# | Rank | Similarity | Title + Abs. | Year | PMID |
|---|---|---|---|---|---|
| 0 | 1 | 2 | 3 | 4 | 5 |
| 9693 | 0 | 1.0000 | Antibody-mediated crosslinking of gut bacteria hinders the spread of antibiotic resistance. The body is home to a diverse microbiota, mainly in the gut. Resistant bacteria are selected by antibiotic treatments, and once resistance becomes widespread in a population of hosts, antibiotics become useless. Here, we develop a multiscale model of the interaction between antibiotic use and resistance spread in a host population, focusing on an important aspect of within-host immunity. Antibodies secreted in the gut enchain bacteria upon division, yielding clonal clusters of bacteria. We demonstrate that immunity-driven bacteria clustering can hinder the spread of a novel resistant bacterial strain in a host population. We quantify this effect both in the case where resistance preexists and in the case where acquiring a new resistance mutation is necessary for the bacteria to spread. We further show that the reduction of spread by clustering can be countered when immune hosts are silent carriers, and are less likely to get treated, and/or have more contacts. We demonstrate the robustness of our findings to including stochastic within-host bacterial growth, a fitness cost of resistance, and its compensation. Our results highlight the importance of interactions between immunity and the spread of antibiotic resistance, and argue in the favor of vaccine-based strategies to combat antibiotic resistance. | 2019 | 30957218 |
| 9492 | 1 | 0.9999 | The 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. | 2018 | 29191398 |
| 9614 | 2 | 0.9999 | Antibiotic-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. | 2017 | 28629950 |
| 9534 | 3 | 0.9998 | Defining 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. | 2023 | 36475750 |
| 9463 | 4 | 0.9998 | Predictable and unpredictable evolution of antibiotic resistance. Evolution of bacteria towards antibiotic resistance is unavoidable as it represents a particular aspect of the general evolution of bacteria. Thus, at the very best, the only hope we can have in the field of resistance is to delay dissemination of resistant bacteria or resistance genes. Resistance to antibiotics in bacteria can result from mutations in resident structural or regulatory genes or from horizontal acquisition of foreign genetic information. In this review, we will consider the predictable future of the relationship between bacteria and antibiotics. | 2008 | 18397243 |
| 9485 | 5 | 0.9998 | Evolution of Drug Resistance in Bacteria. Resistance to antibiotics is an important and timely problem of contemporary medicine. Rapid evolution of resistant bacteria calls for new preventive measures to slow down this process, and a longer-term progress cannot be achieved without a good understanding of the mechanisms through which drug resistance is acquired and spreads in microbial populations. Here, we discuss recent experimental and theoretical advances in our knowledge how the dynamics of microbial populations affects the evolution of antibiotic resistance . We focus on the role of spatial and temporal drug gradients and show that in certain situations bacteria can evolve de novo resistance within hours. We identify factors that lead to such rapid onset of resistance and discuss their relevance for bacterial infections. | 2016 | 27193537 |
| 9472 | 6 | 0.9998 | Bacteriophage and Bacterial Susceptibility, Resistance, and Tolerance to Antibiotics. Bacteriophages, viruses that infect and replicate within bacteria, impact bacterial responses to antibiotics in complex ways. Recent studies using lytic bacteriophages to treat bacterial infections (phage therapy) demonstrate that phages can promote susceptibility to chemical antibiotics and that phage/antibiotic synergy is possible. However, both lytic and lysogenic bacteriophages can contribute to antimicrobial resistance. In particular, some phages mediate the horizontal transfer of antibiotic resistance genes between bacteria via transduction and other mechanisms. In addition, chronic infection filamentous phages can promote antimicrobial tolerance, the ability of bacteria to persist in the face of antibiotics. In particular, filamentous phages serve as structural elements in bacterial biofilms and prevent the penetration of antibiotics. Over time, these contributions to antibiotic tolerance favor the selection of resistance clones. Here, we review recent insights into bacteriophage contributions to antibiotic susceptibility, resistance, and tolerance. We discuss the mechanisms involved in these effects and address their impact on bacterial fitness. | 2022 | 35890320 |
| 4276 | 7 | 0.9998 | Phages 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. | 2012 | 23028398 |
| 4275 | 8 | 0.9998 | Antibiotic resistance and its cost: is it possible to reverse resistance? Most antibiotic resistance mechanisms are associated with a fitness cost that is typically observed as a reduced bacterial growth rate. The magnitude of this cost is the main biological parameter that influences the rate of development of resistance, the stability of the resistance and the rate at which the resistance might decrease if antibiotic use were reduced. These findings suggest that the fitness costs of resistance will allow susceptible bacteria to outcompete resistant bacteria if the selective pressure from antibiotics is reduced. Unfortunately, the available data suggest that the rate of reversibility will be slow at the community level. Here, we review the factors that influence the fitness costs of antibiotic resistance, the ways by which bacteria can reduce these costs and the possibility of exploiting them. | 2010 | 20208551 |
| 4273 | 9 | 0.9998 | Mathematical 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. | 2014 | 24467935 |
| 9494 | 10 | 0.9998 | Within-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. | 2024 | 38949703 |
| 8999 | 11 | 0.9998 | Growth-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. | 2022 | 35311576 |
| 9621 | 12 | 0.9998 | Bacterial biodiversity drives the evolution of CRISPR-based phage resistance. About half of all bacteria carry genes for CRISPR-Cas adaptive immune systems(1), which provide immunological memory by inserting short DNA sequences from phage and other parasitic DNA elements into CRISPR loci on the host genome(2). Whereas CRISPR loci evolve rapidly in natural environments(3,4), bacterial species typically evolve phage resistance by the mutation or loss of phage receptors under laboratory conditions(5,6). Here we report how this discrepancy may in part be explained by differences in the biotic complexity of in vitro and natural environments(7,8). Specifically, by using the opportunistic pathogen Pseudomonas aeruginosa and its phage DMS3vir, we show that coexistence with other human pathogens amplifies the fitness trade-offs associated with the mutation of phage receptors, and therefore tips the balance in favour of the evolution of CRISPR-based resistance. We also demonstrate that this has important knock-on effects for the virulence of P. aeruginosa, which became attenuated only if the bacteria evolved surface-based resistance. Our data reveal that the biotic complexity of microbial communities in natural environments is an important driver of the evolution of CRISPR-Cas adaptive immunity, with key implications for bacterial fitness and virulence. | 2019 | 31645729 |
| 9686 | 13 | 0.9998 | Selective pressures for public antibiotic resistance. The rapid increase of antibiotic-resistant pathogens is severely limiting our current treatment possibilities. An important subset of the resistance mechanisms conferring antibiotic resistance have public effects, allowing otherwise susceptible bacteria to also survive antibiotic treatment. As susceptible bacteria can survive treatment without bearing the metabolic cost of producing the resistance mechanism, there is potential to increase their relative frequency in the population and, as such, select against resistant bacteria. Multiple studies showed that this altered selection for resistance is dependent on various environmental and treatment parameters. In this review, we provide a comprehensive overview of their most important findings and describe the main factors impacting the selection for resistance. In-depth understanding of the driving forces behind selection can aid in the design and implementation of alternative treatments which limit the risk of resistance development. | 2025 | 39158370 |
| 9456 | 14 | 0.9998 | Antibiotic treatments and microbes in the gut. Antibiotic therapies are important in combating disease-causing microorganisms and maintaining host health. It is widely accepted that exposure of the gut microbiota to antibiotics can lead to decreased susceptibility and the development of multi-drug-resistant disease-causing organisms, which can be a major clinical problem. It is also important to consider that antibiotics not only target pathogenic bacteria in the gut, but also can have damaging effects on the ecology of commensal species. This can reduce intrinsic colonization resistance and contribute to problems with antibiotic resistance, including lateral transfer of resistance genes. Our knowledge of the impact of antibiotic treatment on the ecology of the normal microbiota has been increased by recent advances in molecular methods and use of in vitro model systems to investigate the impact of antibiotics on the biodiversity of gut populations and the spread of antibiotic resistance. These highlight the need for more detailed structural and functional information on the long-term antibiotic-associated alterations in the gut microbiome, and spread of antibiotic resistance genes. This will be crucial for the development of strategies, such as targeted therapeutics, probiotics, prebiotics and synbiotics, to prevent perturbations in the gut microbiota, the restoration of beneficial species and improvements in host health. | 2014 | 24471523 |
| 9491 | 15 | 0.9998 | Mutation and evolution of antibiotic resistance: antibiotics as promoters of antibiotic resistance? Antibiotic resistance appearance and spread have been classically considered the result of a process of natural selection, directed by the use of antibiotics. Bacteria, that have to face the antibiotic challenge, evolve to acquire resistance and, under this strong selective pressure, only the fittest survive, leading to the spread of resistance mechanisms and resistant clones. Horizontal transference of resistance mechanisms seems to be the main way of antibiotic resistance acquisition. Nevertheless, recent findings on hypermutability and antibiotic-induced hypermutation in bacteria have modified the landscape. Here, we present a review of the last data on molecular mechanisms of hypermutability in bacteria and their relationship with the acquisition of antibiotic resistance. Finally, we discuss the possibility that antibiotics may act not only as selectors for antibiotic resistant bacteria but also as resistance promoters. | 2002 | 12102604 |
| 4065 | 16 | 0.9998 | The role of the natural environment in the emergence of antibiotic resistance in gram-negative bacteria. During the past 10 years, multidrug-resistant Gram-negative Enterobacteriaceae have become a substantial challenge to infection control. It has been suggested by clinicians that the effectiveness of antibiotics is in such rapid decline that, depending on the pathogen concerned, their future utility can be measured in decades or even years. Unless the rise in antibiotic resistance can be reversed, we can expect to see a substantial rise in incurable infection and fatality in both developed and developing regions. Antibiotic resistance develops through complex interactions, with resistance arising by de-novo mutation under clinical antibiotic selection or frequently by acquisition of mobile genes that have evolved over time in bacteria in the environment. The reservoir of resistance genes in the environment is due to a mix of naturally occurring resistance and those present in animal and human waste and the selective effects of pollutants, which can co-select for mobile genetic elements carrying multiple resistant genes. Less attention has been given to how anthropogenic activity might be causing evolution of antibiotic resistance in the environment. Although the economics of the pharmaceutical industry continue to restrict investment in novel biomedical responses, action must be taken to avoid the conjunction of factors that promote evolution and spread of antibiotic resistance. | 2013 | 23347633 |
| 9701 | 17 | 0.9998 | Environmental 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. | 2018 | 29069382 |
| 9611 | 18 | 0.9998 | Parallel 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. | 2022 | 35188102 |
| 9386 | 19 | 0.9998 | Bacteriophages 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. | 2015 | 26037122 |