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.

Rampant Parasexuality Evolves in a Hospital Pathogen during Antibiotic Selection.

Horizontal gene transfer threatens the therapeutic success of antibiotics by facilitating the rapid dissemination of resistance alleles among bacterial species. The conjugative mobile element Tn916 provides an excellent context for examining the role of adaptive parasexuality as it carries the tetracycline-resistance allele tetM and has been identified in a wide range of pathogens. We have used a combination of experimental evolution and allelic frequency measurements to gain insights into the adaptive trajectories leading to tigecycline resistance in a hospital strain of Enterococcus faecalis and predict what mechanisms of resistance are most likely to appear in the clinical setting. Here, we show that antibiotic selection led to the near fixation of adaptive alleles that simultaneously altered TetM expression and produced remarkably increased levels of Tn916 horizontal gene transfer. In the absence of drug, approximately 1 in 120,000 of the nonadapted E. faecalis S613 cells had an excised copy of Tn916, whereas nearly 1 in 50 cells had an excised copy of Tn916 upon selection for resistance resulting in a more than 1,000-fold increase in conjugation rates. We also show that tigecycline, a translation inhibitor, selected for a mutation in the ribosomal S10 protein. Our results show the first example of mutations that concurrently confer resistance to an antibiotic and lead to constitutive conjugal-transfer of the resistance allele. Selection created a highly parasexual phenotype and high frequency of Tn916 jumping demonstrating how the use of antibiotics can lead directly to the proliferation of resistance in, and potentially among, pathogens.

The ribosomal S10 protein is a general target for decreased tigecycline susceptibility.

Tigecycline is a translational inhibitor with efficacy against a wide range of pathogens. Using experimental evolution, we adapted Acinetobacter baumannii, Enterococcus faecium, Escherichia coli, and Staphylococcus aureus to growth in elevated tigecycline concentrations. At the end of adaptation, 35 out of 47 replicate populations had clones with a mutation in rpsJ, the gene that encodes the ribosomal S10 protein. To validate the role of mutations in rpsJ in conferring tigecycline resistance, we showed that mutation of rpsJ alone in Enterococcus faecalis was sufficient to increase the tigecycline MIC to the clinical breakpoint of 0.5 µg/ml. Importantly, we also report the first identification of rpsJ mutations associated with decreased tigecycline susceptibility in A. baumannii, E. coli, and S. aureus. The identified S10 mutations across both Gram-positive and -negative species cluster in the vertex of an extended loop that is located near the tigecycline-binding pocket within the 16S rRNA. These data indicate that S10 is a general target of tigecycline adaptation and a relevant marker for detecting reduced susceptibility in both Gram-positive and -negative pathogens.

Small changes in enzyme function can lead to surprisingly large fitness effects during adaptive evolution of antibiotic resistance.

In principle, evolutionary outcomes could be largely predicted if all of the relevant physicochemical variants of a particular protein function under selection were known and integrated into an appropriate physiological model. We have tested this principle by generating a family of variants of the tetracycline resistance protein TetX2 and identified the physicochemical properties most correlated with organismal fitness. Surprisingly, small changes in the K(m(MCN)), less than twofold, were sufficient to produce highly successful adaptive mutants over clinically relevant drug concentrations. We then built a quantitative model directly relating the in vitro physicochemical properties of the mutant enzymes to the growth rates of bacteria carrying a single chromosomal copy of the tet(X2) variants over a wide range of minocycline (MCN) concentrations. Importantly, this model allows the prediction of enzymatic properties directly from cellular growth rates as well as the physicochemical-fitness landscape of TetX2. Using experimental evolution and deep sequencing to monitor the allelic frequencies of the seven most biochemically efficient TetX2 mutants in 10 independently evolving populations, we showed that the model correctly predicted the success of the two most beneficial variants tet(X2)(T280A) and tet(X2)(N371I). The structure of the most efficient variant, TetX2(T280A), in complex with MCN at 2.7 Å resolution suggests an indirect effect on enzyme kinetics. Taken together, these findings support an important role for readily accessible small steps in protein evolution that can, in turn, greatly increase the fitness of an organism during natural selection.

Adaptation of Enterococcus faecalis to daptomycin reveals an ordered progression to resistance.

With increasing numbers of hospital-acquired antibiotic resistant infections each year and staggering health care costs, there is a clear need for new antimicrobial agents, as well as novel strategies to extend their clinical efficacy. While genomic studies have provided a wealth of information about the alleles associated with adaptation to antibiotics, they do not provide essential information about the relative importance of genomic changes, their order of appearance, or potential epistatic relationships between adaptive changes. Here we used quantitative experimental evolution of a single polymorphic population in continuous culture with whole-genome sequencing and allelic frequency measurements to study daptomycin (DAP) resistance in the vancomycin-resistant clinical pathogen Enterococcus faecalis S613. Importantly, we sustained both planktonic and nonplanktonic (i.e., biofilm) populations in coculture as the concentration of antibiotic was raised, facilitating the development of more ecological complexity than is typically observed in laboratory evolution. Quantitative experimental evolution revealed a clear order and hierarchy of genetic changes leading to resistance, the signaling and metabolic pathways responsible, and the relative importance of these mutations to the evolution of DAP resistance. Despite the relative simplicity of this ex vivo approach compared to the ecological complexity of the human body, we showed that experimental evolution allows for rapid identification of clinically relevant adaptive molecular pathways and new targets for drug design in pathogens.

Variation, sex, and social cooperation: molecular population genetics of the social amoeba Dictyostelium discoideum.

Dictyostelium discoideum is a eukaryotic microbial model system for multicellular development, cell-cell signaling, and social behavior. Key models of social evolution require an understanding of genetic relationships between individuals across the genome or possibly at specific genes, but the nature of variation within D. discoideum is largely unknown. We re-sequenced 137 gene fragments in wild North American strains of D. discoideum and examined the levels and patterns of nucleotide variation in this social microbial species. We observe surprisingly low levels of nucleotide variation in D. discoideum across these strains, with a mean nucleotide diversity (pi) of 0.08%, and no strong population stratification among North American strains. We also do not find any clear relationship between nucleotide divergence between strains and levels of social dominance and kin discrimination. Kin discrimination experiments, however, show that strains collected from the same location show greater ability to distinguish self from non-self than do strains from different geographic areas. This suggests that a greater ability to recognize self versus non-self may arise among strains that are more likely to encounter each other in nature, which would lead to preferential formation of fruiting bodies with clonemates and may prevent the evolution of cheating behaviors within D. discoideum populations. Finally, despite the fact that sex has rarely been observed in this species, we document a rapid decay of linkage disequilibrium between SNPs, the presence of recombinant genotypes among natural strains, and high estimates of the population recombination parameter rho. The SNP data indicate that recombination is widespread within D. discoideum and that sex as a form of social interaction is likely to be an important aspect of the life cycle.

Probe-based bacterial single-cell RNA sequencing predicts toxin regulation.

Clonal bacterial populations rely on transcriptional variation across individual cells to produce specialized states that increase fitness. Understanding all cell states requires studying isogenic bacterial populations at the single-cell level. Here we developed probe-based bacterial sequencing (ProBac-seq), a method that uses libraries of DNA probes and an existing commercial microfluidic platform to conduct bacterial single-cell RNA sequencing. We sequenced the transcriptome of thousands of individual bacterial cells per experiment, detecting several hundred transcripts per cell on average. Applied to Bacillus subtilis and Escherichia coli, ProBac-seq correctly identifies known cell states and uncovers previously unreported transcriptional heterogeneity. In the context of bacterial pathogenesis, application of the approach to Clostridium perfringens reveals heterogeneous expression of toxin by a subpopulation that can be controlled by acetate, a short-chain fatty acid highly prevalent in the gut. Overall, ProBac-seq can be used to uncover heterogeneity in isogenic microbial populations and identify perturbations that affect pathogenicity.

Cheating does not explain selective differences at high and low relatedness in a social amoeba.

BACKGROUND: Altruism can be favored by high relatedness among interactants. We tested the effect of relatedness in experimental populations of the social amoeba Dictyostelium discoideum, where altruism occurs in a starvation-induced social stage when some amoebae die to form a stalk that lifts the fertile spores above the soil facilitating dispersal. The single cells that aggregate during the social stage can be genetically diverse, which can lead to conflict over spore and stalk allocation. We mixed eight genetically distinct wild isolates and maintained twelve replicated populations at a high and a low relatedness treatment. After one and ten social generations we assessed the strain composition of the populations. We expected that some strains would be out-competed in both treatments. In addition, we expected that low relatedness might allow the persistence of social cheaters as it provides opportunity to exploit other strains. RESULTS: We found that at high relatedness a single clone prevailed in all twelve populations. At low relatedness three clones predominated in all twelve populations. Interestingly, exploitation of some clones by others in the social stage did not explain the results. When we mixed each winner against the pool of five losers, the winner did not prevail in the spores because all contributed fairly to the stalk and spores. Furthermore, the dominant clone at high-relatedness was not cheated by the other two that persisted at low relatedness. A combination of high spore production and short unicellular stage most successfully explained the three successful clones at low relatedness, but not why one of them fared better at high relatedness. Differences in density did not account for the results, as the clones did not differ in vegetative growth rates nor did they change the growth rates over relevant densities. CONCLUSIONS: These results suggest that social competition and something beyond solitary growth differences occurs during the vegetative stage when amoebae eat bacteria and divide by binary fission. The high degree of repeatability of our results indicates that these effects are strong and points to the importance of new approaches to studying interactions in D. discoideum.

Spatial structure leads to ecological breakdown and loss of diversity.

Spatial structure has been identified as a major contributor to the maintenance of diversity. Here, we show that the impact of spatial structure on diversity is strongly affected by the ecological mechanisms maintaining diversity. In well-mixed, unstructured environments, microbial populations can diversify by production of metabolites during growth, providing additional resources for novel specialists. By contrast, spatially structured environments potentially limit such facilitation due to reduced metabolite diffusion. Using replicate microcosms containing the bacterium Escherichia coli, we predicted the loss of diversity during an environmental shift from a spatially unstructured environment to spatially structured conditions. Although spatial structure is frequently observed to be a major promoter of diversity, our results indicate that it can also have negative impacts on diversity.

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.

Unparallel diversification in bacterial microcosms.

Adaptive speciation has gained popularity as a fundamental process underlying the generation of diversity. We tested whether populations respond to similar forms of disruptive selection by diversifying in similar or parallel ways by investigating diversified populations of Escherichia coli B evolved in glucose and glucose-acetate environments. In both environments, the populations have differentiated into two phenotypes, named for their characteristic colony morphologies: large (L) and small (S). Each type is heritable and this polymorphism (or 'diversified pair') appears to be maintained by negative frequency dependence. The L and S phenotypes from different environments are convergent in their colony morphology and growth characteristics. We tested whether diversification was parallel by conducting competition experiments between L and S types from different environments. Our results indicate that replicate diversified pairs from different environments have not diversified in parallel ways and suggest that subtle differences in evolutionary environment can crucially affect the outcome of adaptive diversification.

Acinetobacter baumannii Repeatedly Evolves a Hypermutator Phenotype in Response to Tigecycline That Effectively Surveys Evolutionary Trajectories to Resistance.

The evolution of hypermutators in response to antibiotic treatment in both clinical and laboratory settings provides a unique context for the study of adaptive evolution. With increased mutation rates, the number of hitchhiker mutations within an evolving hypermutator population is remarkably high and presents substantial challenges in determining which mutations are adaptive. Intriguingly however, hypermutators also provide an opportunity to explore deeply the accessible evolutionary trajectories that lead to increased organism fitness, in this case the evolution of antibiotic resistance to the clinically relevant antibiotic tigecycline by the hospital pathogen Acinetobacter baumannii. Using a continuous culture system, AB210M, a clinically derived strain of A. baumannii, was evolved to tigecycline resistance. Analysis of the adapted populations showed that nearly all the successful lineages became hypermutators via movement of a mobile element to inactivate mutS. In addition, metagenomic analysis of population samples revealed another 896 mutations that occurred at a frequency greater than 5% in the population, while 38 phenotypically distinct individual colonies harbored a total of 1712 mutations. These mutations were scattered throughout the genome and affected ~40% of the coding sequences. The most highly mutated gene was adeS, a known tigecycline-resistance gene; however, adeS was not solely responsible for the high level of TGC resistance. Sixteen other genes stood out as potentially relevant to increased resistance. The five most prominent candidate genes (adeS, rpsJ, rrf, msbA, and gna) consistently re-emerged in subsequent replicate population studies suggesting they are likely to play a role in adaptation to tigecycline. Interestingly, the repeated evolution of a hypermutator phenotype in response to antibiotic stress illustrates not only a highly adaptive strategy to resistance, but also a remarkably efficient survey of successful evolutionary trajectories.

Experimental evidence for sympatric ecological diversification due to frequency-dependent competition in Escherichia coli.

We investigate adaptive diversification in experimental Escherichia coli populations grown in serial batch cultures on a mixture of glucose and acetate. All 12 experimental lines were started from the same genetically uniform ancestral strain but became highly polymorphic for colony size after 1000 generations. Five populations were clearly dimorphic and thus serve as a model for an adaptive lineage split. We analyzed the ecological basis for this dimorphism by studying bacterial growth curves. All strains exhibit diauxie, that is, sequential growth on the two resources. Thus, they exhibit phenotypic plasticity, using mostly glucose when glucose is abundant, then switching to acetate when glucose concentration is low. However, the coexisting strains differ in their diauxie pattern, with one cluster in the dimorphic populations growing better in the glucose phase, and the other cluster having a much shorter lag when switching to the acetate phase. Using invasion experiments, we show that the dimorphism of these two ecological types is maintained by frequency-dependent selection. Using a mathematical model for the adaptive dynamics of diauxie behavior, we show that evolutionary branching in diauxie behavior is a plausible theoretical scenario. Our results support the hypothesis that, in our experiments, adaptive diversification from a genetically uniform ancestor occurred due to frequency-dependent ecological interactions. Our results have implications for understanding the evolution of cross-feeding polymorphism in microorganisms, as well as adaptive speciation due to frequency-dependent selection on phenotypic plasticity.

Amino acid repeats cause extraordinary coding sequence variation in the social amoeba Dictyostelium discoideum.

Protein sequences are normally the most conserved elements of genomes owing to purifying selection to maintain their functions. We document an extraordinary amount of within-species protein sequence variation in the model eukaryote Dictyostelium discoideum stemming from triplet DNA repeats coding for long strings of single amino acids. D. discoideum has a very large number of such strings, many of which are polyglutamine repeats, the same sequence that causes various human neurological disorders in humans, like Huntington's disease. We show here that D. discoideum coding repeat loci are highly variable among individuals, making D. discoideum a candidate for the most variable proteome. The coding repeat loci are not significantly less variable than similar non-coding triplet repeats. This pattern is consistent with these amino-acid repeats being largely non-functional sequences evolving primarily by mutation and drift.

Whole genome sequencing of mutation accumulation lines reveals a low mutation rate in the social amoeba Dictyostelium discoideum.

Spontaneous mutations play a central role in evolution. Despite their importance, mutation rates are some of the most elusive parameters to measure in evolutionary biology. The combination of mutation accumulation (MA) experiments and whole-genome sequencing now makes it possible to estimate mutation rates by directly observing new mutations at the molecular level across the whole genome. We performed an MA experiment with the social amoeba Dictyostelium discoideum and sequenced the genomes of three randomly chosen lines using high-throughput sequencing to estimate the spontaneous mutation rate in this model organism. The mitochondrial mutation rate of 6.76×10(-9), with a Poisson confidence interval of 4.1×10(-9) - 9.5×10(-9), per nucleotide per generation is slightly lower than estimates for other taxa. The mutation rate estimate for the nuclear DNA of 2.9×10(-11), with a Poisson confidence interval ranging from 7.4×10(-13) to 1.6×10(-10), is the lowest reported for any eukaryote. These results are consistent with low microsatellite mutation rates previously observed in D. discoideum and low levels of genetic variation observed in wild D. discoideum populations. In addition, D. discoideum has been shown to be quite resistant to DNA damage, which suggests an efficient DNA-repair mechanism that could be an adaptation to life in soil and frequent exposure to intracellular and extracellular mutagenic compounds. The social aspect of the life cycle of D. discoideum and a large portion of the genome under relaxed selection during vegetative growth could also select for a low mutation rate. This hypothesis is supported by a significantly lower mutation rate per cell division in multicellular eukaryotes compared with unicellular eukaryotes.

The repeatability of adaptive radiation during long-term experimental evolution of Escherichia coli in a multiple nutrient environment.

Adaptive radiations occur when a species diversifies into different ecological specialists due to competition for resources and trade-offs associated with the specialization. The evolutionary outcome of an instance of adaptive radiation cannot generally be predicted because chance (stochastic events) and necessity (deterministic events) contribute to the evolution of diversity. With increasing contributions of chance, the degree of parallelism among different instances of adaptive radiations and the predictability of an outcome will decrease. To assess the relative contributions of chance and necessity during adaptive radiation, we performed a selection experiment by evolving twelve independent microcosms of Escherichia coli for 1000 generations in an environment that contained two distinct resources. Specialization to either of these resources involves strong trade-offs in the ability to use the other resource. After selection, we measured three phenotypic traits: 1) fitness, 2) mean colony size, and 3) colony size diversity. We used fitness relative to the ancestor as a measure of adaptation to the selective environment; changes in colony size as a measure of the evolution of new resource specialists because colony size has been shown to correlate with resource specialization; and colony size diversity as a measure of the evolved ecological diversity. Resource competition led to the rapid evolution of phenotypic diversity within microcosms. Measurements of fitness, colony size, and colony size diversity within and among microcosms showed that the repeatability of adaptive radiation was high, despite the evolution of genetic variation within microcosms. Consistent with the observation of parallel evolution, we show that the relative contributions of chance are far smaller and less important than effects due to adaptation for the traits investigated. The two-resource environment imposed similar selection pressures in independent populations and promoted parallel phenotypic adaptive radiations in all independently evolved microcosms.