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938500.9986A generalised model for generalised transduction: the importance of co-evolution and stochasticity in phage mediated antimicrobial resistance transfer. Antimicrobial resistance is a major global challenge. Of particular concern are mobilizable elements that can transfer resistance genes between bacteria, leading to pathogens with new combinations of resistance. To date, mathematical models have largely focussed on transfer of resistance by plasmids, with fewer studies on transfer by bacteriophages. We aim to understand how best to model transfer of resistance by transduction by lytic phages. We show that models of lytic bacteriophage infection with empirically derived realistic phage parameters lead to low numbers of bacteria, which, in low population or localised environments, lead to extinction of bacteria and phage. Models that include antagonistic co-evolution of phage and bacteria produce more realistic results. Furthermore, because of these low numbers, stochastic dynamics are shown to be important, especially to spread of resistance. When resistance is introduced, resistance can sometimes be fixed, and at other times die out, with the probability of each outcome sensitive to bacterial and phage parameters. Specifically, that outcome most strongly depends on the baseline death rate of bacteria, with phage-mediated spread favoured in benign environments with low mortality over more hostile environments. We conclude that larger-scale models should consider spatial compartmentalisation and heterogeneous microenviroments, while encompassing stochasticity and co-evolution.202032490523
938910.9985Individual bacteria in structured environments rely on phenotypic resistance to phage. Bacteriophages represent an avenue to overcome the current antibiotic resistance crisis, but evolution of genetic resistance to phages remains a concern. In vitro, bacteria evolve genetic resistance, preventing phage adsorption or degrading phage DNA. In natural environments, evolved resistance is lower possibly because the spatial heterogeneity within biofilms, microcolonies, or wall populations favours phenotypic survival to lytic phages. However, it is also possible that the persistence of genetically sensitive bacteria is due to less efficient phage amplification in natural environments, the existence of refuges where bacteria can hide, and a reduced spread of resistant genotypes. Here, we monitor the interactions between individual planktonic bacteria in isolation in ephemeral refuges and bacteriophage by tracking the survival of individual cells. We find that in these transient spatial refuges, phenotypic resistance due to reduced expression of the phage receptor is a key determinant of bacterial survival. This survival strategy is in contrast with the emergence of genetic resistance in the absence of ephemeral refuges in well-mixed environments. Predictions generated via a mathematical modelling framework to track bacterial response to phages reveal that the presence of spatial refuges leads to fundamentally different population dynamics that should be considered in order to predict and manipulate the evolutionary and ecological dynamics of bacteria-phage interactions in naturally structured environments.202134637438
938720.9985Indirect Fitness Benefits Enable the Spread of Host Genes Promoting Costly Transfer of Beneficial Plasmids. Bacterial genes that confer crucial phenotypes, such as antibiotic resistance, can spread horizontally by residing on mobile genetic elements (MGEs). Although many mobile genes provide strong benefits to their hosts, the fitness consequences of the process of transfer itself are less clear. In previous studies, transfer has been interpreted as a parasitic trait of the MGEs because of its costs to the host but also as a trait benefiting host populations through the sharing of a common gene pool. Here, we show that costly donation is an altruistic act when it spreads beneficial MGEs favoured when it increases the inclusive fitness of donor ability alleles. We show mathematically that donor ability can be selected when relatedness at the locus modulating transfer is sufficiently high between donor and recipients, ensuring high frequency of transfer between cells sharing donor alleles. We further experimentally demonstrate that either population structure or discrimination in transfer can increase relatedness to a level selecting for chromosomal transfer alleles. Both mechanisms are likely to occur in natural environments. The simple process of strong dilution can create sufficient population structure to select for donor ability. Another mechanism observed in natural isolates, discrimination in transfer, can emerge through coselection of transfer and discrimination alleles. Our work shows that horizontal gene transfer in bacteria can be promoted by bacterial hosts themselves and not only by MGEs. In the longer term, the success of cells bearing beneficial MGEs combined with biased transfer leads to an association between high donor ability, discrimination, and mobile beneficial genes. However, in conditions that do not select for altruism, host bacteria promoting transfer are outcompeted by hosts with lower transfer rate, an aspect that could be relevant in the fight against the spread of antibiotic resistance.201627270455
938430.9985Bacterial evolution and the cost of antibiotic resistance. Bacteria clearly benefit from the possession of an antibiotic resistance gene when the corresponding antibiotic is present. But do resistant bacteria suffer a cost of resistance (i.e., a reduction in fitness) when the antibiotic is absent? If so, then one strategy to control the spread of resistance would be to suspend the use of a particular antibiotic until resistant genotypes declined to low frequency. Numerous studies have indeed shown that resistant genotypes are less fit than their sensitive counterparts in the absence of antibiotic, indicating a cost of resistance. But there is an important caveat: these studies have put resistance genes into naive bacteria, which have no evolutionary history of association with the resistance genes. An important question, therefore, is whether bacteria can overcome the cost of resistance by evolving adaptations that counteract the harmful side-effects of resistance genes. In fact, several experiments (in vitro and in vivo) show that the cost of antibiotic resistance can be substantially diminished, even eliminated, by evolutionary changes in bacteria over rather short periods of time. As a consequence, it becomes increasingly difficult to eliminate resistant genotypes simply by suspending the use of antibiotics.199810943373
938640.9984Bacteriophages limit the existence conditions for conjugative plasmids. Bacteriophages are a major cause of bacterial mortality and impose strong selection on natural bacterial populations, yet their effects on the dynamics of conjugative plasmids have rarely been tested. We combined experimental evolution, mathematical modeling, and individual-based simulations to explain how the ecological and population genetics effects of bacteriophages upon bacteria interact to determine the dynamics of conjugative plasmids and their persistence. The ecological effects of bacteriophages on bacteria are predicted to limit the existence conditions for conjugative plasmids, preventing persistence under weak selection for plasmid accessory traits. Experiments showed that phages drove faster extinction of plasmids in environments where the plasmid conferred no benefit, but they also revealed more complex effects of phages on plasmid dynamics under these conditions, specifically, the temporary maintenance of plasmids at fixation followed by rapid loss. We hypothesized that the population genetic effects of bacteriophages, specifically, selection for phage resistance mutations, may have caused this. Further mathematical modeling and individual-based simulations supported our hypothesis, showing that conjugative plasmids may hitchhike with phage resistance mutations in the bacterial chromosome. IMPORTANCE: Conjugative plasmids are infectious loops of DNA capable of transmitting DNA between bacterial cells and between species. Because plasmids often carry extra genes that allow bacteria to live in otherwise-inhospitable environments, their dynamics are central to understanding bacterial adaptive evolution. The plasmid-bacterium interaction has typically been studied in isolation, but in natural bacterial communities, bacteriophages, viruses that infect bacteria, are ubiquitous. Using experiments, mathematical models, and computer simulations we show that bacteriophages drive plasmid dynamics through their ecological and evolutionary effects on bacteria and ultimately limit the conditions allowing plasmid existence. These results advance our understanding of bacterial adaptation and show that bacteriophages could be used to select against plasmids carrying undesirable traits, such as antibiotic resistance.201526037122
938250.9984The evolution of mutator genes in bacterial populations: the roles of environmental change and timing. Recent studies have found high frequencies of bacteria with increased genomic rates of mutation in both clinical and laboratory populations. These observations may seem surprising in light of earlier experimental and theoretical studies. Mutator genes (genes that elevate the genomic mutation rate) are likely to induce deleterious mutations and thus suffer an indirect selective disadvantage; at the same time, bacteria carrying them can increase in frequency only by generating beneficial mutations at other loci. When clones carrying mutator genes are rare, however, these beneficial mutations are far more likely to arise in members of the much larger nonmutator population. How then can mutators become prevalent? To address this question, we develop a model of the population dynamics of bacteria confronted with ever-changing environments. Using analytical and simulation procedures, we explore the process by which initially rare mutator alleles can rise in frequency. We demonstrate that subsequent to a shift in environmental conditions, there will be relatively long periods of time during which the mutator subpopulation can produce a beneficial mutation before the ancestral subpopulations are eliminated. If the beneficial mutation arises early enough, the overall frequency of mutators will climb to a point higher than when the process began. The probability of producing a subsequent beneficial mutation will then also increase. In this manner, mutators can increase in frequency over successive selective sweeps. We discuss the implications and predictions of these theoretical results in relation to antibiotic resistance and the evolution of mutation rates.200312871898
938360.9984The cost of antibiotic resistance--from the perspective of a bacterium. The possession of an antibiotic resistance gene clearly benefits a bacterium when the corresponding antibiotic is present. But does the resistant bacterium suffer a cost of resistance (i.e. a reduction in fitness) when the antibiotic is absent? If so, then one strategy to control the spread of resistance would be to suspend the use of a particular antibiotic until resistant genotypes declined to low frequency. Numerous studies have indeed shown that resistant genotypes are less fit than their sensitive counterparts in the absence of antibiotic, indicating a cost of resistance. But there is an important caveat: these studies have put antibiotic resistance genes into naïve bacteria, which have no evolutionary history of association with the resistance genes. An important question, therefore, is whether bacteria can overcome the cost of resistance by evolving adaptations that counteract the harmful side-effects of resistance genes. In fact, several experiments have shown that the cost of antibiotic resistance may be substantially diminished, even eliminated, by evolutionary changes in bacteria over rather short periods of time. As a consequence of this adaptation of bacteria to their resistance genes, it becomes increasingly difficult to eliminate resistant genotypes simply by suspending the use of antibiotics.19979189639
958070.9984Antibiotic resistance in bacterial communities. Bacteria are single-celled organisms, but the survival of microbial communities relies on complex dynamics at the molecular, cellular, and ecosystem scales. Antibiotic resistance, in particular, is not just a property of individual bacteria or even single-strain populations, but depends heavily on the community context. Collective community dynamics can lead to counterintuitive eco-evolutionary effects like survival of less resistant bacterial populations, slowing of resistance evolution, or population collapse, yet these surprising behaviors are often captured by simple mathematical models. In this review, we highlight recent progress - in many cases, advances driven by elegant combinations of quantitative experiments and theoretical models - in understanding how interactions between bacteria and with the environment affect antibiotic resistance, from single-species populations to multispecies communities embedded in an ecosystem.202337054512
949080.9984The superbugs: evolution, dissemination and fitness. Since the introduction of antibiotics, bacteria have not only evolved elegant resistance mechanisms to thwart their effect, but have also evolved ways in which to disseminate themselves or their resistance genes to other susceptible bacteria. During the past few years, research has revealed not only how such resistance mechanisms have been able to evolve and to rapidly disseminate, but also how bacteria have, in some cases, been able to adapt to this new burden of resistance with little or no cost to their fitness. Such adaptations make the control of these superbugs all the more difficult.199810066531
937690.9984Historical Contingency Drives Compensatory Evolution and Rare Reversal of Phage Resistance. Bacteria and lytic viruses (phages) engage in highly dynamic coevolutionary interactions over time, yet we have little idea of how transient selection by phages might shape the future evolutionary trajectories of their host populations. To explore this question, we generated genetically diverse phage-resistant mutants of the bacterium Pseudomonas syringae. We subjected the panel of mutants to prolonged experimental evolution in the absence of phages. Some populations re-evolved phage sensitivity, whereas others acquired compensatory mutations that reduced the costs of resistance without altering resistance levels. To ask whether these outcomes were driven by the initial genetic mechanisms of resistance, we next evolved independent replicates of each individual mutant in the absence of phages. We found a strong signature of historical contingency: some mutations were highly reversible across replicate populations, whereas others were highly entrenched. Through whole-genome sequencing of bacteria over time, we also found that populations with the same resistance gene acquired more parallel sets of mutations than populations with different resistance genes, suggesting that compensatory adaptation is also contingent on how resistance initially evolved. Our study identifies an evolutionary ratchet in bacteria-phage coevolution and may explain previous observations that resistance persists over time in some bacterial populations but is lost in others. We add to a growing body of work describing the key role of phages in the ecological and evolutionary dynamics of their host communities. Beyond this specific trait, our study provides a new insight into the genetic architecture of historical contingency, a crucial component of interpreting and predicting evolution.202235994371
9481100.9984Genetic linkage and horizontal gene transfer, the roots of the antibiotic multi-resistance problem. Bacteria carrying resistance genes for many antibiotics are moving beyond the clinic into the community, infecting otherwise healthy people with untreatable and frequently fatal infections. This state of affairs makes it increasingly important that we understand the sources of this problem in terms of bacterial biology and ecology and also that we find some new targets for drugs that will help control this growing epidemic. This brief and eclectic review takes the perspective that we have too long thought about the problem in terms of treatment with or resistance to a single antibiotic at a time, assuming that dissemination of the resistance gene was affected by simple vertical inheritance. In reality antibiotic resistance genes are readily transferred horizontally, even to and from distantly related bacteria. The common agents of bacterial gene transfer are described and also one of the processes whereby nonantibiotic chemicals, specifically toxic metals, in the environment can select for and enrich bacteria with antibiotic multiresistance. Lastly, some speculation is offered on broadening our perspective on this problem to include drugs directed at compromising the ability of the mobile elements themselves to replicate, transfer, and recombine, that is, the three "infrastructure" processes central to the movement of genes among bacteria.200617127524
9534110.9984Defining 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
9581120.9983Lateral gene transfer, bacterial genome evolution, and the Anthropocene. Lateral gene transfer (LGT) has significantly influenced bacterial evolution since the origins of life. It helped bacteria generate flexible, mosaic genomes and enables individual cells to rapidly acquire adaptive phenotypes. In turn, this allowed bacteria to mount strong defenses against human attempts to control their growth. The widespread dissemination of genes conferring resistance to antimicrobial agents has precipitated a crisis for modern medicine. Our actions can promote increased rates of LGT and also provide selective forces to fix such events in bacterial populations. For instance, the use of selective agents induces the bacterial SOS response, which stimulates LGT. We create hotspots for lateral transfer, such as wastewater systems, hospitals, and animal production facilities. Conduits of gene transfer between humans and animals ensure rapid dissemination of recent transfer events, as does modern transport and globalization. As resistance to antibacterial compounds becomes universal, there is likely to be increasing selection pressure for phenotypes with adverse consequences for human welfare, such as enhanced virulence, pathogenicity, and transmission. Improved understanding of the ecology of LGT could help us devise strategies to control this fundamental evolutionary process.201727706829
4273130.9983Mathematical modeling on bacterial resistance to multiple antibiotics caused by spontaneous mutations. We formulate a mathematical model that describes the population dynamics of bacteria exposed to multiple antibiotics simultaneously, assuming that acquisition of resistance is through mutations due to antibiotic exposure. Qualitative analysis reveals the existence of a free-bacteria equilibrium, resistant-bacteria equilibrium and an endemic equilibrium where both bacteria coexist.201424467935
9701140.9983Environmental factors influencing the development and spread of antibiotic resistance. Antibiotic resistance and its wider implications present us with a growing healthcare crisis. Recent research points to the environment as an important component for the transmission of resistant bacteria and in the emergence of resistant pathogens. However, a deeper understanding of the evolutionary and ecological processes that lead to clinical appearance of resistance genes is still lacking, as is knowledge of environmental dispersal barriers. This calls for better models of how resistance genes evolve, are mobilized, transferred and disseminated in the environment. Here, we attempt to define the ecological and evolutionary environmental factors that contribute to resistance development and transmission. Although mobilization of resistance genes likely occurs continuously, the great majority of such genetic events do not lead to the establishment of novel resistance factors in bacterial populations, unless there is a selection pressure for maintaining them or their fitness costs are negligible. To enable preventative measures it is therefore critical to investigate under what conditions and to what extent environmental selection for resistance takes place. In addition, understanding dispersal barriers is not only key to evaluate risks, but also to prevent resistant pathogens, as well as novel resistance genes, from reaching humans.201829069382
9388150.9983Suboptimal environmental conditions prolong phage epidemics in bacterial populations. Infections by filamentous phages, which are usually nonlethal to the bacterial cells, influence bacterial fitness in various ways. While phage-encoded accessory genes, for example virulence genes, can be highly beneficial, the production of viral particles is energetically costly and often reduces bacterial growth. Consequently, if costs outweigh benefits, bacteria evolve resistance, which can shorten phage epidemics. Abiotic conditions are known to influence the net-fitness effect for infected bacteria. Their impact on the dynamics and trajectories of host resistance evolution, however, remains yet unknown. To address this, we experimentally evolved the bacterium Vibrio alginolyticus in the presence of a filamentous phage at three different salinity levels, that is (1) ambient, (2) 50% reduction and (3) fluctuations between reduced and ambient. In all three salinities, bacteria rapidly acquired resistance through super infection exclusion (SIE), whereby phage-infected cells acquired immunity at the cost of reduced growth. Over time, SIE was gradually replaced by evolutionary fitter surface receptor mutants (SRM). This replacement was significantly faster at ambient and fluctuating conditions compared with the low saline environment. Our experimentally parameterized mathematical model explains that suboptimal environmental conditions, in which bacterial growth is slower, slow down phage resistance evolution ultimately prolonging phage epidemics. Our results may explain the high prevalence of filamentous phages in natural environments where bacteria are frequently exposed to suboptimal conditions and constantly shifting selections regimes. Thus, our future ocean may favour the emergence of phage-born pathogenic bacteria and impose a greater risk for disease outbreaks, impacting not only marine animals but also humans.202437337348
9241160.9983Evolutionary Mechanisms Shaping the Maintenance of Antibiotic Resistance. Antibiotics target essential cellular functions but bacteria can become resistant by acquiring either exogenous resistance genes or chromosomal mutations. Resistance mutations typically occur in genes encoding essential functions; these mutations are therefore generally detrimental in the absence of drugs. However, bacteria can reduce this handicap by acquiring additional mutations, known as compensatory mutations. Genetic interactions (epistasis) either with the background or between resistances (in multiresistant bacteria) dramatically affect the fitness cost of antibiotic resistance and its compensation, therefore shaping dissemination of antibiotic resistance mutations. This Review summarizes current knowledge on the evolutionary mechanisms influencing maintenance of resistance mediated by chromosomal mutations, focusing on their fitness cost, compensatory evolution, epistasis, and the effect of the environment on these processes.201829439838
9494170.9983Within-Host Mathematical Models of Antibiotic Resistance. Mathematical models have been used to study the spread of infectious diseases from person to person. More recently studies are developing within-host modeling which provides an understanding of how pathogens-bacteria, fungi, parasites, or viruses-develop, spread, and evolve inside a single individual and their interaction with the host's immune system.Such models have the potential to provide a more detailed and complete description of the pathogenesis of diseases within-host and identify other influencing factors that may not be detected otherwise. Mathematical models can be used to aid understanding of the global antibiotic resistance (ABR) crisis and identify new ways of combating this threat.ABR occurs when bacteria respond to random or selective pressures and adapt to new environments through the acquisition of new genetic traits. This is usually through the acquisition of a piece of DNA from other bacteria, a process called horizontal gene transfer (HGT), the modification of a piece of DNA within a bacterium, or through. Bacteria have evolved mechanisms that enable them to respond to environmental threats by mutation, and horizontal gene transfer (HGT): conjugation; transduction; and transformation. A frequent mechanism of HGT responsible for spreading antibiotic resistance on the global scale is conjugation, as it allows the direct transfer of mobile genetic elements (MGEs). Although there are several MGEs, the most important MGEs which promote the development and rapid spread of antimicrobial resistance genes in bacterial populations are plasmids and transposons. Each of the resistance-spread-mechanisms mentioned above can be modeled allowing us to understand the process better and to define strategies to reduce resistance.202438949703
9000180.9983Modelling 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
4278190.9983Effective antibiotic dosing in the presence of resistant strains. Mathematical models can be very useful in determining efficient and successful antibiotic dosing regimens. In this study, we consider the problem of determining optimal antibiotic dosing when bacteria resistant to antibiotics are present in addition to susceptible bacteria. We consider two different models of resistance acquisition, both involve the horizontal transfer (HGT) of resistant genes from a resistant to a susceptible strain. Modeling studies on HGT and study of optimal antibiotic dosing protocols in the literature, have been mostly focused on transfer of resistant genes via conjugation, with few studies on HGT via transformation. We propose a deterministic ODE based model of resistance acquisition via transformation, followed by a model that takes into account resistance acquisition through conjugation. Using a numerical optimization algorithm to determine the 'best' antibiotic dosing strategy. To illustrate our optimization method, we first consider optimal dosing when all the bacteria are susceptible to the antibiotic. We then consider the case where resistant strains are present. We note that constant periodic dosing may not always succeed in eradicating the bacteria while an optimal dosing protocol is successful. We determine the optimal dosing strategy in two different scenarios: one where the total bacterial population is to be minimized, and the next where we want to minimize the bacterial population at the end of the dosing period. We observe that the optimal strategy in the first case involves high initial dosing with dose tapering as time goes on, while in the second case, the optimal dosing strategy is to increase the dosing at the beginning of the dose cycles followed by a possible dose tapering. As a follow up study we intend to look at models where 'persistent' bacteria may be present in additional to resistant and susceptible strain and determine the optimal dosing protocols in this case.202236215219