Divergent evolution peaks under intermediate population bottlenecks during bacterial experimental evolution

Population demographic history and evolutionary rescue: Influence of a bottleneck event

Rapid environmental change presents a significant challenge to the persistence of natural populations. Rapid adaptation that increases population growth, enabling populations that declined following severe environmental change to grow and avoid extinction, is called evolutionary rescue. Numerous studies have shown that evolutionary rescue can indeed prevent extinction. Here, we extend those results by considering the demographic history of populations. To evaluate how demographic history influences evolutionary rescue, we created 80 populations of red flour beetle, Tribolium castaneum, with three classes of demographic history: diverse populations that did not experience a bottleneck, and populations that experienced either an intermediate or a strong bottleneck. We subjected these populations to a new and challenging environment for six discrete generations and tracked extinction and population size. Populations that did not experience a bottleneck in their demographic history avoided extinction entirely, while more than 20% of populations that experienced an intermediate or strong bottleneck went extinct. Similarly, among the extant populations at the end of the experiment, adaptation increased the growth rate in the novel environment the most for populations that had not experienced a bottleneck in their history. Taken together, these results highlight the importance of considering the demographic history of populations to make useful and effective conservation decisions and management strategies for populations experiencing environmental change that pushes them toward extinction.

Mutators can drive the evolution of multi-resistance to antibiotics

Antibiotic combination therapies are an approach used to counter the evolution of resistance; their purported benefit is they can stop the successive emergence of independent resistance mutations in the same genome. Here, we show that bacterial populations with 'mutators', organisms with defects in DNA repair, readily evolve resistance to combination antibiotic treatment when there is a delay in reaching inhibitory concentrations of antibiotic-under conditions where purely wild-type populations cannot. In populations of Escherichia coli subjected to combination treatment, we detected a diverse array of acquired mutations, including multiple alleles in the canonical targets of resistance for the two drugs, as well as mutations in multi-drug efflux pumps and genes involved in DNA replication and repair. Unexpectedly, mutators not only allowed multi-resistance to evolve under combination treatment where it was favoured, but also under single-drug treatments. Using simulations, we show that the increase in mutation rate of the two canonical resistance targets is sufficient to permit multi-resistance evolution in both single-drug and combination treatments. Under both conditions, the mutator allele swept to fixation through hitch-hiking with single-drug resistance, enabling subsequent resistance mutations to emerge. Ultimately, our results suggest that mutators may hinder the utility of combination therapy when mutators are present. Additionally, by raising the rates of genetic mutation, selection for multi-resistance may have the unwanted side-effect of increasing the potential to evolve resistance to future antibiotic treatments.

Evolutionary history and strength of selection determine the rate of antibiotic resistance adaptation

Bacterial adaptation to stressful environments often produces evolutionary constraints whereby increases in resistance are associated with reduced fitness in a different environment. The exploitation of this resistance-cost trade-off has been proposed as the basis of rational antimicrobial treatment strategies designed to limit the evolution of drug resistance in bacterial pathogens. Recent theoretical, laboratory, and clinical studies have shown that fluctuating selection can maintain drug efficacy and even restore drug susceptibility, but can also increase the rate of adaptation and promote cross-resistance to other antibiotics. In this paper, we combine mathematical modeling, experimental evolution, and whole-genome sequencing to follow evolutionary trajectories towards β-lactam resistance under fluctuating selective conditions. Our experimental model system consists of eight populations of Escherichia coli K12 evolving in parallel to a serial dilution protocol designed to dynamically control the strength of selection for resistance. We implemented adaptive ramps with mild and strong selection, resulting in evolved populations with similar levels of resistance, but with different evolutionary dynamics and diverging genotypic profiles. We found that mutations that emerged under strong selection are unstable in the absence of selection, in contrast to resistance mutations previously selected in the mild selection regime that were stably maintained in drug-free environments and positively selected for when antibiotics were reintroduced. Altogether, our population dynamics model and the phenotypic and genomic analysis of the evolved populations show that the rate of resistance adaptation is contingent upon the strength of selection, but also on evolutionary constraints imposed by prior drug exposures.

Revisiting Antibiotic Resistance: Mechanistic Foundations to Evolutionary Outlook

Antibiotics are the pivotal pillar of contemporary healthcare and have contributed towards its advancement over the decades. Antibiotic resistance emerged as a critical warning to public wellbeing because of unsuccessful management efforts. Resistance is a natural adaptive tool that offers selection pressure to bacteria, and hence cannot be stopped entirely but rather be slowed down. Antibiotic resistance mutations mostly diminish bacterial reproductive fitness in an environment without antibiotics; however, a fraction of resistant populations 'accidentally' emerge as the fittest and thrive in a specific environmental condition, thus favouring the origin of a successful resistant clone. Therefore, despite the time-to-time amendment of treatment regimens, antibiotic resistance has evolved relentlessly. According to the World Health Organization (WHO), we are rapidly approaching a 'post-antibiotic' era. The knowledge gap about antibiotic resistance and room for progress is evident and unified combating strategies to mitigate the inadvertent trends of resistance seem to be lacking. Hence, a comprehensive understanding of the genetic and evolutionary foundations of antibiotic resistance will be efficacious to implement policies to force-stop the emergence of resistant bacteria and treat already emerged ones. Prediction of possible evolutionary lineages of resistant bacteria could offer an unswerving impact in precision medicine. In this review, we will discuss the key molecular mechanisms of resistance development in clinical settings and their spontaneous evolution.

Evolutionary Dynamics of Asexual Hypermutators Adapting to a Novel Environment

How microbes adapt to a novel environment is a central question in evolutionary biology. Although adaptive evolution must be fueled by beneficial mutations, whether higher mutation rates facilitate the rate of adaptive evolution remains unclear. To address this question, we cultured Escherichia coli hypermutating populations, in which a defective methyl-directed mismatch repair pathway causes a 140-fold increase in single-nucleotide mutation rates. In parallel with wild-type E. coli, populations were cultured in tubes containing Luria-Bertani broth, a complex medium known to promote the evolution of subpopulation structure. After 900 days of evolution, in three transfer schemes with different population-size bottlenecks, hypermutators always exhibited similar levels of improved fitness as controls. Fluctuation tests revealed that the mutation rates of hypermutator lines converged evolutionarily on those of wild-type populations, which may have contributed to the absence of fitness differences. Further genome-sequence analysis revealed that, although hypermutator populations have higher rates of genomic evolution, this largely reflects strong genetic linkage. Despite these linkage effects, the evolved population exhibits parallelism in fixed mutations, including those potentially related to biofilm formation, transcription regulation, and mutation-rate evolution. Together, these results are generally inconsistent with a hypothesized positive relationship between the mutation rate and the adaptive speed of evolution, and provide insight into how clonal adaptation occurs in novel environments.

Genomic basis of parallel adaptation varies with divergence in Arabidopsis and its relatives

Parallel adaptation provides valuable insight into the predictability of evolutionary change through replicated natural experiments. A steadily increasing number of studies have demonstrated genomic parallelism, yet the magnitude of this parallelism varies depending on whether populations, species, or genera are compared. This led us to hypothesize that the magnitude of genomic parallelism scales with genetic divergence between lineages, but whether this is the case and the underlying evolutionary processes remain unknown. Here, we resequenced seven parallel lineages of two Arabidopsis species, which repeatedly adapted to challenging alpine environments. By combining genome-wide divergence scans with model-based approaches, we detected a suite of 151 genes that show parallel signatures of positive selection associated with alpine colonization, involved in response to cold, high radiation, short season, herbivores, and pathogens. We complemented these parallel candidates with published gene lists from five additional alpine Brassicaceae and tested our hypothesis on a broad scale spanning ∼0.02 to 18 My of divergence. Indeed, we found quantitatively variable genomic parallelism whose extent significantly decreased with increasing divergence between the compared lineages. We further modeled parallel evolution over the Arabidopsis candidate genes and showed that a decreasing probability of repeated selection on the same standing or introgressed alleles drives the observed pattern of divergence-dependent parallelism. We therefore conclude that genetic divergence between populations, species, and genera, affecting the pool of shared variants, is an important factor in the predictability of genome evolution.

Ecology and molecular targets of hypermutation in the global microbiome

Changes in the sequence of an organism's genome, i.e., mutations, are the raw material of evolution. The frequency and location of mutations can be constrained by specific molecular mechanisms, such as diversity-generating retroelements (DGRs). DGRs have been characterized from cultivated bacteria and bacteriophages, and perform error-prone reverse transcription leading to mutations being introduced in specific target genes. DGR loci were also identified in several metagenomes, but the ecological roles and evolutionary drivers of these DGRs remain poorly understood. Here, we analyze a dataset of >30,000 DGRs from public metagenomes, establish six major lineages of DGRs including three primarily encoded by phages and seemingly used to diversify host attachment proteins, and demonstrate that DGRs are broadly active and responsible for >10% of all amino acid changes in some organisms. Overall, these results highlight the constraints under which DGRs evolve, and elucidate several distinct roles these elements play in natural communities.

Population Bottlenecks Strongly Affect the Evolutionary Dynamics of Antibiotic Persistence

Bacterial persistence is a potential cause of antibiotic therapy failure. Antibiotic-tolerant persisters originate from phenotypic differentiation within a susceptible population, occurring with a frequency that can be altered by mutations. Recent studies have proven that persistence is a highly evolvable trait and, consequently, an important evolutionary strategy of bacterial populations to adapt to high-dose antibiotic therapy. Yet, the factors that govern the evolutionary dynamics of persistence are currently poorly understood. Theoretical studies predict far-reaching effects of bottlenecking on the evolutionary adaption of bacterial populations, but these effects have never been investigated in the context of persistence. Bottlenecking events are frequently encountered by infecting pathogens during host-to-host transmission and antibiotic treatment. In this study, we used a combination of experimental evolution and barcoded knockout libraries to examine how population bottlenecking affects the evolutionary dynamics of persistence. In accordance with existing hypotheses, small bottlenecks were found to restrict the adaptive potential of populations and result in more heterogeneous evolutionary outcomes. Evolutionary trajectories followed in small-bottlenecking regimes additionally suggest that the fitness landscape associated with persistence has a rugged topography, with distinct trajectories toward increased persistence that are accessible to evolving populations. Furthermore, sequencing data of evolved populations and knockout libraries after selection reveal various genes that are potentially involved in persistence, including previously known as well as novel targets. Together, our results do not only provide experimental evidence for evolutionary theories, but also contribute to a better understanding of the environmental and genetic factors that guide bacterial adaptation to antibiotic treatment.

Evolution of Pseudomonas aeruginosa toward higher fitness under standard laboratory conditions

Identifying genetic factors that contribute to the evolution of adaptive phenotypes in pathogenic bacteria is key to understanding the establishment of infectious diseases. In this study, we performed mutation accumulation experiments to record the frequency of mutations and their effect on fitness in hypermutator strains of the environmental bacterium Pseudomonas aeruginosa in comparison to the host-niche-adapted Salmonella enterica. We demonstrate that P. aeruginosa, but not S. enterica, hypermutators evolve toward higher fitness under planktonic conditions. Adaptation to increased growth performance was accompanied by a reversible perturbing of the local genetic context of membrane and cell wall biosynthesis genes. Furthermore, we observed a fine-tuning of complex regulatory circuits involving multiple di-guanylate modulating enzymes that regulate the transition between fast growing planktonic and sessile biofilm-associated lifestyles. The redundancy and local specificity of the di-guanylate signaling pathways seem to allow a convergent shift toward increased growth performance across niche-adapted clonal P. aeruginosa lineages, which is accompanied by a pronounced heterogeneity of their motility, virulence, and biofilm phenotypes.

Evolutionary Rescue of an Environmental Pseudomonas otitidis in Response to Anthropogenic Perturbation

Anthropogenic perturbations introduce novel selective pressures to natural environments, impacting the genomic variability of organisms and thus altering the evolutionary trajectory of populations. Water overexploitation for agricultural purposes and defective policies in Cuatro Cienegas, Coahuila, Mexico, have strongly impacted its water reservoir, pushing entire hydrological systems to the brink of extinction along with their native populations. Here, we studied the effects of continuous water overexploitation on an environmental aquatic lineage of Pseudomonas otitidis over a 13-year period which encompasses three desiccation events. By comparing the genomes of a population sample from 2003 (original state) and 2015 (perturbed state), we analyzed the demographic history and evolutionary response to perturbation of this lineage. Through coalescent simulations, we obtained a demographic model of contraction-expansion-contraction which points to the occurrence of an evolutionary rescue event. Loss of genomic and nucleotide variation alongside an increment in mean and variance of Tajima’s D, characteristic of sudden population expansions, support this observation. In addition, a significant increase in recombination rate (R/θ) was observed, pointing to horizontal gene transfer playing a role in population recovery. Furthermore, the gain of phosphorylation, DNA recombination, small-molecule metabolism and transport and loss of biosynthetic and regulatory genes suggest a functional shift in response to the environmental perturbation. Despite subsequent sampling events in the studied site, no pseudomonad was found until the lagoon completely dried in 2017. We speculate about the causes of P. otitidis final decline or possible extinction. Overall our results are evidence of adaptive responses at the genomic level of bacterial populations in a heavily exploited aquifer.

Bottleneck size and selection level reproducibly impact evolution of antibiotic resistance

During antibiotic treatment, the evolution of bacterial pathogens is fundamentally affected by bottlenecks and varying selection levels imposed by the drugs. Bottlenecks-that is, reductions in bacterial population size-lead to an increased influence of random effects (genetic drift) during bacterial evolution, and varying antibiotic concentrations during treatment may favour distinct resistance variants. Both aspects influence the process of bacterial evolution during antibiotic therapy and thereby treatment outcome. Surprisingly, the joint influence of these interconnected factors on the evolution of antibiotic resistance remains largely unexplored. Here we combine evolution experiments with genomic and genetic analyses to demonstrate that bottleneck size and antibiotic-induced selection reproducibly impact the evolutionary path to resistance in pathogenic Pseudomonas aeruginosa, one of the most problematic opportunistic human pathogens. Resistance is favoured-expectedly-under high antibiotic selection and weak bottlenecks, but-unexpectedly-also under low antibiotic selection and severe bottlenecks. The latter is likely to result from a reduced probability of losing favourable variants through drift under weak selection. Moreover, the absence of high resistance under low selection and weak bottlenecks is caused by the spread of low-resistance variants with high competitive fitness under these conditions. We conclude that bottlenecks, in combination with drug-induced selection, are currently neglected key determinants of pathogen evolution and outcome of antibiotic treatment.

Gene expression noise can promote the fixation of beneficial mutations in fluctuating environments

Nongenetic phenotypic variation can either speed up or slow down adaptive evolution. We show that it can speed up evolution in environments where available carbon and energy sources change over time. To this end, we use an experimentally validated model of Escherichia coli growth on two alternative carbon sources, glucose and acetate. On the superior carbon source (glucose), all cells achieve high growth rates, while on the inferior carbon source (acetate) only a small fraction of the population manages to initiate growth. Consequently, populations experience a bottleneck when the environment changes from the superior to the inferior carbon source. Growth on the inferior carbon source depends on a circuit under the control of a transcription factor that is repressed in the presence of the superior carbon source. We show that noise in the expression of this transcription factor can increase the probability that cells start growing on the inferior carbon source. In doing so, it can decrease the severity of the bottleneck and increase mean population fitness whenever this fitness is low. A modest amount of noise can also enhance the fitness effects of a beneficial allele that increases the fraction of a population initiating growth on acetate. Additionally, noise can protect this allele from extinction, accelerate its spread, and increase its likelihood of going to fixation. Central to the adaptation-enhancing principle we identify is the ability of noise to mitigate population bottlenecks, particularly in environments that fluctuate periodically. Because such bottlenecks are frequent in fluctuating environments, and because periodically fluctuating environments themselves are common, this principle may apply to a broad range of environments and organisms.

Experimental evolution reveals nitrate tolerance mechanisms in Desulfovibrio vulgaris

Elevated nitrate in the environment inhibits sulfate reduction by important microorganisms of sulfate-reducing bacteria (SRB). Several SRB may respire nitrate to survive under elevated nitrate, but how SRB that lack nitrate reductase survive to elevated nitrate remains elusive. To understand nitrate adaptation mechanisms, we evolved 12 populations of a model SRB (i.e., Desulfovibrio vulgaris Hildenborough, DvH) under elevated NaNO₃ for 1000 generations, analyzed growth and acquired mutations, and linked their genotypes with phenotypes. Nitrate-evolved (EN) populations significantly (p < 0.05) increased nitrate tolerance, and whole-genome resequencing identified 119 new mutations in 44 genes of 12 EN populations, among which six functional gene groups were discovered with high mutation frequencies at the population level. We observed a high frequency of nonsense or frameshift mutations in nitrosative stress response genes (NSR: DVU2543, DVU2547, and DVU2548), nitrogen regulatory protein C family genes (NRC: DVU2394-2396, DVU2402, and DVU2405), and nitrate cluster (DVU0246-0249 and DVU0251). Mutagenesis analysis confirmed that loss-of-functions of NRC and NSR increased nitrate tolerance. Also, functional gene groups involved in fatty acid synthesis, iron regulation, and two-component system (LytR/LytS) known to be responsive to multiple stresses, had a high frequency of missense mutations. Mutations in those gene groups could increase nitrate tolerance through regulating energy metabolism, barring entry of nitrate into cells, altering cell membrane characteristics, or conferring growth advantages at the stationary phase. This study advances our understanding of nitrate tolerance mechanisms and has important implications for linking genotypes with phenotypes in DvH.

Efflux pump activity potentiates the evolution of antibiotic resistance across S. aureus isolates

The rise of antibiotic resistance in many bacterial pathogens has been driven by the spread of a few successful strains, suggesting that some bacteria are genetically pre-disposed to evolving resistance. Here, we test this hypothesis by challenging a diverse set of 222 isolates of Staphylococcus aureus with the antibiotic ciprofloxacin in a large-scale evolution experiment. We find that a single efflux pump, norA, causes widespread variation in evolvability across isolates. Elevated norA expression potentiates evolution by increasing the fitness benefit provided by DNA topoisomerase mutations under ciprofloxacin treatment. Amplification of norA provides a further mechanism of rapid evolution in isolates from the CC398 lineage. Crucially, chemical inhibition of NorA effectively prevents the evolution of resistance in all isolates. Our study shows that pre-existing genetic diversity plays a key role in shaping resistance evolution, and it may be possible to predict which strains are likely to evolve resistance and to optimize inhibitor use to prevent this outcome.

Population Bottlenecks Strongly Influence the Evolutionary Trajectory to Fluoroquinolone Resistance in Escherichia coli

Experimental evolution is a powerful tool to study genetic trajectories to antibiotic resistance under selection. A confounding factor is that outcomes may be heavily influenced by the choice of experimental parameters. For practical purposes (minimizing culture volumes), most experimental evolution studies with bacteria use transmission bottleneck sizes of 5 × 106 cfu. We currently have a poor understanding of how the choice of transmission bottleneck size affects the accumulation of deleterious versus high-fitness mutations when resistance requires multiple mutations, and how this relates outcome to clinical resistance. We addressed this using experimental evolution of resistance to ciprofloxacin in Escherichia coli. Populations were passaged with three different transmission bottlenecks, including single cell (to maximize genetic drift) and bottlenecks spanning the reciprocal of the frequency of drug target mutations (108 and 1010). The 1010 bottlenecks selected overwhelmingly mutations in drug target genes, and the resulting genotypes corresponded closely to those found in resistant clinical isolates. In contrast, both the 108 and single-cell bottlenecks selected mutations in three different gene classes: 1) drug targets, 2) efflux pump repressors, and 3) transcription-translation genes, including many mutations with low fitness. Accordingly, bottlenecks smaller than the average nucleotide substitution rate significantly altered the experimental outcome away from genotypes observed in resistant clinical isolates. These data could be applied in designing experimental evolution studies to increase their predictive power and to explore the interplay between different environmental conditions, where transmission bottlenecks might vary, and resulting evolutionary trajectories.

Larger bacterial populations evolve heavier fitness trade-offs and undergo greater ecological specialization

Evolutionary studies over the last several decades have invoked fitness trade-offs to explain why species prefer some environments to others. However, the effects of population size on trade-offs and ecological specialization remain largely unknown. To complicate matters, trade-offs themselves have been visualized in multiple ways in the literature. Thus, it is not clear how population size can affect the various aspects of trade-offs. To address these issues, we conducted experimental evolution with Escherichia coli populations of two different sizes in two nutritionally limited environments, and studied fitness trade-offs from three different perspectives. We found that larger populations evolved greater fitness trade-offs, regardless of how trade-offs are conceptualized. Moreover, although larger populations adapted more to their selection conditions, they also became more maladapted to other environments, ultimately paying heavier costs of adaptation. To enhance the generalizability of our results, we further investigated the evolution of ecological specialization across six different environmental pairs, and found that larger populations specialized more frequently and evolved consistently steeper reaction norms of fitness. This is the first study to demonstrate a relationship between population size and fitness trade-offs, and the results are important in understanding the population genetics of ecological specialization and vulnerability to environmental changes.

The Effect of Population Bottleneck Size and Selective Regime on Genetic Diversity and Evolvability in Bacteria

Population bottlenecks leading to a drastic reduction of the population size are common in the evolutionary dynamics of natural populations; their occurrence is known to have implications for genome evolution due to genetic drift, the consequent reduction in genetic diversity, and the rate of adaptation. Nevertheless, an empirical characterization of the effect of population bottleneck size on evolutionary dynamics of bacteria is currently lacking. In this study, we show that selective conditions have a stronger effect on the evolutionary history of bacteria in comparison to population bottlenecks. We evolved Escherichia coli populations under three different population bottleneck sizes (small, medium, and large) in two temperature regimes (37 °C and 20 °C). We find a high genetic diversity in the large in comparison to the small bottleneck size. Nonetheless, the cold temperature led to reduced genetic diversity regardless the bottleneck size; hence, the temperature has a stronger effect on the genetic diversity in comparison to the bottleneck size. A comparison of the fitness gain among the evolved populations reveals a similar pattern where the temperature has a significant effect on the fitness. Our study demonstrates that population bottlenecks are an important determinant of bacterial evolvability; their consequences depend on the selective conditions and are best understood via their effect on the standing genetic variation.

Disparate responses to salinity across species and organizational levels in anchialine shrimps

Environmentally induced plasticity in gene expression is one of the underlying mechanisms of adaptation to habitats with variable environments. For example, euryhaline crustaceans show predictable changes in the expression of ion-transporter genes during salinity transfers, although studies have typically been limited to specific genes, taxa and ecosystems of interest. Here, we investigated responses to salinity change at multiple organizational levels in five species of shrimp representing at least three independent invasions of the anchialine ecosystem, defined as habitats with marine and freshwater influences with spatial and temporal fluctuations in salinity. Although all five species were generally strong osmoregulators, salinity-induced changes in gill physiology and gene expression were highly species specific. While some species exhibited patterns similar to those of previously studied euryhaline crustaceans, instances of distinct and atypical patterns were recovered from closely related species. Species-specific patterns were found when examining: (1) numbers and identities of differentially expressed genes, (2) salinity-induced expression of genes predicted a priori to play a role in osmoregulation, and (3) salinity-induced expression of orthologs shared among all species. Notably, ion transport genes were unchanged in the atyid Halocaridina rubra while genes normally associated with vision and light perception were among those most highly upregulated. Potential reasons for species-specific patterns are discussed, including variation among anchialine habitats in salinity regimes and divergent evolution in anchialine taxa. Underexplored mechanisms of osmoregulation in crustaceans revealed here by the application of transcriptomic approaches to ecologically and taxonomically understudied systems are also explored.

Cryptic genetic variation accelerates evolution by opening access to diverse adaptive peaks

Cryptic genetic variation can facilitate adaptation in evolving populations. To elucidate the underlying genetic mechanisms, we used directed evolution in Escherichia coli to accumulate variation in populations of yellow fluorescent proteins and then evolved these proteins toward the new phenotype of green fluorescence. Populations with cryptic variation evolved adaptive genotypes with greater diversity and higher fitness than populations without cryptic variation, which converged on similar genotypes. Populations with cryptic variation accumulated neutral or deleterious mutations that break the constraints on the order in which adaptive mutations arise. In doing so, cryptic variation opens paths to adaptive genotypes, creates historical contingency, and reduces the predictability of evolution by allowing different replicate populations to climb different adaptive peaks and explore otherwise-inaccessible regions of an adaptive landscape.

What can be learned by scanning the genome for molecular convergence in wild populations?

Convergent evolution, where independent lineages evolve similar phenotypes in response to similar challenges, can provide valuable insight into how selection operates and the limitations it encounters. However, it has only recently become possible to explore how convergent evolution is reflected at the genomic level. The overlapping outlier approach (OOA), where genome scans of multiple independent lineages are used to find outliers that overlap and therefore identify convergently evolving loci, is becoming popular. Here, we present a quantitative analysis of 34 studies that used this approach across many sampling designs, taxa, and sampling intensities. We found that OOA studies with increased biological sampling power within replicates have increased likelihood of finding overlapping, "convergent" signals of adaptation between them. When identifying convergent loci as overlapping outliers, it is tempting to assume that any false-positive outliers derived from individual scans will fail to overlap across replicates, but this cannot be guaranteed. We highlight how population demographics and genomic context can contribute toward both true convergence and false positives in OOA studies. We finish with an exploration of emerging methods that couple genome scans with phenotype and environmental measures, leveraging added information from genome data to more directly test hypotheses of the likelihood of convergent evolution.

Mutational Evolution of Pseudomonas aeruginosa Resistance to Ribosome-Targeting Antibiotics

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

Environmental pleiotropy and demographic history direct adaptation under antibiotic selection

Evolutionary rescue following environmental change requires mutations permitting population growth in the new environment. If change is severe enough to prevent most of the population reproducing, rescue becomes reliant on mutations already present. If change is sustained, the fitness effects in both environments, and how they are associated—termed ‘environmental pleiotropy’—may determine which alleles are ultimately favoured. A population’s demographic history—its size over time—influences the variation present. Although demographic history is known to affect the probability of evolutionary rescue, how it interacts with environmental pleiotropy during severe and sustained environmental change remains unexplored. Here, we demonstrate how these factors interact during antibiotic resistance evolution, a key example of evolutionary rescue fuelled by pre-existing mutations with pleiotropic fitness effects. We combine published data with novel simulations to characterise environmental pleiotropy and its effects on resistance evolution under different demographic histories. Comparisons among resistance alleles typically revealed no correlation for fitness—i.e., neutral pleiotropy—above and below the sensitive strain’s minimum inhibitory concentration. Resistance allele frequency following experimental evolution showed opposing correlations with their fitness effects in the presence and absence of antibiotic. Simulations demonstrated that effects of environmental pleiotropy on allele frequencies depended on demographic history. At the population level, the major influence of environmental pleiotropy was on mean fitness, rather than the probability of evolutionary rescue or diversity. Our work suggests that determining both environmental pleiotropy and demographic history is critical for predicting resistance evolution, and we discuss the practicalities of this during in vivo evolution.

Effects of Transmission Bottlenecks on the Diversity of Influenza A Virus

We investigate the fate of de novo mutations that occur during the in-host replication of a pathogenic virus, predicting the probability that such mutations are passed on during disease transmission to a new host. Using influenza A virus as a model organism, we develop a life-history model of the within-host dynamics of the infection, deriving a multitype branching process with a coupled deterministic model to capture the population of available target cells. We quantify the fate of neutral mutations and mutations affecting five life-history traits: clearance, attachment, budding, cell death, and eclipse phase timing. Despite the severity of disease transmission bottlenecks, our results suggest that in a single transmission event, several mutations that appeared de novo in the donor are likely to be transmitted to the recipient. Even in the absence of a selective advantage for these mutations, the sustained growth phase inherent in each disease transmission cycle generates genetic diversity that is not eliminated during the transmission bottleneck.

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.

Adaptations of an RNA virus to increasing thermal stress

Environments can change in incremental fashions, where a shift from one state to another occurs over multiple organismal generations. The rate of the environmental change is expected to influence how and how well populations adapt to the final environmental state. We used a model system, the lytic RNA bacteriophage Φ6, to investigate this question empirically. We evolved viruses for thermostability by exposing them to heat shocks that increased to a maximum temperature at different rates. We observed increases in the ability of many heat-shocked populations to survive high temperature heat shocks. On their first exposure to the highest temperature, populations that experienced a gradual increase in temperature had higher average survival than populations that experienced a rapid temperature increase. However, at the end of the experiment, neither the survival of populations at the highest temperature nor the number of mutations per population varied significantly according to the rate of thermal change. We also evaluated mutations from the endpoint populations for their effects on viral thermostability and growth. As expected, some mutations did increase viral thermostability. However, other mutations decreased thermostability but increased growth rate, suggesting that benefits of an increased replication rate may have sometimes outweighed the benefits of enhanced thermostability. Our study highlights the importance of considering the effects of multiple selective pressures, even in environments where a single factor changes.

Adaptive benefits from small mutation supplies in an antibiotic resistance enzyme

Populations with large mutation supplies adapt via the "greedy" substitution of the fittest genotype available, leading to fast and repeatable short-term responses. At longer time scales, smaller mutation supplies may in theory lead to larger improvements when distant high-fitness genotypes more readily evolve from lower-fitness intermediates. Here we test for long-term adaptive benefits from small mutation supplies using in vitro evolution of an antibiotic-degrading enzyme in the presence of a novel antibiotic. Consistent with predictions, large mutant libraries cause rapid initial adaptation via the substitution of cohorts of mutations, but show later deceleration and convergence. Smaller libraries show on average smaller initial, but also more variable, improvements, with two lines yielding alleles with exceptionally high resistance levels. These two alleles share three mutations with the large-library alleles, which are known from previous work, but also have unique mutations. Replay evolution experiments and analyses of the adaptive landscape of the enzyme suggest that the benefit resulted from a combination of avoiding mutational cohorts leading to local peaks and chance. Our results demonstrate adaptive benefits from limited mutation supplies on a rugged fitness landscape, which has implications for artificial selection protocols in biotechnology and argues for a better understanding of mutation supplies in clinical settings.

Mutation supply and the repeatability of selection for antibiotic resistance

Whether evolution can be predicted is a key question in evolutionary biology. Here we set out to better understand the repeatability of evolution, which is a necessary condition for predictability. We explored experimentally the effect of mutation supply and the strength of selective pressure on the repeatability of selection from standing genetic variation. Different sizes of mutant libraries of antibiotic resistance gene TEM-1 β-lactamase in Escherichia coli, generated by error-prone PCR, were subjected to different antibiotic concentrations. We determined whether populations went extinct or survived, and sequenced the TEM gene of the surviving populations. The distribution of mutations per allele in our mutant libraries followed a Poisson distribution. Extinction patterns could be explained by a simple stochastic model that assumed the sampling of beneficial mutations was key for survival. In most surviving populations, alleles containing at least one known large-effect beneficial mutation were present. These genotype data also support a model which only invokes sampling effects to describe the occurrence of alleles containing large-effect driver mutations. Hence, evolution is largely predictable given cursory knowledge of mutational fitness effects, the mutation rate and population size. There were no clear trends in the repeatability of selected mutants when we considered all mutations present. However, when only known large-effect mutations were considered, the outcome of selection is less repeatable for large libraries, in contrast to expectations. We show experimentally that alleles carrying multiple mutations selected from large libraries confer higher resistance levels relative to alleles with only a known large-effect mutation, suggesting that the scarcity of high-resistance alleles carrying multiple mutations may contribute to the decrease in repeatability at large library sizes.