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

Limit of detection of Salmonella ser. Enteritidis using culture-based versus culture-independent diagnostic approaches

To prevent the spread of foodborne illnesses, the presence of pathogens in the food chain is monitored by government agencies and food producers. The culture-based methods currently employed are sensitive but time- and labor-intensive, leading to increasing interest in exploring culture-independent diagnostic tests (CIDTs) for pathogen detection. However, few studies quantify the relative sensitivity and reliability of these CIDTs compared to current approaches. To address this issue, we conducted a comparison of the limit of detection (LOD50) for Salmonella between a culture-based method and three CIDTs: qPCR (targeting invA and stn), metabarcode (16S) sequencing, and shotgun metagenomic sequencing. Samples of chicken feed and chicken caecal contents were spiked with S. serovar Enteritidis and subjected to culture- and DNA-based detection methods. To explore the impact of non-selective enrichment on LOD50, all samples underwent both immediate DNA extraction and overnight enrichment prior to gDNA extraction. In addition to this spike-in experiment, feed and caecal samples acquired from the field were tested with culturing, qPCR, and metabarcoding. In general, LOD50 was comparable between qPCR and shotgun sequencing methods. Overnight microbiological enrichment resulted in an improvement in LOD50 with up to a three-log decrease. However, Salmonella reads were detected in some unspiked feed samples, suggesting false-positive detection of Salmonella. In addition, the LOD50 in feeds was three logs lower than in caecal contents, underscoring the impact of background microbiota on Salmonella detection using all methods.

IMPORTANCE

The appeal of culture-independent diagnostic tests (CIDTs) is increased speed with lowered cost, as well as the potential to detect multiple pathogen species in a single analysis and to monitor other areas of concern such as antimicrobial resistance genes or virulence factors. This study provides quantitative data on the sensitivity of CIDTs relative to current approaches, which is essential for determining the feasibility of implementing these methods in pathogen surveillance programs.

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.

Foodborne bacterial pathogens: genome-based approaches for enduring and emerging threats in a complex and changing world

Foodborne illnesses pose a substantial health and economic burden, presenting challenges in prevention due to the diverse microbial hazards that can enter and spread within food systems. Various factors, including natural, political and commercial drivers, influence food production and distribution. The risks of foodborne illness will continue to evolve in step with these drivers and with changes to food systems. For example, climate impacts on water availability for agriculture, changes in food sustainability targets and evolving customer preferences can all have an impact on the ecology of foodborne pathogens and the agrifood niches that can carry microorganisms. Whole-genome and metagenome sequencing, combined with microbial surveillance schemes and insights from the food system, can provide authorities and businesses with transformative information to address risks and implement new food safety interventions across the food chain. In this Review, we describe how genome-based approaches have advanced our understanding of the evolution and spread of enduring bacterial foodborne hazards as well as their role in identifying emerging foodborne hazards. Furthermore, foodborne hazards exist in complex microbial communities across the entire food chain, and consideration of these co-existing organisms is essential to understanding the entire ecology supporting pathogen persistence and transmission in an evolving food system.

A cross-sectional comparison of gut metagenomes between dairy workers and community controls

BACKGROUND

As a nexus of routine antibiotic use and zoonotic pathogen presence, the livestock farming environment is a potential hotspot for the emergence of zoonotic diseases and antibiotic resistant bacteria. Livestock can further facilitate disease transmission by serving as intermediary hosts for pathogens before a spillover event. In light of this, we aimed to characterize the microbiomes and resistomes of dairy workers, whose exposure to the livestock farming environment places them at risk for facilitating community transmission of antibiotic resistant genes and emerging zoonotic diseases.

RESULTS

Using shotgun sequencing, we investigated differences in the taxonomy, diversity and gene presence of 10 dairy farm workers and 6 community controls' gut metagenomes, contextualizing these samples with additional publicly available gut metagenomes. We found no significant differences in the prevalence of resistance genes, virulence factors, or taxonomic composition between the two groups. The lack of statistical significance may be attributed, in part, to the limited sample size of our study or the potential similarities in exposures between the dairy workers and community controls. We did, however, observe patterns warranting further investigation including greater abundance of tetracycline resistance genes and prevalence of cephamycin resistance genes as well as lower average gene diversity (even after accounting for differential sequencing depth) in dairy workers' metagenomes. We also found evidence of commensal organism association with tetracycline resistance genes in both groups (including Faecalibacterium prausnitzii, Ligilactobacillus animalis, and Simiaoa sunii).

CONCLUSIONS

This study highlights the utility of shotgun metagenomics in examining the microbiomes and resistomes of livestock workers, focusing on a cohort of dairy workers in the United States. While our study revealed no statistically significant differences between groups in taxonomy, diversity and gene presence, we observed patterns in antibiotic resistance gene abundance and prevalence that align with findings from previous studies of livestock workers in China and Europe. Our results lay the groundwork for future research involving larger cohorts of dairy and non-dairy workers to better understand the impact of occupational exposure to livestock farming on the microbiomes and resistomes of workers.

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.

A Review on Microbiological Source Attribution Methods of Human Salmonellosis: From Subtyping to Whole-Genome Sequencing

Salmonella is one of the main causes of human foodborne illness. It is endemic worldwide, with different animals and animal-based food products as reservoirs and vehicles of infection. Identifying animal reservoirs and potential transmission pathways of Salmonella is essential for prevention and control. There are many approaches for source attribution, each using different statistical models and data streams. Some aim to identify the animal reservoir, while others aim to determine the point at which exposure occurred. With the advance of whole-genome sequencing (WGS) technologies, new source attribution models will greatly benefit from the discriminating power gained with WGS. This review discusses some key source attribution methods and their mathematical and statistical tools. We also highlight recent studies utilizing WGS for source attribution and discuss open questions and challenges in developing new WGS methods. We aim to provide a better understanding of the current state of these methodologies with application to Salmonella and other foodborne pathogens that are common sources of illness in the poultry and human sectors.

The need for One Health systems-thinking approaches to understand multiscale dissemination of antimicrobial resistance

Although the effects of antimicrobial resistance (AMR) are most obvious at clinical treatment failure, AMR evolution, transmission, and dispersal happen largely in environmental settings, for example within farms, waterways, livestock, and wildlife. We argue that systems-thinking, One Health approaches are crucial for tackling AMR, by understanding and predicting how anthropogenic activities interact within environmental subsystems, to drive AMR emergence and transmission. Innovative computational methods integrating big data streams (eg, from clinical, agricultural, and environmental monitoring) will accelerate our understanding of AMR, supporting decision making. There are challenges to accessing, integrating, synthesising, and interpreting such complex, multidimensional, heterogeneous datasets, including the lack of specific metrics to quantify anthropogenic AMR. Moreover, data confidentiality, geopolitical and cultural variation, surveillance gaps, and science funding cause biases, uncertainty, and gaps in AMR data and metadata. Combining systems-thinking with modelling will allow exploration, scaling-up, and extrapolation of existing data. This combination will provide vital understanding of the dynamic movement and transmission of AMR within and among environmental subsystems, and its effects across the greater system. Consequently, strategies for slowing down AMR dissemination can be modelled and compared for efficacy and cost-effectiveness.

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.

Modeling the limits of detection for antimicrobial resistance genes in agri-food samples: a comparative analysis of bioinformatics tools

BACKGROUND

Although the spread of antimicrobial resistance (AMR) through food and its production poses a significant concern, there is limited research on the prevalence of AMR bacteria in various agri-food products. Sequencing technologies are increasingly being used to track the spread of AMR genes (ARGs) in bacteria, and metagenomics has the potential to bypass some of the limitations of single isolate characterization by allowing simultaneous analysis of the agri-food product microbiome and associated resistome. However, metagenomics may still be hindered by methodological biases, presence of eukaryotic DNA, and difficulties in detecting low abundance targets within an attainable sequence coverage. The goal of this study was to assess whether limits of detection of ARGs in agri-food metagenomes were influenced by sample type and bioinformatic approaches.

RESULTS

We simulated metagenomes containing different proportions of AMR pathogens and analysed them for taxonomic composition and ARGs using several common bioinformatic tools. Kraken2/Bracken estimates of species abundance were closest to expected values. However, analysis by both Kraken2/Bracken indicated presence of organisms not included in the synthetic metagenomes. Metaphlan3/Metaphlan4 analysis of community composition was more specific but with lower sensitivity than the Kraken2/Bracken analysis. Accurate detection of ARGs dropped drastically below 5X isolate genome coverage. However, it was sometimes possible to detect ARGs and closely related alleles at lower coverage levels if using a lower ARG-target coverage cutoff (< 80%). While KMA and CARD-RGI only predicted presence of expected ARG-targets or closely related gene-alleles, SRST2 (which allows read to map to multiple targets) falsely reported presence of distantly related ARGs at all isolate genome coverage levels. The presence of background microbiota in metagenomes influenced the accuracy of ARG detection by KMA, resulting in mcr-1 detection at 0.1X isolate coverage in the lettuce but not in the beef metagenome.

CONCLUSIONS

This study demonstrates accurate detection of ARGs in synthetic metagenomes using various bioinformatic methods, provided that reads from the ARG-encoding organism exceed approximately 5X isolate coverage (i.e. 0.4% of a 40 million read metagenome). While lowering thresholds for target gene detection improved sensitivity, this led to the identification of alternative ARG-alleles, potentially confounding the identification of critical ARGs in the resistome. Further advancements in sequencing technologies providing increased coverage depth or extended read lengths may improve ARG detection in agri-food metagenomic samples, enabling use of this approach for tracking clinically important ARGs in agri-food samples.

Commercial farmed swine harbour a variety of pathogenic bacteria and antimicrobial resistance genes

Introduction. The northern region of Thailand serves as a crucial area for swine production, contributing to the Thai community food supply. Previous studies have highlighted the presence of foodborne bacterial pathogens originating from swine farms in this region, posing a threat to both human and animal health.Gap statement. Multiple swine bacterial pathogens have been studied at a species level, but the distribution and co-occurrence of bacterial pathogens in agricultural swine has not been well established.Aim. Our study employed the intestinal scraping technique to directly examine the bacterial micro-organisms interacting with the swine host.Methodology. We used shotgun metagenomic sequencing to analyse the bacterial pathogens inhabiting the caecal microbiome of swine from five commercial farms in northern Thailand.Results. A variety of pathogenic and opportunistic bacteria were identified, including Escherichia coli, Clostridium botulinum, Staphylococcus aureus and the Corynebacterium genus. From a One Health perspective, these species are important foodborne and opportunistic pathogens in both humans and agricultural animals, making swine a critical pathogen reservoir that can cause illness in humans, especially farm workers. Additionally, the swine caecal microbiome contains commensal bacteria such as Bifidobacterium, Lactobacillus and Faecalibacterium, which are associated with normal physiology and feed utilization in healthy swine. Antimicrobial resistance genes were also detected in all samples, specifically conferring resistance to tetracycline and aminoglycosides, which have historically been used extensively in swine farming.Conclusion. The findings further support the need for improved sanitation standards in swine farms, and additional monitoring of agricultural animals and farm workers to reduce contamination and improved produce safety for human consumption.

Comparative resistome, mobilome, and microbial composition of retail chicken originated from conventional, organic, and antibiotic-free production systems

The aim of this study was to investigate the microbial composition, and the profiles of antimicrobial resistance genes (ARGs, resistome) and mobile genetic elements (mobilome) of retail chicken carcasses originated from conventional intensive production systems (CO), certified antimicrobial-free intensive production systems (AF), and certified organic production systems with restricted antimicrobial use (OR). DNA samples were collected from 72 chicken carcasses according to a cross-sectional study design. Shot-gun metagenomics was performed by means of Illumina high throughput DNA sequencing followed by downstream bioinformatic analyses. Gammaproteobacteria was the most abundant bacterial class in all groups. Although CO, AF, and OR did not differ in terms of alpha- and beta-microbial diversity, the abundance of some taxa differed significantly across the groups, including spoilage-associated organisms such as Pseudomonas and Acinetobacter. The co-resistome comprised 29 ARGs shared by CO, AF and OR, including genes conferring resistance to beta-lactams (blaACT-8, 10, 13, 29; blaOXA-212;blaOXA-275 and ompA), aminoglycosides (aph(3')-IIIa, VI, VIa and spd), tetracyclines (tet KL (W/N/W and M), lincosamides (inu A,C) and fosfomycin (fosA). ARGs were significantly less abundant (P < 0.05) in chicken carcasses from AF and OR compared with CO. Regarding mobile genetic elements (MGEs), transposases accounted for 97.2% of the mapped genes. A higher abundance (P = 0.037) of MGEs was found in CO compared to OR. There were no significant differences in ARGs or MGEs diversity among groups according to the Simpson´s index. In summary, retail frozen chicken carcasses from AF and OR systems show similar ARGs, MGEs and microbiota profiles compared with CO, even though the abundance of ARGs and MGEs was higher in chicken carcasses from CO, probably due to a higher selective pressure.

Current Uses and Future Perspectives of Genomic Technologies in Clinical Microbiology

Recent advancements in sequencing technology and data analytics have led to a transformative era in pathogen detection and typing. These developments not only expedite the process, but also render it more cost-effective. Genomic analyses of infectious diseases are swiftly becoming the standard for pathogen analysis and control. Additionally, national surveillance systems can derive substantial benefits from genomic data, as they offer profound insights into pathogen epidemiology and the emergence of antimicrobial-resistant strains. Antimicrobial resistance (AMR) is a pressing global public health issue. While clinical laboratories have traditionally relied on culture-based antimicrobial susceptibility testing, the integration of genomic data into AMR analysis holds immense promise. Genomic-based AMR data can furnish swift, consistent, and highly accurate predictions of resistance phenotypes for specific strains or populations, all while contributing invaluable insights for surveillance. Moreover, genome sequencing assumes a pivotal role in the investigation of hospital outbreaks. It aids in the identification of infection sources, unveils genetic connections among isolates, and informs strategies for infection control. The One Health initiative, with its focus on the intricate interconnectedness of humans, animals, and the environment, seeks to develop comprehensive approaches for disease surveillance, control, and prevention. When integrated with epidemiological data from surveillance systems, genomic data can forecast the expansion of bacterial populations and species transmissions. Consequently, this provides profound insights into the evolution and genetic relationships of AMR in pathogens, hosts, and the environment.

Host specific adaptations of Ligilactobacillus aviarius to poultry

The genus Ligilactobacillus encompasses species adapted to vertebrate hosts and fermented food. Their genomes encode adaptations to the host lifestyle. Reports of gut microbiota from chicken and turkey gastrointestinal tract have shown a high persistence of Ligilactobacillus aviarius along the digestive system compared to other species found in the same host. However, its adaptations to poultry as a host has not yet been described. In this work, the pan-genome of Ligilactobacillus aviarius was explored to describe the functional adaptability to the gastrointestinal environment. The core genome is composed of 1179 gene clusters that are present at least in one copy that codifies to structural, ribosomal and biogenesis proteins. The rest of the identified regions were classified into three different functional clusters of orthologous groups (clusters) that codify carbohydrate metabolism, envelope biogenesis, viral defence mechanisms, and mobilome inclusions. The pan-genome of Ligilactobacillus aviarius is a closed pan-genome, frequently found in poultry and highly prevalent across chicken faecal samples. The genome of L. aviarius codifies different clusters of glycoside hydrolases and glycosyltransferases that mediate interactions with the host cells. Accessory features, such as antiviral mechanisms and prophage inclusions, variate amongst strains from different GIT sections. This information provides hints about the interaction of this species with viral particles and other bacterial species. This work highlights functional adaptability traits present in L. aviarius that make it a dominant key member of the poultry gut microbiota and enlightens the convergent ecological relation of this species to the poultry gut environment.

Extended Spectrum β-Lactamase-Producing Enterobacterales of Shrimp and Salmon Available for Purchase by Consumers in Canada-A Risk Profile Using the Codex Framework

The extended-spectrum β-lactamase (ESBL)-producing Enterobacterales (ESBL-EB) encompass several important human pathogens and are found on the World Health Organization (WHO) priority pathogens list of antibiotic-resistant bacteria. They are a group of organisms which demonstrate resistance to third-generation cephalosporins (3GC) and their presence has been documented worldwide, including in aquaculture and the aquatic environment. This risk profile was developed following the Codex Guidelines for Risk Analysis of Foodborne Antimicrobial Resistance with the objectives of describing the current state of knowledge of ESBL-EB in relation to retail shrimp and salmon available to consumers in Canada, the primary aquacultured species consumed in Canada. The risk profile found that Enterobacterales and ESBL-EB have been found in multiple aquatic environments, as well as multiple host species and production levels. Although the information available did not permit the conclusion as to whether there is a human health risk related to ESBLs in Enterobacterales in salmon and shrimp available for consumption by Canadians, ESBL-EB in imported seafood available at the retail level in Canada have been found. Surveillance activities to detect ESBL-EB in seafood are needed; salmon and shrimp could be used in initial surveillance activities, representing domestic and imported products.

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.

Characteristics of aerosols from swine farms: A review of the past two-decade progress

With the rapid development of large-scale and intensive swine production, the emission of aerosols from swine farms has become a growing concern, attracting extensive attention. While aerosols are found in various environments, those from swine farms are distinguished from human habitats, such as residential, suburban, and urban areas. In order to gain a comprehensive understanding of aerosols from swine farms, this paper reviewed relevant studies conducted between 2000 and 2022. The main components, concentrations, and size distribution of the aerosols were systematically reviewed. The differences between aerosols from swine farms and human living and working environments were compared. Finally, the sources, influencing factors, and reduction technologies for aerosols from swine farms were thoroughly elucidated. The results demonstrated that the concentrations of aerosols inside swine farms varied considerably, and most exceeded safety thresholds. However, further exploration is needed to fully understand the difference in airborne microorganism community structure and particles with small sizes (<1 μm) between swine farms and human living and working environments. More airborne bacterial and viruses were adhered to large particles in swine houses, while the proportion of airborne fungi in the respirable fraction was similar to that of human living and working environments. In addition, swine farms have a higher abundance and diversity of potential pathogens, airborne resistant microorganisms and resistant genes compared to the human living and working environments. The aerosols of swine farms mainly originated from sources such as manure, feed, swine hair and skin, secondary production, and waste treatment. According to the source analysis and factors influencing aerosols in swine farms, various technologies could be employed to mitigate aerosol emissions, and some end-of-pipe technologies need to be further improved before they are widely applied. Swine farms are advised not to increase aerosol concentration in human living and working environments, in order to decrease the impact of aerosols from swine farms on human health and restrain the spread of airborne potential pathogens. This review provides critical insights into aerosols of swine farms, offering guidance for taking appropriate measures to enhance air quality inside and surrounding swine farms.

Differences in gut metagenomes between dairy workers and community controls: a cross-sectional study

Background

As a nexus of routine antibiotic use and zoonotic pathogen presence, the livestock farming environment is a potential hotspot for the emergence of zoonotic diseases and antibiotic resistant bacteria. Livestock can further facilitate disease transmission by serving as intermediary hosts for pathogens as they undergo evolution prior to a spillover event. In light of this, we are interested in characterizing the microbiome and resistome of dairy workers, whose exposure to the livestock farming environment places them at risk for facilitating community transmission of antibiotic resistant genes and emerging zoonotic diseases.

Results

Using shotgun sequencing, we investigated differences in the taxonomy, diversity and gene presence of the human gut microbiome of 10 dairy farm workers and 6 community controls, supplementing these samples with additional publicly available gut metagenomes. We observed greater abundance of tetracycline resistance genes and prevalence of cephamycin resistance genes in dairy workers' metagenomes, and lower average gene diversity. We also found evidence of commensal organism association with plasmid-mediated tetracycline resistance genes in both dairy workers and community controls (including Faecalibacterium prausnitzii, Ligilactobacillus animalis, and Simiaoa sunii). However, we did not find significant differences in the prevalence of resistance genes or virulence factors overall, nor differences in the taxonomic composition of dairy worker and community control metagenomes.

Conclusions

This study presents the first metagenomics analysis of United States dairy workers, providing insights into potential risks of exposure to antibiotics and pathogens in animal farming environments. Previous metagenomic studies of livestock workers in China and Europe have reported increased abundance and carriage of antibiotic resistance genes in livestock workers. While our investigation found no strong evidence for differences in the abundance or carriage of antibiotic resistance genes and virulence factors between dairy worker and community control gut metagenomes, we did observe patterns in the abundance of tetracycline resistance genes and the prevalence of cephamycin resistance genes that is consistent with previous work.

Antimicrobial resistance monitoring in the Danish swine production by phenotypic methods and metagenomics from 1999 to 2018

BackgroundIn Denmark, antimicrobial resistance (AMR) in pigs has been monitored since 1995 by phenotypic approaches using the same indicator bacteria. Emerging methodologies, such as metagenomics, may allow novel surveillance ways.AimThis study aimed to assess the relevance of indicator bacteria (Escherichia coli and Enterococcus faecalis) for AMR surveillance in pigs, and the utility of metagenomics.MethodsWe collated existing data on AMR and antimicrobial use (AMU) from the Danish surveillance programme and performed metagenomics sequencing on caecal samples that had been collected/stored through the programme during 1999-2004 and 2015-2018. We compared phenotypic and metagenomics results regarding AMR, and the correlation of both with AMU.ResultsVia the relative abundance of AMR genes, metagenomics allowed to rank these genes as well as the AMRs they contributed to, by their level of occurrence. Across the two study periods, resistance to aminoglycosides, macrolides, tetracycline, and beta-lactams appeared prominent, while resistance to fosfomycin and quinolones appeared low. In 2015-2018 sulfonamide resistance shifted from a low occurrence category to an intermediate one. Resistance to glycopeptides consistently decreased during the entire study period. Outcomes of both phenotypic and metagenomics approaches appeared to positively correlate with AMU. Metagenomics further allowed to identify multiple time-lagged correlations between AMU and AMR, the most evident being that increased macrolide use in sow/piglets or fatteners led to increased macrolide resistance with a lag of 3-6 months.ConclusionWe validated the long-term usefulness of indicator bacteria and showed that metagenomics is a promising approach for AMR surveillance.

Reservoirs of antimicrobial resistance in the context of One Health

The emergence and spread of antimicrobial resistance (AMR) and resistant bacteria, are a global public health challenge. Through horizontal gene transfer, potential pathogens can acquire antimicrobial resistance genes (ARGs) that can subsequently be spread between human, animal, and environmental reservoirs. To understand the dissemination of ARGs and linked microbial taxa, it is necessary to map the resistome within different microbial reservoirs. By integrating knowledge on ARGs in the different reservoirs, the One Health approach is crucial to our understanding of the complex mechanisms and epidemiology of AMR. Here, we highlight the latest insights into the emergence and spread of AMR from the One Health perspective, providing a baseline of understanding for future scientific investigations into this constantly growing global health threat.

Unravelling the reservoirs for colonisation of infants with Campylobacter spp. in rural Ethiopia: protocol for a longitudinal study during a global pandemic and political tensions

INTRODUCTION

Undernutrition is an underlying cause of mortality in children under five (CU5) years of age. Animal-source foods have been shown to decrease malnutrition in CU5. Livestock are important reservoirs for Campylobacter bacteria, which are recognised as risk factors for child malnutrition. Increasing livestock production may be beneficial for improving nutrition of children but these benefits may be negated by increased exposure to Campylobacter and research is needed to evaluate the complex pathways of Campylobacter exposure and infection applicable to low-income and middle-income countries. We aim to identify reservoirs of infection with Campylobacter spp. of infants in rural Eastern Ethiopia and evaluate interactions with child health (environmental enteric dysfunction and stunting) in the context of their sociodemographic environment.

METHODS AND ANALYSIS

This longitudinal study involves 115 infants who are followed from birth to 12 months of age and are selected randomly from 10 kebeles of Haramaya woreda, East Hararghe zone, Oromia region, Ethiopia. Questionnaire-based information is obtained on demographics, livelihoods, wealth, health, nutrition and women empowerment; animal ownership/management and diseases; and water, sanitation and hygiene. Faecal samples are collected from infants, mothers, siblings and livestock, drinking water and soil. These samples are analysed by a range of phenotypic and genotypic microbiological methods to characterise the genetic structure of the Campylobacter population in each of these reservoirs, which will support inference about the main sources of exposure for infants.

ETHICS AND DISSEMINATION

Ethical approval was obtained from the University of Florida Internal Review Board (IRB201903141), the Haramaya University Institutional Health Research Ethics Committee (COHMS/1010/3796/20) and the Ethiopia National Research Ethics Review Committee (SM/14.1/1059/20). Written informed consent is obtained from all participating households. Research findings will be disseminated to stakeholders through conferences and peer-reviewed journals and through the Feed the Future Innovation Lab for Livestock Systems.

A global phylogenomic and metabolic reconstruction of the large intestine bacterial community of domesticated cattle

BACKGROUND

The large intestine is a colonization site of beneficial microbes complementing the nutrition of cattle but also of zoonotic and animal pathogens. Here, we present the first global gene catalog of cattle fecal microbiomes, a proxy of the large intestine microbiomes, from 436 metagenomes from six countries.

RESULTS

Phylogenomics suggested that the reconstructed genomes and their close relatives form distinct branches and produced clustering patterns that were reminiscent of the metagenomics sample origin. Bacterial taxa had distinct metabolic profiles, and complete metabolic pathways were mainly linked to carbohydrates and amino acids metabolism. Dietary changes affected the community composition, diversity, and potential virulence. However, predicted enzymes, which were part of complete metabolic pathways, remained present, albeit encoded by different microbes.

CONCLUSIONS

Our findings provide a global insight into the phylogenetic relationships and the metabolic potential of a rich yet understudied bacterial community and suggest that it provides valuable services to the host. However, we tentatively infer that members of that community are not irreplaceable, because similar to previous findings, symbionts of complex bacterial communities of mammals are expendable if there are substitutes that can perform the same task. Video Abstract.

OUP accepted manuscript

The intestinal microbiota plays a crucial role in health and changes in its composition are linked with major global human diseases. Fully understanding what shapes the human intestinal microbiota composition and knowing ways of modulating the composition are critical for promotion of life-course health, combating diseases, and reducing global health disparities. We aim to provide a foundation for understanding what shapes the human intestinal microbiota on an individual and global scale, and how interventions could utilize this information to promote life-course health and reduce global health disparities. We briefly review experiences within the first 1,000 days of life and how long-term exposures to environmental elements or geographic specific cultures have lasting impacts on the intestinal microbiota. We also discuss major public health threats linked to the intestinal microbiota, including antimicrobial resistance and disappearing microbial diversity due to globalization. In order to promote global health, we argue that the interplay of the larger ecosystem with intestinal microbiota research should be utilized for future research and urge for global efforts to conserve microbial diversity.

OUP accepted manuscript

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.

FI: The Fecobiome Initiative

Animal husbandry has been key to the sustainability of human societies for millennia. Livestock animals, such as cattle, convert plants to protein biomass due to a compartmentalized gastrointestinal tract (GIT) and the complementary contributions of a diverse GIT microbiota, thereby providing humans with meat and dairy products. Research on cattle gut microbial symbionts has mainly focused on the rumen (which is the primary fermentation compartment) and there is a paucity of functional insight on the intestinal (distal end) microbiota, where most foodborne zoonotic bacteria reside. Here, we present the Fecobiome Initiative (or FI), an international effort that aims at facilitating collaboration on research projects related to the intestinal microbiota, disseminating research results, and increasing public availability of resources. By doing so, the FI can help mitigate foodborne and animal pathogens that threaten livestock and human health, reduce the emergence and spread of antimicrobial resistance in cattle and their proximate environment, and potentially improve the welfare and nutrition of animals. We invite all researchers interested in this type of research to join the FI through our website: www.fecobiome.com

The cathelicidin CATH-2 efficiently neutralizes LPS- and E. coli-induced activation of porcine bone marrow derived macrophages

Infectious diseases in pigs cause monetary loss to farmers and pose a zoonotic risk. Therefore, it is important to obtain more porcine specific immunological knowledge as a measure to protect against infectious diseases, for example by exploring immunomodulators that are usable as vaccine adjuvants. Cathelicidins are a class of host defence peptides (HDPs) able to directly kill microbes as well as exert a diverse range of effects on the immune system. The peptides have shown promise as immunomodulatory peptides in many applications, including vaccines. However, it is currently unknown what the precise effect of these peptides is on porcine immune cells and whether peptides of other species might also have a strong immunomodulatory effect on porcine macrophages. Mononuclear bone marrow cells of pigs, aged 5-6 months, were cultured into M1 or M2 macrophages and stimulated with LPS or whole bacteria in the presence of host defence peptides (HDPs). CATH-2 and LL-37 strongly inhibited LPS-induced activation of M1 macrophages, the inhibition of LPS-induced activation of M2 macrophages by HDPs was milder, showing that the peptides have selective effects on different cell types. Upon stimulation with whole bacteria, only CATH-2 could effectively inhibit macrophage activation, showing the potent anti-inflammatory potential of this peptide. These results show that porcine peptides are not necessarily the most active in a porcine system, and that CATH-2 is effective in a porcine system as an anti-inflammatory immune modulator, which can be used, for example, in inactivated pathogen vaccines.

Risk Factors for Antimicrobial Resistance in Turkey Farms: A Cross-Sectional Study in Three European Countries

Food-producing animals are an important reservoir and potential source of transmission of antimicrobial resistance (AMR) to humans. However, research on AMR in turkey farms is limited. This study aimed to identify risk factors for AMR in turkey farms in three European countries (Germany, France, and Spain). Between 2014 and 2016, faecal samples, antimicrobial usage (AMU), and biosecurity information were collected from 60 farms. The level of AMR in faecal samples was quantified in three ways: By measuring the abundance of AMR genes through (i) shotgun metagenomics sequencing (n = 60), (ii) quantitative real-time polymerase chain reaction (qPCR) targeting ermB, tetW, sul2, and aph3'-III; (n = 304), and (iii) by identifying the phenotypic prevalence of AMR in Escherichia coli isolates by minimum inhibitory concentrations (MIC) (n = 600). The association between AMU or biosecurity and AMR was explored. Significant positive associations were detected between AMU and both genotypic and phenotypic AMR for specific antimicrobial classes. Beta-lactam and colistin resistance (metagenomics sequencing); ampicillin and ciprofloxacin resistance (MIC) were associated with AMU. However, no robust AMU-AMR association was detected by analyzing qPCR targets. In addition, no evidence was found that lower biosecurity increases AMR abundance. Using multiple complementary AMR detection methods added insights into AMU-AMR associations at turkey farms.