Combining mathematical models and statistical methods to understand and predict the dynamics of antibiotic-sensitive mutants in a population of resistant bacteria during experimental evolution

Costs of antibiotic resistance genes depend on host strain and environment and can influence community composition

Antibiotic resistance genes (ARGs) benefit host bacteria in environments containing corresponding antibiotics, but it is less clear how they are maintained in environments where antibiotic selection is weak or sporadic. In particular, few studies have measured if the direct effect of ARGs on host fitness is fixed or if it depends on the host strain, perhaps marking some ARG-host combinations as selective refuges that can maintain ARGs in the absence of antibiotic selection. We quantified the fitness effects of six ARGs in 11 diverse Escherichia spp. strains. Three ARGs (blaTEM-116, cat and dfrA5, encoding resistance to β-lactams, chloramphenicol, and trimethoprim, respectively) imposed an overall cost, but all ARGs had an effect in at least one host strain, reflecting a significant strain interaction effect. A simulation predicts these interactions can cause the success of ARGs to depend on available host strains, and, to a lesser extent, can cause host strain success to depend on the ARGs present in a community. These results indicate the importance of considering ARG effects across different host strains, and especially the potential of refuge strains to allow resistance to persist in the absence of direct selection, in efforts to understand resistance dynamics.

Inferring stability and persistence in the vaginal microbiome: A stochastic model of ecological dynamics

The interplay of stochastic and ecological processes that govern the establishment and persistence of host-associated microbial communities is not well understood. Here we illustrate the conceptual and practical advantages of fitting stochastic population dynamics models to multi-species bacterial time series data. We show how the stability properties, fluctuation regimes and persistence probabilities of human vaginal microbial communities can be better understood by explicitly accommodating three sources of variability in ecological stochastic models of multi-species abundances: 1) stochastic biotic and abiotic forces, 2) ecological feedback and 3) sampling error. Rooting our modeling tool in stochastic population dynamics modeling theory was key to apply standardized measures of a community's reaction to environmental variation that ultimately depends on the nature and intensity of the intra-specific and inter-specific interaction strengths. Using estimates of model parameters, we developed a Risk Prediction Monitoring (RPM) tool that estimates temporal changes in persistence probabilities for any bacterial group of interest. This method mirrors approaches that are often used in conservation biology in which a measure of extinction risks is periodically updated with any change in a population or community. Additionally, we show how to use estimates of interaction strengths and persistence probabilities to formulate hypotheses regarding the molecular mechanisms and genetic composition that underpin different types of interactions. Instead of seeking a definition of "dysbiosis" we propose to translate concepts of theoretical ecology and conservation biology methods into practical approaches for the management of human-associated bacterial communities.

Interaction with a phage gene underlie costs of a β-lactamase

The fitness cost of an antibiotic resistance gene (ARG) can differ across host strains, creating refuges that allow the maintenance of an ARG in the absence of direct selection for its resistance phenotype. Despite the importance of such ARG-host interactions for predicting ARG dynamics, the basis of ARG fitness costs and their variability between hosts are not well understood. We determined the genetic basis of a host-dependent cost of a β-lactamase, blaTEM-116*, that conferred a significant cost in one Escherichia coli strain but was close to neutral in 11 other Escherichia spp. strains. Selection of a blaTEM-116*-encoding plasmid in the strain in which it initially had a high cost resulted in rapid and parallel compensation for that cost through mutations in a P1-like phage gene, relAP1. When the wild-type relAP1 gene was added to a strain in which it was not present and in which blaTEM-116* was neutral, it caused the ARG to become costly. Thus, relAP1 is both necessary and sufficient to explain blaTEM-116* costs in at least some host backgrounds. To our knowledge, these findings represent the first demonstrated case of the cost of an ARG being influenced by a genetic interaction with a phage gene. The interaction between a phage gene and a plasmid-borne ARG highlights the complexity of selective forces determining the maintenance and spread of ARGs and, by extension, encoding phage and plasmids in natural bacterial communities.IMPORTANCEAntibiotic resistance genes (ARGs) play a major role in the increasing problem of antibiotic resistance in clinically relevant bacteria. Selection of these genes occurs in the presence of antibiotics, but their eventual success also depends on the sometimes substantial costs they impose on host bacteria in antibiotic-free environments. We evolved an ARG that confers resistance to penicillin-type antibiotics in one host in which it did confer a cost and in one host in which it did not. We found that costs were rapidly and consistently reduced through parallel genetic changes in a gene encoded by a phage that was infecting the costly host. The unmutated version of this gene was sufficient to cause the ARG to confer a cost in a host in which it was originally neutral, demonstrating an antagonism between the two genetic elements and underlining the range and complexity of pressures determining ARG dynamics in natural populations.

A mathematician's guide to plasmids: an introduction to plasmid biology for modellers

Plasmids, extrachromosomal DNA molecules commonly found in bacterial and archaeal cells, play an important role in bacterial genetics and evolution. Our understanding of plasmid biology has been furthered greatly by the development of mathematical models, and there are many questions about plasmids that models would be useful in answering. In this review, we present an introductory, yet comprehensive, overview of the biology of plasmids suitable for modellers unfamiliar with plasmids who want to get up to speed and to begin working on plasmid-related models. In addition to reviewing the diversity of plasmids and the genes they carry, their key physiological functions, and interactions between plasmid and host, we also highlight selected plasmid topics that may be of particular interest to modellers and areas where there is a particular need for theoretical development. The world of plasmids holds a great variety of subjects that will interest mathematical biologists, and introducing new modellers to the subject will help to expand the existing body of plasmid theory.

Biofilms preserve the transmissibility of a multi-drug resistance plasmid

Self-transmissible multidrug resistance (MDR) plasmids are a major health concern because they can spread antibiotic resistance to pathogens. Even though most pathogens form biofilms, little is known about how MDR plasmids persist and evolve in biofilms. We hypothesize that (i) biofilms act as refugia of MDR plasmids by retaining them in the absence of antibiotics longer than well-mixed planktonic populations and that (ii) the evolutionary trajectories that account for the improvement of plasmid persistence over time differ between biofilms and planktonic populations. In this study, we evolved Acinetobacter baumannii with an MDR plasmid in biofilm and planktonic populations with and without antibiotic selection. In the absence of selection, biofilm populations were better able to maintain the MDR plasmid than planktonic populations. In planktonic populations, plasmid persistence improved rapidly but was accompanied by a loss of genes required for the horizontal transfer of plasmids. In contrast, in biofilms, most plasmids retained their transfer genes, but on average, plasmid, persistence improved less over time. Our results showed that biofilms can act as refugia of MDR plasmids and favor the horizontal mode of plasmid transfer, which has important implications for the spread of MDR.

Histone-Like Nucleoid Structuring Protein Modulates the Fitness of tet(X4)-Bearing IncX1 Plasmids in Gram-Negative Bacteria

The emergence of plasmid-mediated tigecycline resistance gene tet(X4) poses a challenging threat to public health. Based on the analysis of tet(X4)-positive plasmids in the NCBI database, we found that the IncX1-type plasmid is one of the most common vectors for spreading tet(X4) gene, but the mechanisms by which these plasmids adapt to host bacteria and maintain the persistence of antibiotic resistance genes (ARGs) remain unclear. Herein, we investigated the underlying mechanisms of how host bacteria modulate the fitness cost of IncX1 plasmids carrying tet(X4) gene. Interestingly, we found that the tet(X4)-bearing IncX1 plasmids encoding H-NS protein imposed low or no fitness cost in Escherichia coli and Klebsiella pneumoniae; instead, they partially promoted the virulence and biofilm formation in host bacteria. Regression analysis revealed that the expression of hns gene in plasmids was positively linked to the relative fitness of host bacteria. Furthermore, when pCE2::hns was introduced, the fitness of tet(X4)-positive IncX1 plasmid pRF55-1 without hns gene was significantly improved, indicating that hns mediates the improvement of fitness. Finally, we showed that the expression of hns gene is negatively correlated with the expression of tet(X4) gene, suggesting that the regulatory effect of H-NS on adaptability may be attributed to its inhibitory effect on the expression of ARGs. Together, our findings suggest the important role of plasmid-encoded H-NS protein in modulating the fitness of tet(X4)-bearing IncX1 plasmids, which shed new insight into the dissemination of tet(X4) gene in a biological environment.

Mathematical Models of Plasmid Population Dynamics

With plasmid-mediated antibiotic resistance thriving and threatening to become a serious public health problem, it is paramount to increase our understanding of the forces that enable the spread and maintenance of drug resistance genes encoded in mobile genetic elements. The relevance of plasmids as vehicles for the dissemination of antibiotic resistance genes, in addition to the extensive use of plasmid-derived vectors for biotechnological and industrial purposes, has promoted the in-depth study of the molecular mechanisms controlling multiple aspects of a plasmids' life cycle. This body of experimental work has been paralleled by the development of a wealth of mathematical models aimed at understanding the interplay between transmission, replication, and segregation, as well as their consequences in the ecological and evolutionary dynamics of plasmid-bearing bacterial populations. In this review, we discuss theoretical models of plasmid dynamics that span from the molecular mechanisms of plasmid partition and copy-number control occurring at a cellular level, to their consequences in the population dynamics of complex microbial communities. We conclude by discussing future directions for this exciting research topic.

Layman N, Redwood AJ, Chan B, Bull JJ. Methods for measuring the evolutionary stability of engineered genomes to improve their longevity

Diverse applications rely on engineering microbes to carry and express foreign transgenes. This engineered baggage rarely benefits the microbe and is thus prone to rapid evolutionary loss when the microbe is propagated. For applications where a transgene must be maintained for extended periods of growth, slowing the rate of transgene evolution is critical and can be achieved by reducing either the rate of mutation or the strength of selection. Because the benefits realized by changing these quantities will not usually be equal, it is important to know which will yield the greatest improvement to the evolutionary half-life of the engineering. Here, we provide a method for jointly estimating the mutation rate of transgene loss and the strength of selection favoring these transgene-free, revertant individuals. The method requires data from serial transfer experiments in which the frequency of engineered genomes is monitored periodically. Simple mathematical models are developed that use these estimates to predict the half-life of the engineered transgene and provide quantitative predictions for how alterations to mutation and selection will influence longevity. The estimation method and predictive tools have been implemented as an interactive web application, MuSe.

Coevolution of host-plasmid pairs facilitates the emergence of novel multidrug resistance

Multidrug resistance (MDR) of pathogens is an ongoing public health crisis exacerbated by the horizontal transfer of antibiotic resistance genes via conjugative plasmids. Factors that stabilize these plasmids in bacterial communities contribute to an even higher incidence of MDR, given the increased likelihood that a host will already contain a plasmid when it acquires another through conjugation. Here, we show one such stabilizing factor is host-plasmid coevolution under antibiotic selection, which facilitated the emergence of MDR via two distinct plasmids in communities consisting of Escherichia coli and Klebsiella pneumoniae once antibiotics were removed. In our system, evolution promoted greater stability of a plasmid in its coevolved host. Further, pleiotropic effects resulted in greater plasmid persistence in both novel host-plasmid combinations and, in some cases, multi-plasmid hosts. This evolved stability favoured the generation of MDR cells and thwarted their loss within communities with multiple plasmids. By selecting for plasmid persistence, the application of antibiotics may promote MDR well after their original period of use.

Coalescence modeling of intrainfection Bacillus anthracis populations allows estimation of infection parameters in wild populations

Bacillus anthracis, the etiological agent of anthrax, is a well-established model organism. For B. anthracis and most other infectious diseases, knowledge regarding transmission and infection parameters in natural systems, in large part, comprises data gathered from closely controlled laboratory experiments. Fatal, natural anthrax infections transmit the bacterium through new host-pathogen contacts at carcass sites, which can occur years after death of the previous host. For the period between contact and death, all of our knowledge is based upon experimental data from domestic livestock and laboratory animals. Here we use a noninvasive method to explore the dynamics of anthrax infections, by evaluating the terminal diversity of B. anthracis in anthrax carcasses. We present an application of population genetics theory, specifically, coalescence modeling, to intrainfection populations of B. anthracis to derive estimates for the duration of the acute phase of the infection and effective population size converted to the number of colony-forming units establishing infection in wild plains zebra (Equus quagga). Founding populations are small, a few colony-forming units, and infections are rapid, lasting roughly between 1 d and 3 d in the wild. Our results closely reflect experimental data, showing that small founding populations progress acutely, killing the host within days. We believe this method is amendable to other bacterial diseases from wild, domestic, and human systems.

Quantifying the impact of treatment history on plasmid-mediated resistance evolution in human gut microbiota

To understand how antibiotic use affects the risk of a resistant infection, we present a computational model of the population dynamics of gut microbiota including antibiotic resistance-conferring plasmids. We then describe how this model is parameterized based on published microbiota data. Finally, we investigate how treatment history affects the prevalence of resistance among opportunistic enterobacterial pathogens. We simulate treatment histories and identify which properties of prior antibiotic exposure are most influential in determining the prevalence of resistance. We find that resistance prevalence can be predicted by 3 properties, namely the total days of drug exposure, the duration of the drug-free period after last treatment, and the center of mass of the treatment pattern. Overall this work provides a framework for capturing the role of the microbiome in the selection of antibiotic resistance and highlights the role of treatment history for the prevalence of resistance.

The effect of spatiotemporal antibiotic inhomogeneities on the evolution of resistance

Combating the evolution of widespread antibiotic resistance is one of the most pressing challenges facing modern medicine. Recent research has demonstrated that the evolution of pathogens with high levels of resistance can be accelerated by spatial and temporal inhomogeneities in antibiotic concentration, which frequently arise in patients and the environment. Strategies to predict and counteract the effects of such inhomogeneities will be critical in the fight against resistance. In this paper we develop a mechanistic framework for modelling the adaptive evolution of resistance in the presence of spatiotemporal antibiotic concentrations, which treats the adaptive process as an interaction between two mutually orthogonal forces; the first returns cells to their wild-type state in the absence of antibiotic selection, and the second selects for increased coping ability in the presence of an antibiotic. We apply our model to investigate laboratory adaptation experiments, and then extend it to consider the case in which multiple strategies for resistance undergo competitive evolution.

Salicylate Increases Fitness Cost Associated with MarA-Mediated Antibiotic Resistance

Antibiotic resistance is generally associated with a fitness deficit resulting from the burden of producing and maintaining resistance machinery. This additional cost suggests that resistant bacteria will be outcompeted by susceptible bacteria in conditions without antibiotics. However, in practice, this process is slow in part because of regulation that minimizes expression of these genes in the absence of antibiotics. This suggests that if it were possible to turn on their expression, the cost would increase, thereby accelerating removal of resistant strains. Experimental and theoretical studies have shown that environmental chemicals can change the fitness cost associated with resistance and therefore have a significant impact on population dynamics. The multiple antibiotic resistance activator (MarA) is a clinically important regulator in Escherichia coli that activates downstream genes to increase resistance against multiple classes of antibiotics. Salicylate is an inducer of MarA that can be found in the environment and derepresses marA's expression. In this study, we sought to unravel the interplay between salicylate and the fitness cost of MarA-mediated antibiotic resistance. Using salicylate as an inducer of MarA, we found that a wide spectrum of concentrations can increase burden in resistant strains compared to susceptible strains. Induction resulted in rapid exclusion of resistant bacteria from mixed populations of antibiotic-resistant and susceptible cells. A mathematical model captures the process and predicts its effect in various environmental conditions. Our work provides a quantitative understanding of salicylate exposure on the fitness of different MarA variants and suggests that salicylate can lead to selection against MarA-mediated resistant strains. More generally, our findings show that natural inducers may serve to bias population membership and could impact antibiotic resistance and other important phenotypes.

Spatial structure facilitates the accumulation and persistence of antibiotic-resistant mutants in biofilms

The emergence and spread of antibiotic resistance in bacterial pathogens are a global crisis. Because many bacterial infections are caused by pathogens that reside in biofilms, we sought to investigate how biofilms influence the evolution of antibiotic resistance. We hypothesize that the inherent spatial structure of biofilms facilitates the accumulation and persistence of spontaneously evolved antibiotic-resistant mutants. To test this, we tracked the frequency of mutants resistant to kanamycin and rifampicin in biofilm populations of Escherichia coli before, during, and after an antibiotic treatment regimen. Our results show that biofilms accumulate resistant mutants even in the absence of antibiotics. This resistance was found to be heritable and thus unlike the phenotypic plasticity of so-called "persister cells" that have been shown to occur in biofilms. Upon exposure to an antibiotic, resistant mutants swept to high frequency. Following the conclusion of treatment, these resistant mutants remained at unexpectedly high frequencies in the biofilms for over 45 days. In contrast, when samples from kanamycin-treated biofilms were used to found well-mixed liquid cultures and propagated by serial transfer, the frequency of resistant cells dramatically decreased as they were outcompeted by sensitive clones. These observations suggest that the emergence of antibiotic resistance through spontaneous mutations in spatially structured biofilms may significantly contribute to the emergence and persistence of mutants that are resistant to antibiotics used to treat bacterial infections.

Simulated wastewater reduced Klebsiella michiganensis strain LH-2 viability and corresponding antibiotic resistance gene abundance in bio-electrochemical reactors

A previous study revealed that the electrolytic stimulation process in bio-electrochemical reactors (BER) can accelerate growth of sulfadiazine (SDZ) antibiotic resistant bacteria (ARB) in nutrient broth medium. However, the influence of different medium nutrient richness on the fate of ARB and the relative abundance of their corresponding antibiotic resistance genes (ARGs) in this process is unknown. Specifically, it is not clear if the fate of ARB in minimal nutrition simulated wastewater is the same as in nutrient broth under electrolytic stimulation. Therefore, in this study, nutrient broth medium and the simulated wastewater were compared to identify differences in the relative abundance of Klebsiella michiganensis LH-2 ARGs in response to the electrolytic stimulation process, as well as the fate of the strain in simulated wastewater. Lower biomass, specific growth rates and viable bacterial counts were obtained in response to the application of increasing current to simulated wastewater medium. Furthermore, the percentage of ARB lethality, which was reflected by flow cytometry analysis, increased with current in the medium. A significant positive correlation of sul genes and intI gene relative abundance versus current was also observed in nutrient broth. However, a significant negative correlation was observed in simulated wastewater because of the higher metabolic burden, which may have led to decreased ARB viability. Further investigation showed that the decrease in ARGs abundance was responsible for decreased strain tolerance to SDZ in simulated wastewater. These results reveal that minimal nutrition simulated wastewater may reduce ARB and ARGs propagation in BER.

Human dissemination of genes and microorganisms in Earth's Critical Zone

Earth's Critical Zone sustains terrestrial life and consists of the thin planetary surface layer between unaltered rock and the atmospheric boundary. Within this zone, flows of energy and materials are mediated by physical processes and by the actions of diverse organisms. Human activities significantly influence these physical and biological processes, affecting the atmosphere, shallow lithosphere, hydrosphere, and biosphere. The role of organisms includes an additional class of biogeochemical cycling, this being the flow and transformation of genetic information. This is particularly the case for the microorganisms that govern carbon and nitrogen cycling. These biological processes are mediated by the expression of functional genes and their translation into enzymes that catalyze geochemical reactions. Understanding human effects on microbial activity, fitness and distribution is an important component of Critical Zone science, but is highly challenging to investigate across the enormous physical scales of impact ranging from individual organisms to the planet. One arena where this might be tractable is by studying the dynamics and dissemination of genes for antibiotic resistance and the organisms that carry such genes. Here we explore the transport and transformation of microbial genes and cells through Earth's Critical Zone. We do so by examining the origins and rise of antibiotic resistance genes, their subsequent dissemination, and the ongoing colonization of diverse ecosystems by resistant organisms.

Mathematical modelling of the antibiotic-induced morphological transition of Pseudomonas aeruginosa

Here we formulate a mechanistic mathematical model to describe the growth dynamics of P. aeruginosa in the presence of the β-lactam antibiotic meropenem. The model is mechanistic in the sense that carrying capacity is taken into account through the dynamics of nutrient availability rather than via logistic growth. In accordance with our experimental results we incorporate a sub-population of cells, differing in morphology from the normal bacillary shape of P. aeruginosa bacteria, which we assume have immunity from direct antibiotic action. By fitting this model to experimental data we obtain parameter values that give insight into the growth of a bacterial population that includes different cell morphologies. The analysis of two parameters sets, that produce different long term behaviour, allows us to manipulate the system theoretically in order to explore the advantages of a shape transition that may potentially be a mechanism that allows P. aeruginosa to withstand antibiotic effects. Our results suggest that inhibition of this shape transition may be detrimental to bacterial growth and thus suggest that the transition may be a defensive mechanism implemented by bacterial machinery. In addition to this we provide strong theoretical evidence for the potential therapeutic strategy of using antimicrobial peptides (AMPs) in combination with meropenem. This proposed combination therapy exploits the shape transition as AMPs induce cell lysis by forming pores in the cytoplasmic membrane, which becomes exposed in the spherical cells.

Reversing resistance: different routes and common themes across pathogens

Resistance spreads rapidly in pathogen or pest populations exposed to biocides, such as fungicides and antibiotics, and in many cases new biocides are in short supply. How can resistance be reversed in order to prolong the effectiveness of available treatments? Some key parameters affecting reversion of resistance are well known, such as the fitness cost of resistance. However, the population biological processes that actually cause resistance to persist or decline remain poorly characterized, and consequently our ability to manage reversion of resistance is limited. Where do susceptible genotypes that replace resistant lineages come from? What is the epidemiological scale of reversion? What information do we need to predict the mechanisms or likelihood of reversion? Here, we define some of the population biological processes that can drive reversion, using examples from a wide range of taxa and biocides. These processes differ primarily in the origin of revertant genotypes, but also in their sensitivity to factors such as coselection and compensatory evolution that can alter the rate of reversion, and the likelihood that resistance will re-emerge upon re-exposure to biocides. We therefore argue that discriminating among different types of reversion allows for better prediction of where resistance is most likely to persist.

Plasmid stability analysis based on a new theoretical model employing stochastic simulations

Here, we present a simple theoretical model to study plasmid stability, based on one input parameter which is the copy number of plasmids present in a host cell. The Monte Carlo approach was used to analyze random fluctuations affecting plasmid replication and segregation leading to gradual reduction in the plasmid population within the host cell. This model was employed to investigate maintenance of pEC156 derivatives, a high-copy number ColE1-type Escherichia coli plasmid that carries an EcoVIII restriction-modification system. Plasmid stability was examined in selected Escherichia coli strains (MG1655, wild-type; MG1655 pcnB, and hyper-recombinogenic JC8679 sbcA). We have compared the experimental data concerning plasmid maintenance with the simulations and found that the theoretical stability patterns exhibited an excellent agreement with those empirically tested. In our simulations, we have investigated the influence of replication fails (α parameter) and uneven partition as a consequence of multimer resolution fails (δ parameter), and the post-segregation killing factor (β parameter). All of these factors act at the same time and affect plasmid inheritance at different levels. In case of pEC156-derivatives we concluded that multimerization is a major determinant of plasmid stability. Our data indicate that even small changes in the fidelity of segregation can have serious effects on plasmid stability. Use of the proposed mathematical model can provide a valuable description of plasmid maintenance, as well as enable prediction of the probability of the plasmid loss.

Emerging patterns of plasmid-host coevolution that stabilize antibiotic resistance

Multidrug resistant bacterial pathogens have become a serious global human health threat, and conjugative plasmids are important drivers of the rapid spread of resistance to last-resort antibiotics. Whereas antibiotics have been shown to select for adaptation of resistance plasmids to their new bacterial hosts, or vice versa, a general evolutionary mechanism has not yet emerged. Here we conducted an experimental evolution study aimed at determining general patterns of plasmid-bacteria evolution. Specifically, we found that a large conjugative resistance plasmid follows the same evolutionary trajectories as its non-conjugative mini-replicon in the same and other species. Furthermore, within a single host-plasmid pair three distinct patterns of adaptive evolution led to increased plasmid persistence: i) mutations in the replication protein gene (trfA1); ii) the acquisition by the resistance plasmid of a transposon from a co-residing plasmid encoding a putative toxin-antitoxin system; iii) a mutation in the host's global transcriptional regulator gene fur. Since each of these evolutionary solutions individually have been shown to increase plasmid persistence in other plasmid-host pairs, our work points towards common mechanisms of plasmid stabilization. These could become the targets of future alternative drug therapies to slow down the spread of antibiotic resistance.

Sulfamethoxazole, tetracycline and oxytetracycline and related antibiotic resistance genes in a large-scale landfill, China

Landfills are likely to be important reservoirs of antibiotics and antibiotic resistant genes (ARGs) as they receive unused and unwanted antibiotics and ARGs in municipal solid waste (MSW). The distribution, transportation and dynamics of antibiotics and ARGs in landfills remain largely unknown. In the present study, 3 antibiotics - sulfamethoxazole (SMX), tetracycline (TC), and oxytetracycline (OTC) - and their related ARGs (sulI and tetO) were quantified in 51 refuse samples from different depths at 8 locations within a large-scale landfill in central China. The average concentration of OTC was the highest, up to 100.9±141.81μg/kg (dw, n=48), followed by TC (63.8±37.7μg/kg, n=40), and SMX (47.9±8.1μg/kg, n=30). Both sulI and tetO were detected in all samples. Of the ARGs, sul1 (-3.06±1.18, n=51, log10 ARGs/16SrDNA) was more abundant than tetO (-4.37±0.97) in all refuse samples (p<0.05). Both sulI and tetO negatively correlated to refuse age, suggesting they are attenuated during landfill stabilization. OTC and TC positively correlated to tetO (r=0.41, p<0.01) and sulI (r=0.29, p=0.04), respectively. Chemical conditions (e.g. moisture content and nitrate concentrations) within the refuse correlated to antibiotics and ARGs suggesting environmental factors impact the distribution of antibiotics and ARGs in landfill matrix. This study is the first comprehensive in situ landfill study to connect the concentrations of antibiotic residues to ARGs.

MATHEMATICAL MODELING OF BACTERIAL RESISTANCE TO ANTIBIOTICS BY MUTATIONS AND PLASMIDS

Diversity of drugs against bacterial infections, and development of resistance to such drugs are increasing. We formulate and analyze a deterministic model for the population dynamics of sensitive and resistant bacteria to multiple bactericidal and bacteriostatic antibiotics, assuming that drug resistance is acquired through mutations and plasmid transmission. Model equilibria are determined from qualitative analysis, and numerical simulations are used to assess temporal dynamics of sensitive and drug-resistant bacteria. The model presents three possibilities: elimination of bacteria, persistence of only resistant bacteria, or coexistence of sensitive and resistant bacteria. Evolution to one of these scenarios depends on thresholds numbers involving sensitive and resistant bacteria.

Evolutionary Paths That Expand Plasmid Host-Range: Implications for Spread of Antibiotic Resistance

The World Health Organization has declared the emergence of antibiotic resistance to be a global threat to human health. Broad-host-range plasmids have a key role in causing this health crisis because they transfer multiple resistance genes to a wide range of bacteria. To limit the spread of antibiotic resistance, we need to gain insight into the mechanisms by which the host range of plasmids evolves. Although initially unstable plasmids have been shown to improve their persistence through evolution of the plasmid, the host, or both, the means by which this occurs are poorly understood. Here, we sought to identify the underlying genetic basis of expanded plasmid host-range and increased persistence of an antibiotic resistance plasmid using a combined experimental-modeling approach that included whole-genome resequencing, molecular genetics and a plasmid population dynamics model. In nine of the ten previously evolved clones, changes in host and plasmid each slightly improved plasmid persistence, but their combination resulted in a much larger improvement, which indicated positive epistasis. The only genetic change in the plasmid was the acquisition of a transposable element from a plasmid native to the Pseudomonas host used in these studies. The analysis of genetic deletions showed that the critical genes on this transposon encode a putative toxin-antitoxin (TA) and a cointegrate resolution system. As evolved plasmids were able to persist longer in multiple naïve hosts, acquisition of this transposon also expanded the plasmid's host range, which has important implications for the spread of antibiotic resistance.

Multidrug evolutionary strategies to reverse antibiotic resistance

Antibiotic treatment has two conflicting effects: the desired, immediate effect of inhibiting bacterial growth and the undesired, long-term effect of promoting the evolution of resistance. Although these contrasting outcomes seem inextricably linked, recent work has revealed several ways by which antibiotics can be combined to inhibit bacterial growth while, counterintuitively, selecting against resistant mutants. Decoupling treatment efficacy from the risk of resistance can be achieved by exploiting specific interactions between drugs, and the ways in which resistance mutations to a given drug can modulate these interactions or increase the sensitivity of the bacteria to other compounds. Although their practical application requires much further development and validation, and relies on advances in genomic diagnostics, these discoveries suggest novel paradigms that may restrict or even reverse the evolution of resistance.

Relationships between antibiotics and antibiotic resistance gene levels in municipal solid waste leachates in Shanghai, China

Many studies have quantified antibiotics and antibiotic resistance gene (ARG) levels in soils, surface waters, and waste treatment plants (WTPs). However, similar work on municipal solid waste (MSW) landfill leachates is limited, which is concerning because antibiotics disposal is often in the MSW stream. Here we quantified 20 sulfonamide (SA), quinolone (FQ), tetracycline (TC), macrolide (ML), and chloramphenicol (CP) antibiotics, and six ARGs (sul1, sul2, tetQ, tetM, ermB, and mefA) in MSW leachates from two Shanghai transfer stations (TS; sites Hulin (HL) and Xupu (XP)) and one landfill reservoir (LR) in April and July 2014. Antibiotic levels were higher in TS than LR leachates (985 ± 1965 ng/L vs 345 ± 932 ng/L, n = 40), which was because of very high levels in the HL leachates (averaging at 1676 ± 5175 ng/L, n = 40). The mean MLs (3561 ± 8377 ng/L, n = 12), FQs (975 ± 1608 ng/L, n = 24), and SAs (402 ± 704 ng/L, n = 42) classes of antibiotics were highest across all samples. ARGs were detected in all leachate samples with normalized sul2 and ermB levels being especially elevated (-1.37 ± 1.2 and -1.76 ± 1.6 log (copies/16S-rDNA), respectively). However, ARG abundances did not correlate with detected antibiotic levels, except for tetW and tetQ with TC levels (r = 0.88 and 0.81, respectively). In contrast, most measured ARGs did significantly correlate with heavy metal levels (p < 0.05), especially with Cd and Cr. This study shows high levels of ARGs and antibiotics can prevail in MSW leachates and landfills may be an underappreciated as a source of antibiotics and ARGs to the environment.

Mathematical modeling of bacterial kinetics to predict the impact of antibiotic colonic exposure and treatment duration on the amount of resistant enterobacteria excreted

Fecal excretion of antibiotics and resistant bacteria in the environment are major public health threats associated with extensive farming and modern medical care. Innovative strategies that can reduce the intestinal antibiotic concentrations during treatments are in development. However, the effect of lower exposure on the amount of resistant enterobacteria excreted has not been quantified, making it difficult to anticipate the impact of these strategies. Here, we introduce a bacterial kinetic model to capture the complex relationships between drug exposure, loss of susceptible enterobacteria and growth of resistant strains in the feces of piglets receiving placebo, 1.5 or 15 mg/kg/day ciprofloxacin, a fluoroquinolone, for 5 days. The model could well describe the kinetics of drug susceptible and resistant enterobacteria observed during treatment, and up to 22 days after treatment cessation. Next, the model was used to predict the expected amount of resistant enterobacteria excreted over an average piglet's lifetime (150 days) when varying drug exposure and treatment duration. For the clinically relevant dose of 15 mg/kg/day for 5 days, the total amount of resistant enterobacteria excreted was predicted to be reduced by 75% and 98% when reducing treatment duration to 3 and 1 day treatment, respectively. Alternatively, for a fixed 5-days treatment, the level of resistance excreted could be reduced by 18%, 33%, 57.5% and 97% if 3, 5, 10 and 30 times lower levels of colonic drug concentrations were achieved, respectively. This characterization on in vivo data of the dynamics of resistance to antibiotics in the colonic flora could provide new insights into the mechanism of dissemination of resistance and can be used to design strategies aiming to reduce it.

Fecal excretion of antibiotics and resistant bacteria in the environment are major public health threats associated with extensive farming. Innovative strategies that reduce the intestinal antibiotic concentrations during treatment are in development and could help prevent the dissemination of resistance. In order to anticipate the impact of these strategies, the effect of lower exposure on the amount of resistant enterobacteria excreted needs to be quantified precisely. Here, we introduce a bacterial kinetic model to capture the complex relationships between dosage regimen, antibiotic fecal concentrations, loss of susceptible enterobacteria and growth of resistant strains in the feces of piglets receiving different doses of ciprofloxacin for 5 days. We use this model to evaluate by simulation how much it would be necessary to reduce the antibiotic colonic concentration in order to prevent the expansion of antibiotic resistance. This approach provides new insights into the mechanism of dissemination of resistance during treatments and can be used to design strategies to reduce it.

Dynamics of soil bacterial communities in response to repeated application of manure containing sulfadiazine

Large amounts of manure have been applied to arable soils as fertilizer worldwide. Manure is often contaminated with veterinary antibiotics which enter the soil together with antibiotic resistant bacteria. However, little information is available regarding the main responders of bacterial communities in soil affected by repeated inputs of antibiotics via manure. In this study, a microcosm experiment was performed with two concentrations of the antibiotic sulfadiazine (SDZ) which were applied together with manure at three different time points over a period of 133 days. Samples were taken 3 and 60 days after each manure application. The effects of SDZ on soil bacterial communities were explored by barcoded pyrosequencing of 16S rRNA gene fragments amplified from total community DNA. Samples with high concentration of SDZ were analyzed on day 193 only. Repeated inputs of SDZ, especially at a high concentration, caused pronounced changes in bacterial community compositions. By comparison with the initial soil, we could observe an increase of the disturbance and a decrease of the stability of soil bacterial communities as a result of SDZ manure application compared to the manure treatment without SDZ. The number of taxa significantly affected by the presence of SDZ increased with the times of manure application and was highest during the treatment with high SDZ-concentration. Numerous taxa, known to harbor also human pathogens, such as Devosia, Shinella, Stenotrophomonas, Clostridium, Peptostreptococcus, Leifsonia, Gemmatimonas, were enriched in the soil when SDZ was present while the abundance of bacteria which typically contribute to high soil quality belonging to the genera Pseudomonas and Lysobacter, Hydrogenophaga, and Adhaeribacter decreased in response to the repeated application of manure and SDZ.

Resource competition may lead to effective treatment of antibiotic resistant infections

Drug resistance is a common problem in the fight against infectious diseases. Recent studies have shown conditions (which we call antiR) that select against resistant strains. However, no specific drug administration strategies based on this property exist yet. Here, we mathematically compare growth of resistant versus sensitive strains under different treatments (no drugs, antibiotic, and antiR), and show how a precisely timed combination of treatments may help defeat resistant strains. Our analysis is based on a previously developed model of infection and immunity in which a costly plasmid confers antibiotic resistance. As expected, antibiotic treatment increases the frequency of the resistant strain, while the plasmid cost causes a reduction of resistance in the absence of antibiotic selection. Our analysis suggests that this reduction occurs under competition for limited resources. Based on this model, we estimate treatment schedules that would lead to a complete elimination of both sensitive and resistant strains. In particular, we derive an analytical expression for the rate of resistance loss, and hence for the time necessary to turn a resistant infection into sensitive (tclear). This time depends on the experimentally measurable rates of pathogen division, growth and plasmid loss. Finally, we estimated tclear for a specific case, using available empirical data, and found that resistance may be lost up to 15 times faster under antiR treatment when compared to a no treatment regime. This strategy may be particularly suitable to treat chronic infection. Finally, our analysis suggests that accounting explicitly for a resistance-decaying rate may drastically change predicted outcomes in host-population models.

A modeling framework for the evolution and spread of antibiotic resistance: literature review and model categorization

Antibiotic-resistant infections complicate treatment and increase morbidity and mortality. Mathematical modeling has played an integral role in improving our understanding of antibiotic resistance. In these models, parameter sensitivity is often assessed, while model structure sensitivity is not. To examine the implications of this, we first reviewed the literature on antibiotic-resistance modeling published between 1993 and 2011. We then classified each article's model structure into one or more of 6 categories based on the assumptions made in those articles regarding within-host and population-level competition between antibiotic-sensitive and antibiotic-resistant strains. Each model category has different dynamic implications with respect to how antibiotic use affects resistance prevalence, and therefore each may produce different conclusions about optimal treatment protocols that minimize resistance. Thus, even if all parameter values are correctly estimated, inferences may be incorrect because of the incorrect selection of model structure. Our framework provides insight into model selection.

Tetracycline resistance gene maintenance under varying bacterial growth rate, substrate and oxygen availability, and tetracycline concentration

Neither amplification nor attenuation of antibiotic resistance genes (ARG) in the environment are well understood processes. Here, we report on continuous culture and batch experiments to determine how tetracycline (TC), aerobic vs anaerobic conditions, bacterial growth rate, and medium richness affect the maintenance of plasmid-borne TC resistance (Tet(R)) genes. The response of E. coli (a model resistant strain excreted by farm animals) versus Pseudomonas aeruginosa (a model bacterium that could serve as a reservoir for ARGs in the environment) were compared to gain insight into response variability. Complete loss of the Tet(R) RP1 plasmid (56 kb) occurred for P. aeruginosa in the absence of TC, and faster loss was observed in continuous culture at higher growth rates. In contrast, E. coli retained its smaller pSC101 plasmid (9.3 kb) after 500 generations without TC (albeit at lower levels, with ratios of resistance to 16S rDNA genes decreasing by about 2-fold). A higher rate of ARG loss was observed in P. aeruginosa when grown in minimal growth medium (M9) than in richer Luria broth. Faster ARG loss occurred in E. coli under anaerobic (fermentative) conditions than under aerobic conditions. Thus, in these two model strains it was observed that conditions that ease the metabolic burden of plasmid reproduction (e.g., higher substrate and O2 availability) enhanced resistance plasmid maintenance; such conditions (in the presence of residual antibiotics) may be conducive to the establishment and preservation of ARG reservoirs in the environment. These results underscore the need to consider antibiotic concentrations, redox conditions, and substrate availability in efforts to evaluate ARG propagation and natural attenuation.

CRISPR-Cas systems preferentially target the leading regions of MOBF conjugative plasmids

Most prokaryotes contain CRISPR-Cas immune systems that provide protection against mobile genetic elements. We have focused on the ability of CRISPR-Cas to block plasmid conjugation, and analyzed the position of target sequences (protospacers) on conjugative plasmids. The analysis reveals that protospacers are non-uniformly distributed over plasmid regions in a pattern that is determined by the plasmid's mobilization type (MOB). While MOBP plasmids are most frequently targeted in the region entering the recipient cell last (lagging region), MOBF plasmids are mostly targeted in the region entering the recipient cell first (leading region). To explain this protospacer distribution bias, we propose two mutually non-exclusive hypotheses: (1) spacers are acquired more frequently from either the leading or lagging region depending on the MOB type (2) CRISPR-interference is more efficient when spacers target these preferred regions. To test the latter hypothesis, we analyzed Type I-E CRISPR-interference against MOBF prototype plasmid F in Escherichia coli. Our results show that plasmid conjugation is effectively inhibited, but the level of immunity is not affected by targeting the plasmid in the leading or lagging region. Moreover, CRISPR-immunity levels do not depend on whether the incoming single-stranded plasmid DNA, or the DNA strand synthesized in the recipient is targeted. Our findings indicate that single-stranded DNA may not be a target for Type I-E CRISPR-Cas systems, and suggest that the protospacer distribution bias might be due to spacer acquisition preferences.

Genomic analysis by deep sequencing of the probiotic Lactobacillus brevis KB290 harboring nine plasmids reveals genomic stability

We determined the complete genome sequence of Lactobacillus brevis KB290, a probiotic lactic acid bacterium isolated from a traditional Japanese fermented vegetable. The genome contained a 2,395,134-bp chromosome that housed 2,391 protein-coding genes and nine plasmids that together accounted for 191 protein-coding genes. KB290 contained no virulence factor genes, and several genes related to presumptive cell wall-associated polysaccharide biosynthesis and the stress response were present in L. brevis KB290 but not in the closely related L. brevis ATCC 367. Plasmid-curing experiments revealed that the presence of plasmid pKB290-1 was essential for the strain's gastrointestinal tract tolerance and tendency to aggregate. Using next-generation deep sequencing of current and 18-year-old stock strains to detect low frequency variants, we evaluated genome stability. Deep sequencing of four periodic KB290 culture stocks with more than 1,000-fold coverage revealed 3 mutation sites and 37 minority variation sites, indicating long-term stability and providing a useful method for assessing the stability of industrial bacteria at the nucleotide level.

Escherichia coli adapts to tetracycline resistance plasmid (pBR322) by mutating endogenous potassium transport: in silico hypothesis testing

Antibiotic resistance exerts a metabolic cost on bacteria and presumably a fitness disadvantage in the absence of antibiotics. However, several studies have shown that bacteria can evolve to eliminate this cost. Escherichia coli can adapt to the plasmid pBR322 carrying the tetA tetracycline-resistance gene (codes for the TetA efflux pump) by a chromosome mutation, which requires an intact tetA gene on the plasmid. The TetA pump can mediate potassium uptake. Here, the hypothesis that TetA replaces the endogenous K(+) uptake system Trk is explored using a multi-level modeling approach that explicitly resolves relevant intracellular processes (e.g., metabolism and K(+) uptake) and simulates individual bacteria in competition. The general behavior of the model is consistent with observations from the literature (e.g., growth rate and K(+) limitation). In competition experiments without tetracycline, the model correctly predicts the fitness advantage of naive susceptible over naive resistant, evolved resistant over naive resistant and evolved resistant over evolved susceptible strains. Trk takes up about 10 times the K(+) required, which costs energy. TetA takes up less K(+) , which is more efficient and leads to the evolution of the Trk mutant. The evolved Trk mutant relies on TetA to take up K(+) , and thus, carrying the plasmid is advantageous even in the absence of the antibiotic.

The role of clonal interference in the evolutionary dynamics of plasmid-host adaptation

Promiscuous plasmids replicate in a wide range of bacteria and therefore play a key role in the dissemination of various host-beneficial traits, including antibiotic resistance. Despite the medical relevance, little is known about the evolutionary dynamics through which drug resistance plasmids adapt to new hosts and thereby persist in the absence of antibiotics. We previously showed that the incompatibility group P-1 (IncP-1) minireplicon pMS0506 drastically improved its stability in novel host Shewanella oneidensis MR-1 after 1,000 generations under antibiotic selection for the plasmid. The only mutations found were those affecting the N terminus of the plasmid replication initiation protein TrfA1. Our aim in this study was to gain insight into the dynamics of plasmid evolution. Changes in stability and genotype frequencies of pMS0506 were monitored in evolving populations of MR-1 (pMS0506). Genotypes were determined by sequencing trfA1 amplicons from individual clones and by 454 pyrosequencing of whole plasmids from entire populations. Stability of pMS0506 drastically improved by generation 200. Many evolved plasmid genotypes with point mutations as well as in-frame and frameshift deletions and duplications in trfA1 were observed in all lineages with both sequencing methods. Strikingly, multiple genotypes were simultaneously present at high frequencies (>10%) in each population. Their relative abundances changed over time, but after 1,000 generations only one or two genotypes dominated the populations. This suggests that hosts with different plasmid genotypes were competing with each other, thus affecting the evolutionary trajectory. Plasmids can thus rapidly improve their stability, and clonal interference plays a significant role in plasmid-host adaptation dynamics.

Promiscuous plasmids play an important role in the spread of antibiotic resistance and many other traits between closely and distantly related bacteria. However, little is known about the dynamics by which these broad-host-range antibiotic resistance plasmids adapt to novel bacteria and thereby become more persistent, even in the absence of antibiotics. In this study, we show that after no more than 200 generations of growth in the presence of antibiotics, a plasmid that was initially poorly maintained in a novel bacterial host evolved to become drastically more persistent in the absence of antibiotics. In each of the evolving populations, an unexpectedly large number of bacterial variants arose with distinct mutations in the plasmid’s replication initiation protein. Our results suggest that clonal interference, characterized by competition between variant clones in a population, plays a major role in the evolution of the persistence of drug resistance.

Fitness of the pMV158 replicon in Streptococcus pneumoniae

Promiscuous, rolling-circle replication plasmid pMV158 determines tetracycline resistance to its host and can be mobilized by conjugation. Plasmid pLS1 is a deletion derivative of pMV158 that has lost its conjugative mobilization ability. Both plasmids replicate efficiently and are stably inherited in Streptococcus pneumoniae. We have analyzed the effect of pMV158 and pLS1 carriage on the bacterial growth rate. Whereas the parental plasmid does not significantly modify the cell doubling time, pLS1 slows down the growth of the bacterial host by 8-9%. The bases of the differential burden caused by pMV158 and pLS1 carriage are not yet understood. The negligible cost of the pMV158 parental natural plasmid on the host might explain the prevalence of small, multicopy, rolling-circle replication plasmids, even though they lack any selectable trait.

Contribution of mathematical modeling to the fight against bacterial antibiotic resistance

PURPOSE OF REVIEW

Modeling of antibiotic resistance in pathogenic bacteria responsible for human disease has developed considerably over the last decade. Herein, we summarize the main published studies to illustrate the contribution of models for understanding both within-host and population-based phenomena. We then suggest possible topics for future studies.

RECENT FINDINGS

Model building of bacterial resistance has involved epidemiologists, biologists and modelers with two different objectives. First, modeling has helped largely in identifying and understanding the factors and biological phenomena responsible for the emergence and spread of resistant strains. Second, these models have become important decision support tools for medicine and public health.

SUMMARY

Major improvements of models in the coming years should take into account specific pathogen characteristics (resistance mechanisms, multiple colonization phenomena, cooperation and competition among species) and better description of the contacts associated with transmission risk within populations.

Identification of bacterial plasmids based on mobility and plasmid population biology

Plasmids contain a backbone of core genes that remains relatively stable for long evolutionary periods, making sense to speak about plasmid species. The identification and characterization of the core genes of a plasmid species has a special relevance in the study of its epidemiology and modes of transmission. Besides, this knowledge will help to unveil the main routes that genes, for example antibiotic resistance (AbR) genes, use to travel from environmental reservoirs to human pathogens. Global dissemination of multiple antibiotic resistances and virulence traits by plasmids is an increasing threat for the treatment of many bacterial infectious diseases. To follow the dissemination of virulence and AbR genes, we need to identify the causative plasmids and follow their path from reservoirs to pathogens. In this review, we discuss how the existing diversity in plasmid genetic structures gives rise to a large diversity in propagation strategies. We would like to propose that, using an identification methodology based on plasmid mobility types, we can follow the propagation routes of most plasmids in Gammaproteobacteria, as well as their cargo genes, in complex ecosystems. Once the dissemination routes are known, designing antidissemination drugs and testing their efficacy will become feasible. We discuss in this review how the existing diversity in plasmid genetic structures gives rise to a large diversity in propagation strategies. We would like to propose that, by using an identification methodology based on plasmid mobility types, we can follow the propagation routes of most plasmids in ?-proteobacteria, as well as their cargo genes, in complex ecosystems.

Selection pressure required for long-term persistence of blaCMY-2-positive IncA/C plasmids

Multidrug resistance blaCMY-2 plasmids that confer resistance to expanded-spectrum cephalosporins have been found in multiple bacterial species collected from different hosts worldwide. The widespread distribution of blaCMY-2 plasmids may be driven by antibiotic use that selects for the dissemination and persistence of these plasmids. Alternatively, these plasmids may persist and spread in bacterial populations in the absence of selection pressure if a balance exists among conjugative transfer, segregation loss during cell division, and fitness cost to the host. We conducted a series of experiments (both in vivo and in vitro) to study these mechanisms for three blaCMY-2 plasmids, peH4H, pAR060302, and pAM04528. Results of filter mating experiments showed that the conjugation efficiency of blaCMY-2 plasmids is variable, from <10(-7) for pAM04528 and peH4H to ∼10(-3) for pAR060302. Neither peH4H nor pAM04528 was transferred from Escherichia coli strain DH10B, but peH4H was apparently mobilized by the coresident trimethoprim resistance-encoding plasmid pTmpR. Competition studies showed that carriage of blaCMY-2 plasmids imposed a measurable fitness cost on the host bacteria both in vitro (0.095 to 0.25) and in vivo (dairy calf model). Long-term passage experiments in the absence of antibiotics demonstrated that plasmids with limited antibiotic resistance phenotypes arose, but eventually drug-sensitive, plasmid-free clones dominated the populations. Given that plasmid decay or loss is inevitable, we infer that some level of selection is required for the long-term persistence of blaCMY-2 plasmids in bacterial populations.

Antimicrobial resistance ofEscherichia coliandEnterococcus faecalisin housed laying-hen flocks in Europe

The aim of this study was to determine the potential association between housing type and multiple drug resistance (MDR) inEscherichia coliandEnterococcus faecalisisolates recovered from 283 laying-hen flocks. In each flock, a cloacal swab from four hens was collected and produced 1102E. coliand 792E. faecalisisolates. Broth microdilution was used to test susceptibility to antimicrobials. Country and housing type interacted differently with the MDR levels of both species. In theE. colimodel, housing in a raised-floor system was associated with an increased risk of MDR compared to the conventional battery system [odds ratio (OR) 2·12, 95% confidence interval (CI) 1·13–3·97)]. In theE. faecalismodel the MDR levels were lower in free-range systems than in conventional battery cages (OR 0·51, 95% CI 0·27–0·94). In Belgium, ceftiofur-resistantE. coliisolates were more numerous than in the other countries.

The population genetics of antibiotic resistance: integrating molecular mechanisms and treatment contexts

Despite efforts from a range of disciplines, our ability to predict and combat the evolution of antibiotic resistance in pathogenic bacteria is limited. This is because resistance evolution involves a complex interplay between the specific drug, bacterial genetics and both natural and treatment ecology. Incorporating details of the molecular mechanisms of drug resistance and ecology into evolutionary models has proved useful in predicting the dynamics of resistance evolution. However, putting these models to practical use will require extensive collaboration between mathematicians, molecular biologists, evolutionary ecologists and clinicians.

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.

Sociobiological control of plasmid copy number in bacteria

All genes critical for plasmid replication regulation are located on the plasmid rather than on the host chromosome. It is possible therefore that there can be copy-up “cheater” mutants. In spite of this possibility, low copy number plasmids appear to exist stably in host populations. We examined this paradox using a multilevel selection model. Simulations showed that, a slightly higher copy number mutant could out-compete the wild type. Consequently, another mutant with still higher copy number could invade the first invader. However, the realized benefit of increasing intra-host fitness was saturating whereas that of inter-host fitness was exponential. As a result, above a threshold, intra-host selection was overcompensated by inter-host selection and the low copy number wild type plasmid could back invade a very high copy number plasmid. This led to a rock-paper-scissor (RPS) like situation that allowed the coexistence of plasmids with varied copy numbers. Furthermore, another type of cheater that had lost the genes required for conjugation but could hitchhike on a conjugal plasmid, could further reduce the advantage of copy-up mutants. These sociobiological interactions may compliment molecular mechanisms of replication regulation in stabilizing the copy numbers.

Modelling conjugation with stochastic differential equations

Conjugation is an important mechanism involved in the transfer of resistance between bacteria. In this article a stochastic differential equation based model consisting of a continuous time state equation and a discrete time measurement equation is introduced to model growth and conjugation of two Enterococcus faecium strains in a rich exhaustible media. The model contains a new expression for a substrate dependent conjugation rate. A maximum likelihood based method is used to estimate the model parameters. Different models including different noise structure for the system and observations are compared using a likelihood-ratio test and Akaike's information criterion. Experiments indicating conjugation on the agar plates selecting for transconjugants motivates the introduction of an extended model, for which conjugation on the agar plate is described in the measurement equation. This model is compared to the model without plate conjugation. The modelling approach described in this article can be applied generally when modelling dynamical systems.

Mutational neighbourhood and mutation supply rate constrain adaptation in Pseudomonas aeruginosa

Understanding adaptation by natural selection requires understanding the genetic factors that determine which beneficial mutations are available for selection. Here, using experimental evolution of rifampicin-resistant Pseudomonas aeruginosa, we show that different genotypes vary in their capacity for adaptation to the cost of antibiotic resistance. We then use sequence data to show that the beneficial mutations associated with fitness recovery were specific to particular genetic backgrounds, suggesting that genotypes had access to different sets of beneficial mutations. When we manipulated the supply rate of beneficial mutations, by altering effective population size during evolution, we found that it constrained adaptation in some selection lines by restricting access to rare beneficial mutations, but that the effect varied among the genotypes in our experiment. These results suggest that mutational neighbourhood varies even among genotypes that differ by a single amino acid change, and this determines their capacity for adaptation as well as the influence of population biology processes that alter mutation supply rate.

Competition favours reduced cost of plasmids to host bacteria

Conjugative plasmids of Gram-negative bacteria have both vertical and horizontal modes of transmission: they are segregated to daughter cells during division, and transferred between hosts by plasmid-encoded conjugative machinery. Despite maintaining horizontal mobility, many plasmids carry fertility inhibition (fin) systems that repress their own conjugative transfer. To assess the ecological basis of self-transfer repression, we compared the invasion of bacterial populations by fin(+) and fin(-) variants of the plasmid R1 using a computational model and co-culture competitions. We observed that the fin(+) variant had a modest cost to the host (measured by reduction in growth rate), while the fin(-) variant incurred a larger cost. In simulations and empirical competitions the fin(-) plasmid invaded cultures quickly, but was subsequently displaced by the fin(+) plasmid. This indicated a competitive advantage to reducing horizontal transmission and allowing increased host replication. Computational simulations predicted that the advantage associated with reduced cost to the host would be maintained over a wide range of environmental conditions and plasmid costs. We infer that vertical transmission in concert with competitive exclusion favour decreased horizontal mobility of plasmids. Similar dynamics may exert evolutionary pressure on parasites, such as temperate bacteriophages and vertically transmitted animal viruses, to limit their rates of horizontal transfer.

Resistance Gene Replacement in the mosquito Culex pipiens: fitness estimation from long-term cline series

How adaptation appears and is later refined by natural selection has been the object of intense theoretical work. However, the testing of these theories is limited by our ability to estimate the strength of natural selection in nature. Using a long-term cline series, we estimate the selection coefficients acting on different alleles at the same locus to analyze the allele replacement observed in the insecticide resistance gene Ester in the mosquito Culex pipiens in the Montpellier area, southern France. Our method allows us to accurately account for the resistance allele replacement observed in this area since 1986. A first resistance allele appeared early, which was replaced by a second resistance allele providing the same advantage but at a lower cost, itself being replaced by a third resistance allele with both higher advantage and cost. It shows that amelioration of the adaptation (here resistance to insecticide) through allele replacement was successively achieved by selection of first a generalist allele (i.e., with a low fitness variance across environments) and later a specialist allele (i.e., with a large fitness variance across environments). More generally, we discuss how precise estimates of the strength of selection obtained from field data help us understand the process of amelioration of adaptation.

Experimental evolution of an essential Bacillus gene in an E. coli host

The acquisition of foreign genes by HGT potentially greatly speeds up adaptation by allowing faster evolution of beneficial traits. The evolutionary integration of novel genes into host gene expression and physiology is critical for adaptation by HGT, but remains largely unknown. We are exploring the evolutionary consequences of gene acquisition in populations of Escherichia coli in real time. A plasmid bearing the genes necessary for sucrose catabolism was constructed and introduced into a single E. coli genotype. Wild-type E. coli is generally incapable of utilizing sucrose, but E. coli transformants were able to grow on sucrose as a sole carbon and energy source, albeit poorly. Twelve replicate populations were initiated and propagated in sucrose minimal media for 300 generations. Over this time, we observed large fitness improvements in the selected environment. These results demonstrate the potential for HGT to substantially increase microbial niche breadth.