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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

Antimicrobial resistance is a persistent challenge in human and veterinary medicine, which is often encoded on plasmids which are transmissible between bacterial cells. Incompatibility is the inability of two plasmids to be stably maintained in one cell which is caused by the presence of identical or closely related shared determinants between two plasmids originating from partition or replication mechanisms. For I-complex plasmids in Enterobacteriacae, replication- based incompatibility is caused by the small antisense RNA stem-loop structure called RNAI. The I-complex plasmid group IncK consists of two compatible subgroups, IncK1 and IncK2, for which the RNAI differs only by five nucleotides. In this study we focussed on the interaction of the IncK1 and IncK2 RNAI structures by constructing minireplicons containing the replication region of IncK1 or IncK2 plasmids coupled with a kanamycin resistance marker. Using minireplicons excludes involvement of incompatibility mechanisms other than RNAI. Additionally, we performed single nucleotide mutagenesis targeting the five nucleotides that differ between the IncK1 and IncK2 RNAI sequences of these minireplicons. The obtained results show that a single nucleotide change in the RNAI structure is responsible for the compatible phenotype of IncK1 with IncK2 plasmids. Only nucleotides in the RNAI top loop and interior loop have an effect on minireplicon incompatibility with wild type plasmids, while mutations in the stem of the RNAI structure had no significant effect on incompatibility. Understanding the molecular basis of incompatibility is relevant for future in silico predictions of plasmid incompatibility.

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, bla CTX-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 considere

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.

Although often overlooked, the use of disinfectants can lead to antimicrobial resistance and this may exacerbate resistance to antibiotics. Here, we explain why all antimicrobial agents, including disinfectants, should be used prudently in a way that is guided by evidence.

The quantification and identification of new plasmid-acquiring bacteria in representative mating conditions is critical to characterize the risk of horizontal gene transfer in the environment. This study aimed to quantify conjugation events resulting from manure application to soils and identify the transconjugants resulting from these events. Conjugation was quantified at multiple time points by plating and flow cytometry, and the transconjugants were recovered by fluorescence-activated cell sorting and identified by 16S rRNA sequencing. Overall, transconjugants were only observed within the first 4 days after manure application and at values close to the detection limits of this experimental system (1.00-2.49 log CFU/g of manured soil, ranging between 10(-5) and 10(-4) transconjugants-to-donor ratios). In the pool of recovered transconjugants, we found amplicon sequence variants (ASVs) of genera whose origin was traced to soils (Bacillus and Nocardioides) and manure (Comamonas and Rahnella). This work showed that gene transfer from fecal to soil bacteria occurred despite the less-than-optimal conditions faced by manure bacteria when transferred to soils, but these events were rare, mainly happened shortly after manure application, and the plasmid did not colonize the soil community. This study provides important information to determine the risks of AMR spread via manure application.

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.

Objectives To explore the effects of using different indicators to quantify antimicrobial usage (AMU) in livestock and compare outcomes with antimicrobial resistance (AMR) data. Methods Three indicators were used to quantify AMU, two indicators in which the denominator varied: defined daily doses per average mass of the animals present per year (DDD/AY) and defined daily doses per population correction unit (DDD/PCU) and one in which the numerator varied: milligrams of active ingredient per PCU (mg/PCU). AMU was compared with antimicrobial resistance data from the national monitoring programme from 2013 to 2018 with the proportion of Escherichia coli isolates fully susceptible to a predefined panel of antimicrobials for the broiler, dairy cattle and pig farming livestock sectors in the Netherlands. Results The ranking of livestock sectors differs between sectors when using different indicators to express AMU. Dairy cattle rank lowest when expressing AMU in DDD/AY, followed by pigs and broilers corresponding to the rankings of the sectors for AMR. When changing the denominator to PCU, the ranking in AMU is reversed: use ranks highest in dairy cattle and lowest broilers. Conclusions Using different denominators in AMU indicators has a major impact on measured use. This might result in misinterpretation of effects of interventions on AMU and the associations of AMU with AMR across animal sectors. From an epidemiological perspective, indicators that take into account time at risk of exposure to antimicrobials are to be preferred and reflect the AMR risk most accurately.