Microbiota of bovine milk, teat skin, and teat canal: Similarity and variation due to sampling technique and milk fraction

The impact of kit, environment, and sampling contamination on the observed microbiome of bovine milk

In low-microbial biomass samples such as bovine milk, contaminants can outnumber endogenous bacteria. Because of this, milk microbiome research suffers from a critical knowledge gap, namely, does non-mastitis bovine milk contain a native microbiome? In this study, we sampled external and internal mammary epithelia and stripped and cisternal milk and used numerous negative controls, including air and sampling controls and extraction and library preparation blanks, to identify the potential sources of contamination. Two algorithms were used to mathematically remove contaminants and track the potential movement of microbes among samples. Results suggest that the majority (i.e., >75%) of sequence data generated from bovine milk and mammary epithelium samples represents contaminating DNA. Contaminants in milk samples were primarily sourced from DNA extraction kits and the internal and external skin of the teat, while teat canal and apex samples were mainly contaminated during the sampling process. After decontamination, the milk microbiome displayed a more dispersed, less diverse, and compositionally distinct bacterial profile compared with epithelial samples. Similar microbial compositions were observed between cisternal and stripped milk samples, as well as between teat apex and canal samples. Staphylococcus and Acinetobacter were the predominant genera detected in milk sample sequences, and bacterial culture showed growth of Staphylococcus and Corynebacterium spp. in 50% (7/14) of stripped milk samples and growth of Staphylococcus spp. in 7% (1/14) of cisternal milk samples. Our study suggests that microbiome data generated from milk samples obtained from clinically healthy bovine udders may be heavily biased by contaminants that enter the sample during sample collection and processing workflows.IMPORTANCEObtaining a non-contaminated sample of bovine milk is challenging due to the nature of the sampling environment and the route by which milk is typically extracted from the mammary gland. Furthermore, the very low bacterial biomass of bovine milk exacerbates the impacts of contaminant sequences in downstream analyses, which can lead to severe biases. Our finding showed that bovine milk contains very low bacterial biomass and each contamination event (including sampling procedure and DNA extraction process) introduces bacteria and/or DNA fragments that easily outnumber the native bacterial cells. This finding has important implications for our ability to draw robust conclusions from milk microbiome data, especially if the data have not been subjected to rigorous decontamination procedures. Based on these findings, we strongly urge researchers to include numerous negative controls into their sampling and sample processing workflows and to utilize several complementary methods for identifying potential contaminants within the resulting sequence data. These measures will improve the accuracy, reliability, reproducibility, and interpretability of milk microbiome data and research.

Integrated analysis of transcriptome and milk metagenome in subclinical mastitic and healthy cows

OBJECTIVE

Abnormally increased somatic cell counts (SCCs) in milk is usually a sign of bovine subclinical mastitis. Mutual interaction between the host and its associated microbiota plays an important role in developing such diseases. The main objective of this study was to explore the difference between cows with elevated SCCs and healthy cattle from the perspective of host-microbe interplay.

METHODS

A total of 31 milk samples and 23 bovine peripheral blood samples were collected from Holstein dairy cattle to conduct an integrated analysis of transcriptomic and metagenomics.

RESULTS

The results showed that Ralstonia and Sphingomonas were enriched in cows with subclinical mastitis. The relative abundance of the two bacteria was positively correlated with the expression level of bovine transcobalamin 1 and uridine phosphorylase 1 encoding gene. Moreover, functional analysis revealed a distinct alternation in some important microbial biological processes.

CONCLUSION

These results reveal the relative abundance of Ralstonia and Sphingomonas other than common mastitis-causing pathogens varied from healthy cows to those with subclinical mastitis and might be associated with elevated SCCs. Potential association was observed between bovine milk microbiota composition and the transcriptional pattern of some genes, thus providing new insights to understand homeostasis of bovine udder.

Production, Composition and Nutritional Properties of Organic Milk: A Critical Review

Milk is one of the most valuable products in the food industry with most milk production throughout the world being carried out using conventional management, which includes intensive and traditional systems. The intensive use of fertilizers, antibiotics, pesticides and concerns regarding animal health and the environment have given increasing importance to organic dairy and dairy products in the last two decades. This review aims to compare the production, nutritional, and compositional properties of milk produced by conventional and organic dairy management systems. We also shed light on the health benefits of milk and the worldwide scenario of the organic dairy production system. Most reports suggest milk has beneficial health effects with very few, if any, adverse effects reported. Organic milk is reported to confer additional benefits due to its lower omega-6-omega-3 ratio, which is due to the difference in feeding practices, with organic cows predominantly pasture fed. Despite the testified animal, host, and environmental benefits, organic milk production is difficult in several regions due to the cost-intensive process and geographical conditions. Finally, we offer perspectives for a better future and highlight knowledge gaps in the organic dairy management system.

Indirect Sensing of Subclinical Intramammary Infections in Dairy Herds with a Milking Robot

This study determined the impact of subclinical intramammary infections (IMIs), such as the major and minor udder pathogens (MaPs and MiPs), on the somatic cell count (SCC) in cow milk and investigated the possibilities of indirect sensing of the udder pathogens using the mastitis detection index (MDi) (DeLaval, Tumba, Sweden). The MDi incorporates quarter-level milk electrical conductivity, blood in milk, and milking interval. The case group (n = 21; MDi ≥ 1.4) was compared with the control group (n = 24; MDi < 1.4) for the presence of IMIs. The microbiological investigation of udder quarter foremilk samples was performed two times with an interval of 10 to 14 days. The case and control groups differed in terms of the occurrence of MaPs and MiPs in milk. During the continuous subclinical IMI and the episodic MaP infection, a higher SCC was detected compared with the episodic MiP infection or quarters without IMI. The novel finding of this study was that by using the milk quality sensor for the sensing of subclinical IMIs, there was an indication for the successful detection of episodic MaPs. However, the sensing of the continuous subclinical IMIs was not possible in the current study and still needs to be investigated.

Effects of Intramammary Antimicrobial Treatment on the Milk Microbiota Composition in Mild Clinical Bovine Mastitis Caused by Gram-Positive Bacteria

The purpose of this study was to clarify the effects of antimicrobial treatment for mild mastitis caused by Gram-positive bacteria on the milk microbiota in dairy cattle. Sixteen quarters of sixteen cows with mild clinical mastitis from the same herd were included in the study. On the day of onset (day 0), the cows were randomly allocated to a no-treatment (NT; n = 10) group or an intramammary antimicrobial treatment (AMT) group that received AMT starting on day 0 (AMT-AMT group; n = 6). The next day (day 1), the cows in the NT group were randomly allocated into an NT group (NT-NT group; n = 3) that received no treatment or an AMT group that received AMT starting on day 1 (NT-AMT group; n = 7). Milk samples were collected on days 0, 1, 3 and 7, and the milk microbiota of each sample was comprehensively analyzed via 16S rRNA gene amplicon sequencing of the milk DNA. During the treatment period, the milk microbiota of the NT-NT group did not change, but those of the NT-AMT and AMT-AMT groups changed significantly on days three and seven. Thus, the use of antimicrobials for mild mastitis caused by Gram-positive bacteria changes the milk microbiota composition.

The bovine milk microbiome - an evolving science

Improved access to genome based, culture independent methods has generated great interest in defining the bovine milk microbiome. Several comprehensive reviews of this subject have recently been published and the purpose of this short review is to consolidate current understanding of the relevance and biological significance of this emerging topic. In contrast to mucosal organs that contain rich and well-characterized culturable and nonculturable microbial communities, milk obtained from the healthy bovine mammary gland usually contains few or no viable bacteria. The low bacterial biomass of milk has created methodological challenges that have resulted in considerable variability in results of studies that have used genomic methods to define the microbiota of milk obtained from healthy or diseased mammary glands. While genomes from several bacterial genera are routinely identified from samples of milk, teat skin and the teat canal, the viability, origin, and function of these organisms is uncertain as environmental factors have been shown to strongly influence the composition of these bacterial populations. Possible sources of microbial DNA include bacteria introduced from skin or the environment, bacteria trapped in teat canal keratin or bacteria engulfed by phagocytes. Researchers have not achieved consensus about key concepts such as the presence of a core commensal milk microbiome or dysbiosis as part of a causal pathway disrupting udder health. Understanding of the bovine milk microbiome has been greatly impeded by a lack of standardized methods used to collect, process, and assess bovine milk samples. Sample collection is a critical first step that will determine the validity of results. To minimize contamination with external sources of bacterial DNA, teat sanitation methods used for collection of milk samples that will be subjected to extraction and amplification of bacteria DNA should far exceed aseptic techniques used for collection of milk samples that will be submitted for microbiological culture. A number of laboratory issues have yet to be resolved. Contamination of low biomass samples with bacterial DNA from laboratory reagents is a well-known issue that has affected results of studies using bovine milk samples and results of sequencing of negative controls should always be reported. Replication of experiments has rarely been performed and consistency in results are lacking. While progress has been made, standardization of methods and replication using samples originating from differing farm conditions are critically needed to solidify knowledge of this emerging topic.

Examination of the microbiota of normal cow milk using MinIONTM nanopore sequencing

The aim of this study was to evaluate the microbiota of normal milk in dairy cows and their relationship with host factors, such as the age of the cow (Age), somatic cell counts in milk (SCCs), and days in milk (DIM). We investigated 48 milk samples from 22 cows with no systemic or local clinical signs using MinION^TM nanopore sequencing for a 16S rRNA gene amplicon. Bacterial richness was positively correlated with the DIM (P=0.043), and both the Shannon-Wiener Index and Simpson’s Index, which are metrics of alpha-diversity, were also significantly positively correlated with the SCC (P<0.001). The composition ratios of both Actinobacteria at the phylum level and Kocuria spp. at the genus level in the milk microbiota were significantly correlated with the SCC (P<0.001 and P<0.001, respectively). In the beta-diversity test, the one-way analysis of similarities test showed a significant difference (P=0.0051) between the low- and high-SCC groups. This study clarified that the composition of the normal milk microbiota in this herd was related to the SCC. It also raised the possibility of variations in bacterial genera in the normal milk microbiota between the low- and high-SCC groups. However, to clarify the actual condition of the milk microbiota and to elucidate the relationship with the SCC, it is necessary to perform further analyses taking into account not only the relative abundance, but also the absolute abundance of microbes.

Bovine Milk Microbiota: Comparison among Three Different DNA Extraction Protocols To Identify a Better Approach for Bacterial Analysis

The bovine udder is colonized by a huge quantity of microorganisms that constitute the intramammary ecosystem, with a specific role in modulating not only udder homeostasis and mastitis susceptibility, but also the quality of the dairy products. However, generating high-quality bacterial DNA can be critical, especially starting from a complex biological matrix like milk, characterized by high fat, protein, and calcium contents. Here, bacterial DNA was recovered from a commercial ultra-high-temperature (UHT) milk sample artificially spiked with a predetermined mock community composition and from three bulk tank milk (raw milk) samples. The DNA was isolated using three different protocols to evaluate the effect of the extraction procedures on the milk microbiota composition. In the mock community experiment, the bacterial profiles generated by the three DNA extraction protocols were profoundly different, with the genera Staphylococcus, Lactobacillus, Listeria, and Salmonella underestimated by all the protocols. Only one protocol revealed values close to the expected abundances for Escherichia/Shigella spp., Bacillus spp., Enterococcus spp., and Pseudomonas spp. On the other hand, the nonspiked UHT milk sample exhibited a similar microbiota composition, revealing the prevalence of Acinetobacter spp., for all the DNA extraction protocols. For the raw milk samples, the three DNA extraction kits performed differently, revealing significant separations in both the microbial richness (alpha diversity) and composition (beta diversity). Our study highlights the presence of significant differences among these procedures, probably due to the different DNA extracting capacities and to the different properties of the milk samples, revealing that the selection of DNA extraction protocol is a critical point.

IMPORTANCE The advance of high-throughput technologies has increased our knowledge of the world of microorganisms, especially of microbial populations inhabiting living animals. This study provides evidence that milk, as other complex sources, could be critical for generating high-quality DNA for microbiota analysis. In addition, it demonstrates that the microbial population highlighted by metagenomic studies changes in relation to different DNA extraction procedures, revealing that attention should be paid especially when comparing different studies.

Milking system and premilking routines have strong effect on the microbial community in bulk tank milk

In this study, we investigated the variation in the microbial community present in bulk tank milk samples and the potential effect of different farm management factors. Bulk tank milk samples were collected repeatedly over one year from 42 farms located in northern Sweden. Total and thermoresistant bacteria counts and 16S rRNA gene-based amplicon sequencing were used to characterize microbial community composition. The microbial community was in general heterogeneous both within and between different farms and the community composition in the bulk tank milk was commonly dominated by Pseudomonas, Acinetobacter, Streptococcus, unclassified Peptostreptococcaceae, and Staphylococcus. Principal component analysis including farm factor variables and microbial taxa data revealed that the microbial community in milk was affected by type of milking system. Milk from farms using an automatic (robot) milking system (AMS) and loose housing showed different microbial community composition compared with milk from tiestall farms. A discriminant analysis model revealed that this difference was dependent on several microbial taxa. Among farms using an automatic milking system, there were further differences in the microbial community composition depending on the brand of the milking robot used. On tiestall farms, routines for teat preparation and cleaning of the milking equipment affected the microbial community composition in milk. Total bacteria count (TBC) in milk differed between the farm types, and TBC were higher on AMS than tiestall farms (log 4.05 vs. log 3.79 TBC/mL for AMS and tiestalls, respectively). Among tiestall farms, milk from farms using a chemical agent in connection to teat preparation and a more frequent use of acid to clean the milking equipment had lower TBC in milk, than milk from farms using water for teat preparation and a less frequent use of acid to clean the milking equipment (log 3.68 vs. 4.02 TBC/mL). There were no significant differences in the number of thermoresistant bacteria between farm types. The evaluated factors explained only a small proportion of total variation in the microbiota data, however, despite this, the study highlights the effect of routines associated with teat preparation and cleaning of the milking equipment on raw milk microbiota, irrespective of type of milking system used.

Amplicon-sequencing of raw milk microbiota: impact of DNA extraction and library-PCR

Abstract

The highly complex raw milk matrix challenges the sample preparation for amplicon-sequencing due to low bacterial counts and high amounts of eukaryotic DNA originating from the cow. In this study, we optimized the extraction of bacterial DNA from raw milk for microbiome analysis and evaluated the impact of cycle numbers in the library-PCR. The selective lysis of eukaryotic cells by proteinase K and digestion of released DNA before bacterial lysis resulted in a high reduction of mostly eukaryotic DNA and increased the proportion of bacterial DNA. Comparative microbiome analysis showed that a combined enzymatic and mechanical lysis procedure using the DNeasy^® PowerFood^® Microbial Kit with a modified protocol was best suitable to achieve high DNA quantities after library-PCR and broad coverage of detected bacterial biodiversity. Increasing cycle numbers during library-PCR systematically altered results for species and beta-diversity with a tendency to overrepresentation or underrepresentation of particular taxa. To limit PCR bias, high cycle numbers should thus be avoided. An optimized DNA extraction yielding sufficient bacterial DNA and enabling higher PCR efficiency is fundamental for successful library preparation. We suggest that a protocol using ethylenediaminetetraacetic acid (EDTA) to resolve casein micelles, selective lysis of somatic cells, extraction of bacterial DNA with a combination of mechanical and enzymatic lysis, and restriction of PCR cycles for analysis of raw milk microbiomes is optimal even for samples with low bacterial numbers.

Key points

• Sample preparation for high-throughput 16S rRNA gene sequencing of raw milk microbiota.

• Reduction of eukaryotic DNA by enzymatic digestion.

• Shift of detected microbiome caused by high cycle numbers in library-PCR.

Supplementary Information

The online version contains supplementary material available at 10.1007/s00253-021-11353-4.