Mathematical model of plasmid-mediated resistance to ceftiofur in commensal enteric Escherichia coli of cattle

Contagious acquisition of antimicrobial resistance is critical for explaining emergence in western Canadian feedlots-insights from an agent-based modelling tool

Introduction

Antimicrobial resistance (AMR) is a growing threat to the efficacy of antimicrobials in humans and animals, including those used to control bovine respiratory disease (BRD) in high-risk calves entering western Canadian feedlots. Successful mitigation strategies require an improved understanding of the epidemiology of AMR. Specifically, the relative contributions of antimicrobial use (AMU) and contagious transmission to AMR emergence in animal populations are unknown.

Materials and methods

A stochastic, continuous-time agent-based model (ABM) was developed to explore the dynamics of population-level AMR in Mannheimia haemolytica in pens of high-risk cattle on a typical western Canadian feedlot. The model was directly informed and parameterized with proprietary data from partner veterinary practices and AMU/AMR surveillance data where possible. Hypotheses about how AMR emerges in the feedlot environment were represented by model configurations in which detectable AMR was impacted by (1) only selection arising from AMU; (2) only transmission between animals in the same pen; and (3) both AMU-linked selection and transmission. Automated calibration experiments were used to estimate unknown parameters of interest for select antimicrobial classes. Calibrated parameter values were used in a series of Monte Carlo experiments to generate simulated outputs at both the pen and feedlot levels. Key model outputs included the prevalence of AMR by class at multiple time points across the feeding period. This study compared the relative performances of these model configurations with respect to reproducing empirical AMR data.

Results

Across all antimicrobial classes of interest, model configurations which included the potential for contagious acquisition of AMR offered stronger fits to the empirical data. Notably, sensitivity analyses demonstrated that model outputs were more robust to changes in the assumptions underscoring AMU than to those affecting the likelihood of transmission.

Discussion

This study establishes a feedlot simulation tool that can be used to explore questions related to antimicrobial stewardship in the context of BRD management. The ABM stands out for its unique hierarchical depiction of AMR in a commercial feedlot and its grounding in robust epidemiological data. Future experiments will allow for both AMU-linked selection and transmission of AMR and can accommodate parameter modifications as required.

Quantifying trade-offs between therapeutic efficacy and resistance dissemination for enrofloxacin dose regimens in cattle

The use of antimicrobial drugs in food-producing animals contributes to the selection pressure on pathogenic and commensal bacteria to become resistant. This study aims to evaluate the existence of trade-offs between treatment effectiveness, cost, and the dynamics of resistance in gut commensal bacteria. We developed a within-host ordinary differential equation model to track the dynamics of antimicrobial drug concentrations and bacterial populations in the site of infection (lung) and the gut. The model was parameterized to represent enrofloxacin treatment for bovine respiratory disease (BRD) caused by Pastereulla multocida in cattle. Three approved enrofloxacin dosing regimens were compared for their effects on resistance on P. multocida and commensal E. coli: 12.5 mg/kg and 7.5 mg/kg as a single dose, and 5 mg/kg as three doses. Additionally, we explored non-FDA-approved regimes. Our results indicated that both 12.5 mg/kg and 7.5 mg/kg as a single dose scenario increased the most the treatment costs and prevalence of P. multocida resistance in the lungs, while 5 mg/kg as three doses increased resistance in commensal E. coli bacteria in the gut the most out of the approved scenarios. A proposed non-FDA-approved scenario (7.5 mg/kg, two doses 24 h apart) showed low economic costs, minimal P. multocida, and moderate effects on resistant E. coli. Overall, the scenarios that decrease P. multocida, including resistant P. multocida did not coincide with those that decrease resistant E. coli the most, suggesting a trade-off between both outcomes. The sensitivity analysis suggests that bacterial populations were the most sensitive to drug conversion factors into plasma ( β ), elimination of the drug from the colon ( ϑ ), fifty percent sensitive bacteria (P. multocida) killing effect ( L s50 ), fifty percent of bacteria (E. coli) above ECOFF killing effect ( C r50 ), and net drug transfer rate in the lung ( γ ) parameters.

Modelling the impact of wastewater flows and management practices on antimicrobial resistance in dairy farms

Dairy slurry is a major source of environmental contamination with antimicrobial resistant genes and bacteria. We developed mathematical models and conducted on-farm research to explore the impact of wastewater flows and management practices on antimicrobial resistance (AMR) in slurry. Temporal fluctuations in cephalosporin-resistant Escherichia coli were observed and attributed to farm activities, specifically the disposal of spent copper and zinc footbath into the slurry system. Our model revealed that resistance should be more frequently observed with relevant determinants encoded chromosomally rather than on plasmids, which was supported by reanalysis of sequenced genomes from the farm. Additionally, lower resistance levels were predicted in conditions with lower growth and higher death rates. The use of muck heap effluent for washing dirty channels did not explain the fluctuations in cephalosporin resistance. These results highlight farm-specific opportunities to reduce AMR pollution, beyond antibiotic use reduction, including careful disposal or recycling of waste antimicrobial metals.

Quantifying trade-offs between therapeutic efficacy and resistance dissemination for enrofloxacin dose regimens in cattle

The use of antimicrobial drugs in food-producing animals increases the selection pressure on pathogenic and commensal bacteria to become resistant. This study aims to evaluate the existence of trade-offs between treatment effectiveness, cost, and the dissemination of resistance in gut commensal bacteria. We developed a within-host ordinary differential equation model to track the dynamics of antimicrobial drug concentrations and bacterial populations in the site of infection (lung) and the gut. The model was parameterized to represent enrofloxacin treatment for bovine respiratory disease (BRD) caused by Pastereulla multocida in cattle. Three approved enrofloxacin dosing regimens were compared for their effects on resistance on P. multocida and commensal E. coli: 12.5 mg/kg and 7.5 mg/kg as a single dose, and 5 mg/kg as three doses. Additionally, we explored non-approved regimes. Our results indicated that both 12.5 mg/kg and 7.5 mg/kg as a single dose scenario increased the most the treatment costs and prevalence of P. multocida resistance in the lungs, while 5 mg/kg as three doses increased resistance in commensal E. coli bacteria in the gut the most out of the approved scenarios. A proposed scenario (7.5 mg/kg, two doses 24 hours apart) showed low economic costs, minimal P. multocida, and moderate effects on resistant E. coli. Overall, the scenarios that decrease P. multocida, including resistant P. multocida did not coincide with the scenarios that decrease resistant E. coli the most, suggesting a trade-off between both outcomes. The sensitivity analysis indicates that bacterial populations were the most sensitive to drug conversion factors into plasma (β), elimination of the drug from the colon (υ), fifty percent sensitive bacteria (P. multocida) killing effect (Ls50), fifty percent of bacteria (E. coli) above ECOFF killing effect (Cr50), and net drug transfer rate in the lung (γ) parameters.

Mathematical modelling of antibiotic interaction on evolution of antibiotic resistance: an analytical approach

Background

The emergence and spread of antibiotic-resistant pathogens have led to the exploration of antibiotic combinations to enhance clinical effectiveness and counter resistance development. Synergistic and antagonistic interactions between antibiotics can intensify or diminish the combined therapy's impact. Moreover, these interactions can evolve as bacteria transition from wildtype to mutant (resistant) strains. Experimental studies have shown that the antagonistically interacting antibiotics against wildtype bacteria slow down the evolution of resistance. Interestingly, other studies have shown that antibiotics that interact antagonistically against mutants accelerate resistance. However, it is unclear if the beneficial effect of antagonism in the wildtype bacteria is more critical than the detrimental effect of antagonism in the mutants. This study aims to illuminate the importance of antibiotic interactions against wildtype bacteria and mutants on the deacceleration of antimicrobial resistance.

Methods

To address this, we developed and analyzed a mathematical model that explores the population dynamics of wildtype and mutant bacteria under the influence of interacting antibiotics. The model investigates the relationship between synergistic and antagonistic antibiotic interactions with respect to the growth rate of mutant bacteria acquiring resistance. Stability analysis was conducted for equilibrium points representing bacteria-free conditions, all-mutant scenarios, and coexistence of both types. Numerical simulations corroborated the analytical findings, illustrating the temporal dynamics of wildtype and mutant bacteria under different combination therapies.

Results

Our analysis provides analytical clarification and numerical validation that antibiotic interactions against wildtype bacteria exert a more significant effect on reducing the rate of resistance development than interactions against mutants. Specifically, our findings highlight the crucial role of antagonistic antibiotic interactions against wildtype bacteria in slowing the growth rate of resistant mutants. In contrast, antagonistic interactions against mutants only marginally affect resistance evolution and may even accelerate it.

Conclusion

Our results emphasize the importance of considering the nature of antibiotic interactions against wildtype bacteria rather than mutants when aiming to slow down the acquisition of antibiotic resistance.

Persistent effects of intramammary ceftiofur treatment on the gut microbiome and antibiotic resistance in dairy cattle

BACKGROUND

Intramammary (IMM) ceftiofur treatment is commonly used in dairy farms to prevent mastitis, though its impact on the cattle gut microbiome and selection of antibiotic-resistant bacteria has not been elucidated. Herein, we enrolled 40 dairy (Holstein) cows at the end of the lactation phase for dry-cow therapy: 20 were treated with IMM ceftiofur (Spectramast®DC) and a non-antibiotic internal teat sealant (bismuth subnitrate) and 20 (controls) received only bismuth subnitrate. Fecal grab samples were collected before and after treatment (weeks 1, 2, 3, 5, 7, and 9) for bacterial quantification and metagenomic next-generation sequencing.

RESULTS

Overall, 90% and 24% of the 278 samples had Gram-negative bacteria with resistance to ampicillin and ceftiofur, respectively. Most of the cows treated with ceftiofur did not have an increase in the number of resistant bacteria; however, a subset (25%) shed higher levels of ceftiofur-resistant bacteria for up to 2 weeks post-treatment. At week 5, the antibiotic-treated cows had lower microbiota abundance and richness, whereas a greater abundance of genes encoding extended-spectrum β-lactamases (ESBLs), CfxA, ACI-1, and CMY, was observed at weeks 1, 5 and 9. Moreover, the contig and network analyses detected associations between β-lactam resistance genes and phages, mobile genetic elements, and specific genera. Commensal bacterial populations belonging to Bacteroidetes most commonly possessed ESBL genes followed by members of Enterobacteriaceae.

CONCLUSION

This study highlights variable, persistent effects of IMM ceftiofur treatment on the gut microbiome and resistome in dairy cattle. Antibiotic-treated cattle had an increased abundance of specific taxa and genes encoding ESBL production that persisted for 9 weeks. Fecal shedding of ESBL-producing Enterobacteriaceae, which was classified as a serious public health threat, varied across animals. Together, these findings highlight the need for additional studies aimed at identifying factors associated with shedding levels and the dissemination and persistence of antibiotic resistance determinants on dairy farms across geographic locations.

Standardization and evaluation of indicators for quantifying antimicrobial use on U.S. dairy farms

Antimicrobial resistance (AMR) is a global One Health threat. A portion of AMR development can be attributed to antimicrobial use (AMU) in animals, including dairy cattle. Quantifying AMU on U.S. dairy farms is necessary to inform antimicrobial stewardship strategies and help evaluate the relationship between AMU and AMR. Many AMU indicators have been proposed for quantifying AMU in dairy cattle. However, these indicators are difficult to interpret and compare because they differ in the type of data used, the calculation approach, and the definitions of variables and parameters used in the calculation. Therefore, we selected 16 indicators (count-based, mass-based, and dose-based) applicable for quantifying AMU on U.S. dairy farms. We systematized the indicators by standardizing their variables and parameters to improve their interchangeability, interpretation, and comparability. We scored indicators against six data-driven criteria (assessing their accuracy, data and effort needs, and level of privacy concern) and five stewardship-driven criteria (assessing their ability to capture trends and inform antimicrobial stewardship). The derived standardized indicators will aid farmers and veterinarians in selecting suitable indicators based on data availability and stewardship needs on a farm. The comparison of indicators revealed a trade-off requiring farmers to balance the granularity of data necessary for an accurate indicator and effort to collect the data, and a trade-off relevant to farmers interested in data sharing to inform stewardship because more accurate indicators are typically based on more sensitive information. Indicators with better accuracy tended to score better in stewardship criteria. Overall, two dose-based indicators, estimating the number of treatments and administered doses, scored best in accuracy and stewardship. Conversely, two count-based indicators, estimating the length of AMU, and a mass-based indicator, estimating the mass of administered antimicrobials, performed best in the effort and privacy criteria. These findings are expected to benefit One Health by aiding the uptake of farm-level AMU indicators by U.S. dairy farms.

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.

The pharmacokinetic-pharmacodynamic modelling framework as a tool to predict drug resistance evolution

Pharmacokinetic-pharmacodynamic (PKPD) models, which describe how drug concentrations change over time and how that affects pathogen growth, have proven highly valuable in designing optimal drug treatments aimed at bacterial eradication. However, the fast rise of antimicrobial resistance calls for increased focus on an additional treatment optimization criterion: avoidance of resistance evolution. We demonstrate here how coupling PKPD and population genetics models can be used to determine treatment regimens that minimize the potential for antimicrobial resistance evolution. Importantly, the resulting modelling framework enables the assessment of resistance evolution in response to dynamic selection pressures, including changes in antimicrobial concentration and the emergence of adaptive phenotypes. Using antibiotics and antimicrobial peptides as an example, we discuss the empirical evidence and intuition behind individual model parameters. We further suggest several extensions of this framework that allow a more comprehensive and realistic prediction of bacterial escape from antimicrobials through various phenotypic and genetic mechanisms.

Optimization and Validation of Dosage Regimen for Ceftiofur against Pasteurella multocida in Swine by Physiological Based Pharmacokinetic-Pharmacodynamic Model

Model informed drug development is a valuable tool for drug development and clinical application due to its ability to integrate variability and uncertainty of data. This study aimed to determine an optimal dosage of ceftiofur against P. multocida by ex vivo pharmacokinetic/pharmacodynamic (PK/PD) model and validate the dosage regimens by Physiological based Pharmacokinetic-Pharmacodynamic (PBPK/PD) model. The pharmacokinetic profiles of ceftiofur both in plasma and bronchoalveolar lavage fluid (BALF) are determined. PD performance of ceftiofur against P. multocida was investigated. By establishing PK/PD model, PK/PD parameters and doses were determined. PBPK model and PBPK/PD model were developed to validate the dosage efficacy. The PK/PD parameters, AUC_{0–24 h}/MIC, for bacteriostatic action, bactericidal action and elimination were determined as 44.02, 89.40, and 119.90 h and the corresponding dosages were determined as 0.22, 0.46, and 0.64 mg/kg, respectively. AUC_{24 h}/MIC and AUC _{72 h}/MIC are simulated by PBPK model, compared with the PK/PD parameters, the therapeutic effect can reach probability of target attainment (PTA) of 90%. The time-courses of bacterial growth were predicted by the PBPK/PD model, which indicated the dosage of 0.46 mg/kg body weight could inhibit the bacterial growth and perform good bactericidal effect.

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.

Prevalence of antimicrobial resistance genes and its association with restricted antimicrobial use in food-producing animals: a systematic review and meta-analysis

BACKGROUND

There is ongoing debate regarding potential associations between restrictions of antimicrobial use and prevalence of antimicrobial resistance (AMR) in bacteria.

OBJECTIVES

To summarize the effects of interventions reducing antimicrobial use in food-producing animals on the prevalence of AMR genes (ARGs) in bacteria from animals and humans.

METHODS

We published a full systematic review of restrictions of antimicrobials in food-producing animals and their associations with AMR in bacteria. Herein, we focus on studies reporting on the association between restricted antimicrobial use and prevalence of ARGs. We used multilevel mixed-effects models and a semi-quantitative approach based on forest plots to summarize findings from studies.

RESULTS

A positive effect of intervention [reduction in prevalence or number of ARGs in group(s) with restricted antimicrobial use] was reported from 29 studies for at least one ARG. We detected significant associations between a ban on avoparcin and diminished presence of the vanA gene in samples from animals and humans, whereas for the mecA gene, studies agreed on a positive effect of intervention in samples only from animals. Comparisons involving mcr-1, blaCTX-M, aadA2, vat(E), sul2, dfrA5, dfrA13, tet(E) and tet(P) indicated a reduced prevalence of genes in intervention groups. Conversely, no effects were detected for β-lactamases other than blaCTX-M and the remaining tet genes.

CONCLUSIONS

The available body of scientific evidence supported that restricted use of antimicrobials in food animals was associated with an either lower or equal presence of ARGs in bacteria, with effects dependent on ARG, host species and restricted drug.

Towards a general model for predicting minimal metal concentrations co-selecting for antibiotic resistance plasmids

Many antibiotic resistance genes co-occur with resistance genes for transition metals, such as copper, zinc, or mercury. In some environments, a positive correlation between high metal concentration and high abundance of antibiotic resistance genes has been observed, suggesting co-selection due to metal presence. Of particular concern is the use of copper and zinc in animal husbandry, leading to potential co-selection for antibiotic resistance in animal gut microbiomes, slurry, manure, or amended soils. For antibiotics, predicted no effect concentrations have been derived from laboratory measured minimum inhibitory concentrations and some minimal selective concentrations have been investigated in environmental settings. However, minimal co-selection concentrations for metals are difficult to identify. Here, we use mathematical modelling to provide a general mechanistic framework to predict minimal co-selective concentrations for metals, given knowledge of their toxicity at different concentrations. We apply the method to copper (Cu), zinc (Zn), mercury (Hg), lead (Pb) and silver (Ag), predicting their minimum co-selective concentrations in mg/L (Cu: 5.5, Zn: 1.6, Hg: 0.0156, Pb: 21.5, Ag: 0.152). To exemplify use of these thresholds, we consider metal concentrations from slurry and slurry-amended soil from a UK dairy farm that uses copper and zinc as additives for feed and antimicrobial footbath: the slurry is predicted to be co-selective, but not the slurry-amended soil. This modelling framework could be used as the basis for defining standards to mitigate risks of antimicrobial resistance applicable to a wide range of environments, including manure, slurry and other waste streams.

Antibiotics and Antibiotic Resistance Genes in Animal Manure - Consequences of Its Application in Agriculture

Antibiotic resistance genes (ARGs) are a relatively new type of pollutant. The rise in antibiotic resistance observed recently is closely correlated with the uncontrolled and widespread use of antibiotics in agriculture and the treatment of humans and animals. Resistant bacteria have been identified in soil, animal feces, animal housing (e.g., pens, barns, or pastures), the areas around farms, manure storage facilities, and the guts of farm animals. The selection pressure caused by the irrational use of antibiotics in animal production sectors not only promotes the survival of existing antibiotic-resistant bacteria but also the development of new resistant forms. One of the most critical hot-spots related to the development and dissemination of ARGs is livestock and poultry production. Manure is widely used as a fertilizer thanks to its rich nutrient and organic matter content. However, research indicates that its application may pose a severe threat to human and animal health by facilitating the dissemination of ARGs to arable soil and edible crops. This review examines the pathogens, potentially pathogenic microorganisms and ARGs which may be found in animal manure, and evaluates their effect on human health through their exposure to soil and plant resistomes. It takes a broader view than previous studies of this topic, discussing recent data on antibiotic use in farm animals and the effect of these practices on the composition of animal manure; it also examines how fertilization with animal manure may alter soil and crop microbiomes, and proposes the drivers of such changes and their consequences for human health.

A Model to Investigate the Impact of Farm Practice on Antimicrobial Resistance in UK Dairy Farms

The ecological and human health impact of antibiotic use and the related antimicrobial resistance (AMR) in animal husbandry is poorly understood. In many countries, there has been considerable pressure to reduce overall antibiotic use in agriculture or to cease or minimise use of human critical antibiotics. However, a more nuanced approach would consider the differential impact of use of different antibiotic classes; for example, it is not known whether reduced use of bacteriostatic or bacteriolytic classes of antibiotics would be of greater value. We have developed an ordinary differential equation model to investigate the effects of farm practice on the spread and persistence of AMR in the dairy slurry tank environment. We model the chemical fate of bacteriolytic and bacteriostatic antibiotics within the slurry and their effect on a population of bacteria, which are capable of resistance to both types of antibiotic. Through our analysis, we find that changing the rate at which a slurry tank is emptied may delay the proliferation of multidrug-resistant bacteria by up to five years depending on conditions. This finding has implications for farming practice and the policies that influence waste management practices. We also find that, within our model, the development of multidrug resistance is particularly sensitive to the use of bacteriolytic antibiotics, rather than bacteriostatic antibiotics, and this may be cause for controlling the usage of bacteriolytic antibiotics in agriculture.

Impact of Ceftiofur Administration in Steers on the Prevalence and Antimicrobial Resistance of Campylobacter spp

Bacterial resistance to ceftiofur raises health concerns due to ceftiofur’s extensive veterinary usage and structural similarity with the human antibiotic ceftriaxone. Ceftiofur crystalline-free acid (CCFA) and ceftiofur hydrochloride (CHCL) are ceftiofur types used therapeutically in cattle, but their potential impacts on Campylobacter prevalence and antimicrobial resistance remain unclear. In this study two groups of steers were each treated with CCFA or CHCL. In vivo active drug concentrations were measured and fecal samples were analyzed for Campylobacter for up to 42 days post-treatment. Following administration, the colonic concentration of ceftiofur initially increased then dropped to pre-treatment levels by day 8. The estimated prevalence of Campylobacter spp. was significantly (p = 0.0009) higher during the first week after CCFA treatment than after CHCL treatment (81.3% vs. 45.2%). Campylobacter jejuni predominated overall, with other Campylobacter spp. mainly identified in the first week after CCFA treatment. No treatment impacts were noted on ceftiofur minimum inhibitory concentration (MIC) for C. jejuni (10–20 μg/mL). More C. jejuni genotypes were detected in CCFA-treated than CHCL-treated steers. These findings suggest that ceftiofur did not significantly impact Campylobacter prevalence or ceftiofur MIC. However, CHCL may be preferable due to the lower likelihood of temporary increases in Campylobacter prevalence.

Transcriptome changes and polymyxin resistance of acid-adapted Escherichia coli O157:H7 ATCC 43889

Background

Acid treatment is commonly used for controlling or killing pathogenic microorganisms on medical devices and environments; however, inadequate acid treatment may cause acid tolerance response (ATR) and offer cross-protection against environmental stresses, including antimicrobials. This study aimed to characterise an Escherichia coli strain that can survive in the acidic gastrointestinal environment.

Results

We developed an acid-tolerant E. coli O157:H7 ATCC 43889 (ATCC 43889) strain that can survive at pH 2.75 via cell adaptation in low pH conditions. We also performed RNA sequencing and qRT-PCR to compare differentially expressed transcripts between acid-adapted and non-adapted cells. Genes related to stress resistance, including kdpA and bshA were upregulated in the acid-adapted ATCC 43889 strain. Furthermore, the polymyxin resistance gene arnA was upregulated in the acid-adapted cells, and resistance against polymyxin B and colistin (polymyxin E) was observed. As polymyxins are important antibiotics, effective against multidrug-resistant gram-negative bacterial infections, the emergence of polymyxin resistance in acid-adapted E. coli is a serious public health concern.

Conclusion

The transcriptomic and phenotypic changes analysed in this study during the adaptation of E. coli to acid environments can provide useful information for developing intervention technologies and mitigating the risk associated with the emergence and spread of antimicrobial resistance.

A generalised model for generalised transduction: the importance of co-evolution and stochasticity in phage mediated antimicrobial resistance transfer

Antimicrobial resistance is a major global challenge. Of particular concern are mobilizable elements that can transfer resistance genes between bacteria, leading to pathogens with new combinations of resistance. To date, mathematical models have largely focussed on transfer of resistance by plasmids, with fewer studies on transfer by bacteriophages. We aim to understand how best to model transfer of resistance by transduction by lytic phages. We show that models of lytic bacteriophage infection with empirically derived realistic phage parameters lead to low numbers of bacteria, which, in low population or localised environments, lead to extinction of bacteria and phage. Models that include antagonistic co-evolution of phage and bacteria produce more realistic results. Furthermore, because of these low numbers, stochastic dynamics are shown to be important, especially to spread of resistance. When resistance is introduced, resistance can sometimes be fixed, and at other times die out, with the probability of each outcome sensitive to bacterial and phage parameters. Specifically, that outcome most strongly depends on the baseline death rate of bacteria, with phage-mediated spread favoured in benign environments with low mortality over more hostile environments. We conclude that larger-scale models should consider spatial compartmentalisation and heterogeneous microenviroments, while encompassing stochasticity and co-evolution.

Modeling transport of antibiotic resistant bacteria in aquatic environment using stochastic differential equations

Contaminated sites are recognized as the "hotspot" for the development and spread of antibiotic resistance in environmental bacteria. It is very challenging to understand mechanism of development of antibiotic resistance in polluted environment in the presence of different anthropogenic pollutants. Uncertainties in the environmental processes adds complexity to the development of resistance. This study attempts to develop mathematical model by using stochastic partial differential equations for the transport of fluoroquinolone and its resistant bacteria in riverine environment. Poisson's process is assumed for the diffusion approximation in the stochastic partial differential equations (SPDE). Sensitive analysis is performed to evaluate the parameters and variables for their influence over the model outcome. Based on their sensitivity, the model parameters and variables are chosen and classified into environmental, demographic, and anthropogenic categories to investigate the sources of stochasticity. Stochastic partial differential equations are formulated for the state variables in the model. This SPDE model is then applied to the 100 km stretch of river Musi (South India) and simulations are carried out to assess the impact of stochasticity in model variables on the resistant bacteria population in sediments. By employing the stochasticity in model variables and parameters we came to know that environmental and anthropogenic variations are not able to affect the resistance dynamics at all. Demographic variations are able to affect the distribution of resistant bacteria population uniformly with standard deviation between 0.087 and 0.084, however, is not significant to have any biological relevance to it. The outcome of the present study is helpful in simplifying the model for practical applications. This study is an ongoing effort to improve the model for the transport of antibiotics and transport of antibiotic resistant bacteria in polluted river. There is a wide gap between the knowledge of stochastic resistant bacterial growth dynamics and the knowledge of transport of antibiotic resistance in polluted aquatic environment, this study is one step towards filling up that gap.

A One Health Comparative Assessment of Antimicrobial Resistance in Generic and Extended-Spectrum Cephalosporin-Resistant Escherichia coli from Beef Production, Sewage and Clinical Settings

This study aimed to compare antimicrobial resistance (AMR) in extended-spectrum cephalosporin-resistant and generic Escherichia coli from a One Health continuum of the beef production system in Alberta, Canada. A total of 705 extended-spectrum cephalosporin-resistant E. coli (ESC^r) were obtained from: cattle feces (CFeces, n = 382), catch basins (CBasins, n = 137), surrounding streams (SStreams, n = 59), beef processing plants (BProcessing, n = 4), municipal sewage (MSewage; n = 98) and human clinical specimens (CHumans, n = 25). Generic isolates (663) included: CFeces (n = 142), CBasins (n = 185), SStreams (n = 81), BProcessing (n = 159) and MSewage (n = 96). All isolates were screened for antimicrobial susceptibility to 9 antimicrobials and two clavulanic acid combinations. In ESC^r, oxytetracycline (87.7%), ampicillin (84.4%) and streptomycin (73.8%) resistance phenotypes were the most common, with source influencing AMR prevalence (p < 0.001). In generic E. coli, oxytetracycline (51.1%), streptomycin (22.6%), ampicillin (22.5%) and sulfisoxazole (14.3%) resistance were most common. Overall, 88.8% of ESC^r, and 26.7% of generic isolates exhibited multi-drug resistance (MDR). MDR in ESC^r was high from all sources: CFeces (97.1%), MSewage (96.9%), CHumans (96%), BProcessing (100%), CBasins (70.5%) and SStreams (61.4%). MDR in generic E. coli was lower with CFeces (45.1%), CBasins (34.6%), SStreams (23.5%), MSewage (13.6%) and BProcessing (10.7%). ESBL phenotypes were confirmed in 24.7% (n = 174) ESC^r and 0.6% of generic E. coli. Prevalence of bla genes in ESC^r were bla_CTXM (30.1%), bla_CTXM-1 (21.6%), bla_TEM (20%), bla_CTXM-9 (7.9%), bla_OXA (3.0%), bla_CTXM-2 (6.4%), bla_SHV (1.4%) and AmpC β-lactamase bla_CMY (81.3%). The lower AMR in ESC^r from SStreams and BProcessing and higher AMR in CHumans and CFeces likely reflects antimicrobial use in these environments. Although MDR levels were higher in ESC^r as compared to generic E. coli, AMR to the same antimicrobials ranked high in both ESC^r and generic E. coli sub-populations. This suggests that both sub-populations reflect similar AMR trends and are equally useful for AMR surveillance. Considering that MDR ESC^r MSewage isolates were obtained without enrichment, while those from CFeces were obtained with enrichment, MSewage may serve as a hot spot for MDR emergence and dissemination.

The effect of enrofloxacin on enteric Escherichia coli: Fitting a mathematical model to in vivo data

Antimicrobial drugs administered systemically may cause the emergence and dissemination of antimicrobial resistance among enteric bacteria. To develop logical, research-based recommendations for food animal veterinarians, we must understand how to maximize antimicrobial drug efficacy while minimizing risk of antimicrobial resistance. Our objective is to evaluate the effect of two approved dosing regimens of enrofloxacin (a single high dose or three low doses) on Escherichia coli in cattle. We look specifically at bacteria above and below the epidemiological cutoff (ECOFF), above which the bacteria are likely to have an acquired or mutational resistance to enrofloxacin. We developed a differential equation model for the antimicrobial drug concentrations in plasma and colon, and bacteria populations in the feces. The model was fit to animal data of drug concentrations in the plasma and colon obtained using ultrafiltration probes. Fecal E. coli counts and minimum inhibitory concentrations were measured for the week after receiving the antimicrobial drug. We predict that the antimicrobial susceptibility of the bacteria above the ECOFF pre-treatment strongly affects the composition of the bacteria following treatment. Faster removal of the antimicrobial drugs from the colon throughout the study leads to improved clearance of bacteria above the ECOFF in the low dose regimen. If we assume a fitness cost is associated with bacteria above the ECOFF, the increased fitness costs leads to reduction of bacteria above the ECOFF in the low dose study. These results suggest the initial E. coli susceptibility is a strong indicator of how steers respond to antimicrobial drug treatment.

Mathematical modelling to study the horizontal transfer of antimicrobial resistance genes in bacteria: current state of the field and recommendations

Antimicrobial resistance (AMR) is one of the greatest public health challenges we are currently facing. To develop effective interventions against this, it is essential to understand the processes behind the spread of AMR. These are partly dependent on the dynamics of horizontal transfer of resistance genes between bacteria, which can occur by conjugation (direct contact), transformation (uptake from the environment) or transduction (mediated by bacteriophages). Mathematical modelling is a powerful tool to investigate the dynamics of AMR; however, the extent of its use to study the horizontal transfer of AMR genes is currently unclear. In this systematic review, we searched for mathematical modelling studies that focused on horizontal transfer of AMR genes. We compared their aims and methods using a list of predetermined criteria and used our results to assess the current state of this research field. Of the 43 studies we identified, most focused on the transfer of single genes by conjugation in Escherichia coli in culture and its impact on the bacterial evolutionary dynamics. Our findings highlight the existence of an important research gap in the dynamics of transformation and transduction and the overall public health implications of horizontal transfer of AMR genes. To further develop this field and improve our ability to control AMR, it is essential that we clarify the structural complexity required to study the dynamics of horizontal gene transfer, which will require cooperation between microbiologists and modellers.

PK/PD modeling of Ceftiofur Sodium against Haemophilus parasuis infection in pigs

BACKGROUND

Ceftiofur Sodium is widely used in China. Our aim was to determine Ceftiofur Sodium activity and optimize dosing regimens against the pathogen Haemophilus parasuis using an in vitro and ex vivo pharmacokinetics/pharmacodynamics modeling approach. By adopting these strategies, we wanted to extend the effective life of Ceftiofur Sodium in reduce drug-resistance in pigs.

RESULTS

We established an H. parasuis infection model in pigs, and assessed the pharmacokinetics of Ceftiofur Sodium in both healthy and infected animals. After Ceftiofur Sodium (10 mg/kg, i.m.) administration to healthy and H. parasuis-infected pigs, plasma based desfuroylceftiofur (a metabolite of Ceftiofur Sodium) was measured by High Performance Liquid Chromatography. The pharmacokinetics of Ceftiofur Sodium (desfuroylceftiofur) was consistent with a two-compartment open model, with first-order absorption. We observed no significant differences (P > 0.05) in pharmacokinetic parameters between healthy and infected pigs. Pharmacodynamics data showed that Ceftiofur Sodium was highly inhibitory against H. parasuis, with MIC, MBC, and MPC values of 0.003125, 0.0125 and 0.032 μg/mL, respectively. Desfuroylceftiofur in plasma also had strong bactericidal activity. Almost all H. parasuis cultured in plasma medium of Ceftiofur Sodium-inoculated healthy pigs, at each time point, were killed within 24 h. A weaker antibacterial activity was measured in infected-pig plasma medium at 18, 24, 36, and 48 h, after Ceftiofur Sodium inoculation. Pharmacokinetic parameters were combined with ex vivo pharmacodynamic parameters, and the bacteriostatic effect (36.006 h), bactericidal effect (71.637 h) and clearance (90.619 h) within 24 h, were determined using the Hill equation. Dose-calculation equations revealed the optimal dose of Ceftiofur Sodium to be 0.599-1.507 mg/kg.

CONCLUSIONS

There were no significant differences in Ceftiofur Sodium pharmacokinetic parameters between healthy and infected pigs, although pharmacokinetics/pharmacodynamics fitting curves showed obviously differences. The optimal dose of Ceftiofur Sodium was lower than recommended (3 mg/kg), which may provide improved treatments for Glässers disease, with lower drug-resistance possibility.

Application of dynamic modelling techniques to the problem of antibacterial use and resistance: a scoping review

Selective pressure exerted by the widespread use of antibacterial drugs is accelerating the development of resistant bacterial populations. The purpose of this scoping review was to summarise the range of studies that use dynamic models to analyse the problem of bacterial resistance in relation to antibacterial use in human and animal populations. A comprehensive search of the peer-reviewed literature was performed and non-duplicate articles (n = 1486) were screened in several stages. Charting questions were used to extract information from the articles included in the final subset (n = 81). Most studies (86%) represent the system of interest with an aggregate model; individual-based models are constructed in only seven articles. There are few examples of inter-host models outside of human healthcare (41%) and community settings (38%). Resistance is modelled for a non-specific bacterial organism and/or antibiotic in 40% and 74% of the included articles, respectively. Interventions with implications for antibacterial use were investigated in 67 articles and included changes to total antibiotic consumption, strategies for drug management and shifts in category/class use. The quality of documentation related to model assumptions and uncertainty varies considerably across this subset of articles. There is substantial room to improve the transparency of reporting in the antibacterial resistance modelling literature as is recommended by best practice guidelines.

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.

Effects of intramuscularly administered enrofloxacin on the susceptibility of commensal intestinal Escherichia coli in pigs (sus scrofa domestica)

BACKGROUND

In the European Union, various fluoroquinolones are authorised for the treatment of food producing animals. Each administration poses an increased risk of development and spread of antimicrobial resistance. The aim of this study was to investigate the impact of parenteral administration of enrofloxacin on the prevalence of enrofloxacin and ciprofloxacin susceptibilities in the commensal intestinal E. coli population.

METHODS

E. coli isolates from faeces of twelve healthy pigs were included. Six pigs were administered enrofloxacin on day 1 to 3 and after two weeks for further three days. The other pigs formed the control group. MIC values were determined. Virulence and resistance genes were detected by PCR. Phylogenetic grouping was performed by PCR. Enrofloxacin and ciprofloxacin were analysed in sedimentation samples by HPLC.

RESULTS

Susceptibility shifts in commensal E. coli isolates were determined in both groups. Non-wildtype E. coli could be cultivated from two animals of the experimental group for the first time one week after the first administration and from one animal of the control group on day 28. The environmental load with enrofloxacin in sedimentation samples showed the highest amount between days one and five. The repeated parenteral administration of enrofloxacin to pigs resulted in rapidly increased MIC values (day 28: MIC up to 4 mg/L, day 35: MIC ≥ 32mg/L). E. coli populations of the control group in the same stable without direct contact to the experimental group were affected.

CONCLUSION

The parenteral administration of enrofloxacin to piglets considerably reduced the number of the susceptible intestinal E. coli population which was replaced by E. coli strains with increased MIC values against enrofloxacin. Subsequently also pigs of the control were affected suggesting a transferability of strains from the experimental group through the environment to the control group especially as we could isolate the same PFGE strains from both pig groups and the environment.

Monte Carlo Simulations Suggest Current Chlortetracycline Drug-Residue Based Withdrawal Periods Would Not Control Antimicrobial Resistance Dissemination from Feedlot to Slaughterhouse

Antimicrobial use in beef cattle can increase antimicrobial resistance prevalence in their enteric bacteria, including potential pathogens such as Escherichia coli. These bacteria can contaminate animal products at slaughterhouses and cause food-borne illness, which can be difficult to treat if it is due to antimicrobial resistant bacteria. One potential intervention to reduce the dissemination of resistant bacteria from feedlot to consumer is to impose a withdrawal period after antimicrobial use, similar to the current withdrawal period designed to prevent drug residues in edible animal meat. We investigated tetracycline resistance in generic E. coli in the bovine large intestine during and after antimicrobial treatment by building a mathematical model of oral chlortetracycline pharmacokinetics-pharmacodynamics and E. coli population dynamics. We tracked three E. coli subpopulations (susceptible, intermediate, and resistant) during and after treatment with each of three United States chlortetracycline indications (liver abscess reduction, disease control, disease treatment). We compared the proportion of resistant E. coli before antimicrobial use to that at several time points after treatment and found a greater proportion of resistant enteric E. coli after the current withdrawal periods than prior to treatment. In order for the proportion of resistant E. coli in the median beef steer to return to the pre-treatment level, withdrawal periods of 15 days after liver abscess reduction dosing (70 mg daily), 31 days after disease control dosing (350 mg daily), and 36 days after disease treatment dosing (22 mg/kg bodyweight for 5 days) are required in this model. These antimicrobial resistance withdrawal periods would be substantially longer than the current U.S. withdrawals of 0–2 days or Canadian withdrawals of 5–10 days. One published field study found similar time periods necessary to reduce the proportion of resistant E. coli following chlortetracycline disease treatment to those suggested by this model, but additional carefully designed field studies are necessary to confirm the model results. This model is limited to biological processes within the cattle and does not include resistance selection in the feedlot environment or co-selection of chlortetracycline resistance following other antimicrobial use.

A novel method for synthesis of α-spinasterol and its antibacterial activities in combination with ceftiofur

In this study, we designed a novel method of the synthesis of α-spinasterol from commercially available stigmasterol and explored the combinational effect of the α-spinasterol with ceftiofur in vitro against S. pullorum cvcc533, S. pneumoniae CAU0070, E. coli, and S. aureus. α-Spinasterol was obtained by a key reaction of Bamford-Stevens reaction with a desirable yield for five steps. The combination of α-spinasterol and ceftiofur showed stronger synergetic effect against the four pathogenic strains compared with that of stigmasterol and ceftiofur alone. In time-kill analyses, at concentrations above the MICs, ceftiofur in combination with α-spinasterol exhibited time-dependency and concentration-dependency comparing to time dependency with ceftiofur alone. We conclude that the combination usage of α-spinasterol and ceftiofur is an effective and promising strategy against the four pathogenic bacterial strains in vitro.

A proposed analytic framework for determining the impact of an antimicrobial resistance intervention

Antimicrobial use (AMU) is increasingly threatened by antimicrobial resistance (AMR). The FDA is implementing risk mitigation measures promoting prudent AMU in food animals. Their evaluation is crucial: the AMU/AMR relationship is complex; a suitable framework to analyze interventions is unavailable. Systems science analysis, depicting variables and their associations, would help integrate mathematics/epidemiology to evaluate the relationship. This would identify informative data and models to evaluate interventions. This National Institute for Mathematical and Biological Synthesis AMR Working Group's report proposes a system framework to address the methodological gap linking livestock AMU and AMR in foodborne bacteria. It could evaluate how AMU (and interventions) impact AMR. We will evaluate pharmacokinetic/dynamic modeling techniques for projecting AMR selection pressure on enteric bacteria. We study two methods to model phenotypic AMR changes in bacteria in the food supply and evolutionary genotypic analyses determining molecular changes in phenotypic AMR. Systems science analysis integrates the methods, showing how resistance in the food supply is explained by AMU and concurrent factors influencing the whole system. This process is updated with data and techniques to improve prediction and inform improvements for AMU/AMR surveillance. Our proposed framework reflects both the AMR system's complexity, and desire for simple, reliable conclusions.

Circulating of CMY-2 β-lactamase gene in weaned pigs and their environment in a commercial farm and the effect of feed supplementation with a clay mineral

AIMS

To investigate the mechanisms leading to an increase in the prevalence of blaCMY -2 conferring resistance to ceftiofur in pigs receiving a feed medicated with chlortetracycline and penicillin, and to examine the effect of supplementation with a clay mineral on this phenomenon.

METHODS AND RESULTS

In 138 blaCMY -2 -positive Escherichia coli isolates from faeces of pigs receiving feed supplemented or not with 2% clinoptilolite, from day 2 to day 28 after weaning, isolates from the two groups differed significantly with respect to their phylogenetic group: phylotype A predominated in the supplemented group, whereas phylotypes B1 and D predominated in the control group, as determined by PCR. In 36 representative isolates, pulsed-field gel electrophoresis and antimicrobial susceptibility testing revealed that the blaCMY -2 -positive E. coli isolates were polyclonal with diverse antimicrobial resistance patterns and blaCMY -2 -carrying plasmids of incompatibility (Inc) groups, A/C, I1 and ColE were observed in transformants as detected by PCR. Enterobacter cloacae possessing blaCMY -2 -carrying IncA/C plasmids were found in the pens before introduction of this batch of pigs. The blaCMY -2 -positive E. coli isolates were more clonally diverse in the control group than the supplemented group.

CONCLUSIONS

The blaCMY -2 gene appears to have spread both horizontally and clonally in this batch of pigs and may have spread from previous batches of pigs via plasmids carried by Ent. cloacae and expanded in animals of the present batch in the presence of the selection pressure due to administration of chlortetracycline and penicillin in the feed. Feed supplementation may have an effect on clonal diversity of blaCMY -2 -positive isolates.

SIGNIFICANCE AND IMPACT OF THE STUDY

Implementation of improved hygiene measures, decreased administration of certain antimicrobials on farm and feed supplementation with certain ingredients may limit antimicrobial resistance spread between and within batches of animals.

Models of antimicrobial pressure on intestinal bacteria of the treated host populations

Antimicrobial drugs are used to treat pathogenic bacterial infections in animals and humans. The by-stander enteric bacteria of the treated host's intestine can become exposed to the drug or its metabolites reaching the intestine in antimicrobially active form. We consider which processes and variables need to be accounted for to project the antimicrobial concentrations in the host's intestine. Those include: the drug's fraction (inclusive of any active metabolites) excreted in bile; the drug's fractions and intestinal segments of excretion via other mechanisms; the rates and intestinal segments of the drug's absorption and re-absorption; the rates and intestinal segments of the drug's abiotic and biotic degradation in the intestine; the digesta passage time through the intestinal segments; the rates, mechanisms, and reversibility of the drug's sorption to the digesta and enteric microbiome; and the volume of luminal contents in the intestinal segments. For certain antimicrobials, the antimicrobial activity can further depend on the aeration and chemical conditions in the intestine. Model forms that incorporate the inter-individual variation in those relevant variables can support projections of the intestinal antimicrobial concentrations in populations of treated host, such as food animals. To illustrate the proposed modeling framework, we develop two examples of treatments of bovine respiratory disease in beef steers by oral chlortetracycline and injectable third-generation cephalosporin ceftiofur. The host's diet influences the digesta passage time, volume, and digesta and microbiome composition, and may influence the antimicrobial loss due to degradation and sorption in the intestine. We consider two diet compositions in the illustrative simulations. The examples highlight the extent of current ignorance and need for empirical data on the variables influencing the selective pressures imposed by antimicrobial treatments on the host's intestinal bacteria.

Modelling of tetracycline resistance gene transfer by commensal Escherichia coli food isolates that survived in gastric fluid conditions

Antimicrobial resistance (AR) is a major public health concern and a food safety issue worldwide. Escherichia coli strains, indicators of antibiotic resistance, are a source of horizontal gene transfer to other bacteria in the human intestinal system. A probabilistic exposure model was used to estimate the transfer of the AR gene tet(A). The acid resistance and kinetic behaviour of E. coli was analysed as a function of pH to describe the inactivation of E. coli in simulated gastric fluid (SGF), the major host barrier against exogenous micro-organisms. The kinetic parameters of microbial inactivation in SGF were estimated using GInaFiT, and log-linear + tail and Weibull models were found to be suitable for commensal and enterohaemorrhagic E. coli (EHEC), respectively. A probabilistic exposure model was developed to estimate E. coli survival in gastric pH conditions as well as gene transfer from resistant to susceptible cells in humans. E. coli-contaminated retail foods for consumption without further cooking and gastric pH data in South Korea were considered as an example. The model predicts that 22-33% of commensal E. coli can survive under gastric pH conditions of Koreans. The estimated total mean tet(A) transfer level by commensal E. coli was 1.68 × 10^-4-8.15 × 10^-4 log CFU/mL/h. The inactivation kinetic parameters of E. coli in SGF and the quantitative exposure model can provide useful information regarding risk management options to control the spread of AR.

Mathematical Modeling Tools to Study Preharvest Food Safety

This article provides an overview of the emerging field of mathematical modeling in preharvest food safety. We describe the steps involved in developing mathematical models, different types of models, and their multiple applications. The introduction to modeling is followed by several sections that introduce the most common modeling approaches used in preharvest systems. We finish the chapter by outlining potential future directions for the field.

Modeling the growth dynamics of multiple Escherichia coli strains in the pig intestine following intramuscular ampicillin treatment

Background

This study evaluated how dosing regimen for intramuscularly-administered ampicillin, composition of Escherichia coli strains with regard to ampicillin susceptibility, and excretion of bacteria from the intestine affected the level of resistance among Escherichia coli strains in the intestine of nursery pigs. It also examined the dynamics of the composition of bacterial strains during and after the treatment. The growth responses of strains to ampicillin concentrations were determined using in vitro growth curves. Using these results as input data, growth predictions were generated using a mathematical model to simulate the competitive growth of E. coli strains in a pig intestine under specified plasma concentration profiles of ampicillin.

Results

In vitro growth results demonstrated that the resistant strains did not carry a fitness cost for their resistance, and that the most susceptible strains were more affected by increasing concentrations of antibiotics that the rest of the strains. The modeling revealed that short treatment duration resulted in lower levels of resistance and that dosing frequency did not substantially influence the growth of resistant strains. Resistance levels were found to be sensitive to the number of competing strains, and this effect was enhanced by longer duration of treatment. High excretion of bacteria from the intestine favored resistant strains over sensitive strains, but at the same time it resulted in a faster return to pre-treatment levels after the treatment ended. When the duration of high excretion was set to be limited to the treatment time (i.e. the treatment was assumed to result in a cure of diarrhea) resistant strains required longer time to reach the previous level.

Conclusion

No fitness cost was found to be associated with ampicillin resistance in E. coli. Besides dosing factors, epidemiological factors (such as number of competing strains and bacterial excretion) influenced resistance development and need to be considered further in relation to optimal treatment strategies. The modeling approach used in the study is generic, and could be used for prediction of the effect of treatment with other drugs and other administration routes for effect on resistance development in the intestine of pigs.

Electronic supplementary material

The online version of this article (doi:10.1186/s12866-016-0823-3) contains supplementary material, which is available to authorized users.

Multistrain models predict sequential multidrug treatment strategies to result in less antimicrobial resistance than combination treatment

Background

Combination treatment is increasingly used to fight infections caused by bacteria resistant to two or more antimicrobials. While multiple studies have evaluated treatment strategies to minimize the emergence of resistant strains for single antimicrobial treatment, fewer studies have considered combination treatments. The current study modeled bacterial growth in the intestine of pigs after intramuscular combination treatment (i.e. using two antibiotics simultaneously) and sequential treatments (i.e. alternating between two antibiotics) in order to identify the factors that favor the sensitive fraction of the commensal flora.

Growth parameters for competing bacterial strains were estimated from the combined in vitro pharmacodynamic effect of two antimicrobials using the relationship between concentration and net bacterial growth rate. Predictions of in vivo bacterial growth were generated by a mathematical model of the competitive growth of multiple strains of Escherichia coli.

Results

Simulation studies showed that sequential use of tetracycline and ampicillin reduced the level of double resistance, when compared to the combination treatment. The effect of the cycling frequency (how frequently antibiotics are alternated in a sequential treatment) of the two drugs was dependent upon the order in which the two drugs were used.

Conclusion

Sequential treatment was more effective in preventing the growth of resistant strains when compared to the combination treatment. The cycling frequency did not play a role in suppressing the growth of resistant strains, but the specific order of the two antimicrobials did. Predictions made from the study could be used to redesign multidrug treatment strategies not only for intramuscular treatment in pigs, but also for other dosing routes.

Electronic supplementary material

The online version of this article (doi:10.1186/s12866-016-0724-5) contains supplementary material, which is available to authorized users.

Antimicrobial Susceptibility of Enteric Gram Negative Facultative Anaerobe Bacilli in Aerobic versus Anaerobic Conditions

Antimicrobial treatments result in the host’s enteric bacteria being exposed to the antimicrobials. Pharmacodynamic models can describe how this exposure affects the enteric bacteria and their antimicrobial resistance. The models utilize measurements of bacterial antimicrobial susceptibility traditionally obtained in vitro in aerobic conditions. However, in vivo enteric bacteria are exposed to antimicrobials in anaerobic conditions of the lower intestine. Some of enteric bacteria of food animals are potential foodborne pathogens, e.g., Gram-negative bacilli Escherichia coli and Salmonella enterica. These are facultative anaerobes; their physiology and growth rates change in anaerobic conditions. We hypothesized that their antimicrobial susceptibility also changes, and evaluated differences in the susceptibility in aerobic vs. anaerobic conditions of generic E. coli and Salmonella enterica of diverse serovars isolated from cattle feces. Susceptibility of an isolate was evaluated as its minimum inhibitory concentration (MIC) measured by E-Test^® following 24 hours of adaptation to the conditions on Mueller-Hinton agar, and on a more complex tryptic soy agar with 5% sheep blood (BAP) media. We considered all major antimicrobial drug classes used in the U.S. to treat cattle: β-lactams (specifically, ampicillin and ceftriaxone E-Test^®), aminoglycosides (gentamicin and kanamycin), fluoroquinolones (enrofloxacin), classical macrolides (erythromycin), azalides (azithromycin), sulfanomides (sulfamethoxazole/trimethoprim), and tetracyclines (tetracycline). Statistical analyses were conducted for the isolates (n≥30) interpreted as susceptible to the antimicrobials based on the clinical breakpoint interpretation for human infection. Bacterial susceptibility to every antimicrobial tested was statistically significantly different in anaerobic vs. aerobic conditions on both media, except for no difference in susceptibility to ceftriaxone on BAP agar. A satellite experiment suggested that during first days in anaerobic conditions the susceptibility changes with time. The results demonstrate that assessing effects of antimicrobial treatments on resistance in the host’s enteric bacteria that are Gram negative facultative Anaerobe Bacilli requires data on the bacterial antimicrobial susceptibility in the conditions resembling those in the intestine.

Mathematical modelling of antimicrobial resistance in agricultural waste highlights importance of gene transfer rate

Antimicrobial resistance is of global concern. Most antimicrobial use is in agriculture; manures and slurry are especially important because they contain a mix of bacteria, including potential pathogens, antimicrobial resistance genes and antimicrobials. In many countries, manures and slurry are stored, especially over winter, before spreading onto fields as organic fertilizer. Thus, these are a potential location for gene exchange and selection for resistance. We develop and analyse a mathematical model to quantify the spread of antimicrobial resistance in stored agricultural waste. We use parameters from a slurry tank on a UK dairy farm as an exemplar. We show that the spread of resistance depends in a subtle way on the rates of gene transfer and antibiotic inflow. If the gene transfer rate is high, then its reduction controls resistance, while cutting antibiotic inflow has little impact. If the gene transfer rate is low, then reducing antibiotic inflow controls resistance. Reducing length of storage can also control spread of resistance. Bacterial growth rate, fitness costs of carrying antimicrobial resistance and proportion of resistant bacteria in animal faeces have little impact on spread of resistance. Therefore, effective treatment strategies depend critically on knowledge of gene transfer rates.

Pharmacokinetics of enrofloxacin and ceftiofur in plasma, interstitial fluid, and gastrointestinal tract of calves after subcutaneous injection, and bactericidal impacts on representative enteric bacteria

This study's objectives were to determine intestinal antimicrobial concentrations in calves administered enrofloxacin or ceftiofur sodium subcutaneously, and their impact on representative enteric bacteria. Ultrafiltration devices were implanted in the ileum and colon of 12 steers, which received either enrofloxacin or ceftiofur sodium. Samples were collected over 48 h after drug administration for pharmacokinetic/pharmacodynamic analysis. Enterococcus faecalis or Salmonella enterica (5 × 10(5) CFU/mL of each) were exposed in vitro to peak and tail (48 h postadministration) concentrations of both drugs at each location for 24 h to determine inhibition of growth and change in MIC. Enrofloxacin had tissue penetration factors of 1.6 and 2.5 in the ileum and colon, while ciprofloxacin, an active metabolite of enrofloxacin, was less able to cross into the intestine (tissue penetration factors of 0.7 and 1.7). Ceftiofur was rapidly eliminated leading to tissue penetration factors of 0.39 and 0.25. All concentrations of enrofloxacin were bactericidal for S. enterica and significantly reduced E. faecalis. Peak ceftiofur concentration was bactericidal for S. enterica, and tail concentrations significantly reduced growth. E. faecalis experienced growth at all ceftiofur concentrations. The MICs for both organisms exposed to peak and tail concentrations of antimicrobials were unchanged at the end of the study. Enrofloxacin and ceftiofur achieved intestinal concentrations capable of reducing intestinal bacteria, yet the short exposure of ceftiofur in the intestine may select for resistant organisms.

Occurrence of Antimicrobial-Resistant Escherichia coli and Salmonella enterica in the Beef Cattle Production and Processing Continuum

Specific concerns have been raised that third-generation cephalosporin-resistant (3GC(r)) Escherichia coli, trimethoprim-sulfamethoxazole-resistant (COT(r)) E. coli, 3GC(r) Salmonella enterica, and nalidixic acid-resistant (NAL(r)) S. enterica may be present in cattle production environments, persist through beef processing, and contaminate final products. The prevalences and concentrations of these organisms were determined in feces and hides (at feedlot and processing plant), pre-evisceration carcasses, and final carcasses from three lots of fed cattle (n = 184). The prevalences and concentrations were further determined for strip loins from 103 of the carcasses. 3GC(r) Salmonella was detected on 7.6% of hides during processing and was not detected on the final carcasses or strip loins. NAL(r) S. enterica was detected on only one hide. 3GC(r) E. coli and COT(r) E. coli were detected on 100.0% of hides during processing. Concentrations of 3GC(r) E. coli and COT(r) E. coli on hides were correlated with pre-evisceration carcass contamination. 3GC(r) E. coli and COT(r) E. coli were each detected on only 0.5% of final carcasses and were not detected on strip loins. Five hundred and 42 isolates were screened for extraintestinal pathogenic E. coli (ExPEC) virulence-associated markers. Only two COT(r) E. coli isolates from hides were ExPEC, indicating that fed cattle products are not a significant source of ExPEC causing human urinary tract infections. The very low prevalences of these organisms on final carcasses and their absence on strip loins demonstrate that current sanitary dressing procedures and processing interventions are effective against antimicrobial-resistant bacteria.

Pharmacokinetic-pharmacodynamic model to evaluate intramuscular tetracycline treatment protocols to prevent antimicrobial resistance in pigs

High instances of antimicrobial resistance are linked to both routine and excessive antimicrobial use, but excessive or inappropriate use represents an unnecessary risk. The competitive growth advantages of resistant bacteria may be amplified by the strain dynamics; in particular, the extent to which resistant strains outcompete susceptible strains under antimicrobial pressure may depend not only on the antimicrobial treatment strategies but also on the epidemiological parameters, such as the composition of the bacterial strains in a pig. This study evaluated how variation in the dosing protocol for intramuscular administration of tetracycline and the composition of bacterial strains in a pig affect the level of resistance in the intestine of a pig. Predictions were generated by a mathematical model of competitive growth of Escherichia coli strains in pigs under specified plasma concentration profiles of tetracycline. All dosing regimens result in a clear growth advantage for resistant strains. Short treatment duration was found to be preferable, since it allowed less time for resistant strains to outcompete the susceptible ones. Dosing frequency appeared to be ineffective at reducing the resistance levels. The number of competing strains had no apparent effect on the resistance level during treatment, but possession of fewer strains reduced the time to reach equilibrium after the end of treatment. To sum up, epidemiological parameters may have more profound influence on growth dynamics than dosing regimens and should be considered when designing improved treatment protocols.

Progression to multi-scale models and the application to food system intervention strategies

The aim of this article is to discuss how the systems science approach can be used to optimize intervention strategies in food animal systems. It advocates the idea that the challenges of maintaining a safe food supply are best addressed by integrating modeling and mathematics with biological studies critical to formulation of public policy to address these challenges. Much information on the biology and epidemiology of food animal systems has been characterized through single-discipline methods, but until now this information has not been thoroughly utilized in a fully integrated manner. The examples are drawn from our current research. The first, explained in depth, uses clinical mastitis to introduce the concept of dynamic programming to optimize management decisions in dairy cows (also introducing the curse of dimensionality problem). In the second example, a compartmental epidemic model for Johne's disease with different intervention strategies is optimized. The goal of the optimization strategy depends on whether there is a relationship between Johne's and Crohn's disease. If so, optimization is based on eradication of infection; if not, it is based on the cow's performance only (i.e., economic optimization, similar to the mastitis example). The third example focuses on food safety to introduce risk assessment using Listeria monocytogenes and Salmonella Typhimurium. The last example, practical interventions to effectively manage antibiotic resistance in beef and dairy cattle systems, introduces meta-population modeling that accounts for bacterial growth not only in the host (cow), but also in the cow's feed, drinking water and the housing environment. Each example stresses the need to progress toward multi-scale modeling. The article ends with examples of multi-scale systems, from food supply systems to Johne's disease. Reducing the consequences of foodborne illnesses (i.e., minimizing disease occurrence and associated costs) can only occur through an understanding of the system as a whole, including all its complexities. Thus the goal of future research should be to merge disciplines such as molecular biology, applied mathematics and social sciences to gain a better understanding of complex systems such as the food supply chain.

How fitness reduced, antimicrobial resistant bacteria survive and spread: a multiple pig-multiple bacterial strain model

More than 30% of E. coli strains sampled from pig farms in Denmark over the last five years were resistant to the commonly used antimicrobial tetracycline. This raises a number of questions: How is this high level sustained if resistant bacteria have reduced growth rates? Given that there are multiple susceptible and resistant bacterial strains in the pig intestines, how can we describe their coexistence? To what extent does the composition of these multiple strains in individual pigs influence the total bacterial population of the pig pen? What happens to a complex population when antimicrobials are used? To investigate these questions, we created a model where multiple strains of bacteria coexist in the intestines of pigs sharing a pen, and explored the parameter limits of a stable system; both with and without an antimicrobial treatment. The approach taken is a deterministic bacterial population model with stochastic elements of bacterial distributions and transmission. The rates that govern the model are process-oriented to represent growth, excretion, and uptake from environment, independent of herd and meta-population structures. Furthermore, an entry barrier and elimination process for the individual strains in each pig were implemented. We demonstrate how competitive growth between multiple bacterial strains in individual pigs, and the transmission between pigs in a pen allow for strains of antimicrobial resistant bacteria to persist in a pig population to different extents, and how quickly they can become dominant if antimicrobial treatment is initiated. The level of spread depends in a non-linear way of the parameters that govern excretion and uptake. Furthermore, the sampling of initial distributions of strains and stochastic transmission events give rise to large variation in how homogenous and how resistant the bacterial population becomes. Most important: resistant bacteria are demonstrated to survive with a disadvantage in growth rate of well over 10%.

Impact of treatment strategies on cephalosporin and tetracycline resistance gene quantities in the bovine fecal metagenome

The study objective was to determine the effects of two treatment regimens on quantities of ceftiofur and tetracycline resistance genes in feedlot cattle. The two regimens were ceftiofur crystalline-free acid (CCFA) administered to either one or all steers within a pen and subsequent feeding/not feeding of therapeutic doses of chlortetracycline. A 26-day randomized controlled field trial was conducted on 176 steers. Real-time PCR was used to quantify bla_CMY-2, bla_CTX-M, tet(A), tet(B), and 16S rRNA gene copies/gram of feces from community DNA. A significant increase in ceftiofur resistance and a decrease in tetracycline resistance elements were observed among the treatment groups in which all steers received CCFA treatment, expressed as gene copies/gram of feces. Subsequent chlortetracycline administration led to rapid expansion of both ceftiofur and tetracycline resistance gene copies/gram of feces. Our data suggest that chlortetracycline is contraindicated when attempting to avoid expansion of resistance to critically important third-generation cephalosporins.

Modeling the infection dynamics of bacteriophages in enteric Escherichia coli: estimating the contribution of transduction to antimicrobial gene spread

Animal-associated bacterial communities are infected by bacteriophages, although the dynamics of these infections are poorly understood. Transduction by bacteriophages may contribute to transfer of antimicrobial resistance genes, but the relative importance of transduction among other gene transfer mechanisms is unknown. We therefore developed a candidate deterministic mathematical model of the infection dynamics of enteric coliphages in commensal Escherichia coli in the large intestine of cattle. We assumed the phages were associated with the intestine and were predominantly temperate. Model simulations demonstrated how, given the bacterial ecology and infection dynamics, most (>90%) commensal enteric E. coli bacteria may become lysogens of enteric coliphages during intestinal transit. Using the model and the most liberal assumptions about transduction efficiency and resistance gene frequency, we approximated the upper numerical limits ("worst-case scenario") of gene transfer through specialized and generalized transduction in E. coli by enteric coliphages when the transduced genetic segment is picked at random. The estimates were consistent with a relatively small contribution of transduction to lateral gene spread; for example, generalized transduction delivered the chromosomal resistance gene to up to 8 E. coli bacteria/hour within the population of 1.47 × 10(8) E. coli bacteria/liter luminal contents. In comparison, the plasmidic blaCMY-2 gene carried by ~2% of enteric E. coli was transferred by conjugation at a rate at least 1.4 × 10(3) times greater than our generalized transduction estimate. The estimated numbers of transductants varied nonlinearly depending on the ecology of bacteria available for phages to infect, that is, on the assumed rates of turnover and replication of enteric E. coli.

Modelling dynamics of plasmid-gene mediated antimicrobial resistance in enteric bacteria using stochastic differential equations

The ubiquitous commensal bacteria harbour genes of antimicrobial resistance (AMR), often on conjugative plasmids. Antimicrobial use in food animals subjects their enteric commensals to antimicrobial pressure. A fraction of enteric Escherichia coli in cattle exhibit plasmid-gene mediated AMR to a third-generation cephalosporin ceftiofur. We adapted stochastic differential equations with diffusion approximation (a compartmental stochastic mathematical model) to research the sources and roles of stochasticity in the resistance dynamics, both during parenteral antimicrobial therapy and in its absence. The results demonstrated that demographic stochasticity among enteric E. coli in the occurrence of relevant events was important for the AMR dynamics only when bacterial numbers were depressed during therapy. However, stochasticity in the parameters of enteric E. coli ecology, whether externally or intrinsically driven, contributed to a wider distribution of the resistant E. coli fraction, both during therapy and in its absence, with stochasticities in individual parameters interacting in their contribution.

Do antibiotic residues in soils play a role in amplification and transmission of antibiotic resistant bacteria in cattle populations?

When we consider factors that contribute to the emergence, amplification, and persistence of antibiotic resistant bacteria, the conventional assumption is that antibiotic use is the primary driver in these processes and that selection occurs primarily in the patient or animal. Evidence suggests that this may not always be the case. Experimental trials show that parenteral administration of a third-generation cephalosporin (ceftiofur) in cattle has limited or short-term effects on the prevalence of ceftiofur-resistant bacteria in the gastrointestinal tract. While this response may be sufficient to explain a pattern of widespread resistance to cephalosporins, approximately two-thirds of ceftiofur metabolites are excreted in the urine raising the possibility that environmental selection plays an important additive role in the amplification and maintenance of antibiotic resistant E. coli on farms. Consequently, we present a rationale for an environmental selection hypothesis whereby excreted antibiotic residues such as ceftiofur are a significant contributor to the proliferation of antibiotic resistant bacteria in food animal systems. We also present a mathematical model of our hypothesized system as a guide for designing experiments to test this hypothesis. If supported for antibiotics such as ceftiofur, then there may be new approaches to combat the proliferation of antibiotic resistance beyond the prudent use mantra.

Influence of therapeutic ceftiofur treatments of feedlot cattle on fecal and hide prevalences of commensal Escherichia coli resistant to expanded-spectrum cephalosporins, and molecular characterization of resistant isolates

In the United States, the blaCMY-2 gene contained within incompatibility type A/C (IncA/C) plasmids is frequently identified in extended-spectrum-cephalosporin-resistant (ESC(r)) Escherichia coli strains from both human and cattle sources. Concerns have been raised that therapeutic use of ceftiofur in cattle may increase the prevalence of ESC(r) E. coli. We report that herd ESC(r) E. coli fecal and hide prevalences throughout the residency of cattle at a feedlot, including during the period of greatest ceftiofur use at the feedlot, were either not significantly different (P ≥ 0.05) or significantly less (P < 0.05) than the respective prevalences at arrival. Longitudinal sampling of cattle treated with ceftiofur demonstrated that once the transient increase of ESC(r) E. coli shedding that follows ceftiofur injection abated, ceftiofur-injected cattle were no more likely than untreated members of the same herd to shed ESC(r) E. coli. Pulsed-field gel electrophoresis (PFGE) genotyping, antibiotic resistance phenotyping, screening for presence of the blaCMY-2 gene, and plasmid replicon typing were performed on 312 ESC(r) E. coli isolates obtained during six sampling periods spanning the 10-month residence of cattle at the feedlot. The identification of only 26 unique PFGE genotypes, 12 of which were isolated during multiple sampling periods, suggests that clonal expansion of feedlot-adapted blaCMY-2 E. coli strains contributed more to the persistence of blaCMY-2 than horizontal transfer of IncA/C plasmids between E. coli strains at this feedlot. We conclude that therapeutic use of ceftiofur at this cattle feedlot did not significantly increase the herd prevalence of ESC(r) E. coli.

Extended-spectrum cephalosporin-resistant Gram-negative organisms in livestock: an emerging problem for human health?

Escherichia coli, Salmonella spp. and Acinetobacter spp. are important human pathogens. Serious infections due to these organisms are usually treated with extended-spectrum cephalosporins (ESCs). However, in the past two decades we have faced a rapid increasing of infections and colonization caused by ESC-resistant (ESC-R) isolates due to production of extended-spectrum-β-lactamases (ESBLs), plasmid-mediated AmpCs (pAmpCs) and/or carbapenemase enzymes. This situation limits drastically our therapeutic armamentarium and puts under peril the human health. Animals are considered as potential reservoirs of multidrug-resistant (MDR) Gram-negative organisms. The massive and indiscriminate use of antibiotics in veterinary medicine has contributed to the selection of ESC-R E. coli, ESC-R Salmonella spp. and, to less extent, MDR Acinetobacter spp. among animals, food, and environment. This complex scenario is responsible for the expansion of these MDR organisms which may have life-threatening clinical significance. Nowadays, the prevalence of food-producing animals carrying ESC-R E. coli and ESC-R Salmonella (especially those producing CTX-M-type ESBLs and the CMY-2 pAmpC) has reached worryingly high values. More recently, the appearance of carbapenem-resistant isolates (i.e., VIM-1-producing Enterobacteriaceae and NDM-1 or OXA-23-producing Acinetobacter spp.) in livestock has even drawn greater concerns. In this review, we describe the aspects related to the spread of the above MDR organisms among pigs, cattle, and poultry, focusing on epidemiology, molecular mechanisms of resistance, impact of antibiotic use, and strategies to contain the overall problem. The link and the impact of ESC-R organisms of livestock origin for the human scenario are also discussed.