The objective of this pilot study was to evaluate the influence of sampling technique and exposure to different bedding types on the milk microbiome of healthy primiparous cows. Primiparous Holstein cows (n = 20) with no history of clinical mastitis or monthly somatic cell counts >150,000 cells/mL were selected for this study. From each enrolled cow, a composite milk sample was aseptically collected from all 4 mammary quarters (individual quarter somatic cell counts <100,000 cells/mL), 1 individual quarter milk sample was collected using conventional aseptic technique, and 2 individual quarter milk samples were collected directly from the gland cistern using a needle and vacuum tube. All milk samples were cultured using standard milk microbiological techniques and DNA was extracted. Extracted DNA was subjected to PCR and next-generation sequencing for microbiota determination. All samples yielded relatively little total DNA. Amplification of PCR was successful in 45, 40, and 83% of composite, conventional, and cisternal samples, respectively. Bacteria were successfully cultured from 35% of composite milk samples but from none of the quarter milk samples collected using conventional or cisternal sampling techniques. Bacterial DNA sequences were assigned to operational taxonomic units (OTU) based on 97% sequence similarity, and bacterial richness and diversity were determined. Most samples were dominated by low-prevalence OTU and of the 4,051 identified OTU, only 14 were prevalent at more than 1% each. These included bacteria typically recovered from environmental sources. Chao richness was greatest in composite samples and was 636, 347, and 356 for composite, conventional quarter, and cisternal milk samples, respectively. Shannon diversity was similar among sample types and ranged from 3.88 (quarter) to 4.17 (composite). Richness and diversity did not differ by bedding type among cisternal samples, but the power of this pilot study was limited due to small sample size. Despite the small sample size, for milk samples collected from the gland cistern, overall bacterial community composition differed among bedding types. These results demonstrate that sampling technique and bedding type may be associated with the microbiota detected in bovine milk, and we suggest that these variables should be considered in designing and reporting studies about the milk microbiota.

The objective of this longitudinal cohort study was to describe the milk microbiota of dairy cow mammary glands based on inflammation status before and after the dry period. Individual mammary quarters were assigned to cohorts based on culture results and somatic cell count (SCC) at dryoff and twice in the first 2 weeks post-calving. Mammary glands that were microbiologically negative and had low SCC (< 100,000 cells/mL) at all 3 sampling periods were classified as Healthy (n = 80). Microbiologically negative mammary glands that had SCC ≥150,000 cells/mL at dryoff and the first post-calving sample were classified as Chronic Culture-Negative Inflammation (CHRON; n = 17). Quarters that did not have both culture-negative milk and SCC ≥ 150,000 cells/mL at dryoff but were culture-negative with SCC ≥ 150,000 at both post-calving sampling periods were classified as Culture-Negative New Inflammation (NEWINF; n = 6). Mammary glands with bacterial growth and SCC ≥ 150,000 cells/mL at all 3 periods were classified as Positive (POS; n = 3). Milk samples were collected from all enrolled quarters until 150 days in milk and subjected to microbiota analysis. Milk samples underwent total DNA extraction, a 40-cycle PCR to amplify the V4 region of the bacterial 16S rRNA gene, and next-generation sequencing. Healthy quarters had the lowest rate of PCR and sequencing success (53, 67, 83, and 67% for Healthy, CHRON, NEWINF, and POS, respectively). Chao richness was greatest in milk collected from Healthy quarters and Shannon diversity was greater in milk from Healthy and CHRON quarters than in milk collected from glands in the NEWINF or POS cohorts. Regardless of cohort, season was associated with both richness and diversity, but stage of lactation was not. The most prevalent OTUs included typical gut- and skin-associated bacteria such as those in the phylum Bacteroidetes and the genera Enhydrobacter and Corynebacterium. The increased sequencing success in quarters with worse health outcomes, combined with the lack of bacterial growth in most samples and the high PCR cycle number required for amplification of bacterial DNA, suggests that the milk microbiota of culture-negative, healthy mammary glands is less abundant than that of culture-negative glands with a history of inflammation.

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Escherichia coli isolated from bovine milk samples submitted to the Ohio Agricultural Research and Development Center Mastitis Laboratory (Wooster) in 1985 to 1987 and in 2009 were compared for antimicrobial susceptibility and prevalence of antimicrobial resistance genes. Forty-four isolates from 1985 to 1987 and 55 isolates from 2009 were tested. Minimum inhibitory concentrations of 15 antimicrobials were determined using a commercially available broth microdilution system. Multiplex polymerase chain reaction was performed for gene detection. The percentage of isolates susceptible to trimethoprim/sulfamethoxazole, ampicillin, and kanamycin was lower in those collected in 1985 to 1987 than in isolates collected in 2009. Susceptibility did not differ between isolates from 1985 to 1987 and isolates from 2009 for the 12 other antimicrobials tested. A trimethoprim/sulfamethoxazole resistance gene was detected more frequently in isolates from 1985 to 1987 than in isolates from 2009. Gene frequencies for streptomycin resistance and tetracycline resistance were similar among 1985 to 1987 isolates and 2009 isolates. Resistance to most antimicrobials did not differ between isolates submitted to a mastitis diagnostic laboratory in 1985 to 1987 and those submitted in 2009. Changes observed indicated an increase in frequency of susceptibility in isolates to trimethoprim/sulfamethoxazole, ampicillin, and kanamycin in 2009 isolates compared with 1985 to 1987 isolates.

The objective of these experiments was to determine adaptation by ruminants to dietary sulfur. In Exp. 1, lambs (n = 54; BW = 33.6 ± 0.4 kg) were allotted to 3 treatments: 1) 0% added dietary S (0%S), 2) 0.2% added dietary S (0.2%S), or 3) 0.4% added dietary S (0.4%S). Sulfur was added to the diet as Na(2)SO(4). Lambs fed the 0.2%S and 0.4%S diets had greater (P < 0.01) ADG and G:F compared to those fed the 0%S diet. There was time × diet interaction (P < 0.01) on ruminal hydrogen sulfide gas (H(2)S) concentrations. Ruminal H(2)S was not detected in lambs fed 0%S at any time. Ruminal H2S were not affected (P > 0.19) by diet on d 1 or 8; however, H(2)S were greater (P < 0.01) for lambs fed 0.2%S and 0.4%S than for lambs fed 0%S on d 15, 22, and 29 (0.2% was 931, 846, and 1,131 mg/L and 0.4% was 975, 737, and 1,495 mg/L on d 15, 22, and 29, respectively). These data suggest it takes at least 29 d for peak ruminal H(2)S to occur after exposure to Na(2)SO(4). In Exp. 2, lambs (n = 66; BW = 51.1 ± 0.4 kg) were allotted to 3 treatments: 1) 60% dried distillers grains with solubles (DDGS), 2) corn-based diet with Na(2)SO(4), or 3) corn-based diet with H(2)SO(4). All diets were formulated to contain 0.4%S. Lambs fed Na(2)SO(4) had greater (P < 0.05) ADG, DMI, and G:F than those fed H(2)SO(4) or 60% DDGS. A time × diet interaction occurred (P < 0.01) for ruminal H(2)S. There was no difference (P = 0.82) in H(2)S of lambs on d 1. However, at d 14 and 27 lambs fed supplemental Na(2)SO(4) had the lowest H(2)S concentrations while lambs fed 60% DDGS had the greatest (P < 0.01 on both d); lambs fed H(2)SO(4) were intermediate and different than both. These data suggest that at the same dietary S concentration, acidic S sources increased H(2)S and decreased DMI and ADG. In Exp. 3, Angus cross calves (n = 72; average initial BW = 324 ± 3 kg) were allotted to 3 treatments: 1) corn-based control d 0 through 85 (0%DDGS), 2) gradual step up to 60% DDGS diet (20% DDGS d 0 to 6, 40% DDGS d 7 to 13, 50% DDGS d 14 to 20, and 60% DDGS d 21 to 85; Step-up), or 3) 60% DDGS d 0 to 85 (60%DDGS). Overall, cattle fed 0%DDGS had increased (P < 0.05) DMI and ADG compared with those fed 60%DDGS or Step-up, and G:F was not affected (P = 0.42) by dietary treatment. On d 14, ruminal H(2)S concentrations were greater (P < 0.01) for cattle fed 60%DDGS and Step-up than for those fed 0%DDGS, and they did not differ (P ≥ 0.22) between DDGS-containing diets. These data illustrate that source of S impacts ruminal S metabolism and that S from DDGS is more readily reduced than S from Na(2)SO(4) or H(2)SO(4).

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