Antimicrobial resistance genes aph(3')-III, erm(B), sul2 and tet(W) abundance in animal faeces, meat, production environments and human faeces in Europe.

BACKGROUND: Real-time quantitative PCR (qPCR) is an affordable method to quantify antimicrobial resistance gene (ARG) targets, allowing comparisons of ARG abundance along animal production chains. OBJECTIVES: We present a comparison of ARG abundance across various animal species, production environments and humans in Europe. AMR variation sources were quantified. The correlation of ARG abundance between qPCR data and previously published metagenomic data was assessed. METHODS: A cross-sectional study was conducted in nine European countries, comprising 9572 samples. qPCR was used to quantify abundance of ARGs [aph(3')-III, erm(B), sul2, tet(W)] and 16S rRNA. Variance component analysis was conducted to explore AMR variation sources. Spearman's rank correlation of ARG abundance values was evaluated between pooled qPCR data and earlier published pooled metagenomic data. RESULTS: ARG abundance varied strongly among animal species, environments and humans. This variation was dominated by between-farm variation (pigs) or within-farm variation (broilers, veal calves and turkeys). A decrease in ARG abundance along pig and broiler production chains ('farm to fork') was observed. ARG abundance was higher in farmers than in slaughterhouse workers, and lowest in control subjects. ARG abundance showed a high correlation (Spearman's ρ > 0.7) between qPCR data and metagenomic data of pooled samples. CONCLUSIONS: qPCR analysis is a valuable tool to assess ARG abundance in a large collection of livestock-associated samples. The between-country and between-farm variation of ARG abundance could partially be explained by antimicrobial use and farm biosecurity levels. ARG abundance in human faeces was related to livestock antimicrobial resistance exposure.

Risk factors for the abundance of antimicrobial resistance genes aph(3')-III, erm(B), sul2 and tet(W) in pig and broiler faeces in nine European countries.

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.

Determinants for antimicrobial resistance genes in farm dust on 333 poultry and pig farms in nine European countries.

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.

Quantitative and qualitative analysis of antimicrobial usage at farm and flock level on 181 broiler farms in nine European countries.

OBJECTIVES: To control the emerging threat of antimicrobial resistance, international policy appeals for appropriate monitoring of antimicrobial usage (AMU) at supranational, species and farm level. The aim of this study was to quantify AMU in broilers at farm and flock level in nine European countries. METHODS: Antimicrobial treatment data of one flock and purchased antimicrobials over one year were collected at 181 European broiler farms. Afterwards AMU was quantified using treatment incidence (TI) per 100 days based on Defined Daily Dose (DDDvet), Defined Course Dose (DCDvet) or Used Daily Dose (UDDvet) values. Total AMU at flock level was obtained by summing the TIDDDvet of all treatments in the sampled flock (TIDDDvetFl*). RESULTS: The median TIDDDvetFl* was 9.0 (95% CI 5.5-10.8), meaning that broilers were treated with antimicrobials during 9% of their rearing period. TIDDDvetFl* varied considerably within and between countries. However, in every country at least one untreated flock was present. Average TIDDDvetFl* at country level ranged from 3.3 to 36.7. Polymyxins, extended-spectrum aminopenicillins and fluoroquinolones were the most used antimicrobials, accounting for 26%, 26% and 18% of total AMU, respectively. Twenty-six percent of the farms started a treatment on day 1 of production, and 49% of overall AMU was administered within the first week. CONCLUSIONS: Results show that rearing broilers without AMU is feasible. However, a huge variation in AMU in terms of amount, moment of administration and antimicrobial classes was observed. This shows that there is still ground to be covered when it comes to AMU on broiler farms.

Quantitative and qualitative analysis of antimicrobial usage patterns in 180 selected farrow-to-finish pig farms from nine European countries based on single batch and purchase data.

OBJECTIVES: Farm-level quantification of antimicrobial usage (AMU) in pig farms. METHODS: In a cross-sectional study, AMU data on group treatments administered to a single batch of fattening pigs from birth to slaughter (group treatment data) and antimicrobials purchased during 1 year (purchase data) were collected at 180 pig farms in nine European countries. AMU was quantified using treatment incidence (TI) based on defined (DDDvet) and used (UDDvet) daily doses and defined (DCDvet) and used (UCDvet) course doses. RESULTS: The majority of antimicrobial group treatments were administered to weaners (69.5% of total TIDDDvet) followed by sucklers (22.5% of total TIDDDvet). AMU varied considerably between farms with a median TIDDDvet of 9.2 and 7.1 for a standardized rearing period of 200 days based on group treatment and purchase data, respectively. In general, UDDvet and UCDvet were higher than DDDvet and DCDvet, respectively, suggesting that either the defined doses were set too low or that group treatments were often dosed too high and/or administered for too long. Extended-spectrum penicillins (31.2%) and polymyxins (24.7%) were the active substances most often used in group treatments, with the majority administered through feed or water (82%). Higher AMU at a young age was associated with higher use in older pigs. CONCLUSIONS: Collecting farm-level AMU data of good quality is challenging and results differ based on how data are collected (group treatment data versus purchase data) and reported (defined versus used daily and course doses).

The antimicrobial resistome in relation to antimicrobial use and biosecurity in pig farming, a metagenome-wide association study in nine European countries.

OBJECTIVES: Previous studies in food-producing animals have shown associations between antimicrobial use (AMU) and resistance (AMR) in specifically isolated bacterial species. Multi-country data are scarce and only describe between-country differences. Here we investigate associations between the pig faecal mobile resistome and characteristics at the farm-level across Europe. METHODS: A cross-sectional study was conducted among 176 conventional pig farms from nine European countries. Twenty-five faecal samples from fattening pigs were pooled per farm and acquired resistomes were determined using shotgun metagenomics and the Resfinder reference database, i.e. the full collection of horizontally acquired AMR genes (ARGs). Normalized fragments resistance genes per kilobase reference per million bacterial fragments (FPKM) were calculated. Specific farm-level data (AMU, biosecurity) were collected. Random-effects meta-analyses were performed by country, relating farm-level data to relative ARG abundances (FPKM). RESULTS: Total AMU during fattening was positively associated with total ARG (total FPKM). Positive associations were particularly observed between widely used macrolides and tetracyclines, and ARGs corresponding to the respective antimicrobial classes. Significant AMU-ARG associations were not found for ß-lactams and only few colistin ARGs were found, despite high use of these antimicrobial classes in younger pigs. Increased internal biosecurity was directly related to higher abundances of ARGs mainly encoding macrolide resistance. These effects of biosecurity were independent of AMU in mutually adjusted models. CONCLUSIONS: Using resistome data in association studies is unprecedented and adds accuracy and new insights to previously observed AMU-AMR associations. Major components of the pig resistome are positively and independently associated with on-farm AMU and biosecurity conditions.

Associations between antimicrobial use and the faecal resistome on broiler farms from nine European countries.

OBJECTIVES: To determine associations between farm- and flock-level antimicrobial usage (AMU), farm biosecurity status and the abundance of faecal antimicrobial resistance genes (ARGs) on broiler farms. METHODS: In the cross-sectional pan-European EFFORT study, conventional broiler farms were visited and faeces, AMU information and biosecurity records were collected. The resistomes of pooled faecal samples were determined by metagenomic analysis for 176 farms. A meta-analysis approach was used to relate total and class-specific ARGs (expressed as fragments per kb reference per million bacterial fragments, FPKM) to AMU (treatment incidence per DDD, TIDDDvet) per country and subsequently across all countries. In a similar way, the association between biosecurity status (Biocheck.UGent) and the resistome was explored. RESULTS: Sixty-six (38%) flocks did not report group treatments but showed a similar resistome composition and roughly similar ARG levels to antimicrobial-treated flocks. Nevertheless, we found significant positive associations between ß-lactam, tetracycline, macrolide and lincosamide, trimethoprim and aminoglycoside antimicrobial flock treatments and ARG clusters conferring resistance to the same class. Similar associations were found with purchased products. In gene-level analysis for ß-lactams and macrolides, lincosamides and streptogramins, a significant positive association was found with the most abundant gene clusters blaTEM and erm(B). Little evidence was found for associations with biosecurity. CONCLUSIONS: The faecal microbiome in European broilers contains a high diversity of ARGs, even in the absence of current antimicrobial selection pressure. Despite this, the relative abundance of genes and the composition of the resistome is positively related to AMU in European broiler farms for several antimicrobial classes.

Risk factors for antimicrobial use in Dutch pig farms: A cross-sectional study.

BACKGROUND: Antimicrobial use (AMU) has decreased significantly in Dutch pig farms since 2009. However, this decrease has stagnated recently, with relatively high AMU levels persisting mainly among weaners. The aim of this study was to identify farm-level characteristics associated with: i) total AMU and ii) use of specific antimicrobial classes. METHODS: In 2020, cross-sectional data from 154 Dutch pig farms were collected, including information on AMU and farm characteristics. A mixed-effects conditional Random Forest analysis was applied to select the subset of features that was best associated with AMU. RESULTS: The main risk factors for total AMU in weaners were vaccination for PRRS in sucklings, being a conventional farm (vs. not), high within-farm density, and early weaning. The main protective factors for total AMU in sows/sucklings were E. coli vaccination in sows and having boars for estrus detection from own production. Regarding antimicrobial class-specific outcomes, several risk factors overlapped for weaners and sows/sucklings, such as farmer's non-tertiary education, not having free-sow systems during lactation, and conventional farming. An additional risk factor for weaners was having fully slatted floors. For fatteners, the main risk factor for total AMU was PRRS vaccination in sucklings. CONCLUSIONS: Several factors found here to be associated with AMU. Some were known but others were novel, such as farmer's tertiary education, low pig aggression and free-sow systems which were all associated with lower AMU. These factors provide targets for developing tailor-made interventions, as well as an evidence-based selection of features for further causal assessment and mediation analysis.

The European livestock resistome.

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 animal populations across Europe finding that the resistome and AMR levels are also shaped by factors related to bacterial diversity, as well as dispersal limitations. Thus, future studies and interventions aimed at reducing AMR should not only address antimicrobial usage but also consider other epidemiological and ecological factors.

Characterising the gut microbiome of stranded harbour seals (Phoca vitulina) in rehabilitation.

Animal rehabilitation centres provide a unique opportunity to study the microbiome of wild animals because subjects will be handled for their treatment and can therefore be sampled longitudinally. However, rehabilitation may have unintended consequences on the animals' microbiome because of a less varied and suboptimal diet, possible medical treatment and exposure to a different environment and human handlers. Our study describes the gut microbiome of two large seal cohorts, 50 pups (0-30 days old at arrival) and 23 weaners (more than 60 days old at arrival) of stranded harbour seals admitted for rehabilitation at the Sealcentre Pieterburen in the Netherlands, and the effect of rehabilitation on it. Faecal samples were collected from all seals at arrival, two times during rehabilitation and before release. Only seals that did not receive antimicrobial treatment were included in the study. The average time in rehabilitation was 95 days for the pups and 63 days for the weaners. We observed that during rehabilitation, there was an increase in the relative abundance of some of the Campylobacterota spp and Actinobacteriota spp. The alpha diversity of the pups' microbiome increased significantly during their rehabilitation (p-value <0.05), while there were no significant changes in alpha diversity over time for weaners. We hypothesize that aging is the main reason for the observed changes in the pups' microbiome. At release, the sex of a seal pup was significantly associated with the microbiome's alpha (i.e., Shannon diversity was higher for male pups, p-value <0.001) and beta diversity (p-value 0.001). For weaners, variation in the microbiome composition (beta diversity) at release was partly explained by sex and age of the seal (p-values 0.002 and 0.003 respectively). We mainly observed variables known to change the gut microbiome composition (e.g., age and sex) and conclude that rehabilitation in itself had only minor effects on the gut microbiome of seal pups and seal weaners.

Longitudinal study of the short- and long-term effects of hospitalisation and oral trimethoprim-sulfadiazine administration on the equine faecal microbiome and resistome.

BACKGROUND: Hospitalisation and antimicrobial treatment are common in horses and significantly impact the intestinal microbiota. Antimicrobial treatment might also increase levels of resistant bacteria in faeces, which could spread to other ecological compartments, such as the environment, other animals and humans. In this study, we aimed to characterise the short- and long-term effects of transportation, hospitalisation and trimethoprim-sulfadiazine (TMS) administration on the faecal microbiota and resistome of healthy equids. METHODS: In a longitudinal experimental study design, in which the ponies served as their own control, faecal samples were collected from six healthy Welsh ponies at the farm (D0-D13-1), immediately following transportation to the hospital (D13-2), during 7 days of hospitalisation without treatment (D14-D21), during 5 days of oral TMS treatment (D22-D26) and after discharge from the hospital up to 6 months later (D27-D211). After DNA extraction, 16S rRNA gene sequencing was performed on all samples. For resistome analysis, shotgun metagenomic sequencing was performed on selected samples. RESULTS: Hospitalisation without antimicrobial treatment did not significantly affect microbiota composition. Oral TMS treatment reduced alpha-diversity significantly. Kiritimatiellaeota, Fibrobacteres and Verrucomicrobia significantly decreased in relative abundance, whereas Firmicutes increased. The faecal microbiota composition gradually recovered after discontinuation of TMS treatment and discharge from the hospital and, after 2 weeks, was more similar to pre-treatment composition than to composition during TMS treatment. Six months later, however, microbiota composition still differed significantly from that at the start of the study and Spirochaetes and Verrucomicrobia were less abundant. TMS administration led to a significant (up to 32-fold) and rapid increase in the relative abundance of resistance genes sul2, tetQ, ant6-1a, and aph(3")-lb. lnuC significantly decreased directly after treatment. Resistance genes sul2 (15-fold) and tetQ (six-fold) remained significantly increased 6 months later. CONCLUSIONS: Oral treatment with TMS has a rapid and long-lasting effect on faecal microbiota composition and resistome, making the equine hindgut a reservoir and potential source of resistant bacteria posing a risk to animal and human health through transmission. These findings support the judicious use of antimicrobials to minimise long-term faecal presence, excretion and the spread of antimicrobial resistance in the environment. Video Abstract.

Factors associated with antimicrobial use in pig and veal calf farms in the Netherlands: A multi-method longitudinal data analysis.

Minimizing antimicrobial use (AMU) in livestock is needed to control antimicrobial resistance (AMR). In the Netherlands, the livestock sector reduced AMU by almost 70 % since 2009, but this reduction stagnated in recent years. With only therapeutic AMU allowed, it is clear that besides socio-economic and behavioral factors, also the farm technical characteristics influence the conditions under which farmers need AMU. These characteristics pertain to farm management, including biosecurity, vaccination schemes, nutrition, micro-climate and husbandry practices. Identifying farm-related risk factors for AMU is needed to control AMR in a sustainable and pragmatic way. This need, often concerns the overall contribution of seemingly related (rather than individualized) factors. Here, risk factors for AMU in pig and calf farms were determined using two approaches: a typical risk factor analysis based on generalized estimating equations (GEEs) or hierarchical mixed-effects models and a multiblock partial least-squares regression analysis. These methods were applied to longitudinal data from two previous studies, i.e. a panel study and an intervention study involving 36 multiplier pig farms and 51 veal calf farms in the Netherlands, respectively. The multiblock analysis allowed us to quantify the importance of each factor and their respective block (i.e. farm management domain). For pigs, factors related to internal biosecurity had the highest impact on AMU, while for calves, these were mainly related to micro-climate. Structural characteristics, such as farm size and production type, followed in importance for both sectors. While both methods provided similar outcomes, the multiblock approach provided further insights by grouping and comparing factors believed to be inter-related.

The Equine Faecal Microbiota of Healthy Horses and Ponies in The Netherlands: Impact of Host and Environmental Factors.

Several studies have described the faecal microbiota of horses and the factors that influence its composition, but the variation in results is substantial. This study aimed to investigate the microbiota composition in healthy equids in The Netherlands under standard housing and management conditions and to evaluate the effect of age, gender, horse type, diet, pasture access, the season of sampling and location on it. Spontaneously produced faecal samples were collected from the stall floor of 79 healthy horses and ponies at two farms. The validity of this sampling technique was evaluated in a small pilot study including five ponies showing that the microbiota composition of faecal samples collected up to 6 h after spontaneous defaecation was similar to that of the samples collected rectally. After DNA extraction, Illumina Miseq 16S rRNA sequencing was performed to determine microbiota composition. The effect of host and environmental factors on microbiota composition were determined using several techniques (NMDS, PERMANOVA, DESeq2). Bacteroidetes was the largest phylum found in the faecal microbiota (50.1%), followed by Firmicutes (28.4%). Alpha-diversity and richness decreased significantly with increasing age. Location, age, season, horse type and pasture access had a significant effect on beta-diversity. The current study provides important baseline information on variation in faecal microbiota in healthy horses and ponies under standard housing and management conditions. These results indicate that faecal microbiota composition is affected by several horse-related and environment-related factors, and these factors should be considered in future studies of the equine faecal microbiota.

Farm dust resistomes and bacterial microbiomes in European poultry and pig farms.

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 this study. 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.

Addressing Learning Needs on the Use of Metagenomics in Antimicrobial Resistance Surveillance.

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 factors. 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.

Association of antimicrobial usage with faecal abundance of aph(3')-III, ermB, sul2 and tetW resistance genes in veal calves in three European countries.

BACKGROUND: High antimicrobial use (AMU) and antimicrobial resistance (AMR) in veal calves remain a source of concern. As part of the EFFORT project, the association between AMU and the abundance of faecal antimicrobial resistance genes (ARGs) in veal calves in three European countries was determined. METHODS: In 2015, faecal samples of veal calves close to slaughter were collected from farms located in France, Germany and the Netherlands (20 farms in France, 20 farms in the Netherlands and 21 farms in Germany; 25 calves per farm). Standardized questionnaires were used to record AMU and farm characteristics. In total, 405 faecal samples were selected for DNA extraction and quantitative polymerase chain reaction to quantify the abundance (16S normalized concentration) of four ARGs [aph(3')-III, ermB, sul2 and tetW] encoding for resistance to frequently used antimicrobials in veal calves. Multiple linear mixed models with random effects for country and farm were used to relate ARGs to AMU and farm characteristics. RESULTS: A significant positive association was found between the use of trimethoprim/sulfonamides and the concentration of sul2 in faeces from veal calves. A higher weight of calves on arrival at the farm was negatively associated with aph(3')-III and ermB. Lower concentrations of aph(3')-III were found at farms with non-commercial animals present. Furthermore, farms using only water for the cleaning of stables had a significantly lower abundance of faecal ermB and tetW compared with other farms. CONCLUSION: A positive association was found between the use of trimethoprim/sulfonamides and the abundance of sul2 in faeces in veal calves. Additionally, other relevant risk factors associated with ARGs in veal calves were identified, such as weight on arrival at the farm and cleaning practices.

Description and determinants of the faecal resistome and microbiome of farmers and slaughterhouse workers: A metagenome-wide cross-sectional study.

BACKGROUND: By studying the entire human faecal resistome and associated microbiome, the diversity and abundance of faecal antimicrobial resistance genes (ARGs) can be comprehensively characterized. Prior culture-based studies have shown associations between occupational exposure to livestock and carriage of specific antimicrobial resistant bacteria. Using shotgun metagenomics, the present study investigated 194 faecal resistomes and bacteriomes from humans occupationally exposed to ARGs in livestock (i.e. pig and poultry farmers, employees and family members and pig slaughterhouse workers) and a control population (Lifelines cohort) in the Netherlands. In addition, we sought to identify determinants for the human resistome and bacteriome composition by applying a combination of multivariate (NMDS, PERMANOVA, SIMPER and DESeq2 analysis) and multivariable regression analysis techniques. RESULTS: Pig slaughterhouse workers and pig farmers carried higher total ARG abundances in their stools compared to broiler farmers and control subjects. Tetracycline, ß-lactam and macrolide resistance gene clusters dominated the resistome of all studied groups. No significant resistome alpha diversity differences were found among the four populations. However, the resistome beta diversity showed a separation of the mean resistome composition of pig and pork exposed workers from broiler farmers and controls, independent of their antimicrobial use. We demonstrated differences in resistome composition between slaughter line positions, pig versus poultry exposed workers, as well as differences between farmers and employees versus family members. In addition, we found a significant correlation between the bacteriome and resistome, and significant differences in the bacteriome composition between and within the studied subpopulations. Finally, an in-depth analysis of pig and poultry farms - of which also farm livestock resistomes were analysed - showed positive associations between the number of on-farm working hours and human faecal AMR loads. CONCLUSION: We found that the total normalized faecal ARG carriage was larger in persons working in the Dutch pork production chain compared to poultry farmers and controls. Additionally, we showed significant differences in resistome and bacteriome composition of pig and pork exposed workers compared to a control group, as well as within-population (farms, slaughterhouse) compositional differences. The number of on-farm working hours and the farm type (pig or broiler) that persons live or work on are determinants for the human faecal resistome. Overall, our results may suggest direct or indirect livestock contact as a determinant for human ARG carriage. Future studies should further focus on the connection between the human and livestock resistome (i.e. transmission routes) to substantiate the evidence for livestock-associated resistome acquisition.

Occupational Exposure and Carriage of Antimicrobial Resistance Genes (tetW, ermB) in Pig Slaughterhouse Workers.

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.

Abundance and diversity of the faecal resistome in slaughter pigs and broilers in nine European countries.

Antimicrobial resistance (AMR) in bacteria and associated human morbidity and mortality is increasing. The use of antimicrobials in livestock selects for AMR that can subsequently be transferred to humans. This flow of AMR between reservoirs demands surveillance in livestock and in humans. We quantified and characterized the acquired resistance gene pools (resistomes) of 181 pig and 178 poultry farms from nine European countries, sequencing more than 5,000 Gb of DNA using shotgun metagenomics. We quantified acquired AMR using the ResFinder database and a second database constructed for this study, consisting of AMR genes identified through screening environmental DNA. The pig and poultry resistomes were very different in abundance and composition. There was a significant country effect on the resistomes, more so in pigs than in poultry. We found higher AMR loads in pigs, whereas poultry resistomes were more diverse. We detected several recently described, critical AMR genes, including mcr-1 and optrA, the abundance of which differed both between host species and between countries. We found that the total acquired AMR level was associated with the overall country-specific antimicrobial usage in livestock and that countries with comparable usage patterns had similar resistomes. However, functionally determined AMR genes were not associated with total drug use.

Author Correction: Abundance and diversity of the faecal resistome in slaughter pigs and broilers in nine European countries.

In the version of this Article originally published, the surname of author Oksana Lukjancenko was spelt incorrectly as 'Lukjacenko'. This has now been corrected.