Abstract
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.
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.
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.
Previous research on stabilization methods for microbiome investigations has largely focused on human fecal samples. There are a few studies using feces from other species, but no published studies ...investigating preservation of samples collected from cattle. Given that microbial taxa are differentially impacted during storage it is warranted to study impacts of preservation methods on microbial communities found in samples outside of human fecal samples. Here we tested methods of preserving bovine fecal respiratory specimens for up to 2 weeks at four temperatures (room temperature, 4°C, -20°C, and -80°C) by comparing microbial diversity and community composition to samples extracted immediately after collection. Importantly, fecal specimens preserved and analyzed were technical replicates, providing a look at the effects of preservation method in the absence of biological variation. We found that preservation with the OMNIgene®•GUT kit resulted in community structure most like that of fresh samples extracted immediately, even when stored at room temperature (~20°C). Samples that were flash-frozen without added preservation solution were the next most representative of original communities, while samples preserved with ethanol were the least representative. These results contradict previous reports that ethanol is effective in preserving fecal communities and suggest for studies investigating cattle either flash-freezing of samples without preservative or preservation with OMNIgene®•GUT will yield more representative microbial communities.
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.
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.
Prior data from our group showed that first-lactation cows under organic management in United States have a high prevalence of Staphylococcus aureus, Streptococcus spp., and Staphylococcus ...chromogenes intramammary infections (IMI) in early lactation. Nonetheless, the relationship between IMI, udder health, and milk production in organically reared primiparous cows remains elusive. The objectives of this observational study were to investigate the relationship between presence and persistence of IMI in the first 35 d in milk (DIM) and somatic cell count (SCC) and milk production during the first 6 mo of lactation on first-lactation organic dairy cows. The analysis included a total of 1,348 composite milk samples collected during the first 35 DIM that were submitted for milk culture and 1,674 Dairy Herd Improvement Association (DHIA) tests during the first 180 DIM from 333 heifers in 4 organic dairy farms, enrolled between February 2019 and January 2020. The association between IMI in the first 35 DIM and new high SCC (SCC > 200,000 cells/mL) and milk production during the first 6 mo of lactation was investigated using Cox proportional hazards regression and mixed linear regression, respectively. The association between IMI persistence (harboring the same microorganism as reported by the laboratory for 2 or more samples) in the first 35 DIM and number of DHIA tests with high SCC during the first 6 mo of lactation was modeled using negative binomial regression. The presence of IMI by Staph. aureus (hazard ratio HR 95% confidence interval {CI}: 3.35 2.64, 4.25) or Streptococcus spp. (HR 95% CI: 2.25 2.12, 2.39) during the first 35 DIM was associated with an increased risk of new high SCC during the first 6 mo of lactation. Milk production was reduced when Streptococcus spp. were identified in milk samples. However, there was no evidence of a difference in milk production in Staph. aureus IMI. Isolation of non-aureus staphylococci and mammaliicocci was related to a mild increase in the hazards of high SCC (HR 95% CI: 1.34 0.97, 1.85) and a decrease in milk production during one or more postpartum tests. Presence of gram-negative or Streptococcus-like organisms IMI was not associated with either high SCC or milk production. Presence of Bacillus IMI was associated with a lower hazard of new high SCC (HR 95% CI: 0.45 0.30, 0.68), and higher milk production during the first 180 d of lactation (overall estimate 95% CI: 1.7 kg/d 0.3, 3.0). The persistence of IMI in the first 35 DIM was associated with the number of tests with high SCC during the lactation for all microorganisms except for Staphylococcus chromogenes. Therefore, our results suggest that the persistence of IMI in the first 35 DIM could be an important factor to understand the association between IMI detected in early lactation and lactational SCC and milk production in organic dairy heifers. Our study described associations between IMI, udder health, and milk production in first-lactation organic dairy cows that are consistent with findings from conventional dairy farms.
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.
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.
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.
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.
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.
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.
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.
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