The cost of multiple drug resistance in Pseudomonas aeruginosa

Genotype-by-environment interactions govern fitness changes associated with adaptive mutations in two-component response systems

Introduction: Two-component response systems (TCRS) are the main mechanism by which prokaryotes acclimate to changing environments. These systems are composed of a membrane bound histidine kinase (HK) that senses external signals and a response regulator (RR) that activates transcription of response genes. Despite their known role in acclimation, little is known about the role TCRS play in environmental adaptation. Several experimental evolution studies have shown the acquisition of mutations in TCRS during adaptation, therefore here we set out to characterize the adaptive mechanism resulting from these mutations and evaluate whether single nucleotide changes in one gene could induce variable genotype-by-environment (GxE) interactions. Methods: To do this, we assessed fitness changes and differential gene expression for four adaptive mutations in cusS, the gene that encodes the HK CusS, acquired by Escherichia coli during silver adaptation. Results: Fitness assays showed that as the environment changed, each mutant displayed a unique fitness profile with greatest fitness in the original selection environment. RNAseq then indicated that, in ± silver nitrate, each mutant induces a primary response that upregulates cusS, its RR cusR, and constitutively expresses the target response genes cusCFBA. This then induces a secondary response via differential expression of genes regulated by the CusR through TCRS crosstalk. Finally, each mutant undergoes fitness tuning through unique tertiary responses that result in gene expression patterns specific for the genotype, the environment and optimized for the original selection conditions. Discussion: This three-step response shows that different mutations in a single gene leads to individualized phenotypes governed by unique GxE interactions that not only contribute to transcriptional divergence but also to phenotypic plasticity.

Translating eco-evolutionary biology into therapy to tackle antibiotic resistance

Antibiotic resistance is currently one of the most important public health problems. The golden age of antibiotic discovery ended decades ago, and new approaches are urgently needed. Therefore, preserving the efficacy of the antibiotics currently in use and developing compounds and strategies that specifically target antibiotic-resistant pathogens is critical. The identification of robust trends of antibiotic resistance evolution and of its associated trade-offs, such as collateral sensitivity or fitness costs, is invaluable for the design of rational evolution-based, ecology-based treatment approaches. In this Review, we discuss these evolutionary trade-offs and how such knowledge can aid in informing combination or alternating antibiotic therapies against bacterial infections. In addition, we discuss how targeting bacterial metabolism can enhance drug activity and impair antibiotic resistance evolution. Finally, we explore how an improved understanding of the original physiological function of antibiotic resistance determinants, which have evolved to reach clinical resistance after a process of historical contingency, may help to tackle antibiotic resistance.

Pervasive genotype-by-environment interactions shape the fitness effects of antibiotic resistance mutations

The fitness effects of antibiotic resistance mutations are a major driver of resistance evolution. While the nutrient environment affects bacterial fitness, experimental studies of resistance typically measure fitness of mutants in a single environment only. We explored how the nutrient environment affected the fitness effects of rifampicin-resistant rpoB mutations in Escherichia coli under several conditions critical for the emergence and spread of resistance-the presence of primary or secondary antibiotic, or the absence of any antibiotic. Pervasive genotype-by-environment (GxE) interactions determined fitness in all experimental conditions, with rank order of fitness in the presence and absence of antibiotics being strongly dependent on the nutrient environment. GxE interactions also affected the magnitude and direction of collateral effects of secondary antibiotics, in some cases so drastically that a mutant that was highly sensitive in one nutrient environment exhibited cross-resistance to the same antibiotic in another. It is likely that the mutant-specific impact of rpoB mutations on the global transcriptome underpins the observed GxE interactions. The pervasive, mutant-specific GxE interactions highlight the importance of doing what is rarely done when studying the evolution and spread of resistance in experimental and clinical work: assessing fitness of antibiotic-resistant mutants across a range of relevant environments.

Antibiotic Cycling Affects Resistance Evolution Independently of Collateral Sensitivity

Antibiotic cycling has been proposed as a promising approach to slow down resistance evolution against currently employed antibiotics. It remains unclear, however, to which extent the decreased resistance evolution is the result of collateral sensitivity, an evolutionary trade-off where resistance to one antibiotic enhances the sensitivity to the second, or due to additional effects of the evolved genetic background, in which mutations accumulated during treatment with a first antibiotic alter the emergence and spread of resistance against a second antibiotic via other mechanisms. Also, the influence of antibiotic exposure patterns on the outcome of drug cycling is unknown. Here, we systematically assessed the effects of the evolved genetic background by focusing on the first switch between two antibiotics against Salmonella Typhimurium, with cefotaxime fixed as the first and a broad variety of other drugs as the second antibiotic. By normalizing the antibiotic concentrations to eliminate the effects of collateral sensitivity, we demonstrated a clear contribution of the evolved genetic background beyond collateral sensitivity, which either enhanced or reduced the adaptive potential depending on the specific drug combination. We further demonstrated that the gradient strength with which cefotaxime was applied affected both cefotaxime resistance evolution and adaptation to second antibiotics, an effect that was associated with higher levels of clonal interference and reduced cost of resistance in populations evolved under weaker cefotaxime gradients. Overall, our work highlights that drug cycling can affect resistance evolution independently of collateral sensitivity, in a manner that is contingent on the antibiotic exposure pattern.

Antimicrobial Peptide Combination Can Hinder Resistance Evolution

Antibiotic-resistant microbial pathogens are becoming a major threat to human health. Therefore, there is an urgent need to develop new alternatives to conventional antibiotics. One such promising alternative is antimicrobial peptides (AMPs), which are produced by virtually all organisms and typically inhibit bacteria via membrane disruption. However, previous studies demonstrated that bacteria can rapidly develop AMP resistance. Here, we study whether combination therapy, known to be able to inhibit the evolution of resistance to conventional antibiotics, can also hinder the evolution of AMP resistance. To do so, we evolved the opportunistic pathogen Staphylococcus aureus in the presence of individual AMPs, AMP pairs, and a combinatorial antimicrobial peptide library. Treatment with some AMP pairs indeed hindered the evolution of resistance compared with individual AMPs. In particular, resistance to pairs was delayed when resistance to the individual AMPs came at a cost of impaired bacterial growth and did not confer cross-resistance to other tested AMPs. The lowest level of resistance evolved during treatment with the combinatorial antimicrobial peptide library termed random antimicrobial peptide mixture, which contains more than a million different peptides. A better understanding of how AMP combinations affect the evolution of resistance is a crucial step in order to design "resistant proof" AMP cocktails that will offer a sustainable treatment option for antibiotic-resistant pathogens. IMPORTANCE The main insights gleaned from this study are the following. (i) AMP combination treatment can delay the evolution of resistance in S. aureus. Treatment with some AMP pairs resulted in significantly lower resistance then treatment with either of the individual AMPs. Treatment with a random AMP library resulted in no detectable resistance. (ii) The rate at which resistance to combination arises correlates with the cost of resistance to individual AMPs and their cross-resistance. In particular, combinations to which the least resistance arose involved AMPs with high fitness cost of resistance and low cross-resistance. (iii) No broad-range AMP resistance evolved. Strains that evolved resistance to some AMPs typically remained sensitive to other AMPs, alleviating concerns regarding the evolution of resistance to immune system AMPs in response to AMP treatment.

Rapid decline of ceftazidime resistance in antibiotic-free and sub-lethal environments is contingent on genetic background

Trade-offs of antibiotic resistance evolution, such as fitness cost and collateral sensitivity (CS), could be exploited to drive evolution toward antibiotic susceptibility. Decline of resistance may occur when resistance to other drug leads to CS to the first one and when compensatory mutations, or genetic reversion of the original ones, reduce fitness cost. Here we describe the impact of antibiotic-free and sublethal environments on declining ceftazidime resistance in different Pseudomonas aeruginosa resistant mutants. We determined that decline of ceftazidime resistance occurs within 450 generations, which is caused by newly acquired mutations and not by reversion of the original ones, and that the original CS of these mutants is preserved. In addition, we observed that the frequency and degree of this decline is contingent on genetic background. Our results are relevant to implement evolution-based therapeutic approaches, as well as to redefine global policies of antibiotic use, such as drug cycling.

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

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

Metabonomics reveals an alleviation of fitness cost in resistant E. coli competing against susceptible E. coli at sub-MIC doxycycline

High concentrations of antibiotics may induce bacterial resistance mutations and further lead to fitness costs by reducing growth of resistant bacteria. However, antibiotic concentrations faced by bacteria are usually low in common environments, which leads to questions about how resistant bacteria with fitness costs regulate metabolism to coexist or compete with susceptible bacteria during sublethal challenge. Our study revealed that a low proportion (< 15%) of resistant bacteria coexisted with susceptible bacteria due to the fitness cost without doxycycline. However, the cost for the resistant strain decreased at a doxycycline concentration of 1 mg/L and even disappeared when the doxycycline concentration was 2 mg/L. Metabonomics analysis revealed that bypass carbon metabolism and biosynthesis of secondary metabolites were the primary metabolic pathways enriching various upregulated metabolites in resistant bacteria without doxycycline. Moreover, the alleviation of fitness cost for resistant bacteria competed with susceptible bacteria at 1 mg/L doxycycline was correlated with the downregulation of the biomarkers pyruvate and pilocarpine. Our study offered new insight into the metabolic mechanisms by which the fitness cost of resistant mutants was reduced at doxycycline concentrations as low as 1 mg/L and identified various potential metabolites to limit the spread of antimicrobial resistance in the environment.

An Efficient, Counter-Selection-Based Method for Prophage Curing in Pseudomonas aeruginosa Strains

Prophages are bacteriophages in the lysogenic state, where the viral genome is inserted within the bacterial chromosome. They contribute to strain genetic variability and can influence bacterial phenotypes. Prophages are highly abundant among the strains of the opportunistic pathogen Pseudomonas aeruginosa and were shown to confer specific traits that can promote strain pathogenicity. The main difficulty of studying those regions is the lack of a simple prophage-curing method for P. aeruginosa strains. In this study, we developed a novel, targeted-curing approach for prophages in P. aeruginosa. In the first step, we tagged the prophage for curing with an ampicillin resistance cassette (ampR) and further used this strain for the sacB counter-selection marker’s temporal insertion into the prophage region. The sucrose counter-selection resulted in different variants when the prophage-cured mutant is the sole variant that lost the ampR cassette. Next, we validated the targeted-curing with local PCR amplification and Whole Genome Sequencing. The application of the strategy resulted in high efficiency both for curing the Pf4 prophage of the laboratory wild-type (WT) strain PAO1 and for PR2 prophage from the clinical, hard to genetically manipulate, 39016 strain. We believe this method can support the research and growing interest in prophage biology in P. aeruginosa as well as additional Gram-negative bacteria.

Rapid and robust evolution of collateral sensitivity in Pseudomonas aeruginosa antibiotic-resistant mutants

The analysis of trade-offs, as collateral sensitivity, associated with the acquisition of antibiotic resistance, is mainly based on the use of model strains. However, the possibility of exploiting these trade-offs for fighting already resistant isolates has not been addressed in depth, despite the fact that bacterial pathogens are frequently antibiotic-resistant, forming either homogeneous or heterogeneous populations. Using a set of Pseudomonas aeruginosa-resistant mutants, we found that ceftazidime selects pyomelanogenic tobramycin-hypersusceptible mutants presenting chromosomal deletions in the analyzed genetic backgrounds. Since pyomelanogenic resistant mutants frequently coexist with other morphotypes in patients with cystic fibrosis, we analyzed the exploitation of this trade-off to drive extinction of heterogeneous resistant populations by using tobramycin/ceftazidime alternation. Our work shows that this approach is feasible because phenotypic trade-offs associated with the use of ceftazidime are robust. The identification of conserved collateral sensitivity networks may guide the rational design of evolution-based antibiotic therapies in P. aeruginosa infections.

Factors favouring the evolution of multidrug resistance in bacteria

The evolution of multidrug antibiotic resistance in commensal bacteria is an important public health concern. Commensal bacteria such as Escherichia coli, Streptococcus pneumoniae or Staphylococcus aureus, are also opportunistic pathogens causing a large fraction of the community-acquired and hospital-acquired bacterial infections. Multidrug resistance (MDR) makes these infections harder to treat with antibiotics and may thus cause substantial additional morbidity and mortality. Here, we develop an evolutionary epidemiology model to identify the factors favouring the evolution of MDR in commensal bacteria. The model describes the evolution of antibiotic resistance in a commensal bacterial species evolving in a host population subjected to multiple antibiotic treatments. We combine statistical analysis of a large number of simulations and mathematical analysis to understand the model behaviour. We find that MDR evolves more readily when it is less costly than expected from the combinations of single resistances (positive epistasis). MDR frequently evolves when bacteria are in contact with multiple drugs prescribed in the host population, even if individual hosts are only treated with a single drug at a time. MDR is favoured when the host population is structured in different classes that vary in their rates of antibiotic treatment. However, under most circumstances, recombination between loci involved in resistance does not meaningfully affect the equilibrium frequency of MDR. Together, these results suggest that MDR is a frequent evolutionary outcome in commensal bacteria that encounter the variety of antibiotics prescribed in the host population. A better characterization of the variability in antibiotic use across the host population (e.g. across age classes or geographical location) would help predict which MDR genotypes will most readily evolve.

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.

Antibiotic Resistance Evolution Is Contingent on the Quorum-Sensing Response in Pseudomonas aeruginosa

Different works have explored independently the evolution toward antibiotic resistance and the role of eco-adaptive mutations in the adaptation to a new habitat (as the infected host) of bacterial pathogens. However, knowledge about the connection between both processes is still limited. We address this issue by comparing the evolutionary trajectories toward antibiotic resistance of a Pseudomonas aeruginosa lasR defective mutant and its parental wild-type strain, when growing in presence of two ribosome-targeting antibiotics. Quorum-sensing lasR defective mutants are selected in P. aeruginosa populations causing chronic infections. Further, we observed they are also selected in vitro as a first adaptation for growing in culture medium. By using experimental evolution and whole-genome sequencing, we found that the evolutionary trajectories of P. aeruginosa in presence of these antibiotics are different in lasR defective and in wild-type backgrounds, both at the phenotypic and the genotypic levels. Recreation of a set of mutants in both genomic backgrounds (either wild type or lasR defective) allowed us to determine the existence of negative epistatic interactions between lasR and antibiotic resistance determinants. These epistatic interactions could lead to mutual contingency in the evolution of antibiotic resistance when P. aeruginosa colonizes a new habitat in presence of antibiotics. If lasR mutants are selected first, this would constraint antibiotic resistance evolution. Conversely, when resistance mutations (at least those studied in the present work) are selected, lasR mutants may not be selected in presence of antibiotics. These results underlie the importance of contingency and epistatic interactions in modulating antibiotic resistance evolution.

Antibiotic resistance in Pseudomonas aeruginosa - Mechanisms, epidemiology and evolution

Antibiotics are powerful drugs used in the treatment of bacterial infections. The inappropriate use of these medicines has driven the dissemination of antibiotic resistance (AR) in most bacteria. Pseudomonas aeruginosa is an opportunistic pathogen commonly involved in environmental- and difficult-to-treat hospital-acquired infections. This species is frequently resistant to several antibiotics, being in the "critical" category of the WHO's priority pathogens list for research and development of new antibiotics. In addition to a remarkable intrinsic resistance to several antibiotics, P. aeruginosa can acquire resistance through chromosomal mutations and acquisition of AR genes. P. aeruginosa has one of the largest bacterial genomes and possesses a significant assortment of genes acquired by horizontal gene transfer (HGT), which are frequently localized within integrons and mobile genetic elements (MGEs), such as transposons, insertion sequences, genomic islands, phages, plasmids and integrative and conjugative elements (ICEs). This genomic diversity results in a non-clonal population structure, punctuated by specific clones that are associated with significant morbidity and mortality worldwide, the so-called high-risk clones. Acquisition of MGEs produces a fitness cost in the host, that can be eased over time by compensatory mutations during MGE-host coevolution. Even though plasmids and ICEs are important drivers of AR, the underlying evolutionary traits that promote this dissemination are poorly understood. In this review, we provide a comprehensive description of the main strategies involved in AR in P. aeruginosa and the leading drivers of HGT in this species. The most recently developed genomic tools that allowed a better understanding of the features contributing for the success of P. aeruginosa are discussed.

On the evolutionary ecology of multidrug resistance in bacteria

Resistance against different antibiotics appears on the same bacterial strains more often than expected by chance, leading to high frequencies of multidrug resistance. There are multiple explanations for this observation, but these tend to be specific to subsets of antibiotics and/or bacterial species, whereas the trend is pervasive. Here, we consider the question in terms of strain ecology: explaining why resistance to different antibiotics is often seen on the same strain requires an understanding of the competition between strains with different resistance profiles. This work builds on models originally proposed to explain another aspect of strain competition: the stable coexistence of antibiotic sensitivity and resistance observed in a number of bacterial species. We first identify a partial structural similarity in these models: either strain or host population structure stratifies the pathogen population into evolutionarily independent sub-populations and introduces variation in the fitness effect of resistance between these sub-populations, thus creating niches for sensitivity and resistance. We then generalise this unified underlying model to multidrug resistance and show that models with this structure predict high levels of association between resistance to different drugs and high multidrug resistance frequencies. We test predictions from this model in six bacterial datasets and find them to be qualitatively consistent with observed trends. The higher than expected frequencies of multidrug resistance are often interpreted as evidence that these strains are out-competing strains with lower resistance multiplicity. Our work provides an alternative explanation that is compatible with long-term stability in resistance frequencies.

Competing evolutionary paths in growing populations with applications to multidrug resistance

Investigating the emergence of a particular cell type is a recurring theme in models of growing cellular populations. The evolution of resistance to therapy is a classic example. Common questions are: when does the cell type first occur, and via which sequence of steps is it most likely to emerge? For growing populations, these questions can be formulated in a general framework of branching processes spreading through a graph from a root to a target vertex. Cells have a particular fitness value on each vertex and can transition along edges at specific rates. Vertices represent cell states, say genotypes or physical locations, while possible transitions are acquiring a mutation or cell migration. We focus on the setting where cells at the root vertex have the highest fitness and transition rates are small. Simple formulas are derived for the time to reach the target vertex and for the probability that it is reached along a given path in the graph. We demonstrate our results on several scenarios relevant to the emergence of drug resistance, including: the orderings of resistance-conferring mutations in bacteria and the impact of imperfect drug penetration in cancer.

How long does it take for a treatment naive, growing bacterial colony to be able to survive exposure to a cocktail of antibiotics? En route to multidrug resistance, what order did the drugs become impotent in? Questions such as these that pertain to the emergence of a significant cell type in a growing population arise frequently. They are often investigated via mathematical modelling but biologically insightful results are challenging to obtain. Here we outline a general framework of a stochastically growing population spreading through a graph to study such questions and provide simple formulas as answers. The significant cell type appears upon the population reaching a target vertex. Due to their simplicity, the derived formulas are widely accessible and can be used to guide and develop intuition on a range of biological scenarios. We demonstrate this on several settings including: how a region where drugs cannot penetrate affects the emergence of resistance, and, the ordering of mutations that leads to drugs being ineffective.

A benzimidazole-based ruthenium(IV) complex inhibits Pseudomonas aeruginosa biofilm formation by interacting with siderophores and the cell envelope, and inducing oxidative stress

Pseudomonas aeruginosa biofilm-associated infections are a serious medical problem, and new compounds and therapies acting through novel mechanisms are much needed. Herein, the authors report a ruthenium(IV) complex that reduces P. aeruginosa PAO1 biofilm formation by 84%, and alters biofilm morphology and the living-to-dead cell ratio at 1 mM concentration. Including the compound in the culture medium altered the pigments secreted by PAO1, and fluorescence spectra revealed a decrease in pyoverdine. Scanning electron microscopy showed that the ruthenium complex did not penetrate the bacterial cell wall, but accumulated on external cell structures. Fluorescence quenching experiments indicated strong binding of the ruthenium complex to both plasmid DNA and bovine serum albumin. Formamidopyrimidine DNA N-glycosylase (Fpg) protein digestion of plasmid DNA isolated after ruthenium(IV) complex treatment revealed the generation of oxidative stress, which was further proved by the observed upregulation of catalase and superoxide dismutase gene expression.

Antagonistic pleiotropy for carbon use is rare in new mutations

Pleiotropic effects of mutations underlie diverse biological phenomena such as ageing and specialization. In particular, antagonistic pleiotropy ("AP": when a mutation has opposite fitness effects in different environments) generates tradeoffs, which may constrain adaptation. Models of adaptation typically assume that AP is common - especially among large-effect mutations - and that pleiotropic effect sizes are positively correlated. Empirical tests of these assumptions have focused on de novo beneficial mutations arising under strong selection. However, most mutations are actually deleterious or neutral, and may contribute to standing genetic variation that can subsequently drive adaptation. We quantified the incidence, nature, and effect size of pleiotropy for carbon utilization across 80 single mutations in Escherichia coli that arose under mutation accumulation (i.e., weak selection). Although ∼46% of the mutations were pleiotropic, only 11% showed AP; among beneficial mutations, only ∼4% showed AP. In some environments, AP was more common in large-effect mutations; and AP effect sizes across environments were often negatively correlated. Thus, AP for carbon use is generally rare (especially among beneficial mutations); is not consistently enriched in large-effect mutations; and often involves weakly deleterious antagonistic effects. Our unbiased quantification of mutational effects therefore suggests that antagonistic pleiotropy may be unlikely to cause maladaptive tradeoffs.

Rapid evolution of generalized resistance mechanisms can constrain the efficacy of phage-antibiotic treatments

Antimicrobial resistance has been estimated to be responsible for over 700,000 deaths per year; therefore, new antimicrobial therapies are urgently needed. One way to increase the efficiency of antibiotics is to use them in combination with bacteria-specific parasitic viruses, phages, which have been shown to exert additive or synergistic effects in controlling bacteria. However, it is still unclear to what extent these combinatory effects are limited by rapid evolution of resistance, especially when the pathogen grows as biofilm on surfaces typical for many persistent and chronic infections. To study this, we used a microcosm system, where genetically isogenic populations of Pseudomonas aeruginosa PAO1 bacterial pathogen were exposed to a phage 14/1, gentamycin or a combination of them both in a spatially structured environment. We found that even though antibiotic and phage-antibiotic treatments were equally effective at controlling bacteria in the beginning of the experiment, combination treatment rapidly lost its efficacy in both planktonic and biofilm populations. In a mechanistic manner, this was due to rapid resistance evolution: While both antibiotic and phage selected for increased resistance on their own, phage selection correlated positively with increase in antibiotic resistance, while biofilm growth, which provided generalized resistance mechanism, was favoured most in the combination treatment. Only relatively small cost of resistance and weak evidence for coevolutionary dynamics were observed. Together, these results suggest that spatial heterogeneity can promote rapid evolution of generalized resistance mechanisms without corresponding increase in phage infectivity, which could potentially limit the effectiveness of phage-antibiotic treatments in the evolutionary timescale.

Predictable Phenotypes of Antibiotic Resistance Mutations

Antibiotic-resistant bacteria represent a major threat to our ability to treat bacterial infections. Two factors that determine the evolutionary success of antibiotic resistance mutations are their impact on resistance level and the fitness cost. Recent studies suggest that resistance mutations commonly show epistatic interactions, which would complicate predictions of their stability in bacterial populations. We analyzed 13 different chromosomal resistance mutations and 10 host strains of Salmonella enterica and Escherichia coli to address two main questions. (i) Are there epistatic interactions between different chromosomal resistance mutations? (ii) How does the strain background and genetic distance influence the effect of chromosomal resistance mutations on resistance and fitness? Our results show that the effects of combined resistance mutations on resistance and fitness are largely predictable and that epistasis remains rare even when up to four mutations were combined. Furthermore, a majority of the mutations, especially target alteration mutations, demonstrate strain-independent phenotypes across different species. This study extends our understanding of epistasis among resistance mutations and shows that interactions between different resistance mutations are often predictable from the characteristics of the individual mutations.

The spread of antibiotic-resistant bacteria imposes an urgent threat to public health. The ability to forecast the evolutionary success of resistant mutants would help to combat dissemination of antibiotic resistance. Previous studies have shown that the phenotypic effects (fitness and resistance level) of resistance mutations can vary substantially depending on the genetic context in which they occur. We conducted a broad screen using many different resistance mutations and host strains to identify potential epistatic interactions between various types of resistance mutations and to determine the effect of strain background on resistance phenotypes. Combinations of several different mutations showed a large amount of phenotypic predictability, and the majority of the mutations displayed strain-independent phenotypes. However, we also identified a few outliers from these patterns, illustrating that the choice of host organism can be critically important when studying antibiotic resistance mutations.

Evolution of bacteria specialization along an antibiotic dose gradient

Antibiotic and pesticide resistance of pathogens are major and pressing worldwide issues. Resistance evolution is often considered in simplified ecological contexts: treated versus nontreated environments. In contrast, antibiotic usually present important dose gradients: from ecosystems to hospitals to polluted soils, in treated patients across tissues. However, we do not know whether adaptation to low or high doses involves different phenotypic traits, and whether these traits trade‐off with each other. In this study, we investigated the occurrence of such fitness trade‐offs along a dose gradient by evolving experimentally resistant lines of Escherichia coli at different antibiotic concentrations for ∼400 generations. Our results reveal fast evolution toward specialization following the first mutational step toward resistance, along with pervasive trade‐offs among different evolution doses. We found clear and regular fitness patterns of specialization, which converged rapidly from different initial starting points. These findings are consistent with a simple fitness peak shift model as described by the classical evolutionary ecology theory of adaptation across environmental gradients. We also found that the fitness costs of resistance tend to be compensated through time at low doses whereas they increase through time at higher doses. This cost evolution follows a linear trend with the log‐dose of antibiotic along the gradient. These results suggest a general explanation for the variability of the fitness costs of resistance and their evolution. Overall, these findings call for more realistic models of resistance management incorporating dose‐specialization.

Environmental and genetic modulation of the phenotypic expression of antibiotic resistance

Antibiotic resistance can be acquired by mutation or horizontal transfer of a resistance gene, and generally an acquired mechanism results in a predictable increase in phenotypic resistance. However, recent findings suggest that the environment and/or the genetic context can modify the phenotypic expression of specific resistance genes/mutations. An important implication from these findings is that a given genotype does not always result in the expected phenotype. This dissociation of genotype and phenotype has important consequences for clinical bacteriology and for our ability to predict resistance phenotypes from genetics and DNA sequences. A related problem concerns the degree to which the genes/mutations currently identified in vitro can fully explain the in vivo resistance phenotype, or whether there is a significant additional amount of presently unknown mutations/genes (genetic ‘dark matter’) that could contribute to resistance in clinical isolates. Finally, a very important question is whether/how we can identify the genetic features that contribute to making a successful pathogen, and predict why some resistant clones are very successful and spread globally? In this review, we describe different environmental and genetic factors that influence phenotypic expression of antibiotic resistance genes/mutations and how this information is needed to understand why particular resistant clones spread worldwide and to what extent we can use DNA sequences to predict evolutionary success.

Sublethal streptomycin concentrations and lytic bacteriophage together promote resistance evolution

Sub-minimum inhibiting concentrations (sub-MICs) of antibiotics frequently occur in natural environments owing to wide-spread antibiotic leakage by human action. Even though the concentrations are very low, these sub-MICs have recently been shown to alter bacterial populations by selecting for antibiotic resistance and increasing the rate of adaptive evolution. However, studies are lacking on how these effects reverberate into key ecological interactions, such as bacteria-phage interactions. Previously, co-selection of bacteria by phages and antibiotic concentrations exceeding MICs has been hypothesized to decrease the rate of resistance evolution because of fitness costs associated with resistance mutations. By contrast, here we show that sub-MICs of the antibiotic streptomycin (Sm) increased the rate of phage resistance evolution, as well as causing extinction of the phage. Notably, Sm and the phage in combination also enhanced the evolution of Sm resistance compared with Sm alone. These observations demonstrate the potential of sub-MICs of antibiotics to impact key ecological interactions in microbial communities with evolutionary outcomes that can radically differ from those associated with high concentrations. Our findings also contribute to the understanding of ecological and evolutionary factors essential for the management of the antibiotic resistance problem.This article is part of the themed issue 'Human influences on evolution, and the ecological and societal consequences'.

The effect of selection history on extinction risk during severe environmental change

Environments rarely remain the same over time, and populations are therefore frequently at risk of going extinct when changes are significant enough to reduce fitness. Although many studies have investigated what attributes of the new environments and of the populations experiencing these changes will affect their probability of going extinct, limited work has been directed towards determining the role of population history on the probability of going extinct during severe environmental change. Here, we compare the extinction risk of populations with a history of selection in a benign environment, to populations with a history of selection in one or two stressful environments. We exposed spores and lines of the green alga Chlamydomonas reinhardtii from these three different histories to a range of severe environmental changes. We found that the extinction risk was higher for populations with a history of selection in stressful environments compared to populations with a history of selection in a benign environment. This effect was not due to differences in initial population sizes. Finally, the rates of extinction were highly repeatable within histories, indicating strong historical contingency of extinction risk. Hence, information on the selection history of a population can be used to predict their probability of going extinct during environmental change.

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.

Positive epistasis of major low-cost drug resistance mutations rpoB531-TTG and katG315-ACC depends on the phylogenetic background of Mycobacterium tuberculosis strains

Mycobacterium tuberculosis Beijing genotype strains increasingly circulate in different world regions, either as historical endemic, e.g. in East Asia, or recently imported, e.g. in South America, and this family is regarded as the most successful lineage of the global tuberculosis (TB) epidemic. Here we analysed the transmission capacity of these strains in the context of their phylogenetic background and drug resistance mutations. The study collection included all multidrug resistant (MDR) strains of Beijing genotype isolated in Beijing Chest Hospital, the largest tertiary TB facility in North China, in 2011-2013 (n = 278). Strains were subjected to NTF/IS6110 and 24-loci MIRU-VNTR analysis. Drug resistance mutations were detected in rpoB, katG, inhA and oxyR-ahpC. A total of 58 and 220 strains were assigned to the ancient and modern Beijing sublineages, respectively. 24-MIRU-VNTR clustering was higher in modern versus ancient Beijing strains (35.9% vs. 12.1%; P <0.001). After taking into consideration the presence of rpoB and katG mutations, clustering decreased to 15.9% in modern and 0% in ancient strains. The most frequent combination of mutations (rpoB531-TTG and katG315-ACC) was more prevalent in clustered versus non-clustered isolates in the modern sublineage (23/35 vs. 47/185; P <0.0001). To conclude, a combination of the known low-fitness-cost rpoB531-TTG and katG315-ACC mutations likely facilitates the increased transmission ability of MDR strains of the modern but not ancient Beijing sublineage. Accordingly, positive epistasis of major low-cost drug resistance-conferring mutations is influenced by the phylogenetic background of M. tuberculosis strains.

Fitness costs associated with the acquisition of antibiotic resistance

Acquisition of antibiotic resistance is a relevant problem for human health. The selection and spread of antibiotic-resistant organisms not only compromise the treatment of infectious diseases, but also the implementation of different therapeutic procedures as organ transplantation, advanced surgery or chemotherapy, all of which require proficient methods for avoiding infections. It has been generally accepted that the acquisition of antibiotic resistance will produce a general metabolic burden: in the absence of selection, the resistant organisms would be outcompeted by the susceptible ones. If that was always true, discontinuation of antibiotic use would render the disappearance of resistant microorganisms. However, several studies have shown that, once resistance emerges, the recovery of a fully susceptible population even in the absence of antibiotics is not easy. In the present study, we review updated information on the effect of the acquisition of antibiotic resistance in bacterial physiology as well as on the mechanisms that allow the compensation of the fitness costs associated with the acquisition of resistance.

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.

Fisher's geometrical model and the mutational patterns of antibiotic resistance across dose gradients

Fisher's geometrical model (FGM) has been widely used to depict the fitness effects of mutations. It is a general model with few underlying assumptions that gives a large and comprehensive view of adaptive processes. It is thus attractive in several situations, for example adaptation to antibiotics, but comes with limitations, so that more mechanistic approaches are often preferred to interpret experimental data. It might be possible however to extend FGM assumptions to better account for mutational data. This is theoretically challenging in the context of antibiotic resistance because resistance mutations are assumed to be rare. In this article, we show with Escherichia coli how the fitness effects of resistance mutations screened at different doses of nalidixic acid vary across a dose-gradient. We found experimental patterns qualitatively consistent with the basic FGM (rate of resistance across doses, gamma distributed costs) but also unexpected patterns such as a decreasing mean cost of resistance with increasing screen dose. We show how different extensions involving mutational modules and variations in trait covariance across environments, can be discriminated based on these data. Overall, simple extensions of the FGM accounted well for complex mutational effects of resistance mutations across antibiotic doses.

Enhanced Survival of Rifampin- and Streptomycin-Resistant Escherichia coli Inside Macrophages

The evolution of multiple-antibiotic-resistant bacteria is an increasing global problem. Even though mutations causing resistance usually incur a fitness cost in the absence of antibiotics, the magnitude of such costs varies across environments and genomic backgrounds. We studied how the combination of mutations that confer resistance to rifampin (Rif(r)) and streptomycin (Str(r)) affects the fitness of Escherichia coli when it interacts with cells from the immune system, i.e., macrophages (Mϕs). We found that 13 Rif(r) Str(r) doubly resistant genotypes, of the 16 tested, show a survival advantage inside Mϕs, indicating that double resistance can be highly beneficial in this environment. Our results suggest that there are multiple paths to acquire multiple-drug resistance in this context, i.e., if a clone carrying Rif(r) allele H526 or S531 acquires a second mutation conferring Str(r), the resulting double mutant has a high probability of showing increased survival inside Mϕs. On the other hand, we found two cases of sign epistasis between mutations, leading to a significant decrease in bacterial survival. Remarkably, infection of Mϕs with one of these combinations, K88R+H526Y, resulted in an altered pattern of gene expression in the infected Mϕs. This indicates that the fitness effects of resistance may depend on the pattern of gene expression of infected host cells. Notwithstanding the benefits of resistance found inside Mϕs, the Rif(r) Str(r) mutants have massive fitness costs when the bacteria divide outside Mϕs, indicating that the maintenance of double resistance may depend on the time spent within and outside phagocytic cells.

Do tradeoffs structure antibiotic inhibition, resistance, and resource use among soil-borne Streptomyces?

Background

Tradeoffs among competing traits are believed to be crucial to the maintenance of diversity in complex communities. The production of antibiotics to inhibit competitors and resistance to antibiotic inhibition are two traits hypothesized to be critical to microbial fitness in natural habitats, yet data on costs or tradeoffs associated with these traits are limited. In this work we characterized tradeoffs between antibiotic inhibition or resistance capacities and growth efficiencies or niche widths for a broad collection of Streptomyces from soil.

Results

Streptomyces isolates tended to have either very little or very high inhibitory capacity. In contrast, Streptomyces isolates were most commonly resistant to antibiotic inhibition by an intermediate number of other isolates. Streptomyces with either very high antibiotic inhibitory or resistance capacities had less efficient growth and utilized a smaller number of resources for growth (smaller niche width) than those with low inhibition or resistance capacities, suggesting tradeoffs between antibiotic inhibitory or resistance and resource use phenotypes.

Conclusions

This work suggests that life-history tradeoffs may be crucial to the maintenance of the vast diversity of antibiotic inhibitory and resistance phenotypes found among Streptomyces in natural communities.

Electronic supplementary material

The online version of this article (doi:10.1186/s12862-015-0470-6) contains supplementary material, which is available to authorized users.

Constraints on adaptation of Escherichia coli to mixed-resource environments increase over time

Can a population evolved in two resources reach the same fitness in both as specialist populations evolved in each of the individual resources? This question is central to theories of ecological specialization, the maintenance of genetic variation, and sympatric speciation, yet relatively few experiments have examined costs of generalism over long-term adaptation. We tested whether selection in environments containing two resources limits a population's ability to adapt to the individual resources by comparing the fitness of replicate Escherichia coli populations evolved for 6000 generations in the presence of glucose or lactose alone (specialists), or in varying presentations of glucose and lactose together (generalists). We found that all populations had significant fitness increases in both resources, though the magnitude and rate of these increases differed. For the first 4000 generations, most generalist populations increased in fitness as quickly in the individual resources as the corresponding specialist populations. From 5000 generations, however, a widespread cost of adaptation affected all generalists, indicating a growing constraint on their abilities to adapt to two resources simultaneously. Our results indicate that costs of generalism are prevalent, but may influence evolutionary trajectories only after a period of cost-free adaptation.

Multiple Resistance at No Cost: Rifampicin and Streptomycin a Dangerous Liaison in the Spread of Antibiotic Resistance

Evidence is mounting that epistasis is widespread among mutations. The cost of carrying two deleterious mutations, or the advantage of acquiring two beneficial alleles, is typically lower that the sum of their individual effects. Much less is known on epistasis between beneficial and deleterious mutations, even though this is key to the amount of genetic hitchhiking that may occur during evolution. This is particularly important in the context of antibiotic resistance: Most resistances are deleterious, but some can be beneficial and remarkably rifampicin resistance can emerge de novo in populations evolving without antibiotics. Here we show pervasive positive pairwise epistasis on Escherichia coli fitness between beneficial mutations, which confer resistance to rifampicin, and deleterious mutations, which confer resistance to streptomycin. We find that 65% of double resistant strains outcompete sensitive bacteria in an environment devoid of antibiotics. Weak beneficial mutations may therefore overcome strong deleterious mutations and can even render double mutants strong competitors.

Fitness Costs of Drug Resistance Mutations in Multidrug-Resistant Mycobacterium tuberculosis: A Household-Based Case-Control Study

BACKGROUND

The projected long-term prevalence of multidrug-resistant (MDR) tuberculosis depends upon the relative fitness of MDR Mycobacterium tuberculosis strains, compared with non-MDR strains. While many experimental models have tested the in vitro or in vivo fitness costs of various drug resistance mutations, fewer epidemiologic studies have attempted to validate these experimental findings.

METHODS

We performed a case-control study comparing drug resistance-associated mutations from MDR M. tuberculosis strains causing multiple cases in a household to matched MDR strains without evidence of secondary household cases.

RESULTS

Eighty-eight multiple-case and 88 single-case household MDR strains were analyzed for 10 specific drug resistance-associated polymorphisms previously associated with fitness effects. We found that the isoniazid-resistant katG Ser315Thr mutation occurred more than twice as frequently in multiple-case households than in single-case households (odds ratio [OR], 2.39; 95% confidence interval [CI], 1.21-4.70), corroborating previous experimental findings. However, strains carrying both the katG Ser315Thr mutation and the rpsL Lys43Arg mutation were less likely to be found in multiple-case households (OR, 0.09; 95% CI, .01-.73), suggesting a negative epistatic interaction which contrasts previous findings.

CONCLUSIONS

The case-control design presents a useful approach for assessing in vivo fitness effects of drug resistance mutations.

Selection history and epistatic interactions impact dynamics of adaptation to novel environmental stresses

In rapidly changing environments, selection history may impact the dynamics of adaptation. Mutations selected in one environment may result in pleiotropic fitness trade-offs in subsequent novel environments, slowing the rates of adaptation. Epistatic interactions between mutations selected in sequential stressful environments may slow or accelerate subsequent rates of adaptation, depending on the nature of that interaction. We explored the dynamics of adaptation during sequential exposure to herbicides with different modes of action in Chlamydomonas reinhardtii. Evolution of resistance to two of the herbicides was largely independent of selection history. For carbetamide, previous adaptation to other herbicide modes of action positively impacted the likelihood of adaptation to this herbicide. Furthermore, while adaptation to all individual herbicides was associated with pleiotropic fitness costs in stress-free environments, we observed that accumulation of resistance mechanisms was accompanied by a reduction in overall fitness costs. We suggest that antagonistic epistasis may be a driving mechanism that enables populations to more readily adapt in novel environments. These findings highlight the potential for sequences of xenobiotics to facilitate the rapid evolution of multiple-drug and -pesticide resistance, as well as the potential for epistatic interactions between adaptive mutations to facilitate evolutionary rescue in rapidly changing environments.

Origin and proliferation of multiple-drug resistance in bacterial pathogens

SUMMARY

Many studies report the high prevalence of multiply drug-resistant (MDR) strains. Because MDR infections are often significantly harder and more expensive to treat, they represent a growing public health threat. However, for different pathogens, different underlying mechanisms are traditionally used to explain these observations, and it is unclear whether each bacterial taxon has its own mechanism(s) for multidrug resistance or whether there are common mechanisms between distantly related pathogens. In this review, we provide a systematic overview of the causes of the excess of MDR infections and define testable predictions made by each hypothetical mechanism, including experimental, epidemiological, population genomic, and other tests of these hypotheses. Better understanding the cause(s) of the excess of MDR is the first step to rational design of more effective interventions to prevent the origin and/or proliferation of MDR.

Fighting microbial drug resistance: a primer on the role of evolutionary biology in public health

Although microbes have been evolving resistance to antimicrobials for millennia, the spread of resistance in pathogen populations calls for the development of new drugs and treatment strategies. We propose that successful, long-term resistance management requires a better understanding of how resistance evolves in the first place. This is an opportunity for evolutionary biologists to engage in public health, a collaboration that has substantial precedent. Resistance evolution has been an important tool for developing and testing evolutionary theory, especially theory related to the genetic basis of new traits and constraints on adaptation. The present era is no exception. The articles in this issue highlight the breadth of current research on resistance evolution and also its challenges. In this introduction, we review the conceptual advances that have been achieved from studying resistance evolution and describe a path forward.

The genetic basis of the fitness costs of antimicrobial resistance: a meta-analysis approach

The evolution of antibiotic resistance carries a fitness cost, expressed in terms of reduced competitive ability in the absence of antibiotics. This cost plays a key role in the dynamics of resistance by generating selection against resistance when bacteria encounter an antibiotic-free environment. Previous work has shown that the cost of resistance is highly variable, but the underlying causes remain poorly understood. Here, we use a meta-analysis of the published resistance literature to determine how the genetic basis of resistance influences its cost. We find that on average chromosomal resistance mutations carry a larger cost than acquiring resistance via a plasmid. This may explain why resistance often evolves by plasmid acquisition. Second, we find that the cost of plasmid acquisition increases with the breadth of its resistance range. This suggests a potentially important limit on the evolution of extensive multidrug resistance via plasmids. We also find that epistasis can significantly alter the cost of mutational resistance. Overall, our study shows that the cost of antimicrobial resistance can be partially explained by its genetic basis. It also highlights both the danger associated with plasmidborne resistance and the need to understand why resistance plasmids carry a relatively low cost.

A window of opportunity to control the bacterial pathogen Pseudomonas aeruginosa combining antibiotics and phages

The evolution of antibiotic resistance in bacteria is a global concern and the use of bacteriophages alone or in combined therapies is attracting increasing attention as an alternative. Evolutionary theory predicts that the probability of bacterial resistance to both phages and antibiotics will be lower than to either separately, due for example to fitness costs or to trade-offs between phage resistance mechanisms and bacterial growth. In this study, we assess the population impacts of either individual or combined treatments of a bacteriophage and streptomycin on the nosocomial pathogen Pseudomonas aeruginosa. We show that combining phage and antibiotics substantially increases bacterial control compared to either separately, and that there is a specific time delay in antibiotic introduction independent of antibiotic dose, that minimizes both bacterial density and resistance to either antibiotics or phage. These results have implications for optimal combined therapeutic approaches.

Plasmid-encoded tetracycline efflux pump protein alters bacterial stress responses and ecological fitness of Acinetobacter oleivorans

Acquisition of the extracellular tetracycline (TC) resistance plasmid pAST2 affected host gene expression and phenotype in the oil-degrading soil bacterium, Acinetobacter oleivorans DR1. Whole-transcriptome profiling of DR1 cells harboring pAST2 revealed that all the plasmid genes were highly expressed under TC conditions, and the expression levels of many host chromosomal genes were modulated by the presence of pAST2. The host energy burden imposed by replication of pAST2 led to (i) lowered ATP concentrations, (ii) downregulated expression of many genes involved in cellular growth, and (iii) reduced growth rate. Interestingly, some phenotypes were restored by deleting the plasmid-encoded efflux pump gene tetH, suggesting that the membrane integrity changes resulting from the incorporation of efflux pump proteins also resulted in altered host response under the tested conditions. Alteration of membrane integrity by tetH deletion was shown by measuring permeability of fluorescent probe and membrane hydrophobicity. The presence of the plasmid conferred peroxide and superoxide resistance to cells, but only peroxide resistance was diminished by tetH gene deletion, suggesting that the plasmid-encoded membrane-bound efflux pump protein provided peroxide resistance. The downregulation of fimbriae-related genes presumably led to reduced swimming motility, but this phenotype was recovered by tetH gene deletion. Our data suggest that not only the plasmid replication burden, but also its encoded efflux pump protein altered host chromosomal gene expression and phenotype, which also alters the ecological fitness of the host in the environment.

Costs of antibiotic resistance - separating trait effects and selective effects

Antibiotic resistance can impair bacterial growth or competitive ability in the absence of antibiotics, frequently referred to as a ‘cost’ of resistance. Theory and experiments emphasize the importance of such effects for the distribution of resistance in pathogenic populations. However, recent work shows that costs of resistance are highly variable depending on environmental factors such as nutrient supply and population structure, as well as genetic factors including the mechanism of resistance and genetic background. Here, we suggest that such variation can be better understood by distinguishing between the effects of resistance mechanisms on individual traits such as growth rate or yield (‘trait effects’) and effects on genotype frequencies over time (‘selective effects’). We first give a brief overview of the biological basis of costs of resistance and how trait effects may translate to selective effects in different environmental conditions. We then review empirical evidence of genetic and environmental variation of both types of effects and how such variation may be understood by combining molecular microbiological information with concepts from evolution and ecology. Ultimately, disentangling different types of costs may permit the identification of interventions that maximize the cost of resistance and therefore accelerate its decline.

Exposure to phages has little impact on the evolution of bacterial antibiotic resistance on drug concentration gradients

The use of phages for treating bacterial pathogens has recently been advocated as an alternative to antibiotic therapy. Here, we test a hypothesis that bacteria treated with phages may show more limited evolution of antibiotic resistance as the fitness costs of resistance to phages may add to those of antibiotic resistance, further reducing the growth performance of antibiotic-resistant bacteria. We did this by studying the evolution of phage-exposed and phage-free Pseudomonas fluorescens cultures on concentration gradients of single drugs, including cefotaxime, chloramphenicol, and kanamycin. During drug treatment, the level of bacterial antibiotic resistance increased through time and was not affected by the phage treatment. Exposure to phages did not cause slower growth in antibiotic-resistant bacteria, although it did so in antibiotic-susceptible bacteria. We observed significant reversion of antibiotic resistance after drug use being terminated, and the rate of reversion was not affected by the phage treatment. The results suggest that the fitness costs caused by resistance to phages are unlikely to be an important constraint on the evolution of bacterial antibiotic resistance in heterogeneous drug environments. Further studies are needed for the interaction of fitness costs of antibiotic resistance with other factors.

Rates of fitness decline and rebound suggest pervasive epistasis

Unraveling the factors that determine the rate of adaptation is a major question in evolutionary biology. One key parameter is the effect of a new mutation on fitness, which invariably depends on the environment and genetic background. The fate of a mutation also depends on population size, which determines the amount of drift it will experience. Here, we manipulate both population size and genotype composition and follow adaptation of 23 distinct Escherichia coli genotypes. These have previously accumulated mutations under intense genetic drift and encompass a substantial fitness variation. A simple rule is uncovered: the net fitness change is negatively correlated with the fitness of the genotype in which new mutations appear—a signature of epistasis. We find that Fisher's geometrical model can account for the observed patterns of fitness change and infer the parameters of this model that best fit the data, using Approximate Bayesian Computation. We estimate a genomic mutation rate of 0.01 per generation for fitness altering mutations, albeit with a large confidence interval, a mean fitness effect of mutations of −0.01, and an effective number of traits nine in mutS⁻E. coli. This framework can be extended to confront a broader range of models with data and test different classes of fitness landscape models.

The cost of antibiotic resistance depends on evolutionary history in Escherichia coli

BACKGROUND

The persistence of antibiotic resistance depends on the fitness effects of resistance elements in the absence of antibiotics. Recent work shows that the fitness effect of a given resistance mutation is influenced by other resistance mutations on the same genome. However, resistant bacteria acquire additional beneficial mutations during evolution in the absence of antibiotics that do not alter resistance directly but may modify the fitness effects of new resistance mutations.

RESULTS

We experimentally evolved rifampicin-resistant and sensitive Escherichia coli in a drug-free environment, before measuring the effects of new resistance elements on fitness in antibiotic-free conditions. Streptomycin-resistance mutations had small fitness effects in rifampicin-resistant genotypes that had adapted to antibiotic-free growth medium, compared to the same genotypes without adaptation. We observed a similar effect when resistance was encoded by a different mechanism and carried on a plasmid. Antibiotic-sensitive bacteria that adapted to the same conditions showed the same pattern for some resistance elements but not others.

CONCLUSIONS

Epistatic variation of costs of resistance can result from evolution in the absence of antibiotics, as well as the presence of other resistance mutations.

Predation in homogeneous and heterogeneous phage environments affects virulence determinants of Pseudomonas aeruginosa

The rise of bacterial variants in the presence of lytic phages has been one of the basic grounds for evolution studies. However, there are incongruent results among different studies investigating the effect of phage resistance acquisition on bacterial fitness and virulence. We used experimental evolution to generate three classes of Pseudomonas aeruginosa variants under selective pressure from two different homogeneous phage environments and one heterogeneous phage environment. The fitness and virulence determinants of the variants, such as growth, motility, biofilm formation, resistance to oxidative stress, and the production of siderophores and chromophores, changed significantly compared to the control. Variants with similar colony morphology that were developed through different phage treatments have different phenotypic traits. Also, mRNA transcription for genes associated with certain phenotypic traits changed significantly; however, sequencing did not reveal any point mutations in selected gene loci. Furthermore, the appearance of small colony variants and melanogenic variants and the increase in pyocyanin and pyoverdin production for some variants are believed to affect the virulence of the population. The knowledge gained from this study will fundamentally contribute to our understanding of the evolutionary dynamics of bacteria under phage selective pressure which is crucial to the efficient utilization of bacteriophages in medical contexts.

Rifampicin Resistance: Fitness Costs and the Significance of Compensatory Evolution

Seventy years after the introduction of antibiotic chemotherapy to treat tuberculosis, problems caused by drug-resistance in Mycobacterium tuberculosis have become greater than ever. The discovery and development of novel drugs and drug combination therapies will be critical to managing these problematic infections. However, to maintain effective therapy in the long-term and to avoid repeating the mistakes of the past, it is essential that we understand how resistance to antibiotics evolves in M. tuberculosis. Recent studies in genomics and genetics, employing both clinical isolates and model organisms, have revealed that resistance to the frontline anti-tuberculosis drug, rifampicin, is very strongly associated with the selection of fitness compensatory mutations in the different subunits of RNA polymerase. This mode of resistance evolution may also apply to other drugs, and knowledge of the rates and mechanisms could be used to design improved diagnostics and by tracking the evolution of infectious strains, to inform the optimization of therapies.

Epistasis between antibiotic resistance mutations drives the evolution of extensively drug-resistant tuberculosis

BACKGROUND AND OBJECTIVES

Multidrug resistant (MDR) bacteria are a growing threat to global health. Studies focusing on single antibiotics have shown that drug resistance is often associated with a fitness cost in the absence of drug. However, little is known about the fitness cost associated with resistance to multiple antibiotics.

METHODOLOGY

We used Mycobacterium smegmatis as a model for human tuberculosis (TB) and an in vitro competitive fitness assay to explore the combined fitness effects and interaction between mutations conferring resistance to rifampicin (RIF) and ofloxacin (OFX); two of the most important first- and second-line anti-TB drugs, respectively.

RESULTS

We found that 4 out of 17 M. smegmatis mutants (24%) resistant to RIF and OFX showed a statistically significantly higher or lower competitive fitness than expected when assuming a multiplicative model of fitness effects of each individual mutation. Moreover, 6 out of the 17 double drug-resistant mutants (35%) had a significantly higher fitness than at least one of the corresponding single drug-resistant mutants. The particular combinations of resistance mutations associated with no fitness deficit in M. smegmatis were the most frequent among 151 clinical isolates of MDR and extensively drug-resistant (XDR) Mycobacterium tuberculosis from South Africa.

CONCLUSIONS AND IMPLICATIONS

Our results suggest that epistasis between drug resistance mutations in mycobacteria can lead to MDR strains with no fitness deficit, and that these strains are positively selected in settings with a high burden of drug-resistant TB. Taken together, our findings support a role for epistasis in the evolution and epidemiology of MDR- and XDR-TB.