Collateral sensitivity of antibiotic-resistant microbes

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.

Distinguishing mutants that resist drugs via different mechanisms by examining fitness tradeoffs

There is growing interest in designing multidrug therapies that leverage tradeoffs to combat resistance. Tradeoffs are common in evolution and occur when, for example, resistance to one drug results in sensitivity to another. Major questions remain about the extent to which tradeoffs are reliable, specifically, whether the mutants that provide resistance to a given drug all suffer similar tradeoffs. This question is difficult because the drug-resistant mutants observed in the clinic, and even those evolved in controlled laboratory settings, are often biased towards those that provide large fitness benefits. Thus, the mutations (and mechanisms) that provide drug resistance may be more diverse than current data suggests. Here, we perform evolution experiments utilizing lineage-tracking to capture a fuller spectrum of mutations that give yeast cells a fitness advantage in fluconazole, a common antifungal drug. We then quantify fitness tradeoffs for each of 774 evolved mutants across 12 environments, finding these mutants group into classes with characteristically different tradeoffs. Their unique tradeoffs may imply that each group of mutants affects fitness through different underlying mechanisms. Some of the groupings we find are surprising. For example, we find some mutants that resist single drugs do not resist their combination, while others do. And some mutants to the same gene have different tradeoffs than others. These findings, on one hand, demonstrate the difficulty in relying on consistent or intuitive tradeoffs when designing multidrug treatments. On the other hand, by demonstrating that hundreds of adaptive mutations can be reduced to a few groups with characteristic tradeoffs, our findings may yet empower multidrug strategies that leverage tradeoffs to combat resistance. More generally speaking, by grouping mutants that likely affect fitness through similar underlying mechanisms, our work guides efforts to map the phenotypic effects of mutation.

The evolution of antimicrobial peptide resistance in Pseudomonas aeruginosa is severely constrained by random peptide mixtures

The prevalence of antibiotic-resistant pathogens has become a major threat to public health, requiring swift initiatives for discovering new strategies to control bacterial infections. Hence, antibiotic stewardship and rapid diagnostics, but also the development, and prudent use, of novel effective antimicrobial agents are paramount. Ideally, these agents should be less likely to select for resistance in pathogens than currently available conventional antimicrobials. The usage of antimicrobial peptides (AMPs), key components of the innate immune response, and combination therapies, have been proposed as strategies to diminish the emergence of resistance. Herein, we investigated whether newly developed random antimicrobial peptide mixtures (RPMs) can significantly reduce the risk of resistance evolution in vitro to that of single sequence AMPs, using the ESKAPE pathogen Pseudomonas aeruginosa (P. aeruginosa) as a model gram-negative bacterium. Infections of this pathogen are difficult to treat due the inherent resistance to many drug classes, enhanced by the capacity to form biofilms. P. aeruginosa was experimentally evolved in the presence of AMPs or RPMs, subsequentially assessing the extent of resistance evolution and cross-resistance/collateral sensitivity between treatments. Furthermore, the fitness costs of resistance on bacterial growth were studied and whole-genome sequencing used to investigate which mutations could be candidates for causing resistant phenotypes. Lastly, changes in the pharmacodynamics of the evolved bacterial strains were examined. Our findings suggest that using RPMs bears a much lower risk of resistance evolution compared to AMPs and mostly prevents cross-resistance development to other treatments, while maintaining (or even improving) drug sensitivity. This strengthens the case for using random cocktails of AMPs in favour of single AMPs, against which resistance evolved in vitro, providing an alternative to classic antibiotics worth pursuing.

Emerging contaminants: A One Health perspective

Environmental pollution is escalating due to rapid global development that often prioritizes human needs over planetary health. Despite global efforts to mitigate legacy pollutants, the continuous introduction of new substances remains a major threat to both people and the planet. In response, global initiatives are focusing on risk assessment and regulation of emerging contaminants, as demonstrated by the ongoing efforts to establish the UN's Intergovernmental Science-Policy Panel on Chemicals, Waste, and Pollution Prevention. This review identifies the sources and impacts of emerging contaminants on planetary health, emphasizing the importance of adopting a One Health approach. Strategies for monitoring and addressing these pollutants are discussed, underscoring the need for robust and socially equitable environmental policies at both regional and international levels. Urgent actions are needed to transition toward sustainable pollution management practices to safeguard our planet for future generations.

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.

Distinguishing mutants that resist drugs via different mechanisms by examining fitness tradeoffs

There is growing interest in designing multidrug therapies that leverage tradeoffs to combat resistance. Tradeoffs are common in evolution and occur when, for example, resistance to one drug results in sensitivity to another. Major questions remain about the extent to which tradeoffs are reliable, specifically, whether the mutants that provide resistance to a given drug all suffer similar tradeoffs. This question is difficult because the drug-resistant mutants observed in the clinic, and even those evolved in controlled laboratory settings, are often biased towards those that provide large fitness benefits. Thus, the mutations (and mechanisms) that provide drug resistance may be more diverse than current data suggests. Here, we perform evolution experiments utilizing lineage-tracking to capture a fuller spectrum of mutations that give yeast cells a fitness advantage in fluconazole, a common antifungal drug. We then quantify fitness tradeoffs for each of 774 evolved mutants across 12 environments, finding these mutants group into 6 classes with characteristically different tradeoffs. Their unique tradeoffs may imply that each group of mutants affects fitness through different underlying mechanisms. Some of the groupings we find are surprising. For example, we find some mutants that resist single drugs do not resist their combination, while others do. And some mutants to the same gene have different tradeoffs than others. These findings, on one hand, demonstrate the difficulty in relying on consistent or intuitive tradeoffs when designing multidrug treatments. On the other hand, by demonstrating that hundreds of adaptive mutations can be reduced to a few groups with characteristic tradeoffs, our findings may yet empower multidrug strategies that leverage tradeoffs to combat resistance. More generally speaking, by grouping mutants that likely affect fitness through similar underlying mechanisms, our work guides efforts to map the phenotypic effects of mutation.

NaClO Co-selects antibiotic and disinfectant resistance in Klebsiella pneumonia: Implications for the potential risk of extensive disinfectant use during COVID-19 pandemic

The inappropriate use of antibiotics is widely recognized as the primary driver of bacterial antibiotic resistance. However, less attention has been given to the potential induction of multidrug-resistant bacteria through exposure to disinfectants. In this study, Klebsiella pneumonia, an opportunistic pathogen commonly associated with hospital and community-acquired infection, was experimentally exposed to NaClO at both minimum inhibitory concentration (MIC) and sub-MIC levels over a period of 60 days. The result demonstrated that NaClO exposure led to enhanced resistance of K. pneumonia to both NaClO itself and five antibiotics (erythromycin, polymyxin B, gentamicin, tetracycline, and ciprofloxacin). Concurrently, the evolved resistant strains exhibited fitness costs, as evidenced by decreased growth rates. Whole population sequencing revealed that both concentrations of NaClO exposure caused genetic mutations in the genome of K. pneumonia. Some of these mutations were known to be associated with antibiotic resistance, while others had not previously been identified as such. In addition, 11 identified mutations were located in the virulence factors, demonstrating that NaClO exposure may also impact the pathogenicity of K. pneumoniae. Overall, this study highlights the potential for the widespread use of NaClO-containing disinfectants during the COVID-19 pandemic to contribute to the emergence of antibiotic-resistant bacteria. ENVIRONMENTAL IMPLICATION: Considering the potential hazardous effects of disinfectant residues on environment, organisms and biodiversity, the sharp rise in use of disinfectants during COVID-19 pandemic has been considered highly likely to cause worldwide secondary disasters in ecosystems and human health. This study demonstrated that NaClO exposure enhanced the resistance of K. pneumonia to both NaClO and five antibiotics (erythromycin, polymyxin B, gentamicin, tetracycline, and ciprofloxacin), highlighting the widespread use of NaClO-containing disinfectants during the COVID-19 pandemic may increase the emergence of antibiotic-resistant bacteria in the environment.

Collateral sensitivity increases the efficacy of a rationally designed bacteriophage combination to control Salmonella enterica

The ability of virulent bacteriophages to lyse bacteria influences bacterial evolution, fitness, and population structure. Knowledge of both host susceptibility and resistance factors is crucial for the successful application of bacteriophages as biological control agents in clinical therapy, food processing, and agriculture. In this study, we isolated 12 bacteriophages termed SPLA phage which infect the foodborne pathogen Salmonella enterica. To determine phage host range, a diverse collection of Enterobacteriaceae and Salmonella enterica was used and genes involved in infection by six SPLA phages were identified using Salmonella Typhimurium strain ST4/74. Candidate host receptors included lipopolysaccharide (LPS), cellulose, and BtuB. Lipopolysaccharide was identified as a susceptibility factor for phage SPLA1a and mutations in LPS biosynthesis genes spontaneously emerged during culture with S. Typhimurium. Conversely, LPS was a resistance factor for phage SPLA5b which suggested that emergence of LPS mutations in culture with SPLA1a represented collateral sensitivity to SPLA5b. We show that bacteria-phage co-culture with SPLA1a and SPLA5b was more successful in limiting the emergence of phage resistance compared to single phage co-culture. Identification of host susceptibility and resistance genes and understanding infection dynamics are critical steps in the rationale design of phage cocktails against specific bacterial pathogens.IMPORTANCEAs antibiotic resistance continues to emerge in bacterial pathogens, bacterial viruses (phage) represent a potential alternative or adjunct to antibiotics. One challenge for their implementation is the predisposition of bacteria to rapidly acquire resistance to phages. We describe a functional genomics approach to identify mechanisms of susceptibility and resistance for newly isolated phages that infect and lyse Salmonella enterica and use this information to identify phage combinations that exploit collateral sensitivity, thus increasing efficacy. Collateral sensitivity is a phenomenon where resistance to one class of antibiotics increases sensitivity to a second class of antibiotics. We report a functional genomics approach to rationally design a phage combination with a collateral sensitivity dynamic which resulted in increased efficacy. Considering such evolutionary trade-offs has the potential to manipulate the outcome of phage therapy in favor of resolving infection without selecting for escape mutants and is applicable to other virus-host interactions.

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.

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.

Evolutionary Epidemiology Consequences of Trait-Dependent Control of Heterogeneous Parasites

AbstractDisease control can induce both demographic and evolutionary responses in host-parasite systems. Foreseeing the outcome of control therefore requires knowledge of the eco-evolutionary feedback between control and system. Previous work has assumed that control strategies have a homogeneous effect on the parasite population. However, this is not true when control targets those traits that confer to the parasite heterogeneous levels of resistance, which can additionally be related to other key parasite traits through evolutionary trade-offs. In this work, we develop a minimal model coupling epidemiological and evolutionary dynamics to explore possible trait-dependent effects of control strategies. In particular, we consider a parasite expressing continuous levels of a trait-determining resource exploitation and a control treatment that can be either positively or negatively correlated with that trait. We demonstrate the potential of trait-dependent control by considering that the decision maker may want to minimize both the damage caused by the disease and the use of treatment, due to possible environmental or economic costs. We identify efficient strategies showing that the optimal type of treatment depends on the amount applied. Our results pave the way for the study of control strategies based on evolutionary constraints, such as collateral sensitivity and resistance costs, which are receiving increasing attention for both public health and agricultural purposes.

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.

Nothing makes sense in drug resistance except in the light of evolution

Our ability to fight infectious diseases is being increasingly compromised due to the emergence and spread of pathogens that become resistant to one or several drugs. This phenomenon is ubiquitous among pathogens and has parallels in cancer treatment. Given the urgency of the problem, there is a need for a paradigm shift in drug therapy toward one in which the objective to prevent the evolution of drug resistance is considered alongside the main objective of eliminating the infection or tumor. Here, I stress the importance of considering an evolutionary perspective to achieve this goal, and review recent advances in this direction, including therapies that exploit the fitness trade-offs of resistance.

Bacterial memory in antibiotic resistance evolution and nanotechnology in evolutionary biology

Bacterial memory refers to the phenomenon in which past experiences influence current behaviors in response to changing environments. It serves as a crucial process that enables adaptation and evolution. We first summarize the state-of-art approaches regarding history-dependent behaviors that impact growth dynamics and underlying mechanisms. Then, the phenotypic and genotypic origins of memory and how encoded memory modulates drug tolerance/resistance are reviewed. We also provide a summary of possible memory effects induced by antimicrobial nanoparticles. The regulatory networks and genetic underpinnings responsible for memory building partially overlap with nanoparticle and drug exposures, which may raise concerns about the impact of nanotechnology on adaptation. Finally, we provide a perspective on the use of nanotechnology to harness bacterial memory based on its unique mode of actions on information processing and transmission in bacteria. Exploring bacterial memory mechanisms provides valuable insights into acclimation, evolution, and the potential applications of nanotechnology in harnessing memory.

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.

Analysis of whiB7 in Mycobacterium tuberculosis reveals novel AT-hook deletion mutations

Mutations in whiB7 have been associated with both hypersusceptibility and resistance to various antibiotics in Mycobacterium tuberculosis (Mtb). Unlocking the secrets of antibiotic resistance in the bacterium, we examined mutations in the coding sequences of whiB7 of over 40,000 diverse Mtb isolates. Our results unveil the dominant c.191delG (Gly64delG) mutation, present in all members of the lineage L1.2.2 and its impact on WhiB7's conserved GVWGG-motif, causing conformational changes and deletion of the C-terminal AT-hook. Excitingly, we discovered six unique mutations associated with partial or total deletion of the AT-hook, specific to certain sublineages. Our findings suggest the selective pressures driving these mutations, underlining the potential of genomics to advance our understanding of Mtb's antibiotic resistance. As tuberculosis remains a global health threat, our study offers valuable insights into the diverse nature and functional consequences of whiB7 mutations, paving the way for the development of novel therapeutic interventions.

Cultivating antimicrobial resistance: how intensive agriculture ploughs the way for antibiotic resistance

Antimicrobial resistance (AMR) is a growing threat to public health, global food security and animal welfare. Despite efforts in antibiotic stewardship, AMR continues to rise worldwide. Anthropogenic activities, particularly intensive agriculture, play an integral role in the dissemination of AMR genes within natural microbial communities - which current antibiotic stewardship typically overlooks. In this review, we examine the impact of anthropogenically induced temperature fluctuations, increased soil salinity, soil fertility loss, and contaminants such as metals and pesticides on the de novo evolution and dissemination of AMR in the environment. These stressors can select for AMR - even in the absence of antibiotics - via mechanisms such as cross-resistance, co-resistance and co-regulation. Moreover, anthropogenic stressors can prime bacterial physiology against stress, potentially widening the window of opportunity for the de novo evolution of AMR. However, research to date is typically limited to the study of single isolated bacterial species - we lack data on how intensive agricultural practices drive AMR over evolutionary timescales in more complex microbial communities. Furthermore, a multidisciplinary approach to fighting AMR is urgently needed, as it is clear that the drivers of AMR extend far beyond the clinical environment.

Identification of collateral sensitivity and evolutionary landscape of chemotherapy-induced drug resistance using cellular barcoding technology

Background: One of the most significant challenges impeding cancer treatment effectiveness is drug resistance. Combining evolutionary understanding with drug resistance can pave the way for the identification of second-line drug options that can overcome drug resistance. Although capecitabine and irinotecan are commonly used therapeutic agents in the treatment of CRC patients, resistance to these agents is common. The underlying clonal dynamics of resistance to these agents using high-resolution barcode technology and identification of effective second-line drugs in this context remain unclear. Methods and materials: Caco-2 and HT-29 cell lines were barcoded, and then capecitabine and irinotecan resistant derivatives of these cell lines were established. The frequencies of barcodes from resistant cell lines and harvested medium, longitudinally, were determined. Collateral drug sensitivity testing was carried out on resistant Caco-2 and HT-29 cell lines using single agents or drug combinations. The SyngeryFinder tool was used to analyse drug combination testing. Results: In Caco-2 and HT-29 cell lines, barcode frequency measurements revealed clonal dynamics of capecitabine and irinotecan formed by both pre-existing and de novo barcodes, indicating the presence of polyclonal drug resistance. The temporal dynamics of clonal evolution in Caco-2 and HT-29 cell lines were demonstrated by longitudinal analysis of pre-existing and de novo barcodes from harvested medium. In Caco-2 and HT-29 cell lines, collateral drug sensitivity revealed a number of drugs that were effective alone and in combination. Conclusion: The use of barcoding technology reveals the clonal dynamics of chemotherapy-induced drug resistance not only from harvested cell populations, but also from longitudinal sampling throughout the course of clonal evolution. Second-line drugs that sensitize drug-resistant CRC cell lines are identified through collateral drug testing.

Reduced selection for antibiotic resistance in community context is maintained despite pressure by additional antibiotics

Selection for antibiotic resistance at very low antibiotic concentrations has been demonstrated for individual antibiotics in single species experiments. Furthermore, selection in these focal strains is reduced when taking place in complex microbial community context. However, in the environment, bacteria are rarely exposed to single, but rather complex mixtures of selective agents. Here, we explored how the presence of a second selective agent affects selection dynamics between isogenic pairs of focal E. coli strains, differing exclusively in a single resistance determinant, in the absence and presence of a model wastewater community across a gradient of antibiotics. An additional antibiotic that exclusively affects the model wastewater community, but to which the focal strains are resistant to, was chosen as the second selective agent. This allowed exploring how inhibition alters the community's ability to reduce selection. In the presence of the community, the selection coefficient at specific antibiotic concentrations was consistently decreased compared to the absence of the community. While pressure through the second antibiotic significantly decreased the activity and diversity of the community, its ability to reduce selection was consistently maintained at levels comparable to those recorded in absence of the second antibiotic. This indicates that the observed effects of community context on selection dynamics are rather based on competitive or protective effects between the focal strains and a small proportion of bacteria within the community, than on general competition for nutrients. These findings have implications for our understanding of the evolution and selection for multi-drug resistant strains.

Bayesian network modeling of patterns of antibiotic cross-resistance by bacterial sample source

BACKGROUND

Antimicrobial resistance is a major healthcare burden, aggravated when it extends to multiple drugs. While cross-resistance is well-studied experimentally, it is not the case in clinical settings, and especially not while considering confounding. Here, we estimated patterns of cross-resistance from clinical samples, while controlling for multiple clinical confounders and stratifying by sample sources.

METHODS

We employed additive Bayesian network (ABN) modelling to examine antibiotic cross- resistance in five major bacterial species, obtained from different sources (urine, wound, blood, and sputum) in a clinical setting, collected in a large hospital in Israel over a 4-year period. Overall, the number of samples available were 3525 for E coli, 1125 for K pneumoniae, 1828 for P aeruginosa, 701 for P mirabilis, and 835 for S aureus.

RESULTS

Patterns of cross-resistance differ across sample sources. All identified links between resistance to different antibiotics are positive. However, in 15 of 18 instances, the magnitudes of the links are significantly different between sources. For example, E coli exhibits adjusted odds ratios of gentamicin-ofloxacin cross-resistance ranging from 3.0 (95%CI [2.3,4.0]) in urine samples to 11.0 (95%CI [5.2,26.1]) in blood samples. Furthermore, we found that for P mirabilis, the magnitude of cross-resistance among linked antibiotics is higher in urine than in wound samples, whereas the opposite is true for K pneumoniae and P aeruginosa.

CONCLUSIONS

Our results highlight the importance of considering sample sources when assessing likelihood of antibiotic cross-resistance. The information and methods described in our study can refine future estimation of cross-resistance patterns and facilitate determination of antibiotic treatment regimens.

The evolution of colistin resistance increases bacterial resistance to host antimicrobial peptides and virulence

Antimicrobial peptides (AMPs) offer a promising solution to the antibiotic resistance crisis. However, an unresolved serious concern is that the evolution of resistance to therapeutic AMPs may generate cross-resistance to host AMPs, compromising a cornerstone of the innate immune response. We systematically tested this hypothesis using globally disseminated mobile colistin resistance (MCR) that has been selected by the use of colistin in agriculture and medicine. Here, we show that MCR provides a selective advantage to Escherichia coli in the presence of key AMPs from humans and agricultural animals by increasing AMP resistance. Moreover, MCR promotes bacterial growth in human serum and increases virulence in a Galleria mellonella infection model. Our study shows how the anthropogenic use of AMPs can drive the accidental evolution of resistance to the innate immune system of humans and animals. These findings have major implications for the design and use of therapeutic AMPs and suggest that MCR may be difficult to eradicate, even if colistin use is withdrawn.

Collateral sensitivity profiling in drug-resistant Escherichia coli identifies natural products suppressing cephalosporin resistance

The rapid emergence of antimicrobial resistance presents serious health challenges to the management of infectious diseases, a problem that is further exacerbated by slowing rates of antimicrobial drug discovery in recent years. The phenomenon of collateral sensitivity (CS), whereby resistance to one drug is accompanied by increased sensitivity to another, provides new opportunities to address both these challenges. Here, we present a high-throughput screening platform termed Collateral Sensitivity Profiling (CSP) to map the difference in bioactivity of large chemical libraries across 29 drug-resistant strains of E. coli. CSP screening of 80 commercial antimicrobials demonstrated multiple CS interactions. Further screening of a 6195-member natural product library revealed extensive CS relationships in nature. In particular, we report the isolation of known and new analogues of borrelidin A with potent CS activities against cephalosporin-resistant strains. Co-dosing ceftazidime with borrelidin A slows broader cephalosporin resistance with no recognizable resistance to borrelidin A itself.

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.

Potent acyl-CoA synthetase 10 inhibitors kill Plasmodium falciparum by disrupting triglyceride formation

Identifying how small molecules act to kill malaria parasites can lead to new "chemically validated" targets. By pressuring Plasmodium falciparum asexual blood stage parasites with three novel structurally-unrelated antimalarial compounds (MMV665924, MMV019719 and MMV897615), and performing whole-genome sequence analysis on resistant parasite lines, we identify multiple mutations in the P. falciparum acyl-CoA synthetase (ACS) genes PfACS10 (PF3D7_0525100, M300I, A268D/V, F427L) and PfACS11 (PF3D7_1238800, F387V, D648Y, and E668K). Allelic replacement and thermal proteome profiling validates PfACS10 as a target of these compounds. We demonstrate that this protein is essential for parasite growth by conditional knockdown and observe increased compound susceptibility upon reduced expression. Inhibition of PfACS10 leads to a reduction in triacylglycerols and a buildup of its lipid precursors, providing key insights into its function. Analysis of the PfACS11 gene and its mutations point to a role in mediating resistance via decreased protein stability.

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.

Fast drug rotation reduces bacterial resistance evolution in a microcosm experiment

Drug rotation (cycling), in which multiple drugs are administrated alternatively, has the potential for limiting resistance evolution in pathogens. The frequency of drug alternation could be a major factor to determine the effectiveness of drug rotation. Drug rotation practices often have low frequency of drug alternation, with an expectation of resistance reversion. Here we, based on evolutionary rescue and compensatory evolution theories, suggest that fast drug rotation can limit resistance evolution in the first place. This is because fast drug rotation would give little time for the evolutionarily rescued populations to recover in population size and genetic diversity, and thus decrease the chance of future evolutionary rescue under alternate environmental stresses. We experimentally tested this hypothesis using the bacterium Pseudomonas fluorescens and two antibiotics (chloramphenicol and rifampin). Increasing drug rotation frequency reduced the chance of evolutionary rescue, and most of the finally surviving bacterial populations were resistant to both drugs. Drug resistance incurred significant fitness costs, which did not differ among the drug treatment histories. A link between population sizes during the early stages of drug treatment and the end-point fates of populations (extinction vs survival) suggested that population size recovery and compensatory evolution before drug shift increase the chance of population survival. Our results therefore advocate fast drug rotation as a promising approach to reduce bacterial resistance evolution, which in particular could be a substitute for drug combination when the latter has safety risks.

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.

Plasticity and Stereotypic Rewiring of the Transcriptome Upon Bacterial Evolution of Antibiotic Resistance

Bacterial evolution of antibiotic resistance frequently has deleterious side effects on microbial growth, virulence, and susceptibility to other antimicrobial agents. However, it is unclear how these trade-offs could be utilized for manipulating antibiotic resistance in the clinic, not least because the underlying molecular mechanisms are poorly understood. Using laboratory evolution, we demonstrate that clinically relevant resistance mutations in Escherichia coli constitutively rewire a large fraction of the transcriptome in a repeatable and stereotypic manner. Strikingly, lineages adapted to functionally distinct antibiotics and having no resistance mutations in common show a wide range of parallel gene expression changes that alter oxidative stress response, iron homeostasis, and the composition of the bacterial outer membrane and cell surface. These common physiological alterations are associated with changes in cell morphology and enhanced sensitivity to antimicrobial peptides. Finally, the constitutive transcriptomic changes induced by resistance mutations are largely distinct from those induced by antibiotic stresses in the wild type. This indicates a limited role for genetic assimilation of the induced antibiotic stress response during resistance evolution. Our work suggests that diverse resistance mutations converge on similar global transcriptomic states that shape genetic susceptibility to antimicrobial compounds.

Impacts of dietary copper on the swine gut microbiome and antibiotic resistome

Restrictions on antibiotic growth promoters have prompted livestock producers to use alternative growth promoters, and dietary copper (Cu) supplementation is currently being widely used in pig production. However, elevated doses of dietary Cu constitute a risk for co-selection of antibiotic resistance and the risk may depend on the type of Cu-based feed additives being used. We here report the first controlled experiment investigating the impact of two contrasting Cu-based feed additives on the overall swine gut microbiome and antibiotic resistome. DNA was extracted from fecal samples (n = 96) collected at four time points during 116 days from 120 pigs allotted to three dietary treatments: control, divalent copper sulfate (CuSO₄; 250 μg Cu g^-1 feed), and monovalent copper oxide (Cu₂O; 250 μg Cu g^-1 feed). Bacterial community composition, antibiotic resistance genes (ARGs), and mobile genetic elements (MGEs) were assessed, and bioavailable Cu ([Cu]_bio) was determined using whole-cell bacterial bioreporters. Cu supplementation to feed increased total Cu concentrations ([Cu]_total) and [Cu]_bio in feces 8-10 fold and at least 670-1000 fold, respectively, but with no significant differences between the two Cu sources. The swine gut microbiome harbored highly abundant and diverse ARGs and MGEs irrespective of the treatments throughout the experiment. Microbiomes differed significantly between pig growth stages and tended to converge over time, but only minor changes in the bacterial community composition and resistome could be linked to Cu supplementation. A significant correlation between bacterial community composition (i.e., bacterial taxa present) and ARG prevalence patterns were observed by Procrustes analysis. Overall, results of the experiment did not provide evidence for Cu-induced co-selection of ARGs or MGEs even at a Cu concentration level exceeding the maximal permitted level for pig diets in the EU (25 to 150 μg Cu g^-1 feed depending on pig age).

Resistance-resistant antibacterial treatment strategies

Antibiotic resistance is a major danger to public health that threatens to claim the lives of millions of people per year within the next few decades. Years of necessary administration and excessive application of antibiotics have selected for strains that are resistant to many of our currently available treatments. Due to the high costs and difficulty of developing new antibiotics, the emergence of resistant bacteria is outpacing the introduction of new drugs to fight them. To overcome this problem, many researchers are focusing on developing antibacterial therapeutic strategies that are "resistance-resistant"-regimens that slow or stall resistance development in the targeted pathogens. In this mini review, we outline major examples of novel resistance-resistant therapeutic strategies. We discuss the use of compounds that reduce mutagenesis and thereby decrease the likelihood of resistance emergence. Then, we examine the effectiveness of antibiotic cycling and evolutionary steering, in which a bacterial population is forced by one antibiotic toward susceptibility to another antibiotic. We also consider combination therapies that aim to sabotage defensive mechanisms and eliminate potentially resistant pathogens by combining two antibiotics or combining an antibiotic with other therapeutics, such as antibodies or phages. Finally, we highlight promising future directions in this field, including the potential of applying machine learning and personalized medicine to fight antibiotic resistance emergence and out-maneuver adaptive pathogens.

TCA and SSRI Antidepressants Exert Selection Pressure for Efflux-Dependent Antibiotic Resistance Mechanisms in Escherichia coli

Microbial diversity is reduced in the gut microbiota of animals and humans treated with selective serotonin reuptake inhibitors (SSRIs) and tricyclic antidepressants (TCAs). The mechanisms driving the changes in microbial composition, while largely unknown, is critical to understand considering that the gut microbiota plays important roles in drug metabolism and brain function. Using Escherichia coli, we show that the SSRI fluoxetine and the TCA amitriptyline exert strong selection pressure for enhanced efflux activity of the AcrAB-TolC pump, a member of the resistance-nodulation-cell division (RND) superfamily of transporters. Sequencing spontaneous fluoxetine- and amitriptyline-resistant mutants revealed mutations in marR and lon, negative regulators of AcrAB-TolC expression. In line with the broad specificity of AcrAB-TolC pumps these mutants conferred resistance to several classes of antibiotics. We show that the converse also occurs, as spontaneous chloramphenicol-resistant mutants displayed cross-resistance to SSRIs and TCAs. Chemical-genomic screens identified deletions in marR and lon, confirming the results observed for the spontaneous resistant mutants. In addition, deletions in 35 genes with no known role in drug resistance were identified that conferred cross-resistance to antibiotics and several displayed enhanced efflux activities. These results indicate that combinations of specific antidepressants and antibiotics may have important effects when both are used simultaneously or successively as they can impose selection for common mechanisms of resistance. Our work suggests that selection for enhanced efflux activities is an important factor to consider in understanding the microbial diversity changes associated with antidepressant treatments. IMPORTANCE Antidepressants are prescribed broadly for psychiatric conditions to alter neuronal levels of synaptic neurotransmitters such as serotonin and norepinephrine. Two categories of antidepressants are selective serotonin reuptake inhibitors (SSRIs) and tricyclic antidepressants (TCAs); both are among the most prescribed drugs in the United States. While it is well-established that antidepressants inhibit reuptake of neurotransmitters there is evidence that they also impact microbial diversity in the gastrointestinal tract. However, the mechanisms and therefore biological and clinical effects remain obscure. We demonstrate antidepressants may influence microbial diversity through strong selection for mutant bacteria with increased AcrAB-TolC activity, an efflux pump that removes antibiotics from cells. Furthermore, we identify a new group of genes that contribute to cross-resistance between antidepressants and antibiotics, several act by regulating efflux activity, underscoring overlapping mechanisms. Overall, this work provides new insights into bacterial responses to antidepressants important for understanding antidepressant treatment effects.

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.

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.

Zinc(II), Palladium(II), and Metal-Free Phthalocyanines Bearing Nipagin-Functionalized Substituents against Candida auris and Selected Multidrug-Resistant Microbes

Due to the rapidly increasing problem of antibiotic resistance in recent years, the use of phthalocyanines as photosensitizers with their superior properties in photodynamic antimicrobial therapy (PACT) applications has become important. In this study, magnesium(II) 1,4,8,11,15,18,22,25-octakis(4-[4-butoxycarbonylphenoxy]butyloxy)phthalocyanine was used in the demetalation reaction in trifluoroacetic acid, and subsequently subjected to metalation reaction in dimethylformamide with zinc(II) acetate and bis(benzonitrile)palladium(II) chloride towards zinc(II) and palladium(II) derivatives. Three phthalocyanines, including a demetalated one as well as two metalated, in the core with zinc(II) and palladium(II) were characterized using 1D and 2D NMR spectroscopy and mass spectrometry. In addition, all macrocycles were subjected to absorption and emission studies as well as photostability tests. In a photochemical study, zinc(II) and palladium(II) phthalocyanine complexes appeared to be efficient singlet oxygen generators. There were noted quantum yields of singlet oxygen generation for zinc(II) phthalocyanine derivative in DMF and DMSO at 0.55 and 0.72, whereas for palladium(II) complex at 0.73 and 0.77, respectively. Liposomal formulations of phthalocyanine derivatives were prepared, and their activity was evaluated against a broad spectrum of antibiotic-resistant microorganisms, such as methicillin-resistant Staphylococcus aureus (MRSA), Escherichia coli (ESBL+), Candida albicans resistant to fluconazole, C. auris, and against dermatophytes. Phthalocyanine palladium(II) complex showed the highest bactericidal activity against all antibiotic-resistant microorganisms, including reducing C. auris growth at 3.54 log.

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.

A flux-based machine learning model to simulate the impact of pathogen metabolic heterogeneity on drug interactions

Drug combinations are a promising strategy to counter antibiotic resistance. However, current experimental and computational approaches do not account for the entire complexity involved in combination therapy design, such as the effect of pathogen metabolic heterogeneity, changes in the growth environment, drug treatment order, and time interval. To address these limitations, we present a comprehensive approach that uses genome-scale metabolic modeling and machine learning to guide combination therapy design. Our mechanistic approach (a) accommodates diverse data types, (b) accounts for time- and order-specific interactions, and (c) accurately predicts drug interactions in various growth conditions and their robustness to pathogen metabolic heterogeneity. Our approach achieved high accuracy (area under the receiver operating curve (AUROC) = 0.83 for synergy, AUROC = 0.98 for antagonism) in predicting drug interactions for Escherichia coli cultured in 57 metabolic conditions based on experimental validation. The entropy in bacterial metabolic response was predictive of combination therapy outcomes across time scales and growth conditions. Simulation of metabolic heterogeneity using population FBA identified two subpopulations of E. coli cells defined by the levels of three proteins (eno, fadB, and fabD) in glycolysis and lipid metabolism that influence cell tolerance to a broad range of antibiotic combinations. Analysis of the vast landscape of condition-specific drug interactions revealed a set of 24 robustly synergistic drug combinations with potential for clinical use.

Breaking the Rebellion: Photodynamic Inactivation against Erwinia amylovora Resistant to Streptomycin

Global crop production depends on strategies to counteract the ever-increasing spread of plant pathogens. Antibiotics are often used for large-scale treatments. As a result, Erwinia amylovora, causal agent of the contagious fire blight disease, has already evolved resistance to streptomycin (Sm). Photodynamic Inactivation (PDI) of microorganisms has been introduced as innovative method for plant protection. The aim of this study is to demonstrate that E. amylovora resistant to Sm (E. amylovora^SmR) can be killed by PDI. Two photosensitizers, the synthetic B17-0024, and the natural derived anionic sodium magnesium chlorophyllin (Chl) with cell-wall-permeabilizing agents are compared in terms of their photo-killing efficiency in liquid culture with or without 100 µg/mL Sm. In vitro experiments were performed at photosensitizer concentrations of 1, 10 or 100 µM and 5 or 30 min incubation in the dark, followed by illumination at 395 nm (radiant exposure 26.6 J/cm²). The highest inactivation of seven log steps was achieved at 100 µM B17-0024 after 30 min incubation. Shorter incubation (5 min), likely to represent field conditions, reduced the photo-killing to 5 log steps. Chlorophyllin at 100 µM in combination with 1.2% polyaspartic acid (PASA) reduced the number of bacteria by 6 log steps. While PASA itself caused some light independent toxicity, an antibacterial effect (3 log reduction) was achieved only in combination with Chl, even at concentrations as low as 10 µM. Addition of 100 µg/mL Sm to media did not significantly increase the efficacy of the photodynamic treatment. This study proves principle that PDI can be used to treat plant diseases even if causative bacteria are resistant to conventional treatment. Therefore, PDI based on natural photosensitizers might represent an eco-friendly treatment strategy especially in organic farming.

A Phage Foundry Framework to Systematically Develop Viral Countermeasures to Combat Antibiotic-Resistant Bacterial Pathogens

At its current rate, the rise of antimicrobial-resistant (AMR) infections is predicted to paralyze our industries and healthcare facilities while becoming the leading global cause of loss of human life. With limited new antibiotics on the horizon, we need to invest in alternative solutions. Bacteriophages (phages)-viruses targeting bacteria-offer a powerful alternative approach to tackle bacterial infections. Despite recent advances in using phages to treat recalcitrant AMR infections, the field lacks systematic development of phage therapies scalable to different applications. We propose a Phage Foundry framework to establish metrics for phage characterization and to fill the knowledge and technological gaps in phage therapeutics. Coordinated investment in AMR surveillance, sampling, characterization, and data sharing procedures will enable rational exploitation of phages for treatments. A fully realized Phage Foundry will enhance the sharing of knowledge, technology, and viral reagents in an equitable manner and will accelerate the biobased economy.

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.

Collateral sensitivity to pleuromutilins in vancomycin-resistant Enterococcus faecium

The acquisition of resistance to one antibiotic sometimes leads to collateral sensitivity to a second antibiotic. Here, we show that vancomycin resistance in Enterococcus faecium is associated with a remarkable increase in susceptibility to pleuromutilin antibiotics (such as lefamulin), which target the bacterial ribosome. The trade-off between vancomycin and pleuromutilins is mediated by epistasis between the van gene cluster and msrC, encoding an ABC-F protein that protects bacterial ribosomes from antibiotic targeting. In mouse models of vancomycin-resistant E. faecium colonization and septicemia, pleuromutilin treatment reduces colonization and improves survival more effectively than standard therapy (linezolid). Our findings suggest that pleuromutilins may be useful for the treatment of vancomycin-resistant E. faecium infections.

Collateral responses to classical cytotoxic chemotherapies are heterogeneous and sensitivities are sparse

Chemotherapy resistance is a major obstacle to curing cancer patients. Combination drug regimens have shown promise as a method to overcome resistance; however, to date only some cancers have been cured with this method. Collateral sensitivity-the phenomenon whereby resistance to one drug is co-occurrent with sensitivity to a second drug-has been gaining traction as a promising new concept to guide rational design of combination regimens. Here we evolved over 100 subclones of the Eµ-Myc; p19^ARF-/- cell line to be resistant to one of four classical chemotherapy agents: doxorubicin, vincristine, paclitaxel, and cisplatin. We then surveyed collateral responses to acquisition of resistance to these agents. Although numerous collateral sensitivities have been documented for antibiotics and targeted cancer therapies, we observed only one collateral sensitivity: half of cell lines that acquired resistance to paclitaxel also acquired a collateral sensitivity to verapamil. However, we found that the mechanism of this collateral sensitivity was unrelated to the mechanism of paclitaxel resistance. Interestingly, we observed heterogeneity in the phenotypic response to acquisition of resistance to most of the drugs we tested, most notably for paclitaxel, suggesting the existence of multiple different states of resistance. Surprisingly, this phenotypic heterogeneity in paclitaxel resistant cell lines was unrelated to transcriptomic heterogeneity among those cell lines. These features of phenotypic and transcriptomic heterogeneity must be taken into account in future studies of treated tumor subclones and in design of chemotherapy combinations.

Rapid decline of ceftazidime resistance in antibiotic-free and sub-lethal environments is contingent on genetic background

Trade-offs of antibiotic resistance evolution, such as fitness cost and collateral sensitivity (CS), could be exploited to drive evolution toward antibiotic susceptibility. Decline of resistance may occur when resistance to other drug leads to CS to the first one and when compensatory mutations, or genetic reversion of the original ones, reduce fitness cost. Here we describe the impact of antibiotic-free and sublethal environments on declining ceftazidime resistance in different Pseudomonas aeruginosa resistant mutants. We determined that decline of ceftazidime resistance occurs within 450 generations, which is caused by newly acquired mutations and not by reversion of the original ones, and that the original CS of these mutants is preserved. In addition, we observed that the frequency and degree of this decline is contingent on genetic background. Our results are relevant to implement evolution-based therapeutic approaches, as well as to redefine global policies of antibiotic use, such as drug cycling.

Type Strains of Entomopathogenic Nematode-Symbiotic Bacterium Species, Xenorhabdus szentirmaii (EMC) and X. budapestensis (EMA), Are Exceptional Sources of Non-Ribosomal Templated, Large-Target-Spectral, Thermotolerant-Antimicrobial Peptides (by Both), and Iodinin (by EMC)

Antimicrobial multidrug resistance (MDR) is a global challenge, not only for public health, but also for sustainable agriculture. Antibiotics used in humans should be ruled out for use in veterinary or agricultural settings. Applying antimicrobial peptide (AMP) molecules, produced by soil-born organisms for protecting (soil-born) plants, seems a preferable alternative. The natural role of peptide-antimicrobials, produced by the prokaryotic partner of entomopathogenic-nematode/bacterium (EPN/EPB) symbiotic associations, is to sustain monoxenic conditions for the EPB in the gut of the semi-anabiotic infective dauer juvenile (IJ) EPN. They keep pathobiome conditions balanced for the EPN/EPB complex in polyxenic (soil, vanquished insect cadaver) niches. Xenorhabdus szentirmaii DSM16338(T) (EMC), and X. budapestensis DSM16342(T) (EMA), are the respective natural symbionts of EPN species Steinernema rarum and S. bicornutum. We identified and characterized both of these 15 years ago. The functional annotation of the draft genome of EMC revealed 71 genes encoding non-ribosomal peptide synthases, and polyketide synthases. The large spatial Xenorhabdus AMP (fabclavine), was discovered in EMA, and its biosynthetic pathway in EMC. The AMPs produced by EMA and EMC are promising candidates for controlling MDR prokaryotic and eukaryotic pathogens (bacteria, oomycetes, fungi, protozoa). EMC releases large quantity of iodinin (1,6-dihydroxyphenazine 5,10-dioxide) in a water-soluble form into the media, where it condenses to form spectacular water-insoluble, macroscopic crystals. This review evaluates the scientific impact of international research on EMA and EMC.

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.

Meropenem-induced reduction in colistin susceptibility in Pseudomonas aeruginosa strain ATCC 27853

Antibiotic-resistant strains of Pseudomonas aeruginosa are a global threat to public health. The knowledge of mechanisms underlying antibiotic resistance is essential to counter P. aeruginosa infections. This study describes the phenomenon of meropenem-induced cross-resistance to colistin in the ATCC 27853 strain of P. aeruginosa. The study was conducted in the specimens of P. aeruginosa grown from the reference ATCC 27853 strain in the medium containing meropenem gradients. Susceptibility of the isolates to carbapenems and colistin was assessed using the agar dilution method; susceptibly to colistin was assessed using the broth microdilution method. A total of 93 P. Aeruginosa isolates were analyzed; of them two demonstrated reduced susceptibility to carbapenems (meropenem, imipenem) and colistin. Whole-genome sequencing of the isolates was performed on a MGISEQ-2000 platform. Missense mutations in the oprD and mexD genes and a nonsense mutation in the phoQ gene were detected. We conclude that exposure of P. aeruginosa to meropenem can lead to cross-resistance to colistin, a last resort drug for P. aeruginosa infections.

Bugs on Drugs: A Drosophila melanogaster Gut Model to Study In Vivo Antibiotic Tolerance of E. coli

With an antibiotic crisis upon us, we need to boost antibiotic development and improve antibiotics’ efficacy. Crucial is knowing how to efficiently kill bacteria, especially in more complex in vivo conditions. Indeed, many bacteria harbor antibiotic-tolerant persisters, variants that survive exposure to our most potent antibiotics and catalyze resistance development. However, persistence is often only studied in vitro as we lack flexible in vivo models. Here, I explored the potential of using Drosophila melanogaster as a model for antimicrobial research, combining methods in Drosophila with microbiology techniques: assessing fly development and feeding, generating germ-free or bacteria-associated Drosophila and in situ microscopy. Adult flies tolerate antibiotics at high doses, although germ-free larvae show impaired development. Orally presented E. coli associates with Drosophila and mostly resides in the crop. E. coli shows an overall high antibiotic tolerance in vivo potentially resulting from heterogeneity in growth rates. The hipA7 high-persistence mutant displays an increased antibiotic survival while the expected low persistence of ΔrelAΔspoT and ΔrpoS mutants cannot be confirmed in vivo. In conclusion, a Drosophila model for in vivo antibiotic tolerance research shows high potential and offers a flexible system to test findings from in vitro assays in a broader, more complex condition.

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.