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.

Source Attribution of Antibiotic Resistance Genes in Estuarine Aquaculture: A Machine Learning Approach.

Aquaculture located in urban river estuaries, where other anthropogenic activities may occur, has an impact on and may be affected by the environment where they are inserted, namely by the exchange of antimicrobial resistance genes. The latter may ultimately, through the food chain, represent a source of resistance genes to the human resistome. In an exploratory study of the presence of resistance genes in aquaculture sediments located in urban river estuaries, two machine learning models were applied to predict the source of 34 resistome observations in the aquaculture sediments of oysters and gilt-head sea bream, located in the estuaries of the Sado and Lima Rivers and in the Aveiro Lagoon, as well as in the sediments of the Tejo River estuary, where Japanese clams and mussels are collected. The first model included all 34 resistomes, amounting to 53 different antimicrobial resistance genes used as source predictors. The most important antimicrobial genes for source attribution were tetracycline resistance genes tet(51) and tet(L); aminoglycoside resistance gene aadA6; beta-lactam resistance gene blaBRO-2; and amphenicol resistance gene cmx_1. The second model included only oyster sediment resistomes, amounting to 30 antimicrobial resistance genes as predictors. The most important antimicrobial genes for source attribution were the aminoglycoside resistance gene aadA6, followed by the tetracycline genes tet(L) and tet(33). This exploratory study provides the first information about antimicrobial resistance genes in intensive and semi-intensive aquaculture in Portugal, helping to recognize the importance of environmental control to maintain the integrity and the sustainability of aquaculture farms.

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.

Metagenomics-Based Approach to Source-Attribution of Antimicrobial Resistance Determinants - Identification of Reservoir Resistome Signatures.

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 broilers and turkeys, and the majority of these resistome dissimilarities can be explained by a small set of AMR determinants. We identified resistome signatures for each individual reservoir, which include AMR determinants significantly associated with on-farm antimicrobial use. We attributed human resistomes to different livestock reservoirs using Random Forests, which allowed identifying pigs as a potential source of AMR in humans. This study thus demonstrates that it is possible to apply metagenomics in AMR source-attribution.

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.

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.

Effect of slaughterhouse and day of sample on the probability of a pig carcass being Salmonella-positive according to the Enterobacteriaceae count in the largest Brazilian pork production region.

Sources of contamination of carcasses during slaughter include infected pigs as well as environmentally related sources. There are many microbial indicators that can be used in the processing of food to assess food hygiene and the safety of food processing. The presence of some microbial indicators can be viewed as a result of direct or indirect contamination of a food with fecal material. The presence of Enterobacteriaceae is often used as a hygiene indicator, as they are found both in the environment and in the intestine of warm-blooded animals. An association between Salmonella isolation and Enterobacteriaceae count (EC) on pre-chill carcasses has been described, however the impact of slaughterhouse and the day of sampling on the occurrence of Salmonella has not been previously investigated. To this end, mixed logistic regressions (MLRs) with random effects and fixed slopes were performed to assess the change in EC and its correlation with Salmonella occurrence using two data sets. The first describes the EC and Salmonella isolation in 60 pork carcasses in one slaughterhouse sampled at 11 different slaughter steps, including the carcass as a random effect. The second describes the EC and Salmonella isolation on 1150 pre-chill carcasses sampled in 13 slaughterhouses over 230 sampling days, and the model combined two random intercepts, slaughterhouse and date of sampling nested with slaughterhouse (day/slaughterhouse). Statistically significant associations (p<0.0001) between the log of the EC and Salmonella occurrence were found in all models. Nevertheless, although a strong association was found between Enterobacteriaceae and Salmonella contamination in pork carcasses, this association was not constant, given that there was a high variation in the probability of a carcass being positive for Salmonella according to the EC mainly between days of samples. The effect of the day of sampling on Salmonella prevalence was so large that the predictive value of the EC count for Salmonella isolation on a daily basis was compromised. It is possible that on some days batches with a high prevalence of Salmonella carriers shedding a high number of Salmonella were slaughtered. On these days, the potential for contamination/cross-contamination of carcasses will be so large that even hygienic slaughter, confirmed by the low EC on carcasses, will not be able to prevent the presence of Salmonella on some carcasses. The results of this study demonstrate that, despite the statistically significant association found, it may be difficult to predict when hygiene failure measured via EC actually indicates Salmonella contamination, and neither the inverse.

The impact of screening-test negative samples not enumerated by MPN.

In microbiological surveys, false negative results in detection tests precluding the enumeration by MPN may occur. The objective of this study was to illustrate the impact of screening test failure on the probability distribution of Salmonella concentrations in pork using a Bayesian method. A total of 276 swab samples in four slaughter steps (69 samples in each slaughter step: after dehairing, after singeing, after evisceration, and before chilling) were screened for Salmonella and enumerated by the MPN method. Salmonella contamination data were fitted to a lognormal distribution by using a Bayesian model that uses the number of positive tubes at each dilution in an MPN analysis to estimate the parameters of the concentration distribution. With Salmonella paired data, three data sets were used for each slaughter step: one that includes the positives in the screening test only, a second one that includes false negative results from the screening, and a third that considers the entire data set. The relative sensitivity of the screening test was also calculated assuming as gold standard samples with confirmed Salmonella. Salmonella was confirmed by a reference laboratory in 29 samples either by screening or MPN method. The relative sensitivity of the screening test was 69% (CI 95%: 52%-85%). The data set that included enumerations from screen-negative samples (false negative results) tended to have higher µÌ‚ and smaller σ̂ in comparison with the data set that discards false negative results, suggesting that the lack of sensitivity of the screening test affects the distribution that describes the contamination across the population. Numerous surveys on fitting distribution methods of microbial censored data have been published and discuss source of bias due to fitting method. Results of this survey contribute with that discussion by illustrating another possible source of bias due to failure of the screening methods preceding the MPN.

Human risk from thermotolerant Campylobacter on broiler meat in Denmark.

This paper describes a new approach by which changes over time in the relative risk of human campylobacteriosis from broiler meat are evaluated through quantitative microbiological risk assessment modelling. Danish surveillance data collected at retail from 2001 to 2010 on numbers of thermotolerant Campylobacter spp. on Danish produced and imported chilled and frozen broiler meat were the basis for the investigation. The aim was to explore if the risk from the different meat categories had changed over time as a consequence of implemented intervention strategies. The results showed a slight decrease from 2005 to 2008 in the human risk from Danish produced broiler meat, and a decrease from 2005 to 2010 in the risk from imported chilled meat. This risk reduction coincides with control measures implemented to reduce Campylobacter in Danish and imported chilled broiler meat. The human risk of campylobacteriosis from Danish frozen meat increased but remained lower compared to chilled meat. In total, the relative risk from broiler meat available for sale in Denmark increased from 2001 to 2005 after which the risk decreased to a level similar to the period 2001-2002. The use of QMRA in the evaluation of intervention strategies based on monitoring data provided an added value, compared to the traditional approach of only using changes in prevalence. The estimated human health risk is a function of prevalence and the distribution of concentrations, and therefore takes best usage of the available data, while providing the most relevant outcome for food safety risk managers.