Alternative Evolutionary Paths to Bacterial Antibiotic Resistance Cause Distinct Collateral Effects

Chloramphenicol and gentamicin reduce the evolution of resistance to phage ΦX174 by suppressing a subset of E. coli LPS mutants

Bacteriophages infect gram-negative bacteria by attaching to molecules present on the bacterial surface, often lipopolysaccharides (LPS). Modification of LPS can lead to resistance to phage infection. In addition, LPS modifications can impact antibiotic susceptibility, allowing for phage-antibiotic synergism. The evolutionary mechanism(s) behind such synergistic interactions remain largely unclear. Here, we show that the presence of antibiotics can affect the evolution of resistance to phage infection, using phage ΦX174 and Escherichia coli C. We use a collection of 34 E. coli C LPS strains, each of which is resistant to ΦX174, and has either a "rough" or "deep rough" LPS phenotype. Growth of the bacterial strains with the deep rough phenotype is inhibited at low concentrations of chloramphenicol and, to a much lesser degree, gentamicin. Treating E. coli C wild type with ΦX174 and chloramphenicol eliminates the emergence of mutants with the deep rough phenotype, and thereby slows the evolution of resistance to phage infection. At slightly lower chloramphenicol concentrations, phage resistance rates are similar to those observed at high concentrations; yet, we show that the diversity of possible mutants is much larger than at higher chloramphenicol concentrations. These data suggest that specific antibiotic concentrations can lead to synergistic phage-antibiotic interactions that disappear at higher antibiotic concentrations. Overall, we show that the change in survival of various ΦX174-resistant E. coli C mutants in the presence of antibiotics can explain the observed phage-antibiotic synergism.

Systematic mapping of antibiotic cross-resistance and collateral sensitivity with chemical genetics

By acquiring or evolving resistance to one antibiotic, bacteria can become cross-resistant to a second antibiotic, which further limits therapeutic choices. In the opposite scenario, initial resistance leads to collateral sensitivity to a second antibiotic, which can inform cycling or combinatorial treatments. Despite their clinical relevance, our knowledge of both interactions is limited. We used published chemical genetics data of the Escherichia coli single-gene deletion library in 40 antibiotics and devised a metric that discriminates between known cross-resistance and collateral-sensitivity antibiotic interactions. Thereby we inferred 404 cases of cross-resistance and 267 of collateral-sensitivity, expanding the number of known interactions by over threefold. We further validated 64/70 inferred interactions using experimental evolution. By identifying mutants driving these interactions in chemical genetics, we demonstrated that a drug pair can exhibit both interactions depending on the resistance mechanism. Finally, we applied collateral-sensitive drug pairs in combination to reduce antibiotic-resistance development in vitro.

Dynamic collateral sensitivity profiles highlight opportunities and challenges for optimizing antibiotic treatments

As failure rates for traditional antimicrobial therapies escalate, recent focus has shifted to evolution-based therapies to slow resistance. Collateral sensitivity-the increased susceptibility to one drug associated with evolved resistance to a different drug-offers a potentially exploitable evolutionary constraint, but the manner in which collateral effects emerge over time is not well understood. Here, we use laboratory evolution in the opportunistic pathogen Enterococcus faecalis to phenotypically characterize collateral profiles through evolutionary time. Specifically, we measure collateral profiles for 400 strain-antibiotic combinations over the course of 4 evolutionary time points as strains are selected in increasing concentrations of antibiotic. We find that at a global level-when results from all drugs are combined-collateral resistance dominates during early phases of adaptation, when resistance to the selecting drug is lower, while collateral sensitivity becomes increasingly likely with further selection. At the level of individual populations; however, the trends are idiosyncratic; for example, the frequency of collateral sensitivity to ceftriaxone increases over time in isolates selected by linezolid but decreases in isolates selected by ciprofloxacin. We then show experimentally how dynamic collateral sensitivity relationships can lead to time-dependent dosing windows that depend on finely timed switching between drugs. Finally, we develop a stochastic mathematical model based on a Markov decision process consistent with observed dynamic collateral profiles to show measurements across time are required to optimally constrain antibiotic resistance.

Neutral drift upon threshold-like selection promotes variation in antibiotic resistance phenotype

Heritable phenotypic variation plays a central role in evolution by conferring rapid adaptive capacity to populations. Mechanisms that can explain genetic diversity by describing connections between genotype and organismal fitness have been described. However, the difficulty of acquiring comprehensive data on genotype-phenotype-environment relationships has hindered the efforts to explain how the ubiquitously observed phenotypic variation in populations emerges and is maintained. To address this challenge, we establish an experimental system where we can examine the genotype-phenotype relationships in a controlled environment. We perform long-term experimental evolution on VIM-2 β-lactamase, an antibiotic-resistance enzyme, to explore the conditions that promote the emergence and maintenance of phenotypic variation. We found that evolution in a static environment with low antibiotic concentrations can promote and maintain significant phenotypic variation within populations. Notably, evolution of VIM-2 under selection with a low antibiotic concentration led to variants that conferred resistance to over 100-fold higher antibiotic concentrations than used in selection. A model based on the previously described threshold-like relationship between enzyme phenotype and fitness generated using VIM-2's all single amino acid variants, sufficiently explains the emergence of standing phenotypic variation under static environmental conditions. Overall, our approach provides a tractable model for studying phenotypic variation and evolvability at the population level.

Collateral Sensitivity to β-Lactam Antibiotics in Evolved Apramycin-Resistant MRSA

Collateral sensitivity is an evolutionary trade-off for bacteria where acquiring resistance to one antibiotic results in an increased sensitivity to another antibiotic. This study was designed to evaluate the collateral sensitivity of methicillin-resistant Staphylococcus aureus (MRSA) to β-lactam antibiotics induced by the evolution of resistance to apramycin. Collateral sensitivity to ampicillin, cephazolin, ceftriaxone, cefotaxime, cefepime and cefquinome occurred after MRSA were exposed to apramycin and induced to acquire resistance. This sensitivity was associated with reduced β-lactamase activity and decreased expression of the mecA gene. We also found a decrease in the proton motive force and decreased efflux activity. These results provide new insights into collateral sensitivity-based strategies for the treatment of MRSA.

Whole genome CRISPRi screening identifies druggable vulnerabilities in an isoniazid resistant strain of Mycobacterium tuberculosis

Drug-resistant strains of Mycobacterium tuberculosis are a major global health problem. Resistance to the front-line antibiotic isoniazid is often associated with mutations in the katG-encoded bifunctional catalase-peroxidase. We hypothesise that perturbed KatG activity would generate collateral vulnerabilities in isoniazid-resistant katG mutants, providing potential pathway targets to combat isoniazid resistance. Whole genome CRISPRi screens, transcriptomics, and metabolomics were used to generate a genome-wide map of cellular vulnerabilities in an isoniazid-resistant katG mutant strain of M. tuberculosis. Here, we show that metabolic and transcriptional remodelling compensates for the loss of KatG but in doing so generates vulnerabilities in respiration, ribosome biogenesis, and nucleotide and amino acid metabolism. Importantly, these vulnerabilities are more sensitive to inhibition in an isoniazid-resistant katG mutant and translated to clinical isolates. This work highlights how changes in the physiology of drug-resistant strains generates druggable vulnerabilities that can be exploited to improve clinical outcomes.

Collateral sensitivity counteracts the evolution of antifungal drug resistance in Candida auris

Antifungal drug resistance represents a serious global health threat, necessitating new treatment strategies. Here we investigated collateral sensitivity (CS), in which resistance to one drug increases sensitivity to another, and cross-resistance (XR), in which one drug resistance mechanism reduces susceptibility to multiple drugs, since CS and XR dynamics can guide treatment design to impede resistance development, but have not been systematically explored in pathogenic fungi. We used experimental evolution and mathematical modelling of Candida auris population dynamics during cyclic and combined drug exposures and found that especially CS-based drug cycling can effectively prevent the emergence of drug resistance. In addition, we found that a CS-based treatment switch can actively select against or eradicate resistant sub-populations, highlighting the potential to consider CS in therapeutic decision-making upon resistance detection. Furthermore, we show that some CS trends are robust among different strains and resistance mechanisms. Overall, these findings provide a promising direction for improved antifungal treatment approaches.

Navigating collateral sensitivity: insights into the mechanisms and applications of antibiotic resistance trade-offs

The swift rise of antibiotic resistance, coupled with limited new antibiotic discovery, presents a significant hurdle to global public health, demanding innovative therapeutic solutions. Recently, collateral sensitivity (CS), the phenomenon in which resistance to one antibiotic increases vulnerability to another, has come to light as a potential path forward in this attempt. Targeting either unidirectional or reciprocal CS holds promise for constraining the emergence of drug resistance and notably enhancing treatment outcomes. Typically, the alteration of bacterial physiology, such as bacterial membrane potential, expression of efflux pumps, cell wall structures, and endogenous enzymatic actions, are involved in evolved collateral sensitivity. In this review, we present a thorough overview of CS in antibiotic therapy, including its definition, importance, and underlying mechanisms. We describe how CS can be exploited to prevent the emergence of resistance and enhance the results of treatment, but we also discuss the challenges and restrictions that come with implementing this practice. Our review underscores the importance of continued exploration of CS mechanisms in the broad spectrum and clinical validation of therapeutic approaches, offering insights into its role as a valuable tool in combating antibiotic resistance.

Drug combinations targeting antibiotic resistance

While the rise of antibiotic resistance poses a global health challenge, the development of new antibiotics has slowed down over the past decades. This turned the attention of researchers towards the rational design of drug combination therapies to combat antibiotic resistance. In this review we discuss how drug combinations can exploit the deleterious pleiotropic effects of antibiotic resistance and conclude that each drug interaction has its prospective therapeutic application.

Unraveling the determinants of antibiotic resistance evolution in farmland under fertilizations

Organic fertilization is a major driver potentiating soil antibiotic resistance in farmland. However, it remains unclear how bacterial antibiotic resistance evolves in fertilized soils and even spreads to crops. Compared with no fertilizer and commercial fertilizer treatments, organic fertilizers markedly increased the abundance of soil antibiotic resistance genes (ARGs) but the relatively weaker transfer of resistance genes from soil to crops. The introduction of organic fertilizers enriches the soil with nutrients, driving indigenous microorganisms towards a K-strategy. The pH, EC, and nutrients as key drivers influenced the ARGs abundance. The neutral (pH 7.2), low salt (TDS 1.4 %) and mesotrophic (carbon content 3.54 g/L) habitats similar to the soil environment conditioned by organic fertilizers. These environmental conditions clearly prolonged the persistence of resistant plasmids, and facilitated their dissemination to massive conjugators soil microbiome but not to plant endophytes. This suggested that organic fertilizers inhibited the spread of ARGs to crops. Moreover, the composition of conjugators showed differential selection of resistant plasmids by endophytes under these conditions. This study sheds light on the evolution and dissemination of antibiotic resistance in farmlands and can aid in the development of antimicrobial resistance control strategies in agriculture.

The effect of antibiotic selection on collateral effects and evolvability of uropathogenic Escherichia coli

Trimethoprim is recommended as a first-line treatment of urinary tract infections (UTIs) in the UK. In 2018, 31.4% of Escherichia coli isolated from UTIs in England were trimethoprim-resistant, leading to overreliance on other first and second-line antibiotics. Here, we assessed whether, in principle, prior selection with trimethoprim results in collateral effects to other antibiotics recommended for the treatment of UTIs. As collateral effects, we considered changes in susceptibility, mutation-selection window and population establishment probability. We selected 10 trimethoprim-resistant derivatives from three clinical isolates of uropathogenic Escherichia coli. We found that mutations conferring trimethoprim resistance did not have any collateral effects on fosfomycin. In contrast, resistance to trimethoprim resulted in decreased susceptibility (collateral resistance) to nitrofurantoin, below the clinical breakpoint and narrowed the mutation-selection window, thereby reducing the maximum concentration for selection of nitrofurantoin resistance mutations. Our analyses demonstrate that multiple collateral responses should be accounted for when predicting and optimising antibiotic use, limiting future antimicrobial resistance emergence.

Preserving the efficacy of antibiotics to tackle antibiotic resistance

Different international agencies recognize that antibiotic resistance is one of the most severe human health problems that humankind is facing. Traditionally, the introduction of new antibiotics solved this problem but various scientific and economic reasons have led to a shortage of novel antibiotics at the pipeline. This situation makes mandatory the implementation of approaches to preserve the efficacy of current antibiotics. The concept is not novel, but the only action taken for such preservation had been the 'prudent' use of antibiotics, trying to reduce the selection pressure by reducing the amount of antibiotics. However, even if antibiotics are used only when needed, this will be insufficient because resistance is the inescapable outcome of antibiotics' use. A deeper understanding of the alterations in the bacterial physiology upon acquisition of resistance and during infection will help to design improved strategies to treat bacterial infections. In this article, we discuss the interconnection between antibiotic resistance (and antibiotic activity) and bacterial metabolism, particularly in vivo, when bacteria are causing infection. We discuss as well how understanding evolutionary trade-offs, as collateral sensitivity, associated with the acquisition of resistance may help to define evolution-based therapeutic strategies to fight antibiotic resistance and to preserve currently used antibiotics.

Cross-talk of MLST and transcriptome unveiling antibiotic resistance mechanism of carbapenem resistance Acinetobacter baumannii clinical strains isolated in Guiyang, China

Introduction

Acinetobacter baumannii (A. baumannii) is an important opportunistic pathogen causing nosocomial infection in the clinic. The occurrence rate of antibiotic resistance is increasing year by year, resulting in a highly serious situation of bacterial resistance.

Methods

To better understand the local epidemiology of multidrug-resistant A. baumannii, an investigation was conducted on the antibiotic resistance of different types of A. baumannii and its relationship with the genes of A. baumannii. Furthermore, the molecular mechanism underlying antibiotic resistance in A. baumannii was investigated through transcriptome analysis.

Results

These results showed that a total of 9 STs were detected. It was found that 99% of the strains isolated in the hospital belonged to the same STs, and the clone complex CC208 was widely distributed in various departments and all kinds of samples. Furthermore, these A. baumannii strains showed high resistance to ertapenem, biapenem, meropenem, and imipenem, among which the resistance to ertapenem was the strongest. The detection rate of bla OXA-51 gene in these carbapenem resistance A. baumannii (CRAB) reached 100%; Additionally, the transcriptome results showed that the resistance genes were up-regulated in resistance strains, and these genes involved in biofilm formation, efflux pumps, peptidoglycan biosynthesis, and chaperonin synthesis.

Discussion

These results suggest that the CC208 STs were the main clonal complex, and showed high carbapenem antibiotic resistance. All these resistant strains were distributed in various departments, but most of them were distributed in intensive care units (ICU). The bla OXA-23 was the main antibiotic resistance genotype; In summary, the epidemic trend of clinical A. baumannii in Guiyang, China was analyzed from the molecular level, and the resistance mechanism of A. baumannii to carbapenem antibiotics was analyzed with transcriptome, which provided a theoretical basis for better control of A. baumannii.

A study of antibiotic resistance pattern of clinical bacterial pathogens isolated from patients in a tertiary care hospital

We investigated antibiotic resistance pattern in clinical bacterial pathogens isolated from in-patients and out-patients, and compared it with non-clinical bacterial isolates. 475 bacterial strains isolated from patients were examined for antibiotic resistance. Staphylococcus spp. (148; 31.1%) were found to be the most prevalent, followed by Klebsiella pneumoniae (135; 28.4%), Escherichia coli (74; 15.5%), Pseudomonas aeruginosa (65; 13.6%), Enterobacter spp. (28; 5.8%), and Acinetobacter spp. (25; 5.2%). Drug-resistant bacteria isolated were extended spectrum-β-lactamase K. pneumoniae (8.8%), E. coli (20%), metallo-β-lactamase P. aeruginosa (14; 2.9%), erythromycin-inducing clindamycin resistant (7.4%), and methicillin-resistant Staphylococcus species (21.6%). Pathogens belonging to the Enterobacteriaceae family were observed to undergo directional selection developing resistance against antibiotics ciprofloxacin, piperacillin-tazobactam, cefepime, and cefuroxime. Pathogens in the surgical ward exhibited higher levels of antibiotic resistance, while non-clinical P. aeruginosa and K. pneumoniae strains were more antibiotic-susceptible. Our research assisted in identifying the drugs that can be used to control infections caused by antimicrobial resistant bacteria in the population and in monitoring the prevalence of drug-resistant bacterial pathogens.

Laboratory Evolution of Antimicrobial Resistance in Bacteria to Develop Rational Treatment Strategies

Laboratory evolution studies, particularly with Escherichia coli, have yielded invaluable insights into the mechanisms of antimicrobial resistance (AMR). Recent investigations have illuminated that, with repetitive antibiotic exposures, bacterial populations will adapt and eventually become tolerant and resistant to the drugs. Through intensive analyses, these inquiries have unveiled instances of convergent evolution across diverse antibiotics, the pleiotropic effects of resistance mutations, and the role played by loss-of-function mutations in the evolutionary landscape. Moreover, a quantitative analysis of multidrug combinations has shed light on collateral sensitivity, revealing specific drug combinations capable of suppressing the acquisition of resistance. This review article introduces the methodologies employed in the laboratory evolution of AMR in bacteria and presents recent discoveries concerning AMR mechanisms derived from laboratory evolution. Additionally, the review outlines the application of laboratory evolution in endeavors to formulate rational treatment strategies.

The Pseudomonas aeruginosa Resistome: Permanent and Transient Antibiotic Resistance, an Overview

One of the most concerning characteristics of Pseudomonas aeruginosa is its low susceptibility to several antibiotics of common use in clinics, as well as its facility to acquire increased resistance levels. Consequently, the study of the antibiotic resistance mechanisms of this bacterium is of relevance for human health. For such a study, different types of resistance should be distinguished. The intrinsic resistome is composed of a set of genes, present in the core genome of P. aeruginosa, which contributes to its characteristic, species-specific, phenotype of susceptibility to antibiotics. Acquired resistance refers to those genetic events, such as the acquisition of mutations or antibiotic resistance genes that reduce antibiotic susceptibility. Finally, antibiotic resistance can be transiently acquired in the presence of specific compounds or under some growing conditions. The current article provides information on methods currently used to analyze intrinsic, mutation-driven, and transient antibiotic resistance in P. aeruginosa.

Heterogeneous Phenotypic Responses of Antibiotic-Resistant Salmonella Typhimurium to Food Preservative-Related Stresses

This study was designed to evaluate the response of antibiotic-resistant Salmonella Typhimurium to food preservative-related stresses, such as lactic acid and sodium chloride (NaCl). S. Typhimurium cells were exposed to 1 µg/mL of ciprofloxacin (CIP), 0.2% lactic acid (LA), 6% NaCl, CIP followed by LA (CIP-LA), and CIP followed by NaCl (CIP-NaCl). The untreated S. Typhimurium cells were the control (CON). All treatments were as follows: CON, CIP, LA, NaCl, CIP-LA, and CIP-NaCl. The phenotypic heterogeneity was evaluated by measuring the antimicrobial susceptibility, bacterial fluctuation, cell injury, persistence, and cross-resistance. The CIP, CIP-LA, and CIP-NaCl groups were highly resistant to ciprofloxacin, showing MIC values of 0.70, 0.59, and 0.54 µg/mL, respectively, compared to the CON group (0.014 µg/mL). The susceptibility to lactic acid was not changed after exposure to NaCl, while that to NaCl was decreased after exposure to NaCl. The Eagle phenomenon was observed in the CIP, CIP-LA, and CIP-NaCl groups, showing Eagle effect concentrations (EECs) of more than 8 µg/mL. No changes in the MBCs of lactic acid and NaCl were observed in the CIP, LA, and CIP-LA groups, and the EECs of lactic acid and NaCl were not detected in all treatments. The bacterial fluctuation rates of the CIP-LA and CIP-NaCl groups were considerably increased to 33% and 41%, respectively, corresponding to the injured cell proportions of 82% and 89%. CIP-NaCl induced persister cells as high as 2 log cfu/mL. The LA and NaCl treatments decreased the fitness cost. The CIP-NaCl treatment showed positive cross-resistance to erythromycin (ERY) and tetracycline (TET), while the LA and NaCl treatments were collaterally susceptible to chloramphenicol (CHL), ciprofloxacin (CIP), piperacillin (PIP), and TET. The results provide new insight into the fate of antibiotic-resistant S. Typhimurium during food processing and preservation.

The evolution of resistance to synergistic multi-drug combinations is more complex than evolving resistance to each individual drug component

Multidrug antibiotic resistance is an urgent public health concern. Multiple strategies have been suggested to alleviate this problem, including the use of antibiotic combinations and cyclic therapies. We examine how adaptation to (1) combinations of drugs affects resistance to individual drugs, and to (2) individual drugs alters responses to drug combinations. To evaluate this, we evolved multiple strains of drug resistant Staphylococcus epidermidis in the lab. We show that evolving resistance to four highly synergistic combinations does not result in cross-resistance to all of their components. Likewise, prior resistance to one antibiotic in a combination does not guarantee survival when exposed to the combination. We also identify four 3-step and four 2-step treatments that inhibit bacterial growth and confer collateral sensitivity with each step, impeding the development of multidrug resistance. This study highlights the importance of considering higher-order drug combinations in sequential therapies and how antibiotic interactions can influence the evolutionary trajectory of bacterial populations.

Translating eco-evolutionary biology into therapy to tackle antibiotic resistance

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

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

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

Ciprofloxacin and Tetracycline Resistance Cause Collateral Sensitivity to Aminoglycosides in Salmonella Typhimurium

The objective of this study was to evaluate collateral sensitivity and cross-resistance of antibiotic-induced resistant Salmonella Typhimurium to various antibiotics. S. Typhimurium ATCC 19585 (STWT) was exposed to ciprofloxacin, gentamicin, kanamycin, and tetracycline to induce antibiotic resistance, respectively, assigned as STCIP, STGEN, STKAN, and STTET. The susceptibilities of the antibiotic-induced resistant mutants to cefotaxime, chloramphenicol, ciprofloxacin, gentamicin, kanamycin, polymyxin B, streptomycin, tetracycline, and tobramycin were determined in the absence and presence of CCCP and PAβN. STCIP showed the cross-resistance to tetracycline and collateral sensitivity to gentamicin (1/2 fold) and kanamycin (1/4 fold). STTET was also cross-resistant to ciprofloxacin (128-fold) and collateral sensitive to gentamicin (1/4-fold) and kanamycin (1/8-fold). The cross-resistance and collateral sensitivity of STCIP and STTET were associated with the AcrAB-TolC efflux pump and outer membrane porin proteins (OmpC). This study provides new insight into the collateral sensitivity phenomenon, which can be used for designing effective antibiotic treatment regimens to control antibiotic-resistant bacteria.

Alternate Antimicrobial Therapies and Their Companion Tests

New antimicrobial approaches are essential to counter antimicrobial resistance. The drug development pipeline is exhausted with the emergence of resistance, resulting in unsuccessful trials. The lack of an effective drug developed from the conventional drug portfolio has mandated the introspection into the list of potentially effective unconventional alternate antimicrobial molecules. Alternate therapies with clinically explicable forms include monoclonal antibodies, antimicrobial peptides, aptamers, and phages. Clinical diagnostics optimize the drug delivery. In the era of diagnostic-based applications, it is logical to draw diagnostic-based treatment for infectious diseases. Selection criteria of alternate therapeutics in infectious diseases include detection, monitoring of response, and resistance mechanism identification. Integrating these diagnostic applications is disruptive to the traditional therapeutic development. The challenges and mitigation methods need to be noted. Applying the goals of clinical pharmacokinetics that include enhancing efficacy and decreasing toxicity of drug therapy, this review analyses the strong correlation of alternate antimicrobial therapeutics in infectious diseases. The relationship between drug concentration and the resulting effect defined by the pharmacodynamic parameters are also analyzed. This review analyzes the perspectives of aligning diagnostic initiatives with the use of alternate therapeutics, with a particular focus on companion diagnostic applications in infectious diseases.

Collateral sensitivity: An evolutionary trade-off between antibiotic resistance mechanisms, attractive for dealing with drug-resistance crisis

Background

The discovery and development of antimicrobial drugs were one of the most significant advances in medicine, but the evolution of microbial resistance limited the efficiency of these drugs.

Aim

This paper reviews the collateral sensitivity in bacteria and its potential and limitation as a new target for treating infections.

Results and Discussion

Knowledge mechanisms of resistance to antimicrobial agents are useful to trace a practical approach to treat and control of resistant pathogens. The effect of a resistance mechanism to certain antibiotics on the susceptibility or resistance to other drugs is a key point that may be helpful for applying a strategy to control resistance challenges. In an evolutionary trade-off known as collateral sensitivity, the resistance mechanism to a certain drug may be mediated by the hypersensitivity to other drugs. Collateral sensitivity has been described for different drugs in various bacteria, but the molecular mechanisms affecting susceptibility are not well demonstrated. Collateral sensitivity could be studied to detect its potential in the battle against resistance crisis as well as in the treatment of pathogens adapting to antibiotics. Collateral sensitivity-based antimicrobial therapy may have the potential to limit the emergence of antibiotic resistance.

The Effects of Preservatives on Antibiotic- and Preservative-Resistant Microbes and Nitrogen/Sulfur Cycle Associated Microbial Communities in Freshwater River Sediments

The intensive use of benzoic acid (BA), 4-hydroxybenzoic acid (HB), and dehydroacetate (DHA) as additives and preservatives in cosmetics and foods causes emerging environmental pollutions. Anthropogenic releases of BA, HB and DHA are primarily emissions into water and soil. However, few studies investigate the effects of BA, HB and DHA on microbial communities in freshwater river sediments. The aim of this study is to reveal the effects of BA, HB and DHA on microbial communities in freshwater river sediments. Tetracycline-, sulfamethoxazole- and preservative-resistant microbes were increased in the river sediments treated with BA, HB and DHA. The relative abundances of methanogen- and xenobiotic-degradation-associated microbial communities were also increased in the BA-, HB- and DHA-treated sediments. The relative abundance of four nitrogen cycle associated microbial groups (anammox, nitrogen fixation, denitrification, and dissimilatory nitrate reduction) were increased after the eighth week in the BA-, HB- and DHA-treated sediments. For the sulfur cycle, the relative abundance of thiosulfate oxidation associated microbial communities were increased after the eighth week in the BA-, HB- and DHA-treated sediments. Results of this study provide insight into the effects of BA, HB and DHA on antibiotic resistance, nitrogen cycle, sulfur cycle, drug resistance and methane production in freshwater aquatic environments.

The evolution of antibiotic resistance in an incurable and ultimately fatal infection: A retrospective case study

Background and objectives

The processes by which pathogens evolve within a host dictate the efficacy of treatment strategies designed to slow antibiotic resistance evolution and influence population-wide resistance levels. The aim of this study is to describe the underlying genetic and phenotypic changes leading to antibiotic resistance within a patient who died as resistance evolved to available antibiotics. We assess whether robust patterns of collateral sensitivity and response to combinations existed that might have been leveraged to improve therapy.

Methodology

We used whole-genome sequencing of nine isolates taken from this patient over 279 days of a chronic infection with Enterobacter hormaechei, and systematically measured changes in resistance against five of the most relevant drugs considered for treatment.

Results

The entirety of the genetic change is consistent with de novo mutations and plasmid loss events, without acquisition of foreign genetic material via horizontal gene transfer. The nine isolates fall into three genetically distinct lineages, with early evolutionary trajectories being supplanted by previously unobserved multi-step evolutionary trajectories. Importantly, although the population evolved resistance to all the antibiotics used to treat the infection, no single isolate was resistant to all antibiotics. Evidence of collateral sensitivity and response to combinations therapy revealed inconsistent patterns across this diversifying population.

Conclusions

Translating antibiotic resistance management strategies from theoretical and laboratory data to clinical situations, such as this, will require managing diverse population with unpredictable resistance trajectories.

Collateral Sensitivity to Fosfomycin of Tobramycin-Resistant Mutants of Pseudomonas aeruginosa Is Contingent on Bacterial Genomic Background

Understanding the consequences in bacterial physiology of the acquisition of drug resistance is needed to identify and exploit the weaknesses derived from it. One of them is collateral sensitivity, a potentially exploitable phenotype that, unfortunately, is not always conserved among different isolates. The identification of robust, conserved collateral sensitivity patterns is then relevant for the translation of this knowledge into clinical practice. We have previously identified a robust fosfomycin collateral sensitivity pattern of Pseudomonas aeruginosa that emerged in different tobramycin-resistant clones. To go one step further, here, we studied if the acquisition of resistance to tobramycin is associated with robust collateral sensitivity to fosfomycin among P. aeruginosa isolates. To that aim, we analyzed, using adaptive laboratory evolution approaches, 23 different clinical isolates of P. aeruginosa presenting diverse mutational resistomes. Nine of them showed collateral sensitivity to fosfomycin, indicating that this phenotype is contingent on the genetic background. Interestingly, collateral sensitivity to fosfomycin was linked to a larger increase in tobramycin minimal inhibitory concentration. Further, we unveiled that fosA low expression, rendering a higher intracellular accumulation of fosfomycin, and a reduction in the expression of the P. aeruginosa alternative peptidoglycan-recycling pathway enzymes, might be on the basis of the collateral sensitivity phenotype.

Tackling antibiotic resistance by inducing transient and robust collateral sensitivity

Collateral sensitivity (CS) is an evolutionary trade-off traditionally linked to the mutational acquisition of antibiotic resistance (AR). However, AR can be temporally induced, and the possibility that this causes transient, non-inherited CS, has not been addressed. Mutational acquisition of ciprofloxacin resistance leads to robust CS to tobramycin in pre-existing antibiotic-resistant mutants of Pseudomonas aeruginosa. Further, the strength of this phenotype is higher when nfxB mutants, over-producing the efflux pump MexCD-OprJ, are selected. Here, we induce transient nfxB-mediated ciprofloxacin resistance by using the antiseptic dequalinium chloride. Notably, non-inherited induction of AR renders transient tobramycin CS in the analyzed antibiotic-resistant mutants and clinical isolates, including tobramycin-resistant isolates. Further, by combining tobramycin with dequalinium chloride we drive these strains to extinction. Our results support that transient CS could allow the design of new evolutionary strategies to tackle antibiotic-resistant infections, avoiding the acquisition of AR mutations on which inherited CS depends.

Collateral sensitivity between tetracyclines and aminoglycosides constrains resistance evolution in carbapenem-resistant Klebsiella pneumoniae

AIMS

The acquisition of resistance to one antibiotic may confer an increased sensitivity to another antibiotic in bacteria, which is an evolutionary trade-off between different resistance mechanisms, defined as collateral sensitivity (CS). Exploiting the role of CS in treatment design could be an effective method to suppress or even reverse resistance evolution.

METHODS

Using experimental evolution, we systematically studied the CS between aminoglycosides and tetracyclines in carbapenem-resistant Klebsiella pneumoniae (CRKP) and explored the underlying mechanisms through genomic and transcriptome analyses. The application of CS-based therapies for resistance suppression, including combination therapy and alternating antibiotic therapy, was further evaluated in vitro and in vivo.

RESULTS

Reciprocal CS existed between tetracyclines and aminoglycosides in CRKP. The increased sensitivity of aminoglycoside-resistant strains to tetracyclines was associated with the alteration of bacterial membrane potential, whereas the unbalanced oxidation-reduction process of tetracycline-resistant strains may lead to an increased bacterial sensitivity to aminoglycosides. CS-based combination therapy could efficiently constrain the evolution of CRKP resistance in vitro and in vivo. In addition, alternating antibiotic therapy can re-sensitize CRKP to previously resistant drugs, thereby maintaining the trade-off.

CONCLUSIONS

These results provide new insights into constraining the evolution of CRKP resistance through CS-based therapies.

Rapid Phenotypic Convergence towards Collateral Sensitivity in Clinical Isolates of Pseudomonas aeruginosa Presenting Different Genomic Backgrounds

Collateral sensitivity (CS) is an evolutionary trade-off by which acquisition of resistance to an antibiotic leads to increased susceptibility to another. This Achilles' heel of antibiotic resistance could be exploited to design evolution-based strategies for treating bacterial infections. To date, most studies in the field have focused on the identification of CS patterns in model strains. However, one of the main requirements for the clinical application of this trade-off is that it must be robust and has to emerge in different genomic backgrounds, including preexisting drug-resistant isolates, since infections are frequently caused by pathogens already resistant to antibiotics. Here, we report the first analysis of CS robustness in clinical strains of Pseudomonas aeruginosa presenting different ab initio mutational resistomes. We identified a robust CS pattern associated with short-term evolution in the presence of ciprofloxacin of clinical P. aeruginosa isolates, including representatives of high-risk epidemic clones belonging to sequence type (ST) 111, ST175, and ST244. We observed the acquisition of different ciprofloxacin resistance mutations in strains presenting varied STs and different preexisting mutational resistomes. Importantly, despite these genetic differences, the use of ciprofloxacin led to a robust CS to aztreonam and tobramycin. In addition, we describe the possible application of this evolutionary trade-off to drive P. aeruginosa infections to extinction by using the combination of ciprofloxacin-tobramycin or ciprofloxacin-aztreonam. Our results support the notion that the identification of robust patterns of CS may establish the basis for developing evolution-informed treatment strategies to tackle bacterial infections, including those due to antibiotic-resistant pathogens. IMPORTANCE Collateral sensitivity (CS) is a trade-off of antibiotic resistance evolution that could be exploited to design strategies for treating bacterial infections. Clinical application of CS requires it to robustly emerge in different genomic backgrounds. In this study, we performed an analysis to identify robust patterns of CS associated with the use of ciprofloxacin in clinical isolates of P. aeruginosa presenting different mutational resistomes and including high-risk epidemic clones (ST111, ST175, and ST244). We demonstrate the robustness of CS to tobramycin and aztreonam and the potential application of this evolutionary observation to drive P. aeruginosa infections to extinction. Our results support the notion that the identification of robust CS patterns may establish the basis for developing evolutionary strategies to tackle bacterial infections, including those due to antibiotic-resistant pathogens.

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.

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.

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.

Variability in Adaptive Resistance of Salmonella Typhimurium to Sublethal Levels of Antibiotics

This study was designed to evaluate the adaptive resistance of Salmonella Typhimurium under continuous sublethal selective pressure. Salmonella Typhimurium ATCC 19585 (STATCC) and S. Typhimurium CCARM 8009 (STCCARM) were sequentially cultured for 3 days at 37 °C in trypticase soy broth containing 1/2 × MICs of cefotaxime (CEF1/2), chloramphenicol (CHL1/2), gentamicin (GEN1/2), and polymyxin B (POL1/2). The STATCC and STCCARM exposed to CEF1/2, CHL1/2, GEN1/2, and POL1/2 were evaluated using antibiotic susceptibility, cross-resistance, and relative fitness. The susceptibilities of STATCC exposed to GEN1/2 and POL1/2 were increased by a 2-fold (gentamicin) and 8-fold (polymyxin B) increase in minimum inhibitory concentration (MIC) values, respectively. The MIC values of STCCARM exposed to CEF1/2, CHL1/2, GEN1/2, and POL1/2 were increased by 4-fold (cefotaxime), 2-fold (chloramphenicol), 2-fold (gentamicin), and 8-fold (polymyxin B). The highest heterogeneous fractions were observed for the STATCC exposed to CEF1/2 (38%) and POL1/2 (82%). The STCCARM exposed to GEN1/2 was cross-resistant to cefotaxime (p < 0.05), chloramphenicol (p < 0.01), and polymyxin B (p < 0.05). The highest relative fitness levels were 0.92 and 0.96, respectively, in STATCC exposed to CEF1/2 and STCCARM exposed to POL1/2. This study provides new insight into the fate of persistent cells and also guidance for antibiotic use.

Mutational basis of Meropenem resistance in Pseudomonas aeruginosa

The carbapenem-resistant strains of Pseudomonas aeruginosa are considered as the dangerous pathogens of critical priority. Deciphering the mechanisms underlying the development of carbopenem resistance is an urgent challenge faced by modern medical science. The study was aimed to describe the diversity and fixation of mutations associated with the development of carbapenem resistance during the P. aeruginosa adaptation to the increasing meropenem concentrations. The objects of the study were P. aeruginosa isolates obtained by growing the ATCC 27853 P. aeruginosa reference strain exposed to increasing concentrations of meropenem. The isolates were tested for meropenem susceptibility using E-tests (Epsilometer tests) and by the agar dilution method. Genomes of the isolates were sequenced in the MGISEQ-2000 whole-genome sequencer. The findings show that in experimental settings P. aeruginosa develops high meropenem resistance very quickly (in 6 days). Evolution of resistance is associated with cloning involving the emergence of multiple clones with various genotypes. Mutagenesis that involves 11 genes, including oprD, pbuE, nalD, nalC, spoT, mlaA, mexD, mexR, oprM, mraY, pbp3, provides the basis for cloning. Regardless of the levels of their meropenem resistance, some of the emerging clones do not progressively develop and are replaced by more successful clones.

Antimicrobial peptides: Sustainable application informed by evolutionary constraints

The proliferation and global expansion of multidrug-resistant (MDR) bacteria have deepened the need to develop novel antimicrobials. Antimicrobial peptides (AMPs) are regarded as promising antibacterial agents because of their broad-spectrum antibacterial activity and multifaceted mechanisms of action with non-specific targets. However, if AMPs are to be applied sustainably, knowledge of how they induce resistance in pathogenic bacteria must be mastered to avoid repeating the traditional antibiotic resistance mistakes currently faced. Furthermore, the evolutionary constraints on the acquisition of AMP resistance by microorganisms in the natural environment, such as functional compatibility and fitness trade-offs, inform the translational application of AMPs. Consequently, the shortcut to achieve sustainable utilization of AMPs is to uncover the evolutionary constraints of bacteria on AMP resistance in nature and find the tricks to exploit these constraints, such as applying AMP cocktails to minimize the efficacy of selection for resistance or combining nanomaterials to maximize the costs of AMP resistance. Altogether, this review dissects the benefits, challenges, and opportunities of utilizing AMPs against disease-causing bacteria, and highlights the use of AMP cocktails or nanomaterials to proactively address potential AMP resistance crises in the future.

Drug Combinations to Prevent Antimicrobial Resistance: Various Correlations and Laws, and Their Verifications, Thus Proposing Some Principles and a Preliminary Scheme

Antimicrobial resistance (AMR) has been a serious threat to human health, and combination therapy is proved to be an economic and effective strategy for fighting the resistance. However, the abuse of drug combinations conversely accelerates the spread of AMR. In our previous work, we concluded that the mutant selection indexes (SIs) of one agent against a specific bacterial strain are closely related to the proportions of two agents in a drug combination. To discover probable correlations, predictors and laws for further proposing feasible principles and schemes guiding the AMR-preventing practice, here, three aspects were further explored. First, the power function (y = axb, a > 0) correlation between the SI (y) of one agent and the ratio (x) of two agents in a drug combination was further established based on the mathematical and statistical analyses for those experimental data, and two rules a1 × MIC1 = a2 × MIC2 and b1 + b2 = −1 were discovered from both equations of y = a1xb1 and y = a2xb2 respectively for two agents in drug combinations. Simultaneously, it was found that one agent with larger MPC alone for drug combinations showed greater potency for narrowing itself MSW and preventing the resistance. Second, a new concept, mutation-preventing selection index (MPSI) was proposed and used for evaluating the mutation-preventing potency difference of two agents in drug combination; a positive correlation between the MPSI and the mutant prevention concentration (MPC) or minimal inhibitory concentration (MIC) was subsequently established. Inspired by this, the significantly positive correlation, contrary to previous reports, between the MIC and the corresponding MPC of antimicrobial agents against pathogenic bacteria was established using 181 data pairs reported. These results together for the above three aspects indicate that the MPCs in alone and combination are very important indexes for drug combinations to predict the mutation-preventing effects and the trajectories of collateral sensitivity, and while the MPC of an agent can be roughly calculated from its corresponding MIC. Subsequently, the former conclusion was further verified and improved via antibiotic exposure to 43 groups designed as different drug concentrations and various proportions. The results further proposed that the C/MPC for the agent with larger proportion in drug combinations can be considered as a predictor and is the key to judge whether the resistance and the collateral sensitivity occur to two agents. Based on these above correlations, laws, and their verification experiments, some principles were proposed, and a diagram of the mutation-preventing effects and the resistant trajectories for drug combinations with different concentrations and ratios of two agents was presented. Simultaneously, the reciprocal of MPC alone (1/MPC), proposed as the stress factors of two agents in drug combinations, together with their SI in combination, is the key to predict the mutation-preventing potency and control the trajectories of collateral sensitivity. Finally, a preliminary scheme for antimicrobial combinations preventing AMR was further proposed for subsequent improvement research and clinic popularization, based on the above analyses and discussion. Moreover, some similar conclusions were speculated for triple or multiple drug combinations.

Evolutionary history and strength of selection determine the rate of antibiotic resistance adaptation

Bacterial adaptation to stressful environments often produces evolutionary constraints whereby increases in resistance are associated with reduced fitness in a different environment. The exploitation of this resistance-cost trade-off has been proposed as the basis of rational antimicrobial treatment strategies designed to limit the evolution of drug resistance in bacterial pathogens. Recent theoretical, laboratory, and clinical studies have shown that fluctuating selection can maintain drug efficacy and even restore drug susceptibility, but can also increase the rate of adaptation and promote cross-resistance to other antibiotics. In this paper, we combine mathematical modeling, experimental evolution, and whole-genome sequencing to follow evolutionary trajectories towards β-lactam resistance under fluctuating selective conditions. Our experimental model system consists of eight populations of Escherichia coli K12 evolving in parallel to a serial dilution protocol designed to dynamically control the strength of selection for resistance. We implemented adaptive ramps with mild and strong selection, resulting in evolved populations with similar levels of resistance, but with different evolutionary dynamics and diverging genotypic profiles. We found that mutations that emerged under strong selection are unstable in the absence of selection, in contrast to resistance mutations previously selected in the mild selection regime that were stably maintained in drug-free environments and positively selected for when antibiotics were reintroduced. Altogether, our population dynamics model and the phenotypic and genomic analysis of the evolved populations show that the rate of resistance adaptation is contingent upon the strength of selection, but also on evolutionary constraints imposed by prior drug exposures.

Phage resistance-mediated trade-offs with antibiotic resistance in Salmonella Typhimurium

This study was designed to evaluate the trade-offs between phage resistance and antibiotic resistance of Salmonella Typhimurium (ST^KCCM) exposed to bacteriophage PBST10 and antibiotics (ampicillin and ciprofloxacin). ST^KCCM was serially exposed to control (no PBST10/antibiotic added), phage alone, ampicillin alone, ampicillin with phage, ciprofloxacin alone, and ciprofloxacin with phage for 8 days at 37 °C. The treated cells were used to evaluate the antibiotic susceptibility, β-lactamase activity, relative fitness, gene expression, and phage-resistance frequency. The antibiotic susceptibility of ST^KCCM to ampicillin was increased in the presence of phages. The β-lactamase activity was significantly increased in the phage alone and ampicillin with phage. The combination treatments of phages and antibiotics resulted in a greater fitness cost. The efflux pump-associated tolC was suppressed in ST^KCCM exposed to phage alone. The highest phage-resistance frequencies were observed at phage alone, followed by ampicillin with phage and ciprofloxacin with phage. The tolC-suppressed cells showed the enhanced antibiotic susceptibility. This study provides useful information for designing effective phage-antibiotic combination treatments. The evolutionary trade-offs of phage-resistant bacteria with antibiotic resistance might be good targets for controlling antibiotic-resistant bacteria.

Influence of Lonicera japonica and Radix Puerariae Crude Extracts on the Fecal Microbiome and Nutrient Apparent Digestibility of Finishing Pigs

This study aims to investigate the influence of adding Lonicera japonica (L. japonica) and Radix Puerariae crude extracts and their mixture to the diet of finishing pigs on their fecal microbes and nutrient apparent digestibility. A total of 72 healthy Duroc × Landrace × Yorkshire crossbred barrows without significant differences in body weight (93 ± 2 kg) were selected and randomly divided into four groups (18 in each group). Three replicate pens per group (six pigs per pen) were used, and two pigs were evaluated for each pen. The groups were fed the following diets: control group (CON), basic diet; chlorogenic acid group (CGA group), basic diet + 1 kg/ton L. japonica crude extract; Pueraria flavonoid group (PF group), basic diet + 1 kg/ton Radix Puerariae crude extract; and mix group (Mix group), basic diet + 0.5 kg/ton L. japonica crude extract + 0.5 kg/ton Radix Puerariae crude extract. The following results were obtained: (1) At the phylum level, Bacteroidetes, Firmicutes, Spirochaetes, Proteobacteria, Fibrobaeteres, and Kiritimatiellaeota were the main components of the fecal microbiota (top 5); the relative abundance of bacteria from phyla Firmicutes significantly increased in the Mix group than in the CON group (p < 0.05). At the genus level, Treponema_2, Rikenellaceae_RC9_gut_group, uncultured_bacterium_f_Lachnospiraceae, uncultured_bacterium_f_Prevotellaceae, and Prevotellaceae_NK3B31_group were the main components of the fecal microbiota (top 5); the relative abundance of bacteria from genus Lactobacillus significantly increased in the Mix group than in the CON group (p < 0.05). Chao1 and Ace counts were significantly higher in group CGA than in the CON group and group Mix (p < 0.05). The alpha and beta diversities and the relative abundance of fecal microbes were higher in all test groups than in the CON group. (2) The protein digestibility was significantly higher in the CGA and PF groups than in the CON group, and the TP digestibility was significantly higher in the CGA than in the CON and Mix groups (p < 0.05). In conclusion, Lonicera japonica and Radix Puerariae crude extract supplementation in the diet significantly changed fecal microbiota and improved the protein and TP digestibility of finishing pigs.

Assessment of listing and categorisation of animal diseases within the framework of the Animal Health Law (Regulation (EU) No 2016/429): antimicrobial-resistant Pseudomonas aeruginosa in dogs and cats

Pseudomonas aeruginosa (P. aeruginosa) was identified among the most relevant antimicrobial‐resistant (AMR) bacteria in the EU for dogs and cats in a previous scientific opinion. Thus, it has been assessed according to the criteria of the Animal Health Law (AHL), in particular criteria of Article 7 on disease profile and impacts, Article 5 on its eligibility to be listed, Annex IV for its categorisation according to disease prevention and control rules as in Article 9, and Article 8 for listing animal species related to the bacterium. The assessment has been performed following a methodology previously published. The outcome is the median of the probability ranges provided by the experts, which indicates whether each criterion is fulfilled (lower bound ≥ 66%) or not (upper bound ≤ 33%), or whether there is uncertainty about fulfilment. Reasoning points are reported for criteria with uncertain outcome. According to the assessment here performed, it is uncertain whether AMR P. aeruginosa can be considered eligible to be listed for Union intervention according to Article 5 of the AHL (33–90% probability). According to the criteria in Annex IV, for the purpose of categorisation related to the level of prevention and control as in Article 9 of the AHL, the AHAW Panel concluded that the bacterium does not meet the criteria in Sections 1, 2, 3 and 4 (Categories A, B, C and D; 0–5%, 1–5%, 5–33% and 5–33% probability of meeting the criteria, respectively) and the AHAW Panel was uncertain whether it meets the criteria in Section 5 (Category E, 33–90% probability of meeting the criteria). The animal species to be listed for AMR P. aeruginosa according to Article 8 criteria are mainly dogs and cats.

Allele-specific collateral and fitness effects determine the dynamics of fluoroquinolone resistance evolution

A promising strategy to overcome the evolution of antibiotic-resistant bacteria is to use collateral sensitivity-informed antibiotic treatments that rely on cycling or mixing of antibiotics, such that that resistance toward one antibiotic confers increased sensitivity to the other. Here, focusing on multistep fluoroquinolone resistance in Streptococcus pneumoniae, we show that antibiotic resistance induces diverse collateral responses whose magnitude and direction are determined by allelic identity. Using mathematical simulations, we show that these effects can be exploited via combination treatment regimens to suppress the de novo emergence of resistance during treatment.

Collateral sensitivity (CS), which arises when resistance to one antibiotic increases sensitivity toward other antibiotics, offers treatment opportunities to constrain or reverse the evolution of antibiotic resistance. The applicability of CS-informed treatments remains uncertain, in part because we lack an understanding of the generality of CS effects for different resistance mutations, singly or in combination. Here, we address this issue in the gram-positive pathogen Streptococcus pneumoniae by measuring collateral and fitness effects of clinically relevant gyrA and parC alleles and their combinations that confer resistance to fluoroquinolones. We integrated these results in a mathematical model that allowed us to evaluate how different in silico combination treatments impact the dynamics of resistance evolution. We identified common and conserved CS effects of different gyrA and parC alleles; however, the spectrum of collateral effects was unique for each allele or allelic pair. This indicated that allelic identity can impact the evolutionary dynamics of resistance evolution during monotreatment and combination treatment. Our model simulations, which included the experimentally derived antibiotic susceptibilities and fitness effects, and antibiotic-specific pharmacodynamics revealed that both collateral and fitness effects impact the population dynamics of resistance evolution. Overall, we provide evidence that allelic identity and interactions can have a pronounced impact on collateral effects to different antibiotics and suggest that these need to be considered in models examining CS-based therapies.

Acquisition of Daptomycin Resistance by Enterococcus faecium Confers Collateral Sensitivity to Glycopeptides

Daptomycin is a last-line antibiotic used in the treatment of multidrug-resistant Enterococcus faecium infections. Alarmingly, daptomycin-resistant E. faecium isolates have emerged. In this study, we investigated the evolution and mechanisms of daptomycin resistance in clinical E. faecium isolates and the corresponding acquisition of collateral sensitivity (CS) as an evolutionary trade-off. We evolved daptomycin resistance in six daptomycin-susceptible E. faecium isolates to obtain daptomycin-resistant mutants. The six E. faecium strains successfully acquired high-level resistance to daptomycin in vitro, but this led to fitness costs in terms of growth, in vitro competition, and virulence. Mutations in liaFSR, yycFG, and cls; increased surface positive charge; thicker cell walls; and elevated expression of dltABCD and tagGH were observed in daptomycin-resistant mutants. Surprisingly, we observed the emergence of CS in SC1762 isolates after the induction of daptomycin resistance. Compared with parental strains, the SC1174-D strain (i.e., daptomycin-resistant mutant of SC1174; non-CS) showed significantly upregulated expression of the vanA gene cluster. However, in SC1762-D (i.e., daptomycin-resistant mutant of SC1762), all vanA cluster genes except the vanX gene were obviously downregulated. Further in silico analyses revealed that an IS1216E-based composite transposon was generated in SC1762-D, and it disrupted the vanH gene, likely affecting the structure and expression of the vanA gene cluster and resulting in resensitization to glycopeptides. Overall, this study reports a novel form of CS between daptomycin and glycopeptides in E. faecium. Further, it provides a valuable foundation for developing effective regimens and sequential combinations of daptomycin and glycopeptides against E. faecium.

The predictive potential of different molecular markers linked to amikacin susceptibility phenotypes in Pseudomonas aeruginosa

Informed antibiotic prescription offers a practical solution to antibiotic resistance problem. With the increasing affordability of different sequencing technologies, molecular-based resistance prediction would direct proper antibiotic selection and preserve available agents. Amikacin is a broad-spectrum aminoglycoside exhibiting higher clinical efficacy and less resistance rates in Ps. aeruginosa due to its structural nature and its ability to achieve higher serum concentrations at lower therapeutic doses. This study examines the predictive potential of molecular markers underlying amikacin susceptibility phenotypes in order to provide improved diagnostic panels. Using a predictive model, genes and variants underlying amikacin resistance have been statistically and functionally explored in a large comprehensive and diverse set of Ps. aeruginosa completely sequenced genomes. Different genes and variants have been examined for their predictive potential and functional correlation to amikacin susceptibility phenotypes. Three predictive sets of molecular markers have been identified and can be used in a complementary manner, offering promising molecular diagnostics. armR, nalC, nalD, mexR, mexZ, ampR, rmtD, nalDSer32Asn, fusA1Y552C, fusA1D588G, arnAA170T, and arnDG206C have been identified as the best amikacin resistance predictors in Ps. aeruginosa while faoAT385A, nuoGA890T, nuoGA574T, lptAT55A, lptAR62S, pstBR87C, gidBE126G, gidBQ28K, amgSE108Q, and rplYQ41L have been identified as the best amikacin susceptibility predictors. Combining different measures of predictive performance together with further functional analysis can help design new and more informative molecular diagnostic panels. This would greatly inform and direct point of care diagnosis and prescription, which would consequently preserve amikacin functionality and usefulness.

Mutational background influences P. aeruginosa ciprofloxacin resistance evolution but preserves collateral sensitivity robustness

Bacterial adaptation to the presence of an antibiotic often involves evolutionary trade-offs, such as increased susceptibility to other drugs (collateral sensitivity). Its exploitation to design improved therapeutic strategies is only feasible if collateral sensitivity is robust, reproducible, and emerges in resistant mutants; these issues are rarely addressed in available publications. We describe a robust collateral sensitivity phenotype that emerges in different antibiotic-resistance mutational backgrounds, due to different genetic events, and propose therapeutic strategies effective for treating infections caused by Pseudomonas aeruginosa antibiotic-resistant mutants. Since conserved collateral sensitivity phenotypes do not confer adaptation to the presence of antibiotics, our results are also relevant for understanding convergent evolution processes in which the force selecting the emerging phenotype remains unclear.

Collateral sensitivity is an evolutionary trade-off whereby acquisition of the adaptive phenotype of resistance to an antibiotic leads to the nonadaptive increased susceptibility to another. The feasibility of harnessing such a trade-off to design evolutionary-based approaches for treating bacterial infections has been studied using model strains. However, clinical application of collateral sensitivity requires its conservation among strains presenting different mutational backgrounds. Particularly relevant is studying collateral sensitivity robustness of already-antibiotic-resistant mutants when challenged with a new antimicrobial, a common situation in clinics that has hardly been addressed. We submitted a set of diverse Pseudomonas aeruginosa antibiotic-resistant mutants to short-term evolution in the presence of different antimicrobials. Ciprofloxacin selects different clinically relevant resistance mutations in the preexisting resistant mutants, which gave rise to the same, robust, collateral sensitivity to aztreonam and tobramycin. We then experimentally determined that alternation of ciprofloxacin with aztreonam is more efficient than ciprofloxacin–tobramycin alternation in driving the extinction of the analyzed antibiotic-resistant mutants. Also, we show that the combinations ciprofloxacin–aztreonam or ciprofloxacin–tobramycin are the most effective strategies for eliminating the tested P. aeruginosa antibiotic-resistant mutants. These findings support that the identification of conserved collateral sensitivity patterns may guide the design of evolution-based strategies to treat bacterial infections, including those due to antibiotic-resistant mutants. Besides, this is an example of phenotypic convergence in the absence of parallel evolution that, beyond the antibiotic-resistance field, could facilitate the understanding of evolution processes, where the selective forces giving rise to new, not clearly adaptive phenotypes remain unclear.

Rapid expansion and extinction of antibiotic resistance mutations during treatment of acute bacterial respiratory infections

Acute bacterial infections are often treated empirically, with the choice of antibiotic therapy updated during treatment. The effects of such rapid antibiotic switching on the evolution of antibiotic resistance in individual patients are poorly understood. Here we find that low-frequency antibiotic resistance mutations emerge, contract, and even go to extinction within days of changes in therapy. We analyzed Pseudomonas aeruginosa populations in sputum samples collected serially from 7 mechanically ventilated patients at the onset of respiratory infection. Combining short- and long-read sequencing and resistance phenotyping of 420 isolates revealed that while new infections are near-clonal, reflecting a recent colonization bottleneck, resistance mutations could emerge at low frequencies within days of therapy. We then measured the in vivo frequencies of select resistance mutations in intact sputum samples with resistance-targeted deep amplicon sequencing (RETRA-Seq), which revealed that rare resistance mutations not detected by clinically used culture-based methods can increase by nearly 40-fold over 5–12 days in response to antibiotic changes. Conversely, mutations conferring resistance to antibiotics not administered diminish and even go to extinction. Our results underscore how therapy choice shapes the dynamics of low-frequency resistance mutations at short time scales, and the findings provide a possibility for driving resistance mutations to extinction during early stages of infection by designing patient-specific antibiotic cycling strategies informed by deep genomic surveillance.

It remains unclear how rapid antibiotic switching affects the evolution of antibiotic resistance in individual patients. Here, Chung et al. combine short- and long-read sequencing and resistance phenotyping of 420 serial isolates of Pseudomonas aeruginosa collected from the onset of respiratory infection, and show that rare resistance mutations can increase by nearly 40-fold over 5–12 days in response to antibiotic changes, while mutations conferring resistance to antibiotics not administered diminish and even go to extinction.

Convergent phenotypic evolution towards fosfomycin collateral sensitivity of Pseudomonas aeruginosa antibiotic-resistant mutants

The rise of antibiotic resistance and the reduced amount of novel antibiotics support the need of developing novel strategies to fight infections, based on improving the use of the antibiotics we already have. Collateral sensitivity is an evolutionary trade-off associated with the acquisition of antibiotic resistance that can be exploited to tackle this relevant health problem. However, different works have shown that patterns of collateral sensitivity are not always conserved, thus precluding the exploitation of this evolutionary trade-off to fight infections. In this work, we identify a robust pattern of collateral sensitivity to fosfomycin in Pseudomonas aeruginosa antibiotic-resistant mutants, selected by antibiotics belonging to different structural families. We characterize the underlying mechanism of the collateral sensitivity observed, which is a reduced expression of the genes encoding the peptidoglycan-recycling pathway, which preserves the peptidoglycan synthesis in situations where its de novo synthesis is blocked, and a reduced expression of fosA, encoding a fosfomycin-inactivating enzyme. We propose that the identification of robust collateral sensitivity patterns, as well as the understanding of the molecular mechanisms behind these phenotypes, would provide valuable information to design evolution-based strategies to treat bacterial infections.

Role of Efflux Pump-Mediated Antibiotic Resistance in Quorum Sensing-Regulated Biofilm Formation by Salmonella Typhimurium

This study was designed to assess the influence of efflux pump activity on the biofilm formation in Salmonella Typhimurium. Salmonella enterica subsp. enterica serovar Typhimurium ATCC 19585 (STWT) and clinically isolated S. Typhimurium CCARM 8009 (STCI) were treated with ceftriaxone (CEF), chloramphenicol (CHL), ciprofloxacin (CIP), erythromycin (ERY), norfloxacin (NOR), and tetracycline (TET) in autoinducer-containing media in the absence and presence of phenylalanine-arginine β-naphthylamide (PAβN) to compare efflux pump activity with biofilm-forming ability. The susceptibilities of STWT and STCI were increased in the presence of PAβN. ERY+PAβN showed the highest decrease in the minimum inhibitory concentration (MIC) of ERY from 256 to 2 μg/mL against STWT and STCI. The antimicrobial activity of NOR against planktonic cells was significantly increased in the presence of PAβN, showing the lowest numbers of STWT (3.2 log CFU/cm2), and the TET+PAβN effectively inhibited the growth of STCI (5.2 log CFU/cm2). The lowest biofilm-forming abilities were observed at NOR+PAβN against STWT (biofilm-forming index, BFI < 0.41) and CEF+PAβN against STCI (BFI = 0.32). The bacteria swimming motility and relative fitness varied depending on the antibiotic and PAβN treatments. The motility diameters of STWT were significantly decreased by NOR+PAβN (6 mm) and TET+PAβN (15 mm), while the lowest motility of STCI was observed at CIP+PAβN (8 mm). The significant decrease in the relative fitness levels of STWT and STCI was observed at CIP+PAβN and NOR+PAβN. The PAβN as an efflux pump inhibitor (EPI) can improve the antimicrobial and anti-biofilm efficacy of antibiotics against S. Typhimurium. This study provides useful information for understanding the role of efflux pump activity in quorum sensing-regulated biofilm formation and also emphasizes the necessity of the discovery of novel EPIs for controlling biofilm formation by antibiotic-resistant pathogens.

Collateral Sensitivity Interactions between Antibiotics Depend on Local Abiotic Conditions

Mutations conferring resistance to one antibiotic can increase (cross-resistance) or decrease (collateral sensitivity) resistance to others. Antibiotic combinations displaying collateral sensitivity could be used in treatments that slow resistance evolution. However, lab-to-clinic translation requires understanding whether collateral effects are robust across different environmental conditions. Here, we isolated and characterized resistant mutants of Escherichia coli using five antibiotics, before measuring collateral effects on resistance to other paired antibiotics. During both isolation and phenotyping, we varied conditions in ways relevant in nature (pH, temperature, and bile). This revealed that local abiotic conditions modified expression of resistance against both the antibiotic used during isolation and other antibiotics. Consequently, local conditions influenced collateral sensitivity in two ways: by favoring different sets of mutants (with different collateral sensitivities) and by modifying expression of collateral effects for individual mutants. These results place collateral sensitivity in the context of environmental variation, with important implications for translation to real-world applications. IMPORTANCE When bacteria become resistant to an antibiotic, the genetic changes involved sometimes increase (cross-resistance) or decrease (collateral sensitivity) their resistance to other antibiotics. Antibiotic combinations showing repeatable collateral sensitivity could be used in treatment to slow resistance evolution. However, collateral sensitivity interactions may depend on the local environmental conditions that bacteria experience, potentially reducing repeatability and clinical application. Here, we show that variation in local conditions (pH, temperature, and bile salts) can influence collateral sensitivity in two ways: by favoring different sets of mutants during bacterial resistance evolution (with different collateral sensitivities to other antibiotics) and by modifying expression of collateral effects for individual mutants. This suggests that translation from the lab to the clinic of new approaches exploiting collateral sensitivity will be influenced by local abiotic conditions.

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.