ABSTRACT
Ruminants are a critical human food source and have been implicated as a potentially important source of global methane emissions. Because of their unique digestive physiology, ruminants rely upon a symbiotic relationship with the complex and rich community of microorganism in the foregut to allow digestion of complex carbohydrates. This study used 16S rRNA gene sequencing to investigate the composition of microbial communities from three rumen micro-environments of cattle fed identical diets: (1) free fluid, (2) the fibrous pack, and (3) the mucosa. Community composition analysis revealed that while a phylogenetic core including the most abundant and most common ruminal taxa (members of Bacteroidetes and Firmicutes) existed across micro-environments, the abundances of these taxa differed significantly between fluid- and mucosa-associated communities, and specific lineages were discriminant of individual micro-environments. Members of Firmicutes, specifically Clostridiales, Lachnospiraceae, Mogibacteriaceae, Christenellaceae, and Erysipelotrichaceae were significantly more abundant in fluid communities, while members of Bacteroidetes, namely Muribaculaceae and Prevotellaceae were more abundant in mucosa-associated communities. Additionally, Methanobacteriaceae, a family of methanogenic Archaea, was more abundant in fluid-associated communities. A set of four more diverse lineages were discriminant of pack-associated communities that included Succinivibrionaceae, RFP12 (Verruco-5), Fibrobacteraceae, and Spirochaetaceae. Our findings indicate that different ecological niches within each micro-environment have resulted in significant differences in the diversity and community structure of microbial communities from rumen fluid, pack, and mucosa without the influence of diet that will help contextualize the influence of other environmental factors.
ABSTRACT
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.
ABSTRACT
Biofilm formation by foodborne pathogens is a serious threat to food safety and public health. Meat processing plants may harbor various microorganisms and occasional foodborne pathogens; thus, the environmental microbial community might impact pathogen survival via mixed biofilm formation. We collected floor drain samples from two beef plants with different E. coli O157:H7 prevalence history and investigated the effects of the environmental microorganisms on pathogen sanitizer tolerance. The results showed that biofilm forming ability and bacterial species composition varied considerably based on the plants and drain locations. E. coli O157:H7 cells obtained significantly higher sanitizer tolerance in mixed biofilms by samples from the plant with recurrent E. coli O157:H7 prevalence than those mixed with samples from the other plant. The mixed biofilm that best protected E. coli O157:H7 also had the highest species diversity. The percentages of the species were altered significantly after sanitization, suggesting that the community composition affects the role and tolerance level of each individual species. Therefore, the unique environmental microbial community, their ability to form biofilms on contact surfaces and the interspecies interactions all play roles in E. coli O157:H7 persistence by either enhancing or reducing pathogen survival within the biofilm community.
ABSTRACT
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 ß-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, ß-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.
ABSTRACT
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.