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Metagenomic sequencing has proven to be a powerful tool in the monitoring of antimicrobial resistance (AMR). Here, we provide a comparative analysis of the resistome from pigs, poultry, veal calves, turkey, and rainbow trout, for a total of 538 herds across nine European countries. We calculated the effects of per-farm management practices and antimicrobial usage (AMU) on the resistome in pigs, broilers, and veal calves. We also provide an in-depth study of the associations between bacterial diversity, resistome diversity, and AMR abundances as well as co-occurrence analysis of bacterial taxa and antimicrobial resistance genes (ARGs) and the universality of the latter. The resistomes of veal calves and pigs clustered together, as did those of avian origin, while the rainbow trout resistome was different. Moreover, we identified clear core resistomes for each specific food-producing animal species. We identified positive associations between bacterial alpha diversity and both resistome alpha diversity and abundance. Network analyses revealed very few taxa-ARG associations in pigs but a large number for the avian species. Using updated reference databases and optimized bioinformatics, previously reported significant associations between AMU, biosecurity, and AMR in pig and poultry farms were validated. AMU is an important driver for AMR; however, our integrated analyses suggest that factors contributing to increased bacterial diversity might also be associated with higher AMR load. We also found that dispersal limitations of ARGs are shaping livestock resistomes, and future efforts to fight AMR should continue to emphasize biosecurity measures.IMPORTANCEUnderstanding the occurrence, diversity, and drivers for antimicrobial resistance (AMR) is important to focus future control efforts. So far, almost all attempts to limit AMR in livestock have addressed antimicrobial consumption. We here performed an integrated analysis of the resistomes of five important farmed ani

OBJECTIVES: The occurrence and zoonotic potential of antimicrobial resistance (AMR) in pigs and broilers has been studied intensively in past decades. Here, we describe AMR levels of European pig and broiler farms and determine the potential risk factors.METHODS: We collected faeces from 181 pig farms and 181 broiler farms in nine European countries. Real-time quantitative PCR (qPCR) was used to quantify the relative abundance of four antimicrobial resistance genes (ARGs) [aph(3')-III, erm(B), sul2 and tet(W)] in these faeces samples. Information on antimicrobial use (AMU) and other farm characteristics was collected through a questionnaire. A mixed model using country and farm as random effects was performed to evaluate the relationship of AMR with AMU and other farm characteristics. The correlation between individual qPCR data and previously published pooled metagenomic data was evaluated. Variance component analysis was conducted to assess the variance contribution of all factors.RESULTS: The highest abundance of ARG was for tet(W) in pig faeces and erm(B) in broiler faeces. In addition to the significant positive association between corresponding ARG and AMU levels, we also found on-farm biosecurity measures were associated with relative ARG abundance in both pigs and broilers. Between-country and between-farm variation can partially be explained by AMU. Different ARG targets may have different sample size requirements to represent the overall farm level precisely.CONCLUSIONS: qPCR is an efficient tool for targeted assessment of AMR in livestock-related samples. The AMR variation between samples was mainly contributed to by between-country, between-farm and within-farm differences, and then by on-farm AMU.

Livestock feces with antimicrobial resistant bacteria reaches the farm floor, manure pit, farm land and wider environment by run off and aerosolization. Little research has been done on the role of dust in the spread of antimicrobial resistance (AMR) in farms. Concentrations and potential determinants of antimicrobial resistance genes (ARGs) in farm dust are at present not known. Therefore in this study absolute ARG levels, representing the levels people and animals might be exposed to, and relative abundances of ARGs, representing the levels in the bacterial population, were quantified in airborne farm dust using qPCR. Four ARGs were determined in 947 freshly settled farm dust samples, captured with electrostatic dustfall collectors (EDCs), from 174 poultry (broiler) and 159 pig farms across nine European countries. By using linear mixed modeling, associations with fecal ARG levels, antimicrobial use (AMU) and farm and animal related parameters were determined. Results show similar relative abundances in farm dust as in feces and a significant positive association (ranging between 0.21 and 0.82) between the two reservoirs. AMU in pigs was positively associated with ARG abundances in dust from the same stable. Higher biosecurity standards were associated with lower relative ARG abundances in poultry and higher relative ARG abundances in pigs. Lower absolute ARG levels in dust were driven by, among others, summer season and certain bedding materials for poultry, and lower animal density and summer season for pigs. This study indicates different pathways that contribute to shaping the dust resistome in livestock farms, related to dust generation, or affecting the bacterial microbiome. Farm dust is a large reservoir of ARGs from which transmission to bacteria in other reservoirs can possibly occur. The identified determinants of ARG abundances in farm dust can guide future research and potentially farm management policy.

Antimicrobial resistance (AMR) threatens our public health and is mainly driven by antimicrobial usage (AMU). For this reason the World Health Organization calls for detailed monitoring of AMU over all animal sectors involved. Therefore, we aimed to quantify AMU on turkey farms. First, turkey-specific Defined Daily Dose (DDDturkey) was determined. These were compared to the broiler alternative from the European Surveillance of Veterinary Antimicrobial Consumption (DDDvet), that mention DDDvet as a proxy for other poultry species. DDDturkey ranged from being 81.5% smaller to 48.5% larger compared to its DDDvet alternative for broilers. Second, antimicrobial treatments were registered on 60 turkey farms divided over France, Germany and Spain between 2014 and 2016 (20 flocks per country). Afterwards, AMU was quantified using treatment incidence (TI) per 100 days. TI expresses the percentage of the rearing period that the turkeys were treated with a standard dose of antimicrobials. Minimum, median and maximum TI at flock level and based on DDDturkey = 0.0, 10.0 and 65.7, respectively. Yet, a huge variation in amounts of antimicrobials used at flock level was observed, both within and between countries. Seven farms (12%) did not use any antimicrobials. Aminopenicillins, polymyxins, and fluoroquinolones were responsible for 72.2% of total AMU. The proportion of treating farms peaked on week five of the production cycle (41.7%), and 79.4% of the total AMU was administered in the first half of production. To conclude, not all DDDvet values for broilers can be applied to turkeys. Additionally, the results of AMU show potential for reducing and improving AMU on turkey farms, especially concerning the usage of critically important antimicrobials., Unión Europea. FP7, Depto. de Sanidad Animal, Fac. de Veterinaria, Centro de Vigilancia Sanitaria Veterinaria (VISAVET), TRUE, pub

Food-producing animals are an important reservoir and potential source of transmission of antimicrobial resistance (AMR) to humans. However, research on AMR in turkey farms is limited. This study aimed to identify risk factors for AMR in turkey farms in three European countries (Germany, France, and Spain). Between 2014 and 2016, faecal samples, antimicrobial usage (AMU), and biosecurity information were collected from 60 farms. The level of AMR in faecal samples was quantified in three ways: By measuring the abundance of AMR genes through (i) shotgun metagenomics sequencing (n = 60), (ii) quantitative real-time polymerase chain reaction (qPCR) targeting ermB, tetW, sul2, and aph3′-III; (n = 304), and (iii) by identifying the phenotypic prevalence of AMR in Escherichia coli isolates by minimum inhibitory concentrations (MIC) (n = 600). The association between AMU or biosecurity and AMR was explored. Significant positive associations were detected between AMU and both genotypic and phenotypic AMR for specific antimicrobial classes. Beta-lactam and colistin resistance (metagenomics sequencing); ampicillin and ciprofloxacin resistance (MIC) were associated with AMU. However, no robust AMU-AMR association was detected by analyzing qPCR targets. In addition, no evidence was found that lower biosecurity increases AMR abundance. Using multiple complementary AMR detection methods added insights into AMU-AMR associations at turkey farms.

Food-producing animals are an important reservoir and potential source of transmission of antimicrobial resistance (AMR) to humans. However, research on AMR in turkey farms is limited. This study aimed to identify risk factors for AMR in turkey farms in three European countries (Germany, France, and Spain). Between 2014 and 2016, faecal samples, antimicrobial usage (AMU), and biosecurity information were collected from 60 farms. The level of AMR in faecal samples was quantified in three ways: By measuring the abundance of AMR genes through (i) shotgun metagenomics sequencing (n = 60), (ii) quantitative real-time polymerase chain reaction (qPCR) targeting ermB, tetW, sul2, and aph3′-III; (n = 304), and (iii) by identifying the phenotypic prevalence of AMR in Escherichia coli isolates by minimum inhibitory concentrations (MIC) (n = 600). The association between AMU or biosecurity and AMR was explored. Significant positive associations were detected between AMU and both genotypic and phenotypic AMR for specific antimicrobial classes. Beta-lactam and colistin resistance (metagenomics sequencing); ampicillin and ciprofloxacin resistance (MIC) were associated with AMU. However, no robust AMU-AMR association was detected by analyzing qPCR targets. In addition, no evidence was found that lower biosecurity increases AMR abundance. Using multiple complementary AMR detection methods added insights into AMU-AMR associations at turkey farms.

Metagenomics can unveil the genetic content of the total microbiota in different environments, such as food products and the guts of humans and livestock. It is therefore considered of great potential to investigate the transmission of foodborne hazards as part of source-attribution studies. Source-attribution of antimicrobial resistance (AMR) has traditionally relied on pathogen isolation, while metagenomics allows investigating the full span of AMR determinants. In this study, we hypothesized that the relative abundance of fecal resistome components can be associated with specific reservoirs, and that resistomes can be used for AMR source-attribution. We used shotgun-sequences from fecal samples of pigs, broilers, turkeys- and veal calves collected across Europe, and fecal samples from humans occupationally exposed to livestock in one country (pig slaughterhouse workers, pig and broiler farmers). We applied both hierarchical and flat forms of the supervised classification ensemble algorithm Random Forests to classify resistomes into corresponding reservoir classes. We identified country-specific and -independent AMR determinants, and assessed the impact of country-specific determinants when attributing AMR resistance in humans. Additionally, we performed a similarity percentage analysis with the full spectrum of AMR determinants to identify resistome signatures for the different reservoirs. We showed that the number of AMR determinants necessary to attribute a resistome into the correct reservoir increases with a larger reservoir heterogeneity, and that the impact of country-specific resistome signatures on prediction varies between countries. We predicted a higher occupational exposure to AMR determinants among workers exposed to pigs than among those exposed to broilers. Additionally, results suggested that AMR exposure on pig farms was higher than in pig slaughterhouses. Human resistomes were more similar to pig and veal calves’ resistomes than to those of broi

BACKGROUND: Livestock farms are a reservoir of antimicrobial resistant bacteria from feces. Airborne dust-bound bacteria can spread across the barn and to the outdoor environment. Therefore, exposure to farm dust may be of concern for animals, farmers and neighboring residents. Although dust is a potential route of transmission, little is known about the resistome and bacterial microbiome of farm dust.OBJECTIVES: We describe the resistome and bacterial microbiome of pig and poultry farm dust and their relation with animal feces resistomes and bacterial microbiomes, and on-farm antimicrobial usage (AMU). In addition, the relation between dust and farmers' stool resistomes was explored.METHODS: In the EFFORT-study, resistomes and bacterial microbiomes of indoor farm dust collected on Electrostatic Dust fall Collectors (EDCs), and animal feces of 35 conventional broiler and 44 farrow-to-finish pig farms from nine European countries were determined by shotgun metagenomic analysis. The analysis also included 79 stool samples from farmers working or living at 12 broiler and 19 pig farms and 46 human controls. Relative abundance of and variation in resistome and bacterial composition of farm dust was described and compared to animal feces and farmers' stool.RESULTS: The farm dust resistome contained a large variety of antimicrobial resistance genes (ARGs); more than the animal fecal resistome. For both poultry and pigs, composition of dust resistomes finds (partly) its origin in animal feces as dust resistomes correlated significantly with fecal resistomes. The dust bacterial microbiome also correlated significantly with the dust resistome composition. A positive association between AMU in animals on the farm and the total abundance of the dust resistome was found. Occupational exposure to pig farm dust or animal feces may contribute to farmers' resistomes, however no major shifts in farmers resistome towards feces or dust resistomes were found in t

As a consequence of human and animal antimicrobial use (AMU), antimicrobial resistance (AMR) has emerged. Antimicrobial resistant bacteria – containing antimicrobial resistance genes (ARGs) – are ubiquitous in our living environment. Not only can humans be directly exposed to AMR bacteria in livestock, livestock bacteria could potentially also serve as a reservoir for horizontal gene transfer through which human pathogenic bacteria can acquire ARGs. Studies investigating determinants for livestock and human AMR carriage should therefore also include the study of ARGs to enable the estimation of the overall exposure of humans to – and the risk posed by – AMR. This thesis concerns the epidemiological analysis of AMR in the European food chain. It describes how AMU and AMR in livestock affect AMR in humans and focuses on identifying determinants for AMR at the genomic level. It elaborates on how the pig and poultry gut resistome, i.e. the full collection of ARGs in the gut, is affected by AMU, livestock farm management and on-farm biosecurity practices. Molecular techniques like qPCR and next-generation sequencing techniques (i.e. metagenomic sequencing) are applied to identify an umbrella of on-farm AMR mitigation measures targeted at the livestock resistome, while generating data regarding the genetic characteristics of resistance. This work also analyses AMR in, and the faecal resistome and bacteriome of, persons occupationally exposed to AMR in livestock (i.e. farmers and slaughterhouse workers), who might not only be highly exposed but also serve as entry points for the spread of AMR bacteria and ARGs to the general population. Finally, the strengths and limitations of the application of metagenomic methods within AMR surveillance networks are discussed. A more detailed summary can be found in the addendum to this thesis (page 256, in English and Dutch).

OBJECTIVES: Slaughterhouse staff is occupationally exposed to antimicrobial resistant bacteria. Studies reported high antimicrobial resistance gene (ARG) abundances in slaughter pigs. This cross-sectional study investigated occupational exposure to tetracycline (tetW) and macrolide (ermB) resistance genes and assessed determinants for faecal tetW and ermB carriage among pig slaughterhouse workers.METHODS: During 2015-2016, 483 faecal samples and personal questionnaires were collected from workers in a Dutch pig abattoir, together with 60 pig faecal samples. Human dermal and respiratory exposure was assessed by examining 198 carcass, 326 gloves, and 33 air samples along the line, next to 198 packed pork chops to indicate potential consumer exposure. Samples were analyzed by qPCR (tetW, ermB). A job exposure matrix was created by calculating the percentage of tetW and ermB positive carcasses or gloves for each job position. Multiple linear regression models were used to link exposure to tetW and ermB carriage.RESULTS: Workers are exposed to tetracycline and macrolide resistance genes along the slaughter line. Tetw and ermB gradients were found for carcasses, gloves, and air filters. One packed pork chop contained tetW, ermB was non-detectable. Human faecal tetW and ermB concentrations were lower than in pig faeces. Associations were found between occupational tetW exposure and human faecal tetW carriage, yet, not after model adjustments. Sampling round, nationality, and smoking were determinants for ARG carriage.CONCLUSION: We demonstrated clear environmental tetracycline and macrolide resistance gene exposure gradients along the slaughter line. No robust link was found between ARG exposure and human faecal ARG carriage.

Luiken REC, Van Gompel L, Bossers A, Munk P, Joosten P, Hansen RB, Knudsen BE, Garcia-Cobos S, Dewulf J, Aarestrup FM, Wagenaar JA, Smit LAM, Mevius DJ, Heederik DJJ, Schmitt H; EFFORT-group. : : : : : [ Highlights ] -- An analysis of farm dust from 79 pig and poultry farms using metagenomics. -- Farm dust resistomes are compared to animal fecal and farmers stool resistomes. -- Farm dust bacterial microbiomes have an abundant and rich resistome. -- Animal fecal resistomes are an important, but not the only, source of farm dust ARGs. -- Antimicrobial usage in the animals is positively associated with dust resistome abundance. :: [ Objectives ] We describe the resistome and bacterial microbiome of pig and poultry farm dust and their relation with animal feces resistomes and bacterial microbiomes, and on-farm antimicrobial usage (AMU). In addition, the relation between dust and farmers stool resistomes was explored. [ Conclusion ] Poultry and pig farm dust resistomes are rich and abundant and associated with the fecal resistome of the animals and the dust bacterial microbiome., Luiken REC, Van Gompel L, Bossers A, Munk P, Joosten P, Hansen RB, Knudsen BE, Garcia-Cobos S, Dewulf J, Aarestrup FM, Wagenaar JA, Smit LAM, Mevius DJ, Heederik DJJ, Schmitt H; EFFORT-group. : : : : : [ Highlights ] -- An analysis of farm dust from 79 pig and poultry farms using metagenomics. -- Farm dust resistomes are compared to animal fecal and farmers stool resistomes. -- Farm dust bacterial microbiomes have an abundant and rich resistome. -- Animal fecal resistomes are an important, but not the only, source of farm dust ARGs. -- Antimicrobial usage in the animals is positively associated with dust resistome abundance. :: [ Objectives ] We describe the resistome and bacterial microbiome of pig and poultry farm dust and their relation with animal feces resistomes and bacterial microbiomes, and on-farm antimicrobial usage (AMU). In addition, the relation between dust and farmers stool resistomes was explored. [ Conclusion ] Poultry and pig farm dust resistomes are rich and abundant and associated with the fecal resistome of the animals and the dust bacterial microbiome.

One Health surveillance of antimicrobial resistance (AMR) depends on a harmonized method for detection of AMR. Metagenomics-based surveillance offers the possibility to compare resistomes within and between different target populations. Its potential to be embedded into policy in the future calls for a timely and integrated knowledge dissemination strategy. We developed a blended training (e-learning and a workshop) on the use of metagenomics in surveillance of pathogens and AMR. The objectives were to highlight the potential of metagenomics in the context of integrated surveillance, to demonstrate its applicability through hands-on training and to raise awareness to bias factors1. The target participants included staff of competent authorities responsible for AMR monitoring and academic staff. The training was organized in modules covering the workflow, requirements, benefits and challenges of surveillance by metagenomics. The training had 41 participants. The face-to-face workshop was essential to understand the expectations of the participants about the transition to metagenomics-based surveillance. After revision of the e-learning, we released it as a Massive Open Online Course (MOOC), now available at https://www.coursera.org/learn/metagenomics. This course has run in more than 20 sessions, with more than 3,000 learners enrolled, from more than 120 countries. Blended learning and MOOCs are useful tools to deliver knowledge globally and across disciplines. The released MOOC can be a reference knowledge source for international players in the application of metagenomics in surveillance.

Objectives: To explore the dynamics of faecal ESBL/AmpC shedding in dairy cattle and farmers, a study was conducted to examine changes in shedding by individual animals, as well as environmental exposure, and to study the association between antimicrobial use (AMU) and ESBL/AmpC shedding.Methods: The study comprised a cross-sectional survey of 20 farms and a 1 year follow-up of 10 farms. Faecal samples were cultured by both direct inoculation on MacConkey agar + 1 mg/L cefotaxime (MC+) and enrichment in LB-broth + 1 mg/L cefotaxime with subsequent inoculation on MC+. Dust samples were collected using electrostatic dustfall collectors (EDCs). Human faecal samples were collected by the farmers. Presence of ESBL/AmpC genes was screened for by PCR and sequencing. Using mixed effects logistic regression, ORs were determined and population-attributable fractions (PAFs) calculated subsequently.Results: In Phase 1, 8/20 farms were positive for ESBL/AmpC and, with 2 negative farms, were selected for Phase 2. Transient shedding of dominant allele variants was observed in the animals. EDCs and human faecal samples did not reflect what was observed in the animals. AMU was related to shedding of ESBLs in the next sampling moment [OR 14.6 (95% CI 3.0-80.0)] and the PAF of AMU was 0.36 (95% CI 0.08-0.77). Calves fed with colostrum from cows on dry-off therapy was not a risk factor [OR 1.7 (95% CI 0.7-4.9, P = 0.28)].Conclusions: The presence of ESBL/AmpC could only be partly explained by AMU. No link was shown between shedding in cattle and humans or the environment. Interventions should focus on prevention of introduction.