It has been proposed that livestock production effluents such as wastewater, airborne dust and manure increase the density of antimicrobial resistant bacteria and genes in the environment. The public health risk posed by this proposed outcome has been difficult to quantify using traditional microbiological approaches. We utilized shotgun metagenomics to provide a first description of the resistome of North American dairy and beef production effluents, and identify factors that significantly impact this resistome. We identified 34 mechanisms of antimicrobial drug resistance within 34 soil, manure and wastewater samples from feedlot, ranch and dairy operations. The majority of resistance-associated sequences found in all samples belonged to tetracycline resistance mechanisms. We found that the ranch samples contained significantly fewer resistance mechanisms than dairy and feedlot samples, and that the resistome of dairy operations differed significantly from that of feedlots. The resistome in soil, manure and wastewater differed, suggesting that management of these effluents should be tailored appropriately. By providing a baseline of the cattle production waste resistome, this study represents a solid foundation for future efforts to characterize and quantify the public health risk posed by livestock effluents.

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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. botulinum were 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.

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.

This study quantified relationships between USDA instrument marbling measurements and LM sensory attributes (tenderness, flavor, juiciness), and shear force. Heifer (n = 390) and steer (n = 328) carcasses (all A-maturity) were selected at 4 beef processing plants in Colorado, Kansas, Nebraska, and Texas to represent 7 marbling degrees: traces (TR), slight (SL), small (SM), modest (MT), moderate (MD), slightly abundant (SA), and moderately abundant (MA). Classification into marbling groups was based on marbling scores determined using USDA-approved VBG 2000 grading systems. Strip loin steaks were obtained from both sides of each carcass and aged for 14 d. One steak was used to obtain Warner-Bratzler shear force (WBSF) and slice shear force (SSF) measurements. The other steak was evaluated by a trained sensory panel for juiciness, tenderness, intensity of flavors characterized as meaty/brothy, buttery/beef fat, bloody/serumy, livery/organy, and grassy; and overall sensory experience (negative or positive). Instrument marbling score explained 45%, 40%, 32%, 71%, and 61% of the observed variation in panel ratings for juiciness, tenderness, meaty/brothy flavor intensity, buttery/beef fat flavor intensity, and overall sensory experience, respectively. Increased degree of marbling resulted in steaks having greater (P < 0.001) juiciness (MA > SA > MD > MT > SM > SL = TR), meaty/brothy flavor (MA = SA > MD = MT > SM > SL > TR), and buttery/beef fat flavor (MA > SA > MD > MT > SM > SL > TR). Steak tenderness also increased (P < 0.001) as marbling degree increased; however, tenderness differences among marbling degrees differed for steers (MA = SA > MD = MT > SM > SL = TR) and heifers (MA = SA > MD > MT > SM > SL > TR). Steaks produced by steers had lower (P < 0.05) WBSF and SSF values, and were rated as more tender by sensory panelists than steaks produced by heifers, but the effect of sex on panel tenderness was significant only among steaks with TR marbling. Results of this study showed that instrument-based classification of beef carcasses, according to differences in marbling, effectively identified subsequent differences in strip loin steak sensory performance. Nearly all (98 to 99%) steaks with MA or SA marbling, and most (between 80% and 90%) steaks with MD and MT marbling, received positive ratings for overall sensory experience. In comparison, 62% of SM steaks, 29% of SL steaks, and 15% of TR steaks received positive sensory experience ratings.