History of antibiotic adaptation influences microbial evolutionary dynamics during subsequent treatment

Using phage to drive selections toward restoring antibiotic sensitivity in Pseudomonas aeruginosa via chromosomal deletions

Phage therapy has re-emerged in modern medicine as a robust antimicrobial strategy in response to the increasing prevalence of antimicrobial-resistant bacteria. However, bacterial resistance to phages can also arise via a variety of molecular mechanisms. In fact, several clinical studies on phage therapy have reported the occurrence of phage-resistant variants, representing a significant concern for the successful development of phage-based therapies. In this context, the fitness trade-offs between phage and antibiotic resistance have revealed new avenues in the field of phage therapy as a countermeasure against phage resistance. This strategy forces to restore the antibiotic susceptibility of antimicrobial-resistant bacteria as compensation for the development of phage resistance. Here, we present the key achievements of these fitness trade-offs, notably focusing on the enhancement of antibiotic sensitivity through the induction of large chromosomal deletions by bacteriophage infection. We also describe the challenges of this strategy that need to be overcome to promote favorable therapeutic outcomes and discuss future directions. The insights gained from the trade-offs between phage and antibiotic sensitivity will help maximize the potential of phage therapy for the treatment of infectious diseases.

Could traces of fluoroquinolones in food induce ciprofloxacin resistance in Escherichia coli and Klebsiella pneumoniae? An in vivo study in Galleria mellonella with important implications for maximum residue limits in food

We hypothesized that the residual concentrations of fluoroquinolones allowed in food (acceptable daily intake-ADIs) could select for ciprofloxacin resistance in our resident microbiota. We developed models of chronic Escherichia coli and Klebsiella pneumoniae infection in Galleria mellonella larvae and exposed them to ADI doses of ciprofloxacin via single dosing and daily dosing regimens. The emergence of ciprofloxacin resistance was assessed via isolation of the target bacteria in selective agar plates. Exposure to as low as one-tenth of the ADI dose of the single and daily dosing regimens of ciprofloxacin resulted in the selection of ciprofloxacin resistance in K. pneumoniae but not E. coli. This resistance was associated with cross-resistance to doxycycline and ceftriaxone. Whole genome sequencing revealed inactivating mutations in the transcription repressors, ramR and rrf2, as well as mutations in gyrA and gyrB. We found that ciprofloxacin doses 10-fold lower than those classified as acceptable for daily intake could induce resistance to ciprofloxacin in K. pneumoniae. These results suggest that it would be prudent to include the induction of antimicrobial resistance as a significant criterion for determining ADIs and the associated maximum residue limits in food.IMPORTANCEThis study found that the concentrations of ciprofloxacin/enrofloxacin allowed in food can induce de novo ciprofloxacin resistance in Klebsiella pneumoniae. This suggests that it would be prudent to reconsider the criteria used to determine "safe" upper concentration limits in food.

The evolution of diverse antimicrobial responses in vancomycin-intermediate Staphylococcus aureus and its therapeutic implications

Staphylococcus aureus causes endocarditis, osteomyelitis, and bacteremia. Clinicians often prescribe vancomycin as an empiric therapy to account for methicillin-resistant S. aureus (MRSA) and narrow treatment based on culture susceptibility results. However, these results reflect a single time point before empiric treatment and represent a limited subset of the total bacterial population within the patient. Thus, while they may indicate that the infection is susceptible to a particular drug, this recommendation may no longer be accurate during therapy. Here, we addressed how antibiotic susceptibility changes over time by accounting for evolution. We evolved 18 methicillin-susceptible S. aureus (MSSA) populations under increasing vancomycin concentrations until they reached intermediate resistance levels. Sequencing revealed parallel mutations that affect cell membrane stress response and cell-wall biosynthesis. The populations exhibited repeated cross-resistance to daptomycin and varied responses to meropenem, gentamicin, and nafcillin. We accounted for this variability by deriving likelihood estimates that express a population's probability of exhibiting a drug response following vancomycin treatment. Our results suggest antistaphylococcal penicillins are preferable first-line treatments for MSSA infections but also highlight the inherent uncertainty that evolution poses to effective therapies. Infections may take varied evolutionary paths; therefore, considering evolution as a probabilistic process should inform our therapeutic choices.

Tolfenpyrad displays Francisella-targeted antibiotic activity that requires an oxidative stress response regulator for sensitivity

IMPORTANCE

Francisella species are highly pathogenic bacteria that pose a threat to global health security. These bacteria can be made resistant to antibiotics through facile methods, and we lack a safe and protective vaccine. Given their history of development as bioweapons, new treatment options must be developed to bolster public health preparedness. Here, we report that tolfenpyrad, a pesticide that is currently in use worldwide, effectively inhibits the growth of Francisella. This drug has an extensive history of use and a plethora of safety and toxicity data, making it a good candidate for development as an antibiotic. We identified mutations in Francisella novicida that confer resistance to tolfenpyrad and characterized a transcriptional regulator that is required for sensitivity to both tolfenpyrad and reactive oxygen species.

Ribosome-binding antibiotics increase bacterial longevity and growth efficiency

Antibiotics, by definition, reduce bacterial growth rates in optimal culture conditions; however, the real-world environments bacteria inhabit see rapid growth punctuated by periods of low nutrient availability. How antibiotics mediate population decline during these periods is poorly understood. Bacteria cannot optimize for all environmental conditions because a growth-longevity tradeoff predicts faster growth results in faster population decline, and since bacteriostatic antibiotics slow growth, they should also mediate longevity. We quantify how antibiotics, their targets, and resistance mechanisms influence longevity using populations of Escherichia coli and, as the tradeoff predicts, populations are maintained for longer if they encounter ribosome-binding antibiotics doxycycline and erythromycin, a finding that is not observed using antibiotics with alternative cellular targets. This tradeoff also predicts resistance mechanisms that increase growth rates during antibiotic treatment could be detrimental during nutrient stresses, and indeed, we find resistance by ribosomal protection removes benefits to longevity provided by doxycycline. We therefore liken ribosomal protection to a "Trojan horse" because it provides protection from an antibiotic but, during nutrient stresses, it promotes the demise of the bacteria. Seeking mechanisms to support these observations, we show doxycycline promotes efficient metabolism and reduces the concentration of reactive oxygen species. Seeking generality, we sought another mechanism that affects longevity and we found the number of doxycycline targets, namely, the ribosomal RNA operons, mediates growth and longevity even without antibiotics. We conclude that slow growth, as observed during antibiotic treatment, can help bacteria overcome later periods of nutrient stress.

Doxycycline PEP can induce doxycycline resistance in Klebsiella pneumoniae in a Galleria mellonella model of PEP

Background

Four randomized controlled trials have now established that doxycycline post exposure (sex) prophylaxis (PEP) can reduce the incidence of chlamydia and syphilis in men who have sex with men. These studies have concluded that the risk of selecting for antimicrobial resistance is low. We evaluated this risk in vitro and in vivo using a Galleria mellonella infection model.

Methods

We evaluated how long it took for doxycycline resistance to emerge during passage on doxycycline containing agar plates in 4 species - Escherichia coli, Klebsiella pneumoniae, Neisseria gonorrhoeae and Neisseria subflava. We then assessed if K. pneumoniae could acquire resistance to doxycycline (and cross resistance to other antimicrobials) during intermittent exposure to doxycycline in a Galleria mellonella model of doxycycline PEP.

Results

In our passage experiments, we found that resistance first emerged in K. pneumoniae. By day 7 the K. pneumoniae MIC had increased from 2 mg/L to a median of 96 mg/L (IQR 64-96). Under various simulations of doxycycline PEP in the G. mellonella model, the doxycycline MIC of K. pneumoniae increased from 2 mg/L to 48 mg/L (IQR 48-84). Ceftriaxone and ciprofloxacin MICs increased over ten-fold. Whole genome sequencing revealed acquired mutations in ramR which regulates the expression of the AcrAB-TolC efflux pump.

Conclusion

Doxycycline PEP can select for doxycycline, ceftriaxone and ciprofloxacin resistance in K. pneumoniae in a G. mellonella model. The emergent ramR mutations were similar to those seen in circulating strains of K. pneumoniae. These findings suggest that we need to assess the effect of doxycycline PEP on resistance induction on a broader range of bacterial species than has hitherto been the case.

Understanding Antimicrobial Resistance Using Genome-Scale Metabolic Modeling

The urgent necessity to fight antimicrobial resistance is universally recognized. In the search of new targets and strategies to face this global challenge, a promising approach resides in the study of the cellular response to antimicrobial exposure and on the impact of global cellular reprogramming on antimicrobial drugs' efficacy. The metabolic state of microbial cells has been shown to undergo several antimicrobial-induced modifications and, at the same time, to be a good predictor of the outcome of an antimicrobial treatment. Metabolism is a promising reservoir of potential drug targets/adjuvants that has not been fully exploited to date. One of the main problems in unraveling the metabolic response of cells to the environment resides in the complexity of such metabolic networks. To solve this problem, modeling approaches have been developed, and they are progressively gaining in popularity due to the huge availability of genomic information and the ease at which a genome sequence can be converted into models to run basic phenotype predictions. Here, we review the use of computational modeling to study the relationship between microbial metabolism and antimicrobials and the recent advances in the application of genome-scale metabolic modeling to the study of microbial responses to antimicrobial exposure.

The evolution of antibiotic resistance is associated with collateral drug phenotypes in Mycobacterium tuberculosis

The increasing incidence of drug resistance in Mycobacterium tuberculosis has diminished the efficacy of almost all available antibiotics, complicating efforts to combat the spread of this global health burden. Alongside the development of new drugs, optimised drug combinations are needed to improve treatment success and prevent the further spread of antibiotic resistance. Typically, antibiotic resistance leads to reduced sensitivity, yet in some cases the evolution of drug resistance can lead to enhanced sensitivity to unrelated drugs. This phenomenon of collateral sensitivity is largely unexplored in M. tuberculosis but has the potential to identify alternative therapeutic strategies to combat drug-resistant strains that are unresponsive to current treatments. Here, by using drug susceptibility profiling, genomics and evolutionary studies we provide evidence for the existence of collateral drug sensitivities in an isogenic collection M. tuberculosis drug-resistant strains. Furthermore, in proof-of-concept studies, we demonstrate how collateral drug phenotypes can be exploited to select against and prevent the emergence of drug-resistant strains. This study highlights that the evolution of drug resistance in M. tuberculosis leads to collateral drug responses that can be exploited to design improved drug regimens.

Assessment of phenotypic heterogeneity in Salmonella Typhimurium preadapted to ciprofloxacin and tetracycline

Bacterial population exposed to stressful antibiotic conditions consists of various subpopulations such as tolerant, persister, and resistant cells. The aim of this study was to evaluate the phenotypic heterogeneity of Salmonella Typhimurium preadapted to sublethal concentrations of antibiotics. Salmonella Typhimurium cells were treated with 1/2 × MIC of antibiotics for the first 48 h and successively 1 × MIC for the second 24 h at 37°C, including untreated control (CON), no antibiotic and 1 × MIC ciprofloxacin (NON-CIP), 1/2 × MIC ciprofloxacin and 1 × MIC ciprofloxacin (CIP-CIP), 1/2 × MIC tetracycline and 1 × MIC ciprofloxacin (TET-CIP), no antibiotic and 1 × MIC tetracycline (NON-TET), 1/2 × MIC ciprofloxacin and 1 × MIC tetracycline (CIP-TET), and 1/2 × MIC tetracycline and 1 × MIC tetracycline (TET-TET). All treatments were evaluated by antibiotic susceptibility, ATP level, relative fitness, cross-resistance, and persistence. S. Typhimurium cells were more susceptible to non-adapted NON-CIP and NON-TET (>3-log reduction) than pre-adapted CIP-CIP, TET-CIP, CIP-TET, and TET-TET. CON exhibited the highest ATP level, corresponding to the viable cell number. The relative fitness levels were more than 0.95 for all treatments, except for NON-CIP (0.78). The resistance to ciprofloxacin and tetracycline was increased at all treatments with the exception of NON-TET. The persister cells were noticeably induced at CIP-TET treatment, showing more than 5 log CFU mL-1. The results suggest that the antibiotic preadaptation led to heterogeneous populations including persisters that can develop to resistance. This study provides new insight in the bacterial persistence associated with their potential risk and paves the way to design antibiotic therapy targeting dormant bacteria.

Sequential antibiotic therapy in the laboratory and in the patient

Laboratory experiments suggest that rapid cycling of antibiotics during the course of treatment could successfully counter resistance evolution. Drugs involving collateral sensitivity could be particularly suitable for such therapies. However, the environmental conditions in vivo differ from those in vitro. One key difference is that drugs can be switched abruptly in the laboratory, while in the patient, pharmacokinetic processes lead to changing antibiotic concentrations including periods of dose overlaps from consecutive administrations. During such overlap phases, drug-drug interactions may affect the evolutionary dynamics. To address the gap between the laboratory and potential clinical applications, we set up two models for comparison-a 'laboratory model' and a pharmacokinetic-pharmacodynamic 'patient model'. The analysis shows that in the laboratory, the most rapid cycling suppresses the bacterial population always at least as well as other regimens. For patient treatment, however, a little slower cycling can sometimes be preferable if the pharmacodynamic curve is steep or if drugs interact antagonistically. When resistance is absent prior to treatment, collateral sensitivity brings no substantial benefit unless the cell division rate is low and drug cycling slow. By contrast, drug-drug interactions strongly influence the treatment efficiency of rapid regimens, demonstrating their importance for the optimal choice of drug pairs.

Towards evolutionary predictions: Current promises and challenges

Evolution has traditionally been a historical and descriptive science, and predicting future evolutionary processes has long been considered impossible. However, evolutionary predictions are increasingly being developed and used in medicine, agriculture, biotechnology and conservation biology. Evolutionary predictions may be used for different purposes, such as to prepare for the future, to try and change the course of evolution or to determine how well we understand evolutionary processes. Similarly, the exact aspect of the evolved population that we want to predict may also differ. For example, we could try to predict which genotype will dominate, the fitness of the population or the extinction probability of a population. In addition, there are many uses of evolutionary predictions that may not always be recognized as such. The main goal of this review is to increase awareness of methods and data in different research fields by showing the breadth of situations in which evolutionary predictions are made. We describe how diverse evolutionary predictions share a common structure described by the predictive scope, time scale and precision. Then, by using examples ranging from SARS-CoV2 and influenza to CRISPR-based gene drives and sustainable product formation in biotechnology, we discuss the methods for predicting evolution, the factors that affect predictability and how predictions can be used to prevent evolution in undesirable directions or to promote beneficial evolution (i.e. evolutionary control). We hope that this review will stimulate collaboration between fields by establishing a common language for evolutionary predictions.

The Effects of Antibiotic Combination Treatments on Pseudomonas aeruginosa Tolerance Evolution and Coexistence with Stenotrophomonas maltophilia

The Pseudomonas aeruginosa bacterium is a common pathogen of cystic fibrosis (CF) patients due to its ability to evolve resistance to antibiotics during treatments. While P. aeruginosa resistance evolution is well-characterized in monocultures, it is less well-understood in polymicrobial CF infections. Here, we investigated how exposure to ciprofloxacin, colistin, or tobramycin antibiotics, administered at sub-minimum inhibitory concentration (MIC) doses, both alone and in combination, shaped the tolerance evolution of P. aeruginosa (PAO1 lab and clinical CF LESB58 strains) in the absence and presence of a commonly co-occurring species, Stenotrophomonas maltophilia. The increases in antibiotic tolerances were primarily driven by the presence of that antibiotic in the treatment. We observed a reciprocal cross-tolerance between ciprofloxacin and tobramycin, and, when combined, the selected antibiotics increased the MICs for all of the antibiotics. Though the presence of S. maltophilia did not affect the tolerance or the MIC evolution, it drove P. aeruginosa into extinction more frequently in the presence of tobramycin due to its relatively greater innate tobramycin tolerance. In contrast, P. aeruginosa dominated and drove S. maltophilia extinct in most other treatments. Together, our findings suggest that besides driving high-level antibiotic tolerance evolution, sub-MIC antibiotic exposure can alter competitive bacterial interactions, leading to target pathogen extinctions in multispecies communities. IMPORTANCE Cystic fibrosis (CF) is a genetic condition that results in thick mucus secretions in the lungs that are susceptible to chronic bacterial infections. The bacterial pathogen Pseudomonas aeruginosa is often associated with morbidity in CF and is difficult to treat due to its high resistance to antibiotics. The resistance evolution of Pseudomonas aeruginosa is poorly understood in polymicrobial infections that are typical of CF. To study this, we exposed P. aeruginosa to sublethal concentrations of ciprofloxacin, colistin, or tobramycin antibiotics in the absence and presence of a commonly co-occurring CF species, Stenotrophomonas maltophilia. We found that low-level antibiotic concentrations selected for high-level antibiotic resistance. While P. aeruginosa dominated in most antibiotic treatments, S. maltophilia drove it into extinction in the presence of tobramycin due to an innately higher tobramycin resistance. Our findings suggest that, besides driving high-level antibiotic tolerance evolution, sublethal antibiotic exposure can magnify competition in bacterial communities, which can lead to target pathogen extinctions in multispecies communities.

Analysis of the evolution of resistance to multiple antibiotics enables prediction of the Escherichia coli phenotype-based fitness landscape

The fitness landscape represents the complex relationship between genotype or phenotype and fitness under a given environment, the structure of which allows the explanation and prediction of evolutionary trajectories. Although previous studies have constructed fitness landscapes by comprehensively studying the mutations in specific genes, the high dimensionality of genotypic changes prevents us from developing a fitness landscape capable of predicting evolution for the whole cell. Herein, we address this problem by inferring the phenotype-based fitness landscape for antibiotic resistance evolution by quantifying the multidimensional phenotypic changes, i.e., time-series data of resistance for eight different drugs. We show that different peaks of the landscape correspond to different drug resistance mechanisms, thus supporting the validity of the inferred phenotype-fitness landscape. We further discuss how inferred phenotype-fitness landscapes could contribute to the prediction and control of evolution. This approach bridges the gap between phenotypic/genotypic changes and fitness while contributing to a better understanding of drug resistance evolution.

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.

Assessment of a plasmid conjugation procedure to monitor horizontal transfer of an extended-spectrum β-lactamase resistance gene under food chain scenarios

Plasmids are relevant reservoirs of antimicrobial resistance genes (ARGs) which confer adaptive advantages to their host and can be horizontally transferred. The aims of this study were to develop a conjugation procedure to monitor the horizontal transfer of a 193 kb plasmid containing the extended-spectrum β-lactamase production gene bla _CTX-M-14 between two Escherichia coli strains under a range of food chain-related scenarios, including temperature (20-37 °C), pH (5.0-9.0) or the presence of some biocidal agents (benzalkonium chloride, sodium hypochlorite or peracetic acid). The average conjugation rate in LB broth after 18 h at 37 °C was 2.09e-04 and similar rates were observed in a food matrix (cow's milk). The conjugation was reduced at temperatures below 37 °C, at alkaline pH (especially at pH 9.0) or in the presence of benzalkonium chloride. Peracetic acid and sodium hypochlorite slightly increased conjugation rates, which reached 5.59e-04 and 6.77e-03, respectively. The conjugation procedure described can be used to identify risk scenarios leading to an enhanced ARGs transmission via plasmid conjugation, as well as to identify novel intervention strategies impairing plasmid conjugation and tackling antimicrobial resistance.

Historical contingency drives compensatory evolution and rare reversal of phage resistance

Bacteria and lytic viruses (phages) engage in highly dynamic coevolutionary interactions over time, yet we have little idea of how transient selection by phages might shape the future evolutionary trajectories of their host populations. To explore this question, we generated genetically diverse phage-resistant mutants of the bacterium Pseudomonas syringae. We subjected the panel of mutants to prolonged experimental evolution in the absence of phages. Some populations re-evolved phage sensitivity, whereas others acquired compensatory mutations that reduced the costs of resistance without altering resistance levels. To ask whether these outcomes were driven by the initial genetic mechanisms of resistance, we next evolved independent replicates of each individual mutant in the absence of phages. We found a strong signature of historical contingency: some mutations were highly reversible across replicate populations, whereas others were highly entrenched. Through whole-genome sequencing of bacteria over time, we also found that populations with the same resistance gene acquired more parallel sets of mutations than populations with different resistance genes, suggesting that compensatory adaptation is also contingent on how resistance initially evolved. Our study identifies an evolutionary ratchet in bacteria–phage coevolution and may explain previous observations that resistance persists over time in some bacterial populations but is lost in others. We add to a growing body of work describing the key role of phages in the ecological and evolutionary dynamics of their host communities. Beyond this specific trait, our study provides a new insight into the genetic architecture of historical contingency, a crucial component of interpreting and predicting evolution.

Probing the growth and mechanical properties of Bacillus subtilis biofilms through genetic mutation strategies

Bacterial communities form biofilms on various surfaces by synthesizing a cohesive and protective extracellular matrix, and these biofilms protect microorganisms against harsh environmental conditions. Bacillus subtilis is a widely used experimental species, and its biofilms are used as representative models of beneficial biofilms. Specifically, B. subtilis biofilms are known to be rich in extracellular polymeric substances (EPS) and other biopolymers such as DNA and proteins like the amyloid protein TasA and the hydrophobic protein BslA. These materials, which form an interconnected, cohesive, three-dimensional polymer network, provide the mechanical stability of biofilms and mediate their adherence to surfaces among other functional contributions. Here, we explored how genetically-encoded components specifically contribute to regulate the growth status, mechanical properties, and antibiotic resistance of B. subtilis biofilms, thereby establishing a solid empirical basis for understanding how various genetic engineering efforts are likely to affect the structure and function of biofilms. We noted discrete contributions to biofilm morphology, mechanical properties, and survival from major biofilm components such as EPS, TasA and BslA. For example, EPS plays an important role in maintaining the stability of the mechanical properties and the antibiotic resistance of biofilms, whereas BslA has a significant impact on the resolution that can be obtained for printing applications. This work provides a deeper understanding of the internal interactions of biofilm components through systematic genetic manipulations. It thus not only broadens the application prospects of beneficial biofilms, but also serves as the basis of future strategies for targeting and effectively removing harmful biofilms.

Quantifying the impact of ecological memory on the dynamics of interacting communities

Ecological memory refers to the influence of past events on the response of an ecosystem to exogenous or endogenous changes. Memory has been widely recognized as a key contributor to the dynamics of ecosystems and other complex systems, yet quantitative community models often ignore memory and its implications.

Recent modeling studies have shown how interactions between community members can lead to the emergence of resilience and multistability under environmental perturbations. We demonstrate how memory can be introduced in such models using the framework of fractional calculus. We study how the dynamics of a well-characterized interaction model is affected by gradual increases in ecological memory under varying initial conditions, perturbations, and stochasticity.

Our results highlight the implications of memory on several key aspects of community dynamics. In general, memory introduces inertia into the dynamics. This favors species coexistence under perturbation, enhances system resistance to state shifts, mitigates hysteresis, and can affect system resilience both ways depending on the time scale considered. Memory also promotes long transient dynamics, such as long-standing oscillations and delayed regime shifts, and contributes to the emergence and persistence of alternative stable states. Our study highlights the fundamental role of memory in communities, and provides quantitative tools to introduce it in ecological models and analyse its impact under varying conditions.

An ecosystem is said to exhibit ecological memory when its future states do not only depend on its current state but also on its initial state and trajectory. Memory may arise through various mechanisms as organisms adapt to their environment, modify it, and accumulate biotic and abiotic material. It may also emerge from phenotypic heterogeneity at the population level. Despite its commonness in nature, ecological memory and its potential influence on ecosystem dynamics have been so far overlooked in many applied contexts. Here, we use modeling to investigate how memory can influence the dynamics, composition, and stability landscape of communities. We incorporate long-term memory effects into a multi-species model recently introduced to investigate alternative stable states in microbial communities. We assess the impact of memory on key aspects of model behavior and further examine our findings using a model parameterized by empirical data from the human gut microbiota. Our approach for modeling long-term memory and studying its implications has the potential to improve our understanding of microbial community dynamics and ultimately our ability to predict, manipulate, and experimentally design microbial ecosystems. It could also be applied more broadly in the study of systems composed of interacting components.

Strong selective environments determine evolutionary outcome in time‐dependent fitness seascapes

The impact of fitness landscape features on evolutionary outcomes has attracted considerable interest in recent decades. However, evolution often occurs under time‐dependent selection in so‐called fitness seascapes where the landscape is under flux. Fitness seascapes are an inherent feature of natural environments, where the landscape changes owing both to the intrinsic fitness consequences of previous adaptations and extrinsic changes in selected traits caused by new environments. The complexity of such seascapes may curb the predictability of evolution. However, empirical efforts to test this question using a comprehensive set of regimes are lacking. Here, we employed an in vitro microbial model system to investigate differences in evolutionary outcomes between time‐invariant and time‐dependent environments, including all possible temporal permutations, with three subinhibitory antimicrobials and a viral parasite (phage) as selective agents. Expectedly, time‐invariant environments caused stronger directional selection for resistances compared to time‐dependent environments. Intriguingly, however, multidrug resistance outcomes in both cases were largely driven by two strong selective agents (rifampicin and phage) out of four agents in total. These agents either caused cross‐resistance or obscured the phenotypic effect of other resistance mutations, modulating the evolutionary outcome overall in time‐invariant environments and as a function of exposure epoch in time‐dependent environments. This suggests that identifying strong selective agents and their pleiotropic effects is critical for predicting evolution in fitness seascapes, with ramifications for evolutionarily informed strategies to mitigate drug resistance evolution.

Influence of Sub-Inhibitory Dosage of Cefotaxime on Multidrug Resistant Staphylococcus haemolyticus Isolated from Sick Neonatal Care Unit

Staphylococcus haemolyticus has emerged to be a frequently encountered late-onset sepsis pathogen among newborn infants. Critical care of neonates involves substantial usage of antibiotics and these pathogens are often exposed to sub-optimal doses of antibiotics which can augment maintenance of selection determinants and a range of physiological effects, prime among them being biofilm formation. Therefore, in this study, the outcome of a sub-inhibitory dosage of a commonly prescribed third-generation antibiotic, cefotaxime (CTX), on multidrug resistant (MDR) S. haemolyticus, was investigated. A total of 19 CTX-resistant, MDR and 5 CTX-susceptible strains isolated from neonates were included. Biofilm-forming abilities of S. haemolyticus isolates in the presence of sub-optimal CTX (30 μg/mL) were determined by crystal violet assays and extracellular DNA (eDNA) quantitation. CTX was found to significantly enhance biofilm production among the non-susceptible isolates (p-valueWilcoxintest—0.000008) with an increase in eDNA levels (p-valueWilcoxintest—0.000004). Further, in the absence of antibiotic selection in vitro, populations of MDR isolates, JNM56C1 and JNM60C2 remained antibiotic non-susceptible after >500 generations of growth. These findings demonstrate that sub-optimal concentration of CTX induces biofilm formation and short-term non-exposure to antibiotics does not alter non-susceptibility among S. haemolyticus isolates under the tested conditions.

Bactericidal and antioxidant effects of essential oils from Satureja montana L., Myristica fragrans H. AND Cymbopogon flexuosus

The extraction and characterization of the essential oils (EO) from Satureja montana L., Myristica fragrans H. and Cymbopogon flexuosus and the determination of their antibacterial and antioxidante activities were achieved. The EO were identified by gas chromatography/mass spectrometry and quantified by gas chromatography using a flame ionization detector. The antibacterial potential against Escherichia coli and Staphylococcus aureus was evaluated by cell susceptibility assays and by scanning electron microscopy. The antioxidant activity was evaluated by the 2,2-diphenyl-1-picrylhydrazyl assay, by β-carotene bleaching and by determining the reducing power. Borneol (36.18%), γ-terpineol (12.66%), and carvacrol (11.07%) were the principal components in the EO from S. montana, and sabinene (49.23%) and α-pinene (13.81%) were found in the EO from M. fragrans. Geranial (59.66%) and neral (38.98%) isomers were the only major components in the EO from C. flexuosus. The EO from S. montana was effective against E. coli, with minimum inhibitory and bactericidal concentrations (MIC and MBC) of 6.25 µl mL^-1 , whereas bactericidal potential against both was observed for the EO from M. fragrans; MIC = 6.25 ml mL^-1 for S. aureus and MBC = 12.5 µL mL^-1 for E. coli. A significant protective role on lipid substrates in the β-carotene bleaching assay was seen for the EO from S. montana and M. fragrans. Overall, such EO can be promising agents against pathogenic bacteria and for protecting biomolecules during oxidative stress.

Antimicrobial Stewardship from Health Professionals' Perspective: Awareness, Barriers, and Level of Implementation of the Program

This study aimed to evaluate health professionals' perceptions regarding the level of implementation of the Antimicrobials Stewardship (AMS) programs in Jordanian tertiary hospitals and to assess the perceived barriers to its implementation. During this cross-sectional study, a total of 157 healthcare providers agreed to participate (response rate 96.3%). Participants were asked to complete an electronic survey after meeting them at their working sites. Only 43.9% of the healthcare providers (n = 69) reported having an AMS committee in their hospital settings. The results suggested that private hospitals have significantly better AMS implementation compared to public hospitals among four areas (p ≤ 0.05). Moreover, the results showed that the most widely available strategies to implement AMS were infectious disease/microbiology advice (n = 112, 71.3%), and treatment guidelines (n = 111, 70.7%). Additionally, the study revealed that the main barrier to AMS implementation was the lack of information technology support (n = 125, 79.6%). These findings could draw managers' attention to the importance of AMS and support the health care provider's practice of AMS in Jordanian tertiary hospitals by making the right decisions and the required modifications regarding the strategies needed for the implementation of AMS programs.

Revisiting Antibiotic Resistance: Mechanistic Foundations to Evolutionary Outlook

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

The Effects of Sub-inhibitory Antibiotic Concentrations on Pseudomonas aeruginosa: Reduced Susceptibility Due to Mutations

Pseudomonas aeruginosa chronically infects in the lungs of people with cystic fibrosis and other forms of lung disease. Infections are treated with antibiotics, but over time, the bacteria acquire mutations that reduce their antibiotic susceptibility. The effects of inhibitory amounts of antibiotics in selecting for antibiotic-resistant mutants have been well studied. However, the concentrations of antibiotics that reach infecting bacteria can be sub-inhibitory and but may nonetheless promote emergence of antibiotic-resistant bacteria. Therefore, the aim of this research was to investigate the effects of sub-inhibitory concentrations of antibiotics on the antibiotic susceptibility of P. aeruginosa. Two P. aeruginosa reference strains, PAO1 and PA14, and six isolates from individuals with cystic fibrosis were studied. The bacteria were passaged in the presence of antibiotics (ceftazidime, ciprofloxacin, meropenem or tobramycin) at sub-inhibitory amounts. Fifteen populations of bacteria (up to five per strain) were exposed to each of the four antibiotics. Antibiotic susceptibility was determined following 10 passages on agar supplemented with antibiotic and compared with susceptibility prior to antibiotic exposure. Antibiotic exposure resulted in susceptibility being significantly (>2-fold) reduced for 13 of the 60 populations. Seven samples had reduced susceptibility to ciprofloxacin, three to tobramycin, two to ceftazidime and one to meropenem. Whole-genome sequencing revealed the mutations arising following antibiotic exposure. Mutants with reduced antibiotic susceptibility had mutations in genes known to affect antibiotic resistance, including regulators of efflux pumps (mexR, mexS, mexZ and nalC) and the fusA1 gene that is associated with aminoglycoside resistance. Genes not previously associated with resistance, including gacS, sigX and crfX and two genes with no known function, were also mutated in some isolates with reduced antibiotic susceptibility. Our results show that exposure to sub-inhibitory amounts of antibiotics can select for mutations that reduce the susceptibility of P. aeruginosa to antibiotics and that the profile of mutations is different from that arising during selection with inhibitory antibiotic concentrations. It is likely that exposure to sub-inhibitory amounts of antibiotics during infection contributes to P. aeruginosa becoming antibiotic-resistant.

β-lactam Resistance in Pseudomonas aeruginosa: Current Status, Future Prospects

Pseudomonas aeruginosa is a major opportunistic pathogen, causing a wide range of acute and chronic infections. β-lactam antibiotics including penicillins, carbapenems, monobactams, and cephalosporins play a key role in the treatment of P. aeruginosa infections. However, a significant number of isolates of these bacteria are resistant to β-lactams, complicating treatment of infections and leading to worse outcomes for patients. In this review, we summarize studies demonstrating the health and economic impacts associated with β-lactam-resistant P. aeruginosa. We then describe how β-lactams bind to and inhibit P. aeruginosa penicillin-binding proteins that are required for synthesis and remodelling of peptidoglycan. Resistance to β-lactams is multifactorial and can involve changes to a key target protein, penicillin-binding protein 3, that is essential for cell division; reduced uptake or increased efflux of β-lactams; degradation of β-lactam antibiotics by increased expression or altered substrate specificity of an AmpC β-lactamase, or by the acquisition of β-lactamases through horizontal gene transfer; and changes to biofilm formation and metabolism. The current understanding of these mechanisms is discussed. Lastly, important knowledge gaps are identified, and possible strategies for enhancing the effectiveness of β-lactam antibiotics in treating P. aeruginosa infections are considered.

Polygenic Adaptation and Clonal Interference Enable Sustained Diversity in Experimental Pseudomonas aeruginosa Populations

How biodiversity arises and can be maintained in asexual microbial populations growing on a single resource remains unclear. Many models presume that beneficial genotypes will outgrow others and purge variation via selective sweeps. Environmental structure like that found in biofilms, which are associated with persistence during infection and other stressful conditions, may oppose this process and preserve variation. We tested this hypothesis by evolving Pseudomonas aeruginosa populations in biofilm-promoting arginine media for 3 months, using both a bead model of the biofilm life cycle and planktonic serial transfer. Surprisingly, adaptation and diversification were mostly uninterrupted by fixation events that eliminate diversity, with hundreds of mutations maintained at intermediate frequencies. The exceptions included genotypes with mutator alleles that also accelerated genetic diversification. Despite the rarity of hard sweeps, a remarkable 40 genes acquired parallel mutations in both treatments and often among competing genotypes within a population. These incomplete soft sweeps include several transporters (including pitA, pntB, nosD, and pchF) suggesting adaptation to the growth media that becomes highly alkaline during growth. Further, genes involved in signal transduction (including gacS, aer2, bdlA, and PA14_71750) reflect likely adaptations to biofilm-inducing conditions. Contrary to evolution experiments that select mutations in a few genes, these results suggest that some environments may expose a larger fraction of the genome and select for many adaptations at once. Thus, even growth on a sole carbon source can lead to persistent genetic and phenotypic variation despite strong selection that would normally purge diversity.

Multiple novel traits without immediate benefits originate in bacteria evolving on single antibiotics

How new traits originate in evolution is a fundamental question of evolutionary biology. When such traits arise, they can either be immediately beneficial in their environment of origin, or they may become beneficial only in a future environment. Compared to immediately beneficial novel traits, novel traits without immediate benefits remain poorly studied. Here we use experimental evolution to study novel traits that are not immediately beneficial but that allow bacteria to survive in new environments. Specifically, we evolved multiple E. coli populations in five antibiotics with different mechanisms of action, and then determined their ability to grow in more than 200 environments that are different from the environment in which they evolved. Our populations evolved viability in multiple environments that contain not just clinically relevant antibiotics, but a broad range of antimicrobial molecules, such as surfactants, organic and inorganic salts, nucleotide analogues and pyridine derivatives. Genome sequencing of multiple evolved clones shows that pleiotropic mutations are important for the origin of these novel traits. Our experiments, which lasted fewer than 250 generations, demonstrate that evolution can readily create an enormous reservoir of latent traits in microbial populations. These traits can facilitate adaptive evolution in a changing world.

Advantages of laboratory natural selection in the applied sciences

In the past three decades, laboratory natural selection has become a widely used technique in biological research. Most studies which have utilized this technique are in the realm of basic science, often testing hypotheses related to mechanisms of evolutionary change or ecological dynamics. While laboratory natural selection is currently utilized heavily in this setting, there is a significant gap with its usage in applied studies, especially when compared to the other selection experiment methodologies like artificial selection and directed evolution. This is despite avenues of research in the applied sciences which seem well suited to laboratory natural selection. In this review, we place laboratory natural selection in context with other selection experiments, identify the characteristics which make it well suited for particular kinds of applied research and briefly cover key examples of the usefulness of selection experiments within applied science. Finally, we identify three promising areas of inquiry for laboratory natural selection in the applied sciences: bioremediation technology, identifying mechanisms of drug resistance and optimizing biofuel production. Although laboratory natural selection is currently less utilized in applied science when compared to basic research, the method has immense promise in the field moving forward.

Finding the right sequence of drugs

Rapidly switching between similar antibiotics may help to slow down the evolution of resistance.

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.

High potency of sequential therapy with only β-lactam antibiotics

Evolutionary adaptation is a major source of antibiotic resistance in bacterial pathogens. Evolution-informed therapy aims to constrain resistance by accounting for bacterial evolvability. Sequential treatments with antibiotics that target different bacterial processes were previously shown to limit adaptation through genetic resistance trade-offs and negative hysteresis. Treatment with homogeneous sets of antibiotics is generally viewed to be disadvantageous as it should rapidly lead to cross-resistance. We here challenged this assumption by determining the evolutionary response of Pseudomonas aeruginosa to experimental sequential treatments involving both heterogenous and homogeneous antibiotic sets. To our surprise, we found that fast switching between only β-lactam antibiotics resulted in increased extinction of bacterial populations. We demonstrate that extinction is favored by low rates of spontaneous resistance emergence and low levels of spontaneous cross-resistance among the antibiotics in sequence. The uncovered principles may help to guide the optimized use of available antibiotics in highly potent, evolution-informed treatment designs.

Overuse of antibiotic drugs is leading to the appearance of antibiotic-resistant bacteria; this is, bacteria with mutations that allow them to survive treatment with specific antibiotics. This has made some bacterial infections difficult or impossible to treat. Learning more about how bacteria evolve resistance to antibiotics could help scientists find ways to prevent it and develop more effective treatments.

Changing antibiotics frequently may be one way to prevent bacteria from evolving resistance. That way if a bacterium acquires mutations that allow it to escape one antibiotic, another antibiotic will kill it, stopping it from dividing and preventing the appearance of descendants with resistance to several antibiotics. In order to use this approach, testing is needed to find the best sequences of antibiotics to apply and the optimal timings of treatment.

To find out more, Batra, Roemhild et al. grew bacteria in the laboratory and exposed them to different sequences of antibiotics, switching antibiotics at different time intervals. This showed that sequential treatments with different antibiotics can limit bacterial evolution, especially when antibiotics are switched quickly. Unexpectedly, one of the most effective sequences used very similar antibiotics. This was surprising because using similar antibiotics should lead to the evolution of cross-resistance, which is when a drug causes changes that make the bacterium less sensitive to other treatments. However, in the tested case, cross-resistance did not evolve when antibiotics were switched quickly, thereby ensuring efficiency of treatment.

Batra et al. show that alternating sequences of antibiotics may be an effective strategy to prevent drug resistance. Because the experiments were done in a laboratory setting it will be important to verify the results in studies in animals and humans before the approach can be used in medical or veterinary settings. If the results are confirmed, it could reduce the need to develop new antibiotics, which is expensive and time consuming.

Genomic evolution of antibiotic resistance is contingent on genetic background following a long-term experiment with Escherichia coli

Antibiotic resistance is a growing health concern. Efforts to control resistance would benefit from an improved ability to forecast when and how it will evolve. Epistatic interactions between mutations can promote divergent evolutionary trajectories, which complicates our ability to predict evolution. We recently showed that differences between genetic backgrounds can lead to idiosyncratic responses in the evolvability of phenotypic resistance, even among closely related Escherichia coli strains. In this study, we examined whether a strain's genetic background also influences the genotypic evolution of resistance. Do lineages founded by different genotypes take parallel or divergent mutational paths to achieve their evolved resistance states? We addressed this question by sequencing the complete genomes of antibiotic-resistant clones that evolved from several different genetic starting points during our earlier experiments. We first validated our statistical approach by quantifying the specificity of genomic evolution with respect to antibiotic treatment. As expected, mutations in particular genes were strongly associated with each drug. Then, we determined that replicate lines evolved from the same founding genotypes had more parallel mutations at the gene level than lines evolved from different founding genotypes, although these effects were more subtle than those showing antibiotic specificity. Taken together with our previous work, we conclude that historical contingency can alter both genotypic and phenotypic pathways to antibiotic resistance.

Predicting Pseudomonas aeruginosa susceptibility phenotypes from whole genome sequence resistome analysis

OBJECTIVES

The aim was to develop and validate a Pseudomonas aeruginosa genotypic resistance score, based on analysis of the whole genome sequence resistome, to predict antimicrobial susceptibility phenotypes.

METHODS

A scoring system based on the analysis of mutation-driven resistance in 40 chromosomal genes and horizontally acquired resistance (Resfinder) was developed for ceftazidime, ceftolozane/tazobactam, meropenem, ciprofloxacin and tobramycin. Resistance genes/mutations were scored from 0 (no effect) to 1 (EUCAST clinical resistance). One hundred wild-type strains obtained from 51 different hospitals during a 2017 multicentre study were fully sequenced and analysed in order to define a catalogue of natural polymorphisms in the 40 chromosomal resistance genes. The capacity of genotypic score to predict the susceptibility phenotype was tested in 204 isolates randomly selected from the 51 hospitals (four from each hospital).

RESULTS

The analysis of the 100 wild-type isolates yielded a catalogue of 455 natural polymorphisms in the 40 genes involved in mutational resistance. However, resistance mutations and high-risk clones (such as ST235) were also documented among a few wild-type isolates. Overall, the capacity of the genotypic score (<0.5) for predicting phenotypic susceptibility (S + I in the case of meropenem) was very high (95-100%). In contrast, the capacity of the genotypic score to predict resistance (≥1) was far more variable depending on the agent. Prediction of meropenem clinical resistance was particularly low (18/39, 46.1%), whereas it classified clinical ceftolozane/tazobactam resistance in 100% (7/7) of cases.

DISCUSSION

Although a margin for improvement was evidenced in this proof of concept study, an overall good correlation between the genotypic resistance score and the susceptibility profile was documented. Further refining of the scoring system, automatization and testing of large international cohorts should follow.

Insights into collateral susceptibility and collateral resistance in Acinetobacter baumannii during antimicrobial adaptation

The susceptibility of Acinetobacter baumannii exposed to primary antibiotic can be either increased or decreased when exposed to secondary antibiotic. This study was designed to assess the relative fitness, collateral susceptibility and collateral resistance of polymyxin B- (PMB-) adapted A. baumannii to ciprofloxacin (CIP), meropenem (MER), PMB, tetracycline (TET) and tobramycin (TOB). Strains of wild-type A. baumannii KACC 12454 (AB^KACC ), wild-type A. baumannii CCARM 12088 (AB^CCARM ), PMB-adapted AB^KACC , PMB-adapted AB^CCARM , stabilized AB^KACC and stabilized AB^CCARM were used in this study. Compared to the wild-type AB^KACC , the MICs of PMB were increased from 2 to 128 μg ml^-1 against PMB-adapted AB^KACC , while MICs of CIP, MER, TET and TOB were decreased from 2 to 1 μg ml^-1 , 16 to 1 μg ml^-1 , 16 to 2 μg ml^-1 and 64 to 16 μg ml^-1 , respectively. The PMB-adapted AB^CCARM was resistant to CIP (32 μg ml^-1 ) and PMB (64 μg ml^-1 ) compared to the wild-type AB^CCARM . The resistance of stabilized AB^KACC and AB^CCARM to all antibiotics was lost after antibiotic-free culture in the exception of CIP and TET. The susceptibilities of wild-type, PMB-adapted and stabilized AB^KACC and AB^CCARM to CIP, MER, PMB, TET and TOB were increased in the presence of β-lactamase and efflux pump inhibitors. The high levels of relative fitness were observed for stabilized AB^KACC , PMB-adapted AB^CCARM and stabilized AB^CCARM . The stabilized AB^KACC and PMB-adapted AB^CCARM were highly heteroresistance to PMB and TET, respectively. The PMB-adapted AB^KACC and AB^CCARM showed various antibiotic patterns, known as collateral susceptibility and collateral resistance. The results provide useful information for designing effective antibiotic regimens that can enhance the antibiotic activity against A. baumannii infections.

The Genomic Basis of Rapid Adaptation to Antibiotic Combination Therapy in Pseudomonas aeruginosa

Combination therapy is a common antibiotic treatment strategy that aims at minimizing the risk of resistance evolution in several infectious diseases. Nonetheless, evidence supporting its efficacy against the nosocomial opportunistic pathogen Pseudomonas aeruginosa remains elusive. Identification of the possible evolutionary paths to resistance in multidrug environments can help to explain treatment outcome. For this purpose, we here performed whole-genome sequencing of 127 previously evolved populations of P. aeruginosa adapted to sublethal doses of distinct antibiotic combinations and corresponding single-drug treatments, and experimentally characterized several of the identified variants. We found that alterations in the regulation of efflux pumps are the most favored mechanism of resistance, regardless of the environment. Unexpectedly, we repeatedly identified intergenic variants in the adapted populations, often with no additional mutations and usually associated with genes involved in efflux pump expression, possibly indicating a regulatory function of the intergenic regions. The experimental analysis of these variants demonstrated that the intergenic changes caused similar increases in resistance against single and multidrug treatments as those seen for efflux regulatory gene mutants. Surprisingly, we could find no substantial fitness costs for a majority of these variants, most likely enhancing their competitiveness toward sensitive cells, even in antibiotic-free environments. We conclude that the regulation of efflux is a central target of antibiotic-mediated selection in P. aeruginosa and that, importantly, changes in intergenic regions may represent a usually neglected alternative process underlying bacterial resistance evolution, which clearly deserves further attention in the future.

To give or not to give antibiotics is not the only question

In a 1945 Nobel Lecture, Sir Alexander Fleming warned against the overuse of antibiotics, particularly in response to public pressure. In the subsequent decades, evidence has shown that bacteria can become resistant to almost any available molecule. One key question is how the emergence and dissemination of resistant bacteria or resistance genes can be delayed. Although some clinicians remain sceptical, in this Personal View, we argue that the prescription of fewer antibiotics and shorter treatment duration is just as effective as longer regimens that remain the current guideline. Additionally, we discuss the fact that shorter antibiotic treatments exert less selective pressure on microorganisms, preventing the development of resistance. By contrast, longer treatments associated with a strong selective pressure favour the emergence of resistant clones within commensal organisms. We also emphasise that more studies are needed to identify the optimal duration of antibiotic therapy for common infections, which is important for making changes to the current guidelines, and to identify clinical biomarkers to guide antibiotic treatment in both hospital and ambulatory settings.

Systematic Investigation of Resistance Evolution to Common Antibiotics Reveals Conserved Collateral Responses across Common Human Pathogens

As drug resistance continues to grow, treatment strategies that turn resistance into a disadvantage for the organism will be increasingly relied upon to treat infections and to lower the rate of multidrug resistance. The majority of work in this area has investigated how resistance evolution toward a single antibiotic effects a specific organism’s collateral response to a wide variety of antibiotics. The results of these studies have been used to identify networks of drugs which can be used to drive resistance in a particular direction.

As drug resistance continues to grow, treatment strategies that turn resistance into a disadvantage for the organism will be increasingly relied upon to treat infections and to lower the rate of multidrug resistance. The majority of work in this area has investigated how resistance evolution toward a single antibiotic effects a specific organism’s collateral response to a wide variety of antibiotics. The results of these studies have been used to identify networks of drugs which can be used to drive resistance in a particular direction. However, little is known about the extent of evolutionary conservation of these responses across species. We sought to address this knowledge gap by performing a systematic resistance evolution study of the ESKAPE pathogens (Enterococcus faecium, Staphylococcus aureus, Klebsiella pneumoniae, Acinetobacter baumannii, Pseudomonas aeruginosa, and Enterobacter cloacae) under uniform growth conditions using five clinically relevant antibiotics with diverse modes of action. Evolved lineages were analyzed for collateral effects and the molecular mechanisms behind the observed phenotypes. Fourteen universal cross-resistance and two global collateral sensitivity relationships were found among the lineages. Genomic analyses revealed drug-dependent divergent and conserved evolutionary trajectories among the pathogens. Our findings suggest that collateral responses may be preserved across species. These findings may help extend the contribution of previous collateral network studies in the development of treatment strategies to address the problem of antibiotic resistance.

Antimicrobial drug resistance mechanisms among Mollicutes

Representatives of the Mollicutes class are the smallest, wall-less bacteria capable of independent reproduction. They are widespread in nature, most are commensals, and some are pathogens of humans, animals and plants. They are also the main contaminants of cell cultures and vaccine preparations. Despite limited biosynthetic capabilities, they are highly adaptable and capable of surviving under various stress and extreme conditions, including antimicrobial selective pressure. This review describes current understanding of antibiotic resistance (ABR) mechanisms in Mollicutes. Protective mechanisms in these bacteria include point mutations, which may include non-target genes, and unique gene exchange mechanisms, contributing to transfer of ABR genes. Better understanding of the mechanisms of emergence and dissemination of ABR in Mollicutes is crucial to control these hypermutable bacteria and prevent the occurrence of highly ABR strains.

Development and Application of a Core Genome Multilocus Sequence Typing Scheme for the Health Care-Associated Pathogen Pseudomonas aeruginosa

Pseudomonas aeruginosa is an opportunistic human pathogen that frequently causes health care-associated infections (HAIs). Due to its metabolic diversity and ability to form biofilms, this Gram-negative nonfermenting bacterium can persist in the health care environment, which can lead to prolonged HAI outbreaks. We describe the creation of a core genome multilocus sequence typing (cgMLST) scheme to provide a stable platform for the rapid comparison of P. aeruginosa isolates using whole-genome sequencing (WGS) data. We used a diverse set of 58 complete P. aeruginosa genomes to curate a set of 4,440 core genes found in each isolate, representing ∼64% of the average genome size. We then expanded the alleles for each gene using 1,991 contig-level genome sequences. The scheme was used to analyze genomes from four historical HAI outbreaks to compare the phylogenies generated using cgMLST to those of other means (traditional MLST, pulsed-field gel electrophoresis [PFGE], and single-nucleotide variant [SNV] analysis). The cgMLST scheme provides sufficient resolution for analyzing individual outbreaks, as well as the stability for comparisons across a variety of isolates encountered in surveillance studies, making it a valuable tool for the rapid analysis of P. aeruginosa genomes.

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.

A model for the interplay between plastic tradeoffs and evolution in changing environments

Performance tradeoffs are ubiquitous in both ecological and evolutionary modeling, yet they are usually postulated and built into fitness and ecological landscapes. However, tradeoffs depend on genetic background and evolutionary history and can themselves evolve. We present a simple model capable of capturing the key feedback loop: evolutionary history shapes tradeoff strength, which, in turn, shapes evolutionary future. One consequence of this feedback is that genomes with identical fitness can have different evolutionary properties shaped by prior environmental exposure. Another is that, generically, the best adaptations to one environment may evolve in another. Our simple framework bridges the gap between the phenotypic Fisher's Geometric Model and the genotypic properties, such as modularity and evolvability, and can serve as a rich playground for investigating evolution in multiple or changing environments.

Assessment of Phenotype Microarray plates for rapid and high-throughput analysis of collateral sensitivity networks

The crisis of antimicrobial resistance is driving research into the phenomenon of collateral sensitivity. Sometimes, when a bacterium evolves resistance to one antimicrobial, it becomes sensitive to others. In this study, we have investigated the utility of Phenotype Microarray (PM) plates for identifying collateral sensitivities with unprecedented throughput. We assessed the relative resistance/sensitivity phenotypes of nine strains of Staphylococcus aureus (two laboratory strains and seven clinical isolates) towards the 72 antimicrobials contained in three PM plates. In general, the PM plates reported on resistance and sensitivity with a high degree of reproducibility. However, a rigorous comparison of PM growth phenotypes with minimum inhibitory concentration (MIC) measurements revealed a trade-off between throughput and accuracy. Small differences in PM growth phenotype did not necessarily correlate with changes in MIC. Thus, we conclude that PM plates are useful for the rapid and high-throughput assessment of large changes in collateral sensitivity phenotypes during the evolution of antimicrobial resistance, but more subtle examples of cross-resistance or collateral sensitivity cannot be identified reliably using this approach.

Evaluating the efficacy of an algae-based treatment to mitigate elicitation of antibiotic resistance

Antibiotics in the effluents of municipal wastewater treatment plants (WWTP) may create selective pressures to induce antibiotic resistance in bacteria downstream. This study evaluates ciprofloxacin (CIP) removal by a freshwater alga, Scenedesmus dimorphus, to assess the efficacy of algae-based tertiary treatment in reducing effluent-induced CIP resistance. Results show significant CIP removal in light-exposed samples without algae and experimental algae (EA) samples: 53% and 93%, respectively, over 144 h. A residual antibiotic potency assay reveals that untreated CIP is significantly more growth-inhibiting to a model bacterium (Escherichia coli) than the algae-treated and light-exposed samples during short exposures (6 h). Adaptive laboratory evolution (ALE), again using E. coli, reveals that treated samples exhibit reduced capacity to elicit CIP resistance during sustained exposures compared to untreated CIP. Finally, observed CIP resistance in the CIP-exposed ALE lineages is corroborated via genotype characterization, which reveals the presence of resistance-associated mutations in gyrase subunit A (gyrA) that are not present in ALE lineages exposed to algae treated or light-exposed samples. As such, algae-mediated tertiary treatment could be effective in suppressing CIP resistance in bacterial communities downstream from WWTP. In addition, ALE is useful for assessing the potential of wastewater-relevant samples to elicit antibiotic resistance downstream.

Evolutionary stability of collateral sensitivity to antibiotics in the model pathogen Pseudomonas aeruginosa

Evolution is at the core of the impending antibiotic crisis. Sustainable therapy must thus account for the adaptive potential of pathogens. One option is to exploit evolutionary trade-offs, like collateral sensitivity, where evolved resistance to one antibiotic causes hypersensitivity to another one. To date, the evolutionary stability and thus clinical utility of this trade-off is unclear. We performed a critical experimental test on this key requirement, using evolution experiments with Pseudomonas aeruginosa, and identified three main outcomes: (i) bacteria commonly failed to counter hypersensitivity and went extinct; (ii) hypersensitivity sometimes converted into multidrug resistance; and (iii) resistance gains frequently caused re-sensitization to the previous drug, thereby maintaining the trade-off. Drug order affected the evolutionary outcome, most likely due to variation in the effect size of collateral sensitivity, epistasis among adaptive mutations, and fitness costs. Our finding of robust genetic trade-offs and drug-order effects can guide design of evolution-informed antibiotic therapy.

Antimicrobial resistance in mollicutes: known and newly emerging mechanisms

This review is devoted to the mechanisms of antibiotic resistance in mollicutes (class Bacilli, subclass Mollicutes), the smallest self-replicating bacteria, that can cause diseases in plants, animals and humans, and also contaminate cell cultures and vaccine preparations. Research in this area has been mainly based on the ubiquitous mollicute and the main contaminant of cell cultures, Acholeplasma laidlawii. The omics technologies applied to this and other bacteria have yielded a complex picture of responses to antimicrobials, including their removal from the cell, the acquisition of antibiotic resistance genes and mutations that potentially allow global reprogramming of many cellular processes. This review provides a brief summary of well-known resistance mechanisms that have been demonstrated in several mollicutes species and, in more detail, novel mechanisms revealed in A. laidlawii, including the least explored vesicle-mediated transfer of short RNAs with a regulatory potency. We hope that this review highlights new avenues for further studies on antimicrobial resistance in these bacteria for both a basic science and an application perspective of infection control and management in clinical and research/production settings.

Diversification of Pseudomonas aeruginosa within the cystic fibrosis lung and its effects on antibiotic resistance

The evolution and diversification of bacterial pathogens within human hosts represent potential barriers to the diagnosis and treatment of life-threatening infections. Tremendous genetic and phenotypic diversity is characteristic of host adaptation in strains of Pseudomonas aeruginosa that infect the airways of individuals with chronic lung diseases and prove to be extremely difficult to eradicate. In this MiniReview, we examine recent advances in understanding within-host diversity and antimicrobial resistance in P. aeruginosa populations from the lower airways of individuals with the fatal genetic disease cystic fibrosis and the potential impacts that this diversity may have on detecting and interpreting antimicrobial susceptibility within these populations.

Evolutionary pathways to antibiotic resistance are dependent upon environmental structure and bacterial lifestyle

Bacterial populations vary in their stress tolerance and population structure depending upon whether growth occurs in well-mixed or structured environments. We hypothesized that evolution in biofilms would generate greater genetic diversity than well-mixed environments and lead to different pathways of antibiotic resistance. We used experimental evolution and whole genome sequencing to test how the biofilm lifestyle influenced the rate, genetic mechanisms, and pleiotropic effects of resistance to ciprofloxacin in Acinetobacter baumannii populations. Both evolutionary dynamics and the identities of mutations differed between lifestyle. Planktonic populations experienced selective sweeps of mutations including the primary topoisomerase drug targets, whereas biofilm-adapted populations acquired mutations in regulators of efflux pumps. An overall trade-off between fitness and resistance level emerged, wherein biofilm-adapted clones were less resistant than planktonic but more fit in the absence of drug. However, biofilm populations developed collateral sensitivity to cephalosporins, demonstrating the clinical relevance of lifestyle on the evolution of resistance.

A bacterium known as Acinetobacter baumannii causes serious lung infections in people with weakened immune systems. These illnesses are becoming more common largely because A. baumannii is increasingly developing resistance to antibiotics.

Inside the airways, individual A. baumannii cells can stick together and coat themselves in a slimy substance to form a structure called biofilm, which physically protects bacteria from antibiotics. This may be one of the reasons why it is often harder to treat bacterial infections associated with biofilms.

Another possibility is that bacteria may evolve differently in biofilms compared with cells living independently. For example, A. baumannii may colonize several regions of the lungs during an infection, leading to distinct groups of bacteria that experience different conditions and evolve separately. Each population may therefore respond differently to an antibiotic. In contrast, bacteria living independently in a well-mixed population – such as in the bloodstream of their host – would be more likely to all evolve in the same way.

Santos-Lopez, Marshall et al. tested this theory by exposing populations of A. baumannii that lived either independently or in biofilms to increasing levels of an antibiotic called ciprofloxacin. The genetic information of these cells was examined as the populations were evolving, and the bacteria were also put in contact with other types of antibiotics.

The analyses revealed that bacteria in well-mixed populations shared the same limited number of mutations: these gave the bacteria high levels of resistance to the antibiotic’s primary target, an enzyme involved in DNA processes. The bacteria had also become resistant to other classes of antibiotics.

In contrast, the bacteria in biofilm populations evolved to be more genetically diverse, exhibiting different types of mutations that helped the cells to pump out the drug. These bacteria were less resistant to ciprofloxacin and more sensitive to other types of antibiotics.

Further experiments looked into the fitness of the bacteria – their ability to survive, reproduce and compete with each other. High levels of antibiotic resistance came with lower fitness: biofilm bacteria had evolved to become being fitter than those from well-mixed population. Even in the absence of drugs, these populations were in fact fitter than the original cells.

Overall, understanding how the lifestyles of bacteria affect the way they respond to drugs may help researchers to develop new approaches that limit the spread of antibiotic resistance and improve treatment.

Within-Host Adaptation Mediated by Intergenic Evolution in Pseudomonas aeruginosa

Bacterial pathogens evolve during the course of infection as they adapt to the selective pressures that confront them inside the host. Identification of adaptive mutations and their contributions to pathogen fitness remains a central challenge. Although mutations can either target intergenic or coding regions in the pathogen genome, studies of host adaptation have focused predominantly on molecular evolution within coding regions, whereas the role of intergenic mutations remains unclear. Here, we address this issue and investigate the extent to which intergenic mutations contribute to the evolutionary response of a clinically important bacterial pathogen, Pseudomonas aeruginosa, to the host environment, and whether intergenic mutations have distinct roles in host adaptation. We characterize intergenic evolution in 44 clonal lineages of P. aeruginosa and identify 77 intergenic regions in which parallel evolution occurs. At the genetic level, we find that mutations in regions under selection are located primarily within regulatory elements upstream of transcriptional start sites. At the functional level, we show that some of these mutations both increase or decrease transcription of genes and are directly responsible for evolution of important pathogenic phenotypes including antibiotic sensitivity. Importantly, we find that intergenic mutations facilitate essential genes to become targets of evolution. In summary, our results highlight the evolutionary significance of intergenic mutations in creating host-adapted strains, and that intergenic and coding regions have different qualitative contributions to this process.

Burkholderia multivorans Exhibits Antibiotic Collateral Sensitivity

Burkholderia multivorans is a member of the Burkholderia cepacia complex whose members are inherently resistant to many antibiotics and can cause chronic lung infections in patients with cystic fibrosis. A possible treatment for chronic infections arises from the existence of collateral sensitivity (CS)-acquired resistance to a treatment antibiotic results in a decreased resistance to a nontreatment antibiotic. Determining CS patterns for bacteria involved in chronic infections may lead to sustainable treatment regimens that reduce development of multidrug-resistant bacterial strains. CS has been found to occur in Escherichia coli, Pseudomonas aeruginosa, and Staphylococcus aureus. Here, we report that B. multivorans exhibits antibiotic CS, as well as cross-resistance (CR), describe CS and CR networks for six antibiotics (ceftazidime, chloramphenicol, levofloxacin, meropenem, minocycline, and trimethoprim-sulfamethoxazole), and identify candidate genes involved in CS. Characterization of CS and CR patterns allows antibiotics to be separated into two clusters based on the treatment drug to which the evolved strain developed primary resistance, suggesting an antibiotic therapy strategy of switching between members of these two clusters.

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.