Evolutionary landscapes of Pseudomonas aeruginosa towards ribosome-targeting antibiotic resistance depend on selection strength

Sub-MIC vancomycin enhances the antibiotic tolerance of vancomycin-intermediate Staphylococcus aureus through downregulation of protein succinylation

Bacteria develop tolerance after transient exposure to antibiotics, and tolerance is a significant driver of resistance. The purpose of this study is to evaluate the mechanisms underlying tolerance formation in vancomycin-intermediate Staphylococcus aureus (VISA) strains. VISA strains were cultured with sub-minimum inhibitory concentrations (sub-MICs) of vancomycin. Enhanced vancomycin tolerance was observed in VISA strains with distinct genetic lineages. Western blot revealed that the VISA protein succinylation (Ksucc) levels decreased with the increase in vancomycin exposure. Importantly, Ksucc modification, vancomycin tolerance, and cell wall synthesis were simultaneously affected after deletion of SacobB, which encodes a desuccinylase in S. aureus. Several Ksucc sites were identified in MurA, and vancomycin MIC levels of murA mutant and Ksucc-simulated (MurA(K69E) and MurA(K191E)) mutants were reduced. The vancomycin MIC levels of K65-MurA(K191E) in particular decreased to 1 mg/L, converting VISA strain K65 to a vancomycin-susceptible S. aureus strain. We further demonstrated that the enzymatic activity of MurA was dependent on Ksucc modification. Our data suggested the influence of vancomycin exposure on bacterial tolerance, and protein Ksucc modification is a novel mechanism in regulating vancomycin tolerance.

Unveiling the Microbiome Landscape: A Metagenomic Study of Bacterial Diversity, Antibiotic Resistance, and Virulence Factors in the Sediments of the River Ganga, India

The global rise in antibiotic resistance, fueled by indiscriminate antibiotic usage in medicine, aquaculture, agriculture, and the food industry, presents a significant public health challenge. Urban wastewater and sewage treatment plants have become key sources of antibiotic resistance proliferation. The present study focuses on the river Ganges in India, which is heavily impacted by human activities and serves as a potential hotspot for the spread of antibiotic resistance. We conducted a metagenomic analysis of sediment samples from six distinct locations along the river to assess the prevalence and diversity of antibiotic resistance genes (ARGs) within the microbial ecosystem. The metagenomic analysis revealed the predominance of Proteobacteria across regions of the river Ganges. The antimicrobial resistance (AMR) genes and virulence factors were determined by various databases. In addition to this, KEGG and COG analysis revealed important pathways related to AMR. The outcomes highlight noticeable regional differences in the prevalence of AMR genes. The findings suggest that enhancing health and sanitation infrastructure could play a crucial role in mitigating the global impact of AMR. This research contributes vital insights into the environmental aspects of antibiotic resistance, highlighting the importance of targeted public health interventions in the fight against AMR.

Understanding resistance acquisition by Pseudomonas aeruginosa and possible pharmacological approaches in palliating its pathogenesis

Pseudomonas aeruginosa can utilize various virulence factors necessary for host infection and persistence. These virulence factors include pyocyanin, proteases, exotoxins, 2-heptyl-4-hydroxyquinoline N-oxide (HQNO), phospholipases, and siderophores that enable the bacteria to cause severe infections in immunocompromised individuals. P. aeruginosa falls into the category of nosocomial pathogens that are typically resistant to available antibiotics and therapeutic approaches. P. aeruginosa bio-film formation is a major concern in hospitals because it can cause chronic infection and increase the risk of mortality. Therefore, the development of new strategies to disrupt biofilm formation and improve antibiotic efficacy for the treatment of P. aeruginosa infections is crucial. Anti-biofilm and anti-quorum sensing (QS) activity can be viewed as an anti-virulence approach to control the infectious nature of P. aeruginosa. Inhibition of QS and biofilm formation can be achieved through pharmacological approaches such as phytochemicals and essential oils, which have shown promising results in laboratory studies. A regulatory protein called LasR plays a key role in QS signaling to coordinate gene expression. Designing an antagonist molecule that mimics the natural autoinducer might be the best approach for LasR inhibition. Here we reviewed the mechanism behind antibiotic resistance and alternative approaches to combat the pathogenicity of P. aeruginosa.

Pervasive Selection for Clinically Relevant Resistance and Media Adaptive Mutations at Very Low Antibiotic Concentrations

Experimental evolution studies have shown that weak antibiotic selective pressures (i.e., when the antibiotic concentrations are far below the minimum inhibitory concentration, MIC) can select resistant mutants, raising several unanswered questions. First, what are the lowest antibiotic concentrations at which selection for de novo resistance mutations can occur? Second, with weak antibiotic selections, which other types of adaptive mutations unrelated to the antibiotic selective pressure are concurrently enriched? Third, are the mutations selected under laboratory settings at subMIC also observed in clinical isolates? We addressed these questions using Escherichia coli populations evolving at subMICs in the presence of either of four clinically used antibiotics: fosfomycin, nitrofurantoin, tetracycline, and ciprofloxacin. Antibiotic resistance evolution was investigated at concentrations ranging from 1/4th to 1/2000th of the MIC of the susceptible strain (MICsusceptible). Our results show that evolution was rapid across all the antibiotics tested, and selection for fosfomycin- and nitrofurantoin-resistant mutants was observed at a concentration as low as 1/2000th of MICsusceptible. Several of the evolved resistant mutants showed increased growth yield and exponential growth rates, and outcompeted the susceptible ancestral strain in the absence of antibiotics as well, suggesting that adaptation to the growth environment occurred in parallel with the selection for resistance. Genomic analysis of the resistant mutants showed that several of the mutations selected under these conditions are also found in clinical isolates, demonstrating that experimental evolution at very low antibiotic levels can help in identifying novel mutations that contribute to bacterial adaptation during subMIC exposure in real-life settings.

Low Ciprofloxacin Concentrations Select Multidrug-Resistant Mutants Overproducing Efflux Pumps in Clinical Isolates of Pseudomonas aeruginosa

Low antibiotic concentrations present in natural environments are a severe and often neglected threat to public health. Even if they are present below their MICs, they may select for antibiotic-resistant pathogens. Notably, the minimal subinhibitory concentrations that select resistant bacteria, and define the respective sub-MIC selective windows, differ between antibiotics. The establishment of these selective concentrations is needed for risk-assessment studies regarding the presence of antibiotics in different habitats. Using short-term evolution experiments in a set of 12 Pseudomonas aeruginosa clinical isolates (including high-risk clones with ubiquitous distribution), we have determined that ciprofloxacin sub-MIC selective windows are strain specific and resistome dependent. Nonetheless, in all cases, clinically relevant multidrug-resistant (MDR) mutants emerged upon exposure to low ciprofloxacin concentrations, with these concentrations being below the levels reported in ciprofloxacin-polluted natural habitats where P. aeruginosa can be present. This feature expands the conditions and habitats where clinically relevant quinolone-resistant mutants can emerge. In addition, we established the lowest concentration threshold beyond which P. aeruginosa, regardless of the strain, becomes resistant to ciprofloxacin. Three days of exposure under this sub-MIC "risk concentration" led to the selection of MDR mutants that displayed resistance mechanisms usually ascribed to high selective pressures, i.e., the overproduction of the efflux pumps MexCD-OprJ and MexEF-OprN. From a One-Health viewpoint, these data stress the transcendent role of low drug concentrations, which can be encountered in natural ecosystems, in aggravating the antibiotic resistance problem, especially when it comes to pathogens of environmental origin. IMPORTANCE It has been established that antibiotic concentrations below MICs can select antibiotic-resistant pathogens, a feature of relevance for analyzing the role of nonclinical ecosystems in antibiotic resistance evolution. The range of concentrations where this selection occurs defines the sub-MIC selective window, whose width depends on the antibiotic. Herein, we have determined the ciprofloxacin sub-MIC selective windows of a set of Pseudomonas aeruginosa clinical isolates (including high-risk clones with worldwide distribution) and established the lowest concentration threshold, notably an amount reported to be present in natural ecosystems, beyond which this pathogen acquires resistance. Importantly, our results show that this ciprofloxacin sub-MIC selects for multidrug-resistant mutants overproducing clinically relevant efflux pumps. From a One-Health angle, this information supports that low antimicrobial concentrations, present in natural environments, may have a relevant role in worsening the antibiotic resistance crisis, particularly regarding pathogens with environmental niches, such as P. aeruginosa.

Biofilm antimicrobial susceptibility through an experimental evolutionary lens

Experimental evolution experiments in which bacterial populations are repeatedly exposed to an antimicrobial treatment, and examination of the genotype and phenotype of the resulting evolved bacteria, can help shed light on mechanisms behind reduced susceptibility. In this review we present an overview of why it is important to include biofilms in experimental evolution, which approaches are available to study experimental evolution in biofilms and what experimental evolution has taught us about tolerance and resistance in biofilms. Finally, we present an emerging consensus view on biofilm antimicrobial susceptibility supported by data obtained during experimental evolution studies.

Gold nanocluster adjuvant enables the eradication of persister cells by antibiotics and abolishes the emergence of resistance

Persister cells are responsible for relapses of infections common in cystic fibrosis and chronic suppurative otitis media (CSOM). Yet, there are no Food and Drug Administration (FDA) approved antibiotics to eradicate persister cells. Frustratingly, the global preclinical bacterial pipeline does not contain antibacterial agents targeting persister cells. Therefore, we report a nontraditional antimicrobial chemotherapy strategy based on gold nanoclusters adjuvant to eradicate persister cells by existing antibiotics belonging to that different class. Compared to killing with antibiotics alone, combining antibiotics and AuNC@CPP sterilizes persister cells and biofilms. Enhanced killing of up to 4 orders of magnitude in a validated mouse model of CSOM with Pseudomonas aeruginosa infection was observed when combining antibiotics and AuNC@CPP, informing a potential approach to improve the treatment of CSOM. We established that the mechanism of action of AuNC@CPP is due to disruption of the proton gradient and membrane hyperpolarization. The method presented here could compensate for the lack of new antibiotics to combat persister cells. This method could also benefit the current effort to slow resistance development because AuNC@CPP abolished the emergence of drug-resistant strains induced by antibiotics.

Evolution of Habitat-Dependent Antibiotic Resistance in Pseudomonas aeruginosa

Pseudomonas aeruginosa is an opportunistic human pathogen that usually causes difficult-to-treat infections due to its low intrinsic antibiotic susceptibility and outstanding capacity for becoming resistant to antibiotics. In addition, it has a remarkable metabolic versatility, being able to grow in different habitats, from natural niches to different and changing inpatient environments. Study of the environmental conditions that shape genetic and phenotypic changes of P. aeruginosa toward antibiotic resistance supposes a novelty, since experimental evolution assays are usually performed with well-defined antibiotics in regular laboratory growth media. Therefore, in this work we address the extent to which the nutrients’ availability may constrain the evolution of antibiotic resistance. We determined that P. aeruginosa genetic trajectories toward resistance to tobramycin, ceftazidime, and ceftazidime-avibactam are different when evolving in laboratory rich medium, urine, or synthetic sputum. Furthermore, our study, linking genotype with phenotype, showed a clear impact of each analyzed environment on both the fitness and resistance level associated with particular resistance mutations. This indicates that the phenotype associated with specific resistance mutations is variable and dependent on the bacterial metabolic state in each particular habitat. Our results support that the design of evolution-based strategies to tackle P. aeruginosa infections should be based on robust patterns of evolution identified within each particular infection and body location.

IMPORTANCE Predicting evolution toward antibiotic resistance (AR) and its associated trade-offs, such as collateral sensitivity, is important to design evolution-based strategies to tackle AR. However, the effect of nutrients' availability on such evolution, particularly those that can be found under in vivo infection conditions, has been barely addressed. We analyzed the evolutionary patterns of P. aeruginosa in the presence of antibiotics in different media, including urine and synthetic sputum, whose compositions are similar to the ones in infections, finding that AR evolution differs, depending on growth conditions. Furthermore, the representative mutants isolated under each condition tested render different AR levels and fitness costs, depending on nutrients’ availability, supporting the idea that environmental constraints shape the phenotypes associated with specific AR mutations. Consequently, the selection of AR mutations that render similar phenotypes is environment dependent. The analysis of evolution patterns toward AR requires studying growth conditions mimicking those that bacteria face during in vivo evolution.

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.

The population genetics of collateral resistance and sensitivity

Resistance mutations against one drug can elicit collateral sensitivity against other drugs. Multi-drug treatments exploiting such trade-offs can help slow down the evolution of resistance. However, if mutations with diverse collateral effects are available, a treated population may evolve either collateral sensitivity or collateral resistance. How to design treatments robust to such uncertainty is unclear. We show that many resistance mutations in Escherichia coli against various antibiotics indeed have diverse collateral effects. We propose to characterize such diversity with a joint distribution of fitness effects (JDFE) and develop a theory for describing and predicting collateral evolution based on simple statistics of the JDFE. We show how to robustly rank drug pairs to minimize the risk of collateral resistance and how to estimate JDFEs. In addition to practical applications, these results have implications for our understanding of evolution in variable environments.

Drugs known as antibiotics are the main treatment for most serious infections caused by bacteria. However, many bacteria are acquiring genetic mutations that make them resistant to the effects of one or more types of antibiotics, making them harder to eliminate.

One way to tackle drug-resistant bacteria is to develop new types of antibiotics; however, in recent years, the rate at which new antibiotics have become available has been dwindling. Using two or more existing drugs, one after another, can also be an effective way to eliminate resistant bacteria. The success of any such ‘multi-drug’ treatment lies in being able to predict whether mutations that make the bacteria resistant to one drug simultaneously make it sensitive to another, a phenomenon known as collateral sensitivity.

Different resistance mutations may have different collateral effects: some may increase the bacteria’s sensitivity to the second drug, while others might make the bacteria more resistant. However, it is currently unclear how to design robust multi-drug treatments that take this diversity of collateral effects into account.

Here, Ardell and Kryazhimskiy used a concept called JDFE (short for the joint distribution of fitness effects) to describe the diversity of collateral effects in a population of bacteria exposed to a single drug. This information was then used to mathematically model how collateral effects evolved in the population over time.

Ardell and Kryazhimskiy showed that this approach can predict how likely a population is to become collaterally sensitive or collaterally resistant to a second antibiotic. Drug pairs can then be ranked according to the risk of collateral resistance emerging, so long as information on the variety of resistance mutations available to the bacteria are included in the model.

Each year, more than 700,000 people die from infections caused by bacteria that are resistant to one or more antibiotics. The findings of Ardell and Kryazhimskiy may eventually help clinicians design multi-drug treatments that effectively eliminate bacterial infections and help to prevent more bacteria from evolving resistance to antibiotics. However, to achieve this goal, more research is needed to fully understand the range collateral effects caused by resistance mutations.

Evolution under low antibiotic concentrations: a risk for the selection of Pseudomonas aeruginosa multidrug-resistant mutants in nature

Antibiotic pollution of non-clinical environments might have a relevant impact on human health if resistant pathogens are selected. However, this potential risk is often overlooked, since drug concentrations in nature are usually below their minimal inhibitory concentrations (MICs). Albeit, antibiotic resistant bacteria can be selected even at sub-MIC concentrations, in a range known as the sub-MIC selective window. Using short-term evolution experiments, we have determined the sub-MIC selective windows of the opportunistic pathogen Pseudomonas aeruginosa for seven antibiotics of clinical relevance, finding the ones of quinolones to be the widest, and the ones of polymyxin B and imipenem, the narrowest. Clinically relevant multidrug-resistant mutants arose within the sub-MIC selective windows of most antibiotics tested, being some of these phenotypes mediated by efflux pumps' activity. The fact that the concentration of antibiotics reported in aquatic ecosystems - colonizable by P. aeruginosa - are, in occasions, higher than the ones that select multidrug-resistant mutants in our assays, has implications for understanding the role of different ecosystems and conditions in the emergence of antibiotic resistance from a One-Health perspective. Further, it reinforces the importance of procuring accurate information on the sub-MIC selective windows for drugs of clinical value in pathogens with environmental niches.

Heterogeneity in populations of enterohaemorrhagic Escherichia coli undergoing D-serine adaptation

Phenotypic and genetic heterogeneities are conserved features of prokaryotic populations. During periods of stress, this programmed diversity increases the likelihood that variants within the population will survive the adverse conditions, allowing for proliferation. Phenotypic heterogeneity can have a mutational or indeed a non-mutational basis as observed in bet-hedging strategies adopted by antibiotic-tolerant persister cells. Genetic variants can arise by phase variation (slip-strand mispairing, promoter inversions etc.), nucleotide polymorphisms resulting from replication errors or larger rearrangements such as deletions and insertions. In the face of selective pressures, these alterations may be neutral, beneficial or deleterious.We recently described the genetic basis of tolerance to a normally toxic metabolite, D-serine (D-ser) in enterohaemorrhagic E. coli (EHEC). Here we summarize our work in the context of population dynamics, provide further discussion on the distinction between these tolerance mechanisms and the importance of heterogeneity for maximising adaptive potential.

The Acquisition of Colistin Resistance Is Associated to the Amplification of a Large Chromosomal Region in Klebsiella pneumoniae kp52145

The appearance of carbapenem-resistant Klebsiella pneumoniae has increased the use of colistin as a last-resort antibiotic for treating infections by this pathogen. A consequence of its use has been the spread of colistin-resistant strains, in several cases carrying colistin resistance genes. In addition, when susceptible strains are confronted with colistin during treatment, mutation is a major cause of the acquisition of resistance. To analyze the mechanisms of resistance that might be selected during colistin treatment, an experimental evolution assay for 30 days using as a model the clinical K. pneumoniae kp52145 isolate in the presence of increasing amounts of colistin was performed. All evolved populations presented a decreased susceptibility to colistin, without showing cross-resistance to antibiotics belonging to other structural families. We did not find any common mutation in the evolved mutants, neither in already known genes, previously known to be associated with the resistance phenotype, nor in new ones. The only common genetic change observed in the strains that evolved in the presence of colistin was the amplification of a 34 Kb sequence, homologous to a prophage (Enterobacteria phage Fels-2). Our data support that gene amplification can be a driving force in the acquisition of colistin resistance by K. pneumoniae.

Prokaryotic life finds a way: insights from evolutionary experimentation in bacteria

While evolution proceeds through the generation of random variant alleles, the application of selective pressures can select for subsets of mutations that confer fitness-improving physiological benefits. This, in essence, defines the process of adaptive evolution. The rapid replication rate of bacteria has allowed for the design of experiments to study these processes over a reasonable timeframe within a laboratory setting. This has been greatly assisted by advances in tractability of diverse microorganisms, next generation sequencing technologies and bioinformatic analysis pipelines. Examining the processes by which organisms adapt their genetic code to cope with sub-optimal growth conditions has yielded a wealth of molecular insight into diverse biological processes. Here we discuss how the study of adaptive evolutionary trajectories in bacteria has allowed for improved understanding of stress responses, revealed important insight into microbial physiology, allowed for the production of highly optimised strains for use in biotechnology and increased our knowledge of the role of genomic plasticity in chronic infections.