Drinking Water and Biofilm as Sources of Antimicrobial Resistance in Free-Range Organic Broiler Farms.

Drinking water distribution systems (DWDSs) represent an ideal environment for biofilm formation, which can harbor pathogenic and antimicrobial-resistant bacteria. This study aimed to assess longitudinally the microbial community composition and antimicrobial resistance (AMR), as determined by 16S rRNA NGS and qPCR, respectively, in drinking water (DW) and biofilm from DWDSs, as well as faeces, of free-range organic broiler farms. The role of DWDSs in AMR gene (ARG) dissemination within the farm environment and transmission to animals, was also assessed. DW and biofilm microbial communities differed from those of faecal samples. Moreover, potentially pathogenic and opportunistic bacteria (e.g., Staphylococcaceae) were identified in water and biofilms. High prevalence and abundance of ARGs conferring resistance to carbapenems (i.e., blaNDM), 3rd and 4th generation cephalosporins (i.e., blaCMY-2), (fluoro)quinolones (i.e., qnrS), and polymyxins (i.e., mcr-3 and mcr-5) were detected in DW, biofilm, and faecal samples, which is of concern for both animal and human health. Although other factors (e.g., feed, pests, and wildlife) may contribute to the dissemination of AMR in free-range organic poultry farms, this study indicates that DWDSs can also play a role.

Use of whole genome sequencing for surveillance and control of foodborne diseases: status quo and quo vadis.

Improvements in sequencing quality, availability, speed and costs results in an increased presence of genomics in infectious disease applications. Nevertheless, there are still hurdles in regard to the optimal use of WGS for public health purposes. Here, we discuss the current state ("status quo") and future directions ("quo vadis") based on literature regarding the use of genomics in surveillance, hazard characterization and source attribution of foodborne pathogens. The future directions include the application of new techniques, such as machine learning and network approaches that may overcome the current shortcomings. These include the use of fixed genomic distances in cluster delineation, disentangling similarity or lack thereof in source attribution, and difficulties ascertaining function in hazard characterization. Although, the aforementioned methods can relatively easily be applied technically, an overarching challenge is the inference and biological/epidemiological interpretation of these large amounts of high-resolution data. Understanding the context in terms of bacterial isolate and host diversity allows to assess the level of representativeness in regard to sources and isolates in the dataset, which in turn defines the level of certainty associated with defining clusters, sources and risks. This also marks the importance of metadata (clinical, epidemiological, and biological) when using genomics for public health purposes.

Profiling the fecal microbiome and its modulators across the lifespan in the Netherlands.

Defining what constitutes a healthy microbiome throughout our lives remains an ongoing challenge. Understanding to what extent host and environmental factors can influence it has been the primary motivation for large population studies worldwide. Here, we describe the fecal microbiome of 3,746 individuals (0-87 years of age) in a nationwide study in the Netherlands, in association with extensive questionnaires. We validate previous findings, such as infant-adult trajectories, and explore the collective impact of our variables, which explain over 40% of the variation in microbiome composition. We identify associations with less explored factors, particularly those ethnic related, which show the largest impact on the adult microbiome composition, diversity, metabolic profiles, and CAZy (carbohydrate-active enzyme) repertoires. Understanding the sources of microbiome variability is crucial, given its potential as a modifiable target with therapeutic possibilities. With this work, we aim to serve as a foundational element for the design of health interventions and fundamental research.

Association between antimicrobial usage in livestock and antimicrobial resistance in Escherichia coli isolates from human urinary tract infections in the Netherlands, 2009-2020.

BACKGROUND: In the last decade, veterinary antimicrobial usage (AMU) and antimicrobial resistance (AMR) among indicator bacteria in livestock have decreased substantially in the Netherlands. The extent to which this decrease has affected AMR levels among human infections remains unclear. OBJECTIVES: To assess the association between AMU in livestock and AMR in Escherichia coli isolates from human urinary tract infections (UTIs). METHODS: Data on AMR and AMU between 2009 and 2020 from Dutch national surveillance programmes for humans and livestock were used. Associations between AMU in four major livestock sectors and AMR in humans were assessed for 10 antimicrobial classes and the ESBL resistance profile, using logistic regression analysis. Associations between AMU and AMR in livestock, between AMR in livestock and in humans, and between AMU and AMR in humans were also assessed. RESULTS: Statistical significance was reached for 16/31 of the tested associations between AMU in livestock and AMR in human E. coli UTIs. Of the significant associations, 11 were positive (OR 1.01-1.24), whereas 5 were negative (OR 0.96-0.99). All associations between human AMU and AMR in E. coli isolates from UTIs were positive and statistically significant. Weak but significant positive correlations were also observed between livestock AMR and human AMR. CONCLUSIONS: Although several significant associations between AMU in livestock and AMR in human UTIs caused by E. coli were observed, the associations between AMU and AMR were generally stronger within the human and animal populations. This indicates that potential zoonotic spread of AMR in E. coli causing human UTIs from livestock sources is limited.

Temporal association of antimicrobial use in livestock with antimicrobial resistance in non-typhoid Salmonella human infections in the Netherlands, 2008-2019.

Background: Antimicrobial use (AMU) in livestock contributes to antimicrobial resistance (AMR) among zoonotic pathogens, such as non-typhoid Salmonella (NTS). Since 2009, the Netherlands has made substantial efforts to reduce AMU in livestock. Objectives: To assess the association between AMU in livestock and AMR in NTS human isolates. Additionally, associations between AMU in broilers/pigs and AMR in NTS broiler/pig isolates, and between AMR in broilers/pigs and in human NTS isolates were assessed. The focus was on Salmonella Enteritidis (SE) and Salmonella Typhimurium including its monophasic variant (ST/STM). Methods: A national population registry-based study was conducted in the Netherlands from 2008 to 2019. Multivariable logistic regression models were used to assess the associations between livestock AMU and NTS resistance proportion in humans and broilers/pigs, overall as well as per class-specific antimicrobials. Correlation analysis was performed to relate AMR proportions between human and broiler/pig NTS isolates. Results: For SE, only a positive association between penicillins use in broilers and resistance to ampicillin among human isolates was significant. For ST/STM, most associations between AMU in livestock and AMR among human isolates were significantly positive, overall and per class-specific antimicrobials, namely for penicillins-ampicillin, tetracyclines-tetracycline and sulfonamides/trimethoprim-sulfamethoxazole/trimethoprim. Significantly positive associations between AMU in broilers/pigs and AMR in broiler/pig ST/STM isolates were also observed, but not between broiler/pig and human AMR levels. Conclusions: Significant associations were generally found between livestock AMU and AMR in human and broiler/pig ST/STM isolates. However, confounding factors, such as imported meat and travel are of concern. To fully comprehend the impact of livestock AMU on resistance in human NTS isolates, it is imperative to enhance AMR surveillance of NTS.

Livestock-associated spatial risk factors for human salmonellosis and campylobacteriosis.

AIMS: Most human infections with non-typhoid Salmonella (NTS) or Campylobacter are zoonotic in nature and acquired though consumption of contaminated food of mainly animal origin. However, individuals may also acquire salmonellosis or campylobacteriosis through non-foodborne transmission pathways, such as those mediated by the environment. This emphasizes the need to consider both direct and indirect exposure to livestock sources as a possible transmission route for NTS and Campylobacter. Therefore, this study aimed at assessing whether salmonellosis and campylobacteriosis incidence is spatially associated with exposure to livestock (i.e. small ruminants, dairy cows, veal calves, laying hens, broiler chickens and pigs) in the Netherlands for the years 2007-2019 and 2014-2019 respectively. METHODS AND RESULTS: Risk factors (population-weighted number of animals) and their population attributable fractions were determined using a Poisson regression model with a log-link function fitted using integrated nested Laplace approximation. The analyses were performed for different hexagonal sizes (90, 50, 25 and 10 km2) and accounted for geographical coverage of the diagnostic laboratory catchment areas. Moreover, serological data were used to look into the possible effects of acquired immunity due to repeated exposure to the pathogen through the environment that would potentially hinder the analyses based on the incidence of reported cases. A linear mixed-effects model was then fitted where the postal code areas were included as a random effect. Livestock was not consistently significantly associated with acquiring salmonellosis or campylobacteriosis in the Netherlands. CONCLUSIONS: Results showed that living in livestock-rich areas in the Netherlands is not a consistently significant, spatially restricted risk factor for acquiring salmonellosis or campylobacteriosis, thereby supporting current knowledge that human infections with Salmonella and Campylobacter are mainly foodborne.

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.

Attitudes towards zoonotic disease risk vary across sociodemographic, communication and health-related factors: A general population survey on literacy about zoonoses in the Netherlands.

Introduction: Literacy about zoonoses can contribute people adapt their behaviour to minimize zoonotic risks. In this study, associations between sociodemographic factors and zoonotic risk-averse attitudes were explored. Objective: To determine factors significantly associated with literacy about zoonoses across sociodemographic groups to inform targeted interventions aiming at improving awareness and zoonotic risk-avoidance behaviours. Method: Data was collected in 2022 using an online survey of a nationally representative sample of residents in the Netherlands. A multivariable logistic regression analysis, accounting for multiple hypothesis testing, was applied to assess whether there were significant associations between socio-demographic factors and attitudes towards zoonosis prevention. Results: A total of 2039 respondents completed the survey. People who were female, older, highly educated and those who searched for information about zoonoses, were relatively more likely to report behaviours favourable to the prevention of zoonoses. However, people with limited language and computer skills and immunocompromised people were significantly more likely to report risky behaviours. There were no significant associations found for pregnant women, dog and cat owners, those with an intermediate level of education and those who do have contact with farm animals. Conclusion: Certain sociodemographic groups display significantly riskier attitudes towards zoonoses. These groups provide targets where to improve literacy about zoonoses. This also implies that there is room for improvement in literacy about zoonoses, particularly among immunocompromised people and people with limited language and limited computer skills.

Effects of long-term exposure to outdoor air pollution on COVID-19 incidence: A population-based cohort study accounting for SARS-CoV-2 exposure levels in the Netherlands.

Several studies have linked air pollution to COVID-19 morbidity and severity. However, these studies do not account for exposure levels to SARS-CoV-2, nor for different sources of air pollution. We analyzed individual-level data for 8.3 million adults in the Netherlands to assess associations between long-term exposure to ambient air pollution and SARS-CoV-2 infection (i.e., positive test) and COVID-19 hospitalisation risks, accounting for spatiotemporal variation in SARS-CoV-2 exposure levels during the first two major epidemic waves (February 2020-February 2021). We estimated average annual concentrations of PM10, PM2.5 and NO2 at residential addresses, overall and by PM source (road traffic, industry, livestock, other agricultural sources, foreign sources, other Dutch sources), at 1 × 1 km resolution, and weekly SARS-CoV-2 exposure at municipal level. Using generalized additive models, we performed interval-censored survival analyses to assess associations between individuals' average exposure to PM10, PM2.5 and NO2 in the three years before the pandemic (2017-2019) and COVID-19-outcomes, adjusting for SARS-CoV-2 exposure, individual and area-specific confounders. In single-pollutant models, per interquartile (IQR) increase in exposure, PM10 was associated with 7% increased infection risk and 16% increased hospitalisation risk, PM2.5 with 8% increased infection risk and 18% increased hospitalisation risk, and NO2 with 3% increased infection risk and 11% increased hospitalisation risk. Bi-pollutant models suggested that effects were mainly driven by PM. Associations for PM were confirmed when stratifying by urbanization degree, epidemic wave and testing policy. All emission sources of PM, except industry, showed adverse effects on both outcomes. Livestock showed the most detrimental effects per unit exposure, whereas road traffic affected severity (hospitalisation) more than infection risk. This study shows that long-term exposure to air pollution increases both SARS-CoV-2 infection and COVID-19 hospitalisation risks, even after controlling for SARS-CoV-2 exposure levels, and that PM may have differential effects on these COVID-19 outcomes depending on the emission source.

Outdoor air pollution as a risk factor for testing positive for SARS-CoV-2: A nationwide test-negative case-control study in the Netherlands.

Air pollution is a known risk factor for several diseases, but the extent to which it influences COVID-19 compared to other respiratory diseases remains unclear. We performed a test-negative case-control study among people with COVID-19-compatible symptoms who were tested for SARS-CoV-2 infection, to assess whether their long- and short-term exposure to ambient air pollution (AAP) was associated with testing positive (vs. negative) for SARS-CoV-2. We used individual-level data for all adult residents in the Netherlands who were tested for SARS-CoV-2 between June and November 2020, when only symptomatic people were tested, and modeled ambient concentrations of PM10, PM2.5, NO2 and O3 at geocoded residential addresses. In long-term exposure analysis, we selected individuals who did not change residential address in 2017-2019 (1.7 million tests) and considered the average concentrations of PM10, PM2.5 and NO2 in that period, and different sources of PM (industry, livestock, other agricultural activities, road traffic, other Dutch sources, foreign sources). In short-term exposure analysis, individuals not changing residential address in the two weeks before testing day (2.7 million tests) were included in the analyses, thus considering 1- and 2-week average concentrations of PM10, PM2.5, NO2 and O3 before testing day as exposure. Mixed-effects logistic regression analysis with adjustment for several confounders, including municipality and testing week to account for spatiotemporal variation in viral circulation, was used. Overall, there was no statistically significant effect of long-term exposure to the studied pollutants on the odds of testing positive vs. negative for SARS-CoV-2. However, significant positive associations of long-term exposure to PM10 and PM2.5 from specifically foreign and livestock sources, and to PM10 from other agricultural sources, were observed. Short-term exposure to PM10 (adjusting for NO2) and PM2.5 were also positively associated with increased odds of testing positive for SARS-CoV-2. While these exposures seemed to increase COVID-19 risk relative to other respiratory diseases, the underlying biological mechanisms remain unclear. This study reinforces the need to continue to strive for better air quality to support public health.

Comparing human and animal antimicrobial usage: a critical appraisal of the indicators used is needed.

Comparisons between antimicrobial usage (AMU) in humans and food-producing animals are regularly made. The accuracy of such comparisons depends on the indicators used to quantify AMU. Indicators for AMU quantitatively relate use data (the numerator) to population data (the denominator). The denominator should be a proxy for the population at risk in a certain period when comparing the exposure of different populations to antimicrobials. Denominators based on numbers of animals slaughtered, such as the commonly used population correction unit, do not consider the time at risk of antimicrobial treatment. Production-based indicators underestimate animal AMU. Additionally, production-based indicators are fundamentally different from indicators used to quantify human AMU. Using such indicators to compare human and animal AMU therefore leads to biased results. More caution should be taken in selecting the indicator to quantify AMU when comparing AMU in food-producing animals and humans.

Animal sources of antimicrobial-resistant bacterial infections in humans: a systematic review.

Bacterial antimicrobial resistance (AMR) is among the leading global health challenges of the century. Animals and their products are known contributors to the human AMR burden, but the extent of this contribution is not clear. This systematic literature review aimed to identify studies investigating the direct impact of animal sources, defined as livestock, aquaculture, pets, and animal-based food, on human AMR. We searched four scientific databases and identified 31 relevant publications, including 12 risk assessments, 16 source attribution studies, and three other studies. Most studies were published between 2012 and 2022, and most came from Europe and North America, but we also identified five articles from South and South-East Asia. The studies differed in their methodologies, conceptual approaches (bottom-up, top-down, and complex), definitions of the AMR hazard and outcome, the number and type of sources they addressed, and the outcome measures they reported. The most frequently addressed animal source was chicken, followed by cattle and pigs. Most studies investigated bacteria-resistance combinations. Overall, studies on the direct contribution of animal sources of AMR are rare but increasing. More recent publications tailor their methodologies increasingly towards the AMR hazard as a whole, providing grounds for future research to build on.

Gut Colonization by ESBL-Producing Escherichia coli in Dogs Is Associated with a Distinct Microbiome and Resistome Composition.

The gut microbiome of humans and animals acts as a reservoir of extended-spectrum beta-lactamase-producing Escherichia coli (ESBL-EC). Dogs are known for having a high prevalence of ESBL-EC in their gut microbiota, although their ESBL-EC carrier status often shifts over time. We hypothesized that the gut microbiome composition of dogs is implicated in ESBL-EC colonization status. Therefore, we assessed whether ESBL-EC carriage in dogs is associated with changes in the gut microbiome and resistome. Fecal samples were collected longitudinally from 57 companion dogs in the Netherlands every 2 weeks for a total of 6 weeks (n = 4 samples/dog). Carriage of ESBL-EC was determined through selective culturing and PCR and in line with previous studies, we observed a high prevalence of ESBL-EC carriage in dogs. Using 16s rRNA gene profiling we found significant associations between detected ESBL-EC carriage and an increased abundance of Clostridium sensu stricto 1, Enterococcus, Lactococcus, and the shared genera of Escherichia-Shigella in the dog microbiome. A resistome capture sequencing approach (ResCap) furthermore, revealed associations between detected ESBL-EC carriage and the increased abundance of the antimicrobial resistance genes: cmlA, dfrA, dhfR, floR, and sul3. In summary, our study showed that ESBL-EC carriage is associated with a distinct microbiome and resistome composition. IMPORTANCE The gut microbiome of humans and animals is an important source of multidrug resistant pathogens, including beta-lactamase-producing Escherichia coli (ESBL-EC). In this study, we assessed if the carriage of ESBL-EC in dogs was associated with changes in gut composition of bacteria and antimicrobial resistant genes (ARGs). Therefore, stool samples from 57 dogs were collected every 2 weeks for a total of 6 weeks. Sixty eight percent of the dogs carried ESBL-EC during at least one of the time points analyzed. By investigating the gut microbiome and resistome composition, we observed specific changes at time points when dogs were colonized with ESBL-EC compared to time points whenESBL-EC were not detected. In conclusion, our study highlights the importance to study the microbial diversity in companion animals, as gut colonization of particular antimicrobial resistant bacteria might be an indication of a changed microbial composition that is associated with the selection of particular ARGs.

Assessing potential determinants of the stagnating trend in Salmonella Enteritidis human infections in Europe and options for intervention: A multi-criteria decision analysis.

Background: After years of significant decline, the incidence of Salmonella enterica serotype Enteritidis (SE) human infections in Europe has started stagnating in recent years. The reasons for this stagnation remain largely unclear and are possibly multifactorial and interconnected in nature. We assessed and ranked several potential determinants of the stagnating SE trend in Europe, as well as different options for intervention at the level of poultry health and production, public health (infra)structure, and pathogen biology. Methods: A Multi-Criteria Decision-Analysis (MCDA) approach based on the Analytical Hierarchy Process was used. Through two separate surveys, a European panel of Salmonella experts first provided weights for several pre-defined criteria and subsequently scored different potential determinants and options for intervention (i.e. alternatives) against the criteria, during 2020-21. The weighting and scoring were based on Saaty's pairwise comparisons. The final ranking of the alternatives was derived from the summation of the products of each criterion weight with the score of the corresponding alternative. Sensitivity analyses were performed to assess the impact of different methodological choices, including European regions, and domains of expertise on the ranking of the determinants and options for intervention. Results: The first and second-ranked determinants of the stagnated trend in human SE infections were related to poultry health and production, namely "inadequacies of sampling programmes" and "premature relaxation of control measures". This ranking agreed with the ranking of the options for intervention, which were also those at the poultry health and production level, specifically "stricter biosecurity", "improving sampling", and "better/increased vaccination". Differences in rankings were observed among European regions and domains of expertise. Conclusions: The rankings of potential determinants and options for intervention for the stagnating SE trend in Europe pointed to the level of poultry health and production. Salmonella-control activities in poultry in Europe are harmonized across countries since many years, but the results of this study suggest that further improvements may be necessary for some countries. A multidisciplinary collaboration among veterinarians, public health professionals, and microbiologists is needed to further understand the origins of the stagnating SE trend and to identify effective interventions in order to reverse the trend, contextually in a given country, following a One Health approach.

Assessing phenotypic virulence of Salmonella enterica across serovars and sources.

Introduction: Whole genome sequencing (WGS) is increasingly used for characterizing foodborne pathogens and it has become a standard typing technique for surveillance and research purposes. WGS data can help assessing microbial risks and defining risk mitigating strategies for foodborne pathogens, including Salmonella enterica. Methods: To test the hypothesis that (combinations of) different genes can predict the probability of infection [P(inf)] given exposure to a certain pathogen strain, we determined P(inf) based on invasion potential of 87 S. enterica strains belonging to 15 serovars isolated from animals, foodstuffs and human patients, in an in vitro gastrointestinal tract (GIT) model system. These genomes were sequenced with WGS and screened for genes potentially involved in virulence. A random forest (RF) model was applied to assess whether P(inf) of a strain could be predicted based on the presence/absence of those genes. Moreover, the association between P(inf) and biofilm formation in different experimental conditions was assessed. Results and Discussion: P(inf) values ranged from 6.7E-05 to 5.2E-01, showing variability both among and within serovars. P(inf) values also varied between isolation sources, but no unambiguous pattern was observed in the tested serovars. Interestingly, serovars causing the highest number of human infections did not show better ability to invade cells in the GIT model system, with strains belonging to other serovars displaying even higher infectivity. The RF model did not identify any virulence factor as significant P(inf) predictors. Significant associations of P(inf) with biofilm formation were found in all the different conditions for a limited number of serovars, indicating that the two phenotypes are governed by different mechanisms and that the ability to form biofilm does not correlate with the ability to invade epithelial cells. Other omics techniques therefore seem more promising as alternatives to identify genes associated with P(inf), and different hypotheses, such as gene expression rather than presence/absence, could be tested to explain phenotypic virulence [P(inf)].

When COVID-19 sits on people's laps: A systematic review of SARS-CoV-2 infection prevalence in household dogs and cats.

During the COVID-19 pandemic, questions were raised about whether SARS-CoV-2 can infect pets and the potential risks posed to and by their human owners. We performed a systematic review of studies on SARS-CoV-2 infection prevalence in naturally infected household dogs and cats conducted worldwide and published before January 2022. Data on SARS-CoV-2 infection prevalence, as determined by either molecular or serological methods, and accompanying information, were summarized. Screening studies targeting the general dog or cat populations were differentiated from those targeting households with known COVID-19-positive people. Studies focusing on stray, sheltered or working animals were excluded. In total, 17 studies were included in this review. Fourteen studies investigated cats, 13 investigated dogs, and 10 investigated both. Five studies reported molecular prevalence, 16 reported seroprevalence, and four reported both. All but two studies started and ended in 2020. Studies were conducted in eight European countries (Italy, France, Spain, Croatia, Germany, the Netherlands, UK, Poland), three Asian countries (Iran, Japan, China) and the USA. Both molecular and serological prevalence in the general pet population were usually below 5%, but exceeded 10% when COVID-19 positive people were known to be present in the household. A meta-analysis provided pooled seroprevalence estimates in the general pet population: 2.75% (95% Confidence Interval [CI]: 1.56-4.79%) and 0.82% (95% CI: 0.26-2.54%) for cats and dogs, respectively. This review highlighted the need for a better understanding of the possible epizootic implications of the COVID-19 pandemic, as well as the need for global standards for SARS-CoV-2 detection in pets.

Biosecurity and antimicrobial use in broiler farms across nine European countries: toward identifying farm-specific options for reducing antimicrobial usage.

Broiler chickens are among the main livestock sectors worldwide. With individual treatments being inapplicable, contrary to many other animal species, the need for antimicrobial use (AMU) is relatively high. AMU in animals is known to drive the emergence and spread of antimicrobial resistance (AMR). High farm biosecurity is a cornerstone for animal health and welfare, as well as food safety, as it protects animals from the introduction and spread of pathogens and therefore the need for AMU. The goal of this study was to identify the main biosecurity practices associated with AMU in broiler farms and to develop a statistical model that produces customised recommendations as to which biosecurity measures could be implemented on a farm to reduce its AMU, including a cost-effectiveness analysis of the recommended measures. AMU and biosecurity data were obtained cross-sectionally in 2014 from 181 broiler farms across nine European countries (Belgium, Bulgaria, Denmark, France, Germany, Italy, the Netherlands, Poland and Spain). Using mixed-effects random forest analysis (Mix-RF), recursive feature elimination was implemented to determine the biosecurity measures that best predicted AMU at the farm level. Subsequently, an algorithm was developed to generate AMU reduction scenarios based on the implementation of these measures. In the final Mix-RF model, 21 factors were present: 10 about internal biosecurity, 8 about external biosecurity and 3 about farm size and productivity, with the latter showing the largest (Gini) importance. Other AMU predictors, in order of importance, were the number of depopulation steps, compliance with a vaccination protocol for non-officially controlled diseases, and requiring visitors to check in before entering the farm. K-means clustering on the proximity matrix of the final Mix-RF model revealed that several measures interacted with each other, indicating that high AMU levels can arise for various reasons depending on the situation. The algorithm utilised the AMU predictive power of biosecurity measures while accounting also for their interactions, representing a first step toward aiding the decision-making process of veterinarians and farmers who are in need of implementing on-farm biosecurity measures to reduce their AMU.

Repetitive non-typhoidal Salmonella exposure is an environmental risk factor for colon cancer and tumor growth.

During infection, Salmonella hijacks essential host signaling pathways. These molecular manipulations disrupt cellular integrity and may induce oncogenic transformation. Systemic S. Typhi infections are linked to gallbladder cancer, whereas severe non-typhoidal Salmonella (NTS) infections are associated with colon cancer (CC). These diagnosed infections, however, represent only a small fraction of all NTS infections as many infections are mild and go unnoticed. To assess the overall impact of NTS infections, we performed a retrospective serological study on NTS exposure in patients with CC. The magnitude of exposure to NTS, as measured by serum antibody titer, is significantly positively associated with CC. Repetitively infecting mice with low NTS exposure showed similar accelerated tumor growth to that observed after high NTS exposure. At the cellular level, NTS preferably infects (pre-)transformed cells, and each infection round exponentially increases the rate of transformed cells. Thus, repetitive exposure to NTS associates with CC risk and accelerates tumor growth.

Amoxicillin and thiamphenicol treatments may influence the co-selection of resistance genes in the chicken gut microbiota.

The aim of this study was to assess the dynamics of microbial communities and antimicrobial resistance genes (ARGs) in the chicken gut following amoxicillin and thiamphenicol treatments and potential co-selection of ARGs. To this purpose, the microbial community composition, using 16S rRNA NGS, and the abundance of ARGs conferring resistance to ß-lactams and phenicols, using qPCRs, were determined. Results revealed that the administered antimicrobials did not significantly reduce the gut microbiota diversity, but changed its composition, with taxa (e.g. Gallibacterium and Megamonas) being enriched after treatment and replacing other bacteria (e.g. Streptococcus and Bifidobacterium). Positive correlations were found between ARGs (e.g. cmlA, blaCMY-2, and blaSHV) and the relative abundance of specific taxa (e.g. Lactobacillus and Subdoligranulum). The selective pressure exerted by both amoxicillin and thiamphenicol resulted in an increased abundance of ARGs conferring resistance to ß-lactams (e.g. blaTEM-1, blaSHV, and blaCTX-M1-like) and phenicols (e.g. floR and cmlA). These findings, together with the co-occurrence of genes conferring resistance to the two antimicrobial classes (e.g. blaTEM-1 and cmlA), suggest a possible interaction among antimicrobials on resistance emergence, possibly due to the presence of mobile genetic elements (MGEs) carrying multiple resistance determinants.