Testing the role of genetic background in parallel evolution using the comparative experimental evolution of antibiotic resistance

The distribution of beneficial mutational effects between two sister yeast species poorly explains natural outcomes of vineyard adaptation

Domesticated strains of Saccharomyces cerevisiae have adapted to resist copper and sulfite, two chemical stressors commonly used in winemaking. S. paradoxus, has not adapted to these chemicals despite being consistently present in sympatry with S. cerevisiae in vineyards. This contrast represents a case of apparent evolutionary constraints favoring greater adaptive capacity in S. cerevisiae. In this study, we used a comparative mutagenesis approach to test whether S. paradoxus is mutationally constrained with respect to acquiring greater copper and sulfite resistance. For both species, we assayed the rate, effect size, and pleiotropic costs of resistance mutations and sequenced a subset of 150 mutants isolated from our screen. We found that the distributions of mutational effects displayed by the two species were very similar and poorly explained the natural pattern. We also found that chromosome VIII aneuploidy and loss of function mutations in PMA1 confer copper resistance in both species, whereas loss of function mutations in REG1 were only a viable route to copper resistance in S. cerevisiae. We also observed a single de novo duplication of the CUP1 gene in S. paradoxus but none in S. cerevisiae. For sulfite, loss of function mutations in RTS1 and KSP1 confer resistance in both species, but mutations in RTS1 have larger average effects in S. paradoxus. Our results show that even when the distributions of mutational effects are largely similar, species can differ in the adaptive paths available to them. They also demonstrate that assays of the distribution of mutational effects may lack predictive insight concerning adaptive outcomes.

Rolling the evolutionary dice: Neisseria commensals as proxies for elucidating the underpinnings of antibiotic resistance mechanisms and evolution in human pathogens

Species within the genus Neisseria are adept at sharing adaptive allelic variation, with commensal species repeatedly transferring resistance to their pathogenic relative Neisseria gonorrhoeae. However, resistance in commensals is infrequently characterized, limiting our ability to predict novel and potentially transferable resistance mechanisms that ultimately may become important clinically. Unique evolutionary starting places of each Neisseria species will have distinct genomic backgrounds, which may ultimately control the fate of evolving populations in response to selection as epistatic and additive interactions coerce lineages along divergent evolutionary trajectories. Alternatively, similar genetic content present across species due to shared ancestry may constrain existing adaptive solutions. Thus, identifying the paths to resistance across commensals may aid in characterizing the Neisseria resistome-or the reservoir of alleles within the genus as well as its depth. Here, we use in vitro evolution of four commensal species to investigate the potential and repeatability of resistance evolution to two antimicrobials, the macrolide azithromycin and the β-lactam penicillin. After 20 days of selection, commensals evolved resistance to penicillin and azithromycin in 11/16 and 12/16 cases, respectively. Almost all cases of resistance emergence converged on mutations within ribosomal components or the mtrRCDE efflux pump for azithromycin-based selection and mtrRCDE, penA, and rpoB for penicillin selection, thus supporting constrained adaptive solutions despite divergent evolutionary starting points across the genus for these particular drugs. Though drug-selected loci were limited, we do identify novel resistance-imparting mutations. Continuing to explore paths to resistance across different experimental conditions and genomic backgrounds, which could shunt evolution down alternative evolutionary trajectories, will ultimately flesh out the full Neisseria resistome.IMPORTANCENeisseria gonorrhoeae is a global threat to public health due to its rapid acquisition of antibiotic resistance to all first-line treatments. Recent work has documented that alleles acquired from close commensal relatives have played a large role in the emergence of resistance to macrolides and beta-lactams within gonococcal populations. However, commensals have been relatively underexplored for the resistance genotypes they may harbor. This leaves a gap in our understanding of resistance that could be rapidly acquired by the gonococcus through a known highway of horizontal gene exchange. Here, we characterize resistance mechanisms that can emerge in commensal Neisseria populations via in vitro selection to multiple antimicrobials and begin to define the number of paths to resistance. This study, and other similar works, may ultimately aid both surveillance efforts and clinical diagnostic development by nominating novel and conserved resistance mechanisms that may be at risk of rapid dissemination to pathogen populations.

Mutation bias and adaptation in bacteria

Genetic mutation, which provides the raw material for evolutionary adaptation, is largely a stochastic force. However, there is ample evidence showing that mutations can also exhibit strong biases, with some mutation types and certain genomic positions mutating more often than others. It is becoming increasingly clear that mutational bias can play a role in determining adaptive outcomes in bacteria in both the laboratory and the clinic. As such, understanding the causes and consequences of mutation bias can help microbiologists to anticipate and predict adaptive outcomes. In this review, we provide an overview of the mechanisms and features of the bacterial genome that cause mutational biases to occur. We then describe the environmental triggers that drive these mechanisms to be more potent and outline the adaptive scenarios where mutation bias can synergize with natural selection to define evolutionary outcomes. We conclude by describing how understanding mutagenic genomic features can help microbiologists predict areas sensitive to mutational bias, and finish by outlining future work that will help us achieve more accurate evolutionary forecasts.

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.

Rolling the evolutionary dice: Neisseria commensals as proxies for elucidating the underpinnings of antibiotic resistance mechanisms and evolution in human pathogens

Species within the genus Neisseria are especially adept at sharing adaptive allelic variation across species' boundaries, with commensal species repeatedly transferring resistance to their pathogenic relative N. gonorrhoeae. However, resistance in commensal Neisseria is infrequently characterized at both the phenotypic and genotypic levels, limiting our ability to predict novel and potentially transferable resistance mechanisms that ultimately may become important clinically. Unique evolutionary starting places of each Neisseria species will have distinct genomic backgrounds, which may ultimately control the fate of evolving populations in response to selection, as epistatic and additive interactions may coerce lineages along divergent evolutionary trajectories. However alternatively, similar genetic content present across species due to shared ancestry may constrain the adaptive solutions that exist. Thus, identifying the paths to resistance across commensals may aid in characterizing the Neisseria resistome - or the reservoir of alleles within the genus, as well as its depth. Here, we use in vitro evolution of four commensal species to investigate the potential for and repeatability of resistance evolution to two antimicrobials, the macrolide azithromycin and the β-lactam penicillin. After 20 days of selection, commensals evolved elevated minimum inhibitory concentrations (MICs) to penicillin and azithromycin in 11/16 and 12/16 cases respectively. Almost all cases of resistance emergence converged on mutations within ribosomal components or the mtrRCDE efflux pump for azithromycin-based selection, and mtrRCDE or penA for penicillin selection; thus, supporting constrained adaptive solutions despite divergent evolutionary starting points across the genus for these particular drugs. However, continuing to explore the paths to resistance across different experimental conditions and genomic backgrounds, which could shunt evolution down alternative evolutionary trajectories, will ultimately flesh out the full Neisseria resistome.

Genomic alterations involved in fluoroquinolone resistance development in Staphylococcus aureus

AIM

Fluoroquinolone (FQ) is a potent antibiotic class. However, resistance to this class emerges quickly which hinders its application. In this study, mechanisms leading to the emergence of multidrug-resistant (MDR) Staphylococcus aureus (S. aureus) strains under FQ exposure were investigated.

METHODOLOGY

S. aureus ATCC 29213 was serially exposed to ciprofloxacin (CIP), ofloxacin (OFL), or levofloxacin (LEV) at sub-minimum inhibitory concentrations (sub-MICs) for 12 days to obtain S. aureus -1 strains and antibiotic-free cultured for another 10 days to obtain S. aureus-2 strains. The whole genome (WGS) and target sequencing were applied to analyze genomic alterations; and RT-qPCR was used to access the expressions of efflux-related genes, alternative sigma factors, and genes involved in FQ resistance.

RESULTS

A strong and irreversible increase of MICs was observed in all applied FQs (32 to 128 times) in all S. aureus-1 and remained 16 to 32 times in all S. aureus-2. WGS indicated 10 noticeable mutations occurring in all FQ-exposed S. aureus including 2 insdel mutations in SACOL0573 and rimI; a synonymous mutation in hslO; and 7 missense mutations located in an untranslated region. GrlA, was found mutated (R570H) in all S. aureus-1 and -2. Genes encoding for efflux pumps and their regulator (norA, norB, norC, and mgrA); alternative sigma factors (sigB and sigS); acetyltransferase (rimI); methicillin resistance (fmtB); and hypothetical protein BJI72_0645 were overexpressed in FQ-exposed strains.

CONCLUSION

The emergence of MDR S. aureus was associated with the mutations in the FQ-target sequences and the overexpression of efflux pump systems and their regulators.

Trait drift in microalgae and applications for strain improvement

Microalgae are increasingly used to generate a wide range of commercial products, and there is growing evidence that microalgae-based products can be produced sustainably. However, industrial production of microalgal biomass is not as developed as other biomanufacturing platform technologies. In addition, results of bench-scale research often fail to translate to large-scale or mass production systems. This disconnect may result from trait drift and evolution occurring, through time, in response to unique drivers in each environment, such as cultivation regimes, weather, and pests. Moreover, outdoor and indoor cultivation of microalgae has the potential to impose negative selection pressures, which makes the maintenance of desired traits a challenge. In this context, this review sheds the light on our current understanding of trait drift and evolution in microalgae. We delineate the basics of phenotype plasticity and evolution, with a focus on how microalgae respond under various conditions. In addition, we review techniques that exploit phenotypic plasticity and evolution for strain improvement in view of industrial commercial applications, highlighting associated advantages and shortcomings. Finally, we suggest future research directions and recommendations to overcome unwanted trait drift and evolution in microalgae cultivation.

Detecting bacterial adaptation within individual microbiomes

The human microbiome harbours a large capacity for within-person adaptive mutations. Commensal bacterial strains can stably colonize a person for decades, and billions of mutations are generated daily within each person's microbiome. Adaptive mutations emerging during health might be driven by selective forces that vary across individuals, vary within an individual, or are completely novel to the human population. Mutations emerging within individual microbiomes might impact the immune system, the metabolism of nutrients or drugs, and the stability of the community to perturbations. Despite this potential, relatively little attention has been paid to the possibility of adaptive evolution within complex human-associated microbiomes. This review discusses the promise of studying within-microbiome adaptation, the conceptual and technical limitations that may have contributed to an underappreciation of adaptive de novo mutations occurring within microbiomes to date, and methods for detecting recent adaptive evolution. This article is part of a discussion meeting issue 'Genomic population structures of microbial pathogens'.

Pre-existing chromosomal polymorphisms in pathogenic E. coli potentiate the evolution of resistance to a last-resort antibiotic

Bacterial pathogens show high levels of chromosomal genetic diversity, but the influence of this diversity on the evolution of antibiotic resistance by plasmid acquisition remains unclear. Here, we address this problem in the context of colistin, a 'last line of defence' antibiotic. Using experimental evolution, we show that a plasmid carrying the MCR-1 colistin resistance gene dramatically increases the ability of Escherichia coli to evolve high-level colistin resistance by acquiring mutations in lpxC, an essential chromosomal gene involved in lipopolysaccharide biosynthesis. Crucially, lpxC mutations increase colistin resistance in the presence of the MCR-1 gene, but decrease the resistance of wild-type cells, revealing positive sign epistasis for antibiotic resistance between the chromosomal mutations and a mobile resistance gene. Analysis of public genomic datasets shows that lpxC polymorphisms are common in pathogenic E. coli, including those carrying MCR-1, highlighting the clinical relevance of this interaction. Importantly, lpxC diversity is high in pathogenic E. coli from regions with no history of MCR-1 acquisition, suggesting that pre-existing lpxC polymorphisms potentiated the evolution of high-level colistin resistance by MCR-1 acquisition. More broadly, these findings highlight the importance of standing genetic variation and plasmid/chromosomal interactions in the evolutionary dynamics of antibiotic resistance.

Evolved resistance to a novel cationic peptide antibiotic requires high mutation supply

Background and Objectives

A key strategy for resolving the antibiotic resistance crisis is the development of new drugs with antimicrobial properties. The engineered cationic antimicrobial peptide WLBU2 (also known as PLG0206) is a promising broad-spectrum antimicrobial compound that has completed Phase I clinical studies. It has activity against Gram-negative and Gram-positive bacteria including infections associated with biofilm. No definitive mechanisms of resistance to WLBU2 have been identified.

Methodology

Here, we used experimental evolution under different levels of mutation supply and whole genome sequencing (WGS) to detect the genetic pathways and probable mechanisms of resistance to this peptide. We propagated populations of wild-type and hypermutator Pseudomonas aeruginosa in the presence of WLBU2 and performed WGS of evolved populations and clones.

Results

Populations that survived WLBU2 treatment acquired a minimum of two mutations, making the acquisition of resistance more difficult than for most antibiotics, which can be tolerated by mutation of a single target. Major targets of resistance to WLBU2 included the orfN and pmrB genes, previously described to confer resistance to other cationic peptides. More surprisingly, mutations that increase aggregation such as the wsp pathway were also selected despite the ability of WLBU2 to kill cells growing in a biofilm.

Conclusions and implications

The results show how experimental evolution and WGS can identify genetic targets and actions of new antimicrobial compounds and predict pathways to resistance of new antibiotics in clinical practice.

Predicting Parallelism and Quantifying Divergence in Microbial Evolution Experiments

The degree to which independent populations subjected to identical environmental conditions evolve in similar ways is a fundamental question in evolution. To address this question, microbial populations are often experimentally passaged in a given environment and sequenced to examine the tendency for similar mutations to repeatedly arise. However, there remains the need to develop an appropriate statistical framework to identify genes that acquired more mutations in one environment than in another (i.e., divergent evolution), genes that serve as genetic candidates of adaptation. Here, we develop a mathematical model to evaluate evolutionary outcomes among replicate populations in the same environment (i.e., parallel evolution), which can then be used to identify genes that contribute to divergent evolution. Applying this approach to data sets from evolve-and-resequence experiments, we found that the distribution of mutation counts among genes can be predicted as an ensemble of independent Poisson random variables with zero free parameters. Building on this result, we propose that the degree of divergent evolution at a given gene between populations from two different environments can be modeled as the difference between two Poisson random variables, known as the Skellam distribution. We then propose and apply a statistical test to identify specific genes that contribute to divergent evolution. By focusing on predicting patterns among replicate populations in a given environment, we are able to identify an appropriate test for divergence between environments that is grounded in first principles.

IMPORTANCE There is currently no universally accepted framework for identifying genes that contribute to molecular divergence between microbial populations in different environments. To address this absence, we developed a null model to describe the distribution of mutation counts among genes. We find that divergent evolution within a given gene can be modeled as the absolute difference in the total number of mutations observed between two environments. This quantity is effectively captured by a probability distribution known as the Skellam distribution, providing an appropriate statistical test for researchers seeking to identify the set of genes that contribute to divergent evolution in microbial evolution experiments.

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

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

The roles of history, chance, and natural selection in the evolution of antibiotic resistance

History, chance, and selection are the fundamental factors that drive and constrain evolution. We designed evolution experiments to disentangle and quantify effects of these forces on the evolution of antibiotic resistance. Previously, we showed that selection of the pathogen Acinetobacter baumannii in both structured and unstructured environments containing the antibiotic ciprofloxacin produced distinct genotypes and phenotypes, with lower resistance in biofilms as well as collateral sensitivity to β-lactam drugs (Santos-Lopez et al., 2019). Here we study how this prior history influences subsequent evolution in new β-lactam antibiotics. Selection was imposed by increasing concentrations of ceftazidime and imipenem and chance differences arose as random mutations among replicate populations. The effects of history were reduced by increasingly strong selection in new drugs, but not erased, at times revealing important contingencies. A history of selection in structured environments constrained resistance to new drugs and led to frequent loss of resistance to the initial drug by genetic reversions and not compensatory mutations. This research demonstrates that despite strong selective pressures of antibiotics leading to genetic parallelism, history can etch potential vulnerabilities to orthogonal drugs.

Contrasting levels of genetic predictability in the evolution of resistance to major classes of fungicides

The evolution of resistance has been seen across all major classes of xenobiotics, including antimicrobial drugs and agricultural pesticides. This repeated emergence of resistance is a case of phenotypic parallel evolution, but often the parallelism extends to the molecular level too, with multiple species gaining the same mutation in response to the same chemical treatment. We review the degree of repeatability in target-site resistance mutations affecting different classes of site-specific agricultural fungicides used in crop protection, comparing the extent to which resistance in different pathogen species has evolved via the same or different mutations. For all major fungicide target sites, substantial levels of molecular parallel evolution can be seen, with at least one mutation recurring in over 50% of species. Target-site mutations appear to be most repeatable in cytochrome b, target site of quinone-outside inhibitor fungicides, and least predictable for CYP51, target site of the azoles. Intermediate levels of repeatability are seen for the MBC target site β-tubulin, and the SDHI target site succinate dehydrogenase. Repeatability may be lower where there are selective trade-offs between resistance and pleiotropic fitness penalties, or differing levels of cross-resistance across members of a fungicide class; or where single mutations confer only partial resistance, and epistatic interactions between multiple mutations result in a rugged fitness landscape. This affects the predictive power of in vitro mutation studies, and has practical implications for resistance monitoring strategies and diagnostic methods.

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.

Parallel Evolution of Tobramycin Resistance across Species and Environments

The rise of antimicrobial resistance is a leading medical threat, motivating efforts to forecast both its evolutionary dynamics and its genetic causes. Aminoglycosides are a major class of antibiotics that disrupt translation, but resistance may occur by a number of mechanisms. Here, we show the repeated evolution of resistance to the aminoglycoside tobramycin in both P. aeruginosa and A. baumannii via mutations in fusA1, encoding elongation factor G, and ptsP, encoding the nitrogen-specific phosphotransferase system. Laboratory evolution and whole-population genome sequencing were used to identify these targets, but mutations at identical amino acid positions were also found in published genomes of diverse bacterial species and clinical isolates. We also identified other resistance mechanisms associated with growth in biofilms that likely interfere with drug binding or uptake. Characterizing the evolution of multiple species in the presence of antibiotics can identify new, repeatable causes of resistance that may be predicted and counteracted by alternative treatment.

Different species exposed to a common stress may adapt by mutations in shared pathways or in unique systems, depending on how past environments have molded their genomes. Understanding how diverse bacterial pathogens evolve in response to an antimicrobial treatment is a pressing example of this problem, where discovery of molecular parallelism could lead to clinically useful predictions. Evolution experiments with pathogens in environments containing antibiotics, combined with periodic whole-population genome sequencing, can be used to identify many contending routes to antimicrobial resistance. We separately propagated two clinically relevant Gram-negative pathogens, Pseudomonas aeruginosa and Acinetobacter baumannii, in increasing concentrations of tobramycin in two different environments each: planktonic and biofilm. Independently of the pathogen, the populations adapted to tobramycin selection by parallel evolution of mutations in fusA1, encoding elongation factor G, and ptsP, encoding phosphoenolpyruvate phosphotransferase. As neither gene is a direct target of this aminoglycoside, mutations to either are unexpected and underreported causes of resistance. Additionally, both species acquired antibiotic resistance-associated mutations that were more prevalent in the biofilm lifestyle than in the planktonic lifestyle; these mutations were in electron transport chain components in A. baumannii and lipopolysaccharide biosynthesis enzymes in P. aeruginosa populations. Using existing databases, we discovered site-specific parallelism of fusA1 mutations that extends across bacterial phyla and clinical isolates. This study suggests that strong selective pressures, such as antibiotic treatment, may result in high levels of predictability in molecular targets of evolution, despite differences between organisms’ genetic backgrounds and environments.

The Genetic Background Modulates the Evolution of Fluoroquinolone-Resistance in Mycobacterium tuberculosis

Fluoroquinolones (FQ) form the backbone in experimental treatment regimens against drug-susceptible tuberculosis. However, little is known on whether the genetic variation present in natural populations of Mycobacterium tuberculosis (Mtb) affects the evolution of FQ-resistance (FQ-R). To investigate this question, we used nine genetically distinct drug-susceptible clinical isolates of Mtb and measured their frequency of resistance to the FQ ofloxacin (OFX) in vitro. We found that the Mtb genetic background led to differences in the frequency of OFX-resistance (OFX-R) that spanned two orders of magnitude and substantially modulated the observed mutational profiles for OFX-R. Further, in vitro assays showed that the genetic background also influenced the minimum inhibitory concentration and the fitness effect conferred by a given OFX-R mutation. To test the clinical relevance of our in vitro work, we surveyed the mutational profile for FQ-R in publicly available genomic sequences from clinical Mtb isolates, and found substantial Mtb lineage-dependent variability. Comparison of the clinical and the in vitro mutational profiles for FQ-R showed that 51% and 39% of the variability in the clinical frequency of FQ-R gyrA mutation events in Lineage 2 and Lineage 4 strains, respectively, can be attributed to how Mtb evolves FQ-R in vitro. As the Mtb genetic background strongly influenced the evolution of FQ-R in vitro, we conclude that the genetic background of Mtb also impacts the evolution of FQ-R in the clinic.

Experimental evolution of gallium resistance in Escherichia coli

Background and Objectives

Metallic antimicrobial materials are of growing interest due to their potential to control pathogenic and multidrug-resistant bacteria. Yet we do not know if utilizing these materials can lead to genetic adaptations that produce even more dangerous bacterial varieties.

Methodology

Here we utilize experimental evolution to produce strains of Escherichia coli K-12 MG1655 resistant to, the iron analog, gallium nitrate (Ga(NO₃)₃). Whole genome sequencing was utilized to determine genomic changes associated with gallium resistance. Computational modeling was utilized to propose potential molecular mechanisms of resistance.

Results

By day 10 of evolution, increased gallium resistance was evident in populations cultured in medium containing a sublethal concentration of gallium. Furthermore, these populations showed increased resistance to ionic silver and iron (III), but not iron (II) and no increase in traditional antibiotic resistance compared with controls and the ancestral strain. In contrast, the control populations showed increased resistance to rifampicin relative to the gallium-resistant and ancestral population. Genomic analysis identified hard selective sweeps of mutations in several genes in the gallium (III)-resistant lines including: fecA (iron citrate outer membrane transporter), insl1 (IS30 tranposase) one intergenic mutations arsC →/→ yhiS; (arsenate reductase/pseudogene) and in one pseudogene yedN ←; (iapH/yopM family). Two additional significant intergenic polymorphisms were found at frequencies > 0.500 in fepD ←/→ entS (iron-enterobactin transporter subunit/enterobactin exporter, iron-regulated) and yfgF ←/→ yfgG (cyclic-di-GMP phosphodiesterase, anaerobic/uncharacterized protein). The control populations displayed mutations in the rpoB gene, a gene associated with rifampicin resistance.

Conclusions

This study corroborates recent results observed in experiments utilizing pathogenic Pseudomonas strains that also showed that Gram-negative bacteria can rapidly evolve resistance to an atom that mimics an essential micronutrient and shows the pleiotropic consequences associated with this adaptation.

Lay summary

We utilize experimental evolution to produce strains of Escherichia coli K-12 MG1655 resistant to, the iron analog, gallium nitrate (Ga(NO₃)₃). Whole genome sequencing was utilized to determine genomic changes associated with gallium resistance. Computational modeling was utilized to propose potential molecular mechanisms of resistance.

Microbial evolutionary medicine: from theory to clinical practice

Medicine and clinical microbiology have traditionally attempted to identify and eliminate the agents that cause disease. However, this traditional approach is becoming inadequate for dealing with a changing disease landscape. Major challenges to human health are non-communicable chronic diseases, often driven by altered immunity and inflammation, and communicable infections from agents which harbour antibiotic resistance. This Review focuses on the so-called evolutionary medicine framework, to study how microbial communities influence human health. The evolutionary medicine framework aims to predict and manipulate microbial effects on human health by integrating ecology, evolutionary biology, microbiology, bioinformatics, and clinical expertise. We focus on the potential of evolutionary medicine to address three key challenges: detecting microbial transmission, predicting antimicrobial resistance, and understanding microbe-microbe and human-microbe interactions in health and disease, in the context of the microbiome.

Effects of Beneficial Mutations in pykF Gene Vary over Time and across Replicate Populations in a Long-Term Experiment with Bacteria

The fitness effects of mutations can depend on the genetic backgrounds in which they occur and thereby influence future opportunities for evolving populations. In particular, mutations that fix in a population might change the selective benefit of subsequent mutations, giving rise to historical contingency. We examine these effects by focusing on mutations in a key metabolic gene, pykF, that arose independently early in the history of 12 Escherichia coli populations during a long-term evolution experiment. Eight different evolved nonsynonymous mutations conferred similar fitness benefits of ∼10% when transferred into the ancestor, and these benefits were greater than the one conferred by a deletion mutation. In contrast, the same mutations had highly variable fitness effects, ranging from ∼0% to 25%, in evolved clones isolated from the populations at 20,000 generations. Two mutations that were moved into these evolved clones conferred similar fitness effects in a given clone, but different effects between the clones, indicating epistatic interactions between the evolved pykF alleles and the other mutations that had accumulated in each evolved clone. We also measured the fitness effects of six evolved pykF alleles in the same populations in which they had fixed, but at seven time points between 0 and 50,000 generations. Variation in fitness effects was high at intermediate time points, and declined to a low level at 50,000 generations, when the mean fitness effect was lowest. Our results demonstrate the importance of genetic context in determining the fitness effects of different beneficial mutations even within the same gene.

(Non)Parallel Evolution

Parallel evolution across replicate populations has provided evolutionary biologists with iconic examples of adaptation. When multiple populations colonize seemingly similar habitats, they may evolve similar genes, traits, or functions. Yet, replicated evolution in nature or in the laboratory often yields inconsistent outcomes: Some replicate populations evolve along highly similar trajectories, whereas other replicate populations evolve to different extents or in distinct directions. To understand these heterogeneous outcomes, biologists are increasingly treating parallel evolution not as a binary phenomenon but rather as a quantitative continuum ranging from parallel to nonparallel. By measuring replicate populations’ positions along this (non)parallel continuum, we can test hypotheses about evolutionary and ecological factors that influence the extent of repeatable evolution. We review evidence regarding the manifestation of (non)parallel evolution in the laboratory, in natural populations, and in applied contexts such as cancer. We enumerate the many genetic, ecological, and evolutionary processes that contribute to variation in the extent of parallel evolution.

Genomics of experimental adaptation of Staphylococcus aureus to a natural combination of insect antimicrobial peptides

Antimicrobial peptides (AMP) are highly conserved immune effectors across the tree of life and are employed as combinations. In the beetle Tenebrio molitor, a defensin and a coleoptericin are highly expressed in vivo after inoculation with S. aureus. The defensin displays strong in vitro activity but no survival benefit in vivo. The coleoptericin provides a survival benefit in vivo, but no activity in vitro. This suggests a potentiating effect in vivo, and here we wanted to investigate the effects of this combination on resistance evolution using a bottom-approach in vitro starting with a combination of two abundant AMPs only. We experimentally evolved S. aureus in the presence of the defensin and a combination of the defensin and coleoptericin. Genome re-sequencing showed that resistance was associated with mutations in either the pmt or nsa operons. Strains with these mutations show longer lag phases, slower Vmax, and nsa mutants reach lower final population sizes. Mutations in the rpo operon showed a further increase in the lag phase in nsa mutants but not in pmt mutants. In contrast, final MICs (minimum inhibitory concentrations) do not differ according to mutation. All resistant lines display AMP but not antibiotic cross-resistance. Costly resistance against AMPs readily evolves for an individual AMP as well as a naturally occurring combination in vitro and provides broad protection against AMPs. Such non-specific resistance could result in strong selection on host immune systems that rely on cocktails of AMPs.

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.

Directed evolution of multiple genomic loci allows the prediction of antibiotic resistance

Antibiotic development is frequently plagued by the rapid emergence of drug resistance. However, assessing the risk of resistance development in the preclinical stage is difficult. Standard laboratory evolution approaches explore only a small fraction of the sequence space and fail to identify exceedingly rare resistance mutations and combinations thereof. Therefore, new rapid and exhaustive methods are needed to accurately assess the potential of resistance evolution and uncover the underlying mutational mechanisms. Here, we introduce directed evolution with random genomic mutations (DIvERGE), a method that allows an up to million-fold increase in mutation rate along the full lengths of multiple predefined loci in a range of bacterial species. In a single day, DIvERGE generated specific mutation combinations, yielding clinically significant resistance against trimethoprim and ciprofloxacin. Many of these mutations have remained previously undetected or provide resistance in a species-specific manner. These results indicate pathogen-specific resistance mechanisms and the necessity of future narrow-spectrum antibacterial treatments. In contrast to prior claims, we detected the rapid emergence of resistance against gepotidacin, a novel antibiotic currently in clinical trials. Based on these properties, DIvERGE could be applicable to identify less resistance-prone antibiotics at an early stage of drug development. Finally, we discuss potential future applications of DIvERGE in synthetic and evolutionary biology.

Identifying and exploiting genes that potentiate the evolution of antibiotic resistance

There is an urgent need to develop novel approaches for predicting and preventing the evolution of antibiotic resistance. Here we show that the ability to evolve de novo resistance to a clinically important β-lactam antibiotic, ceftazidime, varies drastically across the genus Pseudomonas. This variation arises because strains possessing the ampR global transcriptional regulator evolve resistance at a high rate. This does not arise because of mutations in ampR. Instead, this regulator potentiates evolution by allowing mutations in conserved peptidoglycan biosynthesis genes to induce high levels of β-lactamase expression. Crucially, blocking this evolutionary pathway by co-administering ceftazidime with the β-lactamase inhibitor avibactam can be used to eliminate pathogenic P. aeruginosa populations before they can evolve resistance. In summary, our study shows that identifying potentiator genes that act as evolutionary catalysts can be used to both predict and prevent the evolution of antibiotic resistance.

Divergent evolution peaks under intermediate population bottlenecks during bacterial experimental evolution

There is growing evidence that parallel molecular evolution is common, but its causes remain poorly understood. Demographic parameters such as population bottlenecks are predicted to be major determinants of parallelism. Here, we test the hypothesis that bottleneck intensity shapes parallel evolution by elucidating the genomic basis of adaptation to antibiotic-supplemented media in hundreds of populations of the bacterium Pseudomonas fluorescens Pf0-1. As expected, bottlenecking decreased the rate of phenotypic and molecular adaptation. Surprisingly, bottlenecking had no impact on the likelihood of parallel adaptive molecular evolution at a genome-wide scale. However, bottlenecking had a profound impact on the genes involved in antibiotic resistance. Specifically, under either intense or weak bottlenecking, resistance predominantly evolved by strongly beneficial mutations which provide high levels of antibiotic resistance. In contrast with intermediate bottlenecking regimes, resistance evolved by a greater diversity of genetic mechanisms, significantly reducing the observed levels of parallel genetic evolution. Our results demonstrate that population bottlenecking can be a major predictor of parallel evolution, but precisely how may be more complex than many simple theoretical predictions.

The Search for 'Evolution-Proof' Antibiotics

The effectiveness of antibiotics has been widely compromised by the evolution of resistance among pathogenic bacteria. It would be restored by the development of antibiotics to which bacteria cannot evolve resistance. We first discuss two kinds of 'evolution-proof' antibiotic. The first comprises literally evolution-proof antibiotics to which bacteria cannot become resistant by mutation or horizontal gene transfer. The second category comprises agents to which resistance may arise, but so rarely that it does not become epidemic. The likelihood that resistance to a novel agent will spread is evaluated here by a simple model that includes biological and therapeutic parameters governing the evolution of resistance within hosts and the transmission of resistant strains between hosts. This model leads to the conclusion that epidemic spread is unlikely if the frequency of mutations that confer resistance falls below a defined minimum value, and it identifies potential targets for intervention to prevent the evolution of resistance. Whether or not evolution-proof antibiotics are ever found, searching for them is likely to improve the deployment of new and existing agents by advancing our understanding of how resistance evolves.

Epistasis between antibiotic resistance mutations and genetic background shape the fitness effect of resistance across species of Pseudomonas

Antibiotic resistance often evolves by mutations at conserved sites in essential genes, resulting in parallel molecular evolution between divergent bacterial strains and species. Whether these resistance mutations are having parallel effects on fitness across bacterial taxa, however, is unclear. This is an important point to address, because the fitness effects of resistance mutations play a key role in the spread and maintenance of resistance in pathogen populations. We address this idea by measuring the fitness effect of a collection of rifampicin resistance mutations in the β subunit of RNA polymerase (rpoB) across eight strains that span the diversity of the genus Pseudomonas. We find that almost 50% of rpoB mutations have background-dependent fitness costs, demonstrating that epistatic interactions between rpoB and the rest of the genome are common. Moreover, epistasis is typically strong, and it is the dominant genetic determinant of the cost of resistance mutations. To investigate the functional basis of epistasis, and because rpoB plays a central role in transcription, we measured the effects of common rpoB mutations on transcriptional efficiency across three strains of Pseudomonas. Transcriptional efficiency correlates strongly to fitness across strains, and epistasis arises because individual rpoB mutations have differential effects on transcriptional efficiency in different genetic backgrounds.

Epistasis and the Evolution of Antimicrobial Resistance

The fitness effects of a mutation can depend, sometimes dramatically, on genetic background; this phenomenon is often referred to as “epistasis.” Epistasis can have important practical consequences in the context of antimicrobial resistance (AMR). For example, genetic background plays an important role in determining the costs of resistance, and hence in whether resistance will persist in the absence of antibiotic pressure. Furthermore, interactions between resistance mutations can have important implications for the evolution of multi-drug resistance. I argue that there is a need to better characterize the extent and nature of epistasis for mutations and horizontally transferred elements conferring AMR, particularly in clinical contexts. Furthermore, I suggest that epistasis should be an important consideration in attempts to slow or limit the evolution of AMR.

Differential paralog divergence modulates genome evolution across yeast species

Evolutionary outcomes depend not only on the selective forces acting upon a species, but also on the genetic background. However, large timescales and uncertain historical selection pressures can make it difficult to discern such important background differences between species. Experimental evolution is one tool to compare evolutionary potential of known genotypes in a controlled environment. Here we utilized a highly reproducible evolutionary adaptation in Saccharomyces cerevisiae to investigate whether experimental evolution of other yeast species would select for similar adaptive mutations. We evolved populations of S. cerevisiae, S. paradoxus, S. mikatae, S. uvarum, and interspecific hybrids between S. uvarum and S. cerevisiae for ~200–500 generations in sulfate-limited continuous culture. Wild-type S. cerevisiae cultures invariably amplify the high affinity sulfate transporter gene, SUL1. However, while amplification of the SUL1 locus was detected in S. paradoxus and S. mikatae populations, S. uvarum cultures instead selected for amplification of the paralog, SUL2. We measured the relative fitness of strains bearing deletions and amplifications of both SUL genes from different species, confirming that, converse to S. cerevisiae, S. uvarum SUL2 contributes more to fitness in sulfate limitation than S. uvarum SUL1. By measuring the fitness and gene expression of chimeric promoter-ORF constructs, we were able to delineate the cause of this differential fitness effect primarily to the promoter of S. uvarum SUL1. Our data show evidence of differential sub-functionalization among the sulfate transporters across Saccharomyces species through recent changes in noncoding sequence. Furthermore, these results show a clear example of how such background differences due to paralog divergence can drive changes in genome evolution.

Both comparative genomics and experimental evolution are powerful tools that can be used to make inferences about evolutionary processes. Together, these approaches provide the opportunity to observe evolutionary adaptation over millions of years where selective history is largely unknown, and over short timescales under controlled selective pressures in the laboratory. We have used comparative experimental evolution to observe the evolutionary fate of an adaptive mutation, and determined to what degree the outcome is conditional on the genetic background. We evolved several populations of different yeast species for over 200 generations in sulfate-limited conditions to determine how the differences in genomic context can alter evolutionary routes when challenged with a nutrient limitation selection pressure. We find that the gene encoding a high affinity sulfur transporter becomes amplified in most species of Saccharomyces, except in S. uvarum, in which the amplification of the paralogous sulfate transporter gene SUL2 is recovered. We attribute this change in amplification preference to mutations in the non-coding region of SUL1, likely due to reduced expression of this gene in S. uvarum. We conclude that the adaptive mutations selected for in each organism depend on the genomic context, even when faced with the same environmental condition.

Strain Diversity and the Evolution of Antibiotic Resistance

Drug resistance is best thought of as an ongoing biological process. Resistant bacteria must emerge, become established and ultimately transmit in order to be relevant to human health. In this context, genetic diversity can influence the rate and likelihood of resistance emerging; it can also modulate the net physiological impact of resistance and the propensity of an organism to improve any defects that arise from it. Combined, these effects can have an impact on a larger scale, with highly transmissible drug-resistant bacterial strains posing a formidable threat to global health. These considerations are pertinent to the future of tuberculosis control as well. In this chapter, we review our current understanding of the impact of genetic diversity in the broadest sense on the evolution of drug-resistant members of the Mycobacterium tuberculosis complex.

Evolution by flight and fight: diverse mechanisms of adaptation by actively motile microbes

Evolutionary adaptation can be achieved by mechanisms accessible to all organisms, including faster growth and interference competition, but self-generated motility offers additional possibilities. We tested whether 55 populations of the bacterium Myxococcus xanthus that underwent selection for increased fitness at the leading edge of swarming colonies adapted by swarming faster toward unused resources or by other means. Populations adapted greatly but diversified markedly in both swarming phenotypes and apparent mechanisms of adaptation. Intriguingly, although many adapted populations swarm intrinsically faster than their ancestors, numerous others do not. Some populations evolved interference competition toward their ancestors, whereas others gained the ability to facultatively increase swarming rate specifically upon direct interaction with ancestral competitors. Our results both highlight the diverse range of mechanisms by which actively motile organisms can adapt evolutionarily and help to explain the high levels of swarming-phenotype diversity found in local soil populations of M. xanthus.

Persistence and resistance as complementary bacterial adaptations to antibiotics

Bacterial persistence represents a simple of phenotypic heterogeneity, whereby a proportion of cells in an isogenic bacterial population can survive exposure to lethal stresses such as antibiotics. In contrast, genetically based antibiotic resistance allows for continued growth in the presence of antibiotics. It is unclear, however, whether resistance and persistence are complementary or alternative evolutionary adaptations to antibiotics. Here, we investigate the co‐evolution of resistance and persistence across the genus Pseudomonas using comparative methods that correct for phylogenetic nonindependence. We find that strains of Pseudomonas vary extensively in both their intrinsic resistance to antibiotics (ciprofloxacin and rifampicin) and persistence following exposure to these antibiotics. Crucially, we find that persistence correlates positively to antibiotic resistance across strains. However, we find that different genes control resistance and persistence implying that they are independent traits. Specifically, we find that the number of type II toxin–antitoxin systems (TAs) in the genome of a strain is correlated to persistence, but not resistance. Our study shows that persistence and antibiotic resistance are complementary, but independent, evolutionary adaptations to stress and it highlights the key role played by TAs in the evolution of persistence.

Adaptation to Parasites and Costs of Parasite Resistance in Mutator and Nonmutator Bacteria

Parasitism creates selection for resistance mechanisms in host populations and is hypothesized to promote increased host evolvability. However, the influence of these traits on host evolution when parasites are no longer present is unclear. We used experimental evolution and whole-genome sequencing of Escherichia coli to determine the effects of past and present exposure to parasitic viruses (phages) on the spread of mutator alleles, resistance, and bacterial competitive fitness. We found that mutator alleles spread rapidly during adaptation to any of four different phage species, and this pattern was even more pronounced with multiple phages present simultaneously. However, hypermutability did not detectably accelerate adaptation in the absence of phages and recovery of fitness costs associated with resistance. Several lineages evolved phage resistance through elevated mucoidy, and during subsequent evolution in phage-free conditions they rapidly reverted to nonmucoid, phage-susceptible phenotypes. Genome sequencing revealed that this phenotypic reversion was achieved by additional genetic changes rather than by genotypic reversion of the initial resistance mutations. Insertion sequence (IS) elements played a key role in both the acquisition of resistance and adaptation in the absence of parasites; unlike single nucleotide polymorphisms, IS insertions were not more frequent in mutator lineages. Our results provide a genetic explanation for rapid reversion of mucoidy, a phenotype observed in other bacterial species including human pathogens. Moreover, this demonstrates that the types of genetic change underlying adaptation to fitness costs, and consequently the impact of evolvability mechanisms such as increased point-mutation rates, depend critically on the mechanism of resistance.

Experimental evolution reveals hidden diversity in evolutionary pathways

Replicate populations of natural and experimental organisms often show evidence of parallel genetic evolution, but the causes are unclear. The wrinkly spreader morph of Pseudomonas fluorescens arises repeatedly during experimental evolution. The mutational causes reside exclusively within three pathways. By eliminating these, 13 new mutational pathways were discovered with the newly arising WS types having fitnesses similar to those arising from the commonly passaged routes. Our findings show that parallel genetic evolution is strongly biased by constraints and we reveal the genetic bases. From such knowledge, and in instances where new phenotypes arise via gene activation, we suggest a set of principles: evolution proceeds firstly via pathways subject to negative regulation, then via promoter mutations and gene fusions, and finally via activation by intragenic gain-of-function mutations. These principles inform evolutionary forecasting and have relevance to interpreting the diverse array of mutations associated with clinically identical instances of disease in humans.

DOI:http://dx.doi.org/10.7554/eLife.07074.001

Different living things often develop similar strategies to adapt to the environments in which they live. Sometimes two species that share a common ancestor independently evolve the same trait by changing the exact same genes. This is called ‘parallel evolution’, and it has led some scientists to ask: are there certain traits that can only evolve in a limited number of ways? Or are there other ways to evolve the same trait that, for some reason, are not explored?

Experimentally, investigating these questions is challenging, but parallel evolution occurs in the laboratory as well as in the wild. Many commonly studied organisms—such as fruit flies or bacteria—can be used in relevant studies, because they can be grown in large numbers and then exposed to identical environments. However, if this method fails to find a new way that a trait can evolve, it doesn't mean that alternative mechanisms do not exist.

Lind et al. used a different approach that instead relies on removing all of the known pathways that can be mutated to produce a given trait and then seeing if that trait can still evolve via mutations elsewhere. The experiments involved a bacterium called Pseudomonas fluorescens that can evolve to grow flattened and wrinkled colonies (instead of smooth, round ones) when it has to compete for access to oxygen.

Previous experiments had shown that the evolution of the so-called ‘wrinkly spreader’ form can be caused by mutations in one of three biological pathways. But P. fluorescens can survive unharmed without these pathways, which enabled Lind et al. to ask if there might be other ways that this trait could evolve. Bacteria without these three pathways were engineered and then grown under oxygen-deprived conditions. This experiment produced 91 new mutants that each had the wrinkly spreader phenotype. Further experiments revealed that together these mutants represented 13 previously unrecognized ways that the ‘wrinkly spreader’ phenotype can evolve.

The new rare mutants had similar fitness as the previously known, common ones—so this cannot explain why they hadn't been seen before. Lind et al. instead suggest a set of principles to explain why these newly discovered pathways are rarely mutated and how genetic constraints can bias the outcome of evolution. Further work could investigate whether these principles can help us to predict the course of evolution in other biological contexts, such as in the evolution of antibiotic resistance.

DOI:http://dx.doi.org/10.7554/eLife.07074.002

Limits to compensatory adaptation and the persistence of antibiotic resistance in pathogenic bacteria

Antibiotic resistance carries a fitness cost that could potentially limit the spread of resistance in bacterial pathogens. In spite of this cost, a large number of experimental evolution studies have found that resistance is stably maintained in the absence of antibiotics as a result of compensatory evolution. Clinical studies, on the other hand, have found that resistance in pathogen populations usually declines after antibiotic use is stopped, suggesting that compensatory adaptation is not effective in vivo. In this article, we argue that this disagreement arises because there are limits to compensatory adaptation in nature that are not captured by the design of current laboratory selection experiments. First, clinical treatment fails to eradicate antibiotic-sensitive strains, and competition between sensitive and resistant strains leads to the rapid loss of resistance following treatment. Second, laboratory studies overestimate the efficacy of compensatory adaptation in nature by failing to capture costs associated with compensatory mutations. Taken together, these ideas can potentially reconcile evolutionary theory with the clinical dynamics of antibiotic resistance and guide the development of strategies for containing resistance in clinical pathogens.