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.

Residential exposure to microbial emissions from livestock farms: Implementation and evaluation of land use regression and random forest spatial models.

Adverse health effects have been linked with exposure to livestock farms, likely due to airborne microbial agents. Accurate exposure assessment is crucial in epidemiological studies, however limited studies have modelled bioaerosols. This study used measured concentrations in air of livestock commensals (Escherichia coli (E. coli) and Staphylococcus species (spp.)), and antimicrobial resistance genes (tetW and mecA) at 61 residential sites in a livestock-dense region in the Netherlands. For each microbial agent, land use regression (LUR) and random forest (RF) models were developed using Geographic Information System (GIS)-derived livestock-related characteristics as predictors. The mean and standard deviation of annual average concentrations (gene copies/m3) of E. coli, Staphylococcus spp., tetW and mecA were as follows: 38.9 (±1.98), 2574 (±3.29), 20991 (±2.11), and 15.9 (±2.58). Validated through 10-fold cross-validation (CV), the models moderately explained spatial variation of all microbial agents. The best performing model per agent explained respectively 38.4%, 20.9%, 33.3% and 27.4% of the spatial variation of E. coli, Staphylococcus spp., tetW and mecA. RF models had somewhat better performance than LUR models. Livestock predictors related to poultry and pig farms dominated all models. To conclude, the models developed enable enhanced estimates of airborne livestock-related microbial exposure in future epidemiological studies. Consequently, this will provide valuable insights into the public health implications of exposure to specific microbial agents.

Short-term residential exposure to endotoxin emitted from livestock farms in relation to lung function in non-farming residents.

BACKGROUND: Evidence on the public health relevance of exposure to livestock farm emissions is increasing. Research mostly focused on chemical air pollution, less on microbial exposure, while endotoxins are suggested relevant bacterial components in farm emissions. Acute respiratory health effects of short-term exposure to livestock-related air pollution has been shown for NH3 and PM10, but has not yet been studied for endotoxin. We aimed to assess associations between lung function and short-term exposure to livestock farming emitted endotoxin in co-pollutant models with NH3 and PM10. METHODS: In 2014/2015, spirometry was conducted in 2308 non-farming residents living in a rural area in the Netherlands. Residential exposure to livestock farming emitted endotoxin during the week prior to spirometry was estimated by dispersion modelling. The model was applied to geo-located individual barns within 10 km of each home address using provincial farm data and local hourly meteorological conditions. Regional week-average measured concentrations of NH3 and PM10 were obtained through monitoring stations. Lung function parameters (FEV1, FVC, FEV1/FVC, MMEF) were expressed in %-predicted value based on GLI-2012. Exposure-response analyses were performed by linear regression modelling. RESULTS: Week-average endotoxin exposure was negatively associated with FVC, independently from regional NH3 and PM10 exposure. A 1.1% decline in FVC was estimated for an increase of endotoxin exposure from 10th to 90th percentile. Stratified analyses showed a larger decline (3.2%) for participants with current asthma and/or COPD. FEV1 was negatively associated with week-average endotoxin exposure, but less consistent after co-pollutant adjustment. FEV1/FVC and MMEF were not associated with week-average endotoxin exposure. CONCLUSIONS: Lower lung function in non-farming residents was observed in relation to short-term residential exposure to livestock farming emitted endotoxin. This study indicates the probable relevance of exposure to microbial emissions from livestock farms considering public health besides chemical air pollution, necessitating future research incorporating both.

Seasonality of antimicrobial use in Dutch food-producing animals.

Due to globally increasing antimicrobial resistance (AMR), it is pivotal to understand factors contributing to antimicrobial use (AMU) to enable development and implementation of AMR-reducing interventions. Therefore, we explored seasonal variations of systemic AMU in food-producing animals in the Netherlands. Dutch surveillance data from January 2013 to December 2018 from cattle, pig, and broiler farms were used. AMU was expressed as the number of Defined Daily Dosages Animal per month (DDDA/animal-month) per farm by animal sector, antimicrobial line (first, second, and third), antimicrobial class, and farm type. Seasonality of AMU was analyzed using Generalized Additive Models (GAMs) with DDDA/animal-month as outcome variable, and year and month as independent variables. Year and month were modelled as smooth terms represented with penalized regression splines.Significant seasonality of AMU was found in the cattle and pig sectors, but not in broilers. Significant seasonality of AMU was found mainly for first-line antimicrobials. In the cattle sector, a significant increase during winter was found for the use of amphenicols (an increase of 23.8%) and long-acting macrolides (an increase of 3.4%). In the pig sector, seasonality of AMU was found for pleuromutilins (p < 0.001) with an increase of 20% in October-November. The seasonality of pleuromutilins was stronger in sows/piglets (an increase of 47%) than in fattening pigs (16% increase). Only in fattening pigs, the use of amphenicols showed a significant seasonality with an increase of 11% during winter (P < 0.001). AMU in cattle and pig sectors shows seasonal variations likely caused by seasonality of diseases. In broilers, no AMU seasonality was observed, possibly due to the controlled environment in Dutch farms. In the context of the one health concept, future studies are necessary to explore whether this seasonality is present in other populations and whether it has implications for antimicrobial resistance in humans through the food chain.

Quantifying topical antimicrobial use before and during participation in an antimicrobial stewardship programme in Dutch companion animal clinics.

The emergence of bacterial strains resistant to topical antimicrobials in both human and veterinary medicine has raised concerns over retaining the efficacy of these preparations. Yet, little information is available regarding the use of topical antimicrobials in either sector for planning targeted interventions. This study aims to quantify the use of topical antimicrobials in 44 Dutch companion animal clinics before and during their participation in an antimicrobial stewardship programme (ASP), to explore the effect of the intervention on topical antimicrobial use (AMU). Hence, prescription and clinic animal population data, collected from July 2012 until June 2018 were used. Specifically, the period from July 2012 until June 2015 was defined as pre-intervention period, whereas clinics started to participate in the ASP from March 2016 onwards. As quantification metric, the Defined Daily Dose for Animals (DDDA) was used and a mixed effect times series model with auto-regression was applied to monthly topical AMU data. The intervention effect was modelled using a step function with a change in (linear) time trend and clinic characteristics, as potential determinants of topical AMU, were assessed using a multivariable regression model. A seasonal pattern was identified, in the pre-intervention period, where topical AMU was highest in July-August and lowest in February-March. In addition, total topical AMU appeared to significantly decrease over time in the pre-intervention period and the proportion of dogs in the clinic was positively associated with topical AMU. The intervention effect was significant only for second line and for skin product AMU. This study demonstrates that during participation in an ASP, second line and skin product AMU decreased in Dutch companion animal clinics. Additionally, this study demonstrates the existence of a seasonal effect and a decrease in topical AMU over time already before introduction of a targeted intervention.

Longitudinal Study of Dynamic Epidemiology of Extended-Spectrum Beta-Lactamase-Producing Escherichia coli in Pigs and Humans Living and/or Working on Pig Farms.

Extended-spectrum beta-lactamase (ESBL)-producing Enterobacterales have been increasingly isolated from pigs, highlighting their potential for transmission to humans living and/or working within pig farms. As longitudinal data on the prevalence and the molecular characteristics of such isolates from the high-risk farming population remain scarce, we performed a long-term study on 39 Dutch pig farms. Fecal samples from pigs, farmers, family members, and employees were collected during four sampling occasions with a 6-month period. The presence of ESBL-producing Enterobacterales and their molecular characteristics (ESBL gene, plasmid, and sequence types) were determined by standard methods. Data on personal and farm characteristics were collected using questionnaires. ESBL-producing Escherichia coli was present in pigs at least once for 18 of 39 farms and in 17 of 146 farmers, family members, and/or employees. Among these 417 E. coli isolates, blaCTX-M-1 was the most frequently observed ESBL gene in pigs (n = 261) and humans (n = 25). Despite the great variety in plasmid (sub)types and E. coli sequence types (STs), we observed genetic similarity between human- and pig-derived isolates in (i) ESBL gene, plasmid (sub)type, and ST, suggesting potential clonal transmission in seven farms, and (ii) only ESBL gene and plasmid (sub)type, highlighting the possibility of horizontal transfer in four farms. Five pig farmers carried ESBL producers repeatedly, of whom two carried an identical combination of gene, plasmid (sub)type, and ST over time. Human ESBL carriage was associated with both presence of ESBL producers in pigs and average number of hours working on the pig farm per week, while prolonged human carriage was observed only incidentally. IMPORTANCE Extended-spectrum beta-lactamase (ESBL)-producing Escherichia coli represents a public health hazard due to reduced therapeutic options for the treatment of infections. Although direct contact with pigs is considered a risk factor for human ESBL-producing E. coli carriage through occupational exposure, nationwide data regarding the occurrence of such isolates among pigs and humans living and/or working on farms remain scarce. Therefore, we determined (i) the longitudinal dynamics in prevalence and molecular characteristics of ESBL-producing E. coli in Dutch pig farmers and their pigs over time and (ii) the potential transmission events between these reservoirs based on genetic relatedness and epidemiological associations in longitudinal data. Our data suggesting the possibility of clonal and horizontal dissemination of ESBL-producing Escherichia coli between pigs and pig farmers can be used to inform targeted intervention strategies to decrease the within-farm human exposure to ESBL-producing E. coli.

Detection of SARS-CoV-2 in Air and on Surfaces in Rooms of Infected Nursing Home Residents.

There is an ongoing debate on airborne transmission of Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) as a risk factor for infection. In this study, the level of SARS-CoV-2 in air and on surfaces of SARS-CoV-2 infected nursing home residents was assessed to gain insight in potential transmission routes. During outbreaks, air samples were collected using three different active and one passive air sampling technique in rooms of infected patients. Oropharyngeal swabs (OPS) of the residents and dry surface swabs were collected. Additionally, longitudinal passive air samples were collected during a period of 4 months in common areas of the wards. Presence of SARS-CoV-2 RNA was determined using RT-qPCR, targeting the RdRp- and E-genes. OPS, samples of two active air samplers and surface swabs with Ct-value ≤35 were tested for the presence of infectious virus by cell culture. In total, 360 air and 319 surface samples from patient rooms and common areas were collected. In rooms of 10 residents with detected SARS-CoV-2 RNA in OPS, SARS-CoV-2 RNA was detected in 93 of 184 collected environmental samples (50.5%) (lowest Ct 29.5), substantially more than in the rooms of residents with negative OPS on the day of environmental sampling (n = 2) (3.6%). SARS-CoV-2 RNA was most frequently present in the larger particle size fractions [>4 µm 60% (6/10); 1-4 µm 50% (5/10); <1 µm 20% (2/10)] (Fischer exact test P = 0.076). The highest proportion of RNA-positive air samples on room level was found with a filtration-based sampler 80% (8/10) and the cyclone-based sampler 70% (7/10), and impingement-based sampler 50% (5/10). SARS-CoV-2 RNA was detected in 10 out of 12 (83%) passive air samples in patient rooms. Both high-touch and low-touch surfaces contained SARS-CoV-2 genome in rooms of residents with positive OPS [high 38% (21/55); low 50% (22/44)]. In one active air sample, infectious virus in vitro was detected. In conclusion, SARS-CoV-2 is frequently detected in air and on surfaces in the immediate surroundings of room-isolated COVID-19 patients, providing evidence of environmental contamination. The environmental contamination of SARS-CoV-2 and infectious aerosols confirm the potential for transmission via air up to several meters.

SARS-CoV-2 outbreaks in secondary school settings in the Netherlands during fall 2020; silent circulation.

BACKGROUND: In fall 2020 when schools in the Netherlands operated under a limited set of COVID-19 measures, we conducted outbreaks studies in four secondary schools to gain insight in the level of school transmission and the role of SARS-CoV-2 transmission via air and surfaces. METHODS: Outbreak studies were performed between 11 November and 15 December 2020 when the wild-type variant of SARS-CoV-2 was dominant. Clusters of SARS-CoV-2 infections within schools were identified through a prospective school surveillance study. All school contacts of cluster cases, irrespective of symptoms, were invited for PCR testing twice within 48 h and 4-7 days later. Combined NTS and saliva samples were collected at each time point along with data on recent exposure and symptoms. Surface and active air samples were collected in the school environment. All samples were PCR-tested and sequenced when possible. RESULTS: Out of 263 sampled school contacts, 24 tested SARS-CoV-2 positive (secondary attack rate 9.1%), of which 62% remained asymptomatic and 42% had a weakly positive test result. Phylogenetic analysis on 12 subjects from 2 schools indicated a cluster of 8 and 2 secondary cases, respectively, but also other distinct strains within outbreaks. Of 51 collected air and 53 surface samples, none were SARS-CoV-2 positive. CONCLUSION: Our study confirmed within school SARS-CoV-2 transmission and substantial silent circulation, but also multiple introductions in some cases. Absence of air or surface contamination suggests environmental contamination is not widespread during school outbreaks.

Establishing farm dust as a useful viral metagenomic surveillance matrix.

Farm animals may harbor viral pathogens, some with zoonotic potential which can possibly cause severe clinical outcomes in animals and humans. Documenting the viral content of dust may provide information on the potential sources and movement of viruses. Here, we describe a dust sequencing strategy that provides detailed viral sequence characterization from farm dust samples and use this method to document the virus communities from chicken farm dust samples and paired feces collected from the same broiler farms in the Netherlands. From the sequencing data, Parvoviridae and Picornaviridae were the most frequently found virus families, detected in 85-100% of all fecal and dust samples with a large genomic diversity identified from the Picornaviridae. Sequences from the Caliciviridae and Astroviridae familes were also obtained. This study provides a unique characterization of virus communities in farmed chickens and paired farm dust samples and our sequencing methodology enabled the recovery of viral genome sequences from farm dust, providing important tracking details for virus movement between livestock animals and their farm environment. This study serves as a proof of concept supporting dust sampling to be used in viral metagenomic surveillance.

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.

Residential proximity to livestock animals and mortality from respiratory diseases in The Netherlands: A prospective census-based cohort study.

BACKGROUND: There is increasing evidence of associations between residential proximity to livestock farms and respiratory morbidity, but less is known about potential effects on respiratory mortality among residents. OBJECTIVES: We aimed to assess potential associations between respiratory mortality and residential proximity to (intensive) livestock farming. METHODS: In DUELS, a national census-based cohort, we selected all inhabitants from rural and semi-urban areas of the Netherlands, aged ≥30 years and living at the same address for five years up to baseline (2004). We followed these ∼4 million individuals for respiratory mortality (respiratory system diseases, chronic lower respiratory diseases, pneumonia) from 2005 to 2012. We computed the average number of cattle, pigs, chicken, and mink present in 500 m, 1000 m, 1500 m and 2000 m of each individual's residence in the period 1999-2003. Analyses were conducted using Cox proportional hazards regression, adjusting for potential confounders at individual and neighbourhood level. RESULTS: We found evidence that living up to 2000 m of pig farms was associated with respiratory mortality, namely from chronic lower respiratory diseases, with Hazard Ratios ranging from 1.06 (1.02, 1.10) in people living close to low numbers (

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.

Genomic evolution of antimicrobial resistance in Escherichia coli.

The emergence of antimicrobial resistance (AMR) is one of the biggest health threats globally. In addition, the use of antimicrobial drugs in humans and livestock is considered an important driver of antimicrobial resistance. The commensal microbiota, and especially the intestinal microbiota, has been shown to have an important role in the emergence of AMR. Mobile genetic elements (MGEs) also play a central role in facilitating the acquisition and spread of AMR genes. We isolated Escherichia coli (n = 627) from fecal samples in respectively 25 poultry, 28 swine, and 15 veal calf herds from 6 European countries to investigate the phylogeny of E. coli at country, animal host and farm levels. Furthermore, we examine the evolution of AMR in E. coli genomes including an association with virulence genes, plasmids and MGEs. We compared the abundance metrics retrieved from metagenomic sequencing and whole genome sequenced of E. coli isolates from the same fecal samples and farms. The E. coli isolates in this study indicated no clonality or clustering based on country of origin and genetic markers; AMR, and MGEs. Nonetheless, mobile genetic elements play a role in the acquisition of AMR and virulence genes. Additionally, an abundance of AMR was agreeable between metagenomic and whole genome sequencing analysis for several AMR classes in poultry fecal samples suggesting that metagenomics could be used as an indicator for surveillance of AMR in E. coli isolates and vice versa.

High Coxiella burnetii Seroconversion Rate in Veterinary Students, the Netherlands, 2006-2010.

We examined Coxiella burnetii seroconversion rates by measuring C. burnetii IgG among 2 cohorts of veterinary students. During follow-up of 118 seronegative veterinary students, 23 students seroconverted. Although the clinical importance of the presence of antibodies is unknown, veterinary students should be informed about the potential risks for Q fever.

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.

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.

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.

Prediction of human active mobility in rural areas: development and validity tests of three different approaches.

BACKGROUND/AIM: Active mobility may play a relevant role in the assessment of environmental exposures (e.g. traffic-related air pollution, livestock emissions), but data about actual mobility patterns are work intensive to collect, especially in large study populations, therefore estimation methods for active mobility may be relevant for exposure assessment in different types of studies. We previously collected mobility patterns in a group of 941 participants in a rural setting in the Netherlands, using week-long GPS tracking. We had information regarding personal characteristics, self-reported data regarding weekly mobility patterns and spatial characteristics. The goal of this study was to develop versatile estimates of active mobility, test their accuracy using GPS measurements and explore the implications for exposure assessment studies. METHODS: We estimated hours/week spent on active mobility based on personal characteristics (e.g. age, sex, pre-existing conditions), self-reported data (e.g. hours spent commuting per bike) or spatial predictors such as home and work address. Estimated hours/week spent on active mobility were compared with GPS measured hours/week, using linear regression and kappa statistics. RESULTS: Estimated and measured hours/week spent on active mobility had low correspondence, even the best predicting estimation method based on self-reported data, resulted in a R2 of 0.09 and Cohen's kappa of 0.07. A visual check indicated that, although predicted routes to work appeared to match GPS measured tracks, only a small proportion of active mobility was captured in this way, thus resulting in a low validity of overall predicted active mobility. CONCLUSIONS: We were unable to develop a method that could accurately estimate active mobility, the best performing method was based on detailed self-reported information but still resulted in low correspondence. For future studies aiming to evaluate the contribution of home-work traffic to exposure, applying spatial predictors may be appropriate. Measurements still represent the best possible tool to evaluate mobility patterns.