Conserved collateral antibiotic susceptibility networks in diverse clinical strains of Escherichia coli

Invariant set theory for predicting potential failure of antibiotic cycling

Collateral sensitivity, where resistance to one drug confers heightened sensitivity to another, offers a promising strategy for combating antimicrobial resistance, yet predicting resultant evolutionary dynamics remains a significant challenge. We propose here a mathematical model that integrates fitness trade-offs and adaptive landscapes to predict the evolution of collateral sensitivity pathways, providing insights into optimizing sequential drug therapies. Our approach embeds collateral information into a network of switched systems, allowing us to abstract the effects of sequential antibiotic exposure on antimicrobial resistance. We analyze the system stability at disease-free equilibrium and employ set-control theory to tailor therapeutic windows. Consequently, we propose a computational algorithm to identify effective sequential therapies to counter antibiotic resistance. By leveraging our theory with data on collateral sensivity interactions, we predict scenarios that may prevent bacterial escape for chronic Pseudomonas aeruginosa infections.

Ceftazidime-avibactam use selects multidrug-resistance and prevents designing collateral sensitivity-based therapies against Pseudomonas aeruginosa

Ceftazidime-avibactam is a β-lactam/β-lactamase inhibitor combination restricted for the treatment of multidrug-resistant infections of Pseudomonas aeruginosa non-susceptible to ceftazidime and resistant to carbapenems. Crucially, it has not been studied if its use could allow the design or application of new or stablished evolution-based strategies that exploit the increased susceptibility that emerges when resistance is acquired (collateral sensitivity, CS). Works in the field have focused on the study of CS in model strains, but to be exploited it must robustly emerge in pre-existing resistant mutants that can coexist in a patient. This is the first analysis of CS robustness on this last-resort drug. We evolved 15 clinical isolates on ceftazidime-avibactam and in absence of inhibitor, and here we show that we found no robust -exploitable- pattern of CS. This, together with the selection of cross-resistance and the impossibility of using previously described CS-based strategies, supports that avibactam should be restricted for the treatment of particular genotypes.

Evolutionary trajectory of bacterial resistance to antibiotics and antimicrobial peptides in Escherichia coli

The global crisis of antimicrobial resistance poses a major threat to human health, underscoring the urgency of developing new antibacterial strategies. Antimicrobial peptides (AMPs) are promising alternatives to antibiotic therapy, yet potential microbial resistance is of great concern. Resistance is often accompanied by fitness costs, which may in turn influence the spread of drug-resistant bacteria and their susceptibility to other antimicrobial agents. Herein, we investigate the evolutionary trajectory of bacterial resistance to antibiotics and AMPs in Escherichia coli, and evaluate the fitness costs and collateral sensitivity of drug-resistant strains. We reveal that E. coli develops resistance to antibiotics, particularly ciprofloxacin and kanamycin, at a notably faster rate than to AMPs. Moreover, antibiotic-evolved strains exhibit slightly higher fitness costs than AMP-evolved bacteria, primarily manifested in reduced bacterial growth and swimming motility. Notably, we demonstrate that trimethoprim-resistant E. coli, with mutations in thyA gene, displays enhanced susceptibility to pexiganan, as evidenced by both in vitro and in vivo studies. Overall, our findings shed new insights for the clinical deployment of AMPs and propose innovative therapeutic strategies for combating antibiotic-resistant bacterial infections.IMPORTANCEThe global spread of antimicrobial resistance necessitates the development of innovative anti-infective strategies. Antimicrobial peptides (AMPs) represent promising alternatives in the post-antibiotic era. By monitoring the evolutionary trajectory of bacterial resistance to eight antibiotics and ten AMPs in Escherichia coli, we demonstrate that E. coli exhibits slower emergence of resistance against AMPs compared with antibiotics. Additionally, these antibiotic-resistant strains incur significant fitness costs, particularly in bacterial growth and motility. Most importantly, we find that some antibiotic-resistant strains show collateral sensitivity to specific AMPs in both in vitro and animal infection models, which is conducive to accelerating the development of AMP-based antibacterial treatment.

Exploring the effect of sequential antibiotic exposure in resistant Escherichia coli causing urinary tract infections: a proof of principle study

Antimicrobial resistance development, particularly in infections such as urinary tract infections (UTIs), is a global clinical concern. The objective of this study was to determine if sequential antibiotic exposure with ciprofloxacin and mecillinam can reduce the growth of resistant clinical Escherichia coli strains, thus improving the effectiveness of antibiotic therapy. Six E. coli isolates with heterogeneous resistance to ciprofloxacin and/or mecillinam obtained from patients with UTIs were exposed to one of the antibiotics (0.75 × minimum inhibitory concentration, MIC) for 1 h. This was followed by treatment with the second antibiotic at different concentrations (0.0375/0.075/0.375/0.75 × MIC). Continuous growth measurements were conducted in order to assess the impact of sequential exposure. One representative strain was selected for intact cell counting. In addition, a checkerboard assay was conducted to investigate the synergistic impact of ciprofloxacin and mecillinam, and genetic analyses were performed to identify the mechanisms of resistance for all isolates. The six E. coli strains were phylogenetically different, and none exhibited a synergistic effect for ciprofloxacin and mecillinam. Our data suggest that sequential exposure to mecillinam and ciprofloxacin appears to reduce the growth capacity of clinical E. coli isolates with phenotypic resistance to either or both agents. Sequential antibiotic exposure may be an interesting strategy to improve the antibiotic efficacy of current agents to overcome phenotypic resistance in E. coli.

IMPORTANCE

As global rates of antibiotic resistance increase and the development of new antibiotics become more difficult and costly, it is important to explore alternative strategies to improve the effectiveness of existing antibiotics. Previous studies have shown that sequential exposure of Pseudomonas aeruginosa to two antibiotics can effectively kill the bacteria and reduce the likelihood of resistance developing. However, the potential of this sequential approach for the treatment of Escherichia coli infections has not been thoroughly investigated. In our study, we conducted a proof-of-principle study to determine whether sequential exposure to mecillinam and ciprofloxacin can overcome phenotypic resistance to one or both drugs. We found that when E. coli were treated with subinhibitory doses of mecillinam followed by ciprofloxacin, their growth was significantly inhibited compared to treatment with ciprofloxacin alone, suggesting that sequential antibiotic exposure may be a viable strategy for treating infections caused by resistant E. coli.

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.

Evolutionary Novelties in Bacteria and the Missing Backdrop of the Environment

Evolutionary novelty has been one of the central themes in the field of evolutionary biology for many years. Structural and functional innovations such as scales in the reptiles, fins in the fishes and mammary glands in the mammals have been the focus of the studies. Insights obtained from these studies have shaped the criterion for the identification of novelty as well as provide the framework for studying novelty. In this article, I argue that unicellular organisms present an excellent opportunity for the investigation of evolutionary novelty. Even though bacteria share some fundamental aspects of novelty with higher organisms, there are definite departures. Here, I outline these departures in four different contexts: criterion for the identification of novelty, types of evolutionary novelties, level of biological complexity that bacteria embody and, most importantly, the role of the environment. Identifying the role of the environment allows the categorisation of novelty as probable or improbable and adaptive or latent. This categorisation of novel traits, based on the role of the environment, can facilitate the study of novelty in bacteria. Insights obtained from such studies are crucial for understanding the fundamental aspects of evolutionary novelty.

Antibiotic resistant bacteria survive treatment by doubling while shrinking

Many antibiotics that are used in healthcare, farming, and aquaculture end up in environments with different spatial structures that might promote heterogeneity in the emergence of antibiotic resistance. However, the experimental evolution of microbes at sub-inhibitory concentrations of antibiotics has been mainly carried out at the population level which does not allow capturing single-cell responses to antibiotics. Here, we investigate and compare the emergence of resistance to ciprofloxacin in Escherichia coli in well-mixed and structured environments using experimental evolution, genomics, and microfluidics-based time-lapse microscopy. We discover that resistance to ciprofloxacin and cross-resistance to other antibiotics is stronger in the well-mixed environment due to the emergence of target mutations, whereas efflux regulator mutations emerge in the structured environment. The latter mutants also harbor sub-populations of persisters that survive high concentrations of ciprofloxacin that inhibit bacterial growth at the population level. In contrast, genetically resistant bacteria that display target mutations also survive high concentrations of ciprofloxacin that inhibit their growth via population-level antibiotic tolerance. These resistant and tolerant bacteria keep doubling while shrinking in size in the presence of ciprofloxacin and regain their original size after antibiotic removal, which constitutes a newly discovered phenotypic response. This new knowledge sheds light on the diversity of strategies employed by bacteria to survive antibiotics and poses a stepping stone for understanding the link between mutations at the population level and phenotypic single-cell responses.

IMPORTANCE

The evolution of antimicrobial resistance poses a pressing challenge to global health with an estimated 5 million deaths associated with antimicrobial resistance every year globally. Here, we investigate the diversity of strategies employed by bacteria to survive antibiotics. We discovered that bacteria evolve genetic resistance to antibiotics while simultaneously displaying tolerance to very high doses of antibiotics by doubling while shrinking in size.

Insights into durability against resistance from the antibiotic nitrofurantoin

Nitrofurantoin has shown exceptional durability against resistance over 70 years of use. This longevity stems from factors such as rapid achievement of therapeutic concentrations, multiple physiological targets against bacteria, low risk of horizontal gene transfer, and the need to acquire multiple mutations to achieve resistance. These combined features limit resistance emergence and spread of nitrofurantoin resistance. We propose nitrofurantoin as an exemplar for developing other durable treatments.

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.

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.

β-lactamase expression induces collateral sensitivity in Escherichia coli

Major antibiotic groups are losing effectiveness due to the uncontrollable spread of antimicrobial resistance (AMR) genes. Among these, β-lactam resistance genes -encoding β-lactamases- stand as the most common resistance mechanism in Enterobacterales due to their frequent association with mobile genetic elements. In this context, novel approaches that counter mobile AMR are urgently needed. Collateral sensitivity (CS) occurs when the acquisition of resistance to one antibiotic increases susceptibility to another antibiotic and can be exploited to eliminate AMR selectively. However, most CS networks described so far emerge as a consequence of chromosomal mutations and cannot be leveraged to tackle mobile AMR. Here, we dissect the CS response elicited by the acquisition of a prevalent antibiotic resistance plasmid to reveal that the expression of the β-lactamase gene blaOXA-48 induces CS to colistin and azithromycin. We next show that other clinically relevant mobile β-lactamases produce similar CS responses in multiple, phylogenetically unrelated E. coli strains. Finally, by combining experiments with surveillance data comprising thousands of antibiotic susceptibility tests, we show that β-lactamase-induced CS is pervasive within Enterobacterales. These results highlight that the physiological side-effects of β-lactamases can be leveraged therapeutically, paving the way for the rational design of specific therapies to block mobile AMR or at least counteract their effects.

Climate warming promotes collateral antibiotic resistance development in cyanobacteria

Both cyanobacterial blooms and antibiotic resistance have aggravated worldwide and posed a great threat to public health in recent years. As a significant source and reservoir of water environmental resistome, cyanobacteria exhibit confusing discrepancy between their reduced susceptibility and their chronic exposure to antibiotic mixtures at sub-inhibitory concentrations. How the increasing temperature affects the adaptive evolution of cyanobacteria-associated antibiotic resistance in response to low-level antibiotic combinations under climate change remains unclear. Here we profiled the antibiotic interaction and collateral susceptibility networks among 33 commonly detected antibiotics in 600 cyanobacterial strains isolated from 50 sites across four eutrophicated lakes in China. Cyanobacteria-associated antibiotic resistance level was found positively correlated to antibiotic heterogeneity across all sites. Among 528 antibiotic combinations, antagonism was observed for 62 % interactions and highly conserved within cyanobacterial species. Collateral resistance was detected in 78.5 % of pairwise antibiotic interaction, leading to a widened or shifted upwards mutant selection window for increased opportunity of acquiring second-step mutations. We quantified the interactive promoting effect of collateral resistance and increasing temperature on the evolution of both phenotypic and genotypic cyanobacteria-associated resistance under chronic exposure to environmental level of antibiotic combinations. With temperature increasing from 16 °C to 36 °C, the evolvability index and genotypic resistance level increased by 1.25 - 2.5 folds and 3 - 295 folds in the collateral-resistance-informed lineages, respectively. Emergence of resistance mutation pioneered by tolerance, which was jointly driven by mutation rate and persister fraction, was found to be accelerated by increased temperature and antibiotic switching rate. Our findings provided mechanic insights into the boosting effect of climate warming on the emergence and development of cyanobacteria-associated resistance against collateral antibiotic phenotypes.

Phage-inspired strategies to combat antibacterial resistance

Antimicrobial resistance (AMR) in clinically priority pathogensis now a major threat to public health worldwide. Phages are bacterial parasites that efficiently infect or kill specific strains and represent the most abundant biological entities on earth, showing great attraction as potential antibacterial therapeutics in combating AMR. This review provides a summary of phage-inspired strategies to combat AMR. We firstly cover the phage diversity, and then explain the biological principles of phage therapy that support the use of phages in the post-antimicrobial era. Furthermore, we state the versatility methods of phage therapy both from direct access as well as collateral access. Among the direct access approaches, we discuss the use of phage cocktail therapy, phage-encoded endolysins and the bioengineering for function improvement of used phages or endolysins. On the other hand, we introduce the collateral access, including the phages antimicrobial immunity combined therapy and phage-based novel antibacterial mimic molecules. Nowadays, more and more talented and enthusiastic scientist, doctors, pharmacists, media, authorities, and industry are promoting the progress of phage therapy, and proposed more phages-inspired strategy to make them more tractable to combat AMR and benefit more people, more animal and diverse environment in "one health" framework.

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.

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.

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.

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.

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.

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

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

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.

Environmental complexity is more important than mutation in driving the evolution of latent novel traits in E. coli

Recent experiments show that adaptive Darwinian evolution in one environment can lead to the emergence of multiple new traits that provide no immediate benefit in this environment. Such latent non-adaptive traits, however, can become adaptive in future environments. We do not know whether mutation or environment-driven selection is more important for the emergence of such traits. To find out, we evolve multiple wild-type and mutator E. coli populations under two mutation rates in simple (single antibiotic) environments and in complex (multi-antibiotic) environments. We then assay the viability of evolved populations in dozens of new environments and show that all populations become viable in multiple new environments different from those they had evolved in. The number of these new environments increases with environmental complexity but not with the mutation rate. Genome sequencing demonstrates the reason: Different environments affect pleiotropic mutations differently. Our experiments show that the selection pressure provided by an environment can be more important for the evolution of novel traits than the mutational supply experienced by a wild-type and a mutator strain of E. coli.

Novel traits without immediate fitness benefit evolve frequently but we don’t know whether mutation or environment-driven selection drives this evolution. Here, using experimental evolution of E. coli populations, the authors demonstrate the importance of selection in the evolution of latent novel traits.

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 Instability of Collateral Susceptibility Networks in Ciprofloxacin-Resistant Clinical Escherichia coli Strains

Collateral sensitivity and resistance occur when resistance development toward one antimicrobial either potentiates or deteriorates the effect of others. Previous reports on collateral effects on susceptibility focus on newly acquired resistance determinants and propose that novel treatment guidelines informed by collateral networks may reduce the evolution, selection, and spread of antimicrobial resistance. In this study, we investigate the evolutionary stability of collateral networks in five ciprofloxacin-resistant, clinical Escherichia coli strains. After 300 generations of experimental evolution without antimicrobials, we show complete fitness restoration in four of five genetic backgrounds and demonstrate evolutionary instability in collateral networks of newly acquired resistance determinants. We show that compensatory mutations reducing efflux expression are the main drivers destabilizing initial collateral networks and identify rpoS as a putative target for compensatory evolution. Our results add another layer of complexity to future predictions and clinical application of collateral networks.

The EnvZ/OmpR Two-Component System Regulates the Antimicrobial Activity of TAT-RasGAP317-326 and the Collateral Sensitivity to Other Antibacterial Agents

The rapid emergence of antibiotic-resistant bacteria poses a serious threat to public health worldwide. Antimicrobial peptides (AMPs) are promising antibiotic alternatives; however, little is known about bacterial mechanisms of AMP resistance and the interplay between AMP resistance and the bacterial response to other antimicrobials. In this study, we identified Escherichia coli mutants resistant to the TAT-RasGAP_317-326 antimicrobial peptide and found that resistant bacteria show collateral sensitivity to other AMPs and antibacterial agents. We determined that resistance to TAT-RasGAP_317-326 peptide arises through mutations in the histidine kinase EnvZ, a member of the EnvZ/OmpR two-component system responsible for osmoregulation in E. coli. In particular, we found that TAT-RasGAP_317-326 binding and entry is compromised in E. coli peptide-resistant mutants. We showed that peptide resistance is associated with transcriptional regulation of a number of pathways and EnvZ-mediated resistance is dependent on the OmpR response regulator but is independent of the OmpC and OmpF outer membrane porins. Our findings provide insight into the bacterial mechanisms of TAT-RasGAP_317-326 resistance and demonstrate that resistance to this AMP is associated with collateral sensitivity to other antibacterial agents. IMPORTANCE Antimicrobial peptides (AMP) are promising alternatives to classical antibiotics in the fight against antibiotic resistance. Resistance toward antimicrobial peptides can occur, but little is known about the mechanisms driving this phenomenon. Moreover, there is limited knowledge on how AMP resistance relates to the bacterial response to other antimicrobial agents. Here, we address these questions in the context of the antimicrobial peptide TAT-RasGAP_317-326. We show that resistant Escherichia coli strains can be selected and do not show resistance to other antimicrobial agents. Resistance is caused by a mutation in a regulatory pathway, which lowers binding and entry of the peptide in E. coli. Our results highlight a mechanism of resistance that is specific to TAT-RasGAP_317-326. Further research is required to characterize these mechanisms and to evaluate the potential of antimicrobial combinations to curb the development of antimicrobial resistance.

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.

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.

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.

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.

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.

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

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

The chemotherapeutic drug methotrexate selects for antibiotic resistance

BACKGROUND

Understanding drivers of antibiotic resistance evolution is fundamental for designing optimal treatment strategies and interventions to reduce the spread of antibiotic resistance. Various cytotoxic drugs used in cancer chemotherapy have antibacterial properties, but how bacterial populations are affected by these selective pressures is unknown. Here we test the hypothesis that the widely used cytotoxic drug methotrexate affects the evolution and selection of antibiotic resistance.

METHODS

First, we determined methotrexate susceptibility (IC90) and selective abilities in a collection of Escherichia coli and Klebsiella pneumoniae strains with and without pre-existing trimethoprim resistance determinants. We constructed fluorescently labelled pairs of E. coli MG1655 differing only in trimethoprim resistance determinants and determined the minimum selective concentrations of methotrexate using flow-cytometry. We further used an experimental evolution approach to investigate the effects of methotrexate on de novo trimethoprim resistance evolution.

FINDINGS

We show that methotrexate can select for acquired trimethoprim resistance determinants located on the chromosome or a plasmid. Additionally, methotrexate co-selects for genetically linked resistance determinants when present together with trimethoprim resistance on a multi-drug resistance plasmid. These selective effects occur at concentrations 40- to >320-fold below the methotrexate minimal inhibitory concentration.

INTERPRETATION

Our results strongly suggest a selective role of methotrexate for virtually any antibiotic resistance determinant when present together with trimethoprim resistance on a multi-drug resistance plasmid. The presented results may have significant implications for patient groups strongly depending on effective antibiotic treatment.

FUNDING

PJJ was supported by UiT The Arctic University of Norway and the Northern Norway Regional Health Authority (SFP1292-16/HNF1586-21) and JPI-EC-AMR (Project 271,176/H10). DIA was supported by the Swedish Research Council (grant 2017-01,527). The publication charges for this article have been funded by a grant from the publication fund of UiT The Arctic University of Norway.

Identification of antibiotic collateral sensitivity and resistance interactions in population surveillance data

BACKGROUND

Collateral effects of antibiotic resistance occur when resistance to one antibiotic agent leads to increased resistance or increased sensitivity to a second agent, known respectively as collateral resistance (CR) and collateral sensitivity (CS). Collateral effects are relevant to limit impact of antibiotic resistance in design of antibiotic treatments. However, methods to detect antibiotic collateral effects in clinical population surveillance data of antibiotic resistance are lacking.

OBJECTIVES

To develop a methodology to quantify collateral effect directionality and effect size from large-scale antimicrobial resistance population surveillance data.

METHODS

We propose a methodology to quantify and test collateral effects in clinical surveillance data based on a conditional t-test. Our methodology was evaluated using MIC data for 419 Escherichia coli strains, containing MIC data for 20 antibiotics, which were obtained from the Pathosystems Resource Integration Center (PATRIC) database.

RESULTS

We demonstrate that the proposed approach identifies several antibiotic combinations that show symmetrical or non-symmetrical CR and CS. For several of these combinations, collateral effects were previously confirmed in experimental studies. We furthermore provide insight into the power of our method for multiple collateral effect sizes and MIC distributions.

CONCLUSIONS

Our proposed approach is of relevance as a tool for analysis of large-scale population surveillance studies to provide broad systematic identification of collateral effects related to antibiotic resistance, and is made available to the community as an R package. This method can help mapping CS and CR, which could guide combination therapy and prescribing in the future.

Allogenous Selection of Mutational Collateral Resistance: Old Drugs Select for New Resistance Within Antibiotic Families

Allogeneous selection occurs when an antibiotic selects for resistance to more advanced members of the same family. The mechanisms of allogenous selection are (a) collateral expansion, when the antibiotic expands the gene and gene-containing bacterial populations favoring the emergence of other mutations, inactivating the more advanced antibiotics; (b) collateral selection, when the old antibiotic selects its own resistance but also resistance to more modern drugs; (c) collateral hyper-resistance, when resistance to the old antibiotic selects in higher degree for populations resistant to other antibiotics of the family than to itself; and (d) collateral evolution, when the simultaneous or sequential use of antibiotics of the same family selects for new mutational combinations with novel phenotypes in this family, generally with higher activity (higher inactivation of the antibiotic substrates) or broader spectrum (more antibiotics of the family are inactivated). Note that in some cases, collateral selection derives from collateral evolution. In this article, examples of allogenous selection are provided for the major families of antibiotics. Improvements in minimal inhibitory concentrations with the newest drugs do not necessarily exclude “old” antibiotics of the same family of retaining some selective power for resistance to the newest agents. If this were true, the use of older members of the same drug family would facilitate the emergence of mutational resistance to the younger drugs of the family, which is frequently based on previously established resistance traits. The extensive use of old drugs (particularly in low-income countries and in farming) might be significant for the emergence and selection of resistance to the novel members of the family, becoming a growing source of variation and selection of resistance to the whole family. In terms of future research, it could be advisable to focus antimicrobial drug discovery more on the identification of new targets and new (unique) classes of antimicrobial agents, than on the perpetual chemical exploitation of classic existing ones.

Identification of antibiotic pairs that evade concurrent resistance via a retrospective analysis of antimicrobial susceptibility test results

Background

Some antibiotic pairs display a property known as collateral sensitivity in which the evolution of resistance to one antibiotic increases sensitivity to the other. Alternating between collaterally sensitive antibiotics has been proposed as a sustainable solution to the problem of antibiotic resistance. We aimed to identify antibiotic pairs that could be considered for treatment strategies based on alternating antibiotics.

Methods

We did a retrospective analysis of 448 563 antimicrobial susceptibility test results acquired over a 4-year period (Jan 1, 2015, to Dec 31, 2018) from 23 hospitals in the University of Pittsburgh Medical Center (Pittsburgh, PA, USA) hospital system. We used a score based on mutual information to identify pairs of antibiotics displaying disjoint resistance, wherein resistance to one antibiotic is commonly associated with susceptibility to the other and vice versa. We applied this approach to the six most frequently isolated bacterial pathogens (Escherichia coli, Staphylococcus aureus, Klebsiella pneumoniae, Enterococcus faecalis, Pseudomonas aeruginosa, and Proteus mirabilis) and subpopulations of each created by conditioning on resistance to individual antibiotics. To identify higher-order antibiotic interactions, we predicted rates of multidrug resistance for triplets of antibiotics using Markov random fields and compared these to the observed rates.

Findings

We identified 69 antibiotic pairs displaying varying degrees of disjoint resistance for subpopulations of the six bacterial species. However, disjoint resistance was rarely conserved at the species level, with only 6 (0·7%) of 875 antibiotic pairs showing evidence of disjoint resistance. Instead, more than half of antibiotic pairs (465 [53·1%] of 875) exhibited signatures of concurrent resistance, whereby resistance to one antibiotic is associated with resistance to another. We found concurrent resistance to extend to more than two antibiotics, with observed rates of resistance to three antibiotics being higher than predicted from pairwise information alone.

Interpretation

The high frequency of concurrent resistance shows that bacteria have means of counteracting multiple antibiotics at a time. The almost complete absence of disjoint resistance at the species level implies that treatment strategies based on alternating between antibiotics might require subspecies level pathogen identification and be limited to a few antibiotic pairings.

Funding

US National Institutes of Health.

Indications for medical antibiotic prophylaxis and potential targets for antimicrobial stewardship intervention: a narrative review

BACKGROUND

Most of the antimicrobial stewardship (AMS) literature has focused on antimicrobial consumption for the treatment of infections, for the prophylaxis of surgical site infection and for the prevention of endocarditis. The role of AMS for medical antibiotic prophylaxis (AP) has not been adequately addressed.

AIMS

To identify targets for AMS interventions for medical AP in adult patients.

SOURCES

Targeted searches were conducted in PubMed.

CONTENT

The various indications for medical AP and relevant evidence from practice guidelines are outlined. The following were identified as potential targets for AMS interventions: (a) addressing under-utilization of antibiotic-sparing strategies (e.g. for recurrent urinary tract infections, recurrent soft-tissue infections, recurrent exacerbations associated with bronchiectasis or chronic obstructive pulmonary disease), (b) reducing unnecessary AP beyond recommended indications (e.g. for acute pancreatitis, bite wounds, or urinary catheter manipulations), (c) reducing the use of AP with a broader spectrum than necessary, (d) reducing the use of AP for longer than the recommended duration (e.g. AP for prevention of osteomyelitis in open fractures or AP in high-risk neutropenia), (e) evaluating the role of antibiotic cycling to prevent the emergence of resistance during prolonged AP (e.g. in recurrent urinary tract infections or prophylaxis for spontaneous bacterial peritonitis), and (f) addressing research gaps regarding appropriate indications or antibiotic regimens for medical prophylaxis.

IMPLICATIONS

This review summarizes current trends in AP and proposes targets for AMS interventions.

Design principles of collateral sensitivity-based dosing strategies

Collateral sensitivity (CS)-based antibiotic treatments, where increased resistance to one antibiotic leads to increased sensitivity to a second antibiotic, may have the potential to limit the emergence of antimicrobial resistance. However, it remains unclear how to best design CS-based treatment schedules. To address this problem, we use mathematical modelling to study the effects of pathogen- and drug-specific characteristics for different treatment designs on bacterial population dynamics and resistance evolution. We confirm that simultaneous and one-day cycling treatments could supress resistance in the presence of CS. We show that the efficacy of CS-based cycling therapies depends critically on the order of drug administration. Finally, we find that reciprocal CS is not essential to suppress resistance, a result that significantly broadens treatment options given the ubiquity of one-way CS in pathogens. Overall, our analyses identify key design principles of CS-based treatment strategies and provide guidance to develop treatment schedules to suppress resistance.

Price equation captures the role of drug interactions and collateral effects in the evolution of multidrug resistance

Bacterial adaptation to antibiotic combinations depends on the joint inhibitory effects of the two drugs (drug interaction [DI]) and how resistance to one drug impacts resistance to the other (collateral effects [CE]). Here we model these evolutionary dynamics on two-dimensional phenotype spaces that leverage scaling relations between the drug-response surfaces of drug-sensitive (ancestral) and drug-resistant (mutant) populations. We show that evolved resistance to the component drugs - and in turn, the adaptation of growth rate - is governed by a Price equation whose covariance terms encode geometric features of both the two-drug-response surface (DI) in ancestral cells and the correlations between resistance levels to those drugs (CE). Within this framework, mean evolutionary trajectories reduce to a type of weighted gradient dynamics, with the drug interaction dictating the shape of the underlying landscape and the collateral effects constraining the motion on those landscapes. We also demonstrate how constraints on available mutational pathways can be incorporated into the framework, adding a third key driver of evolution. Our results clarify the complex relationship between drug interactions and collateral effects in multidrug environments and illustrate how specific dosage combinations can shift the weighting of these two effects, leading to different and temporally explicit selective outcomes.

Emergence and dissemination of antimicrobial resistance in Escherichia coli causing bloodstream infections in Norway in 2002-17: a nationwide, longitudinal, microbial population genomic study

BACKGROUND

The clonal diversity underpinning trends in multidrug resistant Escherichia coli causing bloodstream infections remains uncertain. We aimed to determine the contribution of individual clones to resistance over time, using large-scale genomics-based molecular epidemiology.

METHODS

This was a longitudinal, E coli population, genomic, cohort study that sampled isolates from 22 512 E coli bloodstream infections included in the Norwegian surveillance programme on resistant microbes (NORM) from 2002 to 2017. 15 of 22 laboratories were able to share their isolates, and the first 22·5% of isolates from each year were requested. We used whole genome sequencing to infer the population structure (PopPUNK), and we investigated the clade composition of the dominant multidrug resistant clonal complex (CC)131 using genetic markers previously reported for sequence type (ST)131, effective population size (BEAST), and presence of determinants of antimicrobial resistance (ARIBA, PointFinder, and ResFinder databases) over time. We compared these features between the 2002-10 and 2011-17 time periods. We also compared our results with those of a longitudinal study from the UK done between 2001 and 2011.

FINDINGS

Of the 3500 isolates requested from the participating laboratories, 3397 (97·1%) were received, of which 3254 (95·8%) were successfully sequenced and included in the analysis. A significant increase in the number of multidrug resistant CC131 isolates from 71 (5·6%) of 1277 in 2002-10 to 207 (10·5%) of 1977 in 2011-17 (p<0·0001), was the largest clonal expansion. CC131 was the most common clone in extended-spectrum β-lactamase (ESBL)-positive isolates (75 [58·6%] of 128) and fluoroquinolone non-susceptible isolates (148 [39·2%] of 378). Within CC131, clade A increased in prevalence from 2002, whereas the global multidrug resistant clade C2 was not observed until 2007. Multiple de-novo acquisitions of both blaCTX-M ESBL-encoding genes in clades A and C1 and gain of phenotypic fluoroquinolone non-susceptibility across the clade A phylogeny were observed. We estimated that exponential increases in the effective population sizes of clades A, C1, and C2 occurred in the mid-2000s, and in clade B a decade earlier. The rate of increase in the estimated effective population size of clade A (Ne=3147) was nearly ten-times that of C2 (Ne=345), with clade A over-represented in Norwegian CC131 isolates (75 [27·0%] of 278) compared with the UK study (8 [5·4%] of 147 isolates).

INTERPRETATION

The early and sustained establishment of predominantly antimicrobial susceptible CC131 clade A isolates, relative to multidrug resistant clade C2 isolates, suggests that resistance is not necessary for clonal success. However, even in the low antibiotic use setting of Norway, resistance to important antimicrobial classes has rapidly been selected for in CC131 clade A isolates. This study shows the importance of genomic surveillance in uncovering the complex ecology underlying multidrug resistance dissemination and competition, which have implications for the design of strategies and interventions to control the spread of high-risk multidrug resistant clones.

FUNDING

Trond Mohn Foundation, European Research Council, Marie Skłodowska-Curie Actions, and the Wellcome Trust.

Collateral sensitivity associated with antibiotic resistance plasmids

Collateral sensitivity (CS) is a promising alternative approach to counteract the rising problem of antibiotic resistance (ABR). CS occurs when the acquisition of resistance to one antibiotic produces increased susceptibility to a second antibiotic. Recent studies have focused on CS strategies designed against ABR mediated by chromosomal mutations. However, one of the main drivers of ABR in clinically relevant bacteria is the horizontal transfer of ABR genes mediated by plasmids. Here, we report the first analysis of CS associated with the acquisition of complete ABR plasmids, including the clinically important carbapenem-resistance conjugative plasmid pOXA-48. In addition, we describe the conservation of CS in clinical E. coli isolates and its application to selectively kill plasmid-carrying bacteria. Our results provide new insights that establish the basis for developing CS-informed treatment strategies to combat plasmid-mediated ABR.

Antibiotic resistance: turning evolutionary principles into clinical reality

Antibiotic resistance is one of the major challenges facing modern medicine worldwide. The past few decades have witnessed rapid progress in our understanding of the multiple factors that affect the emergence and spread of antibiotic resistance at the population level and the level of the individual patient. However, the process of translating this progress into health policy and clinical practice has been slow. Here, we attempt to consolidate current knowledge about the evolution and ecology of antibiotic resistance into a roadmap for future research as well as clinical and environmental control of antibiotic resistance. At the population level, we examine emergence, transmission and dissemination of antibiotic resistance, and at the patient level, we examine adaptation involving bacterial physiology and host resilience. Finally, we describe new approaches and technologies for improving diagnosis and treatment and minimizing the spread of resistance.

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

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

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

Phage-antibiotic combinations: a promising approach to constrain resistance evolution in bacteria

Antibiotic resistance has reached dangerously high levels throughout the world. A growing number of bacteria pose an urgent, serious, and concerning threat to public health. Few new antibiotics are available to clinicians and only few are in development, highlighting the need for new strategies to overcome the antibiotic resistance crisis. Combining existing antibiotics with phages, viruses the infect bacteria, is an attractive and promising alternative to standalone therapies. Phage-antibiotic combinations have been shown to suppress the emergence of resistance in bacteria, and sometimes even reverse it. Here, we discuss the mechanisms by which phage-antibiotic combinations reduce resistance evolution, and the potential limitations these mechanisms have in steering microbial resistance evolution in a desirable direction. We also emphasize the importance of gaining a better understanding of mechanisms behind physiological and evolutionary phage-antibiotic interactions in complex in-patient environments.

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.

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

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