Growth-Dependent Predation and Generalized Transduction of Antimicrobial Resistance by Bacteriophage. - Related Documents




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899901.0000Growth-Dependent Predation and Generalized Transduction of Antimicrobial Resistance by Bacteriophage. Bacteriophage (phage) are both predators and evolutionary drivers for bacteria, notably contributing to the spread of antimicrobial resistance (AMR) genes by generalized transduction. Our current understanding of this complex relationship is limited. We used an interdisciplinary approach to quantify how these interacting dynamics can lead to the evolution of multidrug-resistant bacteria. We cocultured two strains of methicillin-resistant Staphylococcus aureus, each harboring a different antibiotic resistance gene, with generalized transducing phage. After a growth phase of 8 h, bacteria and phage surprisingly coexisted at a stable equilibrium in our culture, the level of which was dependent on the starting concentration of phage. We detected double-resistant bacteria as early as 7 h, indicating that transduction of AMR genes had occurred. We developed multiple mathematical models of the bacteria and phage relationship and found that phage-bacteria dynamics were best captured by a model in which phage burst size decreases as the bacteria population reaches stationary phase and where phage predation is frequency-dependent. We estimated that one in every 10(8) new phage generated was a transducing phage carrying an AMR gene and that double-resistant bacteria were always predominantly generated by transduction rather than by growth. Our results suggest a shift in how we understand and model phage-bacteria dynamics. Although rates of generalized transduction could be interpreted as too rare to be significant, they are sufficient in our system to consistently lead to the evolution of multidrug-resistant bacteria. Currently, the potential of phage to contribute to the growing burden of AMR is likely underestimated. IMPORTANCE Bacteriophage (phage), viruses that can infect and kill bacteria, are being investigated through phage therapy as a potential solution to the threat of antimicrobial resistance (AMR). In reality, however, phage are also natural drivers of bacterial evolution by transduction when they accidentally carry nonphage DNA between bacteria. Using laboratory work and mathematical models, we show that transduction leads to evolution of multidrug-resistant bacteria in less than 8 h and that phage production decreases when bacterial growth decreases, allowing bacteria and phage to coexist at stable equilibria. The joint dynamics of phage predation and transduction lead to complex interactions with bacteria, which must be clarified to prevent phage from contributing to the spread of AMR.202235311576
427610.9999Phages limit the evolution of bacterial antibiotic resistance in experimental microcosms. The evolution of multi-antibiotic resistance in bacterial pathogens, often resulting from de novo mutations, is creating a public health crisis. Phages show promise for combating antibiotic-resistant bacteria, the efficacy of which, however, may also be limited by resistance evolution. Here, we suggest that phages may be used as supplements to antibiotics in treating initially sensitive bacteria to prevent resistance evolution, as phages are unaffected by most antibiotics and there should be little cross-resistance to antibiotics and phages. In vitro experiments using the bacterium Pseudomonas fluorescens, a lytic phage, and the antibiotic kanamycin supported this prediction: an antibiotic-phage combination dramatically decreased the chance of bacterial population survival that indicates resistance evolution, compared with antibiotic treatment alone, whereas the phage alone did not affect bacterial survival. This effect of the combined treatment in preventing resistance evolution was robust to immigration of bacteria from an untreated environment, but not to immigration from environment where the bacteria had coevolved with the phage. By contrast, an isogenic hypermutable strain constructed from the wild-type P. fluorescens evolved resistance to all treatments regardless of immigration, but typically suffered very large fitness costs. These results suggest that an antibiotic-phage combination may show promise as an antimicrobial strategy.201223028398
900020.9999Modelling the synergistic effect of bacteriophage and antibiotics on bacteria: Killers and drivers of resistance evolution. Bacteriophage (phage) are bacterial predators that can also spread antimicrobial resistance (AMR) genes between bacteria by generalised transduction. Phage are often present alongside antibiotics in the environment, yet evidence of their joint killing effect on bacteria is conflicted, and the dynamics of transduction in such systems are unknown. Here, we combine in vitro data and mathematical modelling to identify conditions where phage and antibiotics act in synergy to remove bacteria or drive AMR evolution. We adapt a published model of phage-bacteria dynamics, including transduction, to add the pharmacodynamics of erythromycin and tetracycline, parameterised from new in vitro data. We simulate a system where two strains of Staphylococcus aureus are present at stationary phase, each carrying either an erythromycin or tetracycline resistance gene, and where multidrug-resistant bacteria can be generated by transduction only. We determine rates of bacterial clearance and multidrug-resistant bacteria appearance, when either or both antibiotics and phage are present at varying timings and concentrations. Although phage and antibiotics act in synergy to kill bacteria, by reducing bacterial growth antibiotics reduce phage production. A low concentration of phage introduced shortly after antibiotics fails to replicate and exert a strong killing pressure on bacteria, instead generating multidrug-resistant bacteria by transduction which are then selected for by the antibiotics. Multidrug-resistant bacteria numbers were highest when antibiotics and phage were introduced simultaneously. The interaction between phage and antibiotics leads to a trade-off between a slower clearing rate of bacteria (if antibiotics are added before phage), and a higher risk of multidrug-resistance evolution (if phage are added before antibiotics), exacerbated by low concentrations of phage or antibiotics. Our results form hypotheses to guide future experimental and clinical work on the impact of phage on AMR evolution, notably for studies of phage therapy which should investigate varying timings and concentrations of phage and antibiotics.202236449520
961230.9999Using experimental evolution to explore natural patterns between bacterial motility and resistance to bacteriophages. Resistance of bacteria to phages may be gained by alteration of surface proteins to which phages bind, a mechanism that is likely to be costly as these molecules typically have critical functions such as movement or nutrient uptake. To address this potential trade-off, we combine a systematic study of natural bacteria and phage populations with an experimental evolution approach. We compare motility, growth rate and susceptibility to local phages for 80 bacteria isolated from horse chestnut leaves and, contrary to expectation, find no negative association between resistance to phages and bacterial motility or growth rate. However, because correlational patterns (and their absence) are open to numerous interpretations, we test for any causal association between resistance to phages and bacterial motility using experimental evolution of a subset of bacteria in both the presence and absence of naturally associated phages. Again, we find no clear link between the acquisition of resistance and bacterial motility, suggesting that for these natural bacterial populations, phage-mediated selection is unlikely to shape bacterial motility, a key fitness trait for many bacteria in the phyllosphere. The agreement between the observed natural pattern and the experimental evolution results presented here demonstrates the power of this combined approach for testing evolutionary trade-offs.201121509046
961140.9999Parallel evolution of Pseudomonas aeruginosa phage resistance and virulence loss in response to phage treatment in vivo and in vitro. With rising antibiotic resistance, there has been increasing interest in treating pathogenic bacteria with bacteriophages (phage therapy). One limitation of phage therapy is the ease at which bacteria can evolve resistance. Negative effects of resistance may be mitigated when resistance results in reduced bacterial growth and virulence, or when phage coevolves to overcome resistance. Resistance evolution and its consequences are contingent on the bacteria-phage combination and their environmental context, making therapeutic outcomes hard to predict. One solution might be to conduct 'in vitro evolutionary simulations' using bacteria-phage combinations from the therapeutic context. Overall, our aim was to investigate parallels between in vitro experiments and in vivo dynamics in a human participant. Evolutionary dynamics were similar, with high levels of resistance evolving quickly with limited evidence of phage evolution. Resistant bacteria-evolved in vitro and in vivo-had lower virulence. In vivo, this was linked to lower growth rates of resistant isolates, whereas in vitro phage resistant isolates evolved greater biofilm production. Population sequencing suggests resistance resulted from selection on de novo mutations rather than sorting of existing variants. These results highlight the speed at which phage resistance can evolve in vivo, and how in vitro experiments may give useful insights for clinical evolutionary outcomes.202235188102
427150.9999Multi-step vs. single-step resistance evolution under different drugs, pharmacokinetics, and treatment regimens. The success of antimicrobial treatment is threatened by the evolution of drug resistance. Population genetic models are an important tool in mitigating that threat. However, most such models consider resistance emergence via a single mutational step. Here, we assembled experimental evidence that drug resistance evolution follows two patterns: (i) a single mutation, which provides a large resistance benefit, or (ii) multiple mutations, each conferring a small benefit, which combine to yield high-level resistance. Using stochastic modeling, we then investigated the consequences of these two patterns for treatment failure and population diversity under various treatments. We find that resistance evolution is substantially limited if more than two mutations are required and that the extent of this limitation depends on the combination of drug type and pharmacokinetic profile. Further, if multiple mutations are necessary, adaptive treatment, which only suppresses the bacterial population, delays treatment failure due to resistance for a longer time than aggressive treatment, which aims at eradication.202134001313
382760.9999The fitness cost of horizontally transferred and mutational antimicrobial resistance in Escherichia coli. Antimicrobial resistance (AMR) in bacteria implies a tradeoff between the benefit of resistance under antimicrobial selection pressure and the incurred fitness cost in the absence of antimicrobials. The fitness cost of a resistance determinant is expected to depend on its genetic support, such as a chromosomal mutation or a plasmid acquisition, and on its impact on cell metabolism, such as an alteration in an essential metabolic pathway or the production of a new enzyme. To provide a global picture of the factors that influence AMR fitness cost, we conducted a systematic review and meta-analysis focused on a single species, Escherichia coli. By combining results from 46 high-quality studies in a multilevel meta-analysis framework, we find that the fitness cost of AMR is smaller when provided by horizontally transferable genes such as those encoding beta-lactamases, compared to mutations in core genes such as those involved in fluoroquinolone and rifampicin resistance. We observe that the accumulation of acquired AMR genes imposes a much smaller burden on the host cell than the accumulation of AMR mutations, and we provide quantitative estimates of the additional cost of a new gene or mutation. These findings highlight that gene acquisition is more efficient than the accumulation of mutations to evolve multidrug resistance, which can contribute to the observed dominance of horizontally transferred genes in the current AMR epidemic.202337455716
427770.9999Exposure to phages has little impact on the evolution of bacterial antibiotic resistance on drug concentration gradients. The use of phages for treating bacterial pathogens has recently been advocated as an alternative to antibiotic therapy. Here, we test a hypothesis that bacteria treated with phages may show more limited evolution of antibiotic resistance as the fitness costs of resistance to phages may add to those of antibiotic resistance, further reducing the growth performance of antibiotic-resistant bacteria. We did this by studying the evolution of phage-exposed and phage-free Pseudomonas fluorescens cultures on concentration gradients of single drugs, including cefotaxime, chloramphenicol, and kanamycin. During drug treatment, the level of bacterial antibiotic resistance increased through time and was not affected by the phage treatment. Exposure to phages did not cause slower growth in antibiotic-resistant bacteria, although it did so in antibiotic-susceptible bacteria. We observed significant reversion of antibiotic resistance after drug use being terminated, and the rate of reversion was not affected by the phage treatment. The results suggest that the fitness costs caused by resistance to phages are unlikely to be an important constraint on the evolution of bacterial antibiotic resistance in heterogeneous drug environments. Further studies are needed for the interaction of fitness costs of antibiotic resistance with other factors.201424665341
961580.9999Persistence and resistance as complementary bacterial adaptations to antibiotics. Bacterial persistence represents a simple of phenotypic heterogeneity, whereby a proportion of cells in an isogenic bacterial population can survive exposure to lethal stresses such as antibiotics. In contrast, genetically based antibiotic resistance allows for continued growth in the presence of antibiotics. It is unclear, however, whether resistance and persistence are complementary or alternative evolutionary adaptations to antibiotics. Here, we investigate the co-evolution of resistance and persistence across the genus Pseudomonas using comparative methods that correct for phylogenetic nonindependence. We find that strains of Pseudomonas vary extensively in both their intrinsic resistance to antibiotics (ciprofloxacin and rifampicin) and persistence following exposure to these antibiotics. Crucially, we find that persistence correlates positively to antibiotic resistance across strains. However, we find that different genes control resistance and persistence implying that they are independent traits. Specifically, we find that the number of type II toxin-antitoxin systems (TAs) in the genome of a strain is correlated to persistence, but not resistance. Our study shows that persistence and antibiotic resistance are complementary, but independent, evolutionary adaptations to stress and it highlights the key role played by TAs in the evolution of persistence.201626999656
949290.9999The Search for 'Evolution-Proof' Antibiotics. The effectiveness of antibiotics has been widely compromised by the evolution of resistance among pathogenic bacteria. It would be restored by the development of antibiotics to which bacteria cannot evolve resistance. We first discuss two kinds of 'evolution-proof' antibiotic. The first comprises literally evolution-proof antibiotics to which bacteria cannot become resistant by mutation or horizontal gene transfer. The second category comprises agents to which resistance may arise, but so rarely that it does not become epidemic. The likelihood that resistance to a novel agent will spread is evaluated here by a simple model that includes biological and therapeutic parameters governing the evolution of resistance within hosts and the transmission of resistant strains between hosts. This model leads to the conclusion that epidemic spread is unlikely if the frequency of mutations that confer resistance falls below a defined minimum value, and it identifies potential targets for intervention to prevent the evolution of resistance. Whether or not evolution-proof antibiotics are ever found, searching for them is likely to improve the deployment of new and existing agents by advancing our understanding of how resistance evolves.201829191398
4262100.9999Fitness cost of antibiotic susceptibility during bacterial infection. Advances in high-throughput DNA sequencing allow for a comprehensive analysis of bacterial genes that contribute to virulence in a specific infectious setting. Such information can yield new insights that affect decisions on how to best manage major public health issues such as the threat posed by increasing antimicrobial drug resistance. Much of the focus has been on the consequences of the selective advantage conferred on drug-resistant strains during antibiotic therapy. It is thought that the genetic and phenotypic changes that confer resistance also result in concomitant reductions in in vivo fitness, virulence, and transmission. However, experimental validation of this accepted paradigm is modest. Using a saturated transposon library of Pseudomonas aeruginosa, we identified genes across many functional categories and operons that contributed to maximal in vivo fitness during lung infections in animal models. Genes that bestowed both intrinsic and acquired antibiotic resistance provided a positive in vivo fitness advantage to P. aeruginosa during infection. We confirmed these findings in the pathogenic bacteria Acinetobacter baumannii and Vibrio cholerae using murine and rabbit infection models, respectively. Our results show that efforts to confront the worldwide increase in antibiotic resistance might be exacerbated by fitness advantages that enhance virulence in drug-resistant microbes.201526203082
9259110.9999Static recipient cells as reservoirs of antibiotic resistance during antibiotic therapy. How does taking the full course of antibiotics prevent antibiotic resistant bacteria establishing in patients? We address this question by testing the possibility that horizontal/lateral gene transfer (HGT) is critical for the accumulation of the antibiotic-resistance phenotype while bacteria are under antibiotic stress. Most antibiotics prevent bacterial reproduction, some by preventing de novo gene expression. Nevertheless, in some cases and at some concentrations, the effects of most antibiotics on gene expression may not be irreversible. If the stress is removed before the bacteria are cleared from the patients by normal turnover, gene expression restarts, converting the residual population to phenotypic resistance. Using mathematical models we investigate how static recipients of resistance genes carried by plasmids accumulate resistance genes, and how specifically an environment cycling between presence and absence of the antibiotic uniquely favors the evolution of horizontally mobile resistance genes. We found that the presence of static recipients can substantially increase the persistence of the plasmid and that this effect is most pronounced when the cost of carriage of the plasmid decreases the cell's growth rate by as much as a half or more. In addition, plasmid persistence can be enhanced even when conjugation rates are as low as half the rate required for the plasmid to persist as a parasite on its own.200616723146
9700120.9999Predation and selection for antibiotic resistance in natural environments. Genes encoding resistance to antibiotics appear, like the antibiotics themselves, to be ancient, originating long before the rise of the era of anthropogenic antibiotics. However, detailed understanding of the specific biological advantages of antibiotic resistance in natural environments is still lacking, thus limiting our efforts to prevent environmental influx of resistance genes. Here, we propose that antibiotic-resistant cells not only evade predation from antibiotic producers but also take advantage of nutrients released from cells that are killed by the antibiotic-producing bacteria. Thus, predation is potentially an important mechanism for driving antibiotic resistance during slow or stationary phase of growth when nutrients are deprived. This adds to explain the ancient nature and widespread occurrence of antibiotic resistance in natural environments unaffected by anthropogenic antibiotics. In particular, we suggest that nutrient-poor environments including indoor environments, for example, clean rooms and intensive care units may serve as a reservoir and source for antibiotic-producing as well as antibiotic-resistant bacteria.201626989434
4269130.9999Whole-cell modeling of E. coli colonies enables quantification of single-cell heterogeneity in antibiotic responses. Antibiotic resistance poses mounting risks to human health, as current antibiotics are losing efficacy against increasingly resistant pathogenic bacteria. Of particular concern is the emergence of multidrug-resistant strains, which has been rapid among Gram-negative bacteria such as Escherichia coli. A large body of work has established that antibiotic resistance mechanisms depend on phenotypic heterogeneity, which may be mediated by stochastic expression of antibiotic resistance genes. The link between such molecular-level expression and the population levels that result is complex and multi-scale. Therefore, to better understand antibiotic resistance, what is needed are new mechanistic models that reflect single-cell phenotypic dynamics together with population-level heterogeneity, as an integrated whole. In this work, we sought to bridge single-cell and population-scale modeling by building upon our previous experience in "whole-cell" modeling, an approach which integrates mathematical and mechanistic descriptions of biological processes to recapitulate the experimentally observed behaviors of entire cells. To extend whole-cell modeling to the "whole-colony" scale, we embedded multiple instances of a whole-cell E. coli model within a model of a dynamic spatial environment, allowing us to run large, parallelized simulations on the cloud that contained all the molecular detail of the previous whole-cell model and many interactive effects of a colony growing in a shared environment. The resulting simulations were used to explore the response of E. coli to two antibiotics with different mechanisms of action, tetracycline and ampicillin, enabling us to identify sub-generationally-expressed genes, such as the beta-lactamase ampC, which contributed greatly to dramatic cellular differences in steady-state periplasmic ampicillin and was a significant factor in determining cell survival.202337327241
3826140.9999Co-resistance: an opportunity for the bacteria and resistance genes. Co-resistance involves transfer of several genes into the same bacteria and/or the acquisition of mutations in different genetic loci affecting different antimicrobials whereas pleiotropic resistance implies the same genetic event affecting several antimicrobials. There is an increasing prevalence of isolates with co-resistance which are over-represented within the so-called high-risk clones. Compensatory events avoid fitness cost of co-resistance, even in the absence of antimicrobials. Nevertheless, they might be selected by different antimicrobials and a single agent might select co-resistant isolates. This process, named as co-selection, is not avoided with cycling or mixing strategies of antimicrobial use. Co-resistance and co-selection processes increase the opportunity for persistence of the bacteria and resistance genes and should be considered when designing strategies for decreasing antimicrobial resistance.201121840259
9614150.9999Antibiotic-Independent Adaptive Effects of Antibiotic Resistance Mutations. Antibiotic usage selects for the accumulation and spread of antibiotic-resistant bacteria. However, resistance can also accumulate in the absence of antibiotic exposure. Antibiotics are often designed to target widely distributed regulatory housekeeping genes. The targeting of such genes enables these antibiotics to be useful against a wider variety of pathogens. This review highlights work suggesting that regulatory housekeeping genes of the type targeted by many antibiotics function as hubs of adaptation to conditions unrelated to antibiotic exposure. As a result of this, some mutations to the regulatory housekeeping gene targets of antibiotics confer both antibiotic resistance and an adaptive effect unrelated to antibiotic exposure. Such antibiotic-independent adaptive effects of resistance mutations may substantially affect the dynamics of antibiotic resistance accumulation and spread.201728629950
4061160.9999Beyond serial passages: new methods for predicting the emergence of resistance to novel antibiotics. Market launching of a new antibiotic requires knowing in advance its benefits and possible risks, and among them how rapidly resistance will emerge and spread among bacterial pathogens. This information is not only useful from a public health point of view, but also for pharmaceutical industry, in order to reduce potential waste of resources in the development of a compound that might be discontinued at the short term because of resistance development. Most assays currently used for predicting the emergence of resistance are based on culturing the target bacteria by serial passages in the presence of increasing concentrations of antibiotics. Whereas these assays may be valuable for identifying mutations that might cause resistance, they are not useful to establish how fast resistance might appear, neither to address the risk of spread of resistance genes by horizontal gene transfer. In this article, we review recent information pertinent for a more accurate prediction on the emergence and dispersal of antibiotic resistance.201121835695
8998170.9999Density-dependent adaptive resistance allows swimming bacteria to colonize an antibiotic gradient. During antibiotic treatment, antibiotic concentration gradients develop. Little is know regarding the effects of antibiotic gradients on populations of nonresistant bacteria. Using a microfluidic device, we show that high-density motile Escherichia coli populations composed of nonresistant bacteria can, unexpectedly, colonize environments where a lethal concentration of the antibiotic kanamycin is present. Colonizing bacteria establish an adaptively resistant population, which remains viable for over 24 h while exposed to the antibiotic. Quantitative analysis of multiple colonization events shows that collectively swimming bacteria need to exceed a critical population density in order to successfully colonize the antibiotic landscape. After colonization, bacteria are not dormant but show both growth and swimming motility under antibiotic stress. Our results highlight the importance of motility and population density in facilitating adaptive resistance, and indicate that adaptive resistance may be a first step to the emergence of genetically encoded resistance in landscapes of antibiotic gradients.201626140531
9534180.9999Defining the Benefits of Antibiotic Resistance in Commensals and the Scope for Resistance Optimization. Antibiotic resistance is a major medical and public health challenge, characterized by global increases in the prevalence of resistant strains. The conventional view is that all antibiotic resistance is problematic, even when not in pathogens. Resistance in commensal bacteria poses risks, as resistant organisms can provide a reservoir of resistance genes that can be horizontally transferred to pathogens or may themselves cause opportunistic infections in the future. While these risks are real, we propose that commensal resistance can also generate benefits during antibiotic treatment of human infection, by promoting continued ecological suppression of pathogens. To define and illustrate this alternative conceptual perspective, we use a two-species mathematical model to identify the necessary and sufficient ecological conditions for beneficial resistance. We show that the benefits are limited to species (or strain) interactions where commensals suppress pathogen growth and are maximized when commensals compete with, rather than prey on or otherwise exploit pathogens. By identifying benefits of commensal resistance, we propose that rather than strictly minimizing all resistance, resistance management may be better viewed as an optimization problem. We discuss implications in two applied contexts: bystander (nontarget) selection within commensal microbiomes and pathogen treatment given polymicrobial infections. IMPORTANCE Antibiotic resistance is commonly viewed as universally costly, regardless of which bacterial cells express resistance. Here, we derive an opposing logic, where resistance in commensal bacteria can lead to reductions in pathogen density and improved outcomes on both the patient and public health scales. We use a mathematical model of commensal-pathogen interactions to define the necessary and sufficient conditions for beneficial resistance, highlighting the importance of reciprocal ecological inhibition to maximize the benefits of resistance. More broadly, we argue that determining the benefits as well as the costs of resistances in human microbiomes can transform resistance management from a minimization to an optimization problem. We discuss applied contexts and close with a review of key resistance optimization dimensions, including the magnitude, spectrum, and mechanism of resistance.202336475750
9436190.9998Phenotypic Resistance to Antibiotics. The development of antibiotic resistance is usually associated with genetic changes, either to the acquisition of resistance genes, or to mutations in elements relevant for the activity of the antibiotic. However, in some situations resistance can be achieved without any genetic alteration; this is called phenotypic resistance. Non-inherited resistance is associated to specific processes such as growth in biofilms, a stationary growth phase or persistence. These situations might occur during infection but they are not usually considered in classical susceptibility tests at the clinical microbiology laboratories. Recent work has also shown that the susceptibility to antibiotics is highly dependent on the bacterial metabolism and that global metabolic regulators can modulate this phenotype. This modulation includes situations in which bacteria can be more resistant or more susceptible to antibiotics. Understanding these processes will thus help in establishing novel therapeutic approaches based on the actual susceptibility shown by bacteria during infection, which might differ from that determined in the laboratory. In this review, we discuss different examples of phenotypic resistance and the mechanisms that regulate the crosstalk between bacterial metabolism and the susceptibility to antibiotics. Finally, information on strategies currently under development for diminishing the phenotypic resistance to antibiotics of bacterial pathogens is presented.201327029301