MEGARes: an antimicrobial resistance database for high throughput sequencing

Antimicrobial resistance has become an imminent concern for public health. As methods for detection and characterization of antimicrobial resistance move from targeted culture and polymerase chain reaction to high throughput metagenomics, appropriate resources for the analysis of large-scale data are required. Currently, antimicrobial resistance databases are tailored to smaller-scale, functional profiling of genes using highly descriptive annotations. Such characteristics do not facilitate the analysis of large-scale, ecological sequence datasets such as those produced with the use of metagenomics for surveillance. In order to overcome these limitations, we present MEGARes (https://megares.meglab.org), a hand-curated antimicrobial resistance database and annotation structure that provides a foundation for the development of high throughput acyclical classifiers and hierarchical statistical analysis of big data. MEGARes can be browsed as a stand-alone resource through the website or can be easily integrated into sequence analysis pipelines through download. Also via the website, we provide documentation for AmrPlusPlus, a user-friendly Galaxy pipeline for the analysis of high throughput sequencing data that is pre-packaged for use with the MEGARes database.

MEGARes 2.0: a database for classification of antimicrobial drug, biocide and metal resistance determinants in metagenomic sequence data

Antimicrobial resistance (AMR) is a threat to global public health and the identification of genetic determinants of AMR is a critical component to epidemiological investigations. High-throughput sequencing (HTS) provides opportunities for investigation of AMR across all microbial genomes in a sample (i.e. the metagenome). Previously, we presented MEGARes, a hand-curated AMR database and annotation structure developed to facilitate the analysis of AMR within metagenomic samples (i.e. the resistome). Along with MEGARes, we released AmrPlusPlus, a bioinformatics pipeline that interfaces with MEGARes to identify and quantify AMR gene accessions contained within a metagenomic sequence dataset. Here, we present MEGARes 2.0 (https://megares.meglab.org), which incorporates previously published resistance sequences for antimicrobial drugs, while also expanding to include published sequences for metal and biocide resistance determinants. In MEGARes 2.0, the nodes of the acyclic hierarchical ontology include four antimicrobial compound types, 57 classes, 220 mechanisms of resistance, and 1,345 gene groups that classify the 7,868 accessions. In addition, we present an updated version of AmrPlusPlus (AMR ++ version 2.0), which improves accuracy of classifications, as well as expanding scalability and usability.

Use of Metagenomic Shotgun Sequencing Technology To Detect Foodborne Pathogens within the Microbiome of the Beef Production Chain

Foodborne illnesses associated with pathogenic bacteria are a global public health and economic challenge. The diversity of microorganisms (pathogenic and nonpathogenic) that exists within the food and meat industries complicates efforts to understand pathogen ecology. Further, little is known about the interaction of pathogens within the microbiome throughout the meat production chain. Here, a metagenomic approach and shotgun sequencing technology were used as tools to detect pathogenic bacteria in environmental samples collected from the same groups of cattle at different longitudinal processing steps of the beef production chain: cattle entry to feedlot, exit from feedlot, cattle transport trucks, abattoir holding pens, and the end of the fabrication system. The log read counts classified as pathogens per million reads for Salmonella enterica,Listeria monocytogenes,Escherichia coli,Staphylococcus aureus, Clostridium spp. (C. botulinum and C. perfringens), and Campylobacter spp. (C. jejuni,C. coli, and C. fetus) decreased over subsequential processing steps. Furthermore, the normalized read counts for S. enterica,E. coli, and C. botulinumwere greater in the final product than at the feedlots, indicating that the proportion of these bacteria increased (the effect on absolute numbers was unknown) within the remaining microbiome. From an ecological perspective, data indicated that shotgun metagenomics can be used to evaluate not only the microbiome but also shifts in pathogen populations during beef production. Nonetheless, there were several challenges in this analysis approach, one of the main ones being the identification of the specific pathogen from which the sequence reads originated, which makes this approach impractical for use in pathogen identification for regulatory and confirmation purposes.

MEGARes and AMR++, v3.0: an updated comprehensive database of antimicrobial resistance determinants and an improved software pipeline for classification using high-throughput sequencing

Antimicrobial resistance (AMR) is considered a critical threat to public health, and genomic/metagenomic investigations featuring high-throughput analysis of sequence data are increasingly common and important. We previously introduced MEGARes, a comprehensive AMR database with an acyclic hierarchical annotation structure that facilitates high-throughput computational analysis, as well as AMR++, a customized bioinformatic pipeline specifically designed to use MEGARes in high-throughput analysis for characterizing AMR genes (ARGs) in metagenomic sequence data. Here, we present MEGARes v3.0, a comprehensive database of published ARG sequences for antimicrobial drugs, biocides, and metals, and AMR++ v3.0, an update to our customized bioinformatic pipeline for high-throughput analysis of metagenomic data (available at MEGLab.org). Database annotations have been expanded to include information regarding specific genomic locations for single-nucleotide polymorphisms (SNPs) and insertions and/or deletions (indels) when required by specific ARGs for resistance expression, and the updated AMR++ pipeline uses this information to check for presence of resistance-conferring genetic variants in metagenomic sequenced reads. This new information encompasses 337 ARGs, whose resistance-conferring variants could not previously be confirmed in such a manner. In MEGARes 3.0, the nodes of the acyclic hierarchical ontology include 4 antimicrobial compound types, 59 resistance classes, 233 mechanisms and 1448 gene groups that classify the 8733 accessions.

Enrichment allows identification of diverse, rare elements in metagenomic resistome-virulome sequencing

BACKGROUND

Shotgun metagenomic sequencing is increasingly utilized as a tool to evaluate ecological-level dynamics of antimicrobial resistance and virulence, in conjunction with microbiome analysis. Interest in use of this method for environmental surveillance of antimicrobial resistance and pathogenic microorganisms is also increasing. In published metagenomic datasets, the total of all resistance- and virulence-related sequences accounts for < 1% of all sequenced DNA, leading to limitations in detection of low-abundance resistome-virulome elements. This study describes the extent and composition of the low-abundance portion of the resistome-virulome, using a bait-capture and enrichment system that incorporates unique molecular indices to count DNA molecules and correct for enrichment bias.

RESULTS

The use of the bait-capture and enrichment system significantly increased on-target sequencing of the resistome-virulome, enabling detection of an additional 1441 gene accessions and revealing a low-abundance portion of the resistome-virulome that was more diverse and compositionally different than that detected by more traditional metagenomic assays. The low-abundance portion of the resistome-virulome also contained resistance genes with public health importance, such as extended-spectrum betalactamases, that were not detected using traditional shotgun metagenomic sequencing. In addition, the use of the bait-capture and enrichment system enabled identification of rare resistance gene haplotypes that were used to discriminate between sample origins.

CONCLUSIONS

These results demonstrate that the rare resistome-virulome contains valuable and unique information that can be utilized for both surveillance and population genetic investigations of resistance. Access to the rare resistome-virulome using the bait-capture and enrichment system validated in this study can greatly advance our understanding of microbiome-resistome dynamics.

Characterization of the Microbial Resistome in Conventional and "Raised Without Antibiotics" Beef and Dairy Production Systems

Metagenomic investigations have the potential to provide unprecedented insights into microbial ecologies, such as those relating to antimicrobial resistance (AMR). We characterized the microbial resistome in livestock operations raising cattle conventionally (CONV) or without antibiotic exposures (RWA) using shotgun metagenomics. Samples of feces, wastewater from catchment basins, and soil where wastewater was applied were collected from CONV and RWA feedlot and dairy farms. After DNA extraction and sequencing, shotgun metagenomic reads were aligned to reference databases for identification of bacteria (Kraken) and antibiotic resistance genes (ARGs) accessions (MEGARes). Differences in microbial resistomes were found across farms with different production practices (CONV vs. RWA), types of cattle (beef vs. dairy), and types of sample (feces vs. wastewater vs. soil). Feces had the greatest number of ARGs per sample (mean = 118 and 79 in CONV and RWA, respectively), with tetracycline efflux pumps, macrolide phosphotransferases, and aminoglycoside nucleotidyltransferases mechanisms of resistance more abundant in CONV than in RWA feces. Tetracycline and macrolide–lincosamide–streptogramin classes of resistance were more abundant in feedlot cattle than in dairy cow feces, whereas the β-lactam class was more abundant in dairy cow feces. Lack of congruence between ARGs and microbial communities (procrustes analysis) suggested that other factors (e.g., location of farms, cattle source, management practices, diet, horizontal ARGs transfer, and co-selection of resistance), in addition to antimicrobial use, could have impacted resistome profiles. For that reason, we could not establish a cause–effect relationship between antimicrobial use and AMR, although ARGs in feces and effluents were associated with drug classes used to treat animals according to farms’ records (tetracyclines and macrolides in feedlots, β-lactams in dairies), whereas ARGs in soil were dominated by multidrug resistance. Characterization of the “resistance potential” of animal-derived and environmental samples is the first step toward incorporating metagenomic approaches into AMR surveillance in agricultural systems. Further research is needed to assess the public-health risk associated with different microbial resistomes.

Investigating Effects of Tulathromycin Metaphylaxis on the Fecal Resistome and Microbiome of Commercial Feedlot Cattle Early in the Feeding Period

The objective was to examine effects of treating commercial beef feedlot cattle with therapeutic doses of tulathromycin, a macrolide antimicrobial drug, on changes in the fecal resistome and microbiome using shotgun metagenomic sequencing. Two pens of cattle were used, with all cattle in one pen receiving metaphylaxis treatment (800 mg subcutaneous tulathromycin) at arrival to the feedlot, and all cattle in the other pen remaining unexposed to parenteral antibiotics throughout the study period. Fecal samples were collected from 15 selected cattle in each group just prior to treatment (Day 1), and again 11 days later (Day 11). Shotgun sequencing was performed on isolated metagenomic DNA, and reads were aligned to a resistance and a taxonomic database to identify alignments to antimicrobial resistance (AMR) gene accessions and microbiome content. Overall, we identified AMR genes accessions encompassing 9 classes of AMR drugs and encoding 24 unique AMR mechanisms. Statistical analysis was used to identify differences in the resistome and microbiome between the untreated and treated groups at both timepoints, as well as over time. Based on composition and ordination analyses, the resistome and microbiome were not significantly different between the two groups on Day 1 or on Day 11. However, both the resistome and microbiome changed significantly between these two sampling dates. These results indicate that the transition into the feedlot-and associated changes in diet, geography, conspecific exposure, and environment-may exert a greater influence over the fecal resistome and microbiome of feedlot cattle than common metaphylactic antimicrobial drug treatment.

Large effects of consumer offense on ecosystem structure and function

Study of the role of within-species adaptation in ecological dynamics has focused largely on prey adaptations that reduce consumption risk (prey defense). Few, if any, studies have examined how consumer adaptations to overcome prey defenses (consumer offense) affect ecosystem structure and function. We manipulated two sets of genotypes of a planktonic herbivore (Daphnia pulicaria) in a highly productive ecosystem with abundant toxic prey (cyanobacteria). The two sets of consumer genotypes varied widely in their tolerance of toxic cyanobacteria in the diet (i.e., sensitive vs. tolerant). We found a large effect of tolerant D. pulicaria on phytoplankton biomass and gross primary productivity but no effect of sensitive genotypes, this result stemming from genotype-specific differences in population growth in the presence of toxic prey. The former effect was as large as effects seen in previous Daphnia manipulations at similar productivity levels. Thus, we demonstrated that the effect of consumer genotypes with contrasting offensive adaptations was as large as the effect of consumer presence/absence.

Effects of a Saccharomyces cerevisiae fermentation product on liver abscesses, fecal microbiome, and resistome in feedlot cattle raised without antibiotics

Liver abscesses in feedlot cattle form secondary to high concentrate feeds and rumen acidosis. Antimicrobial drugs are commonly included in cattle feed for prevention of liver abscesses, but concerns regarding antimicrobial resistance have increased the need for alternative treatments. A block randomized clinical trial was conducted to evaluate the effects of a Saccharomyces cerevisiae fermentation product (SCFP) on liver abscesses, fecal microbiomes, and resistomes in cattle raised without antibiotics in a Colorado feedlot. At enrollment, steers (n = 4,689) were sorted, by weight and source, into 2 pens comprising a block (n = 14 blocks, 28 pens); pens were randomly allocated to either the control group or the treatment group, where the diet was supplemented with SCFP. Prior to harvest, composited feces were collected for characterization of the microbiome and resistome using 16S rRNA gene and shotgun sequencing. At harvest, liver abscess severity was quantified for individual cattle. There were no statistical differences detected by treatment group in animal health, liver abscess prevalence or severity. Organisms classified to phylum, Elusimicrobia were more abundant in the feces of treated cattle, however, there were no differences in the resistome by treatment group. Both microbiome and resistome varied significantly among enrollment blocks.

Investigation of tylosin in feed of feedlot cattle and effects on liver abscess prevalence, and fecal and soil microbiomes and resistomes1

Liver abscesses in feedlot cattle are detrimental to animal performance and economic return. Tylosin, a macrolide antibiotic, is used to reduce prevalence of liver abscesses, though there is variable efficacy among different groups of cattle. There is an increased importance in better understanding the etiology and pathogenesis of this condition because of growing concern over antibiotic resistance and increased scrutiny regarding use of antibiotics in food animal production. The objective of this study was to compare the microbiomes and antimicrobial resistance genes (resistomes) of feces of feedlot cattle administered or not administered tylosin and in their pen soil in 3 geographical regions with differing liver abscess prevalences. Cattle (total of 2,256) from 3 geographical regions were selected for inclusion based on dietary supplementation with tylosin (yes/no). Feces and pen soil samples were collected before harvest, and liver abscesses were identified at harvest. Shotgun and 16S rRNA amplicon sequencing were used to evaluate the soil and feces. Microbiome and resistome composition of feces (as compared by UniFrac distances and Euclidian distances, respectively) did not differ (P > 0.05) among tylosin or no tylosin-administered cattle. However, feedlot location was associated with differences (P ≤ 0.05) of resistomes and microbiomes. Using LASSO, a statistical model identified both fecal and soil microbial communities as predictive of liver abscess prevalence in pens. This model explained 75% of the variation in liver abscess prevalence, though a larger sample size would be needed to increase robustness of the model. These data suggest that tylosin exposure does not have a large impact on cattle resistomes or microbiomes, but instead, location of cattle production may be a stronger driver of both the resistome and microbiome composition of feces.

Antimicrobial Resistance in U.S. Retail Ground Beef with and without Label Claims Regarding Antibiotic Use

ABSTRACT

Antibiotics used during food animal production account for approximately 77% of U.S. antimicrobial consumption by mass. Ground beef products labeled as raised without antibiotics (RWA) are perceived to harbor lower levels of antimicrobial-resistant bacteria than conventional (CONV) products with no label claims regarding antimicrobial use. Retail ground beef samples were obtained from six U.S. cities. Samples with an RWA or U.S. Department of Agriculture Organic claim (n = 299) were assigned to the RWA production system. Samples lacking these claims (n = 300) were assigned to the CONV production system. Each sample was cultured for the detection of five antimicrobial-resistant bacteria. Genomic DNA was isolated from each sample, and a quantitative PCR assay was used to determine the abundance of 10 antimicrobial resistance (AMR) genes. Prevalence of tetracycline-resistant Escherichia coli (CONV, 46.3%; RWA, 34.4%; P < 0.01) and erythromycin-resistant Enterococcus (CONV, 48.0%; RWA, 37.5%; P = 0.01) was higher in CONV ground beef. Salmonella was detected in 1.2% of samples. The AMR gene blaCTX-M (CONV, 4.1 log-normalized abundance; RWA, 3.8 log-normalized abundance; P < 0.01) was more abundant in CONV ground beef. The AMR genes mecA (CONV, 4.4 log-normalized abundance; RWA, 4.9 log-normalized abundance; P = 0.05), tet(A) (CONV, 3.9 log-normalized abundance; RWA, 4.5 log-normalized abundance; P < 0.01), tet(B) (CONV, 3.9 log-normalized abundance; RWA, 4.5 log-normalized abundance; P < 0.01), and tet(M) (CONV, 5.4 log-normalized abundance; RWA, 5.8 log-normalized abundance; P < 0.01) were more abundant in RWA ground beef. Although these results suggest that antimicrobial use during U.S. cattle production does not increase human exposure to antimicrobial-resistant bacteria via ground beef, quantitative microbiological risk assessments are required for authoritative determination of the human health impacts of the use of antimicrobial agents during beef production.

HIGHLIGHTS

Metagenomic Characterization of the Microbiome and Resistome of Retail Ground Beef Products

Ground beef can be a reservoir for a variety of bacteria, including spoilage organisms, and pathogenic foodborne bacteria. These bacteria can exhibit antimicrobial resistance (AMR) which is a public health concern if resistance in pathogens leads to treatment failure in humans. Culture-dependent techniques are commonly used to study individual bacterial species, but these techniques are unable to describe the whole community of microbial species (microbiome) and the profile of AMR genes they carry (resistome), which is critical for getting a holistic perspective of AMR. The objective of this study was to characterize the microbiome and resistome of retail ground beef products labeled as coming from conventional or raised without antibiotics (RWA) production systems. Sixteen ground beef products were purchased from 6 retail grocery outlets in Fort Collins, CO, half of which were labeled as produced from cattle raised conventionally and half of products were from RWA production. Total DNA was extracted and isolated from each sample and subjected to 16S rRNA amplicon sequencing for microbiome characterization and target-enriched shotgun sequencing to characterize the resistome. Differences in the microbiome and resistome of RWA and conventional ground beef were analyzed using the R programming software. Our results suggest that the resistome and microbiome of retail ground beef products with RWA packaging labels do not differ from products that do not carry claims regarding antimicrobial drug exposures during cattle production. The resistome predominantly consisted of tetracycline resistance making up more than 90% of reads mapped to resistance gene accessions in our samples. Firmicutes and Proteobacteria predominated in the microbiome of all samples (69.6% and 29.0%, respectively), but Proteobacteria composed a higher proportion in ground beef from conventionally raised cattle. In addition, our results suggest that product management, such as packaging type, could exert a stronger influence on the microbiome than the resistome in consumer-ready products. Metagenomic analyses of ground beef is a promising tool to investigate community-wide shifts in retail ground beef. Importantly, however, results from metagenomic sequencing must be carefully considered in parallel with traditional methods to better characterize the risk of AMR in retail products.

A Cautionary Report for Pathogen Identification Using Shotgun Metagenomics; A Comparison to Aerobic Culture and Polymerase Chain Reaction for Salmonella enterica Identification

This study was conducted to compare aerobic culture, polymerase chain reaction (PCR), lateral flow immunoassay (LFI), and shotgun metagenomics for identification of Salmonella enterica in feces collected from feedlot cattle. Samples were analyzed in parallel using all four tests. Results from aerobic culture and PCR were 100% concordant and indicated low S. enterica prevalence (3/60 samples positive). Although low S. enterica prevalence restricted formal statistical comparisons, LFI and deep metagenomic sequencing results were discordant with these results. Specifically, metagenomic analysis using k-mer-based classification against the RefSeq database indicated that 11/60 of samples contained sequence reads that matched to the S. enterica genome and uniquely identified this species of bacteria within the sample. However, further examination revealed that plasmid sequences were often included with bacterial genomic sequence data submitted to NCBI, which can lead to incorrect taxonomic classification. To circumvent this classification problem, we separated all plasmid sequences included in bacterial RefSeq genomes and reassigned them to a unique taxon so that they would not be uniquely associated with specific bacterial species such as S. enterica. Using this revised database and taxonomic structure, we found that only 6/60 samples contained sequences specific for S. enterica, suggesting increased relative specificity. Reads identified as S. enterica in these six samples were further evaluated using BLAST and NCBI's nr/nt database, which identified that only 2/60 samples contained reads exclusive to S. enterica chromosomal genomes. These two samples were culture- and PCR-negative, suggesting that even deep metagenomic sequencing suffers from lower sensitivity and specificity in comparison to more traditional pathogen detection methods. Additionally, no sample reads were taxonomically classified as S. enterica with two other metagenomic tools, Metagenomic Intra-species Diversity Analysis System (MIDAS) and Metagenomic Phylogenetic Analysis 2 (MetaPhlAn2). This study re-affirmed that the traditional techniques of aerobic culture and PCR provide similar results for S. enterica identification in cattle feces. On the other hand, metagenomic results are highly influenced by the classification method and reference database employed. These results highlight the nuances of computational detection of species-level sequences within short-read metagenomic sequence data, and emphasize the need for cautious interpretation of such results.

Characterization and comparison of the microbiomes and resistomes of colostrum from selectively treated dry cows

Professionals in animal agriculture promote prudent use of antimicrobials to address public and animal health concerns, such as reduction of antimicrobial residues and antimicrobial resistance (AMR) in products. Few studies evaluate the effect of selective dry-cow therapy on preservation of the milk microbiome or the profile of AMR genes (the resistome) present at freshening. Our objectives were to characterize and compare the microbiomes and resistomes in the colostrum of cows with low somatic cell count that were treated or not treated with intramammary cephapirin benzathine at dry-off. From a larger parent study, cows on a New York dairy farm eligible for dry-off and with histories of somatic cell counts ≤200,000 cells/mL were enrolled to this study (n = 307). Cows were randomly assigned to receive an intramammary antimicrobial and external teat sealant (ABXTS) or sealant only (TS) at dry-off. Composite colostrum samples taken within 4 h of freshening, and quarter milk samples taken at 1 to 7 d in milk were subjected to aerobic culture. The DNA extraction was performed on colostrum from cows with culture-negative samples (ABXTS = 43; TS = 33). The DNA from cows of the same treatment group and parity were pooled (26 pools; ABXTS = 12; TS = 14) for 16S rRNA metagenomic sequencing. Separately, the resistome was captured using a custom RNA bait library for target-enriched sequencing. Sequencing reads were aligned to taxonomic and AMR databases to characterize the microbiome and resistome, respectively. The R statistical program was used to tabulate abundances and to analyze differences in diversity measures and in composition between treatment groups. In the microbiome, the most abundant phyla were Firmicutes (68%), Proteobacteria (23%), Actinobacteria (4%), and Bacteroidetes (3%). Shannon and richness diversity means were 0.93 and 14.7 for ABXTS and 0.94 and 13.1 for TS, respectively. Using analysis of similarities (ANOSIM), overall microbiome composition was found to be similar between treatment groups at the phylum (ANOSIM R = 0.005), class (ANOSIM R = 0.04), and order (ANOSIM R = -0.04) levels. In the resistome, we identified AMR gene accessions associated with 14 unique mechanisms of resistance across 9 different drug classes in 14 samples (TS = 9, ABXTS = 5). The majority of reads aligned to gene accessions that confer resistance to aminoglycoside (TS = ABXTS each 35% abundance), tetracycline (TS = 22%, ABXTS = 54%), and β-lactam classes (TS = 15%, ABXTS = 12%). Shannon diversity means for AMR class and mechanism, respectively, were 0.66 and 0.69 for TS and 0.19 and 0.19 for ABXTS. Resistome richness diversity means for class and mechanism were 3.1 and 3.4 for TS and 1.4 and 1.4 for ABXTS. Finally, resistome composition was similar between groups at the class (ANOSIM R = -0.20) and mechanism levels (ANOSIM R = 0.01). Although no critical differences were found between treatment groups regarding their microbiome or resistome composition in this study, a larger sample size, deeper sequencing, and additional methodology is needed to identify more subtle differences, such as between lower-abundance features.

The impacts of viral infection and subsequent antimicrobials on the microbiome-resistome of growing pigs

BACKGROUND

Antimicrobials are used in food-producing animals for purposes of preventing, controlling, and/or treating infections. In swine, a major driver of antimicrobial use is porcine reproductive and respiratory syndrome (PRRS), which is caused by a virus that predisposes infected animals to secondary bacterial infections. Numerous antimicrobial protocols are used to treat PRRS, but we have little insight into how these treatment schemes impact antimicrobial resistance (AMR) dynamics within the fecal microbiome of commercial swine. The aim of this study was to determine whether different PRRS-relevant antimicrobial treatment protocols were associated with differences in the fecal microbiome and resistome of growing pigs. To accomplish this, we used a metagenomics approach to characterize and compare the longitudinal wean-to-market resistome and microbiome of pigs challenged with PRRS virus and then exposed to different antimicrobial treatments, and a group of control pigs not challenged with PRRS virus and having minimal antimicrobial exposure. Genomic DNA was extracted from pen-level composite fecal samples from each treatment group and subjected to metagenomic sequencing and microbiome-resistome bioinformatic and statistical analysis. Microbiome-resistome profiles were compared over time and between treatment groups.

RESULTS

Fecal microbiome and resistome compositions both changed significantly over time, with a dramatic and stereotypic shift between weaning and 9 days post-weaning (dpw). Antimicrobial resistance gene (ARG) richness and diversity were significantly higher at earlier time points, while microbiome richness and diversity were significantly lower. The post-weaning shift was characterized by transition from a Bacteroides-dominated enterotype to Lactobacillus- and Streptococcus-dominated enterotypes. Both the microbiome and resistome stabilized by 44 dpw, at which point the trajectory of microbiome-resistome maturation began to diverge slightly between the treatment groups, potentially due to physical clustering of the pigs. Challenge with PRRS virus seemed to correspond to the re-appearance of many very rare and low-abundance ARGs within the feces of challenged pigs. Despite very different antimicrobial exposures after challenge with PRRS virus, resistome composition remained largely similar between the treatment groups. Differences in ARG abundance between the groups were mostly driven by temporal changes in abundance that occurred prior to antimicrobial exposures, with the exception of ermG, which increased in the feces of treated pigs, and was significantly more abundant in the feces of these pigs compared to the pigs that did not receive post-PRRS antimicrobials.

CONCLUSIONS

The fecal microbiome-resistome of growing pigs exhibited a stereotypic trajectory driven largely by weaning and physiologic aging of the pigs. Events such as viral illness, antimicrobial exposures, and physical grouping of the pigs exerted significant yet relatively minor influence over this trajectory. Therefore, the AMR profile of market-age pigs is the culmination of the life history of the individual pigs and the populations to which they belong. Disease status alone may be a significant driver of AMR in market-age pigs, and understanding the interaction between disease processes and antimicrobial exposures on the swine microbiome-resistome is crucial to developing effective, robust, and reproducible interventions to control AMR. Video Abstract.

Characterization of the microbiota and resistome of bulk tank milk samples from Prince Edward Island dairy farms

Bulk tank milk (BTM) is regularly used for surveillance on dairy farms for disease conditions such as mastitis and Johne's disease. In this study, we used 16S rRNA sequencing and bait-capture enrichment to characterize the microbiota and resistome of BTM, and investigate potential differences between the cream or pellet fractions. A total of 12 BTM samples were taken from 12 Prince Edward Island dairy farms, in Atlantic Canada, in duplicates. The DNA was analyzed by high-throughput sequencing of the 16S rRNA gene and a suite of antimicrobial resistance (AMR) genes. Target-capture enrichment of AMR genes was conducted before shotgun sequencing. The bioinformatics pipelines QIIME 2 and AMR++ were used for microbiota and resistome analysis, respectively. Differences between microbiotae were evaluated qualitatively with nonmetric multidimensional scaling and quantitatively with permutational ANOVA of UniFrac distances. A total of 47 phyla were present across the BTM samples. Firmicutes, Bacteroidetes, Proteobacteria, and Actinobacteria were the most abundant phyla. At the genus level, Corynebacterium, Acinetobacter, Lactobacillus, and Turicibacter were the most abundant. There was no significant difference in the Faith's phylogenetic diversity between the cream and pellet fraction. Faith's phylogenetic diversity differed marginally by stall type. There were 10,217 hits across 80 unique AMR genes, with tetracycline resistance being the most common class.

Resistomes and microbiome of meat trimmings and colon content from culled cows raised in conventional and organic production systems

BACKGROUND

The potential to distribute bacteria resistant to antimicrobial drugs in the meat supply is a public health concern. Market cows make up a fifth of the U.S. beef produced but little is known about the entire population of bacteria (the microbiome) and entirety of all resistance genes (the resistome) that are found in this population. The objective of this study was to characterize and compare the resistomes and microbiome of beef, dairy, and organic dairy market cows at slaughter.

METHODS

Fifty-four (N = 54) composite samples of both colon content and meat trimmings rinsate samples were collected over six visits to two harvest facilities from cows raised in three different production systems: conventional beef, conventional dairy, and organic dairy (n = 3 samples per visit per production system). Metagenomic DNA obtained from samples were analyzed using target-enriched sequencing (resistome) and 16S rRNA gene sequencing (microbiome).

RESULTS

All colon content samples had at least one identifiable antimicrobial resistance gene (ARG), while 21 of the 54 meat trimmings samples harbored at least one identifiable ARGs. Tetracycline ARGs were the most abundant class in both colon content and carcass meat trimmings. The resistome found on carcass meat trimmings was not significantly different by production system (P = 0.84, R2 = 0.00) or harvest facility (P = 0.10, R2 = 0.09). However, the resistome of colon content differed (P = 0.01; R2 = 0.05) among production systems, but not among the harvest facilities (P = 0.41; R2 = 0.00). Amplicon sequencing revealed differences (P < 0.05) in microbial populations in both meat trimmings and colon content between harvest facilities but not production systems (P > 0.05).

CONCLUSIONS

These data provide a baseline characterization of an important segment of the beef industry and highlight the effect that the production system where cattle are raised and the harvest facilities where an animal is processed can impact associated microbiome and resistomes.

Genomic diversity of class I integrons from antimicrobial resistant strains of Salmonella Typhimurium isolated from livestock, poultry and humans

Introduction

Multidrug resistance (MDR) is a serious issue prevalent in various agriculture-related foodborne pathogens including Salmonella enterica (S. enterica) Typhimurium. Class I integrons have been detected in Salmonella spp. strains isolated from food producing animals and humans and likely play a critical role in transmitting antimicrobial resistance within and between livestock and human populations.

Objective

The main objective of our study was to characterize class I integron presence to identify possible integron diversity among and between antimicrobial resistant Salmonella Typhimurium isolates from various host species, including humans, cattle, swine, and poultry.

Methods

An association between integron presence with multidrug resistance was evaluated. One hundred and eighty-three S. Typhimurium isolates were tested for antimicrobial resistance (AMR). Class I integrons were detected and sequenced. Similarity of AMR patterns between host species was also studied within each integron type.

Results

One hundred seventy-four (95.1%) of 183 S.Typhimurium isolates were resistant to at least one antimicrobial and 82 (44.8%) were resistant to 5 or more antimicrobials. The majority of isolates resistant to at least one antimicrobial was from humans (45.9%), followed by swine (19.1%) and then bovine (16.9%) isolates; poultry showed the lowest number (13.1%) of resistant isolates. Our study has demonstrated high occurrence of class I integrons in S. Typhimurium across different host species. Only one integron size was detected in poultry isolates. There was a significant association between integron presence of any size and specific multidrug resistance pattern among the isolates from human, bovine and swine.

Conclusions

Our study has demonstrated a high occurrence of class I integrons of different sizes in Salmonella Typhimurium across various host species and their association with multidrug resistance. This demonstration indicates that multidrug resistant Salmonella Typhimurium is of significant public health occurrence and reflects on the importance of judicious use of antimicrobials among livestock and poultry.

Investigation of intramammary infections in primiparous cows during early lactation on organic dairy farms

Previous studies have shown that organically raised dairy cows have an increased prevalence of Staphylococcus aureus compared with conventionally raised dairy cows. However, little information exists about the dynamics of intramammary infection (IMI) in primiparous cows during early lactation on organic dairy farms. The objective of this study was to describe the IMI dynamics of primiparous cows on certified organic farms during early lactation. This longitudinal study enrolled 503 primiparous cows from 5 organic dairy farms from February 2019 to January 2020. Quarter-level milk samples were collected aseptically on a weekly basis during the first 5 wk of lactation. Samples were pooled by cow and time point into composite samples inside a sterilized laminar hood and submitted for microbiological culture. For each of the different microorganisms identified, we estimated the prevalence in each postpartum sample, period prevalence (PP), cumulative incidence, and persistence of IMI. Logistic regression models were used to investigate whether the prevalence of IMI differed by farm or sampling time points and whether IMI persistence differed between detected microorganisms. Our findings revealed a high prevalence of Staphylococcus aureus (PP = 18.9%), non-aureus staphylococci and closely related mammaliicoccal species (PP = 52.1%), and Streptococcus spp. and Streptococcus-like organisms (PP = 32.1%) within the study population. The prevalence of these microorganisms varied significantly between farms. Staphylococcus aureus and Staphylococcus chromogenes exhibited significantly higher IMI persistence compared with other detected bacterial taxa, confirming the divergent epidemiological behavior in terms of IMI chronicity across different microorganisms. This study improves our understanding of the epidemiology of mastitis-causing pathogens in organically raised primiparous cows, which can be used to tailor mastitis control plans for this unique yet growing subpopulation of dairy cows.

The value of preoperative mammograms in nononcologic breast surgery

It remains unclear whether preoperative mammograms are necessary in young patients having nononcologic breast surgery. Various authors have recommended mammography in all such cases, in conflict with guidelines from the American Cancer Society. We conducted a retrospective study to determine the utility of preoperative mammograms in young women. From 1989 through 1994, 208 patients under 35 years of age had elective breast surgery in our institution. Fifty-one (24.5%) had preoperative mammography. No malignancies were diagnosed. We believe mammograms are not routinely needed before elective breast surgery in patients under 35 years of age.

More than an anthropogenic phenomenon: Antimicrobial resistance in ungulates from natural and agricultural environments

Widely considered an anthropogenic phenomenon, antimicrobial resistance (AMR) is a naturally occurring mechanism that microorganisms use to gain competitive advantage. AMR represents a significant threat to public health and has generated criticism towards the overuse of antimicrobial drugs. Livestock have been proposed as important reservoirs for AMR accumulation. Here, we show that assemblages of AMR genes in cattle and ungulates from natural environments (Yellowstone and Rocky Mountain National Parks) are all dominated by genes conferring resistance to tetracyclines. However, cattle feces contained higher proportions of erm(A-X) genes conferring resistance to macrolide antibiotics. Medically important AMR genes differed between cattle and natural ungulates, but cumulatively were more predominant in natural soils. Our findings suggest that the commonly described predominance of tetracycline resistance in cattle feces is a natural phenomenon among multiple ungulate species and not solely a result of antimicrobial drug exposure. Yet, the virtual absence of macrolide resistance genes in natural ungulates suggests that macrolide usage in agriculture may enrich these genes in cattle. Our results show that antimicrobial use in agriculture may be promoting a potential reservoir for specific types of AMR (i.e., macrolide resistance) but that a significant proportion of the ungulate resistome appears to have natural origins.

Evaluating the effects of antimicrobial drug use on the ecology of antimicrobial resistance and microbial community structure in beef feedlot cattle

Introduction

Use of antimicrobial drugs (AMDs) in food producing animals has received increasing scrutiny because of concerns about antimicrobial resistance (AMR) that might affect consumers. Previously, investigations regarding AMR have focused largely on phenotypes of selected pathogens and indicator bacteria, such as Salmonella enterica or Escherichia coli. However, genes conferring AMR are known to be distributed and shared throughout microbial communities. The objectives of this study were to employ target-enriched metagenomic sequencing and 16S rRNA gene amplicon sequencing to investigate the effects of AMD use, in the context of other management and environmental factors, on the resistome and microbiome in beef feedlot cattle.

Methods

This study leveraged samples collected during a previous longitudinal study of cattle at beef feedlots in Canada. This included fecal samples collected from randomly selected individual cattle, as well as composite-fecal samples from randomly selected pens of cattle. All AMD use was recorded and characterized across different drug classes using animal defined daily dose (ADD) metrics.

Results

Overall, fecal resistome composition was dominated by genes conferring resistance to tetracycline and macrolide-lincosamide-streptogramin (MLS) drug classes. The diversity of bacterial phyla was greater early in the feeding period and decreased over time in the feedlot. This decrease in diversity occurred concurrently as the microbiome represented in different individuals and different pens shifted toward a similar composition dominated by Proteobacteria and Firmicutes. Some antimicrobial drug exposures in individuals and groups were associated with explaining a statistically significant proportion of the variance in the resistome, but the amount of variance explained by these important factors was very small (<0.6% variance each), and smaller than associations with other factors measured in this study such as time and feedlot ID. Time in the feedlot was associated with greater changes in the resistome for both individual animals and composite pen-floor samples, although the proportion of the variance associated with this factor was small (2.4% and 1.2%, respectively).

Discussion

Results of this study are consistent with other investigations showing that, compared to other factors, AMD exposures did not have strong effects on antimicrobial resistance or the fecal microbial ecology of beef cattle.

MEGARes 2.0: a database for classification of antimicrobial drug, biocide and metal resistance determinants in metagenomic sequence data

Antimicrobial resistance (AMR) is a threat to global public health and the identification of genetic determinants of AMR is a critical component to epidemiological investigations. High-throughput sequencing (HTS) provides opportunities for investigation of AMR across all microbial genomes in a sample (i.e. the metagenome). Previously, we presented MEGARes, a hand-curated AMR database and annotation structure developed to facilitate the analysis of AMR within metagenomic samples (i.e. the resistome). Along with MEGARes, we released AmrPlusPlus, a bioinformatics pipeline that interfaces with MEGARes to identify and quantify AMR gene accessions contained within a metagenomic sequence dataset. Here, we present MEGARes 2.0 (https://megares.meglab.org), which incorporates previously published resistance sequences for antimicrobial drugs, while also expanding to include published sequences for metal and biocide resistance determinants. In MEGARes 2.0, the nodes of the acyclic hierarchical ontology include four antimicrobial compound types, 57 classes, 220 mechanisms of resistance, and 1,345 gene groups that classify the 7,868 accessions. In addition, we present an updated version of AmrPlusPlus (AMR ++ version 2.0), which improves accuracy of classifications, as well as expanding scalability and usability.

The teat skin microbiota of organic primiparous dairy cows is dynamic during the transition period

BACKGROUND

The transition period is a critical developmental period for dairy cows, during which the udder undergoes numerous physiological changes that can impact future cow health and performance. The teat skin is an important anatomical feature of the dairy cow, as it is continuously exposed to the environment, and also represents an important barrier against microbes that could invade the teat canal and mammary gland. Yet little is known about the temporal dynamics of the teat skin microbiota during the transition period. Therefore, the main objective of this study was to describe the temporal composition of the teat skin microbiota during the transition period in primiparous dairy cows using 16S rRNA sequencing.

RESULTS

Teat skin swabs were collected throughout the transition period from 710 cows starting their first lactation on 5 certified organic dairy farms. Samples were collected bi-weekly beginning 8 weeks prepartum and then weekly for 4-5 weeks after calving. A total of 4827 teat skin swabs were collected and sequenced, and the resulting sequence data were analyzed by farm and time. Microbial richness, diversity and bacterial load changed dynamically as animals moved through late-stage gestation, parturition and lactation. However, the direction, timing and magnitude of these changes were unique to each farm. Principal component analysis revealed that the composition and structure of the teat skin microbiota also underwent a massive shift during the transition period, with significant differences between phases of the transition period, i.e., late-stage gestation, parturition and lactation. This trend was also observed when samples were categorized into community types using Dirichlet Multinomial Mixture models.

CONCLUSIONS

We observe that the teat skin microbiota comprises a diverse community of bacteria and archaea that experience large shifts in abundance and composition as cows move through the transition period. These shifts begin several weeks prior to calving and continue into the first few weeks postpartum, likely driven by a combination of changing environment, management and host physiology during the same period of time. The specific dynamics of these shifts seem to be fairly unique to each farm, which suggests that farm-level factors are important considerations for future work on the teat skin microbiota of transitioning first-lactation dairy cows.

Slaughtering processes impact microbial communities and antimicrobial resistance genes of pig carcasses

Several steps in the abattoir can influence the presence of microbes and associated resistance genes (ARGs) on the animal carcasses used for further meat processing. We investigated how these processes influence the resistome-microbiome of groups of pigs with different on-farm antimicrobial exposure status, from the moment they entered the abattoir until the end of carcass processing. Using a targeted enrichment metagenomic approach, we identified 672 unique ARGs conferring resistance to 43 distinct AMR classes from pooled skin (N = 42) and carcass swabs (N = 63) collected sequentially before, during, and after the slaughter process and food safety interventions. We observed significant variations in the resistome and microbial profiles of pigs before and after slaughter, as well as a significant decline in ARG counts, diversity, and microbial DNA load during slaughter and carcass processing, irrespective of prior antimicrobial treatments on the farm. These results suggest that existing interventions in the abattoir are effective in reducing not only the pathogen load but also the overall bacterial burden, including ARGs on pork carcasses. Concomitant with reductions in microbial and ARG counts, we observed an increase in the relative abundance of non-drug-specific ARGs, such as those conferring resistance to metals and biocides, and in particular mercury. Using a strict colocalization procedure, we found that most mercury ARGs were associated with genomes from the Pseudomonadaceae and Enterobacteriaceae families. Collectively, these findings demonstrate that slaughter and processing practices within the abattoir can shape the microbial and ARG profiles of pork carcasses during the transition from living muscle to meat.