Background The pig gastrointestinal tract hosts a diverse microbiome, which can serve to select and maintain a reservoir of antimicrobial resistance genes (ARG). Studies suggest that the types and quantities of antimicrobial resistance (AMR) in fecal bacteria change as the animal host ages, yet the temporal dynamics of AMR within communities of bacteria in pigs during a full production cycle remains largely unstudied. Results A longitudinal study was performed to evaluate the dynamics of fecal microbiome and AMR in a cohort of pigs during a production cycle; from birth to market age. Our data showed that piglet fecal microbial communities assemble rapidly after birth and become more diverse with age. Individual piglet fecal microbiomes progressed along similar trajectories with age-specific community types/enterotypes and showed a clear shift from E. coli/Shigella-, Fusobacteria-, Bacteroides-dominant enterotypes to Prevotella-, Megaspheara-, and Lactobacillus-dominated enterotypes with aging. Even when the fecal microbiome was the least diverse, the richness of ARGs, quantities of AMR gene copies, and counts of AMR fecal bacteria were highest in piglets at 2 days of age; subsequently, these declined over time, likely due to age-related competitive changes in the underlying microbiome. ARGs conferring resistance to metals and multi-compound/biocides were detected predominately at the earliest sampled ages. Conclusions The fecal microbiome and resistome—along with evaluated descriptors of phenotypic antimicrobial susceptibility of fecal bacteria—among a cohort of pigs, demonstrated opposing trajectories in diversity primarily driven by the aging of 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.

The primary objective of this observational study was to evaluate the prevalence of contamination from independently collected quarter-level milk samples pooled in a laboratory and subjected to bacterial culture. To address this objective, weekly quarter-level milk samples were collected longitudinally from a cohort of 503 primiparous cows from five organic dairy farms during the first 5 weeks after calving. Individual quarter milk samples were pooled in a laboratory using aseptic technique (“lab-pooled”) and subjected to bacterial culture. In the sample set of 2,006 lab-pooled milk samples, 207 (10.3%) were classified as contaminated using a standard definition (i.e., growth of three or more distinct microorganisms). Subsequent culturing of corresponding quarter-level milk samples revealed that many of the contaminated lab-pooled sample results (i.e., 46.7%) were the result of intramammary infections with different pathogens across the quarters, rather than actual contamination within any single quarter (i.e., “true contamination”). The odds of true contamination were lower when the lab-pooled sample exhibited growth of three microorganisms compared to more than 3 microorganisms. Our findings suggest that pooling of quarter samples within a laboratory setting may yield lower rates of contamination compared to those previously reported from samples composited on-farm, but that current cut-offs to define contamination may need to be evaluated for use with lab-pooled samples. Further investigation of use of lab-pooled samples may be warranted to reduce costs while still providing useful scientific insight.

Background Bovine mastitis is one of the most economically important diseases affecting dairy cows. The choice of bedding material has been identified as an important risk factor contributing to the development of mastitis. However, few reports examine both the culturable and nonculturable microbial composition of commonly used bedding materials, i.e., the microbiome. Given the prevalence of nonculturable microbes in most environments, this information could be an important step to understanding whether and how the bedding microbiome acts as a risk factor for mastitis. Therefore, our objective was to characterize the microbiome composition and diversity of bedding material microbiomes, before and after use. Methods We collected 88 bedding samples from 44 dairy farms in the U.S. Unused (from storage pile) and used (out of stalls) bedding materials were collected from four bedding types: new sand (NSA), recycled manure solids (RMS), organic non-manure (ON) and recycled sand (RSA). Samples were analyzed using 16S rRNA sequencing of the V3–V4 region. Results The overall composition as well as the counts of several microbial taxa differed between bedding types, with Proteobacteria, Actinobacteria, Bacteroidetes and Firmicutes dominating across all types. Used bedding contained a significantly different microbial composition than unused bedding, but the magnitude of this difference varied by bedding type, with RMS bedding exhibiting the smallest difference. In addition, positive correlations were observed between 16S rRNA sequence counts of potential mastitis pathogens (bacterial genera) and corresponding bedding bacterial culture data. Conclusion Our results strengthen the role of bedding as a potential source of mastitis pathogens. The consistent shift in the microbiome of all bedding types that occurred during use by dairy cows deserves further investigation to understand whether this shift promotes pathogen colonization and/or persistence, or whether it can differentially impact udder health outcomes. Future studies of bedding and udder health may be strengthened by including a microbiome component to the study design.