Pseudomonas aeruginosa populations in the cystic fibrosis lung lose susceptibility to newly applied β-lactams within 3 days

Tobramycin-resistant small colony variant mutant of Salmonella enterica serovar Typhimurium shows collateral sensitivity to nitrofurantoin

The increasing antibiotic resistance poses a significant global health challenge, threatening our ability to combat infectious diseases. The phenomenon of collateral sensitivity, whereby resistance to one antibiotic is accompanied by increased sensitivity to another, offers potential avenues for novel therapeutic interventions against infections unresponsive to classical treatments. In this study, we elucidate the emergence of tobramycin (TOB)-resistant small colony variants (SCVs) due to mutations in the hemL gene, which render S. Typhimurium more susceptible to nitrofurantoin (NIT). Mechanistic studies demonstrate that the collateral sensitivity in TOB-resistant S. Typhimurium SCVs primarily stems from disruptions in haem biosynthesis. This leads to dysfunction in the electron transport chain (ETC) and redox imbalance, ultimately inducing lethal accumulation of reactive oxygen species (ROS). Additionally, the upregulation of nfsA/B expressions facilitates the conversion of NIT prodrug into its active form, promoting ROS-mediated bacterial killing and contributing to this collateral sensitivity pattern. Importantly, alternative NIT therapy demonstrates a significant reduction of bacterial load by more than 2.24-log10 cfu/g in the murine thigh infection and colitis models. Our findings corroborate the collateral sensitivity of S. Typhimurium to nitrofurans as a consequence of evolving resistance to aminoglycosides. This provides a promising approach for treating infections due to aminoglycoside-resistant strains.

Ecological and evolutionary mechanisms driving within-patient emergence of antimicrobial resistance

The ecological and evolutionary mechanisms of antimicrobial resistance (AMR) emergence within patients and how these vary across bacterial infections are poorly understood. Increasingly widespread use of pathogen genome sequencing in the clinic enables a deeper understanding of these processes. In this Review, we explore the clinical evidence to support four major mechanisms of within-patient AMR emergence in bacteria: spontaneous resistance mutations; in situ horizontal gene transfer of resistance genes; selection of pre-existing resistance; and immigration of resistant lineages. Within-patient AMR emergence occurs across a wide range of host niches and bacterial species, but the importance of each mechanism varies between bacterial species and infection sites within the body. We identify potential drivers of such differences and discuss how ecological and evolutionary analysis could be embedded within clinical trials of antimicrobials, which are powerful but underused tools for understanding why these mechanisms vary between pathogens, infections and individuals. Ultimately, improving understanding of how host niche, bacterial species and antibiotic mode of action combine to govern the ecological and evolutionary mechanism of AMR emergence in patients will enable more predictive and personalized diagnosis and antimicrobial therapies.

Identifying Novel Therapeutics for the Resistant Mutant "F533L" in PBP3 of Pseudomonas aeruginosa Using ML Techniques

Pseudomonas aeruginosa (P. aeruginosa) is a highly infectious and antibiotic-resistant bacterium, which causes acute and chronic nosocomial infections. P. aeruginosa exhibits multidrug resistance due to the emergence of resistant mutants. The bacterium takes advantage of intrinsic and acquired resistance mechanisms to resist almost every antibiotic. To overcome the drug-resistance problem, there is a need to develop effective drugs against antibiotic-resistant mutants. Therefore, in this study, we selected the F533L mutation in PBP3 (penicillin-binding protein 3) because of its important role in β-lactam recognition. To target this mutation, we screened 147 antibacterial compounds from PubChem through a machine-learning model developed based on the decision stump algorithm with 75.75% accuracy and filtered out 55 compounds. Subsequently, out of 55 compounds, 47 compounds were filtered based on their drug-like activity. These 47 compounds were subjected to virtual screening to obtain binding affinity compounds. The binding affinity range of all 47 compounds was -11.3 to -4.6 kcal mol-1. The top 10 compounds were examined according to their binding with the mutation point. A molecular dynamic simulation of the top 8 compounds was conducted to understand the stability of the compounds containing the mutated PBP3. Out of 8 compounds, 3 compounds, namely, macozinone, antibacterial agent 71, and antibacterial agent 123, showed good stability and were validated by RMSD, RMSF, and binding-free analysis. The findings of this study revealed promising antibacterial compounds against the F533L mutant PBP3. Furthermore, developments in these compounds may pave the way for novel therapeutic interventions.

Variation in the response to antibiotics and life-history across the major Pseudomonas aeruginosa clone type (mPact) panel

Pseudomonas aeruginosa is a ubiquitous, opportunistic human pathogen. Since it often expresses multidrug resistance, new treatment options are urgently required. Such new treatments are usually assessed with one of the canonical laboratory strains, PAO1 or PA14. However, these two strains are unlikely representative of the strains infecting patients, because they have adapted to laboratory conditions and do not capture the enormous genomic diversity of the species. Here, we characterized the major P. aeruginosa clone type (mPact) panel. This panel consists of 20 strains, which reflect the species' genomic diversity, cover all major clone types, and have both patient and environmental origins. We found significant strain variation in distinct responses toward antibiotics and general growth characteristics. Only few of the measured traits are related, suggesting independent trait optimization across strains. High resistance levels were only identified for clinical mPact isolates and could be linked to known antimicrobial resistance (AMR) genes. One strain, H01, produced highly unstable AMR combined with reduced growth under drug-free conditions, indicating an evolutionary cost to resistance. The expression of microcolonies was common among strains, especially for strain H15, which also showed reduced growth, possibly indicating another type of evolutionary trade-off. By linking isolation source, growth, and virulence to life history traits, we further identified specific adaptive strategies for individual mPact strains toward either host processes or degradation pathways. Overall, the mPact panel provides a reasonably sized set of distinct strains, enabling in-depth analysis of new treatment designs or evolutionary dynamics in consideration of the species' genomic diversity.

IMPORTANCE

New treatment strategies are urgently needed for high-risk pathogens such as the opportunistic and often multidrug-resistant pathogen Pseudomonas aeruginosa. Here, we characterize the major P. aeruginosa clone type (mPact) panel. It consists of 20 strains with different origins that cover the major clone types of the species as well as its genomic diversity. This mPact panel shows significant variation in (i) resistance against distinct antibiotics, including several last resort antibiotics; (ii) related traits associated with the response to antibiotics; and (iii) general growth characteristics. We further developed a novel approach that integrates information on resistance, growth, virulence, and life-history characteristics, allowing us to demonstrate the presence of distinct adaptive strategies of the strains that focus either on host interaction or resource processing. In conclusion, the mPact panel provides a manageable number of representative strains for this important pathogen for further in-depth analyses of treatment options and evolutionary dynamics.

Temperature dependence of the mutation rate towards antibiotic resistance

Objectives

Environmental conditions can influence mutation rates in bacteria. Fever is a common response to infection that alters the growth conditions of infecting bacteria. Here we examine how a temperature change, such as is associated with fever, affects the mutation rate towards antibiotic resistance.

Methods

We used a fluctuation test to assess the mutation rate towards antibiotic resistance in Escherichia coli at two different temperatures: 37°C (normal temperature) and 40°C (fever temperature). We performed this measurement for three different antibiotics with different modes of action: ciprofloxacin, rifampicin and ampicillin.

Results

In all cases, the mutation rate towards antibiotic resistance turned out to be temperature dependent, but in different ways. Fever temperatures led to a reduced mutation rate towards ampicillin resistance and an elevated mutation rate towards ciprofloxacin and rifampicin resistance.

Conclusions

This study shows that the mutation rate towards antibiotic resistance is impacted by a small change in temperature, such as associated with fever. This opens a new avenue to mitigate the emergence of antibiotic resistance by coordinating the choice of an antibiotic with the decision of whether or not to suppress fever when treating a patient. Hence, optimized combinations of antibiotics and fever suppression strategies may be a new weapon in the battle against antibiotic resistance.

Effect of glucose on growth and co-culture of Staphylococcus aureus and Pseudomonas aeruginosa in artificial sputum medium

People with cystic fibrosis-related diabetes (CFRD) suffer from chronic infections with Staphylococcus aureus and/or Pseudomonas aeruginosa. In people with CFRD, the concentration of glucose in the airway surface liquid (ASL) was shown to be elevated from 0.4 to 4 mM. The effect of glucose on bacterial growth/interactions in ASL is not well understood and here we studied the relationship between these lung pathogens in artificial sputum medium (ASM), an environment similar to ASL in vivo. S. aureus exhibited more rapid adaptation to growth in ASM than P. aeruginosa. Supplementation of ASM with glucose significantly increased the growth of S. aureus (p < 0.01, n = 5) and P. aeruginosa (p < 0.001, n = 3). ASM conditioned by the presence of S. aureus promoted growth of P. aeruginosa with less lag time compared with non-conditioned ASM, or conditioned medium that had been heated to 121 °C. Stable co-culture of S. aureus and P. aeruginosa could be established in a 50:50 mix of ASM and S. aureus-conditioned supernatant. These data indicate that glucose, in a nutrient depleted environment, can promote the growth of S. aureus and P. aeruginosa. In addition, heat labile factors present in S. aureus pre-conditioned ASM promoted the growth of P. aeruginosa. We suggest that the use of ASM allows investigation of the effects of nutrients such as glucose on common lung pathogens. ASM could be further used to understand the relationship between S. aureus and P. aeruginosa in a co-culture scenario. Our model of stable co-culture could be extrapolated to include other common lung pathogens and could be used to better understand disease progression in vitro.

Whole-Genome Sequencing Reveals Diversity of Carbapenem-Resistant Pseudomonas aeruginosa Collected through CDC's Emerging Infections Program, United States, 2016-2018

The CDC's Emerging Infections Program (EIP) conducted population- and laboratory-based surveillance of US carbapenem-resistant Pseudomonas aeruginosa (CRPA) from 2016 through 2018. To characterize the pathotype, 1,019 isolates collected through this project underwent antimicrobial susceptibility testing and whole-genome sequencing. Sequenced genomes were classified using the seven-gene multilocus sequence typing (MLST) scheme and a core genome (cg)MLST scheme was used to determine phylogeny. Both chromosomal and horizontally transmitted mechanisms of carbapenem resistance were assessed. There were 336 sequence types (STs) among the 1,019 sequenced genomes, and the genomes varied by an average of 84.7% of the cgMLST alleles used. Mutations associated with dysfunction of the porin OprD were found in 888 (87.1%) of the genomes and were correlated with carbapenem resistance, and a machine learning model incorporating hundreds of genetic variations among the chromosomal mechanisms of resistance was able to classify resistant genomes. While only 7 (0.1%) isolates harbored carbapenemase genes, 66 (6.5%) had acquired non-carbapenemase β-lactamase genes, and these were more likely to have OprD dysfunction and be resistant to all carbapenems tested. The genetic diversity demonstrates that the pathotype includes a variety of strains, and clones previously identified as high-risk make up only a minority of CRPA strains in the United States. The increased carbapenem resistance in isolates with acquired non-carbapenemase β-lactamase genes suggests that horizontally transmitted mechanisms aside from carbapenemases themselves may be important drivers of the spread of carbapenem resistance in P. aeruginosa.

The physiology and genetics of bacterial responses to antibiotic combinations

Several promising strategies based on combining or cycling different antibiotics have been proposed to increase efficacy and counteract resistance evolution, but we still lack a deep understanding of the physiological responses and genetic mechanisms that underlie antibiotic interactions and the clinical applicability of these strategies. In antibiotic-exposed bacteria, the combined effects of physiological stress responses and emerging resistance mutations (occurring at different time scales) generate complex and often unpredictable dynamics. In this Review, we present our current understanding of bacterial cell physiology and genetics of responses to antibiotics. We emphasize recently discovered mechanisms of synergistic and antagonistic drug interactions, hysteresis in temporal interactions between antibiotics that arise from microbial physiology and interactions between antibiotics and resistance mutations that can cause collateral sensitivity or cross-resistance. We discuss possible connections between the different phenomena and indicate relevant research directions. A better and more unified understanding of drug and genetic interactions is likely to advance antibiotic therapy.

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.

Pseudomonas aeruginosa adaptation and evolution in patients with cystic fibrosis

Intense genome sequencing of Pseudomonas aeruginosa isolates from cystic fibrosis (CF) airways has shown inefficient eradication of the infecting bacteria, as well as previously undocumented patient-to-patient transmission of adapted clones. However, genome sequencing has limited potential as a predictor of chronic infection and of the adaptive state during infection, and thus there is increasing interest in linking phenotypic traits to the genome sequences. Phenotypic information ranges from genome-wide transcriptomic analysis of patient samples to determination of more specific traits associated with metabolic changes, stress responses, antibiotic resistance and tolerance, biofilm formation and slow growth. Environmental conditions in the CF lung shape both genetic and phenotypic changes of P. aeruginosa during infection. In this Review, we discuss the adaptive and evolutionary trajectories that lead to early diversification and late convergence, which enable P. aeruginosa to succeed in this niche, and we point out how knowledge of these biological features may be used to guide diagnosis and therapy.

Antibiotic resistance heterogeneity and LasR diversity within Pseudomonas aeruginosa populations from pneumonia in intensive care unit patients

This study investigated within-host heterogeneity of 66 Pseudomonas aeruginosa populations from pneumonia in 51 critically ill ventilated patients by examining 30 colonies per bronchoalveolar lavage (BAL). Differences in antibiotic susceptibility and quorum-sensing (QS) phenotypes were observed between the members of 14 (21.2%) and 10 (15.2%) populations, respectively. A significant association was found between QS deficiency and ceftazidime resistance. QS deficiency was associated with various lasR modifications, and was observed in 25 of 51 (49.0%) patients, including seven patients who received ≤48 h of ventilation. This study confirms the need to examine diverse colonies when analysing BAL cultures, particularly in β-lactam-exposed patients, to avoid missing ceftazidime- or imipenem-resistant isolates.

Antimicrobial resistance of ocular microbes and the role of antimicrobial peptides

Isolation of antimicrobial-resistant microbes from ocular infections may be becoming more frequent. Infections caused by these microbes can be difficult to treat and lead to poor outcomes. However, new therapies are being developed which may help improve clinical outcomes. This review examines recent reports on the isolation of antibiotic-resistant microbes from ocular infections. In addition, an overview of the development of some new antibiotic therapies is given. The recent literature regarding antibiotic use and resistance, isolation of antibiotic-resistant microbes from ocular infections and the development of potential new antibiotics that can be used to treat these infections was reviewed. Ocular microbial infections are a global public health issue as they can result in vision loss which compromises quality of life. Approximately 70 per cent of ocular infections are caused by bacteria including Chlamydia trachomatis, Staphylococcus aureus, and Pseudomonas aeruginosa and fungi such as Candida albicans, Aspergillus spp. and Fusarium spp. Resistance to first-line antibiotics such as fluoroquinolones and azoles has increased, with resistance of S. aureus isolates from the USA to fluoroquinolones reaching 32 per cent of isolates and 35 per cent being methicillin-resistant (MRSA). Lower levels of MRSA (seven per cent) were isolated by an Australian study. Antimicrobial peptides, which are broad-spectrum alternatives to antibiotics, have been tested as possible new drugs. Several have shown promise in animal models of keratitis, especially treating P. aeruginosa, S. aureus or C. albicans infections. Reports of increasing resistance of ocular isolates to mainstay antibiotics are a concern, and there is evidence that for ocular surface disease this resistance translates into worse clinical outcomes. New antibiotics are being developed, but not by large pharmaceutical companies and mostly in university research laboratories and smaller biotech companies. Antimicrobial peptides show promise in treating keratitis.

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.

Mechanisms of Resistance to Ceftolozane/Tazobactam in Pseudomonas aeruginosa: Results of the GERPA Multicenter Study

Resistance mechanisms of Pseudomonas aeruginosa to ceftolozane/tazobactam (C/T) were assessed on a collection of 420 nonredundant strains nonsusceptible to ceftazidime (MIC > 8 μg/ml) and/or imipenem (>4 μg/ml), collected by 36 French hospital laboratories over a one-month period (the GERPA study). Rates of C/T resistance (MIC > 4/4 μg/ml) were equal to 10% in this population (42/420 strains), and 23.2% (26/112) among the isolates resistant to both ceftazidime and imipenem. A first group of 21 strains (50%) was found to harbor various extended-spectrum β-lactamases (1 OXA-14; 2 OXA-19; 1 OXA-35; 1 GES-9; and 3 PER-1), carbapenemases (2 GES-5; 1 IMP-8; and 8 VIM-2), or both (1 VIM-2/OXA-35 and 1 VIM-4/SHV-2a). All the strains of this group belonged to widely distributed epidemic clones (ST111, ST175, CC235, ST244, ST348, and ST654), and were highly resistant to almost all the antibiotics tested except colistin. A second group was composed of 16 (38%) isolates moderately resistant to C/T (MICs from 8/4 to 16/4 μg/ml), of which 7 were related to international clones (ST111, ST253, CC274, ST352, and ST386). As demonstrated by targeted mass spectrometry, cloxacillin-based inhibition tests, and gene bla _PDC deletion experiments, this resistance phenotype was correlated with an extremely high production of cephalosporinase PDC. In part accounting for this strong PDC upregulation, genomic analyses revealed the presence of mutations in the regulator AmpR (D135N/G in 6 strains) and enzymes of the peptidoglycan recycling pathway, such as AmpD, PBP4, and Mpl (9 strains). Finally, all of the 5 (12%) remaining C/T-resistant strains (group 3) appeared to encode PDC variants with mutations known to improve the hydrolytic activity of the β-lactamase toward ceftazidime and C/T (F147L, ΔL223-Y226, E247K, and N373I). Collectively, our results highlight the importance of both intrinsic and transferable mechanisms in C/T-resistant P. aeruginosa Which mutational events lead some clinical strains to massively produce the natural cephalosporinase PDC remains incompletely understood.

CombiANT: Antibiotic interaction testing made easy

Antibiotic combination therapies are important for the efficient treatment of many types of infections, including those caused by antibiotic-resistant pathogens. Combination treatment strategies are typically used under the assumption that synergies are conserved across species and strains, even though recent results show that the combined treatment effect is determined by specific drug–strain interactions that can vary extensively and unpredictably, both between and within bacterial species. To address this problem, we present a new method in which antibiotic synergy is rapidly quantified on a case-by-case basis, allowing for improved combination therapy. The novel CombiANT methodology consists of a 3D-printed agar plate insert that produces defined diffusion landscapes of 3 antibiotics, permitting synergy quantification between all 3 antibiotic pairs with a single test. Automated image analysis yields fractional inhibitory concentration indices (FICis) with high accuracy and precision. A technical validation with 3 major pathogens, Escherichia coli, Pseudomonas aeruginosa, and Staphylococcus aureus, showed equivalent performance to checkerboard methodology, with the advantage of strongly reduced assay complexity and costs for CombiANT. A synergy screening of 10 antibiotic combinations for 12 E. coli urinary tract infection (UTI) clinical isolates illustrates the need for refined combination treatment strategies. For example, combinations of trimethoprim (TMP) + nitrofurantoin (NIT) and TMP + mecillinam (MEC) showed synergy, but only for certain individual isolates, whereas MEC + NIT combinations showed antagonistic interactions across all tested strains. These data suggest that the CombiANT methodology could allow personalized clinical synergy testing and large-scale screening. We anticipate that CombiANT will greatly facilitate clinical and basic research of antibiotic synergy.

Existing methods for identifying efficient combinations of antibiotics are time-consuming and costly, restricting their use in clinics and research. This study describes the novel CombiANT methodology, which uses defined diffusion landscapes of three antibiotics to permit rapid and low-cost synergy quantification between all antibiotic pairs.

Evolutionary Approaches to Combat Antibiotic Resistance: Opportunities and Challenges for Precision Medicine

The rise of antimicrobial resistance (AMR) in bacterial pathogens is acknowledged by the WHO as a major global health crisis. It is estimated that in 2050 annually up to 10 million people will die from infections with drug resistant pathogens if no efficient countermeasures are implemented. Evolution of pathogens lies at the core of this crisis, which enables rapid adaptation to the selective pressures imposed by antimicrobial usage in both medical treatment and agriculture, consequently promoting the spread of resistance genes or alleles in bacterial populations. Approaches developed in the field of Evolutionary Medicine attempt to exploit evolutionary insight into these adaptive processes, with the aim to improve diagnostics and the sustainability of antimicrobial therapy. Here, we review the concept of evolutionary trade-offs in the development of AMR as well as new therapeutic approaches and their impact on host-microbiome-pathogen interactions. We further discuss the possible translation of evolution-informed treatments into clinical practice, considering both the rapid cure of the individual patients and the prevention of AMR.

Phenotypic Variation and Carbapenem Resistance Potential in OXA-499-Producing Acinetobacter pittii

Acinetobacter pittii is increasingly recognized as a clinically important species. Here, we identified a carbapenem-non-resistant A. pittii clinical isolate, A1254, harboring bla_OXA–499, bla_OXA–826, and bla_ADC–221. The bla_OXA–499 genetic environment in A1254 was identical to that of another OXA-499-producing, but carbapenem-resistant, A. pittii isolate, YMC2010/8/T346, indicating the existence of phenotypic variation among OXA-499-producing A. pittii strains. Under imipenem-selective pressure, the A1254 isolate developed resistance to carbapenems in 60 generations. Two carbapenem-resistant mutants (CAB009 and CAB010) with mutations in the bla_OXA–499 promoter region were isolated from two independently evolved populations (CAB001 and CAB004). The CAB009 mutant, with a mutation at position −14 (A to G), exhibited a four-fold higher carbapenem minimum inhibitory concentration (MIC) and a 4.53 ± 0.19 log₂ fold change higher expression level of bla_OXA–499 than the ancestor strain, A1254. The other mutant, CAB010, with a mutation at position −42 (G to A), showed a two-fold higher carbapenem MIC and a 1.65 ± 0.25 log₂ fold change higher bla_OXA–499 expression level than the ancestor strain. The bla_OXA–499 gene and its promoter region were amplified from the wild-type strain and two mutant isolates and then individually cloned into the pYMAb2-Hyg^r vector and expressed in Acinetobacter baumannii ATCC 17978, A. pittii LMG 1035, and A. pittii A1254. All the transformed strains were resistant to carbapenem, irrespective of whether they harbored the initial or an evolved promoter sequence, and transformed strains expressing the promoter from the most resistant mutant, CAB009, showed the highest carbapenem MICs, with values of 32–64 μg/ml for imipenem and 128 μg/ml for meropenem. RNA sequencing was performed to confirm the contribution of bla_OXA–499 to the development of carbapenem resistance. Although the CAB009 and CAB010 transcriptional patterns were different, bla_OXA–499 was the only differentially expressed gene shared by the two mutants. Our results indicate that carbapenem-non-resistant Acinetobacter spp. strains carrying bla_OXA genes have the potential to develop carbapenem resistance and need to be further investigated and monitored to prevent treatment failure due to the development of resistance.

Molecular mechanisms of collateral sensitivity to the antibiotic nitrofurantoin

Antibiotic resistance increasingly limits the success of antibiotic treatments, and physicians require new ways to achieve efficient treatment despite resistance. Resistance mechanisms against a specific antibiotic class frequently confer increased susceptibility to other antibiotic classes, a phenomenon designated collateral sensitivity (CS). An informed switch of antibiotic may thus enable the efficient treatment of resistant strains. CS occurs in many pathogens, but the mechanisms that generate hypersusceptibility are largely unknown. We identified several molecular mechanisms of CS against the antibiotic nitrofurantoin (NIT). Mutants that are resistant against tigecycline (tetracycline), mecillinam (β-lactam), and protamine (antimicrobial peptide) all show CS against NIT. Their hypersusceptibility is explained by the overexpression of nitroreductase enzymes combined with increased drug uptake rates, or increased drug toxicity. Increased toxicity occurs through interference of the native drug-response system for NIT, the SOS response, with growth. A mechanistic understanding of CS will help to develop drug switches that combat resistance.

Resistance mechanisms against a specific antibiotic class frequently often confer negative cross-resistance to other antibiotic classes, a phenomenon known as collateral sensitivity. This study shows that collateral sensitivity in bacteria can be explained by a combination of several mechanisms that can be exploited to develop drug switches that combat resistance.

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.