fluctuating environments are enriched in genotypes with neutral fitness effects and an absence of extreme fitness genotypes contributing to the maintenance of genetic diversity. We also identified a unique class of genotypes whose frequencies oscillate sinusoidally with a period matching the environmental fluctuation. Oscillatory behavior corresponds to large differences in short-term fitness that are not observed across long timescales pointing to the importance of balancing selection in maintaining genetic diversity in fluctuating environments. Our results are consistent with a high degree of environmental specificity in the distribution of fitness effects and the combined effects of reduced and balancing selection in maintaining genetic diversity in the presence of variable selection.

A sink host allows a specialist herbivore to persist in a seasonal source

In seasonal environments, sinks that are more persistent than sources may serve as temporal stepping stones for specialists. However, this possibility has to our knowledge, not been demonstrated to date, as such environments are thought to select for generalists, and the role of sinks, both in the field and in the laboratory, is difficult to document. Here, we used laboratory experiments to show that herbivorous arthropods associated with seasonally absent main (source) habitats can endure on a suboptimal (sink) host for several generations, albeit with a negative growth rate. Additionally, they dispersed towards this host less often than towards the main host and accepted it less often than the main host. Finally, repeated experimental evolution attempts revealed no adaptation to the suboptimal host. Nevertheless, field observations showed that arthropods are found in suboptimal habitats when the main habitat is unavailable. Together, these results show that evolutionary rescue in the suboptimal habitat is not possible. Instead, the sink habitat functions as a temporal stepping stone, allowing for the persistence of a specialist when the source habitat is gone.

The cost of evolved constitutive lac gene expression is usually, but not always, maintained during evolution of generalist populations

Beneficial mutations can become costly following an environmental change. Compensatory mutations can relieve these costs, while not affecting the selected function, so that the benefits are retained if the environment shifts back to be similar to the one in which the beneficial mutation was originally selected. Compensatory mutations have been extensively studied in the context of antibiotic resistance, responses to specific genetic perturbations, and in the determination of interacting gene network components. Few studies have focused on the role of compensatory mutations during more general adaptation, especially as the result of selection in fluctuating environments where adaptations to different environment components may often involve trade-offs. We examine whether costs of a mutation in lacI, which deregulated the expression of the lac operon in evolving populations of Escherichia coli bacteria, were compensated. This mutation occurred in multiple replicate populations selected in environments that fluctuated between growth on lactose, where the mutation was beneficial, and on glucose, where it was deleterious. We found that compensation for the cost of the lacI mutation was rare, but, when it did occur, it did not negatively affect the selected benefit. Compensation was not more likely to occur in a particular evolution environment. Compensation has the potential to remove pleiotropic costs of adaptation, but its rarity indicates that the circumstances to bring about the phenomenon may be peculiar to each individual or impeded by other selected mutations.

Compensatory adaptation and diversification subsequent to evolutionary rescue in a model adaptive radiation

Biological populations may survive lethal environmental stress through evolutionary rescue. The rescued populations typically suffer a reduction in growth performance and harbor very low genetic diversity compared with their parental populations. The present study addresses how population size and within-population diversity may recover through compensatory evolution, using the experimental adaptive radiation of bacterium Pseudomonas fluorescens. We exposed bacterial populations to an antibiotic treatment and then imposed a one-individual-size population bottleneck on those surviving the antibiotic stress. During the subsequent compensatory evolution, population size increased and leveled off very rapidly. The increase of diversity was of slower paces and persisted longer. In the very early stage of compensatory evolution, populations of large sizes had a greater chance to diversify; however, this productivity-diversification relationship was not observed in later stages. Population size and diversity from the end of the compensatory evolution was not contingent on initial population growth performance. We discussed the possibility that our results be explained by the emergence of a "holey" fitness landscape under the antibiotic stress.

Adaptive evolution of sulfite tolerance in Brettanomyces bruxellensis

Brettanomyces bruxellensis is considered one of the most problematic microbes associated with wine production. Sulfur dioxide is commonly used to inhibit the growth of B. bruxellensis and limit the potential wine spoilage. Brettanomyces bruxellensis wine isolates can grow at higher concentrations of this preservative than isolates from other sources. Thus, it has been suggested that the use of sulfite may have selected for B. bruxellensis strains better adapted to survive in the winemaking environment. We utilized laboratory adaptive evolution to determine the potential for this to occur. Three B. bruxellensis strains, representative of known genetic variation within the species, were subjected to increasing sublethal sulfur dioxide concentrations. Individual clones isolated from evolved populations displayed enhanced sulfite tolerance, ranging from 1.6 to 2.5 times higher than the corresponding parental strains. Whole-genome sequencing of sulfite-tolerant clones derived from two of the parental strains revealed structural variations affecting 270 genes. The region containing the sulfite efflux pump encoding gene, SSU1, showed clear copy number variants in all sequenced clones. Regardless of parental strain genetic background, SSU1 copy number changes were reproducibly associated with one SSU1 haplotype. This work clearly demonstrates adaptive evolution of B. bruxellensis when exposed to sublethal sulfites and suggests that, similar to Saccharomyces cerevisiae wine yeast, the mechanism responsible involves the gene SSU1.

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.

Hidden paths to endless forms most wonderful: parasite-blind diversification of host quality

Evolutionary diversification can occur in allopatry or sympatry, can be driven by selection or unselected, and can be phenotypically manifested immediately or remain latent until manifested in a newly encountered environment. Diversification of host-parasite interactions is frequently studied in the context of intrinsically selective coevolution, but the potential for host-parasite interaction phenotypes to diversify latently during parasite-blind host evolution is rarely considered. Here, we use a social bacterium experimentally adapted to several environments in the absence of phage to analyse allopatric diversification of host quality-the degree to which a host population supports a viral epidemic. Phage-blind evolution reduced host quality overall, with some bacteria becoming completely resistant to growth suppression by phage. Selective-environment differences generated only mild divergence in host quality. However, selective environments nonetheless played a major role in shaping evolution by determining the degree of stochastic diversification among replicate populations within treatments. Ancestral motility genotype was also found to strongly shape patterns of latent host-quality evolution and diversification. These outcomes show that (i) adaptive landscapes can differ in how they constrain stochastic diversification of a latent phenotype and (ii) major effects of selection on biological diversification can be missed by focusing on trait means. Collectively, our findings suggest that latent-phenotype evolution should inform host-parasite evolution theory and that diversification should be conceived broadly to include latent phenotypes.

Historical Contingency Causes Divergence in Adaptive Expression of the lac Operon

Populations of Escherichia coli selected in constant and fluctuating environments containing lactose often adapt by substituting mutations in the lacI repressor that cause constitutive expression of the lac operon. These mutations occur at a high rate and provide a significant benefit. Despite this, eight of 24 populations evolved for 8,000 generations in environments containing lactose contained no detectable repressor mutations. We report here on the basis of this observation. We find that, given relevant mutation rates, repressor mutations are expected to have fixed in all evolved populations if they had maintained the same fitness effect they confer when introduced to the ancestor. In fact, reconstruction experiments demonstrate that repressor mutations have become neutral or deleterious in those populations in which they were not detectable. Populations not fixing repressor mutations nevertheless reached the same fitness as those that did fix them, indicating that they followed an alternative evolutionary path that made redundant the potential benefit of the repressor mutation, but involved unique mutations of equivalent benefit. We identify a mutation occurring in the promoter region of the uspB gene as a candidate for influencing the selective choice between these paths. Our results detail an example of historical contingency leading to divergent evolutionary outcomes.

Evolution in alternating environments with tunable interlandscape correlations

Natural populations are often exposed to temporally varying environments. Evolutionary dynamics in varying environments have been extensively studied, although understanding the effects of varying selection pressures remains challenging. Here, we investigate how cycling between a pair of statistically related fitness landscapes affects the evolved fitness of an asexually reproducing population. We construct pairs of fitness landscapes that share global fitness features but are correlated with one another in a tunable way, resulting in landscape pairs with specific correlations. We find that switching between these landscape pairs, depending on the ruggedness of the landscape and the interlandscape correlation, can either increase or decrease steady-state fitness relative to evolution in single environments. In addition, we show that switching between rugged landscapes often selects for increased fitness in both landscapes, even in situations where the landscapes themselves are anticorrelated. We demonstrate that positively correlated landscapes often possess a shared maximum in both landscapes that allows the population to step through sub-optimal local fitness maxima that often trap single landscape evolution trajectories. Finally, we demonstrate that switching between anticorrelated paired landscapes leads to ergodic-like dynamics where each genotype is populated with nonzero probability, dramatically lowering the steady-state fitness in comparison to single landscape evolution.

Environmental fluctuations and their effects on microbial communities, populations and individuals

From the homeostasis of human health to the cycling of Earth's elements, microbial activities underlie environmental, medical and industrial processes. These activities occur in chemical and physical landscapes that are highly dynamic and experienced by bacteria as fluctuations. In this review, we first discuss how bacteria can experience both spatial and temporal heterogeneity in their environments as temporal fluctuations of various timescales (seconds to seasons) and types (nutrient, sunlight, fluid flow, etc.). We then focus primarily on nutrient fluctuations to discuss how bacterial communities, populations and single cells respond to environmental fluctuations. Overall, we find that environmental fluctuations are ubiquitous and diverse, and strongly shape microbial behavior, ecology and evolution when compared with environments in which conditions remain constant over time. We hope this review may serve as a guide toward understanding the significance of environmental fluctuations in microbial life, such that their contributions and implications can be better assessed and exploited.

Hidden paths to endless forms most wonderful: Complexity of bacterial motility shapes diversification of latent phenotypes

BACKGROUND

Evolution in one selective environment often latently generates phenotypic change that is manifested only later in different environments, but the complexity of behavior important to fitness in the original environment might influence the character of such latent-phenotype evolution. Using Myxococcus xanthus, a bacterium possessing two motility systems differing in effectiveness on hard vs. soft surfaces, we test (i) whether and how evolution while swarming on one surface-the selective surface-latently alters motility on the alternative surface type and (ii) whether patterns of such latent-phenotype evolution depend on the complexity of ancestral motility, specific ancestral motility genotypes and/or the selective surface of evolution. We analysze an experiment in which populations established from three ancestral genotypes-one with both motility systems intact and two others with one system debilitated-evolved while swarming across either hard or soft agar in six evolutionary treatments. We then compare motility-phenotype patterns across selective vs. alternative surface types.

RESULTS

Latent motility evolution was pervasive but varied in character as a function of the presence of one or two functional motility systems and, for some individual-treatment comparisons, the specific ancestral genotype and/or selective surface. Swarming rates on alternative vs. selective surfaces were positively correlated generally among populations with one functional motility system but not among those with two. This suggests that opportunities for pleiotropy and epistasis generated by increased genetic complexity underlying behavior can alter the character of latent-phenotype evolution. No tradeoff between motility performance across surface types was detected in the dual-system treatments, even after adaptation on a surface on which one motility system dominates strongly over the other in driving movement, but latent-phenotype evolution was instead idiosyncratic in these treatments. We further find that the magnitude of stochastic diversification at alternative-surface swarming among replicate populations greatly exceeded diversification of selective-surface swarming within some treatments and varied across treatments.

CONCLUSION

Collectively, our results suggest that increases in the genetic and mechanistic complexity of behavior can increase the complexity of latent-phenotype evolution outcomes and illustrate that diversification manifested during evolution in one environment can be augmented greatly by diversification of latent phenotypes manifested later.

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

BACKGROUND

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

RESULTS

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

CONCLUSIONS

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

Creating outbred and inbred populations in haplodiploids to measure adaptive responses in the laboratory

Laboratory studies are often criticized for not being representative of processes occurring in natural populations. One reason for this is the fact that laboratory populations generally do not capture enough of the genetic variation of natural populations. This can be mitigated by mixing the genetic background of several field populations when creating laboratory populations. From these outbred populations, it is possible to generate inbred lines, thereby freezing and partitioning part of their variability, allowing each genotype to be characterized independently. Many studies addressing adaptation of organisms to their environment, such as those involving quantitative genetics or experimental evolution, rely on inbred or outbred populations, but the methodology underlying the generation of such biological resources is usually not explicitly documented. Here, we developed different procedures to circumvent common pitfalls of laboratory studies, and illustrate their application using two haplodiploid species, the spider mites Tetranychus urticae and Tetranychus evansi. First, we present a method that increases the chance of capturing high amounts of variability when creating outbred populations, by performing controlled crosses between individuals from different field-collected populations. Second, we depict the creation of inbred lines derived from such outbred populations, by performing several generations of sib-mating. Third, we outline an experimental evolution protocol that allows the maintenance of a constant population size at the beginning of each generation, thereby preventing bottlenecks and diminishing extinction risks. Finally, we discuss the advantages of these procedures and emphasize that sharing such biological resources and combining them with available genetic tools will allow consistent and comparable studies that greatly contribute to our understanding of ecological and evolutionary processes.

Environment-dependent costs and benefits of recombination in independently evolved populations of Escherichia coli

Understanding of the causes by which reproductive isolation arises remains limited. We examine the role of adaptation in driving reproductive isolation among 12 Escherichia coli populations evolved in two different environments. We found that, regardless of whether parents were selected in the same or different environments, the average fitness of recombinants was lower than the expected, consistent with a prevailing influence of incompatibility between independently accumulated mutations. Exceptions to this pattern occurred among recombinants of some parents evolved in different environments. These recombinants were less fit than expected in the selective environment of one parent, but more fit than expected in the selective environment of the other parent. Our results indicate that both parallel and divergent adaptation can quickly lead to intrinsic genetic barriers contributing to the initial stages of speciation and show that these barriers can be complex, for example, depending on the environment in which recombinant offspring are tested.

Predicting microbial growth in a mixed culture from growth curve data

Determining the fitness of specific microbial genotypes has extensive application in microbial genetics, evolution, and biotechnology. While estimates from growth curves are simple and allow high throughput, they are inaccurate and do not account for interactions between costs and benefits accruing over different parts of a growth cycle. For this reason, pairwise competition experiments are the current "gold standard" for accurate estimation of fitness. However, competition experiments require distinct markers, making them difficult to perform between isolates derived from a common ancestor or between isolates of nonmodel organisms. In addition, competition experiments require that competing strains be grown in the same environment, so they cannot be used to infer the fitness consequence of different environmental perturbations on the same genotype. Finally, competition experiments typically consider only the end-points of a period of competition so that they do not readily provide information on the growth differences that underlie competitive ability. Here, we describe a computational approach for predicting density-dependent microbial growth in a mixed culture utilizing data from monoculture and mixed-culture growth curves. We validate this approach using 2 different experiments with Escherichia coli and demonstrate its application for estimating relative fitness. Our approach provides an effective way to predict growth and infer relative fitness in mixed cultures.

Evolutionary highways to persistent bacterial infection

Persistent infections require bacteria to evolve from their naïve colonization state by optimizing fitness in the host via simultaneous adaptation of multiple traits, which can obscure evolutionary trends and complicate infection management. Accordingly, here we screen 8 infection-relevant phenotypes of 443 longitudinal Pseudomonas aeruginosa isolates from 39 young cystic fibrosis patients over 10 years. Using statistical modeling, we map evolutionary trajectories and identify trait correlations accounting for patient-specific influences. By integrating previous genetic analyses of 474 isolates, we provide a window into early adaptation to the host, finding: (1) a 2–3 year timeline of rapid adaptation after colonization, (2) variant “naïve” and “adapted” states reflecting discordance between phenotypic and genetic adaptation, (3) adaptive trajectories leading to persistent infection via three distinct evolutionary modes, and (4) new associations between phenotypes and pathoadaptive mutations. Ultimately, we effectively deconvolute complex trait adaptation, offering a framework for evolutionary studies and precision medicine in clinical microbiology.

The pathogen Pseudomonas aeruginosa undergoes complex trait adaptation within cystic fibrosis patients. Here, Bartell, Sommer, and colleagues use statistical modeling of longitudinal isolates to characterize the joint genetic and phenotypic evolutionary trajectories of P. aeruginosa within hosts.

Adaptation Through Lifestyle Switching Sculpts the Fitness Landscape of Evolving Populations: Implications for the Selection of Drug-Resistant Bacteria at Low Drug Pressures

Novel genotypes evolve under selection through mutations in pre-existing genes. However, mutations have pleiotropic phenotypic effects that influence the fitness of emerging genotypes in complex ways. The evolution of antimicrobial resistance is mediated by selection of mutations in genes coding for antibiotic-target proteins. Drug-resistance is commonly associated with a fitness cost due to the impact of resistance-conferring mutations on protein function and/or stability. These costs are expected to prohibit the selection of drug-resistant mutations at low drug pressures. Using laboratory evolution of rifampicin resistance in Escherichia coli, we show that when exposed intermittently to low concentration (0.1 × minimal inhibitory concentration) of rifampicin, the evolution of canonical drug resistance was indeed unfavorable. Instead, these bacterial populations adapted by evolving into small-colony variants that displayed enhanced pellicle-forming ability. This shift in lifestyle from planktonic to pellicle-like was necessary for enhanced fitness at low drug pressures, and was mediated by the genetic activation of the fim operon promoter, which allowed expression of type I fimbriae. Upon continued low drug exposure, these bacteria evolved exclusively into high-level drug-resistant strains through mutations at a limited set of loci within the rifampicin-resistance determining region of the rpoB gene. We show that our results are explained by mutation-specific epistasis, resulting in differential impact of lifestyle switching on the competitive fitness of different rpoB mutations. Thus, lifestyle-alterations that are selected at low selection pressures have the potential to modify the fitness effects of mutations, change the genetic structure, and affect the ultimate fate of evolving populations.

Contingency and determinism in evolution: Replaying life’s tape

Historical processes display some degree of “contingency,” meaning their outcomes are sensitive to seemingly inconsequential events that can fundamentally change the future. Contingency is what makes historical outcomes unpredictable. Unlike many other natural phenomena, evolution is a historical process. Evolutionary change is often driven by the deterministic force of natural selection, but natural selection works upon variation that arises unpredictably through time by random mutation, and even beneficial mutations can be lost by chance through genetic drift. Moreover, evolution has taken place within a planetary environment with a particular history of its own. This tension between determinism and contingency makes evolutionary biology a kind of hybrid between science and history. While philosophers of science examine the nuances of contingency, biologists have performed many empirical studies of evolutionary repeatability and contingency. Here, we review the experimental and comparative evidence from these studies. Replicate populations in evolutionary “replay” experiments often show parallel changes, especially in overall performance, although idiosyncratic outcomes show that the particulars of a lineage’s history can affect which of several evolutionary paths is taken. Comparative biologists have found many notable examples of convergent adaptation to similar conditions, but quantification of how frequently such convergence occurs is difficult. On balance, the evidence indicates that evolution tends to be surprisingly repeatable among closely related lineages, but disparate outcomes become more likely as the footprint of history grows deeper. Ongoing research on the structure of adaptive landscapes is providing additional insight into the interplay of fate and chance in the evolutionary process.

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.

Escherichia coli cultures maintain stable subpopulation structure during long-term evolution

How genetic variation is generated and maintained remains a central question in evolutionary biology. When presented with a complex environment, microbes can take advantage of genetic variation to exploit new niches. Here we present a massively parallel experiment where WT and repair-deficient (∆mutL) Escherichia coli populations have evolved over 3 y in a spatially heterogeneous and nutritionally complex environment. Metagenomic sequencing revealed that these initially isogenic populations evolved and maintained stable subpopulation structure in just 10 mL of medium for up to 10,000 generations, consisting of up to five major haplotypes with many minor haplotypes. We characterized the genomic, transcriptomic, exometabolomic, and phenotypic differences between clonal isolates, revealing subpopulation structure driven primarily by spatial segregation followed by differential utilization of nutrients. In addition to genes regulating the import and catabolism of nutrients, major polymorphisms of note included insertion elements transposing into fimE (regulator of the type I fimbriae) and upstream of hns (global regulator of environmental-change and stress-response genes), both known to regulate biofilm formation. Interestingly, these genes have also been identified as critical to colonization in uropathogenic E. coli infections. Our findings illustrate the complexity that can arise and persist even in small cultures, raising the possibility that infections may often be promoted by an evolving and complex pathogen population.

Adaptation costs to constant and alternating polluted environments

Some populations quickly adapt to strong and novel selection pressures caused by anthropogenic stressors. However, this short-term evolutionary response to novel and harsh environmental conditions may lead to adaptation costs, and evaluating these costs is important if we want to understand the evolution of resistance to anthropogenic stressors. In this experimental evolution study, we exposed Caenorhabditis elegans populations to uranium (U populations), salt (NaCl populations) and alternating uranium/salt treatments (U/NaCl populations) and to a control environment (C populations), over 22 generations. In parallel, we ran common-garden and reciprocal-transplant experiments to assess the adaptive costs for populations that have evolved in the different environmental conditions. Our results showed rapid evolutionary changes in life history characteristics of populations exposed to the different pollution regimes. Furthermore, adaptive costs depended on the type of pollutant: pollution-adapted populations had lower fitness than C populations, when the populations were returned to their original environment. Fitness in uranium environments was lower for NaCl populations than for U populations. In contrast, fitness in salt environments was similar between U and NaCl populations. Moreover, fitness of U/NaCl populations showed similar or higher fitness in both the uranium and the salt environments compared to populations adapted to constant uranium or salt environments. Our results show that adaptive evolution to a particular stressor can lead to either adaptive costs or benefits once in contact with another stressor. Furthermore, we did not find any evidence that adaptation to alternating stressors was associated with additional adaption costs. This study highlights the need to incorporate adaptive cost assessments when undertaking ecological risk assessments of pollutants.

Protein abundances can distinguish between naturally-occurring and laboratory strains of Yersinia pestis, the causative agent of plague

The rapid pace of bacterial evolution enables organisms to adapt to the laboratory environment with repeated passage and thus diverge from naturally-occurring environmental ("wild") strains. Distinguishing wild and laboratory strains is clearly important for biodefense and bioforensics; however, DNA sequence data alone has thus far not provided a clear signature, perhaps due to lack of understanding of how diverse genome changes lead to convergent phenotypes, difficulty in detecting certain types of mutations, or perhaps because some adaptive modifications are epigenetic. Monitoring protein abundance, a molecular measure of phenotype, can overcome some of these difficulties. We have assembled a collection of Yersinia pestis proteomics datasets from our own published and unpublished work, and from a proteomics data archive, and demonstrated that protein abundance data can clearly distinguish laboratory-adapted from wild. We developed a lasso logistic regression classifier that uses binary (presence/absence) or quantitative protein abundance measures to predict whether a sample is laboratory-adapted or wild that proved to be ~98% accurate, as judged by replicated 10-fold cross-validation. Protein features selected by the classifier accord well with our previous study of laboratory adaptation in Y. pestis. The input data was derived from a variety of unrelated experiments and contained significant confounding variables. We show that the classifier is robust with respect to these variables. The methodology is able to discover signatures for laboratory facility and culture medium that are largely independent of the signature of laboratory adaptation. Going beyond our previous laboratory evolution study, this work suggests that proteomic differences between laboratory-adapted and wild Y. pestis are general, potentially pointing to a process that could apply to other species as well. Additionally, we show that proteomics datasets (even archived data collected for different purposes) contain the information necessary to distinguish wild and laboratory samples. This work has clear applications in biomarker detection as well as biodefense.

Laboratory Evolution to Alternating Substrate Environments Yields Distinct Phenotypic and Genetic Adaptive Strategies

Adaptive laboratory evolution (ALE) experiments are often designed to maintain a static culturing environment to minimize confounding variables that could influence the adaptive process, but dynamic nutrient conditions occur frequently in natural and bioprocessing settings. To study the nature of carbon substrate fitness tradeoffs, we evolved batch cultures of Escherichia coli via serial propagation into tubes alternating between glucose and either xylose, glycerol, or acetate. Genome sequencing of evolved cultures revealed several genetic changes preferentially selected for under dynamic conditions and different adaptation strategies depending on the substrates being switched between; in some environments, a persistent "generalist" strain developed, while in another, two "specialist" subpopulations arose that alternated dominance. Diauxic lag phenotype varied across the generalists and specialists, in one case being completely abolished, while gene expression data distinguished the transcriptional strategies implemented by strains in pursuit of growth optimality. Genome-scale metabolic modeling techniques were then used to help explain the inherent substrate differences giving rise to the observed distinct adaptive strategies. This study gives insight into the population dynamics of adaptation in an alternating environment and into the underlying metabolic and genetic mechanisms. Furthermore, ALE-generated optimized strains have phenotypes with potential industrial bioprocessing applications.IMPORTANCE Evolution and natural selection inexorably lead to an organism's improved fitness in a given environment, whether in a laboratory or natural setting. However, despite the frequent natural occurrence of complex and dynamic growth environments, laboratory evolution experiments typically maintain simple, static culturing environments so as to reduce selection pressure complexity. In this study, we investigated the adaptive strategies underlying evolution to fluctuating environments by evolving Escherichia coli to conditions of frequently switching growth substrate. Characterization of evolved strains via a number of different data types revealed the various genetic and phenotypic changes implemented in pursuit of growth optimality and how these differed across the different growth substrates and switching protocols. This work not only helps to establish general principles of adaptation to complex environments but also suggests strategies for experimental design to achieve desired evolutionary outcomes.

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.

Convergence and Divergence in a Long-Term Experiment with Bacteria

Suitably designed experiments offer the possibility of quantifying evolutionary convergence because the fraction of replicate populations that converge is known. Here I review an experiment with Escherichia coli, in which 12 populations were founded from the same ancestral strain and have evolved for almost 30 years and more than 65,000 generations under the same conditions. The tension between divergence and convergence has been a major focus of this experiment. I summarize analyses of competitive fitness, correlated responses to different environments, cell morphology, the capacity to use a previously untapped resource, mutation rates, genomic changes, and within-population polymorphisms. These analyses reveal convergence, divergence, and often a complicated mix thereof. Complications include concordance in the direction of evolutionary change with sustained quantitative variation among populations, and the potential for a given trait to exhibit divergence on one timescale and convergence on another. Despite these complications, which also occur in nature, experiments provide a powerful way to study evolutionary convergence based on analyzing replicate lineages that experience the same environment.

Evolution of evolvability and phenotypic plasticity in virtual cells

BACKGROUND

Changing environmental conditions pose a challenge for the survival of species. To meet this challenge organisms adapt their phenotype by physiological regulation (phenotypic plasticity) or by evolving. Regulatory mechanisms that ensure a constant internal environment in the face of continuous external fluctuations (homeostasis) are ubiquitous and essential for survival. However, more drastic and enduring environmental change, often requires lineages to adapt by mutating. In vitro evolutionary experiments with microbes show that adaptive, large phenotypic changes occur remarkably quickly, requiring only a few mutations. It has been proposed that the high evolvability demonstrated by these microbes, is an evolved property. If both regulation (phenotypic plasticity) and evolvability can evolve as strategies to adapt to change, what are the conditions that favour the emergence of either of these strategy? Does evolution of one strategy hinder or facilitate evolution of the other strategy?

RESULTS

Here we investigate this with computational evolutionary modelling in populations of Virtual Cells. During a preparatory evolutionary phase, Virtual Cells evolved homeostasis regulation for internal metabolite concentrations in a fluctuating environment. The resulting wild-type Virtual Cell strains (WT-VCS) were then exposed to periodic, drastic environmental changes, while maintaining selection on homeostasis regulation. In different sets of simulations the nature and frequencies of environmental change were varied. Pre-evolved WT-VCS were highly evolvable, showing rapid evolutionary adaptation after novel environmental change. Moreover, continued low frequency changes resulted in evolutionary restructuring of the genome that enables even faster adaptation with very few mutations. In contrast, when change frequency is high, lineages evolve phenotypic plasticity that allows them to be fit in different environments without mutations. Yet, evolving phenotypic plasticity is a comparatively slow process. Under intermediate change frequencies, both strategies occur.

CONCLUSIONS

We conclude that evolving a homeostasis mechanisms predisposes lineage to be evolvable to novel environmental conditions. Moreover, after continued evolution, evolvability can be a viable alternative with comparable fitness to regulated phenotypic plasticity in all but the most rapidly changing environments.

Environmental fluctuations do not select for increased variation or population-based resistance in Escherichia coli

Little is known about the mechanisms that enable organisms to cope with unpredictable environments. To address this issue, we used replicate populations of Escherichia coli selected under complex, randomly changing environments. Under four novel stresses that had no known correlation with the selection environments, individual cells of the selected populations had significantly lower lag and greater yield compared to the controls. More importantly, there were no outliers in terms of growth, thus ruling out the evolution of population-based resistance. We also assayed the standing phenotypic variation of the selected populations, in terms of their growth on 94 different substrates. Contrary to expectations, there was no increase in the standing variation of the selected populations, nor was there any significant divergence from the ancestors. This suggested that the greater fitness in novel environments is brought about by selection at the level of the individuals, which restricts the suite of traits that can potentially evolve through this mechanism. Given that day-to-day climatic variability of the world is rising, these results have potential public health implications. Our results also underline the need for a very different kind of theoretical approach to study the effects of fluctuating environments.

Escherichia coli populations adapt to complex, unpredictable fluctuations by minimizing trade-offs across environments

In nature, organisms are simultaneously exposed to multiple stresses (i.e. complex environments) that often fluctuate unpredictably. Although both these factors have been studied in isolation, the interaction of the two remains poorly explored. To address this issue, we selected laboratory populations of Escherichia coli under complex (i.e. stressful combinations of pH, H₂ O₂ and NaCl) unpredictably fluctuating environments for ~900 generations. We compared the growth rates and the corresponding trade-off patterns of these populations to those that were selected under constant values of the component stresses (i.e. pH, H₂ O₂ and NaCl) for the same duration. The fluctuation-selected populations had greater mean growth rate and lower variation for growth rate over all the selection environments experienced. However, whereas the populations selected under constant stresses experienced trade-offs in the environments other than those in which they were selected, the fluctuation-selected populations could bypass the across-environment trade-offs almost entirely. Interestingly, trade-offs were found between growth rates and carrying capacities. The results suggest that complexity and fluctuations can strongly affect the underlying trade-off structure in evolving populations.

Genetic Regulation of Phenotypic Plasticity and Canalisation in Yeast Growth

The ability of a genotype to show diverse phenotypes in different environments is called phenotypic plasticity. Phenotypic plasticity helps populations to evade extinctions in novel environments, facilitates adaptation and fuels evolution. However, most studies focus on understanding the genetic basis of phenotypic regulation in specific environments. As a result, while it's evolutionary relevance is well established, genetic mechanisms regulating phenotypic plasticity and their overlap with the environment specific regulators is not well understood. Saccharomyces cerevisiae is highly sensitive to the environment, which acts as not just external stimulus but also as signalling cue for this unicellular, sessile organism. We used a previously published dataset of a biparental yeast population grown in 34 diverse environments and mapped genetic loci regulating variation in phenotypic plasticity, plasticity QTL, and compared them with environment-specific QTL. Plasticity QTL is one whose one allele exhibits high plasticity whereas the other shows a relatively canalised behaviour. We mapped phenotypic plasticity using two parameters-environmental variance, an environmental order-independent parameter and reaction norm (slope), an environmental order-dependent parameter. Our results show a partial overlap between pleiotropic QTL and plasticity QTL such that while some plasticity QTL are also pleiotropic, others have a significant effect on phenotypic plasticity without being significant in any environment independently. Furthermore, while some plasticity QTL are revealed only in specific environmental orders, we identify large effect plasticity QTL, which are order-independent such that whatever the order of the environments, one allele is always plastic and the other is canalised. Finally, we show that the environments can be divided into two categories based on the phenotypic diversity of the population within them and the two categories have differential regulators of phenotypic plasticity. Our results highlight the importance of identifying genetic regulators of phenotypic plasticity to comprehensively understand the genotype-phenotype map.

A case study in evolutionary contingency

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

Experimental evolution of the grain of metabolic specialization in yeast

Adaptation to any given environment may be accompanied by a cost in terms of reduced growth in the ancestral or some alternative environment. Ecologists explain the cost of adaptation through the concept of a trade‐off, by which gaining a new trait involves losing another trait. Two mechanisms have been invoked to explain the evolution of trade‐offs in ecological systems, mutational degradation, and functional interference. Mutational degradation occurs when a gene coding a specific trait is not under selection in the resident environment; therefore, it may be degraded through the accumulation of mutations that are neutral in the resident environment but deleterious in an alternative environment. Functional interference evolves if the gene or a set of genes have antagonistic effects in two or more ecologically different traits. Both mechanisms pertain to a situation where the selection and the alternative environments are ecologically different. To test this hypothesis, we conducted an experiment in which 12 experimental populations of wild yeast were each grown in a minimal medium supplemented with a single substrate. We chose 12 different carbon substrates that were metabolized through similar and different pathways in order to represent a wide range of ecological conditions. We found no evidence for trade‐offs between substrates on the same pathway. The indirect response of substrates on other pathways, however, was consistently negative, with little correlation between the direct and indirect responses. We conclude that the grain of specialization in this case is the metabolic pathway and that specialization appears to evolve through mutational degradation.