Although high-throughput DNA sequencing-based methods have been of great value for determining the composition of microbial communities in various environments, there is the potential for inaccuracies arising from the sequencing of DNA from dead microorganisms. In this pilot study, we compared different sequencing-based methods to assess their relative accuracy with respect to distinguishing between viable and non-viable cells, using a live and heat-inactivated model community spiked into bovine milk. The methods used were shotgun metagenomics with and without propidium monoazide (PMA) treatment, RNA-based 16S rRNA sequencing and metatranscriptomics. The results showed that methods were generally accurate, though significant differences were found depending on the library types and sequencing technologies. Different molecular targets were the basis for variations in the results generated using different library types, while differences in the derived composition data from Oxford Nanopore Technologies-and Illumina-based sequencing likely reflect a combination of different sequencing depths, error rates and bioinformatics pipelines. Although PMA was successfully applied in this study, further optimisation is required before it can be applied in a more universal context for complex microbiomes. Overall, these methods show promise and represent another important step towards the ultimate establishment of approaches that can be applied to accurately identify live microorganisms in milk and other food niches.

Previous human milk studies have confirmed the existence of a highly diverse bacterial community using culture-independent and targeted culture-dependent techniques. However, culture-enriched molecular profiling of milk microbiota has not been done. Additionally, the impact of storage conditions and milk fractionation on microbiota composition is not understood. In this feasibility study, we optimized and applied culture-enriched molecular profiling to study culturable milk microbiota in eight milk samples collected from mothers of infants admitted to a neonatal intensive care unit. Fresh samples were immediately plated or stored at -80°C for 2 weeks (short-term frozen). Long-term samples were stored at -20°C for >6 months. Samples were cultured using 10 different culture media and incubated both aerobically and anaerobically. We successfully isolated major milk bacteria, including Streptococcus, Staphylococcus and Bifidobacterium, from fresh milk samples, but were unable to culture any bacteria from the long-term frozen samples. Short-term freezing shifted the composition of viable milk bacteria from the original composition in fresh samples. Nevertheless, the inter-individual variability of milk microbiota composition was observed even after short-term storage. There was no major difference in the overall milk microbiota composition between milk fractions in this feasibility study. This is among the first studies on culture-enriched molecular profiling of the milk microbiota demonstrating the effect of storage and fractionation on milk microbiota composition.

Lactating cows are routinely treated at dry-off with antibiotic infusions in each quarter for the cure and prevention of pathogenic intramammary infection, which remains the most common disease in dairy herds. This approach is known as blanket dry-cow therapy, usually effective for the prevention and cure of infections, but has been shown to potentially contribute to the emergence and spreading of antibiotic resistant bacterial strains. Exploring the use of non-antibiotic treatments coupled with selective dry-cow therapy is necessary to reduce the risk of antibiotic resistance and potential interference with milk microbiome balance. The impact of selective dry-cow therapy on the physiological milk microbiome needs to be carefully evaluated. In this small-scale trial, five healthy (no mastits, SCC <200,000 cells mL-1) second-parity cows from dry-off to 5 days after calving were sampled. For every cow, each quarter received a different treatment: (i) bismuth salnitrate (internal teat sealant, OrbSeal®, Zoetis, Italy), front right quarter; (ii) cephalonium dihydrate (Cepravin®, MSD, Italy), rear right quarter; (iii) benzathine cloxacillin (Cloxalene dry, Ati, Italy), rear left quarter. No treatment was applied to the remaining quarter (front left) which served as experimental control. For 16S rRNA gene sequencing, bacterial DNA was extracted from 5 ml of milk samples, amplified using the primers for the V3-V4 hypervariable regions and sequenced in one MiSeq (Illumina) run with 2 × 250-base paired-end reads. Bacteriological results confirmed that the quarters were all healthy. The phyla Proteobacteria, Firmicutes, and Actinobacteria were the most abundant for all treatments and controls at all three timepoints, accounting for over 80% of the entire milk microbiota composition. No significant differences were found between treatments and controls in terms of the major alpha and beta diversity indexes, revealing that antibiotic, and non-antibiotic treatments for selective dry-cow therapy did not alter significantly the milk microbiome of dairy cows. The milk microbiota composition showed a clear evolution over the lactation cycle, and the overall changes in the milk microbiota diversity over the lactation cycle were mainly independent of treatments.

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.

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.